diff --git a/data/covid/preprints-summary.csv b/data/covid/preprints-summary.csv index 5f7c985e..e1af6591 100644 --- a/data/covid/preprints-summary.csv +++ b/data/covid/preprints-summary.csv @@ -1,47 +1,47 @@ -evolutionary biology,allergy and immunology,biophysics,dermatology,psychiatry and clinical psychology,pathology,obstetrics and gynecology,pediatrics,epidemiology,oncology,bioinformatics,infectious diseases,microbiology,primary care research,genomics,scientific communication and education,orthopedics,cardiovascular medicine,intensive care and critical care medicine,radiology and imaging,genetic and genomic medicine,Total,neurology,surgery,emergency medicine,hiv aids,public and global health,health policy,month,health systems and quality improvement,dentistry and oral medicine,respiratory medicine,pharmacology and therapeutics,geriatric medicine,occupational and environmental health,molecular biology,systems biology,ophthalmology,immunology,biochemistry,health informatics,health economics -,,,,,,,,2,1,,1,,,,,,,,,,4,,,,,,,Nov-23,,,,,,,,,,,,, -,,,,,,,,1,,,1,,,,,,,,,,5,,,,,,,Oct-23,,,1,,,,,,,1,,1, -,,,,,,,,,,,1,,,,,,,,,,1,,,,,,,Sep-23,,,,,,,,,,,,, -,,,,,,,,4,,,,,1,,,,,,,,7,,,,,1,,Aug-23,,,,,,1,,,,,,, -,,,,,,,,3,,,,,,,,,,,,1,7,,,,,1,,Jul-23,2,,,,,,,,,,,, -,,,,,,,,1,,,2,,,,1,1,,,,,7,,,,,,,Jun-23,,,,,,1,,,,,,1, -,,,,,,,,2,,,1,,,,,,,,,,6,,,,,1,,May-23,,,1,,,,,,,1,,, -,,,,,,,,,,,1,,,,,,,,,,3,,,,,2,,Apr-23,,,,,,,,,,,,, -,,,,1,,,,2,,,3,,,,,,,,,,9,,,,,2,,Mar-23,,,,,,1,,,,,,, -,,,,,,,,4,,,,,,,,,,,,,8,1,,,,2,,Feb-23,,,1,,,,,,,,,, -,,,,,,,,5,,,1,,,,,,,,,,6,,,,,,,Jan-23,,,,,,,,,,,,, -,,,,,1,,,3,,,4,,,,,,,,,,12,,,,,1,1,Dec-22,,,2,,,,,,,,,, -,,,,,,,,,,,4,,,,,,,,,,4,,,,,,,Nov-22,,,,,,,,,,,,, -,,,,,,,,1,,,2,,,,,,1,,,,6,,,,,2,,Oct-22,,,,,,,,,,,,, -,,,,,,,1,1,,,2,1,,,,,,,,,9,,,,,1,,Sep-22,,,1,,,2,,,,,,, -,,,,,,,,4,,,3,,,,,,,,,,10,,,,,3,,Aug-22,,,,,,,,,,,,, -,,,,,,,1,2,,,3,,,,,,,,,,8,,,,,,,Jul-22,,,,,,,,,,1,,1, -,,,,4,,,,6,,,4,,,,,,,,,1,17,,,,,1,,Jun-22,,,,,,,,,,,,1, -,,,,2,,,,2,,,4,1,1,,,,,,,,13,,,,,1,,May-22,1,,,,,,,,,,,,1 -,,,,,,,,5,,,3,1,,,,,1,,,,16,,,,,1,,Apr-22,2,,1,,,1,,,,,,,1 -1,,,,1,,,,9,,,5,,1,,,,,,,,18,,,,,,,Mar-22,,,1,,,,,,,,,, -,,,,,,,,6,,,4,,,,,,,,,,12,1,,,,1,,Feb-22,,,,,,,,,,,,, -,,,,,,,,4,,,3,,,,,,1,,,,13,,,,,1,,Jan-22,,,,,,1,,,,1,,2, -,,,,,,,1,10,,,8,1,1,,,,1,,,,24,1,,,,1,,Dec-21,,,,,,,,,,,,, -,,1,,1,,,,9,,,5,,1,1,,,,1,,,25,1,,,,3,,Nov-21,2,,,,,,,,,,,, -,,,,2,,,1,4,,,3,,,,,,,,,,11,,,,,,,Oct-21,,,,,1,,,,,,,, -,,,,,,,,6,,,5,,,,,,1,1,,,17,,,,,2,,Sep-21,,,,1,,,,,,,,1, -,,,,,,,,2,,,2,,,,,,1,1,,,11,,,,,2,,Aug-21,,,1,,,1,,,,,,1, -,,,,,,,1,3,1,,10,,,,,,,1,,1,24,,,1,,4,,Jul-21,,,2,,,,,,,,,, -,1,,,1,,,1,7,,,6,,1,,,,,1,,,26,,,,,4,,Jun-21,1,,,,,1,,,,1,,1, -,,,1,,,,,11,,,8,,,,,,,,,1,23,,,,,1,,May-21,,,,,,,,,,,,1, -,1,,,1,,,,3,,,7,1,1,,,,,,,,19,,,,,1,,Apr-21,1,,,,,2,,,,,,1, -,,,,1,,,1,5,,,17,,,,,,,,1,1,38,1,1,,,5,,Mar-21,,,,,2,,,,,,1,2, -,,,,,,,,9,,,9,,,,,,1,,,,24,,1,,,1,,Feb-21,1,,,,,,,,,,,1,1 -,,,,1,,,,4,,,7,,1,,,,,1,,,22,,,,,3,1,Jan-21,1,1,,,1,,,,,1,,, -,,,,2,,,,4,,,4,1,1,2,,,2,,,,23,,,,,3,,Dec-20,1,,,,,,,,,,,3, -,,,,,,,,5,,1,12,,,,,,,,,,25,,,,,4,1,Nov-20,,,,,,,,,,1,,1, -,,,,3,,,,6,1,1,12,,1,,,,,,,,28,,,,,,1,Oct-20,,,,,1,,,1,,1,,, -,,,,2,,,,6,,,7,1,1,,,,,1,,,25,,,3,1,2,,Sep-20,,,,,,,,,,,,1, -,,,,,,1,,6,,,12,,,,,,,,,1,27,,,2,,2,,Aug-20,1,,,,,1,1,,,,,, -,,,,1,,,,10,,,8,,,1,,,,1,,,27,,,,,4,,Jul-20,,,1,,,,,,,1,,, -,,,,4,,,,7,1,1,10,,,,,,1,3,,,37,,,,,3,1,Jun-20,1,,1,,1,,,,1,1,,1, -,,,,,,,,8,1,1,9,,,,,,2,1,,,36,,,,,9,,May-20,,,1,,1,1,,,,,,1,1 -,,,,,,,,7,,,7,,,1,,,,,,2,19,,,,,1,,Apr-20,1,,,,,,,,,,,, -,,,,,,,,3,,,1,,,,,,,,,,7,,,,,3,,Mar-20,,,,,,,,,,,,, -,,,,,,,,4,,,1,,,,,,,,,,7,,,,,2,,Feb-20,,,,,,,,,,,,, +obstetrics and gynecology,health systems and quality improvement,intensive care and critical care medicine,dentistry and oral medicine,month,pediatrics,hiv aids,genetic and genomic medicine,emergency medicine,cardiovascular medicine,dermatology,pathology,infectious diseases,bioinformatics,immunology,orthopedics,scientific communication and education,health informatics,public and global health,health policy,epidemiology,microbiology,allergy and immunology,respiratory medicine,health economics,ophthalmology,Total,molecular biology,evolutionary biology,neurology,genomics,psychiatry and clinical psychology,occupational and environmental health,geriatric medicine,radiology and imaging,oncology,surgery,biophysics,biochemistry,pharmacology and therapeutics,primary care research +,,,,Nov-23,,,,,,,,1,,,,,,,,2,,,,,,4,,,,,,,,,1,,,,, +,,,,Oct-23,,,,,,,,1,,1,,,1,,,1,,,1,,,5,,,,,,,,,,,,,, +,,,,Sep-23,,,,,,,,1,,,,,,,,,,,,,,1,,,,,,,,,,,,,, +,,,,Aug-23,,,,,,,,,,,,,,1,,4,,,,,,7,,,,,,1,,,,,,,,1 +,2,,,Jul-23,,,1,,,,,,,,,,,1,,3,,,,,,7,,,,,,,,,,,,,, +,,,,Jun-23,,,,,,,,2,,,1,1,1,,,1,,,,,,7,,,,,,1,,,,,,,, +,,,,May-23,,,,,,,,1,,1,,,,1,,1,,,1,,,5,,,,,,,,,,,,,, +,,,,Apr-23,,,,,,,,1,,,,,,2,,,,,,,,3,,,,,,,,,,,,,, +,,,,Mar-23,,,,,,,,3,,,,,,2,,1,,,,,,8,,,,,1,1,,,,,,,, +,,,,Feb-23,,,,,,,,,,,,,,2,,4,,,1,,,8,,,1,,,,,,,,,,, +,,,,Jan-23,,,,,,,,1,,,,,,,,5,,,,,,6,,,,,,,,,,,,,, +,,,,Dec-22,,,,,,,1,4,,,,,,1,1,3,,,2,,,12,,,,,,,,,,,,,, +,,,,Nov-22,,,,,,,,4,,,,,,,,,,,,,,4,,,,,,,,,,,,,, +,,,,Oct-22,,,,,1,,,2,,,,,,2,,1,,,,,,6,,,,,,,,,,,,,, +,,,,Sep-22,,,,,,,,2,,,,,,1,,1,1,,1,,,8,,,,,,2,,,,,,,, +,,,,Aug-22,,,,,,,,2,,,,,,3,,4,,,,,,9,,,,,,,,,,,,,, +,,,,Jul-22,1,,,,,,,3,,1,,,1,,,2,,,,,,8,,,,,,,,,,,,,, +,,,,Jun-22,,,1,,,,,4,,,,,1,1,,6,,,,,,18,,,,,5,,,,,,,,, +,1,,,May-22,,,,,,,,5,,,,,,1,,1,1,,,1,,13,,,,,2,,,,,,,,,1 +,2,,,Apr-22,,,,,1,,,3,,,,,,1,,5,1,,1,1,,16,,,,,,1,,,,,,,, +,,,,Mar-22,,,,,,,,5,,,,,,,,8,,,1,,,16,,1,,,1,,,,,,,,, +,,,,Feb-22,,,,,,,,4,,,,,,1,,6,,,,,,12,,,1,,,,,,,,,,, +,,,,Jan-22,,,,,1,,,3,,1,,,2,1,,5,,,,,,14,,,,,,1,,,,,,,, +,,,,Dec-21,1,,,,1,,,8,,,,,,1,,9,1,,,,,22,,,,,,,,,,,,,,1 +,2,1,,Nov-21,,,,,,,,5,,,,,,3,,9,,,,,,24,,,1,1,,,,,,,1,,,1 +,,,,Oct-21,1,,,,,,,3,,,,,,,,4,,,,,,11,,,,,2,,1,,,,,,, +,,1,,Sep-21,,,,,1,,,5,,,,,1,2,,6,,,,,,17,,,,,,,,,,,,,1, +,,1,,Aug-21,,,,,1,,,3,,,,,1,3,,1,,,1,,,12,,,,,,1,,,,,,,, +,,1,,Jul-21,1,,1,1,,,,12,,,,,,4,,3,,,1,,,25,,,,,,,,,1,,,,, +,1,1,,Jun-21,1,,,,,,,7,,1,,,1,4,,7,,1,,,,28,,,1,,1,1,,,,,,,,1 +,,,,May-21,,,1,,,1,,7,,,,,1,1,,11,,,,,,23,,,,,1,,,,,,,,, +,1,,,Apr-21,,,,,,,,6,,,,,1,1,,4,1,1,,,,18,,,,,,2,,,,,,,,1 +,,,,Mar-21,1,,1,,,,,15,,,,,1,4,,6,,,,,,35,,,1,,1,,2,1,,1,,1,, +,1,,,Feb-21,,,,,1,,,9,,,,,1,1,,9,,,,1,,24,,,,,,,,,,1,,,, +,1,1,1,Jan-21,,,,,,,,8,,1,,,,3,1,4,,,,,,23,,,,,1,,1,,,,,,,1 +,1,,,Dec-20,,,,,2,,,4,,,,,3,2,,3,1,,,,,21,,,,2,2,,,,,,,,,1 +,,,,Nov-20,,,,,,,,12,1,1,,,1,5,1,6,,,,,,27,,,,,,,,,,,,,, +,,1,,Oct-20,,,,,,,,12,1,1,,,1,,1,6,,,,,,29,,,,,3,,1,,1,,,,,1 +,,1,,Sep-20,,1,,3,,,,8,,,,,1,3,,6,1,,,,,27,,,,,2,,,,,,,,,1 +1,1,,,Aug-20,,,1,2,,,,10,,,,,,2,,6,,,,,,24,1,,,,,,,,,,,,, +,,1,,Jul-20,,,,,1,,,8,,1,,,,4,,10,,,1,,,28,,,,1,1,,,,,,,,, +,1,3,,Jun-20,,,,,1,,,10,1,1,,,1,3,1,7,,,1,,1,37,,,,,4,,1,,1,,,,, +,,1,,May-20,,,,,2,,,10,1,,,,1,9,,7,,,1,1,,36,,,,,,1,1,,1,,,,, +,1,,,Apr-20,,,2,,,,,6,,,,,,1,,7,,,,,,18,,,,1,,,,,,,,,, +,,,,Mar-20,,,,,,,,1,,,,,,3,,4,,,,,,8,,,,,,,,,,,,,, +,,,,Feb-20,,,,,,,,1,,,,,,2,,4,,,,,,7,,,,,,,,,,,,,, diff --git a/data/covid/preprints.csv b/data/covid/preprints.csv index 1ac68278..cb77b58a 100644 --- a/data/covid/preprints.csv +++ b/data/covid/preprints.csv @@ -245,13 +245,6 @@ ResultsAmong 20,112 observations across four population surveys, 13% reported ha ConclusionsLong COVID was associated with financial disruption in the UK. If our findings reflect causal effects, extending employment protection and financial support to people with long COVID may be warranted.",public and global health,fuzzy,100,100 bioRxiv,10.1101/2023.05.24.541920,2023-05-25,https://biorxiv.org/cgi/content/short/2023.05.24.541920,"Dichotomy of neutralizing antibody, B cell and T cell responses to SARS-CoV-2 vaccination and protection in healthy adults",Edward J Carr; Hermaleigh Townsley; Mary Y Wu; Katalin A Wilkinson; Philip S Hobson; Dina Levi; Sina Namjou; Harriet V Mears; Agnieszka Hobbs; Martina Ragno; Lou S Herman; Ruth Harvey; Chris Bailey; Ashley S Fowler; Emine Hatipoglu; Yenting Ngai; Bobbi Clayton; Murad Miah; Philip Bawumia; Mauro Miranda; Callie Smith; Chelsea Sawyer; Gavin Kelly; Viyaasan Mahalingasivam; Bang Zheng; Stephen JW Evans; Vincenzo Libri; Andrew Riddell; Jerome Nicod; Nicola O'Reilly; Michael Howell; Bryan Williams; Robert J Wilkinson; George Kassiotis; Charles Swanton; Sonia Gandhi; Rupert CL Beale; David LV Bauer; Emma C Wall,The Francis Crick Institute; The Francis Crick Institute; The Francis Crick Institute; The Francis Crick Institute; The Francis Crick Institute; The Francis Crick Institute; The Francis Crick Institute; The Francis Crick Institute; The Francis Crick Institute; The Francis Crick Institute; The Francis Crick Institute; Worldwide Influenza Centre; The Francis Crick Institute; The Francis Crick Institute; National Institute for Health Research (NIHR) University College London Hospitals (UCLH) Biomedical Research Centre and NIHR UCLH Clinical Research Facility; National Institute for Health Research (NIHR) University College London Hospitals (UCLH) Biomedical Research Centre and NIHR UCLH Clinical Research Facility; The Francis Crick Institute; The Francis Crick Institute; The Francis Crick Institute; The Francis Crick Institute; The Francis Crick Institute; The Francis Crick Institute; The Francis Crick Institute; London School of Hygiene & Tropical Medicine; London School of Hygiene & Tropical Medicine; London School of Hygiene & Tropical Medicine; National Institute for Health Research (NIHR) University College London Hospitals (UCLH) Biomedical Research Centre and NIHR UCLH Clinical Research Facility; The Francis Crick Institute; The Francis Crick Institute; The Francis Crick Institute; The Francis Crick Institute; National Institute for Health Research (NIHR) University College London Hospitals (UCLH) Biomedical Research Centre and NIHR UCLH Clinical Research Facility; The Francis Crick Institute; The Francis Crick Institute; The Francis Crick Institute; UCL; The Francis Crick Institute; The Francis Crick Institute; The Francis Crick Institute,"Heterogeneity in SARS-CoV-2 vaccine responses is not understood. Here, we identify four patterns of live-virus neutralizing antibody responses: individuals with hybrid immunity (with confirmed prior infection); rare individuals with low responses (paucity of S1-binding antibodies); and surprisingly, two further groups with distinct serological repertoires. One group - broad responders - neutralize a range of SARS-CoV-2 variants, whereas the other - narrow responders - neutralize fewer, less divergent variants. This heterogeneity does not correlate with Ancestral S1-binding antibody, rather the quality of the serological response. Furthermore, IgDlowCD27-CD137+ B cells and CCR6+ CD4+ T cells are enriched in broad responders before dose 3. Notably, broad responders have significantly longer infection-free time after their third dose. Understanding the control and persistence of these serological profiles could allow personalized approaches to enhance serological breadth after vaccination.",immunology,fuzzy,100,100 -medRxiv,10.1101/2023.05.23.23289798,2023-05-24,https://medrxiv.org/cgi/content/short/2023.05.23.23289798,Primary Care Post-COVID syndrome Diagnosis and Referral Coding,Robert Willans; Gail Allsopp; Pall Jonsson; Fiona Glen; Felix Greaves; John Macleod; Yinghui Wei; Sebastian Bacon; Amir Mehrkar; Alex Walker; Brian MacKenna; Louis Fisher; Ben Goldacre; - The OpenSAFELY Collaborative; - The CONVALESCENCE Collaborative,"National Institute of Health and Care Excellence; Royal College of General Practitioners; National Institute of Health and Care Excellence; National Institute of Health and Care Excellence; National Institute of Health and Care Excellence; University of Bristol; University of Plymouth; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford; ; ","IntroductionGuidelines for diagnosing and managing Post-COVID syndrome have been rapidly developed. Consistency of the application of these guidelines in primary care is unknown. Electronic health records provide an opportunity to review the use of codes relating to Post-COVID syndrome. This paper explores the use of primary care records as a surrogate uptake measure for NICEs rapid guideline ""managing the long-term effects of COVID-19"" by measuring the use of Post-COVID syndrome diagnosis and referral codes in the pathway. - -MethodWith the approval of NHS England we used routine clinical data from the OpenSafely-EMIS/-TPP platforms. Counts of Post-COVID syndrome diagnosis and referral codes were generated from a cohort of all adults, establishing numbers of diagnoses and referrals following diagnosis. The relationship between Post-COVID syndrome diagnosis and referral codes was explored with reference to NICEs rapid guideline. - -ResultsOf over 45 million patients, 69,220 (0.15%) had a Post-COVID syndrome diagnostic code, and 67,741 (0.15%) had a referral code. 78% of referral codes did not have an associated diagnosis code. 79% of diagnosis codes had no subsequent referral code. Only 18,633 (0.04%) had both. There were higher rates of both diagnosis and referral in those who were more deprived, female and some ethnic groups. - -DiscussionThis study demonstrates variation in diagnosis and referral coding rates for Post-COVID syndrome across different patient groups. The results, with limited crossover of referral and diagnostic codes, suggest only one type of code is usually recorded. Recording one code limits the use of routine data for monitoring Post-COVID syndrome diagnosis and management, but suggests several areas for improvement in coding. Post-COVID syndrome coding, particularly diagnosis coding, needs to improve before administrators and researchers can use it to evaluate care pathways.",epidemiology,fuzzy,100,100 medRxiv,10.1101/2023.05.17.23290105,2023-05-24,https://medrxiv.org/cgi/content/short/2023.05.17.23290105,Within-host SARS-CoV-2 viral kinetics informed by complex life course exposures reveals different intrinsic properties of Omicron and Delta variants,Timothy W Russell; Hermaleigh Townsley; Sam Abbott; Joel Hellewell; Edward J Carr; Lloyd Chapman; Rachael Pung; Billy J Quilty; David Hodgson; Ashley Fowler; Lorin Adams; Christopher Bailey; Harriet V Mears; Ruth Harvey; Bobbi Clayton; Nicola O'Reilly; Yenting Ngai; Jerome Nicod; Steve Gamblin; Bryan Williams; Sonia Gandhi; Charles Swanton; Rupert Beale; David LV Bauer; Emma C Wall; Adam Kucharski,London School of Hygiene and Tropical Medicine; The Francis Crick Institute; London School of Hygiene and Tropical Medicine; European Molecular Biology Laboratory; The Francis Crick Institute; Lancaster University; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; The Francis Crick Institute; The Francis Crick Institute; The Francis Crick Institute; The Francis Crick Institute; The Francis Crick Institute; The Francis Crick Institute; The Francis Crick Institute; The Francis Crick Institute; The Francis Crick Institute; The Francis Crick Institute; National Institute for Health Research (NIHR) University College London Hospitals (UCLH); The Francis Crick Institute; The Francis Crick Institute; The Francis Crick Institute; The Francis Crick Institute; The Francis Crick Institute; London School of Hygiene and Tropical Medicine,"The emergence of successive SARS-CoV-2 variants of concern (VOC) during 2020-22, each exhibiting increased epidemic growth relative to earlier circulating variants, has created a need to understand the drivers of such growth. However, both pathogen biology and changing host characteristics - such as varying levels of immunity - can combine to influence replication and transmission of SARS-CoV-2 within and between hosts. Disentangling the role of variant and host in individual-level viral shedding of VOCs is essential to inform COVID-19 planning and response, and interpret past epidemic trends. Using data from a prospective observational cohort study of healthy adult volunteers undergoing weekly occupational health PCR screening, we developed a Bayesian hierarchical model to reconstruct individual-level viral kinetics and estimate how different factors shaped viral dynamics, measured by PCR cycle threshold (Ct) values over time. Jointly accounting for both inter-individual variation in Ct values and complex host characteristics - such as vaccination status, exposure history and age - we found that age and number of prior exposures had a strong influence on peak viral replication. Older individuals and those who had at least five prior antigen exposures to vaccination and/or infection typically had much lower levels of shedding. Moreover, we found evidence of a correlation between the speed of early shedding and duration of incubation period when comparing different VOCs and age groups. Our findings illustrate the value of linking information on participant characteristics, symptom profile and infecting variant with prospective PCR sampling, and the importance of accounting for increasingly complex population exposure landscapes when analysing the viral kinetics of VOCs.",epidemiology,fuzzy,100,100 medRxiv,10.1101/2023.05.08.23289442,2023-05-11,https://medrxiv.org/cgi/content/short/2023.05.08.23289442,Cohort Profile: Post-hospitalisation COVID-19 study (PHOSP-COVID),Omer Elneima; Hamish J C McAuley; Olivia C Leavy; James D Chalmers; Alex Horsley; Ling-Pei Ho; Michael Marks; Krisnah Poinasamy; Betty Raman; Aarti Shikotra; Amisha Singapuri; Marco Sereno; Victoria C Harris; Linzy Houchen-Wolloff; Ruth M Saunders; Neil J Greening; Matthew Richardson; Jennifer K Quint; Andrew Briggs; Annemarie B Docherty; Steven Kerr; Ewen M Harrison; Nazir I Lone; Mathew Thorpe; Liam G Heaney; Keir E Lewis; Raminder Aul; Paul Beirne; Charlotte E Bolton; Jeremy S Brown; Gourab Choudhury; Nawar Diar Bakerly; Nicholas Easom; Carlos Echevarria; Jonathan Fuld; Nick Hart; John R Hurst; Mark G Jones; Dhruv Parekh; Paul E Pfeffer; Najib M Rahman; Sarah L Rowland-Jones; AA Roger Thompson; Caroline Jolley; Ajay M Shah; Dan G Wootton; Trudie Chalder; Melanie J Davies; Anthony De Soyza; John R Geddes; William Greenhalf; Simon Heller; Luke S Howard; Joseph Jacob; R Gisli Jenkins; Janet M Lord; William D-C Man; Gerry P McCann; Stefan Neubauer; Peter JM Openshaw; Joanna C Porter; Matthew J Rowland; Janet T Scott; Malcolm G Semple; Sally J Singh; David C Thomas; Mark Toshner; Aziz Sheikh; Chris E Brightling; Louise v Wain; Rachael A Evans; - on behalf of the PHOSP-COVID Collaborative Group,"The Institute for Lung Health, NIHR Leicester Biomedical Research Centre-Respiratory, University of Leicester, Leicester, UK; The Institute for Lung Health, NIHR Leicester Biomedical Research Centre-Respiratory, University of Leicester, Leicester, UK; Department of Population Health Sciences, University of Leicester, Leicester, UK; University of Dundee, Ninewells Hospital and Medical School, Dundee, UK; Division of Infection, Immunity & Respiratory Medicine, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK; MRC Human Immunology Unit, University of Oxford, Oxford, UK; Department of Clinical Research, London School of Hygiene & Tropical Medicine, London, UK; Asthma and Lung UK, London, UK; Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK; The Institute for Lung Health, NIHR Leicester Biomedical Research Centre-Respiratory, University of Leicester, Leicester, UK; The Institute for Lung Health, NIHR Leicester Biomedical Research Centre-Respiratory, University of Leicester, Leicester, UK; The Institute for Lung Health, NIHR Leicester Biomedical Research Centre-Respiratory, University of Leicester, Leicester, UK; The Institute for Lung Health, NIHR Leicester Biomedical Research Centre-Respiratory, University of Leicester, Leicester, UK; Centre for Exercise and Rehabilitation Science, NIHR Leicester Biomedical Research Centre- Respiratory, University of Leicester, Leicester, UK; The Institute for Lung Health, NIHR Leicester Biomedical Research Centre-Respiratory, University of Leicester, Leicester, UK; The Institute for Lung Health, NIHR Leicester Biomedical Research Centre-Respiratory, University of Leicester, Leicester, UK; The Institute for Lung Health, NIHR Leicester Biomedical Research Centre-Respiratory, University of Leicester, Leicester, UK; National Heart and Lung Institute, Imperial College London, London, UK; London School of Hygiene & Tropical Medicine, London, UK; Centre for Medical Informatics, The Usher Institute, University of Edinburgh, Edinburgh, UK; The Roslin Institute, University of Edinburgh, Edinburgh, UK; Centre for Medical Informatics, The Usher Institute, University of Edinburgh, Edinburgh, UK; Centre for Medical Informatics, The Usher Institute, University of Edinburgh, Edinburgh, UK; Centre for Medical Informatics, The Usher Institute, University of Edinburgh, Edinburgh, UK; Wellcome-Wolfson Institute for Experimental Medicine, Queens University Belfast, Belfast, UK; Hywel Dda University Health Board, Wales, UK; St George's University Hospitals NHS Foundation Trust, London, UK; Leeds Teaching Hospitals NHS Trust, Leeds, UK; NIHR Nottingham Biomedical Research Centre, University of Nottingham, Nottingham, UK; UCL Respiratory, Department of Medicine, University College London, London, UK; Centre for Inflammation Research, University of Edinburgh, Edinburgh, UK; Salford Royal NHS Foundation Trust, Manchester, UK; Infection Research Group, Hull University Teaching Hospitals, Hull, UK; Translational and Clinical Research Institute, Newcastle University, Newcastle Upon Tyne, UK; Department of Respiratory Medicine, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK; Lane Fox Respiratory Unit, Guy's and St Thomas' NHS Foundation Trust, London, UK; Royal Free London NHS Foundation Trust, London, UK; Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton, UK; Institute of Inflammation and Ageing, University of Birmingham, Birmingham, UK; Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK; NIHR Oxford Biomedical Research Centre, Oxford, UK; University of Sheffield, Sheffield, UK; University of Sheffield, Sheffield, UK; Centre for Human & Applied Physiological Sciences, School of Basic & Medical Biosciences, Faculty of Life Sciences & Medicine, King's College London, London, UK; King's College London British Heart Foundation Centre, London, UK; NIHR Health Protection Research Unit in Emerging and Zoonotic Infections, University of Liverpool, Liverpool, UK; Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK; NIHR Leicester Biomedical Research Centre, University of Leicester, Leicester, UK; Population Health Sciences Institute, Newcastle University, Newcastle Upon Tyne, UK; NIHR Oxford Health Biomedical Research Centre, University of Oxford, Oxford, UK; The CRUK Liverpool Experimental Cancer Medicine Centre, Liverpool, UK; Department of Oncology and Metabolism, University of Sheffield, Sheffield, UK; Imperial College Healthcare NHS Trust, London, UK; Centre for Medical Image Computing, University College London, London, UK; National Heart and Lung Institute, Imperial College London, London, UK; MRC-Versus Arthritis Centre for Musculoskeletal Ageing Research, Institute of Inflammation and Ageing, University of Birmingham, Birmingham, UK; Royal Brompton & Harefield Hospitals, Guy's and St. Thomas' NHS Foundation Trust, London, UK; Department of Cardiovascular Sciences, University of Leicester and the NIHR Leicester Biomedical Research Centre, Glenfield Hospital, Leicester; NIHR Oxford Biomedical Research Centre, Oxford, UK; National Heart and Lung Institute, Imperial College London, London, UK; UCL Respiratory, Department of Medicine, University College London, London, UK; Kadoorie Centre for Critical Care Research, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK; MRC-University of Glasgow Center for Virus research; NIHR Health Protection Research Unit in Emerging and Zoonotic Infections, University of Liverpool, Liverpool, UK; Centre for Exercise and Rehabilitation Science, NIHR Leicester Biomedical Research Centre-Respiratory, University of Leicester, Leicester, UK; Department of Immunology and Inflammation, Imperial College London, London, UK; NIHR Cambridge Biomedical Research Centre, Cambridge, United Kingdom; Centre for Medical Informatics, The Usher Institute, University of Edinburgh, Edinburgh, UK; The Institute for Lung Health, NIHR Leicester Biomedical Research Centre-Respiratory, University of Leicester, Leicester, UK; Department of Population Health Sciences, University of Leicester, Leicester, UK; The Institute for Lung Health, NIHR Leicester Biomedical Research Centre-Respiratory, University of Leicester, Leicester, UK; ","O_LIPHOSP-COVID is a national UK multi-centre cohort study of patients who were hospitalised for COVID-19 and subsequently discharged. C_LIO_LIPHOSP-COVID was established to investigate the medium- and long-term sequelae of severe COVID-19 requiring hospitalisation, understand the underlying mechanisms of these sequelae, evaluate the medium- and long-term effects of COVID-19 treatments, and to serve as a platform to enable future studies, including clinical trials. @@ -320,13 +313,6 @@ C_LI How this study might affect research, practice or policyO_LIThe findings contribute to the evidence base that long-COVID differences occur across industries and occupations, provides insights for employees, employers, occupational and healthcare for the industries and occupations that may need additional support for return- to-work policies and highlights sectors and occupations where further research is needed to understand the mechanisms resulting in long-COVID and how occupational factors influence the risk of developing long-COVID or interact with long-COVID to increase the impact on activities. C_LI",public and global health,fuzzy,100,100 -medRxiv,10.1101/2023.03.21.23287524,2023-03-22,https://medrxiv.org/cgi/content/short/2023.03.21.23287524,Employment outcomes of people with Long Covid symptoms: community-based cohort study,Daniel Ayoubkhani; Francesco Zaccardi; Koen B Pouwels; Ann Sarah Walker; Donald Houston; Nisreen A Alwan; Josh Martin; Kamlesh Khunti; Vahe Nafilyan,Office for National Statistics; University of Leicester; University of Oxford; University of Oxford; University of Portsmouth; University of Southampton; Bank of England; University of Leicester; Office for National Statistics,"BackgroundEvidence on the long-term employment consequences of SARS-CoV-2 infection is lacking. We used data from a large, community-based sample in the UK to estimate associations between Long Covid and subsequent employment outcomes. - -MethodsThis was an observational, longitudinal study using a pre-post design. We included survey participants from 3 February 2021 to 30 September 2022 when they were aged 16 to 64 years and not in full-time education. Using conditional logit modelling, we explored the time-varying relationship between Long Covid status [≥]12 weeks after a first test-confirmed SARS-CoV-2 infection (reference: pre-infection) and labour market inactivity (neither working nor looking for work) or workplace absence lasting [≥]4 weeks. - -ResultsOf 206,299 included participants (mean age 45 years, 54% female, 92% white), 15% were ever inactive in the labour market and 10% were ever long-term absent during follow-up. Compared with pre-infection, inactivity was higher in participants reporting Long Covid 30 to <40 weeks (adjusted odds ratio (aOR): 1.45; 95% CI: 1.17 to 1.81) or 40 to <52 weeks (1.34; 1.05 to 1.72) post-infection. Combining with official statistics on Long Covid prevalence, our estimates translate to 27,000 (95% CI: 6,000 to 47,000) working-age adults in the UK being inactive because of Long Covid in July 2022. - -ConclusionsLong Covid is likely to have contributed to reduced levels of participation in the UK labour market, though it is unlikely to be the sole driver. Further research is required to quantify the contribution of other factors, such as indirect health effects of the pandemic.",epidemiology,fuzzy,100,100 medRxiv,10.1101/2023.03.15.23287300,2023-03-19,https://medrxiv.org/cgi/content/short/2023.03.15.23287300,Risk factors for SARS-CoV-2 infection: A test-negative case-control study with additional population controls,Marjut Sarjomaa; Chi Zhang; Yngvar Tveten; Hege Kersten; Harald Reiso; Randi Eikeland; Johny Kongerud; Kristine Karlsrud Berg; Carina Thilesen; Svein Arne Nordbo; Ingeborg Aaberge; Jan Vandenbroucke; Neil Pearce; Anne Kristin Fell,Telemark Hospital: Sykehuset Telemark HF; Norwegian Institute of Public Health: Folkehelseinstituttet; Telemark Hospital: Sykehuset Telemark HF; Telemark Hospital: Sykehuset Telemark HF; Sorlandet Hospital; Sorlandet Hospital; University of Oslo; Sorlandet Sykehus HF; Unilabs Laboratory Medicine; St Olavs Hospital; Norwegian Institute of Public Health; Leiden University Medical Center; London School of Hygiene and Tropical Medicine; Telemark Hospital: Sykehuset Telemark HF,"ObjectivesTo assess risk factors for SARS-CoV-2 infection by first comparing positive cases with negative controls as determined by polymerase chain reaction (PCR) testing and then comparing these two groups with an additional population control group. Design and settingTest-negative design (TND), multicentre case-control study with additional population controls in South Eastern Norway. @@ -751,26 +737,6 @@ FindingsOf 8,799,079 visits, 147,278 (1{middle dot}7%) were PCR-positive. Over t InterpretationChange-points in growth rates of SARS-CoV-2 can be detected in near real-time using ISR and second derivatives of GAMs. To increase certainty about changes in epidemic trajectories both methods could be run in parallel. Running either method in near real-time on different infection surveillance data streams could provide timely warnings of changing underlying epidemiology. FundingUK Health Security Agency, Department of Health and Social Care (UK), Welsh Government, Department of Health (on behalf of the Northern Ireland Government), Scottish Government, National Institute for Health Research.",epidemiology,fuzzy,100,100 -medRxiv,10.1101/2022.09.11.22279823,2022-09-12,https://medrxiv.org/cgi/content/short/2022.09.11.22279823,Effects of the COVID-19 pandemic on the mental health of clinically extremely vulnerable children and children living with clinically extremely vulnerable people in Wales: A data linkage study,Laura Elizabeth Cowley; Karen Hodgson; Jiao Song; Tony Whiffen; Jacinta Tan; Ann John; Amrita Bandyopadhyay; Alisha R Davies,Swansea University; Public Health Wales; Public Health Wales; Welsh Government; University of Oxford; Swansea University; Swansea University; Public Health Wales,"ObjectivesTo determine whether clinically extremely vulnerable (CEV) children or children living with a CEV person in Wales were at greater risk of presenting with anxiety or depression in primary or secondary care during the COVID-19 pandemic compared with children in the general population, and to compare patterns of anxiety and depression during the pandemic (23rd March 2020-31st January 2021, referred to as 2020/21) and before the pandemic (March 23rd 2019-January 31st 2020, referred to as 2019/20), between CEV children and the general population. - -DesignPopulation-based cross-sectional cohort study using anonymised, linked, routinely collected health and administrative data held in the Secure Anonymised Information Linkage Databank. CEV individuals were identified using the COVID-19 Shielded Patient List. - -SettingPrimary and secondary healthcare settings covering 80% of the population of Wales. - -ParticipantsChildren aged 2-17 in Wales: CEV (3,769); living with a CEV person (20,033); or neither (415,009). - -Primary outcome measureFirst record of anxiety or depression in primary or secondary healthcare in 2019/20 and 2020/21, identified using Read and ICD-10 codes. - -ResultsA Cox regression model adjusted for demographics and history of anxiety or depression revealed that only CEV children were at greater risk of presenting with anxiety or depression during the pandemic compared with the general population (Hazard Ratio=2.27, 95% Confidence Interval=1.94-2.66, p<0.001). Compared with the general population, the risk amongst CEV children was higher in 2020/21 (Risk Ratio 3.04) compared with 2019/20 (Risk Ratio 1.90). In 2020/21, the cumulative incidence of anxiety or depression increased slightly amongst CEV children, but declined amongst the general population. - -ConclusionsDifferences in the cumulative incidences of recorded anxiety or depression in healthcare between CEV children and the general population were largely driven by a reduction in presentations to healthcare services by children in the general population during the pandemic. - -Strengths and limitations of this studyO_LIStrengths of this study include its novelty, national focus and clinical relevance; to date this is the first population-based study examining the effects of the COVID-19 pandemic on healthcare use for anxiety or depression amongst clinically extremely vulnerable (CEV) children and children living with a CEV person in Wales -C_LIO_LIWe compared 2020/21 data with pre-pandemic 2019/20 data for CEV children and children in the general population, to place the impact of the COVID-19 pandemic in the context of longer-term patterns of healthcare use -C_LIO_LIWe used a novel approach and linked multiple datasets to identify a cohort of children living with a CEV person in Wales during the COVID-19 pandemic -C_LIO_LIThere was heterogeneity within the Shielded Patient List that was used to create the cohorts of children identified as CEV or living with a CEV person, in terms of the type and severity of individuals underlying conditions; the manner in which people were added to the list; the time point that people were added to the list; and the extent to which people followed the shielding guidance -C_LIO_LIRoutinely collected healthcare data does not capture self-reported health, and is likely to underestimate the burden of common mental disorders in the population -C_LI",pediatrics,fuzzy,100,100 medRxiv,10.1101/2022.09.09.22279754,2022-09-09,https://medrxiv.org/cgi/content/short/2022.09.09.22279754,Contact patterns of UK home delivery drivers and their use of protective measures during the COVID-19 pandemic: a cross-sectional study,Jessica R E Bridgen; Hua Wei; Carl A Whitfield; Yang Han; Ian Hall; Chris Jewell; Martie JA van Tongeren; Jonathan M Read,Lancaster University; The University of Manchester; University of Manchester; University of Manchester; University of Manchester; Lancaster University; University of Manchester; Lancaster University,"ObjectivesTo quantify contact patterns of UK home delivery drivers and identify protective measures adopted during the pandemic. MethodsWe conducted a cross-sectional online survey to measure the interactions of 170 UK delivery drivers during a working shift between 7 December 2020 and 31 March 2021. @@ -787,27 +753,6 @@ ResultsRelaxation of COVID-19 restrictions from April 2021 coincided with reduce ConclusionsRelaxation of COVID-19 restrictions coincided with decreased face covering use, increased social mixing and a rebound in ARI and asthma exacerbations. Associations between incident ARI and risk of moderate/severe asthma exacerbation were similar for non-COVID-19 ARI and COVID-19, both before and after emergence of the SARS-CoV-2 omicron variant. FundingBarts Charity, UKRI",respiratory medicine,fuzzy,100,100 -medRxiv,10.1101/2022.08.29.22279359,2022-08-31,https://medrxiv.org/cgi/content/short/2022.08.29.22279359,Prophylactic Treatment of COVID-19 in Care Homes Trial (PROTECT-CH),Philip M Bath; Jonathan Ball; Matthew Boyd; Heather Gage; Matthew Glover; Maureen Godfrey; Bruce Guthrie; Jonathan Hewitt; Robert Howard; Thomas Jaki; Edmund Juszczak; Daniel Lasserson; Paul Leighton; Val Leyland; Wei Shen Lim; Pip Logan; Garry Meakin; Alan Montgomery; Reuben Ogollah; Peter Passmore; Philip Quinlan; Caroline Rick; Simon Royal; Susan D Shenkin; Clare Upton; Adam L Gordon; - PROTECT-CH Trialists,University of Nottingham; University of Nottingham; University of Nottingham; University of Surrey; University of Surrey; Private person; University of Edinburgh; Llandough Hospital; University College London; University of Cambridge; University of Nottingham; University of Warwick; University of Nottingham; Private person; Nottingham University Hospitals NHS Trust; University of Nottingham; University of Nottingham; University of Nottingham; University of Nottingham; Queen's University Belfast; University of Nottingham; University of Nottingham; Cripps Health Centre; University of Edinburgh; University of Nottingham; University of Nottingham; ,"BackgroundCoronavirus disease 2019 (COVID-19) is associated with significant mortality and morbidity in care homes. Novel or repurposed antiviral drugs may reduce infection and disease severity through reducing viral replication and inflammation. - -ObjectiveTo compare the safety and efficacy of antiviral agents (ciclesonide, niclosamide) for preventing SARS-CoV-2 infection and COVID-19 severity in care home residents. - -DesignCluster-randomised open-label blinded endpoint platform clinical trial testing antiviral agents in a post-exposure prophylaxis paradigm. - -SettingCare homes across all four United Kingdom member countries. - -ParticipantsCare home residents 65 years of age or older. - -InterventionsCare homes were to be allocated at random by computer to 42 days of antiviral agent plus standard care versus standard of care and followed for 60 days after randomisation. - -Main outcome measuresThe primary four-level ordered categorical outcome with participants classified according to the most serious of all-cause mortality, all-cause hospitalisation, SARS-CoV-2 infection and no infection. Analysis using ordinal logistic regression was by intention to treat. Other outcomes included the components of the primary outcome and transmission. - -ResultsDelays in contracting between NIHR and the manufacturers of potential antiviral agents significantly delayed any potential start date. Having set up the trial (protocol, approvals, insurance, website, database, routine data algorithms, training materials), the trial was stopped in September 2021 prior to contracting of care homes and general practitioners in view of the success of vaccination in care homes with significantly reduced infections, hospitalisations and deaths. As a result, the sample size target (based on COVID-19 rates and deaths occurring in February-June 2020) became unfeasible. - -LimitationsCare home residents were not approached about the trial and so were not consented and did not receive treatment. Hence, the feasibility of screening, consent, treatment and data acquisition, and potential benefit of post exposure prophylaxis were never tested. Further, contracting between the University of Nottingham and the PIs, GPs and care homes was not completed, so the feasibility of contracting with all the different groups at the scale needed was not tested. - -ConclusionsThe role of post exposure prophylaxis of COVID-19 in care home residents was not tested because of changes in COVID-19 incidence, prevalence and virulence as a consequence of the vaccination programme that rendered the study unfeasible. Significant progress was made in describing and developing the infrastructure necessary for a large scale Clinical Trial of Investigational Medicinal Products in care homes in all four UK nations. - -Future workThe role of post-exposure prophylaxis of COVID-19 in care home residents remains to be defined. Significant logistical barriers to conducting research in care homes during a pandemic need to be removed before such studies are possible in the required short timescale.",infectious diseases,fuzzy,100,100 medRxiv,10.1101/2022.08.29.22279333,2022-08-30,https://medrxiv.org/cgi/content/short/2022.08.29.22279333,A case-crossover study of the effect of vaccination on SARS-CoV-2 transmission relevant behaviours during a period of national lockdown in England and Wales,Aimee Serisier; Sarah Beale; Yamina I Boukari; Susan J Hoskins; Vincent Nguyen; Thomas Edward Byrne; Wing Lam Erica Fong; Ellen Fragaszy; Cyril Geismar; Jana Kovar; Alexei Yavlinsky; Andrew Hayward; Robert W Aldridge,University College London; University College London; University College London; Univerity College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London,"BackgroundStudies of COVID-19 vaccine effectiveness show increases in COVID-19 cases within 14 days of a first dose, potentially reflecting post-vaccination behaviour changes associated with SARS-CoV-2 transmission before vaccine protection. However, direct evidence for a relationship between vaccination and behaviour is lacking. We aimed to examine the association between vaccination status and self-reported non-household contacts and non-essential activities during a national lockdown in England and Wales. MethodsParticipants (n=1,154) who had received the first dose of a COVID-19 vaccine reported non-household contacts and non-essential activities from February to March 2021 in monthly surveys during a national lockdown in England and Wales. We used a case-crossover study design and conditional logistic regression to examine the association between vaccination status (pre-vaccination vs. 14 days post-vaccination) and self-reported contacts and activities within individuals. Stratified subgroup analyses examined potential effect heterogeneity by sociodemographic characteristics such as sex, household income or age group. @@ -1025,6 +970,15 @@ MethodsIn an online survey distributed to all staff at 18 geographically dispers ResultsWe identified 33 topics, grouped into two domains, each containing four themes. Our findings emphasise: the deleterious effect of increased workloads, lack of PPE, inconsistent advice/guidance, and lack of autonomy; differing experiences of home working as negative/positive; and the benefits of supportive leadership and peers in ameliorating challenges. Themes varied by demographics and time: discussion of home working decreasing over time, while discussion of workplace challenges increased. Discussion of mental health was lowest between September-November 2020, between the first and second waves of COVID-19 in the UK. DiscussionOur findings represent the most salient experiences of HCWs through the pandemic. STM enabled statistical examination of how the qualitative themes raised differed according to participant characteristics. This relatively underutilised methodology in healthcare research can provide more nuanced, yet generalisable, evidence than that available via surveys or small interview studies, and should be used in future research.",psychiatry and clinical psychology,fuzzy,100,100 +medRxiv,10.1101/2022.06.16.22276476,2022-06-16,https://medrxiv.org/cgi/content/short/2022.06.16.22276476,Moral injury and psychological wellbeing in UK healthcare staff,Victoria Williamson; Danielle Lamb; Matthew Hotopf; Rosalind Raine; Sharon Stevelink; Simon Wessely; Mary Jane Docherty; Ira Madan; Dominic Murphy; Neil Greenberg,King's College London; UCL; King's College London; King's College London; King's College London; King's College London; South London and Maudsley NHS Foundation Trust; Guy's and St Thomas' NHS Foundation Trust; King's College London; King's College London,"BackgroundPotentially morally injurious events (PMIEs) can negatively impact mental health. The COVID-19 pandemic may have placed healthcare staff at risk of moral injury. + +AimTo examine the impact of PMIE on healthcare staff wellbeing. + +Method12,965 healthcare staff (clinical and non-clinical) were recruited from 18 NHS-England trusts into a survey of PMIE exposure and wellbeing. + +ResultsPMIEs were significantly associated with adverse mental health symptoms across healthcare staff. Specific work factors were significantly associated with experiences of moral injury, including being redeployed, lack of PPE, and having a colleague die of COVID-19. Nurses who reported symptoms of mental disorders were more likely to report all forms of PMIEs than those without symptoms (AOR 2.7; 95% CI 2.2, 3.3). Doctors who reported symptoms were only more likely to report betrayal events, such as breach of trust by colleagues (AOR 2.7, 95% CI 1.5, 4.9). + +ConclusionsA considerable proportion of NHS healthcare staff in both clinical and non-clinical roles report exposure to PMIEs during the COVID-19 pandemic. Prospective research is needed to identify the direction of causation between moral injury and mental disorder as well as continuing to monitor the longer term outcomes of exposure to PMIEs.",psychiatry and clinical psychology,fuzzy,100,100 medRxiv,10.1101/2022.06.14.22276391,2022-06-16,https://medrxiv.org/cgi/content/short/2022.06.14.22276391,Factors associated with COVID-19 vaccine uptake in people with kidney disease: an OpenSAFELY cohort study,- The OpenSAFELY Collaborative; Edward PK Parker; John Tazare; William J Hulme; Christopher Bates; Rupert Beale; Edward J Carr; Jonathan Cockburn; Helen J Curtis; Louis Fisher; Amelia CA Green; Sam Harper; Frank Hester; Elsie MF Horne; Fiona Loud; Susan Lyon; Viyaasan Mahalingasivam; Amir Mehrkar; Linda Nab; John Parry; Shalini Santhakumaran; Retha Steenkamp; Jonathan AC Sterne; Alex J Walker; Elizabeth J Williamson; Michelle Willicombe; Bang Zheng; Ben Goldacre; Dorothea Nitsch; Laurie A Tomlinson,"-; London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK; London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX2 6GG, UK; TPP, TPP House, 129 Low Lane, Horsforth, Leeds, LS18 5PX, UK; The Francis Crick Institute, London, NW1 1AT, UK; UCL Department of Renal Medicine, Royal Free Hospital, London, UK; The Francis Crick Institute, London, NW1 1AT, UK; TPP, TPP House, 129 Low Lane, Horsforth, Leeds, LS18 5PX, UK; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX2 6GG, UK; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX2 6GG, UK; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX2 6GG, UK; TPP, TPP House, 129 Low Lane, Horsforth, Leeds, LS18 5PX, UK; TPP, TPP House, 129 Low Lane, Horsforth, Leeds, LS18 5PX, UK; Population Health Sciences, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK; NIHR Bristol Biomedical Research Centre, Bristol, UK; Kidney Care UK, Alton, UK; Patient Council, UK Kidney Association, Bristol, UK; London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX2 6GG, UK; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX2 6GG, UK; TPP, TPP House, 129 Low Lane, Horsforth, Leeds, LS18 5PX, UK; UK Renal Registry, Bristol, UK; UK Renal Registry, Bristol, UK; Population Health Sciences, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK; NIHR Bristol Biomedical Research Centre, Bristol, UK; H; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX2 6GG, UK; London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK; Centre for Inflammatory Disease, Department of Immunology and Inflammation, Imperial College London, Hammersmith Campus, Du Cane Road London, W12 0NN, UK; London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX2 6GG, UK; London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK; UK Renal Registry, Bristol, UK; London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK","BackgroundKidney disease is a significant risk factor for COVID-19-related mortality. Achieving high COVID-19 vaccine coverage among people with kidney disease is therefore a public health priority. MethodsWith the approval of NHS England, we performed a retrospective cohort study using the OpenSAFELY-TPP platform. Individual-level routine clinical data from 24 million people in England were included. A cohort of individuals with stage 3-5 chronic kidney disease (CKD) or receiving renal replacement therapy (RRT) at the start of the COVID-19 vaccine roll-out was identified based on evidence of reduced estimated glomerular filtration rate or inclusion in the UK Renal Registry. Individual-level factors associated with vaccine uptake were explored via Cox proportional hazards models. @@ -1104,13 +1058,6 @@ ResultsBetween December 16, 2021 and February 10, 2022, 3331 and 2689 patients w ConclusionIn routine care of non-hospitalised high-risk adult patients with COVID-19 in England, those who received sotrovimab were at lower risk of severe COVID-19 outcomes than those receiving molnupiravir.",epidemiology,fuzzy,100,100 medRxiv,10.1101/2022.05.21.22275368,2022-05-23,https://medrxiv.org/cgi/content/short/2022.05.21.22275368,"Variant-specific symptoms of COVID-19 among 1,542,510 people in England",Matthew Whitaker; Joshua Elliott; Barbara Bodinier; Wendy S Barclay; Helen Ward; Graham Cooke; Christl A Donnelly; Marc Chadeau-Hyam; Paul Elliott,Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London School of Public Health,"Infection with SARS-CoV-2 virus is associated with a wide range of symptoms. The REal-time Assessment of Community Transmission -1 (REACT-1) study has been monitoring the spread and clinical manifestation of SARS-CoV-2 among random samples of the population in England from 1 May 2020 to 31 March 2022. We show changing symptom profiles associated with the different variants over that period, with lower reporting of loss of sense of smell and taste for Omicron compared to previous variants, and higher reporting of cold-like and influenza-like symptoms, controlling for vaccination status. Contrary to the perception that recent variants have become successively milder, Omicron BA.2 was associated with reporting more symptoms, with greater disruption to daily activities, than BA.1. With restrictions lifted and routine testing limited in many countries, monitoring the changing symptom profiles associated with SARS-CoV-2 infection and induced changes in daily activities will become increasingly important.",infectious diseases,fuzzy,96,100 -medRxiv,10.1101/2022.05.19.22275214,2022-05-22,https://medrxiv.org/cgi/content/short/2022.05.19.22275214,Antibody levels following vaccination against SARS-CoV-2: associations with post-vaccination infection and risk factors,Nathan J Cheetham; Milla Kibble; Andrew Wong; Richard J Silverwood; Anika Knuppel; Dylan M Williams; Olivia K L Hamilton; Paul H Lee; Charis Bridger Staatz; Giorgio Di Gessa; Jingmin Zhu; Srinivasa Vittal Katikireddi; George B Ploubidis; Ellen J Thompson; Ruth C E Bowyer; Xinyuan Zhang; Golboo Abbasian; Maria Paz Garcia; Deborah Hart; Jeffrew Seow; Carl Graham; Neophytos Kouphou; Sam Acors; Michael H Malim; Ruth E Mitchell; Kate Northstone; Daniel Major-Smith; Sarah Matthews; Thomas Breeze; Michael Crawford; Lynn Molloy; Alex Siu Fung Kwong; Katie J Doores; Nishi Chaturvedi; Emma L Duncan; Nicholas J Timpson; Claire J Steves,King's College London; University of Cambridge; University College London; University College London; University College London; University College London; University of Glasgow; University of Leicester; University College London; University College London; University College London; University of Glasgow; University College London; King's College London; King's College London; King's College London; King's College London; King's College London; King's College London; King's College London; King's College London; King's College London; King's College London; King's College London; University of Bristol; University of Bristol; University of Bristol; University of Bristol; University of Bristol; University of Bristol; University of Bristol; University of Bristol; King's College London; University College London; King's College London; University of Bristol; King's College London,"SARS-CoV-2 antibody levels can be used to assess humoral immune responses following SARS-CoV-2 infection or vaccination, and may predict risk of future infection. From cross-sectional antibody testing of 9,361 individuals from TwinsUK and ALSPAC UK population-based longitudinal studies (jointly in April-May 2021, and TwinsUK only in November 2021-January 2022), we tested associations between antibody levels following vaccination and: (1) SARS-CoV-2 infection following vaccination(s); (2) health, socio-demographic, SARS-CoV-2 infection and SARS-CoV-2 vaccination variables. - -Within TwinsUK, single-vaccinated individuals with the lowest 20% of anti-Spike antibody levels at initial testing had 3-fold greater odds of SARS-CoV-2 infection over the next six to nine months, compared to the top 20%. In TwinsUK and ALSPAC, individuals identified as at increased risk of COVID-19 complication through the UK ""Shielded Patient List"" had consistently greater odds (2 to 4-fold) of having antibody levels in the lowest 10%. Third vaccination increased absolute antibody levels for almost all individuals, and reduced relative disparities compared with earlier vaccinations. - -These findings quantify the association between antibody level and risk of subsequent infection, and support a policy of triple vaccination for the generation of protective antibodies. - -Lay summaryIn this study, we analysed blood samples from 9,361 participants from two studies in the UK: an adult twin registry, TwinsUK (4,739 individuals); and the Avon Longitudinal Study of Parents and Children, ALSPAC (4,622 individuals). We did this work as part of the UK Government National Core Studies initiative researching COVID-19. We measured blood antibodies which are specific to SARS-CoV-2 (which causes COVID-19). Having a third COVID-19 vaccination boosted antibody levels. More than 90% of people from TwinsUK had levels after third vaccination that were greater than the average level after second vaccination. Importantly, this was the case even in individuals on the UK ""Shielded Patient List"". We found that people with lower antibody levels after first vaccination were more likely to report having COVID-19 later on, compared to people with higher antibody levels. People on the UK ""Shielded Patient List"", and individuals who reported that they had poorer general health, were more likely to have lower antibody levels after vaccination. In contrast, people who had had a previous COVID-19 infection were more likely to have higher antibody levels following vaccination compared to people without infection. People receiving the Oxford/AstraZeneca rather than the Pfizer BioNTech vaccine had lower antibody levels after one or two vaccinations. However, after a third vaccination, there was no difference in antibody levels between those who had Oxford/AstraZeneca and Pfizer BioNTech vaccines for their first two doses. These findings support having a third COVID-19 vaccination to boost antibodies.",epidemiology,fuzzy,100,100 medRxiv,10.1101/2022.05.11.22274964,2022-05-16,https://medrxiv.org/cgi/content/short/2022.05.11.22274964,Mental health outcomes following COVID-19 infection: Evidence from 11 UK longitudinal population studies,Ellen J Thompson; Jean Stafford; Bettina Moltrecht; Charlotte F Huggins; Alex S F Kwong; Richard J Shaw; Paola Zaninotto; Kishan Patel; Richard J Silverwood; Eoin McElroy; Matthias Pierce; Michael J Green; Ruth Bowyer; Jane Maddock; Kate Tilling; Srinivasa Vittal Katikireddi; George B Ploubidis; Professor D Porteous; Nicholas J Timpson; Nish Chaturvedi; Claire Steves; Praveetha Patalay,"Department of Twin Research and Genetic Epidemiology Kings College London; MRC Unit for Lifelong Health and Ageing, UCL; Centre for Longitudinal Studies UCL Social Research Institute University College London; Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh; Division of Psychiatry, University of Edinburgh; Population Health Sciences, University of Bristol; MRC/CSO Social & Public Health Sciences Unit, Institute of Health & Wellbeing, University of Glasgow; Department of Epidemiology and Public Health UCL; MRC Unit for Lifelong Health and Ageing UCL; Centre for Longitudinal Studies UCL Social Research Institute University College London; School of Psychology Ulster University; Division of Psychology & Mental Health The University of Manchester; MRC CSO Social and Public Health Sciences Unit University of Glasgow; Department of Twin Research and Genetic Epidemiology King's College London; MRC Unit for Lifelong Health and Ageing UCL; MRC Integrative Epidemiology Unit University of Bristol; MRC CSO Social and Public Health Sciences UnitUniversity of Glasgow; Centre for Longitudinal Studies UCL Social Research Institute University College London; Centre for Genomic and Experimental Medicine University of Edinburgh; MRC Integrative Epidemiology Unit University of Bristol; MRC Unit for Lifelong Health and Ageing UCL; Department of Twin Research and Genetic Epidemiology King's College London; Centre for Longitudinal Studies and MRC Unit for Lifelong Health and Ageing University College London","BackgroundEvidence on associations between COVID-19 illness and mental health is mixed. We examined longitudinal associations between COVID-19 and mental health while considering: 1) pre-pandemic mental health, 2) time since infection; 3) subgroup differences; and 4) confirmation of infection via self-reported test, and serology data. MethodsUsing data from 11 UK longitudinal studies, involving 54,442 participants, with 2 to 8 repeated measures of mental health and COVID-19 between April 2020 and April 2021, we standardised continuous mental health scales within each study across time. We investigated associations between COVID-19 (self-report, test-confirmed, serology-confirmed) and mental health using multilevel generalised estimating equations. We examined whether associations varied by age, sex, ethnicity, education and pre-pandemic mental health. Effect-sizes were pooled in random-effects meta-analyses. @@ -1188,6 +1135,11 @@ C_LI C_TEXTBOX",primary care research,fuzzy,100,100 medRxiv,10.1101/2022.05.03.22274395,2022-05-05,https://medrxiv.org/cgi/content/short/2022.05.03.22274395,Development and evaluation of low-volume tests to detect and characterise antibodies to SARS-CoV-2,Alice Halliday; Anna E Long; Holly E Baum; Amy C Thomas; Kathryn L Shelley; Elizabeth Oliver; Kapil Gupta; Ore Francis; Maia Kavanagh Williamson; Natalie Di Bartolo; Matthew J Randell; Yassin Ben Khoud; Ilana Kelland; Georgina Mortimer; Olivia Ball; Charlie Plumptre; Kyla Chandler; Ulrike Obst; Massimiliano Secchi; Lorenzo Piemonti; Vito Lampasona; Joyce Smith; Michaela Gregorova; Lea Knezevic; Jane Metz; Rachael Barr; Begonia Morales-Aza; Jennifer Oliver; Lucy Collingwood; Benjamin Hitchings; Susan Ring; Linda Wooldridge; Laura Rivino; Nicholas J Timpson; Jorgen McKernon; Peter Muir; Fergus W Hamilton; David Arnold; Derek N Woolfson; Anu Goenka; Andrew D Davidson; Ashley Mark Toye; Imre Berger; Mick Bailey; Kathleen M Gillespie; Alistair JK Williams; Adam Finn,"University of Bristol; University of Bristol; University of Bristol; University of Bristol; University of Bristol; University of Bristol; University of Bristol; University of Bristol; University of Bristol; University of Bristol; University of Bristol; University of Bristol; University of Bristol; University of Bristol; University of Bristol; University of Bristol; University of Bristol; University of Bristol; IRCCS Ospedale San Raffaele; IRCCS Ospedale San Raffaele; IRCCS Ospedale San Raffaele; University of Bristol; University of Bristol; University of Bristol; University of Bristol; University of Bristol; University of Bristol; University of Bristol; University of Bristol; University of Bristol; University of Bristol; University of Bristol; University of Bristol; University of Bristol; National Infection Service, UK Health Security Agency, Southmead Hospital, Bristol, UK; National Infection Service, UK Health Security Agency, Southmead Hospital, Bristol, UK; University of Bristol; University of Bristol; University of Bristol; University of Bristol; University of Bristol; University of Bristol; University of Bristol; University of Bristol; University of Bristol; University of Bristol; University of Bristol","Low-volume antibody assays can be used to track SARS-CoV-2 infection rates in settings where active testing for virus is limited and remote sampling is optimal. We developed 12 ELISAs detecting total or antibody isotypes to SARS-CoV-2 nucleocapsid, spike protein or its receptor binding domain (RBD), 3 anti-RBD isotype specific luciferase immunoprecipitation system (LIPS) assays and a novel Spike-RBD bridging LIPS total-antibody assay. We utilised pre-pandemic (n=984) and confirmed/suspected recent COVID-19 sera taken pre-vaccination rollout in 2020 (n=269). Assays measuring total antibody discriminated best between pre-pandemic and COVID-19 sera and were selected for diagnostic evaluation. In the blind evaluation, two of these assays (Spike Pan ELISA and Spike-RBD Bridging LIPS assay) demonstrated >97% specificity and >92% sensitivity for samples from COVID- 19 patients taken >21 days post symptom onset or PCR test. These assays offered better sensitivity for the detection of COVID-19 cases than a commercial assay which requires 100-fold larger serum volumes. This study demonstrates that low-volume in- house antibody assays can provide good diagnostic performance, and highlights the importance of using well-characterised samples and controls for all stages of assay development and evaluation. These cost-effective assays may be particularly useful for seroprevalence studies in low and middle-income countries.",infectious diseases,fuzzy,100,100 +medRxiv,10.1101/2022.05.03.22274602,2022-05-03,https://medrxiv.org/cgi/content/short/2022.05.03.22274602,Accident and emergency (AE) attendance in England following infection with SARS-CoV-2 Omicron or Delta,Daniel J Grint; Kevin Wing; Hamish P Gibbs; Stephen JW Evans; Elizabeth J Williamson; Krishnan Bhaskaran; Helen I McDonald; Alex J Walker; David Evans; George Hickman; Rohini Mathur; Anna Schultze; Christopher T Rentsch; John Tazare; Ian J Douglas; Helen J Curtis; Caroline E Morton; Sebastian CJ Bacon; Simon Davy; Brian MacKenna; Peter Inglesby; Richard Croker; John Parry; Frank Hester; Sam Harper; Nicholas J DeVito; William J Hulme; Christopher Bates; Jonathan Cockburn; Amir Mehrkar; Ben Goldacre; Rosalind M Eggo; Laurie Tomlinson,London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; University of Oxford; University of Oxford; University of Oxford; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; TPP; TPP; TPP; University of Oxford; University of Oxford; TPP; TPP; University of Oxford; University of Oxford; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine,"The SARS-CoV-2 Omicron variant is increasing in prevalence around the world. Accurate estimation of disease severity associated with Omicron is critical for pandemic planning. We found lower risk of accident and emergency (AE) attendance following SARS-CoV-2 infection with Omicron compared to Delta (HR: 0.39 (95% CI: 0.30 - 0.51; P<.0001). For AE attendances that lead to hospital admission, Omicron was associated with an 85% lower hazard compared with Delta (HR: 0.14 (95% CI: 0.09 - 0.24; P<.0001)). + +Conflicts of InterestsNothing to declare. + +Funding statementThis work was supported by the Medical Research Council MR/V015737/1. TPP provided technical expertise and infrastructure within their data centre pro bono in the context of a national emergency. Rosalind Eggo is funded by HDR UK (grant: MR/S003975/1), MRC (grant: MC_PC 19065), NIHR (grant: NIHR200908).",infectious diseases,fuzzy,100,100 medRxiv,10.1101/2022.04.29.22274267,2022-05-01,https://medrxiv.org/cgi/content/short/2022.04.29.22274267,Multi-omics identify LRRC15 as a COVID-19 severity predictor and persistent pro-thrombotic signals in convalescence,Jack S Gisby; Norzawani B Buang; Artemis Papadaki; Candice L Clarke; Talat H Malik; Nicholas Medjeral-Thomas; Damiola Pinheiro; Paige M Mortimer; Shanice Lewis; Eleanor Sandhu; Stephen P McAdoo; Maria F Prendecki; Michelle Willicombe; Matthew C Pickering; Marina Botto; David C Thomas; James E Peters,Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London,"Patients with end-stage kidney disease (ESKD) are at high risk of severe COVID-19. Here, we performed longitudinal blood sampling of ESKD haemodialysis patients with COVID-19, collecting samples pre-infection, serially during infection, and after clinical recovery. Using plasma proteomics, and RNA-sequencing and flow cytometry of immune cells, we identified transcriptomic and proteomic signatures of COVID-19 severity, and found distinct temporal molecular profiles in patients with severe disease. Supervised learning revealed that the plasma proteome was a superior indicator of clinical severity than the PBMC transcriptome. We showed that both the levels and trajectory of plasma LRRC15, a proposed co-receptor for SARS-CoV-2, are the strongest predictors of clinical outcome. Strikingly, we observed that two months after the acute infection, patients still display dysregulated gene expression related to vascular, platelet and coagulation pathways, including PF4 (platelet factor 4), which may explain the prolonged thrombotic risk following COVID-19.",infectious diseases,fuzzy,100,100 medRxiv,10.1101/2022.04.28.22273177,2022-04-29,https://medrxiv.org/cgi/content/short/2022.04.28.22273177,Occupational differences in SARS-CoV-2 infection: Analysis of the UK ONS Coronavirus (COVID-19) Infection Survey,Sarah Rhodes; Jack Wilkinson; Neil Pearce; Will Mueller; Mark Cherrie; Katie Stocking; Matthew Gittins; Srinivasa Vittal Katikireddi; Martie van Tongeren,University of Manchester; University of Manchester; London School of Hygiene and Tropical Medicine; Institute of Occupational Medicine; Institute of Occupational Medicine; University of Manchester; University of Manchester; University of Glasgow; University of Manchester,"BackgroundConsiderable concern remains about how occupational SARS-CoV-2 risk has evolved during the COVID-19 pandemic. We aimed to ascertain which occupations had the greatest risk of SARS-CoV-2 infection and explore how relative differences varied over the pandemic. @@ -1397,15 +1349,6 @@ ConclusionThis work suggests that, without interventions, significant transmissi Author summaryDuring the COVID-19 pandemic the home-delivery sector was vital to maintaining peoples access to certain goods, and sustaining levels of economic activity for a variety of businesses. However, this important work necessarily involved contact with a large number of customers as well as colleagues. This means that questions have often been raised about whether enough was being done to keep customers and staff safe. Estimating the potential risk to customers and staff is complex, but here we tackle this problem by building a model of workplace and customer contacts, from which we simulate SARS-CoV-2 transmission. By involving industry representatives in the development of this model, we have simulated interventions that have either been applied or considered, and so the findings of this study are relevant to decisions made in that sector. Furthermore, we can learn generic lessons from this specific case study which apply to many types of shared workplace as well as highlighting implications of the highly stochastic nature of disease transmission in small populations.",epidemiology,fuzzy,100,100 medRxiv,10.1101/2022.03.17.22272535,2022-03-18,https://medrxiv.org/cgi/content/short/2022.03.17.22272535,Comparison of the 2021 COVID-19 'Roadmap' Projections against Public Health Data,Matt J Keeling; Louise J Dyson; Michael Tildesley; Edward M Hill; Sam M Moore,University of Warwick; University of Warwick; University of Warwick; University of Warwick; University of Warwick,"Control and mitigation of the COVID-19 pandemic in England has relied on a combination of vaccination and non-pharmaceutical interventions (NPIs). Some of these NPIs are extremely costly (economically and socially), so it was important to relax these promptly without overwhelming already burdened health services. The eventual policy was a Roadmap of four relaxation steps throughout 2021, taking England from lock-down to the cessation of all restrictions on social interaction. In a series of six Roadmap documents generated throughout 2021, models assessed the potential risk of each relaxation step. Here we show that the model projections generated a reliable estimation of medium-term hospital admission trends, with the data points up to September 2021 generally lying within our 95% prediction intervals. The greatest uncertainties in the modelled scenarios came from vaccine efficacy estimates against novel variants, and from assumptions about human behaviour in the face of changing restrictions and risk.",epidemiology,fuzzy,100,100 medRxiv,10.1101/2022.03.15.22272362,2022-03-16,https://medrxiv.org/cgi/content/short/2022.03.15.22272362,Community-level characteristics of COVID-19 vaccine hesitancy in England: A nationwide cross-sectional study,Georges Bucyibaruta; Marta Blangialdo; Garyfallos Konstantinoudis,Imperial College London; Imperial College London; Imperial College London,"One year after the start of the COVID-19 vaccination programme in England, more than 43 million people older than 12 years old had received at least a first dose. Nevertheless, geographical differences persist, and vaccine hesitancy is still a major public health concern; understanding its determinants is crucial to managing the COVID-19 pandemic and preparing for future ones. In this cross-sectional population-based study we used cumulative data on the first dose of vaccine received by 01-01-2022 at Middle Super Output Area level in England. We used Bayesian hierarchical spatial models and investigated if the geographical differences in vaccination uptake can be explained by a range of community-level characteristics covering socio-demographics, political view, COVID-19 health risk awareness and targeting of high risk groups and accessibility. Deprivation is the covariate most strongly associated with vaccine uptake (Odds Ratio 0.55, 95%CI 0.54-0.57; most versus least deprived areas). The most ethnically diverse areas have a 38% (95%CI 36-40%) lower odds of vaccine uptake compared with those least diverse. Areas with the highest proportion of population between 12 and 24 years old had lower odds of vaccination (0.87, 95%CI 0.85-0.89). Finally increase in vaccine accessibility is associated with higher COVID-19 uptake (OR 1.07, 95%CI 1.03-1.12). Our results suggest that one year after the start of the vaccination programme, there is still evidence of inequalities in uptake, affecting particularly minorities and marginalised groups. Strategies including prioritising active outreach across communities and removing practical barriers and factors that make vaccines less accessible are needed to level up the differences.",epidemiology,fuzzy,94,100 -medRxiv,10.1101/2022.03.14.22272283,2022-03-14,https://medrxiv.org/cgi/content/short/2022.03.14.22272283,Migrants' primary care utilisation before and during the COVID-19 pandemic in England: An interrupted time series,Claire X Zhang; Yamina Boukari; Neha Pathak; Rohini Mathur; Srinivasa Vittal Katikireddi; Parth Patel; Inês Campos-Matos; Dan Lewer; Vincent Nguyen; Greg Hugenholtz; Rachel Burns; Amy R Mulick; Alasdair Henderson; Robert W Aldridge,UCL; University College London; University College London; London School of Hygiene and Tropical Medicine; University of Glasgow; University College London; Department of Health and Social Care; University College London; University College London; University College London; University College London; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; UCL,"BackgroundHow international migrants access and use primary care in England is poorly understood. We aimed to compare primary care consultation rates between international migrants and non-migrants in England before and during the COVID-19 pandemic (2015- 2020). - -MethodsUsing linked data from the Clinical Practice Research Datalink (CPRD) GOLD and the Office for National Statistics, we identified migrants using country-of-birth, visa-status or other codes indicating international migration. We ran a controlled interrupted time series (ITS) using negative binomial regression to compare rates before and during the pandemic. - -FindingsIn 262,644 individuals, pre-pandemic consultation rates per person-year were 4.35 (4.34-4.36) for migrants and 4.6 (4.59-4.6) for non-migrants (RR:0.94 [0.92-0.96]). Between 29 March and 26 December 2020, rates reduced to 3.54 (3.52-3.57) for migrants and 4.2 (4.17-4.23) for non-migrants (RR:0.84 [0.8-0.88]). Overall, this represents an 11% widening of the pre-pandemic difference in consultation rates between migrants and non-migrants during the first year of the pandemic (RR:0.89, 95%CI:0.84-0.94). This widening was greater for children, individuals whose first language was not English, and individuals of White British, White non-British and Black/African/Caribbean/Black British ethnicities. - -InterpretationMigrants were less likely to use primary care before the pandemic and the first year of the pandemic exacerbated this difference. As GP practices retain remote and hybrid models of service delivery, they must improve services and ensure they are accessible and responsive to migrants healthcare needs. - -FundingThis study was funded by the Medical Research Council (MR/V028375/1) and Wellcome Clinical Research Career Development Fellowship (206602).",primary care research,fuzzy,100,100 medRxiv,10.1101/2022.03.10.22272177,2022-03-13,https://medrxiv.org/cgi/content/short/2022.03.10.22272177,The Omicron SARS-CoV-2 epidemic in England during February 2022,Marc Chadeau-Hyam; David Tang; Oliver Eales; Barbara Bodinier; Haowei Wang; Jakob Jonnerby; Matthew Whitaker; Joshua Elliott; David Haw; Caroline E. Walters; Christina Atchinson; Peter J. Diggle; Andrew J. Page; Deborah Ashby; Wendy Barclay; Graham Taylor; Graham Cooke; Helen Ward; Ara Darzi; Christl A Donnelly; Paul Elliott,"School of Public Health, Imperial College London, UK; School of Public Health, Imperial College London, UK; School of Public Health, Imperial College London, UKMRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergency; School of Public Health, Imperial College London, UK; School of Public Health, Imperial College London, UKMRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergency; School of Public Health, Imperial College London, UKMRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergency; School of Public Health, Imperial College London, UK; Imperial College Healthcare NHS Trust, UKDepartment of Infectious Disease, Imperial College London, UK; School of Public Health, Imperial College London, UKMRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergency; School of Public Health, Imperial College London, UKMRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergency; School of Public Health, Imperial College London, UK; CHICAS, Lancaster Medical School, Lancaster University, UK and Health Data Research, UK; Quadram Institute, Norwich, UK; School of Public Health, Imperial College London, UK; Department of Infectious Disease, Imperial College London, UK; Department of Infectious Disease, Imperial College London, UK; Department of Infectious Disease, Imperial College London, UKImperial College Healthcare NHS Trust, UKNational Institute for Health Research Imperial Biomedical; School of Public Health, Imperial College London, UKImperial College Healthcare NHS Trust, UKNational Institute for Health Research Imperial Biomedical Research; Imperial College Healthcare NHS Trust, UKNational Institute for Health Research Imperial Biomedical Research Centre, UKInstitute of Global Health Innovation at ; School of Public Health, Imperial College London, UKMRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergency; School of Public Health, Imperial College London, UKImperial College Healthcare NHS Trust, UKNational Institute for Health Research Imperial Biomedical Research","BackgroundThe third wave of COVID-19 in England peaked in January 2022 resulting from the rapid transmission of the Omicron variant. However, rates of hospitalisations and deaths were substantially lower than in the first and second waves MethodsIn the REal-time Assessment of Community Transmission-1 (REACT-1) study we obtained data from a random sample of 94,950 participants with valid throat and nose swab results by RT-PCR during round 18 (8 February to 1 March 2022). @@ -1436,31 +1379,6 @@ Research in contextO_ST_ABSEvidence before this studyC_ST_ABSWe searched PubMed, Added value of this studyThis study is among the first to provide a detailed analysis of a wide range of risk factors for breakthrough SARS-CoV-2 infection, both after the primary course of vaccination and after a booster dose. Our large study size and detailed data have allowed us to investigate associations with various sociodemographic, clinical, pharmacological, and nutritional factors. Monthly follow-up data have additionally given us the opportunity to consider the effects of behaviours that may have changed across the pandemic, while adjusting for local SARS-CoV-2 incidence. Implications of all the available evidenceOur findings add to growing evidence that risk factors for SARS-CoV-2 infection after primary or booster vaccinations can differ to those in unvaccinated populations, with effects attenuated for previously observed risk factors such as body-mass index and Asian ethnicity. The clear difference we observed between the efficacies of ChAdOx1 and BNT162b2 as the primary course of vaccination appears to have been reduced by the use of BNT162b2 boosters, but not by mNRA-1273 boosters. As more countries introduce booster vaccinations, future population-based studies with longer follow-up will be needed to investigate our findings further.",epidemiology,fuzzy,100,100 -medRxiv,10.1101/2022.03.13.22272176,2022-03-13,https://medrxiv.org/cgi/content/short/2022.03.13.22272176,Vaccination against SARS-CoV-2 in UK school-aged children and young people decreases infection rates and reduces COVID-19 symptoms,Erika Molteni; Liane S Canas; Kerstin Klaser; Jie Deng; Sunil S Bhopal; Robert C Hughes; Liyuan Chen; Benjamin Murray; Eric Kerfoot; Michela Antonelli; Carole Helene Sudre; Joan Capdevila Pujol; Lorenzo Polidori; Anna May; Alexander Hammers; Jonathan Wolf; Timothy Spector; Claire J Steves; Sebastien Ourselin; Michael Absoud; Marc Modat; Emma L Duncan,"King's College London; King's College London; King's College London; King's College London; Newcastle University; London School of Hygiene & Tropical Medicine, London; King's College London; King's College London; King's College London; King's College London; King's College London; Zoe Limited, London, UK; Zoe Limited, London, UK; Zoe Limited, London, UK; King's College London; Zoe Limited, London, UK; King's College London; King's College London; King's College London; King's College London; King's College London; King's College London","BackgroundWe aimed to explore the effectiveness of one-dose BNT162b2 vaccination upon SARS-CoV-2 infection, its effect on COVID-19 presentation, and post-vaccination symptoms in children and young people (CYP) in the UK during periods of Delta and Omicron variant predominance. - -MethodsIn this prospective longitudinal cohort study, we analysed data from 115,775 CYP aged 12-17 years, proxy-reported through the Covid Symptom Study (CSS) smartphone application. We calculated post-vaccination infection risk after one dose of BNT162b2, and described the illness profile of CYP with post-vaccination SARS- CoV-2 infection, compared to unvaccinated CYP, and post-vaccination side-effects. - -FindingsBetween August 5, 2021 and February 14, 2022, 25,971 UK CYP aged 12-17 years received one dose of BNT162b2 vaccine. Vaccination reduced (proxy-reported) infection risk (-80{middle dot}4% and -53{middle dot}7% at 14-30 days with Delta and Omicron variants respectively, and -61{middle dot}5% and -63{middle dot}7% after 61-90 days). The probability of remaining infection-free diverged soon after vaccination, and was greater in CYP with prior SARS-CoV-2 infection. Vaccinated CYP who contracted SARS-CoV-2 during the Delta period had milder disease than unvaccinated CYP; during the Omicron period this was only evident in children aged 12-15 years. Overall disease profile was similar in both vaccinated and unvaccinated CYP. Post-vaccination local side-effects were common, systemic side-effects were uncommon, and both resolved quickly. - -InterpretationOne dose of BNT162b2 vaccine reduced risk of SARS-CoV-2 infection for at least 90 days in CYP aged 12-17 years. Vaccine protection varied for SARS-CoV-2 variant type (lower for Omicron than Delta variant), and was enhanced by pre-vaccination SARS-CoV-2 infection. Severity of COVID-19 presentation after vaccination was generally milder, although unvaccinated CYP also had generally mild disease. Overall, vaccination was well-tolerated. - -FundingUK Government Department of Health and Social Care, Chronic Disease Research Foundation, The Wellcome Trust, UK Engineering and Physical Sciences Research Council, UK Research and Innovation London Medical Imaging & Artificial Intelligence Centre for Value Based Healthcare, UK National Institute for Health Research, UK Medical Research Council, British Heart Foundation and Alzheimers Society, and ZOE Limited. - -Research in context - -Evidence before this studyWe searched PubMed database for peer-reviewed articles and medRxiv for preprint papers, published between January 1, 2021 and February 15, 2022 using keywords (""SARS-CoV-2"" OR ""COVID-19"") AND (child* OR p?ediatric* OR teenager*) AND (""vaccin*"" OR ""immunization campaign"") AND (""efficacy"" OR ""effectiveness"" OR ""symptoms"") AND (""delta"" or ""omicron"" OR ""B.1.617.2"" OR ""B.1.1.529""). The PubMed search retrieved 36 studies, of which fewer than 30% specifically investigated individuals <18 years. - -Eleven studies explored SARS-CoV-2 viral transmission: seroprevalence in children (n=4), including age-dependency of susceptibility to SARS-CoV-2 infection (n=1), SARS-CoV-2 transmission in schools (n=5), and the effect of school closure on viral transmission (n=1). - -Eighteen documents reported clinical aspects, including manifestation of infection (n=13), symptomatology, disease duration, and severity in children. Other studies estimated emergency department visits, hospitalization, need for intensive care, and/or deaths in children (n=4), and explored prognostic factors (n=1). - -Thirteen studies explored vaccination-related aspects, including vaccination of children within specific paediatric co-morbidity groups (e.g., children with Down syndrome, inflammatory bowel disease, and cancer survivors, n=4), mRNA vaccine efficacy in children and adolescents from the general population (n=7), and the relation between vaccination and severity of disease and hospitalization cases (n=2). Four clinical trials were conducted using mRNA vaccines in minors, also exploring side effects. Sixty percent of children were found to have side effects after BNT162b2 vaccination, and especially after the second dose; however, most symptoms were mild and transient apart from rare uncomplicated skin ulcers. Two studies focused on severe adverse effects and safety of SARS-CoV-2 vaccines in children, reporting on myocarditis episodes and two cases of Guillain-Barre syndrome. All other studies were beyond the scope of our research. - -Added value of this studyWe assessed multiple components of the UK vaccination campaign in a cohort of children and young people (CYP) aged 12-17 years drawn from a large UK community-based citizen-science study, who received a first dose of BNT162b2 vaccine. We describe a variant-dependent protective effect of the first dose against both Delta and Omicron, with additional protective effect of pre-vaccination SARS- CoV-2 infection on post-vaccination re-infection. We compare the illness profile in CYP infected post-vaccination with that of unvaccinated CYP, demonstrating overall milder disease with fewer symptoms for vaccinated CYP. We describe local and systemic side-effects during the first week following first-dose vaccination, confirming that local symptoms are common, systemic symptoms uncommon, and both usually transient. - -Implications of all the available evidenceOur data confirm that first dose BNT162b2 vaccination in CYP reduces risk of infection by SARS-CoV-2 variants, with generally local and brief side-effects. If infected after vaccination, COVID-19 is milder, if manifest at all. The study aims to contribute quantitative evidence to the risk-benefit evaluation of vaccination in CYP to inform discussion regarding rationale for their vaccination and the designing of national immunisation campaigns for this age group; and applies citizen-science approaches in the conduct of epidemiological surveillance and data collection in the UK community. - -Importantly, this study was conducted during Delta and Omicron predominance in UK; specificity of vaccine efficacy to variants is also illustrated; and results may not be generalizable to future SARS-CoV-2 strains.",epidemiology,fuzzy,94,100 medRxiv,10.1101/2022.03.10.22272081,2022-03-12,https://medrxiv.org/cgi/content/short/2022.03.10.22272081,Interstitial lung damage following COVID-19 hospitalisation: an interim analysis of the UKILD Post-COVID study.,I Stewart; J Jacob; PM George; PL Molyneaux; JC Porter; RJ Allen; JK Baillie; SL Barratt; P Beirne; SM Bianchi; JF Blaikley; J Chalmers; RC Chambers; N Chadhuri; C Coleman; G Collier; EK Denneny; A Docherty; O Elneima; RA Evans; L Fabbri; MA Gibbons; FV Gleeson; B Gooptu; NJ Greening; B Guillen Guio; IP Hall; NA Hanley; V Harris; E Harrison; M Heightman; TE Hillman; A Horsley; L Houchen-Wolloff; I Jarrold; SR Johnson; MG Jones; F Khan; R Lawson; OC Leavy; N Lone; M Marks; H McAuley; P Mehta; E Omer; D Parekh; K Piper Hanley; M Plate; J Pearl; K Poinasamy; JK Quint; B Raman; M Richardson; P Rivera-Ortega; L Saunders; R Saunders; MG Semple; M Sereno; A Shikotra; AJ Simpson; A Singapuri; DJF Smith; M Spears; LG Spencer; S Stanel; D Thickett; AAR Thompson; M Thorpe; R Thwaites; SLF Walsh; S Walker; ND Weatherley; M Weeks; JM Wild; DG Wootton; CE Brightling; LP Ho; LV Wain; RG Jenkins,"National Heart & Lung Institute, Imperial College London; Respiratory Medicine, University College London; Royal Brompton and Harefield NHS Foundation Trust; National Heart & Lung Institute, Imperial College London; University College London; University of Leicester; University of Edinburgh; North Bristol NHS Trust; Leeds Teaching Hospitals & University of Leeds; Sheffield Teaching Hospitals NHS Foundation Trust; University of Manchester; University of Dundee; Respiratory Medicine, University College London; University of Manchester; University of Nottingham; University of Sheffield; University College London; University of Edinburgh; University Hospitals of Leicester NHS Trust; University Hospitals of Leicester NHS Trust; National Heart & Lung Institute, Imperial College London; Royal Devon and Exeter NHS Foundation Trust; Oxford University Hospitals NHS Foundation Trust; University of Leicester; University of Leicester; University of Leicester; University of Nottingham; University of Manchester; University Hospitals of Leicester NHS Trust; University of Edinburgh; University College London Hospital; University College London Hospital; University of Manchester; University Hospitals of Leicester NHS Trust; Asthma UK British Lung Foundation; University of Nottingham; Faculty of Medicine, University of Southampton; University of Nottingham; Sheffield Teaching Hospitals NHS Foundation Trust; University of Leicester; Usher Institute, University of Edinburgh; University College London Hospital; University of Leicester; University College London Hospital; University of Leicester; University of Birmingham; University of Manchester; University College London Hospital; University of Leicester; British Lung Foundation; National Heart & Lung Institute, Imperial College London; University of Oxford; University of Leicester; University of Manchester; University of Sheffield; University of Leicester; Liverpool University; University of Leicester; University Hospitals of Leicester NHS Trust; Newcastle University; University of Leicester; Royal Brompton and Harefield NHS Foundation Trust; Perth Royal Infirmary, NHS Tayside; Liverpool University Hospitals NHS Foundation Trust; University of Manchester; University of Birmingham; University of Sheffield; University of Edinburgh; National Heart & Lung Institute, Imperial College London; National Heart & Lung Institute, Imperial College London; Sheffield Teaching NHS Foundation Trust; Sheffield Teaching NHS Foundation Trust; National Heart & Lung Institute, Imperial College London; Sheffield Teaching NHS Foundation Trust; University of Liverpool; University Hospitals of Leicester NHS Trust; University of Oxford; University of Leicester; National Heart & Lung Institute, Imperial College London","IntroductionShared characteristics between COVID-19 and pulmonary fibrosis, including symptoms, genetic architecture, and circulating biomarkers, suggests interstitial lung disease (ILD) development may be associated with SARS-CoV-2 infection. MethodsThe UKILD Post-COVID study planned interim analysis was designed to stratify risk groups and estimate the prevalence of Post-COVID Interstitial Lung Damage (ILDam) using the Post-HOSPitalisation COVID-19 (PHOSP-COVID) Study. Demographics, radiological patterns and missing data were assessed descriptively. Bayes binomial regression was used to estimate the risk ratio of persistent lung damage >10% involvement in linked, clinically indicated CT scans. Indexing thresholds of percent predicted DLco, chest X-ray findings and severity of admission were used to generate risk strata. Number of cases within strata were used to estimate the amount of suspected Post-COVID ILDam. @@ -1708,6 +1626,7 @@ Method and FindingsThis multi-phase, prospective mixed-methods study took place ConclusionsThe SBQ-LC is a comprehensive patient-reported assessment of Long COVID symptom burden developed using modern psychometric methods. It measures symptoms of Long COVID important to individuals with lived experience and may be used to evaluate the impact of interventions and inform best practice in clinical management.",health informatics,fuzzy,100,100 medRxiv,10.1101/2022.01.13.22268948,2022-01-14,https://medrxiv.org/cgi/content/short/2022.01.13.22268948,Algorithmic Fairness and Bias Mitigation for Clinical Machine Learning: Insights from Rapid COVID-19 Diagnosis by Adversarial Learning,Jenny Yang; Andrew AS Soltan; Yang Yang; David A Clifton,The University of Oxford; University of Oxford; The University of Oxford; The University of Oxford,"Machine learning is becoming increasingly prominent in healthcare. Although its benefits are clear, growing attention is being given to how machine learning may exacerbate existing biases and disparities. In this study, we introduce an adversarial training framework that is capable of mitigating biases that may have been acquired through data collection or magnified during model development. For example, if one class is over-presented or errors/inconsistencies in practice are reflected in the training data, then a model can be biased by these. To evaluate our adversarial training framework, we used the statistical definition of equalized odds. We evaluated our model for the task of rapidly predicting COVID-19 for patients presenting to hospital emergency departments, and aimed to mitigate regional (hospital) and ethnic biases present. We trained our framework on a large, real-world COVID-19 dataset and demonstrated that adversarial training demonstrably improves outcome fairness (with respect to equalized odds), while still achieving clinically-effective screening performances (NPV>0.98). We compared our method to the benchmark set by related previous work, and performed prospective and external validation on four independent hospital cohorts. Our method can be generalized to any outcomes, models, and definitions of fairness.",health informatics,fuzzy,100,100 medRxiv,10.1101/2022.01.05.21268323,2022-01-06,https://medrxiv.org/cgi/content/short/2022.01.05.21268323,Lineage replacement and evolution captured by the United Kingdom Covid Infection Survey,Katrina A Lythgoe; Tanya Golubchik; Matthew Hall; Thomas House; Roberto Cahuantzi; George MacIntyre-Cockett; Helen Fryer; Laura Thomson; Anel Nurtay; Mahan Ghafari; David Buck; Angie Green; Amy Trebes; Paolo Piazza; Lorne J Lonie; Ruth Studley; Emma Rourke; Darren Smith; Matthew Bashton; Andrew Nelson; Matthew Crown; Clare McCann; Gregory R Young; Rui Andre Nunes de Santos; Zack Richards; Adnan Tariq; - Wellcome Sanger Institute COVID-19 Surveillance Team; - COVID-19 Infection Survey Group; - The COVID-19 Genomics UK (COG-UK) consortium; Christophe Fraser; Ian Diamond; Jeff Barrett; Ann Sarah Walker; David Bonsall,University of Oxford; University of Oxford; University of Oxford; University of Manchester; University of Manchester; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; Office for National Statistics; Office for National Statistics; Northumbria University; Northumbria University; Northumbria University; Northumbria University; Northumbria University; Northumbria University; Northumbria University; Northumbria University; Northumbria University; Wellcome Sanger Institute; Office for National Statistics; ; University of Oxford; Office for National Statistics; Wellcome Sanger Institute; University of Oxford; University of Oxford,"The Office for National Statistics COVID-19 Infection Survey (ONS-CIS) is the largest surveillance study of SARS-CoV-2 positivity in the community, and collected data on the United Kingdom (UK) epidemic from April 2020 until March 2023 before being paused. Here, we report on the epidemiological and evolutionary dynamics of SARS-CoV-2 determined by analysing the sequenced samples collected by the ONS-CIS during this period. We observed a series of sweeps or partial sweeps, with each sweeping lineage having a distinct growth advantage compared to their predecessors. The sweeps also generated an alternating pattern in which most samples had either S-gene target failure (SGTF) or non- SGTF over time. Evolution was characterised by steadily increasing divergence and diversity within lineages, but with step increases in divergence associated with each sweeping major lineage. This led to a faster overall rate of evolution when measured at the between-lineage level compared to within lineages, and fluctuating levels of diversity. These observations highlight the value of viral sequencing integrated into community surveillance studies to monitor the viral epidemiology and evolution of SARS-CoV-2, and potentially other pathogens, particularly in the current phase of the pandemic with routine RT-PCR testing now ended in the community.",epidemiology,fuzzy,100,100 +medRxiv,10.1101/2022.01.01.21268131,2022-01-05,https://medrxiv.org/cgi/content/short/2022.01.01.21268131,Bayesian Estimation of real-time Epidemic Growth Rates using Gaussian Processes: local dynamics of SARS-CoV-2 in England,Laura Marcela Guzman Rincon; Edward M Hill; Louise Dyson; Michael J Tildesley; Matt J Keeling,University of Warwick; University of Warwick; University of Warwick; University of Warwick; University of Warwick,"Quantitative assessments of the recent state of an epidemic and short-term projections into the near future are key public health tools that have substantial policy impacts, helping to determine if existing control measures are sufficient or need to be strengthened. Key to these quantitative assessments is the ability to rapidly and robustly measure the speed with which the epidemic is growing or decaying. Frequently, epidemiological trends are addressed in terms of the (time-varying) reproductive number R. Here, we take a more parsimonious approach and calculate the exponential growth rate, r, using a Bayesian hierarchical model to fit a Gaussian process to the epidemiological data. We show how the method can be employed when only case data from positive tests are available, and the improvement gained by including the total number of tests as a measure of heterogeneous testing effort. Although the methods are generic, we apply them to SARS-CoV-2 cases and testing in England, making use of the available high-resolution spatio-temporal data to determine long-term patterns of national growth, highlight regional growth and spatial heterogeneity.",epidemiology,fuzzy,100,100 medRxiv,10.1101/2021.12.31.21268587,2022-01-02,https://medrxiv.org/cgi/content/short/2021.12.31.21268587,"The adverse impact of COVID-19 pandemic on cardiovascular disease prevention and management in England, Scotland and Wales: A population-scale descriptive analysis of trends in medication data",Caroline E Dale; Rohan Takhar; Ray Carragher; Fatemeh Torabi; Michalis Katsoulis; Stephen Duffield; Seamus Kent; Tanja Mueller; Amanj Kurdi; Stuart McTaggart; Hoda Abbasizanjani; Sam Hollings; Andrew Scourfield; Ronan Lyons; Rowena Griffiths; Jane Lyons; Gareth Davies; Dan Harris; Alex Handy; Mehrdad Alizadeh Mizani; Chris Tomlinson; Mark Ashworth; Spiros Denaxas; Amitava Banerjee; Jonathan Sterne; Kate Lovibond; Paul Brown; Ian Bullard; Rouven Priedon; Mamas A Mamas; Ann Slee; Paula Lorgelly; Munir Pirmohamed; Kamlesh Khunti; Naveed Sattar; Andrew Morris; Cathie Sudlow; Ashley Akbari; Marion Bennie; Reecha Sofat; - CVD-COVID-UK Consortium,"Institute of Health Informatics Research, University College London; Institute of Health Informatics Research, University College London; Strathclyde Institute of Pharmacy & Biomedical Sciences, University of Strathclyde; Swansea University; Institute of Health Informatics Research, University College London; NICE; NICE; University of Strathclyde; Strathclyde Institute of Pharmacy & Biomedical Sciences, University of Strathclyde; Public Health Scotland; Swansea University; NHS Digital, Leeds; UCLH NHS Foundation Trust; Swansea University; Swansea University; Swansea University; Swansea University; Swansea University; Institute of Health Informatics Research, University College London; Institute of Health Informatics Research, University College London; Institute of Health Informatics Research, University College London; King's College London; Institute of Health Informatics Research, University College London; University College London; University of Bristol; Royal College of Physicians; NHS Digital, Leeds; NHS Digital; British Heart Foundation Data Science Centre, Health Data Research UK, London; Keele University; NHSX; Department of Applied Health Research, University College London; University of Liverpool; University of Leicester; University of Glasgow; Health Data Research UK; British Heart Foundation Data Science Centre, Health Data Research UK, London; Swansea University; University of Strathclyde; Institute of Health Informatics Research, University College London; ","ObjectivesTo estimate the impact of the COVID-19 pandemic on cardiovascular disease (CVD) and CVD management using routinely collected medication data as a proxy. DesignDescriptive and interrupted time series analysis using anonymised individual-level population-scale data for 1.32 billion records of dispensed CVD medications across 15.8 million individuals in England, Scotland and Wales. @@ -1753,15 +1672,6 @@ Research in context panelO_ST_ABSEvidence before the studyC_ST_ABSThis study was Added value of this studyWe developed and validated two COVID-19 specific risk prediction scores. One to be used in the initial remote assessment of patients with acute COVID-19 to assess need for monitoring (RECAP-GP). The second one to assess the need for further treatment escalation and includes peripheral saturation of oxygen among the model predictors (RECAP-O2). To our knowledge, this is the first COVID-19 specific risk prediction score to assess and monitor COVID-19 patients risk of deterioration remotely. This will be a valuable resource to complement the use of oximetry in the community clinical decision-making when assessing a patient with acute COVID-19. Implications of all available evidenceTo manage pandemic waves and their demand on healthcare, acute COVID-19 patients require close monitoring in the community and prompt escalation of their treatment. Guidance available so far relies on unvalidated tools and clinician judgement to assess deterioration. COVID-19 specific community-based risk prediction scores such as RECAP may contribute to reducing the uncertainty in the assessment and monitoring of COVID-19 patients, increase safety in clinical practice and improve outcomes by facilitating appropriate treatment escalation.",primary care research,fuzzy,100,100 -medRxiv,10.1101/2021.12.22.21268252,2021-12-24,https://medrxiv.org/cgi/content/short/2021.12.22.21268252,Rapid increase in Omicron infections in England during December 2021: REACT-1 study,Paul Elliott; Barbara Bodinier; Oliver Eales; Haowei Wang; David Haw; Joshua Elliott; Matthew Whitaker; Jakob Jonnerby; David Tang; Caroline E. Walters; Christina Atchinson; Peter J. Diggle; Andrew J. Page; Alex Trotter; Deborah Ashby; Wendy Barclay; Graham Taylor; Helen Ward; Ara Darzi; Graham Cooke; Marc Chadeau-Hyam; Christl A Donnelly,"School of Public Health, Imperial College London, UKImperial College Healthcare NHS Trust, UKNational Institute for Health Research Imperial Biomedical Research; School of Public Health, Imperial College London, UK; School of Public Health, Imperial College London, UKMRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergency; School of Public Health, Imperial College London, UKMRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergency; School of Public Health, Imperial College London, UKMRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergency; Imperial College London; School of Public Health, Imperial College London, UK; School of Public Health, Imperial College London, UKMRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergency; Imperial College London; School of Public Health, Imperial College London, UKMRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergency; School of Public Health, Imperial College London, UK; CHICAS, Lancaster Medical School, Lancaster University, UK and Health Data Research, UK; Quadram Institute, Norwich, UK; Quadram Institute Bioscience; School of Public Health, Imperial College London, UK; Department of Infectious Disease, Imperial College London, UK; Department of Infectious Disease, Imperial College London, UK; School of Public Health, Imperial College London, UKImperial College Healthcare NHS Trust, UKNational Institute for Health Research Imperial Biomedical Research; Imperial College Healthcare NHS Trust, UKNational Institute for Health Research Imperial Biomedical Research Centre, UKInstitute of Global Health Innovation at ; Department of Infectious Disease, Imperial College London, UKImperial College Healthcare NHS Trust, UKNational Institute for Health Research Imperial Biomedical; School of Public Health, Imperial College London, UK; School of Public Health, Imperial College London, UKMRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergency","BackgroundThe highest-ever recorded numbers of daily severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections in England has been observed during December 2021 and have coincided with a rapid rise in the highly transmissible Omicron variant despite high levels of vaccination in the population. Although additional COVID-19 measures have been introduced in England and internationally to contain the epidemic, there remains uncertainty about the spread and severity of Omicron infections among the general population. - -MethodsThe REal-time Assessment of Community Transmission-1 (REACT-1) study has been monitoring the prevalence of SARS-CoV-2 infection in England since May 2020. REACT-1 obtains self-administered throat and nose swabs from a random sample of the population of England at ages 5 years and over. Swabs are tested for SARS-CoV-2 infection by reverse transcription polymerase chain reaction (RT-PCR) and samples testing positive are sent for viral genome sequencing. To date 16 rounds have been completed, each including [~]100,000 or more participants with data collected over a period of 2 to 3 weeks per month. Socio-demographic, lifestyle and clinical information (including previous history of COVID-19 and symptoms prior to swabbing) is collected by online or telephone questionnaire. Here we report results from round 14 (9-27 September 2021), round 15 (19 October - 05 November 2021) and round 16 (23 November - 14 December 2021) for a total of 297,728 participants with a valid RT-PCR test result, of whom 259,225 (87.1%) consented for linkage to their NHS records including detailed information on vaccination (vaccination status, date). We used these data to estimate community prevalence and trends by age and region, to evaluate vaccine effectiveness against infection in children ages 12 to 17 years, and effect of a third (booster) dose in adults, and to monitor the emergence of the Omicron variant in England. - -ResultsWe observed a high overall prevalence of 1.41% (1.33%, 1.51%) in the community during round 16. We found strong evidence of an increase in prevalence during round 16 with an estimated reproduction number R of 1.13 (1.06, 1.09) for the whole of round 16 and 1.27 (1.14, 1.40) when restricting to observations from 1 December onwards. The reproduction number in those aged 18-54 years was estimated at 1.23 (1.14, 1.33) for the whole of round 16 and 1.41 (1.23, 1.61) from 1 December. Our data also provide strong evidence of a steep increase in prevalence in London with an estimated R of 1.62 (1.34, 1.93) from 1 December onwards and a daily prevalence reaching 6.07% (4.06%, 9.00%) on 14 December 2021. As of 1 to 11 December 2021, of the 275 lineages determined, 11 (4.0%) corresponded to the Omicron variant. The first Omicron infection was detected in London on 3 December, and subsequent infections mostly appeared in the South of England. The 11 Omicron cases were all aged 18 to 54 years, double-vaccinated (reflecting the large numbers of people who have received two doses of vaccine in this age group) but not boosted, 9 were men, 5 lived in London and 7 were symptomatic (5 with classic COVID-19 symptoms: loss or change of sense of smell or taste, fever, persistent cough), 2 were asymptomatic, and symptoms were unknown for 2 cases. The proportion of Omicron (vs Delta or Delta sub-lineages) was found to increase rapidly with a daily increase of 66.0% (32.7%, 127.3%) in the odds of Omicron (vs. Delta) infection, conditional on swab positivity. Highest prevalence of swab positivity by age was observed in (unvaccinated) children aged 5 to 11 years (4.74% [4.15%, 5.40%]) similar to the prevalence observed at these ages in round 15. In contrast, prevalence in children aged 12 to 17 years more than halved from 5.35% (4.78%, 5.99%) in round 15 to 2.31% (1.91%, 2.80%) in round 16. As of 14 December 2021, 76.6% children at ages 12 to 17 years had received at least one vaccine dose; we estimated that vaccine effectiveness against infection was 57.9% (44.1%, 68.3%) in this age group. In addition, the prevalence of swab positivity in adults aged 65 years and over fell by over 40% from 0.84% (0.72%, 0.99%) in round 15 to 0.48% (0.39%,0.59%) in round 16 and for those aged 75 years and over it fell by two-thirds from 0.63% (0.48%,0.82%) to 0.21% (0.13%,0.32%). At these ages a high proportion of participants (>90%) had received a third vaccine dose; we estimated that adults having received a third vaccine dose had a three- to four-fold lower risk of testing positive compared to those who had received two doses. - -ConclusionA large fall in swab positivity from round 15 to round 16 among 12 to 17 year olds, most of whom have been vaccinated, contrasts with the continuing high prevalence among 5 to 11 year olds who have largely not been vaccinated. Likewise there were large falls in swab positivity among people aged 65 years and over, the vast majority of whom have had a third (booster) vaccine dose; these results reinforce the importance of the vaccine and booster campaign. However, the rapidly increasing prevalence of SARS-CoV-2 infections in England during December 2021, coincident with the rapid rise of Omicron infections, may lead to renewed pressure on health services. Additional measures beyond vaccination may be needed to control the current wave of infections and prevent health services (in England and other countries) from being overwhelmed. - -SummaryThe unprecedented rise in SARS-CoV-2 infections is concurrent with rapid spread of the Omicron variant in England and globally. We analysed prevalence of SARS-CoV-2 and its dynamics in England from end of November to mid-December 2021 among almost 100,000 participants from the REACT-1 study. Prevalence was high during December 2021 with rapid growth nationally and in London, and of the proportion of infections due to Omicron. We observed a large fall in swab positivity among mostly vaccinated older children (12-17 years) compared with unvaccinated younger children (5-11 years), and in adults who received a third vs. two doses of vaccine. Our results reiterate the importance of vaccination and booster campaigns; however, additional measures may be needed to control the rapid growth of the Omicron variant.",epidemiology,fuzzy,100,100 medRxiv,10.1101/2021.12.21.21268214,2021-12-23,https://medrxiv.org/cgi/content/short/2021.12.21.21268214,Comparative effectiveness of ChAdOx1 versus BNT162b2 vaccines against SARS-CoV-2 infections in England and Wales: A cohort analysis using trial emulation in the Virus Watch community data,Vincent Grigori Nguyen; Alexei Yavlinsky; Sarah Beale; Susan J Hoskins; Vasileios Lampos; Isobel Braithwaite; Thomas Edward Byrne; Wing Lam Erica Fong; Ellen Fragaszy; Cyril Geismar; Jana Kovar; Annalan M D Navaratnam; Parth Patel; Madhumita Shrotri; Sophie Weber; Andrew Hayward; Robert W Aldridge,University College London; University College London; University College London; Univerity College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London,"IntroductionInfections of SARS-CoV-2 in vaccinated individuals have been increasing globally. Understanding the associations between vaccine type and a post-vaccination infection could help prevent further COVID-19 waves. In this paper, we use trial emulation to understand the impact of a phased introduction of the vaccine in the UK driven by vulnerability and exposure status. We estimate the comparative effectiveness of COVID-19 vaccines (ChAdOx1 versus BNT162b2) against post-vaccination infections of SARS-CoV-2 in a community setting in England and Wales. MethodTrial emulation was conducted by pooling results from six cohorts whose recruitment was staggered between 1st January 2021 and 31st March 2021 and followed until 12th November 2021. Eligibility for each trial was based upon age (18+ at the time of vaccination), without prior signs of infection or an infection within the first 14 days of the first dose. Time from vaccination of ChAdOx1 or BNT162b2 until SARS-CoV-2 infection (positive polymerase chain reaction or lateral flow test after 14 of the vaccination) was modelled using Cox proportional hazards model for each cohort and adjusted for age at vaccination, gender, minority ethnic status, clinically vulnerable status and index of multiple deprivation quintile. For those without SARS-CoV-2 infection during the study period, follow-up was until loss-of-follow-up or end of study (12th November 2021). Pooled hazard ratios were generated using random-effects meta-analysis. @@ -1909,13 +1819,6 @@ ResultsBased on analysis of 10475 adult participants including 874 infections ac ConclusionsA high proportion of the second wave of the pandemic was spent under conditions where people were being advised to work from home where possible, and to minimize exposure to shops, and a wide range of other businesses were subject to severe restrictions. Vaccines were being rolled out to high-risk groups. During this time, going to work was an important risk factor for infection but public transport use likely accounted for a lot of this risk. Only a minority of the cohort left home for work or used public or shared transport. By contrast, the majority of participants visited shops and this activity accounted for about one-third of non-household transmission.",infectious diseases,fuzzy,100,100 medRxiv,10.1101/2021.12.08.21267353,2021-12-08,https://medrxiv.org/cgi/content/short/2021.12.08.21267353,The challenge of limited vaccine supplies: impact of prior infection on anti-spike IgG antibody trajectories after a single COVID-19 vaccination,Jia Wei; Philippa Matthews; Nicole Stoesser; Ian Diamond; Ruth Studley; Emma Rourke; Duncan Cook; John Bell; John Newton; Jeremy Farrar; Alison Howarth; Brian Marsden; Sarah Hoosdally; Yvonne Jones; David Stuart; Derrick W Crook; tim E peto; Ann Sarah Walker; David W Eyre; Koen B Pouwels; - COVID-19 Infection Survey team,University of Oxford; University of Oxford; University of Oxford; Office for National Statistics; Office for National Statistics; Office for National Statistics; Office for National Statistics; University of Oxford; Public Health England; Wellcome Trust; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; NIHR Oxford Biomedical Research Centre; oxford university; University of Oxford; University of Oxford; University of Oxford; ,"Given high SARS-CoV-2 incidence, coupled with slow and inequitable vaccine roll-out, there is an urgent need for evidence to underpin optimum vaccine deployment, aiming to maximise global population immunity at speed. We evaluate whether a single vaccination in previously infected individuals generates similar initial and subsequent antibody responses to two vaccinations in those without prior infection. We compared anti-spike IgG antibody responses after a single dose of ChAdOx1, BNT162b2, or mRNA-1273 SARS-CoV-2 vaccines in the COVID-19 Infection Survey in the UK general population. In 100,849 adults who received at least one vaccination, 13,404 (13.3%) had serological and/or PCR evidence of prior infection. Prior infection significantly boosted antibody responses for all three vaccines, producing a higher peak level and longer half-life, and a response comparable to those without prior infection receiving two vaccinations. In those with prior infection, median time above the positivity threshold was estimated to last for >1 year after the first dose. Single-dose vaccination targeted to those previously infected may provide protection in populations with high rates of previous infection faced with limited vaccine supply, as an interim measure while vaccine campaigns are scaled up.",infectious diseases,fuzzy,100,100 -medRxiv,10.1101/2021.12.03.21266112,2021-12-05,https://medrxiv.org/cgi/content/short/2021.12.03.21266112,Brain Injury in COVID-19 is Associated with Autoinflammation and Autoimmunity,Edward J Needham; Alex L Ren; Richard J Digby; Joanne G Outtrim; Dorothy A Chatfield; Virginia FJ Newcombe; Rainer Doffinger; Gabriela Barcenas-Morales; Claudia Fonseca; Michael J Taussig; Rowan M Burnstein; Cordelia Dunai; Nyarie Sithole; Nicholas J Ashton; Henrik Zetterberg; Magnus Gisslen; Eden Arvid; Emelie Marklund; Michael J Griffiths; Jonathan Cavanagh; Gerome Breen; Sarosh R Irani; Anne Elmer; Nathalie Kingston; John R Bradley; Leonie S Taams; Benedict D michael; Edward T Bullmore; Kenneth GC Smith; Paul A Lyons; Alasdair JC Coles; David K Menon; - Cambridge NeuroCOVID Group; - NIHR Cambridge Covid BioResource; - NIHR Cambridge Clinical Research Facility,"Department of Clinical Neurosciences, University of Cambridge, UK; Division of Anaesthesia, Department of Medicine, University of Cambridge, UK.; Division of Anaesthesia, Department of Medicine, University of Cambridge, UK.; Division of Anaesthesia, Department of Medicine, University of Cambridge, UK.; Division of Anaesthesia, Department of Medicine, University of Cambridge, UK.; Division of Anaesthesia, Department of Medicine, University of Cambridge, UK.; Department of Clinical Biochemistry and Immunology, Addenbrooke's Hospital, Cambridge, UK.; Department of Clinical Biochemistry and Immunology, Addenbrooke's Hospital, Cambridge, UK.; Cambridge Protein Arrays Ltd, Babraham Research Campus, Cambridge, UK; Cambridge Protein Arrays Ltd, Babraham Research Campus, Cambridge, UK; Division of Anaesthesia, Department of Medicine, University of Cambridge, UK.; Clinical Infection Microbiology and Neuroimmunology, Institute of Infection, Veterinary and Ecological Science, Liverpool, UK.; Department of Infectious Diseases, Cambridge University NHS Hospitals Foundation Trust, Cambridge, UK.; Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, the Sahlgrenska Academy at the University of Gothenburg, Molndal, Sweden.; Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, the Sahlgrenska Academy at the University of Gothenburg, Molndal, Sweden; C; Department of Infectious Diseases, Institute of Biomedicine, the Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden; Region Vastra Gotaland; Department of Infectious Diseases, Institute of Biomedicine, the Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden; Region Vastra Gotaland; Department of Infectious Diseases, Institute of Biomnedicine, the Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden; Region Vastra Gotalan; Institute of Infection, Veterinary & Ecological Sciences, University of Liverpool, Liverpool, UK.; Centre for Immunobiology, Institute of Infection, Immunity and Inflammation, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, U; Department of Social Genetic and Developmental Psychiatry, King's College London, London, UK.; Oxford Autoimmune Neurology Group, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK; Department of Neurology, Oxford University H; Cambridge Clinical Research Centre, NIHR Clinical Research Facility, Cambridge University Hospitals NHS Foundation Trust, Addenbrooke's Hospital, Cambridge, UK ; NIHR BioResource, Cambridge University Hospitals NHS Foundation, Cambridge Biomedical Campus, Cambridge, UK.; NIHR BioResource, Cambridge University Hospitals NHS Foundation, Cambridge Biomedical Campus, Cambridge, UK; Department of Medicine, University of Cambridge, Ad; Centre for Inflammation Biology and Cancer Immunology and Dept Inflammation Biology, School of Immunology and Microbial Sciences, Kings College London, Guys Cam; Clinical Infection Microbiology and Neuroimmunology, Institute of Infection, Veterinary and Ecological Science, Liverpool, UK.; Department of Psychiatry, University of Cambridge, Herchel Smith Building for Brain and Mind Sciences, Cambridge Biomedical Campus, Cambridge, UK.; Department of Medicine, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK; Cambridge Institute of Therapeutic Immunology and Infectious Disease, Je; Department of Medicine, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK; Cambridge Institute of Therapeutic Immunology and Infectious Disease, Je; Department of Clinical Neurosciences, University of Cambridge, UK; Division of Anaesthesia, Department of Medicine, University of Cambridge, UK.; ; ; ","COVID-19 has been associated with many neurological complications including stroke, delirium and encephalitis. Furthermore, many individuals experience a protracted post-viral syndrome which is dominated by neuropsychiatric symptoms, and is seemingly unrelated to COVID-19 severity. The true frequency and underlying mechanisms of neurological injury are unknown, but exaggerated host inflammatory responses appear to be a key driver of severe COVID-19 more broadly. - -We sought to investigate the dynamics of, and relationship between, serum markers of brain injury (neurofilament light [NfL], Glial Fibrillary Acidic Protein [GFAP] and total Tau) and markers of dysregulated host response including measures of autoinflammation (proinflammatory cytokines) and autoimmunity. Brain injury biomarkers were measured using the Quanterix Simoa HDx platform, cytokine profiling by Luminex (R&D) and autoantibodies by a custom protein microarray. - -During hospitalisation, patients with COVID-19 demonstrated elevations of NfL and GFAP in a severity-dependant manner, and there was evidence of ongoing active brain injury at follow-up 4 months later. Raised NfL and GFAP were associated with both elevations of pro-inflammatory cytokines and the presence of autoantibodies; autoantibodies were commonly seen against lung surfactant proteins as well as brain proteins such as myelin associated glycoprotein, but reactivity was seen to a large number of different antigens. - -Furthermore, a distinct process characterised by elevation of serum total Tau was seen in patients at follow-up, which appeared to be independent of initial disease severity and was not associated with dysregulated immune responses in the same manner as NfL and GFAP.",neurology,fuzzy,100,100 medRxiv,10.1101/2021.11.24.21266818,2021-12-01,https://medrxiv.org/cgi/content/short/2021.11.24.21266818,Trends and associated factors for Covid-19 hospitalisation and fatality risk in 2.3 million adults in England,Thomas Beaney; Ana Luisa Neves; Ahmed Alboksmaty; Kelsey Flott; Aidan Fowler; Jonathan R Benger; Paul Aylin; Sarah Elkin; Ara Darzi; Jonathan Clarke,Imperial College London; Imperial College London; Imperial College London; Imperial College London; NHS England and Improvement; NHS Digital; Imperial College London; Imperial College London; Imperial College London; Imperial College London,"BackgroundThe Covid-19 case fatality ratio varies between countries and over time but it is unclear whether variation is explained by the underlying risk in those infected. This study aims to describe the trends and risk factors for admission and mortality rates over time in England. MethodsIn this retrospective cohort study, we included all adults ([≥]18 years) in England with a positive Covid-19 test result between 1st October 2020 and 30th April 2021. Data were linked to primary and secondary care electronic health records and death registrations. Our outcomes were i) one or more emergency hospital admissions and ii) death from any cause, within 28 days of a positive test. Multivariable multilevel logistic regression was used to model each outcome with patient risk factors and time. @@ -2014,13 +1917,6 @@ What this paper addsIn unvaccinated individuals the protection against hospitali Implications of all the available evidenceThe combination of natural infection and vaccination provides maximal protection against COVID-19: prior vaccination does not seriously impair this protection.",epidemiology,fuzzy,100,100 medRxiv,10.1101/2021.11.19.21266529,2021-11-19,https://medrxiv.org/cgi/content/short/2021.11.19.21266529,Impact of the COVID-19 pandemic on community antibiotic prescribing and stewardship: a qualitative interview study with general practitioners in England,Aleksandra J Borek; Katherine Maitland; Monsey Mcleod; Anne Campbell; Benedict Hayhoe; Christopher C Butler; Liz Morrell; Laurence Roope; Alison Holmes; Ann Sarah Walker; Sarah Tonkin-Crine; - the STEP-UP study team,University of Oxford; University of Oxford; Imperial College London; Imperia College London; Imperial College London; University of Oxford; University of Oxford; University of Oxford; Imperial College London; University of Oxford; University of Oxford; ,"The COVID-19 pandemic has had a profound impact on the delivery of primary care services. We aimed to identify general practitioners (GPs) perceptions and experiences of how the COVID-19 pandemic influenced antibiotic prescribing and antimicrobial stewardship (AMS) in general practice in England. Twenty-four semi-structured interviews were conducted with 18 GPs at two time-points: autumn 2020 (14 interviews) and spring 2021 (10 interviews). Interviews were audio-recorded, transcribed and analysed thematically, taking a longitudinal approach. Participants reported a lower threshold for antibiotic prescribing (and fewer consultations) for respiratory infections and COVID-19 symptoms early in the pandemic, then returning to more usual (pre-pandemic) prescribing. They perceived less impact on antibiotic prescribing for urinary and skin infections. Participants perceived the changing ways of working and consulting (e.g., proportions of remote and in-person consultations), and the changing patient presentations and GP workload as influencing the fluctuations in antibiotic prescribing. This was compounded by decreased engagement with, and priority of, AMS due to COVID-19-related urgent priorities. Re-engagement with AMS is needed, e.g., through reviving antibiotic prescribing feedback and targets/incentives. While the pandemic disrupted the usual ways of working, it also produced opportunities, e.g., for re-organising ways of managing infections and AMS in the future.",primary care research,fuzzy,100,100 -medRxiv,10.1101/2021.11.15.21266264,2021-11-16,https://medrxiv.org/cgi/content/short/2021.11.15.21266264,Association of COVID-19 employment disruption with mental and social wellbeing: evidence from nine UK longitudinal studies,Jacques Wels; Charlotte Booth; Bozena Wielgoszewska; Michael J Green; Giorgio Di Gessa; Charlotte F Huggins; Gareth J Griffith; Alex Siu Fung Kwong; Ruth C E Bowyer; Jane Maddock; Praveetha Patalay; Richard J Silverwood; Emla Fitzsimons; Richard John Shaw; Ellen J Thompson; Andrew Steptoe; Alun Hughes; Nishi Chaturvedi; Claire J Steves; Srinivasa Vittal Katikireddi; George B Ploubidis,University College London; University College London; University College London; University of Glasgow; University College London; University of Edinburgh; University of Bristol; University of Bristol; King's College London; University College London; University College London; University College London; University College London; University of Glasgow; Kings College London; University College London; University College London; University College London; King's College London; University of Glasgow; University College London,"BackgroundThe COVID-19 pandemic has led to major economic disruptions. In March 2020, the UK implemented the Coronavirus Job Retention Scheme - known as furlough - to minimize the impact of job losses. We investigate associations between change in employment status and mental and social wellbeing during the early stages of the pandemic. - -MethodsData were from 25,670 respondents, aged 17 to 66, across nine UK longitudinal studies. Furlough and other employment changes were defined using employment status pre-pandemic and during the first lockdown (April-June 2020). Mental and social wellbeing outcomes included psychological distress, life satisfaction, self-rated health, social contact, and loneliness. Study-specific modified Poisson regression estimates, adjusting for socio-demographic characteristics and pre-pandemic mental and social wellbeing measures, were pooled using meta-analysis. - -ResultsCompared to those who remained working, furloughed workers were at greater risk of psychological distress (adjusted risk ratio, ARR=1.12; 95% CI: 0.97, 1.29), low life satisfaction (ARR=1.14; 95% CI: 1.07, 1.22), loneliness (ARR=1.12; 95% CI: 1.01, 1.23), and poor self-rated health (ARR=1.26; 95% CI: 1.05, 1.50), but excess risk was less pronounced than that of those no longer employed (e.g., ARR for psychological distress=1.39; 95% CI: 1.21, 1.59) or in stable unemployment (ARR=1.33; 95% CI: 1.09, 1.62). - -ConclusionsDuring the early stages of the pandemic, those furloughed had increased risk for poor mental and social wellbeing. However, their excess risk was lower in magnitude than that of those who became or remained unemployed, suggesting that furlough may have partly mitigated poorer outcomes.",psychiatry and clinical psychology,fuzzy,100,100 medRxiv,10.1101/2021.11.15.21266255,2021-11-16,https://medrxiv.org/cgi/content/short/2021.11.15.21266255,"COVID-19 vaccination, risk-compensatory behaviours, and social contacts in four countries in the UK",John Buckell; Joel Jones; Philippa C Matthews; Ian Diamond; Emma Rourke; Ruth Studley; Duncan Cook; Ann Sarah Walker; Koen B Pouwels; - The COVID-19 Infection Survey Team,University of Oxford; Office for National Statistics; University of Oxford; Office for National Statistics; Office for National Statistics; Office for National Statistics; Office for National Statistics; University of Oxford; University of Oxford; ,"The physiological effects of vaccination against SARS-CoV-2 (COVID-19) are well documented, yet the behavioural effects are largely unknown. Risk compensation suggests that gains in personal safety, as a result of vaccination, are offset by increases in risky behaviour, such as socialising, commuting and working outside the home. This is potentially problematic because transmission of SARS-CoV-2 is driven by contacts, which could be amplified by vaccine-related risk compensation behaviours. Here, we show that behaviours were overall unrelated to personal vaccination, but - adjusting for variation in mitigation policies - were responsive to the level of vaccination in the wider population: individuals in the UK were risk compensating when rates of vaccination were rising. This effect was observed across four nations of the UK, each of which varied policies autonomously.",infectious diseases,fuzzy,100,100 medRxiv,10.1101/2021.11.10.21266124,2021-11-11,https://medrxiv.org/cgi/content/short/2021.11.10.21266124,Differences in COVID-19 vaccination coverage by occupation in England: a national linked data study,Vahe Nafilyan; Ted Dolby; Katie Finning; Jasper Morgan; Rhiannon Edge; Myer Glickman; Neil Pearce; Martie Van Tongeren,Office for National Statistics; Office for National Statistics; Office for National Statistics; Office for National Statistics; Lancaster University; Office for National Statistics; London School of Hygiene and Tropical Medicine; University of Manchester,"BackgroundMonitoring differences in COVID-19 vaccination uptake in different groups is crucial to help inform the policy response to the pandemic. A key gap is the absence of data on uptake by occupation. @@ -2420,21 +2316,6 @@ ResultsWe studied 1489 participants returned valid results in both June and Sept DiscussionThese results do not follow the pattern reported from studies specifically designed to monitor seropositivity, which have found greater consistency over time and the influence of presence, timing and severity of symptoms on seroreversion. We suggest several factors that may have contributed to this difference: our low bar in defining initial seropositivity (single test); a non-quantitative test known to have relatively low sensitivity; participants carrying out testing. We would encourage other studies to use these real-world performance characteristics alongside those from laboratory studies to plan and analyse any antibody testing.",occupational and environmental health,fuzzy,100,100 medRxiv,10.1101/2021.08.18.21262237,2021-08-24,https://medrxiv.org/cgi/content/short/2021.08.18.21262237,Impact of Delta on viral burden and vaccine effectiveness against new SARS-CoV-2 infections in the UK,Koen B Pouwels; Emma Pritchard; Philippa Matthews; Nicole B Stoesser; David W Eyre; Karina-Doris Vihta; Thomas House; Jodie Hay; John Bell; John Newton; Jeremy Farrar; Derrick W Crook; Duncan Cook; Emma Rourke; Ruth Studley; Tim E Peto; Ian Diamond; Sarah Walker; - COVID-19 Infection Survey Team,University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Manchester; Glasgow Lighthouse Laboratory; University of Oxford; Public Health England; Wellcome Trust; NIHR Oxford Biomedical Research Centre; Office for National Statistics; Office for National Statistics; Office for National Statistics; Oxford University; Office for National Statistics; University of Oxford; -,"The effectiveness of BNT162b2, ChAdOx1, and mRNA-1273 vaccines against new SARS-CoV-2 infections requires continuous re-evaluation, given the increasingly dominant Delta variant. We investigated the effectiveness of the vaccines in a large community-based survey of randomly selected households across the UK. We found that the effectiveness of BNT162b2 and ChAd0x1 against any infections (new PCR positives) and infections with symptoms or high viral burden is reduced with the Delta variant. A single dose of the mRNA-1273 vaccine had similar or greater effectiveness compared to a single dose of BNT162b2 or ChAdOx1. Effectiveness of two doses remains at least as great as protection afforded by prior natural infection. The dynamics of immunity following second doses differed significantly between BNT162b2 and ChAdOx1, with greater initial effectiveness against new PCR-positives but faster declines in protection against high viral burden and symptomatic infection with BNT162b2. There was no evidence that effectiveness varied by dosing interval, but protection was higher among those vaccinated following a prior infection and younger adults. With Delta, infections occurring following two vaccinations had similar peak viral burden to those in unvaccinated individuals. SARS-CoV-2 vaccination still reduces new infections, but effectiveness and attenuation of peak viral burden are reduced with Delta.",epidemiology,fuzzy,100,100 -medRxiv,10.1101/2021.08.23.21261779,2021-08-24,https://medrxiv.org/cgi/content/short/2021.08.23.21261779,Association of cerebral venous thrombosis with recent COVID-19 vaccination: case-crossover study using ascertainment through neuroimaging in Scotland.,Paul M McKeigue; Raj Burgul; Jennifer Bishop; Chris Robertson; Jim McMenamin; Maureen O'Leary; David A. McAllister; Helen M Colhoun,"University of Edinburgh; Forth Valley Royal Hospital; Public Health Scotland; Department of Mathematics and Statistics, University of Strathclyde; Public Health Scotland; Public Health Scotland; University of Glasgow; University of Edinburgh","ObjectivesTo investigate the association of primary acute cerebral venous thrombosis (CVT) with COVID-19 vaccination through complete ascertainment of all diagnosed CVT in the population of Scotland. - -DesignCase-crossover study comparing recent (1-14 days after vaccination) with less recent exposure to vaccination among cases of CVT. - -SettingNational data for Scotland from 1 December 2020, with diagnosed CVT case ascertainment through neuroimaging studies up to 17 May 2021 and diagnostic coding of hospital discharges up to 28 April 2021 and with linkage to vaccination records. - -Main outcome measurePrimary acute cerebral venous thrombosis - -ResultsOf 50 primary acute CVT cases, 29 were ascertained only from neuroimaging studies, 2 were ascertained only from hospital discharges, and 19 were ascertained from both sources. Of these 50 cases, 14 had received the Astra-Zeneca ChAdOx1 vaccine and 3 the Pfizer BNT162b2 vaccine. The incidence of CVT per million doses in the first 14 days after vaccination was 2.2 (95% credible interval 0.9 to 4.1) for ChAdOx1 and 1 (95% credible interval 0.1 to 2.9) for BNT162b2. The rate ratio for CVT associated with exposure to ChAdOx1 in the first 14 days compared with exposure 15-84 days after vaccination was 3.2 (95% credible interval 1.1 to 9.5). The 95% credible interval for the rate ratio associated with recent versus less recent exposure to BNT162b2 (0.6 to 95.8) was too wide for useful inference. - -ConclusionsThese findings support a causal association between CVT and the AstraZeneca vaccine. The absolute risk of post-vaccination CVT in this population-wide study in Scotland was lower than has been reported for populations in Scandinavia and Germany; the explanation for this is not clear. - -What is already known on this topicThe risk of cerebral venous thrombosis (CVT) within 28 days of receiving the AstraZeneca ChAdOx1 vaccine has been estimated as 18 to 25 per million doses in Germany and Scandinavia, but only 5 per million doses in the UK based on the Yellow Card reporting scheme. Risk estimates based on adverse event reporting systems are subject to under-ascertainment and other biases. - -What this study addsAll diagnosed cases of CVT in Scotland were ascertained by searching neuroimaging studies from December 2020 to May 2021 and linked to national vaccination records. The risk of CVT within 28 days of vaccination with ChAdOx1 was estimated as 3.5 per million doses with an upper bound of 6 per million doses, against a background incidence of about 12 per million adults per year. This indicates that the Yellow Card system has not seriously underestimated the risk in the UK; the explanation for higher risk in other European countries is not clear.",epidemiology,fuzzy,100,100 medRxiv,10.1101/2021.08.19.21262231,2021-08-24,https://medrxiv.org/cgi/content/short/2021.08.19.21262231,Symptoms and SARS-CoV-2 positivity in the general population in the UK,Karina-Doris Vihta; Koen B. Pouwels; Tim Peto; Emma Pritchard; David W. Eyre; Thomas House; Owen Gethings; Ruth Studley; Emma Rourke; Duncan Cook; Ian Diamond; Derrick Crook; Philippa C. Matthews; Nicole Stoesser; Ann Sarah Walker; - COVID-19 Infection Survey team,University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Manchester; Office for National Statistics; Office for National Statistics; Office for National Statistics; Office for National Statistics; Office for National Statistics; University of Oxford; University of Oxford; University of Oxford; University of Oxford; ,"BackgroundSeveral community-based studies have assessed the ability of different symptoms to identify COVID-19 infections, but few have compared symptoms over time (reflecting SARS-CoV-2 variants) and by vaccination status. MethodsUsing data and samples collected by the COVID-19 Infection Survey at regular visits to representative households across the UK, we compared symptoms in new PCR-positives and comparator test-negative controls. @@ -2453,6 +2334,13 @@ ResultsOf 46,162,942 adults, 21,193,814 (46%) had their first vaccination during Rates of intracranial venous thrombosis (ICVT) and thrombocytopenia in adults aged <70 years were higher 1-28 days after ChAdOx1-S (adjusted HRs 2.27, 95% CI:1.33- 3.88 and 1.71, 1.35-2.16 respectively), but not after BNT162b2 (0.59, 0.24-1.45 and 1.00, 0.75-1.34) compared with unvaccinated. The corresponding absolute excess risks of ICVT 1-28 days after ChAdOx1-S were 0.9-3 per million, varying by age and sex. ConclusionsIncreases in ICVT and thrombocytopenia after ChAdOx1-S vaccination in adults aged <70 years were small compared with its effect in reducing COVID-19 morbidity and mortality, although more precise estimates for adults <40 years are needed. For people aged [≥]70 years, rates of arterial or venous thrombotic, events were generally lower after either vaccine.",cardiovascular medicine,fuzzy,100,100 +medRxiv,10.1101/2021.08.23.21262209,2021-08-23,https://medrxiv.org/cgi/content/short/2021.08.23.21262209,Population birth outcomes in 2020 and experiences of expectant mothers during the COVID-19 pandemic: a Born in Wales mixed methods study using routine data,Hope Jones; Mike Seaborne; Laura Cowley; David E Odd; Shantini Paranjothy; Ashley Akbari; Sinead Brophy,Swansea University; Swansea University; Public Health Wales; Cardiff University; University of Aberdeen; Swansea University; Swansea University,"BackgroundPregnancy can be a stressful time and the COVID-19 pandemic has affected all aspects of life. This study aims to investigate the impact of the pandemic on population birth outcomes in Wales, rates of primary immunisations and examine expectant mothers experiences of pregnancy including self-reported levels of stress and anxiety. + +MethodsPopulation-level birth outcomes in Wales: Stillbirths, prematurity, birth weight and Caesarean section births before (2016-2019) and during (2020) the pandemic were compared using national-level routine anonymised data held in the Secure Anonymised Information Linkage (SAIL) Databank. The first three scheduled primary immunisations were compared between 2019 and 2020. Self-reported pregnancy experience: 215 expectant mothers (aged 16+) in Wales completed an online survey about their experiences of pregnancy during the pandemic. The qualitative survey data was analysed using codebook thematic analysis. + +FindingsThere was no significant difference between annual outcomes including gestation and birth weight, stillbirths, and Caesarean sections for infants born in 2020 compared to 2016-2019. There was an increase in late term births ([≥]42 weeks gestation) during the first lockdown (OR: 1.28, p=0.019) and a decrease in moderate to late preterm births (32-36 weeks gestation) during the second lockdown (OR: 0.74, p=0.001). Fewer babies were born in 2020 (N=29,031) compared to 2016-2019 (average N=32,582). All babies received their immunisations in 2020, but there were minor delays in the timings of vaccines. Those due at 8-weeks were 8% less likely to be on time (within 28-days) and at 16-weeks, they were 19% less likely to be on time. The pandemic had a negative impact on the mental health of 71% of survey respondents, who reported anxiety, stress and loneliness; this was associated with attending scans without their partner, giving birth alone, and minimal contact with midwives. + +InterpretationThe pandemic had a negative impact on mothers experiences of pregnancy; however, population-level data suggests that this did not translate to adverse birth outcomes for babies born during the pandemic.",public and global health,fuzzy,100,100 medRxiv,10.1101/2021.08.17.21262196,2021-08-22,https://medrxiv.org/cgi/content/short/2021.08.17.21262196,Controlled evaLuation of Angiotensin Receptor Blockers for COVID-19 respIraTorY disease (CLARITY): Statistical analysis plan for a randomised controlled Bayesian adaptive sample size trial,James McGree; Carinna Hockham; Sradha Kotwal; Arlen Wilcox; Abhinav Bassi; Carol Pollock; Louise M Burrell; Tom Snelling; Vivek Jha; Meg Jardine; Mark Jones,Queensland University of Technology; Imperial College London; University of New South Wales; University of New South Wales; The George Institute for Global Health; Royal North Shore Hospital; University of Melbourne; The University of Sydney; University of New South Wales; University of New South Wales; The University of Sydney,"The CLARITY trial (Controlled evaLuation of Angiotensin Receptor Blockers for COVID-19 respIraTorY Disease) investigates the effectiveness of angiotensin receptor blockers in addition to standard care compared to placebo (in Indian sites) with standard care in reducing the duration and severity of lung failure in patients with COVID-19. The CLARITY trial is a multi-centre, randomised controlled Bayesian adaptive trial with regular planned analyses where pre-specified decision rules will be assessed to determine whether the trial should be stopped due to sufficient evidence of treatment effectiveness or futility. Here we describe the statistical analysis plan for the trial, and define the pre-specified decision rules, including those that could lead to the trial being halted. The primary outcome is clinical status on a 7-point ordinal scale adapted from the WHO Clinical Progression scale assessed at Day 14. The primary analysis will follow the intention-to-treat principle. A Bayesian adaptive trial design was selected because there is considerable uncertainty about the extent of potential benefit of this treatment. Trial registrationClinicalTrials.gov, NCT04394117. Registered on 19 May 2020. @@ -2466,6 +2354,13 @@ medRxiv,10.1101/2021.08.13.21261889,2021-08-18,https://medrxiv.org/cgi/content/s One sentence summeryCare home residents show waning of nucleocapsid specific antibodies and enhanced expression of activation markers on SARS-CoV-2 specific cells",infectious diseases,fuzzy,100,100 medRxiv,10.1101/2021.08.13.21261959,2021-08-13,https://medrxiv.org/cgi/content/short/2021.08.13.21261959,Factors influencing wellbeing in young people during COVID-19.,Michaela James; Hope Jones; Amana Baig; Emily Marchant; Tegan Waites; Charlotte Todd; Karen Hughes; Sinead Brophy,Swansea University; Swansea University; Swansea University; Swansea University; Swansea University; Public Health Wales; Bangor University; Swansea University,"COVID-19 infection and the resultant restrictions has impacted all aspects of life across the world. This study explores factors that promote or support wellbeing for young people during the pandemic, how they differ by age, using a self-reported online survey with those aged 8 - 25 in Wales between September 2020 and February 2021. Open-ended responses were analysed via thematic analysis to provide further context. A total of 6,291 responses were obtained from 81 education settings across Wales (including primary and secondary schools as well as sixth form, colleges and universities). Wellbeing was highest in primary school children and boys and lowest in those who were at secondary school children, who were girls and, those who preferred not to give a gender. Among primary school children, higher wellbeing was seen for those who played with others (rather than alone), were of Asian ethnicity (OR 2.3, 95% CI: 1.26 to 4.3), lived in a safe area (OR: 2.0, 95% CI: 1.67 to 2.5) and had more sleep. To support their wellbeing young people reported they would like to be able to play with their friends more. Among secondary school children those who were of mixed ethnicity reported lower wellbeing (OR: 5.10, 95% CI: 1.70 to 15.80). To support their wellbeing they reported they would like more support with mental health (due to anxiety and pressure to achieve when learning online). This study found self-reported wellbeing differed by gender, ethnicity and deprivation and found younger children report the need for play and to see friends to support wellbeing but older children/young people wanted more support with anxiety and educational pressures.",public and global health,fuzzy,100,100 +medRxiv,10.1101/2021.08.12.21261987,2021-08-13,https://medrxiv.org/cgi/content/short/2021.08.12.21261987,Characterising the persistence of RT-PCR positivity and incidence in a community survey of SARS-CoV-2,Oliver Eales; Caroline E. Walters; Haowei Wang; David Haw; Kylie E. C. Ainslie; Christina Atchinson; Andrew Page; Sophie Prosolek; Alexander J. Trotter; Thanh Le Viet; Nabil-Fareed Alikhan; Leigh M Jackson; Catherine Ludden; - The COVID-19 Genomics UK (COG-UK) Consortium; Deborah Ashby; Christl A Donnelly; Graham Cooke; Wendy Barclay; Helen Ward; Ara Darzi; Paul Elliott; Steven Riley,"School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; School of Public Health, Imperial College London, UK; Quadram Institute, Norwich, UK; Quadram Institute, Norwich, UK; Quadram Institute, Norwich, UK; Quadram Institute, Norwich, UK; Quadram Institute, Norwich, UK; Medical School, University of Exeter, UK; Department of Medicine, University of Cambridge, UK; ; School of Public Health, Imperial College London, UK; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; Department of Infectious Disease, Imperial College London, UK Imperial College Healthcare NHS Trust, UK National Institute for Health Research Imperial Biomedic; Department of Infectious Disease, Imperial College London, UK; School of Public Health, Imperial College London, UK Imperial College Healthcare NHS Trust, UK National Institute for Health Research Imperial Biomedical Resear; Imperial College Healthcare NHS Trust, UK National Institute for Health Research Imperial Biomedical Research Centre, UK Institute of Global Health Innovation a; School of Public Health, Imperial College London, UK Imperial College Healthcare NHS Trust, UK National Institute for Health Research Imperial Biomedical Resear; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc","BackgroundCommunity surveys of SARS-CoV-2 RT-PCR swab-positivity provide prevalence estimates largely unaffected by biases from who presents for routine case testing. The REal-time Assessment of Community Transmission-1 (REACT-1) has estimated swab-positivity approximately monthly since May 2020 in England from RT-PCR testing of self-administered throat and nose swabs in random non-overlapping cross-sectional community samples. Estimating infection incidence from swab-positivity requires an understanding of the persistence of RT-PCR swab positivity in the community. + +MethodsDuring round 8 of REACT-1 from 6 January to 22 January 2021, of the 2,282 participants who tested RT-PCR positive, we recruited 896 (39%) from whom we collected up to two additional swabs for RT-PCR approximately 6 and 9 days after the initial swab. We estimated sensitivity and duration of positivity using an exponential model of positivity decay, for all participants and for subsets by initial N-gene cycle threshold (Ct) value, symptom status, lineage and age. Estimates of infection incidence were obtained for the entire duration of the REACT-1 study using P-splines. + +ResultsWe estimated the overall sensitivity of REACT-1 to detect virus on a single swab as 0.79 (0.77, 0.81) and median duration of positivity following a positive test as 9.7 (8.9, 10.6) days. We found greater median duration of positivity where there was a low N-gene Ct value, in those exhibiting symptoms, or for infection with the Alpha variant. The estimated proportion of positive individuals detected on first swab, P0, was found to be higher for those with an initially low N-gene Ct value and those who were pre-symptomatic. When compared to swab-positivity, estimates of infection incidence over the duration of REACT-1 included sharper features with evident transient increases around the time of key changes in social distancing measures. + +DiscussionHome self-swabbing for RT-PCR based on a single swab, as implemented in REACT-1, has high overall sensitivity. However, participants time-since-infection, symptom status and viral lineage affect the probability of detection and the duration of positivity. These results validate previous efforts to estimate incidence of SARS-CoV-2 from swab-positivity data, and provide a reliable means to obtain community infection estimates to inform policy response.",infectious diseases,fuzzy,100,100 medRxiv,10.1101/2021.08.13.21261861,2021-08-13,https://medrxiv.org/cgi/content/short/2021.08.13.21261861,"Healthcare presentations with self-harm and the association with COVID-19: an e-cohort whole-population-based study using individual-level linked routine electronic health records in Wales, UK, 2016 - March 2021",Marcos del Pozo Banos; Sze Chim Lee; Yasmin Friedmann; Ashley Akbari; Fatemeh Tobari; Keith R Lloyd; Ronan A Lyons; Ann John,"Swansea University Medical School; Swansea University Medical School; Swansea University Medical School; Swansea University, Health Data Research UK; Swansea University Medical School; Swansea University Medical School; Swansea University, Health Data Research UK; Swansea University Medical School","BackgroundMulti-setting population-based studies on healthcare service presentations with self-harm covering the first 12 months of the COVID-19 pandemic are yet to be published. AimsAscertain changes across settings in healthcare service presentations with self-harm during Waves 1 and 2 of the COVID-19 pandemic. @@ -2551,21 +2446,6 @@ MethodsA nationally-representative cohort of U.S. adults (N=5,792) in the Unders ResultsVaccination was associated with a 0.09 decline in distress scores (95% CI:-0.15 to -0.04) (0-12 scale), a 5.7% relative decrease compared to mean scores in the wave prior to vaccination. Vaccination was also associated with an 8.44 percentage point reduction in perceived risk of infection (95% CI:-9.15% to -7.73%), a 7.44-point reduction in perceived risk of hospitalization (95% CI:-8.07% to -6.82%), and a 5.03-point reduction in perceived risk of death (95% CI:-5.57% to -4.49%). Adjusting for risk perceptions decreased the vaccination-distress association by two-thirds. Event study models suggest vaccinated and never vaccinated respondents followed similar PHQ-4 trends pre-vaccination, diverging significantly post-vaccination. Analyses were robust to individual and wave fixed effects, time-varying controls, and several alternative modelling strategies. Results were similar across sociodemographic groups. ConclusionReceiving a COVID-19 vaccination was associated with declines in distress and perceived risks of infection, hospitalization, and death. Vaccination campaigns could promote these additional benefits of being vaccinated.",public and global health,fuzzy,100,100 -medRxiv,10.1101/2021.07.21.21260906,2021-07-22,https://medrxiv.org/cgi/content/short/2021.07.21.21260906,Disentangling post-vaccination symptoms from early COVID-19,Liane S Canas; Marc F. Osterdahl; Jie Deng; Christina Hu; Somesh Selvachandran; Lorenzo Polidori; Anna May; Erika Molteni; Benjamin Murray; Liyuan Chen; Eric Kerfoot; Kerstin Klaser; Michela Antonelli; Alexander Hammers; Tim Spector; Sebastien Ourselin; Claire J. Steves; Carole H. Sudre; Marc Modat; Emma L. Duncan,"School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK; Department of Twin Research and Genetic Epidemiology, Kings College London, London, UK; School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK; ZOE Limited, London, UK; ZOE Limited, London, UK; ZOE Limited, London, UK; ZOE Limited, London, UK; School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK; School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK; School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK; School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK; School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK; School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK; School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK; King's College London & Guy's and St Thomas' PET Centre, London, UK; Department of Twin Research and Genetic Epidemiology, Kings College London, London, UK.; School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK; Department of Twin Research and Genetic Epidemiology, Kings College London, London, UK.; School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK; Medical Research Council Unit for Lifelong Health and Ageing, Departme; School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK; Department of Twin Research and Genetic Epidemiology, Kings College London, London, UK.","BackgroundIdentifying and testing individuals likely to have SARS-CoV-2 is critical for infection control, including post-vaccination. Vaccination is a major public health strategy to reduce SARS-CoV-2 infection globally. Some individuals experience systemic symptoms post-vaccination, which overlap with COVID-19 symptoms. This study compared early post-vaccination symptoms in individuals who subsequently tested positive or negative for SARS-CoV-2, using data from the COVID Symptom Study (CSS) app. - -DesignWe conducted a prospective observational study in UK CSS participants who were asymptomatic when vaccinated with Pfizer-BioNTech mRNA vaccine (BNT162b2) or Oxford-AstraZeneca adenovirus-vectored vaccine (ChAdOx1 nCoV-19) between 8 December 2020 and 17 May 2021, who subsequently reported symptoms within seven days (other than local symptoms at injection site) and were tested for SARS-CoV-2, aiming to differentiate vaccination side-effects per se from superimposed SARS-CoV-2 infection. The post-vaccination symptoms and SARS-CoV-2 test results were contemporaneously logged by participants. Demographic and clinical information (including comorbidities) were also recorded. Symptom profiles in individuals testing positive were compared with a 1:1 matched population testing negative, including using machine learning and multiple models including UK testing criteria. - -FindingsDifferentiating post-vaccination side-effects alone from early COVID-19 was challenging, with a sensitivity in identification of individuals testing positive of 0.6 at best. A majority of these individuals did not have fever, persistent cough, or anosmia/dysosmia, requisite symptoms for accessing UK testing; and many only had systemic symptoms commonly seen post-vaccination in individuals negative for SARS-CoV-2 (headache, myalgia, and fatigue). - -InterpretationPost-vaccination side-effects per se cannot be differentiated from COVID-19 with clinical robustness, either using symptom profiles or machine-derived models. Individuals presenting with systemic symptoms post-vaccination should be tested for SARS-CoV-2, to prevent community spread. - -FundingZoe Limited, UK Government Department of Health and Social Care, Wellcome Trust, UK Engineering and Physical Sciences Research Council, UK National Institute for Health Research, UK Medical Research Council and British Heart Foundation, Alzheimers Society, Chronic Disease Research Foundation, Massachusetts Consortium on Pathogen Readiness (MassCPR). - -Research in contextO_ST_ABSEvidence before this studyC_ST_ABSThere are now multiple surveillance platforms internationally interrogating COVID-19 and/or post-vaccination side-effects. We designed a study to examine for differences between vaccination side-effects and early symptoms of COVID-19. We searched PubMed for peer-reviewed articles published between 1 January 2020 and 21 June 2021, using keywords: ""COVID-19"" AND ""Vaccination"" AND (""mobile application"" OR ""web tool"" OR ""digital survey"" OR ""early detection"" OR ""Self-reported symptoms"" OR ""side-effects""). Of 185 results, 25 studies attempted to differentiate symptoms of COVID-19 vs. post-vaccination side-effects; however, none used artificial intelligence (AI) technologies (""machine learning"") coupled with real-time data collection that also included comprehensive and systematic symptom assessment. Additionally, none of these studies attempt to discriminate the early signs of infection from side-effects of vaccination (specifically here: Pfizer-BioNTech mRNA vaccine (BNT162b2) and Oxford-AstraZeneca adenovirus-vectored vaccine (ChAdOx1 nCoV-19)). Further, none of these studies sought to provide comparisons with current testing criteria used by healthcare services. - -Added value of this studyThis study, in a uniquely large community-based cohort, uses prospective data capture in a novel effort to identify individuals with COVID-19 in the immediate post-vaccination period. Our results show that early symptoms of SARS-CoV-2 cannot be differentiated from vaccination side-effects robustly. Thus, post-vaccination systemic symptoms should not be ignored, and testing should be considered to prevent COVID-19 dissemination by vaccinated individuals. - -Implications of all the available evidenceOur study demonstrates the critical importance of testing symptomatic individuals - even if vaccinated - to ensure early detection of SARS-CoV-2 infection, helping to prevent future pandemic waves in the UK and elsewhere.",respiratory medicine,fuzzy,100,100 medRxiv,10.1101/2021.07.19.21260770,2021-07-22,https://medrxiv.org/cgi/content/short/2021.07.19.21260770,Uptake of infant and pre-school immunisations in Scotland and England during the COVID-19 pandemic: an observational study of routinely collected data,Fiona McQuaid; Rachel Mulholland; Yuma Sangpang Rai; Utkarsh Agrawal; Helen Bedford; Claire Cameron; Cheryl Gibbon; Partho Roy; Aziz Sheikh; Ting Shi; Colin Simpson; Judith Tait; Elise Tessier; Steve Turner; Jaime Villacampa Ortega; Joanne White; Rachael Wood,University of Edinburgh; University of Edinburgh; Public Health England; University of St Andrews; UCL Great Ormond Street Institute of Child Health; Public Health Scotland; Public Health Scotland; Public Health England; University of Edinburgh; University of Edinburgh; Victoria University of Wellington; Public Health Scotland; Public Health England; University of Aberdeen; Public Health Scotland; Public Health England; University of Edinburgh,"BackgroundIn 2020, the COVID-19 pandemic and control measures such as national lockdowns threatened to disrupt routine childhood immunisation programmes. Initial reports from the early weeks of lockdown in the UK and worldwide suggested that uptake could fall putting children at risk from multiple other infectious diseases. In Scotland and England, enhanced surveillance of national data for childhood immunisations was established to inform and rapidly assess the impact of the pandemic on infant and preschool immunisation uptake rates. Methods and findingsWe undertook an observational study using routinely collected data for the year prior to the pandemic (2019), and immediately before, during and after the first period of the UK lockdown in 2020. Data were obtained for Scotland from the Public Health Scotland ""COVID19 wider impacts on the health care system"" dashboard (https://scotland.shinyapps.io/phs-covid-wider-impact/) and for England from ImmForm. @@ -2618,6 +2498,23 @@ Following two doses of Pfizer-BioNTech vaccine, antibody positivity (adjusted fo DiscussionThe successful roll out of the vaccination programme in England has led to a high proportion of individuals having detectable antibodies, particularly in older age groups and those who have had two doses of vaccine. This is likely to be associated with high levels of protection from severe disease, and possibly from infection. Nonetheless, there remain some key groups with a lower prevalence of antibody, notably unvaccinated younger people, certain minority ethnic groups, those living in deprived areas and workers in some public facing employment. Obtaining improved rates of vaccination in these groups is essential to achieving high levels of protection against the virus through population immunity. FundingDepartment of Health and Social Care in England.",infectious diseases,fuzzy,100,100 +medRxiv,10.1101/2021.07.12.21260385,2021-07-16,https://medrxiv.org/cgi/content/short/2021.07.12.21260385,Estimating the effectiveness of first dose of COVID-19 vaccine against mortality in England: a quasi-experimental study,Charlotte Bermingham; Jasper Morgan; Daniel Ayoubkhani; Myer Glickman; Nazrul Islam; Aziz Sheikh; Jonathan Sterne; A. Sarah Walker; Vahé Nafilyan,"Office for National Statistics, Newport, UK; Office for National Statistics, Newport, UK; Office for National Statistics, Newport, UK; Office for National Statistics, Newport, UK; Nuffield Department of Population Health, Big Data Institute, University of Oxford, Oxford, UK; Usher Institute, University of Edinburgh, Edinburgh, UK; Health Data Research UK BREATHE Hub; Bristol Medical School, University of Bristol, UK; Nuffield department of Medicine, University of Oxford, Oxford, UK; Office for National Statistics, Newport, UK","BackgroundEstimating real-world vaccine effectiveness is vital to assess the impact of the vaccination programme on the pandemic and inform the ongoing policy response. However, estimating vaccine effectiveness using observational data is inherently challenging because of the non-randomised design and the potential for unmeasured confounding. + +MethodsWe used a Regression Discontinuity Design (RDD) to estimate vaccine effectiveness against COVID-19 mortality in England, exploiting the discontinuity in vaccination rates resulting from the UKs age-based vaccination priority groups. We used the fact that people aged 80 or over were prioritised for the vaccine roll-out in the UK to compare the risk of COVID-19 and non-COVID-19 death in people aged 75-79 and 80-84. + +FindingsThe prioritisation of vaccination of people aged 80 or above led to a large discrepancy in vaccination rates in people 80-84 compared to those 75-79 at the beginning of the vaccination campaign. We found a corresponding difference in COVID-19 mortality, but not in non-COVID-19 mortality, suggesting that our approach appropriately addresses the issue of unmeasured confounding factors. Our results suggest that the first vaccine dose reduced the risk of COVID-19 death by 52.6% (95% Cl 26.6-84.2) in those aged 80. + +InterpretationsOur results support existing evidence that a first dose of a COVID-19 vaccine has a strong protective effect against COVID-19 mortality in older adults. The RDD estimate of vaccine effectiveness is comparable to previously published studies using different methods, suggesting that unmeasured confounding factors are unlikely to substantially bias these studies. + +FundingOffice for National Statistics. + +Research in ContextO_ST_ABSEvidence before this studyC_ST_ABSWe searched PubMed for studies reporting on the real-world effectiveness of the COVID-19 vaccination on risk of death using terms such as ""COVID-19"", ""vaccine effectiveness"", ""mortality"" and ""death"". The relevant published studies on this topic report vaccine effectiveness estimates against risk of death ranging from 64.2% to 98.7%, for varying times post-vaccination. All of these are observational studies and therefore potentially subject to bias from unmeasured confounding. We found no studies that used a quasi-experimental method such as regression discontinuity design, which is not subject to bias from unmeasured confounding, to calculate the effectiveness of the COVID-19 vaccination on risk of COVID-19 death, or on other outcomes such as hospitalisation or infection. + +Added value of this studyThe estimates of vaccine effectiveness based on observational data may be biased by unmeasured confounding. This study uses a regression discontinuity design to estimate vaccine effectiveness, exploiting the fact that the vaccination campaign in the UK was rolled out following age-based priority groups. This enables the calculation of an unbiased estimate of the effectiveness of the COVID-19 vaccine against risk of death. + +The vaccine effectiveness estimate of 52.6% (95% Cl 26.6-84.2) is slightly lower but similar to previously published estimates, therefore suggesting that these estimates are not substantially affected by unmeasured confounding factors and confirming the effectiveness of the COVID-19 vaccine against risk of COVID-19 death. + +Implications of all the available evidenceObtaining an unbiased estimate of COVID-19 vaccine effectiveness is of vital importance in informing policy for lifting COVID-19 related measures. The regression discontinuity design provides confidence that the existing estimates from observational studies are unlikely to be substantially biased by unmeasured confounding.",infectious diseases,fuzzy,100,100 medRxiv,10.1101/2021.07.12.21260387,2021-07-16,https://medrxiv.org/cgi/content/short/2021.07.12.21260387,Lessons learned and lessons missed: Impact of the Covid-19 pandemic on all-cause mortality in 40 industrialised countries prior to mass vaccination,Vasilis Kontis; James E Bennett; Robbie M Parks; Theo Rashid; Jonathan Pearson-Stuttard; Perviz Asaria; Bin Zhou; Michel Guillot; Colin D Mathers; Young-Ho Khang; Martin McKee; Majid Ezzati,"MRC Centre for Environment and Health, School of Public Health, Imperial College London, London, UK; MRC Centre for Environment and Health, School of Public Health, Imperial College London, London, UK; The Earth Institute, Columbia University, New York, NY, USA, and Department of Environmental Health Sciences, Mailman School of Public Health, Columbia Universi; MRC Centre for Environment and Health, School of Public Health, Imperial College London, London, UK; MRC Centre for Environment and Health, School of Public Health, Imperial College London, London, UK; MRC Centre for Environment and Health, School of Public Health, Imperial College London, London, UK; MRC Centre for Environment and Health, School of Public Health, Imperial College London, London, UK; Population Studies Center, Department of Sociology, University of Pennsylvania, Philadelphia, PA, USA and French Institute for Demographic Studies (INED), Paris; Independent Researcher, Geneva, Switzerland; Institute of Health Policy and Management, Seoul National University, Seoul, Republic of Korea; Department of Health Services Research and Policy, London School of Hygiene & Tropical Medicine, London, UK; MRC Centre for Environment and Health, School of Public Health, Imperial College London, London, UK and Regional Institute for Population Studies, University of","Industrialised countries have varied in their early response to the Covid-19 pandemic, and how they have adapted to new situations and knowledge since the pandemic began. These variations in preparedness and policy may lead to different death tolls from Covid-19 as well as from other diseases. We applied an ensemble of 16 Bayesian probabilistic models to vital statistics data to estimate the impacts of the pandemic on weekly all-cause mortality for 40 industrialised countries from mid-February 2020 through mid-February 2021, before a large segment of the population was vaccinated in any of these countries. Taken over the entire year, an estimated 1,401,900 (95% credible interval 1,259,700-1,572,500) more people died in these 40 countries than would have been expected had the pandemic not taken place. This is equivalent to 140 (126-157) additional deaths per 100,000 people and a 15% (13-17) increase in deaths over this period in all of these countries combined. In Iceland, Australia and New Zealand, mortality was lower over this period than what would be expected if the pandemic had not occurred, while South Korea and Norway experienced no detectable change in mortality. In contrast, the populations of the USA, Czechia, Slovakia and Poland experienced at least 20% higher mortality. There was substantial heterogeneity across countries in the dynamics of excess mortality. The first wave of the pandemic, from mid-February to the end of May 2020, accounted for over half of excess deaths in Scotland, Spain, England and Wales, Canada, Sweden, Belgium and Netherlands. At the other extreme, the period between mid-September 2020 and mid-February 2021 accounted for over 90% of excess deaths in Bulgaria, Croatia, Czechia, Hungary, Latvia, Montenegro, Poland, Slovakia and Slovenia. Until the great majority of national and global populations have vaccine-acquired immunity, minimising the death toll of the pandemic from Covid-19 and other diseases will remain dependent on actions to delay and contain infections and continue routine health and social care.",public and global health,fuzzy,100,100 medRxiv,10.1101/2021.07.13.21260444,2021-07-16,https://medrxiv.org/cgi/content/short/2021.07.13.21260444,Adoption and continued use of mobile contact tracing technology: Multilevel explanations from a three-wave panel survey and linked data,Laszlo Horvath; Susan Banducci; Joshua Blamire; Cathrine Degnen; Oliver James; Andrew Jones; Daniel Stevens; Katharine Tyler,"University of Exeter; University of Exeter; University of Exeter; Newcastle University, UK; University of Exeter; University of Exeter; University of Exeter; University of Exeter","ObjectiveTo identify the key individual-level (demographics, attitudes, mobility) and contextual (Covid-19 case numbers, tiers of mobility restrictions, urban districts) determinants of adopting the NHS Covid-19 contact tracing app and continued use over-time. @@ -2637,6 +2534,21 @@ C_LIO_LIIntegrating demographic/structural and attitudinal explanations relating C_LIO_LILimitation: studied population is England (see Section 2.3) where overall mobility is restricted in wave 3 during national lockdown, allowing for limited opportunities for app usage e.g. venue check-ins; C_LIO_LIDrawing on our findings, an ethnic minority booster sample will in the future allow us to better understand inequalities across and within diverse ethnic populations. C_LI",public and global health,fuzzy,100,100 +medRxiv,10.1101/2021.07.14.21260488,2021-07-16,https://medrxiv.org/cgi/content/short/2021.07.14.21260488,SARS-CoV-2 Antibody Lateral Flow Assay for antibody prevalence studies following vaccine roll out: a Diagnostic Accuracy Study,Alexandra H C Cann; Candice L Clarke; Jonathan C Brown; Tina Thomson; Maria Prendecki; Maya Moshe; Anjna Badhan; Paul Elliott; Ara Darzi; Steven Riley; Deborah Ashby; Michelle Willicombe; Peter Kelleher; Paul Randell; Helen Ward; Wendy Barclay; Graham Cooke,"Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London School of Public Health; Imperial College London; Dept Inf Dis Epi, Imperial College; Imperial College London; Imperial College London; Imperial College London; Imperial College Healthcare NHS Trust, UK; Imperial College London; Department of Infectious Disease, Imperial College London, UK; Imperial College London","BackgroundLateral flow immunoassays (LFIAs) have the potential to deliver affordable, large scale antibody testing and provide rapid results without the support of central laboratories. As part of the development of the REACT programme extensive evaluation of LFIA performance was undertaken with individuals following natural infection. Here we assess the performance of the selected LFIA to detect antibody responses in individuals who have received at least one dose of SARS-CoV-2 vaccine. + +MethodsThis is a prospective diagnostic accuracy study. + +SettingSampling was carried out at renal outpatient clinic and healthcare worker testing sites at Imperial College London NHS Trust. Laboratory analyses were performed across Imperial College London sites and university facilities. + +ParticipantsTwo cohorts of patients were recruited; the first was a cohort of 108 renal transplant patients attending clinic following SARS-CoV-2 vaccine booster, the second cohort comprised 40 healthcare workers attending for first SARS-CoV-2 vaccination, and 21 day follow up. A total of 186 paired samples were collected. + +InterventionsDuring the participants visit, capillary blood samples were analysed on LFIA device, while paired venous sampling was sent for serological assessment of antibodies to the spike protein (anti-S) antibodies. Anti-S IgG were detected using the Abbott Architect SARS-CoV-2 IgG Quant II CMIA. + +Main outcome measuresThe accuracy of Fortress LFIA in detecting IgG antibodies to SARS-CoV-2 compared to anti-spike protein detection on Abbott Assay. + +ResultsUsing the threshold value for positivity on serological testing of [≥]7.10 BAU/ml, the overall performance of the test produces an estimate of sensitivity of 91.94% (95% CI 85.67% to 96.06%) and specificity of 93.55% (95% CI 84.30% to 98.21%) using the Abbott assay as reference standard. + +ConclusionsFortress LFIA performs well in the detection of antibody responses for intended purpose of population level surveys, but does not meet criteria for individual testing.",infectious diseases,fuzzy,100,100 medRxiv,10.1101/2021.07.09.21260271,2021-07-16,https://medrxiv.org/cgi/content/short/2021.07.09.21260271,Quantifying within-school SARS-CoV-2 transmission and the impact of lateral flow testing in secondary schools in England,Trystan Leng; Edward M Hill; Alex Holmes; Emma Southall; Robin N Thompson; Michael J Tildesley; Matt J Keeling; Louise Dyson,University of Warwick; University of Warwick; University of Warwick; University of Warwick; University of Warwick; University of Warwick; University of Warwick; University of Warwick,"BackgroundTo control within-school SARS-CoV-2 transmission in England, secondary school pupils have been encouraged to participate in twice weekly mass testing via lateral flow device tests (LFTs) from 8th March 2021, to complement an isolation of close contacts policy in place since 31st August 2020. Strategies involving the isolation of close contacts can lead to high levels of absences, negatively impacting pupils. MethodsWe fit a stochastic individual-based model of secondary schools to both community swab testing data and secondary school absences data. By simulating epidemics in secondary schools from 31st August 2020 until 21st May 2021, we quantify within-school transmission of SARS-CoV-2 in secondary schools in England, the impact of twice weekly mass testing on within-school transmission, and the potential impact of alternative strategies to the isolation of close contacts in reducing pupil absences. @@ -2754,6 +2666,15 @@ One Sentence SummarySpatial analysis identifies IFN{gamma} response signatures a medRxiv,10.1101/2021.06.17.21259100,2021-06-20,https://medrxiv.org/cgi/content/short/2021.06.17.21259100,COVID-19 Transmission Dynamics Underlying Epidemic Waves in Kenya,Samuel P C Brand; John Ojal; Rabia Aziza; Vincent Were; Emelda Okiro; Ivy Kombe; Caroline Mburu; Morris Ogero; Ambrose Agweyu; George M Warimwe; James Nyagwange; Henry Karanja; John Gitonga; Daisy Mugo; Sophie Uyoga; Ifedayo M O Adetifa; J Anthony G Scott; Edward Otieno; Nickson Murunga; Mark Otiende; Lynette I Ochola-Oyier; Charles N Agoti; George Githinji; Kadondi Kasera; Patrick Amoth; Mercy Mwangangi; Rashid Aman; Wangari Ng'ang'a; Benjamin Tsofa; Philip Bejon; Matt J Keeling; D James Nokes; Edwine Barasa,"University of Warwick; Kenya Medical Research Institute (KEMRI) -Wellcome Trust Research Programme (KWTRP), Kilifi, Kenya; University of Warwick; Health Economics Research Unit, KEMRI-Wellcome Trust Research Programme, Nairobi, Kenya; Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom; Kenya Medical Research Institute (KEMRI) -Wellcome Trust Research Programme (KWTRP), Kilifi, Kenya; Kenya Medical Research Institute (KEMRI) -Wellcome Trust Research Programme (KWTRP), Kilifi, Kenya; Kenya Medical Research Institute (KEMRI) -Wellcome Trust Research Programme (KWTRP), Kilifi, Kenya; Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom; Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom; Kenya Medical Research Institute (KEMRI) -Wellcome Trust Research Programme (KWTRP), Kilifi, Kenya; Kenya Medical Research Institute (KEMRI) -Wellcome Trust Research Programme (KWTRP), Kilifi, Kenya; Kenya Medical Research Institute (KEMRI) -Wellcome Trust Research Programme (KWTRP), Kilifi, Kenya; Kenya Medical Research Institute (KEMRI) -Wellcome Trust Research Programme (KWTRP), Kilifi, Kenya; Kenya Medical Research Institute (KEMRI) -Wellcome Trust Research Programme (KWTRP), Kilifi, Kenya; Department of Infectious Diseases Epidemiology, London School of Hygiene and Tropical Medicine, London, United Kingdom; Department of Infectious Diseases Epidemiology, London School of Hygiene and Tropical Medicine, London, United Kingdom; Kenya Medical Research Institute (KEMRI) -Wellcome Trust Research Programme (KWTRP), Kilifi, Kenya; Kenya Medical Research Institute (KEMRI) -Wellcome Trust Research Programme (KWTRP), Kilifi, Kenya; Kenya Medical Research Institute (KEMRI) -Wellcome Trust Research Programme (KWTRP), Kilifi, Kenya; Kenya Medical Research Institute (KEMRI) -Wellcome Trust Research Programme (KWTRP), Kilifi, Kenya; Kenya Medical Research Institute (KEMRI) -Wellcome Trust Research Programme (KWTRP), Kilifi, Kenya; Kenya Medical Research Institute (KEMRI) -Wellcome Trust Research Programme (KWTRP), Kilifi, Kenya; Ministry of Health, Government of Kenya, Nairobi, Kenya; Ministry of Health, Government of Kenya, Nairobi, Kenya; Ministry of Health, Government of Kenya, Nairobi, Kenya; Ministry of Health, Government of Kenya, Nairobi, Kenya; Presidential Policy & Strategy Unit, The Presidency, Government of Kenya; Kenya Medical Research Institute (KEMRI) -Wellcome Trust Research Programme (KWTRP), Kilifi, Kenya; Kenya Medical Research Institute (KEMRI) -Wellcome Trust Research Programme (KWTRP), Kilifi, Kenya; University of Warwick; Kenya Medical Research Institute (KEMRI) -Wellcome Trust Research Programme (KWTRP), Kilifi, Kenya; Kenya Medical Research Institute (KEMRI) -Wellcome Trust Research Programme (KWTRP), Kilifi, Kenya","Policy decisions on COVID-19 interventions should be informed by a local, regional and national understanding of SARS-CoV-2 transmission. Epidemic waves may result when restrictions are lifted or poorly adhered to, variants with new phenotypic properties successfully invade, or when infection spreads to susceptible sub-populations. Three COVID-19 epidemic waves have been observed in Kenya. Using a mechanistic mathematical model we explain the first two distinct waves by differences in contact rates in high and low social-economic groups, and the third wave by the introduction of a new higher-transmissibility variant. Reopening schools led to a minor increase in transmission between the second and third waves. Our predictions of current population exposure in Kenya ([~]75% June 1st) have implications for a fourth wave and future control strategies. One Sentence SummaryCOVID-19 spread in Kenya is explained by mixing heterogeneity and a variant less constrained by high population exposure",epidemiology,fuzzy,100,100 +medRxiv,10.1101/2021.06.15.21258542,2021-06-16,https://medrxiv.org/cgi/content/short/2021.06.15.21258542,"Casirivimab and imdevimab in patients admitted to hospital with COVID-19 (RECOVERY): a randomised, controlled, open-label, platform trial",Peter W Horby; Marion Mafham; Leon Peto; Mark Campbell; Guilherme Pessoa-Amorim; Enti Spata; Natalie Staplin; Jonathan R Emberson; Benjamin Prudon; Paul Hine; Thomas Brown; Christopher A Green; Rahuldeb Sarkar; Purav Desai; Bryan Yates; Tom Bewick; Simon Tiberi; Tim Felton; J Kenneth Baillie; Maya H Buch; Lucy C Chappell; Jeremy N Day; Saul N Faust; Thomas Jaki; Katie Jeffery; Edmund Juszczak; Wei Shen Lim; Alan Montgomery; Andrew Mumford; Kathryn Rowan; Guy Thwaites; David M Weinreich; Richard Haynes; Martin J Landray,"Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom; Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom; Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom; Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom; Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom; MRC Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom; MRC Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom; MRC Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom; North Tees and Hartlepool NHS Foundation Trust, Hartlepool, United Kingdom; Liverpool University Hospitals NHS Foundation Trust; Portsmouth Hospitals University NHS Foundation Trust, Portsmouth, United Kingdom; University Hospitals Birmingham NHS Foundation Trust; Medway NHS Foundation Trust; Calderdale and Huddersfield NHS Foundation Trust; Northumbria Healthcare NHS Foundation Trust; University Hospitals Of Derby and Burton NHS Foundation Trust; Barts Health NHS Trust; Manchester University NHS Foundation Trust; Roslin Institute, University of Edinburgh, Edinburgh, United Kingdom; Centre for Musculoskeletal Research, University of Manchester, Manchester, United Kingdom; School of Life Sciences, Kings College London, London, United Kingdom; Oxford University Clinical Research Unit, Ho Chi Minh City, Viet Nam, and Nuffield Department of Medicine, University of Oxford, United Kingdom; NIHR Southampton Clinical Research Facility and Biomedical Research Centre, University Hospital Southampton NHS Foundation Trust and University of Southampton, ; Department of Mathematics and Statistics, Lancaster University, Lancaster, United Kingdom; Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom; School of Medicine, University of Nottingham, Nottingham, United Kingdom; Respiratory Medicine Department, Nottingham University Hospitals NHS Foundation Trust, Nottingham, United Kingdom; School of Medicine, University of Nottingham, Nottingham, United Kingdom; School of Cellular and Molecular Medicine, University of Bristol, Bristol, United Kingdom; Intensive Care National Audit and Research Centre, London, United Kingdom; Oxford University Clinical Research Unit, Ho Chi Minh City, Viet Nam, and Nuffield Department of Medicine, University of Oxford, United Kingdom; Regeneron Pharmaceuticals Inc, Tarrytown, NY, USA; MRC Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom; Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom","BackgroundREGEN-COV is a combination of 2 monoclonal antibodies (casirivimab and imdevimab) that bind to two different sites on the receptor binding domain of the SARS-CoV-2 spike protein. We aimed to evaluate the efficacy and safety of REGEN-COV in patients admitted to hospital with COVID-19. + +MethodsIn this randomised, controlled, open-label platform trial, several possible treatments were compared with usual care in patients hospitalised with COVID-19. Eligible and consenting patients were randomly allocated (1:1) to either usual standard of care alone (usual care group) or usual care plus a single dose of REGEN-COV 8g (casirivimab 4g and imdevimab 4g) by intravenous infusion (REGEN-COV group). The primary outcome was 28-day mortality assessed first among patients without detectable antibodies to SARS-CoV-2 at randomisation (seronegative) and then in the overall population. The trial is registered with ISRCTN (50189673) and clinicaltrials.gov (NCT04381936). + +FindingsBetween 18 September 2020 and 22 May 2021, 9785 patients were randomly allocated to receive usual care plus REGEN-COV or usual care alone, including 3153 (32%) seronegative patients, 5272 (54%) seropositive patients and 1360 (14%) patients with unknown baseline antibody status. In the primary efficacy population of seronegative patients, 396 (24%) of 1633 patients allocated to REGEN-COV and 451 (30%) of 1520 patients allocated to usual care died within 28 days (rate ratio 0{middle dot}80; 95% CI 0{middle dot}70-0{middle dot}91; p=0{middle dot}0010). In an analysis involving all randomised patients (regardless of baseline antibody status), 944 (20%) of 4839 patients allocated to REGEN-COV and 1026 (21%) of 4946 patients allocated to usual care died within 28 days (rate ratio 0{middle dot}94; 95% CI 0{middle dot}86-1{middle dot}03; p=0{middle dot}17). The proportional effect of REGEN-COV on mortality differed significantly between seropositive and seronegative patients (p value for heterogeneity = 0{middle dot}001). + +InterpretationIn patients hospitalised with COVID-19, the monoclonal antibody combination of casirivimab and imdevimab (REGEN-COV) reduced 28-day mortality among patients who were seronegative at baseline. + +FundingUK Research and Innovation (Medical Research Council) and National Institute of Health Research (Grant ref: MC_PC_19056).",infectious diseases,fuzzy,100,100 medRxiv,10.1101/2021.06.11.21258730,2021-06-16,https://medrxiv.org/cgi/content/short/2021.06.11.21258730,Relative perceived importance of different settings for SARS-CoV2 acquisition in England and Wales: Analysis of the Virus Watch Community Cohort,Sarah Beale; Thomas Edward Byrne; Ellen Benard Fragaszy; Jana Kovar; Vincent Grigori Nguyen; Anna Aryee; Wing Lam Erica Fong; Cyril Roman Geismar; Parth Patel; Madhumita Shrotri; Nicholas Patni; Isobel Braithwaite; Annalan Mathew Dwight Navaratnam; Robert William Aldridge; Andrew C Hayward,University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University of Oxford; University College London; University College London; University College London; University College London,"We aimed to assess the relative importance of different settings for SARS-CoV2 transmission in a large community cohort. We demonstrate the importance of home, work and education as venues for transmission. In children, education was most important and in older adults essential shopping was of high importance. Our findings support public health messaging about infection control at home, advice on working from home and restrictions in different venues.",public and global health,fuzzy,100,100 medRxiv,10.1101/2021.06.08.21258551,2021-06-15,https://medrxiv.org/cgi/content/short/2021.06.08.21258551,NHS CHECK: protocol for a cohort study investigating the psychosocial impact of the COVID-19 pandemic on healthcare workers,Danielle Lamb; Neil Greenberg; Matthew Hotopf; Rosalind Raine; Reza Razavi; Rupa Bhundia; Hannah Scott; Ewan Carr; Rafael Gafoor; Ioannis Bakolis; Siobhan Hegarty; Emilia Souliou; Anne Marie Rafferty; Rebecca Rhead; Danny Weston; Sam Gnanapragasam; Sally Marlow; Simon Wessely; Sharon Stevelink,UCL; King's College London; King's College London; UCL; King's College London; King's College London; King's College London; King's College London; ICL; King's College London; King's College London; King's College London; King's College London; King's College London; King's College London; King's College London; King's College London; King's College London; King's College London,"IntroductionThe COVID-19 pandemic has had profound effects on the working lives of healthcare workers (HCWs), but the extent to which their well-being and mental health have been affected remains unclear. This longitudinal cohort study aims to recruit a cohort of NHS healthcare workers, conducting surveys at regular intervals to provide evidence about the prevalence of symptoms of mental disorders, investigate associated factors such as occupational contexts and support interventions available. @@ -2767,6 +2688,7 @@ C_LIO_LIThe diagnostic interview component of the study will allow us to establi C_LIO_LIThe qualitative interviews will give deeper insight into the support programmes that HCWs find most helpful, and provide ideas for Trusts to improve their offer to staff. C_LIO_LIThe three components of the study give breadth and depth lacking in much of the mental health and wellbeing research currently available, but there is a risk of over-burdening already stretched HCWs. C_LI",psychiatry and clinical psychology,fuzzy,100,100 +medRxiv,10.1101/2021.06.11.21258690,2021-06-15,https://medrxiv.org/cgi/content/short/2021.06.11.21258690,Brain imaging before and after COVID-19 in UK Biobank,Gwenaëlle Douaud; Soojin Lee; Fidel Alfaro-Almagro; Christoph Arthofer; Chaoyue Wang; Paul McCarthy; Frederik Lange; Jesper L.R. Andersson; Ludovica Griffanti; Eugene Duff; Saad Jbabdi; Bernd Taschler; Peter Keating; Anderson M. Winkler; Rory Collins; Paul M. Matthews; Naomi Allen; Karla L. Miller; Thomas E. Nichols; Stephen M. Smith,"FMRIB Centre, Wellcome Centre for Integrative Neuroimaging (WIN), Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK; FMRIB Centre, Wellcome Centre for Integrative Neuroimaging (WIN), Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK; FMRIB Centre, Wellcome Centre for Integrative Neuroimaging (WIN), Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK; FMRIB Centre, Wellcome Centre for Integrative Neuroimaging (WIN), Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK; FMRIB Centre, Wellcome Centre for Integrative Neuroimaging (WIN), Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK; FMRIB Centre, Wellcome Centre for Integrative Neuroimaging (WIN), Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK; FMRIB Centre, Wellcome Centre for Integrative Neuroimaging (WIN), Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK; FMRIB Centre, Wellcome Centre for Integrative Neuroimaging (WIN), Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK; FMRIB Centre, Wellcome Centre for Integrative Neuroimaging (WIN), Nuffield Department of Clinical Neurosciences, University of Oxford; OHBA, Wellcome Centre for; FMRIB Centre, Wellcome Centre for Integrative Neuroimaging (WIN), Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK; Department of; FMRIB Centre, Wellcome Centre for Integrative Neuroimaging (WIN), Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK; FMRIB Centre, Wellcome Centre for Integrative Neuroimaging (WIN), Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK; Ear Institute, University College London, London, UK; National Institutes of Mental Health, National Institutes of Health, Bethesda, MD, USA; Nuffield Department of Population Health, University of Oxford, Oxford, UK; UK Dementia Research Institute and Department of Brain Sciences, Imperial College, London, UK; Nuffield Department of Population Health, University of Oxford, Oxford, UK; FMRIB Centre, Wellcome Centre for Integrative Neuroimaging (WIN), Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK; Big Data Institute, University of Oxford, Oxford, UK; FMRIB Centre, Wellcome Centre for Integrative Neuroimaging (WIN), Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK","There is strong evidence for brain-related abnormalities in COVID-191-13. It remains unknown however whether the impact of SARS-CoV-2 infection can be detected in milder cases, and whether this can reveal possible mechanisms contributing to brain pathology. Here, we investigated brain changes in 785 UK Biobank participants (aged 51-81) imaged twice, including 401 cases who tested positive for infection with SARS-CoV-2 between their two scans, with 141 days on average separating their diagnosis and second scan, and 384 controls. The availability of pre-infection imaging data reduces the likelihood of pre-existing risk factors being misinterpreted as disease effects. We identified significant longitudinal effects when comparing the two groups, including: (i) greater reduction in grey matter thickness and tissue-contrast in the orbitofrontal cortex and parahippocampal gyrus, (ii) greater changes in markers of tissue damage in regions functionally-connected to the primary olfactory cortex, and (iii) greater reduction in global brain size. The infected participants also showed on average larger cognitive decline between the two timepoints. Importantly, these imaging and cognitive longitudinal effects were still seen after excluding the 15 cases who had been hospitalised. These mainly limbic brain imaging results may be the in vivo hallmarks of a degenerative spread of the disease via olfactory pathways, of neuroinflammatory events, or of the loss of sensory input due to anosmia. Whether this deleterious impact can be partially reversed, or whether these effects will persist in the long term, remains to be investigated with additional follow up.",neurology,fuzzy,100,100 medRxiv,10.1101/2021.06.09.21258629,2021-06-14,https://medrxiv.org/cgi/content/short/2021.06.09.21258629,IMPACT OF COVID-19 PANDEMIC ON SICKNESS ABSENCE FOR MENTAL ILL HEALTH IN NATIONAL HEALTH SERVICE STAFF,Diana van der Plaat; Rhiannon Edge; David Coggon; Martie van Tongersen; Rupert Muiry; Vaughan Parsons; Paul Cullinan; Ira Madan,Imperial College London; University of Lancaster; University of Southampton; University of Manchester; Guy's and St Thomas NHS Foundation Trust; Guy's and St Thomas NHS Foundation Trust; Imperial College London; Guy's and St Thomas' NHS Foundation Trust,"ObjectiveTo explore the patterns of sickness absence in National Health Service (NHS) staff attributable to mental ill health during the first wave of the Covid-19 epidemic in March - July 2020 DesignCase-referent analysis of a secondary data set @@ -3012,7 +2934,27 @@ ResultsIn total, 1,317 confirmed workplace outbreaks were identified from HPZone In total, 390 outbreaks were identified from SOI data and 264 of them allowed for estimation of attack rates. The overall median attack rate was 3.4% of the employed persons with confirmed COVID-19 at a workplace with an outbreak. Most of these outbreaks (162) had an attack rate less than 6%. However, in a small number of outbreaks (57) the attack rate was over 15%. The attack rates increased as the size of the enterprise decreased. The highest attack rate was for outbreaks in close contact services (median 16.5%), which was followed by outbreaks in restaurants and catering (median 10.2%), and in manufacturers and packers of non-food products (median 6.7%). ConclusionsOur linked dataset analysis approach allows early identification of geographical regions and industrial sectors with higher rates of COVID-19 workplace outbreaks as well as estimation of attack rates by enterprise size and sector. This can be used to inform interventions to limit transmission of the virus. Our approach to analysing the workplace outbreak data can also be applied to calculation of outbreak rates and attack rates in other types of settings such as care homes, hospitals and educational settings.",epidemiology,fuzzy,100,100 -medRxiv,10.1101/2021.05.08.21256867,2021-05-14,https://medrxiv.org/cgi/content/short/2021.05.08.21256867,SARS-CoV-2 lineage dynamics in England from January to March 2021 inferred from representative community samples,Oliver Eales; Andrew Page; Sonja N. Tang; Caroline E. Walters; Haowei Wang; David Haw; Alexander J. Trotter; Thanh Le Viet; Ebenezer Foster-Nyarko; Sophie Prosolek; Christina Atchinson; Deborah Ashby; Graham Cooke; Wendy Barclay; Christl A Donnelly; Justin O'Grady; Erik Volz; - The COVID-19 Genomics UK (COG-UK) Consortium; Ara Darzi; Helen Ward; Paul Elliott; Steven Riley,"School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; Quadram Institute, Norwich, UK; School of Public Health, Imperial College London, UK; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; Quadram Institute, Norwich, UK; Quadram Institute, Norwich, UK; Quadram Institute, Norwich, UK; Quadram Institute, Norwich, UK; School of Public Health, Imperial College London, UK; School of Public Health, Imperial College London, UK; Department of Infectious Disease, Imperial College London, UK Imperial College Healthcare NHS Trust, UK National Institute for Health Research Imperial Biomedic; Department of Infectious Disease, Imperial College London, UK; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; Quadram Institute, Norwich, UK; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; ; Imperial College Healthcare NHS Trust, UK National Institute for Health Research Imperial Biomedical Research Centre, UK Institute of Global Health Innovation a; School of Public Health, Imperial College London, UK Imperial College Healthcare NHS Trust, UK National Institute for Health Research Imperial Biomedical Resear; School of Public Health, Imperial College London, UK Imperial College Healthcare NHS Trust, UK National Institute for Health Research Imperial Biomedical Resear; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc","Genomic surveillance for SARS-CoV-2 lineages informs our understanding of possible future changes in transmissibility and vaccine efficacy. However, small changes in the frequency of one lineage over another are often difficult to interpret because surveillance samples are obtained from a variety of sources. Here, we describe lineage dynamics and phylogenetic relationships using sequences obtained from a random community sample who provided a throat and nose swab for rt-PCR during the first three months of 2021 as part of the REal-time Assessment of Community Transmission-1 (REACT-1) study. Overall, diversity decreased during the first quarter of 2021, with the B.1.1.7 lineage (first identified in Kent) predominant, driven by a 0.3 unit higher reproduction number over the prior wild type. During January, positive samples were more likely B.1.1.7 in younger and middle-aged adults (aged 18 to 54) than in other age groups. Although individuals infected with the B.1.1.7 lineage were no more likely to report one or more classic COVID-19 symptoms compared to those infected with wild type, they were more likely to be antibody positive 6 weeks after infection. Viral load was higher in B.1.1.7 infection as measured by cycle threshold (Ct) values, but did not account for the increased rate of testing positive for antibodies. The presence of infections with non-imported B.1.351 lineage (first identified in South Africa) during January, but not during February or March, suggests initial establishment in the community followed by fade-out. However, this occurred during a period of stringent social distancing and targeted public health interventions and does not immediately imply similar lineages could not become established in the future. Sequence data from representative community surveys such as REACT-1 can augment routine genomic surveillance.",infectious diseases,fuzzy,100,100 +medRxiv,10.1101/2021.05.11.21257040,2021-05-13,https://medrxiv.org/cgi/content/short/2021.05.11.21257040,Trajectories of child emotional and behavioural difficulties before and during the COVID-19 pandemic in a longitudinal UK cohort,Elise Paul; Daphne Kounali; Alex Siu Fung Kwong; Daniel Smith; Ilaria Costantini; Deborah A Lawlor; Kapil Sayal; Helen Bould; Nicholas J Timpson; Kate Northstone; Melanie Lewcock; Kate J Tilling; Rebecca Pearson,University College London; University of Bristol; University of Bristol; University of Bristol; University of Bristol; University of Bristol; University of Nottingham; University of Bristol; University of Bristol; University of Bristol; University of Bristol; University of Bristol; University of Bristol,"ImportanceCOVID-19 public health mitigation measures are likely to have detrimental effects on emotional and behavioural problems in children. However, longitudinal studies with pre-pandemic data are scarce. + +ObjectiveTo explore trajectories of childrens emotional and behavioural difficulties during the COVID-19 pandemic. + +Design and settingData were from children from the third generation of a birth cohort study; the Avon Longitudinal Study of Parents and Children - Generation 2 (ALSPAC-G2) in the southwest of England. + +ParticipantsThe study population comprised of 708 children (median age at COVID-19 data collection was 4.4 years, SD=2.9, IQR= [2.2 to 6.9]), whose parents provided previous pre-pandemic surveys and a survey between 26 May and 5 July 2020 that focused on information about the COVID-19 pandemic as restrictions from the first lockdown in the UK were eased. + +ExposuresWe employed multi-level mixed effects modelling with random intercepts and slopes to examine whether childrens trajectories of emotional and behavioural difficulties (a combined total difficulties score) during the pandemic differ from expected pre-pandemic trajectories. + +Main outcomesChildren had up to seven measurements of emotional and behavioural difficulties from infancy to late childhood, using developmentally appropriate scales such as the Emotionality Activity Sociability Temperament Survey in infancy and Strengths and Difficulties Questionnaire in childhood. + +ResultsThe observed normative pattern of childrens emotional and behavioural difficulties pre-pandemic, was characterised by an increase in scores during infancy peaking around the age of 2, and then declining throughout the rest of childhood. Pre-pandemic, the decline in difficulties scores after age 2 was 0.6 points per month; but was approximately one third of that in post-pandemic trajectories (there was a difference in mean rate of decline after age 2 of 0.2 points per month in pre vs during pandemic trajectories [95 % CI: 0.10 to 0.30, p <0.001]). This lower decline in scores over the years translated to older children having pandemic difficulty scores higher than would be expected from pre-pandemic trajectories (for example, an estimated 10.0 point (equivalent of 0.8 standard deviations) higher score (95% CI: 5.0 to 15.0) by age 8.5 years). Results remained similar although somewhat attenuated after adjusting for maternal anxiety and age. + +Conclusion and relevanceThe COVID-19 pandemic may be associated with greater persistence of emotional and behavioural difficulties after the age 2. Emotional difficulties in childhood predict later mental health problems. Further evidence and monitoring of emotional and behavioural difficulties are required to fully understand the potential role of the pandemic on young children. + +Key FindingsO_ST_ABSQuestionC_ST_ABSHow has the COVID-19 pandemic influenced emotional difficulties in young children? + +FindingsUsing repeated longitudinal data from before and during the pandemic we provide evidence that emotional difficulty scores of primary school aged children are higher by an estimated 10.0 points (0.8 standard deviations) (95% CI: 5.0 to 15.0) by age 8.5 years than would be expected based on pre pandemic data. + +MeaningThe level of difference in emotional difficulties found in the current study has been linked to increased likelihood of mental health problems in adolescence and adulthood. Therefore, this increase in difficulties needs careful monitoring and support.",psychiatry and clinical psychology,fuzzy,100,100 medRxiv,10.1101/2021.05.06.21256755,2021-05-13,https://medrxiv.org/cgi/content/short/2021.05.06.21256755,Clinical coding of long COVID in English primary care: a federated analysis of 58 million patient records in situ using OpenSAFELY,- The OpenSAFELY Collaborative; Alex J Walker; Brian MacKenna; Peter Inglesby; Christopher T Rentsch; Helen J Curtis; Caroline E Morton; Jessica Morley; Amir Mehrkar; Sebastian CJ Bacon; George Hickman; Christopher Bates; Richard Croker; David Evans; Tom Ward; Jonathan Cockburn; Simon Davy; Krishnan Bhaskaran; Anna Schultze; Elizabeth J Williamson; William J Hulme; Helen I McDonald; Laurie Tomlinson; Rohini Mathur; Rosalind M Eggo; Kevin Wing; Angel YS Wong; Harriet Forbes; John Tazare; John Parry; Frank Hester; Sam Harper; Shaun O'Hanlon; Alex Eavis; Richard Jarvis; Dima Avramov; Paul Griffiths; Aaron Fowles; Nasreen Parkes; Ian J Douglas; Stephen JW Evans; Liam Smeeth; Ben Goldacre,; University of Oxford; University of Oxford; University of Oxford; London School of Hygiene and Tropical Medicine; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; TPP; University of Oxford; University of Oxford; University of Oxford; TPP; University of Oxford; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; University of Oxford; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; TPP; TPP; TPP; EMIS; EMIS; EMIS; EMIS; EMIS; EMIS; EMIS; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; University of Oxford,"BackgroundLong COVID is a term to describe new or persistent symptoms at least four weeks after onset of acute COVID-19. Clinical codes to describe this phenomenon were released in November 2020 in the UK, but it is not known how these codes have been used in practice. MethodsWorking on behalf of NHS England, we used OpenSAFELY data encompassing 96% of the English population. We measured the proportion of people with a recorded code for long COVID, overall and by demographic factors, electronic health record software system, and week. We also measured variation in recording amongst practices. @@ -3086,6 +3028,19 @@ MethodsParticipants (n=20120-25228 across surveys) reported their daily activiti ResultsRelative to participants in the least deprived areas, participants in the most deprived areas persistently exhibited elevated risk of exposure to vehicle sharing (aRR range across time points 1.73-8.52), public transport (aRR 3.13-5.73), work or education outside of the household (aRR 1.09-1.21), essential shops (aRR 1.09-1.13) and non-household contacts (aRR 1.15-1.19) across multiple survey periods. ConclusionDifferential exposure to essential public activities in deprived communities is likely to contribute to inequalities in infection risk and outcomes during the COVID-19 pandemic. Public health interventions to reduce exposure during essential activities and financial and practical support to enable low-paid workers to stay at home during periods of intense transmission may reduce COVID-related inequalities.",epidemiology,fuzzy,100,100 +medRxiv,10.1101/2021.04.24.21255968,2021-04-27,https://medrxiv.org/cgi/content/short/2021.04.24.21255968,MORTALITY OF CARE HOME RESIDENTS AND COMMUNITY-DWELLING CONTROLS DURING THE COVID-19 PANDEMIC IN 2020: MATCHED COHORT STUDY,Martin C Gulliford; A Toby Prevost; Andrew Clegg; Emma C Rezel-Potts,King's College London; King's College London; University of Leeds; King's College London,"ObjectiveTo estimate mortality of care home (CH) residents, and matched community-dwelling controls, during the Covid-19 pandemic from primary care electronic health records. + +DesignMatched cohort study + +SettingGeneral practices contributing to the Clinical Practice Research Datalink Aurum Database in England. + +ParticipantsThere were 83,627 CH residents contributing data in 2020, with 26,923 deaths; 80,730 (97%) were matched on age, gender and general practice with 300,445 community-dwelling adults. + +Main outcome measuresAll-cause mortality. Adjusted rate ratios (RR) by negative binomial regression were adjusted for age, gender, number of long-term conditions (LTCs), frailty category, region, calendar month or week, and clustering by general practice. + +ResultsDuring April 2020, the mortality rate of CH residents was 27.2 deaths per 1,000 patients per week, compared with 2.31 per 1,000 for controls, RR 11.1 (95% confidence interval 10.1 to 12.2). Compared with CH residents, LTCs and frailty were differentially associated with greater mortality in community-dwelling controls. During April 2020, mortality rates per 1,000 patients per week for persons with 9+ LTCs were: CH, 37.9; controls 17.7; RR 2.14 (1.18 to 3.89). In severe frailty, mortality rates were: CH, 29.6; controls 5.1; RR 6.17 (5.74 to 6.62). + +ConclusionsIndividual-patient data from primary care electronic health records may be used to estimate mortality in care home residents. Mortality is substantially higher than for community-dwelling comparators and showed a disproportionate increase in the first wave of the Covid-19 pandemic. Multiple morbidity and frailty were associated with greater absolute risks but lower relative risks because community-dwelling frail or multi-morbid patients also experienced high mortality.",epidemiology,fuzzy,100,100 medRxiv,10.1101/2021.04.21.21255807,2021-04-27,https://medrxiv.org/cgi/content/short/2021.04.21.21255807,A randomised clinical trial of azithromycin versus standard care in ambulatory COVID-19 - the ATOMIC2 trial,Timothy SC Hinks; Lucy Cureton; Ruth Knight; Ariel Wang; Jennifer L Cane; Vicki S Barber; Joanna Black; Susan J Dutton; James Melhorn; Maisha Jabeen; Phil Moss; Rajendar Garlapati; Tanya Baron; Graham Johnson; Fleur Cantle; David Clarke; Samer Elkhodair; Jonathan Underwood; Daniel Lasserson; Ian D Pavord; Sophie B Morgan; Duncan Richards,"University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; St George's Hospital, London; East Lancashire NHS Hospitals; Oxford University Hospitals NHS Trust; Royal Derby Hospital; Kings College Hospital, London; Royal Berkshire Hospital; University College London Hospital; Cardiff University; Oxford University Hospitals NHS Trust; University of Oxford; University of Oxford; University of Oxford","BackgroundThe antibacterial, anti-inflammatory and antiviral properties of azithromycin suggest therapeutic potential against COVID-19. Randomised data in mild-moderate disease are lacking. We assessed whether azithromycin is effective in reducing hospitalisation in patients with mild-moderate COVID-19. MethodsThis open-label, randomised superiority clinical trial at 19 centres in the United Kingdom enrolled adults, [≥]18 years, presenting to hospitals with clinically-diagnosed highly-probable or confirmed COVID-19 infection, with <14 days symptoms, considered suitable for initial ambulatory management. Patients were randomised (1:1) to azithromycin (500 mg daily orally for 14 days) or to standard care without macrolides. The primary outcome was the difference in proportion of participants with death or hospital admission from any cause over the 28 days from randomisation, assessed according to intention-to-treat (ITT). Trial registration: ClinicalTrials.gov, NCT04381962, Study closed. @@ -3118,21 +3073,6 @@ The dry run showed four main sources of contamination that led to the modificati ConclusionCareful consideration of biosafety issues and contextual factors associated with care home are mandatory for safe use the POCT. Whilst POCT may have some utility for ruling out COVID-19, further diagnostic accuracy evaluations are needed to promote effective adoption.",health systems and quality improvement,fuzzy,90,100 medRxiv,10.1101/2021.04.22.21255911,2021-04-23,https://medrxiv.org/cgi/content/short/2021.04.22.21255911,The impact of SARS-CoV-2 vaccines on antibody responses in the general population in the United Kingdom,Jia Wei; Nicole Stoesser; Philippa C Matthews; Ruth Studley; Iain Bell; John I Bell; John N Newton; Jeremy Farrar; Ian Diamond; Emma Rourke; Alison Howarth; Brian D Marsden; Sarah Hoosdally; E Yvonne Jones; David I Stuart; Derrick W Crook; Tim EA Peto; Koen B Pouwels; David W Eyre; A Sarah Walker; - COVID-19 Infection Survey team,"University of Oxford; University of Oxford; University of Oxford; Office for National Statistics, UK; Office for National Statistics, UK; University of Oxford; Public Health England; Wellcome Trust; Office for National Statistics, UK; Office for National Statistics, UK; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; ","Real-world data on antibody response post-vaccination in the general population are limited. 45,965 adults in the UKs national COVID-19 Infection Survey receiving Pfizer-BioNTech or Oxford-AstraZeneca vaccines had 111,360 anti-spike IgG measurements. Without prior infection, seroconversion rates and quantitative antibody levels post single dose were lower in older individuals, especially >60y. Two doses achieved high responses across all ages, particularly increasing seroconversion in older people, to similar levels to those achieved after prior infection followed by a single dose. Antibody levels rose more slowly and to lower levels with Oxford-AstraZeneca vs Pfizer-BioNTech, but waned following a single Pfizer-BioNTech dose. Latent class models identified four responder phenotypes: older people, males, and those having long-term health conditions were more commonly low responders. Where supplies are limited, vaccines should be prioritised for those not previously infected, and second doses to individuals >60y. Further data on the relationship between vaccine-mediated protection and antibody responses are needed.",infectious diseases,fuzzy,100,100 -medRxiv,10.1101/2021.04.22.21255913,2021-04-23,https://medrxiv.org/cgi/content/short/2021.04.22.21255913,Impact of vaccination on SARS-CoV-2 cases in the community: a population-based study using the UK COVID-19 Infection Survey,Emma Pritchard; Philippa Matthews; Nicole Stoesser; David Eyre; Owen Gethings; Karina-Doris Vitha; Joel Jones; Thomas House; Harper VanSteenhouse; Iain Bell; John Bell; John Newton; Jeremy Farrar; Ian Diamond; Emma Rourke; Ruth Studley; Derrick W Crook; tim E peto; Ann Sarah Walker; Koen B Pouwels,"University of Oxford; University of Oxford; University of Oxford; University of Oxford; Office for National Statistics; University of Oxford; Office for National Statistics; University of Manchester; Glasgow Lighthouse Laboratory; Office for National Statistics; University of Oxford; Public Health England; Wellcome Trust; Office for National Statistics,; Office for National Statistics; Office for National Statistics; NIHR Oxford Biomedical Research Centre; oxford university; University of Oxford; University of Oxford","ObjectivesTo assess the effectiveness of COVID-19 vaccination in preventing SARS-CoV-2 infection in the community. - -DesignProspective cohort study. - -SettingThe UK population-representative longitudinal COVID-19 Infection Survey. - -Participants373,402 participants aged [≥]16 years contributing 1,610,562 RT-PCR results from nose and throat swabs between 1 December 2020 and 3 April 2021. - -Main outcome measuresNew RT-PCR-positive episodes for SARS-CoV-2 overall, by self-reported symptoms, by cycle threshold (Ct) value (<30 versus [≥]30), and by gene positivity (compatible with the B.1.1.7 variant versus not). - -ResultsOdds of new SARS-CoV-2 infection were reduced 65% (95% CI 60 to 70%; P<0.001) in those [≥]21 days since first vaccination with no second dose versus unvaccinated individuals without evidence of prior infection (RT-PCR or antibody). In those vaccinated, the largest reduction in odds was seen post second dose (70%, 95% CI 62 to 77%; P<0.001).There was no evidence that these benefits varied between Oxford-AstraZeneca and Pfizer-BioNTech vaccines (P>0.9).There was no evidence of a difference in odds of new SARS-CoV-2 infection for individuals having received two vaccine doses and with evidence of prior infection but not vaccinated (P=0.89). Vaccination had a greater impact on reducing SARS-CoV-2 infections with evidence of high viral shedding Ct<30 (88% reduction after two doses; 95% CI 80 to 93%; P<0.001) and with self-reported symptoms (90% reduction after two doses; 95% CI 82 to 94%; P<0.001); effects were similar for different gene positivity patterns. - -ConclusionVaccination with a single dose of Oxford-AstraZeneca or Pfizer-BioNTech vaccines, or two doses of Pfizer-BioNTech, significantly reduced new SARS-CoV-2 infections in this large community surveillance study. Greater reductions in symptomatic infections and/or infections with a higher viral burden are reflected in reduced rates of hospitalisations/deaths, but highlight the potential for limited ongoing transmission from asymptomatic infections in vaccinated individuals. - -RegistrationThe study is registered with the ISRCTN Registry, ISRCTN21086382.",infectious diseases,fuzzy,100,100 medRxiv,10.1101/2021.04.12.21255275,2021-04-19,https://medrxiv.org/cgi/content/short/2021.04.12.21255275,Children develop strong and sustained cross-reactive immune responses against spike protein following SARS-CoV-2 infection,Alexander C Dowell; Megan S. Butler; Elizabeth Jinks; Gokhan Tut; Tara Lancaster; Panagiota Sylla; Jusnara Begum; Rachel Bruton; Hayden Pearce; Kriti Verma; Nicola Logan; Grace Tyson; Eliska Spalkova; Sandra Margielewska-Davies; Graham S. Taylor; Eleni Syrimi; Frances Baawuah; Joanne Beckmann; Ifeanyichukwu Okike; Shazaad Ahmad; Joanna Garstang; Andrew Brent; Bernadette Brent; Georgina Ireland; Felicity Aiano; Zahin Amin-Chowdhury; Samuel Jones; Ray Borrow; Ezra Linley; Rafaq Azad; John Wright; Dagmar Waiblinger; Chris Davis; Emma C Thomson; Massimo Palmarini; Brian James Willett; Wendy S Barclay; John Poh; Vanessa Saliba; Gayatri Amirthalingam; Kevin Brown; Mary Ramsay; Jianmin Zuo; Paul Moss; Shamez Ladhani,"Institute of Immunology & Immunotherapy, Collage of Medical and Dental Sciences, University of Birmingham, Birmingham, B15 2TT, UK; Institute of Immunology & Immunotherapy, Collage of Medical and Dental Sciences, University of Birmingham, Birmingham, B15 2TT, UK; Institute of Immunology & Immunotherapy, Collage of Medical and Dental Sciences, University of Birmingham, Birmingham, B15 2TT, UK; Institute of Immunology & Immunotherapy, Collage of Medical and Dental Sciences, University of Birmingham, Birmingham, B15 2TT, UK; Institute of Immunology & Immunotherapy, Collage of Medical and Dental Sciences, University of Birmingham, Birmingham, B15 2TT, UK; Institute of Immunology & Immunotherapy, Collage of Medical and Dental Sciences, University of Birmingham, Birmingham, B15 2TT, UK; Institute of Immunology & Immunotherapy, Collage of Medical and Dental Sciences, University of Birmingham, Birmingham, B15 2TT, UK; University of Birmingham; Institute of Immunology & Immunotherapy, Collage of Medical and Dental Sciences, University of Birmingham, Birmingham, B15 2TT, UK; University of Birmingham; MRC-University of Glasgow Centre for Virus Research, 464 Bearsden Road, Glasgow G61-1QH, UK; MRC-University of Glasgow Centre for Virus Research, 464 Bearsden Road, Glasgow G61-1QH, UK; Institute of Immunology & Immunotherapy, Collage of Medical and Dental Sciences, University of Birmingham, Birmingham, B15 2TT, UK; Institute of Immunology & Immunotherapy, Collage of Medical and Dental Sciences, University of Birmingham, Birmingham, B15 2TT, UK; Institute of Immunology & Immunotherapy, Collage of Medical and Dental Sciences, University of Birmingham, Birmingham, B15 2TT, UK; Institute of Immunology & Immunotherapy, Collage of Medical and Dental Sciences, University of Birmingham, Birmingham, B15 2TT, UK; Public Health England, 61 Colindale Avenue, London NW9 5EQ, UK; East London NHS Foundation Trust, 9 Allie Street, London E1 8DE, UK; Public Health England, 61 Colindale Avenue, London NW9 5EQ, UK 4. University Hospitals of Derby and Burton NHS Foundation Trust, Uttoxeter New Road, Derby; Manchester University NHS Foundation Trust, Oxford Road, Manchester M13 9WL, UK; Birmingham Community Healthcare NHS Trust, Holt Street, Aston B7 4BN, UK; Oxford University Hospitals NHS Foundation Trust, Old Road, Oxford OX3 7HE University of Oxford, Wellington Square, Oxford OX1 2JD, UK; Oxford University Hospitals NHS Foundation Trust, Old Road, Oxford OX3 7HE; Public Health England, 61 Colindale Avenue, London NW9 5EQ, UK; Public Health England, 61 Colindale Avenue, London NW9 5EQ, UK; Public Health England, 61 Colindale Avenue, London NW9 5EQ, UK; Public Health England, 61 Colindale Avenue, London NW9 5EQ, UK; Public Health England, Manchester Royal Infirmary, Manchester, United Kingdom; Public Health England, Manchester Royal Infirmary, Manchester, United Kingdom; Bradford Teaching Hospitals NHS Foundation Trust; Bradford Teaching Hospitals NHS Foundation Trust; Bradford Teaching Hospitals NHS Foundation Trust; University of Glasgow; University of Glasgow; University of Glasgow; University of Glasgow; Imperial College, London; Public Health England, 61 Colindale Avenue, London NW9 5EQ, UK; Public Health England, 61 Colindale Avenue, London NW9 5EQ, UK; Public Health England, 61 Colindale Avenue, London NW9 5EQ, UK; Public Health England, 61 Colindale Avenue, London NW9 5EQ, UK; Public Health England, 61 Colindale Avenue, London NW9 5EQ, UK; Institute of Immunology & Immunotherapy, Collage of Medical and Dental Sciences, University of Birmingham, Birmingham, B15 2TT, UK; Institute of Immunology & Immunotherapy, Collage of Medical and Dental Sciences, University of Birmingham, Birmingham, B15 2TT, UK; Public Health England, 61 Colindale Avenue, London NW9 5EQ, UK","SARS-CoV-2 infection is generally mild or asymptomatic in children but the biological basis for this is unclear. We studied the profile of antibody and cellular immunity in children aged 3-11 years in comparison with adults. Antibody responses against spike and receptor binding domain (RBD) were high in children and seroconversion boosted antibody responses against seasonal Beta-coronaviruses through cross-recognition of the S2 domain. Seroneutralisation assays against alpha, beta and delta SARS-CoV-2 variants demonstrated comparable neutralising activity between children and adults. T cell responses against spike were >2-fold higher in children compared to adults and displayed a TH1 cytokine profile. SARS-CoV-2 spike-specific T cells were also detected in many seronegative children, revealing pre-existing responses that were cross-reactive with seasonal Alpha and Beta-coronaviruses. Importantly, all children retained high antibody titres and cellular responses at 6 months after infection whilst relative antibody waning was seen in adults. Spike-specific responses in children also remained broadly stable beyond 12 months. Children thus distinctly generate robust, cross-reactive and sustained immune responses after SARS-CoV-2 infection with focussed specificity against spike protein. These observations demonstrate novel features of SARS-CoV-2-specific immune responses in children and may provide insight into their relative clinical protection. Furthermore, this information will help to guide the introduction of vaccination regimens in the paediatric population.",allergy and immunology,fuzzy,100,100 medRxiv,10.1101/2021.04.08.21255100,2021-04-15,https://medrxiv.org/cgi/content/short/2021.04.08.21255100,REACT-1 round 10 report: Level prevalence of SARS-CoV-2 swab-positivity in England during third national lockdown in March 2021,Steven Riley; Oliver Eales; David Haw; Caroline E. Walters; Haowei Wang; Kylie E. C. Ainslie; Christina Atchinson; Claudio Fronterre; Peter J. Diggle; Deborah Ashby; Christl A Donnelly; Graham Cooke; Wendy Barclay; Helen Ward; Ara Darzi; Paul Elliott,"School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; School of Public Health, Imperial College London, UK; CHICAS, Lancaster Medical School, Lancaster University, UK and Health Data Research, UK; CHICAS, Lancaster Medical School, Lancaster University, UK and Health Data Research, UK; School of Public Health, Imperial College London, UK; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; Department of Infectious Disease, Imperial College London, UK Imperial College Healthcare NHS Trust, UK National Institute for Health Research Imperial Biomedic; Department of Infectious Disease, Imperial College London, UK; School of Public Health, Imperial College London, UK Imperial College Healthcare NHS Trust, UK National Institute for Health Research Imperial Biomedical Resear; Imperial College Healthcare NHS Trust, UK National Institute for Health Research Imperial Biomedical Research Centre, UK Institute of Global Health Innovation a; School of Public Health, Imperial College London, UK Imperial College Healthcare NHS Trust, UK National Institute for Health Research Imperial Biomedical Resear","BackgroundIn England, hospitalisations and deaths due to SARS-CoV-2 have been falling consistently since January 2021 during the third national lockdown of the COVID-19 pandemic. The first significant relaxation of that lockdown occurred on 8 March when schools reopened. @@ -3214,15 +3154,6 @@ ResultsThirty-three papers met the inclusion criteria, only three of which were ConclusionsThe limited evidence suggests that health certification in relation to COVID-19 - outside of the context of international travel - has the potential for harm as well as benefit. Realising the benefits while minimising the harms will require real-time evaluations allowing modifications to maximise the potential contribution of certification to enable safer access to a range of activities.",public and global health,fuzzy,100,100 medRxiv,10.1101/2021.04.07.21254497,2021-04-09,https://medrxiv.org/cgi/content/short/2021.04.07.21254497,Characterising contact in disease outbreaks via a network model of spatial-temporal proximity,Ashleigh C Myall; Robert L Peach; Yu Wan; Siddharth Mookerjee; Elita Jauneikaite; Frankie Bolt; James Richard Price; Frances Davies; Andrea Yeong Wiesse; Alison Holmes; Mauricio Barahona,Imperial College London; Imperial College London; Imperial College London; Imperial College NHS Trust; Imperial College London; Imperial College London; Imperial College London; Imperial College NHS Trust; University of Edinburgh; Imperial College London; Imperial College London,"Contact tracing is a key tool in epidemiology to identify and control outbreaks of infectious diseases. Existing contact tracing methodologies produce contact maps of individuals based on a binary definition of contact which can be hampered by missing data and indirect contacts. Here, we present a Spatial-temporal Epidemiological Proximity (StEP) model to recover contact maps in disease outbreaks based on movement data. The StEP model accounts for imperfect data by considering probabilistic contacts between individuals based on spatial-temporal proximity of their movement trajectories, creating a robust movement network despite possible missing data and unseen transmission routes. Using real-world data we showcase the potential of StEP for contact tracing with outbreaks of multidrug-resistant bacteria and COVID-19 in a large hospital group in London, UK. In addition to the core structure of contacts that can be recovered using traditional methods of contact tracing, the StEP model reveals missing contacts that connect seemingly separate outbreaks. Comparison with genomic data further confirmed that these recovered contacts indeed improve characterisation of disease transmission and so highlights how the StEP framework can inform effective strategies of infection control and prevention.",epidemiology,fuzzy,100,100 -medRxiv,10.1101/2021.04.01.21254765,2021-04-07,https://medrxiv.org/cgi/content/short/2021.04.01.21254765,"Mental health inequalities in healthcare, economic, and housing disruption during COVID -19: an investigation in 12 longitudinal studies",Giorgio Di Gessa; Jane Maddock; Michael J Green; Ellen J Thompson; Eoin McElroy; Helena L Davies; Jessica Mundy; Anna J Stevenson; Alex S.F Kwong; Gareth J Griffith; Srinivasa Vittal Katikireddi; Claire L Niedzwiedz; George B Ploubidis; Emla Fitzsimons; Morag Henderson; Richard J. Silverwood; Nishi Chaturvedi; Gerome Breen; Claire J Steves; Andrew Steptoe; David J Porteous; Praveetha Patalay,"Institute of Epidemiology and Health Care, University College London; MRC Unit for Lifelong Health and Ageing, University College London; MRC/CSO Social & Public Health Sciences Unit, University of Glasgow; Department of Twin Research and Genetic Epidemiology, School of Life Course Sciences, Kings College London; Department of Neuroscience, Psychology and Behaviour, University of Leicester; Social, Genetic & Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, Kings College London; Social, Genetic & Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, Kings College London; Centre for Genomic and Experimental Medicine, University of Edinburgh; Division of Psychiatry, University of Edinburgh and MRC Integrative Epidemiology Unit, University of Bristol; MRC Integrative Epidemiology Unit, University of Bristol; MRC/CSO Social & Public Health Sciences Unit, University of Glasgow; Institute of Health & Wellbeing, University of Glasgow; Centre for Longitudinal Studies, UCL Social Research Institute, University College London; Centre for Longitudinal Studies, UCL Social Research Institute, University College London; Centre for Longitudinal Studies, UCL Social Research Institute, University College London; Centre for Longitudinal Studies, UCL Social Research Institute, University College London; MRC Unit for Lifelong Health and Ageing, University College London; Social, Genetic & Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, Kings College London and Maudsley Biomedical Research Cen; Department of Twin Research and Genetic Epidemiology, School of Life Course Sciences, Kings College London; Institute of Epidemiology and Health Care, University College London; Centre for Genomic and Experimental Medicine, University of Edinburgh; Centre for Longitudinal Studies and MRC Unit for Lifelong Health and Ageing, University College London","BackgroundThe COVID-19 pandemic and associated virus suppression measures have disrupted lives and livelihoods and people already experiencing mental ill-health may have been especially vulnerable. - -AimTo quantify mental health inequalities in disruptions to healthcare, economic activity and housing. - -Method59,482 participants in 12 UK longitudinal adult population studies with data collected prior to and during the COVID-19 pandemic. Within each study we estimated the association between psychological distress assessed pre-pandemic and disruptions since the start of the pandemic to three domains: healthcare (medication access, procedures, or appointments); economic activity (employment, income, or working hours); and housing (change of address or household composition). Meta-analyses were used to pool estimates across studies. - -ResultsAcross the analysed datasets, one to two-thirds of participants experienced at least one disruption, with 2.3-33.2% experiencing disruptions in two or more domains. One standard deviation higher pre-pandemic psychological distress was associated with: (i) increased odds of any healthcare disruptions (OR=1.30; [95% CI:1.20-1.40]) with fully adjusted ORs ranging from 1.24 [1.09-1.41] for disruption to procedures and 1.33 [1.20- 1.49] for disruptions to prescriptions or medication access; (ii) loss of employment (OR=1.13 [1.06-1.21]) and income (OR=1.12 [1.06 -1.19]) and reductions in working hours/furlough (OR=1.05 [1.00-1.09]); (iii) no associations with housing disruptions (OR=1.00 [0.97-1.03]); and (iv) increased likelihood of experiencing a disruption in at least two domains (OR=1.25 [1.18-1.32]) or in one domain (OR=1.11 [1.07-1.16]) relative to no disruption. - -ConclusionPeople experiencing psychological distress pre-pandemic have been more likely to experience healthcare and economic disruptions, and clusters of disruptions across multiple domains during the pandemic. Failing to address these disruptions risks further widening the existing inequalities in mental health.",psychiatry and clinical psychology,fuzzy,100,100 medRxiv,10.1101/2021.04.01.21254789,2021-04-07,https://medrxiv.org/cgi/content/short/2021.04.01.21254789,Mendelian randomisation identifies alternative splicing of the FAS death receptor as a mediator of severe COVID-19,Lucija Klaric; Jack S Gisby; Artemis Papadaki; Marisa D Muckian; Erin Macdonald-Dunlop; Jing Hua Zhao; Alex Tokolyi; Elodie Persyn; Erola Pairo-Castineira; Andrew P Morris; Anette Kalnapenkis; Anne Richmond; Arianna Landini; Ã…sa K Hedman; Bram Prins; Daniela Zanetti; Eleanor Wheeler; Charles Kooperberg; Chen Yao; John R Petrie; Jingyuan Fu; Lasse Folkersen; Mark Walker; Martin Magnusson; Niclas Eriksson; Niklas Mattsson-Carlgren; Paul RHJ Timmers; Shih-Jen Hwang; Stefan Enroth; Stefan Gustafsson; Urmo Vosa; Yan Chen; Agneta Siegbahn; Alexander Reiner; Ã…sa Johansson; Barbara Thorand; Bruna Gigante; Caroline Hayward; Christian Herder; Christian Gieger; Claudia Langenberg; Daniel Levy; Daria V Zhernakova; J Gustav Smith; Harry Campbell; Johan Sundstrom; John Danesh; Karl Michaëlsson; Karsten Suhre; Lars Lind; Lars Wallentin; Leonid Padyukov; Mikael Landén; Nicholas J Wareham; Andreas Göteson; Oskar Hansson; Per Eriksson; Rona J Strawbridge; Themistocles L Assimes; Tõnu Esko; Ulf Gyllensten; J Kenneth Baillie; Dirk S Paul; Peter K Joshi; Adam S Butterworth; Anders Mälarstig; Nicola Pirastu; James F Wilson; James E Peters,"MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh, United Kingdom; Department of Immunology and Inflammation, Faculty of Medicine, Imperial College London, London, United Kingdom; Department of Immunology and Inflammation, Faculty of Medicine, Imperial College London, London, United Kingdom; Centre for Global Health Research, Usher Institute, University of Edinburgh, Teviot Place, Edinburgh, United Kingdom; Centre for Global Health Research, Usher Institute, University of Edinburgh, Teviot Place, Edinburgh, United Kingdom; British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom; Department of Human Genetics, Wellcome Sanger Institute, Hinxton, UK; British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK; Roslin Institute, University of Edinburgh, Easter Bush, Edinburgh, EH25 9RG, UK; Centre for Genetics and Genomics Versus Arthritis, Centre for Musculoskeletal Research, The University of Manchester, Manchester, UK; Institute of Genomics, University of Tartu, Tartu, Estonia; MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh, United Kingdom; Centre for Global Health Research, Usher Institute, University of Edinburgh, Teviot Place, Edinburgh, United Kingdom; Department of Medicine, Karolinska Institute, Stockholm, Sweden; British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom; Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA; MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK; Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA; Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA; Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK; University of Groningen, University Medical Center Groningen, Department of Genetics, Groningen, the Netherlands; Danish National Genome Center, Copenhagen, Denmark.; Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, UK; Department of Clinical Sciences, Lund University, Malmö, Sweden; Uppsala Clinical Research Center (UCR), Uppsala University, Uppsala, Sweden; Clinical Memory Research Unit, Faculty of Medicine, Lund University, Lund, Sweden; MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh, United Kingdom; Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA; Department of Immunology, Genetics and Pathology, Uppsala University, Sweden; Department of Medical Sciences, Uppsala University, Uppsala, Sweden; Institute of Genomics, University of Tartu, Tartu, Estonia; Department of Medicine Solna, Karolinska Institutet; Department of Medical Sciences, Uppsala University, Uppsala, Sweden; Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA; Department of Immunology, Genetics and Pathology, Uppsala University, Sweden; Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, München-Neuherberg, Germany; Division of Cardiovascular Medicine, Dept of Medicine, Karolinska Institutet, Stockholm, Sweden; MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh, United Kingdom; Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany; Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, München-Neuherberg, Germany; MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK; Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA; University of Groningen, University Medical Center Groningen, Department of Genetics, Groningen, the Netherlands; Department of Cardiology, Clinical Sciences, Lund University and SkÃ¥ne University Hospital, Lund, Sweden; Centre for Global Health Research, Usher Institute, University of Edinburgh, Teviot Place, Edinburgh, United Kingdom; Department of Medical Sciences, Uppsala University, Uppsala, Sweden; British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom; Department of Surgcial Sciences, Unit of Medical Epidemiology, Uppsala University, Uppsala, Sweden; Department of Physiology and Biophysics, Weill Cornell Medicine-Qatar, Doha, Qatar; Department of Medical Sciences, Uppsala University, Uppsala, Sweden; Department of Medical Sciences and Uppsala Clinical Research Center, Uppsala University, Uppsala, Sweden; Division of Rheumatology, Department of Medicine Solna, Karolinska Institutet and Karolinska University Hospital, Stockholm, Sweden; Institute of Neuroscience and Physiology, University of Gothenburg, Gothenburg, Sweden; MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK; Institute of Neuroscience and Physiology, University of Gothenburg, Gothenburg, Sweden; Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Lund, Sweden; Division of Cardiovascular Medicine, Department of Medicine Solna, Karolinska Institutet, Stockholm, Sweden; Institute of Health and Wellbeing, College of Medicine, Veterinary and Life Sciences, University of Glasgow, UK; Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA; Institute of Genomics, University of Tartu, Tartu, Estonia; Department of Immunology, Genetics and Pathology, Uppsala University, Sweden; Roslin Institute, University of Edinburgh, Easter Bush, Edinburgh, EH25 9RG, UK; British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK; Centre for Global Health Research, Usher Institute, University of Edinburgh, Teviot Place, Edinburgh, United Kingdom; British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom; Karolinska Institute, Stockholm, Sweden; Centre for Global Health Research, Usher Institute, University of Edinburgh, Teviot Place, Edinburgh, United Kingdom; Centre for Global Health Research, Usher Institute, University of Edinburgh, Teviot Place, Edinburgh, United Kingdom; Department of Immunology and Inflammation, Faculty of Medicine, Imperial College London, London, UK","Severe COVID-19 is characterised by immunopathology and epithelial injury. Proteomic studies have identified circulating proteins that are biomarkers of severe COVID-19, but cannot distinguish correlation from causation. To address this, we performed Mendelian randomisation (MR) to identify proteins that mediate severe COVID-19. Using protein quantitative trait loci (pQTL) data from the SCALLOP consortium, involving meta-analysis of up to 26,494 individuals, and COVID-19 genome-wide association data from the Host Genetics Initiative, we performed MR for 157 COVID-19 severity protein biomarkers. We identified significant MR results for five proteins: FAS, TNFRSF10A, CCL2, EPHB4 and LGALS9. Further evaluation of these candidates using sensitivity analyses and colocalization testing provided strong evidence to implicate the apoptosis-associated cytokine receptor FAS as a causal mediator of severe COVID-19. This effect was specific to severe disease. Using RNA-seq data from 4,778 individuals, we demonstrate that the pQTL at the FAS locus results from genetically influenced alternate splicing causing skipping of exon 6. We show that the risk allele for very severe COVID-19 increases the proportion of transcripts lacking exon 6, and thereby increases soluble FAS. Soluble FAS acts as a decoy receptor for FAS-ligand, inhibiting apoptosis induced through membrane-bound FAS. In summary, we demonstrate a novel genetic mechanism that contributes to risk of severe of COVID-19, highlighting a pathway that may be a promising therapeutic target.",infectious diseases,fuzzy,100,100 medRxiv,10.1101/2021.03.31.21254687,2021-04-05,https://medrxiv.org/cgi/content/short/2021.03.31.21254687,"SARS-CoV-2 infectivity by viral load, S gene variants and demographic factors and the utility of lateral flow devices to prevent transmission",Lennard YW Lee; Stefan Rozmanowski; Matthew Pang; Andre Charlett; Charlotte Anderson; Gareth J Hughes; Matthew Barnard; Leon Peto; Richard Vipond; Alex Sienkiewicz; Susan Hopkins; John Bell; Derrick W Crook; Nick Gent; A Sarah Walker; Tim EA Peto; David W Eyre,University of Oxford; UK Government Department of Health and Social Care; UK Government Department of Health and Social Care; Public Health England; Public Health England; Public Health England; UK Government Department of Health and Social Care; University of Oxford; Public Health England; Public Health England; Public Health England; University of Oxford; University of Oxford; Public Health England; University of Oxford; University of Oxford; University of Oxford,"BackgroundHow SARS-CoV-2 infectivity varies with viral load is incompletely understood. Whether rapid point-of-care antigen lateral flow devices (LFDs) detect most potential transmission sources despite imperfect sensitivity is unknown. @@ -3319,13 +3250,6 @@ ResultsWe observed a small proportion of care home residents with positive PCR t ConclusionsIncreased risk of infection after 21-days was associated with frailty. We found most infections occurred within 28-days of vaccination, suggesting extra precautions to reduce transmission risk should be taken in this time frame.",geriatric medicine,fuzzy,100,100 medRxiv,10.1101/2021.03.16.21253371,2021-03-24,https://medrxiv.org/cgi/content/short/2021.03.16.21253371,Axes of Prognosis: Identifying Subtypes of COVID-19 Outcomes,Emma Whitfield; Claire Coffey; Huayu Zhang; Ting Shi; Xiaodong Wu; Qiang Li; Honghan Wu,"Institute of Health Informatics, UCL, London, United Kingdom; University of Cambridge, Cambridge, United Kingdom; Usher Institute, University of Edinburgh, United Kingdom; Usher Institute, University of Edinburgh, United Kingdom; Shanghai East Hospital, Tongji University, Shanghai, China; Shanghai East Hospital, Tongji University, Shanghai, China; Institute of Health Informatics, UCL, London, United Kingdom","COVID-19 is a disease with vast impact, yet much remains unclear about patient outcomes. Most approaches to risk prediction of COVID-19 focus on binary or tertiary severity outcomes, despite the heterogeneity of the disease. In this work, we identify heterogeneous subtypes of COVID-19 outcomes by considering axes of prognosis. We propose two innovative clustering approaches - Layered Axes and Prognosis Space - to apply on patients outcome data. We then show how these clusters can help predict a patients deterioration pathway on their hospital admission, using random forest classification. We illustrate this methodology on a cohort from Wuhan in early 2020. We discover interesting subgroups of poor prognosis, particularly within respiratory patients, and predict respiratory subgroup membership with high accuracy. This work could assist clinicians in identifying appropriate treatments at patients hospital admission. Moreover, our method could be used to explore subtypes of long COVID and other diseases with heterogeneous outcomes.",health informatics,fuzzy,100,92 -medRxiv,10.1101/2021.03.16.21253377,2021-03-24,https://medrxiv.org/cgi/content/short/2021.03.16.21253377,First and second SARS-CoV-2 waves in inner London: A comparison of admission characteristics and the effects of the B.1.1.7 variant,Luke B Snell; Wenjuan Wang; Adela Alcolea-Medina; Themoula Charalampous; Gaia Nebbia; Rahul Batra; Leonardo de Jongh; Finola Higgins; Yanzhong Wang; Jonathan D Edgeworth; Vasa Curcin,"King's College London; School of Population Health and Environmental Sciences, King's College London, London, UK; Viapath, London, UK; Centre for Clinical Infection and Diagnostics Research, School of Immunology and Microbial Sciences, King's College London, London, UK; Centre for Clinical Infection and Diagnostics Research, School of Immunology and Microbial Sciences, King's College London, London, UK; Centre for Clinical Infection and Diagnostics Research, School of Immunology and Microbial Sciences, King's College London, London, UK; NIHR Biomedical Research Centre, Guy's and St Thomas' NHS Foundation Trust; NIHR Biomedical Research Centre, Guy's and St Thomas' NHS Foundation Trust; School of Population Health and Environmental Sciences, King's College London, London, UK; Centre for Clinical Infection and Diagnostics Research, School of Immunology and Microbial Sciences, King's College London, London, UK; School of Population Health and Environmental Sciences, King's College London, London, UK","IntroductionA second wave of SARS-CoV-2 infection spread across the UK in 2020 linked with emergence of the more transmissible B.1.1.7 variant. The emergence of new variants, particularly during relaxation of social distancing policies and implementation of mass vaccination, highlights the need for real-time integration of detailed patient clinical data alongside pathogen genomic data. We linked clinical data with viral genome sequence data to compare cases admitted during the first and second waves of SARS-CoV-2 infection. - -MethodsClinical, laboratory and demographic data from five electronic health record (EHR) systems was collected for all cases with a positive SARS-CoV-2 RNA test between March 13th 2020 and February 17th 2021. SARS-CoV-2 viral sequencing was performed using Oxford Nanopore Technology. Descriptive data are presented comparing cases between waves, and between cases of B.1.1.7 and non-B.1.1.7 variants. - -ResultsThere were 5810 SARS-CoV-2 RNA positive cases comprising inpatients (n=2341), healthcare workers (n=1549), outpatients (n=874), emergency department (ED) attenders not subsequently admitted (n=532), inter-hospital transfers (n=281) and nosocomial cases (n=233). There were two dominant waves of hospital admissions, with wave one starting from March 13th (n=838) and wave two from October 20th (n=1503), both with a temporally aligned rise in nosocomial cases (n=96 in wave one, n=137 in wave two). 1470 SARS-CoV-2 isolates were successfully sequenced, including 216/838 (26%) admitted cases from wave one, 472/1503 (31%) admitted cases in wave two and 121/233 (52%) nosocomial cases. The first B.1.1.7 variant was identified on 15th November 2020 and increased rapidly such that it comprised 400/472 (85%) of sequenced isolates from admitted cases in wave two. Females made up a larger proportion of admitted cases in wave two (47.3% vs 41.8%, p=0.011), and in those infected with the B.1.1.7 variant compared to non-B.1.1.7 variants (48.0% vs 41.8%, p=0.042). A diagnosis of frailty was less common in wave two (11.5% v 22.8%, p<0.001) and in the group infected with B.1.1.7 (14.5% v 22.4%, p=0.001). There was no difference in severity on admission between waves, as measured by hypoxia at admission (wave one: 64.3% vs wave two: 65.5%, p=0.67). However, a higher proportion of cases infected with the B.1.1.7 variant were hypoxic on admission compared to other variants (70.0% vs 62.5%, p=0.029). - -ConclusionsAutomated EHR data extraction linked with SARS-CoV-2 genome sequence data provides valuable insight into the evolving characteristics of cases admitted to hospital with COVID-19. The proportion of cases with hypoxia on admission was greater in those infected with the B.1.1.7 variant, which supports evidence the B.1.1.7 variant is associated with more severe disease. The number of nosocomial cases was similar in both waves despite introduction of many infection control interventions before wave two, an observation requiring further investigation.",infectious diseases,fuzzy,100,100 medRxiv,10.1101/2021.03.15.21253542,2021-03-24,https://medrxiv.org/cgi/content/short/2021.03.15.21253542,Comparison between one and two dose SARS-CoV-2 vaccine prioritisation for a fixed number of vaccine doses,Edward M Hill; Matt J Keeling,University of Warwick; University of Warwick,"The swift development of SARS-CoV-2 vaccines has been met with worldwide commendation. How-ever, in the context of an ongoing pandemic there is an interplay between infection and vaccination. Whilst infection can grow exponentially, vaccination rates are generally limited by supply and logistics. With the first SARS-CoV-2 vaccines receiving medical approval requiring two doses, there has been scrutiny on the spacing between doses; an elongated period between doses allows more of the population to receive a first vaccine dose in the short-term generating wide-spread partial immunity. Focusing on data from England, we investigated prioritisation of a one dose or two dose vaccination schedule given a fixed number of vaccine doses and with respect to a measure of maximising averted deaths. We optimised outcomes for two different estimates of population size and relative risk of mortality for at-risk groups within the Phase 1 vaccine priority order. Vaccines offering relatively high protection from the first dose favour strategies that prioritise giving more people one dose, although with increasing vaccine supply eventually those eligible and accepting vaccination will receive two doses. Whilst optimal dose timing can substantially reduce the overall mortality risk, there needs to be careful consideration of the logistics of vaccine delivery.",infectious diseases,fuzzy,100,100 medRxiv,10.1101/2021.03.18.21253888,2021-03-23,https://medrxiv.org/cgi/content/short/2021.03.18.21253888,"Long Covid in adults discharged from UK hospitals after Covid-19: A prospective, multicentre cohort study using the ISARIC WHO Clinical Characterisation Protocol.",Louise Sigfrid; Tom M Drake; Ellen Pauley; Edwin C Jesudason; Piero Olliaro; Wei Shen Lim; Annelise Gillesen; Colin Berry; David Lowe; Joanne McPeake; Nazir Lone; Muge Cevik; Daniel Munblit; Anna Casey; Peter Bannister; Clark D Russell; Lynsey Goodwin; Antonia Ho; Lance Turtle; Margret E O'Hara; Claire Hastie; Chloe Donohue; Rebecca Spencer; Cara Donegan; Alison Gummery; Janet Harrison; Hayley Hardwick; Claire E Hastie; Gail Carson; Laura Merson; John Kenneth Baillie; Peter Openshaw; Ewen M Harrison; Annemarie Docherty; Malcolm G Semple; Janet T Scott,"ISARIC Global Support Centre, Centre for Tropical Medicine and Global Health, University of Oxford, Oxford, UK; Centre for Medical Informatics, University of Edinburgh, Edinburgh, UK; University of Edinburgh Medical School, Edinburgh, UK.; NHS Lothian, Edinburgh, UK,; ISARIC Global Support Centre, Centre for Tropical Medicine and Global Health, University of Oxford, Oxford, UK.; Department of Respiratory Medicine, Nottingham University Hospitals NHS Trust, Nottingham, UK.; ISARIC Global Support Centre, Centre for Tropical Medicine and Global Health, University of Oxford, Oxford, UK.; Institute of Cardiovascular and Medical Sciences, University of Glasgow, UK; NHS Greater Glasgow and Clyde, Emergency Department, Glasgow, UK; School of Medicine, Dentistry and Nursing, University of Glasgow, UK; Usher Institute, University of Edinburgh, Edinburgh, UK; University of St Andrews; Sechenov First Moscow State Medical University, Imperial College London, Imperial College London, RSMU; Medical Student, Brighton and Sussex Medical School, UK; Brighton & Sussex Medical School, Brighton, UK; Centre for Inflammation Research, University of Edinburgh, UK; Institute of Infection, Veterinary and Ecological Studies, Univeristy of Liverpool. Tropical and Infectious Diseases Unit, North Manchester General Hospital, De; University of Glasgow, Glasgow, UK; NIHR Health Protection Research Unit in emerging and zoonotic infections, Institute of Infection, Veterinary and Ecological Sciences, University of Liverpool, L; Long COVID Support, Birmingham, UK; Long COVID Support, Birmingham, UK; Liverpool Clinical Trials Centre, University of Liverpool, Liverpool, UK; Institute of Infection, Veterinary and Ecological Sciences (IVES), University of Liverpool, Liverpool, UK.; Institute of Infection, Veterinary and Ecological Sciences (IVES), University of Liverpool, Liverpool, UK.; Institute of Infection, Veterinary and Ecological Sciences (IVES), University of Liverpool, Liverpool, UK.; National Institute of Health Research (NIHR) Health Protection research Unit in Emerging and Zoonotic Infections, Liverpool, UK. 2. Institute of Infection and G; National Institute of Health Research (NIHR) Health Protection research Unit in Emerging and Zoonotic Infections, Liverpool, UK. 2. Institute of Infection and G; Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK.; ISARIC Global Support Centre, Centre for Tropical Medicine and Global Health, University of Oxford, Oxford, UK.; ISARIC Global Support Centre, Centre for Tropical Medicine and Global Health, University of Oxford, Oxford, UK; Roslin Institute, University of Edinburgh, Edinburgh, UK; National Heart and Lung Institute, Imperial College, London UK.; Director Centre for Medical Informatics, Usher Institute, University of Edinburgh, Edinburgh, UK.; Centre for Medical Informatics, Usher Institute, University of Edinburgh, Edinburgh, UK. 2. Intensive Care Unit, Royal Infirmary Edinburgh, Edinburgh, UK; Health Protection Research Unit In Emerging and Zoonotic Infections, Institute of Infection, Veterinary and Ecological Sciences, University of Liverpool, UK 2. ; MRC-University of Glasgow Center for Virus research","Structured AbstractO_ST_ABSObjectivesC_ST_ABSThe long-term consequences of severe Covid-19 requiring hospital admission are not well characterised. The objective of this study was to establish the long-term effects of Covid-19 following hospitalisation and the impact these may have on patient reported outcome measures. @@ -3359,21 +3283,7 @@ FindingsOf 6,775 participants in UKB who had tested positive for infection with InterpretationShorter LTL, indicative of older biological age, is associated with higher risk of adverse COVID-19 outcomes, independent of several major risk factors for COVID-19 including chronological age. Further data are needed to determine whether this association reflects causality. FundingUK Medical Research Council, Biotechnology and Biological Sciences Research Council and British Heart Foundation.",infectious diseases,fuzzy,100,100 -medRxiv,10.1101/2021.03.11.21253275,2021-03-21,https://medrxiv.org/cgi/content/short/2021.03.11.21253275,Effect of vaccination on transmission of COVID-19: an observational study in healthcare workers and their households,Anoop Shah; Ciara Gribben; Jennifer Bishop; Peter Hanlon; David Caldwell; Rachael Wood; Martin Reid; Jim McMenamin; David Goldberg; Diane Stockton; Sharon Hutchinson; Chris Robertson; Paul M McKeigue; Helen M Colhoun; David McAllister,London School of Hygiene and Tropical Medicine; Public Health Scotland; Public Health Scotland; University of Glasgow; Public Health Scotland; PublicHealth Scotland; Public Health Scotland; Public Health Scotland; Public Health Scotland; Public Health Scotland; Public Health Scotland; Public Health Scotland; Public Health Scotland; Public Health Scotland; University of Glasgow,"BackgroundThe effect of vaccination for COVID-19 on onward transmission is unknown. - -MethodsA national record linkage study determined documented COVID-19 cases and hospitalisations in unvaccinated household members of vaccinated and unvaccinated healthcare workers from 8th December 2020 to 3rd March 2021. The primary endpoint was COVID-19 14 days following the first dose. - -ResultsThe cohort comprised of 194,362 household members (mean age 31{middle dot}1 {+/-} 20{middle dot}9 years) and 144,525 healthcare workers (mean age 44{middle dot}4 {+/-} 11{middle dot}4 years). 113,253 (78{middle dot}3%) of healthcare workers received at least one dose of the BNT162b2 mRNA or ChAdOx1 nCoV-19 vaccine and 36,227 (25{middle dot}1%) received a second dose. There were 3,123 and 4,343 documented COVID-19 cases and 175 and 177 COVID-19 hospitalisations in household members of healthcare workers and healthcare workers respectively. Household members of vaccinated healthcare workers had a lower risk of COVID-19 case compared to household members of unvaccinated healthcare worker (rate per 100 person-years 9{middle dot}40 versus 5{middle dot}93; HR 0{middle dot}70, 95% confidence interval [CI] 0{middle dot}63 to 0{middle dot}78). The effect size for COVID-19 hospitalisation was similar, with the confidence interval crossing the null (HR 0{middle dot}77 [95% CI 0{middle dot}53 to 1{middle dot}10]). The rate per 100 person years was lower in vaccinated compared to unvaccinated healthcare workers for documented (20{middle dot}13 versus 8{middle dot}51; HR 0{middle dot}45 [95% CI 0{middle dot}42 to 0{middle dot}49]) and hospitalized COVID-19 (0{middle dot}97 versus 0{middle dot}14; HR 0{middle dot}16 [95% CI 0{middle dot}09 to 0{middle dot}27]). Compared to the period before the first dose, the risk of documented COVID-19 case was lower at [≥] 14 days after the second dose for household members (HR 0{middle dot}46 [95% CI 0{middle dot}30to 0{middle dot}70]) and healthcare workers (HR 0{middle dot}08 [95% CI 0{middle dot}04 to 0{middle dot}17]). - -InterpretationVaccination of health care workers was associated with a substantial reduction in COVID-19 cases in household contacts consistent with an effect of vaccination on transmission.",public and global health,fuzzy,100,100 medRxiv,10.1101/2021.03.17.21253853,2021-03-20,https://medrxiv.org/cgi/content/short/2021.03.17.21253853,"Modelling the impact of rapid tests, tracing and distancing in lower-income countries suggest optimal policies varies with rural-urban settings",Xilin Jiang; Wenfeng Gong; Zlatina Dobreva; Ya Gao; Matthew Quaife; Christophe Fraser; Chris Holmes,"University of Oxford; Bill & Melinda Gates Foundation; Faculty of Public Health and Policy, London School of Hygiene and Tropical Medicine, London, UK; Department of International Health, Johns Hopkins University; Faculty of Public Health and Policy, London School of Hygiene and Tropical Medicine, London, UK; University of Oxford; University of Oxford","Low- and middle-income countries (LMICs) remain of high potential for hotspots for COVID-19 deaths and emerging variants given the inequality of vaccine distribution and their vulnerable healthcare systems. We aim to evaluate containment strategies that are sustainable and effective for LMICs. We constructed synthetic populations with varying contact and household structures to capture LMIC demographic characteristics that vary across communities. Using an agent- based model, we explored the optimal containment strategies for rural and urban communities by designing and simulating setting-specific strategies that deploy rapid diagnostic tests, symptom screening, contact tracing and physical distancing. In low-density rural communities, we found implementing either high quality (sensitivity > 50%) antigen rapid diagnostic tests or moderate physical distancing could contain the transmission. In urban communities, we demonstrated that both physical distancing and case finding are essential for containing COVID-19 (average infection rate < 10%). In high density communities that resemble slums and squatter settlements, physical distancing is less effective compared to rural and urban communities. Lastly, we demonstrated contact tracing is essential for effective containment. Our findings suggested that rapid diagnostic tests could be prioritised for control and monitor COVID-19 transmission and highlighted that contact survey data could guide strategy design to save resources for LMICs. An accompanying open source R package is available for simulating COVID-19 transmission based on contact network models.",epidemiology,fuzzy,100,100 -medRxiv,10.1101/2021.03.18.21253443,2021-03-20,https://medrxiv.org/cgi/content/short/2021.03.18.21253443,Intensity of COVID-19 in care homes following Hospital Discharge in the early stages of the UK epidemic,Joe Hollinghurst; Laura North; Chris Emmerson; Ashley Akbari; Fatemeh Torabi; Ronan A Lyons; Alan G Hawkes; Ed Bennett; Mike B Gravenor; Richard Fry,Swansea University; Swansea University; Public Health Wales; Swansea University; Swansea University; Swansea University; Swansea University; Swansea University; Swansea University; Swansea University,"BackgroundA defining feature of the COVID-19 pandemic in many countries was the tragic extent to which care home residents were affected, and the difficulty preventing introduction and subsequent spread of infection. Management of risk in care homes requires good evidence on the most important transmission pathways. One hypothesised route at the start of the pandemic, prior to widespread testing, was transfer of patients from hospitals, which were experiencing high levels of nosocomial events. - -MethodsWe tested the hypothesis that hospital discharge events increased the intensity of care home cases using a national individually linked health record cohort in Wales, UK. We monitored 186,772 hospital discharge events over the period March to July 2020, tracking individuals to 923 care homes and recording the daily case rate in the homes populated by 15,772 residents. We estimated the risk of an increase in cases rates following exposure to a hospital discharge using multi-level hierarchical logistic regression, and a novel stochastic Hawkes process outbreak model. - -FindingsIn regression analysis, after adjusting for care home size, we found no significant association between hospital discharge and subsequent increases in care home case numbers (odds ratio: 0.99, 95% CI 0.82, 1.90). Risk factors for increased cases included care home size, care home resident density, and provision of nursing care. Using our outbreak model, we found a significant effect of hospital discharge on the subsequent intensity of cases. However, the effect was small, and considerably less than the effect of care home size, suggesting the highest risk of introduction came from interaction with the community. We estimated approximately 1.8% of hospital discharged patients may have been infected. - -InterpretationThere is growing evidence in the UK that the risk of transfer of COVID-19 from the high-risk hospital setting to the high-risk care home setting during the early stages of the pandemic was relatively small. Although access to testing was limited to initial symptomatic cases in each care home at this time, our results suggest that reduced numbers of discharges, selection of patients, and action taken within care homes following transfer all may have contributed to mitigation. The precise key transmission routes from the community remain to be quantified.",health informatics,fuzzy,100,100 medRxiv,10.1101/2021.03.15.21253590,2021-03-17,https://medrxiv.org/cgi/content/short/2021.03.15.21253590,"An integrated analysis of contact tracing and genomics to assess the efficacy of travel restrictions on SARS-CoV-2 introduction and transmission in England from June to September, 2020",Dinesh Aggarwal; Andrew J Page; Ulf Schaefer; George M Savva; Richard Myers; Erik Volz; Nicholas Ellaby; Steven Platt; Natalie Groves; Eileen Gallaghar; Niamh M. Tumelty; Thanh Le-Viet; Gareth J. Hughes; Cong Chen; Charlie Turner; Sophie Logan; Abbie Harrison; - The COVID-19 Genomics UK (COG-UK) Consortium; Sharon J. Peacock; Meera Chand; Ewan M. Harrison,"University of Cambridge, Department of Medicine, Cambridge, UK; Quadram Institute Bioscience, Norwich Research Park, Norwich, NR4 7UQ, UK; Public Health England, 61 Colindale Ave, London, NW9 5EQ, UK; Quadram Institute Bioscience, Norwich Research Park, Norwich, NR4 7UQ, UK; Public Health England, 61 Colindale Ave, London, NW9 5EQ, UK; Imperial College London; Public Health England, 61 Colindale Ave, London, NW9 5EQ, UK; Public Health England, 61 Colindale Ave, London, NW9 5EQ, UK; Public Health England, 61 Colindale Ave, London, NW9 5EQ, UK; Public Health England, 61 Colindale Ave, London, NW9 5EQ, UK; University of Cambridge, Cambridge University Libraries, Cambridge, UK; Quadram Institute Bioscience, Norwich Research Park, Norwich, NR4 7UQ, UK; Public Health England National Infections Service, Field Service, Leeds, UK; Public Health England, 61 Colindale Ave, London, NW9 5EQ, UK; Public Health England, 61 Colindale Ave, London, NW9 5EQ, UK; Public Health England, National Infections Service, Field Service, Nottingham, UK; Public Health England, 61 Colindale Ave, London, NW9 5EQ, UK; ; University of Cambridge, Department of Medicine, Cambridge, UK; Public Health England, 61 Colindale Ave, London, NW9 5EQ, UK; University of Cambridge, Department of Medicine, Cambridge","BackgroundMitigation of SARS-CoV-2 transmission from international travel is a priority. Travellers from countries with travel restrictions (closed travel-corridors) were required to quarantine for 14 days over Summer 2020 in England. We describe the genomic epidemiology of travel-related cases in England and evaluate the effectiveness of this travel policy. MethodsBetween 27/05/2020 and 13/09/2020, probable travel-related SARS-CoV-2 cases and their contacts were identified and combined with UK SARS-CoV-2 sequencing data. The epidemiology and demographics of cases was identified, and the number of contacts per case modelled using negative binomial regression to estimate the effect of travel restriction, and any variation by age, sex and calendar date. Unique travel-related SARS-CoV-2 genomes in the COG-UK dataset were identified to estimate the effect travel restrictions on cluster size generated from these. The Polecat Clustering Tool was used to identify a travel-related SARS-CoV-2 cluster of infection. @@ -3534,6 +3444,13 @@ Prevalence fell by 50% or more across all age groups in round 9 compared to roun ConclusionsCommunity prevalence of swab-positivity has declined markedly between January and February 2021 during lockdown in England, but remains high; the rate of decline has slowed in the most recent period, with a suggestion of pockets of growth. Continued adherence to social distancing and public health measures is required so that infection rates fall to much lower levels. This will help to ensure that the benefits of the vaccination roll-out programme in England are fully realised.",infectious diseases,fuzzy,100,100 medRxiv,10.1101/2021.03.02.21252444,2021-03-03,https://medrxiv.org/cgi/content/short/2021.03.02.21252444,An overview of the National COVID-19 Chest Imaging Database: data quality and cohort analysis,Dominic Cushnan; Oscar Bennett; Rosalind Berka; Ottavia Bertolli; Ashwin Chopra; Samie Dorgham; Alberto Favaro; Tara Ganepola; Mark Halling-Brown; Gergely Imreh; Joseph Jacob; Emily Jefferson; François Lemarchand; Daniel Schofield; Jeremy C Wyatt; - NCCID Collaborative,"AI Lab, NHSX, London, UK; Faculty, London, UK; Faculty, London, UK; Faculty, London, UK; Faculty, London, UK; Faculty, London, UK; Faculty, London, UK; Faculty, London, UK; Scientific Computing, Royal Surrey NHS Foundation Trust, Guildford, UK; Faculty, London, UK; Centre for Medical Image Computing, University College London, London, UK; Health Informatics Centre (HIC), School of Medicine, University of Dundee, UK; AI Lab, NHSX, London, UK; AI Lab, NHSX, London, UK; University of Southampton, Southampton, UK; ","The National COVID-19 Chest Imaging Database (NCCID) is a centralised database containing chest X-rays, chest Computed Tomography (CT) scans and cardiac Magnetic Resonance Images (MRI) from patients across the UK, jointly established by NHSX, the British Society of Thoracic Imaging (BSTI), Royal Surrey NHS Foundation Trust (RSNFT) and Faculty. The objective of the initiative is to support a better understanding of the coronavirus SARS-CoV-2 disease (COVID-19) and development of machine learning (ML) technologies that will improve care for patients hospitalised with a severe COVID-19 infection. The NCCID is now accumulating data from 20 NHS Trusts and Health Boards across England and Wales, with a total contribution of approximately 25,000 imaging studies in the training set (at time of writing) and is actively being used as a research tool by several organisations. This paper introduces the training dataset, including a snapshot analysis performed by NHSX covering: the completeness of clinical data, the availability of image data for the various use-cases (diagnosis, prognosis and longitudinal risk) and potential model confounders within the imaging data. The aim is to inform both existing and potential data users of the NCCIDs suitability for developing diagnostic/prognostic models. In addition, a cohort analysis was performed to measure the representativeness of the NCCID to the wider COVID-19 affected population. Three major aspects were included: geographic, demographic and temporal coverage, revealing good alignment in some categories, e.g., sex and identifying areas for improvements to data collection methods, particularly with respect to geographic coverage. All analyses and discussions are focused on the implications for building ML tools that will generalise well to the clinical use cases.",radiology and imaging,fuzzy,100,100 +medRxiv,10.1101/2021.03.02.21252734,2021-03-03,https://medrxiv.org/cgi/content/short/2021.03.02.21252734,Relation of severe COVID-19 in Scotland to transmission-related factors and risk conditions eligible for shielding support: REACT-SCOT case-control study,Paul M McKeigue; David McAllister; David Caldwell; Ciara Gribben; Jen Bishop; Stuart J McGurnaghan; Matthew Armstrong; Joke Delvaux; Sam Colville; Sharon Hutchinson; Chris Robertson; Nazir Lone; Jim McMenamin; David Goldberg; Helen M Colhoun,University of Edinburgh; University of Glasgow; Public Health Scotland; Public Health Scotland; Public Health Scotland; University of Edinburgh; Public Health Scotland; Public Health Scotland; Public Health Scotland; Glasgow Caledonian University; Public Health Scotland; Strathclyde University; Public Health Scotland; University of Edinburgh; Public Health Scotland; Public Health Scotland; University of Edinburgh,"BackgroundClinically vulnerable individuals have been advised to shield themselves during the COVID-19 epidemic. The objectives of this study were to investigate: (1) the risk of severe COVID-19 in those eligible for shielding, and (2) the relation of severe COVID-19 to transmission-related factors in those in shielding and the general population. + +MethodsAll 178578 diagnosed cases of COVID-19 in Scotland from 1 March 2020 to 18 February 2021 were matched for age, sex and primary care practice to 1744283 controls from the general population. This dataset (REACT-SCOT) was linked to the list of 212702 individuals identified as eligible for shielding. Severe COVID-19 was defined as cases that entered critical care or were fatal. + +ResultsWith those without risk conditions as reference category, the univariate rate ratio for severe COVID-19 was 3.21 (95% CI 3.01 to 3.41) in those with moderate risk conditions and 6.3 (95% CI 5.8 to 6.8) in those eligible for shielding. The highest rate was in solid organ transplant recipients: rate ratio 13.4 (95% CI 9.6 to 18.8). Risk of severe COVID-19 increased with the number of adults but decreased with the number of school-age children in the household. Severe COVID-19 was strongly associated with recent exposure to hospital (defined as 5 to 14 days before presentation date): rate ratio 12.3 (95% CI 11.5 to 13.2) overall. To test for causality, a case-crossover analysis was undertaken; with less recent exposure only (15 to 24 days before first testing positive) as reference category, the rate ratio associated with recent exposure only was 5.9 (95% CI 3.6 to 9.7). The population attributable risk fraction for recent exposure to hospital peaked at 50% in May 2020 and again at 65% in December 2020. + +ConclusionsThe effectiveness of shielding vulnerable individuals was limited by the inability to control transmission in hospital and from other adults in the household. For solid organ transplant recipients, in whom the efficacy of vaccines is uncertain, these results support a policy of offering vaccination to household contacts. Mitigating the impact of the epidemic requires control of nosocomial transmission.",epidemiology,fuzzy,100,100 medRxiv,10.1101/2021.02.27.21252593,2021-03-01,https://medrxiv.org/cgi/content/short/2021.02.27.21252593,Surgical activity in England and Wales during the COVID-19 pandemic: a nationwide observational cohort study,Thomas D Dobbs; John A G Gibson; Alexander J Fowler; Tom E Abbott; Tasnin Shahid; Fatemeh Torabi; Rowena Griffiths; Ronan A Lyons; Rupert M Pearse; Iain S Whitaker,"Swansea University Medical School; Swansea University Medical School; Queen Mary, University of London; Queen Mary University of London; Queen Mary University of London; Swansea University; Swansea University; Swansea University; Queen Mary University of London; Swansea University Medical School","ObjectivesTo report the volume of surgical activity and the number of cancelled surgical procedures during the COVID-19 pandemic. Design and settingAnalysis of electronic health record data from the National Health Service (NHS) in England and Wales. @@ -3560,21 +3477,6 @@ MethodsA cross-sectional community survey in England undertaken between 26 Janua ResultsThe survey comprised 172,099 people, with valid IgG antibody results from 155,172. The overall prevalence of antibodies (weighted to be representative of the population of England and adjusted for test sensitivity and specificity) in England was 13.9% (95% CI 13.7, 14.1) overall, 37.9% (37.2, 38.7) in vaccinated and 9.8% (9.6, 10.0) in unvaccinated people. The prevalence of antibodies (weighted) in unvaccinated people was highest in London at 16.9% (16.3, 17.5), and higher in people of Black (22.4%, 20.8, 24.1) and Asian (20.0%, 19.0, 21.0) ethnicity compared to white (8.5%, 8.3, 8.7) people. The uptake of vaccination by age was highest in those aged 80 years or older (93.5%). Vaccine confidence was high with 92.0% (91.9, 92.1) of people saying that they had accepted or intended to accept the offer. Vaccine confidence varied by age and ethnicity, with lower confidence in young people and those of Black ethnicity. Particular concerns were identified around pregnancy, fertility and allergies. In 971 individuals who received two doses of the Pfizer-BioNTech vaccine, the proportion testing positive was high across all age groups. Following a single dose of Pfizer-BioNTech vaccine after 21 days or more, 84.1% (82.2, 85.9) of people under 60 years tested positive (unadjusted) with a decreasing trend with increasing age, but high responses to a single dose in those with confirmed or suspected prior COVID at 90.1% (87.2, 92.4) across all age groups. ConclusionsThere is uneven distribution of SARS-CoV-2 antibodies in the population with a higher burden in key workers and some minority ethnic groups, similar to the pattern in the first wave. Confidence in the vaccine programme is high overall although it was lower in some of the higher prevalence groups which suggests the need for improved communication about specific perceived risks. Two doses of Pfizer-BioNTech vaccine, or a single dose following previous infection, confers high levels of antibody positivity across all ages. Further work is needed to understand the relationship between antibody positivity, clinical outcomes such as hospitalisation, and transmission.",infectious diseases,fuzzy,100,100 -medRxiv,10.1101/2021.02.25.21252433,2021-03-01,https://medrxiv.org/cgi/content/short/2021.02.25.21252433,Predicting COVID-19 related death using the OpenSAFELY platform,Elizabeth J Williamson; John Tazare; Krishnan Bhaskaran; Helen I McDonald; Alex J Walker; Laurie Tomlinson; Kevin Wing; Sebastian Bacon; Chris Bates; Helen J Curtis; Harriet Forbes; Caroline Minassian; Caroline E Morton; Emily Nightingale; Amir Mehrkar; Dave Evans; Brian D Nicholson; Dave Leon; Peter Inglesby; Brian MacKenna; Nicholas G Davies; Nicholas J DeVito; Henry Drysdale; Jonathan Cockburn; William J Hulme; Jessica Morley; Ian Douglas; Christopher T Rentsch; Rohini Mathur; Angel Wong; Anna Schultze; Richard Croker; John Parry; Frank Hester; Sam Harper; Richard Grieve; David A Harrison; Ewout W Steyerberg; Rosalind M Eggo; Karla Diaz-Ordaz; Ruth Keogh; Stephen JW Evans; Liam Smeeth; Ben Goldacre,"London School of Hygiene & Tropical Medicine, Keppel Street, WC1E 7HT; London School of Hygiene & Tropical Medicine, Keppel Street, WC1E 7HT; London School of Hygiene & Tropical Medicine, Keppel Street, WC1E 7HT; London School of Hygiene & Tropical Medicine, Keppel Street, WC1E 7HT; NIHR Health Protection Research Unit (HPRU) in Immunisation; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; London School of Hygiene & Tropical Medicine, Keppel Street, WC1E 7HT; London School of Hygiene & Tropical Medicine, Keppel Street, WC1E 7HT; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; TPP, TPP House, 129 Low Lane, Horsforth, Leeds, LS18 5PX; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; London School of Hygiene & Tropical Medicine, Keppel Street, WC1E 7HT; London School of Hygiene & Tropical Medicine, Keppel Street, WC1E 7HT; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; London School of Hygiene & Tropical Medicine, Keppel Street, WC1E 7HT; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; London School of Hygiene & Tropical Medicine, Keppel Street, WC1E 7HT; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; London School of Hygiene & Tropical Medicine, Keppel Street, WC1E 7HT; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; TPP, TPP House, 129 Low Lane, Horsforth, Leeds, LS18 5PX; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; London School of Hygiene & Tropical Medicine, Keppel Street, WC1E 7HT; London School of Hygiene & Tropical Medicine, Keppel Street, WC1E 7HT; London School of Hygiene & Tropical Medicine, Keppel Street, WC1E 7HT; London School of Hygiene & Tropical Medicine, Keppel Street, WC1E 7HT; London School of Hygiene & Tropical Medicine, Keppel Street, WC1E 7HT; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; TPP, TPP House, 129 Low Lane, Horsforth, Leeds, LS18 5PX; TPP, TPP House, 129 Low Lane, Horsforth, Leeds, LS18 5PX; TPP, TPP House, 129 Low Lane, Horsforth, Leeds, LS18 5PX; London School of Hygiene & Tropical Medicine, Keppel Street, WC1E 7HT; Intensive Care National Audit & Research Centre (ICNARC), 24 High Holborn, Holborn, London WC1V 6AZ; Leiden University Medical Center, Leiden, the Netherlands; London School of Hygiene & Tropical Medicine, Keppel Street, WC1E 7HT; London School of Hygiene & Tropical Medicine, Keppel Street, WC1E 7HT; London School of Hygiene & Tropical Medicine, Keppel Street, WC1E 7HT; London School of Hygiene & Tropical Medicine, Keppel Street, WC1E 7HT; London School of Hygiene & Tropical Medicine, Keppel Street, WC1E 7HT; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG","ObjectivesTo compare approaches for obtaining relative and absolute estimates of risk of 28-day COVID-19 mortality for adults in the general population of England in the context of changing levels of circulating infection. - -DesignThree designs were compared. (A) case-cohort which does not explicitly account for the time-changing prevalence of COVID-19 infection, (B) 28-day landmarking, a series of sequential overlapping sub-studies incorporating time-updating proxy measures of the prevalence of infection, and (C) daily landmarking. Regression models were fitted to predict 28-day COVID-19 mortality. - -SettingWorking on behalf of NHS England, we used clinical data from adult patients from all regions of England held in the TPP SystmOne electronic health record system, linked to Office for National Statistics (ONS) mortality data, using the OpenSAFELY platform. - -ParticipantsEligible participants were adults aged 18 or over, registered at a general practice using TPP software on 1st March 2020 with recorded sex, postcode and ethnicity. 11,972,947 individuals were included, and 7,999 participants experienced a COVID-19 related death. The study period lasted 100 days, ending 8th June 2020. - -PredictorsA range of demographic characteristics and comorbidities were used as potential predictors. Local infection prevalence was estimated with three proxies: modelled based on local prevalence and other key factors; rate of A&E COVID-19 related attendances; and rate of suspected COVID-19 cases in primary care. - -Main outcome measuresCOVID-19 related death. - -ResultsAll models discriminated well between patients who did and did not experience COVID-19 related death, with C-statistics ranging from 0.92-0.94. Accurate estimates of absolute risk required data on local infection prevalence, with modelled estimates providing the best performance. - -ConclusionsReliable estimates of absolute risk need to incorporate changing local prevalence of infection. Simple models can provide very good discrimination and may simplify implementation of risk prediction tools in practice.",infectious diseases,fuzzy,100,100 medRxiv,10.1101/2021.02.25.21252402,2021-02-28,https://medrxiv.org/cgi/content/short/2021.02.25.21252402,Racial and ethnic differences in COVID-19 vaccine hesitancy and uptake,Long H. Nguyen; Amit D. Joshi; David A. Drew; Jordi Merino; Wenjie Ma; Sohee Kwon; Kai Wang; Mark S. Graham; Lorenzo Polidori; Cristina Menni; Carole H. Sudre; Adjoa Anyane-Yeboa; Christina M. Astley; Erica T. Warner; Christina Hu; Somesh Selvachandran; Richard Davies; Denis Nash; Paul W. Franks; Jonathhan Wolf; Sebastien Ourselin; Claire J Steves; Tim D. Spector; Andrew T. Chan; - COPE Consortium,Massachusetts General Hospital and Harvard Medical School; Massachusetts General Hospital and Harvard Medical School; Massachusetts General Hospital and Harvard Medical School; Massachusetts General Hospital and Harvard Medical School; Massachusetts General Hospital and Harvard Medical School; Massachusetts General Hospital and Harvard Medical School; Massachusetts General Hospital and Harvard Medical School; King's College London; Zoe Global Ltd.; King's College London; King's College London; Massachusetts General Hospital and Harvard Medical School; Broad Institute of MIT and Harvard; Massachusetts General Hospital and Harvard Medical School; Zoe Global Ltd.; Zoe Global Ltd.; Zoe Global Ltd.; City University of New York; Lund University; Zoe Global Ltd.; King's College London; King's College London; King's College London; Massachusetts General Hospital and Harvard Medical School; ,"BackgroundRacial and ethnic minorities have been disproportionately impacted by COVID-19. In the initial phase of population-based vaccination in the United States (U.S.) and United Kingdom (U.K.), vaccine hesitancy and limited access may result in disparities in uptake. MethodsWe performed a cohort study among U.S. and U.K. participants in the smartphone-based COVID Symptom Study (March 24, 2020-February 16, 2021). We used logistic regression to estimate odds ratios (ORs) of COVID-19 vaccine hesitancy (unsure/not willing) and receipt. @@ -3963,6 +3865,15 @@ MethodsThe REal-time Assessment of Community Transmission study-1 (REACT-1) obta ResultsIn round 8a, we found 1,962 positives from 142,909 swabs giving a weighted prevalence of 1.58% (95% CI, 1.49%, 1.68%). Using a constant growth model, we found no strong evidence for either growth or decay averaged across the period; rather, based on data from a limited number of days, prevalence may have started to rise at the end of round 8a. Facebook mobility data showed a marked decrease in activity at the end of December 2020, followed by a rise at the start of the working year in January 2021. Between round 7b and round 8a, prevalence increased in all adult age groups, more than doubling to 0.94% (0.83%, 1.07%) in those aged 65 and over. Large household size, living in a deprived neighbourhood, and Black and Asian ethnicity were all associated with increased prevalence. Both healthcare and care home workers, and other key workers, had increased odds of swab-positivity compared to other workers. ConclusionDuring the initial 10 days of the third COVID-19 lockdown in England in January 2021, prevalence of SARS-CoV-2 was very high with no evidence of decline. Until prevalence in the community is reduced substantially, health services will remain under extreme pressure and the cumulative number of lives lost during this pandemic will continue to increase rapidly.",infectious diseases,fuzzy,100,100 +medRxiv,10.1101/2021.01.15.21249756,2021-01-20,https://medrxiv.org/cgi/content/short/2021.01.15.21249756,Factors associated with deaths due to COVID-19 versus other causes: population-based cohort analysis of UK primary care data and linked national death registrations within the OpenSAFELY platform,Krishnan Bhaskaran; Sebastian CJ Bacon; Stephen JW Evans; Chris J Bates; Christopher T Rentsch; MacKenna Brian; Laurie Tomlinson; Alex J Walker; Anna Schultze; Caroline E Morton; Daniel Grint; Amir Mehrkar; Rosalind M Eggo; Peter Inglesby; Ian J Douglas; Helen I McDonald; Jonathan Cockburn; Elizabeth J Williamson; David Evans; Helen J Curtis; William J Hulme; John Parry; Frank Hester; Sam Harper; David Spiegelhalter; Liam Smeeth; Ben Goldacre,"London School of Hygiene and Tropical Medicine; University of Oxford; London School of Hygiene Tropical Medicine; The Phoenix Partnership; London School of Hygiene and Tropical Medicine; University of Oxford; London School of Hygiene and Tropical Medicine; University of Oxford; London School of Hygiene and Tropical Medicine; University of Oxford; London School of Hygiene and Tropical Medicine; University of Oxford; London School of Hygiene and Tropical Medicine; University of Oxford; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; The Phoenix Partnership; London School of Hygiene and Tropical Medicine; University of Oxford; University of Oxford; University of Oxford; University of Oxford; The Phoenix Partnership; The Phoenix Partnership; Winton Centre for Risk and Evidence Communication, Centre for Mathematical Sciences, University of Cambridge; London School of Hygiene and Tropical Medicine; University of Oxford","BackgroundMortality from COVID-19 shows a strong relationship with age and pre-existing medical conditions, as does mortality from other causes. However it is unclear how specific factors are differentially associated with COVID-19 mortality as compared to mortality from other causes. + +MethodsWorking on behalf of NHS England, we carried out a cohort study within the OpenSAFELY platform. Primary care data from England were linked to national death registrations. We included all adults (aged [≥]18 years) in the database on 1st February 2020 and with >1 year of continuous prior registration, the cut-off date for deaths was 9th November 2020. Associations between individual-level characteristics and COVID-19 and non-COVID deaths were estimated by fitting age- and sex-adjusted logistic models for these two outcomes. + +Results17,456,515 individuals were included. 17,063 died from COVID-19 and 134,316 from other causes. Most factors associated with COVID-19 death were similarly associated with non-COVID death, but the magnitudes of association differed. Older age was more strongly associated with COVID-19 death than non-COVID death (e.g. ORs 40.7 [95% CI 37.7-43.8] and 29.6 [28.9-30.3] respectively for [≥]80 vs 50-59 years), as was male sex, deprivation, obesity, and some comorbidities. Smoking, history of cancer and chronic liver disease had stronger associations with non-COVID than COVID-19 death. All non-white ethnic groups had higher odds than white of COVID-19 death (OR for Black: 2.20 [1.96-2.47], South Asian: 2.33 [2.16-2.52]), but lower odds than white of non-COVID death (Black: 0.88 [0.83-0.94], South Asian: 0.78 [0.75-0.81]). + +InterpretationSimilar associations of most individual-level factors with COVID-19 and non-COVID death suggest that COVID-19 largely multiplies existing risks faced by patients, with some notable exceptions. Identifying the unique factors contributing to the excess COVID-19 mortality risk among non-white groups is a priority to inform efforts to reduce deaths from COVID-19. + +FundingWellcome, Royal Society, National Institute for Health Research, National Institute for Health Research Oxford Biomedical Research Centre, UK Medical Research Council, Health Data Research UK.",infectious diseases,fuzzy,100,100 medRxiv,10.1101/2021.01.19.21249840,2021-01-20,https://medrxiv.org/cgi/content/short/2021.01.19.21249840,Impact of SARS-CoV-2 B.1.1.7 Spike variant on neutralisation potency of sera from individuals vaccinated with Pfizer vaccine BNT162b2,Dami Collier; Anna De Marco; Isabella Ferreira; Bo Meng; Rawlings Datir; Alexandra C. Walls; Steven A. Kemp S; Jessica Bassi; Dora Pinto; Chiara Silacci Fregni; Siro Bianchi; M. Alejandra Tortorici; John Bowen; Katja Culap; Stefano Jaconi; Elisabetta Cameroni; Gyorgy Snell; Matteo S. Pizzuto; Alessandra Franzetti Pellanda; Christian Garzoni; Agostino Riva; - The CITIID-NIHR BioResource COVID-19 Collaboration; Anne Elmer; Nathalie Kingston; Barbara Graves; Laura McCoy; Ken Smith; John Bradley; Ceron Ceron-Gutierrez L; Gabriela Barcenas-Morales; Herbert W. Virgin; Antonio Lanzavecchia; Luca Piccoli; Rainer Doffinger; Mark Wills; David Veesler; Davide Corti; Ravindra Gupta,UCL; Vir Biotechnology; University of Cambridge; University of Cambridge; University of Cambridge; University of Washington; University of Cambridge; Vir Biotechnology; Vir Biotechnology; Vir Biotechnology; Vir Biotechnology; University of Washington; University of Washington; Vir Biotehcnology; Vir Biotechnology; Vir Biotechnology; Vir Biotechnology; Vir Biotechnology; Clinica Luganese Moncucco; Clinica Luganese Moncucco; Luigi Sacco Hospital; ; Addenbrookes Hospital; NIHR; Cambridge NIHR; UCL; University of Cambridge; University of Cambridge; Addenbrookes Hospital; Addenbrookes Hospital; Vir Biotechnology; Vir Biotechnology; Vir Biotechnology; Addenbrookes Hospital; University of Cambridge; University of Washington; Vir Biotechnology; University of Cambridge,"Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) transmission is uncontrolled in many parts of the world, compounded in some areas by higher transmission potential of the B1.1.7 variant now seen in 50 countries. It is unclear whether responses to SARS-CoV-2 vaccines based on the prototypic strain will be impacted by mutations found in B.1.1.7. Here we assessed immune responses following vaccination with mRNA-based vaccine BNT162b2. We measured neutralising antibody responses following a single immunization using pseudoviruses expressing the wild-type Spike protein or the 8 amino acid mutations found in the B.1.1.7 spike protein. The vaccine sera exhibited a broad range of neutralising titres against the wild-type pseudoviruses that were modestly reduced against B.1.1.7 variant. This reduction was also evident in sera from some convalescent patients. Decreased B.1.1.7 neutralisation was also observed with monoclonal antibodies targeting the N-terminal domain (9 out of 10), the Receptor Binding Motif (RBM) (5 out of 31), but not in neutralising mAbs binding outside the RBM. Introduction of the E484K mutation in a B.1.1.7 background to reflect newly emerging viruses in the UK led to a more substantial loss of neutralising activity by vaccine-elicited antibodies and mAbs (19 out of 31) over that conferred by the B.1.1.7 mutations alone. E484K emergence on a B.1.1.7 background represents a threat to the vaccine BNT162b.",infectious diseases,fuzzy,100,100 medRxiv,10.1101/2021.01.14.21249801,2021-01-15,https://medrxiv.org/cgi/content/short/2021.01.14.21249801,Factor V is an immune inhibitor that is expressed at increased levels in leukocytes of patients with severe Covid-19,Jun Wang; Prasanti Kotagiri; Paul Lyons; Federica Mescia; Laura Bergamaschi; Lorinda Turner; Rafia Al-Lamki; Michael D Morgan; Fernando J Calero-Nieto; Karsten Bach; Nicole Mende; Nicola K Wilson; Emily R Watts; - Cambridge Institute of Therapeutic Immunology and Infectious Disease - NIHR Covid BioResource; Patrick Chinnery; Nathalie Kingston; Sofia Papadia; Kathleen Stirrups; Neil Walker; Ravindra K Gupta; Mark Toshner; Michael Weekes; James A Nathan; Sarah Walmsley; Willem Hendrik Ouwehand; Mary Kasanicki; Berthold Gottgens; John C Marioni; Smith GC Smith; Jordan S Pober; John R Bradley,University of Cambridge; University of Cambridge; University of Cambridge; University of Cambridge; University of Cambridge; University of Cambridge; University of Cambridge; University of Cambridge; University of Cambridge; University of Cambridge; University of Cambridge; University of Cambridge; University of Edinburgh; ; University of Cambridge; University of Cambridge; University of Cambridge; University of Cambridge; University of Cambridge; University of Cambridge; University of Cambridge; Cambridge University; University of Cambridge; University of Edinburgh; Prof; Cambridge University Hospitals; University of Cambridge; EMBL-EBI; University of Cambridge; Yale University; University of Cambridge,"Severe Covid-19 is associated with elevated plasma Factor V (FV) and increased risk of thromboembolism. We report that neutrophils, T regulatory cells (Tregs), and monocytes from patients with severe Covid-19 express FV, and expression correlates with T cell lymphopenia. In vitro full length FV, but not FV activated by thrombin cleavage, suppresses T cell proliferation. Increased and prolonged FV expression by cells of the innate and adaptive immune systems may contribute to lymphopenia in severe Covid-19. Activation by thrombin destroys the immunosuppressive properties of FV. Anticoagulation in Covid-19 patients may have the unintended consequence of suppressing the adaptive immune system.",infectious diseases,fuzzy,100,100 medRxiv,10.1101/2021.01.15.21249885,2021-01-15,https://medrxiv.org/cgi/content/short/2021.01.15.21249885,Epidemiology of post-COVID syndrome following hospitalisation with coronavirus: a retrospective cohort study,Daniel Ayoubkhani; Kamlesh Khunti; Vahe Nafilyan; Thomas Maddox; Ben Humberstone; Ian Diamond; Amitava Banerjee,Office for National Statistics; University of Leicester; Office for National Statistics; Office for National Statistics; Office for National Statistics; Office for National Statistics; University College London,"ObjectivesThe epidemiology of post-COVID syndrome (PCS) is currently undefined. We quantified rates of organ-specific impairment following recovery from COVID-19 hospitalisation compared with those in a matched control group, and how the rate ratio (RR) varies by age, sex, and ethnicity. @@ -4068,7 +3979,6 @@ Added value of this studyTranslating current knowledge and uncertainty of vaccin Implications of all the available evidenceVaccination is likely to provide substantial individual protection to those receiving two doses, but the degree of protection to the wider population is still uncertain. While substantial immunisation of the most vulnerable groups will allow for some relaxation of controls, this must be done gradually to prevent large scale public health consequences.",infectious diseases,fuzzy,100,100 medRxiv,10.1101/2020.12.30.20248603,2021-01-01,https://medrxiv.org/cgi/content/short/2020.12.30.20248603,SARS-CoV-2 positivity in asymptomatic-screened dental patients,David I Conway; Shauna Culshaw; Maura Edwards; Claire Clark; Chris Watling; Chris Robertson; Raymond Braid; Emma O'Keefe; Niall McGoldrick; Jacky Burns; Stacey Provan; Harper VanSteenhouse; Jodie Hay; Rory Gunson; - Dental COVID-19 Surveillance Survey Group,University of Glasgow and Public Health Scotland; University of Glasgow; NHS Ayrshire and Arran; Public Health Scotland; Public Health Scotland; Strathclyde University and Public Health Scotland; Public Health Scotland; NHS Fife; NHS Fife; NHS Fife; NHS Greater Glasgow & Clyde; BioClavis Ltd; University of Glasgow; NHS Greater Glasgow & Clyde; ,"Enhanced community surveillance is a key pillar of the public health response to COVID-19. Asymptomatic carriage of SARS-CoV-2 is a potentially significant source of transmission, yet remains relatively poorly understood. Disruption of dental services continues with significantly reduced capacity. Ongoing precautions include pre- and/or at appointment COVID-19 symptom screening and use of enhanced personal protective equipment (PPE). This study aimed to investigate SARS-CoV-2 infection in dental patients to inform community surveillance and improve understanding of risks in the dental setting. Thirty-one dental care centres across Scotland invited asymptomatic screened patients over 5-years-old to participate. Following verbal consent and completion of sociodemographic and symptom history questionnaire, trained dental teams took a combined oropharyngeal and nasal swab sample using standardised VTM-containing testkits. Samples were processed by the Lighthouse Lab and patients informed of their results by SMS/e-mail with appropriate self-isolation guidance in the event of a positive test. Over a 13-week period (from 3August to 31October2020) n=4,032 patients, largely representative of the population, were tested. Of these n=22 (0.5%; 95%CI 0.5%, 0.8%) tested positive for SARS-CoV-2. The positivity rate increased over the period, commensurate with uptick in community prevalence identified across all national testing monitoring data streams. All positive cases were successfully followed up by the national contact tracing program. To the best of our knowledge this is the first report of a COVID-19 testing survey in asymptomatic-screened patients presenting in a dental setting. The positivity rate in this patient group reflects the underlying prevalence in community at the time. These data are a salient reminder, particularly when community infection levels are rising, of the importance of appropriate ongoing Infection Prevention Control and PPE vigilance, which is relevant as healthcare team fatigue increases as the pandemic continues. Dental settings are a valuable location for public health surveillance.",dentistry and oral medicine,fuzzy,100,100 -medRxiv,10.1101/2020.12.24.20248822,2020-12-26,https://medrxiv.org/cgi/content/short/2020.12.24.20248822,Estimated transmissibility and severity of novel SARS-CoV-2 Variant of Concern 202012/01 in England,Nicholas G Davies; Sam Abbott; Rosanna C. Barnard; Christopher I. Jarvis; Adam J. Kucharski; James D Munday; Carl A. B. Pearson; Timothy Russell; Damien Tully; Alex D. Washburne; Tom Wenseleers; Amy Gimma; William Waites; Kerry L. M. Wong; Kevin van Zandvoort; Justin D. Silverman; - CMMID COVID-19 Working Group; - The COVID-19 Genomics UK (COG-UK) Consortium; Karla Diaz-Ordaz; Ruth H Keogh; Rosalind M Eggo; Sebastian Funk; Mark Jit; Katherine E. Atkins; W. John Edmunds,"London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene & Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; Selva Analytics LLC; KU Leuven; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; College of Information Science and Technology, Pennsylvania State University; ; ; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine","A novel SARS-CoV-2 variant, VOC 202012/01 (lineage B.1.1.7), emerged in southeast England in November 2020 and is rapidly spreading towards fixation. Using a variety of statistical and dynamic modelling approaches, we estimate that this variant has a 43-90% (range of 95% credible intervals 38-130%) higher reproduction number than preexisting variants. A fitted two-strain dynamic transmission model shows that VOC 202012/01 will lead to large resurgences of COVID-19 cases. Without stringent control measures, including limited closure of educational institutions and a greatly accelerated vaccine roll-out, COVID-19 hospitalisations and deaths across England in 2021 will exceed those in 2020. Concerningly, VOC 202012/01 has spread globally and exhibits a similar transmission increase (59-74%) in Denmark, Switzerland, and the United States.",epidemiology,fuzzy,100,100 bioRxiv,10.1101/2020.12.23.424229,2020-12-25,https://biorxiv.org/cgi/content/short/2020.12.23.424229,Patterns of within-host genetic diversity in SARS-CoV-2,Gerry Tonkin-Hill; Inigo Martincorena; Roberto Amato; Andrew R J Lawson; Moritz Gerstung; Ian Johnston; David K Jackson; Naomi R Park; Stefanie V Lensing; Michael A Quail; Sónia Gonçalves; Cristina Ariani; Michael Spencer Chapman; William L Hamilton; Luke W Meredith; Grant Hall; Aminu S Jahun; Yasmin Chaudhry; Myra Hosmillo; Malte L Pinckert; Iliana Georgana; Anna Yakovleva; Laura G Caller; Sarah L Caddy; Theresa Feltwell; Fahad A Khokhar; Charlotte J Houldcroft; Martin D Curran; Surendra Parmar; - The COVID-19 Genomics UK (COG-UK) Consortium; Alex Alderton; Rachel Nelson; Ewan Harrison; John Sillitoe; Stephen D Bentley; Jeffrey C Barrett; M. Estee Torok; Ian G Goodfellow; Cordelia Langford; Dominic Kwiatkowski; - Wellcome Sanger Institute COVID-19 Surveillance Team,"Wellcome Sanger Institute; Wellcome Sanger Institute; Wellcome Sanger Institute; Wellcome Sanger Institute; European Bioinformatics Institute; Wellcome Sanger Institute; Wellcome Sanger Institute; Wellcome Sanger Institute; Wellcome Sanger Institute; Wellcome Sanger Institute; Wellcome Sanger Institute; Wellcome Sanger Institute; Wellcome Sanger Institute; Department of Medicine, University of Cambridge; Department of Pathology, University of Cambridge; Department of Pathology, University of Cambridge; Department of Pathology, University of Cambridge; Department of Pathology, University of Cambridge; Department of Pathology, University of Cambridge; Department of Pathology, University of Cambridge; Department of Pathology, University of Cambridge; Department of Pathology, University of Cambridge; Department of Pathology, University of Cambridge and The Francis Crick Institute; Department of Medicine, University of Cambridge; Department of Pathology, University of Cambridge; Department of Medicine, University of Cambridge and Cambridge Institute of Therapeutic Immunology and Infectious Disease; Department of Medicine, University of Cambridge; Public Health England; Public Health England; COG-UK; Wellcome Sanger Institute; Wellcome Sanger Institute; Wellcome Sanger Institute and European Bioinformatics Institute; Wellcome Sanger Institute; Wellcome Sanger Institute; Wellcome Sanger Institute; Department of Medicine, University of Cambridge; Department of Pathology, University of Cambridge; Wellcome Sanger Institute; Wellcome Sanger Institute and Oxford University; ","Monitoring the spread of SARS-CoV-2 and reconstructing transmission chains has become a major public health focus for many governments around the world. The modest mutation rate and rapid transmission of SARS-CoV-2 prevents the reconstruction of transmission chains from consensus genome sequences, but within-host genetic diversity could theoretically help identify close contacts. Here we describe the patterns of within-host diversity in 1,181 SARS-CoV-2 samples sequenced to high depth in duplicate. 95% of samples show within-host mutations at detectable allele frequencies. Analyses of the mutational spectra revealed strong strand asymmetries suggestive of damage or RNA editing of the plus strand, rather than replication errors, dominating the accumulation of mutations during the SARS-CoV-2 pandemic. Within and between host diversity show strong purifying selection, particularly against nonsense mutations. Recurrent within-host mutations, many of which coincide with known phylogenetic homoplasies, display a spectrum and patterns of purifying selection more suggestive of mutational hotspots than recombination or convergent evolution. While allele frequencies suggest that most samples result from infection by a single lineage, we identify multiple putative examples of co-infection. Integrating these results into an epidemiological inference framework, we find that while sharing of within-host variants between samples could help the reconstruction of transmission chains, mutational hotspots and rare cases of superinfection can confound these analyses.",genomics,fuzzy,100,100 medRxiv,10.1101/2020.12.21.20248607,2020-12-22,https://medrxiv.org/cgi/content/short/2020.12.21.20248607,Time use and social mixing during and around festive periods: Potential changes in the age distribution of COVID-19 cases from increased intergenerational interactions,Edwin van Leeuwen; Frank G. Sandmann; Rosalind M. Eggo; - PHE Joint modelling group; Peter J. White,Public Health England; Public Health England; London School of Hygiene &Tropical Medicine; London School of Hygiene & Tropical Medicine; ; Public Health England; Imperial College London,"RationaleAmid the ongoing coronavirus disease 2019 (COVID-19) pandemic in which many countries have adopted physical distancing measures, tiered restrictions, and episodic ""lockdowns,"" the impact of potentially increased social mixing during festive holidays on the age distribution of new COVID-19 cases remains unclear. @@ -4177,13 +4087,6 @@ Following the immediate drop, rates of recorded tests increased on average by 5- ConclusionsCardiovascular disease monitoring in English primary care declined substantially from the time of the first UK lockdown. Despite a consistent recovery in activity, there is still a substantial shortfall in the numbers of recorded measurements to those expected. Strategies are required to ensure cardiovascular disease monitoring is maintained during the COVID-19 pandemic.",primary care research,fuzzy,100,100 medRxiv,10.1101/2020.12.10.20247155,2020-12-14,https://medrxiv.org/cgi/content/short/2020.12.10.20247155,Self-harm presentations to Emergency Departments and Place of Safety during the first wave of the UK COVID-19 pandemic: South London and Maudsley data on service use from February to June 2020.,Eleanor Nuzum; Evangelia Martin; Gemma Morgan; Rina Dutta; Christoph Mueller; Catherine Polling; Megan Pritchard; Sumithra Velupillai; Robert Stewart,South London and Maudsley NHS Foundation Trust; South London and Maudsley NHS Foundation Trust; South London and Maudsley NHS Foundation Trust; King's College London; King's College London; King's College London; King's College London; King's College London; King's College London,"The lockdown and social distancing policy imposed due to the COVID-19 pandemic has had a substantial impact on both mental health service delivery, and the ways in which people are accessing these services. Previous reports from the South London and Maudsley NHS Trust (SLaM; a large mental health service provider for around 1.2m residents in South London) have highlighted increased use of virtual contacts by mental health teams, with dropping numbers of face-to-face contacts over the first wave of the pandemic. There has been concern that the impact of the COVID-19 pandemic would lead to higher mental health emergencies, particularly instances of self-harm. However, with people advised to stay at home during the first wave lockdown, it is as yet unclear whether this impacted mental health service presentations. Taking advantage of SLaMs Clinical Records Interactive Search (CRIS) data resource with daily updates of information from its electronic mental health records, this paper describes overall presentations to Emergency Department (ED) mental health liaison teams, and those with self-harm. The paper focussed on three periods: i) a pre-lockdown period 1st February to 15th March, ii) a lockdown period 16th March to 10th May and iii) a post-lockdown period 11th May to 28th June. In summary, all attendances to EDs for mental health support decreased during the lockdown period, including those with self-harm. All types of self-harm decreased during lockdown, with self-poisoning remaining the most common. Attendances to EDs for mental health support increased post-lockdown, although were only just approaching pre-lockdown levels by the end of June 2020.",psychiatry and clinical psychology,fuzzy,100,100 medRxiv,10.1101/2020.12.05.20241927,2020-12-11,https://medrxiv.org/cgi/content/short/2020.12.05.20241927,Neutralising antibodies drive Spike mediated SARS-CoV-2 evasion,Steven A Kemp; Dami A Collier; Rawlings Datir; Isabella ATM Ferreira; Salma Gayed; Aminu Jahun; Myra Hosmillo; Chloe Rees-Spear; Petra Mlcochova; Ines Ushiro Lumb; David Roberts; Anita Chandra; Nigel Temperton; - The COVID-19 Genomics UK (COG-UK) Consortium; Katherine Sharrocks; Elizabeth Blane; - The CITIID-NIHR BioResource COVID-19 Collaboration; John A Briggs; Marit van Gils; Ken G Smith; John R Bradley; Chris Smith; Rainer Doffinger; Lourdes Ceron-Gutierrez; Gabriela Barcenas-Morales; David Pollock; Richard Goldstein; Anna Smielewska; Jordan P Skittrall; Theo Gouliouris; Ian G Goodfellow; Effrossyni Gkrania-Klotsas; Chris JR Illingworth; Laura E McCoy; Ravindra K Gupta,"Division of Infection and Immunity, University College London, London, UK; Cambridge Institute of Therapeutic Immunology & Infectious Disease (CITIID), Cambridge, UK.; Cambridge Institute of Therapeutic Immunology & Infectious Disease (CITIID), Cambridge, UK.; Cambridge Institute of Therapeutic Immunology & Infectious Disease (CITIID), Cambridge, UK.; Department of Infectious Diseases, Cambridge University NHS Hospitals Foundation Trust, Cambridge, UK.; Department of Pathology, University of Cambridge, Cambridge; Department of Pathology, University of Cambridge, Cambridge; Division of Infection and Immunity, University College London, London, UK.; Cambridge Institute of Therapeutic Immunology & Infectious Disease (CITIID), Cambridge, UK.; Public Health England, Colindale, London, UK; Public Health England, Colindale, London, UK; Cambridge Institute of Therapeutic Immunology & Infectious Disease (CITIID), Cambridge, UK.; Viral Pseudotype Unit, Medway School of Pharmacy, University of Kent, UK; -; Department of Infectious Diseases, Cambridge University NHS Hospitals Foundation Trust, Cambridge, UK.; Department of Medicine, University of Cambridge, Cambridge, UK.; -; Medical Research Council Laboratory of Molecular Biology, Cambridge, UK.; University of Amsterdam; Cambridge Institute of Therapeutic Immunology & Infectious Disease (CITIID), Cambridge, UK.; NIHR Cambridge Clinical Research Facility, Cambridge, UK.; Department of Applied Mathematics and Theoretical Physics, University of Cambridge, UK; Addenbrookes Hospital; Addenbrookes Hospital; Addenbrookes Hospital; University of Colorado School of Medicine; Division of Infection & Immunity, University College London, UK; Department of Virology, Cambridge University NHS Hospitals Foundation Trust; Clinical Microbiology and Public Health Laboratory, Addenbrookes Hospital, Cambridge, UK; Department of Infectious Diseases, Cambridge University NHS Hospitals Foundation Trust, Cambridge, UK.; Department of Pathology, University of Cambridge, Cambridge; Department of Infectious Diseases, Cambridge University NHS Hospitals Foundation Trust, Cambridge, UK.; MRC Biostatistics Unit, University of Cambridge, Cambridge, UK; Division of Infection and Immunity, University College London, London, UK; Cambridge Institute of Therapeutic Immunology & Infectious Disease (CITIID), Cambridge, UK.","SARS-CoV-2 Spike protein is critical for virus infection via engagement of ACE2, and amino acid variation in Spike is increasingly appreciated. Given both vaccines and therapeutics are designed around Wuhan-1 Spike, this raises the theoretical possibility of virus escape, particularly in immunocompromised individuals where prolonged viral replication occurs. Here we report chronic SARS-CoV-2 with reduced sensitivity to neutralising antibodies in an immune suppressed individual treated with convalescent plasma, generating whole genome ultradeep sequences by both short and long read technologies over 23 time points spanning 101 days. Although little change was observed in the overall viral population structure following two courses of remdesivir over the first 57 days, N501Y in Spike was transiently detected at day 55 and V157L in RdRp emerged. However, following convalescent plasma we observed large, dynamic virus population shifts, with the emergence of a dominant viral strain bearing D796H in S2 and{Delta} H69/{Delta}V70 in the S1 N-terminal domain NTD of the Spike protein. As passively transferred serum antibodies diminished, viruses with the escape genotype diminished in frequency, before returning during a final, unsuccessful course of convalescent plasma. In vitro, the Spike escape double mutant bearing{Delta} H69/{Delta}V70 and D796H conferred decreased sensitivity to convalescent plasma, whilst maintaining infectivity similar to wild type. D796H appeared to be the main contributor to decreased susceptibility, but incurred an infectivity defect. The{Delta} H69/{Delta}V70 single mutant had two-fold higher infectivity compared to wild type and appeared to compensate for the reduced infectivity of D796H. Consistent with the observed mutations being outside the RBD, monoclonal antibodies targeting the RBD were not impacted by either or both mutations, but a non RBD binding monoclonal antibody was less potent against{Delta} H69/{Delta}V70 and the double mutant. These data reveal strong selection on SARS-CoV-2 during convalescent plasma therapy associated with emergence of viral variants with reduced susceptibility to neutralising antibodies.",infectious diseases,fuzzy,100,100 -medRxiv,10.1101/2020.12.08.20246231,2020-12-11,https://medrxiv.org/cgi/content/short/2020.12.08.20246231,Artificial intelligence-enabled analysis of UK and US public attitudes on Facebook and Twitter towards COVID-19 vaccinations,Amir Hussain; Ahsen Tahir; Zain Hussain; Zakariya Sheikh; Mandar Gogate; Kia Dashtipour; Azhar Ali; Aziz Sheikh,"Edinburgh Napier University, UK; Edinburgh Napier University, UK; Edinburgh Medical School, College of Medicine and Veterinary Medicine, University of Edinburgh, UK; Edinburgh Medical School, College of Medicine and Veterinary Medicine, University of Edinburgh, UK; Edinburgh Napier University, UK; Edinburgh Napier University, UK; NHS Forth Medical Group, UK & Harvard T.H. Chan School of Public Health, USA; Usher Institute, Edinburgh Medical School, University of Edinburgh, UK","BackgroundGlobal efforts towards the development and deployment of a vaccine for SARS-CoV-2 are rapidly advancing. We developed and applied an artificial-intelligence (AI)-based approach to analyse social-media public sentiment in the UK and the US towards COVID-19 vaccinations, to understand public attitude and identify topics of concern. - -MethodsOver 300,000 social-media posts related to COVID-19 vaccinations were extracted, including 23,571 Facebook-posts from the UK and 144,864 from the US, along with 40,268 tweets from the UK and 98,385 from the US respectively, from 1st March - 22nd November 2020. We used natural language processing and deep learning based techniques to predict average sentiments, sentiment trends and topics of discussion. These were analysed longitudinally and geo-spatially, and a manual reading of randomly selected posts around points of interest helped identify underlying themes and validated insights from the analysis. - -ResultsWe found overall averaged positive, negative and neutral sentiment in the UK to be 58%, 22% and 17%, compared to 56%, 24% and 18% in the US, respectively. Public optimism over vaccine development, effectiveness and trials as well as concerns over safety, economic viability and corporation control were identified. We compared our findings to national surveys in both countries and found them to correlate broadly. - -ConclusionsAI-enabled social-media analysis should be considered for adoption by institutions and governments, alongside surveys and other conventional methods of assessing public attitude. This could enable real-time assessment, at scale, of public confidence and trust in COVID-19 vaccinations, help address concerns of vaccine-sceptics and develop more effective policies and communication strategies to maximise uptake.",public and global health,fuzzy,100,100 medRxiv,10.1101/2020.12.03.20242941,2020-12-07,https://medrxiv.org/cgi/content/short/2020.12.03.20242941,Contrasting factors associated with COVID-19-related ICU and death outcomes: interpretable multivariable analyses of the UK CHESS dataset.,Massimo Cavallaro; Haseeb Moiz; Matt J Keeling; Noel D McCarthy,University of Warwick; University of Warwick; University of Warwick; University of Warwick,"Identification of those at greatest risk of death due to the substantial threat of COVID-19 can benefit from novel approaches to epidemiology that leverage large datasets and complex machine-learning models, provide data-driven intelligence, and guide decisions such as intensive-care unit admission (ICUA). The objective of this study is two-fold, one substantive and one methodological: substantively to evaluate the association of demographic and health records with two related, yet different, outcomes of severe COVID-19 (viz., death and ICUA); methodologically to compare interpretations based on logistic regression and on gradient-boosted decision tree (GBDT) predictions interpreted by means of the Shapley impacts of covariates. Very different association of some factors, e.g., obesity and chronic respiratory diseases, with death and ICUA may guide review of practice. Shapley explanation of GBDTs identified varying effects of some factors among patients, thus emphasising the importance of individual patient assessment. The results of this study are also relevant for the evaluation of complex automated clinical decision systems, which should optimise prediction scores whilst remaining interpretable to clinicians and mitigating potential biases. Author summaryThe design is a retrospective cohort study of 13954 in-patients of ages ranging from 1 to 105 year (IQR: 56, 70, 81) with a confirmed diagnosis of COVID-19 by 28th June 2020. This study used multivariable logistic regression to generate odd ratios (ORs) multiply adjusted for 37 covariates (comorbidities, demographic, and others) selected on the basis of clinical interest and prior findings. Results were supplemented by gradient-boosted decision tree (GBDT) classification to generate Shapley values in order to evaluate the impact of the covariates on model output for all patients. Factors are differentially associated with death and ICUA and among patients. @@ -4285,13 +4188,6 @@ MethodsREACT-1 is a series of community surveys of SARS-CoV-2 RT-PCR swab-positi ResultsOverall weighted prevalence of infection in the community in England was 1.3% or 130 people per 10,000 infected, up from 60 people per 10,000 in the round 5 report (18th September to 5th October 2020), doubling every 24 days on average since the prior round. The corresponding R number was estimated to be 1.2. Prevalence of infection was highest in North West (2.4%, up from 1.2%), followed by Yorkshire and The Humber (2.3% up from 0.84%), West Midlands (1.6% up from 0.60%), North East (1.5% up from 1.1%), East Midlands (1.3% up from 0.56%), London (0.97%, up from 0.54%), South West (0.80% up from 0.33%), South East (0.69% up from 0.29%), and East of England (0.69% up from 0.30%). Rapid growth in the South observed in the first half of round 6 was no longer apparent in the second half of round 6. We also observed a decline in prevalence in Yorkshire and The Humber during this period. Comparing the first and second halves of round 6, there was a suggestion of decline in weighted prevalence in participants aged 5 to 12 years and in those aged 25 to 44 years. While prevalence remained high, in the second half of round 6 there was suggestion of a slight fall then rise that was seen nationally and also separately in both the North and the South. ConclusionThe impact of the second national lockdown in England is not yet known. We provide here a detailed description of swab-positivity patterns at national, regional and local scales for the period immediately preceding lockdown, against which future trends in prevalence can be evaluated.",infectious diseases,fuzzy,100,100 -medRxiv,10.1101/2020.11.18.20230649,2020-11-20,https://medrxiv.org/cgi/content/short/2020.11.18.20230649,A network modelling approach to assess non-pharmaceutical disease controls in a worker population: An application to SARS-CoV-2,Edward M Hill; Benjamin D Atkins; Matt J Keeling; Louise Dyson; Michael J Tildesley,University of Warwick; University of Warwick; University of Warwick; University of Warwick; University of Warwick,"BackgroundAs part of a concerted pandemic response to protect public health, businesses can enact non-pharmaceutical controls to minimise exposure to pathogens in workplaces and premises open to the public. Amendments to working practices can lead to the amount, duration and/or proximity of interactions being changed, ultimately altering the dynamics of disease spread. These modifications could be specific to the type of business being operated. - -MethodsWe use a data-driven approach to parameterise an individual-based network model for transmission of SARS-CoV-2 amongst the working population, stratified into work sectors. The network is comprised of layered contacts to consider the risk of spread in multiple encounter settings (workplaces, households, social and other). We analyse several interventions targeted towards working practices: mandating a fraction of the population to work from home; using temporally asynchronous work patterns; and introducing measures to create COVID-secure workplaces. We also assess the general role of adherence to (or effectiveness of) isolation and test and trace measures and demonstrate the impact of all these interventions across a variety of relevant metrics. - -ResultsThe progress of the epidemic can be significantly hindered by instructing a significant proportion of the workforce to work from home. Furthermore, if required to be present at the workplace, asynchronous work patterns can help to reduce infections when compared with scenarios where all workers work on the same days, particularly for longer working weeks. When assessing COVID-secure workplace measures, we found that smaller work teams and a greater reduction in transmission risk reduced the probability of large, prolonged outbreaks. Finally, following isolation guidance and engaging with contact tracing without other measures is an effective tool to curb transmission, but is highly sensitive to adherence levels. - -ConclusionsIn the absence of sufficient adherence to non-pharmaceutical interventions, our results indicate a high likelihood of SARS-CoV-2 spreading widely throughout a worker population. Given the heterogeneity of demographic attributes across worker roles, in addition to the individual nature of controls such as contact tracing, we demonstrate the utility of a network model approach to investigate workplace-targeted intervention strategies and the role of test, trace and isolation in tackling disease spread.",infectious diseases,fuzzy,100,100 medRxiv,10.1101/2020.11.18.20225029,2020-11-20,https://medrxiv.org/cgi/content/short/2020.11.18.20225029,The Invasive Respiratory Infection Surveillance (IRIS) Initiative reveals significant reductions in invasive bacterial infections during the COVID-19 pandemic,Angela B Brueggemann; Melissa J Jansen van Rensburg; David Shaw; Noel D McCarthy; Keith A Jolley; Martin CJ Maiden; Mark PG van der Linden,University of Oxford; University of Oxford; University of Oxford; University of Warwick; University of Oxford; University of Oxford; University Hospital RWTH Aachen,"BackgroundStreptococcus pneumoniae, Haemophilus influenzae and Neisseria meningitidis are leading causes of invasive diseases including bacteraemic pneumonia and meningitis, and of secondary infections post-viral respiratory disease. They are typically transmitted via respiratory droplets. We investigated rates of invasive disease due to these pathogens during the early phase of the COVID-19 pandemic. MethodsLaboratories in 26 countries across six continents submitted data on cases of invasive disease due to S pneumoniae, H influenzae and N meningitidis from 1 January 2018 to 31 May 2020. Weekly cases in 2020 vs 2018-2019 were compared. Streptococcus agalactiae data were collected from nine laboratories for comparison to a non-respiratory pathogen. The stringency of COVID-19 containment measures was quantified by the Oxford COVID-19 Government Response Tracker. Changes in population movements were assessed by Google COVID-19 Community Mobility Reports. Interrupted time series modelling quantified changes in rates of invasive disease in 2020 relative to when containment measures were imposed. @@ -4306,6 +4202,13 @@ MethodsWe investigated the incidence of SARS-CoV-2 PCR-positive results in serop ResultsA total of 12219 HCWs participated and had anti-spike IgG measured, 11052 were followed up after negative and 1246 after positive antibody results including 79 who seroconverted during follow up. 89 PCR-confirmed symptomatic infections occurred in seronegative individuals (0.46 cases per 10,000 days at risk) and no symptomatic infections in those with anti-spike antibodies. Additionally, 76 (0.40/10,000 days at risk) anti-spike IgG seronegative individuals had PCR-positive tests in asymptomatic screening, compared to 3 (0.21/10,000 days at risk) seropositive individuals. Overall, positive baseline anti-spike antibodies were associated with lower rates of PCR-positivity (with or without symptoms) (adjusted rate ratio 0.24 [95%CI 0.08-0.76, p=0.015]). Rate ratios were similar using anti-nucleocapsid IgG alone or combined with anti-spike IgG to determine baseline status. ConclusionsPrior SARS-CoV-2 infection that generated antibody responses offered protection from reinfection for most people in the six months following infection. Further work is required to determine the long-term duration and correlates of post-infection immunity.",infectious diseases,fuzzy,100,100 +medRxiv,10.1101/2020.11.12.20229955,2020-11-15,https://medrxiv.org/cgi/content/short/2020.11.12.20229955,Mobile consulting (mConsulting) as an option for accessing healthcare services for communities in remote rural areas and urban slums in low- and middle- income countries: A mixed methods study,Bronwyn Harris; Motunrayo Ajisola; Raisa Alam; Jocelyn Antsley Watkins; Theodoros N Arvanitis; Pauline Bakibinga; Beatrice Chipwaza; Nazratun Nayeem Choudhury; Olufunke Fayhun; Peter Kibe; Akinyinka Omigbodun; Eme Owoaje; Senga Pemba; Rachel Potter; Narjis Rizvi; Jackie Sturt; Jonathan A.K Cave; Romaina Iqbal; Caroline Kabaria; Albino Kalolo; Catherine Kyobutungi; Richard J Lilford; Titus Mashanya; Sylvester Ndegese; Omar Rahman; Saleem Sayani; Rita Yusuf; Frances Griffiths,"Warwick Medical School, University of Warwick, UK; Department of Sociology, Faculty of Social Sciences, University of Ibadan, Ibadan, Oyo State, Nigeria; Centre for Health, Population and Development, Independent University Bangladesh, Dhaka, Bangladesh; Warwick Medical School, University of Warwick, UK; Institute of Digital Healthcare, WMG, University of Warwick, UK; African Population and Health Research Center, Nairobi, Kenya; St Francis University College of Health and Allied Sciences, Tanzania; Centre for Health, Population and Development, Independent University Bangladesh, Dhaka, Bangladesh; Department of Sociology, Faculty of Social Sciences, University of Ibadan, Ibadan, Oyo State, Nigeria; African Population and Health Research Center, Nairobi, Kenya; Department of Obstetrics and Gynaecology, Faculty of Clinical Sciences, College of Medicine, University of Ibadan, Ibadan, Oyo State, Nigeria; Department of Community Medicine, Faculty of Public Health, College of Medicine, University of Ibadan, Ibadan, Oyo State, Nigeria; St Francis University College of Health and Allied Sciences, Tanzania; Clinical Trials Unit Warwick Medical School, University of Warwick, University of Warwick, UK; Community Health Sciences Department, Aga Khan University, Karachi, Pakistan; King's College London, Florence Nightingale Faculty of Nursing and Midwifery, London, UK; Department of Economics, University of Warwick, UK; Community Health Sciences Department, Aga Khan University, Karachi, Pakistan; African Population and Health Research Center, Nairobi, Kenya; St Francis University College of Health and Allied Sciences, Tanzania; African Population and Health Research Center, Nairobi, Kenya; Institute of Applied Health Research, College of Medical and Dental Sciences, University of Birmingham, Birmingham, UK; St Francis University College of Health and Allied Sciences, Tanzania; St Francis University College of Health and Allied Sciences, Tanzania; University of Liberal Arts Bangladesh, Dhaka, Bangladesh; Aga Khan Development Network Digital Health Resource Centre (Asia and Africa), Aga Khan University, Karachi, Pakistan; Centre for Health, Population and Development, Independent University Bangladesh, Dhaka, Bangladesh; Warwick Medical School, University of Warwick, UK","ObjectiveRemote or mobile consulting (mConsulting) is being promoted to strengthen health systems, deliver universal health coverage and facilitate safe clinical communication during COVID-19 and beyond. We explored whether mConsulting is a viable option for communities with minimal resources in low- and middle-income countries (LMICs). + +MethodsWe reviewed evidence published since 2018 about mConsulting in LMICs and undertook a scoping study (pre-COVID) in two rural settings (Pakistan, Tanzania) and five urban slums (Kenya, Nigeria, Bangladesh), using policy/document review, secondary analysis of survey data (from the urban sites), and thematic analysis of interviews/workshops with community members, healthcare workers, digital/telecommunications experts, mConsulting providers, local and national decision-makers. Project advisory groups guided the study in each country. + +ResultsWe reviewed five empirical studies and seven reviews, analysed data from 5,219 urban slum households and engaged with 419 stakeholders in rural and urban sites. Regulatory frameworks are available in each country. mConsulting services are operating through provider platforms (n=5-17) and, at community-level, some direct experience of mConsulting with healthcare workers using their own phones was reported - for emergencies, advice and care follow-up. Stakeholder willingness was high, provided challenges are addressed in technology, infrastructure, data security, confidentiality, acceptability and health system integration. mConsulting can reduce affordability barriers and facilitate care-seeking practices. + +ConclusionsThere are indications of readiness for mConsulting in communities with minimal resources. However, wider system strengthening is needed to bolster referrals, specialist services, laboratories and supply-chains to fully realise the continuity of care and responsiveness that mConsulting services offer, particularly during/beyond COVID-19.",public and global health,fuzzy,100,100 medRxiv,10.1101/2020.11.10.20229146,2020-11-13,https://medrxiv.org/cgi/content/short/2020.11.10.20229146,"Awareness, knowledge and trust in the Greek authorities towards COVID-19 pandemic: results from the Epirus Health Study cohort",Afroditi Kanellopoulou; Fotios Koskeridis; Georgios Markozannes; Emmanouil Bouras; Chrysa Soutziou; Konstantinos Chaliasos; Michail T Doumas; Dimitrios E Sigounas; Vasilios T Tzovaras; Agapios Panos; Yiolanda Stergiou; Kassiani Mellou; Dimitrios Papamichail; Eleni Aretouli; Dimitrios Chatzidimitriou; Fani Chatzopoulou; Eleni Bairaktari; Ioanna Tzoulaki; Evangelos Evangelou; Evangelos C Rizos; Evangelia Ntzani; Konstantinos Vakalis; Konstantinos K Tsilidis,"University of Ioannina; University of Ioannina; University of Ioannina; University of Ioannina, Aristotle University of Thessaloniki; Ioannina Medical Care; University of Ioannina; Ioannina Medical Care; Ioannina Medical Care; Ioannina Medical Care; University of Ioannina; University of Ioannina; Hellenic National Public Health Organization; University of West Attica; University of Ioannina, Aristotle University of Thessaloniki; Aristotle University of Thessaloniki; Aristotle University of Thessaloniki; University of Ioannina; University of Ioannina, Imperial College London; University of Ioannina, Imperial College London; University Hospital of Ioannina, European University of Cyprus; University of Ioannina, Brown University; Ioannina Medical Care; University of Ioannina, Imperial College London","BackgroundTo assess the level of knowledge and trust in the policy decisions taken regarding the coronavirus disease (COVID-19) pandemic among Epirus Health Study (EHS) participants. MethodsThe EHS is an ongoing and deeply-phenotyped prospective cohort study that has recruited 667 participants in northwest Greece until August 31st, 2020. Level of knowledge on coronavirus (SARS-CoV-2) transmission and COVID-19 severity was labeled as poor, moderate or good. Variables assessing knowledge and beliefs towards the pandemic were summarized overall and by gender, age group (25-39, 40-49, 50-59, [≥]60 years) and period of report (before the lifting of lockdown measures in Greece: March 30th to May 3rd, and two post-lockdown time periods: May 4th to June 31st, July 1st to August 31st). An exposure-wide association analysis was conducted to evaluate the associations between 153 explanatory variables and participants knowledge. Correction for multiple comparisons was applied using a false discovery rate (FDR) threshold of 5%. @@ -4329,6 +4232,14 @@ Added value of this studyHere we provide the first longitudinal national probabi Implications of all the available evidenceThis study documents an alarming increase in food insecurity in the United Kingdom during the pandemic, with important implications for policy. While Coronavirus the Job Retention Scheme appeared to have conferred some protection, it is clear that not enough has been done to mitigate overall increases food insecurity in the UK. Steps are needed to provide subsidies or food support, especially since during the pandemic emergency food assistance may not be readily accessible. Taken together our results show that, while COVID is first of all a health crisis, it also has potential to become an escalating social and economic crisis if steps are not taken to protect the weak. C_TEXTBOX",public and global health,fuzzy,100,100 +medRxiv,10.1101/2020.11.11.20220962,2020-11-13,https://medrxiv.org/cgi/content/short/2020.11.11.20220962,Short-term forecasts to inform the response to the COVID-19 epidemic in the UK,Sebastian Funk; Sam Abbott; Benjamin D Atkins; Marc Baguelin; J Kenneth Baillie; Paul J Birrell; Joshua Blake; Nikos I Bosse; Joshua Burton; Jonathan Carruthers; Nicholas G Davies; Daniela de Angelis; Louise Dyson; W. John Edmunds; Rosalind M Eggo; Neil M Ferguson; Katy A M Gaythorpe; Erin Gorsich; Glen Guyver-Fletcher; Joel Hellewell; Edward M Hill; Alexander Holmes; Thomas A House; Chris Jewell; Mark Jit; Thibaut Jombart; Indra Joshi; Matt J Keeling; Edward Kendall; Edward S Knock; Adam J Kucharski; Katrina A Lythgoe; Sophie R Meakin; James D Munday; Peter JM Openshaw; Christopher Overton; Filippo Pagani; Jonathan Pearson; Pablo N Perez-Guzman; Lorenzo Pellis; Francesca Scarabel; Malcolm Gracie Semple; Ming Tang; Michael Tildesley; Edwin van Leeuwen; Lilith Whittles; - CMMID COVID-19 Working Group; - Imperial College COVID-19 Response Team; - ISARIC4C Investigators,"London School of Hygiene & Tropical Medicine; London School of Hygiene & Tropical Medicine; University of Warwick; Imperial College; Roslin Institute, University of Edinburgh; Public Health England; University of Cambridge; London School of Hygiene & Tropical Medicine; University of Manchester; Public Health England; London School of Hygiene and Tropical Medicine; University of Cambridge; University of Warwick; London School of Hygiene & Tropical Medicine; London School of Hygiene & Tropical Medicine; Imperial College; Imperial College London; University of Warwick; University of Warwick; London School of Hygiene & Tropical Medicine; University of Warwick; University of Warwick; University of Manchester; Lancaster University; London School of Hygiene & Tropical Medicine; London School of Hygiene & Tropical Medicine; NHSX; University of Warwick; NHS England & NHS Improvement; Imperial College; London School of Hygiene & Tropical Medicine; University of Oxford; London School of Hygiene & Tropical Medicine; London School of Hygiene and Tropical Medicine; Imperial College London; Manchester University; Manchester University; NHSX; Imperial College; The University of Manchester; York University; University of Liverpool; NHS England & NHSE Improvement; University of Warwick; Public Health England; Imperial College; ; ; ","BackgroundShort-term forecasts of infectious disease can aid situational awareness and planning for outbreak response. Here, we report on multi-model forecasts of Covid-19 in the UK that were generated at regular intervals starting at the end of March 2020, in order to monitor expected healthcare utilisation and population impacts in real time. + +MethodsWe evaluated the performance of individual model forecasts generated between 24 March and 14 July 2020, using a variety of metrics including the weighted interval score as well as metrics that assess the calibration, sharpness, bias and absolute error of forecasts separately. We further combined the predictions from individual models into ensemble forecasts using a simple mean as well as a quantile regression average that aimed to maximise performance. We compared model performance to a null model of no change. + +ResultsIn most cases, individual models performed better than the null model, and ensembles models were well calibrated and performed comparatively to the best individual models. The quantile regression average did not noticeably outperform the mean ensemble. + +ConclusionsEnsembles of multi-model forecasts can inform the policy response to the Covid-19 pandemic by assessing future resource needs and expected population impact of morbidity and mortality.",epidemiology,fuzzy,100,100 +medRxiv,10.1101/2020.11.09.20228015,2020-11-12,https://medrxiv.org/cgi/content/short/2020.11.09.20228015,A time-resolved proteomic and diagnostic map characterizes COVID-19 disease progression and predicts outcome,Vadim Demichev; Pinkus Tober-Lau; Tatiana Nazarenko; Charlotte Thibeault; Harry Whitwell; Oliver Lemke; Annika Röhl; Anja Freiwald; Lukasz Szyrwiel; Daniela Ludwig; Clara Correia-Melo; Elisa Theresa Helbig; Paula Stubbemann; Nana-Maria Grüning; Oleg Blyuss; Spyros Vernardis; Matthew White; Christoph B. Messner; Michael Joannidis; Thomas Sonnweber; Sebastian J. Klein; Alex Pizzini; Yvonne Wohlfarter; Sabina Sahanic; Richard Hilbe; Benedikt Schaefer; Sonja Wagner; Mirja Mittermaier; Felix Machleidt; Carmen Garcia; Christoph Ruwwe-Glösenkamp; Tilman Lingscheid; Laure Bosquillon de Jarcy; Miriam S. Stegemann; Moritz Pfeiffer; Linda Jürgens; Sophy Denker; Daniel Zickler; Philipp Enghard; Aleksej Zelezniak; Archie Campbell; Caroline Hayward; David J. Porteous; Riccardo Marioni; Alexander Uhrig; Holger Müller-Redetzky; Heinz Zoller; Judith Löffler-Ragg; Markus A. Keller; Ivan Tancevski; John F. Timms; Alexey Zaikin; Stefan Hippenstiel; Michael Ramharter; Martin Witzenrath; Norbert Suttorp; Kathryn Lilley; Michael Mülleder; Leif Erik Sander; - PA-COVID-19 Study group; Markus Ralser; Florian Kurth,The Francis Crick Institute; Charité - Universitätsmedizin Berlin; University College London; Charite Universitaetsmedizin Berlin; Imperial College London; Charité - Universitätsmedizin Berlin; Charité - Universitätsmedizin Berlin; Charité - Universitätsmedizin Berlin; The Francis Crick Institute; Charité - Universitätsmedizin Berlin; The Francis Crick Institute; Charité - Universitätsmedizin Berlin; Charité - Universitätsmedizin Berlin; Charité - Universitätsmedizin Berlin; Lobachevsky University; The Francis Crick Institute; The Francis Crick Institute; Charité - Universitätsmedizin Berlin; Medical University of Innsbruck; Medical University of Innsbruck; Medical University of Innsbruck; Medical University of Innsbruck; Medical University of Innsbruck; Medical University of Innsbruck; Medical University of Innsbruck; Medical University of Innsbruck; Medical University of Innsbruck; Charité - Universitätsmedizin Berlin; Charité - Universitätsmedizin Berlin; Charité - Universitätsmedizin Berlin; Charité - Universitätsmedizin Berlin; Charité - Universitätsmedizin Berlin; Charité - Universitätsmedizin Berlin; Charité - Universitätsmedizin Berlin; Charité - Universitätsmedizin Berlin; Charité - Universitätsmedizin Berlin; Charité - Universitätsmedizin Berlin; Charité - Universitätsmedizin Berlin; Charité - Universitätsmedizin Berlin; The Francis Crick Institute; The University of Edinburgh; The University of Edinburgh; The University of Edinburgh; University of Edinburgh; Charité - Universitätsmedizin Berlin; Charité - Universitätsmedizin Berlin; Medical University of Innsbruck; Medical University of Innsbruck; Medical University of Innsbruck; Medical University of Innsbruck; University College London; University College London; Charité - Universitätsmedizin Berlin; Bernhard Nocht Institute for Tropical Medicine; Charité - Universitätsmedizin Berlin; Charité - Universitätsmedizin Berlin; The University of Cambridge; Charité - Universitätsmedizin Berlin; Charité - Universitätsmedizin Berlin; ; Charite University Medicine; Charité - Universitätsmedizin Berlin,"COVID-19 is highly variable in its clinical presentation, ranging from asymptomatic infection to severe organ damage and death. There is an urgent need for predictive markers that can guide clinical decision-making, inform about the effect of experimental therapies, and point to novel therapeutic targets. Here, we characterize the time-dependent progression of COVID-19 through different stages of the disease, by measuring 86 accredited diagnostic parameters and plasma proteomes at 687 sampling points, in a cohort of 139 patients during hospitalization. We report that the time-resolved patient molecular phenotypes reflect an initial spike in the systemic inflammatory response, which is gradually alleviated and followed by a protein signature indicative of tissue repair, metabolic reconstitution and immunomodulation. Further, we show that the early host response is predictive for the disease trajectory and gives rise to proteomic and diagnostic marker signatures that classify the need for supplemental oxygen therapy and mechanical ventilation, and that predict the time to recovery of mildly ill patients. In severely ill patients, the molecular phenotype of the early host response predicts survival, in two independent cohorts and weeks before outcome. We also identify age-specific molecular response to COVID-19, which involves increased inflammation and lipoprotein dysregulation in older patients. Our study provides a deep and time resolved molecular characterization of COVID-19 disease progression, and reports biomarkers for risk-adapted treatment strategies and molecular disease monitoring. Our study demonstrates accurate prognosis of COVID-19 outcome from proteomic signatures recorded weeks earlier.",infectious diseases,fuzzy,100,100 medRxiv,10.1101/2020.11.05.20226662,2020-11-07,https://medrxiv.org/cgi/content/short/2020.11.05.20226662,Risk mitigating behaviours in people with inflammatory joint and skin disease during the COVID-19 pandemic differ by treatment type: a cross-sectional patient survey,Satveer K Mahil; Mark Yates; Sinead M Langan; Zenas ZN Yiu; Teresa Tsakok; Nick Dand; Kayleigh J Mason; Helen McAteer; Freya Meynall; Bolaji Coker; Alexandra Vincent; Dominic Urmston; Amber Vesty; Jade Kelly; Camille Lancelot; Lucy Moorhead; Herve Bachelez; Ian N Bruce; Francesca Capon; Claudia Romina Contreras; Andrew P Cope; Claudia De La Cruz; Paola Di Meglio; Paolo Gisondi; Kimme Hyrich; Denis Jullien; Jo Lambert; Hoseah Waweru; Helena Marzo-Ortega; Iain McInnes; Luigi Naldi; Sam Norton; Lluis Puig; Phyllis Spuls; Raj Sengupta; Tiago Torres; RIchard B Warren; John Weinman; Christopher EM Griffiths; Jonathan N Barker; Matthew A Brown; James B Galloway; Catherine H Smith,"St Johns Institute of Dermatology; Centre for Rheumatic Diseases, King's College London; St Johns Institute of Dermatology; Dermatology Centre, Salford Royal NHS Foundation Trust, The University of Manchester, Manchester Academic Health Science Centre, NIHR Manchester Biomedical Rese; St Johns Institute of Dermatology; Department of Medical and Molecular Genetics, School of Basic and Medical Biosciences, Faculty of Life Sciences and Medicine, Kings College London, London, UK. ; Dermatology Centre, Salford Royal NHS Foundation Trust, The University of Manchester, Manchester Academic Health Science Centre, NIHR Manchester Biomedical Rese; The Psoriasis Association, Northampton, UK; St Johns Institute of Dermatology; NIHR Biomedical Research Centre at Guys and St Thomas NHS Foundation Trust and Kings College London, London, UK; NIHR Biomedical Research Centre at Guys and St Thomas NHS Foundation Trust and Kings College London, London, UK; The Psoriasis Association, Northampton, UK; The Psoriasis Association, Northampton, UK; Dermatology Centre, Salford Royal NHS Foundation Trust, The University of Manchester, Manchester Academic Health Science Centre, NIHR Manchester Biomedical Rese; International Federation of Psoriasis Associations; St Johns Institute of Dermatology; Department of Dermatology, AP-HP Hopital Saint-Louis, Paris, France 12INSERM U1163, Imagine Institute for Human Genetic Diseases, Universite de Paris, Paris, Fr; Kellegren Centre for Rheumatology, NIHR Manchester Biomedical Research Centre, Manchester University NHS Foundation Trust, Manchester Academic Health Science Ce; Department of Medical and Molecular Genetics, School of Basic and Medical Biosciences, Faculty of Life Sciences and Medicine, Kings College London, London, UK; Catedra de Dermatologia, Hospital de Clinicas, Facultad de Ciencias Medicas, Universidad Nacional de Asuncion, Paraguay; Centre for Rheumatic Diseases, Kings College London; Clinica Dermacross, Santiago, Chile; NIHR Biomedical Research Centre at Guys and St Thomas NHS Foundation Trust and Kings College London, London, UK; Section of Dermatology and Venereology, University of Verona, Verona, Italy; Kellegren Centre for Rheumatology, NIHR Manchester Biomedical Research Centre, Manchester University NHS Foundation Trust, Manchester Academic Health Science Ce; Department of Dermatology, Edouard Herriot Hospital, Hospices Civils de Lyon, University of Lyon, Lyon, France Groupe de recherche sur le psoriasis (GrPso) de l; Department of Dermatology, Ghent University, Ghent, Belgium; International Federation of Psoriasis Associations Bromma, Sweden; University of Leeds Leeds Institute of Rheumatic and Musculoskeletal Medicine, Section of Musculoskeletal Disease Leeds, West Yorkshire, UK; University of Glasgow, Institute of Infection, Immunity and Inflammation; Centro Studi GISED Bergamo, Italy; Centre for Rheumatic Diseases, Kings College London; Hospital de la Santa Creu i Sant Pau, Dermatology Barcelona, Spain; Amsterdam University Medical Centres, Department of Dermatology, Amsterdam Public Health/Infection and Immunology; Royal National Hospital for Rheumatic Diseases, Bath; Centro Hospitalar do Porto, Portugal; The University of Manchester, Dermatology Centre, Salford Royal NHS Foundation Trust Manchester, Manchester, UK; Kings College London, Institute of Pharmaceutical Sciences London, London, UK; The University of Manchester, Dermatology Centre, Salford Royal NHS Foundation Trust Manchester, Manchester, UK; St Johns Institute of Dermatology; NIHR Biomedical Research Centre at Guys and Saint Thomas NHS Foundation Trust and Kings College London, UK; Centre for Rheumatic Diseases, Kings College London; St Johns Institute of Dermatology","ObjectivesRegistry data suggest that people with immune-mediated inflammatory diseases (IMIDs) receiving targeted systemic therapies have fewer adverse COVID-19 outcomes compared to patients receiving no systemic treatments. We used international patient survey data to explore the hypothesis that greater risk-mitigating behaviour in those receiving targeted therapies may account, at least in part, for this observation. MethodsOnline surveys were completed by individuals with Rheumatic and Musculoskeletal Diseases (RMD) (UK only) or psoriasis (globally) between 4th May and 7th September 2020. We used multiple logistic regression to assess the association between treatment type and risk-mitigating behaviour, adjusting for clinical and demographic characteristics. We characterised international variation in a mixed effects model. @@ -4433,7 +4344,6 @@ RESULTS IN CONTEXTO_ST_ABSEvidence before this studyC_ST_ABSA small study in 47 Added value of this studyTo our knowledge this is the first study to explore changes in healthcare contacts for acute physical and mental health conditions in a large population representative of the UK. We used electronic primary care health records of nearly 10 million individuals across the UK to investigate the indirect impact of COVID-19 on primary care contacts for mental health, acute alcohol-related events, asthma/chronic obstructive pulmonary disease (COPD) exacerbations, and cardiovascular and diabetic emergencies up to July 2020. For all conditions studied, we found primary care contacts dropped dramatically following the introduction of population-wide restriction measures in March 2020. By July 2020, with the exception of unstable angina and acute alcohol-related events, primary care contacts for all conditions studied had not recovered to pre-lockdown levels. In the general population, estimates of the absolute reduction in the number of primary care contacts up to July 2020, compared to what we would expect from previous years varied from fewer than 10 contacts per million for some cardiovascular outcomes, to 12,800 per million for depression and 6,600 for anxiety. In people with COPD, we estimated there were 43,900 per million fewer contacts for COPD exacerbations up to July 2020 than what we would expect from previous years. Implicatins of all the available evidenceWhile our results may represent some genuine reduction in disease frequency (e.g. the restriction measures may have improved diabetic glycaemic control due to more regular daily routines at home), it is more likely the reduced primary care conatcts we saw represent a substantial burden of unmet need (particularly for mental health conditions) that may be reflected in subsequent increased mortality and morbidity. Health service providers should take steps to prepare for increased demand in the coming months and years due to the short and longterm ramifications of reduced access to care for severe acute physical and mental health conditions. Maintaining access to primary care is key to future public health planning in relation to the pandemic.",primary care research,fuzzy,100,100 -bioRxiv,10.1101/2020.10.26.356014,2020-10-28,https://biorxiv.org/cgi/content/short/2020.10.26.356014,"COVID-19 Disease Map, a computational knowledge repository of SARS-CoV-2 virus-host interaction mechanisms",Marek Ostaszewski; Anna Niarakis; Alexander Mazein; Inna Kuperstein; Robert Phair; Aurelio Orta-Resendiz; Vidisha Singh; Sara Sadat Aghamiri; Marcio Luis Acencio; Enrico Glaab; Andreas Ruepp; Gisela Fobo; Corinna Montrone; Barbara Brauner; Goar Frishman; Julia Somers; Matti Hoch; Shailendra Kumar Gupta; Julia Scheel; Hanna Borlinghaus; Tobias Czauderna; Falk Schreiber; Arnau Montagud; Miguel Ponce de Leon; Akira Funahashi; Yusuke Hiki; Noriko Hiroi; Takahiro G Yamada; Andreas Drager; Alina Renz; Muhammad Naveez; Zsolt Bocskei; Daniela Bornigen; Liam Fergusson; Marta Conti; Marius Rameil; Vanessa Nakonecnij; Jakob Vanhoefer; Leonard Schmiester; Muying Wang; Emily E Ackerman; Jason E Shoemaker; Jeremy Zucker; Kristie L Oxford; Jeremy Teuton; Ebru Kocakaya; Gokce Yagmur Summak; Kristina Hanspers; Martina Kutmon; Susan Coort; Lars Eijssen; Friederike Ehrhart; Rex D. A. B.; Denise Slenter; Marvin Martens; Nhung Pham; Robin Haw; Bijay Jassal; Lisa Matthews; Marija Orlic-Milacic; Andrea Senff-Ribeiro; Karen Rothfels; Veronica Shamovsky; Ralf Stephan; Cristoffer Sevilla; Thawfeek Mohamed Varusai; Jean-Marie Ravel; Vera Ortseifen; Silvia Marchesi; Piotr Gawron; Ewa Smula; Laurent Heirendt; Venkata Satagopam; Guanming Wu; Anders Riutta; Martin Golebiewski; Stuart Owen; Carole Goble; Xiaoming Hu; Rupert Overall; Dieter Maier; Angela Bauch; Benjamin M Gyori; John A Bachman; Carlos Vega; Valentin Groues; Miguel Vazquez; Pablo Porras; Luana Licata; Marta Iannuccelli; Francesca Sacco; Denes Turei; Augustin Luna; Ozgun Babur; Sylvain Soliman; Alberto Valdeolivas; Marina Esteban-Medina; Maria Pena-Chilet; Kinza Rian; Tomas Helikar; Bhanwar Lal Puniya; Anastasia Nesterova; Anton Yuryev; Anita de Waard; Dezso Modos; Agatha Treveil; Marton Laszlo Olbei; Bertrand De Meulder; Aurelien Naldi; Aurelien Dugourd; Laurence Calzone; Chris Sander; Emek Demir; Tamas Korcsmaros; Tom C Freeman; Franck Auge; Jacques S Beckmann; Jan Hasenauer; Olaf Wolkenhauer; Egon Willighagen; Alexander R Pico; Chris Evelo; Lincoln D Stein; Henning Hermjakob; Julio Saez-Rodriguez; Joaquin Dopazo; Alfonso Valencia; Hiroaki Kitano; Emmanuel Barillot; Charles Auffray; Rudi Balling; Reinhard Schneider; - the COVID-19 Disease Map Community,"Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg; Department of Biology, Univ. Evry, University of Paris-Saclay, GenHotel, Genopole, 91025, Evry, France; Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg; Institut Curie, PSL Research University, Paris, France.; Integrative Bioinformatics, Inc., 346 Paul Ave, Mountain View, CA, USA; Institut Pasteur, HIV, Inflammation and Persistence Unit, Paris, France; Laboratoire Europeen de Recherche pour la Polyarthrite Rhumatoide - Genhotel, Univ Evry, Universite Paris-Saclay, 2, rue Gaston Cremieux, 91057 EVRY-GENOPOLE ce; Inserm- Institut national de la sante et de la recherche medicale. Saint-Louis Hospital 1 avenue Claude Vellefaux Pavillon Bazin 75475 Paris; Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg; Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg; Institute of Experimental Genetics (IEG), Helmholtz Zentrum Munchen-German Research Center for Environmental Health (GmbH), Ingolstadter Landstrasse 1, D-85764 ; Institute of Experimental Genetics (IEG), Helmholtz Zentrum Munchen-German Research Center for Environmental Health (GmbH), Ingolstadter Landstrasse 1, D-85764 ; Institute of Experimental Genetics (IEG), Helmholtz Zentrum Munchen-German Research Center for Environmental Health (GmbH), Ingolstadter Landstrasse 1, D-85764 ; Institute of Experimental Genetics (IEG), Helmholtz Zentrum Munchen-German Research Center for Environmental Health (GmbH), Ingolstadter Landstrasse 1, D-85764 ; Institute of Experimental Genetics (IEG), Helmholtz Zentrum Munchen-German Research Center for Environmental Health (GmbH), Ingolstadter Landstrasse 1, D-85764 ; Oregong Health & Sciences Univerity; Department of Molecular and Medical Genetics; 3222 SW Research Drive, Portland, Oregon, U.S.A 97239; Department of Systems Biology and Bioinformatics, University of Rostock, 18051 Rostock, Germany; Department of Systems Biology and Bioinformatics, University of Rostock, 18051 Rostock, Germany; Department of Systems Biology and Bioinformatics, University of Rostock, 18051 Rostock, Germany; Department of Computer and Information Science, University of Konstanz, Konstanz, Germany; Monash University, Faculty of Information Technology, Department of Human-Centred Computing, Wellington Rd, Clayton VIC 3800, Australia; Department of Computer and Information Science, University of Konstanz, Konstanz, Germany; Barcelona Supercomputing Center (BSC), Barcelona, Spain; Barcelona Supercomputing Center (BSC), Barcelona, Spain; Keio University, Department of Biosciences and Informatics, 3-14-1 Hiyoshi Kouhoku-ku Yokohama Japan 223-8522; Keio University, Department of Biosciences and Informatics, 3-14-1 Hiyoshi Kouhoku-ku Yokohama Japan 223-8522; Sanyo-Onoda City University, Faculty of Pharmaceutical Sciences, University St.1-1-1, Yamaguchi, Japan 756-0884; Keio University, Department of Biosciences and Informatics, 3-14-1 Hiyoshi Kouhoku-ku Yokohama Japan 223-8522; Computational Systems Biology of Infections and Antimicrobial-Resistant Pathogens, Institute for Bioinformatics and Medical Informatics (IBMI), University of Tu; Computational Systems Biology of Infections and Antimicrobial-Resistant Pathogens, Institute for Bioinformatics and Medical Informatics (IBMI), University of Tu; Riga Technical University, Institute of Applied Computer Systems,1 Kalku Street, LV-1658 Riga, Latvia; Sanofi R&D Translational Sciences; Bioinformatics Core Facility, Universitaetsklinikum Hamburg-Eppendorf, Martinistrasse 52, 20246 Hamburg, Germany; The University of Edinburgh, Royal (Dick) School of Veterinary Medicine, Easter Bush Campus, Midlothian, EH25 9RG; Faculty of Mathematics and Natural Sciences, University of Bonn, Bonn, Germany; University of Bonn, Germany; Faculty of Mathematics and Natural Sciences, University of Bonn, Bonn, Germany; Faculty of Mathematics and Natural Sciences, University of Bonn, Bonn, Germany; Helmholtz Zentrum Munchen - German Research Center for Environmental Health, Institute of Computational Biology, 85764 Neuherberg, Germany; Department of Chemical Engineering, University of Pittsburgh; University of Pittsburgh, Department of Chemical and Petroleum Engineering; Dept. of Chemical & Petroleum Engineering, University of Pittsburgh; Pacific Northwest National Laboratory; Pacific Northwest National Laboratory; Pacific Northwest National Laboratory; Ankara University, Stem Cell Institute, Ceyhun Atif Kansu St. No: 169 06520 Cevizlidere/ANKARA/TURKEY; Ankara University, Stem Cell Institute, Ceyhun Atif Kansu St. No: 169 06520 Cevizlidere/ANKARA/TURKEY; Institute of Data Science and Biotechnology, Gladstone Institutes, San Francisco, CA 94158; Department of Bioinformatics - BiGCaT, NUTRIM, Maastricht University, Maastricht, The Netherlands; Maastricht University, NUTRIM, Bioinformatics-BiGCaT, PO Box 616, 6200 MD, Maastricht, the Netherlands; Department of Bioninformatics-BiGCaT, NUTRIM, Maastricht University, Universiteitssingel 60, 6229 ER Maastricht, The Netherlands; Maastricht University, Department of Bioinformatics, NUTRIM, Universiteitssingel 60; 6229 ER Maastricht; The Netherlands; Center for Systems Biology and Molecular Medicine, Yenepoya (Deemed to be University), Mangalore 575018, India; Department of Bioinformatics-BiGCaT, NUTRIM, Maastricht University, Maastricht, The Netherlands; Department of Bioinformatics - BiGCaT, NUTRIM, Maastricht University, 6229 ER Maastricht, The Netherlands; Maastricht University, NUTRIM, Bioinformatics-BiGCaT, PO Box 616, 6200 MD, Maastricht, the Netherlands; Adaptive Oncology, Ontario Institute for Cancer Research, MaRS Centre, 661 University Avenue, Suite 510, Toronto, Ontario, Canada M5G 0A3; Ontario Institute for Cancer Research (OICR), 661 University Ave Suite 510, Toronto, ON M5G 0A3, Canada; NYU Grossman School of Medicine, New York NY 10016 USA; Ontario Institute for Cancer Research, Department of Computational Biology, MaRS Centre, South Tower, 661 University Avenue, Suite 500, Toronto, Ontario, Canada; Ontario Institute for Cancer Research (OICR) (Canada); Ontario Institute for Cancer Research, Department of Computational Biology, MaRS Centre, South Tower, 661 University Avenue, Suite 500, Toronto, Ontario, Canada; NYU Langone Medical Center, New York, USA; Ontario Institute for Cancer Research, MaRS Centre, 661 University Ave, Suite 510, Toronto, Ontario, Canada; EMBL-EBI, Molecular Systems, Wellcome Genome Campus, Hinxton, Cambridgeshire, CB10 1SD; Reactome, EMBL-EBI, Cambridge, UK; University of Lorraine, INSERM UMR_S 1256, Nutrition, Genetics, and Environmental Risk Exposure (NGERE), Faculty of Medicine of Nancy, F-54000 Nancy, France.; Senior Research Group in Genome Research of Industrial Microorganisms, Center for Biotechnology, Bielefeld University, Universitaetsstrasse 27, 33615 Bielefeld,; Uppsala University - Sweden; Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg; Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg; Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg; Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg; Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University, 3181 S.W. Sam Jackson Park Road, Portland, OR 97239-3098, USA; Gladstone Institutes, Institute for Data Science and Biotechnology, 1650 Owens St., San Francisco, CA 94131, USA; Heidelberg Institute for Theoretical Studies (HITS), Schloss-Wolfsbrunnenweg 35, D-69118 Heidelberg (Germany); The University of Manchester, Department of Computer Science, Oxford Road, Manchester, M13 9PL, UK; The University of Manchester, Department of Computer Science, Oxford Road, Manchester, M13 9PL, UK; Heidelberg Institute for Theoretical Studies (HITS), Schloss-Wolfsbrunnenweg 35, D-69118 Heidelberg (Germany); German Center for Neurodegenerative Diseases (DZNE) Dresden, Tatzberg 41, 01307 Dresden, Germany.; Biomax Informatics AG, Robert-Koch-Str. 2, 82152 Planegg, Germany; Biomax Informatics AG, Robert-Koch-Str. 2, 82152 Planegg, Germany; Harvard Medical School, Laboratory of Systems Pharmacology, 200 Longwood Avenue, Boston, MA; Harvard Medical School, Laboratory of Systems Pharmacology, 200 Longwood Avenue, Boston, MA; Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg; Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg; Barcelona Supercomputing Center (BSC), Barcelona, Spain; EMBL-EBI, Molecular Systems, Wellcome Genome Campus, CB10 1SD, Hinxton, UK; University of Rome Tor Vergata, Department of Biology, Via della Ricerca Scientifica 1, 00133 Rome, Italy; University of Rome Tor Vergata, Department of Biology, Via della Ricerca Scientifica 1, 00133 Rome, Italy; University of Rome Tor Vergata, Department of Biology, Via della Ricerca Scientifica 1, 00133 Rome, Italy; Heidelberg Univarsity, Institute for Computational Biomedicine, BQ 0053, Im Neuenheimer Feld 267, 69120 Heidelberg, Germany; cBio Center, Divisions of Biostatistics and Computational Biology, Department of Data Sciences, Dana-Farber Cancer Institute, Boston, MA, 02215, USA.; University of Massachusetts Boston, Computer Science Department, 100 William T, Morrissey Blvd, Boston, MA 02125; Inria Saclay Ile-de-France; Heidelberg University, Faculty of Medicine and Heidelberg University Hospital, Institute of Computational Biomedicine, Bioquant, 69120 Heidelberg, Germany; Clinical Bioinformatics Area. Fundacion Progreso y Salud (FPS). CDCA, Hospital Virgen del Rocio, 41013, Sevilla, Spain.; Clinical Bioinformatics Area. Fundacion Progreso y Salud (FPS). CDCA, Hospital Virgen del Rocio, 41013, Sevilla, Spain.; Clinical Bioinformatics Area. Fundacion Progreso y Salud (FPS). CDCA, Hospital Virgen del Rocio, 41013, Sevilla, Spain.; University of Nebraska-Lincoln, Department of Biochemistry, 1901 Vine St., Lincoln, NE, 68588, USA; University of Nebraska-Lincoln, Department of Biochemistry, 1901 Vine St., Lincoln, NE, 68588, USA; Elsevier, Life Science Department; Elsevier, Professional Services, 1600 John F Kennedy Blvd #1800, Philadelphia, PA 19103; Elsevier, Research Collaborations Unit, 71 Hanley Lane, Jericho, VT 05465; Quadram Institute Bioscience, Rosalind Franklin Road, Norwich Research Park, Norwich, NR4 7UQ, United Kingdom; Earlham Institute, Norwich Research Park, Norwich, NR4 7UZ, United Kingdom; Earlham Institute, Norwich Research Park, Norwich, NR4 7UZ, United Kingdom; Association EISBM; Inria Saclay - Ile de France, Lifeware group, 91120 Palaiseau, France; Heidelberg University, Faculty of Medicine, and Heidelberg University Hospital, Institute for Computational Biomedicine, Bioquant, Heidelberg, Germany; Institut Curie, PSL Research University, Mines Paris Tech, Inserm, U900, F-75005, Paris, France.; cBio Center, Divisions of Biostatistics and Computational Biology, Department of Data Sciences, Dana-Farber Cancer Institute, Boston, MA, 02215, USA.; Oregon Health and Science University, Department of Molecular and Medical Genetics, 3222 SW Research Drive, Mail Code: L103, Portland, Oregon, U.S.A. 97239; Earlham Institute, Norwich Research Park, NR4 7UZ, Norwich, UK; The Roslin Institute, University of Edinburgh EH25 9RG; Sanofi R&D, Translational Sciences, 1 av Pierre Brossolette 91395 Chilly-Mazarin France; University of Lausanne, Lausanne, Switzerland; Interdisciplinary Research Unit Mathematics and Life Sciences, University of Bonn, Germany; University of Rostock, Dept of Systems Biology & Bioinformatics; Department of Bioinformatics-BiGCaT, NUTRIM, Maastricht University, Maastricht, The Netherlands; Institute of Data Science and Biotechnology, Gladstone Institutes, San Francisco, CA, USA; Dept. Bioinformatics - BiGCaT, Maastricht University, The Netherlands; Ontario Institute for Cancer Research, Adaptive Oncology Theme, 661 University Ave, Toronto, ON M5G 1M1 Canada; European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridgeshire, UK; Institute for Computational Biomedicine Heidelberg University, Faculty of Medicine, Im Neuenheimer Feld 267, 69120 Heidelberg; Clinical Bioinformatics Area. Fundacion Progreso y Salud (FPS). CDCA, Hospital Virgen del Rocio. 41013. Sevilla. Spain.; Barcelona Supercomputing Center (BSC), Barcelona, Spain; Systems Biology Institute, Tokyo Japan; Institut Curie, PSL Research University, Paris, France.; European Institute for Systems Biology and Medicine (EISBM), Vourles, France; Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg; Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg; -","We describe a large-scale community effort to build an open-access, interoperable, and computable repository of COVID-19 molecular mechanisms - the COVID-19 Disease Map. We discuss the tools, platforms, and guidelines necessary for the distributed development of its contents by a multi-faceted community of biocurators, domain experts, bioinformaticians, and computational biologists. We highlight the role of relevant databases and text mining approaches in enrichment and validation of the curated mechanisms. We describe the contents of the Map and their relevance to the molecular pathophysiology of COVID-19 and the analytical and computational modelling approaches that can be applied for mechanistic data interpretation and predictions. We conclude by demonstrating concrete applications of our work through several use cases and highlight new testable hypotheses.",systems biology,fuzzy,100,100 medRxiv,10.1101/2020.10.25.20219048,2020-10-27,https://medrxiv.org/cgi/content/short/2020.10.25.20219048,Viral load in community SARS-CoV-2 cases varies widely and temporally,Ann Sarah Walker; Emma Pritchard; Thomas House; Julie V Robotham; Paul J Birrell; Iain Bell; John I Bell; John N Newton; Jeremy Farrar; Ian Diamond; Ruth Studley; Jodie Hay; Karina-Doris Vihta; Timothy EA Peto; Nicole Stoesser; Philippa C Matthews; David W Eyre; Koen Pouwels; - the COVID-19 Infection Survey team,University of Oxford; University of Oxford; University of Manchester; Public Health England; Public Health England; Office for National Statistics; University of Oxford; Public Health England; Wellcome Trust; Office for National Statistics; Office for National Statistics; University of Glasgow; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; ,"Information on SARS-CoV-2 in representative community surveillance is limited, particularly cycle threshold (Ct) values (a proxy for viral load). Of 3,312,159 nose and throat swabs taken 26-April-2020 to 13-March-2021 in the UKs national COVID-19 Infection Survey, 27,902(0.83%) were RT-PCR-positive, 10,317(37%), 11,012(40%) and 6,550(23%) for 3, 2 or 1 of the N, S and ORF1ab genes respectively, with median Ct=29.2 ([~]215 copies/ml; IQR Ct=21.9-32.8, 14-56,400 copies/ml). Independent predictors of lower Cts (i.e. higher viral load) included self-reported symptoms and more genes detected, with at most small effects of sex, ethnicity and age. Single-gene positives almost invariably had Ct>30, but Cts varied widely in triple-gene positives, including without symptoms. Population-level Cts changed over time, with declining Ct preceding increasing SARS-CoV-2 positivity. Of 6,189 participants with IgG S-antibody tests post-first RT-PCR-positive, 4,808(78%) were ever antibody-positive; Cts were significantly higher in those remaining antibody-negative. Community SARS-CoV-2 Ct values could be a useful epidemiological early-warning indicator. IMPACT STATEMENTCt values from SARS-CoV-2 RT-PCR tests vary widely and over calendar time. They have the potential to be used more broadly in public testing programmes as an ""early-warning"" system for shifts in infectious load and hence transmission.",infectious diseases,fuzzy,100,100 @@ -4545,6 +4455,13 @@ There was evidence of mild organ impairment in heart (32%), lungs (33%), kidneys InterpretationIn a young, low-risk population with ongoing symptoms, almost 70% of individuals have impairment in one or more organs four months after initial symptoms of SARS-CoV-2 infection. There are implications not only for burden of long COVID but also public health approaches which have assumed low risk in young people with no comorbidities. FundingThis work was supported by the UKs National Consortium of Intelligent Medical Imaging through the Industry Strategy Challenge Fund, Innovate UK Grant 104688, and also through the European Unions Horizon 2020 research and innovation programme under grant agreement No 719445.",health policy,fuzzy,100,100 +medRxiv,10.1101/2020.10.12.20211342,2020-10-14,https://medrxiv.org/cgi/content/short/2020.10.12.20211342,Network Graph Representation of COVID-19 Scientific Publications to Aid Knowledge Discovery,George Cernile; Trevor Heritage; Neil Sebire; Ben Gordon; Taralyn Schwering; Shana Kazemlou; Yulia Borecki,Inspirata Ltd; Inspirata Ltd; HDRUK London UK; HDRUK London UK; Inspirata Ltd; Inspirata Ltd; Inspirata Ltd,"IntroductionNumerous scientific journal articles have been rapidly published related to COVID-19 making navigation and understanding of relationships difficult. + +MethodsA graph network was constructed from the publicly available CORD-19 database of COVID-19-related publications using an engine leveraging medical knowledgebases to identify discrete medical concepts and an open source tool (Gephi) used to visualise the network. + +ResultsThe network shows connections between disease, medication and procedures identified from title and abstracts of 195,958 COVID-19 related publications (CORD-19 Dataset). Connections between terms with few publications, those unconnected to the main network and those irrelevant were not displayed. Nodes were coloured by knowledgebase and node size related to the number of publications containing the term. The dataset and visualisations made publicly accessible via a webtool. + +ConclusionKnowledge management approaches (text mining and graph networks) can effectively allow rapid navigation and exploration of entity interrelationships to improve understanding of diseases such as COVID-19.",health informatics,fuzzy,100,100 medRxiv,10.1101/2020.10.12.20211227,2020-10-14,https://medrxiv.org/cgi/content/short/2020.10.12.20211227,High and increasing prevalence of SARS-CoV-2 swab positivity in England during end September beginning October 2020: REACT-1 round 5 updated report,Steven Riley; Kylie E. C. Ainslie; Oliver Eales; Caroline E Walters; Haowei Wang; Christina J Atchison; Claudio Fronterre; Peter J Diggle; Deborah Ashby; Christl A. Donnelly; Graham Cooke; Wendy Barclay; Helen Ward; Ara Darzi; Paul Elliott,"Dept Inf Dis Epi, Imperial College; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Lancaster University; Lancaster University; Imperial College London; Imperial College London; Imperial College; Imperial College London; Imperial College London; Imperial College London; Imperial College London School of Public Health","BackgroundREACT-1 is quantifying prevalence of SARS-CoV-2 infection among random samples of the population in England based on PCR testing of self-administered nose and throat swabs. Here we report results from the fifth round of observations for swabs collected from the 18th September to 5th October 2020. This report updates and should be read alongside our round 5 interim report. MethodsRepresentative samples of the population aged 5 years and over in England with sample size ranging from 120,000 to 175,000 people at each round. Prevalence of PCR-confirmed SARS-CoV-2 infection, estimation of reproduction number (R) and time trends between and within rounds using exponential growth or decay models. @@ -4608,6 +4525,13 @@ medRxiv,10.1101/2020.10.03.20206375,2020-10-06,https://medrxiv.org/cgi/content/s Methods and FindingsA systematic review and meta-analysis of the use of RAS inhibitors in relation to infection with SARS-CoV-2 and/or the severity and mortality associated with COVID-19 was conducted. English language bibliographic databases PubMed, Web of Science, OVID Embase, Scopus, MedRxiv, BioRxiv, searched from Jan 1st, 2020 to July 20th, 2020. 58 observational studies (69,200 COVID-19 patients and 3,103,335 controls) were included. There was no difference in the susceptibility to SARS-CoV-2 infection between RAS inhibitor users and non-users (unadjusted OR 1.05, 95% CI 0.90 to 1.21), (adjusted OR 0.93, 95% CI 0.85 to 1.02), (adjusted HR 1.07, 95% CI 0.87 to 1.31). There was no significant difference in the severe Covid-19 case rate between RAS inhibitor users and non-users (unadjusted OR 1.05, 95% CI 0.81 to 1.36), (adjusted OR 0.76, 95% CI 0.52 to 1.12), or in mortality due to COVID-19 between RAS inhibitor users and non-users (unadjusted OR 1.12, 95% CI 0.88 to 1.44), (adjusted OR 0.97, 95% CI 0.77 to 1.23), (adjusted HR 0.62, 95% CI 0.34 to 1.14). ConclusionsIn the most comprehensive analysis of all available data to date, treatment with RAS inhibitors was not associated with increased risk of infection, severity of disease, or mortality due to COVID-19. The best available evidence suggests that these treatments should not be discontinued on the basis of concern about risk associated with COVID-19.",infectious diseases,fuzzy,100,100 +medRxiv,10.1101/2020.10.03.20206284,2020-10-06,https://medrxiv.org/cgi/content/short/2020.10.03.20206284,The excess insulin requirement in severe COVID-19 compared to non-COVID-19 viral pneumonitis is related to the severity of respiratory failure and pre-existing diabetes.,Sam Lockhart; Harry Griffiths; Bogdan Petrisor; Ammara Usman; Julia Calvo-Latorre; Laura Heales; Vishakha Bansiya; Razeen Mahroof; Andrew Conway Morris,"1. MRC Metabolic Diseases Unit, Wellcome Trust-Medical Research Council Institute of Metabolic Science, University of Cambridge, Cambridge, UK.; John V Farman Intensive Care Unit, Addenbrooke's Hospital, Cambridge; John V Farman Intensive Care Unit, Addenbrooke's Hospital, Cambridge; John V Farman Intensive Care Unit, Addenbrooke's Hospital, Cambridge; Wolfson Diabetes and Endocrinology Clinic, Cambridge University Hospital NHS Foundation Trust, Cambridge; John V Farman Intensive Care Unit, Addenbrooke's Hospital, Cambridge; Wolfson Diabetes and Endocrinology Clinic, Cambridge University Hospital NHS Foundation Trust, Cambridge; John V Farman Intensive Care Unit, Addenbrookes Hospital, Cambridge; University of Cambridge","ObjectiveSevere COVID-19 has been anecdotally associated with high insulin requirements. It has been proposed that this may be driven by a direct diabetogenic effect of the virus that is unique to SARS-CoV-2, but evidence to support this is limited. To explore this, we compared insulin requirements in patients with severe COVID-19 and non-COVID-19 viral pneumonitis. + +Research DesignRetrospective cohort study of patients with severe COVID-19 admitted to our intensive care unit between March and June 2020. A historical control cohort of non-COVID-19 viral pneumonitis patients was identified from routinely collected audit data. + +ResultsInsulin requirements were similar in patients with COVID-19 and non-COVID-19 viral pneumonitis after adjustment for pre-existing diabetes and severity of respiratory failure. + +ConclusionsIn this single center study, we could not find evidence of a unique diabetogenic effect of COVID-19. We suggest that high insulin requirements in this disease relate to its propensity to cause severe respiratory failure in patients with pre-existing metabolic disease.",intensive care and critical care medicine,fuzzy,100,100 medRxiv,10.1101/2020.10.02.20205591,2020-10-04,https://medrxiv.org/cgi/content/short/2020.10.02.20205591,Risk factors associated with SARS-CoV-2 infection and outbreaks in Long Term Care Facilities in England: a national survey,Laura Shallcross; Danielle Burke; Owen Abbott; Alasdair Donaldson; Gemma Hallatt; Andrew Hayward; Susan Hopkins; Maria Krutikov; Katie Sharp; Leone Wardman; Sapphira Thorne,UCL; Office for National Statistics; Office for National Statistics; UK Department of Health and Social Care; Palantir; UCL; Public Health England; UCL; Office for National Statistics; Office for National Statistics; Office for National Statistics,"BackgroundOutbreaks of SARS-CoV-2 have occurred worldwide in Long Term Care Facilities (LTCFs), but the reasons why some facilities are particularly vulnerable to infection are poorly understood. We aimed to identify risk factors for SARS-CoV-2 infection and outbreaks in LTCFs. MethodsCross-sectional survey of all LTCFs providing dementia care or care to adults >65 years in England with linkage to SARS-CoV-2 test results. Exposures included: LTCF characteristics, staffing factors, and use of disease control measures. Main outcomes included risk factors for infection and outbreaks, estimated using multivariable logistic regression, and survey and test-based weighted estimates of SARS-CoV-2 prevalence. @@ -4667,6 +4591,7 @@ There were insufficient data on the effect of CD4+ T cell count and HIV viral lo ConclusionEvidence is emerging that suggests a moderately increased risk of COVID-19 mortality amongst PLWH. Further investigation into the relationship between COVID-19 outcomes and CD4+ T cell count, HIV viral load, ART and the use of TDF is warranted.",hiv aids,fuzzy,91,100 medRxiv,10.1101/2020.09.22.20198754,2020-09-23,https://medrxiv.org/cgi/content/short/2020.09.22.20198754,"Ethnic differences in COVID-19 infection, hospitalisation, and mortality: an OpenSAFELY analysis of 17 million adults in England",Rohini Mathur; Christopher T. Rentsch; Caroline Morton; William J Hulme; Anna Schultze; Brian MacKenna; Rosalind M Eggo; Krishnan Bhaskaran; Angel YS Wong; Elizabeth J Williamson; Harriet Forbes; Kevin Wing; Helen I McDonald; Chris Bates; Seb Bacon; Alex J Walker; David Evans; Peter Inglesby; Amir Mehrkar; Helen J Curtis; Nicholas J DeVito; Richard Croker; Henry Drysdale; Jonathan Cockburn; John Parry; Frank Hester; Sam Harper; Ian J Douglas; Laurie Tomlinson; Stephen Evans; Richard Grieve; David Harrison; Kathy Rowan; Kamlesh Khunti; Nish Chaturvedi; Liam Smeeth; Ben Goldacre,London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; University of Oxford; University of Oxford; London School of Hygiene and Tropical Medicine; University of Oxford; London School of Hygiene & Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Medicine and Tropical Medicine; The Phoenix Partnership; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; The Phoenix Partnership; The Phoenix Partnership; The Phoenix Partnership; The Phoenix Partnership; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; Intensive Care National Audit and Research Centre; Intensive Care National Audit and Research Centre; University of Leicester; University College London; London School of Hygiene and Tropical Medicine; University of Oxford,"Background: COVID-19 has had a disproportionate impact on ethnic minority populations, both in the UK and internationally. To date, much of the evidence has been derived from studies within single healthcare settings, mainly those hospitalised with COVID-19. Working on behalf of NHS England, the aim of this study was to identify ethnic differences in the risk of COVID-19 infection, hospitalisation and mortality using a large general population cohort in England. Methods: We conducted an observational cohort study using linked primary care records of 17.5 million adults between 1 February 2020 and 3 August 2020. Exposure was self-reported ethnicity collapsed into the 5 and 16 ethnicity categories of the English Census. Multivariable Cox proportional hazards regression was used to identify ethnic differences in the risk of being tested and testing positive for SARS-CoV-2 infection, COVID-19 related intensive care unit (ICU) admission, and COVID-19 mortality, adjusted for socio-demographic factors, clinical co-morbidities, geographic region, care home residency, and household size. Results: A total of 17,510,002 adults were included in the study; 63% white (n=11,030,673), 6% south Asian (n=1,034,337), 2% black (n=344,889), 2% other (n=324,730), 1% mixed (n=172,551), and 26% unknown (n=4,602,822). After adjusting for measured explanatory factors, south Asian, black, and mixed groups were marginally more likely to be tested (south Asian HR 1.08, 95%CI 1.07-1.09; black HR 1.08; 95%CI 1.06-1.09, mixed HR 1.03, 95%CI 1.01-1.05), and substantially more likely to test positive for SARS-CoV-2 compared with white adults (south Asian HR 2.02. 95% CI 1.97-2.07; black HR 1.68, 95%CI 1.61-1.76; mixed HR 1.46, 95%CI 1.36-1.56). The risk of being admitted to ICU for COVID-19 was substantially increased in all ethnic minority groups compared with white adults (south Asian HR 2.22, 95%CI 1.96-2.52; black HR 3.07, 95%CI 2.61-3.61; mixed HR 2.86, 95%CI 2.19-3.75, other HR 2.86, 95%CI 2.31-3.63). Risk of COVID-19 mortality was increased by 25-56% in ethnic minority groups compared with white adults (south Asian HR 1.27, 95%CI 1.17-1.38; black HR 1.55, 95%CI 1.38-1.75; mixed HR 1.40, 95%CI 1.12-1.76; other HR 1.25, 95%CI 1.05-1.49). We observed heterogeneity of associations after disaggregation into detailed ethnic groupings; Indian and African groups were at higher risk of all outcomes; Pakistani, Bangladeshi and Caribbean groups were less or equally likely to be tested for SARS-CoV-2, but at higher risk of all other outcomes, Chinese groups were less likely to be tested for and test positive for SARS-CoV-2, more likely to be admitted to ICU, and equally likely to die from COVID-19. Conclusions: We found evidence of substantial ethnic inequalities in the risk of testing positive for SARS-CoV-2, ICU admission, and mortality, which persisted after accounting for explanatory factors, including household size. It is likely that some of this excess risk is related to factors not captured in clinical records such as occupation, experiences of structural discrimination, or inequitable access to health and social services. Prioritizing linkage between health, social care, and employment data and engaging with ethnic minority communities to better understand their lived experiences is essential for generating evidence to prevent further widening of inequalities in a timely and actionable manner.",epidemiology,fuzzy,100,100 +medRxiv,10.1101/2020.09.21.20194019,2020-09-23,https://medrxiv.org/cgi/content/short/2020.09.21.20194019,Putting (Big) Data in Action: Saving Lives with Countrywide Population Movement Monitoring Using Mobile Devices during the COVID-19 Crisis,Miklos Karoly Szocska; Peter Pollner; Istvan Schiszler; Tamas Joo; Tamas Palicz; Martin McKee; - Magyar Telekom Nyrt.; - Telenor Magyarorszag Zrt.; Adam Sohonyai; Jozsef Szoke; Adam Toth; Peter Gaal,"Semmelweis University, Faculty of Health and Public Administration, Health Services Management Training Centre, Digital Health and Data Utilisation Team; Semmelweis University, Faculty of Health and Public Administration, Health Services Management Training Centre, Digital Health and Data Utilisation Team; Semmelweis University, Faculty of Health and Public Administration, Health Services Management Training Centre, Digital Health and Data Utilisation Team; Semmelweis University, Faculty of Health and Public Administration, Health Services Management Training Centre, Digital Health and Data Utilisation Team; Semmelweis University, Faculty of Health and Public Administration, Health Services Management Training Centre, Digital Health and Data Utilisation Team; University of London, London School of Hygiene and Tropical Medicine, Department of Health Services Research and Policy; ; ; Vodafone Hungary; Vodafone Hungary; Vodafone Hungary; Semmelweis University, Faculty of Health and Public Administration, Health Services Management Training Centre, Digital Health and Data Utilisation Team","Many countries have implemented strict social distancing measures in the hope of reducing transmission of SARS-CoV-2 but the effectiveness of these measures is determined by the willingness of populations to comply with restrictions. Consequently, a system of monitoring population movement using existing data sources can inform those making decisions about policy responses to the COVID-19 pandemic. We describe a collaboration with all 3 major domestic telecommunication companies in Hungary to use aggregated anonymous mobile phone usage data to calculate two indices for assessing the effect of movement restrictions: a ""mobility-index"" and a ""stay-at-home (or resting) index"". The strengths and weaknesses of this approach are compared with the smartphone-based, COVID-19 Community Mobility Reports from Google. Data generated by mobile phones have long been identified as a potential means to analyse mass population movement, but its operationalisation raises several technical questions, such as making sense of Call Detail Records, collation of data from different mobile network providers, and personal data protection concerns. The method described here addresses these issues and offers an effective and inexpensive tool to monitor the impact of social distancing measures, achieving high levels of accuracy and resolution. Especially in populations where uptake of smartphones is modest, this method has certain advantages over app-based solutions, with greater population coverage, but it is not an alternative to smartphone-based solutions used for contact tracing and quarantine monitoring. We believe that this method can easily be adapted by other countries.",infectious diseases,fuzzy,100,100 medRxiv,10.1101/2020.09.21.20196428,2020-09-22,https://medrxiv.org/cgi/content/short/2020.09.21.20196428,"Sharing a household with children and risk of COVID-19: a study of over 300,000 adults living in healthcare worker households in Scotland",Rachael Wood; Emma C Thomson; Robert Galbraith; Ciara Gribben; David Caldwell; Jennifer Bishop; Martin Reid; Anoop Shah; Kate Templeton; David Goldberg; Chris Robertson; Sharon Hutchinson; Helen M Colhoun; Paul M McKeigue; David McAllister,"University of Edinburgh, Public Heath Scotland; University of Glasgow; Retired; Public Health Scotland; Public Health Scotland; Public Health Scotland; Public Health Scotland; London School of Hygiene and Tropical Medicine; University of Edinburgh; Public Health Scotland; Public Health Scotland; Public Health Scotland; University of Edinburgh; University of Edinburgh; University of Glasgow","ObjectiveChildren are relatively protected from COVID-19, possibly due to cross-protective immunity. We investigated if contact with children also affords adults a degree of protection from COVID-19. DesignCohort study based on linked administrative data. @@ -4682,6 +4607,7 @@ Main outcomesCOVID-19 requiring hospitalisation, and any COVID-19 (any positive Results241,266, 41,198, 23,783 and 3,850 adults shared a household with 0, 1, 2, and 3 or more young children respectively. Over the study period, the risk of COVID-19 requiring hospitalisation was reduced progressively with increasing numbers of household children - fully adjusted hazard ratio (aHR) 0.93 per child (95% CI 0.79-1.10). The risk of any COVID-19 was similarly reduced, with the association being statistically significant (aHR per child 0.93; 95% CI 0.88-0.98). After schools reopened to all children in August 2020, no association was seen between exposure to young children and risk of any COVID-19 (aHR per child 1.03; 95% CI 0.92-1.14). ConclusionBetween March and October 2020, living with young children was associated with an attenuated risk of any COVID-19 and COVID-19 requiring hospitalisation among adults living in healthcare worker households. There was no evidence that living with young children increased adults risk of COVID-19, including during the period after schools re-opened.",epidemiology,fuzzy,100,100 +medRxiv,10.1101/2020.09.17.20196436,2020-09-21,https://medrxiv.org/cgi/content/short/2020.09.17.20196436,Comparison of COVID-19 outcomes among shielded and non-shielded populations: A general population cohort study of 1.3 million,Bhautesh D Jani; Frederick K Ho; David J Lowe; Jamie P Traynor; Sean MacBride-Stewart; Patrick B Mark; Frances S Mair; Jill P Pell,University of Glasgow; University of Glasgow; NHS Greater Glasgow and Clyde; NHS Greater Glasgow and Clyde; NHS Greater Glasgow and Clyde; University of Glasgow; University of Glasgow; University of Glasgow,"Many western countries used shielding (extended self-isolation) of people presumed to be at high-risk from COVID-19 to protect them and reduce healthcare demand. To investigate the effectiveness of this strategy, we linked family practitioner, prescribing, laboratory, hospital and death records and compared COVID-19 outcomes among shielded and non-shielded individuals in the West of Scotland. Of the 1.3 million population, 27,747 (2.03%) were advised to shield, and 353,085 (26.85%) were classified a priori as moderate risk. COVID-19 testing was more common in the shielded (7.01%) and moderate risk (2.03%) groups, than low risk (0.73%). Referent to low-risk, the shielded group had higher confirmed infections (RR 8.45, 95% 7.44-9.59), case-fatality (RR 5.62, 95% CI 4.47-7.07) and population mortality (RR 57.56, 95% 44.06-75.19). The moderate-risk had intermediate confirmed infections (RR 4.11, 95% CI 3.82-4.42) and population mortality (RR 25.41, 95% CI 20.36-31.71) but, due to their higher prevalence, made the largest contribution to deaths (PAF 75.30%). Age [≥]70 years accounted for 49.55% of deaths. In conclusion, shielding has not been effective at preventing deaths in individuals at high risk. Also, to be effective as a population strategy, shielding criteria would need to be widely expanded to include other criteria, such as the elderly.",public and global health,fuzzy,100,100 medRxiv,10.1101/2020.09.15.20194795,2020-09-18,https://medrxiv.org/cgi/content/short/2020.09.15.20194795,"Acute, non-COVID related medical admissions during the first wave of COVID-19: A retrospective comparison of changing patterns of disease",Bridget Riley; Mary Packer; Suzy Gallier; Elizabeth Sapey; Catherine Atkin,"University Hospitals Birmingham NHS Foundation Trust; University Hospitals Birmingham NHS Foundation Trust; PIONEER Hub, University Hospitals Birmingham NHS Foundation Trust; PIONEER Hub, University of Birmingham; PIONEER Hub, University of Birmingham","BackgroundThe COVID-19 pandemic was associated with social restrictions in the UK from 16th March 2020. It was unclear if the lockdown period was associated with differences in the case-mix of non-COVID acute medical admissions compared with the previous year. MethodsRetrospective data were collected for 1st-30th April 2019 and 1st-30th April 2020 from University Hospitals Birmingham NHS Foundation Trust, one of the largest hospitals in the UK with over 2 million patient contacts per year. The latter time period was chosen to coincide with the peak of COVID-19 cases in the West Midlands. All patients admitted under acute medicine during these time periods were included. COVID-19 was confirmed by SARS-Cov-2 swab or a probable case of COVID-19 based on World Health Organization diagnostic parameters. Non-COVID patients were those with a negative SARS-Cov-2 swab and no suspicion of COVID-19. Data was sourced from UHBs in-house electronic health system (EHS). @@ -4857,19 +4783,6 @@ FindingsUnsupervised clustering identified distinct sub-groups. First, a core sy InterpretationThe large scale of the ISARIC-4C study enabled robust, granular discovery and replication of patient clusters. Clinical interpretation is necessary to determine which of these observations have practical utility. We propose that four patterns are usefully distinct from the core symptom groups: gastro-intestinal disease, productive cough, confusion, and pauci-symptomatic presentations. Importantly, each is associated with an in-hospital mortality which differs from that of patients with core symptoms. These observations deepen our understanding of COVID-19 and will influence clinical diagnosis, risk prediction, and future mechanistic and clinical studies. FundingMedical Research Council; National Institute Health Research; Well-come Trust; Department for International Development; Bill and Melinda Gates Foundation; Liverpool Experimental Cancer Medicine Centre.",infectious diseases,fuzzy,94,100 -medRxiv,10.1101/2020.08.13.20174193,2020-08-15,https://medrxiv.org/cgi/content/short/2020.08.13.20174193,CovidNudge: diagnostic accuracy of a novel lab-free point-of-care diagnostic for SARS-CoV-2,Malick M Gibani; Christofer Toumazou; Mohammadreza Sohbati; Rashmita Sahoo; Maria Karvela; Tsz-Kin Hon; Sara De Mateo; Alison Burdett; K Y Felice Leung; Jake Barnett; Arman Orbeladze; Song Luan; Stavros Pournias; Jiayang Sun; Barnaby Flower; Judith Bedzo-Nutakor; Maisarah Amran; Rachael Quinlan; Keira Skolimowska; Robert Klaber; Gary Davies; David Muir; Paul Randell; Derrick W M Crook; Graham P Taylor; Wendy Barclay; Nabeela Mughal; Luke S P Moore; Katie Jeffery; Graham S Cooke,"Imperial College London; DnaNudge Ltd, Translation and Innovation Hub, Imperial College White City Campus, London; DnaNudge Ltd, Translation and Innovation Hub, Imperial College White City Campus, London; DnaNudge Ltd, Translation and Innovation Hub, Imperial College White City Campus, London; DnaNudge Ltd, Translation and Innovation Hub, Imperial College White City Campus, London; DnaNudge Ltd, Translation and Innovation Hub, Imperial College White City Campus, London; DnaNudge Ltd, Translation and Innovation Hub, Imperial College White City Campus, London; DnaNudge Ltd, Translation and Innovation Hub, Imperial College White City Campus, London; DnaNudge Ltd, Translation and Innovation Hub, Imperial College White City Campus, London; DnaNudge Ltd, Translation and Innovation Hub, Imperial College White City Campus, London; DnaNudge Ltd, Translation and Innovation Hub, Imperial College White City Campus, London; DnaNudge Ltd, Translation and Innovation Hub, Imperial College White City Campus, London; DnaNudge Ltd, Translation and Innovation Hub, Imperial College White City Campus, London; DnaNudge Ltd, Translation and Innovation Hub, Imperial College White City Campus, London; Department of Infectious Disease, Imperial College London, United Kingdom; DnaNudge Ltd, Translation and Innovation Hub, Imperial College White City Campus, London; Imperial College Healthcare NHS Trust, United Kingdom.; Department of Infectious Disease, Imperial College London, United Kingdom; Imperial College Healthcare NHS Trust, United Kingdom; Imperial College Healthcare NHS Trust, United Kingdom; Chelsea & Westminster NHS Foundation Trust, London; Imperial College Healthcare NHS Trust, United Kingdom; Imperial College Healthcare NHS Trust, United Kingdom; NIHR Oxford Biomedical Research Centre; Department of Infectious Disease, Imperial College London, United Kingdom; Department of Infectious Disease, Imperial College London, United Kingdom; Chelsea & Westminster NHS Foundation Trust, London; Chelsea & Westminster NHS Foundation Trust, London; Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom; Department of Infectious Disease, Imperial College London, United Kingdom","3.BackgroundAccess to rapid diagnosis is key to the control and management of SARS-CoV-2. Reverse Transcriptase-Polymerase Chain Reaction (RT-PCR) testing usually requires a centralised laboratory and significant infrastructure. We describe the development and diagnostic accuracy assessment of a novel, rapid point-of-care RT-PCR test, the DnaNudge(R) platform CovidNudge test, which requires no laboratory handling or sample pre-processing. - -MethodsNasopharyngeal swabs are inserted directly into a cartridge which contains all reagents and components required for RT-PCR reactions, including multiple technical replicates of seven SARS-CoV-2 gene targets (rdrp1, rdrp2, e-gene, n-gene, n1, n2 and n3) and human ribonuclease P (RNaseP) as positive control. Between April and May 2020, swab samples were tested in parallel using the CovidNudge direct-to-cartridge platform and standard laboratory RT-PCR using swabs in viral transport medium. Samples were collected from three groups: self-referred healthcare workers with suspected COVID-19 (Group 1, n=280/386; 73%); patients attending the emergency department with suspected COVID-19 (Group 2, n=15/386; 4%) and hospital inpatient admissions with or without suspected COVID-19 (Group 3, n=91/386; 23%). - -ResultsOf 386 paired samples tested across all groups, 67 tested positive on the CovidNudge platform and 71 with standard laboratory RT-PCR. The sensitivity of the test varied by group (Group 1 93% [84-98%], Group 2 100% [48-100%] and Group 3 100% [29-100%], giving an average sensitivity of 94.4% (95% confidence interval 86-98%) and an overall specificity of 100% (95%CI 99-100%; Group 1 100% [98-100%]; Group 2 100% [69-100%] and Group 3 100% [96-100%]). Point of care testing performance was comparable during a period of high (25%) and low (3%) background prevalence. Amplification of the viral nucleocapsid (n1, n2, n3) targets were most sensitive for detection of SARS-CoV2, with the assay able to detect 1x104 viral particles in a single swab. - -ConclusionsThe CovidNudge platform offers a sensitive, specific and rapid point of care test for the presence of SARS-CoV-2 without laboratory handling or sample pre-processing. The implementation of such a device could be used to enable rapid decisions for clinical care and testing programs. - -4. RESEARCH IN CONTEXTO_ST_ABSEvidence before this studyC_ST_ABSThe WHO has highlighted the development of rapid, point-of-care diagnostics for detection of SARS-CoV-2 as a key priority to tackle COVID-19. The Foundation for Innovative Diagnostics (FIND) has identified over 90 point-of-care, near patient or mobile tests for viral detection of SARS-CoV-2. However, the most widely available rapid tests to date require some sample handling which limits their use at point-of-care. In addition, pressure on supply chains is restricting access to current diagnostics and alternatives are needed urgently. - -Added value of this studyWe describe the development and clinical validation of COVID nudge, a novel point-of-care RT-PCR diagnostic, evaluated during the first wave of the SARS-CoV-2 epidemic. The platform is able to achieve high analytic sensitivity and specificity from dry swabs within a self-contained cartridge. The lack of downstream sample handling makes it suitable for use in a range of clinical settings, without need for a laboratory or specialized operator. Multiplexed assays within the cartridge allow inclusion of a positive human control, which reduces the false negative testing rate due to insufficient sampling. - -Implication of the available evidencePoint-of-care testing can relieve pressure on centralized laboratories and increase overall testing capacity, complementing existing approaches. These findings support a role for COVID Nudge as part of strategies to improve access to rapid diagnostics to SARS-CoV-2. Since May 2020, the system has been implemented in UK hospitals and is being rolled out nationwide.",infectious diseases,fuzzy,92,100 medRxiv,10.1101/2020.08.12.20173690,2020-08-14,https://medrxiv.org/cgi/content/short/2020.08.12.20173690,"Antibody prevalence for SARS-CoV-2 in England following first peak of the pandemic: REACT2 study in 100,000 adults",Helen Ward; Christina J Atchison; Matthew Whitaker; Kylie E. C. Ainslie; Joshua Elliott; Lucy C Okell; Rozlyn Redd; Deborah Ashby; Christl A. Donnelly; Wendy Barclay; Ara Darzi; Graham Cooke; Steven Riley; Paul Elliott,"Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Dept Inf Dis Epi, Imperial College; Imperial College London","BackgroundEngland, UK has experienced a large outbreak of SARS-CoV-2 infection. As in USA and elsewhere, disadvantaged communities have been disproportionately affected. MethodsNational REal-time Assessment of Community Transmission-2 (REACT-2) prevalence study using a self-administered lateral flow immunoassay (LFIA) test for IgG among a random population sample of 100,000 adults over 18 years in England, 20 June to 13 July 2020. @@ -4877,7 +4790,6 @@ MethodsNational REal-time Assessment of Community Transmission-2 (REACT-2) preva ResultsData were available for 109,076 participants, yielding 5,544 IgG positive results; adjusted (for test performance) and re-weighted (for sampling) prevalence was 6.0% (95% Cl: 5.8, 6.1). Highest prevalence was in London (13.0% [12.3, 13.6]), among people of Black or Asian (mainly South Asian) ethnicity (17.3% [15.8, 19.1] and 11.9% [11.0, 12.8] respectively) and those aged 18-24 years (7.9% [7.3, 8.5]). Adjusted odds ratio for care home workers with client-facing roles was 3.1 (2.5, 3.8) compared with non-essential workers. One third (32.2%, [31.0-33.4]) of antibody positive individuals reported no symptoms. Among symptomatic cases, most (78.8%) reported symptoms during the peak of the epidemic in England in March (31.3%) and April (47.5%) 2020. We estimate that 3.36 million (3.21, 3.51) people have been infected with SARS-CoV-2 in England to end June 2020, with an overall infection fatality ratio (IFR) of 0.90% (0.86, 0.94); age-specific IFR was similar among people of different ethnicities. ConclusionThe SARS-CoV-2 pandemic in England disproportionately affected ethnic minority groups and health and care home workers. The higher risk of infection in minority ethnic groups may explain their increased risk of hospitalisation and mortality from COVID-19.",infectious diseases,fuzzy,100,100 -medRxiv,10.1101/2020.08.13.20174227,2020-08-14,https://medrxiv.org/cgi/content/short/2020.08.13.20174227,Long-Term Exposure to Outdoor Air Pollution and COVID-19 Mortality: an ecological analysis in England,Zhiqiang Feng; Mark Cherrie; Chris DIBBEN,University of Edinburgh; University of Edinburgh; University of Edinburgh,"There is an urgent need to examine what individual and environmental risk factors are associated with COVID-19 mortality. This objective of this study is to investigate the association between long term exposure to air pollution and COVID-19 mortality. We conducted a nationwide, ecological study using zero-inflated negative binomial models to estimate the association between long term (2014-2018) small area level exposure to NOx, PM2.5, PM10 and SO2 and COVID-19 mortality rates in England adjusting for socioeconomic factors and infection exposure. We found that all four pollutant concentrations were positively associated with COVID-19 mortality. The increase in mortality risk ratio per inter quarter range increase was for PM2.5:11%, 95%CIs 6%-17%), PM10 (5%; 95%CIs 1%-11%), NOx (11%, 95%CIs 6%-15%) and SO2 (7%, 95%CIs 3%-11%) were respectively in adjusted models. Public health intervention may need to protect people who are in highly polluted areas from COVID-19 infections.",occupational and environmental health,fuzzy,100,100 medRxiv,10.1101/2020.08.12.20171405,2020-08-14,https://medrxiv.org/cgi/content/short/2020.08.12.20171405,OpenSAFELY: Do adults prescribed Non-steroidal anti-inflammatory drugs have an increased risk of death from COVID-19?,Angel YS Wong; Brian MacKenna; Caroline Morton; Anna Schultze; Alex J Walker; Krishnan Bhaskaran; Jeremy Brown; Christopher T. Rentsch; Elizabeth Williamson; Henry Drysdale; Richard Croker; Seb Bacon; William Hulme; Chris Bates; Helen J Curtis; Amir Mehrkar; David Evans; Peter Inglesby; Jonathan Cockburn; Helen McDonald; Laurie Tomlinson; Rohini Mathur; Kevin Wing; Harriet Forbes; John Parry; Frank Hester; Sam Harper; Stephen Evans; Liam Smeeth; Ian Douglas; Ben Goldacre,"London School of Hygiene and Tropical Medicine; University of Oxford; University of Oxford; London School of Hygiene and Tropical Medicine; University of Oxford; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; US Department of Veterans Affairs, London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; University of Oxford; University of Oxford; University of Oxford; University of Oxford; TPP; University of Oxford; University of Oxford; University of Oxford; University of Oxford; TPP; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; TPP; TPP; TPP; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; University of Oxford","ImportanceThere has been speculation that non-steroidal anti-inflammatory drugs (NSAIDs) may negatively affect coronavirus disease 2019 (COVID-19) outcomes, yet clinical evidence is limited. ObjectiveTo assess the association between NSAID use and deaths from COVID-19 using OpenSAFELY, a secure analytical platform. @@ -4966,9 +4878,6 @@ Statistical methodsWe estimated hazard ratios (HRs) for ethnic minority groups c ResultsIn the age-adjusted models, people from all ethnic minority groups were at elevated risk of COVID-19 mortality; the HRs for Black males and females were 3.13 [95% confidence interval: 2.93 to 3.34] and 2.40 [2.20 to 2.61] respectively. However, in the fully adjusted model for females, the HRs were close to unity for all ethnic groups except Black (1.29 [1.18 to 1.42]). For males, COVID-19 mortality risk remained elevated for the Black (1.76 [1.63 to 1.90]), Bangladeshi/Pakistani (1.35 [1.21 to 1.49]) and Indian (1.30 [1.19 to 1.43]) groups. The HRs decreased after lockdown for all ethnic groups, particularly Black and Bangladeshi/Pakistani females. ConclusionsDifferences in COVID-19 mortality between ethnic groups were largely attenuated by geographical and socio-economic factors, although some residual differences remained. Lockdown was associated with reductions in excess mortality risk in ethnic minority populations, which has major implications for a second wave of infection or local spikes. Further research is needed to understand the causal mechanisms underpinning observed differences in COVID-19 mortality between ethnic groups.",epidemiology,fuzzy,100,100 -medRxiv,10.1101/2020.08.04.20163782,2020-08-04,https://medrxiv.org/cgi/content/short/2020.08.04.20163782,Fitting models to the COVID-19 outbreak and estimating R,Matt J Keeling; Louise Dyson; Glen Guyver-Fletcher; Alex Holmes; Malcolm G Semple; - ISARIC4C Investigators; Michael J Tildesley; Edward M Hill,University of Warwick; University of Warwick; University of Warwick; University of Warwick; University of Liverpool; ; University of Warwick; University of Warwick,"The COVID-19 pandemic has brought to the fore the need for policy makers to receive timely and ongoing scientific guidance in response to this recently emerged human infectious disease. Fitting mathematical models of infectious disease transmission to the available epidemiological data provides a key statistical tool for understanding the many quantities of interest that are not explicit in the underlying epidemiological data streams. Of these, the effective reproduction number, R, has taken on special significance in terms of the general understanding of whether the epidemic is under control (R < 1). Unfortunately, none of the epidemiological data streams are designed for modelling, hence assimilating information from multiple (often changing) sources of data is a major challenge that is particularly stark in novel disease outbreaks. - -Here, focusing on the dynamics of the first-wave (March-June 2020), we present in some detail the inference scheme employed for calibrating the Warwick COVID-19 model to the available public health data streams, which span hospitalisations, critical care occupancy, mortality and serological testing. We then perform computational simulations, making use of the acquired parameter posterior distributions, to assess how the accuracy of short-term predictions varied over the timecourse of the outbreak. To conclude, we compare how refinements to data streams and model structure impact estimates of epidemiological measures, including the estimated growth rate and daily incidence.",infectious diseases,fuzzy,100,100 medRxiv,10.1101/2020.07.30.20165464,2020-08-02,https://medrxiv.org/cgi/content/short/2020.07.30.20165464,Risk stratification of patients admitted to hospital with covid-19 using the ISARIC WHO Clinical Characterisation Protocol: development and validation of the 4C Mortality Score,Stephen R Knight; Antonia Ho; Riinu Pius; Iain Buchan; Gail Carson; Thomas M Drake; Jake Dunning; Cameron J Fairfield; Carrol Gamble; Christopher A Green; Rishi K Gupta; Sophie Halpin; Hayley Hardwick; Karl Holden; Peter W Horby; Clare Jackson; Kenneth A McLean; Laura Merson; Jonathan S Nguyen-Van-Tam; Lisa Norman; Mahdad Noursadeghi; Piero L Olliaro; Mark G Pritchard; Clark D Russell; Catherine A Shaw; Aziz Sheikh; Tom Solomon; Cathie Sudlow; Olivia V Swann; Lance Turtle; Peter JM Openshaw; J Kenneth Baillie; Malcolm Gracie Semple; Annemarie B Docherty; Ewen M Harrison,"Centre for Medical Informatics, The Usher Institute, University of Edinburgh; Medical Research Council University of Glasgow Centre for Virus Research, Glasgow, UK; Centre for Medical Informatics, Usher Institute, University of Edinburgh, UK; Institute of Population Health Sciences, University of Liverpool; University of Oxford; Centre for Medical Informatics, Usher Institute, University of Edinburgh, UK; National Infection Service Public Health England; Centre for Medical Informatics, Usher Institute, University of Edinburgh, UK; Liverpool Clinical Trials Centre, University of Liverpool, Liverpool, UK; Institute of Microbiology & Infection, University of Birmingham; University College London; Liverpool Clinical Trials Centre, University of Liverpool, Liverpool, UK; NIHR Health Protection Research Unit in Emerging and Zoonotic Infections and Institute of Infection, Veterinary and Ecological Sciences, Faculty of Health and ; NIHR Health Protection Research Unit in Emerging and Zoonotic Infections and Institute of Infection, Veterinary and Ecological Sciences, Faculty of Health and ; ISARIC Global Support Centre, Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK; Liverpool Clinical Trials Centre, University of Liverpool, Liverpool, UK; Centre for Medical Informatics, The Usher Institute, University of Edinburgh; ISARIC Global Support Centre, Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK; Division of Epidemiology and Public Health, University of Nottingham School of Medicine, Nottingham, UK; Centre for Medical Informatics, The Usher Institute, University of Edinburgh; Division of Infection and Immunity, University College London, Gower Street, London, WC1E 6BT; Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford OX3 7LF, United Kingdom; Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford OX3 7LF, United Kingdom; Queens Medical Research Institute, University of Edinburgh, Edinburgh, UK; Department of Clinical Surgery, University of Edinburgh; Centre for Medical Informatics, The Usher Institute, University of Edinburgh; NIHR Health Protection Research Unit in Emerging and Zoonotic Infections and Institute of Infection, Veterinary and Ecological Sciences, Faculty of Health and ; Health Data Research UK, Gibbs Building, 215 Euston Road, London, NW1 2BE; Department of Child Life and Health, University of Edinburgh, UK; NIHR Health Protection Research Unit in Emerging and Zoonotic Infections and Institute of Infection, Veterinary and Ecological Sciences, Faculty of Health and ; National Heart and Lung Institute, Imperial College London, London, UK; Roslin Institute, University of Edinburgh; NIHR Health Protection Research Unit in Emerging and Zoonotic Infections and Institute of Infection, Veterinary and Ecological Sciences, Faculty of Health and ; Centre for Medical Informatics, Usher Institute, University of Edinburgh, UK; Centre for Medical Informatics, Usher Institute, University of Edinburgh, UK","ObjectivesTo develop and validate a pragmatic risk score to predict mortality for patients admitted to hospital with covid-19. DesignProspective observational cohort study: ISARIC WHO CCP-UK study (ISARIC Coronavirus Clinical Characterisation Consortium [4C]). Model training was performed on a cohort of patients recruited between 6 February and 20 May 2020, with validation conducted on a second cohort of patients recruited between 21 May and 29 June 2020. @@ -5096,6 +5005,23 @@ MethodsAn international multicentre audit of patients with a prior diagnosis of Measurements and Main ResultsData from 349 patients with ILD across Europe were included, of whom 161 were admitted to hospital with laboratory or clinical evidence of COVID-19 and eligible for propensity-score matching. Overall mortality was 49% (79/161) in patients with ILD with COVID-19. After matching ILD patients with COVID-19 had higher mortality (HR 1.60, Confidence Intervals 1.17-2.18 p=0.003) compared with age, sex and comorbidity matched controls without ILD. Patients with a Forced Vital Capacity (FVC) of <80% had an increased risk of death versus patients with FVC [≥]80% (HR 1.72, 1.05-2.83). Furthermore, obese patients with ILD had an elevated risk of death (HR 1.98, 1.13-3.46). ConclusionsPatients with ILD are at increased risk of death from COVID-19, particularly those with poor lung function and obesity. Stringent precautions should be taken to avoid COVID-19 in patients with ILD.",respiratory medicine,fuzzy,100,100 +medRxiv,10.1101/2020.07.14.20153734,2020-07-16,https://medrxiv.org/cgi/content/short/2020.07.14.20153734,"Place and causes of acute cardiovascular mortality during the COVID19 pandemic: retrospective cohort study of 580,972 deaths in England and Wales, 2014 to 2020",Jianhua Wu; Mamas Mamas; Mohamed Mohamed; Chun Shing Kwok; Chris Roebuck; Ben Humberstone; Tom Denwood; Tom Luescher; Mark De Belder; John Deanfield; Chris Gale,University of Leeds; Keele University; Keele University; Keele University; NHS Digital; ONS; NHS Digital; Imperial College; Barts Health NHS Trust; UCL; University of Leeds,"ImportanceThe COVID-19 pandemic has resulted in a decline in admissions with cardiovascular (CV) emergencies. The fatal consequences of this are unknown. + +ObjectivesTo describe the place and causes of acute CV death during the COVID-19 pandemic. + +DesignRetrospective nationwide cohort. + +SettingEngland and Wales. + +ParticipantsAll adult (age [≥]18 years) acute CV deaths (n=580,972) between 1st January 2014 and 2nd June 2020. + +ExposureThe COVID-19 pandemic (defined as from the onset of the first COVID-19 death in England on 2nd March 2020). + +Main outcomesPlace (hospital, care home, home) and acute CV events directly contributing to death as stated on the first part of the Medical Certificate of Cause of Death. + +ResultsAfter 2nd March 2020, there were 22,820 acute CV deaths of which 5.7% related to COVID-19, and an excess acute CV mortality of 1752 (+8%) compared with the expected daily deaths in the same period. Deaths in the community accounted for nearly half of all deaths during this period. Care homes had the greatest increase in excess acute CV deaths (1065, +40%), followed by deaths at home (1728, +34%) and in hospital (57, +0%). The most frequent cause of acute CV death during this period was stroke (8,290, 36.3%), followed by acute coronary syndrome (ACS) (5,532, 24.2%), heart failure (5,280, 23.1%), pulmonary embolism (2,067, 9.1%) and cardiac arrest (1,037, 4.5%). Deep vein thrombosis had the greatest increase in cause of excess acute CV death (18, +25%), followed pulmonary embolism (340, +19%) and stroke (782, +10%). The greatest cause of excess CV death in care homes was stroke (700, +48%), compared with cardiac arrest (80, +56%) at home, and pulmonary embolism (126, +14%) and cardiogenic shock (41, +14%) in hospital. + +Conclusions and relevanceThe COVID-19 pandemic has resulted in an inflation in acute CV deaths above that expected for the time of year, nearly half of which occurred in the community. The most common cause of acute CV death was stroke followed by acute coronary syndrome and heart failure. This is key information to optimise messaging to the public and enable health resource planning.",cardiovascular medicine,fuzzy,100,100 medRxiv,10.1101/2020.07.14.20152629,2020-07-15,https://medrxiv.org/cgi/content/short/2020.07.14.20152629,Covid-19 infection and attributable mortality in UK Long Term Care Facilities: Cohort study using active surveillance and electronic records (March-June 2020),Peter F Dutey-Magni; Haydn Williams; Arnoupe Jhass; Greta Rait; Harry Hemingway; Andrew C Hayward; Laura Shallcross,University College London; Four Seasons Healthcare Group; UCL; University College London; University College London; University College London; UCL,"BackgroundEpidemiological data on COVID-19 infection in care homes are scarce. We analysed data from a large provider of long-term care for older people to investigate infection and mortality during the first wave of the pandemic. MethodsCohort study of 179 UK care homes with 9,339 residents and 11,604 staff.We used manager-reported daily tallies to estimate the incidence of suspected and confirmed infection and mortality in staff and residents. Individual-level electronic health records from 8,713 residents were used to model risk factors for confirmed infection, mortality, and estimate attributable mortality. @@ -5634,6 +5560,19 @@ medRxiv,10.1101/2020.05.14.20101824,2020-05-19,https://medrxiv.org/cgi/content/s One sentence summaryUnderstanding travel before, during, and after the introduction of travel restrictions in China in response to the COVID-19 Pandemic.",public and global health,fuzzy,100,100 medRxiv,10.1101/2020.05.11.20098269,2020-05-18,https://medrxiv.org/cgi/content/short/2020.05.11.20098269,Accessibility and allocation of public parks and gardens during COVID-19 social distancing in England and Wales,Niloofar Shoari; Majid Ezzati; Jill Baumgartner; Diego Malacarne; Daniela Fecht,Imperial College London; Imperial College London; McGill University; Imperial College London; Imperial College London,"Visiting parks and gardens may attenuate the adverse physical and mental health impacts of social distancing implemented to reduce the spread of COVID-19. We quantified access to public parks and gardens in urban areas of England and Wales, and the potential for park crowdedness during periods of high use. We combined data from the Office for National Statistics and Ordnance Survey to quantify (i) the number of parks within 500 and 1,000 metres of urban postcodes (i.e., availability), (ii) the distance of postcodes to the nearest park (i.e., accessibility), and (iii) per-capita space in each park for people living within 1,000m. We examined how these measures vary by city and share of homes that are flats. Around 25.4 million people can access public parks or gardens within a ten-minute walk, while 3.8 million residents live farther away; of these 21% are children and 13% are elderly. Areas with a higher share of flats on average are closer to a park but people living in these areas are potentially less able to meet social distancing requirements while in parks during periods of high use. Cities in England and Wales can provide residents with access to green space that enables outdoor exercise and play during social distancing. Cities aiming to facilitate social distancing while keeping public green spaces open might require implementing measures such as dedicated park times for different age groups or entry allocation systems that, combined with smartphone apps or drones, can monitor and manage the total number of people using the park.",public and global health,fuzzy,100,100 +medRxiv,10.1101/2020.05.12.20098921,2020-05-18,https://medrxiv.org/cgi/content/short/2020.05.12.20098921,Behavioural change towards reduced intensity physical activity is disproportionately prevalent among adults with serious health issues or self-perception of high risk during the UK COVID-19 lockdown.,Nina Trivedy Rogers; Naomi Waterlow; Hannah E Brindle; Luisa Enria; Rosalind M Eggo; Shelley Lees; Chrissy h Roberts,University College London (UCL); London School of Hygiene & Tropical Medicine; London School of Hygiene & Tropical Medicine; University of Bath; London School of Hygiene & Tropical Medicine; London School of Hygiene & Tropical Medicine; London School of Hygiene & Tropical Medicine,"ImportanceThere are growing concerns that the UK COVID-19 lockdown has reduced opportunities to maintain health through physical activity, placing individuals at higher risk of chronic disease and leaving them more vulnerable to severe sequelae of COVID-19. + +ObjectiveTo examine whether the UKs lockdown measures have had disproportionate impacts on intensity of physical activity in groups who are, or who perceive themselves to be, at heightened risk from COVID-19. + +Designs, Setting, ParticipantsUK-wide survey of adults aged over 20, data collected between 2020-04-06 and 2020-04-22. + +ExposuresSelf-reported doctor-diagnosed obesity, hypertension, type I/II diabetes, lung disease, cancer, stroke, heart disease. Self-reported disabilities and depression. Sex, gender, educational qualifications, household income, caring for school-age children. Narrative data on coping strategies. + +Main Outcomes and MeasuresChange in physical activity intensity after implementation of UK COVID-19 lockdown (self-reported). + +ResultsMost (60%) participants achieved the same level of intensity of physical activity during the lockdown as before the epidemic. Doing less intensive physical activity during the lockdown was associated with obesity (OR 1.21, 95% CI 1.02-1.41), hypertension (OR 1.52, 1.33-1.71), lung disease (OR 1.31,1.13-1.49), depression (OR 2.02, 1.82-2.22) and disability (OR 2.34, 1.99-2.69). Participants who reduced their physical activity intensity also had higher odds of being female, living alone or having no garden, and more commonly expressed sentiments about personal or household risks in narratives on coping. + +Conclusions and relevanceGroups who reduced physical activity intensity included disproportionate numbers of people with either heightened objective clinical risks or greater tendency to express subjective perceptions of risk. Policy on exercise for health during lockdowns should include strategies to facilitate health promoting levels of physical activity in vulnerable groups, including those with both objective and subjective risks.",infectious diseases,fuzzy,100,100 medRxiv,10.1101/2020.05.09.20082909,2020-05-15,https://medrxiv.org/cgi/content/short/2020.05.09.20082909,Screening of healthcare workers for SARS-CoV-2 highlights the role of asymptomatic carriage in COVID-19 transmission,Lucy Rivett; Sushmita Sridhar; Dominic Sparkes; Matthew Routledge; Nicholas K. Jones; Sally Forrest; Jamie Young; Joana Pereira-Dias; William L Hamilton; Mark Ferris; Estee Torok; Luke Meredith; The CITIID-NIHR COVI Bioresource Collaboration; Martin Curran; Stewart Fuller; Afzal Chaudhry; Ashley Shaw; Richard J. Samsworth; John R. Bradley; Gordon Dougan; Kenneth G. C. Smith; Paul J. Lehner; Nicholas J. Matheson; Giles Wright; Ian Goodfellow; Stephen Baker; Michael P. Weekes,"Department of Infectious Diseases, Cambridge University NHS Hospitals Foundation Trust, Cambridge, UK and Clinical Microbiology & Public Health Laboratory, Publ; Cambridge Institute of Therapeutic Immunology & Infectious Disease (CITIID), University of Cambridge, Cambridge, UK and Wellcome Sanger Institute, Hinxton, UK; Department of Infectious Diseases, Cambridge University NHS Hospitals Foundation Trust, Cambridge, UK and Clinical Microbiology & Public Health Laboratory, Publ; Department of Infectious Diseases, Cambridge University NHS Hospitals Foundation Trust, Cambridge, UK and Clinical Microbiology & Public Health Laboratory, Publ; Department of Infectious Diseases, Cambridge University NHS Hospitals Foundation Trust, Cambridge, UK; Clinical Microbiology & Public Health Cambridge Institute; Cambridge Institute of Therapeutic Immunology & Infectious Disease (CITIID), University of Cambridge, Cambridge, UK; Academic department of Medical Genetics, University of Cambridge, Cambridge, UK; Cambridge Institute of Therapeutic Immunology & Infectious Disease (CITIID), University of Cambridge, Cambridge, UK; Department of Infectious Diseases, Cambridge University NHS Hospitals Foundation Trust, Cambridge, UK and Clinical Microbiology & Public Health Laboratory, Publ; Occupational Health and Wellbeing, Cambridge Biomedical Campus, Cambridge, UK; Department of Medicine, University of Cambridge, Cambridge, UK; Division of Virology, Department of Pathology, University of Cambridge, Cambridge, UK; Cambridge Institute of Therapeutic Immunology & Infectious Disease (CITIID), Jeffrey Cheah Biomedical Centre, Cambridge Biomedical Campus, University of Cambrid; Clinical Microbiology & Public Health Laboratory, Public Health England, Cambridge, UK; National Institutes for Health Research Cambridge Biomedical Research Centre, Cambridge, UK; National Institutes for Health Research Cambridge Biomedical Research Centre, Cambridge, UK; Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK; Statistical Laboratory, Centre for Mathematical Sciences, Cambridge, UK; Department of Medicine, University of Cambridge, Cambridge, UK and National Institutes for Health Research Cambridge Biomedical Research Centre, Cambridge, UK; Cambridge Institute of Therapeutic Immunology & Infectious Disease (CITIID), University of Cambridge, Cambridge, UK and Department of Medicine, University of Ca; Cambridge Institute of Therapeutic Immunology & Infectious Disease (CITIID), University of Cambridge, Cambridge, UK and Department of Medicine, University of Ca; Department of Infectious Diseases, Cambridge University NHS Hospitals Foundation Trust, Cambridge, UK, Cambridge Institute of Therapeutic Immunology & Infectiou; Department of Infectious Diseases, Cambridge University NHS Hospitals Foundation Trust, Cambridge, UK and Cambridge Institute of Therapeutic Immunology & Infect; Occupational Health and Wellbeing, Cambridge Biomedical Campus, Cambridge, UK; Division of Virology, Department of Pathology, University of Cambridge, Cambridge, UK; Cambridge Institute of Therapeutic Immunology & Infectious Disease (CITIID), University of Cambridge, Cambridge, UK and Department of Medicine, University of Ca; Department of Infectious Diseases, Cambridge University NHS Hospitals Foundation Trust, Cambridge, UK and Cambridge Institute of Therapeutic Immunology & Infect","Significant differences exist in the availability of healthcare worker (HCW) SARS-CoV-2 testing between countries, and existing programmes focus on screening symptomatic rather than asymptomatic staff. Over a 3-week period (April 2020), 1,032 asymptomatic HCWs were screened for SARS-CoV-2 in a large UK teaching hospital. Symptomatic staff and symptomatic household contacts were additionally tested. Real-time RT-PCR was used to detect viral RNA from a throat+nose self-swab. 3% of HCWs in the asymptomatic screening group tested positive for SARS-CoV-2. 17/30 (57%) were truly asymptomatic/pauci-symptomatic. 12/30 (40%) had experienced symptoms compatible with coronavirus disease 2019 (COVID-19) >7 days prior to testing, most self-isolating, returning well. Clusters of HCW infection were discovered on two independent wards. Viral genome sequencing showed that the majority of HCWs had the dominant lineage B{middle dot}1. Our data demonstrates the utility of comprehensive screening of HCWs with minimal or no symptoms. This approach will be critical for protecting patients and hospital staff. @@ -5800,21 +5739,6 @@ We illustrate how the potential for the relaxation of restrictions interacts wit We find that the outcome of any future policy is strongly influenced by the contact matrix between segments and the relationships between physical distancing measures and transmission rates. These relationships are difficult to quantify so close monitoring of the epidemic would be essential during and after the exit from lockdown. More generally, S&S has potential applications for any infectious disease for which there are defined proportions of the population who cannot be treated or who are at risk of severe outcomes.",epidemiology,fuzzy,100,100 -medRxiv,10.1101/2020.05.06.20092999,2020-05-07,https://medrxiv.org/cgi/content/short/2020.05.06.20092999,OpenSAFELY: factors associated with COVID-19-related hospital death in the linked electronic health records of 17 million adult NHS patients.,- The OpenSAFELY Collaborative; Elizabeth Williamson; Alex J Walker; Krishnan J Bhaskaran; Seb Bacon; Chris Bates; Caroline E Morton; Helen J Curtis; Amir Mehrkar; David Evans; Peter Inglesby; Jonathan Cockburn; Helen I Mcdonald; Brian MacKenna; Laurie Tomlinson; Ian J Douglas; Christopher T Rentsch; Rohini Mathur; Angel Wong; Richard Grieve; David Harrison; Harriet Forbes; Anna Schultze; Richard T Croker; John Parry; Frank Hester; Sam Harper; Rafael Perera; Stephen Evans; Liam Smeeth; Ben Goldacre,; London School of Hygiene and Tropical Medicine; University of Oxford; London School of Hygiene and Tropical Medicine; University of Oxford; TPP; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; TPP; London School of Hygiene and Tropical Medicine; University of Oxford; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; ICNARC; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; University of Oxford; TPP; TPP; TPP; University of Oxford; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; University of Oxford,"BackgroundEstablishing who is at risk from a novel rapidly arising cause of death, and why, requires a new approach to epidemiological research with very large datasets and timely data. Working on behalf of NHS England we therefore set out to deliver a secure and pseudonymised analytics platform inside the data centre of a major primary care electronic health records vendor establishing coverage across detailed primary care records for a substantial proportion of all patients in England. The following results are preliminary. - -Data sourcesPrimary care electronic health records managed by the electronic health record vendor TPP, pseudonymously linked to patient-level data from the COVID-19 Patient Notification System (CPNS) for death of hospital inpatients with confirmed COVID-19, using the new OpenSAFELY platform. - -Population17,425,445 adults. - -Time period1st Feb 2020 to 25th April 2020. - -Primary outcomeDeath in hospital among people with confirmed COVID-19. - -MethodsCohort study analysed by Cox-regression to generate hazard ratios: age and sex adjusted, and multiply adjusted for co-variates selected prospectively on the basis of clinical interest and prior findings. - -ResultsThere were 5683 deaths attributed to COVID-19. In summary after full adjustment, death from COVID-19 was strongly associated with: being male (hazard ratio 1.99, 95%CI 1.88-2.10); older age and deprivation (both with a strong gradient); uncontrolled diabetes (HR 2.36 95% CI 2.18-2.56); severe asthma (HR 1.25 CI 1.08-1.44); and various other prior medical conditions. Compared to people with ethnicity recorded as white, black people were at higher risk of death, with only partial attenuation in hazard ratios from the fully adjusted model (age-sex adjusted HR 2.17 95% CI 1.84-2.57; fully adjusted HR 1.71 95% CI 1.44-2.02); with similar findings for Asian people (age-sex adjusted HR 1.95 95% CI 1.73-2.18; fully adjusted HR 1.62 95% CI 1.431.82). - -ConclusionsWe have quantified a range of clinical risk factors for death from COVID-19, some of which were not previously well characterised, in the largest cohort study conducted by any country to date. People from Asian and black groups are at markedly increased risk of in-hospital death from COVID-19, and contrary to some prior speculation this is only partially attributable to pre-existing clinical risk factors or deprivation; further research into the drivers of this association is therefore urgently required. Deprivation is also a major risk factor with, again, little of the excess risk explained by co-morbidity or other risk factors. The findings for clinical risk factors are concordant with policies in the UK for protecting those at highest risk. Our OpenSAFELY platform is rapidly adding further NHS patients records; we will update and extend these results regularly.",epidemiology,fuzzy,100,100 medRxiv,10.1101/2020.05.02.20078642,2020-05-06,https://medrxiv.org/cgi/content/short/2020.05.02.20078642,Impact of ethnicity on outcome of severe COVID-19 infection. Data from an ethnically diverse UK tertiary centre,James T Teo; Daniel Bean; Rebecca Bendayan; Richard Dobson; Ajay Shah,Kings College Hospital NHS Foundation Trust; King's College London; King's College London; Kings College London; King's College London,"During the current COVID-19 pandemic, it has been suggested that BAME background patients may be disproportionately affected compared to White but few detailed data are available. We took advantage of near real-time hospital data access and analysis pipelines to look at the impact of ethnicity in 1200 consecutive patients admitted between 1st March 2020 and 12th May 2020 to Kings College Hospital NHS Trust in London (UK). Our key findings are firstly that BAME patients are significantly younger and have different co-morbidity profiles than White individuals. Secondly, there is no significant independent effect of ethnicity on severe outcomes (death or ITU admission) within 14-days of symptom onset, after adjustment for age, sex and comorbidities.",intensive care and critical care medicine,fuzzy,100,100 @@ -6025,9 +5949,6 @@ C_LI",epidemiology,fuzzy,100,100 medRxiv,10.1101/2020.04.02.20051334,2020-04-06,https://medrxiv.org/cgi/content/short/2020.04.02.20051334,Rapid implementation of mobile technology for real-time epidemiology of COVID-19,David A. Drew; Long H. Nguyen; Claire J. Steves; Jonathan Wolf; Tim D. Spector; Andrew T. Chan; COPE Consortium,Massachusetts General Hospital; Massachusetts General Hospital; King's College London; Zoe Global Limited; King's College London; Massachusetts General Hospital; ,"The rapid pace of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic (COVID-19) presents challenges to the robust collection of population-scale data to address this global health crisis. We established the COronavirus Pandemic Epidemiology (COPE) consortium to bring together scientists with expertise in big data research and epidemiology to develop a COVID-19 Symptom Tracker mobile application that we launched in the UK on March 24, 2020 and the US on March 29, 2020 garnering more than 2.25 million users to date. This mobile application offers data on risk factors, herald symptoms, clinical outcomes, and geographical hot spots. This initiative offers critical proof-of-concept for the repurposing of existing approaches to enable rapidly scalable epidemiologic data collection and analysis which is critical for a data-driven response to this public health challenge. One Sentence SummaryCOVID-19 symptom tracker for smartphones",epidemiology,fuzzy,100,100 -medRxiv,10.1101/2020.04.02.20051284,2020-04-06,https://medrxiv.org/cgi/content/short/2020.04.02.20051284,Building an International Consortium for Tracking Coronavirus Health Status,Eran Segal; Feng Zhang; Xihong Lin; Gary King; Ophir Shalem; Smadar Shilo; William E. Allen; Yonatan H. Grad; Casey S. Greene; Faisal Alquaddoomi; Simon Anders; Ran Balicer; Tal Bauman; Ximena Bonilla; Gisel Booman; Andrew T. Chan; Ori Ori Cohen; Silvano Coletti; Natalie Davidson; Yuval Dor; David A. Drew; Olivier Elemento; Georgina Evans; Phil Ewels; Joshua Gale; Amir Gavrieli; Benjamin Geiger; Iman Hajirasouliha; Roman Jerala; Andre Kahles; Olli Kallioniemi; Ayya Keshet; Gregory Landua; Tomer Meir; Aline Muller; Long H. Nguyen; Matej Oresic; Svetlana Ovchinnikova; Hedi Peterson; Jay Rajagopal; Gunnar Ratsch; Hagai Rossman; Johan Rung; Andrea Sboner; Alexandros Sigaras; Tim Spector; Ron Steinherz; Irene Stevens; Jaak Vilo; Paul Wilmes; CCC (Coronavirus Census Collective),"Weizmann Institute of Science; Howard Hughes Medical Institute, Core Member, Broad Institute of MIT and Harvard, United States; Departments of Biostatistics and Statistics, Harvard T.H. Chan School of Public Health; Albert J. Weatherhead III University, Institute for Quantitative Social Science, Harvard University; Department of Genetics, Perelman School of Medicine, University of Pennsylvania, United States; Department of Computer Science and Applied Mathematics, and Department of Molecular Cell Biology, Weizmann Institute of Science, Israel; Society of Fellows, Harvard University, United States; Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, United States; Department of Systems Pharmacology and Translational Therapeutics, Perelman School of Medicine, University of Pennsylvania, United States; ETH Zurich, NEXUS Personalized Health Technologies, Zurich, Switzerland; Center for Molecular Biology (ZMBH), University of Heidelberg, Germany; Clalit Research Institute, Clalit Health Services, Israel; Mapping and Geo-Information Engineering, Civil and Environmental Engineering Faculty, The Technion, Israel; ETH Zurich, Department for Computer Science, Zurich, University Hospital Zurich, Medical Informatics, Zurich and SIB Swiss Institute of Bioinformatics, Zurich, ; Regen Network, Argentina; Massachusetts General Hospital (MGH), United States; Department of Computer Science and Applied Mathematics, and Department of Molecular Cell Biology, Weizmann Institute of Science, Israel; Chelonia Applied Science, Switzerland; ETH Zurich, Department for Computer Science, Zurich, University Hospital Zurich, Medical Informatics, Zurich and SIB Swiss Institute of Bioinformatics, Zurich, ; School of Medicine-IMRIC-Developmental Biology and Cancer Research, The Hebrew University; Massachusetts General Hospital (MGH), United States; Englander Institute for Precision Medicine and Department of Physiology and Biophysics, Weill Cornell Medicine, USA; Institute for Quantitative Social Science, Harvard University; Science for Life Laboratory (SciLifeLab), Department of Biochemistry and Biophysics, Stockholm University, Sweden; symptometrics.org; Department of Computer Science and Applied Mathematics, and Department of Molecular Cell Biology, Weizmann Institute of Science, Israel; Department of immunology, Weizmann Institute of Science, Israel; Englander Institute for Precision Medicine and Department of Physiology and Biophysics, Weill Cornell Medicine, USA; Department of Synthetic biology and Immunology, National Institute of Chemistry, Slovenia; ETH Zurich, Department for Computer Science, Zurich, University Hospital Zurich, Medical Informatics, Zurich and SIB Swiss Institute of Bioinformatics, Zurich, ; Science for Life Laboratory (SciLifeLab), Department of Oncology and Pathology, Karolinska Institutet, Stockholm, Sweden; Department of Computer Science and Applied Mathematics, and Department of Molecular Cell Biology, Weizmann Institute of Science, Israel; Regen Network, United States; Department of Computer Science and Applied Mathematics, and Department of Molecular Cell Biology, Weizmann Institute of Science, Israel; Luxembourg Institute of Socio-Economic Research and University of Luxembourg, Luxembourg; Massachusetts General Hospital (MGH), United States; School of Medical Sciences, Orebro University, Orebro, Sweden, and Turku Bioscience Centre, University of Turku and Abo Akademi University, Turku, Finland; Center for Molecular Biology (ZMBH), University of Heidelberg, Germany; Institute of Computer Science, University of Tartu, Estonia, Estonia; Internal Medicine, Harvard Medical School, Department of Pulmonary Medicine and Critical Care, Massachusetts General Hospital (MGH), United States; ETH Zurich, Department for Computer Science, Zurich, University Hospital Zurich, Medical Informatics, Zurich and SIB Swiss Institute of Bioinformatics, Zurich a; Department of Computer Science and Applied Mathematics, and Department of Molecular Cell Biology, Weizmann Institute of Science, Israel; Science for Life Laboratory (SciLifeLab), Department of Immunology, Genetics and Pathology, Uppsala university, Sweden; Englander Institute for Precision Medicine and Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, USA; Englander Institute for Precision Medicine and Department of Physiology and Biophysics, Weill Cornell Medicine, USA; Kings College, United Kingdom; Regen Network, United States; Science for Life Laboratory (SciLifeLab), Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet, Sweden; Institute of Computer Science, University of Tartu, Estonia, Estonia; Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Luxembourg; ","Information is the most potent protective weapon we have to combat a pandemic, at both the individual and global level. For individuals, information can help us make personal decisions and provide a sense of security. For the global community, information can inform policy decisions and offer critical insights into the epidemic of COVID-19 disease. Fully leveraging the power of information, however, requires large amounts of data and access to it. To achieve this, we are making steps to form an international consortium, Coronavirus Census Collective (CCC, coronaviruscensuscollective.org), that will serve as a hub for integrating information from multiple data sources that can be utilized to understand, monitor, predict, and combat global pandemics. These sources may include self-reported health status through surveys (including mobile apps), results of diagnostic laboratory tests, and other static and real-time geospatial data. This collective effort to track and share information will be invaluable in predicting hotspots of disease outbreak, identifying which factors control the rate of spreading, informing immediate policy decisions, evaluating the effectiveness of measures taken by health organizations on pandemic control, and providing critical insight on the etiology of COVID-19. It will also help individuals stay informed on this rapidly evolving situation and contribute to other global efforts to slow the spread of disease. - -In the past few weeks, several initiatives across the globe have surfaced to use daily self-reported symptoms as a means to track disease spread, predict outbreak locations, guide population measures and help in the allocation of healthcare resources. The aim of this paper is to put out a call to standardize these efforts and spark a collaborative effort to maximize the global gain while protecting participant privacy.",infectious diseases,fuzzy,100,100 medRxiv,10.1101/2020.04.01.20049908,2020-04-06,https://medrxiv.org/cgi/content/short/2020.04.01.20049908,"The effect of non-pharmaceutical interventions on COVID-19 cases, deaths and demand for hospital services in the UK: a modelling study",Nicholas G Davies; Adam J Kucharski; Rosalind M Eggo; Amy Gimma; - CMMID COVID-19 Working Group; W. John Edmunds,London School of Hygiene and Tropical Medicine; London School of Hygiene & Tropical Medicine; London School of Hygiene & Tropical Medicine; London School of Hygiene & Tropical Medicine; -; London School of Hygiene & Tropical Medicine,"BackgroundNon-pharmaceutical interventions have been implemented to reduce transmission of SARS-CoV-2 in the UK. Projecting the size of an unmitigated epidemic and the potential effect of different control measures has been critical to support evidence-based policymaking during the early stages of the epidemic. MethodsWe used a stochastic age-structured transmission model to explore a range of intervention scenarios, including the introduction of school closures, social distancing, shielding of elderly groups, self-isolation of symptomatic cases, and extreme ""lockdown""-type restrictions. We simulated different durations of interventions and triggers for introduction, as well as combinations of interventions. For each scenario, we projected estimated new cases over time, patients requiring inpatient and critical care (intensive care unit, ICU) treatment, and deaths. @@ -6077,6 +5998,7 @@ MethodsWe used data from a survey of social contact behaviour that specifically FindingsGroups of 50+ individuals accounted for 0.5% of reported contact events, and we estimate that the PAF due to groups of 50+ people is 5.4% (95%CI 1.4%, 11.5%). The PAF due to groups of 20+ people is 18.9% (12.7%, 25.7%) and the PAF due to groups of 10+ is 25.2% (19.4%, 31.4%) InterpretationLarge groups of individuals have a relatively small epidemiological impact; small and medium sized groups between 10 and 50 people have a larger impact on an epidemic.",epidemiology,fuzzy,100,100 +medRxiv,10.1101/2020.03.10.20033761,2020-03-13,https://medrxiv.org/cgi/content/short/2020.03.10.20033761,Inferring the number of COVID-19 cases from recently reported deaths,Thibaut Jombart; Kevin van Zandvoort; Tim Russell; Christopher Jarvis; Amy Gimma; Sam Abbott; Samuel Clifford; Sebastian Funk; Hamish Gibbs; Yang Liu; Carl Pearson; Nikos Bosse; Centre for the Mathematical Modelling of Infectious Diseases COVID-19 Working Group; Rosalind M Eggo; Adam J Kucharski; John Edmunds,London School of Hygiene and Tropical Medicine (LSHTM); London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene & Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; ; London School of Hygiene & Tropical Medicine; London School of Hygiene & Tropical Medicine; London School of Hygiene and Tropical Medicine,"We estimate the number of COVID-19 cases from newly reported deaths in a population without previous reports. Our results suggest that by the time a single death occurs, hundreds to thousands of cases are likely to be present in that population. This suggests containment via contact tracing will be challenging at this point, and other response strategies should be considered. Our approach is implemented in a publicly available, user-friendly, online tool.",epidemiology,fuzzy,100,100 medRxiv,10.1101/2020.03.09.20033050,2020-03-12,https://medrxiv.org/cgi/content/short/2020.03.09.20033050,"The effect of control strategies that reduce social mixing on outcomes of the COVID-19 epidemic in Wuhan, China",Kiesha Prem; Yang Liu; Tim Russell; Adam J Kucharski; Rosalind M Eggo; Nicholas Davies; Centre for the Mathematical Modelling of Infectious Diseases COVID-19 Working Group; Mark Jit; Petra Klepac,London School of Hygiene & Tropical Medicine; London School of Hygiene & Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene & Tropical Medicine; London School of Hygiene & Tropical Medicine; London School of Hygiene & Tropical Medicine; ; London School of Hygiene & Tropical Medicine; London School of Hygiene & Tropical Medicine,"BACKGROUNDIn December 2019, a novel strain of SARS-CoV-2 emerged in Wuhan, China. Since then, the city of Wuhan has taken unprecedented measures and efforts in response to the outbreak. METHODSWe quantified the effects of control measures on population contact patterns in Wuhan, China, to assess their effects on the progression of the outbreak. We included the latest estimates of epidemic parameters from a transmission model fitted to data on local and internationally exported cases from Wuhan in the age-structured epidemic framework. Further, we looked at the age-distribution of cases. Lastly, we simulated lifting of the control measures by allowing people to return to work in a phased-in way, and looked at the effects of returning to work at different stages of the underlying outbreak. diff --git a/data/covid/preprints.exact.csv b/data/covid/preprints.exact.csv index 4e6d785a..2e42d93a 100644 --- a/data/covid/preprints.exact.csv +++ b/data/covid/preprints.exact.csv @@ -96,13 +96,6 @@ MethodsWe estimated associations between long COVID (derived using self-reported ResultsAmong 20,112 observations across four population surveys, 13% reported having COVID-19 with symptoms that impeded their ability to function normally - 10.7% had such symptoms for <4 weeks (acute COVID-19), 1.2% had such symptoms for 4-12 weeks (ongoing symptomatic COVID-19) and 0.6% had such symptoms for >12 weeks (post-COVID-19 syndrome). We found that post-COVID-19 syndrome was associated with worse subjective financial well-being (adjusted relative risk ratios (aRRR)=1.57, 95% confidence interval (CI)=1.25, 1.96) and new benefit claims (aRRR=1.79, CI=1.27, 2.53). Associations were broadly similar across sexes and education levels. These results were not meaningfully altered when scaled to represent the population by age. ConclusionsLong COVID was associated with financial disruption in the UK. If our findings reflect causal effects, extending employment protection and financial support to people with long COVID may be warranted.",public and global health,exact,100,100 -medRxiv,10.1101/2023.05.23.23289798,2023-05-24,https://medrxiv.org/cgi/content/short/2023.05.23.23289798,Primary Care Post-COVID syndrome Diagnosis and Referral Coding,Robert Willans; Gail Allsopp; Pall Jonsson; Fiona Glen; Felix Greaves; John Macleod; Yinghui Wei; Sebastian Bacon; Amir Mehrkar; Alex Walker; Brian MacKenna; Louis Fisher; Ben Goldacre; - The OpenSAFELY Collaborative; - The CONVALESCENCE Collaborative,"National Institute of Health and Care Excellence; Royal College of General Practitioners; National Institute of Health and Care Excellence; National Institute of Health and Care Excellence; National Institute of Health and Care Excellence; University of Bristol; University of Plymouth; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford; ; ","IntroductionGuidelines for diagnosing and managing Post-COVID syndrome have been rapidly developed. Consistency of the application of these guidelines in primary care is unknown. Electronic health records provide an opportunity to review the use of codes relating to Post-COVID syndrome. This paper explores the use of primary care records as a surrogate uptake measure for NICEs rapid guideline ""managing the long-term effects of COVID-19"" by measuring the use of Post-COVID syndrome diagnosis and referral codes in the pathway. - -MethodWith the approval of NHS England we used routine clinical data from the OpenSafely-EMIS/-TPP platforms. Counts of Post-COVID syndrome diagnosis and referral codes were generated from a cohort of all adults, establishing numbers of diagnoses and referrals following diagnosis. The relationship between Post-COVID syndrome diagnosis and referral codes was explored with reference to NICEs rapid guideline. - -ResultsOf over 45 million patients, 69,220 (0.15%) had a Post-COVID syndrome diagnostic code, and 67,741 (0.15%) had a referral code. 78% of referral codes did not have an associated diagnosis code. 79% of diagnosis codes had no subsequent referral code. Only 18,633 (0.04%) had both. There were higher rates of both diagnosis and referral in those who were more deprived, female and some ethnic groups. - -DiscussionThis study demonstrates variation in diagnosis and referral coding rates for Post-COVID syndrome across different patient groups. The results, with limited crossover of referral and diagnostic codes, suggest only one type of code is usually recorded. Recording one code limits the use of routine data for monitoring Post-COVID syndrome diagnosis and management, but suggests several areas for improvement in coding. Post-COVID syndrome coding, particularly diagnosis coding, needs to improve before administrators and researchers can use it to evaluate care pathways.",epidemiology,exact,100,100 medRxiv,10.1101/2023.05.17.23290105,2023-05-24,https://medrxiv.org/cgi/content/short/2023.05.17.23290105,Within-host SARS-CoV-2 viral kinetics informed by complex life course exposures reveals different intrinsic properties of Omicron and Delta variants,Timothy W Russell; Hermaleigh Townsley; Sam Abbott; Joel Hellewell; Edward J Carr; Lloyd Chapman; Rachael Pung; Billy J Quilty; David Hodgson; Ashley Fowler; Lorin Adams; Christopher Bailey; Harriet V Mears; Ruth Harvey; Bobbi Clayton; Nicola O'Reilly; Yenting Ngai; Jerome Nicod; Steve Gamblin; Bryan Williams; Sonia Gandhi; Charles Swanton; Rupert Beale; David LV Bauer; Emma C Wall; Adam Kucharski,London School of Hygiene and Tropical Medicine; The Francis Crick Institute; London School of Hygiene and Tropical Medicine; European Molecular Biology Laboratory; The Francis Crick Institute; Lancaster University; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; The Francis Crick Institute; The Francis Crick Institute; The Francis Crick Institute; The Francis Crick Institute; The Francis Crick Institute; The Francis Crick Institute; The Francis Crick Institute; The Francis Crick Institute; The Francis Crick Institute; The Francis Crick Institute; National Institute for Health Research (NIHR) University College London Hospitals (UCLH); The Francis Crick Institute; The Francis Crick Institute; The Francis Crick Institute; The Francis Crick Institute; The Francis Crick Institute; London School of Hygiene and Tropical Medicine,"The emergence of successive SARS-CoV-2 variants of concern (VOC) during 2020-22, each exhibiting increased epidemic growth relative to earlier circulating variants, has created a need to understand the drivers of such growth. However, both pathogen biology and changing host characteristics - such as varying levels of immunity - can combine to influence replication and transmission of SARS-CoV-2 within and between hosts. Disentangling the role of variant and host in individual-level viral shedding of VOCs is essential to inform COVID-19 planning and response, and interpret past epidemic trends. Using data from a prospective observational cohort study of healthy adult volunteers undergoing weekly occupational health PCR screening, we developed a Bayesian hierarchical model to reconstruct individual-level viral kinetics and estimate how different factors shaped viral dynamics, measured by PCR cycle threshold (Ct) values over time. Jointly accounting for both inter-individual variation in Ct values and complex host characteristics - such as vaccination status, exposure history and age - we found that age and number of prior exposures had a strong influence on peak viral replication. Older individuals and those who had at least five prior antigen exposures to vaccination and/or infection typically had much lower levels of shedding. Moreover, we found evidence of a correlation between the speed of early shedding and duration of incubation period when comparing different VOCs and age groups. Our findings illustrate the value of linking information on participant characteristics, symptom profile and infecting variant with prospective PCR sampling, and the importance of accounting for increasingly complex population exposure landscapes when analysing the viral kinetics of VOCs.",epidemiology,exact,100,100 medRxiv,10.1101/2023.05.08.23289442,2023-05-11,https://medrxiv.org/cgi/content/short/2023.05.08.23289442,Cohort Profile: Post-hospitalisation COVID-19 study (PHOSP-COVID),Omer Elneima; Hamish J C McAuley; Olivia C Leavy; James D Chalmers; Alex Horsley; Ling-Pei Ho; Michael Marks; Krisnah Poinasamy; Betty Raman; Aarti Shikotra; Amisha Singapuri; Marco Sereno; Victoria C Harris; Linzy Houchen-Wolloff; Ruth M Saunders; Neil J Greening; Matthew Richardson; Jennifer K Quint; Andrew Briggs; Annemarie B Docherty; Steven Kerr; Ewen M Harrison; Nazir I Lone; Mathew Thorpe; Liam G Heaney; Keir E Lewis; Raminder Aul; Paul Beirne; Charlotte E Bolton; Jeremy S Brown; Gourab Choudhury; Nawar Diar Bakerly; Nicholas Easom; Carlos Echevarria; Jonathan Fuld; Nick Hart; John R Hurst; Mark G Jones; Dhruv Parekh; Paul E Pfeffer; Najib M Rahman; Sarah L Rowland-Jones; AA Roger Thompson; Caroline Jolley; Ajay M Shah; Dan G Wootton; Trudie Chalder; Melanie J Davies; Anthony De Soyza; John R Geddes; William Greenhalf; Simon Heller; Luke S Howard; Joseph Jacob; R Gisli Jenkins; Janet M Lord; William D-C Man; Gerry P McCann; Stefan Neubauer; Peter JM Openshaw; Joanna C Porter; Matthew J Rowland; Janet T Scott; Malcolm G Semple; Sally J Singh; David C Thomas; Mark Toshner; Aziz Sheikh; Chris E Brightling; Louise v Wain; Rachael A Evans; - on behalf of the PHOSP-COVID Collaborative Group,"The Institute for Lung Health, NIHR Leicester Biomedical Research Centre-Respiratory, University of Leicester, Leicester, UK; The Institute for Lung Health, NIHR Leicester Biomedical Research Centre-Respiratory, University of Leicester, Leicester, UK; Department of Population Health Sciences, University of Leicester, Leicester, UK; University of Dundee, Ninewells Hospital and Medical School, Dundee, UK; Division of Infection, Immunity & Respiratory Medicine, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK; MRC Human Immunology Unit, University of Oxford, Oxford, UK; Department of Clinical Research, London School of Hygiene & Tropical Medicine, London, UK; Asthma and Lung UK, London, UK; Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK; The Institute for Lung Health, NIHR Leicester Biomedical Research Centre-Respiratory, University of Leicester, Leicester, UK; The Institute for Lung Health, NIHR Leicester Biomedical Research Centre-Respiratory, University of Leicester, Leicester, UK; The Institute for Lung Health, NIHR Leicester Biomedical Research Centre-Respiratory, University of Leicester, Leicester, UK; The Institute for Lung Health, NIHR Leicester Biomedical Research Centre-Respiratory, University of Leicester, Leicester, UK; Centre for Exercise and Rehabilitation Science, NIHR Leicester Biomedical Research Centre- Respiratory, University of Leicester, Leicester, UK; The Institute for Lung Health, NIHR Leicester Biomedical Research Centre-Respiratory, University of Leicester, Leicester, UK; The Institute for Lung Health, NIHR Leicester Biomedical Research Centre-Respiratory, University of Leicester, Leicester, UK; The Institute for Lung Health, NIHR Leicester Biomedical Research Centre-Respiratory, University of Leicester, Leicester, UK; National Heart and Lung Institute, Imperial College London, London, UK; London School of Hygiene & Tropical Medicine, London, UK; Centre for Medical Informatics, The Usher Institute, University of Edinburgh, Edinburgh, UK; The Roslin Institute, University of Edinburgh, Edinburgh, UK; Centre for Medical Informatics, The Usher Institute, University of Edinburgh, Edinburgh, UK; Centre for Medical Informatics, The Usher Institute, University of Edinburgh, Edinburgh, UK; Centre for Medical Informatics, The Usher Institute, University of Edinburgh, Edinburgh, UK; Wellcome-Wolfson Institute for Experimental Medicine, Queens University Belfast, Belfast, UK; Hywel Dda University Health Board, Wales, UK; St George's University Hospitals NHS Foundation Trust, London, UK; Leeds Teaching Hospitals NHS Trust, Leeds, UK; NIHR Nottingham Biomedical Research Centre, University of Nottingham, Nottingham, UK; UCL Respiratory, Department of Medicine, University College London, London, UK; Centre for Inflammation Research, University of Edinburgh, Edinburgh, UK; Salford Royal NHS Foundation Trust, Manchester, UK; Infection Research Group, Hull University Teaching Hospitals, Hull, UK; Translational and Clinical Research Institute, Newcastle University, Newcastle Upon Tyne, UK; Department of Respiratory Medicine, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK; Lane Fox Respiratory Unit, Guy's and St Thomas' NHS Foundation Trust, London, UK; Royal Free London NHS Foundation Trust, London, UK; Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton, UK; Institute of Inflammation and Ageing, University of Birmingham, Birmingham, UK; Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK; NIHR Oxford Biomedical Research Centre, Oxford, UK; University of Sheffield, Sheffield, UK; University of Sheffield, Sheffield, UK; Centre for Human & Applied Physiological Sciences, School of Basic & Medical Biosciences, Faculty of Life Sciences & Medicine, King's College London, London, UK; King's College London British Heart Foundation Centre, London, UK; NIHR Health Protection Research Unit in Emerging and Zoonotic Infections, University of Liverpool, Liverpool, UK; Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK; NIHR Leicester Biomedical Research Centre, University of Leicester, Leicester, UK; Population Health Sciences Institute, Newcastle University, Newcastle Upon Tyne, UK; NIHR Oxford Health Biomedical Research Centre, University of Oxford, Oxford, UK; The CRUK Liverpool Experimental Cancer Medicine Centre, Liverpool, UK; Department of Oncology and Metabolism, University of Sheffield, Sheffield, UK; Imperial College Healthcare NHS Trust, London, UK; Centre for Medical Image Computing, University College London, London, UK; National Heart and Lung Institute, Imperial College London, London, UK; MRC-Versus Arthritis Centre for Musculoskeletal Ageing Research, Institute of Inflammation and Ageing, University of Birmingham, Birmingham, UK; Royal Brompton & Harefield Hospitals, Guy's and St. Thomas' NHS Foundation Trust, London, UK; Department of Cardiovascular Sciences, University of Leicester and the NIHR Leicester Biomedical Research Centre, Glenfield Hospital, Leicester; NIHR Oxford Biomedical Research Centre, Oxford, UK; National Heart and Lung Institute, Imperial College London, London, UK; UCL Respiratory, Department of Medicine, University College London, London, UK; Kadoorie Centre for Critical Care Research, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK; MRC-University of Glasgow Center for Virus research; NIHR Health Protection Research Unit in Emerging and Zoonotic Infections, University of Liverpool, Liverpool, UK; Centre for Exercise and Rehabilitation Science, NIHR Leicester Biomedical Research Centre-Respiratory, University of Leicester, Leicester, UK; Department of Immunology and Inflammation, Imperial College London, London, UK; NIHR Cambridge Biomedical Research Centre, Cambridge, United Kingdom; Centre for Medical Informatics, The Usher Institute, University of Edinburgh, Edinburgh, UK; The Institute for Lung Health, NIHR Leicester Biomedical Research Centre-Respiratory, University of Leicester, Leicester, UK; Department of Population Health Sciences, University of Leicester, Leicester, UK; The Institute for Lung Health, NIHR Leicester Biomedical Research Centre-Respiratory, University of Leicester, Leicester, UK; ","O_LIPHOSP-COVID is a national UK multi-centre cohort study of patients who were hospitalised for COVID-19 and subsequently discharged. C_LIO_LIPHOSP-COVID was established to investigate the medium- and long-term sequelae of severe COVID-19 requiring hospitalisation, understand the underlying mechanisms of these sequelae, evaluate the medium- and long-term effects of COVID-19 treatments, and to serve as a platform to enable future studies, including clinical trials. @@ -445,26 +438,6 @@ FindingsOf 8,799,079 visits, 147,278 (1{middle dot}7%) were PCR-positive. Over t InterpretationChange-points in growth rates of SARS-CoV-2 can be detected in near real-time using ISR and second derivatives of GAMs. To increase certainty about changes in epidemic trajectories both methods could be run in parallel. Running either method in near real-time on different infection surveillance data streams could provide timely warnings of changing underlying epidemiology. FundingUK Health Security Agency, Department of Health and Social Care (UK), Welsh Government, Department of Health (on behalf of the Northern Ireland Government), Scottish Government, National Institute for Health Research.",epidemiology,exact,100,100 -medRxiv,10.1101/2022.09.11.22279823,2022-09-12,https://medrxiv.org/cgi/content/short/2022.09.11.22279823,Effects of the COVID-19 pandemic on the mental health of clinically extremely vulnerable children and children living with clinically extremely vulnerable people in Wales: A data linkage study,Laura Elizabeth Cowley; Karen Hodgson; Jiao Song; Tony Whiffen; Jacinta Tan; Ann John; Amrita Bandyopadhyay; Alisha R Davies,Swansea University; Public Health Wales; Public Health Wales; Welsh Government; University of Oxford; Swansea University; Swansea University; Public Health Wales,"ObjectivesTo determine whether clinically extremely vulnerable (CEV) children or children living with a CEV person in Wales were at greater risk of presenting with anxiety or depression in primary or secondary care during the COVID-19 pandemic compared with children in the general population, and to compare patterns of anxiety and depression during the pandemic (23rd March 2020-31st January 2021, referred to as 2020/21) and before the pandemic (March 23rd 2019-January 31st 2020, referred to as 2019/20), between CEV children and the general population. - -DesignPopulation-based cross-sectional cohort study using anonymised, linked, routinely collected health and administrative data held in the Secure Anonymised Information Linkage Databank. CEV individuals were identified using the COVID-19 Shielded Patient List. - -SettingPrimary and secondary healthcare settings covering 80% of the population of Wales. - -ParticipantsChildren aged 2-17 in Wales: CEV (3,769); living with a CEV person (20,033); or neither (415,009). - -Primary outcome measureFirst record of anxiety or depression in primary or secondary healthcare in 2019/20 and 2020/21, identified using Read and ICD-10 codes. - -ResultsA Cox regression model adjusted for demographics and history of anxiety or depression revealed that only CEV children were at greater risk of presenting with anxiety or depression during the pandemic compared with the general population (Hazard Ratio=2.27, 95% Confidence Interval=1.94-2.66, p<0.001). Compared with the general population, the risk amongst CEV children was higher in 2020/21 (Risk Ratio 3.04) compared with 2019/20 (Risk Ratio 1.90). In 2020/21, the cumulative incidence of anxiety or depression increased slightly amongst CEV children, but declined amongst the general population. - -ConclusionsDifferences in the cumulative incidences of recorded anxiety or depression in healthcare between CEV children and the general population were largely driven by a reduction in presentations to healthcare services by children in the general population during the pandemic. - -Strengths and limitations of this studyO_LIStrengths of this study include its novelty, national focus and clinical relevance; to date this is the first population-based study examining the effects of the COVID-19 pandemic on healthcare use for anxiety or depression amongst clinically extremely vulnerable (CEV) children and children living with a CEV person in Wales -C_LIO_LIWe compared 2020/21 data with pre-pandemic 2019/20 data for CEV children and children in the general population, to place the impact of the COVID-19 pandemic in the context of longer-term patterns of healthcare use -C_LIO_LIWe used a novel approach and linked multiple datasets to identify a cohort of children living with a CEV person in Wales during the COVID-19 pandemic -C_LIO_LIThere was heterogeneity within the Shielded Patient List that was used to create the cohorts of children identified as CEV or living with a CEV person, in terms of the type and severity of individuals underlying conditions; the manner in which people were added to the list; the time point that people were added to the list; and the extent to which people followed the shielding guidance -C_LIO_LIRoutinely collected healthcare data does not capture self-reported health, and is likely to underestimate the burden of common mental disorders in the population -C_LI",pediatrics,exact,100,100 medRxiv,10.1101/2022.09.01.22279473,2022-09-02,https://medrxiv.org/cgi/content/short/2022.09.01.22279473,Rebound in asthma exacerbations following relaxation of COVID-19 restrictions: a longitudinal population-based study (COVIDENCE UK),Florence Tydeman; Paul Pfeffer; Giulia Vivaldi; Hayley Holt; Mohammad Talaei; David Jolliffe; Gwyneth Davies; Ronan Lyons; Chris Griffiths; Frank Kee; Aziz Sheikh; Seif Shaheen; Adrian R Martineau,Queen Mary University of London; Queen Mary University of London; Queen Mary University of London; Queen Mary University of London; Queen Mary University of London; Queen Mary University of London; Swansea University; Swansea University; Queen Mary University of London; Queen's University Belfast; Edinburgh University; Queen Mary University of London; Queen Mary University of London,"BackgroundThe imposition of restrictions on social mixing early in the COVID-19 pandemic was followed by a reduction in asthma exacerbations in multiple settings internationally. Temporal trends in social mixing, incident acute respiratory infections (ARI) and asthma exacerbations following relaxation of COVID-19 restrictions have not yet been described. MethodsWe conducted a population-based longitudinal study in 2,312 UK adults with asthma between November 2020 and April 2022. Details of face covering use, social mixing, incident ARI and moderate/severe asthma exacerbations were collected via monthly on-line questionnaires. Temporal changes in these parameters were visualised using Poisson generalised additive models. Multilevel logistic regression was used to test for associations between incident ARI and risk of asthma exacerbations, adjusting for potential confounders. @@ -474,27 +447,6 @@ ResultsRelaxation of COVID-19 restrictions from April 2021 coincided with reduce ConclusionsRelaxation of COVID-19 restrictions coincided with decreased face covering use, increased social mixing and a rebound in ARI and asthma exacerbations. Associations between incident ARI and risk of moderate/severe asthma exacerbation were similar for non-COVID-19 ARI and COVID-19, both before and after emergence of the SARS-CoV-2 omicron variant. FundingBarts Charity, UKRI",respiratory medicine,exact,100,100 -medRxiv,10.1101/2022.08.29.22279359,2022-08-31,https://medrxiv.org/cgi/content/short/2022.08.29.22279359,Prophylactic Treatment of COVID-19 in Care Homes Trial (PROTECT-CH),Philip M Bath; Jonathan Ball; Matthew Boyd; Heather Gage; Matthew Glover; Maureen Godfrey; Bruce Guthrie; Jonathan Hewitt; Robert Howard; Thomas Jaki; Edmund Juszczak; Daniel Lasserson; Paul Leighton; Val Leyland; Wei Shen Lim; Pip Logan; Garry Meakin; Alan Montgomery; Reuben Ogollah; Peter Passmore; Philip Quinlan; Caroline Rick; Simon Royal; Susan D Shenkin; Clare Upton; Adam L Gordon; - PROTECT-CH Trialists,University of Nottingham; University of Nottingham; University of Nottingham; University of Surrey; University of Surrey; Private person; University of Edinburgh; Llandough Hospital; University College London; University of Cambridge; University of Nottingham; University of Warwick; University of Nottingham; Private person; Nottingham University Hospitals NHS Trust; University of Nottingham; University of Nottingham; University of Nottingham; University of Nottingham; Queen's University Belfast; University of Nottingham; University of Nottingham; Cripps Health Centre; University of Edinburgh; University of Nottingham; University of Nottingham; ,"BackgroundCoronavirus disease 2019 (COVID-19) is associated with significant mortality and morbidity in care homes. Novel or repurposed antiviral drugs may reduce infection and disease severity through reducing viral replication and inflammation. - -ObjectiveTo compare the safety and efficacy of antiviral agents (ciclesonide, niclosamide) for preventing SARS-CoV-2 infection and COVID-19 severity in care home residents. - -DesignCluster-randomised open-label blinded endpoint platform clinical trial testing antiviral agents in a post-exposure prophylaxis paradigm. - -SettingCare homes across all four United Kingdom member countries. - -ParticipantsCare home residents 65 years of age or older. - -InterventionsCare homes were to be allocated at random by computer to 42 days of antiviral agent plus standard care versus standard of care and followed for 60 days after randomisation. - -Main outcome measuresThe primary four-level ordered categorical outcome with participants classified according to the most serious of all-cause mortality, all-cause hospitalisation, SARS-CoV-2 infection and no infection. Analysis using ordinal logistic regression was by intention to treat. Other outcomes included the components of the primary outcome and transmission. - -ResultsDelays in contracting between NIHR and the manufacturers of potential antiviral agents significantly delayed any potential start date. Having set up the trial (protocol, approvals, insurance, website, database, routine data algorithms, training materials), the trial was stopped in September 2021 prior to contracting of care homes and general practitioners in view of the success of vaccination in care homes with significantly reduced infections, hospitalisations and deaths. As a result, the sample size target (based on COVID-19 rates and deaths occurring in February-June 2020) became unfeasible. - -LimitationsCare home residents were not approached about the trial and so were not consented and did not receive treatment. Hence, the feasibility of screening, consent, treatment and data acquisition, and potential benefit of post exposure prophylaxis were never tested. Further, contracting between the University of Nottingham and the PIs, GPs and care homes was not completed, so the feasibility of contracting with all the different groups at the scale needed was not tested. - -ConclusionsThe role of post exposure prophylaxis of COVID-19 in care home residents was not tested because of changes in COVID-19 incidence, prevalence and virulence as a consequence of the vaccination programme that rendered the study unfeasible. Significant progress was made in describing and developing the infrastructure necessary for a large scale Clinical Trial of Investigational Medicinal Products in care homes in all four UK nations. - -Future workThe role of post-exposure prophylaxis of COVID-19 in care home residents remains to be defined. Significant logistical barriers to conducting research in care homes during a pandemic need to be removed before such studies are possible in the required short timescale.",infectious diseases,exact,100,100 medRxiv,10.1101/2022.08.29.22279333,2022-08-30,https://medrxiv.org/cgi/content/short/2022.08.29.22279333,A case-crossover study of the effect of vaccination on SARS-CoV-2 transmission relevant behaviours during a period of national lockdown in England and Wales,Aimee Serisier; Sarah Beale; Yamina I Boukari; Susan J Hoskins; Vincent Nguyen; Thomas Edward Byrne; Wing Lam Erica Fong; Ellen Fragaszy; Cyril Geismar; Jana Kovar; Alexei Yavlinsky; Andrew Hayward; Robert W Aldridge,University College London; University College London; University College London; Univerity College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London,"BackgroundStudies of COVID-19 vaccine effectiveness show increases in COVID-19 cases within 14 days of a first dose, potentially reflecting post-vaccination behaviour changes associated with SARS-CoV-2 transmission before vaccine protection. However, direct evidence for a relationship between vaccination and behaviour is lacking. We aimed to examine the association between vaccination status and self-reported non-household contacts and non-essential activities during a national lockdown in England and Wales. MethodsParticipants (n=1,154) who had received the first dose of a COVID-19 vaccine reported non-household contacts and non-essential activities from February to March 2021 in monthly surveys during a national lockdown in England and Wales. We used a case-crossover study design and conditional logistic regression to examine the association between vaccination status (pre-vaccination vs. 14 days post-vaccination) and self-reported contacts and activities within individuals. Stratified subgroup analyses examined potential effect heterogeneity by sociodemographic characteristics such as sex, household income or age group. @@ -628,6 +580,15 @@ MethodsIn an online survey distributed to all staff at 18 geographically dispers ResultsWe identified 33 topics, grouped into two domains, each containing four themes. Our findings emphasise: the deleterious effect of increased workloads, lack of PPE, inconsistent advice/guidance, and lack of autonomy; differing experiences of home working as negative/positive; and the benefits of supportive leadership and peers in ameliorating challenges. Themes varied by demographics and time: discussion of home working decreasing over time, while discussion of workplace challenges increased. Discussion of mental health was lowest between September-November 2020, between the first and second waves of COVID-19 in the UK. DiscussionOur findings represent the most salient experiences of HCWs through the pandemic. STM enabled statistical examination of how the qualitative themes raised differed according to participant characteristics. This relatively underutilised methodology in healthcare research can provide more nuanced, yet generalisable, evidence than that available via surveys or small interview studies, and should be used in future research.",psychiatry and clinical psychology,exact,100,100 +medRxiv,10.1101/2022.06.16.22276476,2022-06-16,https://medrxiv.org/cgi/content/short/2022.06.16.22276476,Moral injury and psychological wellbeing in UK healthcare staff,Victoria Williamson; Danielle Lamb; Matthew Hotopf; Rosalind Raine; Sharon Stevelink; Simon Wessely; Mary Jane Docherty; Ira Madan; Dominic Murphy; Neil Greenberg,King's College London; UCL; King's College London; King's College London; King's College London; King's College London; South London and Maudsley NHS Foundation Trust; Guy's and St Thomas' NHS Foundation Trust; King's College London; King's College London,"BackgroundPotentially morally injurious events (PMIEs) can negatively impact mental health. The COVID-19 pandemic may have placed healthcare staff at risk of moral injury. + +AimTo examine the impact of PMIE on healthcare staff wellbeing. + +Method12,965 healthcare staff (clinical and non-clinical) were recruited from 18 NHS-England trusts into a survey of PMIE exposure and wellbeing. + +ResultsPMIEs were significantly associated with adverse mental health symptoms across healthcare staff. Specific work factors were significantly associated with experiences of moral injury, including being redeployed, lack of PPE, and having a colleague die of COVID-19. Nurses who reported symptoms of mental disorders were more likely to report all forms of PMIEs than those without symptoms (AOR 2.7; 95% CI 2.2, 3.3). Doctors who reported symptoms were only more likely to report betrayal events, such as breach of trust by colleagues (AOR 2.7, 95% CI 1.5, 4.9). + +ConclusionsA considerable proportion of NHS healthcare staff in both clinical and non-clinical roles report exposure to PMIEs during the COVID-19 pandemic. Prospective research is needed to identify the direction of causation between moral injury and mental disorder as well as continuing to monitor the longer term outcomes of exposure to PMIEs.",psychiatry and clinical psychology,exact,100,100 medRxiv,10.1101/2022.06.12.22276307,2022-06-13,https://medrxiv.org/cgi/content/short/2022.06.12.22276307,"Occupation, Worker Vulnerability, and COVID-19 Vaccination Uptake: Analysis of the Virus Watch prospective cohort study",Sarah Beale; Rachel Burns; Isobel Braithwaite; Thomas Edward Byrne; Wing Lam Erica Fong; Ellen Fragaszy; Cyril Geismar; Susan J Hoskins; Jana Kovar; Annalan Mathew Dwight Navaratnam; Parth Patel; Alexei Yavlinsky; Martie J Van Tongeren; Robert W Aldridge; Andrew Hayward,University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University of Manchester; University College London; University College London,"BackgroundOccupational disparities in COVID-19 vaccine uptake can impact the effectiveness of vaccination programmes and introduce particular risk for vulnerable workers and those with high workplace exposure. This study aimed to investigate COVID-19 vaccine uptake by occupation, including for vulnerable groups and by occupational exposure status. MethodsWe used data from employed or self-employed adults who provided occupational information as part of the Virus Watch prospective cohort study (n=19,595) and linked this to study-obtained information about vulnerability-relevant characteristics (age, medical conditions, obesity status) and work-related COVID-19 exposure based on the Job Exposure Matrix. Participant vaccination status for the first, second, and third dose of any COVID-19 vaccine was obtained based on linkage to national records and study records. We calculated proportions and Sison-Glaz multinomial 95% confidence intervals for vaccine uptake by occupation overall, by vulnerability-relevant characteristics, and by job exposure. @@ -652,13 +613,6 @@ ResultsFollowing an initial plateau of 1.54% until mid-January, infection preval ConclusionHigh-resolution prevalence data fitted to P-splines allowed us to show that the lockdown was highly effective at reducing risk of infection with school holidays/closures playing a significant part.",infectious diseases,exact,100,100 medRxiv,10.1101/2022.05.23.22275458,2022-05-25,https://medrxiv.org/cgi/content/short/2022.05.23.22275458,Covid-19 is a leading cause of death in children and young people ages 0-19 years in the United States,Seth Flaxman; Charles Whittaker; Elizaveta Semenova; Theo Rashid; Robbie Parks; Alexandra Blenkinsop; H Juliette T Unwin; Swapnil Mishra; Samir Bhatt; Deepti Gurdasani; Oliver Ratmann,"Oxford; Imperial College London; AstraZeneca; Imperial College London; Columbia University; Imperial College London; Imperial College London; University of Copenhagen; University of Copenhagen, Imperial College London; Queen Mary University of London; Imperial College London","Covid-19 has caused more than 1 million deaths in the US, including at least 1,204 deaths among children and young people (CYP) aged 0-19 years, with 796 occurring in the one year period April 1, 2021 - March 31, 2022. Deaths among US CYP are rare in general, and so we argue here that the mortality burden of Covid-19 in CYP is best understood in the context of all other causes of CYP death. Using publicly available data from CDC WONDER on NCHSs 113 Selected Causes of Death, and comparing to mortality in 2019, the immediate pre-pandemic period, we find that Covid-19 mortality is among the 10 leading causes of death in CYP aged 0-19 years in the US, ranking 8th among all causes of deaths, 5th in disease-related causes of deaths (excluding accidents, assault and suicide), and 1st in deaths caused by infectious or respiratory diseases. Covid-19 deaths constitute 2.3% of the 10 leading causes of death in this age group. Covid-19 caused substantially more deaths in CYP than major vaccine-preventable diseases did historically in the period before vaccines became available. Various factors including underreporting and Covid-19s role as a contributing cause of death from other diseases mean that our estimates may understate the true mortality burden of Covid-19. Our findings underscore the public health relevance of Covid-19 to CYP. In the likely future context of sustained SARS-CoV-2 circulation, pharmaceutical and non-pharmaceutical interventions will continue to play an important role in limiting transmission of the virus in CYP and mitigating severe disease.",infectious diseases,exact,100,100 -medRxiv,10.1101/2022.05.19.22275214,2022-05-22,https://medrxiv.org/cgi/content/short/2022.05.19.22275214,Antibody levels following vaccination against SARS-CoV-2: associations with post-vaccination infection and risk factors,Nathan J Cheetham; Milla Kibble; Andrew Wong; Richard J Silverwood; Anika Knuppel; Dylan M Williams; Olivia K L Hamilton; Paul H Lee; Charis Bridger Staatz; Giorgio Di Gessa; Jingmin Zhu; Srinivasa Vittal Katikireddi; George B Ploubidis; Ellen J Thompson; Ruth C E Bowyer; Xinyuan Zhang; Golboo Abbasian; Maria Paz Garcia; Deborah Hart; Jeffrew Seow; Carl Graham; Neophytos Kouphou; Sam Acors; Michael H Malim; Ruth E Mitchell; Kate Northstone; Daniel Major-Smith; Sarah Matthews; Thomas Breeze; Michael Crawford; Lynn Molloy; Alex Siu Fung Kwong; Katie J Doores; Nishi Chaturvedi; Emma L Duncan; Nicholas J Timpson; Claire J Steves,King's College London; University of Cambridge; University College London; University College London; University College London; University College London; University of Glasgow; University of Leicester; University College London; University College London; University College London; University of Glasgow; University College London; King's College London; King's College London; King's College London; King's College London; King's College London; King's College London; King's College London; King's College London; King's College London; King's College London; King's College London; University of Bristol; University of Bristol; University of Bristol; University of Bristol; University of Bristol; University of Bristol; University of Bristol; University of Bristol; King's College London; University College London; King's College London; University of Bristol; King's College London,"SARS-CoV-2 antibody levels can be used to assess humoral immune responses following SARS-CoV-2 infection or vaccination, and may predict risk of future infection. From cross-sectional antibody testing of 9,361 individuals from TwinsUK and ALSPAC UK population-based longitudinal studies (jointly in April-May 2021, and TwinsUK only in November 2021-January 2022), we tested associations between antibody levels following vaccination and: (1) SARS-CoV-2 infection following vaccination(s); (2) health, socio-demographic, SARS-CoV-2 infection and SARS-CoV-2 vaccination variables. - -Within TwinsUK, single-vaccinated individuals with the lowest 20% of anti-Spike antibody levels at initial testing had 3-fold greater odds of SARS-CoV-2 infection over the next six to nine months, compared to the top 20%. In TwinsUK and ALSPAC, individuals identified as at increased risk of COVID-19 complication through the UK ""Shielded Patient List"" had consistently greater odds (2 to 4-fold) of having antibody levels in the lowest 10%. Third vaccination increased absolute antibody levels for almost all individuals, and reduced relative disparities compared with earlier vaccinations. - -These findings quantify the association between antibody level and risk of subsequent infection, and support a policy of triple vaccination for the generation of protective antibodies. - -Lay summaryIn this study, we analysed blood samples from 9,361 participants from two studies in the UK: an adult twin registry, TwinsUK (4,739 individuals); and the Avon Longitudinal Study of Parents and Children, ALSPAC (4,622 individuals). We did this work as part of the UK Government National Core Studies initiative researching COVID-19. We measured blood antibodies which are specific to SARS-CoV-2 (which causes COVID-19). Having a third COVID-19 vaccination boosted antibody levels. More than 90% of people from TwinsUK had levels after third vaccination that were greater than the average level after second vaccination. Importantly, this was the case even in individuals on the UK ""Shielded Patient List"". We found that people with lower antibody levels after first vaccination were more likely to report having COVID-19 later on, compared to people with higher antibody levels. People on the UK ""Shielded Patient List"", and individuals who reported that they had poorer general health, were more likely to have lower antibody levels after vaccination. In contrast, people who had had a previous COVID-19 infection were more likely to have higher antibody levels following vaccination compared to people without infection. People receiving the Oxford/AstraZeneca rather than the Pfizer BioNTech vaccine had lower antibody levels after one or two vaccinations. However, after a third vaccination, there was no difference in antibody levels between those who had Oxford/AstraZeneca and Pfizer BioNTech vaccines for their first two doses. These findings support having a third COVID-19 vaccination to boost antibodies.",epidemiology,exact,100,100 medRxiv,10.1101/2022.05.10.22274890,2022-05-10,https://medrxiv.org/cgi/content/short/2022.05.10.22274890,Biopsychosocial response to the COVID-19 lockdown in people with major depressive disorder and multiple sclerosis.,Sara Siddi; Iago Gine Vazquez; Raquel Bailon; Faith Matcham; Femke Lamers; Spyridon Kontaxis; Estela Laporta Puyal; Esther Garcia; Belen Arranz; Gloria Dallacosta; Anna Isabel Guerrero Perez; Anna Zabalza; Mathias Buron; Giancarlo Comi; Letizia Leocani; Peter Annas; Matthew Hotopf; Brenda Penninx; Melinda Magyari; Per Sorensen; Xavier Montalban; Grace Lavalle; Alina Ivan; Carolin Oetzmann; Katie White; Sonia Difrancesco; Patrick Locatelli; Jordi Aguilo; Vaibhav Narayan; Amos Folarin; Richard Dobson; Judith Anne Dineley; Daniel Leightley; Nicholas Cummins; Yarharth Ranjan; Zulqarnain Rashid; Aki Rintala; Giovanni De Girolamo; Antonio Preti; Sara Simblett; Til Wykes; Inez Myin-Germeys; Josep Maria Haro,"Parc Sanitari Sant Joan de Deu Cibersam; Parc Sanitari Sant Joan de Deu Cibersam; Universidad de Zaragoza; King's College London; Amsterdam UMC Locatie AMC, Amsterdam, North Holland, NL; Universidad de Zaragoza; Universidad de Zaragoza; Universitat Autonoma de Barcelona; Parc Sanitari Sant Joan de Deu Cibersam; Istituto di Ricovero e Cura a Carattere Scientifico Ospedale San Raffaele Milano; Vall d'Hebron Institut de Recerca; Vall d'Hebron Institut de Recerca; Copenhagen University Hospital Kobenhavn; Istituto di Ricovero e Cura a Carattere Scientifico Ospedale San Raffaele Milano; Istituto di Ricovero e Cura a Carattere Scientifico Ospedale San Raffaele Milano; H Lundbeck AS Valby; Institute of Psychiatry, Psychological Medicine; Amsterdam UMC Locatie AMC, Amsterdam, North Holland, NL; Copenhagen University Hospital Kobenhavn; Copenhagen University Hospital Kobenhavn; Vall d'Hebron Institut de Recerca; King's College London; King's College London; King's College London; King's College London; Amsterdam UMC Locatie AMC, Amsterdam, North Holland, NL; University of Bergamo; Universitat Autonoma de Barcelona; King's College London; King's College London; King's College London; King's College London; King's College London; King's College London; King's College London; King's College London; Katholieke Universiteit Leuven; Centro San Giovanni di Dio Fatebenefratelli; Universita degli Studi di Torino; King's College London; King's College London; KU Leuven; Parc Sanitari Sant Joan de Deu Cibersam","BackgroundChanges in lifestyle, finances and work status during COVID-19 lockdowns may have led to biopsychosocial changes in people with pre-existing vulnerabilities such as Major Depressive Disorders (MDD) and Multiple Sclerosis (MS). MethodsData were collected as a part of the RADAR-CNS (Remote Assessment of Disease and Relapse - Central Nervous System) programme. We analyzed the following data from long-term participants in a decentralized multinational study: symptoms of depression, heart rate (HR) during the day and night; social activity; sedentary state, steps and physical activity of varying intensity. Linear mixed-effects regression analyses with repeated measures were fitted to assess the changes among three time periods (pre, during and post-lockdown) across the groups, adjusting for depression severity before the pandemic and gender. @@ -959,15 +913,6 @@ Implications of all the available evidenceWe find evidence that four vaccines, u medRxiv,10.1101/2021.12.23.21268276,2021-12-25,https://medrxiv.org/cgi/content/short/2021.12.23.21268276,Risk of myocarditis following sequential COVID-19 vaccinations by age and sex,Martina Patone; Winnie Xue Mei; Lahiru Handunnetthi; Sharon Dixon; Francesco Zaccardi; Manu Shankar-Hari; Peter Watkinson; Kamlesh Khunti; Anthony Harnden; Carol AC Coupland; Keith M. Channon; Nicholas L Mills; Aziz Sheikh; Julia Hippisley-Cox,University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Leicester; University of Edinburgh; University of Oxford; University of Leicester; University of Oxford; University of Oxford; University of Oxford; University of Edinburgh; University of Edinburgh; University of Oxford,"In an updated self-controlled case series analysis of 42,200,614 people aged 13 years or more, we evaluate the association between COVID-19 vaccination and myocarditis, stratified by age and sex, including 10,978,507 people receiving a third vaccine dose. Myocarditis risk was increased during 1-28 days following a third dose of BNT162b2 (IRR 2.02, 95%CI 1.40, 2.91). Associations were strongest in males younger than 40 years for all vaccine types with an additional 3 (95%CI 1, 5) and 12 (95% CI 1,17) events per million estimated in the 1-28 days following a first dose of BNT162b2 and mRNA-1273, respectively; 14 (95%CI 8, 17), 12 (95%CI 1, 7) and 101 (95%CI 95, 104) additional events following a second dose of ChAdOx1, BNT162b2 and mRNA-1273, respectively; and 13 (95%CI 7, 15) additional events following a third dose of BNT162b2, compared with 7 (95%CI 2, 11) additional events following COVID-19 infection. An association between COVID-19 infection and myocarditis was observed in all ages for both sexes but was substantially higher in those older than 40 years. These findings have important implications for public health and vaccination policy. FundingHealth Data Research UK.",epidemiology,exact,100,100 -medRxiv,10.1101/2021.12.22.21268252,2021-12-24,https://medrxiv.org/cgi/content/short/2021.12.22.21268252,Rapid increase in Omicron infections in England during December 2021: REACT-1 study,Paul Elliott; Barbara Bodinier; Oliver Eales; Haowei Wang; David Haw; Joshua Elliott; Matthew Whitaker; Jakob Jonnerby; David Tang; Caroline E. Walters; Christina Atchinson; Peter J. Diggle; Andrew J. Page; Alex Trotter; Deborah Ashby; Wendy Barclay; Graham Taylor; Helen Ward; Ara Darzi; Graham Cooke; Marc Chadeau-Hyam; Christl A Donnelly,"School of Public Health, Imperial College London, UKImperial College Healthcare NHS Trust, UKNational Institute for Health Research Imperial Biomedical Research; School of Public Health, Imperial College London, UK; School of Public Health, Imperial College London, UKMRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergency; School of Public Health, Imperial College London, UKMRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergency; School of Public Health, Imperial College London, UKMRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergency; Imperial College London; School of Public Health, Imperial College London, UK; School of Public Health, Imperial College London, UKMRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergency; Imperial College London; School of Public Health, Imperial College London, UKMRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergency; School of Public Health, Imperial College London, UK; CHICAS, Lancaster Medical School, Lancaster University, UK and Health Data Research, UK; Quadram Institute, Norwich, UK; Quadram Institute Bioscience; School of Public Health, Imperial College London, UK; Department of Infectious Disease, Imperial College London, UK; Department of Infectious Disease, Imperial College London, UK; School of Public Health, Imperial College London, UKImperial College Healthcare NHS Trust, UKNational Institute for Health Research Imperial Biomedical Research; Imperial College Healthcare NHS Trust, UKNational Institute for Health Research Imperial Biomedical Research Centre, UKInstitute of Global Health Innovation at ; Department of Infectious Disease, Imperial College London, UKImperial College Healthcare NHS Trust, UKNational Institute for Health Research Imperial Biomedical; School of Public Health, Imperial College London, UK; School of Public Health, Imperial College London, UKMRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergency","BackgroundThe highest-ever recorded numbers of daily severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections in England has been observed during December 2021 and have coincided with a rapid rise in the highly transmissible Omicron variant despite high levels of vaccination in the population. Although additional COVID-19 measures have been introduced in England and internationally to contain the epidemic, there remains uncertainty about the spread and severity of Omicron infections among the general population. - -MethodsThe REal-time Assessment of Community Transmission-1 (REACT-1) study has been monitoring the prevalence of SARS-CoV-2 infection in England since May 2020. REACT-1 obtains self-administered throat and nose swabs from a random sample of the population of England at ages 5 years and over. Swabs are tested for SARS-CoV-2 infection by reverse transcription polymerase chain reaction (RT-PCR) and samples testing positive are sent for viral genome sequencing. To date 16 rounds have been completed, each including [~]100,000 or more participants with data collected over a period of 2 to 3 weeks per month. Socio-demographic, lifestyle and clinical information (including previous history of COVID-19 and symptoms prior to swabbing) is collected by online or telephone questionnaire. Here we report results from round 14 (9-27 September 2021), round 15 (19 October - 05 November 2021) and round 16 (23 November - 14 December 2021) for a total of 297,728 participants with a valid RT-PCR test result, of whom 259,225 (87.1%) consented for linkage to their NHS records including detailed information on vaccination (vaccination status, date). We used these data to estimate community prevalence and trends by age and region, to evaluate vaccine effectiveness against infection in children ages 12 to 17 years, and effect of a third (booster) dose in adults, and to monitor the emergence of the Omicron variant in England. - -ResultsWe observed a high overall prevalence of 1.41% (1.33%, 1.51%) in the community during round 16. We found strong evidence of an increase in prevalence during round 16 with an estimated reproduction number R of 1.13 (1.06, 1.09) for the whole of round 16 and 1.27 (1.14, 1.40) when restricting to observations from 1 December onwards. The reproduction number in those aged 18-54 years was estimated at 1.23 (1.14, 1.33) for the whole of round 16 and 1.41 (1.23, 1.61) from 1 December. Our data also provide strong evidence of a steep increase in prevalence in London with an estimated R of 1.62 (1.34, 1.93) from 1 December onwards and a daily prevalence reaching 6.07% (4.06%, 9.00%) on 14 December 2021. As of 1 to 11 December 2021, of the 275 lineages determined, 11 (4.0%) corresponded to the Omicron variant. The first Omicron infection was detected in London on 3 December, and subsequent infections mostly appeared in the South of England. The 11 Omicron cases were all aged 18 to 54 years, double-vaccinated (reflecting the large numbers of people who have received two doses of vaccine in this age group) but not boosted, 9 were men, 5 lived in London and 7 were symptomatic (5 with classic COVID-19 symptoms: loss or change of sense of smell or taste, fever, persistent cough), 2 were asymptomatic, and symptoms were unknown for 2 cases. The proportion of Omicron (vs Delta or Delta sub-lineages) was found to increase rapidly with a daily increase of 66.0% (32.7%, 127.3%) in the odds of Omicron (vs. Delta) infection, conditional on swab positivity. Highest prevalence of swab positivity by age was observed in (unvaccinated) children aged 5 to 11 years (4.74% [4.15%, 5.40%]) similar to the prevalence observed at these ages in round 15. In contrast, prevalence in children aged 12 to 17 years more than halved from 5.35% (4.78%, 5.99%) in round 15 to 2.31% (1.91%, 2.80%) in round 16. As of 14 December 2021, 76.6% children at ages 12 to 17 years had received at least one vaccine dose; we estimated that vaccine effectiveness against infection was 57.9% (44.1%, 68.3%) in this age group. In addition, the prevalence of swab positivity in adults aged 65 years and over fell by over 40% from 0.84% (0.72%, 0.99%) in round 15 to 0.48% (0.39%,0.59%) in round 16 and for those aged 75 years and over it fell by two-thirds from 0.63% (0.48%,0.82%) to 0.21% (0.13%,0.32%). At these ages a high proportion of participants (>90%) had received a third vaccine dose; we estimated that adults having received a third vaccine dose had a three- to four-fold lower risk of testing positive compared to those who had received two doses. - -ConclusionA large fall in swab positivity from round 15 to round 16 among 12 to 17 year olds, most of whom have been vaccinated, contrasts with the continuing high prevalence among 5 to 11 year olds who have largely not been vaccinated. Likewise there were large falls in swab positivity among people aged 65 years and over, the vast majority of whom have had a third (booster) vaccine dose; these results reinforce the importance of the vaccine and booster campaign. However, the rapidly increasing prevalence of SARS-CoV-2 infections in England during December 2021, coincident with the rapid rise of Omicron infections, may lead to renewed pressure on health services. Additional measures beyond vaccination may be needed to control the current wave of infections and prevent health services (in England and other countries) from being overwhelmed. - -SummaryThe unprecedented rise in SARS-CoV-2 infections is concurrent with rapid spread of the Omicron variant in England and globally. We analysed prevalence of SARS-CoV-2 and its dynamics in England from end of November to mid-December 2021 among almost 100,000 participants from the REACT-1 study. Prevalence was high during December 2021 with rapid growth nationally and in London, and of the proportion of infections due to Omicron. We observed a large fall in swab positivity among mostly vaccinated older children (12-17 years) compared with unvaccinated younger children (5-11 years), and in adults who received a third vs. two doses of vaccine. Our results reiterate the importance of vaccination and booster campaigns; however, additional measures may be needed to control the rapid growth of the Omicron variant.",epidemiology,exact,100,100 medRxiv,10.1101/2021.12.21.21268214,2021-12-23,https://medrxiv.org/cgi/content/short/2021.12.21.21268214,Comparative effectiveness of ChAdOx1 versus BNT162b2 vaccines against SARS-CoV-2 infections in England and Wales: A cohort analysis using trial emulation in the Virus Watch community data,Vincent Grigori Nguyen; Alexei Yavlinsky; Sarah Beale; Susan J Hoskins; Vasileios Lampos; Isobel Braithwaite; Thomas Edward Byrne; Wing Lam Erica Fong; Ellen Fragaszy; Cyril Geismar; Jana Kovar; Annalan M D Navaratnam; Parth Patel; Madhumita Shrotri; Sophie Weber; Andrew Hayward; Robert W Aldridge,University College London; University College London; University College London; Univerity College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London,"IntroductionInfections of SARS-CoV-2 in vaccinated individuals have been increasing globally. Understanding the associations between vaccine type and a post-vaccination infection could help prevent further COVID-19 waves. In this paper, we use trial emulation to understand the impact of a phased introduction of the vaccine in the UK driven by vulnerability and exposure status. We estimate the comparative effectiveness of COVID-19 vaccines (ChAdOx1 versus BNT162b2) against post-vaccination infections of SARS-CoV-2 in a community setting in England and Wales. MethodTrial emulation was conducted by pooling results from six cohorts whose recruitment was staggered between 1st January 2021 and 31st March 2021 and followed until 12th November 2021. Eligibility for each trial was based upon age (18+ at the time of vaccination), without prior signs of infection or an infection within the first 14 days of the first dose. Time from vaccination of ChAdOx1 or BNT162b2 until SARS-CoV-2 infection (positive polymerase chain reaction or lateral flow test after 14 of the vaccination) was modelled using Cox proportional hazards model for each cohort and adjusted for age at vaccination, gender, minority ethnic status, clinically vulnerable status and index of multiple deprivation quintile. For those without SARS-CoV-2 infection during the study period, follow-up was until loss-of-follow-up or end of study (12th November 2021). Pooled hazard ratios were generated using random-effects meta-analysis. @@ -1111,13 +1056,6 @@ Key pointsO_ST_ABSQuestionC_ST_ABSIs COVID-19 associated with higher long-term i FindingsIn this cohort study of 48 million adults in England and Wales, COVID-19 was associated with higher incidence, that declined with time since diagnosis, of both arterial thromboses [week 1: adjusted HR [aHR] 21.7 (95% CI 21.0-22.4) weeks 27-49: aHR 1.34 (1.21-1.48)] and venous thromboembolism [week 1: aHR 33.2 (31.3-35.2), weeks 27-49 1.80 (1.50-2.17)]. aHRs were higher, for longer, after hospitalised than non-hospitalised COVID-19. The estimated excess number of arterial thromboses and venous thromboembolisms was 10,500. MeaningAvoidance of COVID-19 infection through vaccination, and use of secondary preventive agents after infection in high-risk patients, may reduce post-COVID-19 acute vascular diseases.",infectious diseases,exact,100,100 -medRxiv,10.1101/2021.11.15.21266264,2021-11-16,https://medrxiv.org/cgi/content/short/2021.11.15.21266264,Association of COVID-19 employment disruption with mental and social wellbeing: evidence from nine UK longitudinal studies,Jacques Wels; Charlotte Booth; Bozena Wielgoszewska; Michael J Green; Giorgio Di Gessa; Charlotte F Huggins; Gareth J Griffith; Alex Siu Fung Kwong; Ruth C E Bowyer; Jane Maddock; Praveetha Patalay; Richard J Silverwood; Emla Fitzsimons; Richard John Shaw; Ellen J Thompson; Andrew Steptoe; Alun Hughes; Nishi Chaturvedi; Claire J Steves; Srinivasa Vittal Katikireddi; George B Ploubidis,University College London; University College London; University College London; University of Glasgow; University College London; University of Edinburgh; University of Bristol; University of Bristol; King's College London; University College London; University College London; University College London; University College London; University of Glasgow; Kings College London; University College London; University College London; University College London; King's College London; University of Glasgow; University College London,"BackgroundThe COVID-19 pandemic has led to major economic disruptions. In March 2020, the UK implemented the Coronavirus Job Retention Scheme - known as furlough - to minimize the impact of job losses. We investigate associations between change in employment status and mental and social wellbeing during the early stages of the pandemic. - -MethodsData were from 25,670 respondents, aged 17 to 66, across nine UK longitudinal studies. Furlough and other employment changes were defined using employment status pre-pandemic and during the first lockdown (April-June 2020). Mental and social wellbeing outcomes included psychological distress, life satisfaction, self-rated health, social contact, and loneliness. Study-specific modified Poisson regression estimates, adjusting for socio-demographic characteristics and pre-pandemic mental and social wellbeing measures, were pooled using meta-analysis. - -ResultsCompared to those who remained working, furloughed workers were at greater risk of psychological distress (adjusted risk ratio, ARR=1.12; 95% CI: 0.97, 1.29), low life satisfaction (ARR=1.14; 95% CI: 1.07, 1.22), loneliness (ARR=1.12; 95% CI: 1.01, 1.23), and poor self-rated health (ARR=1.26; 95% CI: 1.05, 1.50), but excess risk was less pronounced than that of those no longer employed (e.g., ARR for psychological distress=1.39; 95% CI: 1.21, 1.59) or in stable unemployment (ARR=1.33; 95% CI: 1.09, 1.62). - -ConclusionsDuring the early stages of the pandemic, those furloughed had increased risk for poor mental and social wellbeing. However, their excess risk was lower in magnitude than that of those who became or remained unemployed, suggesting that furlough may have partly mitigated poorer outcomes.",psychiatry and clinical psychology,exact,100,100 medRxiv,10.1101/2021.11.15.21266255,2021-11-16,https://medrxiv.org/cgi/content/short/2021.11.15.21266255,"COVID-19 vaccination, risk-compensatory behaviours, and social contacts in four countries in the UK",John Buckell; Joel Jones; Philippa C Matthews; Ian Diamond; Emma Rourke; Ruth Studley; Duncan Cook; Ann Sarah Walker; Koen B Pouwels; - The COVID-19 Infection Survey Team,University of Oxford; Office for National Statistics; University of Oxford; Office for National Statistics; Office for National Statistics; Office for National Statistics; Office for National Statistics; University of Oxford; University of Oxford; ,"The physiological effects of vaccination against SARS-CoV-2 (COVID-19) are well documented, yet the behavioural effects are largely unknown. Risk compensation suggests that gains in personal safety, as a result of vaccination, are offset by increases in risky behaviour, such as socialising, commuting and working outside the home. This is potentially problematic because transmission of SARS-CoV-2 is driven by contacts, which could be amplified by vaccine-related risk compensation behaviours. Here, we show that behaviours were overall unrelated to personal vaccination, but - adjusting for variation in mitigation policies - were responsive to the level of vaccination in the wider population: individuals in the UK were risk compensating when rates of vaccination were rising. This effect was observed across four nations of the UK, each of which varied policies autonomously.",infectious diseases,exact,100,100 medRxiv,10.1101/2021.11.10.21266124,2021-11-11,https://medrxiv.org/cgi/content/short/2021.11.10.21266124,Differences in COVID-19 vaccination coverage by occupation in England: a national linked data study,Vahe Nafilyan; Ted Dolby; Katie Finning; Jasper Morgan; Rhiannon Edge; Myer Glickman; Neil Pearce; Martie Van Tongeren,Office for National Statistics; Office for National Statistics; Office for National Statistics; Office for National Statistics; Lancaster University; Office for National Statistics; London School of Hygiene and Tropical Medicine; University of Manchester,"BackgroundMonitoring differences in COVID-19 vaccination uptake in different groups is crucial to help inform the policy response to the pandemic. A key gap is the absence of data on uptake by occupation. @@ -1302,6 +1240,13 @@ ResultsOf 46,162,942 adults, 21,193,814 (46%) had their first vaccination during Rates of intracranial venous thrombosis (ICVT) and thrombocytopenia in adults aged <70 years were higher 1-28 days after ChAdOx1-S (adjusted HRs 2.27, 95% CI:1.33- 3.88 and 1.71, 1.35-2.16 respectively), but not after BNT162b2 (0.59, 0.24-1.45 and 1.00, 0.75-1.34) compared with unvaccinated. The corresponding absolute excess risks of ICVT 1-28 days after ChAdOx1-S were 0.9-3 per million, varying by age and sex. ConclusionsIncreases in ICVT and thrombocytopenia after ChAdOx1-S vaccination in adults aged <70 years were small compared with its effect in reducing COVID-19 morbidity and mortality, although more precise estimates for adults <40 years are needed. For people aged [≥]70 years, rates of arterial or venous thrombotic, events were generally lower after either vaccine.",cardiovascular medicine,exact,100,100 +medRxiv,10.1101/2021.08.23.21262209,2021-08-23,https://medrxiv.org/cgi/content/short/2021.08.23.21262209,Population birth outcomes in 2020 and experiences of expectant mothers during the COVID-19 pandemic: a Born in Wales mixed methods study using routine data,Hope Jones; Mike Seaborne; Laura Cowley; David E Odd; Shantini Paranjothy; Ashley Akbari; Sinead Brophy,Swansea University; Swansea University; Public Health Wales; Cardiff University; University of Aberdeen; Swansea University; Swansea University,"BackgroundPregnancy can be a stressful time and the COVID-19 pandemic has affected all aspects of life. This study aims to investigate the impact of the pandemic on population birth outcomes in Wales, rates of primary immunisations and examine expectant mothers experiences of pregnancy including self-reported levels of stress and anxiety. + +MethodsPopulation-level birth outcomes in Wales: Stillbirths, prematurity, birth weight and Caesarean section births before (2016-2019) and during (2020) the pandemic were compared using national-level routine anonymised data held in the Secure Anonymised Information Linkage (SAIL) Databank. The first three scheduled primary immunisations were compared between 2019 and 2020. Self-reported pregnancy experience: 215 expectant mothers (aged 16+) in Wales completed an online survey about their experiences of pregnancy during the pandemic. The qualitative survey data was analysed using codebook thematic analysis. + +FindingsThere was no significant difference between annual outcomes including gestation and birth weight, stillbirths, and Caesarean sections for infants born in 2020 compared to 2016-2019. There was an increase in late term births ([≥]42 weeks gestation) during the first lockdown (OR: 1.28, p=0.019) and a decrease in moderate to late preterm births (32-36 weeks gestation) during the second lockdown (OR: 0.74, p=0.001). Fewer babies were born in 2020 (N=29,031) compared to 2016-2019 (average N=32,582). All babies received their immunisations in 2020, but there were minor delays in the timings of vaccines. Those due at 8-weeks were 8% less likely to be on time (within 28-days) and at 16-weeks, they were 19% less likely to be on time. The pandemic had a negative impact on the mental health of 71% of survey respondents, who reported anxiety, stress and loneliness; this was associated with attending scans without their partner, giving birth alone, and minimal contact with midwives. + +InterpretationThe pandemic had a negative impact on mothers experiences of pregnancy; however, population-level data suggests that this did not translate to adverse birth outcomes for babies born during the pandemic.",public and global health,exact,100,100 medRxiv,10.1101/2021.08.17.21262196,2021-08-22,https://medrxiv.org/cgi/content/short/2021.08.17.21262196,Controlled evaLuation of Angiotensin Receptor Blockers for COVID-19 respIraTorY disease (CLARITY): Statistical analysis plan for a randomised controlled Bayesian adaptive sample size trial,James McGree; Carinna Hockham; Sradha Kotwal; Arlen Wilcox; Abhinav Bassi; Carol Pollock; Louise M Burrell; Tom Snelling; Vivek Jha; Meg Jardine; Mark Jones,Queensland University of Technology; Imperial College London; University of New South Wales; University of New South Wales; The George Institute for Global Health; Royal North Shore Hospital; University of Melbourne; The University of Sydney; University of New South Wales; University of New South Wales; The University of Sydney,"The CLARITY trial (Controlled evaLuation of Angiotensin Receptor Blockers for COVID-19 respIraTorY Disease) investigates the effectiveness of angiotensin receptor blockers in addition to standard care compared to placebo (in Indian sites) with standard care in reducing the duration and severity of lung failure in patients with COVID-19. The CLARITY trial is a multi-centre, randomised controlled Bayesian adaptive trial with regular planned analyses where pre-specified decision rules will be assessed to determine whether the trial should be stopped due to sufficient evidence of treatment effectiveness or futility. Here we describe the statistical analysis plan for the trial, and define the pre-specified decision rules, including those that could lead to the trial being halted. The primary outcome is clinical status on a 7-point ordinal scale adapted from the WHO Clinical Progression scale assessed at Day 14. The primary analysis will follow the intention-to-treat principle. A Bayesian adaptive trial design was selected because there is considerable uncertainty about the extent of potential benefit of this treatment. Trial registrationClinicalTrials.gov, NCT04394117. Registered on 19 May 2020. @@ -1315,6 +1260,13 @@ medRxiv,10.1101/2021.08.13.21261889,2021-08-18,https://medrxiv.org/cgi/content/s One sentence summeryCare home residents show waning of nucleocapsid specific antibodies and enhanced expression of activation markers on SARS-CoV-2 specific cells",infectious diseases,exact,100,100 medRxiv,10.1101/2021.08.13.21261959,2021-08-13,https://medrxiv.org/cgi/content/short/2021.08.13.21261959,Factors influencing wellbeing in young people during COVID-19.,Michaela James; Hope Jones; Amana Baig; Emily Marchant; Tegan Waites; Charlotte Todd; Karen Hughes; Sinead Brophy,Swansea University; Swansea University; Swansea University; Swansea University; Swansea University; Public Health Wales; Bangor University; Swansea University,"COVID-19 infection and the resultant restrictions has impacted all aspects of life across the world. This study explores factors that promote or support wellbeing for young people during the pandemic, how they differ by age, using a self-reported online survey with those aged 8 - 25 in Wales between September 2020 and February 2021. Open-ended responses were analysed via thematic analysis to provide further context. A total of 6,291 responses were obtained from 81 education settings across Wales (including primary and secondary schools as well as sixth form, colleges and universities). Wellbeing was highest in primary school children and boys and lowest in those who were at secondary school children, who were girls and, those who preferred not to give a gender. Among primary school children, higher wellbeing was seen for those who played with others (rather than alone), were of Asian ethnicity (OR 2.3, 95% CI: 1.26 to 4.3), lived in a safe area (OR: 2.0, 95% CI: 1.67 to 2.5) and had more sleep. To support their wellbeing young people reported they would like to be able to play with their friends more. Among secondary school children those who were of mixed ethnicity reported lower wellbeing (OR: 5.10, 95% CI: 1.70 to 15.80). To support their wellbeing they reported they would like more support with mental health (due to anxiety and pressure to achieve when learning online). This study found self-reported wellbeing differed by gender, ethnicity and deprivation and found younger children report the need for play and to see friends to support wellbeing but older children/young people wanted more support with anxiety and educational pressures.",public and global health,exact,100,100 +medRxiv,10.1101/2021.08.12.21261987,2021-08-13,https://medrxiv.org/cgi/content/short/2021.08.12.21261987,Characterising the persistence of RT-PCR positivity and incidence in a community survey of SARS-CoV-2,Oliver Eales; Caroline E. Walters; Haowei Wang; David Haw; Kylie E. C. Ainslie; Christina Atchinson; Andrew Page; Sophie Prosolek; Alexander J. Trotter; Thanh Le Viet; Nabil-Fareed Alikhan; Leigh M Jackson; Catherine Ludden; - The COVID-19 Genomics UK (COG-UK) Consortium; Deborah Ashby; Christl A Donnelly; Graham Cooke; Wendy Barclay; Helen Ward; Ara Darzi; Paul Elliott; Steven Riley,"School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; School of Public Health, Imperial College London, UK; Quadram Institute, Norwich, UK; Quadram Institute, Norwich, UK; Quadram Institute, Norwich, UK; Quadram Institute, Norwich, UK; Quadram Institute, Norwich, UK; Medical School, University of Exeter, UK; Department of Medicine, University of Cambridge, UK; ; School of Public Health, Imperial College London, UK; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; Department of Infectious Disease, Imperial College London, UK Imperial College Healthcare NHS Trust, UK National Institute for Health Research Imperial Biomedic; Department of Infectious Disease, Imperial College London, UK; School of Public Health, Imperial College London, UK Imperial College Healthcare NHS Trust, UK National Institute for Health Research Imperial Biomedical Resear; Imperial College Healthcare NHS Trust, UK National Institute for Health Research Imperial Biomedical Research Centre, UK Institute of Global Health Innovation a; School of Public Health, Imperial College London, UK Imperial College Healthcare NHS Trust, UK National Institute for Health Research Imperial Biomedical Resear; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc","BackgroundCommunity surveys of SARS-CoV-2 RT-PCR swab-positivity provide prevalence estimates largely unaffected by biases from who presents for routine case testing. The REal-time Assessment of Community Transmission-1 (REACT-1) has estimated swab-positivity approximately monthly since May 2020 in England from RT-PCR testing of self-administered throat and nose swabs in random non-overlapping cross-sectional community samples. Estimating infection incidence from swab-positivity requires an understanding of the persistence of RT-PCR swab positivity in the community. + +MethodsDuring round 8 of REACT-1 from 6 January to 22 January 2021, of the 2,282 participants who tested RT-PCR positive, we recruited 896 (39%) from whom we collected up to two additional swabs for RT-PCR approximately 6 and 9 days after the initial swab. We estimated sensitivity and duration of positivity using an exponential model of positivity decay, for all participants and for subsets by initial N-gene cycle threshold (Ct) value, symptom status, lineage and age. Estimates of infection incidence were obtained for the entire duration of the REACT-1 study using P-splines. + +ResultsWe estimated the overall sensitivity of REACT-1 to detect virus on a single swab as 0.79 (0.77, 0.81) and median duration of positivity following a positive test as 9.7 (8.9, 10.6) days. We found greater median duration of positivity where there was a low N-gene Ct value, in those exhibiting symptoms, or for infection with the Alpha variant. The estimated proportion of positive individuals detected on first swab, P0, was found to be higher for those with an initially low N-gene Ct value and those who were pre-symptomatic. When compared to swab-positivity, estimates of infection incidence over the duration of REACT-1 included sharper features with evident transient increases around the time of key changes in social distancing measures. + +DiscussionHome self-swabbing for RT-PCR based on a single swab, as implemented in REACT-1, has high overall sensitivity. However, participants time-since-infection, symptom status and viral lineage affect the probability of detection and the duration of positivity. These results validate previous efforts to estimate incidence of SARS-CoV-2 from swab-positivity data, and provide a reliable means to obtain community infection estimates to inform policy response.",infectious diseases,exact,100,100 medRxiv,10.1101/2021.08.05.21259863,2021-08-07,https://medrxiv.org/cgi/content/short/2021.08.05.21259863,Recording of 'COVID-19 vaccine declined' among vaccination priority groups: a cohort study on 57.9 million NHS patients' primary care records in situ using OpenSAFELY,Helen J Curtis; Peter Inglesby; Brian MacKenna; Richard Croker; William J Hulme; Christopher T Rentsch; Krishnan Bhaskaran; Alex J Walker; Caroline E Morton; David Evans; Amir Mehrkar; Sebastian CJ Bacon; Christopher Bates; George Hickman; Tom Ward; Jessica Morley; Jonathan Cockburn; Simon Davy; Anna Schultze; Elizabeth J Williamson; Helen I McDonald; Laurie Tomlinson; Rohini Mathur; Rosalind M Eggo; Kevin Wing; Angel YS Wong; Harriet Forbes; John Tazare; John Parry; Frank Hester; Sam Harper; Shaun O'Hanlon; Alex Eavis; Richard Jarvis; Dima Avramov; Paul Griffiths; Aaron Fowles; Nasreen Parkes; Stephen JW Evans; Ian J Douglas; Liam Smeeth; Ben Goldacre,University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; TPP; University of Oxford; University of Oxford; University of Oxford; TPP; University of Oxford; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; TPP; TPP; TPP; EMIS; EMIS; EMIS; EMIS; EMIS; EMIS; EMIS; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; University of Oxford,"BackgroundAll patients in England within vaccine priority groups were offered a COVID-19 vaccine by mid-April 2021. Clinical record systems contain codes to denote when such an offer has been declined by a patient (although these can in some cases be entered for a variety of other reasons including vaccination delay, or other administrative issues). We set out to describe the patterns of usage of codes for COVID-19 vaccines being declined. MethodsWith the approval of NHS England and using the full pseudonymised primary care records for 57.9 million NHS patients, we identified all patients in key vaccine priority groups: aged over 50, or over 16 and at increased risk from COVID-19 (Clinically Extremely Vulnerable [CEV] or otherwise ""at risk""). We describe the proportion of patients recorded as declining a COVID-19 vaccination for each priority group, and by other clinical and demographic factors; whether patients recorded as ""declined"" subsequently went on to receive a vaccination; and the distribution of code usage across GP practices. @@ -1402,6 +1354,21 @@ Following two doses of Pfizer-BioNTech vaccine, antibody positivity (adjusted fo DiscussionThe successful roll out of the vaccination programme in England has led to a high proportion of individuals having detectable antibodies, particularly in older age groups and those who have had two doses of vaccine. This is likely to be associated with high levels of protection from severe disease, and possibly from infection. Nonetheless, there remain some key groups with a lower prevalence of antibody, notably unvaccinated younger people, certain minority ethnic groups, those living in deprived areas and workers in some public facing employment. Obtaining improved rates of vaccination in these groups is essential to achieving high levels of protection against the virus through population immunity. FundingDepartment of Health and Social Care in England.",infectious diseases,exact,100,100 +medRxiv,10.1101/2021.07.14.21260488,2021-07-16,https://medrxiv.org/cgi/content/short/2021.07.14.21260488,SARS-CoV-2 Antibody Lateral Flow Assay for antibody prevalence studies following vaccine roll out: a Diagnostic Accuracy Study,Alexandra H C Cann; Candice L Clarke; Jonathan C Brown; Tina Thomson; Maria Prendecki; Maya Moshe; Anjna Badhan; Paul Elliott; Ara Darzi; Steven Riley; Deborah Ashby; Michelle Willicombe; Peter Kelleher; Paul Randell; Helen Ward; Wendy Barclay; Graham Cooke,"Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London School of Public Health; Imperial College London; Dept Inf Dis Epi, Imperial College; Imperial College London; Imperial College London; Imperial College London; Imperial College Healthcare NHS Trust, UK; Imperial College London; Department of Infectious Disease, Imperial College London, UK; Imperial College London","BackgroundLateral flow immunoassays (LFIAs) have the potential to deliver affordable, large scale antibody testing and provide rapid results without the support of central laboratories. As part of the development of the REACT programme extensive evaluation of LFIA performance was undertaken with individuals following natural infection. Here we assess the performance of the selected LFIA to detect antibody responses in individuals who have received at least one dose of SARS-CoV-2 vaccine. + +MethodsThis is a prospective diagnostic accuracy study. + +SettingSampling was carried out at renal outpatient clinic and healthcare worker testing sites at Imperial College London NHS Trust. Laboratory analyses were performed across Imperial College London sites and university facilities. + +ParticipantsTwo cohorts of patients were recruited; the first was a cohort of 108 renal transplant patients attending clinic following SARS-CoV-2 vaccine booster, the second cohort comprised 40 healthcare workers attending for first SARS-CoV-2 vaccination, and 21 day follow up. A total of 186 paired samples were collected. + +InterventionsDuring the participants visit, capillary blood samples were analysed on LFIA device, while paired venous sampling was sent for serological assessment of antibodies to the spike protein (anti-S) antibodies. Anti-S IgG were detected using the Abbott Architect SARS-CoV-2 IgG Quant II CMIA. + +Main outcome measuresThe accuracy of Fortress LFIA in detecting IgG antibodies to SARS-CoV-2 compared to anti-spike protein detection on Abbott Assay. + +ResultsUsing the threshold value for positivity on serological testing of [≥]7.10 BAU/ml, the overall performance of the test produces an estimate of sensitivity of 91.94% (95% CI 85.67% to 96.06%) and specificity of 93.55% (95% CI 84.30% to 98.21%) using the Abbott assay as reference standard. + +ConclusionsFortress LFIA performs well in the detection of antibody responses for intended purpose of population level surveys, but does not meet criteria for individual testing.",infectious diseases,exact,100,100 medRxiv,10.1101/2021.07.08.21260185,2021-07-08,https://medrxiv.org/cgi/content/short/2021.07.08.21260185,REACT-1 round 13 interim report: acceleration of SARS-CoV-2 Delta epidemic in the community in England during late June and early July 2021,Steven Riley; Oliver Eales; David Haw; Haowei Wang; Caroline E. Walters; Kylie E.C. Ainslie; Christina Atchinson; Claudio Fronterre; Peter J. Diggle; Deborah Ashby; Christl A Donnelly; Wendy Barclay; Graham Cooke; Helen Ward; Ara Darzi; Paul Elliott,"School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; Imperial College London; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; School of Public Health, Imperial College London, UK; CHICAS, Lancaster Medical School, Lancaster University, UK and Health Data Research, UK; CHICAS, Lancaster Medical School, Lancaster University, UK and Health Data Research, UK; School of Public Health, Imperial College London, UK; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; Department of Infectious Disease, Imperial College London, UK; Department of Infectious Disease, Imperial College London, UK Imperial College Healthcare NHS Trust, UK National Institute for Health Research Imperial Biomedic; School of Public Health, Imperial College London, UK Imperial College Healthcare NHS Trust, UK National Institute for Health Research Imperial Biomedical Resear; Imperial College Healthcare NHS Trust, UK National Institute for Health Research Imperial Biomedical Research Centre, UK Institute of Global Health Innovation a; School of Public Health, Imperial College London, UK Imperial College Healthcare NHS Trust, UK National Institute for Health Research Imperial Biomedical Resear","BackgroundDespite high levels of vaccination in the adult population, cases of COVID-19 have risen exponentially in England since the start of May 2021 driven by the Delta variant. However, with far fewer hospitalisations and deaths per case during the recent growth in cases compared with 2020, it is intended that all remaining social distancing legislation in England will be removed from 19 July 2021. MethodsWe report interim results from round 13 of the REal-time Assessment of Community Transmission-1 (REACT-1) study in which a cross-sectional sample of the population of England was asked to provide a throat and nose swab for RT-PCR and to answer a questionnaire. Data collection for this report (round 13 interim) was from 24 June to 5 July 2021. @@ -1530,7 +1497,6 @@ ResultsIn total, 1,317 confirmed workplace outbreaks were identified from HPZone In total, 390 outbreaks were identified from SOI data and 264 of them allowed for estimation of attack rates. The overall median attack rate was 3.4% of the employed persons with confirmed COVID-19 at a workplace with an outbreak. Most of these outbreaks (162) had an attack rate less than 6%. However, in a small number of outbreaks (57) the attack rate was over 15%. The attack rates increased as the size of the enterprise decreased. The highest attack rate was for outbreaks in close contact services (median 16.5%), which was followed by outbreaks in restaurants and catering (median 10.2%), and in manufacturers and packers of non-food products (median 6.7%). ConclusionsOur linked dataset analysis approach allows early identification of geographical regions and industrial sectors with higher rates of COVID-19 workplace outbreaks as well as estimation of attack rates by enterprise size and sector. This can be used to inform interventions to limit transmission of the virus. Our approach to analysing the workplace outbreak data can also be applied to calculation of outbreak rates and attack rates in other types of settings such as care homes, hospitals and educational settings.",epidemiology,exact,100,100 -medRxiv,10.1101/2021.05.08.21256867,2021-05-14,https://medrxiv.org/cgi/content/short/2021.05.08.21256867,SARS-CoV-2 lineage dynamics in England from January to March 2021 inferred from representative community samples,Oliver Eales; Andrew Page; Sonja N. Tang; Caroline E. Walters; Haowei Wang; David Haw; Alexander J. Trotter; Thanh Le Viet; Ebenezer Foster-Nyarko; Sophie Prosolek; Christina Atchinson; Deborah Ashby; Graham Cooke; Wendy Barclay; Christl A Donnelly; Justin O'Grady; Erik Volz; - The COVID-19 Genomics UK (COG-UK) Consortium; Ara Darzi; Helen Ward; Paul Elliott; Steven Riley,"School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; Quadram Institute, Norwich, UK; School of Public Health, Imperial College London, UK; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; Quadram Institute, Norwich, UK; Quadram Institute, Norwich, UK; Quadram Institute, Norwich, UK; Quadram Institute, Norwich, UK; School of Public Health, Imperial College London, UK; School of Public Health, Imperial College London, UK; Department of Infectious Disease, Imperial College London, UK Imperial College Healthcare NHS Trust, UK National Institute for Health Research Imperial Biomedic; Department of Infectious Disease, Imperial College London, UK; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; Quadram Institute, Norwich, UK; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; ; Imperial College Healthcare NHS Trust, UK National Institute for Health Research Imperial Biomedical Research Centre, UK Institute of Global Health Innovation a; School of Public Health, Imperial College London, UK Imperial College Healthcare NHS Trust, UK National Institute for Health Research Imperial Biomedical Resear; School of Public Health, Imperial College London, UK Imperial College Healthcare NHS Trust, UK National Institute for Health Research Imperial Biomedical Resear; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc","Genomic surveillance for SARS-CoV-2 lineages informs our understanding of possible future changes in transmissibility and vaccine efficacy. However, small changes in the frequency of one lineage over another are often difficult to interpret because surveillance samples are obtained from a variety of sources. Here, we describe lineage dynamics and phylogenetic relationships using sequences obtained from a random community sample who provided a throat and nose swab for rt-PCR during the first three months of 2021 as part of the REal-time Assessment of Community Transmission-1 (REACT-1) study. Overall, diversity decreased during the first quarter of 2021, with the B.1.1.7 lineage (first identified in Kent) predominant, driven by a 0.3 unit higher reproduction number over the prior wild type. During January, positive samples were more likely B.1.1.7 in younger and middle-aged adults (aged 18 to 54) than in other age groups. Although individuals infected with the B.1.1.7 lineage were no more likely to report one or more classic COVID-19 symptoms compared to those infected with wild type, they were more likely to be antibody positive 6 weeks after infection. Viral load was higher in B.1.1.7 infection as measured by cycle threshold (Ct) values, but did not account for the increased rate of testing positive for antibodies. The presence of infections with non-imported B.1.351 lineage (first identified in South Africa) during January, but not during February or March, suggests initial establishment in the community followed by fade-out. However, this occurred during a period of stringent social distancing and targeted public health interventions and does not immediately imply similar lineages could not become established in the future. Sequence data from representative community surveys such as REACT-1 can augment routine genomic surveillance.",infectious diseases,exact,100,100 medRxiv,10.1101/2021.05.06.21256755,2021-05-13,https://medrxiv.org/cgi/content/short/2021.05.06.21256755,Clinical coding of long COVID in English primary care: a federated analysis of 58 million patient records in situ using OpenSAFELY,- The OpenSAFELY Collaborative; Alex J Walker; Brian MacKenna; Peter Inglesby; Christopher T Rentsch; Helen J Curtis; Caroline E Morton; Jessica Morley; Amir Mehrkar; Sebastian CJ Bacon; George Hickman; Christopher Bates; Richard Croker; David Evans; Tom Ward; Jonathan Cockburn; Simon Davy; Krishnan Bhaskaran; Anna Schultze; Elizabeth J Williamson; William J Hulme; Helen I McDonald; Laurie Tomlinson; Rohini Mathur; Rosalind M Eggo; Kevin Wing; Angel YS Wong; Harriet Forbes; John Tazare; John Parry; Frank Hester; Sam Harper; Shaun O'Hanlon; Alex Eavis; Richard Jarvis; Dima Avramov; Paul Griffiths; Aaron Fowles; Nasreen Parkes; Ian J Douglas; Stephen JW Evans; Liam Smeeth; Ben Goldacre,; University of Oxford; University of Oxford; University of Oxford; London School of Hygiene and Tropical Medicine; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; TPP; University of Oxford; University of Oxford; University of Oxford; TPP; University of Oxford; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; University of Oxford; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; TPP; TPP; TPP; EMIS; EMIS; EMIS; EMIS; EMIS; EMIS; EMIS; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; University of Oxford,"BackgroundLong COVID is a term to describe new or persistent symptoms at least four weeks after onset of acute COVID-19. Clinical codes to describe this phenomenon were released in November 2020 in the UK, but it is not known how these codes have been used in practice. MethodsWorking on behalf of NHS England, we used OpenSAFELY data encompassing 96% of the English population. We measured the proportion of people with a recorded code for long COVID, overall and by demographic factors, electronic health record software system, and week. We also measured variation in recording amongst practices. @@ -1595,21 +1561,6 @@ Added value of this studyThe ATOMIC2 trial was uniquely-designed to assess azith Implications of all the available evidenceOur findings, taken together with existing data, suggest there is no evidence that azithromycin reduces hospitalisation, respiratory failure or death compared with standard care, either in early disease in the community, or those hospitalised with severe disease, or in those with moderate disease managed on an ambulatory pathway.",infectious diseases,exact,100,100 medRxiv,10.1101/2021.04.22.21255911,2021-04-23,https://medrxiv.org/cgi/content/short/2021.04.22.21255911,The impact of SARS-CoV-2 vaccines on antibody responses in the general population in the United Kingdom,Jia Wei; Nicole Stoesser; Philippa C Matthews; Ruth Studley; Iain Bell; John I Bell; John N Newton; Jeremy Farrar; Ian Diamond; Emma Rourke; Alison Howarth; Brian D Marsden; Sarah Hoosdally; E Yvonne Jones; David I Stuart; Derrick W Crook; Tim EA Peto; Koen B Pouwels; David W Eyre; A Sarah Walker; - COVID-19 Infection Survey team,"University of Oxford; University of Oxford; University of Oxford; Office for National Statistics, UK; Office for National Statistics, UK; University of Oxford; Public Health England; Wellcome Trust; Office for National Statistics, UK; Office for National Statistics, UK; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; ","Real-world data on antibody response post-vaccination in the general population are limited. 45,965 adults in the UKs national COVID-19 Infection Survey receiving Pfizer-BioNTech or Oxford-AstraZeneca vaccines had 111,360 anti-spike IgG measurements. Without prior infection, seroconversion rates and quantitative antibody levels post single dose were lower in older individuals, especially >60y. Two doses achieved high responses across all ages, particularly increasing seroconversion in older people, to similar levels to those achieved after prior infection followed by a single dose. Antibody levels rose more slowly and to lower levels with Oxford-AstraZeneca vs Pfizer-BioNTech, but waned following a single Pfizer-BioNTech dose. Latent class models identified four responder phenotypes: older people, males, and those having long-term health conditions were more commonly low responders. Where supplies are limited, vaccines should be prioritised for those not previously infected, and second doses to individuals >60y. Further data on the relationship between vaccine-mediated protection and antibody responses are needed.",infectious diseases,exact,100,100 -medRxiv,10.1101/2021.04.22.21255913,2021-04-23,https://medrxiv.org/cgi/content/short/2021.04.22.21255913,Impact of vaccination on SARS-CoV-2 cases in the community: a population-based study using the UK COVID-19 Infection Survey,Emma Pritchard; Philippa Matthews; Nicole Stoesser; David Eyre; Owen Gethings; Karina-Doris Vitha; Joel Jones; Thomas House; Harper VanSteenhouse; Iain Bell; John Bell; John Newton; Jeremy Farrar; Ian Diamond; Emma Rourke; Ruth Studley; Derrick W Crook; tim E peto; Ann Sarah Walker; Koen B Pouwels,"University of Oxford; University of Oxford; University of Oxford; University of Oxford; Office for National Statistics; University of Oxford; Office for National Statistics; University of Manchester; Glasgow Lighthouse Laboratory; Office for National Statistics; University of Oxford; Public Health England; Wellcome Trust; Office for National Statistics,; Office for National Statistics; Office for National Statistics; NIHR Oxford Biomedical Research Centre; oxford university; University of Oxford; University of Oxford","ObjectivesTo assess the effectiveness of COVID-19 vaccination in preventing SARS-CoV-2 infection in the community. - -DesignProspective cohort study. - -SettingThe UK population-representative longitudinal COVID-19 Infection Survey. - -Participants373,402 participants aged [≥]16 years contributing 1,610,562 RT-PCR results from nose and throat swabs between 1 December 2020 and 3 April 2021. - -Main outcome measuresNew RT-PCR-positive episodes for SARS-CoV-2 overall, by self-reported symptoms, by cycle threshold (Ct) value (<30 versus [≥]30), and by gene positivity (compatible with the B.1.1.7 variant versus not). - -ResultsOdds of new SARS-CoV-2 infection were reduced 65% (95% CI 60 to 70%; P<0.001) in those [≥]21 days since first vaccination with no second dose versus unvaccinated individuals without evidence of prior infection (RT-PCR or antibody). In those vaccinated, the largest reduction in odds was seen post second dose (70%, 95% CI 62 to 77%; P<0.001).There was no evidence that these benefits varied between Oxford-AstraZeneca and Pfizer-BioNTech vaccines (P>0.9).There was no evidence of a difference in odds of new SARS-CoV-2 infection for individuals having received two vaccine doses and with evidence of prior infection but not vaccinated (P=0.89). Vaccination had a greater impact on reducing SARS-CoV-2 infections with evidence of high viral shedding Ct<30 (88% reduction after two doses; 95% CI 80 to 93%; P<0.001) and with self-reported symptoms (90% reduction after two doses; 95% CI 82 to 94%; P<0.001); effects were similar for different gene positivity patterns. - -ConclusionVaccination with a single dose of Oxford-AstraZeneca or Pfizer-BioNTech vaccines, or two doses of Pfizer-BioNTech, significantly reduced new SARS-CoV-2 infections in this large community surveillance study. Greater reductions in symptomatic infections and/or infections with a higher viral burden are reflected in reduced rates of hospitalisations/deaths, but highlight the potential for limited ongoing transmission from asymptomatic infections in vaccinated individuals. - -RegistrationThe study is registered with the ISRCTN Registry, ISRCTN21086382.",infectious diseases,exact,100,100 medRxiv,10.1101/2021.04.08.21255099,2021-04-14,https://medrxiv.org/cgi/content/short/2021.04.08.21255099,Occupational risks of COVID-19 in NHS workers in England,Diana van der Plaat; Ira Madan; David Coggon; Martie van Tongeren; Rhiannon Edge; Rupert Muiry; Vaughan Parsons; Paul Cullinan,Imperial College London; Guy's and St Thomas' NHS Foundation Trust; Southampton General Hospital; University of Manchester; Lancaster University; Guy's and St Thomas NHS Foundation Trust; Guy's and St Thomas NHS Foundation Trust; Imperial College London,"ObjectiveTo quantify occupational risks of Covid-19 among healthcare staff during the first wave of the pandemic in England MethodsUsing pseudonymised data on 902,813 individuals continuously employed by 191 National Health Service trusts during 1.1.19 to 31.7.20, we explored demographic and occupational risk factors for sickness absence ascribed to Covid-19 during 9.3.20 to 31.7.20 (n = 92,880). We estimated odds ratios (ORs) by multivariable logistic regression. @@ -1708,28 +1659,7 @@ MethodsWe used Cox proportional hazards models to estimate hazard ratios (HRs) f ResultsWe observed a small proportion of care home residents with positive PCR tests following vaccination 1.05% (N=148), with 90% of infections occurring within 28-days. For the 7-day landmark analysis we found a reduced risk of SARS-CoV-2 infection for vaccinated individuals who had a previous infection; HR (95% confidence interval) 0.54 (0.30,0.95), and an increased HR for those receiving the Pfizer-BioNTECH vaccine compared to the Oxford-AstraZeneca; 3.83 (2.45,5.98). For the 21-day landmark analysis we observed high HRs for individuals with low and intermediate frailty compared to those without; 4.59 (1.23,17.12) and 4.85 (1.68,14.04) respectively. ConclusionsIncreased risk of infection after 21-days was associated with frailty. We found most infections occurred within 28-days of vaccination, suggesting extra precautions to reduce transmission risk should be taken in this time frame.",geriatric medicine,exact,100,100 -medRxiv,10.1101/2021.03.16.21253377,2021-03-24,https://medrxiv.org/cgi/content/short/2021.03.16.21253377,First and second SARS-CoV-2 waves in inner London: A comparison of admission characteristics and the effects of the B.1.1.7 variant,Luke B Snell; Wenjuan Wang; Adela Alcolea-Medina; Themoula Charalampous; Gaia Nebbia; Rahul Batra; Leonardo de Jongh; Finola Higgins; Yanzhong Wang; Jonathan D Edgeworth; Vasa Curcin,"King's College London; School of Population Health and Environmental Sciences, King's College London, London, UK; Viapath, London, UK; Centre for Clinical Infection and Diagnostics Research, School of Immunology and Microbial Sciences, King's College London, London, UK; Centre for Clinical Infection and Diagnostics Research, School of Immunology and Microbial Sciences, King's College London, London, UK; Centre for Clinical Infection and Diagnostics Research, School of Immunology and Microbial Sciences, King's College London, London, UK; NIHR Biomedical Research Centre, Guy's and St Thomas' NHS Foundation Trust; NIHR Biomedical Research Centre, Guy's and St Thomas' NHS Foundation Trust; School of Population Health and Environmental Sciences, King's College London, London, UK; Centre for Clinical Infection and Diagnostics Research, School of Immunology and Microbial Sciences, King's College London, London, UK; School of Population Health and Environmental Sciences, King's College London, London, UK","IntroductionA second wave of SARS-CoV-2 infection spread across the UK in 2020 linked with emergence of the more transmissible B.1.1.7 variant. The emergence of new variants, particularly during relaxation of social distancing policies and implementation of mass vaccination, highlights the need for real-time integration of detailed patient clinical data alongside pathogen genomic data. We linked clinical data with viral genome sequence data to compare cases admitted during the first and second waves of SARS-CoV-2 infection. - -MethodsClinical, laboratory and demographic data from five electronic health record (EHR) systems was collected for all cases with a positive SARS-CoV-2 RNA test between March 13th 2020 and February 17th 2021. SARS-CoV-2 viral sequencing was performed using Oxford Nanopore Technology. Descriptive data are presented comparing cases between waves, and between cases of B.1.1.7 and non-B.1.1.7 variants. - -ResultsThere were 5810 SARS-CoV-2 RNA positive cases comprising inpatients (n=2341), healthcare workers (n=1549), outpatients (n=874), emergency department (ED) attenders not subsequently admitted (n=532), inter-hospital transfers (n=281) and nosocomial cases (n=233). There were two dominant waves of hospital admissions, with wave one starting from March 13th (n=838) and wave two from October 20th (n=1503), both with a temporally aligned rise in nosocomial cases (n=96 in wave one, n=137 in wave two). 1470 SARS-CoV-2 isolates were successfully sequenced, including 216/838 (26%) admitted cases from wave one, 472/1503 (31%) admitted cases in wave two and 121/233 (52%) nosocomial cases. The first B.1.1.7 variant was identified on 15th November 2020 and increased rapidly such that it comprised 400/472 (85%) of sequenced isolates from admitted cases in wave two. Females made up a larger proportion of admitted cases in wave two (47.3% vs 41.8%, p=0.011), and in those infected with the B.1.1.7 variant compared to non-B.1.1.7 variants (48.0% vs 41.8%, p=0.042). A diagnosis of frailty was less common in wave two (11.5% v 22.8%, p<0.001) and in the group infected with B.1.1.7 (14.5% v 22.4%, p=0.001). There was no difference in severity on admission between waves, as measured by hypoxia at admission (wave one: 64.3% vs wave two: 65.5%, p=0.67). However, a higher proportion of cases infected with the B.1.1.7 variant were hypoxic on admission compared to other variants (70.0% vs 62.5%, p=0.029). - -ConclusionsAutomated EHR data extraction linked with SARS-CoV-2 genome sequence data provides valuable insight into the evolving characteristics of cases admitted to hospital with COVID-19. The proportion of cases with hypoxia on admission was greater in those infected with the B.1.1.7 variant, which supports evidence the B.1.1.7 variant is associated with more severe disease. The number of nosocomial cases was similar in both waves despite introduction of many infection control interventions before wave two, an observation requiring further investigation.",infectious diseases,exact,100,100 -medRxiv,10.1101/2021.03.11.21253275,2021-03-21,https://medrxiv.org/cgi/content/short/2021.03.11.21253275,Effect of vaccination on transmission of COVID-19: an observational study in healthcare workers and their households,Anoop Shah; Ciara Gribben; Jennifer Bishop; Peter Hanlon; David Caldwell; Rachael Wood; Martin Reid; Jim McMenamin; David Goldberg; Diane Stockton; Sharon Hutchinson; Chris Robertson; Paul M McKeigue; Helen M Colhoun; David McAllister,London School of Hygiene and Tropical Medicine; Public Health Scotland; Public Health Scotland; University of Glasgow; Public Health Scotland; PublicHealth Scotland; Public Health Scotland; Public Health Scotland; Public Health Scotland; Public Health Scotland; Public Health Scotland; Public Health Scotland; Public Health Scotland; Public Health Scotland; University of Glasgow,"BackgroundThe effect of vaccination for COVID-19 on onward transmission is unknown. - -MethodsA national record linkage study determined documented COVID-19 cases and hospitalisations in unvaccinated household members of vaccinated and unvaccinated healthcare workers from 8th December 2020 to 3rd March 2021. The primary endpoint was COVID-19 14 days following the first dose. - -ResultsThe cohort comprised of 194,362 household members (mean age 31{middle dot}1 {+/-} 20{middle dot}9 years) and 144,525 healthcare workers (mean age 44{middle dot}4 {+/-} 11{middle dot}4 years). 113,253 (78{middle dot}3%) of healthcare workers received at least one dose of the BNT162b2 mRNA or ChAdOx1 nCoV-19 vaccine and 36,227 (25{middle dot}1%) received a second dose. There were 3,123 and 4,343 documented COVID-19 cases and 175 and 177 COVID-19 hospitalisations in household members of healthcare workers and healthcare workers respectively. Household members of vaccinated healthcare workers had a lower risk of COVID-19 case compared to household members of unvaccinated healthcare worker (rate per 100 person-years 9{middle dot}40 versus 5{middle dot}93; HR 0{middle dot}70, 95% confidence interval [CI] 0{middle dot}63 to 0{middle dot}78). The effect size for COVID-19 hospitalisation was similar, with the confidence interval crossing the null (HR 0{middle dot}77 [95% CI 0{middle dot}53 to 1{middle dot}10]). The rate per 100 person years was lower in vaccinated compared to unvaccinated healthcare workers for documented (20{middle dot}13 versus 8{middle dot}51; HR 0{middle dot}45 [95% CI 0{middle dot}42 to 0{middle dot}49]) and hospitalized COVID-19 (0{middle dot}97 versus 0{middle dot}14; HR 0{middle dot}16 [95% CI 0{middle dot}09 to 0{middle dot}27]). Compared to the period before the first dose, the risk of documented COVID-19 case was lower at [≥] 14 days after the second dose for household members (HR 0{middle dot}46 [95% CI 0{middle dot}30to 0{middle dot}70]) and healthcare workers (HR 0{middle dot}08 [95% CI 0{middle dot}04 to 0{middle dot}17]). - -InterpretationVaccination of health care workers was associated with a substantial reduction in COVID-19 cases in household contacts consistent with an effect of vaccination on transmission.",public and global health,exact,100,100 medRxiv,10.1101/2021.03.17.21253853,2021-03-20,https://medrxiv.org/cgi/content/short/2021.03.17.21253853,"Modelling the impact of rapid tests, tracing and distancing in lower-income countries suggest optimal policies varies with rural-urban settings",Xilin Jiang; Wenfeng Gong; Zlatina Dobreva; Ya Gao; Matthew Quaife; Christophe Fraser; Chris Holmes,"University of Oxford; Bill & Melinda Gates Foundation; Faculty of Public Health and Policy, London School of Hygiene and Tropical Medicine, London, UK; Department of International Health, Johns Hopkins University; Faculty of Public Health and Policy, London School of Hygiene and Tropical Medicine, London, UK; University of Oxford; University of Oxford","Low- and middle-income countries (LMICs) remain of high potential for hotspots for COVID-19 deaths and emerging variants given the inequality of vaccine distribution and their vulnerable healthcare systems. We aim to evaluate containment strategies that are sustainable and effective for LMICs. We constructed synthetic populations with varying contact and household structures to capture LMIC demographic characteristics that vary across communities. Using an agent- based model, we explored the optimal containment strategies for rural and urban communities by designing and simulating setting-specific strategies that deploy rapid diagnostic tests, symptom screening, contact tracing and physical distancing. In low-density rural communities, we found implementing either high quality (sensitivity > 50%) antigen rapid diagnostic tests or moderate physical distancing could contain the transmission. In urban communities, we demonstrated that both physical distancing and case finding are essential for containing COVID-19 (average infection rate < 10%). In high density communities that resemble slums and squatter settlements, physical distancing is less effective compared to rural and urban communities. Lastly, we demonstrated contact tracing is essential for effective containment. Our findings suggested that rapid diagnostic tests could be prioritised for control and monitor COVID-19 transmission and highlighted that contact survey data could guide strategy design to save resources for LMICs. An accompanying open source R package is available for simulating COVID-19 transmission based on contact network models.",epidemiology,exact,100,100 -medRxiv,10.1101/2021.03.18.21253443,2021-03-20,https://medrxiv.org/cgi/content/short/2021.03.18.21253443,Intensity of COVID-19 in care homes following Hospital Discharge in the early stages of the UK epidemic,Joe Hollinghurst; Laura North; Chris Emmerson; Ashley Akbari; Fatemeh Torabi; Ronan A Lyons; Alan G Hawkes; Ed Bennett; Mike B Gravenor; Richard Fry,Swansea University; Swansea University; Public Health Wales; Swansea University; Swansea University; Swansea University; Swansea University; Swansea University; Swansea University; Swansea University,"BackgroundA defining feature of the COVID-19 pandemic in many countries was the tragic extent to which care home residents were affected, and the difficulty preventing introduction and subsequent spread of infection. Management of risk in care homes requires good evidence on the most important transmission pathways. One hypothesised route at the start of the pandemic, prior to widespread testing, was transfer of patients from hospitals, which were experiencing high levels of nosocomial events. - -MethodsWe tested the hypothesis that hospital discharge events increased the intensity of care home cases using a national individually linked health record cohort in Wales, UK. We monitored 186,772 hospital discharge events over the period March to July 2020, tracking individuals to 923 care homes and recording the daily case rate in the homes populated by 15,772 residents. We estimated the risk of an increase in cases rates following exposure to a hospital discharge using multi-level hierarchical logistic regression, and a novel stochastic Hawkes process outbreak model. - -FindingsIn regression analysis, after adjusting for care home size, we found no significant association between hospital discharge and subsequent increases in care home case numbers (odds ratio: 0.99, 95% CI 0.82, 1.90). Risk factors for increased cases included care home size, care home resident density, and provision of nursing care. Using our outbreak model, we found a significant effect of hospital discharge on the subsequent intensity of cases. However, the effect was small, and considerably less than the effect of care home size, suggesting the highest risk of introduction came from interaction with the community. We estimated approximately 1.8% of hospital discharged patients may have been infected. - -InterpretationThere is growing evidence in the UK that the risk of transfer of COVID-19 from the high-risk hospital setting to the high-risk care home setting during the early stages of the pandemic was relatively small. Although access to testing was limited to initial symptomatic cases in each care home at this time, our results suggest that reduced numbers of discharges, selection of patients, and action taken within care homes following transfer all may have contributed to mitigation. The precise key transmission routes from the community remain to be quantified.",health informatics,exact,100,100 medRxiv,10.1101/2021.03.04.21252931,2021-03-08,https://medrxiv.org/cgi/content/short/2021.03.04.21252931,A common TMPRSS2 variant protects against severe COVID-19,"Alessia David; Nicholas Parkinson; Thomas P Peacock; Erola Pairo-Castineira; Tarun Khanna; Aurelie Cobat; Albert Tenesa; Vanessa Sancho-Shimizu; - GenOMICC Investigators, ISARIC4C Investigators; Jean-Laurent Casanova; Laurent Abel; Wendy S Barclay; J Kenneth Baillie; Michael J.E. Sternberg","Centre for Integrative System Biology and Bioinformatics, Imperial College London, London; Roslin Institute, University of Edinburgh; Department of Infectious Diseases, Imperial College London; Roslin Institute, University of Edinburgh; Centre for Integrative System Biology and Bioinformatics, Imperial College London; Laboratory of Human Genetics of Infectious Diseases, INSERM; Roslin Institute, University of Edinburgh; Department of Paediatric Infectious Diseases & Virology, Imperial College London; ; St. Giles Laboratory of Human Genetics of Infectious Diseases, The Rockefeller University; Laboratory of Human Genetics of Infectious Diseases, INSERM; Department of Infectious Diseases, Imperial College London; Roslin Institute, University of Edinburgh; Centre for Integrative System Biology and Bioinformatics, Imperial College London","Infection with SARS-CoV-2 has a wide range of clinical presentations, from asymptomatic to life-threatening. Old age is the strongest factor associated with increased COVID19-related mortality, followed by sex and pre-existing conditions. The importance of genetic and immunological factors on COVID19 outcome is also starting to emerge, as demonstrated by population studies and the discovery of damaging variants in genes controlling type I IFN immunity and of autoantibodies that neutralize type I IFNs. The human protein transmembrane protease serine type 2 (TMPRSS2) plays a key role in SARS-CoV-2 infection, as it is required to activate the virus spike protein, facilitating entry into target cells. We focused on the only common TMPRSS2 non-synonymous variant predicted to be damaging (rs12329760), which has a minor allele frequency of [~]25% in the population. In a large population of SARS-CoV-2 positive patients, we show that this variant is associated with a reduced likelihood of developing severe COVID19 (OR 0.87, 95%CI:0.79-0.97, p=0.01). This association was stronger in homozygous individuals when compared to the general population (OR 0.65, 95%CI:0.50-0.84, p=1.3x10-3). We demonstrate in vitro that this variant, which causes the amino acid substitution valine to methionine, impacts the catalytic activity of TMPRSS2 and is less able to support SARS-CoV-2 spike-mediated entry into cells. TMPRSS2 rs12329760 is a common variant associated with a significantly decreased risk of severe COVID19. Further studies are needed to assess the expression of the TMPRSS2 across different age groups. Moreover, our results identify TMPRSS2 as a promising drug target, with a potential role for camostat mesilate, a drug approved for the treatment of chronic pancreatitis and postoperative reflux esophagitis, in the treatment of COVID19. Clinical trials are needed to confirm this.",genetic and genomic medicine,exact,100,100 @@ -1930,6 +1860,15 @@ RESEARCH IN CONTEXTO_ST_ABSEvidence before this studyC_ST_ABSPublic policy measu Added value of this studyCommissioned by the Chief Medical Officer for England, we validated the novel clinical risk prediction model (QCovid) to identify risks of short-term severe outcomes due to COVID-19. We used national linked datasets from general practice, death registry and hospital episode data for a population-representative sample of over 34 million adults. The risk models have excellent discrimination in men and women (Harrells C statistic>0.9) and are well calibrated. QCovid represents a new, evidence-based opportunity for population risk-stratification. Implications of all the available evidenceQCovid has the potential to support public health policy, from enabling shared decision making between clinicians and patients in relation to health and work risks, to targeted recruitment for clinical trials, and prioritisation of vaccination, for example.",public and global health,exact,100,100 +medRxiv,10.1101/2021.01.15.21249756,2021-01-20,https://medrxiv.org/cgi/content/short/2021.01.15.21249756,Factors associated with deaths due to COVID-19 versus other causes: population-based cohort analysis of UK primary care data and linked national death registrations within the OpenSAFELY platform,Krishnan Bhaskaran; Sebastian CJ Bacon; Stephen JW Evans; Chris J Bates; Christopher T Rentsch; MacKenna Brian; Laurie Tomlinson; Alex J Walker; Anna Schultze; Caroline E Morton; Daniel Grint; Amir Mehrkar; Rosalind M Eggo; Peter Inglesby; Ian J Douglas; Helen I McDonald; Jonathan Cockburn; Elizabeth J Williamson; David Evans; Helen J Curtis; William J Hulme; John Parry; Frank Hester; Sam Harper; David Spiegelhalter; Liam Smeeth; Ben Goldacre,"London School of Hygiene and Tropical Medicine; University of Oxford; London School of Hygiene Tropical Medicine; The Phoenix Partnership; London School of Hygiene and Tropical Medicine; University of Oxford; London School of Hygiene and Tropical Medicine; University of Oxford; London School of Hygiene and Tropical Medicine; University of Oxford; London School of Hygiene and Tropical Medicine; University of Oxford; London School of Hygiene and Tropical Medicine; University of Oxford; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; The Phoenix Partnership; London School of Hygiene and Tropical Medicine; University of Oxford; University of Oxford; University of Oxford; University of Oxford; The Phoenix Partnership; The Phoenix Partnership; Winton Centre for Risk and Evidence Communication, Centre for Mathematical Sciences, University of Cambridge; London School of Hygiene and Tropical Medicine; University of Oxford","BackgroundMortality from COVID-19 shows a strong relationship with age and pre-existing medical conditions, as does mortality from other causes. However it is unclear how specific factors are differentially associated with COVID-19 mortality as compared to mortality from other causes. + +MethodsWorking on behalf of NHS England, we carried out a cohort study within the OpenSAFELY platform. Primary care data from England were linked to national death registrations. We included all adults (aged [≥]18 years) in the database on 1st February 2020 and with >1 year of continuous prior registration, the cut-off date for deaths was 9th November 2020. Associations between individual-level characteristics and COVID-19 and non-COVID deaths were estimated by fitting age- and sex-adjusted logistic models for these two outcomes. + +Results17,456,515 individuals were included. 17,063 died from COVID-19 and 134,316 from other causes. Most factors associated with COVID-19 death were similarly associated with non-COVID death, but the magnitudes of association differed. Older age was more strongly associated with COVID-19 death than non-COVID death (e.g. ORs 40.7 [95% CI 37.7-43.8] and 29.6 [28.9-30.3] respectively for [≥]80 vs 50-59 years), as was male sex, deprivation, obesity, and some comorbidities. Smoking, history of cancer and chronic liver disease had stronger associations with non-COVID than COVID-19 death. All non-white ethnic groups had higher odds than white of COVID-19 death (OR for Black: 2.20 [1.96-2.47], South Asian: 2.33 [2.16-2.52]), but lower odds than white of non-COVID death (Black: 0.88 [0.83-0.94], South Asian: 0.78 [0.75-0.81]). + +InterpretationSimilar associations of most individual-level factors with COVID-19 and non-COVID death suggest that COVID-19 largely multiplies existing risks faced by patients, with some notable exceptions. Identifying the unique factors contributing to the excess COVID-19 mortality risk among non-white groups is a priority to inform efforts to reduce deaths from COVID-19. + +FundingWellcome, Royal Society, National Institute for Health Research, National Institute for Health Research Oxford Biomedical Research Centre, UK Medical Research Council, Health Data Research UK.",infectious diseases,exact,100,100 medRxiv,10.1101/2021.01.19.21249840,2021-01-20,https://medrxiv.org/cgi/content/short/2021.01.19.21249840,Impact of SARS-CoV-2 B.1.1.7 Spike variant on neutralisation potency of sera from individuals vaccinated with Pfizer vaccine BNT162b2,Dami Collier; Anna De Marco; Isabella Ferreira; Bo Meng; Rawlings Datir; Alexandra C. Walls; Steven A. Kemp S; Jessica Bassi; Dora Pinto; Chiara Silacci Fregni; Siro Bianchi; M. Alejandra Tortorici; John Bowen; Katja Culap; Stefano Jaconi; Elisabetta Cameroni; Gyorgy Snell; Matteo S. Pizzuto; Alessandra Franzetti Pellanda; Christian Garzoni; Agostino Riva; - The CITIID-NIHR BioResource COVID-19 Collaboration; Anne Elmer; Nathalie Kingston; Barbara Graves; Laura McCoy; Ken Smith; John Bradley; Ceron Ceron-Gutierrez L; Gabriela Barcenas-Morales; Herbert W. Virgin; Antonio Lanzavecchia; Luca Piccoli; Rainer Doffinger; Mark Wills; David Veesler; Davide Corti; Ravindra Gupta,UCL; Vir Biotechnology; University of Cambridge; University of Cambridge; University of Cambridge; University of Washington; University of Cambridge; Vir Biotechnology; Vir Biotechnology; Vir Biotechnology; Vir Biotechnology; University of Washington; University of Washington; Vir Biotehcnology; Vir Biotechnology; Vir Biotechnology; Vir Biotechnology; Vir Biotechnology; Clinica Luganese Moncucco; Clinica Luganese Moncucco; Luigi Sacco Hospital; ; Addenbrookes Hospital; NIHR; Cambridge NIHR; UCL; University of Cambridge; University of Cambridge; Addenbrookes Hospital; Addenbrookes Hospital; Vir Biotechnology; Vir Biotechnology; Vir Biotechnology; Addenbrookes Hospital; University of Cambridge; University of Washington; Vir Biotechnology; University of Cambridge,"Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) transmission is uncontrolled in many parts of the world, compounded in some areas by higher transmission potential of the B1.1.7 variant now seen in 50 countries. It is unclear whether responses to SARS-CoV-2 vaccines based on the prototypic strain will be impacted by mutations found in B.1.1.7. Here we assessed immune responses following vaccination with mRNA-based vaccine BNT162b2. We measured neutralising antibody responses following a single immunization using pseudoviruses expressing the wild-type Spike protein or the 8 amino acid mutations found in the B.1.1.7 spike protein. The vaccine sera exhibited a broad range of neutralising titres against the wild-type pseudoviruses that were modestly reduced against B.1.1.7 variant. This reduction was also evident in sera from some convalescent patients. Decreased B.1.1.7 neutralisation was also observed with monoclonal antibodies targeting the N-terminal domain (9 out of 10), the Receptor Binding Motif (RBM) (5 out of 31), but not in neutralising mAbs binding outside the RBM. Introduction of the E484K mutation in a B.1.1.7 background to reflect newly emerging viruses in the UK led to a more substantial loss of neutralising activity by vaccine-elicited antibodies and mAbs (19 out of 31) over that conferred by the B.1.1.7 mutations alone. E484K emergence on a B.1.1.7 background represents a threat to the vaccine BNT162b.",infectious diseases,exact,100,100 medRxiv,10.1101/2021.01.14.21249801,2021-01-15,https://medrxiv.org/cgi/content/short/2021.01.14.21249801,Factor V is an immune inhibitor that is expressed at increased levels in leukocytes of patients with severe Covid-19,Jun Wang; Prasanti Kotagiri; Paul Lyons; Federica Mescia; Laura Bergamaschi; Lorinda Turner; Rafia Al-Lamki; Michael D Morgan; Fernando J Calero-Nieto; Karsten Bach; Nicole Mende; Nicola K Wilson; Emily R Watts; - Cambridge Institute of Therapeutic Immunology and Infectious Disease - NIHR Covid BioResource; Patrick Chinnery; Nathalie Kingston; Sofia Papadia; Kathleen Stirrups; Neil Walker; Ravindra K Gupta; Mark Toshner; Michael Weekes; James A Nathan; Sarah Walmsley; Willem Hendrik Ouwehand; Mary Kasanicki; Berthold Gottgens; John C Marioni; Smith GC Smith; Jordan S Pober; John R Bradley,University of Cambridge; University of Cambridge; University of Cambridge; University of Cambridge; University of Cambridge; University of Cambridge; University of Cambridge; University of Cambridge; University of Cambridge; University of Cambridge; University of Cambridge; University of Cambridge; University of Edinburgh; ; University of Cambridge; University of Cambridge; University of Cambridge; University of Cambridge; University of Cambridge; University of Cambridge; University of Cambridge; Cambridge University; University of Cambridge; University of Edinburgh; Prof; Cambridge University Hospitals; University of Cambridge; EMBL-EBI; University of Cambridge; Yale University; University of Cambridge,"Severe Covid-19 is associated with elevated plasma Factor V (FV) and increased risk of thromboembolism. We report that neutrophils, T regulatory cells (Tregs), and monocytes from patients with severe Covid-19 express FV, and expression correlates with T cell lymphopenia. In vitro full length FV, but not FV activated by thrombin cleavage, suppresses T cell proliferation. Increased and prolonged FV expression by cells of the innate and adaptive immune systems may contribute to lymphopenia in severe Covid-19. Activation by thrombin destroys the immunosuppressive properties of FV. Anticoagulation in Covid-19 patients may have the unintended consequence of suppressing the adaptive immune system.",infectious diseases,exact,100,100 medRxiv,10.1101/2021.01.15.21249885,2021-01-15,https://medrxiv.org/cgi/content/short/2021.01.15.21249885,Epidemiology of post-COVID syndrome following hospitalisation with coronavirus: a retrospective cohort study,Daniel Ayoubkhani; Kamlesh Khunti; Vahe Nafilyan; Thomas Maddox; Ben Humberstone; Ian Diamond; Amitava Banerjee,Office for National Statistics; University of Leicester; Office for National Statistics; Office for National Statistics; Office for National Statistics; Office for National Statistics; University College London,"ObjectivesThe epidemiology of post-COVID syndrome (PCS) is currently undefined. We quantified rates of organ-specific impairment following recovery from COVID-19 hospitalisation compared with those in a matched control group, and how the rate ratio (RR) varies by age, sex, and ethnicity. @@ -2244,6 +2183,7 @@ We identify potential targets for repurposing of licensed medications. Using Men Our results identify robust genetic signals relating to key host antiviral defence mechanisms, and mediators of inflammatory organ damage in Covid-19. Both mechanisms may be amenable to targeted treatment with existing drugs. Large-scale randomised clinical trials will be essential before any change to clinical practice.",intensive care and critical care medicine,exact,100,100 medRxiv,10.1101/2020.09.22.20198754,2020-09-23,https://medrxiv.org/cgi/content/short/2020.09.22.20198754,"Ethnic differences in COVID-19 infection, hospitalisation, and mortality: an OpenSAFELY analysis of 17 million adults in England",Rohini Mathur; Christopher T. Rentsch; Caroline Morton; William J Hulme; Anna Schultze; Brian MacKenna; Rosalind M Eggo; Krishnan Bhaskaran; Angel YS Wong; Elizabeth J Williamson; Harriet Forbes; Kevin Wing; Helen I McDonald; Chris Bates; Seb Bacon; Alex J Walker; David Evans; Peter Inglesby; Amir Mehrkar; Helen J Curtis; Nicholas J DeVito; Richard Croker; Henry Drysdale; Jonathan Cockburn; John Parry; Frank Hester; Sam Harper; Ian J Douglas; Laurie Tomlinson; Stephen Evans; Richard Grieve; David Harrison; Kathy Rowan; Kamlesh Khunti; Nish Chaturvedi; Liam Smeeth; Ben Goldacre,London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; University of Oxford; University of Oxford; London School of Hygiene and Tropical Medicine; University of Oxford; London School of Hygiene & Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Medicine and Tropical Medicine; The Phoenix Partnership; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; The Phoenix Partnership; The Phoenix Partnership; The Phoenix Partnership; The Phoenix Partnership; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; Intensive Care National Audit and Research Centre; Intensive Care National Audit and Research Centre; University of Leicester; University College London; London School of Hygiene and Tropical Medicine; University of Oxford,"Background: COVID-19 has had a disproportionate impact on ethnic minority populations, both in the UK and internationally. To date, much of the evidence has been derived from studies within single healthcare settings, mainly those hospitalised with COVID-19. Working on behalf of NHS England, the aim of this study was to identify ethnic differences in the risk of COVID-19 infection, hospitalisation and mortality using a large general population cohort in England. Methods: We conducted an observational cohort study using linked primary care records of 17.5 million adults between 1 February 2020 and 3 August 2020. Exposure was self-reported ethnicity collapsed into the 5 and 16 ethnicity categories of the English Census. Multivariable Cox proportional hazards regression was used to identify ethnic differences in the risk of being tested and testing positive for SARS-CoV-2 infection, COVID-19 related intensive care unit (ICU) admission, and COVID-19 mortality, adjusted for socio-demographic factors, clinical co-morbidities, geographic region, care home residency, and household size. Results: A total of 17,510,002 adults were included in the study; 63% white (n=11,030,673), 6% south Asian (n=1,034,337), 2% black (n=344,889), 2% other (n=324,730), 1% mixed (n=172,551), and 26% unknown (n=4,602,822). After adjusting for measured explanatory factors, south Asian, black, and mixed groups were marginally more likely to be tested (south Asian HR 1.08, 95%CI 1.07-1.09; black HR 1.08; 95%CI 1.06-1.09, mixed HR 1.03, 95%CI 1.01-1.05), and substantially more likely to test positive for SARS-CoV-2 compared with white adults (south Asian HR 2.02. 95% CI 1.97-2.07; black HR 1.68, 95%CI 1.61-1.76; mixed HR 1.46, 95%CI 1.36-1.56). The risk of being admitted to ICU for COVID-19 was substantially increased in all ethnic minority groups compared with white adults (south Asian HR 2.22, 95%CI 1.96-2.52; black HR 3.07, 95%CI 2.61-3.61; mixed HR 2.86, 95%CI 2.19-3.75, other HR 2.86, 95%CI 2.31-3.63). Risk of COVID-19 mortality was increased by 25-56% in ethnic minority groups compared with white adults (south Asian HR 1.27, 95%CI 1.17-1.38; black HR 1.55, 95%CI 1.38-1.75; mixed HR 1.40, 95%CI 1.12-1.76; other HR 1.25, 95%CI 1.05-1.49). We observed heterogeneity of associations after disaggregation into detailed ethnic groupings; Indian and African groups were at higher risk of all outcomes; Pakistani, Bangladeshi and Caribbean groups were less or equally likely to be tested for SARS-CoV-2, but at higher risk of all other outcomes, Chinese groups were less likely to be tested for and test positive for SARS-CoV-2, more likely to be admitted to ICU, and equally likely to die from COVID-19. Conclusions: We found evidence of substantial ethnic inequalities in the risk of testing positive for SARS-CoV-2, ICU admission, and mortality, which persisted after accounting for explanatory factors, including household size. It is likely that some of this excess risk is related to factors not captured in clinical records such as occupation, experiences of structural discrimination, or inequitable access to health and social services. Prioritizing linkage between health, social care, and employment data and engaging with ethnic minority communities to better understand their lived experiences is essential for generating evidence to prevent further widening of inequalities in a timely and actionable manner.",epidemiology,exact,100,100 +medRxiv,10.1101/2020.09.21.20194019,2020-09-23,https://medrxiv.org/cgi/content/short/2020.09.21.20194019,Putting (Big) Data in Action: Saving Lives with Countrywide Population Movement Monitoring Using Mobile Devices during the COVID-19 Crisis,Miklos Karoly Szocska; Peter Pollner; Istvan Schiszler; Tamas Joo; Tamas Palicz; Martin McKee; - Magyar Telekom Nyrt.; - Telenor Magyarorszag Zrt.; Adam Sohonyai; Jozsef Szoke; Adam Toth; Peter Gaal,"Semmelweis University, Faculty of Health and Public Administration, Health Services Management Training Centre, Digital Health and Data Utilisation Team; Semmelweis University, Faculty of Health and Public Administration, Health Services Management Training Centre, Digital Health and Data Utilisation Team; Semmelweis University, Faculty of Health and Public Administration, Health Services Management Training Centre, Digital Health and Data Utilisation Team; Semmelweis University, Faculty of Health and Public Administration, Health Services Management Training Centre, Digital Health and Data Utilisation Team; Semmelweis University, Faculty of Health and Public Administration, Health Services Management Training Centre, Digital Health and Data Utilisation Team; University of London, London School of Hygiene and Tropical Medicine, Department of Health Services Research and Policy; ; ; Vodafone Hungary; Vodafone Hungary; Vodafone Hungary; Semmelweis University, Faculty of Health and Public Administration, Health Services Management Training Centre, Digital Health and Data Utilisation Team","Many countries have implemented strict social distancing measures in the hope of reducing transmission of SARS-CoV-2 but the effectiveness of these measures is determined by the willingness of populations to comply with restrictions. Consequently, a system of monitoring population movement using existing data sources can inform those making decisions about policy responses to the COVID-19 pandemic. We describe a collaboration with all 3 major domestic telecommunication companies in Hungary to use aggregated anonymous mobile phone usage data to calculate two indices for assessing the effect of movement restrictions: a ""mobility-index"" and a ""stay-at-home (or resting) index"". The strengths and weaknesses of this approach are compared with the smartphone-based, COVID-19 Community Mobility Reports from Google. Data generated by mobile phones have long been identified as a potential means to analyse mass population movement, but its operationalisation raises several technical questions, such as making sense of Call Detail Records, collation of data from different mobile network providers, and personal data protection concerns. The method described here addresses these issues and offers an effective and inexpensive tool to monitor the impact of social distancing measures, achieving high levels of accuracy and resolution. Especially in populations where uptake of smartphones is modest, this method has certain advantages over app-based solutions, with greater population coverage, but it is not an alternative to smartphone-based solutions used for contact tracing and quarantine monitoring. We believe that this method can easily be adapted by other countries.",infectious diseases,exact,100,100 medRxiv,10.1101/2020.09.21.20196428,2020-09-22,https://medrxiv.org/cgi/content/short/2020.09.21.20196428,"Sharing a household with children and risk of COVID-19: a study of over 300,000 adults living in healthcare worker households in Scotland",Rachael Wood; Emma C Thomson; Robert Galbraith; Ciara Gribben; David Caldwell; Jennifer Bishop; Martin Reid; Anoop Shah; Kate Templeton; David Goldberg; Chris Robertson; Sharon Hutchinson; Helen M Colhoun; Paul M McKeigue; David McAllister,"University of Edinburgh, Public Heath Scotland; University of Glasgow; Retired; Public Health Scotland; Public Health Scotland; Public Health Scotland; Public Health Scotland; London School of Hygiene and Tropical Medicine; University of Edinburgh; Public Health Scotland; Public Health Scotland; Public Health Scotland; University of Edinburgh; University of Edinburgh; University of Glasgow","ObjectiveChildren are relatively protected from COVID-19, possibly due to cross-protective immunity. We investigated if contact with children also affords adults a degree of protection from COVID-19. DesignCohort study based on linked administrative data. @@ -2503,6 +2443,23 @@ MethodsAn international multicentre audit of patients with a prior diagnosis of Measurements and Main ResultsData from 349 patients with ILD across Europe were included, of whom 161 were admitted to hospital with laboratory or clinical evidence of COVID-19 and eligible for propensity-score matching. Overall mortality was 49% (79/161) in patients with ILD with COVID-19. After matching ILD patients with COVID-19 had higher mortality (HR 1.60, Confidence Intervals 1.17-2.18 p=0.003) compared with age, sex and comorbidity matched controls without ILD. Patients with a Forced Vital Capacity (FVC) of <80% had an increased risk of death versus patients with FVC [≥]80% (HR 1.72, 1.05-2.83). Furthermore, obese patients with ILD had an elevated risk of death (HR 1.98, 1.13-3.46). ConclusionsPatients with ILD are at increased risk of death from COVID-19, particularly those with poor lung function and obesity. Stringent precautions should be taken to avoid COVID-19 in patients with ILD.",respiratory medicine,exact,100,100 +medRxiv,10.1101/2020.07.14.20153734,2020-07-16,https://medrxiv.org/cgi/content/short/2020.07.14.20153734,"Place and causes of acute cardiovascular mortality during the COVID19 pandemic: retrospective cohort study of 580,972 deaths in England and Wales, 2014 to 2020",Jianhua Wu; Mamas Mamas; Mohamed Mohamed; Chun Shing Kwok; Chris Roebuck; Ben Humberstone; Tom Denwood; Tom Luescher; Mark De Belder; John Deanfield; Chris Gale,University of Leeds; Keele University; Keele University; Keele University; NHS Digital; ONS; NHS Digital; Imperial College; Barts Health NHS Trust; UCL; University of Leeds,"ImportanceThe COVID-19 pandemic has resulted in a decline in admissions with cardiovascular (CV) emergencies. The fatal consequences of this are unknown. + +ObjectivesTo describe the place and causes of acute CV death during the COVID-19 pandemic. + +DesignRetrospective nationwide cohort. + +SettingEngland and Wales. + +ParticipantsAll adult (age [≥]18 years) acute CV deaths (n=580,972) between 1st January 2014 and 2nd June 2020. + +ExposureThe COVID-19 pandemic (defined as from the onset of the first COVID-19 death in England on 2nd March 2020). + +Main outcomesPlace (hospital, care home, home) and acute CV events directly contributing to death as stated on the first part of the Medical Certificate of Cause of Death. + +ResultsAfter 2nd March 2020, there were 22,820 acute CV deaths of which 5.7% related to COVID-19, and an excess acute CV mortality of 1752 (+8%) compared with the expected daily deaths in the same period. Deaths in the community accounted for nearly half of all deaths during this period. Care homes had the greatest increase in excess acute CV deaths (1065, +40%), followed by deaths at home (1728, +34%) and in hospital (57, +0%). The most frequent cause of acute CV death during this period was stroke (8,290, 36.3%), followed by acute coronary syndrome (ACS) (5,532, 24.2%), heart failure (5,280, 23.1%), pulmonary embolism (2,067, 9.1%) and cardiac arrest (1,037, 4.5%). Deep vein thrombosis had the greatest increase in cause of excess acute CV death (18, +25%), followed pulmonary embolism (340, +19%) and stroke (782, +10%). The greatest cause of excess CV death in care homes was stroke (700, +48%), compared with cardiac arrest (80, +56%) at home, and pulmonary embolism (126, +14%) and cardiogenic shock (41, +14%) in hospital. + +Conclusions and relevanceThe COVID-19 pandemic has resulted in an inflation in acute CV deaths above that expected for the time of year, nearly half of which occurred in the community. The most common cause of acute CV death was stroke followed by acute coronary syndrome and heart failure. This is key information to optimise messaging to the public and enable health resource planning.",cardiovascular medicine,exact,100,100 medRxiv,10.1101/2020.07.14.20152629,2020-07-15,https://medrxiv.org/cgi/content/short/2020.07.14.20152629,Covid-19 infection and attributable mortality in UK Long Term Care Facilities: Cohort study using active surveillance and electronic records (March-June 2020),Peter F Dutey-Magni; Haydn Williams; Arnoupe Jhass; Greta Rait; Harry Hemingway; Andrew C Hayward; Laura Shallcross,University College London; Four Seasons Healthcare Group; UCL; University College London; University College London; University College London; UCL,"BackgroundEpidemiological data on COVID-19 infection in care homes are scarce. We analysed data from a large provider of long-term care for older people to investigate infection and mortality during the first wave of the pandemic. MethodsCohort study of 179 UK care homes with 9,339 residents and 11,604 staff.We used manager-reported daily tallies to estimate the incidence of suspected and confirmed infection and mortality in staff and residents. Individual-level electronic health records from 8,713 residents were used to model risk factors for confirmed infection, mortality, and estimate attributable mortality. @@ -2782,21 +2739,6 @@ MethodsPatients with confirmed SARS-CoV-2 infection requiring admission to Unive ResultsAll patients admitted to UHB with COVID-19 during the study period were included (2217 in total). Fifty-eight percent were male, 69.5% White and the majority (80.2%) had co-morbidities. Eighteen and a half percent were of South Asian ethnicity, and these patients were more likely to be younger, have no co-morbidities but twice the prevalence of diabetes than White patients. SAR and SMR suggested more admissions and deaths in South Asian patients than would be predicted and they were more likely to present with severe disease despite no delay in presentation since symptom onset. South Asian ethnicity was associated with an increased risk of death; both by Cox regression (Hazard Ratio 1.4 (95%CI 1.2-1.8) after adjusting for age, sex, deprivation and comorbidities and by propensity score matching, matching for the same factors but categorising ethnicity into South Asian or not (Hazard ratio 1.3 (1.0-1.6)). ConclusionsThose of South Asian ethnicity appear at risk of worse COVID-19 outcomes, further studies need to establish the underlying mechanistic pathways.",infectious diseases,exact,100,100 -medRxiv,10.1101/2020.05.06.20092999,2020-05-07,https://medrxiv.org/cgi/content/short/2020.05.06.20092999,OpenSAFELY: factors associated with COVID-19-related hospital death in the linked electronic health records of 17 million adult NHS patients.,- The OpenSAFELY Collaborative; Elizabeth Williamson; Alex J Walker; Krishnan J Bhaskaran; Seb Bacon; Chris Bates; Caroline E Morton; Helen J Curtis; Amir Mehrkar; David Evans; Peter Inglesby; Jonathan Cockburn; Helen I Mcdonald; Brian MacKenna; Laurie Tomlinson; Ian J Douglas; Christopher T Rentsch; Rohini Mathur; Angel Wong; Richard Grieve; David Harrison; Harriet Forbes; Anna Schultze; Richard T Croker; John Parry; Frank Hester; Sam Harper; Rafael Perera; Stephen Evans; Liam Smeeth; Ben Goldacre,; London School of Hygiene and Tropical Medicine; University of Oxford; London School of Hygiene and Tropical Medicine; University of Oxford; TPP; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; TPP; London School of Hygiene and Tropical Medicine; University of Oxford; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; ICNARC; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; University of Oxford; TPP; TPP; TPP; University of Oxford; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; University of Oxford,"BackgroundEstablishing who is at risk from a novel rapidly arising cause of death, and why, requires a new approach to epidemiological research with very large datasets and timely data. Working on behalf of NHS England we therefore set out to deliver a secure and pseudonymised analytics platform inside the data centre of a major primary care electronic health records vendor establishing coverage across detailed primary care records for a substantial proportion of all patients in England. The following results are preliminary. - -Data sourcesPrimary care electronic health records managed by the electronic health record vendor TPP, pseudonymously linked to patient-level data from the COVID-19 Patient Notification System (CPNS) for death of hospital inpatients with confirmed COVID-19, using the new OpenSAFELY platform. - -Population17,425,445 adults. - -Time period1st Feb 2020 to 25th April 2020. - -Primary outcomeDeath in hospital among people with confirmed COVID-19. - -MethodsCohort study analysed by Cox-regression to generate hazard ratios: age and sex adjusted, and multiply adjusted for co-variates selected prospectively on the basis of clinical interest and prior findings. - -ResultsThere were 5683 deaths attributed to COVID-19. In summary after full adjustment, death from COVID-19 was strongly associated with: being male (hazard ratio 1.99, 95%CI 1.88-2.10); older age and deprivation (both with a strong gradient); uncontrolled diabetes (HR 2.36 95% CI 2.18-2.56); severe asthma (HR 1.25 CI 1.08-1.44); and various other prior medical conditions. Compared to people with ethnicity recorded as white, black people were at higher risk of death, with only partial attenuation in hazard ratios from the fully adjusted model (age-sex adjusted HR 2.17 95% CI 1.84-2.57; fully adjusted HR 1.71 95% CI 1.44-2.02); with similar findings for Asian people (age-sex adjusted HR 1.95 95% CI 1.73-2.18; fully adjusted HR 1.62 95% CI 1.431.82). - -ConclusionsWe have quantified a range of clinical risk factors for death from COVID-19, some of which were not previously well characterised, in the largest cohort study conducted by any country to date. People from Asian and black groups are at markedly increased risk of in-hospital death from COVID-19, and contrary to some prior speculation this is only partially attributable to pre-existing clinical risk factors or deprivation; further research into the drivers of this association is therefore urgently required. Deprivation is also a major risk factor with, again, little of the excess risk explained by co-morbidity or other risk factors. The findings for clinical risk factors are concordant with policies in the UK for protecting those at highest risk. Our OpenSAFELY platform is rapidly adding further NHS patients records; we will update and extend these results regularly.",epidemiology,exact,100,100 medRxiv,10.1101/2020.05.02.20078642,2020-05-06,https://medrxiv.org/cgi/content/short/2020.05.02.20078642,Impact of ethnicity on outcome of severe COVID-19 infection. Data from an ethnically diverse UK tertiary centre,James T Teo; Daniel Bean; Rebecca Bendayan; Richard Dobson; Ajay Shah,Kings College Hospital NHS Foundation Trust; King's College London; King's College London; Kings College London; King's College London,"During the current COVID-19 pandemic, it has been suggested that BAME background patients may be disproportionately affected compared to White but few detailed data are available. We took advantage of near real-time hospital data access and analysis pipelines to look at the impact of ethnicity in 1200 consecutive patients admitted between 1st March 2020 and 12th May 2020 to Kings College Hospital NHS Trust in London (UK). Our key findings are firstly that BAME patients are significantly younger and have different co-morbidity profiles than White individuals. Secondly, there is no significant independent effect of ethnicity on severe outcomes (death or ITU admission) within 14-days of symptom onset, after adjustment for age, sex and comorbidities.",intensive care and critical care medicine,exact,100,100 @@ -2917,9 +2859,6 @@ What this study addsO_LIAmong individuals showing symptoms severe enough to be g C_LIO_LIWe developed a mathematical model combining symptoms to predict individuals likely to be COVID-19 positive and applied this to over 400,000 individuals in the general population presenting some of the COVID-19 symptoms. C_LIO_LIWe find that [~]13% of those presenting symptoms are likely to have or have had a COVID-19 infection. The proportion was slightly higher in women than in men but is comparable in all age groups, and corresponds to 3.4% of those who filled the app report. C_LI",epidemiology,exact,100,100 -medRxiv,10.1101/2020.04.02.20051284,2020-04-06,https://medrxiv.org/cgi/content/short/2020.04.02.20051284,Building an International Consortium for Tracking Coronavirus Health Status,Eran Segal; Feng Zhang; Xihong Lin; Gary King; Ophir Shalem; Smadar Shilo; William E. Allen; Yonatan H. Grad; Casey S. Greene; Faisal Alquaddoomi; Simon Anders; Ran Balicer; Tal Bauman; Ximena Bonilla; Gisel Booman; Andrew T. Chan; Ori Ori Cohen; Silvano Coletti; Natalie Davidson; Yuval Dor; David A. Drew; Olivier Elemento; Georgina Evans; Phil Ewels; Joshua Gale; Amir Gavrieli; Benjamin Geiger; Iman Hajirasouliha; Roman Jerala; Andre Kahles; Olli Kallioniemi; Ayya Keshet; Gregory Landua; Tomer Meir; Aline Muller; Long H. Nguyen; Matej Oresic; Svetlana Ovchinnikova; Hedi Peterson; Jay Rajagopal; Gunnar Ratsch; Hagai Rossman; Johan Rung; Andrea Sboner; Alexandros Sigaras; Tim Spector; Ron Steinherz; Irene Stevens; Jaak Vilo; Paul Wilmes; CCC (Coronavirus Census Collective),"Weizmann Institute of Science; Howard Hughes Medical Institute, Core Member, Broad Institute of MIT and Harvard, United States; Departments of Biostatistics and Statistics, Harvard T.H. Chan School of Public Health; Albert J. Weatherhead III University, Institute for Quantitative Social Science, Harvard University; Department of Genetics, Perelman School of Medicine, University of Pennsylvania, United States; Department of Computer Science and Applied Mathematics, and Department of Molecular Cell Biology, Weizmann Institute of Science, Israel; Society of Fellows, Harvard University, United States; Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, United States; Department of Systems Pharmacology and Translational Therapeutics, Perelman School of Medicine, University of Pennsylvania, United States; ETH Zurich, NEXUS Personalized Health Technologies, Zurich, Switzerland; Center for Molecular Biology (ZMBH), University of Heidelberg, Germany; Clalit Research Institute, Clalit Health Services, Israel; Mapping and Geo-Information Engineering, Civil and Environmental Engineering Faculty, The Technion, Israel; ETH Zurich, Department for Computer Science, Zurich, University Hospital Zurich, Medical Informatics, Zurich and SIB Swiss Institute of Bioinformatics, Zurich, ; Regen Network, Argentina; Massachusetts General Hospital (MGH), United States; Department of Computer Science and Applied Mathematics, and Department of Molecular Cell Biology, Weizmann Institute of Science, Israel; Chelonia Applied Science, Switzerland; ETH Zurich, Department for Computer Science, Zurich, University Hospital Zurich, Medical Informatics, Zurich and SIB Swiss Institute of Bioinformatics, Zurich, ; School of Medicine-IMRIC-Developmental Biology and Cancer Research, The Hebrew University; Massachusetts General Hospital (MGH), United States; Englander Institute for Precision Medicine and Department of Physiology and Biophysics, Weill Cornell Medicine, USA; Institute for Quantitative Social Science, Harvard University; Science for Life Laboratory (SciLifeLab), Department of Biochemistry and Biophysics, Stockholm University, Sweden; symptometrics.org; Department of Computer Science and Applied Mathematics, and Department of Molecular Cell Biology, Weizmann Institute of Science, Israel; Department of immunology, Weizmann Institute of Science, Israel; Englander Institute for Precision Medicine and Department of Physiology and Biophysics, Weill Cornell Medicine, USA; Department of Synthetic biology and Immunology, National Institute of Chemistry, Slovenia; ETH Zurich, Department for Computer Science, Zurich, University Hospital Zurich, Medical Informatics, Zurich and SIB Swiss Institute of Bioinformatics, Zurich, ; Science for Life Laboratory (SciLifeLab), Department of Oncology and Pathology, Karolinska Institutet, Stockholm, Sweden; Department of Computer Science and Applied Mathematics, and Department of Molecular Cell Biology, Weizmann Institute of Science, Israel; Regen Network, United States; Department of Computer Science and Applied Mathematics, and Department of Molecular Cell Biology, Weizmann Institute of Science, Israel; Luxembourg Institute of Socio-Economic Research and University of Luxembourg, Luxembourg; Massachusetts General Hospital (MGH), United States; School of Medical Sciences, Orebro University, Orebro, Sweden, and Turku Bioscience Centre, University of Turku and Abo Akademi University, Turku, Finland; Center for Molecular Biology (ZMBH), University of Heidelberg, Germany; Institute of Computer Science, University of Tartu, Estonia, Estonia; Internal Medicine, Harvard Medical School, Department of Pulmonary Medicine and Critical Care, Massachusetts General Hospital (MGH), United States; ETH Zurich, Department for Computer Science, Zurich, University Hospital Zurich, Medical Informatics, Zurich and SIB Swiss Institute of Bioinformatics, Zurich a; Department of Computer Science and Applied Mathematics, and Department of Molecular Cell Biology, Weizmann Institute of Science, Israel; Science for Life Laboratory (SciLifeLab), Department of Immunology, Genetics and Pathology, Uppsala university, Sweden; Englander Institute for Precision Medicine and Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, USA; Englander Institute for Precision Medicine and Department of Physiology and Biophysics, Weill Cornell Medicine, USA; Kings College, United Kingdom; Regen Network, United States; Science for Life Laboratory (SciLifeLab), Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet, Sweden; Institute of Computer Science, University of Tartu, Estonia, Estonia; Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Luxembourg; ","Information is the most potent protective weapon we have to combat a pandemic, at both the individual and global level. For individuals, information can help us make personal decisions and provide a sense of security. For the global community, information can inform policy decisions and offer critical insights into the epidemic of COVID-19 disease. Fully leveraging the power of information, however, requires large amounts of data and access to it. To achieve this, we are making steps to form an international consortium, Coronavirus Census Collective (CCC, coronaviruscensuscollective.org), that will serve as a hub for integrating information from multiple data sources that can be utilized to understand, monitor, predict, and combat global pandemics. These sources may include self-reported health status through surveys (including mobile apps), results of diagnostic laboratory tests, and other static and real-time geospatial data. This collective effort to track and share information will be invaluable in predicting hotspots of disease outbreak, identifying which factors control the rate of spreading, informing immediate policy decisions, evaluating the effectiveness of measures taken by health organizations on pandemic control, and providing critical insight on the etiology of COVID-19. It will also help individuals stay informed on this rapidly evolving situation and contribute to other global efforts to slow the spread of disease. - -In the past few weeks, several initiatives across the globe have surfaced to use daily self-reported symptoms as a means to track disease spread, predict outbreak locations, guide population measures and help in the allocation of healthcare resources. The aim of this paper is to put out a call to standardize these efforts and spark a collaborative effort to maximize the global gain while protecting participant privacy.",infectious diseases,exact,100,100 medRxiv,10.1101/2020.03.30.20047217,2020-03-30,https://medrxiv.org/cgi/content/short/2020.03.30.20047217,"Physical interventions to interrupt or reduce the spread of respiratory viruses. Part 1 - Face masks, eye protection and person distancing: systematic review and meta-analysis",Tom Jefferson; Mark Jones; Lubna A Al Ansari; Ghada Bawazeer; Elaine Beller; Justin Clark; John Conly; Chris Del Mar; Elisabeth Dooley; Eliana Ferroni; Paul Glasziou; Tammy Hoffman; Sarah Thorning; Mieke Van Driel,"University of Oxford; Bond University, Australia; Kind Saud University, Saudi Arabia; King Saud, University, Saudi Arabia; Bond University, Australia; Bond University, Australia; Department of Medicine, Microbiology, Immunology & Infectious Diseases, Cumming School of Medicine, University of Calgary and Alberta Health Services , Calgary,; Bond University, Australia; Bond University, Australia; Regione Veneto, Italy; Bond University, Australia; Bond University, Australia; Bond University, Australia; Primary Care Clinical Unit, Faculty of Medicine, University of Queensland, Australia","OBJECTIVETo examine the effectiveness of eye protection, face masks, or person distancing on interrupting or reducing the spread of respiratory viruses. DESIGNUpdate of a Cochrane review that included a meta-analysis of observational studies during the SARS outbreak of 2003. diff --git a/data/covid/preprints.exact.json b/data/covid/preprints.exact.json index b857f8e4..9f592862 100644 --- a/data/covid/preprints.exact.json +++ b/data/covid/preprints.exact.json @@ -223,20 +223,6 @@ "author_similarity": 100, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2023.05.23.23289798", - "date": "2023-05-24", - "link": "https://medrxiv.org/cgi/content/short/2023.05.23.23289798", - "title": "Primary Care Post-COVID syndrome Diagnosis and Referral Coding", - "authors": "Robert Willans; Gail Allsopp; Pall Jonsson; Fiona Glen; Felix Greaves; John Macleod; Yinghui Wei; Sebastian Bacon; Amir Mehrkar; Alex Walker; Brian MacKenna; Louis Fisher; Ben Goldacre; - The OpenSAFELY Collaborative; - The CONVALESCENCE Collaborative", - "affiliations": "National Institute of Health and Care Excellence; Royal College of General Practitioners; National Institute of Health and Care Excellence; National Institute of Health and Care Excellence; National Institute of Health and Care Excellence; University of Bristol; University of Plymouth; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford; ; ", - "abstract": "IntroductionGuidelines for diagnosing and managing Post-COVID syndrome have been rapidly developed. Consistency of the application of these guidelines in primary care is unknown. Electronic health records provide an opportunity to review the use of codes relating to Post-COVID syndrome. This paper explores the use of primary care records as a surrogate uptake measure for NICEs rapid guideline \"managing the long-term effects of COVID-19\" by measuring the use of Post-COVID syndrome diagnosis and referral codes in the pathway.\n\nMethodWith the approval of NHS England we used routine clinical data from the OpenSafely-EMIS/-TPP platforms. Counts of Post-COVID syndrome diagnosis and referral codes were generated from a cohort of all adults, establishing numbers of diagnoses and referrals following diagnosis. The relationship between Post-COVID syndrome diagnosis and referral codes was explored with reference to NICEs rapid guideline.\n\nResultsOf over 45 million patients, 69,220 (0.15%) had a Post-COVID syndrome diagnostic code, and 67,741 (0.15%) had a referral code. 78% of referral codes did not have an associated diagnosis code. 79% of diagnosis codes had no subsequent referral code. Only 18,633 (0.04%) had both. There were higher rates of both diagnosis and referral in those who were more deprived, female and some ethnic groups.\n\nDiscussionThis study demonstrates variation in diagnosis and referral coding rates for Post-COVID syndrome across different patient groups. The results, with limited crossover of referral and diagnostic codes, suggest only one type of code is usually recorded. Recording one code limits the use of routine data for monitoring Post-COVID syndrome diagnosis and management, but suggests several areas for improvement in coding. Post-COVID syndrome coding, particularly diagnosis coding, needs to improve before administrators and researchers can use it to evaluate care pathways.", - "category": "epidemiology", - "match_type": "exact", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2023.05.17.23290105", @@ -713,20 +699,6 @@ "author_similarity": 100, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2022.09.11.22279823", - "date": "2022-09-12", - "link": "https://medrxiv.org/cgi/content/short/2022.09.11.22279823", - "title": "Effects of the COVID-19 pandemic on the mental health of clinically extremely vulnerable children and children living with clinically extremely vulnerable people in Wales: A data linkage study", - "authors": "Laura Elizabeth Cowley; Karen Hodgson; Jiao Song; Tony Whiffen; Jacinta Tan; Ann John; Amrita Bandyopadhyay; Alisha R Davies", - "affiliations": "Swansea University; Public Health Wales; Public Health Wales; Welsh Government; University of Oxford; Swansea University; Swansea University; Public Health Wales", - "abstract": "ObjectivesTo determine whether clinically extremely vulnerable (CEV) children or children living with a CEV person in Wales were at greater risk of presenting with anxiety or depression in primary or secondary care during the COVID-19 pandemic compared with children in the general population, and to compare patterns of anxiety and depression during the pandemic (23rd March 2020-31st January 2021, referred to as 2020/21) and before the pandemic (March 23rd 2019-January 31st 2020, referred to as 2019/20), between CEV children and the general population.\n\nDesignPopulation-based cross-sectional cohort study using anonymised, linked, routinely collected health and administrative data held in the Secure Anonymised Information Linkage Databank. CEV individuals were identified using the COVID-19 Shielded Patient List.\n\nSettingPrimary and secondary healthcare settings covering 80% of the population of Wales.\n\nParticipantsChildren aged 2-17 in Wales: CEV (3,769); living with a CEV person (20,033); or neither (415,009).\n\nPrimary outcome measureFirst record of anxiety or depression in primary or secondary healthcare in 2019/20 and 2020/21, identified using Read and ICD-10 codes.\n\nResultsA Cox regression model adjusted for demographics and history of anxiety or depression revealed that only CEV children were at greater risk of presenting with anxiety or depression during the pandemic compared with the general population (Hazard Ratio=2.27, 95% Confidence Interval=1.94-2.66, p<0.001). Compared with the general population, the risk amongst CEV children was higher in 2020/21 (Risk Ratio 3.04) compared with 2019/20 (Risk Ratio 1.90). In 2020/21, the cumulative incidence of anxiety or depression increased slightly amongst CEV children, but declined amongst the general population.\n\nConclusionsDifferences in the cumulative incidences of recorded anxiety or depression in healthcare between CEV children and the general population were largely driven by a reduction in presentations to healthcare services by children in the general population during the pandemic.\n\nStrengths and limitations of this studyO_LIStrengths of this study include its novelty, national focus and clinical relevance; to date this is the first population-based study examining the effects of the COVID-19 pandemic on healthcare use for anxiety or depression amongst clinically extremely vulnerable (CEV) children and children living with a CEV person in Wales\nC_LIO_LIWe compared 2020/21 data with pre-pandemic 2019/20 data for CEV children and children in the general population, to place the impact of the COVID-19 pandemic in the context of longer-term patterns of healthcare use\nC_LIO_LIWe used a novel approach and linked multiple datasets to identify a cohort of children living with a CEV person in Wales during the COVID-19 pandemic\nC_LIO_LIThere was heterogeneity within the Shielded Patient List that was used to create the cohorts of children identified as CEV or living with a CEV person, in terms of the type and severity of individuals underlying conditions; the manner in which people were added to the list; the time point that people were added to the list; and the extent to which people followed the shielding guidance\nC_LIO_LIRoutinely collected healthcare data does not capture self-reported health, and is likely to underestimate the burden of common mental disorders in the population\nC_LI", - "category": "pediatrics", - "match_type": "exact", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2022.09.01.22279473", @@ -741,20 +713,6 @@ "author_similarity": 100, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2022.08.29.22279359", - "date": "2022-08-31", - "link": "https://medrxiv.org/cgi/content/short/2022.08.29.22279359", - "title": "Prophylactic Treatment of COVID-19 in Care Homes Trial (PROTECT-CH)", - "authors": "Philip M Bath; Jonathan Ball; Matthew Boyd; Heather Gage; Matthew Glover; Maureen Godfrey; Bruce Guthrie; Jonathan Hewitt; Robert Howard; Thomas Jaki; Edmund Juszczak; Daniel Lasserson; Paul Leighton; Val Leyland; Wei Shen Lim; Pip Logan; Garry Meakin; Alan Montgomery; Reuben Ogollah; Peter Passmore; Philip Quinlan; Caroline Rick; Simon Royal; Susan D Shenkin; Clare Upton; Adam L Gordon; - PROTECT-CH Trialists", - "affiliations": "University of Nottingham; University of Nottingham; University of Nottingham; University of Surrey; University of Surrey; Private person; University of Edinburgh; Llandough Hospital; University College London; University of Cambridge; University of Nottingham; University of Warwick; University of Nottingham; Private person; Nottingham University Hospitals NHS Trust; University of Nottingham; University of Nottingham; University of Nottingham; University of Nottingham; Queen's University Belfast; University of Nottingham; University of Nottingham; Cripps Health Centre; University of Edinburgh; University of Nottingham; University of Nottingham; ", - "abstract": "BackgroundCoronavirus disease 2019 (COVID-19) is associated with significant mortality and morbidity in care homes. Novel or repurposed antiviral drugs may reduce infection and disease severity through reducing viral replication and inflammation.\n\nObjectiveTo compare the safety and efficacy of antiviral agents (ciclesonide, niclosamide) for preventing SARS-CoV-2 infection and COVID-19 severity in care home residents.\n\nDesignCluster-randomised open-label blinded endpoint platform clinical trial testing antiviral agents in a post-exposure prophylaxis paradigm.\n\nSettingCare homes across all four United Kingdom member countries.\n\nParticipantsCare home residents 65 years of age or older.\n\nInterventionsCare homes were to be allocated at random by computer to 42 days of antiviral agent plus standard care versus standard of care and followed for 60 days after randomisation.\n\nMain outcome measuresThe primary four-level ordered categorical outcome with participants classified according to the most serious of all-cause mortality, all-cause hospitalisation, SARS-CoV-2 infection and no infection. Analysis using ordinal logistic regression was by intention to treat. Other outcomes included the components of the primary outcome and transmission.\n\nResultsDelays in contracting between NIHR and the manufacturers of potential antiviral agents significantly delayed any potential start date. Having set up the trial (protocol, approvals, insurance, website, database, routine data algorithms, training materials), the trial was stopped in September 2021 prior to contracting of care homes and general practitioners in view of the success of vaccination in care homes with significantly reduced infections, hospitalisations and deaths. As a result, the sample size target (based on COVID-19 rates and deaths occurring in February-June 2020) became unfeasible.\n\nLimitationsCare home residents were not approached about the trial and so were not consented and did not receive treatment. Hence, the feasibility of screening, consent, treatment and data acquisition, and potential benefit of post exposure prophylaxis were never tested. Further, contracting between the University of Nottingham and the PIs, GPs and care homes was not completed, so the feasibility of contracting with all the different groups at the scale needed was not tested.\n\nConclusionsThe role of post exposure prophylaxis of COVID-19 in care home residents was not tested because of changes in COVID-19 incidence, prevalence and virulence as a consequence of the vaccination programme that rendered the study unfeasible. Significant progress was made in describing and developing the infrastructure necessary for a large scale Clinical Trial of Investigational Medicinal Products in care homes in all four UK nations.\n\nFuture workThe role of post-exposure prophylaxis of COVID-19 in care home residents remains to be defined. Significant logistical barriers to conducting research in care homes during a pandemic need to be removed before such studies are possible in the required short timescale.", - "category": "infectious diseases", - "match_type": "exact", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2022.08.29.22279333", @@ -951,6 +909,20 @@ "author_similarity": 100, "affiliation_similarity": 100 }, + { + "site": "medRxiv", + "doi": "10.1101/2022.06.16.22276476", + "date": "2022-06-16", + "link": "https://medrxiv.org/cgi/content/short/2022.06.16.22276476", + "title": "Moral injury and psychological wellbeing in UK healthcare staff", + "authors": "Victoria Williamson; Danielle Lamb; Matthew Hotopf; Rosalind Raine; Sharon Stevelink; Simon Wessely; Mary Jane Docherty; Ira Madan; Dominic Murphy; Neil Greenberg", + "affiliations": "King's College London; UCL; King's College London; King's College London; King's College London; King's College London; South London and Maudsley NHS Foundation Trust; Guy's and St Thomas' NHS Foundation Trust; King's College London; King's College London", + "abstract": "BackgroundPotentially morally injurious events (PMIEs) can negatively impact mental health. The COVID-19 pandemic may have placed healthcare staff at risk of moral injury.\n\nAimTo examine the impact of PMIE on healthcare staff wellbeing.\n\nMethod12,965 healthcare staff (clinical and non-clinical) were recruited from 18 NHS-England trusts into a survey of PMIE exposure and wellbeing.\n\nResultsPMIEs were significantly associated with adverse mental health symptoms across healthcare staff. Specific work factors were significantly associated with experiences of moral injury, including being redeployed, lack of PPE, and having a colleague die of COVID-19. Nurses who reported symptoms of mental disorders were more likely to report all forms of PMIEs than those without symptoms (AOR 2.7; 95% CI 2.2, 3.3). Doctors who reported symptoms were only more likely to report betrayal events, such as breach of trust by colleagues (AOR 2.7, 95% CI 1.5, 4.9).\n\nConclusionsA considerable proportion of NHS healthcare staff in both clinical and non-clinical roles report exposure to PMIEs during the COVID-19 pandemic. Prospective research is needed to identify the direction of causation between moral injury and mental disorder as well as continuing to monitor the longer term outcomes of exposure to PMIEs.", + "category": "psychiatry and clinical psychology", + "match_type": "exact", + "author_similarity": 100, + "affiliation_similarity": 100 + }, { "site": "medRxiv", "doi": "10.1101/2022.06.12.22276307", @@ -1007,20 +979,6 @@ "author_similarity": 100, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2022.05.19.22275214", - "date": "2022-05-22", - "link": "https://medrxiv.org/cgi/content/short/2022.05.19.22275214", - "title": "Antibody levels following vaccination against SARS-CoV-2: associations with post-vaccination infection and risk factors", - "authors": "Nathan J Cheetham; Milla Kibble; Andrew Wong; Richard J Silverwood; Anika Knuppel; Dylan M Williams; Olivia K L Hamilton; Paul H Lee; Charis Bridger Staatz; Giorgio Di Gessa; Jingmin Zhu; Srinivasa Vittal Katikireddi; George B Ploubidis; Ellen J Thompson; Ruth C E Bowyer; Xinyuan Zhang; Golboo Abbasian; Maria Paz Garcia; Deborah Hart; Jeffrew Seow; Carl Graham; Neophytos Kouphou; Sam Acors; Michael H Malim; Ruth E Mitchell; Kate Northstone; Daniel Major-Smith; Sarah Matthews; Thomas Breeze; Michael Crawford; Lynn Molloy; Alex Siu Fung Kwong; Katie J Doores; Nishi Chaturvedi; Emma L Duncan; Nicholas J Timpson; Claire J Steves", - "affiliations": "King's College London; University of Cambridge; University College London; University College London; University College London; University College London; University of Glasgow; University of Leicester; University College London; University College London; University College London; University of Glasgow; University College London; King's College London; King's College London; King's College London; King's College London; King's College London; King's College London; King's College London; King's College London; King's College London; King's College London; King's College London; University of Bristol; University of Bristol; University of Bristol; University of Bristol; University of Bristol; University of Bristol; University of Bristol; University of Bristol; King's College London; University College London; King's College London; University of Bristol; King's College London", - "abstract": "SARS-CoV-2 antibody levels can be used to assess humoral immune responses following SARS-CoV-2 infection or vaccination, and may predict risk of future infection. From cross-sectional antibody testing of 9,361 individuals from TwinsUK and ALSPAC UK population-based longitudinal studies (jointly in April-May 2021, and TwinsUK only in November 2021-January 2022), we tested associations between antibody levels following vaccination and: (1) SARS-CoV-2 infection following vaccination(s); (2) health, socio-demographic, SARS-CoV-2 infection and SARS-CoV-2 vaccination variables.\n\nWithin TwinsUK, single-vaccinated individuals with the lowest 20% of anti-Spike antibody levels at initial testing had 3-fold greater odds of SARS-CoV-2 infection over the next six to nine months, compared to the top 20%. In TwinsUK and ALSPAC, individuals identified as at increased risk of COVID-19 complication through the UK \"Shielded Patient List\" had consistently greater odds (2 to 4-fold) of having antibody levels in the lowest 10%. Third vaccination increased absolute antibody levels for almost all individuals, and reduced relative disparities compared with earlier vaccinations.\n\nThese findings quantify the association between antibody level and risk of subsequent infection, and support a policy of triple vaccination for the generation of protective antibodies.\n\nLay summaryIn this study, we analysed blood samples from 9,361 participants from two studies in the UK: an adult twin registry, TwinsUK (4,739 individuals); and the Avon Longitudinal Study of Parents and Children, ALSPAC (4,622 individuals). We did this work as part of the UK Government National Core Studies initiative researching COVID-19. We measured blood antibodies which are specific to SARS-CoV-2 (which causes COVID-19). Having a third COVID-19 vaccination boosted antibody levels. More than 90% of people from TwinsUK had levels after third vaccination that were greater than the average level after second vaccination. Importantly, this was the case even in individuals on the UK \"Shielded Patient List\". We found that people with lower antibody levels after first vaccination were more likely to report having COVID-19 later on, compared to people with higher antibody levels. People on the UK \"Shielded Patient List\", and individuals who reported that they had poorer general health, were more likely to have lower antibody levels after vaccination. In contrast, people who had had a previous COVID-19 infection were more likely to have higher antibody levels following vaccination compared to people without infection. People receiving the Oxford/AstraZeneca rather than the Pfizer BioNTech vaccine had lower antibody levels after one or two vaccinations. However, after a third vaccination, there was no difference in antibody levels between those who had Oxford/AstraZeneca and Pfizer BioNTech vaccines for their first two doses. These findings support having a third COVID-19 vaccination to boost antibodies.", - "category": "epidemiology", - "match_type": "exact", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2022.05.10.22274890", @@ -1441,20 +1399,6 @@ "author_similarity": 100, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2021.12.22.21268252", - "date": "2021-12-24", - "link": "https://medrxiv.org/cgi/content/short/2021.12.22.21268252", - "title": "Rapid increase in Omicron infections in England during December 2021: REACT-1 study", - "authors": "Paul Elliott; Barbara Bodinier; Oliver Eales; Haowei Wang; David Haw; Joshua Elliott; Matthew Whitaker; Jakob Jonnerby; David Tang; Caroline E. Walters; Christina Atchinson; Peter J. Diggle; Andrew J. Page; Alex Trotter; Deborah Ashby; Wendy Barclay; Graham Taylor; Helen Ward; Ara Darzi; Graham Cooke; Marc Chadeau-Hyam; Christl A Donnelly", - "affiliations": "School of Public Health, Imperial College London, UKImperial College Healthcare NHS Trust, UKNational Institute for Health Research Imperial Biomedical Research; School of Public Health, Imperial College London, UK; School of Public Health, Imperial College London, UKMRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergency; School of Public Health, Imperial College London, UKMRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergency; School of Public Health, Imperial College London, UKMRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergency; Imperial College London; School of Public Health, Imperial College London, UK; School of Public Health, Imperial College London, UKMRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergency; Imperial College London; School of Public Health, Imperial College London, UKMRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergency; School of Public Health, Imperial College London, UK; CHICAS, Lancaster Medical School, Lancaster University, UK and Health Data Research, UK; Quadram Institute, Norwich, UK; Quadram Institute Bioscience; School of Public Health, Imperial College London, UK; Department of Infectious Disease, Imperial College London, UK; Department of Infectious Disease, Imperial College London, UK; School of Public Health, Imperial College London, UKImperial College Healthcare NHS Trust, UKNational Institute for Health Research Imperial Biomedical Research; Imperial College Healthcare NHS Trust, UKNational Institute for Health Research Imperial Biomedical Research Centre, UKInstitute of Global Health Innovation at ; Department of Infectious Disease, Imperial College London, UKImperial College Healthcare NHS Trust, UKNational Institute for Health Research Imperial Biomedical; School of Public Health, Imperial College London, UK; School of Public Health, Imperial College London, UKMRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergency", - "abstract": "BackgroundThe highest-ever recorded numbers of daily severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections in England has been observed during December 2021 and have coincided with a rapid rise in the highly transmissible Omicron variant despite high levels of vaccination in the population. Although additional COVID-19 measures have been introduced in England and internationally to contain the epidemic, there remains uncertainty about the spread and severity of Omicron infections among the general population.\n\nMethodsThe REal-time Assessment of Community Transmission-1 (REACT-1) study has been monitoring the prevalence of SARS-CoV-2 infection in England since May 2020. REACT-1 obtains self-administered throat and nose swabs from a random sample of the population of England at ages 5 years and over. Swabs are tested for SARS-CoV-2 infection by reverse transcription polymerase chain reaction (RT-PCR) and samples testing positive are sent for viral genome sequencing. To date 16 rounds have been completed, each including [~]100,000 or more participants with data collected over a period of 2 to 3 weeks per month. Socio-demographic, lifestyle and clinical information (including previous history of COVID-19 and symptoms prior to swabbing) is collected by online or telephone questionnaire. Here we report results from round 14 (9-27 September 2021), round 15 (19 October - 05 November 2021) and round 16 (23 November - 14 December 2021) for a total of 297,728 participants with a valid RT-PCR test result, of whom 259,225 (87.1%) consented for linkage to their NHS records including detailed information on vaccination (vaccination status, date). We used these data to estimate community prevalence and trends by age and region, to evaluate vaccine effectiveness against infection in children ages 12 to 17 years, and effect of a third (booster) dose in adults, and to monitor the emergence of the Omicron variant in England.\n\nResultsWe observed a high overall prevalence of 1.41% (1.33%, 1.51%) in the community during round 16. We found strong evidence of an increase in prevalence during round 16 with an estimated reproduction number R of 1.13 (1.06, 1.09) for the whole of round 16 and 1.27 (1.14, 1.40) when restricting to observations from 1 December onwards. The reproduction number in those aged 18-54 years was estimated at 1.23 (1.14, 1.33) for the whole of round 16 and 1.41 (1.23, 1.61) from 1 December. Our data also provide strong evidence of a steep increase in prevalence in London with an estimated R of 1.62 (1.34, 1.93) from 1 December onwards and a daily prevalence reaching 6.07% (4.06%, 9.00%) on 14 December 2021. As of 1 to 11 December 2021, of the 275 lineages determined, 11 (4.0%) corresponded to the Omicron variant. The first Omicron infection was detected in London on 3 December, and subsequent infections mostly appeared in the South of England. The 11 Omicron cases were all aged 18 to 54 years, double-vaccinated (reflecting the large numbers of people who have received two doses of vaccine in this age group) but not boosted, 9 were men, 5 lived in London and 7 were symptomatic (5 with classic COVID-19 symptoms: loss or change of sense of smell or taste, fever, persistent cough), 2 were asymptomatic, and symptoms were unknown for 2 cases. The proportion of Omicron (vs Delta or Delta sub-lineages) was found to increase rapidly with a daily increase of 66.0% (32.7%, 127.3%) in the odds of Omicron (vs. Delta) infection, conditional on swab positivity. Highest prevalence of swab positivity by age was observed in (unvaccinated) children aged 5 to 11 years (4.74% [4.15%, 5.40%]) similar to the prevalence observed at these ages in round 15. In contrast, prevalence in children aged 12 to 17 years more than halved from 5.35% (4.78%, 5.99%) in round 15 to 2.31% (1.91%, 2.80%) in round 16. As of 14 December 2021, 76.6% children at ages 12 to 17 years had received at least one vaccine dose; we estimated that vaccine effectiveness against infection was 57.9% (44.1%, 68.3%) in this age group. In addition, the prevalence of swab positivity in adults aged 65 years and over fell by over 40% from 0.84% (0.72%, 0.99%) in round 15 to 0.48% (0.39%,0.59%) in round 16 and for those aged 75 years and over it fell by two-thirds from 0.63% (0.48%,0.82%) to 0.21% (0.13%,0.32%). At these ages a high proportion of participants (>90%) had received a third vaccine dose; we estimated that adults having received a third vaccine dose had a three- to four-fold lower risk of testing positive compared to those who had received two doses.\n\nConclusionA large fall in swab positivity from round 15 to round 16 among 12 to 17 year olds, most of whom have been vaccinated, contrasts with the continuing high prevalence among 5 to 11 year olds who have largely not been vaccinated. Likewise there were large falls in swab positivity among people aged 65 years and over, the vast majority of whom have had a third (booster) vaccine dose; these results reinforce the importance of the vaccine and booster campaign. However, the rapidly increasing prevalence of SARS-CoV-2 infections in England during December 2021, coincident with the rapid rise of Omicron infections, may lead to renewed pressure on health services. Additional measures beyond vaccination may be needed to control the current wave of infections and prevent health services (in England and other countries) from being overwhelmed.\n\nSummaryThe unprecedented rise in SARS-CoV-2 infections is concurrent with rapid spread of the Omicron variant in England and globally. We analysed prevalence of SARS-CoV-2 and its dynamics in England from end of November to mid-December 2021 among almost 100,000 participants from the REACT-1 study. Prevalence was high during December 2021 with rapid growth nationally and in London, and of the proportion of infections due to Omicron. We observed a large fall in swab positivity among mostly vaccinated older children (12-17 years) compared with unvaccinated younger children (5-11 years), and in adults who received a third vs. two doses of vaccine. Our results reiterate the importance of vaccination and booster campaigns; however, additional measures may be needed to control the rapid growth of the Omicron variant.", - "category": "epidemiology", - "match_type": "exact", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2021.12.21.21268214", @@ -1679,20 +1623,6 @@ "author_similarity": 100, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2021.11.15.21266264", - "date": "2021-11-16", - "link": "https://medrxiv.org/cgi/content/short/2021.11.15.21266264", - "title": "Association of COVID-19 employment disruption with mental and social wellbeing: evidence from nine UK longitudinal studies", - "authors": "Jacques Wels; Charlotte Booth; Bozena Wielgoszewska; Michael J Green; Giorgio Di Gessa; Charlotte F Huggins; Gareth J Griffith; Alex Siu Fung Kwong; Ruth C E Bowyer; Jane Maddock; Praveetha Patalay; Richard J Silverwood; Emla Fitzsimons; Richard John Shaw; Ellen J Thompson; Andrew Steptoe; Alun Hughes; Nishi Chaturvedi; Claire J Steves; Srinivasa Vittal Katikireddi; George B Ploubidis", - "affiliations": "University College London; University College London; University College London; University of Glasgow; University College London; University of Edinburgh; University of Bristol; University of Bristol; King's College London; University College London; University College London; University College London; University College London; University of Glasgow; Kings College London; University College London; University College London; University College London; King's College London; University of Glasgow; University College London", - "abstract": "BackgroundThe COVID-19 pandemic has led to major economic disruptions. In March 2020, the UK implemented the Coronavirus Job Retention Scheme - known as furlough - to minimize the impact of job losses. We investigate associations between change in employment status and mental and social wellbeing during the early stages of the pandemic.\n\nMethodsData were from 25,670 respondents, aged 17 to 66, across nine UK longitudinal studies. Furlough and other employment changes were defined using employment status pre-pandemic and during the first lockdown (April-June 2020). Mental and social wellbeing outcomes included psychological distress, life satisfaction, self-rated health, social contact, and loneliness. Study-specific modified Poisson regression estimates, adjusting for socio-demographic characteristics and pre-pandemic mental and social wellbeing measures, were pooled using meta-analysis.\n\nResultsCompared to those who remained working, furloughed workers were at greater risk of psychological distress (adjusted risk ratio, ARR=1.12; 95% CI: 0.97, 1.29), low life satisfaction (ARR=1.14; 95% CI: 1.07, 1.22), loneliness (ARR=1.12; 95% CI: 1.01, 1.23), and poor self-rated health (ARR=1.26; 95% CI: 1.05, 1.50), but excess risk was less pronounced than that of those no longer employed (e.g., ARR for psychological distress=1.39; 95% CI: 1.21, 1.59) or in stable unemployment (ARR=1.33; 95% CI: 1.09, 1.62).\n\nConclusionsDuring the early stages of the pandemic, those furloughed had increased risk for poor mental and social wellbeing. However, their excess risk was lower in magnitude than that of those who became or remained unemployed, suggesting that furlough may have partly mitigated poorer outcomes.", - "category": "psychiatry and clinical psychology", - "match_type": "exact", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2021.11.15.21266255", @@ -2001,6 +1931,20 @@ "author_similarity": 100, "affiliation_similarity": 100 }, + { + "site": "medRxiv", + "doi": "10.1101/2021.08.23.21262209", + "date": "2021-08-23", + "link": "https://medrxiv.org/cgi/content/short/2021.08.23.21262209", + "title": "Population birth outcomes in 2020 and experiences of expectant mothers during the COVID-19 pandemic: a Born in Wales mixed methods study using routine data", + "authors": "Hope Jones; Mike Seaborne; Laura Cowley; David E Odd; Shantini Paranjothy; Ashley Akbari; Sinead Brophy", + "affiliations": "Swansea University; Swansea University; Public Health Wales; Cardiff University; University of Aberdeen; Swansea University; Swansea University", + "abstract": "BackgroundPregnancy can be a stressful time and the COVID-19 pandemic has affected all aspects of life. This study aims to investigate the impact of the pandemic on population birth outcomes in Wales, rates of primary immunisations and examine expectant mothers experiences of pregnancy including self-reported levels of stress and anxiety.\n\nMethodsPopulation-level birth outcomes in Wales: Stillbirths, prematurity, birth weight and Caesarean section births before (2016-2019) and during (2020) the pandemic were compared using national-level routine anonymised data held in the Secure Anonymised Information Linkage (SAIL) Databank. The first three scheduled primary immunisations were compared between 2019 and 2020. Self-reported pregnancy experience: 215 expectant mothers (aged 16+) in Wales completed an online survey about their experiences of pregnancy during the pandemic. The qualitative survey data was analysed using codebook thematic analysis.\n\nFindingsThere was no significant difference between annual outcomes including gestation and birth weight, stillbirths, and Caesarean sections for infants born in 2020 compared to 2016-2019. There was an increase in late term births ([≥]42 weeks gestation) during the first lockdown (OR: 1.28, p=0.019) and a decrease in moderate to late preterm births (32-36 weeks gestation) during the second lockdown (OR: 0.74, p=0.001). Fewer babies were born in 2020 (N=29,031) compared to 2016-2019 (average N=32,582). All babies received their immunisations in 2020, but there were minor delays in the timings of vaccines. Those due at 8-weeks were 8% less likely to be on time (within 28-days) and at 16-weeks, they were 19% less likely to be on time. The pandemic had a negative impact on the mental health of 71% of survey respondents, who reported anxiety, stress and loneliness; this was associated with attending scans without their partner, giving birth alone, and minimal contact with midwives.\n\nInterpretationThe pandemic had a negative impact on mothers experiences of pregnancy; however, population-level data suggests that this did not translate to adverse birth outcomes for babies born during the pandemic.", + "category": "public and global health", + "match_type": "exact", + "author_similarity": 100, + "affiliation_similarity": 100 + }, { "site": "medRxiv", "doi": "10.1101/2021.08.17.21262196", @@ -2043,6 +1987,20 @@ "author_similarity": 100, "affiliation_similarity": 100 }, + { + "site": "medRxiv", + "doi": "10.1101/2021.08.12.21261987", + "date": "2021-08-13", + "link": "https://medrxiv.org/cgi/content/short/2021.08.12.21261987", + "title": "Characterising the persistence of RT-PCR positivity and incidence in a community survey of SARS-CoV-2", + "authors": "Oliver Eales; Caroline E. Walters; Haowei Wang; David Haw; Kylie E. C. Ainslie; Christina Atchinson; Andrew Page; Sophie Prosolek; Alexander J. Trotter; Thanh Le Viet; Nabil-Fareed Alikhan; Leigh M Jackson; Catherine Ludden; - The COVID-19 Genomics UK (COG-UK) Consortium; Deborah Ashby; Christl A Donnelly; Graham Cooke; Wendy Barclay; Helen Ward; Ara Darzi; Paul Elliott; Steven Riley", + "affiliations": "School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; School of Public Health, Imperial College London, UK; Quadram Institute, Norwich, UK; Quadram Institute, Norwich, UK; Quadram Institute, Norwich, UK; Quadram Institute, Norwich, UK; Quadram Institute, Norwich, UK; Medical School, University of Exeter, UK; Department of Medicine, University of Cambridge, UK; ; School of Public Health, Imperial College London, UK; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; Department of Infectious Disease, Imperial College London, UK Imperial College Healthcare NHS Trust, UK National Institute for Health Research Imperial Biomedic; Department of Infectious Disease, Imperial College London, UK; School of Public Health, Imperial College London, UK Imperial College Healthcare NHS Trust, UK National Institute for Health Research Imperial Biomedical Resear; Imperial College Healthcare NHS Trust, UK National Institute for Health Research Imperial Biomedical Research Centre, UK Institute of Global Health Innovation a; School of Public Health, Imperial College London, UK Imperial College Healthcare NHS Trust, UK National Institute for Health Research Imperial Biomedical Resear; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc", + "abstract": "BackgroundCommunity surveys of SARS-CoV-2 RT-PCR swab-positivity provide prevalence estimates largely unaffected by biases from who presents for routine case testing. The REal-time Assessment of Community Transmission-1 (REACT-1) has estimated swab-positivity approximately monthly since May 2020 in England from RT-PCR testing of self-administered throat and nose swabs in random non-overlapping cross-sectional community samples. Estimating infection incidence from swab-positivity requires an understanding of the persistence of RT-PCR swab positivity in the community.\n\nMethodsDuring round 8 of REACT-1 from 6 January to 22 January 2021, of the 2,282 participants who tested RT-PCR positive, we recruited 896 (39%) from whom we collected up to two additional swabs for RT-PCR approximately 6 and 9 days after the initial swab. We estimated sensitivity and duration of positivity using an exponential model of positivity decay, for all participants and for subsets by initial N-gene cycle threshold (Ct) value, symptom status, lineage and age. Estimates of infection incidence were obtained for the entire duration of the REACT-1 study using P-splines.\n\nResultsWe estimated the overall sensitivity of REACT-1 to detect virus on a single swab as 0.79 (0.77, 0.81) and median duration of positivity following a positive test as 9.7 (8.9, 10.6) days. We found greater median duration of positivity where there was a low N-gene Ct value, in those exhibiting symptoms, or for infection with the Alpha variant. The estimated proportion of positive individuals detected on first swab, P0, was found to be higher for those with an initially low N-gene Ct value and those who were pre-symptomatic. When compared to swab-positivity, estimates of infection incidence over the duration of REACT-1 included sharper features with evident transient increases around the time of key changes in social distancing measures.\n\nDiscussionHome self-swabbing for RT-PCR based on a single swab, as implemented in REACT-1, has high overall sensitivity. However, participants time-since-infection, symptom status and viral lineage affect the probability of detection and the duration of positivity. These results validate previous efforts to estimate incidence of SARS-CoV-2 from swab-positivity data, and provide a reliable means to obtain community infection estimates to inform policy response.", + "category": "infectious diseases", + "match_type": "exact", + "author_similarity": 100, + "affiliation_similarity": 100 + }, { "site": "medRxiv", "doi": "10.1101/2021.08.05.21259863", @@ -2169,6 +2127,20 @@ "author_similarity": 100, "affiliation_similarity": 100 }, + { + "site": "medRxiv", + "doi": "10.1101/2021.07.14.21260488", + "date": "2021-07-16", + "link": "https://medrxiv.org/cgi/content/short/2021.07.14.21260488", + "title": "SARS-CoV-2 Antibody Lateral Flow Assay for antibody prevalence studies following vaccine roll out: a Diagnostic Accuracy Study", + "authors": "Alexandra H C Cann; Candice L Clarke; Jonathan C Brown; Tina Thomson; Maria Prendecki; Maya Moshe; Anjna Badhan; Paul Elliott; Ara Darzi; Steven Riley; Deborah Ashby; Michelle Willicombe; Peter Kelleher; Paul Randell; Helen Ward; Wendy Barclay; Graham Cooke", + "affiliations": "Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London School of Public Health; Imperial College London; Dept Inf Dis Epi, Imperial College; Imperial College London; Imperial College London; Imperial College London; Imperial College Healthcare NHS Trust, UK; Imperial College London; Department of Infectious Disease, Imperial College London, UK; Imperial College London", + "abstract": "BackgroundLateral flow immunoassays (LFIAs) have the potential to deliver affordable, large scale antibody testing and provide rapid results without the support of central laboratories. As part of the development of the REACT programme extensive evaluation of LFIA performance was undertaken with individuals following natural infection. Here we assess the performance of the selected LFIA to detect antibody responses in individuals who have received at least one dose of SARS-CoV-2 vaccine.\n\nMethodsThis is a prospective diagnostic accuracy study.\n\nSettingSampling was carried out at renal outpatient clinic and healthcare worker testing sites at Imperial College London NHS Trust. Laboratory analyses were performed across Imperial College London sites and university facilities.\n\nParticipantsTwo cohorts of patients were recruited; the first was a cohort of 108 renal transplant patients attending clinic following SARS-CoV-2 vaccine booster, the second cohort comprised 40 healthcare workers attending for first SARS-CoV-2 vaccination, and 21 day follow up. A total of 186 paired samples were collected.\n\nInterventionsDuring the participants visit, capillary blood samples were analysed on LFIA device, while paired venous sampling was sent for serological assessment of antibodies to the spike protein (anti-S) antibodies. Anti-S IgG were detected using the Abbott Architect SARS-CoV-2 IgG Quant II CMIA.\n\nMain outcome measuresThe accuracy of Fortress LFIA in detecting IgG antibodies to SARS-CoV-2 compared to anti-spike protein detection on Abbott Assay.\n\nResultsUsing the threshold value for positivity on serological testing of [≥]7.10 BAU/ml, the overall performance of the test produces an estimate of sensitivity of 91.94% (95% CI 85.67% to 96.06%) and specificity of 93.55% (95% CI 84.30% to 98.21%) using the Abbott assay as reference standard.\n\nConclusionsFortress LFIA performs well in the detection of antibody responses for intended purpose of population level surveys, but does not meet criteria for individual testing.", + "category": "infectious diseases", + "match_type": "exact", + "author_similarity": 100, + "affiliation_similarity": 100 + }, { "site": "medRxiv", "doi": "10.1101/2021.07.08.21260185", @@ -2421,20 +2393,6 @@ "author_similarity": 100, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2021.05.08.21256867", - "date": "2021-05-14", - "link": "https://medrxiv.org/cgi/content/short/2021.05.08.21256867", - "title": "SARS-CoV-2 lineage dynamics in England from January to March 2021 inferred from representative community samples", - "authors": "Oliver Eales; Andrew Page; Sonja N. Tang; Caroline E. Walters; Haowei Wang; David Haw; Alexander J. Trotter; Thanh Le Viet; Ebenezer Foster-Nyarko; Sophie Prosolek; Christina Atchinson; Deborah Ashby; Graham Cooke; Wendy Barclay; Christl A Donnelly; Justin O'Grady; Erik Volz; - The COVID-19 Genomics UK (COG-UK) Consortium; Ara Darzi; Helen Ward; Paul Elliott; Steven Riley", - "affiliations": "School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; Quadram Institute, Norwich, UK; School of Public Health, Imperial College London, UK; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; Quadram Institute, Norwich, UK; Quadram Institute, Norwich, UK; Quadram Institute, Norwich, UK; Quadram Institute, Norwich, UK; School of Public Health, Imperial College London, UK; School of Public Health, Imperial College London, UK; Department of Infectious Disease, Imperial College London, UK Imperial College Healthcare NHS Trust, UK National Institute for Health Research Imperial Biomedic; Department of Infectious Disease, Imperial College London, UK; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; Quadram Institute, Norwich, UK; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; ; Imperial College Healthcare NHS Trust, UK National Institute for Health Research Imperial Biomedical Research Centre, UK Institute of Global Health Innovation a; School of Public Health, Imperial College London, UK Imperial College Healthcare NHS Trust, UK National Institute for Health Research Imperial Biomedical Resear; School of Public Health, Imperial College London, UK Imperial College Healthcare NHS Trust, UK National Institute for Health Research Imperial Biomedical Resear; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc", - "abstract": "Genomic surveillance for SARS-CoV-2 lineages informs our understanding of possible future changes in transmissibility and vaccine efficacy. However, small changes in the frequency of one lineage over another are often difficult to interpret because surveillance samples are obtained from a variety of sources. Here, we describe lineage dynamics and phylogenetic relationships using sequences obtained from a random community sample who provided a throat and nose swab for rt-PCR during the first three months of 2021 as part of the REal-time Assessment of Community Transmission-1 (REACT-1) study. Overall, diversity decreased during the first quarter of 2021, with the B.1.1.7 lineage (first identified in Kent) predominant, driven by a 0.3 unit higher reproduction number over the prior wild type. During January, positive samples were more likely B.1.1.7 in younger and middle-aged adults (aged 18 to 54) than in other age groups. Although individuals infected with the B.1.1.7 lineage were no more likely to report one or more classic COVID-19 symptoms compared to those infected with wild type, they were more likely to be antibody positive 6 weeks after infection. Viral load was higher in B.1.1.7 infection as measured by cycle threshold (Ct) values, but did not account for the increased rate of testing positive for antibodies. The presence of infections with non-imported B.1.351 lineage (first identified in South Africa) during January, but not during February or March, suggests initial establishment in the community followed by fade-out. However, this occurred during a period of stringent social distancing and targeted public health interventions and does not immediately imply similar lineages could not become established in the future. Sequence data from representative community surveys such as REACT-1 can augment routine genomic surveillance.", - "category": "infectious diseases", - "match_type": "exact", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2021.05.06.21256755", @@ -2533,20 +2491,6 @@ "author_similarity": 100, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2021.04.22.21255913", - "date": "2021-04-23", - "link": "https://medrxiv.org/cgi/content/short/2021.04.22.21255913", - "title": "Impact of vaccination on SARS-CoV-2 cases in the community: a population-based study using the UK COVID-19 Infection Survey", - "authors": "Emma Pritchard; Philippa Matthews; Nicole Stoesser; David Eyre; Owen Gethings; Karina-Doris Vitha; Joel Jones; Thomas House; Harper VanSteenhouse; Iain Bell; John Bell; John Newton; Jeremy Farrar; Ian Diamond; Emma Rourke; Ruth Studley; Derrick W Crook; tim E peto; Ann Sarah Walker; Koen B Pouwels", - "affiliations": "University of Oxford; University of Oxford; University of Oxford; University of Oxford; Office for National Statistics; University of Oxford; Office for National Statistics; University of Manchester; Glasgow Lighthouse Laboratory; Office for National Statistics; University of Oxford; Public Health England; Wellcome Trust; Office for National Statistics,; Office for National Statistics; Office for National Statistics; NIHR Oxford Biomedical Research Centre; oxford university; University of Oxford; University of Oxford", - "abstract": "ObjectivesTo assess the effectiveness of COVID-19 vaccination in preventing SARS-CoV-2 infection in the community.\n\nDesignProspective cohort study.\n\nSettingThe UK population-representative longitudinal COVID-19 Infection Survey.\n\nParticipants373,402 participants aged [≥]16 years contributing 1,610,562 RT-PCR results from nose and throat swabs between 1 December 2020 and 3 April 2021.\n\nMain outcome measuresNew RT-PCR-positive episodes for SARS-CoV-2 overall, by self-reported symptoms, by cycle threshold (Ct) value (<30 versus [≥]30), and by gene positivity (compatible with the B.1.1.7 variant versus not).\n\nResultsOdds of new SARS-CoV-2 infection were reduced 65% (95% CI 60 to 70%; P<0.001) in those [≥]21 days since first vaccination with no second dose versus unvaccinated individuals without evidence of prior infection (RT-PCR or antibody). In those vaccinated, the largest reduction in odds was seen post second dose (70%, 95% CI 62 to 77%; P<0.001).There was no evidence that these benefits varied between Oxford-AstraZeneca and Pfizer-BioNTech vaccines (P>0.9).There was no evidence of a difference in odds of new SARS-CoV-2 infection for individuals having received two vaccine doses and with evidence of prior infection but not vaccinated (P=0.89). Vaccination had a greater impact on reducing SARS-CoV-2 infections with evidence of high viral shedding Ct<30 (88% reduction after two doses; 95% CI 80 to 93%; P<0.001) and with self-reported symptoms (90% reduction after two doses; 95% CI 82 to 94%; P<0.001); effects were similar for different gene positivity patterns.\n\nConclusionVaccination with a single dose of Oxford-AstraZeneca or Pfizer-BioNTech vaccines, or two doses of Pfizer-BioNTech, significantly reduced new SARS-CoV-2 infections in this large community surveillance study. Greater reductions in symptomatic infections and/or infections with a higher viral burden are reflected in reduced rates of hospitalisations/deaths, but highlight the potential for limited ongoing transmission from asymptomatic infections in vaccinated individuals.\n\nRegistrationThe study is registered with the ISRCTN Registry, ISRCTN21086382.", - "category": "infectious diseases", - "match_type": "exact", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2021.04.08.21255099", @@ -2687,34 +2631,6 @@ "author_similarity": 100, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2021.03.16.21253377", - "date": "2021-03-24", - "link": "https://medrxiv.org/cgi/content/short/2021.03.16.21253377", - "title": "First and second SARS-CoV-2 waves in inner London: A comparison of admission characteristics and the effects of the B.1.1.7 variant", - "authors": "Luke B Snell; Wenjuan Wang; Adela Alcolea-Medina; Themoula Charalampous; Gaia Nebbia; Rahul Batra; Leonardo de Jongh; Finola Higgins; Yanzhong Wang; Jonathan D Edgeworth; Vasa Curcin", - "affiliations": "King's College London; School of Population Health and Environmental Sciences, King's College London, London, UK; Viapath, London, UK; Centre for Clinical Infection and Diagnostics Research, School of Immunology and Microbial Sciences, King's College London, London, UK; Centre for Clinical Infection and Diagnostics Research, School of Immunology and Microbial Sciences, King's College London, London, UK; Centre for Clinical Infection and Diagnostics Research, School of Immunology and Microbial Sciences, King's College London, London, UK; NIHR Biomedical Research Centre, Guy's and St Thomas' NHS Foundation Trust; NIHR Biomedical Research Centre, Guy's and St Thomas' NHS Foundation Trust; School of Population Health and Environmental Sciences, King's College London, London, UK; Centre for Clinical Infection and Diagnostics Research, School of Immunology and Microbial Sciences, King's College London, London, UK; School of Population Health and Environmental Sciences, King's College London, London, UK", - "abstract": "IntroductionA second wave of SARS-CoV-2 infection spread across the UK in 2020 linked with emergence of the more transmissible B.1.1.7 variant. The emergence of new variants, particularly during relaxation of social distancing policies and implementation of mass vaccination, highlights the need for real-time integration of detailed patient clinical data alongside pathogen genomic data. We linked clinical data with viral genome sequence data to compare cases admitted during the first and second waves of SARS-CoV-2 infection.\n\nMethodsClinical, laboratory and demographic data from five electronic health record (EHR) systems was collected for all cases with a positive SARS-CoV-2 RNA test between March 13th 2020 and February 17th 2021. SARS-CoV-2 viral sequencing was performed using Oxford Nanopore Technology. Descriptive data are presented comparing cases between waves, and between cases of B.1.1.7 and non-B.1.1.7 variants.\n\nResultsThere were 5810 SARS-CoV-2 RNA positive cases comprising inpatients (n=2341), healthcare workers (n=1549), outpatients (n=874), emergency department (ED) attenders not subsequently admitted (n=532), inter-hospital transfers (n=281) and nosocomial cases (n=233). There were two dominant waves of hospital admissions, with wave one starting from March 13th (n=838) and wave two from October 20th (n=1503), both with a temporally aligned rise in nosocomial cases (n=96 in wave one, n=137 in wave two). 1470 SARS-CoV-2 isolates were successfully sequenced, including 216/838 (26%) admitted cases from wave one, 472/1503 (31%) admitted cases in wave two and 121/233 (52%) nosocomial cases. The first B.1.1.7 variant was identified on 15th November 2020 and increased rapidly such that it comprised 400/472 (85%) of sequenced isolates from admitted cases in wave two. Females made up a larger proportion of admitted cases in wave two (47.3% vs 41.8%, p=0.011), and in those infected with the B.1.1.7 variant compared to non-B.1.1.7 variants (48.0% vs 41.8%, p=0.042). A diagnosis of frailty was less common in wave two (11.5% v 22.8%, p<0.001) and in the group infected with B.1.1.7 (14.5% v 22.4%, p=0.001). There was no difference in severity on admission between waves, as measured by hypoxia at admission (wave one: 64.3% vs wave two: 65.5%, p=0.67). However, a higher proportion of cases infected with the B.1.1.7 variant were hypoxic on admission compared to other variants (70.0% vs 62.5%, p=0.029).\n\nConclusionsAutomated EHR data extraction linked with SARS-CoV-2 genome sequence data provides valuable insight into the evolving characteristics of cases admitted to hospital with COVID-19. The proportion of cases with hypoxia on admission was greater in those infected with the B.1.1.7 variant, which supports evidence the B.1.1.7 variant is associated with more severe disease. The number of nosocomial cases was similar in both waves despite introduction of many infection control interventions before wave two, an observation requiring further investigation.", - "category": "infectious diseases", - "match_type": "exact", - "author_similarity": 100, - "affiliation_similarity": 100 - }, - { - "site": "medRxiv", - "doi": "10.1101/2021.03.11.21253275", - "date": "2021-03-21", - "link": "https://medrxiv.org/cgi/content/short/2021.03.11.21253275", - "title": "Effect of vaccination on transmission of COVID-19: an observational study in healthcare workers and their households", - "authors": "Anoop Shah; Ciara Gribben; Jennifer Bishop; Peter Hanlon; David Caldwell; Rachael Wood; Martin Reid; Jim McMenamin; David Goldberg; Diane Stockton; Sharon Hutchinson; Chris Robertson; Paul M McKeigue; Helen M Colhoun; David McAllister", - "affiliations": "London School of Hygiene and Tropical Medicine; Public Health Scotland; Public Health Scotland; University of Glasgow; Public Health Scotland; PublicHealth Scotland; Public Health Scotland; Public Health Scotland; Public Health Scotland; Public Health Scotland; Public Health Scotland; Public Health Scotland; Public Health Scotland; Public Health Scotland; University of Glasgow", - "abstract": "BackgroundThe effect of vaccination for COVID-19 on onward transmission is unknown.\n\nMethodsA national record linkage study determined documented COVID-19 cases and hospitalisations in unvaccinated household members of vaccinated and unvaccinated healthcare workers from 8th December 2020 to 3rd March 2021. The primary endpoint was COVID-19 14 days following the first dose.\n\nResultsThe cohort comprised of 194,362 household members (mean age 31{middle dot}1 {+/-} 20{middle dot}9 years) and 144,525 healthcare workers (mean age 44{middle dot}4 {+/-} 11{middle dot}4 years). 113,253 (78{middle dot}3%) of healthcare workers received at least one dose of the BNT162b2 mRNA or ChAdOx1 nCoV-19 vaccine and 36,227 (25{middle dot}1%) received a second dose. There were 3,123 and 4,343 documented COVID-19 cases and 175 and 177 COVID-19 hospitalisations in household members of healthcare workers and healthcare workers respectively. Household members of vaccinated healthcare workers had a lower risk of COVID-19 case compared to household members of unvaccinated healthcare worker (rate per 100 person-years 9{middle dot}40 versus 5{middle dot}93; HR 0{middle dot}70, 95% confidence interval [CI] 0{middle dot}63 to 0{middle dot}78). The effect size for COVID-19 hospitalisation was similar, with the confidence interval crossing the null (HR 0{middle dot}77 [95% CI 0{middle dot}53 to 1{middle dot}10]). The rate per 100 person years was lower in vaccinated compared to unvaccinated healthcare workers for documented (20{middle dot}13 versus 8{middle dot}51; HR 0{middle dot}45 [95% CI 0{middle dot}42 to 0{middle dot}49]) and hospitalized COVID-19 (0{middle dot}97 versus 0{middle dot}14; HR 0{middle dot}16 [95% CI 0{middle dot}09 to 0{middle dot}27]). Compared to the period before the first dose, the risk of documented COVID-19 case was lower at [≥] 14 days after the second dose for household members (HR 0{middle dot}46 [95% CI 0{middle dot}30to 0{middle dot}70]) and healthcare workers (HR 0{middle dot}08 [95% CI 0{middle dot}04 to 0{middle dot}17]).\n\nInterpretationVaccination of health care workers was associated with a substantial reduction in COVID-19 cases in household contacts consistent with an effect of vaccination on transmission.", - "category": "public and global health", - "match_type": "exact", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2021.03.17.21253853", @@ -2729,20 +2645,6 @@ "author_similarity": 100, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2021.03.18.21253443", - "date": "2021-03-20", - "link": "https://medrxiv.org/cgi/content/short/2021.03.18.21253443", - "title": "Intensity of COVID-19 in care homes following Hospital Discharge in the early stages of the UK epidemic", - "authors": "Joe Hollinghurst; Laura North; Chris Emmerson; Ashley Akbari; Fatemeh Torabi; Ronan A Lyons; Alan G Hawkes; Ed Bennett; Mike B Gravenor; Richard Fry", - "affiliations": "Swansea University; Swansea University; Public Health Wales; Swansea University; Swansea University; Swansea University; Swansea University; Swansea University; Swansea University; Swansea University", - "abstract": "BackgroundA defining feature of the COVID-19 pandemic in many countries was the tragic extent to which care home residents were affected, and the difficulty preventing introduction and subsequent spread of infection. Management of risk in care homes requires good evidence on the most important transmission pathways. One hypothesised route at the start of the pandemic, prior to widespread testing, was transfer of patients from hospitals, which were experiencing high levels of nosocomial events.\n\nMethodsWe tested the hypothesis that hospital discharge events increased the intensity of care home cases using a national individually linked health record cohort in Wales, UK. We monitored 186,772 hospital discharge events over the period March to July 2020, tracking individuals to 923 care homes and recording the daily case rate in the homes populated by 15,772 residents. We estimated the risk of an increase in cases rates following exposure to a hospital discharge using multi-level hierarchical logistic regression, and a novel stochastic Hawkes process outbreak model.\n\nFindingsIn regression analysis, after adjusting for care home size, we found no significant association between hospital discharge and subsequent increases in care home case numbers (odds ratio: 0.99, 95% CI 0.82, 1.90). Risk factors for increased cases included care home size, care home resident density, and provision of nursing care. Using our outbreak model, we found a significant effect of hospital discharge on the subsequent intensity of cases. However, the effect was small, and considerably less than the effect of care home size, suggesting the highest risk of introduction came from interaction with the community. We estimated approximately 1.8% of hospital discharged patients may have been infected.\n\nInterpretationThere is growing evidence in the UK that the risk of transfer of COVID-19 from the high-risk hospital setting to the high-risk care home setting during the early stages of the pandemic was relatively small. Although access to testing was limited to initial symptomatic cases in each care home at this time, our results suggest that reduced numbers of discharges, selection of patients, and action taken within care homes following transfer all may have contributed to mitigation. The precise key transmission routes from the community remain to be quantified.", - "category": "health informatics", - "match_type": "exact", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2021.03.04.21252931", @@ -2967,6 +2869,20 @@ "author_similarity": 100, "affiliation_similarity": 100 }, + { + "site": "medRxiv", + "doi": "10.1101/2021.01.15.21249756", + "date": "2021-01-20", + "link": "https://medrxiv.org/cgi/content/short/2021.01.15.21249756", + "title": "Factors associated with deaths due to COVID-19 versus other causes: population-based cohort analysis of UK primary care data and linked national death registrations within the OpenSAFELY platform", + "authors": "Krishnan Bhaskaran; Sebastian CJ Bacon; Stephen JW Evans; Chris J Bates; Christopher T Rentsch; MacKenna Brian; Laurie Tomlinson; Alex J Walker; Anna Schultze; Caroline E Morton; Daniel Grint; Amir Mehrkar; Rosalind M Eggo; Peter Inglesby; Ian J Douglas; Helen I McDonald; Jonathan Cockburn; Elizabeth J Williamson; David Evans; Helen J Curtis; William J Hulme; John Parry; Frank Hester; Sam Harper; David Spiegelhalter; Liam Smeeth; Ben Goldacre", + "affiliations": "London School of Hygiene and Tropical Medicine; University of Oxford; London School of Hygiene Tropical Medicine; The Phoenix Partnership; London School of Hygiene and Tropical Medicine; University of Oxford; London School of Hygiene and Tropical Medicine; University of Oxford; London School of Hygiene and Tropical Medicine; University of Oxford; London School of Hygiene and Tropical Medicine; University of Oxford; London School of Hygiene and Tropical Medicine; University of Oxford; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; The Phoenix Partnership; London School of Hygiene and Tropical Medicine; University of Oxford; University of Oxford; University of Oxford; University of Oxford; The Phoenix Partnership; The Phoenix Partnership; Winton Centre for Risk and Evidence Communication, Centre for Mathematical Sciences, University of Cambridge; London School of Hygiene and Tropical Medicine; University of Oxford", + "abstract": "BackgroundMortality from COVID-19 shows a strong relationship with age and pre-existing medical conditions, as does mortality from other causes. However it is unclear how specific factors are differentially associated with COVID-19 mortality as compared to mortality from other causes.\n\nMethodsWorking on behalf of NHS England, we carried out a cohort study within the OpenSAFELY platform. Primary care data from England were linked to national death registrations. We included all adults (aged [≥]18 years) in the database on 1st February 2020 and with >1 year of continuous prior registration, the cut-off date for deaths was 9th November 2020. Associations between individual-level characteristics and COVID-19 and non-COVID deaths were estimated by fitting age- and sex-adjusted logistic models for these two outcomes.\n\nResults17,456,515 individuals were included. 17,063 died from COVID-19 and 134,316 from other causes. Most factors associated with COVID-19 death were similarly associated with non-COVID death, but the magnitudes of association differed. Older age was more strongly associated with COVID-19 death than non-COVID death (e.g. ORs 40.7 [95% CI 37.7-43.8] and 29.6 [28.9-30.3] respectively for [≥]80 vs 50-59 years), as was male sex, deprivation, obesity, and some comorbidities. Smoking, history of cancer and chronic liver disease had stronger associations with non-COVID than COVID-19 death. All non-white ethnic groups had higher odds than white of COVID-19 death (OR for Black: 2.20 [1.96-2.47], South Asian: 2.33 [2.16-2.52]), but lower odds than white of non-COVID death (Black: 0.88 [0.83-0.94], South Asian: 0.78 [0.75-0.81]).\n\nInterpretationSimilar associations of most individual-level factors with COVID-19 and non-COVID death suggest that COVID-19 largely multiplies existing risks faced by patients, with some notable exceptions. Identifying the unique factors contributing to the excess COVID-19 mortality risk among non-white groups is a priority to inform efforts to reduce deaths from COVID-19.\n\nFundingWellcome, Royal Society, National Institute for Health Research, National Institute for Health Research Oxford Biomedical Research Centre, UK Medical Research Council, Health Data Research UK.", + "category": "infectious diseases", + "match_type": "exact", + "author_similarity": 100, + "affiliation_similarity": 100 + }, { "site": "medRxiv", "doi": "10.1101/2021.01.19.21249840", @@ -3555,6 +3471,20 @@ "author_similarity": 100, "affiliation_similarity": 100 }, + { + "site": "medRxiv", + "doi": "10.1101/2020.09.21.20194019", + "date": "2020-09-23", + "link": "https://medrxiv.org/cgi/content/short/2020.09.21.20194019", + "title": "Putting (Big) Data in Action: Saving Lives with Countrywide Population Movement Monitoring Using Mobile Devices during the COVID-19 Crisis", + "authors": "Miklos Karoly Szocska; Peter Pollner; Istvan Schiszler; Tamas Joo; Tamas Palicz; Martin McKee; - Magyar Telekom Nyrt.; - Telenor Magyarorszag Zrt.; Adam Sohonyai; Jozsef Szoke; Adam Toth; Peter Gaal", + "affiliations": "Semmelweis University, Faculty of Health and Public Administration, Health Services Management Training Centre, Digital Health and Data Utilisation Team; Semmelweis University, Faculty of Health and Public Administration, Health Services Management Training Centre, Digital Health and Data Utilisation Team; Semmelweis University, Faculty of Health and Public Administration, Health Services Management Training Centre, Digital Health and Data Utilisation Team; Semmelweis University, Faculty of Health and Public Administration, Health Services Management Training Centre, Digital Health and Data Utilisation Team; Semmelweis University, Faculty of Health and Public Administration, Health Services Management Training Centre, Digital Health and Data Utilisation Team; University of London, London School of Hygiene and Tropical Medicine, Department of Health Services Research and Policy; ; ; Vodafone Hungary; Vodafone Hungary; Vodafone Hungary; Semmelweis University, Faculty of Health and Public Administration, Health Services Management Training Centre, Digital Health and Data Utilisation Team", + "abstract": "Many countries have implemented strict social distancing measures in the hope of reducing transmission of SARS-CoV-2 but the effectiveness of these measures is determined by the willingness of populations to comply with restrictions. Consequently, a system of monitoring population movement using existing data sources can inform those making decisions about policy responses to the COVID-19 pandemic. We describe a collaboration with all 3 major domestic telecommunication companies in Hungary to use aggregated anonymous mobile phone usage data to calculate two indices for assessing the effect of movement restrictions: a \"mobility-index\" and a \"stay-at-home (or resting) index\". The strengths and weaknesses of this approach are compared with the smartphone-based, COVID-19 Community Mobility Reports from Google. Data generated by mobile phones have long been identified as a potential means to analyse mass population movement, but its operationalisation raises several technical questions, such as making sense of Call Detail Records, collation of data from different mobile network providers, and personal data protection concerns. The method described here addresses these issues and offers an effective and inexpensive tool to monitor the impact of social distancing measures, achieving high levels of accuracy and resolution. Especially in populations where uptake of smartphones is modest, this method has certain advantages over app-based solutions, with greater population coverage, but it is not an alternative to smartphone-based solutions used for contact tracing and quarantine monitoring. We believe that this method can easily be adapted by other countries.", + "category": "infectious diseases", + "match_type": "exact", + "author_similarity": 100, + "affiliation_similarity": 100 + }, { "site": "medRxiv", "doi": "10.1101/2020.09.21.20196428", @@ -3989,6 +3919,20 @@ "author_similarity": 100, "affiliation_similarity": 100 }, + { + "site": "medRxiv", + "doi": "10.1101/2020.07.14.20153734", + "date": "2020-07-16", + "link": "https://medrxiv.org/cgi/content/short/2020.07.14.20153734", + "title": "Place and causes of acute cardiovascular mortality during the COVID19 pandemic: retrospective cohort study of 580,972 deaths in England and Wales, 2014 to 2020", + "authors": "Jianhua Wu; Mamas Mamas; Mohamed Mohamed; Chun Shing Kwok; Chris Roebuck; Ben Humberstone; Tom Denwood; Tom Luescher; Mark De Belder; John Deanfield; Chris Gale", + "affiliations": "University of Leeds; Keele University; Keele University; Keele University; NHS Digital; ONS; NHS Digital; Imperial College; Barts Health NHS Trust; UCL; University of Leeds", + "abstract": "ImportanceThe COVID-19 pandemic has resulted in a decline in admissions with cardiovascular (CV) emergencies. The fatal consequences of this are unknown.\n\nObjectivesTo describe the place and causes of acute CV death during the COVID-19 pandemic.\n\nDesignRetrospective nationwide cohort.\n\nSettingEngland and Wales.\n\nParticipantsAll adult (age [≥]18 years) acute CV deaths (n=580,972) between 1st January 2014 and 2nd June 2020.\n\nExposureThe COVID-19 pandemic (defined as from the onset of the first COVID-19 death in England on 2nd March 2020).\n\nMain outcomesPlace (hospital, care home, home) and acute CV events directly contributing to death as stated on the first part of the Medical Certificate of Cause of Death.\n\nResultsAfter 2nd March 2020, there were 22,820 acute CV deaths of which 5.7% related to COVID-19, and an excess acute CV mortality of 1752 (+8%) compared with the expected daily deaths in the same period. Deaths in the community accounted for nearly half of all deaths during this period. Care homes had the greatest increase in excess acute CV deaths (1065, +40%), followed by deaths at home (1728, +34%) and in hospital (57, +0%). The most frequent cause of acute CV death during this period was stroke (8,290, 36.3%), followed by acute coronary syndrome (ACS) (5,532, 24.2%), heart failure (5,280, 23.1%), pulmonary embolism (2,067, 9.1%) and cardiac arrest (1,037, 4.5%). Deep vein thrombosis had the greatest increase in cause of excess acute CV death (18, +25%), followed pulmonary embolism (340, +19%) and stroke (782, +10%). The greatest cause of excess CV death in care homes was stroke (700, +48%), compared with cardiac arrest (80, +56%) at home, and pulmonary embolism (126, +14%) and cardiogenic shock (41, +14%) in hospital.\n\nConclusions and relevanceThe COVID-19 pandemic has resulted in an inflation in acute CV deaths above that expected for the time of year, nearly half of which occurred in the community. The most common cause of acute CV death was stroke followed by acute coronary syndrome and heart failure. This is key information to optimise messaging to the public and enable health resource planning.", + "category": "cardiovascular medicine", + "match_type": "exact", + "author_similarity": 100, + "affiliation_similarity": 100 + }, { "site": "medRxiv", "doi": "10.1101/2020.07.14.20152629", @@ -4451,20 +4395,6 @@ "author_similarity": 100, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2020.05.06.20092999", - "date": "2020-05-07", - "link": "https://medrxiv.org/cgi/content/short/2020.05.06.20092999", - "title": "OpenSAFELY: factors associated with COVID-19-related hospital death in the linked electronic health records of 17 million adult NHS patients.", - "authors": "- The OpenSAFELY Collaborative; Elizabeth Williamson; Alex J Walker; Krishnan J Bhaskaran; Seb Bacon; Chris Bates; Caroline E Morton; Helen J Curtis; Amir Mehrkar; David Evans; Peter Inglesby; Jonathan Cockburn; Helen I Mcdonald; Brian MacKenna; Laurie Tomlinson; Ian J Douglas; Christopher T Rentsch; Rohini Mathur; Angel Wong; Richard Grieve; David Harrison; Harriet Forbes; Anna Schultze; Richard T Croker; John Parry; Frank Hester; Sam Harper; Rafael Perera; Stephen Evans; Liam Smeeth; Ben Goldacre", - "affiliations": "; London School of Hygiene and Tropical Medicine; University of Oxford; London School of Hygiene and Tropical Medicine; University of Oxford; TPP; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; TPP; London School of Hygiene and Tropical Medicine; University of Oxford; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; ICNARC; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; University of Oxford; TPP; TPP; TPP; University of Oxford; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; University of Oxford", - "abstract": "BackgroundEstablishing who is at risk from a novel rapidly arising cause of death, and why, requires a new approach to epidemiological research with very large datasets and timely data. Working on behalf of NHS England we therefore set out to deliver a secure and pseudonymised analytics platform inside the data centre of a major primary care electronic health records vendor establishing coverage across detailed primary care records for a substantial proportion of all patients in England. The following results are preliminary.\n\nData sourcesPrimary care electronic health records managed by the electronic health record vendor TPP, pseudonymously linked to patient-level data from the COVID-19 Patient Notification System (CPNS) for death of hospital inpatients with confirmed COVID-19, using the new OpenSAFELY platform.\n\nPopulation17,425,445 adults.\n\nTime period1st Feb 2020 to 25th April 2020.\n\nPrimary outcomeDeath in hospital among people with confirmed COVID-19.\n\nMethodsCohort study analysed by Cox-regression to generate hazard ratios: age and sex adjusted, and multiply adjusted for co-variates selected prospectively on the basis of clinical interest and prior findings.\n\nResultsThere were 5683 deaths attributed to COVID-19. In summary after full adjustment, death from COVID-19 was strongly associated with: being male (hazard ratio 1.99, 95%CI 1.88-2.10); older age and deprivation (both with a strong gradient); uncontrolled diabetes (HR 2.36 95% CI 2.18-2.56); severe asthma (HR 1.25 CI 1.08-1.44); and various other prior medical conditions. Compared to people with ethnicity recorded as white, black people were at higher risk of death, with only partial attenuation in hazard ratios from the fully adjusted model (age-sex adjusted HR 2.17 95% CI 1.84-2.57; fully adjusted HR 1.71 95% CI 1.44-2.02); with similar findings for Asian people (age-sex adjusted HR 1.95 95% CI 1.73-2.18; fully adjusted HR 1.62 95% CI 1.431.82).\n\nConclusionsWe have quantified a range of clinical risk factors for death from COVID-19, some of which were not previously well characterised, in the largest cohort study conducted by any country to date. People from Asian and black groups are at markedly increased risk of in-hospital death from COVID-19, and contrary to some prior speculation this is only partially attributable to pre-existing clinical risk factors or deprivation; further research into the drivers of this association is therefore urgently required. Deprivation is also a major risk factor with, again, little of the excess risk explained by co-morbidity or other risk factors. The findings for clinical risk factors are concordant with policies in the UK for protecting those at highest risk. Our OpenSAFELY platform is rapidly adding further NHS patients records; we will update and extend these results regularly.", - "category": "epidemiology", - "match_type": "exact", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2020.05.02.20078642", @@ -4633,20 +4563,6 @@ "author_similarity": 100, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2020.04.02.20051284", - "date": "2020-04-06", - "link": "https://medrxiv.org/cgi/content/short/2020.04.02.20051284", - "title": "Building an International Consortium for Tracking Coronavirus Health Status", - "authors": "Eran Segal; Feng Zhang; Xihong Lin; Gary King; Ophir Shalem; Smadar Shilo; William E. Allen; Yonatan H. Grad; Casey S. Greene; Faisal Alquaddoomi; Simon Anders; Ran Balicer; Tal Bauman; Ximena Bonilla; Gisel Booman; Andrew T. Chan; Ori Ori Cohen; Silvano Coletti; Natalie Davidson; Yuval Dor; David A. Drew; Olivier Elemento; Georgina Evans; Phil Ewels; Joshua Gale; Amir Gavrieli; Benjamin Geiger; Iman Hajirasouliha; Roman Jerala; Andre Kahles; Olli Kallioniemi; Ayya Keshet; Gregory Landua; Tomer Meir; Aline Muller; Long H. Nguyen; Matej Oresic; Svetlana Ovchinnikova; Hedi Peterson; Jay Rajagopal; Gunnar Ratsch; Hagai Rossman; Johan Rung; Andrea Sboner; Alexandros Sigaras; Tim Spector; Ron Steinherz; Irene Stevens; Jaak Vilo; Paul Wilmes; CCC (Coronavirus Census Collective)", - "affiliations": "Weizmann Institute of Science; Howard Hughes Medical Institute, Core Member, Broad Institute of MIT and Harvard, United States; Departments of Biostatistics and Statistics, Harvard T.H. Chan School of Public Health; Albert J. Weatherhead III University, Institute for Quantitative Social Science, Harvard University; Department of Genetics, Perelman School of Medicine, University of Pennsylvania, United States; Department of Computer Science and Applied Mathematics, and Department of Molecular Cell Biology, Weizmann Institute of Science, Israel; Society of Fellows, Harvard University, United States; Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, United States; Department of Systems Pharmacology and Translational Therapeutics, Perelman School of Medicine, University of Pennsylvania, United States; ETH Zurich, NEXUS Personalized Health Technologies, Zurich, Switzerland; Center for Molecular Biology (ZMBH), University of Heidelberg, Germany; Clalit Research Institute, Clalit Health Services, Israel; Mapping and Geo-Information Engineering, Civil and Environmental Engineering Faculty, The Technion, Israel; ETH Zurich, Department for Computer Science, Zurich, University Hospital Zurich, Medical Informatics, Zurich and SIB Swiss Institute of Bioinformatics, Zurich, ; Regen Network, Argentina; Massachusetts General Hospital (MGH), United States; Department of Computer Science and Applied Mathematics, and Department of Molecular Cell Biology, Weizmann Institute of Science, Israel; Chelonia Applied Science, Switzerland; ETH Zurich, Department for Computer Science, Zurich, University Hospital Zurich, Medical Informatics, Zurich and SIB Swiss Institute of Bioinformatics, Zurich, ; School of Medicine-IMRIC-Developmental Biology and Cancer Research, The Hebrew University; Massachusetts General Hospital (MGH), United States; Englander Institute for Precision Medicine and Department of Physiology and Biophysics, Weill Cornell Medicine, USA; Institute for Quantitative Social Science, Harvard University; Science for Life Laboratory (SciLifeLab), Department of Biochemistry and Biophysics, Stockholm University, Sweden; symptometrics.org; Department of Computer Science and Applied Mathematics, and Department of Molecular Cell Biology, Weizmann Institute of Science, Israel; Department of immunology, Weizmann Institute of Science, Israel; Englander Institute for Precision Medicine and Department of Physiology and Biophysics, Weill Cornell Medicine, USA; Department of Synthetic biology and Immunology, National Institute of Chemistry, Slovenia; ETH Zurich, Department for Computer Science, Zurich, University Hospital Zurich, Medical Informatics, Zurich and SIB Swiss Institute of Bioinformatics, Zurich, ; Science for Life Laboratory (SciLifeLab), Department of Oncology and Pathology, Karolinska Institutet, Stockholm, Sweden; Department of Computer Science and Applied Mathematics, and Department of Molecular Cell Biology, Weizmann Institute of Science, Israel; Regen Network, United States; Department of Computer Science and Applied Mathematics, and Department of Molecular Cell Biology, Weizmann Institute of Science, Israel; Luxembourg Institute of Socio-Economic Research and University of Luxembourg, Luxembourg; Massachusetts General Hospital (MGH), United States; School of Medical Sciences, Orebro University, Orebro, Sweden, and Turku Bioscience Centre, University of Turku and Abo Akademi University, Turku, Finland; Center for Molecular Biology (ZMBH), University of Heidelberg, Germany; Institute of Computer Science, University of Tartu, Estonia, Estonia; Internal Medicine, Harvard Medical School, Department of Pulmonary Medicine and Critical Care, Massachusetts General Hospital (MGH), United States; ETH Zurich, Department for Computer Science, Zurich, University Hospital Zurich, Medical Informatics, Zurich and SIB Swiss Institute of Bioinformatics, Zurich a; Department of Computer Science and Applied Mathematics, and Department of Molecular Cell Biology, Weizmann Institute of Science, Israel; Science for Life Laboratory (SciLifeLab), Department of Immunology, Genetics and Pathology, Uppsala university, Sweden; Englander Institute for Precision Medicine and Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, USA; Englander Institute for Precision Medicine and Department of Physiology and Biophysics, Weill Cornell Medicine, USA; Kings College, United Kingdom; Regen Network, United States; Science for Life Laboratory (SciLifeLab), Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet, Sweden; Institute of Computer Science, University of Tartu, Estonia, Estonia; Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Luxembourg; ", - "abstract": "Information is the most potent protective weapon we have to combat a pandemic, at both the individual and global level. For individuals, information can help us make personal decisions and provide a sense of security. For the global community, information can inform policy decisions and offer critical insights into the epidemic of COVID-19 disease. Fully leveraging the power of information, however, requires large amounts of data and access to it. To achieve this, we are making steps to form an international consortium, Coronavirus Census Collective (CCC, coronaviruscensuscollective.org), that will serve as a hub for integrating information from multiple data sources that can be utilized to understand, monitor, predict, and combat global pandemics. These sources may include self-reported health status through surveys (including mobile apps), results of diagnostic laboratory tests, and other static and real-time geospatial data. This collective effort to track and share information will be invaluable in predicting hotspots of disease outbreak, identifying which factors control the rate of spreading, informing immediate policy decisions, evaluating the effectiveness of measures taken by health organizations on pandemic control, and providing critical insight on the etiology of COVID-19. It will also help individuals stay informed on this rapidly evolving situation and contribute to other global efforts to slow the spread of disease.\n\nIn the past few weeks, several initiatives across the globe have surfaced to use daily self-reported symptoms as a means to track disease spread, predict outbreak locations, guide population measures and help in the allocation of healthcare resources. The aim of this paper is to put out a call to standardize these efforts and spark a collaborative effort to maximize the global gain while protecting participant privacy.", - "category": "infectious diseases", - "match_type": "exact", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2020.03.30.20047217", diff --git a/data/covid/preprints.json b/data/covid/preprints.json index 4dfeed84..b64d5e45 100644 --- a/data/covid/preprints.json +++ b/data/covid/preprints.json @@ -461,20 +461,6 @@ "author_similarity": 100, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2023.05.23.23289798", - "date": "2023-05-24", - "link": "https://medrxiv.org/cgi/content/short/2023.05.23.23289798", - "title": "Primary Care Post-COVID syndrome Diagnosis and Referral Coding", - "authors": "Robert Willans; Gail Allsopp; Pall Jonsson; Fiona Glen; Felix Greaves; John Macleod; Yinghui Wei; Sebastian Bacon; Amir Mehrkar; Alex Walker; Brian MacKenna; Louis Fisher; Ben Goldacre; - The OpenSAFELY Collaborative; - The CONVALESCENCE Collaborative", - "affiliations": "National Institute of Health and Care Excellence; Royal College of General Practitioners; National Institute of Health and Care Excellence; National Institute of Health and Care Excellence; National Institute of Health and Care Excellence; University of Bristol; University of Plymouth; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford; ; ", - "abstract": "IntroductionGuidelines for diagnosing and managing Post-COVID syndrome have been rapidly developed. Consistency of the application of these guidelines in primary care is unknown. Electronic health records provide an opportunity to review the use of codes relating to Post-COVID syndrome. This paper explores the use of primary care records as a surrogate uptake measure for NICEs rapid guideline \"managing the long-term effects of COVID-19\" by measuring the use of Post-COVID syndrome diagnosis and referral codes in the pathway.\n\nMethodWith the approval of NHS England we used routine clinical data from the OpenSafely-EMIS/-TPP platforms. Counts of Post-COVID syndrome diagnosis and referral codes were generated from a cohort of all adults, establishing numbers of diagnoses and referrals following diagnosis. The relationship between Post-COVID syndrome diagnosis and referral codes was explored with reference to NICEs rapid guideline.\n\nResultsOf over 45 million patients, 69,220 (0.15%) had a Post-COVID syndrome diagnostic code, and 67,741 (0.15%) had a referral code. 78% of referral codes did not have an associated diagnosis code. 79% of diagnosis codes had no subsequent referral code. Only 18,633 (0.04%) had both. There were higher rates of both diagnosis and referral in those who were more deprived, female and some ethnic groups.\n\nDiscussionThis study demonstrates variation in diagnosis and referral coding rates for Post-COVID syndrome across different patient groups. The results, with limited crossover of referral and diagnostic codes, suggest only one type of code is usually recorded. Recording one code limits the use of routine data for monitoring Post-COVID syndrome diagnosis and management, but suggests several areas for improvement in coding. Post-COVID syndrome coding, particularly diagnosis coding, needs to improve before administrators and researchers can use it to evaluate care pathways.", - "category": "epidemiology", - "match_type": "fuzzy", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2023.05.17.23290105", @@ -587,20 +573,6 @@ "author_similarity": 100, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2023.03.21.23287524", - "date": "2023-03-22", - "link": "https://medrxiv.org/cgi/content/short/2023.03.21.23287524", - "title": "Employment outcomes of people with Long Covid symptoms: community-based cohort study", - "authors": "Daniel Ayoubkhani; Francesco Zaccardi; Koen B Pouwels; Ann Sarah Walker; Donald Houston; Nisreen A Alwan; Josh Martin; Kamlesh Khunti; Vahe Nafilyan", - "affiliations": "Office for National Statistics; University of Leicester; University of Oxford; University of Oxford; University of Portsmouth; University of Southampton; Bank of England; University of Leicester; Office for National Statistics", - "abstract": "BackgroundEvidence on the long-term employment consequences of SARS-CoV-2 infection is lacking. We used data from a large, community-based sample in the UK to estimate associations between Long Covid and subsequent employment outcomes.\n\nMethodsThis was an observational, longitudinal study using a pre-post design. We included survey participants from 3 February 2021 to 30 September 2022 when they were aged 16 to 64 years and not in full-time education. Using conditional logit modelling, we explored the time-varying relationship between Long Covid status [≥]12 weeks after a first test-confirmed SARS-CoV-2 infection (reference: pre-infection) and labour market inactivity (neither working nor looking for work) or workplace absence lasting [≥]4 weeks.\n\nResultsOf 206,299 included participants (mean age 45 years, 54% female, 92% white), 15% were ever inactive in the labour market and 10% were ever long-term absent during follow-up. Compared with pre-infection, inactivity was higher in participants reporting Long Covid 30 to <40 weeks (adjusted odds ratio (aOR): 1.45; 95% CI: 1.17 to 1.81) or 40 to <52 weeks (1.34; 1.05 to 1.72) post-infection. Combining with official statistics on Long Covid prevalence, our estimates translate to 27,000 (95% CI: 6,000 to 47,000) working-age adults in the UK being inactive because of Long Covid in July 2022.\n\nConclusionsLong Covid is likely to have contributed to reduced levels of participation in the UK labour market, though it is unlikely to be the sole driver. Further research is required to quantify the contribution of other factors, such as indirect health effects of the pandemic.", - "category": "epidemiology", - "match_type": "fuzzy", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2023.03.15.23287300", @@ -1273,20 +1245,6 @@ "author_similarity": 100, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2022.09.11.22279823", - "date": "2022-09-12", - "link": "https://medrxiv.org/cgi/content/short/2022.09.11.22279823", - "title": "Effects of the COVID-19 pandemic on the mental health of clinically extremely vulnerable children and children living with clinically extremely vulnerable people in Wales: A data linkage study", - "authors": "Laura Elizabeth Cowley; Karen Hodgson; Jiao Song; Tony Whiffen; Jacinta Tan; Ann John; Amrita Bandyopadhyay; Alisha R Davies", - "affiliations": "Swansea University; Public Health Wales; Public Health Wales; Welsh Government; University of Oxford; Swansea University; Swansea University; Public Health Wales", - "abstract": "ObjectivesTo determine whether clinically extremely vulnerable (CEV) children or children living with a CEV person in Wales were at greater risk of presenting with anxiety or depression in primary or secondary care during the COVID-19 pandemic compared with children in the general population, and to compare patterns of anxiety and depression during the pandemic (23rd March 2020-31st January 2021, referred to as 2020/21) and before the pandemic (March 23rd 2019-January 31st 2020, referred to as 2019/20), between CEV children and the general population.\n\nDesignPopulation-based cross-sectional cohort study using anonymised, linked, routinely collected health and administrative data held in the Secure Anonymised Information Linkage Databank. CEV individuals were identified using the COVID-19 Shielded Patient List.\n\nSettingPrimary and secondary healthcare settings covering 80% of the population of Wales.\n\nParticipantsChildren aged 2-17 in Wales: CEV (3,769); living with a CEV person (20,033); or neither (415,009).\n\nPrimary outcome measureFirst record of anxiety or depression in primary or secondary healthcare in 2019/20 and 2020/21, identified using Read and ICD-10 codes.\n\nResultsA Cox regression model adjusted for demographics and history of anxiety or depression revealed that only CEV children were at greater risk of presenting with anxiety or depression during the pandemic compared with the general population (Hazard Ratio=2.27, 95% Confidence Interval=1.94-2.66, p<0.001). Compared with the general population, the risk amongst CEV children was higher in 2020/21 (Risk Ratio 3.04) compared with 2019/20 (Risk Ratio 1.90). In 2020/21, the cumulative incidence of anxiety or depression increased slightly amongst CEV children, but declined amongst the general population.\n\nConclusionsDifferences in the cumulative incidences of recorded anxiety or depression in healthcare between CEV children and the general population were largely driven by a reduction in presentations to healthcare services by children in the general population during the pandemic.\n\nStrengths and limitations of this studyO_LIStrengths of this study include its novelty, national focus and clinical relevance; to date this is the first population-based study examining the effects of the COVID-19 pandemic on healthcare use for anxiety or depression amongst clinically extremely vulnerable (CEV) children and children living with a CEV person in Wales\nC_LIO_LIWe compared 2020/21 data with pre-pandemic 2019/20 data for CEV children and children in the general population, to place the impact of the COVID-19 pandemic in the context of longer-term patterns of healthcare use\nC_LIO_LIWe used a novel approach and linked multiple datasets to identify a cohort of children living with a CEV person in Wales during the COVID-19 pandemic\nC_LIO_LIThere was heterogeneity within the Shielded Patient List that was used to create the cohorts of children identified as CEV or living with a CEV person, in terms of the type and severity of individuals underlying conditions; the manner in which people were added to the list; the time point that people were added to the list; and the extent to which people followed the shielding guidance\nC_LIO_LIRoutinely collected healthcare data does not capture self-reported health, and is likely to underestimate the burden of common mental disorders in the population\nC_LI", - "category": "pediatrics", - "match_type": "fuzzy", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2022.09.09.22279754", @@ -1315,20 +1273,6 @@ "author_similarity": 100, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2022.08.29.22279359", - "date": "2022-08-31", - "link": "https://medrxiv.org/cgi/content/short/2022.08.29.22279359", - "title": "Prophylactic Treatment of COVID-19 in Care Homes Trial (PROTECT-CH)", - "authors": "Philip M Bath; Jonathan Ball; Matthew Boyd; Heather Gage; Matthew Glover; Maureen Godfrey; Bruce Guthrie; Jonathan Hewitt; Robert Howard; Thomas Jaki; Edmund Juszczak; Daniel Lasserson; Paul Leighton; Val Leyland; Wei Shen Lim; Pip Logan; Garry Meakin; Alan Montgomery; Reuben Ogollah; Peter Passmore; Philip Quinlan; Caroline Rick; Simon Royal; Susan D Shenkin; Clare Upton; Adam L Gordon; - PROTECT-CH Trialists", - "affiliations": "University of Nottingham; University of Nottingham; University of Nottingham; University of Surrey; University of Surrey; Private person; University of Edinburgh; Llandough Hospital; University College London; University of Cambridge; University of Nottingham; University of Warwick; University of Nottingham; Private person; Nottingham University Hospitals NHS Trust; University of Nottingham; University of Nottingham; University of Nottingham; University of Nottingham; Queen's University Belfast; University of Nottingham; University of Nottingham; Cripps Health Centre; University of Edinburgh; University of Nottingham; University of Nottingham; ", - "abstract": "BackgroundCoronavirus disease 2019 (COVID-19) is associated with significant mortality and morbidity in care homes. Novel or repurposed antiviral drugs may reduce infection and disease severity through reducing viral replication and inflammation.\n\nObjectiveTo compare the safety and efficacy of antiviral agents (ciclesonide, niclosamide) for preventing SARS-CoV-2 infection and COVID-19 severity in care home residents.\n\nDesignCluster-randomised open-label blinded endpoint platform clinical trial testing antiviral agents in a post-exposure prophylaxis paradigm.\n\nSettingCare homes across all four United Kingdom member countries.\n\nParticipantsCare home residents 65 years of age or older.\n\nInterventionsCare homes were to be allocated at random by computer to 42 days of antiviral agent plus standard care versus standard of care and followed for 60 days after randomisation.\n\nMain outcome measuresThe primary four-level ordered categorical outcome with participants classified according to the most serious of all-cause mortality, all-cause hospitalisation, SARS-CoV-2 infection and no infection. Analysis using ordinal logistic regression was by intention to treat. Other outcomes included the components of the primary outcome and transmission.\n\nResultsDelays in contracting between NIHR and the manufacturers of potential antiviral agents significantly delayed any potential start date. Having set up the trial (protocol, approvals, insurance, website, database, routine data algorithms, training materials), the trial was stopped in September 2021 prior to contracting of care homes and general practitioners in view of the success of vaccination in care homes with significantly reduced infections, hospitalisations and deaths. As a result, the sample size target (based on COVID-19 rates and deaths occurring in February-June 2020) became unfeasible.\n\nLimitationsCare home residents were not approached about the trial and so were not consented and did not receive treatment. Hence, the feasibility of screening, consent, treatment and data acquisition, and potential benefit of post exposure prophylaxis were never tested. Further, contracting between the University of Nottingham and the PIs, GPs and care homes was not completed, so the feasibility of contracting with all the different groups at the scale needed was not tested.\n\nConclusionsThe role of post exposure prophylaxis of COVID-19 in care home residents was not tested because of changes in COVID-19 incidence, prevalence and virulence as a consequence of the vaccination programme that rendered the study unfeasible. Significant progress was made in describing and developing the infrastructure necessary for a large scale Clinical Trial of Investigational Medicinal Products in care homes in all four UK nations.\n\nFuture workThe role of post-exposure prophylaxis of COVID-19 in care home residents remains to be defined. Significant logistical barriers to conducting research in care homes during a pandemic need to be removed before such studies are possible in the required short timescale.", - "category": "infectious diseases", - "match_type": "fuzzy", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2022.08.29.22279333", @@ -1665,6 +1609,20 @@ "author_similarity": 100, "affiliation_similarity": 100 }, + { + "site": "medRxiv", + "doi": "10.1101/2022.06.16.22276476", + "date": "2022-06-16", + "link": "https://medrxiv.org/cgi/content/short/2022.06.16.22276476", + "title": "Moral injury and psychological wellbeing in UK healthcare staff", + "authors": "Victoria Williamson; Danielle Lamb; Matthew Hotopf; Rosalind Raine; Sharon Stevelink; Simon Wessely; Mary Jane Docherty; Ira Madan; Dominic Murphy; Neil Greenberg", + "affiliations": "King's College London; UCL; King's College London; King's College London; King's College London; King's College London; South London and Maudsley NHS Foundation Trust; Guy's and St Thomas' NHS Foundation Trust; King's College London; King's College London", + "abstract": "BackgroundPotentially morally injurious events (PMIEs) can negatively impact mental health. The COVID-19 pandemic may have placed healthcare staff at risk of moral injury.\n\nAimTo examine the impact of PMIE on healthcare staff wellbeing.\n\nMethod12,965 healthcare staff (clinical and non-clinical) were recruited from 18 NHS-England trusts into a survey of PMIE exposure and wellbeing.\n\nResultsPMIEs were significantly associated with adverse mental health symptoms across healthcare staff. Specific work factors were significantly associated with experiences of moral injury, including being redeployed, lack of PPE, and having a colleague die of COVID-19. Nurses who reported symptoms of mental disorders were more likely to report all forms of PMIEs than those without symptoms (AOR 2.7; 95% CI 2.2, 3.3). Doctors who reported symptoms were only more likely to report betrayal events, such as breach of trust by colleagues (AOR 2.7, 95% CI 1.5, 4.9).\n\nConclusionsA considerable proportion of NHS healthcare staff in both clinical and non-clinical roles report exposure to PMIEs during the COVID-19 pandemic. Prospective research is needed to identify the direction of causation between moral injury and mental disorder as well as continuing to monitor the longer term outcomes of exposure to PMIEs.", + "category": "psychiatry and clinical psychology", + "match_type": "fuzzy", + "author_similarity": 100, + "affiliation_similarity": 100 + }, { "site": "medRxiv", "doi": "10.1101/2022.06.14.22276391", @@ -1847,20 +1805,6 @@ "author_similarity": 96, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2022.05.19.22275214", - "date": "2022-05-22", - "link": "https://medrxiv.org/cgi/content/short/2022.05.19.22275214", - "title": "Antibody levels following vaccination against SARS-CoV-2: associations with post-vaccination infection and risk factors", - "authors": "Nathan J Cheetham; Milla Kibble; Andrew Wong; Richard J Silverwood; Anika Knuppel; Dylan M Williams; Olivia K L Hamilton; Paul H Lee; Charis Bridger Staatz; Giorgio Di Gessa; Jingmin Zhu; Srinivasa Vittal Katikireddi; George B Ploubidis; Ellen J Thompson; Ruth C E Bowyer; Xinyuan Zhang; Golboo Abbasian; Maria Paz Garcia; Deborah Hart; Jeffrew Seow; Carl Graham; Neophytos Kouphou; Sam Acors; Michael H Malim; Ruth E Mitchell; Kate Northstone; Daniel Major-Smith; Sarah Matthews; Thomas Breeze; Michael Crawford; Lynn Molloy; Alex Siu Fung Kwong; Katie J Doores; Nishi Chaturvedi; Emma L Duncan; Nicholas J Timpson; Claire J Steves", - "affiliations": "King's College London; University of Cambridge; University College London; University College London; University College London; University College London; University of Glasgow; University of Leicester; University College London; University College London; University College London; University of Glasgow; University College London; King's College London; King's College London; King's College London; King's College London; King's College London; King's College London; King's College London; King's College London; King's College London; King's College London; King's College London; University of Bristol; University of Bristol; University of Bristol; University of Bristol; University of Bristol; University of Bristol; University of Bristol; University of Bristol; King's College London; University College London; King's College London; University of Bristol; King's College London", - "abstract": "SARS-CoV-2 antibody levels can be used to assess humoral immune responses following SARS-CoV-2 infection or vaccination, and may predict risk of future infection. From cross-sectional antibody testing of 9,361 individuals from TwinsUK and ALSPAC UK population-based longitudinal studies (jointly in April-May 2021, and TwinsUK only in November 2021-January 2022), we tested associations between antibody levels following vaccination and: (1) SARS-CoV-2 infection following vaccination(s); (2) health, socio-demographic, SARS-CoV-2 infection and SARS-CoV-2 vaccination variables.\n\nWithin TwinsUK, single-vaccinated individuals with the lowest 20% of anti-Spike antibody levels at initial testing had 3-fold greater odds of SARS-CoV-2 infection over the next six to nine months, compared to the top 20%. In TwinsUK and ALSPAC, individuals identified as at increased risk of COVID-19 complication through the UK \"Shielded Patient List\" had consistently greater odds (2 to 4-fold) of having antibody levels in the lowest 10%. Third vaccination increased absolute antibody levels for almost all individuals, and reduced relative disparities compared with earlier vaccinations.\n\nThese findings quantify the association between antibody level and risk of subsequent infection, and support a policy of triple vaccination for the generation of protective antibodies.\n\nLay summaryIn this study, we analysed blood samples from 9,361 participants from two studies in the UK: an adult twin registry, TwinsUK (4,739 individuals); and the Avon Longitudinal Study of Parents and Children, ALSPAC (4,622 individuals). We did this work as part of the UK Government National Core Studies initiative researching COVID-19. We measured blood antibodies which are specific to SARS-CoV-2 (which causes COVID-19). Having a third COVID-19 vaccination boosted antibody levels. More than 90% of people from TwinsUK had levels after third vaccination that were greater than the average level after second vaccination. Importantly, this was the case even in individuals on the UK \"Shielded Patient List\". We found that people with lower antibody levels after first vaccination were more likely to report having COVID-19 later on, compared to people with higher antibody levels. People on the UK \"Shielded Patient List\", and individuals who reported that they had poorer general health, were more likely to have lower antibody levels after vaccination. In contrast, people who had had a previous COVID-19 infection were more likely to have higher antibody levels following vaccination compared to people without infection. People receiving the Oxford/AstraZeneca rather than the Pfizer BioNTech vaccine had lower antibody levels after one or two vaccinations. However, after a third vaccination, there was no difference in antibody levels between those who had Oxford/AstraZeneca and Pfizer BioNTech vaccines for their first two doses. These findings support having a third COVID-19 vaccination to boost antibodies.", - "category": "epidemiology", - "match_type": "fuzzy", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2022.05.11.22274964", @@ -1973,6 +1917,20 @@ "author_similarity": 100, "affiliation_similarity": 100 }, + { + "site": "medRxiv", + "doi": "10.1101/2022.05.03.22274602", + "date": "2022-05-03", + "link": "https://medrxiv.org/cgi/content/short/2022.05.03.22274602", + "title": "Accident and emergency (AE) attendance in England following infection with SARS-CoV-2 Omicron or Delta", + "authors": "Daniel J Grint; Kevin Wing; Hamish P Gibbs; Stephen JW Evans; Elizabeth J Williamson; Krishnan Bhaskaran; Helen I McDonald; Alex J Walker; David Evans; George Hickman; Rohini Mathur; Anna Schultze; Christopher T Rentsch; John Tazare; Ian J Douglas; Helen J Curtis; Caroline E Morton; Sebastian CJ Bacon; Simon Davy; Brian MacKenna; Peter Inglesby; Richard Croker; John Parry; Frank Hester; Sam Harper; Nicholas J DeVito; William J Hulme; Christopher Bates; Jonathan Cockburn; Amir Mehrkar; Ben Goldacre; Rosalind M Eggo; Laurie Tomlinson", + "affiliations": "London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; University of Oxford; University of Oxford; University of Oxford; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; TPP; TPP; TPP; University of Oxford; University of Oxford; TPP; TPP; University of Oxford; University of Oxford; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine", + "abstract": "The SARS-CoV-2 Omicron variant is increasing in prevalence around the world. Accurate estimation of disease severity associated with Omicron is critical for pandemic planning. We found lower risk of accident and emergency (AE) attendance following SARS-CoV-2 infection with Omicron compared to Delta (HR: 0.39 (95% CI: 0.30 - 0.51; P<.0001). For AE attendances that lead to hospital admission, Omicron was associated with an 85% lower hazard compared with Delta (HR: 0.14 (95% CI: 0.09 - 0.24; P<.0001)).\n\nConflicts of InterestsNothing to declare.\n\nFunding statementThis work was supported by the Medical Research Council MR/V015737/1. TPP provided technical expertise and infrastructure within their data centre pro bono in the context of a national emergency. Rosalind Eggo is funded by HDR UK (grant: MR/S003975/1), MRC (grant: MC_PC 19065), NIHR (grant: NIHR200908).", + "category": "infectious diseases", + "match_type": "fuzzy", + "author_similarity": 100, + "affiliation_similarity": 100 + }, { "site": "medRxiv", "doi": "10.1101/2022.04.29.22274267", @@ -2323,20 +2281,6 @@ "author_similarity": 94, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2022.03.14.22272283", - "date": "2022-03-14", - "link": "https://medrxiv.org/cgi/content/short/2022.03.14.22272283", - "title": "Migrants' primary care utilisation before and during the COVID-19 pandemic in England: An interrupted time series", - "authors": "Claire X Zhang; Yamina Boukari; Neha Pathak; Rohini Mathur; Srinivasa Vittal Katikireddi; Parth Patel; In\u00eas Campos-Matos; Dan Lewer; Vincent Nguyen; Greg Hugenholtz; Rachel Burns; Amy R Mulick; Alasdair Henderson; Robert W Aldridge", - "affiliations": "UCL; University College London; University College London; London School of Hygiene and Tropical Medicine; University of Glasgow; University College London; Department of Health and Social Care; University College London; University College London; University College London; University College London; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; UCL", - "abstract": "BackgroundHow international migrants access and use primary care in England is poorly understood. We aimed to compare primary care consultation rates between international migrants and non-migrants in England before and during the COVID-19 pandemic (2015- 2020).\n\nMethodsUsing linked data from the Clinical Practice Research Datalink (CPRD) GOLD and the Office for National Statistics, we identified migrants using country-of-birth, visa-status or other codes indicating international migration. We ran a controlled interrupted time series (ITS) using negative binomial regression to compare rates before and during the pandemic.\n\nFindingsIn 262,644 individuals, pre-pandemic consultation rates per person-year were 4.35 (4.34-4.36) for migrants and 4.6 (4.59-4.6) for non-migrants (RR:0.94 [0.92-0.96]). Between 29 March and 26 December 2020, rates reduced to 3.54 (3.52-3.57) for migrants and 4.2 (4.17-4.23) for non-migrants (RR:0.84 [0.8-0.88]). Overall, this represents an 11% widening of the pre-pandemic difference in consultation rates between migrants and non-migrants during the first year of the pandemic (RR:0.89, 95%CI:0.84-0.94). This widening was greater for children, individuals whose first language was not English, and individuals of White British, White non-British and Black/African/Caribbean/Black British ethnicities.\n\nInterpretationMigrants were less likely to use primary care before the pandemic and the first year of the pandemic exacerbated this difference. As GP practices retain remote and hybrid models of service delivery, they must improve services and ensure they are accessible and responsive to migrants healthcare needs.\n\nFundingThis study was funded by the Medical Research Council (MR/V028375/1) and Wellcome Clinical Research Career Development Fellowship (206602).", - "category": "primary care research", - "match_type": "fuzzy", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2022.03.10.22272177", @@ -2365,20 +2309,6 @@ "author_similarity": 100, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2022.03.13.22272176", - "date": "2022-03-13", - "link": "https://medrxiv.org/cgi/content/short/2022.03.13.22272176", - "title": "Vaccination against SARS-CoV-2 in UK school-aged children and young people decreases infection rates and reduces COVID-19 symptoms", - "authors": "Erika Molteni; Liane S Canas; Kerstin Klaser; Jie Deng; Sunil S Bhopal; Robert C Hughes; Liyuan Chen; Benjamin Murray; Eric Kerfoot; Michela Antonelli; Carole Helene Sudre; Joan Capdevila Pujol; Lorenzo Polidori; Anna May; Alexander Hammers; Jonathan Wolf; Timothy Spector; Claire J Steves; Sebastien Ourselin; Michael Absoud; Marc Modat; Emma L Duncan", - "affiliations": "King's College London; King's College London; King's College London; King's College London; Newcastle University; London School of Hygiene & Tropical Medicine, London; King's College London; King's College London; King's College London; King's College London; King's College London; Zoe Limited, London, UK; Zoe Limited, London, UK; Zoe Limited, London, UK; King's College London; Zoe Limited, London, UK; King's College London; King's College London; King's College London; King's College London; King's College London; King's College London", - "abstract": "BackgroundWe aimed to explore the effectiveness of one-dose BNT162b2 vaccination upon SARS-CoV-2 infection, its effect on COVID-19 presentation, and post-vaccination symptoms in children and young people (CYP) in the UK during periods of Delta and Omicron variant predominance.\n\nMethodsIn this prospective longitudinal cohort study, we analysed data from 115,775 CYP aged 12-17 years, proxy-reported through the Covid Symptom Study (CSS) smartphone application. We calculated post-vaccination infection risk after one dose of BNT162b2, and described the illness profile of CYP with post-vaccination SARS- CoV-2 infection, compared to unvaccinated CYP, and post-vaccination side-effects.\n\nFindingsBetween August 5, 2021 and February 14, 2022, 25,971 UK CYP aged 12-17 years received one dose of BNT162b2 vaccine. Vaccination reduced (proxy-reported) infection risk (-80{middle dot}4% and -53{middle dot}7% at 14-30 days with Delta and Omicron variants respectively, and -61{middle dot}5% and -63{middle dot}7% after 61-90 days). The probability of remaining infection-free diverged soon after vaccination, and was greater in CYP with prior SARS-CoV-2 infection. Vaccinated CYP who contracted SARS-CoV-2 during the Delta period had milder disease than unvaccinated CYP; during the Omicron period this was only evident in children aged 12-15 years. Overall disease profile was similar in both vaccinated and unvaccinated CYP. Post-vaccination local side-effects were common, systemic side-effects were uncommon, and both resolved quickly.\n\nInterpretationOne dose of BNT162b2 vaccine reduced risk of SARS-CoV-2 infection for at least 90 days in CYP aged 12-17 years. Vaccine protection varied for SARS-CoV-2 variant type (lower for Omicron than Delta variant), and was enhanced by pre-vaccination SARS-CoV-2 infection. Severity of COVID-19 presentation after vaccination was generally milder, although unvaccinated CYP also had generally mild disease. Overall, vaccination was well-tolerated.\n\nFundingUK Government Department of Health and Social Care, Chronic Disease Research Foundation, The Wellcome Trust, UK Engineering and Physical Sciences Research Council, UK Research and Innovation London Medical Imaging & Artificial Intelligence Centre for Value Based Healthcare, UK National Institute for Health Research, UK Medical Research Council, British Heart Foundation and Alzheimers Society, and ZOE Limited.\n\nResearch in context\n\nEvidence before this studyWe searched PubMed database for peer-reviewed articles and medRxiv for preprint papers, published between January 1, 2021 and February 15, 2022 using keywords (\"SARS-CoV-2\" OR \"COVID-19\") AND (child* OR p?ediatric* OR teenager*) AND (\"vaccin*\" OR \"immunization campaign\") AND (\"efficacy\" OR \"effectiveness\" OR \"symptoms\") AND (\"delta\" or \"omicron\" OR \"B.1.617.2\" OR \"B.1.1.529\"). The PubMed search retrieved 36 studies, of which fewer than 30% specifically investigated individuals <18 years.\n\nEleven studies explored SARS-CoV-2 viral transmission: seroprevalence in children (n=4), including age-dependency of susceptibility to SARS-CoV-2 infection (n=1), SARS-CoV-2 transmission in schools (n=5), and the effect of school closure on viral transmission (n=1).\n\nEighteen documents reported clinical aspects, including manifestation of infection (n=13), symptomatology, disease duration, and severity in children. Other studies estimated emergency department visits, hospitalization, need for intensive care, and/or deaths in children (n=4), and explored prognostic factors (n=1).\n\nThirteen studies explored vaccination-related aspects, including vaccination of children within specific paediatric co-morbidity groups (e.g., children with Down syndrome, inflammatory bowel disease, and cancer survivors, n=4), mRNA vaccine efficacy in children and adolescents from the general population (n=7), and the relation between vaccination and severity of disease and hospitalization cases (n=2). Four clinical trials were conducted using mRNA vaccines in minors, also exploring side effects. Sixty percent of children were found to have side effects after BNT162b2 vaccination, and especially after the second dose; however, most symptoms were mild and transient apart from rare uncomplicated skin ulcers. Two studies focused on severe adverse effects and safety of SARS-CoV-2 vaccines in children, reporting on myocarditis episodes and two cases of Guillain-Barre syndrome. All other studies were beyond the scope of our research.\n\nAdded value of this studyWe assessed multiple components of the UK vaccination campaign in a cohort of children and young people (CYP) aged 12-17 years drawn from a large UK community-based citizen-science study, who received a first dose of BNT162b2 vaccine. We describe a variant-dependent protective effect of the first dose against both Delta and Omicron, with additional protective effect of pre-vaccination SARS- CoV-2 infection on post-vaccination re-infection. We compare the illness profile in CYP infected post-vaccination with that of unvaccinated CYP, demonstrating overall milder disease with fewer symptoms for vaccinated CYP. We describe local and systemic side-effects during the first week following first-dose vaccination, confirming that local symptoms are common, systemic symptoms uncommon, and both usually transient.\n\nImplications of all the available evidenceOur data confirm that first dose BNT162b2 vaccination in CYP reduces risk of infection by SARS-CoV-2 variants, with generally local and brief side-effects. If infected after vaccination, COVID-19 is milder, if manifest at all. The study aims to contribute quantitative evidence to the risk-benefit evaluation of vaccination in CYP to inform discussion regarding rationale for their vaccination and the designing of national immunisation campaigns for this age group; and applies citizen-science approaches in the conduct of epidemiological surveillance and data collection in the UK community.\n\nImportantly, this study was conducted during Delta and Omicron predominance in UK; specificity of vaccine efficacy to variants is also illustrated; and results may not be generalizable to future SARS-CoV-2 strains.", - "category": "epidemiology", - "match_type": "fuzzy", - "author_similarity": 94, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2022.03.10.22272081", @@ -2799,6 +2729,20 @@ "author_similarity": 100, "affiliation_similarity": 100 }, + { + "site": "medRxiv", + "doi": "10.1101/2022.01.01.21268131", + "date": "2022-01-05", + "link": "https://medrxiv.org/cgi/content/short/2022.01.01.21268131", + "title": "Bayesian Estimation of real-time Epidemic Growth Rates using Gaussian Processes: local dynamics of SARS-CoV-2 in England", + "authors": "Laura Marcela Guzman Rincon; Edward M Hill; Louise Dyson; Michael J Tildesley; Matt J Keeling", + "affiliations": "University of Warwick; University of Warwick; University of Warwick; University of Warwick; University of Warwick", + "abstract": "Quantitative assessments of the recent state of an epidemic and short-term projections into the near future are key public health tools that have substantial policy impacts, helping to determine if existing control measures are sufficient or need to be strengthened. Key to these quantitative assessments is the ability to rapidly and robustly measure the speed with which the epidemic is growing or decaying. Frequently, epidemiological trends are addressed in terms of the (time-varying) reproductive number R. Here, we take a more parsimonious approach and calculate the exponential growth rate, r, using a Bayesian hierarchical model to fit a Gaussian process to the epidemiological data. We show how the method can be employed when only case data from positive tests are available, and the improvement gained by including the total number of tests as a measure of heterogeneous testing effort. Although the methods are generic, we apply them to SARS-CoV-2 cases and testing in England, making use of the available high-resolution spatio-temporal data to determine long-term patterns of national growth, highlight regional growth and spatial heterogeneity.", + "category": "epidemiology", + "match_type": "fuzzy", + "author_similarity": 100, + "affiliation_similarity": 100 + }, { "site": "medRxiv", "doi": "10.1101/2021.12.31.21268587", @@ -2869,20 +2813,6 @@ "author_similarity": 100, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2021.12.22.21268252", - "date": "2021-12-24", - "link": "https://medrxiv.org/cgi/content/short/2021.12.22.21268252", - "title": "Rapid increase in Omicron infections in England during December 2021: REACT-1 study", - "authors": "Paul Elliott; Barbara Bodinier; Oliver Eales; Haowei Wang; David Haw; Joshua Elliott; Matthew Whitaker; Jakob Jonnerby; David Tang; Caroline E. Walters; Christina Atchinson; Peter J. Diggle; Andrew J. Page; Alex Trotter; Deborah Ashby; Wendy Barclay; Graham Taylor; Helen Ward; Ara Darzi; Graham Cooke; Marc Chadeau-Hyam; Christl A Donnelly", - "affiliations": "School of Public Health, Imperial College London, UKImperial College Healthcare NHS Trust, UKNational Institute for Health Research Imperial Biomedical Research; School of Public Health, Imperial College London, UK; School of Public Health, Imperial College London, UKMRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergency; School of Public Health, Imperial College London, UKMRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergency; School of Public Health, Imperial College London, UKMRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergency; Imperial College London; School of Public Health, Imperial College London, UK; School of Public Health, Imperial College London, UKMRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergency; Imperial College London; School of Public Health, Imperial College London, UKMRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergency; School of Public Health, Imperial College London, UK; CHICAS, Lancaster Medical School, Lancaster University, UK and Health Data Research, UK; Quadram Institute, Norwich, UK; Quadram Institute Bioscience; School of Public Health, Imperial College London, UK; Department of Infectious Disease, Imperial College London, UK; Department of Infectious Disease, Imperial College London, UK; School of Public Health, Imperial College London, UKImperial College Healthcare NHS Trust, UKNational Institute for Health Research Imperial Biomedical Research; Imperial College Healthcare NHS Trust, UKNational Institute for Health Research Imperial Biomedical Research Centre, UKInstitute of Global Health Innovation at ; Department of Infectious Disease, Imperial College London, UKImperial College Healthcare NHS Trust, UKNational Institute for Health Research Imperial Biomedical; School of Public Health, Imperial College London, UK; School of Public Health, Imperial College London, UKMRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergency", - "abstract": "BackgroundThe highest-ever recorded numbers of daily severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections in England has been observed during December 2021 and have coincided with a rapid rise in the highly transmissible Omicron variant despite high levels of vaccination in the population. Although additional COVID-19 measures have been introduced in England and internationally to contain the epidemic, there remains uncertainty about the spread and severity of Omicron infections among the general population.\n\nMethodsThe REal-time Assessment of Community Transmission-1 (REACT-1) study has been monitoring the prevalence of SARS-CoV-2 infection in England since May 2020. REACT-1 obtains self-administered throat and nose swabs from a random sample of the population of England at ages 5 years and over. Swabs are tested for SARS-CoV-2 infection by reverse transcription polymerase chain reaction (RT-PCR) and samples testing positive are sent for viral genome sequencing. To date 16 rounds have been completed, each including [~]100,000 or more participants with data collected over a period of 2 to 3 weeks per month. Socio-demographic, lifestyle and clinical information (including previous history of COVID-19 and symptoms prior to swabbing) is collected by online or telephone questionnaire. Here we report results from round 14 (9-27 September 2021), round 15 (19 October - 05 November 2021) and round 16 (23 November - 14 December 2021) for a total of 297,728 participants with a valid RT-PCR test result, of whom 259,225 (87.1%) consented for linkage to their NHS records including detailed information on vaccination (vaccination status, date). We used these data to estimate community prevalence and trends by age and region, to evaluate vaccine effectiveness against infection in children ages 12 to 17 years, and effect of a third (booster) dose in adults, and to monitor the emergence of the Omicron variant in England.\n\nResultsWe observed a high overall prevalence of 1.41% (1.33%, 1.51%) in the community during round 16. We found strong evidence of an increase in prevalence during round 16 with an estimated reproduction number R of 1.13 (1.06, 1.09) for the whole of round 16 and 1.27 (1.14, 1.40) when restricting to observations from 1 December onwards. The reproduction number in those aged 18-54 years was estimated at 1.23 (1.14, 1.33) for the whole of round 16 and 1.41 (1.23, 1.61) from 1 December. Our data also provide strong evidence of a steep increase in prevalence in London with an estimated R of 1.62 (1.34, 1.93) from 1 December onwards and a daily prevalence reaching 6.07% (4.06%, 9.00%) on 14 December 2021. As of 1 to 11 December 2021, of the 275 lineages determined, 11 (4.0%) corresponded to the Omicron variant. The first Omicron infection was detected in London on 3 December, and subsequent infections mostly appeared in the South of England. The 11 Omicron cases were all aged 18 to 54 years, double-vaccinated (reflecting the large numbers of people who have received two doses of vaccine in this age group) but not boosted, 9 were men, 5 lived in London and 7 were symptomatic (5 with classic COVID-19 symptoms: loss or change of sense of smell or taste, fever, persistent cough), 2 were asymptomatic, and symptoms were unknown for 2 cases. The proportion of Omicron (vs Delta or Delta sub-lineages) was found to increase rapidly with a daily increase of 66.0% (32.7%, 127.3%) in the odds of Omicron (vs. Delta) infection, conditional on swab positivity. Highest prevalence of swab positivity by age was observed in (unvaccinated) children aged 5 to 11 years (4.74% [4.15%, 5.40%]) similar to the prevalence observed at these ages in round 15. In contrast, prevalence in children aged 12 to 17 years more than halved from 5.35% (4.78%, 5.99%) in round 15 to 2.31% (1.91%, 2.80%) in round 16. As of 14 December 2021, 76.6% children at ages 12 to 17 years had received at least one vaccine dose; we estimated that vaccine effectiveness against infection was 57.9% (44.1%, 68.3%) in this age group. In addition, the prevalence of swab positivity in adults aged 65 years and over fell by over 40% from 0.84% (0.72%, 0.99%) in round 15 to 0.48% (0.39%,0.59%) in round 16 and for those aged 75 years and over it fell by two-thirds from 0.63% (0.48%,0.82%) to 0.21% (0.13%,0.32%). At these ages a high proportion of participants (>90%) had received a third vaccine dose; we estimated that adults having received a third vaccine dose had a three- to four-fold lower risk of testing positive compared to those who had received two doses.\n\nConclusionA large fall in swab positivity from round 15 to round 16 among 12 to 17 year olds, most of whom have been vaccinated, contrasts with the continuing high prevalence among 5 to 11 year olds who have largely not been vaccinated. Likewise there were large falls in swab positivity among people aged 65 years and over, the vast majority of whom have had a third (booster) vaccine dose; these results reinforce the importance of the vaccine and booster campaign. However, the rapidly increasing prevalence of SARS-CoV-2 infections in England during December 2021, coincident with the rapid rise of Omicron infections, may lead to renewed pressure on health services. Additional measures beyond vaccination may be needed to control the current wave of infections and prevent health services (in England and other countries) from being overwhelmed.\n\nSummaryThe unprecedented rise in SARS-CoV-2 infections is concurrent with rapid spread of the Omicron variant in England and globally. We analysed prevalence of SARS-CoV-2 and its dynamics in England from end of November to mid-December 2021 among almost 100,000 participants from the REACT-1 study. Prevalence was high during December 2021 with rapid growth nationally and in London, and of the proportion of infections due to Omicron. We observed a large fall in swab positivity among mostly vaccinated older children (12-17 years) compared with unvaccinated younger children (5-11 years), and in adults who received a third vs. two doses of vaccine. Our results reiterate the importance of vaccination and booster campaigns; however, additional measures may be needed to control the rapid growth of the Omicron variant.", - "category": "epidemiology", - "match_type": "fuzzy", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2021.12.21.21268214", @@ -3121,20 +3051,6 @@ "author_similarity": 100, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2021.12.03.21266112", - "date": "2021-12-05", - "link": "https://medrxiv.org/cgi/content/short/2021.12.03.21266112", - "title": "Brain Injury in COVID-19 is Associated with Autoinflammation and Autoimmunity", - "authors": "Edward J Needham; Alex L Ren; Richard J Digby; Joanne G Outtrim; Dorothy A Chatfield; Virginia FJ Newcombe; Rainer Doffinger; Gabriela Barcenas-Morales; Claudia Fonseca; Michael J Taussig; Rowan M Burnstein; Cordelia Dunai; Nyarie Sithole; Nicholas J Ashton; Henrik Zetterberg; Magnus Gisslen; Eden Arvid; Emelie Marklund; Michael J Griffiths; Jonathan Cavanagh; Gerome Breen; Sarosh R Irani; Anne Elmer; Nathalie Kingston; John R Bradley; Leonie S Taams; Benedict D michael; Edward T Bullmore; Kenneth GC Smith; Paul A Lyons; Alasdair JC Coles; David K Menon; - Cambridge NeuroCOVID Group; - NIHR Cambridge Covid BioResource; - NIHR Cambridge Clinical Research Facility", - "affiliations": "Department of Clinical Neurosciences, University of Cambridge, UK; Division of Anaesthesia, Department of Medicine, University of Cambridge, UK.; Division of Anaesthesia, Department of Medicine, University of Cambridge, UK.; Division of Anaesthesia, Department of Medicine, University of Cambridge, UK.; Division of Anaesthesia, Department of Medicine, University of Cambridge, UK.; Division of Anaesthesia, Department of Medicine, University of Cambridge, UK.; Department of Clinical Biochemistry and Immunology, Addenbrooke's Hospital, Cambridge, UK.; Department of Clinical Biochemistry and Immunology, Addenbrooke's Hospital, Cambridge, UK.; Cambridge Protein Arrays Ltd, Babraham Research Campus, Cambridge, UK; Cambridge Protein Arrays Ltd, Babraham Research Campus, Cambridge, UK; Division of Anaesthesia, Department of Medicine, University of Cambridge, UK.; Clinical Infection Microbiology and Neuroimmunology, Institute of Infection, Veterinary and Ecological Science, Liverpool, UK.; Department of Infectious Diseases, Cambridge University NHS Hospitals Foundation Trust, Cambridge, UK.; Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, the Sahlgrenska Academy at the University of Gothenburg, Molndal, Sweden.; Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, the Sahlgrenska Academy at the University of Gothenburg, Molndal, Sweden; C; Department of Infectious Diseases, Institute of Biomedicine, the Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden; Region Vastra Gotaland; Department of Infectious Diseases, Institute of Biomedicine, the Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden; Region Vastra Gotaland; Department of Infectious Diseases, Institute of Biomnedicine, the Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden; Region Vastra Gotalan; Institute of Infection, Veterinary & Ecological Sciences, University of Liverpool, Liverpool, UK.; Centre for Immunobiology, Institute of Infection, Immunity and Inflammation, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, U; Department of Social Genetic and Developmental Psychiatry, King's College London, London, UK.; Oxford Autoimmune Neurology Group, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK; Department of Neurology, Oxford University H; Cambridge Clinical Research Centre, NIHR Clinical Research Facility, Cambridge University Hospitals NHS Foundation Trust, Addenbrooke's Hospital, Cambridge, UK ; NIHR BioResource, Cambridge University Hospitals NHS Foundation, Cambridge Biomedical Campus, Cambridge, UK.; NIHR BioResource, Cambridge University Hospitals NHS Foundation, Cambridge Biomedical Campus, Cambridge, UK; Department of Medicine, University of Cambridge, Ad; Centre for Inflammation Biology and Cancer Immunology and Dept Inflammation Biology, School of Immunology and Microbial Sciences, Kings College London, Guys Cam; Clinical Infection Microbiology and Neuroimmunology, Institute of Infection, Veterinary and Ecological Science, Liverpool, UK.; Department of Psychiatry, University of Cambridge, Herchel Smith Building for Brain and Mind Sciences, Cambridge Biomedical Campus, Cambridge, UK.; Department of Medicine, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK; Cambridge Institute of Therapeutic Immunology and Infectious Disease, Je; Department of Medicine, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK; Cambridge Institute of Therapeutic Immunology and Infectious Disease, Je; Department of Clinical Neurosciences, University of Cambridge, UK; Division of Anaesthesia, Department of Medicine, University of Cambridge, UK.; ; ; ", - "abstract": "COVID-19 has been associated with many neurological complications including stroke, delirium and encephalitis. Furthermore, many individuals experience a protracted post-viral syndrome which is dominated by neuropsychiatric symptoms, and is seemingly unrelated to COVID-19 severity. The true frequency and underlying mechanisms of neurological injury are unknown, but exaggerated host inflammatory responses appear to be a key driver of severe COVID-19 more broadly.\n\nWe sought to investigate the dynamics of, and relationship between, serum markers of brain injury (neurofilament light [NfL], Glial Fibrillary Acidic Protein [GFAP] and total Tau) and markers of dysregulated host response including measures of autoinflammation (proinflammatory cytokines) and autoimmunity. Brain injury biomarkers were measured using the Quanterix Simoa HDx platform, cytokine profiling by Luminex (R&D) and autoantibodies by a custom protein microarray.\n\nDuring hospitalisation, patients with COVID-19 demonstrated elevations of NfL and GFAP in a severity-dependant manner, and there was evidence of ongoing active brain injury at follow-up 4 months later. Raised NfL and GFAP were associated with both elevations of pro-inflammatory cytokines and the presence of autoantibodies; autoantibodies were commonly seen against lung surfactant proteins as well as brain proteins such as myelin associated glycoprotein, but reactivity was seen to a large number of different antigens.\n\nFurthermore, a distinct process characterised by elevation of serum total Tau was seen in patients at follow-up, which appeared to be independent of initial disease severity and was not associated with dysregulated immune responses in the same manner as NfL and GFAP.", - "category": "neurology", - "match_type": "fuzzy", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2021.11.24.21266818", @@ -3275,20 +3191,6 @@ "author_similarity": 100, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2021.11.15.21266264", - "date": "2021-11-16", - "link": "https://medrxiv.org/cgi/content/short/2021.11.15.21266264", - "title": "Association of COVID-19 employment disruption with mental and social wellbeing: evidence from nine UK longitudinal studies", - "authors": "Jacques Wels; Charlotte Booth; Bozena Wielgoszewska; Michael J Green; Giorgio Di Gessa; Charlotte F Huggins; Gareth J Griffith; Alex Siu Fung Kwong; Ruth C E Bowyer; Jane Maddock; Praveetha Patalay; Richard J Silverwood; Emla Fitzsimons; Richard John Shaw; Ellen J Thompson; Andrew Steptoe; Alun Hughes; Nishi Chaturvedi; Claire J Steves; Srinivasa Vittal Katikireddi; George B Ploubidis", - "affiliations": "University College London; University College London; University College London; University of Glasgow; University College London; University of Edinburgh; University of Bristol; University of Bristol; King's College London; University College London; University College London; University College London; University College London; University of Glasgow; Kings College London; University College London; University College London; University College London; King's College London; University of Glasgow; University College London", - "abstract": "BackgroundThe COVID-19 pandemic has led to major economic disruptions. In March 2020, the UK implemented the Coronavirus Job Retention Scheme - known as furlough - to minimize the impact of job losses. We investigate associations between change in employment status and mental and social wellbeing during the early stages of the pandemic.\n\nMethodsData were from 25,670 respondents, aged 17 to 66, across nine UK longitudinal studies. Furlough and other employment changes were defined using employment status pre-pandemic and during the first lockdown (April-June 2020). Mental and social wellbeing outcomes included psychological distress, life satisfaction, self-rated health, social contact, and loneliness. Study-specific modified Poisson regression estimates, adjusting for socio-demographic characteristics and pre-pandemic mental and social wellbeing measures, were pooled using meta-analysis.\n\nResultsCompared to those who remained working, furloughed workers were at greater risk of psychological distress (adjusted risk ratio, ARR=1.12; 95% CI: 0.97, 1.29), low life satisfaction (ARR=1.14; 95% CI: 1.07, 1.22), loneliness (ARR=1.12; 95% CI: 1.01, 1.23), and poor self-rated health (ARR=1.26; 95% CI: 1.05, 1.50), but excess risk was less pronounced than that of those no longer employed (e.g., ARR for psychological distress=1.39; 95% CI: 1.21, 1.59) or in stable unemployment (ARR=1.33; 95% CI: 1.09, 1.62).\n\nConclusionsDuring the early stages of the pandemic, those furloughed had increased risk for poor mental and social wellbeing. However, their excess risk was lower in magnitude than that of those who became or remained unemployed, suggesting that furlough may have partly mitigated poorer outcomes.", - "category": "psychiatry and clinical psychology", - "match_type": "fuzzy", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2021.11.15.21266255", @@ -3933,20 +3835,6 @@ "author_similarity": 100, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2021.08.23.21261779", - "date": "2021-08-24", - "link": "https://medrxiv.org/cgi/content/short/2021.08.23.21261779", - "title": "Association of cerebral venous thrombosis with recent COVID-19 vaccination: case-crossover study using ascertainment through neuroimaging in Scotland.", - "authors": "Paul M McKeigue; Raj Burgul; Jennifer Bishop; Chris Robertson; Jim McMenamin; Maureen O'Leary; David A. McAllister; Helen M Colhoun", - "affiliations": "University of Edinburgh; Forth Valley Royal Hospital; Public Health Scotland; Department of Mathematics and Statistics, University of Strathclyde; Public Health Scotland; Public Health Scotland; University of Glasgow; University of Edinburgh", - "abstract": "ObjectivesTo investigate the association of primary acute cerebral venous thrombosis (CVT) with COVID-19 vaccination through complete ascertainment of all diagnosed CVT in the population of Scotland.\n\nDesignCase-crossover study comparing recent (1-14 days after vaccination) with less recent exposure to vaccination among cases of CVT.\n\nSettingNational data for Scotland from 1 December 2020, with diagnosed CVT case ascertainment through neuroimaging studies up to 17 May 2021 and diagnostic coding of hospital discharges up to 28 April 2021 and with linkage to vaccination records.\n\nMain outcome measurePrimary acute cerebral venous thrombosis\n\nResultsOf 50 primary acute CVT cases, 29 were ascertained only from neuroimaging studies, 2 were ascertained only from hospital discharges, and 19 were ascertained from both sources. Of these 50 cases, 14 had received the Astra-Zeneca ChAdOx1 vaccine and 3 the Pfizer BNT162b2 vaccine. The incidence of CVT per million doses in the first 14 days after vaccination was 2.2 (95% credible interval 0.9 to 4.1) for ChAdOx1 and 1 (95% credible interval 0.1 to 2.9) for BNT162b2. The rate ratio for CVT associated with exposure to ChAdOx1 in the first 14 days compared with exposure 15-84 days after vaccination was 3.2 (95% credible interval 1.1 to 9.5). The 95% credible interval for the rate ratio associated with recent versus less recent exposure to BNT162b2 (0.6 to 95.8) was too wide for useful inference.\n\nConclusionsThese findings support a causal association between CVT and the AstraZeneca vaccine. The absolute risk of post-vaccination CVT in this population-wide study in Scotland was lower than has been reported for populations in Scandinavia and Germany; the explanation for this is not clear.\n\nWhat is already known on this topicThe risk of cerebral venous thrombosis (CVT) within 28 days of receiving the AstraZeneca ChAdOx1 vaccine has been estimated as 18 to 25 per million doses in Germany and Scandinavia, but only 5 per million doses in the UK based on the Yellow Card reporting scheme. Risk estimates based on adverse event reporting systems are subject to under-ascertainment and other biases.\n\nWhat this study addsAll diagnosed cases of CVT in Scotland were ascertained by searching neuroimaging studies from December 2020 to May 2021 and linked to national vaccination records. The risk of CVT within 28 days of vaccination with ChAdOx1 was estimated as 3.5 per million doses with an upper bound of 6 per million doses, against a background incidence of about 12 per million adults per year. This indicates that the Yellow Card system has not seriously underestimated the risk in the UK; the explanation for higher risk in other European countries is not clear.", - "category": "epidemiology", - "match_type": "fuzzy", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2021.08.19.21262231", @@ -3975,6 +3863,20 @@ "author_similarity": 100, "affiliation_similarity": 100 }, + { + "site": "medRxiv", + "doi": "10.1101/2021.08.23.21262209", + "date": "2021-08-23", + "link": "https://medrxiv.org/cgi/content/short/2021.08.23.21262209", + "title": "Population birth outcomes in 2020 and experiences of expectant mothers during the COVID-19 pandemic: a Born in Wales mixed methods study using routine data", + "authors": "Hope Jones; Mike Seaborne; Laura Cowley; David E Odd; Shantini Paranjothy; Ashley Akbari; Sinead Brophy", + "affiliations": "Swansea University; Swansea University; Public Health Wales; Cardiff University; University of Aberdeen; Swansea University; Swansea University", + "abstract": "BackgroundPregnancy can be a stressful time and the COVID-19 pandemic has affected all aspects of life. This study aims to investigate the impact of the pandemic on population birth outcomes in Wales, rates of primary immunisations and examine expectant mothers experiences of pregnancy including self-reported levels of stress and anxiety.\n\nMethodsPopulation-level birth outcomes in Wales: Stillbirths, prematurity, birth weight and Caesarean section births before (2016-2019) and during (2020) the pandemic were compared using national-level routine anonymised data held in the Secure Anonymised Information Linkage (SAIL) Databank. The first three scheduled primary immunisations were compared between 2019 and 2020. Self-reported pregnancy experience: 215 expectant mothers (aged 16+) in Wales completed an online survey about their experiences of pregnancy during the pandemic. The qualitative survey data was analysed using codebook thematic analysis.\n\nFindingsThere was no significant difference between annual outcomes including gestation and birth weight, stillbirths, and Caesarean sections for infants born in 2020 compared to 2016-2019. There was an increase in late term births ([≥]42 weeks gestation) during the first lockdown (OR: 1.28, p=0.019) and a decrease in moderate to late preterm births (32-36 weeks gestation) during the second lockdown (OR: 0.74, p=0.001). Fewer babies were born in 2020 (N=29,031) compared to 2016-2019 (average N=32,582). All babies received their immunisations in 2020, but there were minor delays in the timings of vaccines. Those due at 8-weeks were 8% less likely to be on time (within 28-days) and at 16-weeks, they were 19% less likely to be on time. The pandemic had a negative impact on the mental health of 71% of survey respondents, who reported anxiety, stress and loneliness; this was associated with attending scans without their partner, giving birth alone, and minimal contact with midwives.\n\nInterpretationThe pandemic had a negative impact on mothers experiences of pregnancy; however, population-level data suggests that this did not translate to adverse birth outcomes for babies born during the pandemic.", + "category": "public and global health", + "match_type": "fuzzy", + "author_similarity": 100, + "affiliation_similarity": 100 + }, { "site": "medRxiv", "doi": "10.1101/2021.08.17.21262196", @@ -4017,6 +3919,20 @@ "author_similarity": 100, "affiliation_similarity": 100 }, + { + "site": "medRxiv", + "doi": "10.1101/2021.08.12.21261987", + "date": "2021-08-13", + "link": "https://medrxiv.org/cgi/content/short/2021.08.12.21261987", + "title": "Characterising the persistence of RT-PCR positivity and incidence in a community survey of SARS-CoV-2", + "authors": "Oliver Eales; Caroline E. Walters; Haowei Wang; David Haw; Kylie E. C. Ainslie; Christina Atchinson; Andrew Page; Sophie Prosolek; Alexander J. Trotter; Thanh Le Viet; Nabil-Fareed Alikhan; Leigh M Jackson; Catherine Ludden; - The COVID-19 Genomics UK (COG-UK) Consortium; Deborah Ashby; Christl A Donnelly; Graham Cooke; Wendy Barclay; Helen Ward; Ara Darzi; Paul Elliott; Steven Riley", + "affiliations": "School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; School of Public Health, Imperial College London, UK; Quadram Institute, Norwich, UK; Quadram Institute, Norwich, UK; Quadram Institute, Norwich, UK; Quadram Institute, Norwich, UK; Quadram Institute, Norwich, UK; Medical School, University of Exeter, UK; Department of Medicine, University of Cambridge, UK; ; School of Public Health, Imperial College London, UK; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; Department of Infectious Disease, Imperial College London, UK Imperial College Healthcare NHS Trust, UK National Institute for Health Research Imperial Biomedic; Department of Infectious Disease, Imperial College London, UK; School of Public Health, Imperial College London, UK Imperial College Healthcare NHS Trust, UK National Institute for Health Research Imperial Biomedical Resear; Imperial College Healthcare NHS Trust, UK National Institute for Health Research Imperial Biomedical Research Centre, UK Institute of Global Health Innovation a; School of Public Health, Imperial College London, UK Imperial College Healthcare NHS Trust, UK National Institute for Health Research Imperial Biomedical Resear; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc", + "abstract": "BackgroundCommunity surveys of SARS-CoV-2 RT-PCR swab-positivity provide prevalence estimates largely unaffected by biases from who presents for routine case testing. The REal-time Assessment of Community Transmission-1 (REACT-1) has estimated swab-positivity approximately monthly since May 2020 in England from RT-PCR testing of self-administered throat and nose swabs in random non-overlapping cross-sectional community samples. Estimating infection incidence from swab-positivity requires an understanding of the persistence of RT-PCR swab positivity in the community.\n\nMethodsDuring round 8 of REACT-1 from 6 January to 22 January 2021, of the 2,282 participants who tested RT-PCR positive, we recruited 896 (39%) from whom we collected up to two additional swabs for RT-PCR approximately 6 and 9 days after the initial swab. We estimated sensitivity and duration of positivity using an exponential model of positivity decay, for all participants and for subsets by initial N-gene cycle threshold (Ct) value, symptom status, lineage and age. Estimates of infection incidence were obtained for the entire duration of the REACT-1 study using P-splines.\n\nResultsWe estimated the overall sensitivity of REACT-1 to detect virus on a single swab as 0.79 (0.77, 0.81) and median duration of positivity following a positive test as 9.7 (8.9, 10.6) days. We found greater median duration of positivity where there was a low N-gene Ct value, in those exhibiting symptoms, or for infection with the Alpha variant. The estimated proportion of positive individuals detected on first swab, P0, was found to be higher for those with an initially low N-gene Ct value and those who were pre-symptomatic. When compared to swab-positivity, estimates of infection incidence over the duration of REACT-1 included sharper features with evident transient increases around the time of key changes in social distancing measures.\n\nDiscussionHome self-swabbing for RT-PCR based on a single swab, as implemented in REACT-1, has high overall sensitivity. However, participants time-since-infection, symptom status and viral lineage affect the probability of detection and the duration of positivity. These results validate previous efforts to estimate incidence of SARS-CoV-2 from swab-positivity data, and provide a reliable means to obtain community infection estimates to inform policy response.", + "category": "infectious diseases", + "match_type": "fuzzy", + "author_similarity": 100, + "affiliation_similarity": 100 + }, { "site": "medRxiv", "doi": "10.1101/2021.08.13.21261861", @@ -4143,20 +4059,6 @@ "author_similarity": 100, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2021.07.21.21260906", - "date": "2021-07-22", - "link": "https://medrxiv.org/cgi/content/short/2021.07.21.21260906", - "title": "Disentangling post-vaccination symptoms from early COVID-19", - "authors": "Liane S Canas; Marc F. Osterdahl; Jie Deng; Christina Hu; Somesh Selvachandran; Lorenzo Polidori; Anna May; Erika Molteni; Benjamin Murray; Liyuan Chen; Eric Kerfoot; Kerstin Klaser; Michela Antonelli; Alexander Hammers; Tim Spector; Sebastien Ourselin; Claire J. Steves; Carole H. Sudre; Marc Modat; Emma L. Duncan", - "affiliations": "School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK; Department of Twin Research and Genetic Epidemiology, Kings College London, London, UK; School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK; ZOE Limited, London, UK; ZOE Limited, London, UK; ZOE Limited, London, UK; ZOE Limited, London, UK; School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK; School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK; School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK; School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK; School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK; School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK; School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK; King's College London & Guy's and St Thomas' PET Centre, London, UK; Department of Twin Research and Genetic Epidemiology, Kings College London, London, UK.; School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK; Department of Twin Research and Genetic Epidemiology, Kings College London, London, UK.; School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK; Medical Research Council Unit for Lifelong Health and Ageing, Departme; School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK; Department of Twin Research and Genetic Epidemiology, Kings College London, London, UK.", - "abstract": "BackgroundIdentifying and testing individuals likely to have SARS-CoV-2 is critical for infection control, including post-vaccination. Vaccination is a major public health strategy to reduce SARS-CoV-2 infection globally. Some individuals experience systemic symptoms post-vaccination, which overlap with COVID-19 symptoms. This study compared early post-vaccination symptoms in individuals who subsequently tested positive or negative for SARS-CoV-2, using data from the COVID Symptom Study (CSS) app.\n\nDesignWe conducted a prospective observational study in UK CSS participants who were asymptomatic when vaccinated with Pfizer-BioNTech mRNA vaccine (BNT162b2) or Oxford-AstraZeneca adenovirus-vectored vaccine (ChAdOx1 nCoV-19) between 8 December 2020 and 17 May 2021, who subsequently reported symptoms within seven days (other than local symptoms at injection site) and were tested for SARS-CoV-2, aiming to differentiate vaccination side-effects per se from superimposed SARS-CoV-2 infection. The post-vaccination symptoms and SARS-CoV-2 test results were contemporaneously logged by participants. Demographic and clinical information (including comorbidities) were also recorded. Symptom profiles in individuals testing positive were compared with a 1:1 matched population testing negative, including using machine learning and multiple models including UK testing criteria.\n\nFindingsDifferentiating post-vaccination side-effects alone from early COVID-19 was challenging, with a sensitivity in identification of individuals testing positive of 0.6 at best. A majority of these individuals did not have fever, persistent cough, or anosmia/dysosmia, requisite symptoms for accessing UK testing; and many only had systemic symptoms commonly seen post-vaccination in individuals negative for SARS-CoV-2 (headache, myalgia, and fatigue).\n\nInterpretationPost-vaccination side-effects per se cannot be differentiated from COVID-19 with clinical robustness, either using symptom profiles or machine-derived models. Individuals presenting with systemic symptoms post-vaccination should be tested for SARS-CoV-2, to prevent community spread.\n\nFundingZoe Limited, UK Government Department of Health and Social Care, Wellcome Trust, UK Engineering and Physical Sciences Research Council, UK National Institute for Health Research, UK Medical Research Council and British Heart Foundation, Alzheimers Society, Chronic Disease Research Foundation, Massachusetts Consortium on Pathogen Readiness (MassCPR).\n\nResearch in contextO_ST_ABSEvidence before this studyC_ST_ABSThere are now multiple surveillance platforms internationally interrogating COVID-19 and/or post-vaccination side-effects. We designed a study to examine for differences between vaccination side-effects and early symptoms of COVID-19. We searched PubMed for peer-reviewed articles published between 1 January 2020 and 21 June 2021, using keywords: \"COVID-19\" AND \"Vaccination\" AND (\"mobile application\" OR \"web tool\" OR \"digital survey\" OR \"early detection\" OR \"Self-reported symptoms\" OR \"side-effects\"). Of 185 results, 25 studies attempted to differentiate symptoms of COVID-19 vs. post-vaccination side-effects; however, none used artificial intelligence (AI) technologies (\"machine learning\") coupled with real-time data collection that also included comprehensive and systematic symptom assessment. Additionally, none of these studies attempt to discriminate the early signs of infection from side-effects of vaccination (specifically here: Pfizer-BioNTech mRNA vaccine (BNT162b2) and Oxford-AstraZeneca adenovirus-vectored vaccine (ChAdOx1 nCoV-19)). Further, none of these studies sought to provide comparisons with current testing criteria used by healthcare services.\n\nAdded value of this studyThis study, in a uniquely large community-based cohort, uses prospective data capture in a novel effort to identify individuals with COVID-19 in the immediate post-vaccination period. Our results show that early symptoms of SARS-CoV-2 cannot be differentiated from vaccination side-effects robustly. Thus, post-vaccination systemic symptoms should not be ignored, and testing should be considered to prevent COVID-19 dissemination by vaccinated individuals.\n\nImplications of all the available evidenceOur study demonstrates the critical importance of testing symptomatic individuals - even if vaccinated - to ensure early detection of SARS-CoV-2 infection, helping to prevent future pandemic waves in the UK and elsewhere.", - "category": "respiratory medicine", - "match_type": "fuzzy", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2021.07.19.21260770", @@ -4241,6 +4143,20 @@ "author_similarity": 100, "affiliation_similarity": 100 }, + { + "site": "medRxiv", + "doi": "10.1101/2021.07.12.21260385", + "date": "2021-07-16", + "link": "https://medrxiv.org/cgi/content/short/2021.07.12.21260385", + "title": "Estimating the effectiveness of first dose of COVID-19 vaccine against mortality in England: a quasi-experimental study", + "authors": "Charlotte Bermingham; Jasper Morgan; Daniel Ayoubkhani; Myer Glickman; Nazrul Islam; Aziz Sheikh; Jonathan Sterne; A. Sarah Walker; Vah\u00e9 Nafilyan", + "affiliations": "Office for National Statistics, Newport, UK; Office for National Statistics, Newport, UK; Office for National Statistics, Newport, UK; Office for National Statistics, Newport, UK; Nuffield Department of Population Health, Big Data Institute, University of Oxford, Oxford, UK; Usher Institute, University of Edinburgh, Edinburgh, UK; Health Data Research UK BREATHE Hub; Bristol Medical School, University of Bristol, UK; Nuffield department of Medicine, University of Oxford, Oxford, UK; Office for National Statistics, Newport, UK", + "abstract": "BackgroundEstimating real-world vaccine effectiveness is vital to assess the impact of the vaccination programme on the pandemic and inform the ongoing policy response. However, estimating vaccine effectiveness using observational data is inherently challenging because of the non-randomised design and the potential for unmeasured confounding.\n\nMethodsWe used a Regression Discontinuity Design (RDD) to estimate vaccine effectiveness against COVID-19 mortality in England, exploiting the discontinuity in vaccination rates resulting from the UKs age-based vaccination priority groups. We used the fact that people aged 80 or over were prioritised for the vaccine roll-out in the UK to compare the risk of COVID-19 and non-COVID-19 death in people aged 75-79 and 80-84.\n\nFindingsThe prioritisation of vaccination of people aged 80 or above led to a large discrepancy in vaccination rates in people 80-84 compared to those 75-79 at the beginning of the vaccination campaign. We found a corresponding difference in COVID-19 mortality, but not in non-COVID-19 mortality, suggesting that our approach appropriately addresses the issue of unmeasured confounding factors. Our results suggest that the first vaccine dose reduced the risk of COVID-19 death by 52.6% (95% Cl 26.6-84.2) in those aged 80.\n\nInterpretationsOur results support existing evidence that a first dose of a COVID-19 vaccine has a strong protective effect against COVID-19 mortality in older adults. The RDD estimate of vaccine effectiveness is comparable to previously published studies using different methods, suggesting that unmeasured confounding factors are unlikely to substantially bias these studies.\n\nFundingOffice for National Statistics.\n\nResearch in ContextO_ST_ABSEvidence before this studyC_ST_ABSWe searched PubMed for studies reporting on the real-world effectiveness of the COVID-19 vaccination on risk of death using terms such as \"COVID-19\", \"vaccine effectiveness\", \"mortality\" and \"death\". The relevant published studies on this topic report vaccine effectiveness estimates against risk of death ranging from 64.2% to 98.7%, for varying times post-vaccination. All of these are observational studies and therefore potentially subject to bias from unmeasured confounding. We found no studies that used a quasi-experimental method such as regression discontinuity design, which is not subject to bias from unmeasured confounding, to calculate the effectiveness of the COVID-19 vaccination on risk of COVID-19 death, or on other outcomes such as hospitalisation or infection.\n\nAdded value of this studyThe estimates of vaccine effectiveness based on observational data may be biased by unmeasured confounding. This study uses a regression discontinuity design to estimate vaccine effectiveness, exploiting the fact that the vaccination campaign in the UK was rolled out following age-based priority groups. This enables the calculation of an unbiased estimate of the effectiveness of the COVID-19 vaccine against risk of death.\n\nThe vaccine effectiveness estimate of 52.6% (95% Cl 26.6-84.2) is slightly lower but similar to previously published estimates, therefore suggesting that these estimates are not substantially affected by unmeasured confounding factors and confirming the effectiveness of the COVID-19 vaccine against risk of COVID-19 death.\n\nImplications of all the available evidenceObtaining an unbiased estimate of COVID-19 vaccine effectiveness is of vital importance in informing policy for lifting COVID-19 related measures. The regression discontinuity design provides confidence that the existing estimates from observational studies are unlikely to be substantially biased by unmeasured confounding.", + "category": "infectious diseases", + "match_type": "fuzzy", + "author_similarity": 100, + "affiliation_similarity": 100 + }, { "site": "medRxiv", "doi": "10.1101/2021.07.12.21260387", @@ -4269,6 +4185,20 @@ "author_similarity": 100, "affiliation_similarity": 100 }, + { + "site": "medRxiv", + "doi": "10.1101/2021.07.14.21260488", + "date": "2021-07-16", + "link": "https://medrxiv.org/cgi/content/short/2021.07.14.21260488", + "title": "SARS-CoV-2 Antibody Lateral Flow Assay for antibody prevalence studies following vaccine roll out: a Diagnostic Accuracy Study", + "authors": "Alexandra H C Cann; Candice L Clarke; Jonathan C Brown; Tina Thomson; Maria Prendecki; Maya Moshe; Anjna Badhan; Paul Elliott; Ara Darzi; Steven Riley; Deborah Ashby; Michelle Willicombe; Peter Kelleher; Paul Randell; Helen Ward; Wendy Barclay; Graham Cooke", + "affiliations": "Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London School of Public Health; Imperial College London; Dept Inf Dis Epi, Imperial College; Imperial College London; Imperial College London; Imperial College London; Imperial College Healthcare NHS Trust, UK; Imperial College London; Department of Infectious Disease, Imperial College London, UK; Imperial College London", + "abstract": "BackgroundLateral flow immunoassays (LFIAs) have the potential to deliver affordable, large scale antibody testing and provide rapid results without the support of central laboratories. As part of the development of the REACT programme extensive evaluation of LFIA performance was undertaken with individuals following natural infection. Here we assess the performance of the selected LFIA to detect antibody responses in individuals who have received at least one dose of SARS-CoV-2 vaccine.\n\nMethodsThis is a prospective diagnostic accuracy study.\n\nSettingSampling was carried out at renal outpatient clinic and healthcare worker testing sites at Imperial College London NHS Trust. Laboratory analyses were performed across Imperial College London sites and university facilities.\n\nParticipantsTwo cohorts of patients were recruited; the first was a cohort of 108 renal transplant patients attending clinic following SARS-CoV-2 vaccine booster, the second cohort comprised 40 healthcare workers attending for first SARS-CoV-2 vaccination, and 21 day follow up. A total of 186 paired samples were collected.\n\nInterventionsDuring the participants visit, capillary blood samples were analysed on LFIA device, while paired venous sampling was sent for serological assessment of antibodies to the spike protein (anti-S) antibodies. Anti-S IgG were detected using the Abbott Architect SARS-CoV-2 IgG Quant II CMIA.\n\nMain outcome measuresThe accuracy of Fortress LFIA in detecting IgG antibodies to SARS-CoV-2 compared to anti-spike protein detection on Abbott Assay.\n\nResultsUsing the threshold value for positivity on serological testing of [≥]7.10 BAU/ml, the overall performance of the test produces an estimate of sensitivity of 91.94% (95% CI 85.67% to 96.06%) and specificity of 93.55% (95% CI 84.30% to 98.21%) using the Abbott assay as reference standard.\n\nConclusionsFortress LFIA performs well in the detection of antibody responses for intended purpose of population level surveys, but does not meet criteria for individual testing.", + "category": "infectious diseases", + "match_type": "fuzzy", + "author_similarity": 100, + "affiliation_similarity": 100 + }, { "site": "medRxiv", "doi": "10.1101/2021.07.09.21260271", @@ -4563,6 +4493,20 @@ "author_similarity": 100, "affiliation_similarity": 100 }, + { + "site": "medRxiv", + "doi": "10.1101/2021.06.15.21258542", + "date": "2021-06-16", + "link": "https://medrxiv.org/cgi/content/short/2021.06.15.21258542", + "title": "Casirivimab and imdevimab in patients admitted to hospital with COVID-19 (RECOVERY): a randomised, controlled, open-label, platform trial", + "authors": "Peter W Horby; Marion Mafham; Leon Peto; Mark Campbell; Guilherme Pessoa-Amorim; Enti Spata; Natalie Staplin; Jonathan R Emberson; Benjamin Prudon; Paul Hine; Thomas Brown; Christopher A Green; Rahuldeb Sarkar; Purav Desai; Bryan Yates; Tom Bewick; Simon Tiberi; Tim Felton; J Kenneth Baillie; Maya H Buch; Lucy C Chappell; Jeremy N Day; Saul N Faust; Thomas Jaki; Katie Jeffery; Edmund Juszczak; Wei Shen Lim; Alan Montgomery; Andrew Mumford; Kathryn Rowan; Guy Thwaites; David M Weinreich; Richard Haynes; Martin J Landray", + "affiliations": "Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom; Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom; Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom; Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom; Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom; MRC Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom; MRC Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom; MRC Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom; North Tees and Hartlepool NHS Foundation Trust, Hartlepool, United Kingdom; Liverpool University Hospitals NHS Foundation Trust; Portsmouth Hospitals University NHS Foundation Trust, Portsmouth, United Kingdom; University Hospitals Birmingham NHS Foundation Trust; Medway NHS Foundation Trust; Calderdale and Huddersfield NHS Foundation Trust; Northumbria Healthcare NHS Foundation Trust; University Hospitals Of Derby and Burton NHS Foundation Trust; Barts Health NHS Trust; Manchester University NHS Foundation Trust; Roslin Institute, University of Edinburgh, Edinburgh, United Kingdom; Centre for Musculoskeletal Research, University of Manchester, Manchester, United Kingdom; School of Life Sciences, Kings College London, London, United Kingdom; Oxford University Clinical Research Unit, Ho Chi Minh City, Viet Nam, and Nuffield Department of Medicine, University of Oxford, United Kingdom; NIHR Southampton Clinical Research Facility and Biomedical Research Centre, University Hospital Southampton NHS Foundation Trust and University of Southampton, ; Department of Mathematics and Statistics, Lancaster University, Lancaster, United Kingdom; Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom; School of Medicine, University of Nottingham, Nottingham, United Kingdom; Respiratory Medicine Department, Nottingham University Hospitals NHS Foundation Trust, Nottingham, United Kingdom; School of Medicine, University of Nottingham, Nottingham, United Kingdom; School of Cellular and Molecular Medicine, University of Bristol, Bristol, United Kingdom; Intensive Care National Audit and Research Centre, London, United Kingdom; Oxford University Clinical Research Unit, Ho Chi Minh City, Viet Nam, and Nuffield Department of Medicine, University of Oxford, United Kingdom; Regeneron Pharmaceuticals Inc, Tarrytown, NY, USA; MRC Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom; Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom", + "abstract": "BackgroundREGEN-COV is a combination of 2 monoclonal antibodies (casirivimab and imdevimab) that bind to two different sites on the receptor binding domain of the SARS-CoV-2 spike protein. We aimed to evaluate the efficacy and safety of REGEN-COV in patients admitted to hospital with COVID-19.\n\nMethodsIn this randomised, controlled, open-label platform trial, several possible treatments were compared with usual care in patients hospitalised with COVID-19. Eligible and consenting patients were randomly allocated (1:1) to either usual standard of care alone (usual care group) or usual care plus a single dose of REGEN-COV 8g (casirivimab 4g and imdevimab 4g) by intravenous infusion (REGEN-COV group). The primary outcome was 28-day mortality assessed first among patients without detectable antibodies to SARS-CoV-2 at randomisation (seronegative) and then in the overall population. The trial is registered with ISRCTN (50189673) and clinicaltrials.gov (NCT04381936).\n\nFindingsBetween 18 September 2020 and 22 May 2021, 9785 patients were randomly allocated to receive usual care plus REGEN-COV or usual care alone, including 3153 (32%) seronegative patients, 5272 (54%) seropositive patients and 1360 (14%) patients with unknown baseline antibody status. In the primary efficacy population of seronegative patients, 396 (24%) of 1633 patients allocated to REGEN-COV and 451 (30%) of 1520 patients allocated to usual care died within 28 days (rate ratio 0{middle dot}80; 95% CI 0{middle dot}70-0{middle dot}91; p=0{middle dot}0010). In an analysis involving all randomised patients (regardless of baseline antibody status), 944 (20%) of 4839 patients allocated to REGEN-COV and 1026 (21%) of 4946 patients allocated to usual care died within 28 days (rate ratio 0{middle dot}94; 95% CI 0{middle dot}86-1{middle dot}03; p=0{middle dot}17). The proportional effect of REGEN-COV on mortality differed significantly between seropositive and seronegative patients (p value for heterogeneity = 0{middle dot}001).\n\nInterpretationIn patients hospitalised with COVID-19, the monoclonal antibody combination of casirivimab and imdevimab (REGEN-COV) reduced 28-day mortality among patients who were seronegative at baseline.\n\nFundingUK Research and Innovation (Medical Research Council) and National Institute of Health Research (Grant ref: MC_PC_19056).", + "category": "infectious diseases", + "match_type": "fuzzy", + "author_similarity": 100, + "affiliation_similarity": 100 + }, { "site": "medRxiv", "doi": "10.1101/2021.06.11.21258730", @@ -4591,6 +4535,20 @@ "author_similarity": 100, "affiliation_similarity": 100 }, + { + "site": "medRxiv", + "doi": "10.1101/2021.06.11.21258690", + "date": "2021-06-15", + "link": "https://medrxiv.org/cgi/content/short/2021.06.11.21258690", + "title": "Brain imaging before and after COVID-19 in UK Biobank", + "authors": "Gwena\u00eblle Douaud; Soojin Lee; Fidel Alfaro-Almagro; Christoph Arthofer; Chaoyue Wang; Paul McCarthy; Frederik Lange; Jesper L.R. Andersson; Ludovica Griffanti; Eugene Duff; Saad Jbabdi; Bernd Taschler; Peter Keating; Anderson M. Winkler; Rory Collins; Paul M. Matthews; Naomi Allen; Karla L. Miller; Thomas E. Nichols; Stephen M. Smith", + "affiliations": "FMRIB Centre, Wellcome Centre for Integrative Neuroimaging (WIN), Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK; FMRIB Centre, Wellcome Centre for Integrative Neuroimaging (WIN), Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK; FMRIB Centre, Wellcome Centre for Integrative Neuroimaging (WIN), Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK; FMRIB Centre, Wellcome Centre for Integrative Neuroimaging (WIN), Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK; FMRIB Centre, Wellcome Centre for Integrative Neuroimaging (WIN), Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK; FMRIB Centre, Wellcome Centre for Integrative Neuroimaging (WIN), Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK; FMRIB Centre, Wellcome Centre for Integrative Neuroimaging (WIN), Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK; FMRIB Centre, Wellcome Centre for Integrative Neuroimaging (WIN), Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK; FMRIB Centre, Wellcome Centre for Integrative Neuroimaging (WIN), Nuffield Department of Clinical Neurosciences, University of Oxford; OHBA, Wellcome Centre for; FMRIB Centre, Wellcome Centre for Integrative Neuroimaging (WIN), Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK; Department of; FMRIB Centre, Wellcome Centre for Integrative Neuroimaging (WIN), Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK; FMRIB Centre, Wellcome Centre for Integrative Neuroimaging (WIN), Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK; Ear Institute, University College London, London, UK; National Institutes of Mental Health, National Institutes of Health, Bethesda, MD, USA; Nuffield Department of Population Health, University of Oxford, Oxford, UK; UK Dementia Research Institute and Department of Brain Sciences, Imperial College, London, UK; Nuffield Department of Population Health, University of Oxford, Oxford, UK; FMRIB Centre, Wellcome Centre for Integrative Neuroimaging (WIN), Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK; Big Data Institute, University of Oxford, Oxford, UK; FMRIB Centre, Wellcome Centre for Integrative Neuroimaging (WIN), Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK", + "abstract": "There is strong evidence for brain-related abnormalities in COVID-191-13. It remains unknown however whether the impact of SARS-CoV-2 infection can be detected in milder cases, and whether this can reveal possible mechanisms contributing to brain pathology. Here, we investigated brain changes in 785 UK Biobank participants (aged 51-81) imaged twice, including 401 cases who tested positive for infection with SARS-CoV-2 between their two scans, with 141 days on average separating their diagnosis and second scan, and 384 controls. The availability of pre-infection imaging data reduces the likelihood of pre-existing risk factors being misinterpreted as disease effects. We identified significant longitudinal effects when comparing the two groups, including: (i) greater reduction in grey matter thickness and tissue-contrast in the orbitofrontal cortex and parahippocampal gyrus, (ii) greater changes in markers of tissue damage in regions functionally-connected to the primary olfactory cortex, and (iii) greater reduction in global brain size. The infected participants also showed on average larger cognitive decline between the two timepoints. Importantly, these imaging and cognitive longitudinal effects were still seen after excluding the 15 cases who had been hospitalised. These mainly limbic brain imaging results may be the in vivo hallmarks of a degenerative spread of the disease via olfactory pathways, of neuroinflammatory events, or of the loss of sensory input due to anosmia. Whether this deleterious impact can be partially reversed, or whether these effects will persist in the long term, remains to be investigated with additional follow up.", + "category": "neurology", + "match_type": "fuzzy", + "author_similarity": 100, + "affiliation_similarity": 100 + }, { "site": "medRxiv", "doi": "10.1101/2021.06.09.21258629", @@ -4971,14 +4929,14 @@ }, { "site": "medRxiv", - "doi": "10.1101/2021.05.08.21256867", - "date": "2021-05-14", - "link": "https://medrxiv.org/cgi/content/short/2021.05.08.21256867", - "title": "SARS-CoV-2 lineage dynamics in England from January to March 2021 inferred from representative community samples", - "authors": "Oliver Eales; Andrew Page; Sonja N. Tang; Caroline E. Walters; Haowei Wang; David Haw; Alexander J. Trotter; Thanh Le Viet; Ebenezer Foster-Nyarko; Sophie Prosolek; Christina Atchinson; Deborah Ashby; Graham Cooke; Wendy Barclay; Christl A Donnelly; Justin O'Grady; Erik Volz; - The COVID-19 Genomics UK (COG-UK) Consortium; Ara Darzi; Helen Ward; Paul Elliott; Steven Riley", - "affiliations": "School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; Quadram Institute, Norwich, UK; School of Public Health, Imperial College London, UK; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; Quadram Institute, Norwich, UK; Quadram Institute, Norwich, UK; Quadram Institute, Norwich, UK; Quadram Institute, Norwich, UK; School of Public Health, Imperial College London, UK; School of Public Health, Imperial College London, UK; Department of Infectious Disease, Imperial College London, UK Imperial College Healthcare NHS Trust, UK National Institute for Health Research Imperial Biomedic; Department of Infectious Disease, Imperial College London, UK; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; Quadram Institute, Norwich, UK; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; ; Imperial College Healthcare NHS Trust, UK National Institute for Health Research Imperial Biomedical Research Centre, UK Institute of Global Health Innovation a; School of Public Health, Imperial College London, UK Imperial College Healthcare NHS Trust, UK National Institute for Health Research Imperial Biomedical Resear; School of Public Health, Imperial College London, UK Imperial College Healthcare NHS Trust, UK National Institute for Health Research Imperial Biomedical Resear; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc", - "abstract": "Genomic surveillance for SARS-CoV-2 lineages informs our understanding of possible future changes in transmissibility and vaccine efficacy. However, small changes in the frequency of one lineage over another are often difficult to interpret because surveillance samples are obtained from a variety of sources. Here, we describe lineage dynamics and phylogenetic relationships using sequences obtained from a random community sample who provided a throat and nose swab for rt-PCR during the first three months of 2021 as part of the REal-time Assessment of Community Transmission-1 (REACT-1) study. Overall, diversity decreased during the first quarter of 2021, with the B.1.1.7 lineage (first identified in Kent) predominant, driven by a 0.3 unit higher reproduction number over the prior wild type. During January, positive samples were more likely B.1.1.7 in younger and middle-aged adults (aged 18 to 54) than in other age groups. Although individuals infected with the B.1.1.7 lineage were no more likely to report one or more classic COVID-19 symptoms compared to those infected with wild type, they were more likely to be antibody positive 6 weeks after infection. Viral load was higher in B.1.1.7 infection as measured by cycle threshold (Ct) values, but did not account for the increased rate of testing positive for antibodies. The presence of infections with non-imported B.1.351 lineage (first identified in South Africa) during January, but not during February or March, suggests initial establishment in the community followed by fade-out. However, this occurred during a period of stringent social distancing and targeted public health interventions and does not immediately imply similar lineages could not become established in the future. Sequence data from representative community surveys such as REACT-1 can augment routine genomic surveillance.", - "category": "infectious diseases", + "doi": "10.1101/2021.05.11.21257040", + "date": "2021-05-13", + "link": "https://medrxiv.org/cgi/content/short/2021.05.11.21257040", + "title": "Trajectories of child emotional and behavioural difficulties before and during the COVID-19 pandemic in a longitudinal UK cohort", + "authors": "Elise Paul; Daphne Kounali; Alex Siu Fung Kwong; Daniel Smith; Ilaria Costantini; Deborah A Lawlor; Kapil Sayal; Helen Bould; Nicholas J Timpson; Kate Northstone; Melanie Lewcock; Kate J Tilling; Rebecca Pearson", + "affiliations": "University College London; University of Bristol; University of Bristol; University of Bristol; University of Bristol; University of Bristol; University of Nottingham; University of Bristol; University of Bristol; University of Bristol; University of Bristol; University of Bristol; University of Bristol", + "abstract": "ImportanceCOVID-19 public health mitigation measures are likely to have detrimental effects on emotional and behavioural problems in children. However, longitudinal studies with pre-pandemic data are scarce.\n\nObjectiveTo explore trajectories of childrens emotional and behavioural difficulties during the COVID-19 pandemic.\n\nDesign and settingData were from children from the third generation of a birth cohort study; the Avon Longitudinal Study of Parents and Children - Generation 2 (ALSPAC-G2) in the southwest of England.\n\nParticipantsThe study population comprised of 708 children (median age at COVID-19 data collection was 4.4 years, SD=2.9, IQR= [2.2 to 6.9]), whose parents provided previous pre-pandemic surveys and a survey between 26 May and 5 July 2020 that focused on information about the COVID-19 pandemic as restrictions from the first lockdown in the UK were eased.\n\nExposuresWe employed multi-level mixed effects modelling with random intercepts and slopes to examine whether childrens trajectories of emotional and behavioural difficulties (a combined total difficulties score) during the pandemic differ from expected pre-pandemic trajectories.\n\nMain outcomesChildren had up to seven measurements of emotional and behavioural difficulties from infancy to late childhood, using developmentally appropriate scales such as the Emotionality Activity Sociability Temperament Survey in infancy and Strengths and Difficulties Questionnaire in childhood.\n\nResultsThe observed normative pattern of childrens emotional and behavioural difficulties pre-pandemic, was characterised by an increase in scores during infancy peaking around the age of 2, and then declining throughout the rest of childhood. Pre-pandemic, the decline in difficulties scores after age 2 was 0.6 points per month; but was approximately one third of that in post-pandemic trajectories (there was a difference in mean rate of decline after age 2 of 0.2 points per month in pre vs during pandemic trajectories [95 % CI: 0.10 to 0.30, p <0.001]). This lower decline in scores over the years translated to older children having pandemic difficulty scores higher than would be expected from pre-pandemic trajectories (for example, an estimated 10.0 point (equivalent of 0.8 standard deviations) higher score (95% CI: 5.0 to 15.0) by age 8.5 years). Results remained similar although somewhat attenuated after adjusting for maternal anxiety and age.\n\nConclusion and relevanceThe COVID-19 pandemic may be associated with greater persistence of emotional and behavioural difficulties after the age 2. Emotional difficulties in childhood predict later mental health problems. Further evidence and monitoring of emotional and behavioural difficulties are required to fully understand the potential role of the pandemic on young children.\n\nKey FindingsO_ST_ABSQuestionC_ST_ABSHow has the COVID-19 pandemic influenced emotional difficulties in young children?\n\nFindingsUsing repeated longitudinal data from before and during the pandemic we provide evidence that emotional difficulty scores of primary school aged children are higher by an estimated 10.0 points (0.8 standard deviations) (95% CI: 5.0 to 15.0) by age 8.5 years than would be expected based on pre pandemic data.\n\nMeaningThe level of difference in emotional difficulties found in the current study has been linked to increased likelihood of mental health problems in adolescence and adulthood. Therefore, this increase in difficulties needs careful monitoring and support.", + "category": "psychiatry and clinical psychology", "match_type": "fuzzy", "author_similarity": 100, "affiliation_similarity": 100 @@ -5095,6 +5053,20 @@ "author_similarity": 100, "affiliation_similarity": 100 }, + { + "site": "medRxiv", + "doi": "10.1101/2021.04.24.21255968", + "date": "2021-04-27", + "link": "https://medrxiv.org/cgi/content/short/2021.04.24.21255968", + "title": "MORTALITY OF CARE HOME RESIDENTS AND COMMUNITY-DWELLING CONTROLS DURING THE COVID-19 PANDEMIC IN 2020: MATCHED COHORT STUDY", + "authors": "Martin C Gulliford; A Toby Prevost; Andrew Clegg; Emma C Rezel-Potts", + "affiliations": "King's College London; King's College London; University of Leeds; King's College London", + "abstract": "ObjectiveTo estimate mortality of care home (CH) residents, and matched community-dwelling controls, during the Covid-19 pandemic from primary care electronic health records.\n\nDesignMatched cohort study\n\nSettingGeneral practices contributing to the Clinical Practice Research Datalink Aurum Database in England.\n\nParticipantsThere were 83,627 CH residents contributing data in 2020, with 26,923 deaths; 80,730 (97%) were matched on age, gender and general practice with 300,445 community-dwelling adults.\n\nMain outcome measuresAll-cause mortality. Adjusted rate ratios (RR) by negative binomial regression were adjusted for age, gender, number of long-term conditions (LTCs), frailty category, region, calendar month or week, and clustering by general practice.\n\nResultsDuring April 2020, the mortality rate of CH residents was 27.2 deaths per 1,000 patients per week, compared with 2.31 per 1,000 for controls, RR 11.1 (95% confidence interval 10.1 to 12.2). Compared with CH residents, LTCs and frailty were differentially associated with greater mortality in community-dwelling controls. During April 2020, mortality rates per 1,000 patients per week for persons with 9+ LTCs were: CH, 37.9; controls 17.7; RR 2.14 (1.18 to 3.89). In severe frailty, mortality rates were: CH, 29.6; controls 5.1; RR 6.17 (5.74 to 6.62).\n\nConclusionsIndividual-patient data from primary care electronic health records may be used to estimate mortality in care home residents. Mortality is substantially higher than for community-dwelling comparators and showed a disproportionate increase in the first wave of the Covid-19 pandemic. Multiple morbidity and frailty were associated with greater absolute risks but lower relative risks because community-dwelling frail or multi-morbid patients also experienced high mortality.", + "category": "epidemiology", + "match_type": "fuzzy", + "author_similarity": 100, + "affiliation_similarity": 100 + }, { "site": "medRxiv", "doi": "10.1101/2021.04.21.21255807", @@ -5151,20 +5123,6 @@ "author_similarity": 100, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2021.04.22.21255913", - "date": "2021-04-23", - "link": "https://medrxiv.org/cgi/content/short/2021.04.22.21255913", - "title": "Impact of vaccination on SARS-CoV-2 cases in the community: a population-based study using the UK COVID-19 Infection Survey", - "authors": "Emma Pritchard; Philippa Matthews; Nicole Stoesser; David Eyre; Owen Gethings; Karina-Doris Vitha; Joel Jones; Thomas House; Harper VanSteenhouse; Iain Bell; John Bell; John Newton; Jeremy Farrar; Ian Diamond; Emma Rourke; Ruth Studley; Derrick W Crook; tim E peto; Ann Sarah Walker; Koen B Pouwels", - "affiliations": "University of Oxford; University of Oxford; University of Oxford; University of Oxford; Office for National Statistics; University of Oxford; Office for National Statistics; University of Manchester; Glasgow Lighthouse Laboratory; Office for National Statistics; University of Oxford; Public Health England; Wellcome Trust; Office for National Statistics,; Office for National Statistics; Office for National Statistics; NIHR Oxford Biomedical Research Centre; oxford university; University of Oxford; University of Oxford", - "abstract": "ObjectivesTo assess the effectiveness of COVID-19 vaccination in preventing SARS-CoV-2 infection in the community.\n\nDesignProspective cohort study.\n\nSettingThe UK population-representative longitudinal COVID-19 Infection Survey.\n\nParticipants373,402 participants aged [≥]16 years contributing 1,610,562 RT-PCR results from nose and throat swabs between 1 December 2020 and 3 April 2021.\n\nMain outcome measuresNew RT-PCR-positive episodes for SARS-CoV-2 overall, by self-reported symptoms, by cycle threshold (Ct) value (<30 versus [≥]30), and by gene positivity (compatible with the B.1.1.7 variant versus not).\n\nResultsOdds of new SARS-CoV-2 infection were reduced 65% (95% CI 60 to 70%; P<0.001) in those [≥]21 days since first vaccination with no second dose versus unvaccinated individuals without evidence of prior infection (RT-PCR or antibody). In those vaccinated, the largest reduction in odds was seen post second dose (70%, 95% CI 62 to 77%; P<0.001).There was no evidence that these benefits varied between Oxford-AstraZeneca and Pfizer-BioNTech vaccines (P>0.9).There was no evidence of a difference in odds of new SARS-CoV-2 infection for individuals having received two vaccine doses and with evidence of prior infection but not vaccinated (P=0.89). Vaccination had a greater impact on reducing SARS-CoV-2 infections with evidence of high viral shedding Ct<30 (88% reduction after two doses; 95% CI 80 to 93%; P<0.001) and with self-reported symptoms (90% reduction after two doses; 95% CI 82 to 94%; P<0.001); effects were similar for different gene positivity patterns.\n\nConclusionVaccination with a single dose of Oxford-AstraZeneca or Pfizer-BioNTech vaccines, or two doses of Pfizer-BioNTech, significantly reduced new SARS-CoV-2 infections in this large community surveillance study. Greater reductions in symptomatic infections and/or infections with a higher viral burden are reflected in reduced rates of hospitalisations/deaths, but highlight the potential for limited ongoing transmission from asymptomatic infections in vaccinated individuals.\n\nRegistrationThe study is registered with the ISRCTN Registry, ISRCTN21086382.", - "category": "infectious diseases", - "match_type": "fuzzy", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2021.04.12.21255275", @@ -5291,20 +5249,6 @@ "author_similarity": 100, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2021.04.01.21254765", - "date": "2021-04-07", - "link": "https://medrxiv.org/cgi/content/short/2021.04.01.21254765", - "title": "Mental health inequalities in healthcare, economic, and housing disruption during COVID -19: an investigation in 12 longitudinal studies", - "authors": "Giorgio Di Gessa; Jane Maddock; Michael J Green; Ellen J Thompson; Eoin McElroy; Helena L Davies; Jessica Mundy; Anna J Stevenson; Alex S.F Kwong; Gareth J Griffith; Srinivasa Vittal Katikireddi; Claire L Niedzwiedz; George B Ploubidis; Emla Fitzsimons; Morag Henderson; Richard J. Silverwood; Nishi Chaturvedi; Gerome Breen; Claire J Steves; Andrew Steptoe; David J Porteous; Praveetha Patalay", - "affiliations": "Institute of Epidemiology and Health Care, University College London; MRC Unit for Lifelong Health and Ageing, University College London; MRC/CSO Social & Public Health Sciences Unit, University of Glasgow; Department of Twin Research and Genetic Epidemiology, School of Life Course Sciences, Kings College London; Department of Neuroscience, Psychology and Behaviour, University of Leicester; Social, Genetic & Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, Kings College London; Social, Genetic & Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, Kings College London; Centre for Genomic and Experimental Medicine, University of Edinburgh; Division of Psychiatry, University of Edinburgh and MRC Integrative Epidemiology Unit, University of Bristol; MRC Integrative Epidemiology Unit, University of Bristol; MRC/CSO Social & Public Health Sciences Unit, University of Glasgow; Institute of Health & Wellbeing, University of Glasgow; Centre for Longitudinal Studies, UCL Social Research Institute, University College London; Centre for Longitudinal Studies, UCL Social Research Institute, University College London; Centre for Longitudinal Studies, UCL Social Research Institute, University College London; Centre for Longitudinal Studies, UCL Social Research Institute, University College London; MRC Unit for Lifelong Health and Ageing, University College London; Social, Genetic & Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, Kings College London and Maudsley Biomedical Research Cen; Department of Twin Research and Genetic Epidemiology, School of Life Course Sciences, Kings College London; Institute of Epidemiology and Health Care, University College London; Centre for Genomic and Experimental Medicine, University of Edinburgh; Centre for Longitudinal Studies and MRC Unit for Lifelong Health and Ageing, University College London", - "abstract": "BackgroundThe COVID-19 pandemic and associated virus suppression measures have disrupted lives and livelihoods and people already experiencing mental ill-health may have been especially vulnerable.\n\nAimTo quantify mental health inequalities in disruptions to healthcare, economic activity and housing.\n\nMethod59,482 participants in 12 UK longitudinal adult population studies with data collected prior to and during the COVID-19 pandemic. Within each study we estimated the association between psychological distress assessed pre-pandemic and disruptions since the start of the pandemic to three domains: healthcare (medication access, procedures, or appointments); economic activity (employment, income, or working hours); and housing (change of address or household composition). Meta-analyses were used to pool estimates across studies.\n\nResultsAcross the analysed datasets, one to two-thirds of participants experienced at least one disruption, with 2.3-33.2% experiencing disruptions in two or more domains. One standard deviation higher pre-pandemic psychological distress was associated with: (i) increased odds of any healthcare disruptions (OR=1.30; [95% CI:1.20-1.40]) with fully adjusted ORs ranging from 1.24 [1.09-1.41] for disruption to procedures and 1.33 [1.20- 1.49] for disruptions to prescriptions or medication access; (ii) loss of employment (OR=1.13 [1.06-1.21]) and income (OR=1.12 [1.06 -1.19]) and reductions in working hours/furlough (OR=1.05 [1.00-1.09]); (iii) no associations with housing disruptions (OR=1.00 [0.97-1.03]); and (iv) increased likelihood of experiencing a disruption in at least two domains (OR=1.25 [1.18-1.32]) or in one domain (OR=1.11 [1.07-1.16]) relative to no disruption.\n\nConclusionPeople experiencing psychological distress pre-pandemic have been more likely to experience healthcare and economic disruptions, and clusters of disruptions across multiple domains during the pandemic. Failing to address these disruptions risks further widening the existing inequalities in mental health.", - "category": "psychiatry and clinical psychology", - "match_type": "fuzzy", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2021.04.01.21254789", @@ -5473,20 +5417,6 @@ "author_similarity": 100, "affiliation_similarity": 92 }, - { - "site": "medRxiv", - "doi": "10.1101/2021.03.16.21253377", - "date": "2021-03-24", - "link": "https://medrxiv.org/cgi/content/short/2021.03.16.21253377", - "title": "First and second SARS-CoV-2 waves in inner London: A comparison of admission characteristics and the effects of the B.1.1.7 variant", - "authors": "Luke B Snell; Wenjuan Wang; Adela Alcolea-Medina; Themoula Charalampous; Gaia Nebbia; Rahul Batra; Leonardo de Jongh; Finola Higgins; Yanzhong Wang; Jonathan D Edgeworth; Vasa Curcin", - "affiliations": "King's College London; School of Population Health and Environmental Sciences, King's College London, London, UK; Viapath, London, UK; Centre for Clinical Infection and Diagnostics Research, School of Immunology and Microbial Sciences, King's College London, London, UK; Centre for Clinical Infection and Diagnostics Research, School of Immunology and Microbial Sciences, King's College London, London, UK; Centre for Clinical Infection and Diagnostics Research, School of Immunology and Microbial Sciences, King's College London, London, UK; NIHR Biomedical Research Centre, Guy's and St Thomas' NHS Foundation Trust; NIHR Biomedical Research Centre, Guy's and St Thomas' NHS Foundation Trust; School of Population Health and Environmental Sciences, King's College London, London, UK; Centre for Clinical Infection and Diagnostics Research, School of Immunology and Microbial Sciences, King's College London, London, UK; School of Population Health and Environmental Sciences, King's College London, London, UK", - "abstract": "IntroductionA second wave of SARS-CoV-2 infection spread across the UK in 2020 linked with emergence of the more transmissible B.1.1.7 variant. The emergence of new variants, particularly during relaxation of social distancing policies and implementation of mass vaccination, highlights the need for real-time integration of detailed patient clinical data alongside pathogen genomic data. We linked clinical data with viral genome sequence data to compare cases admitted during the first and second waves of SARS-CoV-2 infection.\n\nMethodsClinical, laboratory and demographic data from five electronic health record (EHR) systems was collected for all cases with a positive SARS-CoV-2 RNA test between March 13th 2020 and February 17th 2021. SARS-CoV-2 viral sequencing was performed using Oxford Nanopore Technology. Descriptive data are presented comparing cases between waves, and between cases of B.1.1.7 and non-B.1.1.7 variants.\n\nResultsThere were 5810 SARS-CoV-2 RNA positive cases comprising inpatients (n=2341), healthcare workers (n=1549), outpatients (n=874), emergency department (ED) attenders not subsequently admitted (n=532), inter-hospital transfers (n=281) and nosocomial cases (n=233). There were two dominant waves of hospital admissions, with wave one starting from March 13th (n=838) and wave two from October 20th (n=1503), both with a temporally aligned rise in nosocomial cases (n=96 in wave one, n=137 in wave two). 1470 SARS-CoV-2 isolates were successfully sequenced, including 216/838 (26%) admitted cases from wave one, 472/1503 (31%) admitted cases in wave two and 121/233 (52%) nosocomial cases. The first B.1.1.7 variant was identified on 15th November 2020 and increased rapidly such that it comprised 400/472 (85%) of sequenced isolates from admitted cases in wave two. Females made up a larger proportion of admitted cases in wave two (47.3% vs 41.8%, p=0.011), and in those infected with the B.1.1.7 variant compared to non-B.1.1.7 variants (48.0% vs 41.8%, p=0.042). A diagnosis of frailty was less common in wave two (11.5% v 22.8%, p<0.001) and in the group infected with B.1.1.7 (14.5% v 22.4%, p=0.001). There was no difference in severity on admission between waves, as measured by hypoxia at admission (wave one: 64.3% vs wave two: 65.5%, p=0.67). However, a higher proportion of cases infected with the B.1.1.7 variant were hypoxic on admission compared to other variants (70.0% vs 62.5%, p=0.029).\n\nConclusionsAutomated EHR data extraction linked with SARS-CoV-2 genome sequence data provides valuable insight into the evolving characteristics of cases admitted to hospital with COVID-19. The proportion of cases with hypoxia on admission was greater in those infected with the B.1.1.7 variant, which supports evidence the B.1.1.7 variant is associated with more severe disease. The number of nosocomial cases was similar in both waves despite introduction of many infection control interventions before wave two, an observation requiring further investigation.", - "category": "infectious diseases", - "match_type": "fuzzy", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2021.03.15.21253542", @@ -5529,20 +5459,6 @@ "author_similarity": 100, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2021.03.11.21253275", - "date": "2021-03-21", - "link": "https://medrxiv.org/cgi/content/short/2021.03.11.21253275", - "title": "Effect of vaccination on transmission of COVID-19: an observational study in healthcare workers and their households", - "authors": "Anoop Shah; Ciara Gribben; Jennifer Bishop; Peter Hanlon; David Caldwell; Rachael Wood; Martin Reid; Jim McMenamin; David Goldberg; Diane Stockton; Sharon Hutchinson; Chris Robertson; Paul M McKeigue; Helen M Colhoun; David McAllister", - "affiliations": "London School of Hygiene and Tropical Medicine; Public Health Scotland; Public Health Scotland; University of Glasgow; Public Health Scotland; PublicHealth Scotland; Public Health Scotland; Public Health Scotland; Public Health Scotland; Public Health Scotland; Public Health Scotland; Public Health Scotland; Public Health Scotland; Public Health Scotland; University of Glasgow", - "abstract": "BackgroundThe effect of vaccination for COVID-19 on onward transmission is unknown.\n\nMethodsA national record linkage study determined documented COVID-19 cases and hospitalisations in unvaccinated household members of vaccinated and unvaccinated healthcare workers from 8th December 2020 to 3rd March 2021. The primary endpoint was COVID-19 14 days following the first dose.\n\nResultsThe cohort comprised of 194,362 household members (mean age 31{middle dot}1 {+/-} 20{middle dot}9 years) and 144,525 healthcare workers (mean age 44{middle dot}4 {+/-} 11{middle dot}4 years). 113,253 (78{middle dot}3%) of healthcare workers received at least one dose of the BNT162b2 mRNA or ChAdOx1 nCoV-19 vaccine and 36,227 (25{middle dot}1%) received a second dose. There were 3,123 and 4,343 documented COVID-19 cases and 175 and 177 COVID-19 hospitalisations in household members of healthcare workers and healthcare workers respectively. Household members of vaccinated healthcare workers had a lower risk of COVID-19 case compared to household members of unvaccinated healthcare worker (rate per 100 person-years 9{middle dot}40 versus 5{middle dot}93; HR 0{middle dot}70, 95% confidence interval [CI] 0{middle dot}63 to 0{middle dot}78). The effect size for COVID-19 hospitalisation was similar, with the confidence interval crossing the null (HR 0{middle dot}77 [95% CI 0{middle dot}53 to 1{middle dot}10]). The rate per 100 person years was lower in vaccinated compared to unvaccinated healthcare workers for documented (20{middle dot}13 versus 8{middle dot}51; HR 0{middle dot}45 [95% CI 0{middle dot}42 to 0{middle dot}49]) and hospitalized COVID-19 (0{middle dot}97 versus 0{middle dot}14; HR 0{middle dot}16 [95% CI 0{middle dot}09 to 0{middle dot}27]). Compared to the period before the first dose, the risk of documented COVID-19 case was lower at [≥] 14 days after the second dose for household members (HR 0{middle dot}46 [95% CI 0{middle dot}30to 0{middle dot}70]) and healthcare workers (HR 0{middle dot}08 [95% CI 0{middle dot}04 to 0{middle dot}17]).\n\nInterpretationVaccination of health care workers was associated with a substantial reduction in COVID-19 cases in household contacts consistent with an effect of vaccination on transmission.", - "category": "public and global health", - "match_type": "fuzzy", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2021.03.17.21253853", @@ -5557,20 +5473,6 @@ "author_similarity": 100, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2021.03.18.21253443", - "date": "2021-03-20", - "link": "https://medrxiv.org/cgi/content/short/2021.03.18.21253443", - "title": "Intensity of COVID-19 in care homes following Hospital Discharge in the early stages of the UK epidemic", - "authors": "Joe Hollinghurst; Laura North; Chris Emmerson; Ashley Akbari; Fatemeh Torabi; Ronan A Lyons; Alan G Hawkes; Ed Bennett; Mike B Gravenor; Richard Fry", - "affiliations": "Swansea University; Swansea University; Public Health Wales; Swansea University; Swansea University; Swansea University; Swansea University; Swansea University; Swansea University; Swansea University", - "abstract": "BackgroundA defining feature of the COVID-19 pandemic in many countries was the tragic extent to which care home residents were affected, and the difficulty preventing introduction and subsequent spread of infection. Management of risk in care homes requires good evidence on the most important transmission pathways. One hypothesised route at the start of the pandemic, prior to widespread testing, was transfer of patients from hospitals, which were experiencing high levels of nosocomial events.\n\nMethodsWe tested the hypothesis that hospital discharge events increased the intensity of care home cases using a national individually linked health record cohort in Wales, UK. We monitored 186,772 hospital discharge events over the period March to July 2020, tracking individuals to 923 care homes and recording the daily case rate in the homes populated by 15,772 residents. We estimated the risk of an increase in cases rates following exposure to a hospital discharge using multi-level hierarchical logistic regression, and a novel stochastic Hawkes process outbreak model.\n\nFindingsIn regression analysis, after adjusting for care home size, we found no significant association between hospital discharge and subsequent increases in care home case numbers (odds ratio: 0.99, 95% CI 0.82, 1.90). Risk factors for increased cases included care home size, care home resident density, and provision of nursing care. Using our outbreak model, we found a significant effect of hospital discharge on the subsequent intensity of cases. However, the effect was small, and considerably less than the effect of care home size, suggesting the highest risk of introduction came from interaction with the community. We estimated approximately 1.8% of hospital discharged patients may have been infected.\n\nInterpretationThere is growing evidence in the UK that the risk of transfer of COVID-19 from the high-risk hospital setting to the high-risk care home setting during the early stages of the pandemic was relatively small. Although access to testing was limited to initial symptomatic cases in each care home at this time, our results suggest that reduced numbers of discharges, selection of patients, and action taken within care homes following transfer all may have contributed to mitigation. The precise key transmission routes from the community remain to be quantified.", - "category": "health informatics", - "match_type": "fuzzy", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2021.03.15.21253590", @@ -5823,6 +5725,20 @@ "author_similarity": 100, "affiliation_similarity": 100 }, + { + "site": "medRxiv", + "doi": "10.1101/2021.03.02.21252734", + "date": "2021-03-03", + "link": "https://medrxiv.org/cgi/content/short/2021.03.02.21252734", + "title": "Relation of severe COVID-19 in Scotland to transmission-related factors and risk conditions eligible for shielding support: REACT-SCOT case-control study", + "authors": "Paul M McKeigue; David McAllister; David Caldwell; Ciara Gribben; Jen Bishop; Stuart J McGurnaghan; Matthew Armstrong; Joke Delvaux; Sam Colville; Sharon Hutchinson; Chris Robertson; Nazir Lone; Jim McMenamin; David Goldberg; Helen M Colhoun", + "affiliations": "University of Edinburgh; University of Glasgow; Public Health Scotland; Public Health Scotland; Public Health Scotland; University of Edinburgh; Public Health Scotland; Public Health Scotland; Public Health Scotland; Glasgow Caledonian University; Public Health Scotland; Strathclyde University; Public Health Scotland; University of Edinburgh; Public Health Scotland; Public Health Scotland; University of Edinburgh", + "abstract": "BackgroundClinically vulnerable individuals have been advised to shield themselves during the COVID-19 epidemic. The objectives of this study were to investigate: (1) the risk of severe COVID-19 in those eligible for shielding, and (2) the relation of severe COVID-19 to transmission-related factors in those in shielding and the general population.\n\nMethodsAll 178578 diagnosed cases of COVID-19 in Scotland from 1 March 2020 to 18 February 2021 were matched for age, sex and primary care practice to 1744283 controls from the general population. This dataset (REACT-SCOT) was linked to the list of 212702 individuals identified as eligible for shielding. Severe COVID-19 was defined as cases that entered critical care or were fatal.\n\nResultsWith those without risk conditions as reference category, the univariate rate ratio for severe COVID-19 was 3.21 (95% CI 3.01 to 3.41) in those with moderate risk conditions and 6.3 (95% CI 5.8 to 6.8) in those eligible for shielding. The highest rate was in solid organ transplant recipients: rate ratio 13.4 (95% CI 9.6 to 18.8). Risk of severe COVID-19 increased with the number of adults but decreased with the number of school-age children in the household. Severe COVID-19 was strongly associated with recent exposure to hospital (defined as 5 to 14 days before presentation date): rate ratio 12.3 (95% CI 11.5 to 13.2) overall. To test for causality, a case-crossover analysis was undertaken; with less recent exposure only (15 to 24 days before first testing positive) as reference category, the rate ratio associated with recent exposure only was 5.9 (95% CI 3.6 to 9.7). The population attributable risk fraction for recent exposure to hospital peaked at 50% in May 2020 and again at 65% in December 2020.\n\nConclusionsThe effectiveness of shielding vulnerable individuals was limited by the inability to control transmission in hospital and from other adults in the household. For solid organ transplant recipients, in whom the efficacy of vaccines is uncertain, these results support a policy of offering vaccination to household contacts. Mitigating the impact of the epidemic requires control of nosocomial transmission.", + "category": "epidemiology", + "match_type": "fuzzy", + "author_similarity": 100, + "affiliation_similarity": 100 + }, { "site": "medRxiv", "doi": "10.1101/2021.02.27.21252593", @@ -5851,20 +5767,6 @@ "author_similarity": 100, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2021.02.25.21252433", - "date": "2021-03-01", - "link": "https://medrxiv.org/cgi/content/short/2021.02.25.21252433", - "title": "Predicting COVID-19 related death using the OpenSAFELY platform", - "authors": "Elizabeth J Williamson; John Tazare; Krishnan Bhaskaran; Helen I McDonald; Alex J Walker; Laurie Tomlinson; Kevin Wing; Sebastian Bacon; Chris Bates; Helen J Curtis; Harriet Forbes; Caroline Minassian; Caroline E Morton; Emily Nightingale; Amir Mehrkar; Dave Evans; Brian D Nicholson; Dave Leon; Peter Inglesby; Brian MacKenna; Nicholas G Davies; Nicholas J DeVito; Henry Drysdale; Jonathan Cockburn; William J Hulme; Jessica Morley; Ian Douglas; Christopher T Rentsch; Rohini Mathur; Angel Wong; Anna Schultze; Richard Croker; John Parry; Frank Hester; Sam Harper; Richard Grieve; David A Harrison; Ewout W Steyerberg; Rosalind M Eggo; Karla Diaz-Ordaz; Ruth Keogh; Stephen JW Evans; Liam Smeeth; Ben Goldacre", - "affiliations": "London School of Hygiene & Tropical Medicine, Keppel Street, WC1E 7HT; London School of Hygiene & Tropical Medicine, Keppel Street, WC1E 7HT; London School of Hygiene & Tropical Medicine, Keppel Street, WC1E 7HT; London School of Hygiene & Tropical Medicine, Keppel Street, WC1E 7HT; NIHR Health Protection Research Unit (HPRU) in Immunisation; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; London School of Hygiene & Tropical Medicine, Keppel Street, WC1E 7HT; London School of Hygiene & Tropical Medicine, Keppel Street, WC1E 7HT; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; TPP, TPP House, 129 Low Lane, Horsforth, Leeds, LS18 5PX; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; London School of Hygiene & Tropical Medicine, Keppel Street, WC1E 7HT; London School of Hygiene & Tropical Medicine, Keppel Street, WC1E 7HT; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; London School of Hygiene & Tropical Medicine, Keppel Street, WC1E 7HT; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; London School of Hygiene & Tropical Medicine, Keppel Street, WC1E 7HT; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; London School of Hygiene & Tropical Medicine, Keppel Street, WC1E 7HT; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; TPP, TPP House, 129 Low Lane, Horsforth, Leeds, LS18 5PX; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; London School of Hygiene & Tropical Medicine, Keppel Street, WC1E 7HT; London School of Hygiene & Tropical Medicine, Keppel Street, WC1E 7HT; London School of Hygiene & Tropical Medicine, Keppel Street, WC1E 7HT; London School of Hygiene & Tropical Medicine, Keppel Street, WC1E 7HT; London School of Hygiene & Tropical Medicine, Keppel Street, WC1E 7HT; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; TPP, TPP House, 129 Low Lane, Horsforth, Leeds, LS18 5PX; TPP, TPP House, 129 Low Lane, Horsforth, Leeds, LS18 5PX; TPP, TPP House, 129 Low Lane, Horsforth, Leeds, LS18 5PX; London School of Hygiene & Tropical Medicine, Keppel Street, WC1E 7HT; Intensive Care National Audit & Research Centre (ICNARC), 24 High Holborn, Holborn, London WC1V 6AZ; Leiden University Medical Center, Leiden, the Netherlands; London School of Hygiene & Tropical Medicine, Keppel Street, WC1E 7HT; London School of Hygiene & Tropical Medicine, Keppel Street, WC1E 7HT; London School of Hygiene & Tropical Medicine, Keppel Street, WC1E 7HT; London School of Hygiene & Tropical Medicine, Keppel Street, WC1E 7HT; London School of Hygiene & Tropical Medicine, Keppel Street, WC1E 7HT; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG", - "abstract": "ObjectivesTo compare approaches for obtaining relative and absolute estimates of risk of 28-day COVID-19 mortality for adults in the general population of England in the context of changing levels of circulating infection.\n\nDesignThree designs were compared. (A) case-cohort which does not explicitly account for the time-changing prevalence of COVID-19 infection, (B) 28-day landmarking, a series of sequential overlapping sub-studies incorporating time-updating proxy measures of the prevalence of infection, and (C) daily landmarking. Regression models were fitted to predict 28-day COVID-19 mortality.\n\nSettingWorking on behalf of NHS England, we used clinical data from adult patients from all regions of England held in the TPP SystmOne electronic health record system, linked to Office for National Statistics (ONS) mortality data, using the OpenSAFELY platform.\n\nParticipantsEligible participants were adults aged 18 or over, registered at a general practice using TPP software on 1st March 2020 with recorded sex, postcode and ethnicity. 11,972,947 individuals were included, and 7,999 participants experienced a COVID-19 related death. The study period lasted 100 days, ending 8th June 2020.\n\nPredictorsA range of demographic characteristics and comorbidities were used as potential predictors. Local infection prevalence was estimated with three proxies: modelled based on local prevalence and other key factors; rate of A&E COVID-19 related attendances; and rate of suspected COVID-19 cases in primary care.\n\nMain outcome measuresCOVID-19 related death.\n\nResultsAll models discriminated well between patients who did and did not experience COVID-19 related death, with C-statistics ranging from 0.92-0.94. Accurate estimates of absolute risk required data on local infection prevalence, with modelled estimates providing the best performance.\n\nConclusionsReliable estimates of absolute risk need to incorporate changing local prevalence of infection. Simple models can provide very good discrimination and may simplify implementation of risk prediction tools in practice.", - "category": "infectious diseases", - "match_type": "fuzzy", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2021.02.25.21252402", @@ -6355,6 +6257,20 @@ "author_similarity": 100, "affiliation_similarity": 100 }, + { + "site": "medRxiv", + "doi": "10.1101/2021.01.15.21249756", + "date": "2021-01-20", + "link": "https://medrxiv.org/cgi/content/short/2021.01.15.21249756", + "title": "Factors associated with deaths due to COVID-19 versus other causes: population-based cohort analysis of UK primary care data and linked national death registrations within the OpenSAFELY platform", + "authors": "Krishnan Bhaskaran; Sebastian CJ Bacon; Stephen JW Evans; Chris J Bates; Christopher T Rentsch; MacKenna Brian; Laurie Tomlinson; Alex J Walker; Anna Schultze; Caroline E Morton; Daniel Grint; Amir Mehrkar; Rosalind M Eggo; Peter Inglesby; Ian J Douglas; Helen I McDonald; Jonathan Cockburn; Elizabeth J Williamson; David Evans; Helen J Curtis; William J Hulme; John Parry; Frank Hester; Sam Harper; David Spiegelhalter; Liam Smeeth; Ben Goldacre", + "affiliations": "London School of Hygiene and Tropical Medicine; University of Oxford; London School of Hygiene Tropical Medicine; The Phoenix Partnership; London School of Hygiene and Tropical Medicine; University of Oxford; London School of Hygiene and Tropical Medicine; University of Oxford; London School of Hygiene and Tropical Medicine; University of Oxford; London School of Hygiene and Tropical Medicine; University of Oxford; London School of Hygiene and Tropical Medicine; University of Oxford; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; The Phoenix Partnership; London School of Hygiene and Tropical Medicine; University of Oxford; University of Oxford; University of Oxford; University of Oxford; The Phoenix Partnership; The Phoenix Partnership; Winton Centre for Risk and Evidence Communication, Centre for Mathematical Sciences, University of Cambridge; London School of Hygiene and Tropical Medicine; University of Oxford", + "abstract": "BackgroundMortality from COVID-19 shows a strong relationship with age and pre-existing medical conditions, as does mortality from other causes. However it is unclear how specific factors are differentially associated with COVID-19 mortality as compared to mortality from other causes.\n\nMethodsWorking on behalf of NHS England, we carried out a cohort study within the OpenSAFELY platform. Primary care data from England were linked to national death registrations. We included all adults (aged [≥]18 years) in the database on 1st February 2020 and with >1 year of continuous prior registration, the cut-off date for deaths was 9th November 2020. Associations between individual-level characteristics and COVID-19 and non-COVID deaths were estimated by fitting age- and sex-adjusted logistic models for these two outcomes.\n\nResults17,456,515 individuals were included. 17,063 died from COVID-19 and 134,316 from other causes. Most factors associated with COVID-19 death were similarly associated with non-COVID death, but the magnitudes of association differed. Older age was more strongly associated with COVID-19 death than non-COVID death (e.g. ORs 40.7 [95% CI 37.7-43.8] and 29.6 [28.9-30.3] respectively for [≥]80 vs 50-59 years), as was male sex, deprivation, obesity, and some comorbidities. Smoking, history of cancer and chronic liver disease had stronger associations with non-COVID than COVID-19 death. All non-white ethnic groups had higher odds than white of COVID-19 death (OR for Black: 2.20 [1.96-2.47], South Asian: 2.33 [2.16-2.52]), but lower odds than white of non-COVID death (Black: 0.88 [0.83-0.94], South Asian: 0.78 [0.75-0.81]).\n\nInterpretationSimilar associations of most individual-level factors with COVID-19 and non-COVID death suggest that COVID-19 largely multiplies existing risks faced by patients, with some notable exceptions. Identifying the unique factors contributing to the excess COVID-19 mortality risk among non-white groups is a priority to inform efforts to reduce deaths from COVID-19.\n\nFundingWellcome, Royal Society, National Institute for Health Research, National Institute for Health Research Oxford Biomedical Research Centre, UK Medical Research Council, Health Data Research UK.", + "category": "infectious diseases", + "match_type": "fuzzy", + "author_similarity": 100, + "affiliation_similarity": 100 + }, { "site": "medRxiv", "doi": "10.1101/2021.01.19.21249840", @@ -6509,20 +6425,6 @@ "author_similarity": 100, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2020.12.24.20248822", - "date": "2020-12-26", - "link": "https://medrxiv.org/cgi/content/short/2020.12.24.20248822", - "title": "Estimated transmissibility and severity of novel SARS-CoV-2 Variant of Concern 202012/01 in England", - "authors": "Nicholas G Davies; Sam Abbott; Rosanna C. Barnard; Christopher I. Jarvis; Adam J. Kucharski; James D Munday; Carl A. B. Pearson; Timothy Russell; Damien Tully; Alex D. Washburne; Tom Wenseleers; Amy Gimma; William Waites; Kerry L. M. Wong; Kevin van Zandvoort; Justin D. Silverman; - CMMID COVID-19 Working Group; - The COVID-19 Genomics UK (COG-UK) Consortium; Karla Diaz-Ordaz; Ruth H Keogh; Rosalind M Eggo; Sebastian Funk; Mark Jit; Katherine E. Atkins; W. John Edmunds", - "affiliations": "London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene & Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; Selva Analytics LLC; KU Leuven; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; College of Information Science and Technology, Pennsylvania State University; ; ; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine", - "abstract": "A novel SARS-CoV-2 variant, VOC 202012/01 (lineage B.1.1.7), emerged in southeast England in November 2020 and is rapidly spreading towards fixation. Using a variety of statistical and dynamic modelling approaches, we estimate that this variant has a 43-90% (range of 95% credible intervals 38-130%) higher reproduction number than preexisting variants. A fitted two-strain dynamic transmission model shows that VOC 202012/01 will lead to large resurgences of COVID-19 cases. Without stringent control measures, including limited closure of educational institutions and a greatly accelerated vaccine roll-out, COVID-19 hospitalisations and deaths across England in 2021 will exceed those in 2020. Concerningly, VOC 202012/01 has spread globally and exhibits a similar transmission increase (59-74%) in Denmark, Switzerland, and the United States.", - "category": "epidemiology", - "match_type": "fuzzy", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "bioRxiv", "doi": "10.1101/2020.12.23.424229", @@ -6705,20 +6607,6 @@ "author_similarity": 100, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2020.12.08.20246231", - "date": "2020-12-11", - "link": "https://medrxiv.org/cgi/content/short/2020.12.08.20246231", - "title": "Artificial intelligence-enabled analysis of UK and US public attitudes on Facebook and Twitter towards COVID-19 vaccinations", - "authors": "Amir Hussain; Ahsen Tahir; Zain Hussain; Zakariya Sheikh; Mandar Gogate; Kia Dashtipour; Azhar Ali; Aziz Sheikh", - "affiliations": "Edinburgh Napier University, UK; Edinburgh Napier University, UK; Edinburgh Medical School, College of Medicine and Veterinary Medicine, University of Edinburgh, UK; Edinburgh Medical School, College of Medicine and Veterinary Medicine, University of Edinburgh, UK; Edinburgh Napier University, UK; Edinburgh Napier University, UK; NHS Forth Medical Group, UK & Harvard T.H. Chan School of Public Health, USA; Usher Institute, Edinburgh Medical School, University of Edinburgh, UK", - "abstract": "BackgroundGlobal efforts towards the development and deployment of a vaccine for SARS-CoV-2 are rapidly advancing. We developed and applied an artificial-intelligence (AI)-based approach to analyse social-media public sentiment in the UK and the US towards COVID-19 vaccinations, to understand public attitude and identify topics of concern.\n\nMethodsOver 300,000 social-media posts related to COVID-19 vaccinations were extracted, including 23,571 Facebook-posts from the UK and 144,864 from the US, along with 40,268 tweets from the UK and 98,385 from the US respectively, from 1st March - 22nd November 2020. We used natural language processing and deep learning based techniques to predict average sentiments, sentiment trends and topics of discussion. These were analysed longitudinally and geo-spatially, and a manual reading of randomly selected posts around points of interest helped identify underlying themes and validated insights from the analysis.\n\nResultsWe found overall averaged positive, negative and neutral sentiment in the UK to be 58%, 22% and 17%, compared to 56%, 24% and 18% in the US, respectively. Public optimism over vaccine development, effectiveness and trials as well as concerns over safety, economic viability and corporation control were identified. We compared our findings to national surveys in both countries and found them to correlate broadly.\n\nConclusionsAI-enabled social-media analysis should be considered for adoption by institutions and governments, alongside surveys and other conventional methods of assessing public attitude. This could enable real-time assessment, at scale, of public confidence and trust in COVID-19 vaccinations, help address concerns of vaccine-sceptics and develop more effective policies and communication strategies to maximise uptake.", - "category": "public and global health", - "match_type": "fuzzy", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2020.12.03.20242941", @@ -6915,20 +6803,6 @@ "author_similarity": 100, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2020.11.18.20230649", - "date": "2020-11-20", - "link": "https://medrxiv.org/cgi/content/short/2020.11.18.20230649", - "title": "A network modelling approach to assess non-pharmaceutical disease controls in a worker population: An application to SARS-CoV-2", - "authors": "Edward M Hill; Benjamin D Atkins; Matt J Keeling; Louise Dyson; Michael J Tildesley", - "affiliations": "University of Warwick; University of Warwick; University of Warwick; University of Warwick; University of Warwick", - "abstract": "BackgroundAs part of a concerted pandemic response to protect public health, businesses can enact non-pharmaceutical controls to minimise exposure to pathogens in workplaces and premises open to the public. Amendments to working practices can lead to the amount, duration and/or proximity of interactions being changed, ultimately altering the dynamics of disease spread. These modifications could be specific to the type of business being operated.\n\nMethodsWe use a data-driven approach to parameterise an individual-based network model for transmission of SARS-CoV-2 amongst the working population, stratified into work sectors. The network is comprised of layered contacts to consider the risk of spread in multiple encounter settings (workplaces, households, social and other). We analyse several interventions targeted towards working practices: mandating a fraction of the population to work from home; using temporally asynchronous work patterns; and introducing measures to create COVID-secure workplaces. We also assess the general role of adherence to (or effectiveness of) isolation and test and trace measures and demonstrate the impact of all these interventions across a variety of relevant metrics.\n\nResultsThe progress of the epidemic can be significantly hindered by instructing a significant proportion of the workforce to work from home. Furthermore, if required to be present at the workplace, asynchronous work patterns can help to reduce infections when compared with scenarios where all workers work on the same days, particularly for longer working weeks. When assessing COVID-secure workplace measures, we found that smaller work teams and a greater reduction in transmission risk reduced the probability of large, prolonged outbreaks. Finally, following isolation guidance and engaging with contact tracing without other measures is an effective tool to curb transmission, but is highly sensitive to adherence levels.\n\nConclusionsIn the absence of sufficient adherence to non-pharmaceutical interventions, our results indicate a high likelihood of SARS-CoV-2 spreading widely throughout a worker population. Given the heterogeneity of demographic attributes across worker roles, in addition to the individual nature of controls such as contact tracing, we demonstrate the utility of a network model approach to investigate workplace-targeted intervention strategies and the role of test, trace and isolation in tackling disease spread.", - "category": "infectious diseases", - "match_type": "fuzzy", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2020.11.18.20225029", @@ -6957,6 +6831,20 @@ "author_similarity": 100, "affiliation_similarity": 100 }, + { + "site": "medRxiv", + "doi": "10.1101/2020.11.12.20229955", + "date": "2020-11-15", + "link": "https://medrxiv.org/cgi/content/short/2020.11.12.20229955", + "title": "Mobile consulting (mConsulting) as an option for accessing healthcare services for communities in remote rural areas and urban slums in low- and middle- income countries: A mixed methods study", + "authors": "Bronwyn Harris; Motunrayo Ajisola; Raisa Alam; Jocelyn Antsley Watkins; Theodoros N Arvanitis; Pauline Bakibinga; Beatrice Chipwaza; Nazratun Nayeem Choudhury; Olufunke Fayhun; Peter Kibe; Akinyinka Omigbodun; Eme Owoaje; Senga Pemba; Rachel Potter; Narjis Rizvi; Jackie Sturt; Jonathan A.K Cave; Romaina Iqbal; Caroline Kabaria; Albino Kalolo; Catherine Kyobutungi; Richard J Lilford; Titus Mashanya; Sylvester Ndegese; Omar Rahman; Saleem Sayani; Rita Yusuf; Frances Griffiths", + "affiliations": "Warwick Medical School, University of Warwick, UK; Department of Sociology, Faculty of Social Sciences, University of Ibadan, Ibadan, Oyo State, Nigeria; Centre for Health, Population and Development, Independent University Bangladesh, Dhaka, Bangladesh; Warwick Medical School, University of Warwick, UK; Institute of Digital Healthcare, WMG, University of Warwick, UK; African Population and Health Research Center, Nairobi, Kenya; St Francis University College of Health and Allied Sciences, Tanzania; Centre for Health, Population and Development, Independent University Bangladesh, Dhaka, Bangladesh; Department of Sociology, Faculty of Social Sciences, University of Ibadan, Ibadan, Oyo State, Nigeria; African Population and Health Research Center, Nairobi, Kenya; Department of Obstetrics and Gynaecology, Faculty of Clinical Sciences, College of Medicine, University of Ibadan, Ibadan, Oyo State, Nigeria; Department of Community Medicine, Faculty of Public Health, College of Medicine, University of Ibadan, Ibadan, Oyo State, Nigeria; St Francis University College of Health and Allied Sciences, Tanzania; Clinical Trials Unit Warwick Medical School, University of Warwick, University of Warwick, UK; Community Health Sciences Department, Aga Khan University, Karachi, Pakistan; King's College London, Florence Nightingale Faculty of Nursing and Midwifery, London, UK; Department of Economics, University of Warwick, UK; Community Health Sciences Department, Aga Khan University, Karachi, Pakistan; African Population and Health Research Center, Nairobi, Kenya; St Francis University College of Health and Allied Sciences, Tanzania; African Population and Health Research Center, Nairobi, Kenya; Institute of Applied Health Research, College of Medical and Dental Sciences, University of Birmingham, Birmingham, UK; St Francis University College of Health and Allied Sciences, Tanzania; St Francis University College of Health and Allied Sciences, Tanzania; University of Liberal Arts Bangladesh, Dhaka, Bangladesh; Aga Khan Development Network Digital Health Resource Centre (Asia and Africa), Aga Khan University, Karachi, Pakistan; Centre for Health, Population and Development, Independent University Bangladesh, Dhaka, Bangladesh; Warwick Medical School, University of Warwick, UK", + "abstract": "ObjectiveRemote or mobile consulting (mConsulting) is being promoted to strengthen health systems, deliver universal health coverage and facilitate safe clinical communication during COVID-19 and beyond. We explored whether mConsulting is a viable option for communities with minimal resources in low- and middle-income countries (LMICs).\n\nMethodsWe reviewed evidence published since 2018 about mConsulting in LMICs and undertook a scoping study (pre-COVID) in two rural settings (Pakistan, Tanzania) and five urban slums (Kenya, Nigeria, Bangladesh), using policy/document review, secondary analysis of survey data (from the urban sites), and thematic analysis of interviews/workshops with community members, healthcare workers, digital/telecommunications experts, mConsulting providers, local and national decision-makers. Project advisory groups guided the study in each country.\n\nResultsWe reviewed five empirical studies and seven reviews, analysed data from 5,219 urban slum households and engaged with 419 stakeholders in rural and urban sites. Regulatory frameworks are available in each country. mConsulting services are operating through provider platforms (n=5-17) and, at community-level, some direct experience of mConsulting with healthcare workers using their own phones was reported - for emergencies, advice and care follow-up. Stakeholder willingness was high, provided challenges are addressed in technology, infrastructure, data security, confidentiality, acceptability and health system integration. mConsulting can reduce affordability barriers and facilitate care-seeking practices.\n\nConclusionsThere are indications of readiness for mConsulting in communities with minimal resources. However, wider system strengthening is needed to bolster referrals, specialist services, laboratories and supply-chains to fully realise the continuity of care and responsiveness that mConsulting services offer, particularly during/beyond COVID-19.", + "category": "public and global health", + "match_type": "fuzzy", + "author_similarity": 100, + "affiliation_similarity": 100 + }, { "site": "medRxiv", "doi": "10.1101/2020.11.10.20229146", @@ -6999,6 +6887,34 @@ "author_similarity": 100, "affiliation_similarity": 100 }, + { + "site": "medRxiv", + "doi": "10.1101/2020.11.11.20220962", + "date": "2020-11-13", + "link": "https://medrxiv.org/cgi/content/short/2020.11.11.20220962", + "title": "Short-term forecasts to inform the response to the COVID-19 epidemic in the UK", + "authors": "Sebastian Funk; Sam Abbott; Benjamin D Atkins; Marc Baguelin; J Kenneth Baillie; Paul J Birrell; Joshua Blake; Nikos I Bosse; Joshua Burton; Jonathan Carruthers; Nicholas G Davies; Daniela de Angelis; Louise Dyson; W. John Edmunds; Rosalind M Eggo; Neil M Ferguson; Katy A M Gaythorpe; Erin Gorsich; Glen Guyver-Fletcher; Joel Hellewell; Edward M Hill; Alexander Holmes; Thomas A House; Chris Jewell; Mark Jit; Thibaut Jombart; Indra Joshi; Matt J Keeling; Edward Kendall; Edward S Knock; Adam J Kucharski; Katrina A Lythgoe; Sophie R Meakin; James D Munday; Peter JM Openshaw; Christopher Overton; Filippo Pagani; Jonathan Pearson; Pablo N Perez-Guzman; Lorenzo Pellis; Francesca Scarabel; Malcolm Gracie Semple; Ming Tang; Michael Tildesley; Edwin van Leeuwen; Lilith Whittles; - CMMID COVID-19 Working Group; - Imperial College COVID-19 Response Team; - ISARIC4C Investigators", + "affiliations": "London School of Hygiene & Tropical Medicine; London School of Hygiene & Tropical Medicine; University of Warwick; Imperial College; Roslin Institute, University of Edinburgh; Public Health England; University of Cambridge; London School of Hygiene & Tropical Medicine; University of Manchester; Public Health England; London School of Hygiene and Tropical Medicine; University of Cambridge; University of Warwick; London School of Hygiene & Tropical Medicine; London School of Hygiene & Tropical Medicine; Imperial College; Imperial College London; University of Warwick; University of Warwick; London School of Hygiene & Tropical Medicine; University of Warwick; University of Warwick; University of Manchester; Lancaster University; London School of Hygiene & Tropical Medicine; London School of Hygiene & Tropical Medicine; NHSX; University of Warwick; NHS England & NHS Improvement; Imperial College; London School of Hygiene & Tropical Medicine; University of Oxford; London School of Hygiene & Tropical Medicine; London School of Hygiene and Tropical Medicine; Imperial College London; Manchester University; Manchester University; NHSX; Imperial College; The University of Manchester; York University; University of Liverpool; NHS England & NHSE Improvement; University of Warwick; Public Health England; Imperial College; ; ; ", + "abstract": "BackgroundShort-term forecasts of infectious disease can aid situational awareness and planning for outbreak response. Here, we report on multi-model forecasts of Covid-19 in the UK that were generated at regular intervals starting at the end of March 2020, in order to monitor expected healthcare utilisation and population impacts in real time.\n\nMethodsWe evaluated the performance of individual model forecasts generated between 24 March and 14 July 2020, using a variety of metrics including the weighted interval score as well as metrics that assess the calibration, sharpness, bias and absolute error of forecasts separately. We further combined the predictions from individual models into ensemble forecasts using a simple mean as well as a quantile regression average that aimed to maximise performance. We compared model performance to a null model of no change.\n\nResultsIn most cases, individual models performed better than the null model, and ensembles models were well calibrated and performed comparatively to the best individual models. The quantile regression average did not noticeably outperform the mean ensemble.\n\nConclusionsEnsembles of multi-model forecasts can inform the policy response to the Covid-19 pandemic by assessing future resource needs and expected population impact of morbidity and mortality.", + "category": "epidemiology", + "match_type": "fuzzy", + "author_similarity": 100, + "affiliation_similarity": 100 + }, + { + "site": "medRxiv", + "doi": "10.1101/2020.11.09.20228015", + "date": "2020-11-12", + "link": "https://medrxiv.org/cgi/content/short/2020.11.09.20228015", + "title": "A time-resolved proteomic and diagnostic map characterizes COVID-19 disease progression and predicts outcome", + "authors": "Vadim Demichev; Pinkus Tober-Lau; Tatiana Nazarenko; Charlotte Thibeault; Harry Whitwell; Oliver Lemke; Annika R\u00f6hl; Anja Freiwald; Lukasz Szyrwiel; Daniela Ludwig; Clara Correia-Melo; Elisa Theresa Helbig; Paula Stubbemann; Nana-Maria Gr\u00fcning; Oleg Blyuss; Spyros Vernardis; Matthew White; Christoph B. Messner; Michael Joannidis; Thomas Sonnweber; Sebastian J. Klein; Alex Pizzini; Yvonne Wohlfarter; Sabina Sahanic; Richard Hilbe; Benedikt Schaefer; Sonja Wagner; Mirja Mittermaier; Felix Machleidt; Carmen Garcia; Christoph Ruwwe-Gl\u00f6senkamp; Tilman Lingscheid; Laure Bosquillon de Jarcy; Miriam S. Stegemann; Moritz Pfeiffer; Linda J\u00fcrgens; Sophy Denker; Daniel Zickler; Philipp Enghard; Aleksej Zelezniak; Archie Campbell; Caroline Hayward; David J. Porteous; Riccardo Marioni; Alexander Uhrig; Holger M\u00fcller-Redetzky; Heinz Zoller; Judith L\u00f6ffler-Ragg; Markus A. Keller; Ivan Tancevski; John F. Timms; Alexey Zaikin; Stefan Hippenstiel; Michael Ramharter; Martin Witzenrath; Norbert Suttorp; Kathryn Lilley; Michael M\u00fclleder; Leif Erik Sander; - PA-COVID-19 Study group; Markus Ralser; Florian Kurth", + "affiliations": "The Francis Crick Institute; Charit\u00e9 - Universit\u00e4tsmedizin Berlin; University College London; Charite Universitaetsmedizin Berlin; Imperial College London; Charit\u00e9 - Universit\u00e4tsmedizin Berlin; Charit\u00e9 - Universit\u00e4tsmedizin Berlin; Charit\u00e9 - Universit\u00e4tsmedizin Berlin; The Francis Crick Institute; Charit\u00e9 - Universit\u00e4tsmedizin Berlin; The Francis Crick Institute; Charit\u00e9 - Universit\u00e4tsmedizin Berlin; Charit\u00e9 - Universit\u00e4tsmedizin Berlin; Charit\u00e9 - Universit\u00e4tsmedizin Berlin; Lobachevsky University; The Francis Crick Institute; The Francis Crick Institute; Charit\u00e9 - Universit\u00e4tsmedizin Berlin; Medical University of Innsbruck; Medical University of Innsbruck; Medical University of Innsbruck; Medical University of Innsbruck; Medical University of Innsbruck; Medical University of Innsbruck; Medical University of Innsbruck; Medical University of Innsbruck; Medical University of Innsbruck; Charit\u00e9 - Universit\u00e4tsmedizin Berlin; Charit\u00e9 - Universit\u00e4tsmedizin Berlin; Charit\u00e9 - Universit\u00e4tsmedizin Berlin; Charit\u00e9 - Universit\u00e4tsmedizin Berlin; Charit\u00e9 - Universit\u00e4tsmedizin Berlin; Charit\u00e9 - Universit\u00e4tsmedizin Berlin; Charit\u00e9 - Universit\u00e4tsmedizin Berlin; Charit\u00e9 - Universit\u00e4tsmedizin Berlin; Charit\u00e9 - Universit\u00e4tsmedizin Berlin; Charit\u00e9 - Universit\u00e4tsmedizin Berlin; Charit\u00e9 - Universit\u00e4tsmedizin Berlin; Charit\u00e9 - Universit\u00e4tsmedizin Berlin; The Francis Crick Institute; The University of Edinburgh; The University of Edinburgh; The University of Edinburgh; University of Edinburgh; Charit\u00e9 - Universit\u00e4tsmedizin Berlin; Charit\u00e9 - Universit\u00e4tsmedizin Berlin; Medical University of Innsbruck; Medical University of Innsbruck; Medical University of Innsbruck; Medical University of Innsbruck; University College London; University College London; Charit\u00e9 - Universit\u00e4tsmedizin Berlin; Bernhard Nocht Institute for Tropical Medicine; Charit\u00e9 - Universit\u00e4tsmedizin Berlin; Charit\u00e9 - Universit\u00e4tsmedizin Berlin; The University of Cambridge; Charit\u00e9 - Universit\u00e4tsmedizin Berlin; Charit\u00e9 - Universit\u00e4tsmedizin Berlin; ; Charite University Medicine; Charit\u00e9 - Universit\u00e4tsmedizin Berlin", + "abstract": "COVID-19 is highly variable in its clinical presentation, ranging from asymptomatic infection to severe organ damage and death. There is an urgent need for predictive markers that can guide clinical decision-making, inform about the effect of experimental therapies, and point to novel therapeutic targets. Here, we characterize the time-dependent progression of COVID-19 through different stages of the disease, by measuring 86 accredited diagnostic parameters and plasma proteomes at 687 sampling points, in a cohort of 139 patients during hospitalization. We report that the time-resolved patient molecular phenotypes reflect an initial spike in the systemic inflammatory response, which is gradually alleviated and followed by a protein signature indicative of tissue repair, metabolic reconstitution and immunomodulation. Further, we show that the early host response is predictive for the disease trajectory and gives rise to proteomic and diagnostic marker signatures that classify the need for supplemental oxygen therapy and mechanical ventilation, and that predict the time to recovery of mildly ill patients. In severely ill patients, the molecular phenotype of the early host response predicts survival, in two independent cohorts and weeks before outcome. We also identify age-specific molecular response to COVID-19, which involves increased inflammation and lipoprotein dysregulation in older patients. Our study provides a deep and time resolved molecular characterization of COVID-19 disease progression, and reports biomarkers for risk-adapted treatment strategies and molecular disease monitoring. Our study demonstrates accurate prognosis of COVID-19 outcome from proteomic signatures recorded weeks earlier.", + "category": "infectious diseases", + "match_type": "fuzzy", + "author_similarity": 100, + "affiliation_similarity": 100 + }, { "site": "medRxiv", "doi": "10.1101/2020.11.05.20226662", @@ -7195,20 +7111,6 @@ "author_similarity": 100, "affiliation_similarity": 100 }, - { - "site": "bioRxiv", - "doi": "10.1101/2020.10.26.356014", - "date": "2020-10-28", - "link": "https://biorxiv.org/cgi/content/short/2020.10.26.356014", - "title": "COVID-19 Disease Map, a computational knowledge repository of SARS-CoV-2 virus-host interaction mechanisms", - "authors": "Marek Ostaszewski; Anna Niarakis; Alexander Mazein; Inna Kuperstein; Robert Phair; Aurelio Orta-Resendiz; Vidisha Singh; Sara Sadat Aghamiri; Marcio Luis Acencio; Enrico Glaab; Andreas Ruepp; Gisela Fobo; Corinna Montrone; Barbara Brauner; Goar Frishman; Julia Somers; Matti Hoch; Shailendra Kumar Gupta; Julia Scheel; Hanna Borlinghaus; Tobias Czauderna; Falk Schreiber; Arnau Montagud; Miguel Ponce de Leon; Akira Funahashi; Yusuke Hiki; Noriko Hiroi; Takahiro G Yamada; Andreas Drager; Alina Renz; Muhammad Naveez; Zsolt Bocskei; Daniela Bornigen; Liam Fergusson; Marta Conti; Marius Rameil; Vanessa Nakonecnij; Jakob Vanhoefer; Leonard Schmiester; Muying Wang; Emily E Ackerman; Jason E Shoemaker; Jeremy Zucker; Kristie L Oxford; Jeremy Teuton; Ebru Kocakaya; Gokce Yagmur Summak; Kristina Hanspers; Martina Kutmon; Susan Coort; Lars Eijssen; Friederike Ehrhart; Rex D. A. B.; Denise Slenter; Marvin Martens; Nhung Pham; Robin Haw; Bijay Jassal; Lisa Matthews; Marija Orlic-Milacic; Andrea Senff-Ribeiro; Karen Rothfels; Veronica Shamovsky; Ralf Stephan; Cristoffer Sevilla; Thawfeek Mohamed Varusai; Jean-Marie Ravel; Vera Ortseifen; Silvia Marchesi; Piotr Gawron; Ewa Smula; Laurent Heirendt; Venkata Satagopam; Guanming Wu; Anders Riutta; Martin Golebiewski; Stuart Owen; Carole Goble; Xiaoming Hu; Rupert Overall; Dieter Maier; Angela Bauch; Benjamin M Gyori; John A Bachman; Carlos Vega; Valentin Groues; Miguel Vazquez; Pablo Porras; Luana Licata; Marta Iannuccelli; Francesca Sacco; Denes Turei; Augustin Luna; Ozgun Babur; Sylvain Soliman; Alberto Valdeolivas; Marina Esteban-Medina; Maria Pena-Chilet; Kinza Rian; Tomas Helikar; Bhanwar Lal Puniya; Anastasia Nesterova; Anton Yuryev; Anita de Waard; Dezso Modos; Agatha Treveil; Marton Laszlo Olbei; Bertrand De Meulder; Aurelien Naldi; Aurelien Dugourd; Laurence Calzone; Chris Sander; Emek Demir; Tamas Korcsmaros; Tom C Freeman; Franck Auge; Jacques S Beckmann; Jan Hasenauer; Olaf Wolkenhauer; Egon Willighagen; Alexander R Pico; Chris Evelo; Lincoln D Stein; Henning Hermjakob; Julio Saez-Rodriguez; Joaquin Dopazo; Alfonso Valencia; Hiroaki Kitano; Emmanuel Barillot; Charles Auffray; Rudi Balling; Reinhard Schneider; - the COVID-19 Disease Map Community", - "affiliations": "Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg; Department of Biology, Univ. Evry, University of Paris-Saclay, GenHotel, Genopole, 91025, Evry, France; Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg; Institut Curie, PSL Research University, Paris, France.; Integrative Bioinformatics, Inc., 346 Paul Ave, Mountain View, CA, USA; Institut Pasteur, HIV, Inflammation and Persistence Unit, Paris, France; Laboratoire Europeen de Recherche pour la Polyarthrite Rhumatoide - Genhotel, Univ Evry, Universite Paris-Saclay, 2, rue Gaston Cremieux, 91057 EVRY-GENOPOLE ce; Inserm- Institut national de la sante et de la recherche medicale. Saint-Louis Hospital 1 avenue Claude Vellefaux Pavillon Bazin 75475 Paris; Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg; Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg; Institute of Experimental Genetics (IEG), Helmholtz Zentrum Munchen-German Research Center for Environmental Health (GmbH), Ingolstadter Landstrasse 1, D-85764 ; Institute of Experimental Genetics (IEG), Helmholtz Zentrum Munchen-German Research Center for Environmental Health (GmbH), Ingolstadter Landstrasse 1, D-85764 ; Institute of Experimental Genetics (IEG), Helmholtz Zentrum Munchen-German Research Center for Environmental Health (GmbH), Ingolstadter Landstrasse 1, D-85764 ; Institute of Experimental Genetics (IEG), Helmholtz Zentrum Munchen-German Research Center for Environmental Health (GmbH), Ingolstadter Landstrasse 1, D-85764 ; Institute of Experimental Genetics (IEG), Helmholtz Zentrum Munchen-German Research Center for Environmental Health (GmbH), Ingolstadter Landstrasse 1, D-85764 ; Oregong Health & Sciences Univerity; Department of Molecular and Medical Genetics; 3222 SW Research Drive, Portland, Oregon, U.S.A 97239; Department of Systems Biology and Bioinformatics, University of Rostock, 18051 Rostock, Germany; Department of Systems Biology and Bioinformatics, University of Rostock, 18051 Rostock, Germany; Department of Systems Biology and Bioinformatics, University of Rostock, 18051 Rostock, Germany; Department of Computer and Information Science, University of Konstanz, Konstanz, Germany; Monash University, Faculty of Information Technology, Department of Human-Centred Computing, Wellington Rd, Clayton VIC 3800, Australia; Department of Computer and Information Science, University of Konstanz, Konstanz, Germany; Barcelona Supercomputing Center (BSC), Barcelona, Spain; Barcelona Supercomputing Center (BSC), Barcelona, Spain; Keio University, Department of Biosciences and Informatics, 3-14-1 Hiyoshi Kouhoku-ku Yokohama Japan 223-8522; Keio University, Department of Biosciences and Informatics, 3-14-1 Hiyoshi Kouhoku-ku Yokohama Japan 223-8522; Sanyo-Onoda City University, Faculty of Pharmaceutical Sciences, University St.1-1-1, Yamaguchi, Japan 756-0884; Keio University, Department of Biosciences and Informatics, 3-14-1 Hiyoshi Kouhoku-ku Yokohama Japan 223-8522; Computational Systems Biology of Infections and Antimicrobial-Resistant Pathogens, Institute for Bioinformatics and Medical Informatics (IBMI), University of Tu; Computational Systems Biology of Infections and Antimicrobial-Resistant Pathogens, Institute for Bioinformatics and Medical Informatics (IBMI), University of Tu; Riga Technical University, Institute of Applied Computer Systems,1 Kalku Street, LV-1658 Riga, Latvia; Sanofi R&D Translational Sciences; Bioinformatics Core Facility, Universitaetsklinikum Hamburg-Eppendorf, Martinistrasse 52, 20246 Hamburg, Germany; The University of Edinburgh, Royal (Dick) School of Veterinary Medicine, Easter Bush Campus, Midlothian, EH25 9RG; Faculty of Mathematics and Natural Sciences, University of Bonn, Bonn, Germany; University of Bonn, Germany; Faculty of Mathematics and Natural Sciences, University of Bonn, Bonn, Germany; Faculty of Mathematics and Natural Sciences, University of Bonn, Bonn, Germany; Helmholtz Zentrum Munchen - German Research Center for Environmental Health, Institute of Computational Biology, 85764 Neuherberg, Germany; Department of Chemical Engineering, University of Pittsburgh; University of Pittsburgh, Department of Chemical and Petroleum Engineering; Dept. of Chemical & Petroleum Engineering, University of Pittsburgh; Pacific Northwest National Laboratory; Pacific Northwest National Laboratory; Pacific Northwest National Laboratory; Ankara University, Stem Cell Institute, Ceyhun Atif Kansu St. No: 169 06520 Cevizlidere/ANKARA/TURKEY; Ankara University, Stem Cell Institute, Ceyhun Atif Kansu St. No: 169 06520 Cevizlidere/ANKARA/TURKEY; Institute of Data Science and Biotechnology, Gladstone Institutes, San Francisco, CA 94158; Department of Bioinformatics - BiGCaT, NUTRIM, Maastricht University, Maastricht, The Netherlands; Maastricht University, NUTRIM, Bioinformatics-BiGCaT, PO Box 616, 6200 MD, Maastricht, the Netherlands; Department of Bioninformatics-BiGCaT, NUTRIM, Maastricht University, Universiteitssingel 60, 6229 ER Maastricht, The Netherlands; Maastricht University, Department of Bioinformatics, NUTRIM, Universiteitssingel 60; 6229 ER Maastricht; The Netherlands; Center for Systems Biology and Molecular Medicine, Yenepoya (Deemed to be University), Mangalore 575018, India; Department of Bioinformatics-BiGCaT, NUTRIM, Maastricht University, Maastricht, The Netherlands; Department of Bioinformatics - BiGCaT, NUTRIM, Maastricht University, 6229 ER Maastricht, The Netherlands; Maastricht University, NUTRIM, Bioinformatics-BiGCaT, PO Box 616, 6200 MD, Maastricht, the Netherlands; Adaptive Oncology, Ontario Institute for Cancer Research, MaRS Centre, 661 University Avenue, Suite 510, Toronto, Ontario, Canada M5G 0A3; Ontario Institute for Cancer Research (OICR), 661 University Ave Suite 510, Toronto, ON M5G 0A3, Canada; NYU Grossman School of Medicine, New York NY 10016 USA; Ontario Institute for Cancer Research, Department of Computational Biology, MaRS Centre, South Tower, 661 University Avenue, Suite 500, Toronto, Ontario, Canada; Ontario Institute for Cancer Research (OICR) (Canada); Ontario Institute for Cancer Research, Department of Computational Biology, MaRS Centre, South Tower, 661 University Avenue, Suite 500, Toronto, Ontario, Canada; NYU Langone Medical Center, New York, USA; Ontario Institute for Cancer Research, MaRS Centre, 661 University Ave, Suite 510, Toronto, Ontario, Canada; EMBL-EBI, Molecular Systems, Wellcome Genome Campus, Hinxton, Cambridgeshire, CB10 1SD; Reactome, EMBL-EBI, Cambridge, UK; University of Lorraine, INSERM UMR_S 1256, Nutrition, Genetics, and Environmental Risk Exposure (NGERE), Faculty of Medicine of Nancy, F-54000 Nancy, France.; Senior Research Group in Genome Research of Industrial Microorganisms, Center for Biotechnology, Bielefeld University, Universitaetsstrasse 27, 33615 Bielefeld,; Uppsala University - Sweden; Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg; Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg; Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg; Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg; Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University, 3181 S.W. Sam Jackson Park Road, Portland, OR 97239-3098, USA; Gladstone Institutes, Institute for Data Science and Biotechnology, 1650 Owens St., San Francisco, CA 94131, USA; Heidelberg Institute for Theoretical Studies (HITS), Schloss-Wolfsbrunnenweg 35, D-69118 Heidelberg (Germany); The University of Manchester, Department of Computer Science, Oxford Road, Manchester, M13 9PL, UK; The University of Manchester, Department of Computer Science, Oxford Road, Manchester, M13 9PL, UK; Heidelberg Institute for Theoretical Studies (HITS), Schloss-Wolfsbrunnenweg 35, D-69118 Heidelberg (Germany); German Center for Neurodegenerative Diseases (DZNE) Dresden, Tatzberg 41, 01307 Dresden, Germany.; Biomax Informatics AG, Robert-Koch-Str. 2, 82152 Planegg, Germany; Biomax Informatics AG, Robert-Koch-Str. 2, 82152 Planegg, Germany; Harvard Medical School, Laboratory of Systems Pharmacology, 200 Longwood Avenue, Boston, MA; Harvard Medical School, Laboratory of Systems Pharmacology, 200 Longwood Avenue, Boston, MA; Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg; Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg; Barcelona Supercomputing Center (BSC), Barcelona, Spain; EMBL-EBI, Molecular Systems, Wellcome Genome Campus, CB10 1SD, Hinxton, UK; University of Rome Tor Vergata, Department of Biology, Via della Ricerca Scientifica 1, 00133 Rome, Italy; University of Rome Tor Vergata, Department of Biology, Via della Ricerca Scientifica 1, 00133 Rome, Italy; University of Rome Tor Vergata, Department of Biology, Via della Ricerca Scientifica 1, 00133 Rome, Italy; Heidelberg Univarsity, Institute for Computational Biomedicine, BQ 0053, Im Neuenheimer Feld 267, 69120 Heidelberg, Germany; cBio Center, Divisions of Biostatistics and Computational Biology, Department of Data Sciences, Dana-Farber Cancer Institute, Boston, MA, 02215, USA.; University of Massachusetts Boston, Computer Science Department, 100 William T, Morrissey Blvd, Boston, MA 02125; Inria Saclay Ile-de-France; Heidelberg University, Faculty of Medicine and Heidelberg University Hospital, Institute of Computational Biomedicine, Bioquant, 69120 Heidelberg, Germany; Clinical Bioinformatics Area. Fundacion Progreso y Salud (FPS). CDCA, Hospital Virgen del Rocio, 41013, Sevilla, Spain.; Clinical Bioinformatics Area. Fundacion Progreso y Salud (FPS). CDCA, Hospital Virgen del Rocio, 41013, Sevilla, Spain.; Clinical Bioinformatics Area. Fundacion Progreso y Salud (FPS). CDCA, Hospital Virgen del Rocio, 41013, Sevilla, Spain.; University of Nebraska-Lincoln, Department of Biochemistry, 1901 Vine St., Lincoln, NE, 68588, USA; University of Nebraska-Lincoln, Department of Biochemistry, 1901 Vine St., Lincoln, NE, 68588, USA; Elsevier, Life Science Department; Elsevier, Professional Services, 1600 John F Kennedy Blvd #1800, Philadelphia, PA 19103; Elsevier, Research Collaborations Unit, 71 Hanley Lane, Jericho, VT 05465; Quadram Institute Bioscience, Rosalind Franklin Road, Norwich Research Park, Norwich, NR4 7UQ, United Kingdom; Earlham Institute, Norwich Research Park, Norwich, NR4 7UZ, United Kingdom; Earlham Institute, Norwich Research Park, Norwich, NR4 7UZ, United Kingdom; Association EISBM; Inria Saclay - Ile de France, Lifeware group, 91120 Palaiseau, France; Heidelberg University, Faculty of Medicine, and Heidelberg University Hospital, Institute for Computational Biomedicine, Bioquant, Heidelberg, Germany; Institut Curie, PSL Research University, Mines Paris Tech, Inserm, U900, F-75005, Paris, France.; cBio Center, Divisions of Biostatistics and Computational Biology, Department of Data Sciences, Dana-Farber Cancer Institute, Boston, MA, 02215, USA.; Oregon Health and Science University, Department of Molecular and Medical Genetics, 3222 SW Research Drive, Mail Code: L103, Portland, Oregon, U.S.A. 97239; Earlham Institute, Norwich Research Park, NR4 7UZ, Norwich, UK; The Roslin Institute, University of Edinburgh EH25 9RG; Sanofi R&D, Translational Sciences, 1 av Pierre Brossolette 91395 Chilly-Mazarin France; University of Lausanne, Lausanne, Switzerland; Interdisciplinary Research Unit Mathematics and Life Sciences, University of Bonn, Germany; University of Rostock, Dept of Systems Biology & Bioinformatics; Department of Bioinformatics-BiGCaT, NUTRIM, Maastricht University, Maastricht, The Netherlands; Institute of Data Science and Biotechnology, Gladstone Institutes, San Francisco, CA, USA; Dept. Bioinformatics - BiGCaT, Maastricht University, The Netherlands; Ontario Institute for Cancer Research, Adaptive Oncology Theme, 661 University Ave, Toronto, ON M5G 1M1 Canada; European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridgeshire, UK; Institute for Computational Biomedicine Heidelberg University, Faculty of Medicine, Im Neuenheimer Feld 267, 69120 Heidelberg; Clinical Bioinformatics Area. Fundacion Progreso y Salud (FPS). CDCA, Hospital Virgen del Rocio. 41013. Sevilla. Spain.; Barcelona Supercomputing Center (BSC), Barcelona, Spain; Systems Biology Institute, Tokyo Japan; Institut Curie, PSL Research University, Paris, France.; European Institute for Systems Biology and Medicine (EISBM), Vourles, France; Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg; Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg; -", - "abstract": "We describe a large-scale community effort to build an open-access, interoperable, and computable repository of COVID-19 molecular mechanisms - the COVID-19 Disease Map. We discuss the tools, platforms, and guidelines necessary for the distributed development of its contents by a multi-faceted community of biocurators, domain experts, bioinformaticians, and computational biologists. We highlight the role of relevant databases and text mining approaches in enrichment and validation of the curated mechanisms. We describe the contents of the Map and their relevance to the molecular pathophysiology of COVID-19 and the analytical and computational modelling approaches that can be applied for mechanistic data interpretation and predictions. We conclude by demonstrating concrete applications of our work through several use cases and highlight new testable hypotheses.", - "category": "systems biology", - "match_type": "fuzzy", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2020.10.25.20219048", @@ -7391,6 +7293,20 @@ "author_similarity": 100, "affiliation_similarity": 100 }, + { + "site": "medRxiv", + "doi": "10.1101/2020.10.12.20211342", + "date": "2020-10-14", + "link": "https://medrxiv.org/cgi/content/short/2020.10.12.20211342", + "title": "Network Graph Representation of COVID-19 Scientific Publications to Aid Knowledge Discovery", + "authors": "George Cernile; Trevor Heritage; Neil Sebire; Ben Gordon; Taralyn Schwering; Shana Kazemlou; Yulia Borecki", + "affiliations": "Inspirata Ltd; Inspirata Ltd; HDRUK London UK; HDRUK London UK; Inspirata Ltd; Inspirata Ltd; Inspirata Ltd", + "abstract": "IntroductionNumerous scientific journal articles have been rapidly published related to COVID-19 making navigation and understanding of relationships difficult.\n\nMethodsA graph network was constructed from the publicly available CORD-19 database of COVID-19-related publications using an engine leveraging medical knowledgebases to identify discrete medical concepts and an open source tool (Gephi) used to visualise the network.\n\nResultsThe network shows connections between disease, medication and procedures identified from title and abstracts of 195,958 COVID-19 related publications (CORD-19 Dataset). Connections between terms with few publications, those unconnected to the main network and those irrelevant were not displayed. Nodes were coloured by knowledgebase and node size related to the number of publications containing the term. The dataset and visualisations made publicly accessible via a webtool.\n\nConclusionKnowledge management approaches (text mining and graph networks) can effectively allow rapid navigation and exploration of entity interrelationships to improve understanding of diseases such as COVID-19.", + "category": "health informatics", + "match_type": "fuzzy", + "author_similarity": 100, + "affiliation_similarity": 100 + }, { "site": "medRxiv", "doi": "10.1101/2020.10.12.20211227", @@ -7545,6 +7461,20 @@ "author_similarity": 100, "affiliation_similarity": 100 }, + { + "site": "medRxiv", + "doi": "10.1101/2020.10.03.20206284", + "date": "2020-10-06", + "link": "https://medrxiv.org/cgi/content/short/2020.10.03.20206284", + "title": "The excess insulin requirement in severe COVID-19 compared to non-COVID-19 viral pneumonitis is related to the severity of respiratory failure and pre-existing diabetes.", + "authors": "Sam Lockhart; Harry Griffiths; Bogdan Petrisor; Ammara Usman; Julia Calvo-Latorre; Laura Heales; Vishakha Bansiya; Razeen Mahroof; Andrew Conway Morris", + "affiliations": "1.\tMRC Metabolic Diseases Unit, Wellcome Trust-Medical Research Council Institute of Metabolic Science, University of Cambridge, Cambridge, UK.; John V Farman Intensive Care Unit, Addenbrooke's Hospital, Cambridge; John V Farman Intensive Care Unit, Addenbrooke's Hospital, Cambridge; John V Farman Intensive Care Unit, Addenbrooke's Hospital, Cambridge; Wolfson Diabetes and Endocrinology Clinic, Cambridge University Hospital NHS Foundation Trust, Cambridge; John V Farman Intensive Care Unit, Addenbrooke's Hospital, Cambridge; Wolfson Diabetes and Endocrinology Clinic, Cambridge University Hospital NHS Foundation Trust, Cambridge; John V Farman Intensive Care Unit, Addenbrookes Hospital, Cambridge; University of Cambridge", + "abstract": "ObjectiveSevere COVID-19 has been anecdotally associated with high insulin requirements. It has been proposed that this may be driven by a direct diabetogenic effect of the virus that is unique to SARS-CoV-2, but evidence to support this is limited. To explore this, we compared insulin requirements in patients with severe COVID-19 and non-COVID-19 viral pneumonitis.\n\nResearch DesignRetrospective cohort study of patients with severe COVID-19 admitted to our intensive care unit between March and June 2020. A historical control cohort of non-COVID-19 viral pneumonitis patients was identified from routinely collected audit data.\n\nResultsInsulin requirements were similar in patients with COVID-19 and non-COVID-19 viral pneumonitis after adjustment for pre-existing diabetes and severity of respiratory failure.\n\nConclusionsIn this single center study, we could not find evidence of a unique diabetogenic effect of COVID-19. We suggest that high insulin requirements in this disease relate to its propensity to cause severe respiratory failure in patients with pre-existing metabolic disease.", + "category": "intensive care and critical care medicine", + "match_type": "fuzzy", + "author_similarity": 100, + "affiliation_similarity": 100 + }, { "site": "medRxiv", "doi": "10.1101/2020.10.02.20205591", @@ -7671,6 +7601,20 @@ "author_similarity": 100, "affiliation_similarity": 100 }, + { + "site": "medRxiv", + "doi": "10.1101/2020.09.21.20194019", + "date": "2020-09-23", + "link": "https://medrxiv.org/cgi/content/short/2020.09.21.20194019", + "title": "Putting (Big) Data in Action: Saving Lives with Countrywide Population Movement Monitoring Using Mobile Devices during the COVID-19 Crisis", + "authors": "Miklos Karoly Szocska; Peter Pollner; Istvan Schiszler; Tamas Joo; Tamas Palicz; Martin McKee; - Magyar Telekom Nyrt.; - Telenor Magyarorszag Zrt.; Adam Sohonyai; Jozsef Szoke; Adam Toth; Peter Gaal", + "affiliations": "Semmelweis University, Faculty of Health and Public Administration, Health Services Management Training Centre, Digital Health and Data Utilisation Team; Semmelweis University, Faculty of Health and Public Administration, Health Services Management Training Centre, Digital Health and Data Utilisation Team; Semmelweis University, Faculty of Health and Public Administration, Health Services Management Training Centre, Digital Health and Data Utilisation Team; Semmelweis University, Faculty of Health and Public Administration, Health Services Management Training Centre, Digital Health and Data Utilisation Team; Semmelweis University, Faculty of Health and Public Administration, Health Services Management Training Centre, Digital Health and Data Utilisation Team; University of London, London School of Hygiene and Tropical Medicine, Department of Health Services Research and Policy; ; ; Vodafone Hungary; Vodafone Hungary; Vodafone Hungary; Semmelweis University, Faculty of Health and Public Administration, Health Services Management Training Centre, Digital Health and Data Utilisation Team", + "abstract": "Many countries have implemented strict social distancing measures in the hope of reducing transmission of SARS-CoV-2 but the effectiveness of these measures is determined by the willingness of populations to comply with restrictions. Consequently, a system of monitoring population movement using existing data sources can inform those making decisions about policy responses to the COVID-19 pandemic. We describe a collaboration with all 3 major domestic telecommunication companies in Hungary to use aggregated anonymous mobile phone usage data to calculate two indices for assessing the effect of movement restrictions: a \"mobility-index\" and a \"stay-at-home (or resting) index\". The strengths and weaknesses of this approach are compared with the smartphone-based, COVID-19 Community Mobility Reports from Google. Data generated by mobile phones have long been identified as a potential means to analyse mass population movement, but its operationalisation raises several technical questions, such as making sense of Call Detail Records, collation of data from different mobile network providers, and personal data protection concerns. The method described here addresses these issues and offers an effective and inexpensive tool to monitor the impact of social distancing measures, achieving high levels of accuracy and resolution. Especially in populations where uptake of smartphones is modest, this method has certain advantages over app-based solutions, with greater population coverage, but it is not an alternative to smartphone-based solutions used for contact tracing and quarantine monitoring. We believe that this method can easily be adapted by other countries.", + "category": "infectious diseases", + "match_type": "fuzzy", + "author_similarity": 100, + "affiliation_similarity": 100 + }, { "site": "medRxiv", "doi": "10.1101/2020.09.21.20196428", @@ -7685,6 +7629,20 @@ "author_similarity": 100, "affiliation_similarity": 100 }, + { + "site": "medRxiv", + "doi": "10.1101/2020.09.17.20196436", + "date": "2020-09-21", + "link": "https://medrxiv.org/cgi/content/short/2020.09.17.20196436", + "title": "Comparison of COVID-19 outcomes among shielded and non-shielded populations: A general population cohort study of 1.3 million", + "authors": "Bhautesh D Jani; Frederick K Ho; David J Lowe; Jamie P Traynor; Sean MacBride-Stewart; Patrick B Mark; Frances S Mair; Jill P Pell", + "affiliations": "University of Glasgow; University of Glasgow; NHS Greater Glasgow and Clyde; NHS Greater Glasgow and Clyde; NHS Greater Glasgow and Clyde; University of Glasgow; University of Glasgow; University of Glasgow", + "abstract": "Many western countries used shielding (extended self-isolation) of people presumed to be at high-risk from COVID-19 to protect them and reduce healthcare demand. To investigate the effectiveness of this strategy, we linked family practitioner, prescribing, laboratory, hospital and death records and compared COVID-19 outcomes among shielded and non-shielded individuals in the West of Scotland. Of the 1.3 million population, 27,747 (2.03%) were advised to shield, and 353,085 (26.85%) were classified a priori as moderate risk. COVID-19 testing was more common in the shielded (7.01%) and moderate risk (2.03%) groups, than low risk (0.73%). Referent to low-risk, the shielded group had higher confirmed infections (RR 8.45, 95% 7.44-9.59), case-fatality (RR 5.62, 95% CI 4.47-7.07) and population mortality (RR 57.56, 95% 44.06-75.19). The moderate-risk had intermediate confirmed infections (RR 4.11, 95% CI 3.82-4.42) and population mortality (RR 25.41, 95% CI 20.36-31.71) but, due to their higher prevalence, made the largest contribution to deaths (PAF 75.30%). Age [≥]70 years accounted for 49.55% of deaths. In conclusion, shielding has not been effective at preventing deaths in individuals at high risk. Also, to be effective as a population strategy, shielding criteria would need to be widely expanded to include other criteria, such as the elderly.", + "category": "public and global health", + "match_type": "fuzzy", + "author_similarity": 100, + "affiliation_similarity": 100 + }, { "site": "medRxiv", "doi": "10.1101/2020.09.15.20194795", @@ -8077,20 +8035,6 @@ "author_similarity": 94, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2020.08.13.20174193", - "date": "2020-08-15", - "link": "https://medrxiv.org/cgi/content/short/2020.08.13.20174193", - "title": "CovidNudge: diagnostic accuracy of a novel lab-free point-of-care diagnostic for SARS-CoV-2", - "authors": "Malick M Gibani; Christofer Toumazou; Mohammadreza Sohbati; Rashmita Sahoo; Maria Karvela; Tsz-Kin Hon; Sara De Mateo; Alison Burdett; K Y Felice Leung; Jake Barnett; Arman Orbeladze; Song Luan; Stavros Pournias; Jiayang Sun; Barnaby Flower; Judith Bedzo-Nutakor; Maisarah Amran; Rachael Quinlan; Keira Skolimowska; Robert Klaber; Gary Davies; David Muir; Paul Randell; Derrick W M Crook; Graham P Taylor; Wendy Barclay; Nabeela Mughal; Luke S P Moore; Katie Jeffery; Graham S Cooke", - "affiliations": "Imperial College London; DnaNudge Ltd, Translation and Innovation Hub, Imperial College White City Campus, London; DnaNudge Ltd, Translation and Innovation Hub, Imperial College White City Campus, London; DnaNudge Ltd, Translation and Innovation Hub, Imperial College White City Campus, London; DnaNudge Ltd, Translation and Innovation Hub, Imperial College White City Campus, London; DnaNudge Ltd, Translation and Innovation Hub, Imperial College White City Campus, London; DnaNudge Ltd, Translation and Innovation Hub, Imperial College White City Campus, London; DnaNudge Ltd, Translation and Innovation Hub, Imperial College White City Campus, London; DnaNudge Ltd, Translation and Innovation Hub, Imperial College White City Campus, London; DnaNudge Ltd, Translation and Innovation Hub, Imperial College White City Campus, London; DnaNudge Ltd, Translation and Innovation Hub, Imperial College White City Campus, London; DnaNudge Ltd, Translation and Innovation Hub, Imperial College White City Campus, London; DnaNudge Ltd, Translation and Innovation Hub, Imperial College White City Campus, London; DnaNudge Ltd, Translation and Innovation Hub, Imperial College White City Campus, London; Department of Infectious Disease, Imperial College London, United Kingdom; DnaNudge Ltd, Translation and Innovation Hub, Imperial College White City Campus, London; Imperial College Healthcare NHS Trust, United Kingdom.; Department of Infectious Disease, Imperial College London, United Kingdom; Imperial College Healthcare NHS Trust, United Kingdom; Imperial College Healthcare NHS Trust, United Kingdom; Chelsea & Westminster NHS Foundation Trust, London; Imperial College Healthcare NHS Trust, United Kingdom; Imperial College Healthcare NHS Trust, United Kingdom; NIHR Oxford Biomedical Research Centre; Department of Infectious Disease, Imperial College London, United Kingdom; Department of Infectious Disease, Imperial College London, United Kingdom; Chelsea & Westminster NHS Foundation Trust, London; Chelsea & Westminster NHS Foundation Trust, London; Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom; Department of Infectious Disease, Imperial College London, United Kingdom", - "abstract": "3.BackgroundAccess to rapid diagnosis is key to the control and management of SARS-CoV-2. Reverse Transcriptase-Polymerase Chain Reaction (RT-PCR) testing usually requires a centralised laboratory and significant infrastructure. We describe the development and diagnostic accuracy assessment of a novel, rapid point-of-care RT-PCR test, the DnaNudge(R) platform CovidNudge test, which requires no laboratory handling or sample pre-processing.\n\nMethodsNasopharyngeal swabs are inserted directly into a cartridge which contains all reagents and components required for RT-PCR reactions, including multiple technical replicates of seven SARS-CoV-2 gene targets (rdrp1, rdrp2, e-gene, n-gene, n1, n2 and n3) and human ribonuclease P (RNaseP) as positive control. Between April and May 2020, swab samples were tested in parallel using the CovidNudge direct-to-cartridge platform and standard laboratory RT-PCR using swabs in viral transport medium. Samples were collected from three groups: self-referred healthcare workers with suspected COVID-19 (Group 1, n=280/386; 73%); patients attending the emergency department with suspected COVID-19 (Group 2, n=15/386; 4%) and hospital inpatient admissions with or without suspected COVID-19 (Group 3, n=91/386; 23%).\n\nResultsOf 386 paired samples tested across all groups, 67 tested positive on the CovidNudge platform and 71 with standard laboratory RT-PCR. The sensitivity of the test varied by group (Group 1 93% [84-98%], Group 2 100% [48-100%] and Group 3 100% [29-100%], giving an average sensitivity of 94.4% (95% confidence interval 86-98%) and an overall specificity of 100% (95%CI 99-100%; Group 1 100% [98-100%]; Group 2 100% [69-100%] and Group 3 100% [96-100%]). Point of care testing performance was comparable during a period of high (25%) and low (3%) background prevalence. Amplification of the viral nucleocapsid (n1, n2, n3) targets were most sensitive for detection of SARS-CoV2, with the assay able to detect 1x104 viral particles in a single swab.\n\nConclusionsThe CovidNudge platform offers a sensitive, specific and rapid point of care test for the presence of SARS-CoV-2 without laboratory handling or sample pre-processing. The implementation of such a device could be used to enable rapid decisions for clinical care and testing programs.\n\n4. RESEARCH IN CONTEXTO_ST_ABSEvidence before this studyC_ST_ABSThe WHO has highlighted the development of rapid, point-of-care diagnostics for detection of SARS-CoV-2 as a key priority to tackle COVID-19. The Foundation for Innovative Diagnostics (FIND) has identified over 90 point-of-care, near patient or mobile tests for viral detection of SARS-CoV-2. However, the most widely available rapid tests to date require some sample handling which limits their use at point-of-care. In addition, pressure on supply chains is restricting access to current diagnostics and alternatives are needed urgently.\n\nAdded value of this studyWe describe the development and clinical validation of COVID nudge, a novel point-of-care RT-PCR diagnostic, evaluated during the first wave of the SARS-CoV-2 epidemic. The platform is able to achieve high analytic sensitivity and specificity from dry swabs within a self-contained cartridge. The lack of downstream sample handling makes it suitable for use in a range of clinical settings, without need for a laboratory or specialized operator. Multiplexed assays within the cartridge allow inclusion of a positive human control, which reduces the false negative testing rate due to insufficient sampling.\n\nImplication of the available evidencePoint-of-care testing can relieve pressure on centralized laboratories and increase overall testing capacity, complementing existing approaches. These findings support a role for COVID Nudge as part of strategies to improve access to rapid diagnostics to SARS-CoV-2. Since May 2020, the system has been implemented in UK hospitals and is being rolled out nationwide.", - "category": "infectious diseases", - "match_type": "fuzzy", - "author_similarity": 92, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2020.08.12.20173690", @@ -8105,20 +8049,6 @@ "author_similarity": 100, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2020.08.13.20174227", - "date": "2020-08-14", - "link": "https://medrxiv.org/cgi/content/short/2020.08.13.20174227", - "title": "Long-Term Exposure to Outdoor Air Pollution and COVID-19 Mortality: an ecological analysis in England", - "authors": "Zhiqiang Feng; Mark Cherrie; Chris DIBBEN", - "affiliations": "University of Edinburgh; University of Edinburgh; University of Edinburgh", - "abstract": "There is an urgent need to examine what individual and environmental risk factors are associated with COVID-19 mortality. This objective of this study is to investigate the association between long term exposure to air pollution and COVID-19 mortality. We conducted a nationwide, ecological study using zero-inflated negative binomial models to estimate the association between long term (2014-2018) small area level exposure to NOx, PM2.5, PM10 and SO2 and COVID-19 mortality rates in England adjusting for socioeconomic factors and infection exposure. We found that all four pollutant concentrations were positively associated with COVID-19 mortality. The increase in mortality risk ratio per inter quarter range increase was for PM2.5:11%, 95%CIs 6%-17%), PM10 (5%; 95%CIs 1%-11%), NOx (11%, 95%CIs 6%-15%) and SO2 (7%, 95%CIs 3%-11%) were respectively in adjusted models. Public health intervention may need to protect people who are in highly polluted areas from COVID-19 infections.", - "category": "occupational and environmental health", - "match_type": "fuzzy", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2020.08.12.20171405", @@ -8245,20 +8175,6 @@ "author_similarity": 100, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2020.08.04.20163782", - "date": "2020-08-04", - "link": "https://medrxiv.org/cgi/content/short/2020.08.04.20163782", - "title": "Fitting models to the COVID-19 outbreak and estimating R", - "authors": "Matt J Keeling; Louise Dyson; Glen Guyver-Fletcher; Alex Holmes; Malcolm G Semple; - ISARIC4C Investigators; Michael J Tildesley; Edward M Hill", - "affiliations": "University of Warwick; University of Warwick; University of Warwick; University of Warwick; University of Liverpool; ; University of Warwick; University of Warwick", - "abstract": "The COVID-19 pandemic has brought to the fore the need for policy makers to receive timely and ongoing scientific guidance in response to this recently emerged human infectious disease. Fitting mathematical models of infectious disease transmission to the available epidemiological data provides a key statistical tool for understanding the many quantities of interest that are not explicit in the underlying epidemiological data streams. Of these, the effective reproduction number, R, has taken on special significance in terms of the general understanding of whether the epidemic is under control (R < 1). Unfortunately, none of the epidemiological data streams are designed for modelling, hence assimilating information from multiple (often changing) sources of data is a major challenge that is particularly stark in novel disease outbreaks.\n\nHere, focusing on the dynamics of the first-wave (March-June 2020), we present in some detail the inference scheme employed for calibrating the Warwick COVID-19 model to the available public health data streams, which span hospitalisations, critical care occupancy, mortality and serological testing. We then perform computational simulations, making use of the acquired parameter posterior distributions, to assess how the accuracy of short-term predictions varied over the timecourse of the outbreak. To conclude, we compare how refinements to data streams and model structure impact estimates of epidemiological measures, including the estimated growth rate and daily incidence.", - "category": "infectious diseases", - "match_type": "fuzzy", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2020.07.30.20165464", @@ -8469,6 +8385,20 @@ "author_similarity": 100, "affiliation_similarity": 100 }, + { + "site": "medRxiv", + "doi": "10.1101/2020.07.14.20153734", + "date": "2020-07-16", + "link": "https://medrxiv.org/cgi/content/short/2020.07.14.20153734", + "title": "Place and causes of acute cardiovascular mortality during the COVID19 pandemic: retrospective cohort study of 580,972 deaths in England and Wales, 2014 to 2020", + "authors": "Jianhua Wu; Mamas Mamas; Mohamed Mohamed; Chun Shing Kwok; Chris Roebuck; Ben Humberstone; Tom Denwood; Tom Luescher; Mark De Belder; John Deanfield; Chris Gale", + "affiliations": "University of Leeds; Keele University; Keele University; Keele University; NHS Digital; ONS; NHS Digital; Imperial College; Barts Health NHS Trust; UCL; University of Leeds", + "abstract": "ImportanceThe COVID-19 pandemic has resulted in a decline in admissions with cardiovascular (CV) emergencies. The fatal consequences of this are unknown.\n\nObjectivesTo describe the place and causes of acute CV death during the COVID-19 pandemic.\n\nDesignRetrospective nationwide cohort.\n\nSettingEngland and Wales.\n\nParticipantsAll adult (age [≥]18 years) acute CV deaths (n=580,972) between 1st January 2014 and 2nd June 2020.\n\nExposureThe COVID-19 pandemic (defined as from the onset of the first COVID-19 death in England on 2nd March 2020).\n\nMain outcomesPlace (hospital, care home, home) and acute CV events directly contributing to death as stated on the first part of the Medical Certificate of Cause of Death.\n\nResultsAfter 2nd March 2020, there were 22,820 acute CV deaths of which 5.7% related to COVID-19, and an excess acute CV mortality of 1752 (+8%) compared with the expected daily deaths in the same period. Deaths in the community accounted for nearly half of all deaths during this period. Care homes had the greatest increase in excess acute CV deaths (1065, +40%), followed by deaths at home (1728, +34%) and in hospital (57, +0%). The most frequent cause of acute CV death during this period was stroke (8,290, 36.3%), followed by acute coronary syndrome (ACS) (5,532, 24.2%), heart failure (5,280, 23.1%), pulmonary embolism (2,067, 9.1%) and cardiac arrest (1,037, 4.5%). Deep vein thrombosis had the greatest increase in cause of excess acute CV death (18, +25%), followed pulmonary embolism (340, +19%) and stroke (782, +10%). The greatest cause of excess CV death in care homes was stroke (700, +48%), compared with cardiac arrest (80, +56%) at home, and pulmonary embolism (126, +14%) and cardiogenic shock (41, +14%) in hospital.\n\nConclusions and relevanceThe COVID-19 pandemic has resulted in an inflation in acute CV deaths above that expected for the time of year, nearly half of which occurred in the community. The most common cause of acute CV death was stroke followed by acute coronary syndrome and heart failure. This is key information to optimise messaging to the public and enable health resource planning.", + "category": "cardiovascular medicine", + "match_type": "fuzzy", + "author_similarity": 100, + "affiliation_similarity": 100 + }, { "site": "medRxiv", "doi": "10.1101/2020.07.14.20152629", @@ -9379,6 +9309,20 @@ "author_similarity": 100, "affiliation_similarity": 100 }, + { + "site": "medRxiv", + "doi": "10.1101/2020.05.12.20098921", + "date": "2020-05-18", + "link": "https://medrxiv.org/cgi/content/short/2020.05.12.20098921", + "title": "Behavioural change towards reduced intensity physical activity is disproportionately prevalent among adults with serious health issues or self-perception of high risk during the UK COVID-19 lockdown.", + "authors": "Nina Trivedy Rogers; Naomi Waterlow; Hannah E Brindle; Luisa Enria; Rosalind M Eggo; Shelley Lees; Chrissy h Roberts", + "affiliations": "University College London (UCL); London School of Hygiene & Tropical Medicine; London School of Hygiene & Tropical Medicine; University of Bath; London School of Hygiene & Tropical Medicine; London School of Hygiene & Tropical Medicine; London School of Hygiene & Tropical Medicine", + "abstract": "ImportanceThere are growing concerns that the UK COVID-19 lockdown has reduced opportunities to maintain health through physical activity, placing individuals at higher risk of chronic disease and leaving them more vulnerable to severe sequelae of COVID-19.\n\nObjectiveTo examine whether the UKs lockdown measures have had disproportionate impacts on intensity of physical activity in groups who are, or who perceive themselves to be, at heightened risk from COVID-19.\n\nDesigns, Setting, ParticipantsUK-wide survey of adults aged over 20, data collected between 2020-04-06 and 2020-04-22.\n\nExposuresSelf-reported doctor-diagnosed obesity, hypertension, type I/II diabetes, lung disease, cancer, stroke, heart disease. Self-reported disabilities and depression. Sex, gender, educational qualifications, household income, caring for school-age children. Narrative data on coping strategies.\n\nMain Outcomes and MeasuresChange in physical activity intensity after implementation of UK COVID-19 lockdown (self-reported).\n\nResultsMost (60%) participants achieved the same level of intensity of physical activity during the lockdown as before the epidemic. Doing less intensive physical activity during the lockdown was associated with obesity (OR 1.21, 95% CI 1.02-1.41), hypertension (OR 1.52, 1.33-1.71), lung disease (OR 1.31,1.13-1.49), depression (OR 2.02, 1.82-2.22) and disability (OR 2.34, 1.99-2.69). Participants who reduced their physical activity intensity also had higher odds of being female, living alone or having no garden, and more commonly expressed sentiments about personal or household risks in narratives on coping.\n\nConclusions and relevanceGroups who reduced physical activity intensity included disproportionate numbers of people with either heightened objective clinical risks or greater tendency to express subjective perceptions of risk. Policy on exercise for health during lockdowns should include strategies to facilitate health promoting levels of physical activity in vulnerable groups, including those with both objective and subjective risks.", + "category": "infectious diseases", + "match_type": "fuzzy", + "author_similarity": 100, + "affiliation_similarity": 100 + }, { "site": "medRxiv", "doi": "10.1101/2020.05.09.20082909", @@ -9575,20 +9519,6 @@ "author_similarity": 100, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2020.05.06.20092999", - "date": "2020-05-07", - "link": "https://medrxiv.org/cgi/content/short/2020.05.06.20092999", - "title": "OpenSAFELY: factors associated with COVID-19-related hospital death in the linked electronic health records of 17 million adult NHS patients.", - "authors": "- The OpenSAFELY Collaborative; Elizabeth Williamson; Alex J Walker; Krishnan J Bhaskaran; Seb Bacon; Chris Bates; Caroline E Morton; Helen J Curtis; Amir Mehrkar; David Evans; Peter Inglesby; Jonathan Cockburn; Helen I Mcdonald; Brian MacKenna; Laurie Tomlinson; Ian J Douglas; Christopher T Rentsch; Rohini Mathur; Angel Wong; Richard Grieve; David Harrison; Harriet Forbes; Anna Schultze; Richard T Croker; John Parry; Frank Hester; Sam Harper; Rafael Perera; Stephen Evans; Liam Smeeth; Ben Goldacre", - "affiliations": "; London School of Hygiene and Tropical Medicine; University of Oxford; London School of Hygiene and Tropical Medicine; University of Oxford; TPP; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; TPP; London School of Hygiene and Tropical Medicine; University of Oxford; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; ICNARC; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; University of Oxford; TPP; TPP; TPP; University of Oxford; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; University of Oxford", - "abstract": "BackgroundEstablishing who is at risk from a novel rapidly arising cause of death, and why, requires a new approach to epidemiological research with very large datasets and timely data. Working on behalf of NHS England we therefore set out to deliver a secure and pseudonymised analytics platform inside the data centre of a major primary care electronic health records vendor establishing coverage across detailed primary care records for a substantial proportion of all patients in England. The following results are preliminary.\n\nData sourcesPrimary care electronic health records managed by the electronic health record vendor TPP, pseudonymously linked to patient-level data from the COVID-19 Patient Notification System (CPNS) for death of hospital inpatients with confirmed COVID-19, using the new OpenSAFELY platform.\n\nPopulation17,425,445 adults.\n\nTime period1st Feb 2020 to 25th April 2020.\n\nPrimary outcomeDeath in hospital among people with confirmed COVID-19.\n\nMethodsCohort study analysed by Cox-regression to generate hazard ratios: age and sex adjusted, and multiply adjusted for co-variates selected prospectively on the basis of clinical interest and prior findings.\n\nResultsThere were 5683 deaths attributed to COVID-19. In summary after full adjustment, death from COVID-19 was strongly associated with: being male (hazard ratio 1.99, 95%CI 1.88-2.10); older age and deprivation (both with a strong gradient); uncontrolled diabetes (HR 2.36 95% CI 2.18-2.56); severe asthma (HR 1.25 CI 1.08-1.44); and various other prior medical conditions. Compared to people with ethnicity recorded as white, black people were at higher risk of death, with only partial attenuation in hazard ratios from the fully adjusted model (age-sex adjusted HR 2.17 95% CI 1.84-2.57; fully adjusted HR 1.71 95% CI 1.44-2.02); with similar findings for Asian people (age-sex adjusted HR 1.95 95% CI 1.73-2.18; fully adjusted HR 1.62 95% CI 1.431.82).\n\nConclusionsWe have quantified a range of clinical risk factors for death from COVID-19, some of which were not previously well characterised, in the largest cohort study conducted by any country to date. People from Asian and black groups are at markedly increased risk of in-hospital death from COVID-19, and contrary to some prior speculation this is only partially attributable to pre-existing clinical risk factors or deprivation; further research into the drivers of this association is therefore urgently required. Deprivation is also a major risk factor with, again, little of the excess risk explained by co-morbidity or other risk factors. The findings for clinical risk factors are concordant with policies in the UK for protecting those at highest risk. Our OpenSAFELY platform is rapidly adding further NHS patients records; we will update and extend these results regularly.", - "category": "epidemiology", - "match_type": "fuzzy", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2020.05.02.20078642", @@ -9925,20 +9855,6 @@ "author_similarity": 100, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2020.04.02.20051284", - "date": "2020-04-06", - "link": "https://medrxiv.org/cgi/content/short/2020.04.02.20051284", - "title": "Building an International Consortium for Tracking Coronavirus Health Status", - "authors": "Eran Segal; Feng Zhang; Xihong Lin; Gary King; Ophir Shalem; Smadar Shilo; William E. Allen; Yonatan H. Grad; Casey S. Greene; Faisal Alquaddoomi; Simon Anders; Ran Balicer; Tal Bauman; Ximena Bonilla; Gisel Booman; Andrew T. Chan; Ori Ori Cohen; Silvano Coletti; Natalie Davidson; Yuval Dor; David A. Drew; Olivier Elemento; Georgina Evans; Phil Ewels; Joshua Gale; Amir Gavrieli; Benjamin Geiger; Iman Hajirasouliha; Roman Jerala; Andre Kahles; Olli Kallioniemi; Ayya Keshet; Gregory Landua; Tomer Meir; Aline Muller; Long H. Nguyen; Matej Oresic; Svetlana Ovchinnikova; Hedi Peterson; Jay Rajagopal; Gunnar Ratsch; Hagai Rossman; Johan Rung; Andrea Sboner; Alexandros Sigaras; Tim Spector; Ron Steinherz; Irene Stevens; Jaak Vilo; Paul Wilmes; CCC (Coronavirus Census Collective)", - "affiliations": "Weizmann Institute of Science; Howard Hughes Medical Institute, Core Member, Broad Institute of MIT and Harvard, United States; Departments of Biostatistics and Statistics, Harvard T.H. Chan School of Public Health; Albert J. Weatherhead III University, Institute for Quantitative Social Science, Harvard University; Department of Genetics, Perelman School of Medicine, University of Pennsylvania, United States; Department of Computer Science and Applied Mathematics, and Department of Molecular Cell Biology, Weizmann Institute of Science, Israel; Society of Fellows, Harvard University, United States; Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, United States; Department of Systems Pharmacology and Translational Therapeutics, Perelman School of Medicine, University of Pennsylvania, United States; ETH Zurich, NEXUS Personalized Health Technologies, Zurich, Switzerland; Center for Molecular Biology (ZMBH), University of Heidelberg, Germany; Clalit Research Institute, Clalit Health Services, Israel; Mapping and Geo-Information Engineering, Civil and Environmental Engineering Faculty, The Technion, Israel; ETH Zurich, Department for Computer Science, Zurich, University Hospital Zurich, Medical Informatics, Zurich and SIB Swiss Institute of Bioinformatics, Zurich, ; Regen Network, Argentina; Massachusetts General Hospital (MGH), United States; Department of Computer Science and Applied Mathematics, and Department of Molecular Cell Biology, Weizmann Institute of Science, Israel; Chelonia Applied Science, Switzerland; ETH Zurich, Department for Computer Science, Zurich, University Hospital Zurich, Medical Informatics, Zurich and SIB Swiss Institute of Bioinformatics, Zurich, ; School of Medicine-IMRIC-Developmental Biology and Cancer Research, The Hebrew University; Massachusetts General Hospital (MGH), United States; Englander Institute for Precision Medicine and Department of Physiology and Biophysics, Weill Cornell Medicine, USA; Institute for Quantitative Social Science, Harvard University; Science for Life Laboratory (SciLifeLab), Department of Biochemistry and Biophysics, Stockholm University, Sweden; symptometrics.org; Department of Computer Science and Applied Mathematics, and Department of Molecular Cell Biology, Weizmann Institute of Science, Israel; Department of immunology, Weizmann Institute of Science, Israel; Englander Institute for Precision Medicine and Department of Physiology and Biophysics, Weill Cornell Medicine, USA; Department of Synthetic biology and Immunology, National Institute of Chemistry, Slovenia; ETH Zurich, Department for Computer Science, Zurich, University Hospital Zurich, Medical Informatics, Zurich and SIB Swiss Institute of Bioinformatics, Zurich, ; Science for Life Laboratory (SciLifeLab), Department of Oncology and Pathology, Karolinska Institutet, Stockholm, Sweden; Department of Computer Science and Applied Mathematics, and Department of Molecular Cell Biology, Weizmann Institute of Science, Israel; Regen Network, United States; Department of Computer Science and Applied Mathematics, and Department of Molecular Cell Biology, Weizmann Institute of Science, Israel; Luxembourg Institute of Socio-Economic Research and University of Luxembourg, Luxembourg; Massachusetts General Hospital (MGH), United States; School of Medical Sciences, Orebro University, Orebro, Sweden, and Turku Bioscience Centre, University of Turku and Abo Akademi University, Turku, Finland; Center for Molecular Biology (ZMBH), University of Heidelberg, Germany; Institute of Computer Science, University of Tartu, Estonia, Estonia; Internal Medicine, Harvard Medical School, Department of Pulmonary Medicine and Critical Care, Massachusetts General Hospital (MGH), United States; ETH Zurich, Department for Computer Science, Zurich, University Hospital Zurich, Medical Informatics, Zurich and SIB Swiss Institute of Bioinformatics, Zurich a; Department of Computer Science and Applied Mathematics, and Department of Molecular Cell Biology, Weizmann Institute of Science, Israel; Science for Life Laboratory (SciLifeLab), Department of Immunology, Genetics and Pathology, Uppsala university, Sweden; Englander Institute for Precision Medicine and Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, USA; Englander Institute for Precision Medicine and Department of Physiology and Biophysics, Weill Cornell Medicine, USA; Kings College, United Kingdom; Regen Network, United States; Science for Life Laboratory (SciLifeLab), Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet, Sweden; Institute of Computer Science, University of Tartu, Estonia, Estonia; Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Luxembourg; ", - "abstract": "Information is the most potent protective weapon we have to combat a pandemic, at both the individual and global level. For individuals, information can help us make personal decisions and provide a sense of security. For the global community, information can inform policy decisions and offer critical insights into the epidemic of COVID-19 disease. Fully leveraging the power of information, however, requires large amounts of data and access to it. To achieve this, we are making steps to form an international consortium, Coronavirus Census Collective (CCC, coronaviruscensuscollective.org), that will serve as a hub for integrating information from multiple data sources that can be utilized to understand, monitor, predict, and combat global pandemics. These sources may include self-reported health status through surveys (including mobile apps), results of diagnostic laboratory tests, and other static and real-time geospatial data. This collective effort to track and share information will be invaluable in predicting hotspots of disease outbreak, identifying which factors control the rate of spreading, informing immediate policy decisions, evaluating the effectiveness of measures taken by health organizations on pandemic control, and providing critical insight on the etiology of COVID-19. It will also help individuals stay informed on this rapidly evolving situation and contribute to other global efforts to slow the spread of disease.\n\nIn the past few weeks, several initiatives across the globe have surfaced to use daily self-reported symptoms as a means to track disease spread, predict outbreak locations, guide population measures and help in the allocation of healthcare resources. The aim of this paper is to put out a call to standardize these efforts and spark a collaborative effort to maximize the global gain while protecting participant privacy.", - "category": "infectious diseases", - "match_type": "fuzzy", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2020.04.01.20049908", @@ -10037,6 +9953,20 @@ "author_similarity": 100, "affiliation_similarity": 100 }, + { + "site": "medRxiv", + "doi": "10.1101/2020.03.10.20033761", + "date": "2020-03-13", + "link": "https://medrxiv.org/cgi/content/short/2020.03.10.20033761", + "title": "Inferring the number of COVID-19 cases from recently reported deaths", + "authors": "Thibaut Jombart; Kevin van Zandvoort; Tim Russell; Christopher Jarvis; Amy Gimma; Sam Abbott; Samuel Clifford; Sebastian Funk; Hamish Gibbs; Yang Liu; Carl Pearson; Nikos Bosse; Centre for the Mathematical Modelling of Infectious Diseases COVID-19 Working Group; Rosalind M Eggo; Adam J Kucharski; John Edmunds", + "affiliations": "London School of Hygiene and Tropical Medicine (LSHTM); London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene & Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; ; London School of Hygiene & Tropical Medicine; London School of Hygiene & Tropical Medicine; London School of Hygiene and Tropical Medicine", + "abstract": "We estimate the number of COVID-19 cases from newly reported deaths in a population without previous reports. Our results suggest that by the time a single death occurs, hundreds to thousands of cases are likely to be present in that population. This suggests containment via contact tracing will be challenging at this point, and other response strategies should be considered. Our approach is implemented in a publicly available, user-friendly, online tool.", + "category": "epidemiology", + "match_type": "fuzzy", + "author_similarity": 100, + "affiliation_similarity": 100 + }, { "site": "medRxiv", "doi": "10.1101/2020.03.09.20033050", diff --git a/data/covid/raw-preprints.json b/data/covid/raw-preprints.json index e351796f..f300661b 100644 --- a/data/covid/raw-preprints.json +++ b/data/covid/raw-preprints.json @@ -3500,7 +3500,7 @@ "rel_date": "2023-11-22", "rel_site": "bioRxiv", "rel_link": "https://biorxiv.org/cgi/content/short/2023.11.22.567964", - "rel_abs": "Coronavirus genomes sequester their start codons within stem-loop 5 (SL5), a structured, 5 genomic RNA element. In most alpha-and betacoronaviruses, the secondary structure of SL5 is predicted to contain a four-way junction of helical stems, some of which are capped with UUYYGU hexaloops. Here, using cryogenic electron microscopy (cryo-EM) and computational modeling with biochemically-determined secondary structures, we present three-dimensional structures of SL5 from six coronaviruses. The SL5 domain of betacoronavirus SARS-CoV-2, resolved at 4.7 [A] resolution, exhibits a T-shaped structure, with its UUYYGU hexaloops at opposing ends of a coaxial stack, the Ts \"bar.\" Further analysis of SL5 domains from SARS-CoV-1 and MERS (7.1 and 6.4-6.9 [A] resolution, respectively) indicate that the junction geometry and inter-hexaloop distances are conserved features across the studied human-infecting betacoronaviruses. The MERS SL5 domain displays an additional tertiary interaction, which is also observed in the non-human-infecting betacoronavirus BtCoV-HKU5 (5.9-8.0 [A] resolution). SL5s from human-infecting alphacoronaviruses, HCoV-229E and HCoV-NL63 (6.5 and 8.4-9.0 [A] resolution, respectively), exhibit the same coaxial stacks, including the UUYYGU-capped bar, but with a phylogenetically distinct crossing angle, an X-shape. As such, all herein studied SL5 domains fold into stable tertiary structures with cross-genus similarities, with implications for potential protein-binding modes and future therapeutic targets.\n\nSignificanceThe three-dimensional structures of viral RNAs are of interest to the study of viral pathogenesis and therapeutic design, but the three-dimensional structures of viral RNAs remain poorly characterized. Here, we provide the first 3D structures of the SL5 domain (124-160 nt, 40.0-51.4 kDa) from the majority of human-infecting coronaviruses. All studied SL5s exhibit a similar 4-way junction, with their crossing angles grouped along phylogenetic boundaries. Further, across all species studied, conserved UUYYGU hexaloop pairs are located at opposing ends, suggesting that their three-dimensional arrangement is important for their as-of-yet unknown function. These conserved tertiary features support the relevance of SL5 for pan-coronavirus fitness and highlight new routes in understanding its molecular and virological roles and in developing SL5-based antivirals.", + "rel_abs": "Coronavirus genomes sequester their start codons within stem-loop 5 (SL5), a structured, 5' genomic RNA element. In most alpha- and betacoronaviruses, the secondary structure of SL5 is predicted to contain a four-way junction of helical stems, some of which are capped with UUYYGU hexaloops. Here, using cryogenic electron microscopy (cryo-EM) and computational modeling with biochemically-determined secondary structures, we present three-dimensional structures of SL5 from six coronaviruses. The SL5 domain of betacoronavirus SARS-CoV-2, resolved at 4.7 [A] resolution, exhibits a T-shaped structure, with its UUYYGU hexaloops at opposing ends of a coaxial stack, the Ts \"arms.\" Further analysis of SL5 domains from SARS-CoV-1 and MERS (7.1 and 6.4-6.9 [A] resolution, respectively) indicate that the junction geometry and inter-hexaloop distances are conserved features across the studied human-infecting betacoronaviruses. The MERS SL5 domain displays an additional tertiary interaction, which is also observed in the non-human-infecting betacoronavirus BtCoV-HKU5 (5.9-8.0 [A] resolution). SL5s from human-infecting alphacoronaviruses, HCoV-229E and HCoV-NL63 (6.5 and 8.4-9.0 [A] resolution, respectively), exhibit the same coaxial stacks, including the UUYYGU-capped arms, but with a phylogenetically distinct crossing angle, an X-shape. As such, all SL5 domains studied herein fold into stable tertiary structures with cross-genus similarities, with implications for potential protein-binding modes and therapeutic targets.\n\nSignificanceThe three-dimensional structures of viral RNAs are of interest to the study of viral pathogenesis and therapeutic design, but the three-dimensional structures of viral RNAs remain poorly characterized. Here, we provide the first 3D structures of the SL5 domain (124-160 nt, 40.0-51.4 kDa) from the majority of human-infecting coronaviruses. All studied SL5s exhibit a similar 4-way junction, with their crossing angles grouped along phylogenetic boundaries. Further, across all species studied, conserved UUYYGU hexaloop pairs are located at opposing ends of a coaxial stack, suggesting that their three-dimensional arrangement is important for their as-of-yet defined function. These conserved tertiary features support the relevance of SL5 for pan-coronavirus fitness and highlight new routes in understanding its molecular and virological roles and in developing SL5-based antivirals.\n\nClassification: Biological Sciences, Biophysics and Computational Biology", "rel_num_authors": 10, "rel_authors": [ { @@ -23850,7 +23850,7 @@ "rel_date": "2023-09-25", "rel_site": "medRxiv", "rel_link": "https://medrxiv.org/cgi/content/short/2023.09.22.23295541", - "rel_abs": "Our understanding of the quality of cellular and humoral immunity conferred by COVID-19 vaccination alone versus vaccination plus SARS-CoV-2 breakthrough (BT) infection remains incomplete. While the current (2023) SARS-CoV-2 immune landscape of Canadians is complex, in late 2021 most Canadians had either just received a third dose of COVID-19 vaccine, or had received their two dose primary series and then experienced an Omicron BT. Herein we took advantage of this coincident timing to contrast cellular and humoral immunity conferred by three doses of vaccine versus two doses plus BT. Our results show that mild BT infection induces cell-mediated immune responses to variants comparable to an intramuscular vaccine booster dose. In contrast, BT subjects had higher salivary IgG and IgA levels against the Omicron Spike and enhanced reactivity to the ancestral Spike for the IgA isotype, which also reacted with SARS-CoV-1. Serum neutralizing antibody levels against the ancestral strain and the variants were also higher after BT infection. Our results support the need for mucosal vaccines to emulate the enhanced mucosal and humoral immunity induced by Omicron without exposing individuals to the risks associated with SARS-CoV-2 infection.\n\nONE SENTENCE SUMMARYOmicron breakthrough elicits cross-reactive systemic and mucosal immune responses in fully vaccinated adults.\n\nGraphical Abstract\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=119 SRC=\"FIGDIR/small/23295541v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (27K):\norg.highwire.dtl.DTLVardef@848618org.highwire.dtl.DTLVardef@7fb9edorg.highwire.dtl.DTLVardef@187a713org.highwire.dtl.DTLVardef@e9da69_HPS_FORMAT_FIGEXP M_FIG C_FIG", + "rel_abs": "Our understanding of the quality of cellular and humoral immunity conferred by COVID-19 vaccination alone versus vaccination plus SARS-CoV-2 breakthrough (BT) infection remains incomplete. While the current (2023) SARS-CoV-2 immune landscape of Canadians is complex, in late 2021 most Canadians had either just received a third dose of COVID-19 vaccine, or had received their two dose primary series and then experienced an Omicron BT. Herein we took advantage of this coincident timing to contrast cellular and humoral immunity conferred by three doses of vaccine versus two doses plus BT. Our results show that mild BT infection induces cell-mediated immune responses to variants comparable to an intramuscular vaccine booster dose. In contrast, BT subjects had higher salivary IgG and IgA levels against the Omicron Spike and enhanced reactivity to the ancestral Spike for the IgA isotype, which also reacted with SARS-CoV-1. Serum neutralizing antibody levels against the ancestral strain and the variants were also higher after BT infection. Our results support the need for mucosal vaccines to emulate the enhanced mucosal and humoral immunity induced by Omicron without exposing individuals to the risks associated with SARS-CoV-2 infection.\n\nONE SENTENCE SUMMARYOmicron breakthrough elicits cross-reactive systemic and mucosal immune responses in fully vaccinated adults.\n\nGraphical Abstract\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=119 SRC=\"FIGDIR/small/23295541v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (27K):\norg.highwire.dtl.DTLVardef@eacaa1org.highwire.dtl.DTLVardef@9d260aorg.highwire.dtl.DTLVardef@12c6933org.highwire.dtl.DTLVardef@ae9c13_HPS_FORMAT_FIGEXP M_FIG C_FIG", "rel_num_authors": 22, "rel_authors": [ { @@ -45911,6 +45911,65 @@ "type": "new results", "category": "synthetic biology" }, + { + "rel_doi": "10.1101/2023.07.27.550811", + "rel_title": "Butyrate Protects against SARS-CoV-2-induced Tissue Damage in Golden Hamsters.", + "rel_date": "2023-07-28", + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2023.07.27.550811", + "rel_abs": "Butyrate, produced by gut microbe during dietary fiber fermentation, plays anti-inflammatory and antioxidant effects in chronic inflammation diseases, yet it remains to be explored whether butyrate has protective effects against viral infections. Here, we demonstrated that butyrate alleviated tissue injury in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-infected golden hamsters with supplementation of butyrate before and during the infection. Butyrate-treated hamsters showed augmentation of type I interferon (IFN) response and activation of endothelial cells without exaggerated inflammation. In addition, butyrate regulated redox homeostasis by enhancing the activity of superoxide dismutase (SOD) to inhibit excessive apoptotic cell death. Therefore, butyrate exhibited an effective prevention against SARS-CoV-2 by upregulating antiviral immune responses and promoting cell survival.\n\nIMPORTANCESince SARS-CoV-2 has caused severe disease characterized by acute respiratory distress syndrome (ARDS) in humans, it is essential to develop therapeutics based on relieving such severe clinical symptoms. Current therapy strategies mainly focus on individuals who have COVID-19, however, there is still a strong need for prevention and treatment of SARS-CoV-2 infection. This study showed that butyrate, a bacterial metabolite, improved the response of SARS-CoV-2-infected hamsters by reducing immunopathology caused by impaired antiviral defenses and inhibiting excessive apoptosis through reduction in oxidative stress.", + "rel_num_authors": 11, + "rel_authors": [ + { + "author_name": "Huan Yu", + "author_inst": "Shantou University" + }, + { + "author_name": "Lunzhi Yuan", + "author_inst": "Xiamen University" + }, + { + "author_name": "Zhigang Yan", + "author_inst": "Shantou University Medical College" + }, + { + "author_name": "Ming Zhou", + "author_inst": "Xiamen University" + }, + { + "author_name": "Jianghui Ye", + "author_inst": "Xiamen University" + }, + { + "author_name": "Kun Wu", + "author_inst": "Xiamen University" + }, + { + "author_name": "Wenjia Chen", + "author_inst": "Shantou University Medical College" + }, + { + "author_name": "Rirong Chen", + "author_inst": "Shantou University Medical College" + }, + { + "author_name": "Ning-Shao Xia", + "author_inst": "Xiamen University" + }, + { + "author_name": "Yi Guan", + "author_inst": "State Key Laboratory of Emerging Infectious Diseases (SKLEID), School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong" + }, + { + "author_name": "Huachen Zhu", + "author_inst": "The University of Hong Kong" + } + ], + "version": "1", + "license": "cc_by_nc_nd", + "type": "new results", + "category": "microbiology" + }, { "rel_doi": "10.1101/2023.07.26.550755", "rel_title": "New design strategies for ultra-specific CRISPR-Cas13a-based RNA-diagnostic tools with single-nucleotide mismatch sensitivity", @@ -47571,91 +47630,51 @@ "category": "psychiatry and clinical psychology" }, { - "rel_doi": "10.1101/2023.07.23.23293040", - "rel_title": "Impact of Emerging COVID-19 variants on psychosocial health: A Systematic Review", + "rel_doi": "10.1101/2023.07.24.23293059", + "rel_title": "Temporal changes in the positivity rate of common enteric viruses among paediatric admissions in coastal Kenya, in the period spanning the COVID-19 pandemic, 2019-2022", "rel_date": "2023-07-24", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.07.23.23293040", - "rel_abs": "BackgroundThe COVID-19 pandemic has had significant psychological effects on individuals and communities around the world. Studies have found that the prevalence of anxiety and depression symptoms increased significantly during the pandemic. The goal of the study is to understand how the emerging new virus variants keep the world in a state of fear and the ways in which mental health measures can be implemented and adopted to alleviate anxiety.\n\nMethodsA broad search for observational studies were carried out in Pubmed, Google Scholar, Clinical Key, and World Medical Library. Studies that reported and/or related the existence of anxiety generated by suffering or not from diseases caused by the new emerging Covid-19 viruses and that for which the full text of the article was accessible were included in the study while systematic review and meta-analysis and studies in groups were excluded.\n\nResults22 studies were included in the review. The deleterious psychosocial effects were the restructuring of life, establishment of unhealthy habits, emergence of \"corona phobia\", fear and stigma of being afflicted with the disease and spreading it to loved ones, and lack of contact with others. Increased rates of depression and anxiety were also seen. The circulating variants responsible for these main psychosocial repercussions were: Epsilon, Zeta, Eta, Iota, Kappa, Alpha, Beta, Gamma, and Delta. Social support was found to be protective.\n\nConclusionHence interventions targeted at promoting mental health should be considered a public health priority.", - "rel_num_authors": 18, + "rel_link": "https://medrxiv.org/cgi/content/short/2023.07.24.23293059", + "rel_abs": "BackgroundThe non-pharmaceutical interventions (NPIs) implemented to curb the spread of SARS-CoV-2 early in the COVID-19 pandemic years, disrupted the activity of other respiratory viruses. There is limited data from low-and-middle income countries (LMICs) to determine whether COVID-19 NPIs also impacted the epidemiology of enteric viruses. We investigated the changes in infection patterns of common enteric viruses among hospitalised children who presented with diarrhoea to a referral hospital in coastal Kenya, in the period spanning the COVID-19 pandemic.\n\nMethodsA total of 870 stool samples from children under 13 years of age admitted to Kilifi County Hospital between January 2019, and December 2022 were screened for rotavirus group A (RVA), norovirus genogroup II (GII), astrovirus, sapovirus, and adenovirus type F40/41 using real-time reverse-transcription polymerase chain reaction. The proportions positive across the four years were compared using the chi-squared test statistic.\n\nResultsOne or more of the five virus targets were detected in 282 (32.4%) cases. A reduction in the positivity rate of RVA cases was observed from 2019 (12.1%, 95% confidence interval (CI) 8.7% - 16.2%) to 2020 (1.7%, 95% CI 0.2% - 6.0%; p < 0.001). However, in the 2022, RVA positivity rate rebounded to 23.5% (95% CI 18.2% - 29.4%). For norovirus GII, the positivity rate fluctuated over the four years with its highest positivity rate observed in 2020 (16.2%; 95% C.I, 10.0% - 24.1%). No astrovirus cases were detected in 2020 and 2021, but the positivity rate in 2022 was similar to that in 2019 (3.1% (95% CI 1.5% - 5.7%) vs 3.3% (95% CI 1.4% - 6.5%)). A higher case fatality rate was observed in 2021 (9.0%) compared to the 2019 (3.2%), 2020 (6.8%) and 2022 (2.1%) (p <0.001).\n\nConclusionOur study finds that in 2020 the transmission of common enteric viruses, especially RVA and astrovirus, in Kilifi Kenya may have been disrupted due to the COVID-19 NPIs. After 2020, local enteric virus transmission patterns appeared to return to pre-pandemic levels coinciding with the removal of most of the government COVID-19 NPIs.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Pratyush Kumar", - "author_inst": "Dr Baba Saheb Ambedkar Medical College and Hospital, Delhi, India" + "author_name": "ARNOLD W. LAMBISIA", + "author_inst": "Kenya Medical Research Institute-Wellcome Trust Research Programme (KWTRP), P.O Box 230-80108 Kilifi, Kenya." }, { - "author_name": "Manali Sarkar", - "author_inst": "MGM MEDICAL COLLEGE NAVI MUMBAI" - }, - { - "author_name": "Morales Femenias Yurkina", - "author_inst": "Logopedia and Phoniatrics Department. Provincial General Teaching Hospital Dr. Antonio Luaces Iraola." - }, - { - "author_name": "Ramya Gnanaraj", - "author_inst": "Madras Medical College, Chennai, India" - }, - { - "author_name": "Daniel Jesus Garcia Martinez", - "author_inst": "Francisco De Vitoria University, Madrid, Spain" - }, - { - "author_name": "Yhojar A. Pisfil-Farronay", - "author_inst": "Emerge, Unidad de Investigacion en Enfermedades Emergentes y Cambio Climatico, Facultad de Salud Publica y Administracion, Universidad Peruana Cayetano Heredia," - }, - { - "author_name": "Laxmi Chaudhary", - "author_inst": "Casualty Medical Officer (CMO), Dr. Baba Saheb Ambedkar Medical College & Hospital, Delhi, India" - }, - { - "author_name": "Poonam Agrawal", - "author_inst": "Dr Baba Saheb Ambedkar Medical College and Hospital, Delhi, India" - }, - { - "author_name": "G P Kaushal", - "author_inst": "Dr Baba Saheb Ambedkar Medical College and Hospital, Delhi, India" - }, - { - "author_name": "Matthew Mbwogge", - "author_inst": "London School of Hygiene & Tropical Medicine" - }, - { - "author_name": "Kumar Abhishek", - "author_inst": "Dr Baba Saheb Ambedkar Medical College and Hospital, Delhi, India" - }, - { - "author_name": "Muhannad Alnaasan", - "author_inst": "University of Aleppo faculty of medicine" + "author_name": "Nickson Murunga", + "author_inst": "Kenya Medical Research Institute-Wellcome Trust Research Programme (KWTRP), P.O Box 230-80108 Kilifi, Kenya." }, { - "author_name": "Maximiliano Ezequiel Arlettaz", - "author_inst": "National University of Entre Rios, Argentina" + "author_name": "Martin Mutunga", + "author_inst": "Kenya Medical Research Institute-Wellcome Trust Research Programme (KWTRP), P.O Box 230-80108 Kilifi, Kenya." }, { - "author_name": "Reem Kozum", - "author_inst": "Aleppo University Hospital" + "author_name": "Robison Cheruiyot", + "author_inst": "Kenya Medical Research Institute-Wellcome Trust Research Programme (KWTRP), P.O Box 230-80108 Kilifi, Kenya." }, { - "author_name": "Miguel Fernando Juarez Moyron", - "author_inst": "National Autonomous University of Mexico" + "author_name": "Grace Maina", + "author_inst": "Kenya Medical Research Institute-Wellcome Trust Research Programme (KWTRP), P.O Box 230-80108 Kilifi, Kenya." }, { - "author_name": "Suhrud Panchawagh", - "author_inst": "Smt. Kashibai Navale Medical College & General Hospital, Pune" + "author_name": "TIMOTHY O. MAKORI", + "author_inst": "Kenya Medical Research Institute-Wellcome Trust Research Programme (KWTRP), P.O Box 230-80108 Kilifi, Kenya." }, { - "author_name": "Asmitha P Reddy", - "author_inst": "Father Muller Medical College, Mangalore, India" + "author_name": "D. James Nokes", + "author_inst": "1. Kenya Medical Research Institute-Wellcome Trust Research Programme (KWTRP), P.O Box 230-80108 Kilifi, Kenya." }, { - "author_name": "Vishnu B Unnithan", - "author_inst": "Seth GS Medical College and KEM Hospital, Mumbai, India." + "author_name": "Charles N Agoti", + "author_inst": "Kenya Medical Research Institute-Wellcome Trust Research Programme (KWTRP), P.O Box 230-80108 Kilifi, Kenya" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "psychiatry and clinical psychology" + "category": "gastroenterology" }, { "rel_doi": "10.1101/2023.07.20.23292983", @@ -49105,51 +49124,71 @@ "category": "biophysics" }, { - "rel_doi": "10.1101/2023.07.20.549891", - "rel_title": "No evidence for the association between COVID-19 and neuroinflammation: A diffusion basis spectrum imaging study.", + "rel_doi": "10.1101/2023.07.19.549731", + "rel_title": "Complete Protection from SARS-CoV-2 Lung Infection in Mice Through Combined Intranasal Delivery of PIKfyve Kinase and TMPRSS2 Protease Inhibitors", "rel_date": "2023-07-20", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2023.07.20.549891", - "rel_abs": "COVID-19 remains a significant international public health concern, with its underlying mechanisms not yet fully elucidated. Recent studies suggest the potential for SARS-CoV-2 infection to induce prolonged inflammation within the central nervous system. However, the evidence primarily stems from limited small-scale case investigations. To address this gap, our study capitalized on longitudinal data from the UK Biobank. This dataset encompassed pre- and post-COVID-19 neuroimaging data from a cohort of 416 individuals (Mage=58.6; n=244 female), including 224 COVID-19 cases (Mage=59.1; n=122 females). Employing an innovative non-invasive Diffusion Basis Spectrum Imaging (DBSI) technique, we calculated putative indicators of neuroinflammation (DBSI-RF) for both gray matter structures and white matter tracts in the brain. We hypothesized that SARS-CoV-2 infection would be associated with elevated DBSI-RF and conducted linear regression analyses with adjustment for age, sex, race, body mass index, smoking frequency, and data acquisition interval. After multiple testing correction using false discovery rate, no statistically significant associations emerged between COVID-19 and neuroinflammation variability (all pFDR>0.05). Nevertheless, several brain regions displayed subtle differences in DBSI-RF values between COVID-19 cases and controls. These regions are either part of the olfactory network (i.e., orbitofrontal cortex) or functionally connected to the olfactory network (e.g., amygdala, caudate), a network that has been implicated in COVID-19 psychopathology. It remains possible that our study did not capture acute and transitory neuroinflammatory effects associated with COVID-19 due to potential symptom resolution before the imaging scan. Future research is warranted to explore the potential time- and symptom-dependent neuroinflammatory relationship with SARS-CoV-2 infection.", - "rel_num_authors": 8, + "rel_link": "https://biorxiv.org/cgi/content/short/2023.07.19.549731", + "rel_abs": "Emerging variants of concern of SARS-CoV-2 can significantly reduce the prophylactic and therapeutic efficacy of vaccines and neutralizing antibodies due to mutations in the viral genome. Targeting cell host factors required for infection provides a complementary strategy to overcome this problem since the host genome is less susceptible to variation during the life span of infection. The enzymatic activities of the endosomal PIKfyve phosphoinositide kinase and the serine protease TMPRSS2 are essential to meditate infection in two complementary viral entry pathways. Simultaneous inhibition in cultured cells of their enzymatic activities with the small molecule inhibitors apilimod dimesylate and nafamostat mesylate synergistically prevent viral entry and infection of native SARS-CoV-2 and vesicular stomatitis virus (VSV)-SARS-CoV-2 chimeras expressing the SARS-CoV-2 surface spike (S) protein and of variants of concern. We now report prophylactic prevention of lung infection in mice intranasally infected with SARS-CoV-2 beta by combined intranasal delivery of very low doses of apilimod dimesylate and nafamostat mesylate, in a formulation that is stable for over 3 months at room temperature. Administration of these drugs up to 6 hours post infection did not inhibit infection of the lungs but substantially reduced death of infected airway epithelial cells. The efficiency and simplicity of formulation of the drug combination suggests its suitability as prophylactic or therapeutic treatment against SARS-CoV-2 infection in households, point of care facilities, and under conditions where refrigeration would not be readily available.", + "rel_num_authors": 13, "rel_authors": [ { - "author_name": "Wei Zhang", - "author_inst": "Washington University in St. Louis" + "author_name": "Ravi Kant", + "author_inst": "University of Helsinki" }, { - "author_name": "Aaron J Gorelik", - "author_inst": "Washington University in St. Louis" + "author_name": "Lauri Kareinen", + "author_inst": "University of Helsinki" }, { - "author_name": "Qing Wang", - "author_inst": "Washington University in St. Louis" + "author_name": "Ravi Ojha", + "author_inst": "University of Helsinki" }, { - "author_name": "Sara A Norton", - "author_inst": "Washington University in St. Louis" + "author_name": "Tomas Strandin", + "author_inst": "University of Helsinki" }, { - "author_name": "Tamara Hershey", - "author_inst": "Washington University in St. Louis" + "author_name": "Saber H. Saber", + "author_inst": "University of Queensland" }, { - "author_name": "Arpana Agrawal", - "author_inst": "Washington University School of Medicine" + "author_name": "Angelina Lesnikova", + "author_inst": "University of Helsinki" }, { - "author_name": "Janine D Bijsterbosch", - "author_inst": "Washington University in St Louis" + "author_name": "Suvi Kuivanen", + "author_inst": "Charite Institute" }, { - "author_name": "Ryan Bogdan", - "author_inst": "Washington University in St. Louis" + "author_name": "Tarja Sironen", + "author_inst": "University of Helsinki" + }, + { + "author_name": "Merja Joensuu", + "author_inst": "The Univeristy of Queensland" + }, + { + "author_name": "Olli Vapalahti", + "author_inst": "University of Helsinki" + }, + { + "author_name": "Tom Kirchhausen", + "author_inst": "Harvard Medical School" + }, + { + "author_name": "Anja Kipar", + "author_inst": "University of Zurich" + }, + { + "author_name": "Giuseppe Balistreri", + "author_inst": "University of Helsinki" } ], "version": "1", "license": "cc_by_nc_nd", "type": "new results", - "category": "neuroscience" + "category": "microbiology" }, { "rel_doi": "10.1101/2023.07.18.549478", @@ -50779,37 +50818,49 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2023.07.14.549077", - "rel_title": "Absence of SARS-CoV-2 in Wildlife of Northeastern Minnesota and Isle Royale National Park", + "rel_doi": "10.1101/2023.07.14.549076", + "rel_title": "Oral immunization with rVSV bivalent vaccine elicits protective immune responses, including ADCC, against both SARS-CoV-2 and Influenza A viruses", "rel_date": "2023-07-15", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2023.07.14.549077", - "rel_abs": "We investigated the presence of SARS-CoV-2 in free-ranging wildlife populations in Northeastern Minnesota on the Grand Portage Indian Reservation and Isle Royale National Park. 120 nasal samples were collected from white-tailed deer, moose, gray wolves, and black bears monitored for conservation efforts during 2022-2023. Samples were tested for viral RNA by RT-qPCR using the CDC N1/N2 primer set. Our data indicate that no wildlife samples were positive for SARS-CoV-2 RNA. Continued surveillance is therefore crucial to better understand the changing landscape of zoonotic SARS-CoV-2 in the Upper Midwest.", - "rel_num_authors": 6, + "rel_link": "https://biorxiv.org/cgi/content/short/2023.07.14.549076", + "rel_abs": "COVID-19 and influenza both cause enormous disease burdens, and vaccines are the primary measures for their control. Since these viral diseases are transmitted through the mucosal surface of the respiratory tract, developing an effective and convenient mucosal vaccine should be a high priority. We previously reported a recombinant vesicular stomatitis virus (rVSV)-based bivalent vaccine (v-EM2/SP{Delta}C1Delta) that protects animals from both SARS-CoV-2 and influenza viruses via intramuscular and intranasal immunization. Here, we further investigated the immune response induced by oral immunization with this vaccine and its protective efficacy in mice. The results demonstrated that the oral cavity delivery, like the intranasal route, elicited strong and protective systemic immune responses against SARS-CoV-2 and influenza A virus. This included high levels of neutralizing antibodies (NAbs) against SARS-CoV-2, as well as strong anti-SARS-CoV-2 spike protein (SP) antibody-dependent cellular cytotoxicity (ADCC) and anti-influenza M2 ADCC responses in mice sera. Furthermore, it provided efficient protection against challenge with influenza H1N1 virus in a mouse model, with a 100% survival rate and a significant low lung viral load of influenza virus. All these findings provide substantial evidence for the effectiveness of oral immunization with the rVSV bivalent vaccine.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "David Castaneda", - "author_inst": "University of Minnesota, Twin Cities" + "author_name": "Maggie Jing Ouyang", + "author_inst": "University of Manitoba" }, { - "author_name": "Edmund J Isaac", - "author_inst": "Grand Portage Band of Lake Superior Chippewa Biology and Environment" + "author_name": "Zhujun Ao", + "author_inst": "University of Manitoba" + }, + { + "author_name": "Titus Olukitibi", + "author_inst": "University of Manitoba" }, { - "author_name": "Todd Kautz", - "author_inst": "Grand Portage Band of Lake Superior Chippewa Biology and Environment" + "author_name": "Peter Lawrynuik", + "author_inst": "University of Manitoba" }, { - "author_name": "Mark C Romanski", - "author_inst": "Isle Royale National Park" + "author_name": "Christopher Shieh", + "author_inst": "University of Manitoba" }, { - "author_name": "Seth A Moore", - "author_inst": "Grand Portage Band of Lake Superior Chippewa Biology and Environment" + "author_name": "Sam Kung", + "author_inst": "University of Manitoba" }, { - "author_name": "Matthew Aliota", - "author_inst": "University of Minnesota Twin Cities" + "author_name": "Keith Fowke", + "author_inst": "University of Manitoba" + }, + { + "author_name": "Darwyn Kobasa", + "author_inst": "Public Health Agency of Canada" + }, + { + "author_name": "Xiaojian Yao", + "author_inst": "University of Manitoba" } ], "version": "1", @@ -52309,131 +52360,43 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2023.07.10.548424", - "rel_title": "An ACE2 decamer viral trap as a durable intervention solution for current and future SARS-CoV", + "rel_doi": "10.1101/2023.07.10.548464", + "rel_title": "Genomic Surveillance of SARS-CoV-2 Using Long-Range PCR Primers", "rel_date": "2023-07-11", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2023.07.10.548424", - "rel_abs": "The capacity of SARS-CoV-2 to evolve poses challenges to conventional prevention and treatment options such as vaccination and monoclonal antibodies, as they rely on viral receptor binding domain (RBD) sequences from previous strains. Additionally, animal CoVs, especially those of the SARS family, are now appreciated as a constant pandemic threat. We present here a new antiviral approach featuring inhalation delivery of a recombinant viral trap composed of ten copies of angiotensin-converting enzyme 2 (ACE2) fused to the IgM Fc. This ACE2 decamer viral trap is designed to inhibit SARS-CoV-2 entry function, regardless of viral RBD sequence variations as shown by its high neutralization potency against all known SARS-CoV-2 variants, including Omicron BQ.1, BQ.1.1, XBB.1 and XBB.1.5. In addition, it demonstrates potency against SARS-CoV-1, human NL63, as well as bat and pangolin CoVs. The multivalent trap is effective in both prophylactic and therapeutic settings since a single intranasal dosing confers protection in human ACE2 transgenic mice against viral challenges. Lastly, this molecule is stable at ambient temperature for more than twelve weeks and can sustain physical stress from aerosolization. These results demonstrate the potential of a decameric ACE2 viral trap as an inhalation solution for ACE2-dependent coronaviruses of current and future pandemic concerns.", - "rel_num_authors": 28, + "rel_link": "https://biorxiv.org/cgi/content/short/2023.07.10.548464", + "rel_abs": "Whole Genome Sequencing (WGS) of the SARS-CoV-2 virus is crucial in the surveillance of the COVID-19 pandemic. Several primer schemes have been developed to sequence the [~]30,000 nucleotide SARS-CoV-2 genome that use a multiplex PCR approach to amplify cDNA copies of the viral genomic RNA. Midnight primers and ARTIC V4.1 primers are the most popular primer schemes that can amplify segments of SARS-CoV-2 (400 bp and 1200 bp, respectively) tiled across the viral RNA genome. Mutations within primer binding sites and primer-primer interactions can result in amplicon dropouts and coverage bias, yielding low-quality genomes with Ns inserted in the missing amplicon regions, causing inaccurate lineage assignments, and making it challenging to monitor lineage-specific mutations in Variants of Concern (VoCs). This study uses seven long-range PCR primers with an amplicon size of [~]4500 bp to tile across the complete SARS-CoV-2 genome. One of these regions includes the full-length S-gene by using a set of flanking primers. Using a small set of long-range primers to sequence SARS-CoV-2 genomes reduces the possibility of amplicon dropout and coverage bias.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Hailong Guo", - "author_inst": "IGM Biosciences" - }, - { - "author_name": "Bomsoo Cho", - "author_inst": "IGM Biosciences" - }, - { - "author_name": "Paul R Hinton", - "author_inst": "IGM Biosciences" - }, - { - "author_name": "Sijia He", - "author_inst": "IGM Biosciences" - }, - { - "author_name": "Yongjun Yu", - "author_inst": "IGM Biosciences" - }, - { - "author_name": "Ashwin Kumar Ramesh", - "author_inst": "Texas Therapeutics Institute, Brown Foundation Institute of Molecular Medicine, The University of Texas Health Science Center at Houston" - }, - { - "author_name": "Jwala Priyadarsini Sivaccumar", - "author_inst": "Texas Therapeutics Institute, Brown Foundation Institute of Molecular Medicine, The University of Texas Health Science Center at Houston" - }, - { - "author_name": "Zhiqiang Ku", - "author_inst": "Texas Therapeutics Institute, Brown Foundation Institute of Molecular Medicine, The University of Texas Health Science Center at Houston" - }, - { - "author_name": "Kristen Campo", - "author_inst": "IGM Biosciences" - }, - { - "author_name": "Sarah Holland", - "author_inst": "IGM Biosciences" - }, - { - "author_name": "Sameer Sachdeva", - "author_inst": "IGM Biosciences" - }, - { - "author_name": "Christopher Mensch", - "author_inst": "IGM Biosciences" - }, - { - "author_name": "Mohamed Dawod", - "author_inst": "IGM Biosciences" - }, - { - "author_name": "Annalis Whitaker", - "author_inst": "University of Vermont" - }, - { - "author_name": "Philip Eisenhauer", - "author_inst": "University of Vermont" - }, - { - "author_name": "Allison Falcone", - "author_inst": "University of Vermont" - }, - { - "author_name": "Rebekah Honce", - "author_inst": "University of Vermont" - }, - { - "author_name": "Jason W. Botten", - "author_inst": "University of Vermont" - }, - { - "author_name": "Stephen F Carroll", - "author_inst": "IGM Biosciences" - }, - { - "author_name": "Bruce A Keyt", - "author_inst": "IGM Biosciences" - }, - { - "author_name": "Andrew W Womack", - "author_inst": "IGM Biosciences" - }, - { - "author_name": "William R Strohl", - "author_inst": "IGM Biosciences" - }, - { - "author_name": "Kai Xu", - "author_inst": "The Ohio State University" + "author_name": "Sangam Kandel", + "author_inst": "University of Arkansas for Medical Sciences" }, { - "author_name": "Zhiqiang An", - "author_inst": "Texas Therapeutics Institute, Brown Foundation Institute of Molecular Medicine, The University of Texas Health Science Center at Houston" + "author_name": "Susanna L. Hartzell", + "author_inst": "Arkansas Children's Research Institute" }, { - "author_name": "Ningyan Zhang", - "author_inst": "Texas Therapeutics Institute, Brown Foundation Institute of Molecular Medicine, The University of Texas Health Science Center at Houston" + "author_name": "Ashton K. Ingold", + "author_inst": "Arkansas Children's Research Institute" }, { - "author_name": "Sha Ha", - "author_inst": "IGM Biosciences" + "author_name": "Grace A. Turner", + "author_inst": "Arkansas Children's Research Institute" }, { - "author_name": "John W Shiver", - "author_inst": "IGM Biosciences" + "author_name": "Joshua L Kennedy", + "author_inst": "University of Arkansas for Medical Sciences" }, { - "author_name": "Tong-Ming Fu", - "author_inst": "IGM Biosciences" + "author_name": "David W. Ussery", + "author_inst": "University of Arkansas for Medical Sciences" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "new results", - "category": "microbiology" + "category": "genomics" }, { "rel_doi": "10.1101/2023.07.10.548360", @@ -52555,7 +52518,7 @@ "rel_date": "2023-07-09", "rel_site": "medRxiv", "rel_link": "https://medrxiv.org/cgi/content/short/2023.07.08.23292389", - "rel_abs": "Antimicrobial peptides (AMPs) are a complex network of 10-100 amino acid sequence molecules, widely distributed in Nature. Even though more than 300 AMPs have been described in mammals, cathelicidins and defensins remain the most investigated to date.\n\nSome publications examined the role of AMPs in COVID-19, but the findings are preliminary and in vivo studies are still lacking. Here, we report the plasma levels of five AMPs (LL-37, -defensin 1, -defensin 3, {beta}-defensin 1 and {beta}-defensin 3) and five cytokines (tumor necrosis factor-, interleukin-1{beta}, interleukin-6, interleukin-10, interferon-{gamma} and monocyte chemoattractant protein-1), in 15 healthy volunteers, 36 COVID-19 patients without Acute Kidney Injury (AKI) and 17 COVID-19 patients with AKI, since AKI is a well-known marker of worse prognosis in Sars-CoV-2 infections.\n\nWe found increased levels of -defensin 1, -defensin 3 and {beta}-defensin 3, but not LL-37 or {beta}-defensin 3, in our COVID-19 population, when compared with the healthy controls, in conjunction with higher levels of interleukin-6, interleukin-10, interferon-{gamma} and monocyte chemoattractant protein-1, putting in evidence that these AMPs and cytokines may have an important role in the systemic inflammatory response and tissue damage that characterizes severe COVID-19.\n\nGraphic Abstract\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=152 SRC=\"FIGDIR/small/23292389v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (45K):\norg.highwire.dtl.DTLVardef@7f49eaorg.highwire.dtl.DTLVardef@cdbd99org.highwire.dtl.DTLVardef@15ab86forg.highwire.dtl.DTLVardef@1028a5c_HPS_FORMAT_FIGEXP M_FIG C_FIG", + "rel_abs": "Antimicrobial peptides (AMPs) are a complex network of 10-100 amino acid sequence molecules, widely distributed in Nature. Even though more than 300 AMPs have been described in mammals, cathelicidins and defensins remain the most investigated to date.\n\nSome publications examined the role of AMPs in COVID-19, but the findings are preliminary and in vivo studies are still lacking. Here, we report the plasma levels of five AMPs (LL-37, -defensin 1, -defensin 3, {beta}-defensin 1 and {beta}-defensin 3) and five cytokines (tumor necrosis factor-, interleukin-1{beta}, interleukin-6, interleukin-10, interferon-{gamma} and monocyte chemoattractant protein-1), in 15 healthy volunteers, 36 COVID-19 patients without Acute Kidney Injury (AKI) and 17 COVID-19 patients with AKI, since AKI is a well-known marker of worse prognosis in Sars-CoV-2 infections.\n\nWe found increased levels of -defensin 1, -defensin 3 and {beta}-defensin 3, but not LL-37 or {beta}-defensin 3, in our COVID-19 population, when compared with the healthy controls, in conjunction with higher levels of interleukin-6, interleukin-10, interferon-{gamma} and monocyte chemoattractant protein-1, putting in evidence that these AMPs and cytokines may have an important role in the systemic inflammatory response and tissue damage that characterizes severe COVID-19.\n\nGraphic Abstract\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=152 SRC=\"FIGDIR/small/23292389v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (45K):\norg.highwire.dtl.DTLVardef@9a3384org.highwire.dtl.DTLVardef@1ac2fd4org.highwire.dtl.DTLVardef@1783e85org.highwire.dtl.DTLVardef@150ca03_HPS_FORMAT_FIGEXP M_FIG C_FIG", "rel_num_authors": 5, "rel_authors": [ { @@ -54127,353 +54090,85 @@ "category": "ecology" }, { - "rel_doi": "10.1101/2023.06.28.23291998", - "rel_title": "Informing pandemic response in the face of uncertainty. An evaluation of the U.S. COVID-19 Scenario Modeling Hub", + "rel_doi": "10.1101/2023.07.03.23292158", + "rel_title": "A new Omicron lineage with Spike Y451H mutation that dominated a new COVID-19 wave in Kilifi, Coastal Kenya: March-May 2023", "rel_date": "2023-07-03", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.06.28.23291998", - "rel_abs": "Our ability to forecast epidemics more than a few weeks into the future is constrained by the complexity of disease systems, our limited ability to measure the current state of an epidemic, and uncertainties in how human action will affect transmission. Realistic longer-term projections (spanning more than a few weeks) may, however, be possible under defined scenarios that specify the future state of critical epidemic drivers, with the additional benefit that such scenarios can be used to anticipate the comparative effect of control measures. Since December 2020, the U.S. COVID-19 Scenario Modeling Hub (SMH) has convened multiple modeling teams to make 6-month ahead projections of the number of SARS-CoV-2 cases, hospitalizations and deaths. The SMH released nearly 1.8 million national and state-level projections between February 2021 and November 2022. SMH performance varied widely as a function of both scenario validity and model calibration. Scenario assumptions were periodically invalidated by the arrival of unanticipated SARS-CoV-2 variants, but SMH still provided projections on average 22 weeks before changes in assumptions (such as virus transmissibility) invalidated scenarios and their corresponding projections. During these periods, before emergence of a novel variant, a linear opinion pool ensemble of contributed models was consistently more reliable than any single model, and projection interval coverage was near target levels for the most plausible scenarios (e.g., 79% coverage for 95% projection interval). SMH projections were used operationally to guide planning and policy at different stages of the pandemic, illustrating the value of the hub approach for long-term scenario projections.", - "rel_num_authors": 84, + "rel_link": "https://medrxiv.org/cgi/content/short/2023.07.03.23292158", + "rel_abs": "We report a newly emerged SARS-CoV-2 Omicron lineage, named FY.4, that has two unique mutations; spike:Y451H and ORF3a:P42L. FY.4 emergence has coincided with increased SARS-CoV-2 cases in coastal Kenya, April-May 2023. We demonstrate the value of continued SARS-CoV-2 genomic surveillance in the post-acute pandemic era in understanding new COVID-19 outbreaks.", + "rel_num_authors": 17, "rel_authors": [ { - "author_name": "Emily Howerton", - "author_inst": "The Pennsylvania State University" - }, - { - "author_name": "Lucie Contamin", - "author_inst": "University of Pittsburgh" - }, - { - "author_name": "Luke C Mullany", - "author_inst": "Johns Hopkins University Applied Physics Lab" - }, - { - "author_name": "Michelle M Qin", - "author_inst": "Harvard University" - }, - { - "author_name": "Nicholas G Reich", - "author_inst": "University of Massachusetts Amherst" - }, - { - "author_name": "Samantha J Bents", - "author_inst": "National Institutes of Health Fogarty International Center" - }, - { - "author_name": "Rebecca K Borchering", - "author_inst": "The Pennsylvania State University, Centers for Disease Control and Prevention" - }, - { - "author_name": "Sung-mok Jung", - "author_inst": "University of North Carolina at Chapel Hill" - }, - { - "author_name": "Sara L Loo", - "author_inst": "Johns Hopkins University Infectious Disease Dynamics" - }, - { - "author_name": "Claire P Smith", - "author_inst": "Johns Hopkins University Infectious Disease Dynamics" - }, - { - "author_name": "John Levander", - "author_inst": "University of Pittsburgh" - }, - { - "author_name": "Jessica Kerr", - "author_inst": "University of Pittsburgh" - }, - { - "author_name": "J. Espino", - "author_inst": "University of Pittsburgh" - }, - { - "author_name": "Willem G van Panhuis", - "author_inst": "National Institute of Allergy and Infectious Diseases" - }, - { - "author_name": "Harry Hochheiser", - "author_inst": "University of Pittsburgh" - }, - { - "author_name": "Marta Galanti", - "author_inst": "Columbia University" - }, - { - "author_name": "Teresa K Yamana", - "author_inst": "Columbia University" - }, - { - "author_name": "Sen Pei", - "author_inst": "Columbia University" - }, - { - "author_name": "Jeffrey Shaman", - "author_inst": "Columbia University" - }, - { - "author_name": "Kaitlin Rainwater-Lovett", - "author_inst": "Johns Hopkins University Applied Physics Lab" - }, - { - "author_name": "Matt Kinsey", - "author_inst": "Johns Hopkins University Applied Physics Lab" - }, - { - "author_name": "Kate Tallaksen", - "author_inst": "Johns Hopkins University Applied Physics Lab" - }, - { - "author_name": "Shelby Wilson", - "author_inst": "Johns Hopkins University Applied Physics Lab" - }, - { - "author_name": "Lauren Shin", - "author_inst": "Johns Hopkins University Applied Physics Lab" - }, - { - "author_name": "Joseph C Lemaitre", - "author_inst": "University of North Carolina at Chapel Hill" - }, - { - "author_name": "Joshua Kaminsky", - "author_inst": "Johns Hopkins University Infectious Disease Dynamics" - }, - { - "author_name": "Juan Dent Hulse", - "author_inst": "Johns Hopkins University Infectious Disease Dynamics" - }, - { - "author_name": "Elizabeth C Lee", - "author_inst": "Johns Hopkins University Infectious Disease Dynamics" - }, - { - "author_name": "Clifton D McKee", - "author_inst": "Johns Hopkins University Infectious Disease Dynamics" - }, - { - "author_name": "Alison Hill", - "author_inst": "Johns Hopkins University Infectious Disease Dynamics" - }, - { - "author_name": "Dean Karlen", - "author_inst": "University of Victoria" - }, - { - "author_name": "Matteo Chinazzi", - "author_inst": "Northeastern University" - }, - { - "author_name": "Jessica T Davis", - "author_inst": "Northeastern University" - }, - { - "author_name": "Kunpeng Mu", - "author_inst": "Northeastern University" - }, - { - "author_name": "Xinyue Xiong", - "author_inst": "Northeastern University" - }, - { - "author_name": "Ana Pastore Piontti", - "author_inst": "Northeastern University" - }, - { - "author_name": "Alessandro Vespignani", - "author_inst": "Northeastern University" - }, - { - "author_name": "Erik T Rosenstrom", - "author_inst": "North Carolina State University" - }, - { - "author_name": "Julie S Ivy", - "author_inst": "North Carolina State University" - }, - { - "author_name": "Maria E Mayorga", - "author_inst": "North Carolina State University" - }, - { - "author_name": "Julie L Swann", - "author_inst": "North Carolina State University" - }, - { - "author_name": "Guido Espana", - "author_inst": "University of Notre Dame" - }, - { - "author_name": "Sean Cavany", - "author_inst": "University of Notre Dame" - }, - { - "author_name": "Sean M Moore", - "author_inst": "University of Notre Dame" - }, - { - "author_name": "Alex Perkins", - "author_inst": "University of Notre Dame" - }, - { - "author_name": "Thomas Hladish", - "author_inst": "University of Florida" - }, - { - "author_name": "Alexander Pillai", - "author_inst": "University of Florida" - }, - { - "author_name": "Kok Ben Toh", - "author_inst": "Northwestern University" - }, - { - "author_name": "Ira Longini Jr.", - "author_inst": "University of Florida" - }, - { - "author_name": "Shi Chen", - "author_inst": "University of North Carolina at Charlotte" - }, - { - "author_name": "Rajib Paul", - "author_inst": "University of North Carolina at Charlotte" - }, - { - "author_name": "Daniel Janies", - "author_inst": "University of North Carolina at Charlotte" - }, - { - "author_name": "Jean-Claude Thill", - "author_inst": "University of North Carolina at Charlotte" - }, - { - "author_name": "Anass Bouchnita", - "author_inst": "University of Texas at El Paso" - }, - { - "author_name": "Kaiming Bi", - "author_inst": "University of Texas at Austin" - }, - { - "author_name": "Michael Lachmann", - "author_inst": "Santa Fe Institute" - }, - { - "author_name": "Spencer J Fox", - "author_inst": "University of Georgia" - }, - { - "author_name": "Lauren A Meyers", - "author_inst": "University of Texas at Austin" - }, - { - "author_name": "- UT COVID-19 Modeling Consortium", - "author_inst": "-" - }, - { - "author_name": "Ajitesh Srivastava", - "author_inst": "University of Southern California" - }, - { - "author_name": "Przemyslaw Porebski", - "author_inst": "University of Virginia" - }, - { - "author_name": "Srinivasan Venkatramanan", - "author_inst": "University of Virginia" - }, - { - "author_name": "Aniruddha Adiga", - "author_inst": "University of Virginia" - }, - { - "author_name": "Bryan Lewis", - "author_inst": "University of Virginia" - }, - { - "author_name": "Brian Klahn", - "author_inst": "University of Virginia" - }, - { - "author_name": "Joseph Outten", - "author_inst": "University of Virginia" - }, - { - "author_name": "Benjamin Hurt", - "author_inst": "University of Virginia" - }, - { - "author_name": "Jiangzhuo Chen", - "author_inst": "University of Virginia" + "author_name": "Mike Javan Mwanga", + "author_inst": "KEMRI Wellcome Trust Research Programme" }, { - "author_name": "Henning Mortveit", - "author_inst": "University of Virginia" + "author_name": "ARNOLD W. LAMBISIA", + "author_inst": "KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya" }, { - "author_name": "Amanda Wilson", - "author_inst": "University of Virginia" + "author_name": "John Mwita Morobe", + "author_inst": "KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya" }, { - "author_name": "Madhav Marathe", - "author_inst": "University of Virginia" + "author_name": "Nickson Murunga", + "author_inst": "KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya" }, { - "author_name": "Stefan Hoops", - "author_inst": "University of Virginia" + "author_name": "Edidah Moraa", + "author_inst": "KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya" }, { - "author_name": "Parantapa Bhattacharya", - "author_inst": "University of Virginia" + "author_name": "Leonard Ndwiga", + "author_inst": "KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya" }, { - "author_name": "Dustin Machi", - "author_inst": "University of Virginia" + "author_name": "Cheruiyot Robinson", + "author_inst": "KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya" }, { - "author_name": "Betsy L Gunnels", - "author_inst": "Centers for Disease Control and Prevention" + "author_name": "Martin Mutunga", + "author_inst": "KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya" }, { - "author_name": "Jessica M Healy", - "author_inst": "Centers for Disease Control and Prevention" + "author_name": "Laura Marcela Guzman Rincon", + "author_inst": "Mathematics Institute, University of Warwick, CV4 7AL, UK" }, { - "author_name": "Rachel B Slayton", - "author_inst": "Centers for Disease Control and Prevention" + "author_name": "Charles Sande", + "author_inst": "KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya" }, { - "author_name": "Michael A Johansson", - "author_inst": "Centers for Disease Control and Prevention" + "author_name": "Joseph Mwangangi", + "author_inst": "KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya" }, { - "author_name": "Matthew Biggerstaff", - "author_inst": "Centers for Disease Control and Prevention" + "author_name": "Philip Bejon", + "author_inst": "KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya" }, { - "author_name": "Shaun Truelove", - "author_inst": "Johns Hopkins University Infectious Disease Dynamics" + "author_name": "lynette Isabella Ochola-Oyier", + "author_inst": "KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya" }, { - "author_name": "Michael C Runge", - "author_inst": "U.S. Geological Survey Eastern Ecological Science Center" + "author_name": "James Nokes", + "author_inst": "School of Life Sciences and Zeeman Institute for Systems Biology and Infectious Disease Epidemiology Research (SBIDER), University of Warwick, Coventry, UK" }, { - "author_name": "Katriona Shea", - "author_inst": "The Pennsylvania State University" + "author_name": "Charles N Agoti", + "author_inst": "KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya" }, { - "author_name": "Cecile Viboud", - "author_inst": "National Institutes of Health Fogarty International Center" + "author_name": "Joyce Nyiro", + "author_inst": "KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya" }, { - "author_name": "Justin Lessler", - "author_inst": "University of North Carolina at Chapel Hill" + "author_name": "George Githinji", + "author_inst": "KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -56533,157 +56228,81 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2023.06.23.23291827", - "rel_title": "Increased circulating fibronectin, depletion of natural IgM and heightened EBV, HSV-1 reactivation in ME/CFS and long COVID", + "rel_doi": "10.1101/2023.06.26.23291883", + "rel_title": "Long-term outcomes of hospitalized SARS-CoV-2/COVID-19 patients with and without neurological involvement: 3-year follow-up assessment", "rel_date": "2023-06-29", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.06.23.23291827", - "rel_abs": "Myalgic Encephalomyelitis/ Chronic Fatigue syndrome (ME/CFS) is a complex, debilitating, long-term illness without a diagnostic biomarker. ME/CFS patients share overlapping symptoms with long COVID patients, an observation which has strengthened the infectious origin hypothesis of ME/CFS. However, the exact sequence of events leading to disease development is largely unknown for both clinical conditions. Here we show antibody response to herpesvirus dUTPases, particularly to that of Epstein-Barr virus (EBV) and HSV-1, increased circulating fibronectin (FN1) levels in serum and depletion of natural IgM against fibronectin ((n)IgM-FN1) are common factors for both severe ME/CFS and long COVID. We provide evidence for herpesvirus dUTPases-mediated alterations in host cell cytoskeleton, mitochondrial dysfunction and OXPHOS. Our data show altered active immune complexes, immunoglobulin-mediated mitochondrial fragmentation as well as adaptive IgM production in ME/CFS patients. Our findings provide mechanistic insight into both ME/CFS and long COVID development. Finding of increased circulating FN1 and depletion of (n)IgM-FN1 as a biomarker for the severity of both ME/CFS and long COVID has an immediate implication in diagnostics and development of treatment modalities.", - "rel_num_authors": 35, + "rel_link": "https://medrxiv.org/cgi/content/short/2023.06.26.23291883", + "rel_abs": "Background and ObjectivesAcute neurological manifestations are a common complication of acute COVID-19 disease. This study investigated the 3-year outcomes of patients with and without significant neurological manifestations during initial COVID-19 hospitalization.\n\nMethodsPatients infected by SARS-CoV-2 between March 1 and April 16, 2020 and hospitalized in the Montefiore Health System in the Bronx, an epicenter of the early pandemic, were included. Follow-up data was captured up to January 23, 2023 (3 years post COVID-19). This cohort consisted of 414 COVID-19 patients with significant neurological manifestations and 1199 propensity-matched COVID- 19 patients without neurological manifestations. Primary outcomes were mortality, stroke, heart attack, major adverse cardiovascular events (MACE), reinfection, and hospital readmission post-discharge. Secondary outcomes were clinical neuroimaging findings (hemorrhage, active stroke, prior stroke, mass effect, and microhemorrhage, white-matter changes, microvascular disease, and volume loss). Predictive models were used to identify risk factors of mortality post-discharge.\n\nResultsMore patients in the neurological cohort were discharged to acute rehabilitation (10.54% vs 3.68%, p<0.0001), skilled nursing facilities (30.67% vs 20.78%, p=0.0002) and fewer to home (55.27% vs 70.21%, p<0.0001) compared to the matched controls. Incidence of readmission for any medical reason (65.70% vs 60.72%, p=0.036), stroke (6.28% vs 2.34%, p<0.0001), and MACE (20.53% vs 16.51%, p=0.032) was higher in the neurological cohort post-discharge. Neurological patients were more likely to die post-discharge (58 (14.01%) vs 94 (7.84%), p=0.0001) compared to controls (HR=2.346, 95% CI=(1.586, 3.470), p<0.0001). The major causes of death post-discharge were heart disease (14.47%), sepsis (13.82%), influenza and pneumonia (11.18%), COVID-19 (8.55%) and acute respiratory distress syndrome (7.89%). Factors associated with mortality after leaving the hospital were belonging to the neurological cohort (OR=1.802 (1.237, 2.608), p=0.002), discharge disposition (OR=1.508, 95% CI=(1.276, 1.775), p<0.0001), congestive heart failure (OR=2.281 (1.429, 3.593), p=0.0004), higher COVID-19 severity score (OR=1.177 (1.062, 1.304), p=0.002), and older age (OR=1.027 (1.010, 1.044), p=0.002). There were no group differences in gross radiological findings, except the neurological cohort showed significantly more age-adjusted brain volume loss (p<0.05) compared to controls.\n\nDiscussionCOVID-19 patients with neurological manifestations have worse long-term outcomes compared to matched controls. These findings raise awareness and the need for closer monitoring and timely interventions for COVID-19 patients with neurological manifestations.", + "rel_num_authors": 16, "rel_authors": [ { - "author_name": "Zheng Liu", - "author_inst": "Institute for Virology and Immunobiology, Julius-Maximilians-University of Wuerzburg, Wuerzburg, Germany" - }, - { - "author_name": "Claudia Hollmann", - "author_inst": "Institute for Virology and Immunobiology, Julius-Maximilians-University of Wuerzburg, Wuerzburg, Germany" - }, - { - "author_name": "Sharada Kalanidhi", - "author_inst": "Stanford Genome Technology Center, Stanford University School of Medicine, Stanford, CA, USA" - }, - { - "author_name": "Arnhild Grothey", - "author_inst": "Institute for Virology and Immunobiology, Julius-Maximilians-University of Wuerzburg, Wuerzburg, Germany" - }, - { - "author_name": "Samuel Keating", - "author_inst": "Institute for Virology and Immunobiology, Julius-Maximilians-University of Wuerzburg, Wuerzburg, Germany" - }, - { - "author_name": "Irene Mena-Palomo", - "author_inst": "Institute for Behavioral Medicine Research (IBMR), The Ohio State University, Columbus, Ohio, USA" - }, - { - "author_name": "Stephanie Lamer", - "author_inst": "Rudolf Virchow Center, Center for Translational Bioimaging, Julius-Maximilians-University of Wuerzburg, Wuerzburg, Germany" - }, - { - "author_name": "Andreas Schlosser", - "author_inst": "Rudolf Virchow Center, Center for Translational Bioimaging, Julius-Maximilians-University of Wuerzburg, Wuerzburg, Germany" - }, - { - "author_name": "Agnes Kaiping", - "author_inst": "Institute for Virology and Immunobiology, Julius-Maximilians-University of Wuerzburg, Wuerzburg, Germany" - }, - { - "author_name": "Carsten Scheller", - "author_inst": "Institute for Virology and Immunobiology, Julius-Maximilians-University of Wuerzburg, Wuerzburg, Germany" - }, - { - "author_name": "Franziska Sotzny", - "author_inst": "Institute for Medical Immunology, Charite-Universitaetsmedizin Berlin, Berlin, Germany" - }, - { - "author_name": "Anna Horn", - "author_inst": "Institute of Clinical Epidemiology and Biometry, Julius-Maximilians-University of Wuerzburg, Wuerzburg, Germany." - }, - { - "author_name": "Carolin Nuernberger", - "author_inst": "Institute of Clinical Epidemiology and Biometry, Julius-Maximilians-University of Wuerzburg, Wuerzburg, Germany." - }, - { - "author_name": "Vladimir Cejka", - "author_inst": "Department of Clinical Research & Epidemiology, Comprehensive Heart Failure Center and Department of Medicine I, University Hospital Wuerzburg, Wuerzburg, Germa" - }, - { - "author_name": "Boshra Afshar", - "author_inst": "Institute for Virology and Immunobiology, Julius Maximilian University of Wuerzburg, Wuerzburg, Germany" - }, - { - "author_name": "Thomas Bahmer", - "author_inst": "Internal Medicine Department I, University Hospital Schleswig-Holstein UKSH - Campus Kiel, Kiel, Germany" - }, - { - "author_name": "Stefan Schreiber", - "author_inst": "Internal Medicine Department I, University Hospital Schleswig-Holstein UKSH - Campus Kiel, Kiel, Germany" - }, - { - "author_name": "Joerg Janne Vehreschild", - "author_inst": "University of Cologne, Faculty of Medicine and University Hospital Cologne, Department I of Internal Medicine, Center for Integrated Oncology Aachen Bonn Cologn" - }, - { - "author_name": "Olga Milljukov", - "author_inst": "Institute of Clinical Epidemiology and Biometry, Julius Maximilian University of Wuerzburg, Wuerzburg, Germany" - }, - { - "author_name": "Christian Schaefer", - "author_inst": "University Medicine Greifswald, Institute of Clinical Chemistry and Laboratory Medicine, Greifswald, Germany" + "author_name": "Anna Eligulashvili", + "author_inst": "Montefiore Health System" }, { - "author_name": "Luzie Kretzler", - "author_inst": "Charite - Universitaetsmedizin Berlin and Berlin Institute of Health (BIH), Berlin, Germany" + "author_name": "Moshe Gordon", + "author_inst": "Montefiore Health System" }, { - "author_name": "Thomas Keil", - "author_inst": "Charite - Universitaetsmedizin Berlin and Berlin Institute of Health (BIH), Berlin, Germany" + "author_name": "Jimmy S Lee", + "author_inst": "Montefiore Health System" }, { - "author_name": "Jens-Peter Reese", - "author_inst": "Institute of Clinical Epidemiology and Biometry, Julius Maximilian University of Wuerzburg, Wuerzburg, Germany" + "author_name": "Jeylin Lee", + "author_inst": "Montefiore Health System" }, { - "author_name": "Felizitas A Eichner", - "author_inst": "Institute of Clinical Epidemiology and Biometry, Julius-Maximilians-University of Wuerzburg, Wuerzburg, Germany." + "author_name": "Shiv Mehrotra-Varma", + "author_inst": "Montefiore Health System" }, { - "author_name": "Lena Schmidbauer", - "author_inst": "Institute of Clinical Epidemiology and Biometry, Julius-Maximilians-University of Wuerzburg, Wuerzburg, Germany" + "author_name": "Jai Mehrotra-Varma", + "author_inst": "Montefiore Health System" }, { - "author_name": "Peter U Heuschmann", - "author_inst": "Institute of Clinical Epidemiology and Biometry, Julius-Maximilians-University of Wuerzburg, Wuerzburg, Germany." + "author_name": "Kevin Hsu", + "author_inst": "New York University Grossman School of Medicine" }, { - "author_name": "Stefan Stoerk", - "author_inst": "Comprehensive Heart Failure Center and Department of Medicine I, University Hospital Wuerzburg, Wuerzburg, Germany" + "author_name": "Imanyah Hilliard", + "author_inst": "Montefiore Health System" }, { - "author_name": "Caroline Morbach", - "author_inst": "Department of Clinical Research & Epidemiology, Comprehensive Heart Failure Center and Department of Medicine I, University Hospital Wuerzburg, Wuerzburg, Germa" + "author_name": "Kristen Lee", + "author_inst": "Montefiore Health System" }, { - "author_name": "Gabriela Riemekasten", - "author_inst": "Klinik fuer Rheumatologie, Universitaetsklinikum Schleswig-Holstein, Luebeck, Germany" + "author_name": "Arleen Li", + "author_inst": "Montefiore Health System" }, { - "author_name": "Niklas Beyersdorf", - "author_inst": "Institute for Virology and Immunobiology, Julius-Maximilians-University of Wuerzburg, Wuerzburg, Germany" + "author_name": "Muhammed Amir Essibayi", + "author_inst": "Montefiore Health System" }, { - "author_name": "Carmen Scheibenbogen", - "author_inst": "Institute for Medical Immunology, Charite-Universitaetsmedizin Berlin, Berlin, Germany" + "author_name": "Judy Yee", + "author_inst": "Montefiore Health System" }, { - "author_name": "Robert K Naviaux", - "author_inst": "Departments of Medicine, Pediatrics, and Pathology, University of California, San Diego School of Medicine, San Diego, USA" + "author_name": "David J Altschul", + "author_inst": "Montefiore Health System" }, { - "author_name": "Marshall Williams", - "author_inst": "Institute for Behavioral Medicine Research (IBMR), The Ohio State University, Columbus, Ohio, USA" + "author_name": "Emad Eskandar", + "author_inst": "Montefiore Health System" }, { - "author_name": "Maria E Ariza", - "author_inst": "Institute for Behavioral Medicine Research (IBMR), The Ohio State University, Columbus, Ohio, USA" + "author_name": "Mark F Mehler", + "author_inst": "Montefiore Health System" }, { - "author_name": "Bhupesh Kumar Prusty", - "author_inst": "Institute for Virology and Immunobiology, Julius-Maximilians-University of Wuerzburg, Wuerzburg, Germany." + "author_name": "Tim Q Duong", + "author_inst": "Montefiore Hospital and Medical Center: Montefiore Medical Center" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -58219,51 +57838,55 @@ "category": "molecular biology" }, { - "rel_doi": "10.1101/2023.06.26.546492", - "rel_title": "Oligomeric state of \u03b2-coronavirus non-structural protein 10 stimulators studied by OmniSEC and Small Angle X-ray Scattering", + "rel_doi": "10.1101/2023.06.22.546100", + "rel_title": "Classification of patients with COVID-19 by blood RNA endotype: A prospective cohort study", "rel_date": "2023-06-26", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2023.06.26.546492", - "rel_abs": "Members of the {beta}-coronavirus family such as SARS-CoV-2, SARS, and MERS have caused pandemics over the last 20 years. Future pandemics are likely and studying the coronavirus family members is necessary for their understanding and treatment. Coronaviruses possess 16 non-structural proteins, many of which are involved in viral replication and other vital functions. Non-structural protein 10 (nsp10) is an essential stimulator of nsp14 and nsp16, modulating RNA proofreading and viral RNA cap formation. Studying nsp10 of pathogenic coronaviruses is central to understanding its multifunctional role. We report the biochemical and biophysical characterisation of full-length nsp10 from MERS, SARS and SARS-CoV-2. Proteins were subjected to a combination of OmniSEC and SEC-MALS to characterise their oligomeric state. Full-length nsp10s were predominantly monomeric in solution, while truncated versions of nsp10 have a higher tendency to oligomerise. Small angle X-ray scattering (SAXS) experiments reveal a globular shape of nsp10 which is conserved in all three coronaviruses, including MERS nsp10, which diverges most from SARS and SARS-CoV-2 nsp10s. In conclusion, unbound nsp10 proteins from SARS, MERS, and SARS-CoV-2 are globular and predominantly monomeric in solution. Additionally, we describe for the first time a functional role of the C-terminus of nsp10 for tight binding to nsp14.", - "rel_num_authors": 8, + "rel_link": "https://biorxiv.org/cgi/content/short/2023.06.22.546100", + "rel_abs": "BackgroundAlthough the development of vaccines has considerably reduced the severity of COVID-19, its incidence is still high. Hence, a targeted approach based on RNA endotypes of a population should be developed to help design biomarker-based therapies for COVID-19.\n\nObjectivesWe evaluated the major RNAs transcribed in blood cells during COVID-19 using PCR to further elucidate its pathogenesis and determine predictive phenotypes in COVID-19 patients.\n\nStudy designIn a discovery cohort of 40 patients with COVID-19, 26,354 RNAs were measured on day 1 and day 7. Five RNAs associated with disease severity and prognosis were derived. In a validation cohort of 153 patients with COVID-19 treated in the intensive care unit, we focused on prolactin (PRL), and toll-like receptor 3 (TLR3) among RNAs, which have a strong association with prognosis, and evaluated the accuracy for predicting survival of PRL-to-TL3 ratios (PRL/TLR3) with the areas under the ROC curves (AUC). The validation cohort was divided into two groups based on the cut-off value in the ROC curve with the maximum AUC. The two groups were defined by high PRL/TLR3 (n=47) and low PRL/TLR3 groups (n=106) and the clinical outcomes were compared.\n\nResultsIn the validation cohort, the AUC for PRL/TLR3 was 0.79, showing superior prognostic ability compared to severity scores such as APACHE II and SOFA. The high PRL/TLR3 group had a significantly higher 28-day mortality than the low PRL/TLR3 group (17.0% vs 0.9%, P<0.01).\n\nConclusionsA new RNA endotype classified using high PRL/TLR3 was associated with mortality in COVID-19 patients.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Wolfgang Knecht", - "author_inst": "Lund University" + "author_name": "Jumpei Yoshimura", + "author_inst": "Osaka Daigaku Igakubu Fuzoku Byoin" }, { - "author_name": "Zoe Fisher", - "author_inst": "European Spallation Source" + "author_name": "Yuki Togami", + "author_inst": "Osaka Daigaku Igakubu Fuzoku Byoin" }, { - "author_name": "Jiaqi Lou", - "author_inst": "University College London" + "author_name": "Takeshi Ebihara", + "author_inst": "Osaka Daigaku Igakubu Fuzoku Byoin" }, { - "author_name": "Celeste Sele", - "author_inst": "Lund University" + "author_name": "Hisatake Matsumoto", + "author_inst": "Osaka Daigaku" }, { - "author_name": "Shumeng Ma", - "author_inst": "University College London" + "author_name": "Yumi Mitsuyama", + "author_inst": "Osaka Daigaku Igakubu Fuzoku Byoin" }, { - "author_name": "Anna Andersson Rasmussen", - "author_inst": "Lund University" + "author_name": "Fuminori Sugihara", + "author_inst": "Osaka Daigaku" }, { - "author_name": "Nikos Nikos Pinotsis", - "author_inst": "Birkbeck College" + "author_name": "Haruhiko Hirata", + "author_inst": "Osaka Daigaku Igakubu Fuzoku Byoin" }, { - "author_name": "Frank Gerhard Kozielski", - "author_inst": "University College London" + "author_name": "Daisuke Okuzaki", + "author_inst": "Osaka Daigaku" + }, + { + "author_name": "Hiroshi Ogura", + "author_inst": "Osaka University Graduate School of Medicine" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "new results", - "category": "biochemistry" + "category": "genetics" }, { "rel_doi": "10.1101/2023.06.23.546214", @@ -59921,51 +59544,83 @@ "category": "bioinformatics" }, { - "rel_doi": "10.1101/2023.06.19.545534", - "rel_title": "SARS-CoV-2 variants of concern exhibit differential gastro-intestinal tropism and pathogenesis in the Syrian golden hamster model.", + "rel_doi": "10.1101/2023.06.18.545507", + "rel_title": "Dysregulated Platelet Function and Thrombosis in Patients with Post-Acute Sequelae of COVID-19", "rel_date": "2023-06-19", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2023.06.19.545534", - "rel_abs": "The Coronavirus Disease 2019 (COVID-19) pandemic caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has taken its toll on worldwide public health infrastructure. SARS-CoV-2 is reported to exhibit wide tissue tropism, contributing to its severe pathogenicity that often culminates in multiple-organ failure. The onslaught of this disease has intensified due to the emergence of variants of concern (VOC), such as Delta and Omicron. These variants have been linked to gastrointestinal (GI) symptoms, suggesting a potential fecal-oral route of viral transmission. Here we compared the broad tissue tropism of ancestral Hong-Kong SARS-CoV-2 (SARS-CoV-2 HK) against Delta and Omicron VOCs in aa hamster model by analyzing tissue samples collected from the upper and lower respiratory system and the GI tract. We observed an overall increase in vRNA load and pro- inflammatory cytokines, especially in GI tracts of animals infected with Delta virus, indicating selective virus tropism and pathology in these tissues. However, no apparent spike in Delta viral load was observed in the large intestine and fecal matter. Overall, our research investigates the wide range of tissues that various SARS-CoV-2 strains can infect in hamsters and presents evidence supporting the increased preference of Delta VOCs for infecting the GI tract.", - "rel_num_authors": 8, + "rel_link": "https://biorxiv.org/cgi/content/short/2023.06.18.545507", + "rel_abs": "BackgroundPost-acute sequelae of COVID-19 (PASC), also referred as Long-COVID, sometimes follows COVID-19, a disease caused by SARS-CoV-2. While SARS-CoV-2 is well-known to promote a prothrombotic state, less is known about the thrombosis risk in PASC.\n\nAimOur objective was to evaluate the platelet function and thrombotic potential in patients following recovery from SARS-CoV-2 with clear symptoms of PASC.\n\nMethodsPASC patients and matched healthy controls were enrolled in the study on average 15 months after documented SARS-CoV-2 infection. Platelet activation was evaluated by Light Transmission Aggregometry (LTA) and flow cytometry in response to platelet surface receptor agonists. Thrombosis in platelet-deplete plasma was evaluated by Factor Xa activity. A microfluidics system assessed thrombosis in whole blood under shear stress conditions.\n\nResultsA mild increase in platelet aggregation in PASC patients through the thromboxane receptor was observed and platelet activation through the glycoprotein VI (GPVI) receptor was decreased in PASC patients compared to age- and sex-matched healthy controls. Thrombosis under shear conditions as well as Factor Xa activity were reduced in PASC patients. Plasma from PASC patients was an extremely potent activator of washed, healthy platelets - a phenomenon not observed when stimulating healthy platelets after incubation with plasma from healthy individuals.\n\nConclusionsPASC patients show dysregulated responses in platelets and coagulation in plasma, likely caused by a circulating molecule that promotes thrombosis. A hitherto undescribed protective response appears to exists in PASC patients to counterbalance ongoing thrombosis that is common to SARS-CoV-2 infection.", + "rel_num_authors": 16, "rel_authors": [ { - "author_name": "Santhosh K Nagraj", - "author_inst": "Indian Institute of Science" + "author_name": "Anu Aggarwal", + "author_inst": "Cleveland Clinic Lerner College of Medicine" }, { - "author_name": "Christy M Joy", - "author_inst": "Indian Institute of Science" + "author_name": "Tamanna K Singh", + "author_inst": "Cleveland Clinic" }, { - "author_name": "Rohan Narayan", - "author_inst": "Indian Institute of Science" + "author_name": "Michael Pham", + "author_inst": "Cleveland Clinic" }, { - "author_name": "Rishad Shiraz", - "author_inst": "Indian Institute Of Science" + "author_name": "Matthew Godwin", + "author_inst": "Cleveland Clinic" }, { - "author_name": "Sumandeep Kaur", - "author_inst": "Indian Institute of Science" + "author_name": "Rui Chen", + "author_inst": "Cleveland Clinic" }, { - "author_name": "Oyahida Khatun", - "author_inst": "Indian Institute Of Science" + "author_name": "Thomas M McIntyre", + "author_inst": "Lerner Research Institute" }, { - "author_name": "Sagar Dubey", - "author_inst": "Indian Institute of Science" + "author_name": "Mina K. Chung", + "author_inst": "Cleveland Clinic" }, { - "author_name": "Shashank Tripathi", - "author_inst": "Indian Institute of Science" + "author_name": "Courtney Jennings", + "author_inst": "Cleveland Clinic" + }, + { + "author_name": "Mariya Ali", + "author_inst": "Cleveland Clinic" + }, + { + "author_name": "Huijun Park", + "author_inst": "Cleveland Clinic" + }, + { + "author_name": "Kristin Englund", + "author_inst": "Cleveland Clinic" + }, + { + "author_name": "Alok A Khorana", + "author_inst": "Cleveland Clinic" + }, + { + "author_name": "Lars Svensson", + "author_inst": "Cleveland Clinic" + }, + { + "author_name": "Samir R. Kapadia", + "author_inst": "Cleveland Clinic" + }, + { + "author_name": "Keith R. McCrae", + "author_inst": "Cleveland Clinic" + }, + { + "author_name": "Scott J Cameron", + "author_inst": "Cleveland Clinic Foundation" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_no", "type": "new results", - "category": "pathology" + "category": "pharmacology and toxicology" }, { "rel_doi": "10.1101/2023.06.18.23291573", @@ -61827,33 +61482,221 @@ "category": "cardiovascular medicine" }, { - "rel_doi": "10.1101/2023.06.08.23291154", - "rel_title": "Neurodivergence as a risk factor for Post-Covid-19 Syndrome", + "rel_doi": "10.1101/2023.06.07.23291077", + "rel_title": "Large scale phenotyping of long COVID inflammation reveals mechanistic subtypes of disease", "rel_date": "2023-06-12", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.06.08.23291154", - "rel_abs": "Neurodivergent (ND) individuals (e.g., Autistic people) are more likely to experience health problems that are characterised by central sensitisation . Recent research suggests that a so-called Long-COVID syndrome might also be explained by a heightened response to internal physiological stimuli, much like in myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS). Using a standardised assessment tool, we examined whether traits associated with Autism would predict long-term COVID-19 symptoms in 267 Healthcare Workers (HCW).. Higher autistic traits predicted COVID-19 symptoms that lasting more than 12 weeks regardless of formal autism diagnosis. A personality measure also showed that negative affect was associated with experiencing COVID-19 symptoms for 4-12 weeks, though the direction of causality in this case is uncertain. Limitations of the present study are 1) the retrospective nature of COVID-19 symptom reporting; 2) likely self-selection bias given the high number of HCWs who reported long-term COVID-19 symptoms; and 3) the gender-bias towards females in our sample.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2023.06.07.23291077", + "rel_abs": "One in ten SARS-CoV-2 infections result in prolonged symptoms termed long COVID, yet disease phenotypes and mechanisms are poorly understood. We studied the blood proteome of 719 adults, grouped by long COVID symptoms. Elevated markers of monocytic inflammation and complement activation were associated with increased likelihood of all symptoms. Elevated IL1R2, MATN2 and COLEC12 associated with cardiorespiratory symptoms, fatigue, and anxiety/depression, while elevated MATN2 and DPP10 associated with gastrointestinal (GI) symptoms, and elevated C1QA was associated with cognitive impairment (the proteome of those with cognitive impairment and GI symptoms being most distinct). Markers of neuroinflammation distinguished cognitive impairment whilst elevated SCG3, indicative of brain-gut axis disturbance, distinguished those with GI symptoms. Women had a higher incidence of long COVID and higher inflammatory markers. Symptoms did not associate with respiratory inflammation or persistent virus in sputum. Thus, persistent inflammation is evident in long COVID, distinct profiles being associated with specific symptoms.", + "rel_num_authors": 51, "rel_authors": [ { - "author_name": "Rachael Kathleen Raw", - "author_inst": "Newcastle University" + "author_name": "Felicity Liew", + "author_inst": "NHLI, Imperial College London" }, { - "author_name": "Jon Rees", - "author_inst": "University of Sunderland" + "author_name": "Claudia Efstathiou", + "author_inst": "NHLI, Imperial College London" }, { - "author_name": "Amy Pearson", - "author_inst": "University of Sunderland" + "author_name": "Sara Fontanella", + "author_inst": "National Heart and Lung Institute, Imperial College London" }, { - "author_name": "David Chadwick", - "author_inst": "James Cook University Hospital" + "author_name": "Matthew Richardson", + "author_inst": "Institute for Lung Health, Leicester NIHR Biomedical Research Centre, University of Leicester" + }, + { + "author_name": "Ruth Saunders", + "author_inst": "Institute for Lung Health, Leicester NIHR Biomedical Research Centre, University of Leicester" + }, + { + "author_name": "Dawid Swieboda", + "author_inst": "NHLI, Imperial College London" + }, + { + "author_name": "Jasmin K Sidhu", + "author_inst": "NHLI, Imperial College London" + }, + { + "author_name": "Stephanie Ascough", + "author_inst": "NHLI, Imperial College London" + }, + { + "author_name": "Shona C Moore", + "author_inst": "University of Liverpool" + }, + { + "author_name": "Noura Mohamed", + "author_inst": "The Imperial Clinical Respiratory Research Unit (ICRRU), Imperial College NHS Trust" + }, + { + "author_name": "Jose Nunag", + "author_inst": "Cardiovascular Research Team, Imperial College Healthcare NHS Trust" + }, + { + "author_name": "Clara King", + "author_inst": "Cardiovascular Research Team, Imperial College Healthcare NHS Trust" + }, + { + "author_name": "Olivia C Leavy", + "author_inst": "University of Leicester" + }, + { + "author_name": "Omer Elneima", + "author_inst": "NIHR Respiratory Biomedical Research Centre, University of Leicester" + }, + { + "author_name": "Hamish Joseph Cameron McAULEY", + "author_inst": "University of Leicester" + }, + { + "author_name": "Aarti Shikotra", + "author_inst": "NIHR Leicester Biomedical Research Centre, University of Leicester" + }, + { + "author_name": "Amisha Singapuri", + "author_inst": "Institute for Lung Health, Leicester NIHR Biomedical Research Centre, University of Leicester" + }, + { + "author_name": "Marco Sereno", + "author_inst": "Institute for Lung Health, Leicester NIHR Biomedical Research Centre, University of Leicester" + }, + { + "author_name": "Victoria C Harris", + "author_inst": "Institute for Lung Health, Leicester NIHR Biomedical Research Centre, University of Leicester" + }, + { + "author_name": "Linzy Houchen-Wolloff", + "author_inst": "University Hospitals of Leicester NHS Trust" + }, + { + "author_name": "Neil J Greening", + "author_inst": "University of Leicester" + }, + { + "author_name": "Nazir I Lone", + "author_inst": "Usher Institute, University of Edinburgh" + }, + { + "author_name": "Mathew Thorpe", + "author_inst": "The University of Edinburgh" + }, + { + "author_name": "AA Roger Thompson", + "author_inst": "Department of Infection, Immunity and Cardiovascular Disease, University of Sheffield" + }, + { + "author_name": "Sarah L Rowland-Jones", + "author_inst": "Department of Infection, Immunity and Cardiovascular Disease, University of Sheffield" + }, + { + "author_name": "Annemarie B Docherty", + "author_inst": "University of Edinburgh" + }, + { + "author_name": "James D Chlamers", + "author_inst": "University of Dundee, Ninewells Hospital and Medical School" + }, + { + "author_name": "Ling-Pei B Ho", + "author_inst": "Oxford University" + }, + { + "author_name": "Alexander Horsley", + "author_inst": "University of Manchester" + }, + { + "author_name": "Betty Raman", + "author_inst": "University of Oxford" + }, + { + "author_name": "Krisnah Poinasamy", + "author_inst": "Asthma + Lung UK, London, UK" + }, + { + "author_name": "Michael Marks", + "author_inst": "London School of Hygiene and Tropical Medicine" + }, + { + "author_name": "Onn Min Kon", + "author_inst": "NHLI, Imperial College London" + }, + { + "author_name": "Luke Howard", + "author_inst": "NHLI, Imperial College London" + }, + { + "author_name": "Daniel G Wootton", + "author_inst": "University of Liverpool" + }, + { + "author_name": "Jennifer K Quint", + "author_inst": "NHLI, Imperial College London" + }, + { + "author_name": "Thushan I deSilva", + "author_inst": "The University of Sheffield" + }, + { + "author_name": "Antonia Ho", + "author_inst": "University of Glasgow" + }, + { + "author_name": "Christopher Chiu", + "author_inst": "NHLI, Imperial College London" + }, + { + "author_name": "Ewen M Harrison", + "author_inst": "University of Edinburgh" + }, + { + "author_name": "William Greenhalf", + "author_inst": "Institute of Systems, Molecular and Integrative Biology, University of Liverpool" + }, + { + "author_name": "J Kenneth Baillie", + "author_inst": "Roslin Institute, University of Edinburgh" + }, + { + "author_name": "Malcolm G Semple", + "author_inst": "3.\tNIHR Health Protection Research Unit in Emerging and Zoonotic Infections, Institute of Infection, Veterinary and Ecological Sciences, University of Liverpool" + }, + { + "author_name": "Rachael A Evans", + "author_inst": "Institute for Lung Health, Leicester NIHR Biomedical Research Centre, University of Leicester" + }, + { + "author_name": "Louise V Wain", + "author_inst": "Department of Population Health Sciences, University of Leicester" + }, + { + "author_name": "Christopher Brightling", + "author_inst": "Institute for Lung Health, Leicester NIHR Biomedical Research Centre, University of Leicester" + }, + { + "author_name": "Lance Turtle", + "author_inst": "NIHR Health Protection Research Unit in Emerging and Zoonotic Infections, Institute of Infection, Veterinary and Ecological Sciences, University of Liverpool" + }, + { + "author_name": "Ryan S Thwaites", + "author_inst": "NHLI, Imperial College London" + }, + { + "author_name": "Peter JM Openshaw", + "author_inst": "NHLI, Imperial College London" + }, + { + "author_name": "- ISARIC4C Investigators", + "author_inst": "-" + }, + { + "author_name": "- PHOSP-COVID collaborative group", + "author_inst": "-" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -63309,55 +63152,47 @@ "category": "biochemistry" }, { - "rel_doi": "10.1101/2023.06.08.544212", - "rel_title": "Towards Pandemic-Scale Ancestral Recombination Graphs of SARS-CoV-2", - "rel_date": "2023-06-08", + "rel_doi": "10.1101/2023.06.06.543529", + "rel_title": "Early acquisition of S-specific Tfh clonotypes after SARS-CoV-2 vaccination is associated with the longevity of anti-S antibodies", + "rel_date": "2023-06-07", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2023.06.08.544212", - "rel_abs": "Recombination is an ongoing and increasingly important feature of circulating lineages of SARS-CoV-2, challenging how we represent the evolutionary history of this virus and giving rise to new variants of potential public health concern by combining transmission and immune evasion properties of different lineages. Detection of new recombinant strains is challenging, with most methods looking for breaks between sets of mutations that characterise distinct lineages. In addition, many basic approaches fundamental to the study of viral evolution assume that recombination is negligible, in that a single phylogenetic tree can represent the genetic ancestry of the circulating strains. Here we present an initial version of sc2ts, a method to automatically detect recombinants in real time and to cohesively integrate them into a genealogy in the form of an ancestral recombination graph (ARG), which jointly records mutation, recombination and genetic inheritance. We infer two ARGs under different sampling strategies, and study their properties. One contains 1.27 million sequences sampled up to June 30, 2021, and the second is more sparsely sampled, consisting of 657K sequences sampled up to June 30, 2022. We find that both ARGs are highly consistent with known features of SARS-CoV-2 evolution, recovering the basic backbone phylogeny, mutational spectra, and recapitulating details on the majority of known recombinant lineages. Using the well-established and feature-rich tskit library, the ARGs can also be stored concisely and processed efficiently using standard Python tools. For example, the ARG for 1.27 million sequences--encoding the inferred reticulate ancestry, genetic variation, and extensive metadata--requires 58MB of storage, and loads in less than a second. The ability to fully integrate the effects of recombination into downstream analyses, to quickly and automatically detect new recombinants, and to utilise an efficient and convenient platform for computation based on well-engineered technologies makes sc2ts a promising approach.", - "rel_num_authors": 9, + "rel_link": "https://biorxiv.org/cgi/content/short/2023.06.06.543529", + "rel_abs": "SARS-CoV-2 vaccines have been used worldwide to combat COVID-19 pandemic. To elucidate the factors that determine the longevity of spike (S)-specific antibodies, we traced the characteristics of S-specific T cell clonotypes together with their epitopes and anti-S antibody titers before and after BNT162b2 vaccination over time. T cell receptor (TCR) {beta} sequences and mRNA expression of the S-responded T cells were investigated using single-cell TCR- and RNA-sequencing. Highly expanded 199 TCR clonotypes upon stimulation with S peptide pools were reconstituted into a reporter T cell line for the determination of epitopes and restricting HLAs. Among them, we could determine 78 S epitopes, most of which were conserved in variants of concern (VOCs). In donors exhibiting sustained anti-S antibody titers (designated as \"sustainers\"), S-reactive T cell clonotypes detected immediately after 2nd vaccination polarized to follicular helper T (Tfh) cells, which was less obvious in \"decliners\". Even before vaccination, S-reactive CD4+ T cell clonotypes did exist, most of which cross-reacted with environmental or symbiotic bacteria. However, these clonotypes contracted after vaccination. Conversely, S-reactive clonotypes dominated after vaccination were undetectable in pre-vaccinated T cell pool, suggesting that highly-responding S-reactive T cells were established by vaccination from rare clonotypes. These results suggest that de novo acquisition of memory Tfh cells upon vaccination contributes to the longevity of anti-S antibody titers.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Shing H Zhan", - "author_inst": "University of Oxford" - }, - { - "author_name": "Anastasia Ignatieva", - "author_inst": "University of Glasgow" - }, - { - "author_name": "Yan Wong", - "author_inst": "University of Oxford" + "author_name": "Xiuyuan Lu", + "author_inst": "Laboratory of Molecular Immunology, Immunology Frontier Research Center, Osaka University, Suita, Osaka, Japan" }, { - "author_name": "Katherine Eaton", - "author_inst": "National Microbiology Laboratory, Public Health Agency of Canada, Canada" + "author_name": "Hiroki Hayashi", + "author_inst": "Department of Health Development and Medicine, Osaka University Graduate School of Medicine, Suita, Osaka, Japan" }, { - "author_name": "Benjamin Jeffery", - "author_inst": "University of Oxford" + "author_name": "Eri Ishikawa", + "author_inst": "Department of Molecular Immunology, Research Institute for Microbial Diseases, Osaka University, Suita, Osaka, Japan" }, { - "author_name": "Duncan S Palmer", - "author_inst": "University of Oxford" + "author_name": "Yukiko Takeuchi", + "author_inst": "Laboratory of Molecular Immunology, Immunology Frontier Research Center, Osaka University, Suita, Osaka, Japan" }, { - "author_name": "Carmen Lia Murall", - "author_inst": "National Microbiology Laboratory, Public Health Agency of Canada, Canada" + "author_name": "Julian Vincent Tabora Dychiao", + "author_inst": "Laboratory of Molecular Immunology, Immunology Frontier Research Center, Osaka University, Suita, Osaka, Japan" }, { - "author_name": "Sarah Otto", - "author_inst": "University of British Columbia" + "author_name": "Hironori Nakagami", + "author_inst": "Department of Health Development and Medicine, Osaka University Graduate School of Medicine, Suita, Osaka, Japan" }, { - "author_name": "Jerome Kelleher", - "author_inst": "University of Oxford" + "author_name": "Sho Yamasaki", + "author_inst": "Department of Molecular Immunology, Research Institute for Microbial Diseases, Osaka University, Suita, Osaka, Japan" } ], "version": "1", - "license": "cc_by", + "license": "cc_no", "type": "new results", - "category": "evolutionary biology" + "category": "immunology" }, { "rel_doi": "10.1101/2023.06.06.543969", @@ -64943,99 +64778,27 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2023.06.02.23290879", - "rel_title": "Estimation of introduction and transmission rates of SARS-CoV-2 in a prospective household study", + "rel_doi": "10.1101/2023.06.04.23290948", + "rel_title": "Mental health issues among medical students: Exploring predictors of mental health in Dhaka during COVID-19 pandemic", "rel_date": "2023-06-05", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.06.02.23290879", - "rel_abs": "Household studies provide an efficient means to study transmission of infectious diseases, enabling estimation of individual susceptibility and infectivity. A main inclusion criterion in such studies is often the presence of an infected person. This precludes estimation of the hazards of pathogen introduction into the household. Here we use data from a prospective household-based study to estimate SARS-CoV-2 age- and time-dependent household introduction hazards together with within household transmission rates in the Netherlands from August 2020 to August 2021. Introduction hazards and within-household transmission rates are estimated with penalized splines and stochastic epidemic models, respectively. The estimated hazard of introduction of SARS-CoV-2 in the households was lower for children (0-12 years) than for adults (relative hazard: 0.62; 95%CrI: 0.34-1.0). Estimated introduction hazards peaked in mid October 2020, mid December 2020, and mid April 2021, preceding peaks in hospital admissions by 1-2 weeks. The best fitting transmission models include increased infectivity of children relative to adults and adolescents, such that the estimated child-to-child transmission probability (0.62; 95%CrI: 0.40-0.81) was considerably higher than the adult-to-adult transmission probability (0.12; 95%CrI: 0.057-0.19). Scenario analyses show that vaccination of adults could have strongly reduced infection attack rates in households and that adding adolescent vaccination would have offered limited added benefit.", - "rel_num_authors": 20, + "rel_link": "https://medrxiv.org/cgi/content/short/2023.06.04.23290948", + "rel_abs": "BackgroundMental health has always been under the shadow of everyones belief about their health. Concerns about mental health have already risen in the whole world. The COVID-19 pandemic has caused havoc worldwide, notably in the educational system. It has been difficult to quantify the influence of COVID-19 on the mental health of medical students in Bangladesh.\n\nAimsThis study was conducted to assess medical students mental health status in Dhaka during COVID-19 pandemic.\n\nMethodsThis study was undertaken at Dhaka Medical College, Dhaka, Bangladesh and 359 medical students were the primary respondents for this study.\n\nResultsDepression, anxiety and stress were found in around half of the study participants. Overall, three-fourth of the medical students had poor mental health status. The research study showed that depression, anxiety and stress were dependent on various socio-demographic and behavioral characteristics of medical students.\n\nConclusionPoor mental health is still highly prevalent in the medical students. Different factors like age, gender, academic year, and physical exercise behavior have affected medical students mental health. This calls for attention towards the needs of the more vulnerable demographics and creating a welcoming environment for medical students.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Michiel van Boven", - "author_inst": "Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands" - }, - { - "author_name": "Christiaan H. van Dorp", - "author_inst": "Department of Pathology & Cell Biology, Columbia University Irving Medical Center, New York, United States" - }, - { - "author_name": "Ilse Westerhof", - "author_inst": "Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands" - }, - { - "author_name": "Vincent Jaddoe", - "author_inst": "Erasmus Medical Center, Rotterdam, the Netherlands" - }, - { - "author_name": "Valerie Heuvelman", - "author_inst": "Erasmus Medical Center, Rotterdam, the Netherlands" - }, - { - "author_name": "Liesbeth Duijts", - "author_inst": "Erasmus Medical Center, Rotterdam, the Netherlands" - }, - { - "author_name": "Elandri Fourie", - "author_inst": "Spaarne Gasthuis, Hoofddorp, the Netherlands" - }, - { - "author_name": "Judith Sluiter-Post", - "author_inst": "Spaarne Gasthuis, Hoofddorp, the Netherlands" - }, - { - "author_name": "Marlies A. van Houten", - "author_inst": "Spaarne Gasthuis, Hoofddorp, the Netherlands" - }, - { - "author_name": "Paul Badoux", - "author_inst": "Regional Public Health Laboratory Kennemerland, Haarlem, the Netherlands" - }, - { - "author_name": "Sjoerd Euser", - "author_inst": "Regional Public Health Laboratory Kennemerland, Haarlem, the Netherlands" + "author_name": "Subigya Man Lama", + "author_inst": "American International University Bangladesh" }, { - "author_name": "Bjorn Herpers", - "author_inst": "Regional Public Health Laboratory Kennemerland, Haarlem, the Netherlands" - }, - { - "author_name": "Dirk Eggink", - "author_inst": "National Institute for Public Health and the Environment, Bilthoven, the Netherlands" - }, - { - "author_name": "Trisja Boom", - "author_inst": "Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands" - }, - { - "author_name": "Joanne Wildenbeest", - "author_inst": "Department of Paediatric Infectious Diseases and Immunology, Wilhelmina Children's hospital, University Medical Center Utrecht, the Netherlands" - }, - { - "author_name": "Louis Bont", - "author_inst": "Department of Paediatric Infectious Diseases and Immunology, Wilhelmina Children's hospital, University Medical Center Utrecht, the Netherlands" - }, - { - "author_name": "Ganna Rozhnova", - "author_inst": "Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands" - }, - { - "author_name": "Marc J. Bonten", - "author_inst": "Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands" - }, - { - "author_name": "Mirjam E. Kretzschmar", - "author_inst": "Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands" - }, - { - "author_name": "Patricia Bruijning-Verhagen", - "author_inst": "Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands" + "author_name": "Md. Toufiq Elahi Ahad", + "author_inst": "American International University Bangladesh" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "psychiatry and clinical psychology" }, { "rel_doi": "10.1101/2023.06.01.23290847", @@ -67341,35 +67104,63 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2023.05.25.23290402", - "rel_title": "Infection by SARS-CoV-2 with alternate frequencies of mRNA vaccine boosting for patients undergoing antineoplastic treatment for cancer", - "rel_date": "2023-05-30", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.05.25.23290402", - "rel_abs": "Patients undergoing antineoplastic therapies often exhibit reduced immune response to COVID-19 vaccination, necessitating assessment of alternate boosting frequencies for these patients. However, data on reinfection risks to guide clinical decision-making is limited. We quantified reinfection risks of SARS-CoV-2 at different mRNA boosting frequencies of patients on antineoplastic therapies. Antibody levels following Pfizer-BioNTech BNT162b2 vaccination were analyzed for patients without cancer, with cancer undergoing various treatments, and treated with different antineoplastic therapeutics. Using long-term antibody data from other coronaviruses in an evolutionary framework, we estimated infection probabilities based on antibody levels and projected waning. We calculated cumulative probabilities of breakthrough infection for alternate booster schedules over two years. Annual boosting reduced risks for targeted or hormonal treatments, immunotherapy, and chemotherapy-immunotherapy combinations similarly to the general population. Patients receiving no treatment or chemotherapy exhibited higher risks, suggesting that accelerated vaccination schedules should be considered. Patients treated with rituximab therapy posed the highest infection risk, suggesting that a combination of frequent boosting and additional interventions may be warranted for mitigating SARS-CoV-2 infection in these patients.", - "rel_num_authors": 4, + "rel_doi": "10.1101/2023.05.29.542720", + "rel_title": "Development of a SARS-COV-2 monoclonal antibody panel and its applicability as a reagent in high-throughput fluorescence reduction neutralization and immunohistochemistry assays", + "rel_date": "2023-05-29", + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2023.05.29.542720", + "rel_abs": "Since its emergence in late 2019, infection by SARS-CoV-2 (COVID-19 disease) has quickly spread worldwide, leading to a pandemic that has caused millions of deaths and huge socio-economic losses. Although vaccination against COVID-19 has significantly reduced disease mortality, it has been shown that protection wanes over time, and that circulating SARS-CoV-2 variants may escape vaccine-derived immunity. Therefore, serological studies are still necessary to assess protection in the population and better guide vaccine booster programs. A common measure of protective immunity is the presence of neutralizing antibodies (nAbs). However, the gold standard method for measuring nAbs (plaque reduction neutralization test, or PRNT) is laborious and time-consuming, limiting its large-scale applicability. In this study, we developed a high-throughput fluorescence reduction neutralization assay (FRNA) to detect SARS-CoV-2 nAbs. Because the assay relies on immunostaining, we also developed and characterized in-house monoclonal antibodies (mAbs) to lower assay costs and reduce the vulnerability of the test to reagent shortages. Using samples collected before the pandemic and from individuals vaccinated against COVID-19, we showed that the results of the FRNA we developed using commercial and in-house mAbs strongly correlated with those of the standard PRNT method while providing results in 70% less time. In addition to providing a fast, reliable, and high-throughput alternative for measuring nAbs, the FRNA can be easily customized to assess other SARS-CoV-2 variants of concern (VOCs).", + "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Jeffrey P. Townsend", - "author_inst": "Yale University" + "author_name": "Gabriela Mattoso", + "author_inst": "Instituto Carlos Chagas / Fiocruz PR" }, { - "author_name": "Hayley Hassler", - "author_inst": "Georgia Institute of Technology" + "author_name": "Allan Cataneo", + "author_inst": "Instituto Carlos Chagas / Fiocruz PR" }, { - "author_name": "Brinda Emu", - "author_inst": "Yale University" + "author_name": "Sonia Mara Raboni", + "author_inst": "Universidade Federal do Parana" }, { - "author_name": "Alex Dornburg", - "author_inst": "University of North Carolina Charlotte" + "author_name": "Meri Bordignon Nogueira", + "author_inst": "Universidade Federal do Parana" + }, + { + "author_name": "Caroline Vaz de Paula", + "author_inst": "PUC PR" + }, + { + "author_name": "Ana Clara Almeida", + "author_inst": "PUC PR" + }, + { + "author_name": "Vanessa Rogerio", + "author_inst": "Instituto Carlos Chagas / Fiocruz PR" + }, + { + "author_name": "Nilson Zanchin", + "author_inst": "Instituto Carlos Chagas / Fiocruz PR" + }, + { + "author_name": "Lucia de Noronha", + "author_inst": "Hospital Marcelino Champagnat" + }, + { + "author_name": "Camila Zanluca", + "author_inst": "Instituto Carlos Chagas / Fiocruz PR" + }, + { + "author_name": "Claudia N Duarte dos Santos", + "author_inst": "Instituto Carlos Chagas / Fiocruz PR" } ], "version": "1", - "license": "cc_by", - "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "license": "cc_no", + "type": "new results", + "category": "microbiology" }, { "rel_doi": "10.1101/2023.05.24.23290499", @@ -69891,77 +69682,49 @@ "category": "psychiatry and clinical psychology" }, { - "rel_doi": "10.1101/2023.05.23.23289798", - "rel_title": "Primary Care Post-COVID syndrome Diagnosis and Referral Coding", + "rel_doi": "10.1101/2023.05.23.23290387", + "rel_title": "Spatiotemporal Variations of \"Triple-demic\" Outbreaks of Respiratory Infections in the United States in the Post-COVID-19 Era", "rel_date": "2023-05-24", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.05.23.23289798", - "rel_abs": "IntroductionGuidelines for diagnosing and managing Post-COVID syndrome have been rapidly developed. Consistency of the application of these guidelines in primary care is unknown. Electronic health records provide an opportunity to review the use of codes relating to Post-COVID syndrome. This paper explores the use of primary care records as a surrogate uptake measure for NICEs rapid guideline \"managing the long-term effects of COVID-19\" by measuring the use of Post-COVID syndrome diagnosis and referral codes in the pathway.\n\nMethodWith the approval of NHS England we used routine clinical data from the OpenSafely-EMIS/-TPP platforms. Counts of Post-COVID syndrome diagnosis and referral codes were generated from a cohort of all adults, establishing numbers of diagnoses and referrals following diagnosis. The relationship between Post-COVID syndrome diagnosis and referral codes was explored with reference to NICEs rapid guideline.\n\nResultsOf over 45 million patients, 69,220 (0.15%) had a Post-COVID syndrome diagnostic code, and 67,741 (0.15%) had a referral code. 78% of referral codes did not have an associated diagnosis code. 79% of diagnosis codes had no subsequent referral code. Only 18,633 (0.04%) had both. There were higher rates of both diagnosis and referral in those who were more deprived, female and some ethnic groups.\n\nDiscussionThis study demonstrates variation in diagnosis and referral coding rates for Post-COVID syndrome across different patient groups. The results, with limited crossover of referral and diagnostic codes, suggest only one type of code is usually recorded. Recording one code limits the use of routine data for monitoring Post-COVID syndrome diagnosis and management, but suggests several areas for improvement in coding. Post-COVID syndrome coding, particularly diagnosis coding, needs to improve before administrators and researchers can use it to evaluate care pathways.", - "rel_num_authors": 15, + "rel_link": "https://medrxiv.org/cgi/content/short/2023.05.23.23290387", + "rel_abs": "ObjectivesThe United States confronted a \"triple-demic\" of influenza, respiratory syncytial virus, and COVID-19 in the winter of 2022, resulting in increased respiratory infections and a higher demand for medical supplies. It is urgent to analyze each epidemic and their co-occurrence in space and time to identify hotspots and provide insights for public health strategy.\n\nMethodsWe used retrospective space-time scan statistics to retrospect the situation of COVID-19, influenza, and RSV in 51 US states from October 2021 to February 2022, and then applied prospective space-time scan statistics to monitor spatiotemporal variations of each individual epidemic, respectively and collectively from October 2022 to February 2023.\n\nResultsOur analysis indicated that compared to the winter of 2021, COVID-19 cases decreased while influenza and RSV infections increased significantly during the winter of 2022. We revealed that a twin-demic high-risk cluster of influenza and COVID-19 but no triple-demic clusters emerged during the winter of 2021. We further identified a large high-risk cluster of triple-demic in the central US from late November, with COVID-19, influenza, and RSV having relative risks of 1.14, 1.90, and 1.59, respectively. The number of states at high risk for multiple-demic increased from 15 in October 2022 to 21 in January 2023.\n\nConclusionOur study provides a novel spatiotemporal perspective to explore and monitor the transmission patterns of the triple epidemic, which could inform public health authorities resource allocation to mitigate future outbreaks.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Robert Willans", - "author_inst": "National Institute of Health and Care Excellence" - }, - { - "author_name": "Gail Allsopp", - "author_inst": "Royal College of General Practitioners" - }, - { - "author_name": "Pall Jonsson", - "author_inst": "National Institute of Health and Care Excellence" - }, - { - "author_name": "Fiona Glen", - "author_inst": "National Institute of Health and Care Excellence" - }, - { - "author_name": "Felix Greaves", - "author_inst": "National Institute of Health and Care Excellence" - }, - { - "author_name": "John Macleod", - "author_inst": "University of Bristol" - }, - { - "author_name": "Yinghui Wei", - "author_inst": "University of Plymouth" - }, - { - "author_name": "Sebastian Bacon", - "author_inst": "Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford" + "author_name": "Wei Luo", + "author_inst": "National University of Singapore" }, { - "author_name": "Amir Mehrkar", - "author_inst": "Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford" + "author_name": "Qianhuang Liu", + "author_inst": "National University of Singapore" }, { - "author_name": "Alex Walker", - "author_inst": "Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford" + "author_name": "Yuxuan Zhou", + "author_inst": "National University of Singapore" }, { - "author_name": "Brian MacKenna", - "author_inst": "Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford" + "author_name": "Yiding Ran", + "author_inst": "National University of Singapore" }, { - "author_name": "Louis Fisher", - "author_inst": "Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford" + "author_name": "Zhaoyin Liu", + "author_inst": "National University of Singapore" }, { - "author_name": "Ben Goldacre", - "author_inst": "Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford" + "author_name": "Weitao Hou", + "author_inst": "National University of Singapore" }, { - "author_name": "- The OpenSAFELY Collaborative", - "author_inst": "" + "author_name": "Sen Pei", + "author_inst": "Columbia University" }, { - "author_name": "- The CONVALESCENCE Collaborative", - "author_inst": "" + "author_name": "Shengjie Lai", + "author_inst": "University of Southampton" } ], "version": "1", - "license": "cc_by", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -71713,71 +71476,63 @@ "category": "obstetrics and gynecology" }, { - "rel_doi": "10.1101/2023.05.17.541098", - "rel_title": "SARS-CoV-2 infection leads to Tau pathological signature in neurons", + "rel_doi": "10.1101/2023.05.16.541033", + "rel_title": "Longitudinal analysis of memory T follicular helper cells and antibody response following CoronaVac vaccination", "rel_date": "2023-05-17", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2023.05.17.541098", - "rel_abs": "BackgroundThe coronavirus disease 19 (COVID-19) has represented an issue for global health since its outbreak in March 2020. It is now evident that the SARS-CoV-2 infection results in a wide range of long-term neurological symptoms and is worryingly associated with the aggravation of Alzheimers disease. Little is known about the molecular basis of these manifestations.\n\nMethodsSeveral SARS-CoV-2 strain variants were used to infect SH-SY5Y neuroblastoma cells and K18-hACE C57BL/6J mice. The Tau phosphorylation profile and aggregation propensity upon infection were investigated using immunoblot and immunofluorescence on cellular extracts, subcellular fractions, and brain tissue. The viral proteins Spike, Nucleocapsid, and Membrane were overexpressed in SH-SY5Y cells and the direct effect on Tau phosphorylation was checked using immunoblot experiments.\n\nResultsUpon infection, Tau is phosphorylated at several pathological epitopes associated with Alzheimers disease and other tauopathies. Moreover, this event increases Taus propensity to form insoluble aggregates and alters its subcellular localization.\n\nConclusionsOur data support the evidence that SARS-CoV-2 infection in the Central Nervous System triggers downstream effects altering Tau function, eventually leading to the impairment of neuronal function.", - "rel_num_authors": 13, + "rel_link": "https://biorxiv.org/cgi/content/short/2023.05.16.541033", + "rel_abs": "The inactivated vaccine CoronaVac is one of the most widely used COVID-19 vaccines globally. However, the longitudinal evolution of the immune response induced by CoronaVac remains elusive compared to other vaccine platforms. Here, we recruited 88 healthy individuals that received 3 doses of CoronaVac vaccine. We longitudinally evaluated their polyclonal and antigen-specific CD4+ T cells and neutralizing antibody response after receiving each dose of vaccine for over 300 days. Both the 2nd and 3rd dose of vaccination induced robust spike-specific neutralizing antibodies, with a 3rd vaccine further increased the overall magnitude of antibody response, and neutralization against Omicron sub-lineages B.1.1.529, BA.2, BA.4/BA.5 and BA.2.75.2. Spike-specific CD4+ T cell and circulating T follicular helper (cTFH) cells were markedly increased by the 2nd and 3rd dose of CoronaVac vaccine, accompanied with altered composition of functional cTFH cell subsets with distinct effector and memory potential. Additionally, cTFH cells are positively correlated with neutralizing antibody titers. Our results suggest that CoronaVac vaccine-induced spike-specific T cells are capable of supporting humoral immunity for long-term immune protection.", + "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Cristina Di Primio", - "author_inst": "Istituto di Neuroscienze" - }, - { - "author_name": "Paola Quaranta", - "author_inst": "Retrovirus Center, Virology Section, Department of Translational Research and New Technologies in Medicine and Surgery, University of Pisa." - }, - { - "author_name": "Marianna Mignanelli", - "author_inst": "Laboratorio di Biologia Bio@SNS, Scuola Normale Superiore di Pisa, Piazza dei Cavalieri 7, Pisa, 56126, Italy" + "author_name": "Pengcheng Zhou", + "author_inst": "University of Queensland Diamantina Institute" }, { - "author_name": "Giacomo Siano", - "author_inst": "BIO@SNS" + "author_name": "Cheng Cao", + "author_inst": "Affiliated Hospital of Jiangnan University" }, { - "author_name": "Matteo Bimbati", - "author_inst": "Institute of Neuroscience, Italian National Research Council (CNR), Via Moruzzi, 1, Pisa 56124, Italy. Department of Biotechnology, University of Verona, 37134," + "author_name": "Tuo Ji", + "author_inst": "Affiliated Hospital of Jiangnan University" }, { - "author_name": "Carmen Rita Piazza", - "author_inst": "Retrovirus Center, Virology Section, Department of Translational Research and New Technologies in Medicine and Surgery, University of Pisa. Department of Medica" + "author_name": "Ting Zheng", + "author_inst": "Hospital for Special Surgery" }, { - "author_name": "Piero Giorgio Spezia", - "author_inst": "Retrovirus Center, Virology Section, Department of Translational Research and New Technologies in Medicine and Surgery, University of Pisa." + "author_name": "Yaping Dai", + "author_inst": "The Fifth People's Hospital of Wuxi" }, { - "author_name": "Paola Perrera", - "author_inst": "Retrovirus Center, Virology Section, Department of Translational Research and New Technologies in Medicine and Surgery, University of Pisa." + "author_name": "Min Liu", + "author_inst": "Jiangnan University" }, { - "author_name": "Fulvio Basolo", - "author_inst": "Department of Surgical, Medical and Molecular Pathology, University Hospital of Pisa, Via Paradisa 2, 56124 Pisa, Italy" + "author_name": "Junfeng Jiang", + "author_inst": "Affiliated Hospital of Jiangnan University" }, { - "author_name": "Anello Marcello Poma", - "author_inst": "Department of Surgical, Medical and Molecular Pathology, University Hospital of Pisa, Via Paradisa 2, 56124 Pisa, Italy" + "author_name": "Daoqi Sun", + "author_inst": "Affiliated Hospital of Jiangnan University" }, { - "author_name": "Mario Costa", - "author_inst": "Institute of Neuroscience, Italian National Research Council (CNR), Via Moruzzi, 1, Pisa 56124, Italy" + "author_name": "Zhonghu Bai", + "author_inst": "Jiangnan University" }, { - "author_name": "Mauro Pistello", - "author_inst": "Retrovirus Center, Virology Section, Department of Translational Research and New Technologies in Medicine and Surgery, University of Pisa. Virology Unit, Pisa " + "author_name": "Xiaojie Lu", + "author_inst": "Affiliated Hospital of Jiangnan University" }, { - "author_name": "Antonino Cattaneo", - "author_inst": "Laboratorio di Biologia Bio@SNS, Scuola Normale Superiore di Pisa, Piazza dei Cavalieri 7, Pisa, 56126, Italy" + "author_name": "Fang Gong", + "author_inst": "Affiliated Hospital of Jiangnan University" } ], "version": "1", "license": "cc_by_nc_nd", "type": "new results", - "category": "neuroscience" + "category": "immunology" }, { "rel_doi": "10.1101/2023.05.16.540953", @@ -73299,51 +73054,67 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2023.05.08.23289661", - "rel_title": "COVID-19 in meat plants: activation of a Target Prevention Plan, in Italy", + "rel_doi": "10.1101/2023.05.11.23289783", + "rel_title": "SARS-CoV-2 introductions to the island of Ireland", "rel_date": "2023-05-11", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.05.08.23289661", - "rel_abs": "During the COVID-19 pandemics, several outbreaks have been recorded all other the world in industrial slaughterhouses and meat processing plants. Occupational preventive medicine in such non-healthcare frontline essential services accounts for combined different environmental, social, and economic factors, to reduce the burden of COVID-19 in the workplaces and in the connected residential settings. In Italy, during the first year of the pandemics, an advocacy action has been activated, targeted on meat plant managers and related food business operators. A risk-oriented control plan was agreed by competent Italian Health Authorities at Region/Province level. A questionnaire focused on the inventoried risk factors reported in the literature in such working places have been developped as supporting tool, and administered on voluntary basis to the interested stakeholders. In addition, an outbreak questionnaire was proposed to the Prevention Depts of the Local Health Units. In the 2021 - 2022 years timeframe, we collected 333 advocacy and 24 outbreak questionnaires, respectively, on 4,765 inventoried plants at national level. Responses came mainly from those districts that locally activated the risk-oriented control plan. The lack of awareness to update the Risk Assessment Document of the meat plant for COVID-19, non instrumental body Temperature checks of workers at the entrance, working force from different subcontractors, poor hygiene in the shared places and insufficient ventilation represented the main critical points recorded. The cross-checks between the results from the advocacy and from the outbreak questionnaires are feeding an after-action review for such food-chain related essential work settings within a One Health approach.", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2023.05.11.23289783", + "rel_abs": "Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has had an unprecedented impact on the people of Ireland as waves of infection spread across the island during the global coronavirus disease 2019 (COVID-19) pandemic. Viral whole-genome sequencing (WGS) has provided insights into SARS-CoV-2 molecular mechanisms of pathogenicity and evolution and contributed to the development of anti-virals and vaccines. High levels of WGS have enabled effective SARS-CoV-2 genomic surveillance on the island of Ireland, leading to the generation of a sizeable data set with potential to provide additional insights into viral epidemiology. Because Ireland is an island, accurate documentation of travel rates to and from other regions, both by air and by sea, are available. Furthermore, the two distinct political jurisdictions on the island allow comparison of the impact of varying public health responses on viral dynamics, including SARS-CoV-2 introduction events.\n\nUsing phylogenomic analysis incorporating sample collection date and location metadata, we describe multiple introduction and spreading events for all major viral lineages to the island of Ireland during the period studied (March 2020-June 2022). The majority of SARS-CoV-2 introductions originated from England, with frequent introductions from USA and northwestern Europe. The clusters of sequences predicted to derive from discrete introduction events (\"introduction clusters\") vary greatly in size, with some involving only one or two cases and others comprising thousands of samples. When introduction cluster samples are mapped sequentially by collection date, they appear predominantly in previously affected or adjacent areas. This mirroring of the phylogenetic relationships by the geospatiotemporal propagation of SARS-CoV-2 validates our analytic approach. By downsampling, we estimate the power to detect introductions to Ireland as a function of sequencing levels. Per capita normalisation of both sequencing levels and detected introductions accounts for biases due to differing sequencing efforts and total populations. This approach showed similar rates of introductions for all major lineages into Northern Ireland (NI) and Republic of Ireland (RoI) with the exception of Delta, which was higher in NI which is likely attributable to higher travel per capita. However, there were similar rates of Delta infection within NI and RoI, suggesting that although travel restrictions will reduce risk of introducing novel variants to the region, they may not substantially decrease total incidence.\n\nOur generalisable methodology to study introduction dynamics and optimal sequencing levels will assist public health authorities to select the most appropriate control measures and viral sequencing strategy.", + "rel_num_authors": 12, "rel_authors": [ { - "author_name": "Giorgio Di Leone", - "author_inst": "ASL Bari, Dipartimento di prevenzione, Servizio Prevenzione e Sicurezza degli Ambienti di Lavoro (SPESAL), Via Giorgio de Chirico, 7 - 70056 Molfetta - Italy" + "author_name": "Alan M. Rice", + "author_inst": "Queen's University Belfast" }, { - "author_name": "Luigi Bertinato", - "author_inst": "Istituto Superiore di Sanita', Segreteria Scientifica Del Presidente, Viale Regina Elena, 299 I-00161 Rome, Italy" + "author_name": "Evan P. Troendle", + "author_inst": "Queen's University Belfast" }, { - "author_name": "Gianfranco Brambilla", - "author_inst": "Istituto Superiore di Sanita', Dipartimento Alimentazione, Nutrizione e Sanita' Pubblica Veterinaria, Viale Regina Elena, 299 I-00161 Rome, Italy" + "author_name": "Stephen Bridgett", + "author_inst": "Queen's University Belfast" }, { - "author_name": "Valerio Manno", - "author_inst": "Istituto Superiore di Sanita', Servizio di Statistica, Viale Regina Elena, 299 I-00161 Rome, Italy" + "author_name": "Behnam Firoozi Nejad", + "author_inst": "Queen's University Belfast" }, { - "author_name": "Flavio Napolano", - "author_inst": "ASL Bari, Dipartimento di prevenzione, Servizio Prevenzione e Sicurezza degli Ambienti di Lavoro (SPESAL), Via Giorgio de Chirico, 7 - 70056 Molfetta - Italy" + "author_name": "Jennifer M. McKinley", + "author_inst": "Queens University Belfast" }, { - "author_name": "Simona Savi", - "author_inst": "ATS Citta' metropolitana di Milano, Servizio Prevenzione e Sicurezza Ambienti di Lavoro (SPESAL), sede di Lodi, Piazza ospitale 10, I- 26900 Lodi, Italy" + "author_name": "- The COVID-19 Genomics UK consortium", + "author_inst": "" + }, + { + "author_name": "- National SARS-CoV-2 Surveillance & Whole Genome Sequencing (WGS) Programme", + "author_inst": "" }, { - "author_name": "Gaetano Settimo", - "author_inst": "Istituto Superiore di Sanita', Dipartimento Ambiente e Salute, Viale Regina Elena, 299 I-00161 Rome, Italy" + "author_name": "Declan T. Bradley", + "author_inst": "Health and Social Care Northern Ireland" }, { - "author_name": "Domenico Lagravinese", - "author_inst": "ASL Bari, Dipartimento di prevenzione, Direzione, Lungomare Starita, 6, I-70100 Bari, Italy" + "author_name": "Derek Fairley", + "author_inst": "Belfast Health and Social Care Trust" + }, + { + "author_name": "Connor G. G. Bamford", + "author_inst": "Queen's University Belfast" + }, + { + "author_name": "Timofey Skvortsov", + "author_inst": "Queen's University Belfast" + }, + { + "author_name": "David A. Simpson", + "author_inst": "Queen's University Belfast" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "occupational and environmental health" + "category": "public and global health" }, { "rel_doi": "10.1101/2023.05.09.23289550", @@ -75121,27 +74892,67 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2023.05.08.23289653", - "rel_title": "A global meta-analysis of effects of green infrastructure on COVID-19 infection and mortality rates", + "rel_doi": "10.1101/2023.05.06.23289604", + "rel_title": "Association of Seizure with COVID-19 Vaccines in Persons with Epilepsy: A Systematic Review and Meta-analysis", "rel_date": "2023-05-08", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.05.08.23289653", - "rel_abs": "Evidence of the benefits of greenspaces or greenness to human wellbeing in the context of COVID-19 is fragmented and sometimes contradictory. This calls for a meta-analysis of existing studies to clarify the matter. Here, we identified 621 studies across the world, which were then filtered down to 13 relevant studies covering Africa, Asia, Europe, and USA. These studies were meta-analysed, with the impacts of greenspaces on COVID-19 infection rate quantified using regression estimates whereas impacts on mortality was measured using mortality rate ratios. We found evidence of significant negative correlations between greenness and both COVID-19 infection and mortality rates. We further found that the impacts on COVID-19 infection and mortality are moderated by year of publication, greenness metrics, sample size, health and political covariates. This clarification has far-reaching implications on policy development towards the establishment and management of green infrastructure for the benefits of human wellbeing.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2023.05.06.23289604", + "rel_abs": "ObjectiveSeizure following immunization, especially in persons with epilepsy (PwE), has long been a concern, and seizure aggravation followed by Coronavirus Disease 2019 (COVID-19) vaccines is a serious issue for PwE. The immunization rate in PwE has been lower compared to same-age controls due to vaccine hesitancy and concerns about seizure control. Herein, we systematically reviewed the seizure activity-related events in PwE following COVID-19 vaccination.\n\nMethodsFour search engines were searched from inception until January 31, 2023, and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses was followed. Random- and fixed-effect models using the logit transformation method were used for meta-analysis. The quality of the studies was evaluated by the Newcastle-Ottawa scale. Outcomes of interest included (a) pooled proportion of increased seizure frequency and (b) pooled incidence proportion of status epilepticus (SE) in PwE receiving COVID-19 vaccines.\n\nResultsOf the 2207 studies identified, 18 met eligibility criteria, of which 16 entered the meta-analysis. The pooled proportion of increased seizure frequency (16 studies-4197 PwE) was 5% (95CI: 3%-6%, I2 =57%), further subcategorized into viral vector (3%, 95CI: 2%-7%, I2 =0%), mRNA (5%, 95CI: 4%-7%, I2 =48%), and inactivated (4%, 95CI: 2%-8%, I2 =77%) vaccines. The pooled incidence proportion of SE (15 studies-2480 PwE) was 0.08% (95CI: 0.02%-0.32%, I2 =0%), further subcategorized into the viral vector (0.00%, 95CI: 0.00%-1.00%, I2 =0%), mRNA (0.09%, 95CI: 0.01%-0.62%, I2 =0%), and inactivated (0.00%, 95CI: 0.00%-1.00%, I2 =0%) vaccines. No significant difference was observed between mRNA and viral vector vaccines (5 studies, 1122 vs. 198 PwE, respectively) regarding increased seizure frequency (OR: 1.10, 95CI: 0.49-2.50, p-value=0.81, I2 =0%).\n\nSignificanceThe meta-analysis proposed a 5% increased seizure frequency following COVID-19 vaccination in PwE, with no difference between mRNA and viral vector vaccines. Furthermore, we found a 0.08% incidence proportion for SE. While this safety evidence is noteworthy, this cost should be weighed against vaccination benefits.", + "rel_num_authors": 12, "rel_authors": [ { - "author_name": "Bopaki Phogole Sr.", - "author_inst": "University of Johannesburg" + "author_name": "Ali Rafati", + "author_inst": "1.School of Medicine, Iran University of Medical Sciences, Tehran, Iran. 2. Rajaie Cardiovascular Medical and Research Center, Iran University of Medical Sc" }, { - "author_name": "Kowiyou Yessoufou", - "author_inst": "University of Johannesburg" + "author_name": "Melika Jameie", + "author_inst": "1. Neuroscience Research Center, Iran University of Medical Sciences, Tehran, Iran. 2.Iranian Center of Neurological Research, Neuroscience Institute, Tehr" + }, + { + "author_name": "Mobina Amanollahi", + "author_inst": "Iranian Center of Neurological Research, Neuroscience Institute, Tehran University of Medical Sciences, Tehran, Iran." + }, + { + "author_name": "Mana Jameie", + "author_inst": "Cardiovascular Diseases Research Institute, Tehran Heart Center, Tehran University of Medical Sciences, Tehran, Iran." + }, + { + "author_name": "Yeganeh Pasebani", + "author_inst": "1.School of Medicine, Iran University of Medical Sciences, Tehran, Iran. 2. Rajaie Cardiovascular Medical and Research Center, Iran University of Medical Sc" + }, + { + "author_name": "Delaram Sakhaei", + "author_inst": "School of Medicine, Sari branch, Islamic Azad University, Sari, Iran." + }, + { + "author_name": "Saba Ilkhani", + "author_inst": "Center for Surgery and Public Health, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA." + }, + { + "author_name": "Sina Rashedi", + "author_inst": "1. Non-communicable Diseases Research Center, Endocrinology and Metabolism Population Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran 2." + }, + { + "author_name": "Mohammad Yazdan Pasebani", + "author_inst": "Islamic Azad University East Tehran Branch, Tehran, Iran." + }, + { + "author_name": "Mohammadreza Azadi", + "author_inst": "School of Medicine, Iran University of Medical Sciences, Tehran, Iran." + }, + { + "author_name": "Mehran Rahimlou", + "author_inst": "Department of Nutrition, School of Medicine, Zanjan University of Medical Sciences, Zanjan, Iran." + }, + { + "author_name": "Churl-Su Kwon", + "author_inst": "Columbia University, Departments of Neurology, Epidemiology, Neurosurgery and the Gertrude H. Sergievsky Center, New York, NY, USA." } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "health policy" + "category": "neurology" }, { "rel_doi": "10.1101/2023.05.05.539520", @@ -76963,63 +76774,51 @@ "category": "health economics" }, { - "rel_doi": "10.1101/2023.05.02.23289410", - "rel_title": "UDCA May Promote COVID-19 Recovery: A Cohort Study with AI-Aided Analysis", - "rel_date": "2023-05-04", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.05.02.23289410", - "rel_abs": "To investigate the impact of ursodeoxycholic acid (UDCA) treatment on the clinical outcome of mild and moderate COVID-19 cases, a retrospective analysis was conducted to evaluate the efficacy of UDCA on patients diagnosed with COVID-19 during the peak of the Omicron outbreak in China. This study presents promising results, demonstrating that UDCA significantly reduced the time to Body Temperature Recovery after admission and a higher daily dose seems to be associated with a better outcome without observed safety concerns. We also introduced VirtualBody, a physiologically plausible artificial neural network model, to generate an accurate depiction of the drug concentration-time curve individually, which represented the absorption, distribution, metabolism, and excretion of UDCA in each patient. It exhibits exceptional performance in modeling the complex PK-PD profile of UDCA, characterized by its endogenous and enterohepatic cycling properties, and further validates the effectiveness of UDCA as a treatment option from the drug exposure-response perspective. Our work highlights the potential of UDCA as a novel treatment option for periodic outbreaks of COVID-19 and introduces a new paradigm for PK-PD analysis in retrospective studies to provide evidence for optimal dosing strategies.", - "rel_num_authors": 11, + "rel_doi": "10.1101/2023.05.02.539139", + "rel_title": "Chronic alcohol consumption dysregulates innate immune response to SARS-CoV-2 in the lung", + "rel_date": "2023-05-03", + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2023.05.02.539139", + "rel_abs": "Alcohol consumption is widespread with over half of the individuals over 18 years of age in the U.S. reporting alcohol use in the last 30 days. Moreover, 9 million Americans engaged in binge or chronic heavy drinking (CHD) in 2019. CHD negatively impacts pathogen clearance and tissue repair, including in the respiratory tract, thereby increasing susceptibility to infection. Although, it has been hypothesized that chronic alcohol consumption negatively impacts COVID-19 outcomes; the interplay between chronic alcohol use and SARS-CoV-2 infection outcomes has yet to be elucidated. Therefore, in this study we investigated the impact of chronic alcohol consumption on SARS-CoV-2 anti-viral responses in bronchoalveolar lavage cell samples from humans with alcohol use disorder and rhesus macaques that engaged in chronic drinking. Our data show that in both humans and macaques, the induction of key antiviral cytokines and growth factors was decreased with chronic ethanol consumption. Moreover, in macaques fewer differentially expressed genes mapped to Gene Ontology terms associated with antiviral immunity following 6 month of ethanol consumption while TLR signaling pathways were upregulated. These data are indicative of aberrant inflammation and reduced antiviral responses in the lung with chronic alcohol drinking.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Yang Yu", - "author_inst": "Nanjing University" - }, - { - "author_name": "Guo Yu", - "author_inst": "China Pharmaceutical University" - }, - { - "author_name": "Lu-Yao Han", - "author_inst": "China Pharmaceutical University" - }, - { - "author_name": "Jian Li", - "author_inst": "Nanjing University" + "author_name": "", + "author_inst": "" }, { - "author_name": "Zhi-Long Zhang", - "author_inst": "Nanjing University" + "author_name": "", + "author_inst": "" }, { - "author_name": "Tian-Shuo Liu", - "author_inst": "Nanjing University" + "author_name": "", + "author_inst": "" }, { - "author_name": "Ming-Feng Li", - "author_inst": "China Pharmaceutical University" + "author_name": "", + "author_inst": "" }, { - "author_name": "De-Chuan Zhan", - "author_inst": "Nanjing University" + "author_name": "", + "author_inst": "" }, { - "author_name": "Shao-Qiu Tang", - "author_inst": "Nanjing University" + "author_name": "", + "author_inst": "" }, { - "author_name": "Zhi-Hua Zhou", - "author_inst": "Nanjing University" + "author_name": "", + "author_inst": "" }, { - "author_name": "Guang-Ji Wang", - "author_inst": "China Pharmaceutical University" + "author_name": "", + "author_inst": "" } ], "version": "1", "license": "cc_by_nc_nd", - "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "type": "new results", + "category": "immunology" }, { "rel_doi": "10.1101/2023.05.02.539155", @@ -79369,61 +79168,25 @@ "category": "health informatics" }, { - "rel_doi": "10.1101/2023.04.27.23289199", - "rel_title": "Evaluation of the Pilot Wastewater Surveillance for SARS-CoV-2 in Norway, June 2022 - March 2023", + "rel_doi": "10.1101/2023.04.26.23289095", + "rel_title": "Inequalities in Healthcare Use during the COVID-19 Pandemic", "rel_date": "2023-04-28", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.04.27.23289199", - "rel_abs": "BackgroundDuring the COVID-19 pandemic, wastewater-based surveillance gained great international interest as an additional tool to monitor SARS-CoV-2. In autumn 2021, the Norwegian Institute of Public Health decided to pilot a national wastewater surveillance (WS) system for SARS-CoV-2 and its variants between June 2022 and March 2023. We evaluated the system to assess if it met its objectives and its attribute-based performance.\n\nMethodsWe adapted the available guidelines for evaluation of surveillance systems. The evaluation was carried out as a descriptive analysis and consisted of the following three steps: (i) description of the WS system, (ii) identification of users and stakeholders, and (iii) analysis of the systems attributes and performance including sensitivity, specificity, timeliness, usefulness, representativeness, simplicity, flexibility, stability, and communication. Cross-correlation analysis was performed to assess the systems ability to provide early warning signal of new wave of infections.\n\nResultsThe pilot WS system was a national surveillance system using existing wastewater infrastructures from the largest Norwegian municipalities. We found that the system was sensitive, timely, useful, representative, simple, flexible, acceptable, and stable to follow the general trend of infection. Preliminary results indicate that the system could provide an early signal of changes in variant distribution. However, challenges may arise with: (i) specificity due to temporary fluctuations of RNA levels in wastewater, (ii) representativeness when downscaling, and (iii) flexibility and acceptability when upscaling the system due to limited resources and/or capacity.\n\nConclusionsOur results showed that the pilot WS system met most of its surveillance objectives. The system was able to provide an early warning signal of 1-2 weeks, and the system was useful to monitor infections at population level and complement routine surveillance when individual testing activity was low. However, temporary fluctuations of WS values need to be carefully interpreted. To improve quality and efficiency, we recommend to standardise and validate methods for assessing trends of new waves of infection and variants, evaluate the WS system using a longer operational period particularly for new variants, and conduct prevalence studies in the population to calibrate the system and improve data interpretation.", - "rel_num_authors": 12, + "rel_link": "https://medrxiv.org/cgi/content/short/2023.04.26.23289095", + "rel_abs": "The COVID-19 pandemic has led to severe reductions in non-COVID related healthcare use, but little is known whether this burden is shared equally across the population. This study investigates whether the reduction in administered care disproportionately affected certain sociodemographic strata, in particular marginalised groups. Using detailed medical claims data from the Dutch universal health care system and rich registry data that cover all residents in The Netherlands, we predict expected healthcare use based on pre-pandemic trends (2017- Feb 2020) and compare these expectations with observed healthcare use in 2020. Our findings reveal a substantial 10% decline in the number of weekly treated patients in 2020 relative to prior years. Furthermore, declines in healthcare use are unequally distributed and are more pronounced for individuals below the poverty line, females, the elderly, and foreign-born individuals, with cumulative relative risk ratios ranging from 1.09 to 1.22 higher than individuals above the poverty line, males, young, and native-born. These inequalities stem predominantly from declines in middle and low urgency procedures, and indicate that the pandemic has not only had an unequal toll in terms of the direct health burden of the pandemic, but has also had a differential impact on the use of non-COVID healthcare.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Ettore Amato", - "author_inst": "Norwegian Institute of Public Health" - }, - { - "author_name": "Susanne Hyllestad", - "author_inst": "Norwegian Institute of Public Health" - }, - { - "author_name": "Petter Heradstveit", - "author_inst": "Norwegian Institute of Public Health" - }, - { - "author_name": "Petter Langlete", - "author_inst": "Norwegian Institute of Public Health" - }, - { - "author_name": "Line Victoria Moen", - "author_inst": "Norwegian Institute of Public Health" - }, - { - "author_name": "Andreas Rohringer", - "author_inst": "Norwegian Institute of Public Health" - }, - { - "author_name": "Joao Pires", - "author_inst": "Norwegian Institute of Public Health" - }, - { - "author_name": "Jose Antonio Baz Lomba", - "author_inst": "Norwegian Institute of Public Health" - }, - { - "author_name": "Karoline Bragstad", - "author_inst": "Norwegian Institute of Public Health" - }, - { - "author_name": "Siri Laura Feruglio", - "author_inst": "Norwegian Institute of Public Health" + "author_name": "Arun Frey", + "author_inst": "University of Oxford" }, { - "author_name": "Preben Aavitsland", - "author_inst": "Norwegian Institute of Public Health" + "author_name": "Andrea Tilstra", + "author_inst": "University of Oxford" }, { - "author_name": "Elisabeth Henie Madslien", - "author_inst": "Norwegian Institute of Public Health" + "author_name": "Mark Donald Verhagen", + "author_inst": "University of Oxford" } ], "version": "1", @@ -81307,51 +81070,231 @@ "category": "biochemistry" }, { - "rel_doi": "10.1101/2023.04.23.537985", - "rel_title": "Mechanism of the Covalent Inhibition of Human Transmembrane Protease Serine 2 as an Original Antiviral Strategy", + "rel_doi": "10.1101/2023.04.24.23289025", + "rel_title": "Researching COVID to enhance recovery (RECOVER) pregnancy study protocol: Rationale, objectives, and design", "rel_date": "2023-04-24", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2023.04.23.537985", - "rel_abs": "The Transmembrane Protease Serine 2 (TMPRSS2) is a human enzyme which is involved in the maturation and post-translation of different proteins. In addition of being overexpressed in cancer cells, TMPRSS2 plays a further fundamental role in favoring viral infections by allowing the fusion of the virus envelope and the cellular membrane, notably in SARS-CoV-2. In this contribution we resort to multiscale molecular modeling to unravel the structural and dynamical features of TMPRSS2 and its interaction with a model lipid bilayer. Furthermore, we shed light into the mechanism of action of a potential inhibitor (Nafamostat), determining the free-energy profile associated with the inhibition reaction, and showing the facile poisoning of the enzyme. Our study, while providing the first atomistically resolved mechanism of TMPRSS2 inhibition, is also fundamental in furnishing a solid framework for further rational design targeting transmembrane proteases in a host-directed antiviral strategy.\n\nTOC GRAPHICS\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=193 SRC=\"FIGDIR/small/537985v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (108K):\norg.highwire.dtl.DTLVardef@19dd8c9org.highwire.dtl.DTLVardef@394c0org.highwire.dtl.DTLVardef@11ad383org.highwire.dtl.DTLVardef@347a8c_HPS_FORMAT_FIGEXP M_FIG C_FIG", - "rel_num_authors": 8, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2023.04.24.23289025", + "rel_abs": "ImportancePregnancy induces unique physiologic changes to the immune response and hormonal changes leading to plausible differences in the risk of developing post-acute sequelae of SARS-CoV-2 (PASC), or Long COVID. Exposure to SARS-CoV-2 during pregnancy may also have long-term ramifications for exposed offspring, and it is critical to evaluate the health outcomes of exposed children. The National Institutes of Health (NIH) Researching COVID to Enhance Recovery (RECOVER) Multi-site Observational Study of PASC aims to evaluate the long-term sequelae of SARS-CoV-2 infection in various populations. RECOVER- Pregnancy was designed specifically to address long-term outcomes in maternal-child dyads.\n\nMethodsRECOVER-Pregnancy cohort is a combined prospective and retrospective cohort that proposes to enroll 2,300 individuals with a pregnancy during the COVID-19 pandemic and their offspring exposed and unexposed in utero, including single and multiple gestations. Enrollment will occur both in person at 27 sites through the Eunice Kennedy Shriver National Institutes of Health Maternal-Fetal Medicine Units Network and remotely through national recruitment by the study team at the University of California San Francisco (UCSF). Adults with and without SARS-CoV-2 infection during pregnancy are eligible for enrollment in the pregnancy cohort and will follow the protocol for RECOVER-Adult including validated screening tools, laboratory analyses and symptom questionnaires followed by more in-depth phenotyping of PASC on a subset of the overall cohort. Offspring exposed and unexposed in utero to SARS-CoV-2 maternal infection will undergo screening tests for neurodevelopment and other health outcomes at 12, 18, 24, 36 and 48 months of age. Blood specimens will be collected at 24 months of age for SARS-CoV-2 antibody testing, storage and anticipated later analyses proposed by RECOVER and other investigators.\n\nDiscussionRECOVER-Pregnancy will address whether having SARS-CoV-2 during pregnancy modifies the risk factors, prevalence, and phenotype of PASC. The pregnancy cohort will also establish whether there are increased risks of adverse long-term outcomes among children exposed in utero.\n\nRegistrationNCT05172024", + "rel_num_authors": 53, "rel_authors": [ { - "author_name": "Angelo Spinello", - "author_inst": "Universita di Palermo" + "author_name": "Torri Metz", + "author_inst": "University of Utah Health" }, { - "author_name": "Emmanuelle Bignon", - "author_inst": "Universite de Lorraine" + "author_name": "Rebecca G. Clifton", + "author_inst": "The George Washington University" }, { - "author_name": "Tom Miclot", - "author_inst": "Universita di Palermo" + "author_name": "Richard Gallagher", + "author_inst": "New York University Grossman School of Medicine" }, { - "author_name": "Stephanie Grandemange", - "author_inst": "Universite de Lorraine" + "author_name": "Rachel S. Gross", + "author_inst": "New York University Grossman School of Medicine" }, { - "author_name": "Alessio Terenzi", - "author_inst": "Universita di Palermo" + "author_name": "Leora I. Horwitz", + "author_inst": "New York University Grossman School of Medicine" }, { - "author_name": "Giampaolo Barone", - "author_inst": "Universita di Palermo" + "author_name": "Vanessa L. Jacoby", + "author_inst": "University of California San Francisco" }, { - "author_name": "Florent Barbault", - "author_inst": "Universite Paris Cite" + "author_name": "Susanne P. Martin-Herz", + "author_inst": "University of California San Francisco" }, { - "author_name": "Antonio MONARI", - "author_inst": "Universite Paris Cite" + "author_name": "Myriam Peralta-Carcelen", + "author_inst": "University of Alabama at Birmingham" + }, + { + "author_name": "Harrison T. Reeder", + "author_inst": "Massachusetts General Hospital" + }, + { + "author_name": "Carmen J. Beamon", + "author_inst": "WakeMed Health and Hospitals" + }, + { + "author_name": "Marie-Abele Bind", + "author_inst": "Massachusetts General Hospital" + }, + { + "author_name": "James Chan", + "author_inst": "Massachusetts General Hospital" + }, + { + "author_name": "A. Ann Chang", + "author_inst": "University of California San Francisco" + }, + { + "author_name": "Lori B. Chibnik", + "author_inst": "Massachusetts General Hospital" + }, + { + "author_name": "Maged M. Costantine", + "author_inst": "The Ohio State University Wexner Medical Center" + }, + { + "author_name": "Megan L. Fitzgerald", + "author_inst": "New York University Grossman School of Medicine" + }, + { + "author_name": "Andrea S. Foulkes", + "author_inst": "Massachusetts General Hospital" + }, + { + "author_name": "Kelly S. Gibson", + "author_inst": "The MetroHealth System" + }, + { + "author_name": "Nicholas G\u00fcthe", + "author_inst": "New York University Grossman School of Medicine" + }, + { + "author_name": "Mounira Habli", + "author_inst": "Trihealth Good Samaritan Hospital Maternal Fetal Medicine" + }, + { + "author_name": "David N. Hackney", + "author_inst": "University Hospitals Cleveland Medical Center: UH Cleveland Medical Center" + }, + { + "author_name": "Matthew K. Hoffman", + "author_inst": "Christiana Care Health System" + }, + { + "author_name": "M. Camille Hoffman", + "author_inst": "University of Colorado School of Medicine: University of Colorado Anschutz Medical Campus School of Medicine" + }, + { + "author_name": "Brenna L. Hughes", + "author_inst": "Duke University" + }, + { + "author_name": "Stuart D. Katz", + "author_inst": "New York University Grossman School of Medicine" + }, + { + "author_name": "Victoria Laleau", + "author_inst": "University of California San Francisco" + }, + { + "author_name": "Gail Mallett", + "author_inst": "Northwestern University Feinberg School of Medicine" + }, + { + "author_name": "Hector Mendez-Figueroa", + "author_inst": "University of Texas McGovern Medical School: The University of Texas Health Science Center at Houston John P and Katherine G McGovern Medical School" + }, + { + "author_name": "Vanessa Monzon", + "author_inst": "University of California San Francisco" + }, + { + "author_name": "Anna Palatnik", + "author_inst": "Medical College of Wisconsin" + }, + { + "author_name": "Kristy T.S. Palomares", + "author_inst": "Saint Peter's University Hospital" + }, + { + "author_name": "Samuel Parry", + "author_inst": "University of Pennsylvania" + }, + { + "author_name": "Christian M. Pettker", + "author_inst": "Yale University School of Medicine" + }, + { + "author_name": "Beth A. Plunkett", + "author_inst": "NorthShore University HealthSystem" + }, + { + "author_name": "Athena Poppas", + "author_inst": "Brown University Warren Alpert Medical School" + }, + { + "author_name": "Uma M. Reddy", + "author_inst": "Columbia University" + }, + { + "author_name": "Dwight J. Rouse", + "author_inst": "Brown University" + }, + { + "author_name": "George R. Saade", + "author_inst": "The University of Texas Medical Branch at Galveston" + }, + { + "author_name": "Grecio J. Sandoval", + "author_inst": "The George Washington University" + }, + { + "author_name": "Shannon M. Schlater", + "author_inst": "University of Utah Health" + }, + { + "author_name": "Frank C. Sciurba", + "author_inst": "University of Pittsburgh" + }, + { + "author_name": "Hyagriv N. Simhan", + "author_inst": "University of Pittsburgh School of Medicine" + }, + { + "author_name": "Daniel W. Skupski", + "author_inst": "Weill Cornell Medicine" + }, + { + "author_name": "Amber Sowles", + "author_inst": "University of Utah Health Hospitals and Clinics" + }, + { + "author_name": "Tanayott Thaweethai", + "author_inst": "Massachusetts General Hospital" + }, + { + "author_name": "Gelise L. Thomas", + "author_inst": "Case Western Reserve University" + }, + { + "author_name": "John M. Thorp Jr.", + "author_inst": "UNC: The University of North Carolina at Chapel Hill" + }, + { + "author_name": "Alan T. Tita", + "author_inst": "University of Alabama at Birmingham" + }, + { + "author_name": "Steven J. Weiner", + "author_inst": "The George Washington University" + }, + { + "author_name": "Samantha Wiegand", + "author_inst": "Wright State University Boonshoft School of Medicine" + }, + { + "author_name": "Lynn M. Yee", + "author_inst": "Northwestern University Feinberg School of Medicine" + }, + { + "author_name": "Valerie J. Flaherman", + "author_inst": "University of California San Francisco" + }, + { + "author_name": "- The RECOVER Initiative", + "author_inst": "-" } ], "version": "1", - "license": "cc_by_nc_nd", - "type": "new results", - "category": "biophysics" + "license": "cc_by", + "type": "PUBLISHAHEADOFPRINT", + "category": "obstetrics and gynecology" }, { "rel_doi": "10.1101/2023.04.21.23288730", @@ -83561,77 +83504,93 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2023.04.18.537104", - "rel_title": "A single inactivating amino acid change in the SARS-CoV-2 NSP3 Mac1 domain attenuates viral replication and pathogenesis in vivo", + "rel_doi": "10.1101/2023.04.17.536926", + "rel_title": "Loss-of-function mutation in Omicron variants reduces spike protein expression and attenuates SARS-CoV-2 infection", "rel_date": "2023-04-18", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2023.04.18.537104", - "rel_abs": "Despite unprecedented efforts, our therapeutic arsenal against SARS-CoV-2 remains limited. The conserved macrodomain 1 (Mac1) in NSP3 is an enzyme exhibiting ADP-ribosylhydrolase activity and a possible drug target. To determine the therapeutic potential of Mac1 inhibition, we generated recombinant viruses and replicons encoding a catalytically inactive NSP3 Mac1 domain by mutating a critical asparagine in the active site. While substitution to alanine (N40A) reduced catalytic activity by [~]10-fold, mutations to aspartic acid (N40D) reduced activity by [~]100-fold relative to wildtype. Importantly, the N40A mutation rendered Mac1 unstable in vitro and lowered expression levels in bacterial and mammalian cells. When incorporated into SARS-CoV-2 molecular clones, the N40D mutant only modestly affected viral fitness in immortalized cell lines, but reduced viral replication in human airway organoids by 10-fold. In mice, N40D replicated at >1000-fold lower levels compared to the wildtype virus while inducing a robust interferon response; all animals infected with the mutant virus survived infection and showed no signs of lung pathology. Our data validate the SARS-CoV-2 NSP3 Mac1 domain as a critical viral pathogenesis factor and a promising target to develop antivirals.", - "rel_num_authors": 15, + "rel_link": "https://biorxiv.org/cgi/content/short/2023.04.17.536926", + "rel_abs": "SARS-CoV-2 Omicron variants emerged in 2022 with >30 novel amino acid mutations in the spike protein alone. While most studies focus on receptor binding domain changes, mutations in the C-terminus of S1 (CTS1), adjacent to the furin cleavage site, have largely been ignored. In this study, we examined three Omicron mutations in CTS1: H655Y, N679K, and P681H. Generating a SARS-CoV-2 triple mutant (YKH), we found that the mutant increased spike processing, consistent with prior reports for H655Y and P681H individually. Next, we generated a single N679K mutant, finding reduced viral replication in vitro and less disease in vivo. Mechanistically, the N679K mutant had reduced spike protein in purified virions compared to wild-type; spike protein decreases were further exacerbated in infected cell lysates. Importantly, exogenous spike expression also revealed that N679K reduced overall spike protein yield independent of infection. Although a loss-of-function mutation, transmission competition demonstrated that N679K had a replication advantage in the upper airway over wild-type SARS-CoV-2 in hamsters, potentially impacting transmissibility. Together, the data show that N679K reduces overall spike protein levels during Omicron infection, which has important implications for infection, immunity, and transmission.", + "rel_num_authors": 19, "rel_authors": [ { - "author_name": "Taha Y Taha", - "author_inst": "Gladstone Institutes" + "author_name": "Michelle N Vu", + "author_inst": "University of Texas Medical Branch at Galveston" }, { - "author_name": "Rahul K Suryawanshi", - "author_inst": "Gladstone Institutes, San Francisco, CA" + "author_name": "R. Elias Alvarado", + "author_inst": "University of Texas Medical Branch" }, { - "author_name": "Irene P Chen", - "author_inst": "Gladstone Institutes, San Francisco, CA; Department of Medicine, University of California, San Francisco, CA" + "author_name": "Dorothea R Morris", + "author_inst": "University of Texas Medical Branch" }, { - "author_name": "Galen J Correy", - "author_inst": "University of California, San Francisco, CA" + "author_name": "Kumari G Lokugamage", + "author_inst": "University of Texas Medical Branch" }, { - "author_name": "Patrick C O'Leary", - "author_inst": "University of California, San Francisco, CA" + "author_name": "Yiyang Zhou", + "author_inst": "University of Texas Medical Branch" }, { - "author_name": "Manasi P Jogalekar", - "author_inst": "University of California, San Francisco, CA" + "author_name": "Angelica L Morgan", + "author_inst": "University of Texas Medical Branch" }, { - "author_name": "Maria McCavitt-Malvido", - "author_inst": "Gladstone Institutes, San Francisco, CA" + "author_name": "Leak K Estes", + "author_inst": "University of Texas Medical Branch" }, { - "author_name": "Morgan Diolaiti", - "author_inst": "University of California, San Francisco, CA" + "author_name": "Alyssa M McLeland", + "author_inst": "University of Texas Medical Branch" }, { - "author_name": "Gabriella R Kimmerly", - "author_inst": "Gladstone Institutes, San Francisco, CA" + "author_name": "Craig Schindewolf", + "author_inst": "University of Texas Medical Branch" }, { - "author_name": "Chia-Lin Tsou", - "author_inst": "Gladstone Institutes, San Francisco, CA" + "author_name": "Jessica A Plante", + "author_inst": "University of Texas Medical Branch" }, { - "author_name": "Luis Martinez-Sobrido", - "author_inst": "Texas Biomedical Research Institute, San Antonio, TX" + "author_name": "Yani P Ahearn", + "author_inst": "University of Texas Medical Branch" }, { - "author_name": "Nevan J Krogan", - "author_inst": "University of California, San Francisco, CA" + "author_name": "William M Meyers", + "author_inst": "University of Texas Medical Branch" }, { - "author_name": "Alan Ashworth", - "author_inst": "University of California, San Francisco, CA" + "author_name": "Jordan T Murray", + "author_inst": "University of Texas Medical Branch" }, { - "author_name": "James S Fraser", - "author_inst": "University of California, San Francisco, CA" + "author_name": "Scott Weaver", + "author_inst": "University of Texas Medical Branch" }, { - "author_name": "Melanie Ott", - "author_inst": "Gladstone Institutes" + "author_name": "David H. Walker", + "author_inst": "The University of Texas Medical Branch at Galveston" + }, + { + "author_name": "William K Russell", + "author_inst": "University of Texas Medical Branch" + }, + { + "author_name": "Andrew Laurence Routh", + "author_inst": "University of Texas Medical Branch, Galveston" + }, + { + "author_name": "Kenneth S Plante", + "author_inst": "University of Texas Medical Branch" + }, + { + "author_name": "Vineet D Menachery", + "author_inst": "University of Texas Medical Branch" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nc", "type": "new results", "category": "microbiology" }, @@ -85075,183 +85034,95 @@ "category": "bioinformatics" }, { - "rel_doi": "10.1101/2023.04.12.534029", - "rel_title": "Analysis of SARS-CoV-2 Recombinant Lineages XBC and XBC.1 in the Philippines and Evidence for Delta-Omicron Co-infection as a Potential Origin", + "rel_doi": "10.1101/2023.04.11.536467", + "rel_title": "An Azapeptide Platform in Conjunction with Covalent Warheads to Uncover High-Potency Inhibitors for SARS-CoV-2 Main Protease", "rel_date": "2023-04-12", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2023.04.12.534029", - "rel_abs": "We report the sequencing and analysis of 60 XBC and 114 XBC.1 SARS-CoV-2 lineages detected in the Philippines from August to September 2022, which are regarded as recombinant lineages of the BA.2 Omicron and B.1.617.2 Delta (21I Clade) variants. The sequences described here place the Philippines as the country with the earliest and highest number of XBC and XBC.1 cases within the included period. Majority of the detected cases were sampled from the adjacent Davao and Soccskargen regions in southern Philippines, but have also been observed at lower proportions in other regions of the country. Time-scaled phylogenetic analysis with global samples from GISAID reaffirms the supposed root of XBC-like cases from the Philippines. Furthermore, the apparent clustering of some foreign cases separate from those collected in the country suggests several occurrences of cross-border transmissions resulting in the spread of XBC-like lineages within and among those countries. The consensus mutation profile shows regions harboring mutations specific to either the Omicron BA.2 or Delta B.1.617.2 lineages, supporting the recombinant nature of XBC. Finally, alternative allele fraction pattern and intrahost mutation analysis revealed that a relatively early case of XBC collected in March 2022 is likely to be an active co-infection event. This suggests that co-infection of Omicron and Delta was already occurring in the Philippines early in 2022, facilitating the generation of recombinants that may have further evolved and gained additional mutations enabling its spread across certain local populations at a later time.\n\nAuthor summaryMore recently, various lineages of the SARS-CoV-2 virus, the causative agent COVID-19 pandemic, have been observed to form recombinant lineages, further expanding the ways by which the virus can evolve and adapt to human interventions. Therefore, a large part of biosurveillance efforts is dedicated to detecting and observing new lineages, including recombinants, for early and effective control. In this paper, we present an analysis of 174 XBC and XBC.1 cases detected in the Philippines between August and September of 2022 which contextualize these cases as some of the earliest reported cases of this hybrid lineage. We show that when compared to cases from other countries collected at a similar time, the earliest cases of the XBC lineage are from the Philippines. Additionally, when samples were reclassified following an update of Pangolin, a tool for assigning SARS-CoV-2 lineages to samples, we found two samples of interest reclassified as XBC pointing to a potential origin via co-infection events occurring as early as March of 2022.", - "rel_num_authors": 41, + "rel_link": "https://biorxiv.org/cgi/content/short/2023.04.11.536467", + "rel_abs": "Main protease (MPro) of SARS-CoV-2, the viral pathogen of COVID-19, is a crucial nonstructural protein that plays a vital role in the replication and pathogenesis of the virus. Its protease function relies on three active site pockets to recognize P1, P2, and P4 amino acid residues in a substrate and a catalytic cysteine residue for catalysis. By converting the P1 C atom in an MPro substrate to nitrogen, we showed that a large variety of azapeptide inhibitors with covalent warheads targeting the MPro catalytic cysteine could be easily synthesized. Through the characterization of these inhibitors, we identified several highly potent MPro inhibitors. Specifically, one inhibitor, MPI89 that contained an aza-2,2-dichloroacetyl warhead, displayed a 10 nM EC50 value in inhibiting SARS-CoV-2 from infecting ACE2+ A549 cells and a selectivity index of 875. The crystallography analyses of MPro bound with 6 inhibitors, including MPI89, revealed that inhibitors used their covalent warheads to covalently engage the catalytic cysteine and the aza-amide carbonyl oxygen to bind to the oxyanion hole. MPI89 represents one of the most potent MPro inhibitors developed so far, suggesting that further exploration of the azapeptide platform and the aza-2,2-dichloroacetyl warhead is needed for the development of potent inhibitors for the SARS-CoV-2 MPro as therapeutics for COVID-19.", + "rel_num_authors": 19, "rel_authors": [ { - "author_name": "Elcid Aaron R. Pangilinan", - "author_inst": "Core Facility for Bioinformatics, Philippine Genome Center, University of the Philippines System" - }, - { - "author_name": "John Michael C. Egana", - "author_inst": "Core Facility for Bioinformatics, Philippine Genome Center, University of the Philippines System" - }, - { - "author_name": "Renato Jacinto Q. Mantaring", - "author_inst": "Core Facility for Bioinformatics, Philippine Genome Center, University of the Philippines System" - }, - { - "author_name": "Alyssa Joyce E. Telles", - "author_inst": "Core Facility for Bioinformatics, Philippine Genome Center, University of the Philippines System" - }, - { - "author_name": "Francis A. Tablizo", - "author_inst": "Core Facility for Bioinformatics, Philippine Genome Center, University of the Philippines System" - }, - { - "author_name": "Carlo M. Lapid", - "author_inst": "Core Facility for Bioinformatics, Philippine Genome Center, University of the Philippines System" - }, - { - "author_name": "Maria Sofia L. Yangzon", - "author_inst": "Core Facility for Bioinformatics, Philippine Genome Center, University of the Philippines System" - }, - { - "author_name": "Joshua Jose S. Endozo", - "author_inst": "Core Facility for Bioinformatics, Philippine Genome Center, University of the Philippines System" - }, - { - "author_name": "Karol Sophia Agape R. Padilla", - "author_inst": "Science Education Institute, Department of Science and Technology; DNA Sequencing Core Facility, Philippine Genome Center, University of the Philippines System" - }, - { - "author_name": "Jarvin E. Nipales", - "author_inst": "DNA Sequencing Core Facility, Philippine Genome Center, University of the Philippines System" - }, - { - "author_name": "Lindsay Clare D.L. Carandang", - "author_inst": "DNA Sequencing Core Facility, Philippine Genome Center, University of the Philippines System" - }, - { - "author_name": "Zipporah Mariebelle R. Enriquez", - "author_inst": "DNA Sequencing Core Facility, Philippine Genome Center, University of the Philippines System" - }, - { - "author_name": "Tricia Anne U. Barot", - "author_inst": "DNA Sequencing Core Facility, Philippine Genome Center, University of the Philippines System" - }, - { - "author_name": "Romano A. Manlimos", - "author_inst": "DNA Sequencing Core Facility, Philippine Genome Center, University of the Philippines System" - }, - { - "author_name": "Kelly Nicole P. Mangonon", - "author_inst": "DNA Sequencing Core Facility, Philippine Genome Center, University of the Philippines System" - }, - { - "author_name": "Ma. Exanil L. Plantig", - "author_inst": "DNA Sequencing Core Facility, Philippine Genome Center, University of the Philippines System" - }, - { - "author_name": "Shiela Mae M. Araiza", - "author_inst": "DNA Sequencing Core Facility, Philippine Genome Center, University of the Philippines System" - }, - { - "author_name": "Jo-Hannah S. Llames", - "author_inst": "DNA Sequencing Core Facility, Philippine Genome Center, University of the Philippines System" - }, - { - "author_name": "Kris P. Punayan", - "author_inst": "DNA Sequencing Core Facility, Philippine Genome Center, University of the Philippines System" - }, - { - "author_name": "Rachelle P. Serrano", - "author_inst": "Clinical Multi-Omics Laboratory, Philippine Genome Center, University of the Philippines System" - }, - { - "author_name": "Anne M. Drueco", - "author_inst": "Clinical Multi-Omics Laboratory, Philippine Genome Center, University of the Philippines System" - }, - { - "author_name": "Honeylett T. Lagnas", - "author_inst": "Clinical Multi-Omics Laboratory, Philippine Genome Center, University of the Philippines System" - }, - { - "author_name": "Philip A. Bistayan", - "author_inst": "Clinical Multi-Omics Laboratory, Philippine Genome Center, University of the Philippines System" + "author_name": "Kaustav Khatua", + "author_inst": "Texas A&M University;" }, { - "author_name": "Aristio C. Aguilar", - "author_inst": "Clinical Multi-Omics Laboratory, Philippine Genome Center, University of the Philippines System" + "author_name": "Yugendar Reddy Alugubelli", + "author_inst": "Texas A&M University;" }, { - "author_name": "Joie G. Charisse Apo", - "author_inst": "Clinical Multi-Omics Laboratory, Philippine Genome Center, University of the Philippines System" + "author_name": "Kai Yang", + "author_inst": "Texas A&M University;" }, { - "author_name": "Yvonne Valerie D. Austria", - "author_inst": "Clinical Multi-Omics Laboratory, Philippine Genome Center, University of the Philippines System" + "author_name": "Veerabhadra Reddy", + "author_inst": "Texas A&M University;" }, { - "author_name": "Ni\u00f1a Francesca M. Bustamante", - "author_inst": "Clinical Multi-Omics Laboratory, Philippine Genome Center, University of the Philippines System" + "author_name": "Lauren Blankenship", + "author_inst": "Texas A&M University;" }, { - "author_name": "Alyssa Jamila R. Caelian", - "author_inst": "Clinical Multi-Omics Laboratory, Philippine Genome Center, University of the Philippines System" + "author_name": "Demonta Coleman", + "author_inst": "Texas A&M University;" }, { - "author_name": "Rudy E. Fernandez", - "author_inst": "Clinical Multi-Omics Laboratory, Philippine Genome Center, University of the Philippines System" + "author_name": "Sandeep Atla", + "author_inst": "Texas A&M University;" }, { - "author_name": "Xerxanne A. Galilea", - "author_inst": "Clinical Multi-Omics Laboratory, Philippine Genome Center, University of the Philippines System" + "author_name": "Sankar Chaki", + "author_inst": "Texas A&M University;" }, { - "author_name": "Marielle M. Gamboa", - "author_inst": "Clinical Multi-Omics Laboratory, Philippine Genome Center, University of the Philippines System" + "author_name": "Zhi Geng", + "author_inst": "Texas A&M University;" }, { - "author_name": "Clarence Jane A. Gervacio", - "author_inst": "Clinical Multi-Omics Laboratory, Philippine Genome Center, University of the Philippines System" + "author_name": "Xinyu Ma", + "author_inst": "Texas A&M University;" }, { - "author_name": "Zyrel V. Mollejon", - "author_inst": "Clinical Multi-Omics Laboratory, Philippine Genome Center, University of the Philippines System" + "author_name": "Jing Xiao", + "author_inst": "Texas A&M University;" }, { - "author_name": "Joshua Paul N. Pineda", - "author_inst": "Clinical Multi-Omics Laboratory, Philippine Genome Center, University of the Philippines System" + "author_name": "Peng-Hsun Chen", + "author_inst": "Texas A&M University;" }, { - "author_name": "Kristel B. Rico", - "author_inst": "Clinical Multi-Omics Laboratory, Philippine Genome Center, University of the Philippines System" + "author_name": "Chia-Chuan Cho", + "author_inst": "Texas A&M University;" }, { - "author_name": "Jan Michael C. Yap", - "author_inst": "Core Facility for Bioinformatics, Philippine Genome Center, University of the Philippines System" + "author_name": "Erol Can Vatansever", + "author_inst": "Texas A&M University;" }, { - "author_name": "Ma. Celeste S. Abad", - "author_inst": "DNA Sequencing Core Facility, Philippine Genome Center, University of the Philippines System" + "author_name": "Yuying Ma", + "author_inst": "Texas A&M University;" }, { - "author_name": "Benedict A. Maralit", - "author_inst": "DNA Sequencing Core Facility, Philippine Genome Center, University of the Philippines System" + "author_name": "Ge Yu", + "author_inst": "Texas A&M University;" }, { - "author_name": "Marc Edsel C. Ayes", - "author_inst": "Clinical Multi-Omics Laboratory, Philippine Genome Center, University of the Philippines System" + "author_name": "Benjamin Neuman", + "author_inst": "Texas A&M University;" }, { - "author_name": "Eva Maria Cutiongco-de la Paz", - "author_inst": "Health Research Program, Philippine Genome Center, University of the Philippines System" + "author_name": "Shiqing Xu", + "author_inst": "Texas A&M University;" }, { - "author_name": "Cynthia P. Saloma", - "author_inst": "Philippine Genome Center, University of the Philippines System" + "author_name": "Wenshe Ray Liu", + "author_inst": "Texas A&M University;" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "new results", - "category": "genetics" + "category": "biochemistry" }, { "rel_doi": "10.1101/2023.04.07.23288144", @@ -87116,139 +86987,143 @@ "category": "nephrology" }, { - "rel_doi": "10.1101/2023.04.04.535604", - "rel_title": "SARS-CoV-2 Spike Protein Accumulation in the Skull-Meninges-Brain Axis: Potential Implications for Long-Term Neurological Complications in post-COVID-19", + "rel_doi": "10.1101/2023.04.05.531513", + "rel_title": "The purinergic receptor P2X7 and the NLRP3 inflammasome are druggable host factors required for SARS-CoV-2 infection", "rel_date": "2023-04-05", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2023.04.04.535604", - "rel_abs": "Coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2), has been associated mainly with a range of neurological symptoms, including brain fog and brain tissue loss, raising concerns about the viruss acute and potential chronic impact on the central nervous system. In this study, we utilized mouse models and human post-mortem tissues to investigate the presence and distribution of the SARS-CoV-2 spike protein in the skull-meninges-brain axis. Our results revealed the accumulation of the spike protein in the skull marrow, brain meninges, and brain parenchyma. The injection of the spike protein alone caused cell death in the brain, highlighting a direct effect on brain tissue. Furthermore, we observed the presence of spike protein in the skull of deceased long after their COVID-19 infection, suggesting that the spikes persistence may contribute to long-term neurological symptoms. The spike protein was associated with neutrophil-related pathways and dysregulation of the proteins involved in the PI3K-AKT as well as complement and coagulation pathway. Overall, our findings suggest that SARS-CoV-2 spike protein trafficking from CNS borders into the brain parenchyma and identified differentially regulated pathways may present insights into mechanisms underlying immediate and long-term consequences of SARS-CoV-2 and present diagnostic and therapeutic opportunities.\n\nGraphical Summary\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=109 SRC=\"FIGDIR/small/535604v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (32K):\norg.highwire.dtl.DTLVardef@b223eforg.highwire.dtl.DTLVardef@15539e9org.highwire.dtl.DTLVardef@4d17a9org.highwire.dtl.DTLVardef@14c63af_HPS_FORMAT_FIGEXP M_FIG C_FIG Short SummaryThe accumulation of SARS-CoV-2 spike protein in the skull-meninges-brain axis presents potential molecular mechanisms and therapeutic targets for neurological complications in long-COVID-19 patients.", - "rel_num_authors": 30, + "rel_link": "https://biorxiv.org/cgi/content/short/2023.04.05.531513", + "rel_abs": "Purinergic receptors and NOD-like receptor protein 3 (NLRP3) inflammasome regulate inflammation and viral infection, but their effects on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection remain poorly understood. Here, we report that the purinergic receptor P2X7 and NLRP3 inflammasome are cellular host factors required for SARS-CoV-2 infection. Lung autopsies from patients with severe coronavirus disease 2019 (COVID-19) reveal that NLRP3 expression is increased in host cellular targets of SARS-CoV-2 including alveolar macrophages, type II pneumocytes and syncytia arising from the fusion of infected macrophages, thus suggesting a potential role of NLRP3 and associated signaling pathways to both inflammation and viral replication. In vitro studies demonstrate that NLRP3-dependent inflammasome activation is detected upon macrophage abortive infection. More importantly, a weak activation of NLRP3 inflammasome is also detected during the early steps of SARS-CoV-2 infection of epithelial cells and promotes the viral replication in these cells. Interestingly, the purinergic receptor P2X7, which is known to control NLRP3 inflammasome activation, also favors the replication of D614G and alpha SARS-CoV-2 variants. Altogether, our results reveal an unexpected relationship between the purinergic receptor P2X7, the NLRP3 inflammasome and the permissiveness to SARS-CoV-2 infection that offers novel opportunities for COVID-19 treatment.", + "rel_num_authors": 31, "rel_authors": [ { - "author_name": "Zhouyi Rong", - "author_inst": "Institute for Tissue Engineering and Regenerative Medicine (iTERM), Helmholtz Center Munich, Neuherberg, Germany." + "author_name": "D\u00e9borah L\u00e9cuyer", + "author_inst": "Universit\u00e9 Paris-Saclay, Inserm UMR1030, Gustave Roussy Cancer Center" }, { - "author_name": "Hongcheng Mai", - "author_inst": "Institute for Tissue Engineering and Regenerative Medicine (iTERM), Helmholtz Center Munich, Neuherberg, Germany." + "author_name": "Roberta Nardacci", + "author_inst": "National Institute for Infectious Diseases \"Lazzaro Spallanzani\", UniCamillus - Saint Camillus International University of Health and Medical Sciences" }, { - "author_name": "Saketh Kapoor", - "author_inst": "Institute for Tissue Engineering and Regenerative Medicine (iTERM), Helmholtz Center Munich, Neuherberg, Germany." + "author_name": "D\u00e9sir\u00e9e Tannous", + "author_inst": "Universit\u00e9 Paris-Saclay, Inserm UMR1030, Gustave Roussy Cancer Center, NH TherAguix SAS" }, { - "author_name": "Victor Puelles", - "author_inst": "III. Department of Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany." + "author_name": "Emie Gutierrez-Mateyron", + "author_inst": "Universit\u00e9 Paris-Saclay, Inserm UMR1030, Gustave Roussy Cancer Center" }, { - "author_name": "Jan Czogalla", - "author_inst": "III. Department of Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany." + "author_name": "Aur\u00e9lia Deva-Nathan", + "author_inst": "Universit\u00e9 Paris-Saclay, Inserm UMR1030, Gustave Roussy Cancer Center" }, { - "author_name": "Julia Schaedler", - "author_inst": "Institute of Legal Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany." + "author_name": "Fr\u00e9d\u00e9ric Subra", + "author_inst": "Universit\u00e9 Paris-Saclay, ENS Paris-Saclay, CNRS UMR 8113" }, { - "author_name": "Jessica Vering", - "author_inst": "Institute of Legal Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany." + "author_name": "Cristina Di Primio", + "author_inst": "Institute of Neuroscience, Italian National Research Council, Laboratory of Biology BIO@SNS, Scuola Normale Superiore" }, { - "author_name": "Claire Delbridge", - "author_inst": "Institute of Pathology, Division of Neuropathology, School of Medicine, Technical University Munich, Munich, Germany." + "author_name": "Paola Quaranta", + "author_inst": "Institute of Neuroscience, Italian National Research Council, Laboratory of Biology BIO@SNS, Scuola Normale Superiore" }, { - "author_name": "Hanno Steinke", - "author_inst": "Institute of Anatomy, University of Leipzig, Leipzig, Germany." + "author_name": "Vanessa Petit", + "author_inst": "Universit\u00e9 Paris-Saclay, Inserm U1274, CEA" }, { - "author_name": "Hannah Frenzel", - "author_inst": "Institute of Anatomy, University of Leipzig, Leipzig, Germany." + "author_name": "Cl\u00e9mence Richetta", + "author_inst": "Universit\u00e9 Paris-Saclay, ENS Paris-Saclay, CNRS UMR 8113" }, { - "author_name": "Katja Schmidt", - "author_inst": "Institute of Anatomy, University of Leipzig, Leipzig, Germany." + "author_name": "Ali Mostefa-Kara", + "author_inst": "Universit\u00e9 Paris-Saclay, Inserm UMR1030, Gustave Roussy Cancer Center" }, { - "author_name": "Oezuem Sehnaz Caliskan", - "author_inst": "Institute for Diabetes and Obesity, Helmholtz Center Munich, Neuherberg, Germany." + "author_name": "Franca Del Nonno", + "author_inst": "National Institute for Infectious Diseases \"Lazzaro Spallanzani\"" }, { - "author_name": "Jochen Martin Wettengel", - "author_inst": "Institute of Virology, School of Medicine, Technical University of Munich, Munich, Germany." + "author_name": "Laura Falasca", + "author_inst": "National Institute for Infectious Diseases \"Lazzaro Spallanzani\"" }, { - "author_name": "Fatma Cherif", - "author_inst": "German Center for Neurodegenerative Diseases (DZNE) Munich, Munich, Germany." + "author_name": "Romain Marlin", + "author_inst": "Universit\u00e9 Paris-Saclay, Inserm, CEA, Center for Immunology of Viral, Auto-immune, Hematological and Bacterial diseases (IMVA- HB/IDMIT)" }, { - "author_name": "Mayar Ali", - "author_inst": "Institute for Tissue Engineering and Regenerative Medicine (iTERM), Helmholtz Center Munich, Neuherberg, Germany." + "author_name": "Pauline Maisonnasse", + "author_inst": "Universit\u00e9 Paris-Saclay, Inserm, CEA, Center for Immunology of Viral, Auto-immune, Hematological and Bacterial diseases (IMVA- HB/IDMIT)" }, { - "author_name": "Zeynep Ilgin Kolabas", - "author_inst": "Institute for Tissue Engineering and Regenerative Medicine (iTERM), Helmholtz Center Munich, Neuherberg, Germany." + "author_name": "Julia Delahousse", + "author_inst": "Universit\u00e9 Paris-Saclay, Inserm UMR1030, Gustave Roussy Cancer Center" }, { - "author_name": "Selin Ulukaya", - "author_inst": "Institute for Tissue Engineering and Regenerative Medicine (iTERM), Helmholtz Center Munich, Neuherberg, Germany." + "author_name": "Juliette Pascaud", + "author_inst": "Universit\u00e9 Paris-Saclay, Inserm, CEA, Center for Immunology of Viral, Auto-immune, Hematological and Bacterial diseases (IMVA- HB/IDMIT), Assistance Publique, H" }, { - "author_name": "Izabela Horvath", - "author_inst": "Institute for Tissue Engineering and Regenerative Medicine (iTERM), Helmholtz Center Munich, Neuherberg, Germany." + "author_name": "Eric Deprez", + "author_inst": "Universit\u00e9 Paris-Saclay, ENS Paris-Saclay, CNRS UMR 8113" }, { - "author_name": "Shan Zhao", - "author_inst": "Institute for Tissue Engineering and Regenerative Medicine (iTERM), Helmholtz Center Munich, Neuherberg, Germany." + "author_name": "Marie Naigeon", + "author_inst": "Gustave Roussy Cancer Center, Universit\u00e9 Paris-Saclay, Inserm, CNRS" }, { - "author_name": "Natalie Krahmer", - "author_inst": "Institute for Diabetes and Obesity, Helmholtz Center Munich, Neuherberg, Germany." + "author_name": "Nathalie Chaput", + "author_inst": "Universit\u00e9 Paris-Saclay, Inserm, CNRS, Gustave Roussy Cancer Center" }, { - "author_name": "Sabina Tahirovic", - "author_inst": "German Center for Neurodegenerative Diseases (DZNE) Munich, Munich, Germany." + "author_name": "Angelo Paci", + "author_inst": "Universit\u00e9 Paris-Saclay, Inserm UMR1030, Gustave Roussy Cancer Center" }, { - "author_name": "Ali Oender Yildirim", - "author_inst": "Institute of Lung Health and Immunity (LHI), Comprehensive Pneumology Center (CPC), Helmholtz Munich, Member of the German Center for Lung Research (DZL), Munic" + "author_name": "V\u00e9ronique Saada", + "author_inst": "Gustave Roussy Cancer Center, Department of Biology and Pathology" }, { - "author_name": "Tobias Huber", - "author_inst": "III. Department of Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany." + "author_name": "David Ghez", + "author_inst": "Universit\u00e9 Paris-Saclay, Inserm UMR1030, Gustave Roussy Cancer Center, Department of Hematology" }, { - "author_name": "Benjamin Ondruschka", - "author_inst": "III. Department of Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany." + "author_name": "Xavier Mariette", + "author_inst": "Universit\u00e9 Paris-Saclay, Inserm, CEA, Center for Immunology of Viral, Auto-immune, Hematological and Bacterial diseases (IMVA- HB/IDMIT), Assistance Publique, H" }, { - "author_name": "Ingo Bechmann", - "author_inst": "Institute of Anatomy, University of Leipzig, Leipzig, Germany." + "author_name": "Mario Costa", + "author_inst": "Institute of Neuroscience, Italian National Research Council, Laboratory of Biology BIO@SNS, Scuola Normale Superiore, Centro Pisano ricerca e implementazione c" }, { - "author_name": "Gregor Ebert", - "author_inst": "Institute of Virology, Technical University of Munich/Helmholtz Center Munich, Munich, Germany." + "author_name": "Mauro Pistello", + "author_inst": "Retrovirus Center, Department of Translational Research, Universita of Pisa, Virology Operative Unit, Pisa University Hospital" }, { - "author_name": "Ulrike Protzer", - "author_inst": "Institute of Virology, School of Medicine, Technical University of Munich, Munich, Germany." + "author_name": "Awatef Allouch", + "author_inst": "Universit\u00e9 Paris-Saclay, Inserm UMR1030, Gustave Roussy Cancer Center, NH TherAguix SAS" + }, + { + "author_name": "Olivier Delelis", + "author_inst": "Universit\u00e9 Paris-Saclay, ENS Paris-Saclay, CNRS UMR 8113" }, { - "author_name": "Harsharan Singh Bhatia", - "author_inst": "Institute for Tissue Engineering and Regenerative Medicine (iTERM), Helmholtz Center Munich, Neuherberg, Germany." + "author_name": "Mauro Piacentini", + "author_inst": "National Institute for Infectious Diseases \"Lazzaro Spallanzani\", Department of Biology, University of Rome \"Tor Vergata\"" }, { - "author_name": "Farida Hellal", - "author_inst": "Institute for Tissue Engineering and Regenerative Medicine (iTERM), Helmholtz Center Munich, Neuherberg, Germany." + "author_name": "Roger Le Grand", + "author_inst": "Universit\u00e9 Paris-Saclay, Inserm, CEA, Center for Immunology of Viral, Auto-immune, Hematological and Bacterial diseases (IMVA- HB/IDMIT)" }, { - "author_name": "Ali Erturk", - "author_inst": "Institute for Tissue Engineering and Regenerative Medicine (iTERM), Helmholtz Center Munich, Neuherberg, Germany." + "author_name": "Jean-Luc Perfettini", + "author_inst": "Universit\u00e9 Paris-Saclay, Inserm UMR1030, Gustave Roussy Cancer Center" } ], "version": "1", "license": "cc_by_nc_nd", "type": "new results", - "category": "neuroscience" + "category": "microbiology" }, { "rel_doi": "10.1101/2023.04.05.535700", @@ -88942,63 +88817,43 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2023.03.31.535059", - "rel_title": "Determinants of species-specific utilization of ACE2 by human and animal coronaviruses", + "rel_doi": "10.1101/2023.03.31.535057", + "rel_title": "miRNA binding pressure channels evolution of SARS-CoV-2 genomes", "rel_date": "2023-03-31", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2023.03.31.535059", - "rel_abs": "Utilization of human ACE2 allowed several bat coronaviruses (CoVs), including the causative agent of COVID-19, to infect humans either directly or via intermediate hosts. Here, we analyzed the ability of Spike proteins from 24 human or animal CoVs to use ACE2 receptors across nine reservoir, potential intermediate and human hosts. We show that overall SARS-CoV-2 Omicron variants evolved more efficient ACE2 usage but mutation of R493Q in BA.5 Spike disrupts utilization of ACE2 from Greater horseshoe bats. Spikes from most CoVs showed species-specific differences in ACE2 usage, partly due to variations in ACE2 residues 31, 41 or 354. Mutation of T403R allowed the RaTG13 bat CoV Spike to use all ACE2 orthologs analysed for viral entry. Sera from COVID-19 vaccinated individuals neutralized the Spike proteins of a range of bat Sarbecoviruses. Our results define determinants of ACE2 receptor usage of diverse CoVs and suggest that COVID-19 vaccination may protect against future zoonoses of SARS-CoV-related bat viruses.\n\nHighlightsO_LIMutation of R493Q in BA.5 Spike disrupts utilization of ACE2 from Greater horseshoe bats\nC_LIO_LIVariations in ACE2 residues 31, 41 or 354 affect utilization by coronavirus Spike proteins\nC_LIO_LIResidue R403 in the Spike protein of bat coronavirus allow broad and effective ACE2 usage\nC_LIO_LISera from COVID-19 vaccinated individuals neutralize Spike proteins of bat Sarbecoviruses\nC_LI", - "rel_num_authors": 11, + "rel_link": "https://biorxiv.org/cgi/content/short/2023.03.31.535057", + "rel_abs": "In somatic cells, microRNAs (miRNAs) bind to the genomes of RNA viruses and influence their translation and replication. Here we demonstrate that a significant number of miRNA binding sites locate in the NSP4 region of the SARS-CoV-2 genome, and the intestinal human miRNAs exert evolutionary pressure on this region. Notably, in infected cells, NSP4 promotes the formation of double-membrane vesicles, which serve as the scaffolds for replication-transcriptional complexes and protect viral RNA from intracellular destruction. In three years of selection, the loss of many miRNA binding sites, in particular, those within the NSP4, has shaped the SARS-CoV-2 genomes to promote the descendants of the BA.2 variants as the dominant strains and define current momentum of the pandemics.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Qingxing Wang", - "author_inst": "Institute of Molecular Virology, Ulm University Medical Center, 89081 Ulm, Germany" - }, - { - "author_name": "Sabrina Noettger", - "author_inst": "Institute of Molecular Virology, Ulm University Medical Center, 89081 Ulm, Germany" - }, - { - "author_name": "Qinya Xie", - "author_inst": "Institute of Molecular Virology, Ulm University Medical Center, 89081 Ulm, Germany" - }, - { - "author_name": "Chiara Pastorio", - "author_inst": "Institute of Molecular Virology, Ulm University Medical Center, 89081 Ulm, Germany" - }, - { - "author_name": "Alina Seidel", - "author_inst": "Institute of Molecular Virology, Ulm University Medical Center, 89081 Ulm, Germany" - }, - { - "author_name": "Janis A. Mueller", - "author_inst": "Institute of Molecular Virology, Ulm University Medical Center, 89081 Ulm, Germany" + "author_name": "Anton Zhiyanov", + "author_inst": "HSE University" }, { - "author_name": "Christoph Jung", - "author_inst": "Institute of Electrochemistry, Ulm University, 89081 Ulm, Germany" + "author_name": "Maxim Shkurnikov", + "author_inst": "HSE University" }, { - "author_name": "Timo Jacob", - "author_inst": "Institute of Electrochemistry, Ulm University, 89081 Ulm, Germany" + "author_name": "Ashot Nersisyan", + "author_inst": "HSE University" }, { - "author_name": "Konstantin M.J. Sparrer", - "author_inst": "Institute of Molecular Virology, Ulm University Medical Center, 89081 Ulm, Germany" + "author_name": "Hui Cai", + "author_inst": "Sun Yat-Sen University" }, { - "author_name": "Fabian Zech", - "author_inst": "Institute of Molecular Virology, Ulm University Medical Center, 89081 Ulm, Germany" + "author_name": "Ancha Baranova", + "author_inst": "George Mason University" }, { - "author_name": "Frank Kirchhoff", - "author_inst": "Institute of Molecular Virology, Ulm University Medical Center, 89081 Ulm, Germany" + "author_name": "Alexander Tonevitsky", + "author_inst": "HSE University" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nd", "type": "new results", - "category": "molecular biology" + "category": "evolutionary biology" }, { "rel_doi": "10.1101/2023.03.30.23287923", @@ -90627,91 +90482,55 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2023.03.28.23287759", - "rel_title": "Single-cell analysis of bronchoalveolar cells in inflammatory and fibrotic post-COVID lung disease", + "rel_doi": "10.1101/2023.03.29.23287906", + "rel_title": "Impact of vaccinations, boosters and lockdowns on COVID-19 waves in French Polynesia", "rel_date": "2023-03-29", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.03.28.23287759", - "rel_abs": "AO_SCPLOWBSTRACTC_SCPLOWO_ST_ABSRationaleC_ST_ABSPersistent pulmonary sequelae are evident in many survivors of acute coronavirus disease 2019 (COVID-19) but the molecular mechanisms responsible are incompletely understood. Post-COVID radiological lung abnormalities comprise two broad categories, organising pneumonia and reticulation, interpreted as indicative of subacute inflammation and fibrosis, respectively. Whether these two patterns represent distinct pathologies, likely to require different treatment strategies is not known.\n\nObjectivesWe sought to identify differences at molecular and cellular level, in the local immunopathology of post-COVID inflammation and fibrosis.\n\nMethodsWe compared single-cell transcriptomic profiles and T cell receptor (TCR) repertoires of bronchoalveolar cells obtained from convalescent individuals with each radiological pattern of post-COVID lung disease (PCLD).\n\nMeasurements and Main ResultsInflammatory and fibrotic PCLD single-cell transcriptomes closely resembled each other across all cell types. However, CD4 central memory T cells (TCM) and CD8 effector memory T cells (TEM) were significantly more abundant in inflammatory PCLD. A greater proportion of CD4 TCM also exhibited clonal expansion in inflammatory PCLD. High levels of clustering of similar TCRs from multiple donors was a striking feature of both PCLD phenotypes, consistent with tissue localised antigen-specific immune responses, but there was no enrichment for known SARS-CoV-2 reactive TCRs.\n\nConclusionsThere is no evidence that radiographic organising pneumonia and reticulation in PCLD are associated with differential immmunopathological pathways. Inflammatory radiology is characterised by greater bronchoalveolar T cell accumulation. Both groups show evidence of shared antigen-specific T cell responses, but the antigenic target for these T cells remains to be identified.\n\nScientific knowledge on the subjectThe immune pathogenesis of persistent pulmonary radiological abnormalities following COVID-19 is poorly understood. Whether post-COVID radiological inflammation and fibrosis represent distinct disease entities with different molecular mechanisms of tissue injury is not known.\n\nWhat this study adds to the fieldSingle-cell bronchoalveolar transcriptomes of inflammatory and fibrotic post-COVID lung disease closely resemble each other across all cell types, but CD4 central memory and CD8 effector memory T cells are more abundant in the inflammatory group. Marked T cell receptor clustering, suggestive of antigen-specific responses is evident in both phenotypes. These two radiological patterns likely represent different manifestations of the same disease process, which may benefit from therapies which target T cells.", - "rel_num_authors": 18, + "rel_link": "https://medrxiv.org/cgi/content/short/2023.03.29.23287906", + "rel_abs": "Estimation of the impact of vaccination and non-pharmaceutical interventions (NPIs) on COVID-19 incidence is complicated by several factors, including the successive emergence of SARS-CoV-2 variants of concern and changing population immunity resulting from vaccination and previous infection. We developed an age-structured multi-strain COVID-19 transmission model and inference framework that could estimate the impact of vaccination and NPIs while accounting for these factors. We applied this framework to French Polynesia, which experienced multiple large COVID-19 waves from multiple variants over the course of the pandemic, interspersed with periods of elimination. We estimated that the vaccination programme averted 49.6% (95% credible interval (CI) 48.7-50.5%) of the 5830 hospitalisations and 64.2% (95% CI 63.1-65.3%) of the 1540 hospital deaths that would have occurred in a baseline scenario without any vaccination up to May 2022. Vaccination also averted an estimated 34.8% (95% CI 34.5-35.2%) of 223,000 symptomatic cases in the baseline scenario. We estimated the booster campaign contributed 4.5%, 1.9% and 0.4% to overall reductions in cases, hospitalisations and hospital deaths respectively. Our results suggested that removing, or altering the timings of, the lockdowns during the first two waves had non-linear effects on overall incidence owing to the resulting effect on accumulation of population immunity. Our estimates of vaccination and booster impact differ from those for other countries due to differences in age structure, previous exposure levels and timing of variant introduction relative to vaccination, emphasising the importance of detailed analysis that accounts for these factors.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Puja Mehta", - "author_inst": "UCL Respiratory, University College London, London, UK" - }, - { - "author_name": "Blanca Sanz-Magallon Duque de Estrada", - "author_inst": "Division of Infection and Immunity, University College London, London, UK" - }, - { - "author_name": "Emma K Denneny", - "author_inst": "UCL Respiratory, University College London, London, UK" - }, - { - "author_name": "Kane Foster", - "author_inst": "UCL Cancer Institute, University College London, London, UK" - }, - { - "author_name": "Carolin T Turner", - "author_inst": "Division of Infection and Immunity, University College London, London, UK" - }, - { - "author_name": "Andreas Mayer", - "author_inst": "Division of Infection and Immunity, University College London, London, UK" - }, - { - "author_name": "Martina Milighetti", - "author_inst": "Division of Infection and Immunity, University College London, London, UK" - }, - { - "author_name": "Manuela Plate", - "author_inst": "UCL Respiratory, University College London, London, UK" - }, - { - "author_name": "Kaylee B Worlock", - "author_inst": "UCL Respiratory, University College London, London, UK" - }, - { - "author_name": "Masahiro Yoshida", - "author_inst": "UCL Respiratory, University College London, London, UK" + "author_name": "Lloyd AC Chapman", + "author_inst": "London School of Hygiene and Tropical Medicine" }, { - "author_name": "Jeremy S Brown", - "author_inst": "UCL Respiratory, University College London, London, UK" + "author_name": "Maite Aubry", + "author_inst": "Institute Louis Malarde" }, { - "author_name": "Marko Z Nikolic", - "author_inst": "UCL Respiratory, University College London, London, UK" + "author_name": "Noemie Maset", + "author_inst": "Cellule Epi-surveillance Plateforme COVID-19, French Polynesia" }, { - "author_name": "Arjun Nair", - "author_inst": "Department of Radiology, University College London Hospitals NHS Foundation Trust, London, UK" + "author_name": "Timothy W Russell", + "author_inst": "London School of Hygiene and Tropical Medicine" }, { - "author_name": "Benjamin M Chain", - "author_inst": "Division of Infection and Immunity, University College London, London, UK" + "author_name": "Edward S Knock", + "author_inst": "Imperial College London" }, { - "author_name": "Mahdad Noursadeghi", - "author_inst": "Division of Infection and Immunity, University College London, London, UK" + "author_name": "John A Lees", + "author_inst": "European Molecular Biology Laboratory, European Bioinformatics Institute" }, { - "author_name": "Rachel C Chambers", - "author_inst": "UCL Respiratory, University College London, London, UK" + "author_name": "Henri-Pierre Mallet", + "author_inst": "Cellule Epi-surveillance Plateforme COVID-19, French Polynesia" }, { - "author_name": "Joanna C Porter", - "author_inst": "UCL Respiratory, University College London, London, UK" + "author_name": "Van-Mai Cao-Lormeau", + "author_inst": "Institute Louis Malarde" }, { - "author_name": "Gillian S Tomlinson", - "author_inst": "Division of Infection and Immunity, University College London, London, UK" + "author_name": "Adam J Kucharski", + "author_inst": "London School of Hygiene and Tropical Medicine" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "respiratory medicine" + "category": "epidemiology" }, { "rel_doi": "10.1101/2023.03.27.23287816", @@ -92353,53 +92172,57 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2023.03.21.23287524", - "rel_title": "Employment outcomes of people with Long Covid symptoms: community-based cohort study", + "rel_doi": "10.1101/2023.03.17.23287415", + "rel_title": "Persons Diagnosed with COVID in England in the Clinical Practice Research Datalink (CPRD): A Cohort Description", "rel_date": "2023-03-22", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.03.21.23287524", - "rel_abs": "BackgroundEvidence on the long-term employment consequences of SARS-CoV-2 infection is lacking. We used data from a large, community-based sample in the UK to estimate associations between Long Covid and subsequent employment outcomes.\n\nMethodsThis was an observational, longitudinal study using a pre-post design. We included survey participants from 3 February 2021 to 30 September 2022 when they were aged 16 to 64 years and not in full-time education. Using conditional logit modelling, we explored the time-varying relationship between Long Covid status [≥]12 weeks after a first test-confirmed SARS-CoV-2 infection (reference: pre-infection) and labour market inactivity (neither working nor looking for work) or workplace absence lasting [≥]4 weeks.\n\nResultsOf 206,299 included participants (mean age 45 years, 54% female, 92% white), 15% were ever inactive in the labour market and 10% were ever long-term absent during follow-up. Compared with pre-infection, inactivity was higher in participants reporting Long Covid 30 to <40 weeks (adjusted odds ratio (aOR): 1.45; 95% CI: 1.17 to 1.81) or 40 to <52 weeks (1.34; 1.05 to 1.72) post-infection. Combining with official statistics on Long Covid prevalence, our estimates translate to 27,000 (95% CI: 6,000 to 47,000) working-age adults in the UK being inactive because of Long Covid in July 2022.\n\nConclusionsLong Covid is likely to have contributed to reduced levels of participation in the UK labour market, though it is unlikely to be the sole driver. Further research is required to quantify the contribution of other factors, such as indirect health effects of the pandemic.", - "rel_num_authors": 9, + "rel_link": "https://medrxiv.org/cgi/content/short/2023.03.17.23287415", + "rel_abs": "ObjectiveTo create case definitions for confirmed COVID diagnoses, COVID vaccination status, and three separate definitions of high risk of severe COVID, as well as to assess whether the implementation of these definitions in a cohort reflected the sociodemographic and clinical characteristics of COVID epidemiology in England.\n\nDesignRetrospective cohort study\n\nSettingElectronic healthcare records from primary care (Clinical Practice Research Datalink, or CPRD) linked to secondary care data (Hospital Episode Statistics, or HES) data covering 24% of the population in England\n\nParticipants2,271,072 persons aged 1 year and older diagnosed with COVID in CPRD Aurum between August 1, 2020 through January 31, 2022.\n\nMain Outcome MeasuresAge, sex, and regional distribution of COVID cases and COVID vaccine doses received prior to diagnosis were assessed separately for the cohorts of cases identified in primary care and those hospitalized for COVID (primary diagnosis code of ICD-10 U07.1 \"COVID-19\"). Smoking status, body mass index and Charlson Comorbidity Index were compared for the two cohorts, as well as for three separate definitions of high risk of severe disease used in the United Kingdom (NHS Highest Risk, PANORAMIC trial eligibility, UK Health Security Agency Clinical Risk prioritization for vaccination).\n\nResultsCompared to national estimates, CPRD case estimates underrepresented older adults in both the primary care (age 65-84: 6% in CPRD vs 9% nationally) and hospitalized (31% vs 40%) cohorts, and overrepresented people living in regions with the highest median wealth areas of England (20% primary care and 20% hospital admitted cases in South East, vs 15% nationally). The majority of non-hospitalized cases and all hospitalized cases had not completed primary series vaccination. In primary care, persons meeting high risk definitions were older, more often smokers, overweight or obese, and had higher Charlson Comorbidity Index score.\n\nConclusionsCPRD primary care data is a robust real-world data source and can be used for some COVID research questions, however limitations of the data availability should be carefully considered. Included in this publication are supplemental files for atotal of over 28,000 codes to define each of three definitions of high risk of severe disease.\n\nSUMMARY BOXESO_ST_ABSWhat is already known on this topic?C_ST_ABSO_LIThe UK Government publishes data on cases, hospital admissions and vaccinations related to COVID in England.\nC_LIO_LIThere are at least three definitions of persons at high-risk of severe COVID in use in England.\nC_LI\n\nWhat this study addsO_LIOur study created case definitions for COVID diagnoses, COVID vaccination, and three separate definitions of high risk of severe COVID for use in the Clinical Practice Research Datalink (CPRD), a database covering 24% of England.\nC_LIO_LIThe COVID population in the CPRD has a different age and regional distribution than national case reports, which future studies may need to consider.\nC_LI", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Daniel Ayoubkhani", - "author_inst": "Office for National Statistics" + "author_name": "Kathleen M Andersen", + "author_inst": "Pfizer Inc" }, { - "author_name": "Francesco Zaccardi", - "author_inst": "University of Leicester" + "author_name": "Leah J McGrath", + "author_inst": "Pfizer Inc" }, { - "author_name": "Koen B Pouwels", - "author_inst": "University of Oxford" + "author_name": "Maya Reimbaeva", + "author_inst": "Pfizer Inc" }, { - "author_name": "Ann Sarah Walker", - "author_inst": "University of Oxford" + "author_name": "Diana Mendes", + "author_inst": "Pfizer Ltd" }, { - "author_name": "Donald Houston", - "author_inst": "University of Portsmouth" + "author_name": "Jennifer L Nguyen", + "author_inst": "Pfizer Inc" }, { - "author_name": "Nisreen A Alwan", - "author_inst": "University of Southampton" + "author_name": "Kiran K Rai", + "author_inst": "Adelphi Real World" }, { - "author_name": "Josh Martin", - "author_inst": "Bank of England" + "author_name": "Theo Tritton", + "author_inst": "Adelphi Real World" }, { - "author_name": "Kamlesh Khunti", - "author_inst": "University of Leicester" + "author_name": "Carmen Tsang", + "author_inst": "Pfizer Ltd" }, { - "author_name": "Vahe Nafilyan", - "author_inst": "Office for National Statistics" + "author_name": "Deepa Malhotra", + "author_inst": "Pfizer Inc" + }, + { + "author_name": "Jingyan Yang", + "author_inst": "Pfizer Inc & Columbia University" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -93911,29 +93734,17 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2023.03.20.23287479", - "rel_title": "Childhood Adversity and COVID-19 Outcomes: Findings from the UK Biobank", + "rel_doi": "10.1101/2023.03.13.23287177", + "rel_title": "New Approach to the SIR Inversion Problem: From the 1905-1906 Plague Outbreak in the Isle of Bombay to the 2021-2022 Omicron Surges in New York City and Los Angeles County", "rel_date": "2023-03-20", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.03.20.23287479", - "rel_abs": "ObjectivesTo investigate the association between childhood adversity and COVID-19-related hospitalization and COVID-19-related mortality in the UK Biobank.\n\nDesignCohort study.\n\nSettingUnited Kingdom.\n\nParticipants151,200 participants in the UK Biobank cohort who had completed the Childhood Trauma Screen, were alive at the start of the COVID-19 pandemic (01-10-2021), and were still active in the UK Biobank when hospitalization and mortality data were most recently updated (11-2021).\n\nMain outcome measuresCOVID-19-related hospitalization and COVID-19-related mortality.\n\nResultsHigher self-reports of childhood adversity were related to greater likelihood of COVID-19-related hospitalization in all statistical models. In models adjusted for age, ethnicity, and sex, childhood adversity was associated with an OR of 1.227 of hospitalization (95% CI=1.153 to 1.306, Childhood Adversity z=6.49, p<0.005) and an OR of 1.25 of a COVID-19 related death (95% CI=1.11 to 1.424, Childhood Adversity z=3.5, p<0.005). Adjustment for potential confounds attenuated these associations, although associations remained statistically significant.\n\nConclusionsChildhood adversity was significantly associated with COVID-19-related hospitalization and COVID-19-related mortality after adjusting for sociodemographic and health confounders. Further research is needed to clarify the biological and psychosocial processes underlying these associations to inform public health intervention and prevention strategies to minimize COVID-19 disparities.\n\nTrial registrationWork Completed under UK Biobank Project ID 92699 (\"Associations between COVID-19 Symptoms & Stressful Life Experiences\").\n\nSummary PromptsO_ST_ABSWhat is already known on this topicC_ST_ABSO_LIDisparities in COVID-19 outcomes are driven by numerous health and sociodemographic risk factors\nC_LIO_LIChildhood adversity is associated with lifelong physical health disparities and early mortality\nC_LIO_LINo known studies to date have examined the association between childhood adversity and COVID-19 mortality and morbidity\nC_LI\n\nWhat the study addsO_LIIn the UK Biobank, childhood adversity was significantly associated with COVID-19-related hospitalization and COVID-19-related mortality.\nC_LIO_LIFor both morbidity and mortality, these links were seen in statistical models adjusted for important sociodemographic and physical health confounders.\nC_LI\n\nHow this study might affect research, practice or policyO_LIModifiable and more proximal psychosocial factors may impact adult health outcomes, including COVID-19-related mortality and hospitalization\nC_LIO_LIAdversity may relate to depression, self-concept, or self-regulation, cascading from childhood experiences to the outcomes that we investigated here.\nC_LIO_LIPinpointing these processes may allow for policy and interventions to lessen the negative impact of COVID-19 in those that have suffered childhood adversity.\nC_LI", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2023.03.13.23287177", + "rel_abs": "We describe a novel approach to recovering the underlying parameters of the SIR dynamic epidemic model from observed data on case incidence or deaths. We formulate a discrete-time approximation to the original continuous-time model and search for the parameter vector that minimizes the standard least squares criterion function. We show that the gradient vector and matrix of second-order derivatives of the criterion function with respect to the parameters adhere to their own systems of difference equations and thus can be exactly calculated iteratively. Applying our new approach, we estimate four-parameter SIR models on two datasets: (1) daily reported cases of COVID-19 during the SARS-CoV-2 Omicron/BA.1 surge of December 2021 - March 2022 in New York City; and (2) weekly deaths from a plague outbreak on the Isle of Bombay during December 1905 - July 1906, originally studied by Kermack and McKendrick in their now-classic 1927 paper. The estimated parameters from the COVID-19 data suggest a duration of persistent infectivity beyond that reported in small-scale clinical studies of mostly symptomatic subjects. The estimated parameters from the plague data suggest that the Bombay outbreak was in fact driven by pneumonic rather than bubonic plague.", + "rel_num_authors": 1, "rel_authors": [ { - "author_name": "Jamie L Hanson", - "author_inst": "University of Pittsburgh" - }, - { - "author_name": "Kristen A O'Connor", - "author_inst": "Saint Vincent College" - }, - { - "author_name": "Dorthea J Adkins", - "author_inst": "University of Pittsburgh" - }, - { - "author_name": "Isabella Kahhale", - "author_inst": "University of Pittsburgh" + "author_name": "Jeffrey E Harris", + "author_inst": "Massachusetts Institute of Technology" } ], "version": "1", @@ -96124,49 +95935,25 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2023.03.11.23287148", - "rel_title": "Increased vaccine sensitivity of an emerging SARS-CoV-2 variant", + "rel_doi": "10.1101/2023.03.11.23287141", + "rel_title": "Predicting COVID-19 pandemic waves with biologically and behaviorally informed universal differential equations", "rel_date": "2023-03-16", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.03.11.23287148", - "rel_abs": "Host immune responses are a key source of selective pressure driving pathogen evolution. Emergence of many SARS-CoV-2 lineages has been associated with improvements in their ability to evade population immunity resulting from both vaccination and infection. Here we show diverging trends of escape from vaccine-derived and infection-derived immunity for the emerging XBB/XBB.1.5 Omicron lineage. Among 31,739 patients tested in ambulatory settings in Southern California from December, 2022 to February, 2023, adjusted odds of prior receipt of 2, 3, 4, and [≥]5 COVID-19 vaccine doses were 10% (95% confidence interval: 1-18%), 11% (3-19%), 13% (3-21%), and 25% (15-34%) lower, respectively, among cases infected with XBB/XBB.1.5 than among cases infected with other co-circulating lineages. Similarly, prior vaccination was associated with greater protection against progression to hospitalization among cases with XBB/XBB.1.5 than among non-XBB/XBB.1.5 cases (70% [30-87%] and 48% [7-71%], respectively, for recipients of [≥]4 doses). In contrast, cases infected with XBB/XBB.1.5 had 17% (11-24%) and 40% (19-65%) higher adjusted odds of having experienced 1 and [≥]2 prior documented infections, respectively, including with pre-Omicron variants. As immunity acquired from SARS-CoV-2 infection becomes increasingly widespread, fitness costs associated with enhanced vaccine sensitivity in XBB/XBB.1.5 may be offset by increased ability to evade infection-derived host responses.", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2023.03.11.23287141", + "rel_abs": "In the early stages of the COVID-19 pandemic, it became clear that pandemic waves and population responses were locked in a mutual feedback loop. The initial lull following strict interventions in the first wave often led to a second wave, as restrictions were relaxed. We test the ability of new hybrid machine learning techniques, namely universal differential equations (UDEs) with learning biases, to make predictions in a such a dynamic behavior-disease setting. We develop a UDE model for COVID-19 and test it both with and without learning biases describing simple assumptions about disease transmission and population response. Our results show that UDEs, particularly when supplied with learning biases, are capable of learning coupled behavior-disease dynamics and predicting second waves in a variety of populations. The model predicts a second wave of infections 55% of the time across all populations, having been trained only on the first wave. The predicted second wave is larger than the first. Without learning biases, model predictions are hampered: the unbiased model predicts a second wave only 25% of the time, typically smaller than the first. The biased model consistently predicts the expected increase in the transmission rate with rising mobility, whereas the unbiased model predicts a decrease in mobility as often as a continued increase. The biased model also achieves better accuracy on its training data thanks to fewer and less severely divergent trajectories. These results indicate that biologically informed machine learning can generate qualitatively correct mid to long-term predictions of COVID-19 pandemic waves.\n\nSignificance statementUniversal differential equations are a relatively new modelling technique where neural networks use data to learn unknown components of a dynamical system. We demonstrate for the first time that this technique is able to extract valuable information from data on a coupled behaviour-disease system. Our model was able to learn the interplay between COVID-19 infections and time spent travelling to retail and recreation locations in order to predict a second wave of cases, having been trained only on the first wave. We also demonstrate that adding additional terms to the universal differential equations loss function that penalize implausible solutions improves training time and leads to improved predictions.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Joseph A Lewnard", - "author_inst": "University of California Berkeley" - }, - { - "author_name": "Vennis Hong", - "author_inst": "Kaiser Permanente Southern California" - }, - { - "author_name": "Jeniffer S Kim", - "author_inst": "Kaiser Permanente Southern California" - }, - { - "author_name": "Sally F Shaw", - "author_inst": "Kaiser Permanente Southern California" - }, - { - "author_name": "Bruno Lewin", - "author_inst": "Kaiser Permanente Southern California" - }, - { - "author_name": "Harpreet Takhar", - "author_inst": "Kaiser Permanente Southern California" - }, - { - "author_name": "Marc Lipsitch", - "author_inst": "US Centers for Disease Control & Prevention" + "author_name": "Bruce Kuwahara", + "author_inst": "University of Waterloo" }, { - "author_name": "Sara Y Tartof", - "author_inst": "Kaiser Permanente Southern California" + "author_name": "Chris Bauch", + "author_inst": "University of Waterloo" } ], "version": "1", - "license": "cc_no", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -97782,27 +97569,39 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2023.03.13.532357", - "rel_title": "Inhibition of SARS-CoV-2 3CLpro in vitro by chemically modified tyrosinase from Agaricus bisporus", + "rel_doi": "10.1101/2023.03.13.532385", + "rel_title": "SARS-CoV-2 N-protein induces the formation of composite \u03b1-synuclein/N-protein fibrils that transform into a strain of \u03b1-synuclein fibrils", "rel_date": "2023-03-13", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2023.03.13.532357", - "rel_abs": "Antiviral compounds are crucial to controlling the SARS-CoV-2 pandemic. Approved drugs have been tested for their efficacy against COVID-19, and new pharmaceuticals are being developed as a complementary tool to vaccines However, there are not any effective treatment against this disease yet. In this work, a cheap and fast purification method of natural tyrosinase from Agaricus bisporus fresh mushrooms was developed in order to evaluate the potential of this enzyme as a therapeutic protein by the inhibition of SARS-CoV-2 3CLpro protease activity in vitro. Tyrosinase showed a mild inhibition of 3CLpro of around 15%. Thus, different variants of this protein were synthesized through chemical modifications, covalently binding different tailor-made glycans and peptides to the amino terminal groups of the protein. These new tyrosinase conjugates were purified and characterized by circular dichroism and fluorescence spectroscopy analyses, and their stability under different conditions. Then all these tyrosinase conjugates were tested in 3CLpro protease inhibition. From them, the conjugate between tyrosinase and dextran-aspartic acid (6kDa) polymer showed the highest inhibition, with an IC50 of 2.5 g/ml and IC90 of 5 g/ml, results that highlight the potential use of modified tyrosinase as a therapeutic protein and opens the possibility of developing this and other enzymes as pharmaceutical drugs against diseases.", - "rel_num_authors": 2, + "rel_link": "https://biorxiv.org/cgi/content/short/2023.03.13.532385", + "rel_abs": "The presence of deposits of alpha-synuclein fibrils in cells of the brain are a hallmark of several -synucleinopathies, including Parkinsons disease. As most disease cases are not familial, it is likely that external factors play a role in disease onset. One of the external factors that may influence disease onset are viral infections. It has recently been shown that in the presence of SARS-Cov-2 N-protein, S fibril formation is faster and proceeds in an unusual two-step aggregation process. Here, we show that faster fibril formation is not due to a SARS-CoV-2 N-protein-catalysed formation of an aggregation-prone nucleus. Instead, aggregation starts with the formation of a population of mixed S/N-protein fibrils with low affinity for S. After the depletion of N-protein, fibril formation comes to a halt, until a slow transformation to fibrils with characteristics of pure S fibril strains occurs. This transformation into a strain of S fibrils subsequently results in a second phase of fibril growth until a new equilibrium is reached. Our findings point at the possible relevance of fibril strain transformation in the cell-to-cell spread of the S pathology and disease onset.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "David Aguilera", - "author_inst": "CSIC" + "author_name": "Slav A. Semerdzhiev", + "author_inst": "Nanobiophysics, Faculty of Science and Technology, MESA + Institute for Nanotechnology and Technical Medical Centre, University of Twente, The Netherlands" }, { - "author_name": "Jose M. Palomo", - "author_inst": "Institute of Catalysis-CSIC" + "author_name": "Ine Segers-Nolten", + "author_inst": "Nanobiophysics, Faculty of Science and Technology, MESA + Institute for Nanotechnology and Technical Medical Centre, University of Twente, The Netherlands" + }, + { + "author_name": "Paul van der Schoot", + "author_inst": "Theory of Polymers and Soft Matter, Eindhoven University of Technology, The Netherlands" + }, + { + "author_name": "Christian Blum", + "author_inst": "Nanobiophysics, Faculty of Science and Technology, MESA + Institute for Nanotechnology and Technical Medical Centre, University of Twente, The Netherlands" + }, + { + "author_name": "Mireille M.A.E. Claessens", + "author_inst": "Nanobiophysics, Faculty of Science and Technology, MESA + Institute for Nanotechnology and Technical Medical Centre, University of Twente, The Netherlands" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_by_nd", "type": "new results", - "category": "biochemistry" + "category": "biophysics" }, { "rel_doi": "10.1101/2023.03.09.23286785", @@ -99740,31 +99539,27 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2023.03.06.23286886", - "rel_title": "Archetypal analysis of COVID-19 in Montana, USA, March 13, 2020 to April 26, 2022", + "rel_doi": "10.1101/2023.03.07.23286899", + "rel_title": "Covid-19 impact on food insecurity in Uganda: a dynamic analysis", "rel_date": "2023-03-09", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.03.06.23286886", - "rel_abs": "Given the potential consequences of infectious diseases, it is important to understand how broad scale incidence variability influences the probability of localized outbreaks. Often, these infectious disease data can involve complex spatial patterns intermixed with temporal trends. Archetypal Analysis is a method to mine complex spatiotemporal epidemiological data, and can be used to discover the dynamics of spatial patterns. The application of Archetypal Analysis to epistemological data is relatively new, and here we present one of the first applications using COVID-19 data from March 13, 2020 to April 26, 2022, in the counties of Montana, USA. We present three views of the data set with Archetypal Analysis. First, we evaluate the entire 56 county data set. Second, we compute mutual information of the 56 counties time series to remove counties whose dynamics are mainly independent from most of the other counties. We choose the top 17 counties ranked in terms of increasing total mutual information. Finally, to compare how population size might influence results, we conducted an analysis with 10 of the largest counties. Using the Archetypal Analysis results, we analyze the disease outbreaks across Montana, comparing and contrasting the three different cases and showing how certain counties can be found in distinct sets of archetypes. Using the reconstruction time series, we show how each outbreak had a unique trajectory across the state in terms of the archetypes.\n\nAuthor summaryArchetypal Analysis provides an additional tool for the study of spatio-temporal epidemiological data. We apply Archetypal Analysis to COVID-19 data and reveal how this approach can be used to analyse the dynamics of each COVID-19 outbreak across the state.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2023.03.07.23286899", + "rel_abs": "Lockdowns were used as a tool to avoid excessive social contact and thus limit the spread of Covid-19. However, the true welfare effects of this policy action are still being determined. This paper studies the impact of these lockdowns on the food security outcomes of households in Uganda using a dynamic probit model. We find that the most consequential determinant of whether a households food security was severely impacted by the lockdown was the initial status of whether a family was food insecure to begin with. Also, an increase in a households economic resources (log consumption per person) significantly influences a reduction in the probability of being severely food insecure. Over time, this creates a wedge of greater inequality between the food security of households who were initially food secure and those who were not. This is despite the use of government cash transfers which have turned out to be ineffective.\n\nHighlightsO_LIA dynamic probit model is used to assess the influence Covid lockdowns have had on food security\nC_LIO_LIHouseholds who were initially severely food insecure experienced greater levels of food insecurity post-lockdown, than those who were not.\nC_LIO_LIIncreased command of economic resources reduces the probability of severe food security\nC_LIO_LIContemporaneous government transfers have not made a significant impact on reducing the probability of severe food insecurity\nC_LI", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Emily Stone", - "author_inst": "University of Montana" + "author_name": "Chisom L Ubabukoh", + "author_inst": "O.P Jindal Global University" }, { - "author_name": "Erin Landguth", - "author_inst": "UM: University of Montana" - }, - { - "author_name": "Sebastian Coombs", - "author_inst": "University of Montana" + "author_name": "Gindo Tampubolon", + "author_inst": "The University of Manchester" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "health economics" }, { "rel_doi": "10.1101/2023.03.07.23286673", @@ -101358,59 +101153,71 @@ "category": "biophysics" }, { - "rel_doi": "10.1101/2023.03.05.23286509", - "rel_title": "COVID-19 vaccination coverage and linkages with public willingness to receive vaccination prior to vaccine roll-out: Evidence from Rwanda", + "rel_doi": "10.1101/2023.03.05.531143", + "rel_title": "Mutations in S2 subunit of SARS-CoV-2 Omicron spike strongly influence its conformation, fusogenicity and neutralization sensitivity", "rel_date": "2023-03-06", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.03.05.23286509", - "rel_abs": "The rapid development of multiple SARS-CoV-2 vaccines within one year of the viruss emergence is unprecedented and redefines the timeline for vaccine approval and rollout. Consequently, over 13 billion COVID-19 vaccine doses have been administered worldwide, accounting for [~]70% of the global population. Despite this steadfast scientific achievement, many inequalities exist in vaccine distribution and procurement, particularly in low- and middle-income countries such as those in Africa. This stems from the cost of COVID-19 vaccines, storage and cold-chain challenges, distribution to remote areas, proper personnel training, and so on. In addition to logistical challenges, many developed nations rapidly procured available vaccines, administering second and third doses and leaving many developing nations without the first dose. In this paper, we explore the level of reception to COVID-19 vaccines prior to their availability in Rwanda using a survey-based approach. While several countries reported spikes in vaccine hesitancy generally coinciding with new information, new policies, or newly reported vaccine risks, Rwanda functions as an exemplar for controlling disease burden and educating locals regarding the benefits of vaccination. We show that, even before COVID-19 vaccines were available, many Rwandans (97%) recognized the importance of COVID-19 vaccination and (93%) were willing to receive a COVID-19 vaccine following vaccine availability. Our results underscore the level of preparedness in Rwanda, which rivals and outcompetes many developed nations in terms of vaccination rate (nearing 80% in Rwanda), vaccine acceptance, and local knowledge relating to vaccination. Furthermore, in addition to the whole-of-government coordination as well as tailored delivery approach, previously developed practices relating to vaccination and communication surrounding the Ebola Virus Disease may have compounded the COVID-19 vaccine program in Rwanda, prior to its implementation.", - "rel_num_authors": 10, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2023.03.05.531143", + "rel_abs": "SARS-CoV-2 has remarkable ability to respond to and evolve against the selection pressure by host immunity exemplified by emergence of Omicron lineage. Here, we characterized the functional significance of mutations in Omicron spike. By systematic transfer of mutations in WT spike we assessed neutralization sensitivity, fusogenicity, and TMPRSS2-dependence for entry. The data revealed that the mutations in both S1 and S2 complement to make Omicron highly resistant. Strikingly, the mutations in Omicron S2 modulated the neutralization sensitivity to NTD- and RBD-antibodies, but not to S2 specific neutralizing antibodies, suggesting that the mutations in S2 were primarily acquired to gain resistance to S1-antibodies. Although all six mutations in S2 appeared to act in concert, D796Y showed greatest impact on neutralization sensitivity and rendered WT virus >100-fold resistant to S309, COVA2-17, and 4A8. S2 mutations greatly reduced the antigenicity for NAbs due to reduced exposure of epitopes. In terms of the entry pathway, S1 or S2 mutations only partially altered the entry phenotype of WT and required both sets of mutations for complete switch to endosomal route and loss of syncytia formation. In particular, N856K and L981F in Omicron reduced fusion capacity and explain why subsequent Omicron variants lost them to regain fusogenicity.", + "rel_num_authors": 13, "rel_authors": [ { - "author_name": "Pacifique Ndishimye", - "author_inst": "Laboratory of Emerging Infectious Diseases, Department of Microbiology and Immunology, Faculty of Medicine, Canadian Centre for Vaccinology CCfV, Dalhousie Univ" + "author_name": "Sahil Kumar", + "author_inst": "CSIR-Institute of Microbial Technology" }, { - "author_name": "Gustavo Sganzerla-Martinez", - "author_inst": "Laboratory of Emerging Infectious Diseases, Department of Microbiology and Immunology, Faculty of Medicine, Canadian Centre for Vaccinology CCfV, Dalhousie Univ" + "author_name": "Rathina Delipan", + "author_inst": "CSIR-Institute of Microbial Technology" }, { - "author_name": "Benjamin Hewins", - "author_inst": "Laboratory of Emerging Infectious Diseases, Department of Microbiology and Immunology, Faculty of Medicine, Canadian Centre for Vaccinology CCfV, Dalhousie Univ" + "author_name": "Debajyoti Chakraborty", + "author_inst": "Indian Institute of Science" }, { - "author_name": "Ali Toloue Ostadgavahi", - "author_inst": "Laboratory of Emerging Infectious Diseases, Department of Microbiology and Immunology, Faculty of Medicine, Canadian Centre for Vaccinology CCfV, Dalhousie Univ" + "author_name": "Kawkab Kanjo", + "author_inst": "Indian Institute of Science" }, { - "author_name": "Anuj Kumar", - "author_inst": "Laboratory of Emerging Infectious Diseases, Department of Microbiology and Immunology, Faculty of Medicine, Canadian Centre for Vaccinology CCfV, Dalhousie Univ" + "author_name": "Randhir Singh", + "author_inst": "Mynvax Private Limited, Bengaluru, India" }, { - "author_name": "Mansi Sharma", - "author_inst": "Laboratory of Emerging Infectious Diseases, Department of Microbiology and Immunology, Faculty of Medicine, Canadian Centre for Vaccinology CCfV, Dalhousie Univ" + "author_name": "Nittu Singh", + "author_inst": "CSIR-Institute of Microbial Technology" }, { - "author_name": "Janvier Karuhije", - "author_inst": "Rwanda Biomedical Centre, Ministry of Health, Kigali, Rwanda" + "author_name": "Samreen Siddiqui", + "author_inst": "Max Super Speciality Hospital" }, { - "author_name": "Menelas Nkeshimana", - "author_inst": "University Teaching Hospital of Kigali, Kigali, Rwanda" + "author_name": "Akansha Tyagi", + "author_inst": "Max Super Speciality Hospital" }, { - "author_name": "Sabin Nsanzimana", - "author_inst": "Ministry of Health, Kigali, Rwanda" + "author_name": "Sujeet Jha", + "author_inst": "Max Super Speciality Hospital" }, { - "author_name": "David Kelvin", - "author_inst": "Laboratory of Emerging Infectious Diseases, Department of Microbiology and Immunology, Faculty of Medicine, Canadian Centre for Vaccinology CCfV, Dalhousie Univ" + "author_name": "Krishan Gopal Thakur", + "author_inst": "CSIR-Institute of Microbial Technology" + }, + { + "author_name": "Rajesh Pandey", + "author_inst": "CSIR Institute of Genomics & Integrative Biology" + }, + { + "author_name": "Raghavan Varadarajan", + "author_inst": "Indian Institute of Science, Bengaluru." + }, + { + "author_name": "Rajesh P Ringe", + "author_inst": "CSIR-Institute of Microbial technology" } ], "version": "1", - "license": "cc_no", - "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "license": "cc_by_nc_nd", + "type": "new results", + "category": "microbiology" }, { "rel_doi": "10.1101/2023.03.03.531067", @@ -103020,35 +102827,27 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2023.03.02.23286677", - "rel_title": "Analysis of SARS-CoV-2 mutations associated with resistance to therapeutic monoclonal antibodies that emerge after treatment.", + "rel_doi": "10.1101/2023.03.01.530717", + "rel_title": "Assessment of neutralization susceptibility of Omicron subvariants XBB.1.5 and BQ.1.1 against broad-spectrum neutralizing antibodies through epitopes mapping", "rel_date": "2023-03-02", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.03.02.23286677", - "rel_abs": "The mutation rate of the Omicron sublineage has led to baseline resistance against all previously authorized anti-Spike monoclonal antibodies (mAbs). Nevertheless, in case more antiviral mAbs will be authorized in the future, it is relevant to understand how frequently treatment-emergent resistance has emerged so far, under different combinations and in different patient subgroups. We report the results of a systematic review of the medical literature for case reports and case series for treatment-emergent immune escape, which is defined as emergence of a resistance-driving mutation in at least 20% of sequences in a given host at a given timepoint. We identified 31 publications detailing 201 cases that included different variants of concern (VOC) and found that the incidence of treatment emergent-resistance ranged from 10% to 50%. Most of the treatment-emergent resistance events occurred in immunocompromised patients. Interestingly, resistance also emerged against cocktails of two mAbs, albeit at lower frequencies. The heterogenous therapeutic management of those cases doesnt allow inferences about the clinical outcome in patients with treatment-emergent resistance. Furthermore, we noted a temporal correlation between the introduction of mAb therapies and a subsequent increase in SARS-CoV-2 sequences across the globe carrying mutations conferring resistance to that mAb, raising concern as to whether these had originated in mAb-treated individuals. Our findings confirm that treatment-emergent immune escape to anti-Spike mAbs represents a frequent and concerning phenomenon and suggests that these are associated with mAb use in immunosuppressed hosts.", - "rel_num_authors": 4, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2023.03.01.530717", + "rel_abs": "The emergence of new variants of the SARS-CoV-2 virus has posed a significant challenge in developing broadly neutralizing antibodies (nAbs) with guaranteed therapeutic potential. Some nAbs, such as Sotrovimab, have exhibited varying levels of efficacy against different variants, while others, such as Bebtelovimab and Bamlanivimab-etesevimab are ineffective against specific variants, including BQ.1.1 and XBB. This highlights the urgent need for developing broadly active mAbs providing prophylactic and therapeutic benefits to high-risk patients, especially in the face of the risk of reinfection from new variants. Here, we aimed to investigate the feasibility of redirecting existing mAbs against new variants of SARS-CoV-2, as well as to understand how BQ.1.1 and XBB.1.5 can evade broadly neutralizing mAbs. By mapping epitopes and escape sites, we discovered that the new variants evade multiple mAbs, including FDA-approved Bebtelovimab, which showed resilience against other Omicron variants. Our approach, which included simulations, free energy perturbations, and shape complementarity analysis, revealed the possibility of identifying mAbs that are effective against both BQ.1.1 and XBB.1.5. We identified two broad-spectrum mAbs, R200-1F9 and R207-2F11, as potential candidates with increased binding affinity to XBB.1.5 and BQ.1.1 compared to the wild-type virus. Additionally, we propose that these mAbs do not interfere with ACE2 and bind to conserved epitopes on the RBD that are not-overlapping, potentially providing a solution to neutralize these new variants either independently or as part of a combination (cocktail) treatment.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Daniele Focosi", - "author_inst": "Pisa University Hospital" - }, - { - "author_name": "Scott McConnell", - "author_inst": "Johns Hopkins Bloomberg School of Public Health" - }, - { - "author_name": "David J Sullivan", - "author_inst": "Johns Hopkins Bloomberg School of Public Health" + "author_name": "Hyun Goo Woo", + "author_inst": "Ajou University" }, { - "author_name": "Arturo Casadevall", - "author_inst": "Johns Hopkins School of Public Health" + "author_name": "Shah Masaud", + "author_inst": "Department of Physiology, Ajou University School of Medicine, Suwon 16499, Republic of Korea" } ], "version": "1", "license": "cc_by_nd", - "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "type": "new results", + "category": "immunology" }, { "rel_doi": "10.1101/2023.03.02.530652", @@ -104798,51 +104597,43 @@ "category": "neurology" }, { - "rel_doi": "10.1101/2023.02.23.23286326", - "rel_title": "Quantifying the impact of SARS-CoV-2 temporal vaccination trends and disparities on disease control", + "rel_doi": "10.1101/2023.02.22.23286167", + "rel_title": "A Snapshot of COVID-19 Incidence, Hospitalizations, and Mortality from Indirect Survey Data in China in January 2023", "rel_date": "2023-02-26", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.02.23.23286326", - "rel_abs": "SARS-CoV-2 vaccines were developed and distributed during a global crisis at unprecedented speed. Still, little is known about trends in vaccine uptake over time, their association with socioeconomic inequality, and the impact of these temporal trends on disease control. By analyzing data from dozens of countries, we examined vaccination rates across high and low socioeconomic (SES) groups, showing that socioeconomic disparities in the fraction of the population vaccinated exist at both national and sub-national levels. We also identified two distinct vaccination trends: one characterized by rapid initial roll-out, quickly reaching a plateau; and another trend that is sigmoidal and slow to begin. Informed by these patterns, we implemented an SES-stratified mechanistic model, finding profound differences across the two vaccination types in the burden of infections and deaths. The timing of initial roll-out has a more significant effect on transmission and deaths than the eventual level of coverage or the degree of SES disparity. Surprisingly, the speed of the roll-out is not associated with wealth inequality or GDP per capita of countries. While socioeconomic disparity should be addressed, accelerating the initial roll-out for all groups is a broadly accessible intervention and has the potential to minimize the burden of infections and deaths across socioeconomic groups.", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2023.02.22.23286167", + "rel_abs": "In this work we estimate the incidence of COVID-19 in China using online indirect surveys (which preserve the privacy of the participants). The indirect surveys deployed collect data on the incidence of COVID-19, asking the participants about the number of cases, deaths, vaccinated, and hospitalized that they know. The incidence of COVID-19 (cases, deaths, etc.) is then estimated using a modified Network Scale-up Method (NSUM). Survey responses (100, 200 and 1,000, respectively) were collected from Australia, the UK, and China in January 2023. The estimates in Australia and the UK are compared with official data, showing that they are in the confidence intervals or rather close. Cronbachs alpha values also indicate good confidence in the estimates. The estimates obtained in China are, among others, that 91% of the population is vaccinated, almost 80% had been infected in the last month, and almost 3% in the last 24 hours.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Sophie L Larsen", - "author_inst": "University of Illinois at Urbana-Champaign" - }, - { - "author_name": "Ikgyu Shin", - "author_inst": "University of Illinois at Urbana Champaign" - }, - { - "author_name": "Jefrin Joseph", - "author_inst": "University of Illinois at Urbana Champaign" + "author_name": "Juan Marcos Ramirez", + "author_inst": "IMDEA Networks Institute, Madrid, Spain" }, { - "author_name": "Haylee West", - "author_inst": "University of Illinois at Urbana Champaign" + "author_name": "Sergio Diaz-Aranda", + "author_inst": "IMDEA Networks Institute, Madrid, Spain; Universidad Carlos III, Madrid, Spain" }, { - "author_name": "Rafael Anorga", - "author_inst": "University of Illinois at Urbana Champaign" + "author_name": "Jose Aguilar", + "author_inst": "IMDEA Networks Institute, Madrid, Spain; CEMISID, Universidad de Los Andes, Merida, 5101, Venezuela; CIDITIC, Universidad EAFIT, Medellin, Colombia" }, { - "author_name": "Gonzalo E Mena", - "author_inst": "University of Oxford" + "author_name": "Oluwasegun Ojo", + "author_inst": "Universidad Carlos III, Madrid, Spain" }, { - "author_name": "Ayesha Mahmud", - "author_inst": "University of California, Berkeley" + "author_name": "Rosa Elvira Lillo", + "author_inst": "Universidad Carlos III, Madrid, Spain" }, { - "author_name": "Pamela P. Martinez", - "author_inst": "University of Illinois at Urbana Champaign" + "author_name": "Antonio Fernandez Anta", + "author_inst": "IMDEA Networks Institute" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "public and global health" }, { "rel_doi": "10.1101/2023.02.24.23285601", @@ -106764,31 +106555,39 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2023.02.15.23286011", - "rel_title": "Underlying Pressures that Black Mothers and Their Children Face: A Qualitative Assessment on the Effects of Racism/Discrimination and the COVID-19 Pandemic", + "rel_doi": "10.1101/2023.02.19.23286148", + "rel_title": "Impact of Pulmonary and Sleep Disorders on COVID-19 Infection Severity in a Large Clinical Biobank", "rel_date": "2023-02-23", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.02.15.23286011", - "rel_abs": "BackgroundPoverty, racism, discrimination, inadequate access to healthcare, and personal, everyday stressors lead to poor health outcomes, especially in African American families in the south. There is limited data on how these stressors are absorbed between the mother and child dyad.\n\nObjectiveTo assess the effects of racism, everyday stressors (i.e. motherhood), and the COVID pandemic on African American/Black mothers and their children.\n\nMethodsUtilizing the Health Belief Model, a survey was developed to assess mother-child stressors relating to three different constructs: racism/discrimination, pandemic/covid-19, and parenting. We interviewed seven black mothers and their children (aged 4-10yo). The families were recruited from a pediatric office in the rural city of Alexander City, Alabama. Interviews took place in an intimate setting and lasted for 1.5-2 hours. Medical students conducted, recorded, and transcribed each interview. The interview assessed the association between the COVID-19 pandemic, personal traumatic events, and racism and discrimination in their everyday lives.\n\nResultsThrough qualitative analysis; racism, daily activities, and the COVID-19 pandemic were demonstrated to be significant stressors for the mothers. Knowledge, school/work, actions, emotions, and seriousness/susceptibility displayed stressors not only in the mom as one would expect, but in the children as well. Using the resilience model, we assessed adversity, coping strategies, and self-efficacy. As one might expect, each situation caused a different level of anxiety; however, the coping strategies varied. Some moms took to smoking to cope with it while others chose suppression. The childrens coping ranged from inconsolable crying and using outlets such as phones to cope.\n\nConclusionUltimately, our qualitative approach saw an association between the pandemic and discrimination. Mothers often felt the need to shield children from the emotions attached to discrimination, and ultimately were unable to. There is a need to explore resilience and assess these stressors and changes in perception over time.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2023.02.19.23286148", + "rel_abs": "RationaleMultiple pulmonary, sleep, and other disorders are associated with the severity of Covid-19 infections but may or may not directly affect the etiology of acute Covid-19 infection. Identifying the relative importance of concurrent risk factors may prioritize respiratory disease outbreaks research.\n\nObjectivesTo identify associations of common preexisting pulmonary and sleep disease on acute Covid-19 infection severity, investigate the relative contributions of each disease and selected risk factors, identify sex-specific effects, and examine whether additional electronic health record (EHR) information would affect these associations.\n\nMethods45 pulmonary and 6 sleep diseases were examined in 37,020 patients with Covid-19. We analyzed three outcomes: death; a composite measure of mechanical ventilation and/or ICU admission; and inpatient admission. The relative contribution of pre-infection covariates including other diseases, laboratory tests, clinical procedures, and clinical note terms was calculated using LASSO. Each pulmonary/sleep disease model was then further adjusted for covariates.\n\nMeasurements and main results37 pulmonary/sleep diseases were associated with at least one outcome at Bonferroni significance, 6 of which had increased relative risk in LASSO analyses. Multiple prospectively collected non-pulmonary/sleep diseases, EHR terms and laboratory results attenuated the associations between preexisting disease and Covid-19 infection severity. Adjustment for counts of prior \"blood urea nitrogen\" phrases in clinical notes attenuated the odds ratio point estimates of 12 pulmonary disease associations with death in women by [≥]1.\n\nConclusionsPulmonary diseases are commonly associated with Covid-19 infection severity. Associations are partially attenuated by prospectively-collected EHR data, which may aid in risk stratification and physiological studies.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Denisia Nesha Thomas", - "author_inst": "Edward Via College of Osteopathic Medicine - Auburn Campus" + "author_name": "Brian E Cade", + "author_inst": "Brigham and Women's Hospital, Harvard Medical School" + }, + { + "author_name": "Syed Moin Hassan", + "author_inst": "Brigham and Women's Hospital, Harvard Medical School, University of Vermont" }, { - "author_name": "Mayra Rodriguez", - "author_inst": "Edward Via College of Osteopathic Medicine - Auburn Campus" + "author_name": "Janet M Mullington", + "author_inst": "Beth Israel Deaconess Medical Center, Harvard Medical School" }, { - "author_name": "Ashley Rizzieri", - "author_inst": "Edward Via College of Osteopathic Medicine - Auburn Campus" + "author_name": "Elizabeth W Karlson", + "author_inst": "Brigham and Women's Hospital, Harvard Medical School" + }, + { + "author_name": "Susan Redline", + "author_inst": "Brigham and Women's Hospital, Harvard Medical School" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "respiratory medicine" }, { "rel_doi": "10.1101/2023.02.22.23286303", @@ -108342,43 +108141,59 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2023.02.12.528210", - "rel_title": "Discovery of a novel merbecovirus cDNA clone contaminating agricultural rice sequencing datasets from Wuhan, China", + "rel_doi": "10.1101/2023.02.20.529234", + "rel_title": "Bovine milk glycoproteins inhibit SARS-CoV-2 and influenza virus co-infection", "rel_date": "2023-02-20", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2023.02.12.528210", - "rel_abs": "HKU4-related coronaviruses are a group of betacoronaviruses belonging to the same merbecovirus subgenus as Middle Eastern Respiratory Syndrome coronavirus (MERS-CoV), which causes severe respiratory illness in humans with a mortality rate of over 30%. The high genetic similarity between HKU4-related coronaviruses and MERS-CoV makes them an attractive subject of research for modeling potential zoonotic spillover scenarios. In this study, we identify a novel coronavirus contaminating agricultural rice RNA sequencing datasets from Wuhan, China. The datasets were generated by the Huazhong Agricultural University in early 2020. We were able to assemble the complete viral genome sequence, which revealed that it is a novel HKU4-related merbecovirus. The assembled genome is 98.38% identical to the closest known full genome sequence, Tylonycteris pachypus bat isolate BtTp-GX2012. Using in silico modeling, we identified that the novel HKU4-related coronavirus spike protein likely binds to human dipeptidyl peptidase 4 (DPP4), the receptor used by MERS-CoV. We further identified that the novel HKU4-related coronavirus genome has been inserted into a bacterial artificial chromosome in a format consistent with previously published coronavirus infectious clones. Additionally, we have found a near complete read coverage of the spike gene of the MERS-CoV reference strain HCoV-EMC/2012, and identify the likely presence of a HKU4-related-MERS chimera in the datasets. Our findings contribute to the knowledge of HKU4-related coronaviruses and document the use of a previously unpublished HKU4 reverse genetics system in apparent MERS-CoV related gain-of-function research. Our study also emphasizes the importance of improved biosafety protocols in sequencing centers and coronavirus research facilities.", - "rel_num_authors": 6, + "rel_link": "https://biorxiv.org/cgi/content/short/2023.02.20.529234", + "rel_abs": "The attachment of S1 subunit of spike (S) protein to angiotensin-converting enzyme 2 (ACE2) is the first and crucial step of SARS-CoV-2 infection. Although S protein and ACE2 are heavily glycosylated, the precise roles of glycans in their interactions are still unclear. Here, we profiled the glycopatterns of S1 subunit of SARS-CoV-2 and ACE2, and found that the galactosylated glycoforms were dominant in both S1 subunit and ACE2. Interestingly, S1 subunit exhibited the property of glycan-binding protein (GBP) and adhered to the ACE2 via binding to the galactosylated glycans on the ACE2. Our earlier findings demonstrated that the sialylated glycoproteins isolated from bovine milk potently inhibit and neutralize viral activity against influenza A virus (IAV). Importantly, we proved further that the galactosylated glycans on isolated glycoproteins bind to the glycan recognition domains of S1 subunit and competitively inhibit binding of S1 subunit to ACE2 and ultimately impede the entry of SARS-CoV-2 pseudovirus into host cells. We provided a potential protein drug that could be multiple simultaneous inhibitor for coronavirus and IAV co-infection.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Adrian Jones", - "author_inst": "Independent bioinformatics researcher" + "author_name": "Hanjie Yu", + "author_inst": "Northwest University" }, { - "author_name": "Daoyu Zhang", - "author_inst": "Independent genetics researcher" + "author_name": "Wentian Chen", + "author_inst": "Northwest University" }, { - "author_name": "Steven E. Massey", - "author_inst": "Department of Biology, University of Puerto Rico - Rio Piedras" + "author_name": "Jian Shu", + "author_inst": "Northwest University" }, { - "author_name": "Yuri Deigin", - "author_inst": "Youthereum Genetics Inc." + "author_name": "Xin Wu", + "author_inst": "Northwest University" }, { - "author_name": "Louis R Nemzer", - "author_inst": "Nova Southeastern University" + "author_name": "Jia Quan", + "author_inst": "Northwest University" + }, + { + "author_name": "Hongwei Cheng", + "author_inst": "Northwest University" + }, + { + "author_name": "Xiaojuan Bao", + "author_inst": "Northwest University" }, { - "author_name": "Steven Carl Quay", - "author_inst": "Atossa Therapeutics, Inc." + "author_name": "Di Wu", + "author_inst": "Wuhan Institute of Virology, Chinese Academy of Sciences" + }, + { + "author_name": "Xilong Wang", + "author_inst": "Northwest University" + }, + { + "author_name": "Zheng Li", + "author_inst": "Northwest University" } ], "version": "1", "license": "cc_no", "type": "new results", - "category": "genomics" + "category": "microbiology" }, { "rel_doi": "10.1101/2023.02.20.529249", @@ -109968,191 +109783,127 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2023.02.13.23285855", - "rel_title": "Early Treatment, Inflammation and Post-COVID Conditions", + "rel_doi": "10.1101/2023.02.15.23285584", + "rel_title": "Post-COVID syndrome is associated with capillary alterations, macrophage infiltration and distinct transcriptomic signatures in skeletal muscles", "rel_date": "2023-02-16", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.02.13.23285855", - "rel_abs": "BackgroundPost-COVID conditions (PCC) are common and have significant morbidity. Risk factors for PCC include advancing age, female sex, obesity, and diabetes mellitus. Little is known about early treatment, inflammation, and PCC.\n\nMethodsAmong 883 individuals with confirmed SARS-CoV-2 infection participating in a randomized trial of CCP vs. control plasma with available biospecimens and symptom data, the association between early COVID treatment, cytokine levels and PCC was evaluated. Cytokine and chemokine levels were assessed at baseline, day 14 and day 90 using a multiplexed sandwich immuosassay (Mesoscale Discovery). Presence of any self-reported PCC symptoms was assessed at day 90. Associations between COVID treatment, cytokine levels and PCC were examined using multivariate logistic regression models.\n\nResultsOne-third of the 882 participants had day 90 PCC symptoms, with fatigue (14.5%) and loss of smell (14.5%) being most common. Cytokine levels decreased from baseline to day 90. In a multivariable analysis including diabetes, body mass index, race, and vaccine status, female sex (adjusted odds ratio[AOR]=2.70[1.93-3.81]), older age (AOR=1.32[1.17-1.50]), and elevated baseline levels of IL-6 (AOR=1.59[1.02-2.47]) were associated with development of PCC. There was a trend for decreased PCC in those with early CCP treatment (<5 days after symptom onset) compared to late CCP treatment.\n\nConclusionIncreased IL-6 levels were associated with the development of PCC and there was a trend for decreased PCC with early CCP treatment in this predominately unvaccinated population. Future treatment studies should evaluate the effect of early treatment and anti-IL-6 therapies on PCC development.\n\nSummaryIncreased IL-6 levels were associated with the development of Post-COVID Conditions (PCC) and there was a trend for decreased PCC with early COVID convalescent plasma treatment in this predominately unvaccinated population.", - "rel_num_authors": 43, + "rel_link": "https://medrxiv.org/cgi/content/short/2023.02.15.23285584", + "rel_abs": "The SARS-CoV-2 pandemic not only resulted in millions of acute infections worldwide, but also caused innumerable cases of post-infectious syndromes, colloquially referred to as \"long COVID\". Due to the heterogeneous nature of symptoms and scarcity of available tissue samples, little is known about the underlying mechanisms. We present an in-depth analysis of skeletal muscle biopsies obtained from eleven patients suffering from enduring fatigue and post-exertional malaise after an infection with SARS-CoV-2. Compared to two independent historical control cohorts, patients with post-COVID exertion intolerance had fewer capillaries, thicker capillary basement membranes and increased numbers of CD169+ macrophages. SARS-CoV-2 RNA could not be detected in the muscle tissues, but transcriptomic analysis revealed distinct gene signatures compared to the two control cohorts, indicating immune dysregulations and altered metabolic pathways. We hypothesize that the initial viral infection may have caused immune-mediated structural changes of the microvasculature, potentially explaining the exercise-dependent fatigue and muscle pain.", + "rel_num_authors": 27, "rel_authors": [ { - "author_name": "Kelly A. Gebo", - "author_inst": "Department of Medicine, Division of Infectious Diseases" - }, - { - "author_name": "Sonya L. Heath", - "author_inst": "Division of Infectious Diseases, University of Alabama at Birmingham, Birmingham, AL" - }, - { - "author_name": "Yuriko Fukuta", - "author_inst": "Department of Medicine, Section of Infectious Diseases, Baylor College of Medicine, Houston, TX" - }, - { - "author_name": "Xianming Zhu", - "author_inst": "Johns Hopkins School of Medicine, Department of Pathology" - }, - { - "author_name": "Sheriza Baksh", - "author_inst": "Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD; Department of Medicine, Division of Infectious Diseases" - }, - { - "author_name": "Alison G. Abraham", - "author_inst": "Department of Medicine, Department of Neurology, Brain Injury Outcomes Division" - }, - { - "author_name": "Feben Habtehyimer", - "author_inst": "The Department of Medicine, Division of Infectious Diseases" - }, - { - "author_name": "David J.D Shade", - "author_inst": "Departments of Molecular Microbiology and Immunology International Health and Epidemiology" - }, - { - "author_name": "Jessica Ruff", - "author_inst": "The Department of Medicine, Division of Infectious Diseases, Department of Pathology" - }, - { - "author_name": "Malathi Ram", - "author_inst": "The Departments of Molecular Microbiology and Immunology" - }, - { - "author_name": "Oliver Laeyendecker", - "author_inst": "Division of Intramural Research, National Institute of Allergy and Infectious Diseases, NIH" - }, - { - "author_name": "Reinaldo E. Fernandez", - "author_inst": "Department of Medicine, Division of Infectious Diseases" - }, - { - "author_name": "Eshan U. Patel", - "author_inst": "Departments of Molecular Microbiology and Immunology, International Health and Epidemiology" - }, - { - "author_name": "Owen R. Baker", - "author_inst": "The Department of Medicine, Division of Infectious Diseases" - }, - { - "author_name": "Shmuel Shoham", - "author_inst": "The Department of Medicine, Division of Infectious Diseases" - }, - { - "author_name": "Edward R. Cachay", - "author_inst": "Department of Medicine, Division of Infectious Diseases, University of California, San Diego, San Diego, CA" + "author_name": "Tom Aschman", + "author_inst": "Institute of Neuropathology, Charite - Universitaetsmedizin Berlin, corporate member of Freie Universitaet Berlin, Humboldt Universitaet zu Berlin and Berlin In" }, { - "author_name": "Judith S. Currier", - "author_inst": "Department of Medicine, Division of Infectious Diseases, University of California, Los Angeles, Los Angeles, CA" + "author_name": "Emanuel Wyler", + "author_inst": "Berlin Institute for Medical Systems Biology, Max Delbrueck Center for Molecular Medicine; Berlin, Germany." }, { - "author_name": "Jonathan M. Gerber", - "author_inst": "Department of Medicine, Division of Hematology and Oncology, University of Massachusetts, Worchester, MA" + "author_name": "Oliver Baum", + "author_inst": "Institute of Physiology, Charite - Universitaetsmedizin Berlin, corporate member of Freie Universitaet Berlin, Humboldt Universitaet zu Berlin and Berlin Instit" }, { - "author_name": "Barry Meisenberg", - "author_inst": "Luminis Health, Annapolis, MD" + "author_name": "Andreas Hentschel", + "author_inst": "Leibniz-Institut fuer Analytische Wissenschaften - ISAS - e.V; Dortmund, Germany." }, { - "author_name": "Donald N. Forthal", - "author_inst": "Department of Medicine, Division of Infectious Diseases, University of California, Irvine, Irvine, CA" + "author_name": "Franziska Legler", + "author_inst": "Experimental and Clinical Research Center and NeuroCure Clinical Research Center, Charite - Universitaetsmedizin Berlin, corporate member of Freie Universitaet " }, { - "author_name": "Laura L. Hammit", - "author_inst": "The Departments of Molecular Microbiology and Immunology, International Health" + "author_name": "Corinna Preusse", + "author_inst": "Institute of Neuropathology, Department of Neurology, Charite - Universitaetsmedizin Berlin, corporate member of Freie Universitaet Berlin, Humboldt Universitae" }, { - "author_name": "Moises A. Huaman", - "author_inst": "Department of Medicine, Division of Infectious Diseases University of Cincinnati, Cincinnati, OH" - }, - { - "author_name": "Adam Levine", - "author_inst": "Department of Emergency Medicine, Rhode Island Hospital Warren Alpert Medical School of Brown University, Providence, RI" + "author_name": "Lil Meyer-Arndt", + "author_inst": "Experimental and Clinical Research Center and NeuroCure Clinical Research Center, Charite - Universitaetsmedizin Berlin, corporate member of Freie Universitaet " }, { - "author_name": "Giselle S. Mosnaim", - "author_inst": "Division of Allergy and Immunology, Department of Medicine" + "author_name": "Ivana Buettnerova", + "author_inst": "Department of Autoimmune Diagnostics, Labor Berlin-Charite Vivantes GmbH; Berlin, Germany." }, { - "author_name": "Bela Patel", - "author_inst": "Northshore University Health System, Evanston, IL; Department of Medicine, Divisions of Pulmonary and Critical Care Medicine, University of Texas Health Science" + "author_name": "Alexandra Foerster", + "author_inst": "Institute of Neuropathology, Charite - Universitaetsmedizin Berlin, corporate member of Freie Universitaet Berlin, Humboldt Universitaet zu Berlin and Berlin In" }, { - "author_name": "James H. Paxton", - "author_inst": "Department of Emergency Medicine, Wayne State University, Detroit, MI" + "author_name": "Derya Cengiz", + "author_inst": "Department of Neurology, Medical Faculty, Heinrich-Heine-University; Duesseldorf, Germany." }, { - "author_name": "Jay S. Raval", - "author_inst": "Department of Pathology, University of New Mexico, Albuquerque, NM" + "author_name": "Luiz Gustavo Teixeira Alves", + "author_inst": "Berlin Institute for Medical Systems Biology, Max Delbrueck Center for Molecular Medicine; Berlin, Germany." }, { - "author_name": "Catherine G. Sutcliffe", - "author_inst": "The Departments of Molecular Microbiology and Immunology, International Health" + "author_name": "Julia Schneider", + "author_inst": "Institute of Virology, Charite - Universitaetsmedizin Berlin, corporate member of Freie Universitaet Berlin, Humboldt Universitaet zu Berlin and Berlin Institut" }, { - "author_name": "Sweta Anjan", - "author_inst": "Department of Medicine, Department of Medicine, Division of Infectious Diseases, University of Miami, Miller School of Medicine, Miami, FL" + "author_name": "Claudia Kedor", + "author_inst": "Institute of Medical Immunology, Charite - Universitaetsmedizin Berlin, corporate member of Freie Universitaet Berlin, Humboldt Universitaet zu Berlin and Berli" }, { - "author_name": "Thomas Gniadek", - "author_inst": "Division of Allergy and Immunology, Department of Medicine and Department of Pathology" + "author_name": "Rebekka Rust", + "author_inst": "Experimental and Clinical Research Center and NeuroCure Clinical Research Center, Charite - Universitaetsmedizin Berlin, corporate member of Freie Universitaet " }, { - "author_name": "Seble Kassaye", - "author_inst": "Departments of Molecular Microbiology and Immunology" + "author_name": "Judith Bellmann-Strobl", + "author_inst": "Experimental and Clinical Research Center and NeuroCure Clinical Research Center, Charite - Universitaetsmedizin Berlin, corporate member of Freie Universitaet " }, { - "author_name": "Janis E. Blair", - "author_inst": "Department of Medicine, Division of Infectious Diseases, Mayo Clinic Hospital, Phoenix, AZ" + "author_name": "Aminaa Sanchin", + "author_inst": "Department of Neurosurgery, Charite - Universitaetsmedizin Berlin, corporate member of Freie Universitaet Berlin, Humboldt Universitaet zu Berlin and Berlin Ins" }, { - "author_name": "Karen Lane", - "author_inst": "Department of Neurology, Brain Injury Outcomes Division" + "author_name": "Peter Vajkoczy", + "author_inst": "Department of Neurosurgery, Charite - Universitaetsmedizin Berlin, corporate member of Freie Universitaet Berlin, Humboldt Universitaet zu Berlin and Berlin Ins" }, { - "author_name": "Nichol A. McBee", - "author_inst": "Department of Neurology, Brain Injury Outcomes Division" + "author_name": "Hans-Hilmar Goebel", + "author_inst": "Institute of Neuropathology, Department of Neurology, Charite - Universitaetsmedizin Berlin, corporate member of Freie Universitaet Berlin, Humboldt Universitae" }, { - "author_name": "Amy L. Gawad", - "author_inst": "Department of Neurology, Brain Injury Outcomes Division" + "author_name": "Markus Landthaler", + "author_inst": "Berlin Institute for Medical Systems Biology, Max Delbrueck Center for Molecular Medicine; Berlin, Germany. Institute for Biology, Humboldt-Universitaet zu Berl" }, { - "author_name": "Piyali Das", - "author_inst": "Department of Neurology, Brain Injury Outcomes Division" + "author_name": "Victor Corman", + "author_inst": "Institute of Virology, Charite - Universitaetsmedizin Berlin, corporate member of Freie Universitaet Berlin, Humboldt Universitaet zu Berlin and Berlin Institut" }, { - "author_name": "Sabra L. Klein", - "author_inst": "The Departments of Molecular Microbiology and Immunology" + "author_name": "Andreas Roos", + "author_inst": "Department of Pediatric Neurology, University Children's Hospital, University of Duisburg-Essen, Faculty of Medicine; Essen, Germany. Heimer-Institut fuer Musk" }, { - "author_name": "Andrew Pekosz", - "author_inst": "The Departments of Molecular Microbiology and Immunology" + "author_name": "Frank L. Heppner", + "author_inst": "Institute of Neuropathology, Charite - Universitaetsmedizin Berlin, corporate member of Freie Universitaet Berlin, Humboldt Universitaet zu Berlin and Berlin In" }, { - "author_name": "Arturo Casadevall", - "author_inst": "The Departments of Molecular Microbiology and Immunology" + "author_name": "Helena Radbruch", + "author_inst": "Institute of Neuropathology, Charite - Universitaetsmedizin Berlin, corporate member of Freie Universitaet Berlin, Humboldt Universitaet zu Berlin and Berlin In" }, { - "author_name": "Evan M. Bloch", - "author_inst": "The Department of Medicine, Department of Pathology" + "author_name": "Friedemann Paul", + "author_inst": "Experimental and Clinical Research Center and NeuroCure Clinical Research Center, Charite - Universitaetsmedizin Berlin, corporate member of Freie Universitaet " }, { - "author_name": "Daniel Hanley", - "author_inst": "Department of Neurology, Brain Injury Outcomes Division" + "author_name": "Carmen Scheibenbogen", + "author_inst": "Institute of Medical Immunology, Charite - Universitaetsmedizin Berlin, corporate member of Freie Universitaet Berlin, Humboldt Universitaet zu Berlin and Berli" }, { - "author_name": "Aaron AR Tobian", - "author_inst": "Johns Hopkins Hospital" + "author_name": "Werner Stenzel", + "author_inst": "Institute of Neuropathology, Charite - Universitaetsmedizin Berlin, corporate member of Freie Universitaet Berlin, Humboldt Universitaet zu Berlin and Berlin In" }, { - "author_name": "David J. Sullivan", - "author_inst": "The Departments of Molecular Microbiology and Immunology International Health and Epidemiology" + "author_name": "Nora F. Dengler", + "author_inst": "Department of Neurosurgery, Charite - Universitaetsmedizin Berlin, corporate member of Freie Universitaet Berlin, Humboldt Universitaet zu Berlin and Berlin Ins" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "neurology" }, { "rel_doi": "10.1101/2023.02.14.23285870", @@ -112034,51 +111785,55 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2023.02.09.527884", - "rel_title": "Nuclear export inhibitor Selinexor targeting XPO1 enhances coronavirus replication.", + "rel_doi": "10.1101/2023.02.10.527147", + "rel_title": "Proteolytic cleavage and inactivation of the TRMT1 tRNA modification enzyme by SARS-CoV-2 main protease", "rel_date": "2023-02-13", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2023.02.09.527884", - "rel_abs": "Nucleocytoplasmic transport of proteins using XPO1 (exportin 1) plays a vital role in cell proliferation and survival. Many viruses also exploit this pathway to promote infection and replication. Thus, inhibiting XPO1-mediated nuclear export with selective inhibitors activates multiple antiviral and anti-inflammatory pathways. The XPO1 inhibitor, Selinexor, is an FDA-approved anticancer drug predicted to have antiviral function against many viruses, including SARS-CoV-2. Unexpectedly, we observed that pretreatment of cultured human cells with Selinexor actually enhanced protein expression and replication of coronaviruses, including SARS-CoV-2. Knockdown of cellular XPO1 protein expression significantly enhanced the replication of coronaviruses in human cells. We further demonstrate that Selinexor treatment reduced the formation of unique cytoplasmic antiviral granules that include RNA helicase DHX9 in the virus-infected cells. These results, for the first time, show that the anti-cancer drug Selinexor enhances the replication of coronaviruses in human cells in vitro and thus should be further explored in vivo for the potential impact on the dual use for anticancer and antiviral therapy.", - "rel_num_authors": 8, + "rel_link": "https://biorxiv.org/cgi/content/short/2023.02.10.527147", + "rel_abs": "Nonstructural protein 5 (Nsp5) is the main protease of SARS-CoV-2 that cleaves viral polyproteins into individual polypeptides necessary for viral replication. Here, we show that Nsp5 binds and cleaves human tRNA methyltransferase 1 (TRMT1), a host enzyme required for a prevalent post-transcriptional modification in tRNAs. Human cells infected with SARS-CoV-2 exhibit a decrease in TRMT1 protein levels and TRMT1-catalyzed tRNA modifications, consistent with TRMT1 cleavage and inactivation by Nsp5. Nsp5 cleaves TRMT1 at a specific position that matches the consensus sequence of SARS-CoV-2 polyprotein cleavage sites, and a single mutation within the sequence inhibits Nsp5-dependent proteolysis of TRMT1. The TRMT1 cleavage fragments exhibit altered RNA binding activity and are unable to rescue tRNA modification in TRMT1-deficient human cells. Compared to wildtype human cells, TRMT1-deficient human cells infected with SARS-CoV-2 exhibit reduced levels of intracellular viral RNA. These findings provide evidence that Nsp5-dependent cleavage of TRMT1 and perturbation of tRNA modification patterns contribute to the cellular pathogenesis of SARS-CoV-2 infection.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Masmudur M. Rahman", - "author_inst": "Biodesign Institute, Arizona State University" + "author_name": "Kejia Zhang", + "author_inst": "University of Rochester" }, { - "author_name": "Bereket Estifanos", - "author_inst": "Biodesign Institute, Arizona State University" + "author_name": "Patrick Eldin", + "author_inst": "CNRS" }, { - "author_name": "Honor L. Glenn", - "author_inst": "Biodesign Institute, Arizona State University" + "author_name": "Jessica H Ciesla", + "author_inst": "University of Rochester Medical Center" }, { - "author_name": "Karen V Kibler", - "author_inst": "Biodesign Institute, Arizona State University" + "author_name": "Laurence Briant", + "author_inst": "CNRS" }, { - "author_name": "Yize Li", - "author_inst": "Biodesign Institute, Arizona State University" + "author_name": "Jenna M Lentini", + "author_inst": "University of Rochester" }, { - "author_name": "Bertram L Jacobs", - "author_inst": "Biodesign Institute, Arizona State University" + "author_name": "Jillian Ramos", + "author_inst": "University of Colorado, Anschutz" }, { - "author_name": "Grant McFadden", - "author_inst": "Biodesign Institute, Arizona State University" + "author_name": "Justin Cobb", + "author_inst": "University of Rochester" }, { - "author_name": "Brenda G. Hogue", - "author_inst": "Biodesign Institute, Arizona State University" + "author_name": "Joshua Munger", + "author_inst": "University of Rochester Medical Center" + }, + { + "author_name": "Dragony Fu", + "author_inst": "University of Rochester" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "new results", - "category": "microbiology" + "category": "molecular biology" }, { "rel_doi": "10.1101/2023.02.10.527906", @@ -113720,67 +113475,55 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2023.02.10.527437", - "rel_title": "Antagonistic pleiotropy plays an important role in governing the evolution and genetic diversity of SARS-CoV-2", + "rel_doi": "10.1101/2023.02.10.528014", + "rel_title": "Effect of the SARS-CoV-2 Delta-associated G15U mutation on the s2m element dimerization and its interactions with miR-1307-3p", "rel_date": "2023-02-10", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2023.02.10.527437", - "rel_abs": "Analyses of the genomic diversity of SARS-CoV-2 found that some sites across the genome appear to have mutated independently multiple times with frequency significantly higher than four-fold sites, which can be either due to mutational bias, i.e., elevated mutation rate in some sites of the genome, or selection of the variants due to antagonistic pleiotropy, a condition where mutations increase some components of fitness at a cost to others. To examine how different forces shaped evolution of SARS-CoV-2 in 2020-2021, we analyzed a large set of genome sequences (~ 2 million). Here we show that while evolution of SARS-CoV-2 during the pandemic was largely mutation-driven, a group of nonsynonymous changes is probably maintained by antagonistic pleiotropy. To test this hypothesis, we studied the function of one such mutation, spike M1237I. Spike I1237 increases viral assembly and secretion, but decreases efficiency of transmission in vitro. Therefore, while the frequency of spike M1237I may increase within hosts, viruses carrying this mutation would be outcompeted at the population level. We also discuss how the antagonistic pleiotropy might facilitate positive epistasis to promote virus adaptation and reconcile discordant estimates of SARS-CoV-2 transmission bottleneck sizes in previous studies.", - "rel_num_authors": 12, + "rel_link": "https://biorxiv.org/cgi/content/short/2023.02.10.528014", + "rel_abs": "The stem loop 2 motif (s2m), a highly conserved 41-nucleotide hairpin structure in the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genome, serves as an attractive therapeutic target that may have important roles in the virus life cycle or interactions with the host. However, the conserved s2m in Delta SARS-CoV-2, a previously dominant variant characterized by high infectivity and disease severity, has received relatively less attention than that of the original SARS-CoV-2 virus. The focus of this work is to identify and define the s2m changes between Delta and SARS-CoV-2 and subsequent impact of those changes upon the s2m dimerization and interactions with the host microRNA miR-1307-3p. Bioinformatics analysis of the GISAID database targeting the s2m element reveals a greater than 99% correlation of a single nucleotide mutation at the 15th position (G15U) in Delta SARS-CoV-2. Based on 1H NMR assignments comparing the imino proton resonance region of s2m and the G15U at 19{degrees}C, we find that the U15-A29 base pair closes resulting in a stabilization of the upper stem without overall secondary structure deviation. Increased stability of the upper stem did not affect the chaperone activity of the viral N protein, as it was still able to convert the kissing dimers formed by s2m G15U into a stable duplex conformation, consistent with the s2m reference. However, we find that the s2m G15U mutation drastically reduces the binding affinity of the host miR-1307-3p. These findings demonstrate that the observed G15U mutation alters the secondary structure of s2m with subsequent impact on viral binding of host miR-1307-3p, with potential consequences on the immune response.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Ding-Chin Lee", - "author_inst": "National Taiwan University College of Medicine" + "author_name": "Caylee L Cunningham", + "author_inst": "Department of Chemistry & Biochemistry, Duquesne University, Pittsburgh PA, 15282" }, { - "author_name": "Jui-Hung Tai", - "author_inst": "National Taiwan University College of Medicine" + "author_name": "Caleb J Frye", + "author_inst": "Department of Chemistry & Biochemistry, Duquesne University, Pittsburgh PA, 15282" }, { - "author_name": "Hsin-Fu Lin", - "author_inst": "National Taiwan University College of Medicine" + "author_name": "Joseph A Makowski", + "author_inst": "Department of Chemistry & Biochemistry, Duquesne University, Pittsburgh PA, 15282" }, { - "author_name": "Tai-Ling Chao", - "author_inst": "National Taiwan University College of Medicine" + "author_name": "Adam H Kensinger", + "author_inst": "Department of Chemistry & Biochemistry, Duquesne University, Pittsburgh PA, 15282" }, { - "author_name": "Yongsen Ruan", - "author_inst": "Sun Yat-sen University School of Life Science" + "author_name": "Morgan Shine", + "author_inst": "Department of Biochemistry & Chemistry, Westminster College, New Wilmington PA, 16172" }, { - "author_name": "Ya-Wen Cheng", - "author_inst": "National Taiwan University College of Medicine" + "author_name": "Ella J Milback", + "author_inst": "Department of Chemistry & Biochemistry, Duquesne University, Pittsburgh PA, 15282" }, { - "author_name": "Yu-Chi Chou", - "author_inst": "Academia Sinica" + "author_name": "Patrick E Lackey", + "author_inst": "Department of Biochemistry & Chemistry, Westminster College, New Wilmington PA, 16172" }, { - "author_name": "You-Yu Lin", - "author_inst": "National Taiwan University College of Medicine" - }, - { - "author_name": "Sui-Yuan Chang", - "author_inst": "National Taiwan University College of Medicine" - }, - { - "author_name": "Pei-Jer Chen", - "author_inst": "National Taiwan University College of Medicine" - }, - { - "author_name": "Shiou-Hwei Yeh", - "author_inst": "National Taiwan University College of Medicine" + "author_name": "Jeffrey D Evanseck", + "author_inst": "Department of Chemistry & Biochemistry, Duquesne University, Pittsburgh PA, 15282" }, { - "author_name": "Hurng-Yi Wang", - "author_inst": "National Taiwan University" + "author_name": "Mihaela Rita Mihailescu", + "author_inst": "Department of Chemistry & Biochemistry, Duquesne University, Pittsburgh PA, 15282" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "new results", - "category": "evolutionary biology" + "category": "biochemistry" }, { "rel_doi": "10.1101/2023.02.09.527920", @@ -115338,87 +115081,47 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2023.02.05.23285494", - "rel_title": "Serosurvey of SARS-COV-2 at a large public university", + "rel_doi": "10.1101/2023.02.07.527419", + "rel_title": "Dogs and cats are less susceptible to the omicron variant of concern of SARS-CoV-2 - a field study", "rel_date": "2023-02-07", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.02.05.23285494", - "rel_abs": "Arizona State University (ASU) is one the largest universities in the United States, with more than 79,000 students attending in-person classes. We conducted a seroprevalence study from September 13-17, 2021 to estimate the number of people in our community with SARS-CoV-2-specific antibodies due to previous exposure to SARS-CoV-2 and/or vaccination. Participants provided their age, gender, race, status (student or employee), and general COVID-19 health-related information like previous exposure and vaccination status. The seroprevalence of the anti-receptor binding domain (RBD) antibody was 90% by a lateral flow assay and 88% by a semi-quantitative chemiluminescent immunoassay. The seroprevalence for anti-nucleocapsid (NC) was 20%. In addition, individuals with previous natural COVID infection plus vaccination had higher anti-RBD antibody levels compared to those who had vaccination only or infection only. Individuals who had a breakthrough infection had the highest anti-RBD antibody levels.\n\nAccurate estimates of the cumulative incidence of SARS-CoV-2 infection can inform the development of university risk mitigation protocols such as encouraging booster shots, extending mask mandates, or reverting to online classes. It could help us to have clear guidance to take action at the first sign of the next surge as well, especially since there is a surge of COVID subvariant infections.", - "rel_num_authors": 17, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2023.02.07.527419", + "rel_abs": "Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) caused a pandemic of unprecedented extent. Beside humans, a number of animal species can be infected, however, in some species differing susceptibilities were observed depending on the virus variant. Here, we serologically investigated cats and dogs living in households with human COVID-19 patients. The study was conducted during the transition period from delta as the dominating variant of concern (VOC) to omicron (BA.1/BA.2) to investigate the frequency of virus transmission of both VOCs from infected owners to their pets. The animal sera were tested by surrogate virus neutralization tests (sVNT) using either the original receptor-binding domain (RBD), enabling the detection of antibodies against the delta variant, or an omicron-specific RBD. Of the 290 canine samples, 20 tested positive by sVNT, but there were marked differences between the sampling time, and, related thereto, the virus variants, the dogs had contact to. While in November 2021 infected owners led to 50% seropositive dogs (18/36), only 0.8% (2/254) of animals with household contacts to SARS-CoV-2 between December 2021 and April 2022 tested positive. In all cases, the positive reaction was recorded against the original RBD. For cats, a similar pattern was seen, as in November 2021 38.1% (16/42) tested positive and between December 2021 and March 2022 only 5.0% (10/199). The markedly reduced ratio of seropositive animals during the period of omicron circulation suggests a considerably lower susceptibility of dogs and cats to this VOC.\n\nTo examine the effect of BA.2, BA.4 and BA.5 omicron subvariants, sera taken in the second and third quarter of 2022 from randomly selected cats were investigated. 2.3% (11/372) tested seropositive and all of them showed a stronger reaction against the original RBD, further supporting the assumption of a lower susceptibility of companion animals to the omicron VOC.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Ching-Wen Hou", - "author_inst": "ASU" - }, - { - "author_name": "Stacy Williams", - "author_inst": "ASU" - }, - { - "author_name": "Kylee Taylor", - "author_inst": "ASU" - }, - { - "author_name": "Veronica Boyle", - "author_inst": "ASU" - }, - { - "author_name": "Bradley Bobbett", - "author_inst": "ASU" - }, - { - "author_name": "Joseph Kouvetakis", - "author_inst": "ASU" - }, - { - "author_name": "Keana Nguyen", - "author_inst": "ASU" - }, - { - "author_name": "Aaron McDonald", - "author_inst": "ASU" - }, - { - "author_name": "Valerie Harris", - "author_inst": "ASU" - }, - { - "author_name": "Benjamin Nussle", - "author_inst": "ASU" - }, - { - "author_name": "Phillip Scharf", - "author_inst": "ASU" + "author_name": "Constantin Klein", + "author_inst": "Friedrich-Loeffler-Institut" }, { - "author_name": "Megan Jehn", - "author_inst": "ASU" + "author_name": "Anna Michelitsch", + "author_inst": "Friedrich-Loeffler-Institut" }, { - "author_name": "Timothy Lant", - "author_inst": "ASU" + "author_name": "Valerie Allendorf", + "author_inst": "Friedrich-Loeffler-Institut" }, { - "author_name": "Mitch Magee", - "author_inst": "ASU" + "author_name": "Franz Josef Conraths", + "author_inst": "Friedrich-Loeffler-Institut" }, { - "author_name": "Yunro Chung", - "author_inst": "ASU" + "author_name": "Martin Beer", + "author_inst": "Friedrich-Loeffler-Institut" }, { - "author_name": "Joshua Labaer", - "author_inst": "ASU" + "author_name": "Nicolai Denzin", + "author_inst": "Friedrich-Loeffler-Institut" }, { - "author_name": "Vel Murugan", - "author_inst": "ASU" + "author_name": "Kerstin Wernike", + "author_inst": "Friedrich-Loeffler-Institut" } ], "version": "1", - "license": "cc_by", - "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "license": "cc_by_nc_nd", + "type": "new results", + "category": "microbiology" }, { "rel_doi": "10.1101/2023.02.07.527429", @@ -117272,27 +116975,43 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2023.02.01.23285134", - "rel_title": "Covid-19 Vaccination in India: An Exploratory Analysis", + "rel_doi": "10.1101/2023.02.01.23285349", + "rel_title": "Minimal mRNA uptake and inflammatory response to COVID-19 mRNA vaccine exposure in human placental explants", "rel_date": "2023-02-02", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.02.01.23285134", - "rel_abs": "Our study is designed to explore the patterns in covid vaccination coverage in India at the district level. We use data from the first six months of covid vaccination drive in India that we combine with several other administrative data to create a unique data set that facilitates heterogeneity analysis across different vaccination phases and districts. We find evidence of past reported infection rates positively correlated with higher first dose covid vaccination outcomes. Higher Deaths as a proportion of district population is associated with lower vaccination uptake but as a percentage of reported infection was positively correlated with first dose covid vaccination. Districts that on average had higher population burden per health centre also had lower covid vaccination rates. Vaccination rates were lower in rural areas relative to urban areas whereas the association with literacy rate was positive. A higher vaccination rate among the population with higher blood pressure and hypertension (one of the comorbidities with covid infection) was observed while vaccination rates were lower among pregnant women and breastfeeding mothers. Districts with higher percentage of children with complete immunisation were associated with higher covid vaccination rates whereas low vaccination rates were observed in districts that reported relatively higher percentage of wasted children.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2023.02.01.23285349", + "rel_abs": "Despite universal recommendations for COVID-19 mRNA vaccination in pregnancy, uptake has been lower than desired. There have been limited studies of the direct impact of COVID-19 mRNA vaccine exposure in human placental tissue. Using a primary human villous explant model, we investigated the uptake of two common mRNA vaccines (BNT162b2 Pfizer-BioNTech or mRNA-1273 Moderna), and whether exposure altered villous cytokine responses. Explants derived from second or third trimester chorionic villi were incubated with vaccines at supraphysiologic concentrations and analyzed at two time points. We observed minimal uptake of mRNA vaccines in placental explants by in situ hybridization and quantitative RT-PCR. No specific or global cytokine response was elicited by either of the mRNA vaccines in multiplexed immunoassays. Our results suggest that the human placenta does not readily absorb the COVID-19 mRNA vaccines nor generate a significant inflammatory response after exposure.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Sandip Kumar Agarwal", - "author_inst": "Indian Institute of Science Education and Research Bhopal" + "author_name": "Veronica Gonzalez", + "author_inst": "Department of Obstetrics, Gynecology, and Reproductive Sciences, University of California, San Francisco" }, { - "author_name": "Maharnab Naha", - "author_inst": "Indian Institute of Science Education and Research Bhopal" + "author_name": "Lin Li", + "author_inst": "Department of Obstetrics, Gynecology, and Reproductive Sciences, University of California, San Francisco" + }, + { + "author_name": "Sirirak Buarpung", + "author_inst": "Department of Obstetrics, Gynecology, and Reproductive Sciences, University of California, San Francisco" + }, + { + "author_name": "Mary Prahl", + "author_inst": "Department of Obstetrics, Gynecology, and Reproductive Sciences, University of California, San Francisco" + }, + { + "author_name": "Joshua F. Robinson", + "author_inst": "Department of Obstetrics, Gynecology, and Reproductive Sciences, University of California, San Francisco" + }, + { + "author_name": "Stephanie L. Gaw", + "author_inst": "Department of Obstetrics, Gynecology, and Reproductive Sciences, University of California, San Francisco" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2023.01.31.526494", @@ -119062,95 +118781,43 @@ "category": "medical education" }, { - "rel_doi": "10.1101/2023.01.28.525917", - "rel_title": "SARS-CoV-2 Mpro protease variants of concern display altered viral and host target processing but retain potency towards antivirals", + "rel_doi": "10.1101/2023.01.27.525936", + "rel_title": "Motifs in SARS-CoV-2 evolution", "rel_date": "2023-01-29", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2023.01.28.525917", - "rel_abs": "Main protease of SARS-CoV-2 (Mpro) is the most promising drug target against coronaviruses due to its essential role in virus replication. With newly emerging variants there is a concern that mutations in Mpro may alter structural and functional properties of protease and subsequently the potency of existing and potential antivirals. We explored the effect of 31 mutations belonging to 5 variants of concern (VOC) on catalytic parameters and substrate specificity, which revealed changes in substrate binding and rate of cleavage of a viral peptide. Crystal structures of 11 Mpro mutants provided structural insight into their altered functionality. Additionally, we show Mpro mutations influence proteolysis of an immunomodulatory host protein Galectin-8 (Gal-8) and subsequent significant decrease in cytokine secretion, providing evidence for alterations in escape of host-antiviral mechanisms. Accordingly, mutations associated with the highly virulent Delta VOC resulted in significant increase in Gal-8 cleavage. Importantly, IC50s of nirmatrelvir (Pfizer) and our irreversible inhibitor AVI-8053 demonstrated no changes in potency for both drugs for all mutants, suggesting Mpro will remain a high-priority antiviral drug candidate as SARS-CoV-2 evolves.", - "rel_num_authors": 19, + "rel_link": "https://biorxiv.org/cgi/content/short/2023.01.27.525936", + "rel_abs": "We present a novel framework enhancing the prediction of whether novel lineage poses the threat of eventually dominating the viral population. The framework is based purely on genomic sequence data, without requiring prior established biological analysis. Its building blocks are sets of co-evolving sites in the alignment (motifs), identified via co-evolutionary signals. The collection of such motifs forms a relational structure over the polymorphic sites. Motifs are constructed using distances quantifying the co-evolutionary coupling of pairs and manifest as co-evolving clusters of sites. We present an approach to genomic surveillance based on this notion of relational structure. Our system will issue an alert regarding a lineage, based on its contribution to drastic changes in the relational structure. We then conduct a comprehensive retrospective analysis of the COVID-19 pandemic based on SARS-CoV-2 genomic sequence data in GISAID from October 2020 to September 2022, across 21 lineages and 27 countries with weekly resolution. We investigate the performance of this surveillance system in terms of its accuracy, timeliness and robustness. Lastly, we study how well each lineage is classified by such a system.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Sizhu Amelia Chen", - "author_inst": "University of Alberta" - }, - { - "author_name": "Elena Arutyunova", - "author_inst": "Department of Biochemistry, Li Ka Shing Institute of Virology, University of Alberta" - }, - { - "author_name": "Jimmy Lu", - "author_inst": "Department of Biochemistry, Li Ka Shing Institute of Virology, University of Alberta" - }, - { - "author_name": "Muhammad Bashir Khan", - "author_inst": "Department of Biochemistry, University of Alberta" - }, - { - "author_name": "Wioletta Rut", - "author_inst": "Department of Chemical Biology and Bioimaging, Wroclaw University of Science and Technology" - }, - { - "author_name": "Mikolaj Zmudzinski", - "author_inst": "Department of Chemical Biology and Bioimaging, Wroclaw University of Science and Technology" - }, - { - "author_name": "Shima Shahbaz", - "author_inst": "Department of Dentistry & Dental Hygiene, University of Alberta" - }, - { - "author_name": "Jegan Iyyathurai", - "author_inst": "Department of Biochemistry, Li Ka Shing Institute of Virology, University of Alberta" - }, - { - "author_name": "Eman Moussa", - "author_inst": "Department of Biochemistry, University of Alberta" - }, - { - "author_name": "Zoe Turner", - "author_inst": "Department of Biochemistry, University of Alberta" - }, - { - "author_name": "Bing Bai", - "author_inst": "Li Ka Shing Applied Virology Institute, Department of Medical Microbiology and Immunology, University of Alberta" - }, - { - "author_name": "Tess Lamer", - "author_inst": "Department of Chemistry, University of Alberta" - }, - { - "author_name": "James A. Nieman", - "author_inst": "Li Ka Shing Applied Virology Institute, Department of Medical Microbiology and Immunology, University of Alberta" - }, - { - "author_name": "John C. Vederas", - "author_inst": "Department of Chemistry, University of Alberta" + "author_name": "Christopher Barrett", + "author_inst": "Biocomplexity Institute and Initiative & Department of Computer Science, University of Virginia" }, { - "author_name": "Olivier Julien", - "author_inst": "Department of Biochemistry, University of Alberta" + "author_name": "Andrei C. Bura", + "author_inst": "Biocomplexity Institute and Initiative, University of Virginia" }, { - "author_name": "Marcin Drag", - "author_inst": "Department of Chemical Biology and Bioimaging, Wroclaw University of Science and Technology" + "author_name": "Qijun He", + "author_inst": "Biocomplexity Institute and Initiative, University of Virginia" }, { - "author_name": "Shokrollah Elahi", - "author_inst": "Department of Dentistry & Dental Hygiene, University of Alberta" + "author_name": "Fenix W. Huang", + "author_inst": "Biocomplexity Institute and Initiative, University of Virginia" }, { - "author_name": "Howard S. Young", - "author_inst": "Department of Biochemistry, University of Alberta" + "author_name": "Thomas J.X. Li", + "author_inst": "University of Virginia" }, { - "author_name": "M. Joanne Lemieux", - "author_inst": "Department of Biochemistry, Li Ka Shing Institute of Virology, University of Alberta" + "author_name": "Christian M. Reidys", + "author_inst": "Biocomplexity Institute and Initiative & Department of Mathematics, University of Virginia" } ], "version": "1", - "license": "cc_no", + "license": "cc_by", "type": "new results", - "category": "biochemistry" + "category": "bioinformatics" }, { "rel_doi": "10.1101/2023.01.28.526023", @@ -121028,55 +120695,115 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2023.01.25.23285015", - "rel_title": "HPV and HBV vaccine hesitancy, intention and uptake in the era of social media and COVID-19: A review", + "rel_doi": "10.1101/2023.01.25.23285014", + "rel_title": "Incident autoimmune diseases in association with a SARS-CoV-2 infection: A matched cohort study", "rel_date": "2023-01-26", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.01.25.23285015", - "rel_abs": "Prior to the COVID-19 pandemic, the World Health Organization named vaccine hesitancy as one of the top 10 threats to global health. The impact of hesitancy on uptake of human papillomavirus (HPV) vaccines was of particular concern, given the markedly lower uptake compared to other adolescent vaccines in some countries, notably the United States. With the recent approval of COVID-19 vaccines coupled with the widespread use of social media, concerns regarding vaccine hesitancy have grown. However, the association between COVID-related vaccine hesitancy and cancer vaccines such as HPV is unclear. To examine the potential association, we performed two reviews using Ovid Medline and APA PsychInfo. Our aim was to answer two questions: (1) Is COVID-19 vaccine hesitancy, intention, or uptake associated with HPV or HBV vaccine hesitancy, intention, or uptake? and (2) Is exposure to COVID-19 vaccine misinformation on social media associated with HPV or HBV vaccine hesitancy, intention, or uptake? Our review identified few published empirical studies that addressed these questions. Our results highlight the urgent need for studies that can shift through the vast quantities of social media data to better understand the link between COVID-19 vaccine misinformation and disinformation and its impact on uptake of cancer vaccines.", - "rel_num_authors": 9, + "rel_link": "https://medrxiv.org/cgi/content/short/2023.01.25.23285014", + "rel_abs": "ObjectivesTo investigate whether the risk of developing an incident autoimmune disease is increased in patients with previous COVID-19 disease compared to people without COVID-19.\n\nMethodA cohort was selected from German routine health care data covering 38.9 million individuals. Based on documented diagnoses, we identified individuals with polymerase chain reaction (PCR)-confirmed COVID-19 through December 31, 2020. Patients were matched 1:3 to control patients without COVID-19. Both groups were followed up until June 30, 2021. We used the four quarters preceding the index date until the end of follow-up to analyze the onset of autoimmune diseases during the post-acute period. Incidence rates (IR) per 1000 person-years were calculated for each outcome and patient group. Poisson models were deployed to estimate the incidence rate ratios (IRRs) of developing an autoimmune disease conditional on a preceding diagnosis of COVID-19.\n\nResultsIn total, 641,704 patients with COVID-19 were included. Comparing the incidence rates in the COVID-19 (IR=15.05, 95% CI: 14.69-15.42) and matched control groups (IR=10.55, 95% CI: 10.25-10.86), we found a 42.63% higher likelihood of acquiring autoimmunity for patients who had suffered from COVID-19. This estimate was similar for common autoimmune diseases, such as Hashimoto thyroiditis, rheumatoid arthritis, or Sjogren syndrome. The highest IRR was observed for autoimmune disease of the vasculitis group. Patients with a more severe course of COVID-19 were at a greater risk for incident autoimmune diseases.\n\nConclusionsSARS-CoV-2 infection is associated with an increased risk of developing new-onset autoimmune diseases after the acute phase of infection.", + "rel_num_authors": 24, "rel_authors": [ { - "author_name": "Emily K Vraga", - "author_inst": "University of Minnesota" + "author_name": "Falko Tesch", + "author_inst": "Center for Evidence-Based Healthcare (ZEGV), University Hospital and Faculty of Medicine Carl Gustav Carus, TU Dresden, Dresden, Germany" }, { - "author_name": "Sonya S Brady", - "author_inst": "University of Minnesota" + "author_name": "Franz Ehm", + "author_inst": "Center for Evidence-Based Healthcare (ZEGV), University Hospital and Faculty of Medicine Carl Gustav Carus, TU Dresden, Dresden, Germany" }, { - "author_name": "Chloe Gansen", - "author_inst": "University of Minnesota" + "author_name": "Annika Vivirito", + "author_inst": "InGef - Institute for Applied Health Research Berlin, Berlin, Germany" }, { - "author_name": "Euna Mehnaz Khan", - "author_inst": "University of Minnesota" + "author_name": "Danny Wende", + "author_inst": "BARMER Institut fuer Gesundheitssystemforschung (bifg), Berlin, Germany" }, { - "author_name": "Sarah L Bennis", - "author_inst": "University of Minnesota" + "author_name": "Manuel Batram", + "author_inst": "Vandage GmbH, Bielefeld, Germany and Faculty for Business Administration and Economics Bielefeld University, Bielefeld, Germany" }, { - "author_name": "Madalyn Nones", - "author_inst": "University of Minnesota" + "author_name": "Friedrich Loser", + "author_inst": "Techniker Krankenkasse, Hamburg, Germany" }, { - "author_name": "Rongwei Tang", - "author_inst": "University of Minnesota" + "author_name": "Simone Menzer", + "author_inst": "IKK classic, Dresden, Germany" }, { - "author_name": "Jaideep Srivastava", - "author_inst": "University of Minnesota" + "author_name": "Josephine Jacob", + "author_inst": "InGef - Institute for Applied Health Research Berlin, Berlin, Germany" }, { - "author_name": "Shalini Kulasingam", - "author_inst": "University of Minnesota" + "author_name": "Martin Roessler", + "author_inst": "BARMER Institut fuer Gesundheitssystemforschung (bifg), Berlin, Germany" + }, + { + "author_name": "Martin Seifert", + "author_inst": "Center for Evidence-Based Healthcare (ZEGV), University Hospital and Faculty of Medicine Carl Gustav Carus, TU Dresden, Dresden, Germany" + }, + { + "author_name": "Barbara Kind", + "author_inst": "Center for Evidence-Based Healthcare (ZEGV), University Hospital and Faculty of Medicine Carl Gustav Carus, TU Dresden, Dresden, Germany" + }, + { + "author_name": "Christina Koenig", + "author_inst": "Techniker Krankenkasse, Hamburg, Germany" + }, + { + "author_name": "Claudia Schulte", + "author_inst": "BARMER Institut fuer Gesundheitssystemforschung (bifg), Berlin, Germany" + }, + { + "author_name": "Tilo Buschmann", + "author_inst": "AOK PLUS, Dresden, Germany" + }, + { + "author_name": "Dagmar Hertle", + "author_inst": "BARMER Institut fuer Gesundheitssystemforschung (bifg), Berlin, Germany" + }, + { + "author_name": "Pedro Ballesteros", + "author_inst": "BARMER Institut fuer Gesundheitssystemforschung (bifg), Berlin, Germany" + }, + { + "author_name": "Stefan Bassler", + "author_inst": "AOK PLUS, Dresden, Germany" + }, + { + "author_name": "Barbara Bertele", + "author_inst": "Techniker Krankenkasse, Hamburg, Berlin" + }, + { + "author_name": "Thomas Bitterer", + "author_inst": "IKK classic, Dresden, Germany" + }, + { + "author_name": "Cordula. Riederer", + "author_inst": "DAK-Gesundheit, Hamburg, Germany" + }, + { + "author_name": "Franziska Sobik", + "author_inst": "DAK-Gesundheit, Hamburg, Germany" + }, + { + "author_name": "Lukas Reitzle", + "author_inst": "Robert Koch Institute, Berlin, Germany" + }, + { + "author_name": "Christa Scheidt-Nave", + "author_inst": "Robert Koch Institute, Berlin, Germany" + }, + { + "author_name": "Jochen Schmitt", + "author_inst": "Center for Evidence-Based Healthcare (ZEGV), University Hospital and Faculty of Medicine Carl Gustav Carus, TU Dresden, Dresden, Germany" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "epidemiology" }, { "rel_doi": "10.1101/2023.01.25.525589", @@ -122822,43 +122549,67 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2023.01.23.525130", - "rel_title": "Prediction of SARS-CoV-2 spike protein mutations using Sequence-to-Sequence and Transformer models", + "rel_doi": "10.1101/2023.01.23.23284899", + "rel_title": "Real-world effectiveness of Azvudine in hospitalized patients with COVID-19: a retrospective cohort study", "rel_date": "2023-01-23", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2023.01.23.525130", - "rel_abs": "In the study of viral epidemics, having information about the structural evolution of the virus can be very helpful in controlling the disease and making vaccines. Various deep learning and natural language processing techniques (NLP) can be used to analyze genetic structure of viruses, namely to predict their mutations. In this paper, by using Sequence-to-Sequence (Seq2Seq) model with Long Short-Term Memory (LSTM) cell and Transformer model with the attention mechanism, we investigate the spike protein mutations of SARS-CoV-2 virus. We make time-series datasets of the spike protein sequences of this virus and generate upcoming spike protein sequences. We also determine the mutations of the generated spike protein sequences, by comparing these sequences with the Wuhan spike protein sequence. We train the models to make predictions in December 2021, February 2022, and October 2022. Furthermore, we find that some of our generated spike protein sequences have been reported in December 2021 and February 2022, which belong to Delta and Omicron variants. The results obtained in the present study could be useful for prediction of future mutations of SARS-CoV-2 and other viruses.", - "rel_num_authors": 6, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2023.01.23.23284899", + "rel_abs": "Current guidelines prioritize the use of the Azvudine in coronavirus disease 2019 (COVID-19) patients. However, the clinical effectiveness of Azvudine in real-world studies was lacking, despite the clinical trials showed shorter time of nucleic acid negative conversion. To evaluate the clinical effectiveness following Azvudine treatment in hospitalized COVID-19 patients, we identified 1505 hospitalized COVID-19 patients during the study period, with a follow-up of up to 29 days. After exclusions and propensity score matching, we included 226 Azvudine recipients and 226 matched controls. The lower crude incidence rate of composite disease progression outcome (4.21 vs. 10.39 per 1000 person-days, P=0.041) and all-cause mortality (1.57 vs. 6.00 per 1000 person-days, P=0.027) were observed among Azvudine recipients compared with matched controls. The incidence rates of initiation of invasive mechanical ventilation were also statistically different between the groups according to the log-rank tests (P=0.020). Azvudine treatment was associated with significantly lower risks of composite disease progression outcome (hazard ratio [HR]: 0.43; 95% confidence interval [CI]: 0.18 to 0.99) and all-cause death (HR: 0.26; 95% CI: 0.07 to 0.94) compared with matched controls. Subgroup analyses indicated robustness of the point estimates of HRs (ranged from 0.14 to 0.84). Notably, male Azvudine recipients had a stronger effectiveness than female recipients with respect to both composite outcome and all-cause death. These findings suggest that Azvudine treatment showed substantial clinical benefits in hospitalized COVID-19 patients, and should be considered for use in this population of patients.", + "rel_num_authors": 12, "rel_authors": [ { - "author_name": "Hamed Ahmadi", - "author_inst": "Iran University of Science and Technology" + "author_name": "Minxue Shen", + "author_inst": "Xiangya hospital of Central South University" }, { - "author_name": "Vahid Nikoofard", - "author_inst": "Rio de Janeiro State University: Universidade do Estado do Rio de Janeiro" + "author_name": "Chenggen Xiao", + "author_inst": "Xiangya hospital of Central South University" }, { - "author_name": "Hossein Nikoofard", - "author_inst": "Iran University of Science and Technology" + "author_name": "Yuming Sun", + "author_inst": "Xiangya hospital of Central South University" }, { - "author_name": "Ruhollah Abdolvahab", - "author_inst": "Iran University of Science and Technology" + "author_name": "Daishi Li", + "author_inst": "Xiangya hospital of Central South University" }, { - "author_name": "Narges Nikoofard", - "author_inst": "University of Kashan" + "author_name": "Ping Wu", + "author_inst": "Xiangya hospital of Central South University" }, { - "author_name": "Mahdi Esmaeilzadeh", - "author_inst": "Iran University of Science and Technology" + "author_name": "Liping Jin", + "author_inst": "Xiangya hospital of Central South University" + }, + { + "author_name": "Qingrong Wu", + "author_inst": "Xiangya hospital of Central South University" + }, + { + "author_name": "Yating Dian", + "author_inst": "Xiangya hospital of Central South University" + }, + { + "author_name": "Yu Meng", + "author_inst": "Xiangya hospital of Central South University" + }, + { + "author_name": "Furong Zeng", + "author_inst": "Xiangya hospital of Central South University" + }, + { + "author_name": "Xiang Chen", + "author_inst": "Xiangya hospital of Central South University" + }, + { + "author_name": "Guangtong Deng", + "author_inst": "Xiangya hospital of Central South University" } ], "version": "1", - "license": "cc_by", - "type": "new results", - "category": "bioinformatics" + "license": "cc_by_nc_nd", + "type": "PUBLISHAHEADOFPRINT", + "category": "infectious diseases" }, { "rel_doi": "10.1101/2023.01.19.23284806", @@ -124516,39 +124267,35 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2023.01.13.23284501", - "rel_title": "The impact on mental health of young Asian Americans due to acts of discrimination and hate crimes during COVID-19", + "rel_doi": "10.1101/2023.01.15.23284579", + "rel_title": "Extensive SARS-CoV-2 testing reveals BA.1/BA.2 asymptomatic rates and underreporting in school children", "rel_date": "2023-01-18", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.01.13.23284501", - "rel_abs": "This article is an examination of the acts of discriminiation and hate crimes against the Asian American community and how their mental health has been impacted. The historical examination of acts against the Asian American community stem from acts against the Asian American community during both the yellow peril and the Roosevelt Era. Alongside current day institutionalized policies that are propagated by the media, the resurrection of historical tropes further act to seclude Asian Americans from mainstream society. These acts of seclusion further drive mental health inequality in Asian American society that include, but are not limited to: anxiety, depression, and psychological stress. These mental health inequalities are further subdivided into different ethnic groups that worsen as data is collected from older generations. More recently, COVID-19 has brought forth an upsurge in hate crimes that has only worsened the ability of Asian American youth to fully develop a racial identity; the upsurge in hate crimes is also coupled with invalidation of interethnic differences and invalidation of their discriminatory experiences. The synthesis of current day research will aid in the understanding of the mental health inequality in the Asian American community and aid in further studies that can address these plights.\n\nPurpose StatementThe purpose of this paper is to investigate how acts of discrimination and hate crimes against the Asian community have impacted the mental health of young Asian Americans. This review seeks to explore the many effects of race-based discrimiation specifically for Asian Americans during and after the COVID-19 (coronavirus pandemic) such as: general feelings of inclusivity, physiological responses as a result of increasing racist encounters, and incidences of mental health experiences. Overall, the paper highlights how these characteristics manifest within the Asian American population and what measures and interventions can be done to protect Asian American from the negative consequences of hate.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2023.01.15.23284579", + "rel_abs": "Case underreporting during the COVID-19 pandemic has been a major challenge to the planning and evaluation of public health responses. Inconsistent underreporting can undermine effective risk assessment due to high uncertainty in predicted future scenarios. Underreporting rates have been particularly high among children and youth, given that asymptomatic school children were often considered a less vulnerable population. In January 2022, the Canadian province of Newfoundland and Labrador (NL) was experiencing an Omicron variant outbreak (BA.1/BA.2 subvariants) and public health officials recommended that all students returning to elementary, junior high, and high schools ([~]59,452 students) complete two rapid antigen tests (RATs) to be performed three days apart. To estimate the prevalence of SARS-CoV-2, we asked parents and guardians to report the results of the RATs completed by K-12 students using an online survey, and to specify the students school level and if students with positive RAT results had symptoms. When comparing the survey responses with the number of cases and tests reported by the NL testing system, we found that 1 out of every 4.3 (3.1-5.3) positive households were captured by provincial case count, with 5.1% positivity estimated from the RAT results, and 1.2% positivity reported by the provincial testing system. The survey data indicate that a higher percentage of SARS-CoV-2 cases were found in elementary schools, with 62.9% of positive cases (95% CI: 44.3%, 83.0%) reported from elementary school students, and the remaining 37.1% (95% CI: 22.7%, 52.9%) reported from junior high and high school students. Asymptomatic infections were 59.8% of the positive cases, with no significant difference between asymptomatic rates in elementary schools (60.8%) or in junior high and high schools (58.1%). Given the low survey participation rate (3.5%), our results may suffer from sample selection biases, and should be interpreted with caution. Nonetheless, our estimate of the underreporting ratio is consistent with ratios calculated from serology data, and our study provides insights into infection prevalence and asymptomatic infections in school children, a currently understudied population.\n\nWe declare thatO_LIThis manuscript is original and is not a violation or infringement of any existing copyright or license\nC_LIO_LIThe manuscript is not under consideration elsewhere\nC_LIO_LIAll authors meet the definition of authorship as set out by the International Committee of Medical Journal Editors (ICMJE)\nC_LIO_LIPermission has been obtained from the copyright holder(s) if indicated, for the use of any third-party textual, graphic, artistic or other material\nC_LI", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Ahmed Gawash", - "author_inst": "Rowan University School of Osteopathic Medicine" - }, - { - "author_name": "David Lo", - "author_inst": "APSEA" + "author_name": "Maria M Martignoni", + "author_inst": "Memorial University of Newfoundland" }, { - "author_name": "Brianna Nghiem", - "author_inst": "Rowan School of Osteopathic Medicine" + "author_name": "Zahra Mohammadi", + "author_inst": "University of Guelph" }, { - "author_name": "Priscilla Rofail", - "author_inst": "Rowan School of Osteopathic Medicine" + "author_name": "JC Loredo-Osti", + "author_inst": "Memorial University of Newfoundland" }, { - "author_name": "Sayan Basu", - "author_inst": "Rowan School of Osteopathic Medicine" + "author_name": "Amy Hurford", + "author_inst": "Memorial University" } ], "version": "1", - "license": "cc_no", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "health policy" }, { "rel_doi": "10.1101/2023.01.17.23284585", @@ -126538,49 +126285,57 @@ "category": "neuroscience" }, { - "rel_doi": "10.1101/2023.01.13.524025", - "rel_title": "Redistribution and activation of CD16brightCD56dim NK cell subset to fight against Omicron subvariant BA.2 after COVID-19 vaccination", + "rel_doi": "10.1101/2023.01.13.523998", + "rel_title": "Maintained imbalance of triglycerides, apolipoproteins, energy metabolites and cytokines in long-term COVID-19 syndrome (LTCS) patients", "rel_date": "2023-01-17", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2023.01.13.524025", - "rel_abs": "With the alarming surge in COVID-19 cases globally, vaccination must be prioritised to achieve herd immunity. Immune dysfunction is detected in the majority of patients with COVID-19; however, it remains unclear whether the immune responses elicited by COVID-19 vaccination function against the Omicron subvariant BA.2. Of the 508 Omicron BA.2-infected patients enrolled, 102 were unvaccinated controls and 406 were vaccinated. Despite the presence of clinical symptoms in both groups, vaccination led to a significant decline in nausea or vomiting, abdominal pain, headache, pulmonary infection, overall clinical symptoms, and a moderate rise in body temperature. Omicron BA.2-infected individuals were also characterised by a mild increase in both serum pro- and anti-inflammatory cytokine levels after vaccination. There were no significant differences or trend changes between T and B lymphocyte subsets; however, a significant expansion of NK lymphocytes in COVID-19-vaccinated patients was observed. Moreover, the most effective CD16brightCD56dim subsets of NK cells showed increased functional capacities, as evidenced by a significantly greater IFN-{gamma} secretion and stronger cytotoxic potential in Omicron BA.2-infected patients after vaccination. Collectively, these results suggest that COVID-19 vaccination interventions promote the redistribution and activation of CD16brightCD56dim NK cell subsets against viral infections, and could facilitate the clinical management of Omicron BA.2-infected patients.", - "rel_num_authors": 9, + "rel_link": "https://biorxiv.org/cgi/content/short/2023.01.13.523998", + "rel_abs": "Deep metabolomic, proteomic and immunologic phenotyping of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) patients have matched a wide diversity of clinical symptoms with potential biomarkers for coronavirus disease 2019 (COVID-19). Within here, several studies described the role of metabolites, lipoproteins and inflammation markers during infection and in recovered patients. In fact, after SARS-CoV-2 viral infection almost 20-30% of patients experience persistent symptoms even after 12 weeks of recovery which has been defined as long-term COVID-19 syndrome (LTCS). Emerging evidence revealed that a dysregulated immune system and persisting inflammation could be one of the key drivers of LTCS. However, how these small biomolecules such as metabolites, lipoprotein, cytokines and chemokines altogether govern pathophysiology is largely underexplored. Thus, a clear understanding how these parameters into an integrated fashion could predict the disease course may help to stratify LTCS patients from acute COVID-19 or recovered specimen and would help to elucidate a potential mechanistic role of these biomolecules during the disease course. Here, we report an integrated analysis of blood serum and plasma by in vitro diagnostics research NMR spectroscopy and flow cytometry-based cytokine quantification in a total of 125 individuals (healthy controls (HC; n=73), recovered (n=12), acute (n=7) and LTCS (n=33)). We identified that in LTCS patients lactate and pyruvate were significantly different from either healthy controls or acute COVID-19 patients. Further correlational analysis of cytokines and metabolites indicated that creatine, glutamine, and high-density lipoprotein (HDL) phospholipids were distributed differentially amongst patients or individuals. Of note, triglycerides and several lipoproteins (apolipoproteins Apo-A1 and A2) in LTCS patients demonstrate COVID-19-like alterations compared to HC. Interestingly, LTCS and acute COVID-19 samples were distinguished mostly by their creatinine, phenylalanine, succinate, 3-hydroxybutyrate (3-HB) and glucose concentrations, illustrating an imbalanced energy metabolism. Most of the cytokines and chemokines were present at low levels in LTCS patients compared with HC except IL-18 chemokine, which tended to be higher in LTCS patients and correlated positively with several amino acids (creatine, histidine, leucine, and valine), metabolites (lactate and 3-HB) and lipoproteins. The identification of these persisting plasma metabolites, lipoprotein and inflammation alterations will help to better stratify LTCS patients from other diseases and could help to predict ongoing severity of LTCS patients.\n\nGraphical abstract\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=127 SRC=\"FIGDIR/small/523998v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (50K):\norg.highwire.dtl.DTLVardef@ecdeacorg.highwire.dtl.DTLVardef@10f0f80org.highwire.dtl.DTLVardef@1c2ddaborg.highwire.dtl.DTLVardef@672120_HPS_FORMAT_FIGEXP M_FIG C_FIG Layman summary & significance of the researchAlmost 20-30% of individuals infected with the SARS-CoV-2 virus regardless of hospitalization status experience long-term COVID-19 syndrome (LTCS). It is devasting for millions of individuals worldwide and hardly anything is known about why some people experience these symptoms even after 3 to 12 months after the acute phase. In this, we attempted to understand whether dysregulated metabolism and inflammation could be contributing factors to the ongoing symptoms in LTCS patients. Total blood triglycerides and the Cory cycle metabolites (lactate and pyruvate) were significantly higher, lipoproteins (Apo-A1 and A2) were drastically lower in LTCS patients compared to healthy controls. Correlation analysis revealed that either age or gender are positively correlated with several metabolites (citrate, glutamate, 3-hydroxybutyrate, glucose) and lipoproteins (Apo-A1, HDL Apo-A1, LDL triglycerides) in LTCS patients. Several cytokines and chemokines were also positively correlated with metabolites and lipoproteins thus, dysregulation in metabolism and inflammation could be a potential contributory factor for LTCS symptoms.", + "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Yang Liu", - "author_inst": "First Affiliated Hospital of Nanchang University" + "author_name": "Gerogy Berezhnoy", + "author_inst": "Tuebingen University" }, { - "author_name": "Huiyun Peng", - "author_inst": "Nanchang University" + "author_name": "Rosi Bissinger", + "author_inst": "Tuebingen University" }, { - "author_name": "Tianxin Xiang", - "author_inst": "Medical Center for Major Public Health Events in Jiangxi Province, the First Affiliated Hospital of Nanchang University" + "author_name": "Anna Liu", + "author_inst": "Tuebingen University" }, { - "author_name": "Fei Xu", - "author_inst": "The First Affiliated Hospital of Nanchang University" + "author_name": "Claire Cannet", + "author_inst": "Brucker Biospin" }, { - "author_name": "Yuhuan Jiang", - "author_inst": "The First Affiliated Hospital of Nanchang University" + "author_name": "Harmut Schaefer", + "author_inst": "Brucker Biospin GmBH" }, { - "author_name": "Lipeng Zhong", - "author_inst": "The First Affiliated Hospital of Nanchang University" + "author_name": "Katharina Kienzele", + "author_inst": "Tuebingen University" }, { - "author_name": "Yanqi Peng", - "author_inst": "The First Affiliated Hospital of Nanchang University" + "author_name": "Michael Bitzer", + "author_inst": "Tuebingen University" }, { - "author_name": "Aiping Le", - "author_inst": "The First Affiliated Hospital of Nanchang University" + "author_name": "Helene Haeberle", + "author_inst": "Tuebingen University" }, { - "author_name": "Wei Zhang", - "author_inst": "Department of Respiratory Medicine, First Affiliated Hospital of Nanchang University, Nanchang" + "author_name": "Siri Goepel", + "author_inst": "Tuebingen University" + }, + { + "author_name": "Christoph Trautwein", + "author_inst": "Tuebingen University" + }, + { + "author_name": "Yogesh Singh", + "author_inst": "Tuebingen University" } ], "version": "1", @@ -128328,43 +128083,63 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2023.01.12.23284479", - "rel_title": "Comparison of different isolation periods for preventing the spread of COVID-19: a rapid systematic review and a modelling study", + "rel_doi": "10.1101/2023.01.12.23284434", + "rel_title": "The role of SARS-CoV-2 variants of concern in children and adolescents with COVID-19: a systematic review", "rel_date": "2023-01-12", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.01.12.23284479", - "rel_abs": "BackgroundThe optimal isolation duration for COVID-19 patients remains unclear. To support an update of WHO Living Clinical management guidelines for COVID-19 (https://www.who.int/publications/i/item/WHO-2019-nCoV-clinical-2022.2), this rapid systematic review and modelling study addresses the effects of different isolation periods for preventing onward transmission leading to hospitalization and death among secondary cases.\n\nMethodsWe searched World Health Organization (WHO) COVID-19 database for clinical studies evaluating the impact of isolation periods for COVID-19 patients up to July 28, 2022. We performed random-effects meta-analyses to summarize testing rates of persistent test positivity rates after COVID-19 infection. We developed a model to compare the effects of the five-day isolation and removal of isolation based on a negative antigen test with ten-day isolation on onward transmission leading to hospitalization and death. We assumed that patients with a positive test are infectious and those with a negative test are not. If the test becomes negative, patients will stay negative. The model included estimates of test positivity rates, effective reproduction number, and hospitalization rate or case fatality rate.\n\nFindingsTwelve studies addressing persistent test positivity rates including 2799 patients proved eligible. Asymptomatic patients (27.1%, 95% CI: 15.8% to 40.0%) had a significantly lower rapid antigen test (RAT) positive rate than symptomatic patients (68.1%, 95% CI: 40.6% to 90.3%) on day 5. The RAT positive rate was 21.5% (95% CI: 0 to 64.1%; moderate certainty) on day 10. Our modelling study suggested that the risk difference (RD) for asymptomatic patients between five-day isolation and ten-day isolation in hospitalization (2 more hospitalizations of secondary cases per 1000 patients isolated, 95% uncertainty interval (UI) 2 more to 3 more) and mortality (1 more per 1000 patients, 95% UI 0 to 1 more) of secondary cases proved very small (very low certainty). For symptomatic patients, the potential impact of five- versus ten-day isolation was much greater in hospitalizations (RD 19 more per 1000 patients, 95% UI 14 more to 24 more; very low certainty) and mortality (RD 5 more per 1000 patients, 95% UI 4 more to 6 more; very low certainty). There may be no difference between removing isolation based on a negative antigen test and ten-day isolation in the onward transmission leading to hospitalization or death, but the average isolation period (mean difference -3 days) will be shorter for the removal of isolation based on a negative antigen test (moderate certainty).\n\nInterpretationFive versus 10 days of isolation in asymptomatic patients may result in a small amount of onward transmission and negligible hospitalization and mortality, but in symptomatic patients concerning transmission and resulting hospitalization and mortality. The evidence is, however, very uncertain.\n\nFundingWHO.\n\nResearch in contextO_ST_ABSEvidence before this studyC_ST_ABSIsolating infected patients and quarantining individuals with a high risk of recent infection remain widely used strategies to prevent the spread of SARS-CoV-2. There are no prior systematic reviews to evaluate effects relevant to decisions regarding protocols for ending COVID-19 isolation. Many modelling studies have, however, evaluated impact of five days of isolation or alternative strategies (e.g. 7 days and 10 days) with or without one negative lateral flow device on secondary infections or additional transmission risk. However, none has focused on the most patient-important outcomes - onward transmission leading to hospitalization or death. The optimal isolation duration for COVID-19 patients remains unclear. We searched WHO COVID-19 database for clinical studies evaluating the impact of isolation periods for COVID-19 patients up to July 28, 2022. We performed random-effects meta-analyses to summarize testing rates of persistent test positivity rates after COVID-19 infection. We used a model to compare the effects of the five-day isolation and removal of isolation based on a negative antigen test with ten-day isolation on onward transmission leading to hospitalization and death.\n\nAdded value of this studyTo our knowledge, this is the first systematic review and modelling study to compare effects of the five-day isolation and removal of isolation based on a negative antigen test with ten-day isolation on most patient-important outcomes - onward transmission leading to hospitalization or death. This study demonstrates that for symptomatic patients the five-day isolation may increase onward transmission and thus hospitalization and mortality of secondary cases compared with the ten-day isolation by a magnitude most would consider important. For asymptomatic patients, the increase in hospitalizations and death may be small enough to be considered unimportant. Removal of isolation based on a negative antigen test will probably shorten the average isolation period compared with isolating all patients for 10 days.\n\nImplications of all the available evidenceOur study provides evidence that 5 versus 10 days of isolation in asymptomatic patients may result in a small amount of onward transmission and negligible hospitalization and mortality, but in symptomatic patients concerning transmission and resulting hospitalization and mortality.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2023.01.12.23284434", + "rel_abs": "BackgroundInfections by SARS-CoV-2 variants of concern (VOCs) might affect children and adolescents differently than earlier viral lineages. We aimed to address five questions about SARS-CoV-2 VOC infections in children and adolescents: i) symptoms and severity, ii) risk factors for severe disease, iii) the risk of becoming infected, iv) the risk of transmission and v) long-term consequences following a VOC infection.\n\nMethodsWe carried out a systematic review. We searched the COVID-19 Open Access Project database up to 1 March 2022 and PubMed up to 9 May 2022 for observational epidemiological studies about alpha, beta, gamma, delta and omicron VOCs among 0 to 18 year olds. We synthesised data for each question descriptively and assessed the risks of bias at the outcome level.\n\nResultsWe included 53 articles, of which 47% were from high-income countries and none were from low-income countries, according to World Bank categories. Most children with any VOC infection presented with mild disease, with more severe disease being described with the delta or the gamma VOC. Diabetes and obesity were reported as risk factors for severe disease during the whole pandemic period. The risk of becoming infected with a SARS-CoV-2 VOC seemed to increase with age, while in daycare settings the risk of onward transmission of VOCs was higher for younger than older children or at least partially vaccinated adults. Long-term symptoms or signs following an infection with a VOC were described in <5% of children and adolescents.\n\nConclusionOverall patterns of SARS-CoV-2 VOC infections in children and adolescents are similar to those of earlier lineages. Comparisons between different pandemic periods, countries and age groups should be improved with complete reporting of relevant contextual factors, including VOCs, vaccination status of study participants and the risk of exposure of the population to SARS-CoV-2.\n\nPROSPERO registration numberCRD42022295207\n\nKey messagesO_ST_ABSWhat is already known on this topicC_ST_ABSSARS-CoV-2 variants of concern (VOCs) might affect children and adolescents differently from earlier viral lineages.\n\nWhat this study addsChildren and adolescents are susceptible to SARS-CoV-2 VOC infection, though they mostly experience mild disease, and can transmit the VOCs. More severe disease was described with the delta or the gamma VOC but comparison within paediatric age groups as well as to adults is hindered by the lack of reporting of contextual factors such as the vaccination status of these groups.\n\nHow this study might affect research practice or policyThe applicability of our findings about clinical presentations, susceptibility and transmissibility of SARS-CoV-2 VOCs is limited by an absence of research from low-and middle-income settings. As new VOCs continue to emerge, new studies are needed globally, with methods and results reported in ways that allow comparison between different VOCs and age groups.", + "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Ya Gao", - "author_inst": "1. Evidence-Based Medicine Center, School of Basic Medical Sciences, Lanzhou University, Lanzhou, China; 2. Department of Health Research Methods, Evidence, and" + "author_name": "Margarethe Wiedenmann", + "author_inst": "Swiss Tropical and Public Health Institute, Basel, Switzerland; University of Basel, Basel, Switzerland" }, { - "author_name": "Yunli Zhao", - "author_inst": "1. National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu, China; 2. Department of Health Research Methods, Evidence" + "author_name": "Aziz Mert Ipekci", + "author_inst": "Institute of Social and Preventive Medicine (ISPM), University of Bern, Bern, Switzerland" }, { - "author_name": "Xi Zhang", - "author_inst": "Department of Mathematics and Statistics, McMaster University, Hamilton, ON, Canada" + "author_name": "Lucia Araujo Chaveron", + "author_inst": "EHESP French School of Public Health, Paris/Rennes, France; Institute Pasteur, Paris, France" }, { - "author_name": "Jinhui Tian", - "author_inst": "Evidence-Based Medicine Center, School of Basic Medical Sciences, Lanzhou University, Lanzhou, China" + "author_name": "Nirmala Prajapati", + "author_inst": "Universite Paris-Saclay, Paris, France; Institut national de la sante et de la recherche medicale (INSERM), Paris, France" }, { - "author_name": "Gordon Guyatt", - "author_inst": "1. Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON, Canada; 2. Department of Medicine, McMaster University, Hamil" + "author_name": "Yin Ting Lam", + "author_inst": "Institute of Social and Preventive Medicine (ISPM), University of Bern, Bern, Switzerland" + }, + { + "author_name": "Muhammad Irfanul Alam", + "author_inst": "EHESP French School of Public Health, Paris/Rennes, France" + }, + { + "author_name": "Arnaud L'Huillier", + "author_inst": "Geneva University Hospitals and Faculty of Medicine, Geneva, Switzerland" + }, + { + "author_name": "Ivan Zhelyazkov", + "author_inst": "University of Sheffield, Sheffield, United Kingdom" + }, + { + "author_name": "Leonie Heron", + "author_inst": "Institute of Social and Preventive Medicine (ISPM), University of Bern, Bern, Switzerland" }, { - "author_name": "Qiukui Hao", - "author_inst": "1. School of Rehabilitation Science, McMaster University, Hamilton, ON, Canada; 2. Department of Health Research Methods, Evidence, and Impact, McMaster Univers" + "author_name": "Nicola Low", + "author_inst": "Institute of Social and Preventive Medicine (ISPM), University of Bern, Bern, Switzerland" + }, + { + "author_name": "Myrofora Goutaki", + "author_inst": "Institute of Social and Preventive Medicine (ISPM), University of Bern, Bern, Switzerland" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "public and global health" }, { "rel_doi": "10.1101/2023.01.10.22284009", @@ -129798,47 +129573,63 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2023.01.09.23284361", - "rel_title": "Research on the mental health status of frontline medical staff during the normalization of the COVID-19 pandemic", + "rel_doi": "10.1101/2023.01.09.23284337", + "rel_title": "SARS-CoV-2 molecular testing and whole genome sequencing following RNA recovery from used BinaxNOW COVID-19 Antigen Self Tests", "rel_date": "2023-01-09", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.01.09.23284361", - "rel_abs": "ObjectiveThis study aimed to investigate the relationship between personality characteristics and psychological health of hospitals frontline medical staff and provide a basis and reference for targeted psychological health education for frontline medical staff and for the staff of related departments to formulate relevant policies.\n\nMethodsThe self-evaluation scale of symptoms (SCL-90) was used to investigate the mental health status of 150 first-line medical staff in Zhejiang Province in response to the new severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pneumonia.\n\nResultsThe average scores of SCL-90 and somatization, obsessive-compulsive, depression, anxiety, hostility, terror, and psychotic factors were significantly higher than those of the normal sample in the first-aid medical staff of Aihu Hubei. The degree of influence on the mental health status of the frontline medical staff in service in Hubei is as follows, from high to low: the degree of suspicion that they may have been infected when new coronavirus pneumonia-related symptoms occur, the degree of fear of being infected and thus bring the infection to their families, and whether they have received a medical check-up recently, as well as a high level of education (both P<0.05).\n\nConclusionThe psychological health level of the frontline medical staff is lower than the national norm. In the context of the increasing number of confirmed cases and the new type of coronavirus pneumonia in the absence of any specific curative treatments, the frontline medical staff is under great psychological pressure. It is necessary to institute targeted mental health promotion to relieve the psychological pressure endured by the frontline medical staff, promote their physical and mental health, and better respond to the pandemic in China.", - "rel_num_authors": 7, + "rel_link": "https://medrxiv.org/cgi/content/short/2023.01.09.23284337", + "rel_abs": "Widespread use of over-the-counter rapid diagnostic tests for SARS-CoV-2 has led to a decrease in availability of clinical samples for viral genomic surveillance. As an alternative sample source, we evaluated RNA isolated from BinaxNOW swabs stored at ambient temperature for SARS-CoV-2 rRT-PCR and full viral genome sequencing. 81 of 103 samples (78.6%) yielded detectable RNA, and 46 of 57 samples (80.7 %) yielded complete genome sequences. Our results illustrate that SARS-CoV-2 RNA extracted from used Binax test swabs provides an important opportunity for improving SARS-CoV-2 genomic surveillance, evaluating transmission clusters, and monitoring within-patient evolution.", + "rel_num_authors": 11, "rel_authors": [ { - "author_name": "ning sun", - "author_inst": "ningbo college of health sciences" + "author_name": "Phuong-Vi Nguyen", + "author_inst": "Emory University School of Medicine" + }, + { + "author_name": "Ludy Registre Carmola", + "author_inst": "Emory University School of Medicine" + }, + { + "author_name": "Ethan Wang", + "author_inst": "Emory University School of Medicine" + }, + { + "author_name": "Leda Bassit", + "author_inst": "Emory University School of Medicine" + }, + { + "author_name": "Anuradha Rao", + "author_inst": "Emory University School of Medicine" }, { - "author_name": "Laiyou Li", - "author_inst": "Ningbo College of Health Sciences" + "author_name": "Morgan Greenleaf", + "author_inst": "Atlanta Center for Microsystems-Engineered Point-of-Care Technologies" }, { - "author_name": "Jinmei Xu", - "author_inst": "Ningbo College of Health Sciences" + "author_name": "Julie A Sullivan", + "author_inst": "Atlanta Center for Microsystems-Engineered Point-of-Care Technologies" }, { - "author_name": "shuping Zhou", - "author_inst": "Ningbo College of Health Sciences" + "author_name": "Greg Martin", + "author_inst": "Emory University School of Medicine" }, { - "author_name": "Hongyu Li", - "author_inst": "Ningbo College of Health Sciences" + "author_name": "Wilbur Lam", + "author_inst": "Emory University School of Medicine" }, { - "author_name": "shuang Yang", - "author_inst": "Ningbo College of Health Sciences" + "author_name": "Jesse Waggoner", + "author_inst": "Emory University School of Medicine" }, { - "author_name": "Chaoyan Fan", - "author_inst": "The Affiliated People's Hospital of Ningbo University" + "author_name": "Anne Piantadosi", + "author_inst": "Emory University School of Medicine" } ], "version": "1", - "license": "cc_by", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "health policy" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2023.01.09.23284335", @@ -131636,33 +131427,29 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2023.01.03.23284127", - "rel_title": "The Defense of Shangri-La: A Thought Experiment of Periodic Community-wide Screening in the Future Pandemic", + "rel_doi": "10.1101/2023.01.04.23284173", + "rel_title": "Mechanistic view on the influence of fluctuations in outdoor temperature on the worsening of the course of the disease and hospitalizations associated with the SARS-CoV-2 Omicron wave in 2022 in the Tomsk region, Russia", "rel_date": "2023-01-05", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.01.03.23284127", - "rel_abs": "ObjectivesIn a dangerous future pandemic without effective vaccines and medicines, a reliable screening-and-isolation strategy can be the last opportunity to keep critical facilities and communities running and avoid a complete shutdown.\n\nMethodsIn this study, we introduced an epidemiological model that included essential parameters of infection transmission and screening. With varying parameters, we studied the dynamics of viral infection in the semi-isolated communities.\n\nResultsIn the scenario with a periodic infection screening once per 3 days and a viral basic reproduction number 3.0, more than 85% of the infection waves have a duration less than 7 days and the infection size in each of the waves is generally less than 4 individuals when the efficiency of infection discovery is 0.9 in the screening. When the period of screening was elongated to once per 7 days, the cases of infection dramatically increased to 5 folds of that mentioned previously. Further, with a weak discovery efficiency of 0.7 and the aforementioned low screening frequency, the spread of infection would be out of control.\n\nConclusionsOur study suggests that frequent periodic screening is capable of controlling a future epidemic in a semi-isolated community without vaccines and medicines.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2023.01.04.23284173", + "rel_abs": "It is well known that low air temperatures negatively affect the human respiratory system and can suppress protective mechanisms in airways epithelial cells.\n\nIn this study, we put forward the hypothesis that the compromised airway epithelium of infected persons can be extremely sensitive to external influences and therefore can be used as an \"indicator\" and serve to investigate the impact of low air temperatures (as and other external factors) on the respiratory system.\n\nHere we supposed that a short-term impact of drop in outdoor temperature on the compromised airway epithelium should lead to increased symptoms and severity of the disease.\n\nWe have analyzed a short-term impact of the air temperature drop on the worsening of disease in patients with COVID-19 (indicated by bursts of daily hospitalizations), which fell on the main epidemic wave in 2022 associated with SARS-CoV-2 Omicron variant.\n\nIt was found that even a small and/or short-term impact of drop in outdoor daily temperatures can lead to increased symptoms and severity of the disease (COVID-19).\n\nWe have identified 14 characteristic points (days) where the temperature drop was more than 3 degrees during the main pandemic wave in 2022. It was shown that each characteristic points clearly associated with characteristic bursts in the number of daily hospitalizations with a time lag of 1-2 days.\n\nThus, it was found that the results of the study can be used in predicting a sudden increase in the number of hospitalizations, which can be used to timely warn clinics and medical hospitals for an increase in the number of seriously ill patients.\n\nThe findings can be used to improve systems to prevent additional risks connected with impact of drop in air temperature on worsening disease in patients and infected people who do not have or have mild or subtle symptoms of the disease - especially during an epidemic or pandemic wave.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Anqi Duan", - "author_inst": "Fudan University" + "author_name": "Alexander Ishmatov", + "author_inst": "V.E. Zuev Institute of Atmospheric Optics SB RAS, Academician Zuev square, 1, Tomsk, Russia, 634055" }, { - "author_name": "Jian Li", - "author_inst": "Fudan University" + "author_name": "Abdrey Bart", + "author_inst": "V.E. Zuev Institute of Atmospheric Optics SB RAS, Academician Zuev square, 1, Tomsk, Russia, 634055" }, { - "author_name": "Zhen Yang", - "author_inst": "Fudan University" - }, - { - "author_name": "YUNGANG HE", - "author_inst": "Fudan University" + "author_name": "Semyon Yakovlev", + "author_inst": "V.E. Zuev Institute of Atmospheric Optics SB RAS, Academician Zuev square, 1, Tomsk, Russia, 634055" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -134086,65 +133873,65 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2023.01.01.22283267", - "rel_title": "Usability and performance of the MicroGEM Sal6830, an RT-PCR saliva-based point-of-care platform to detect SARS-CoV-2 in primary healthcare settings with non-laboratory trained operators.", + "rel_doi": "10.1101/2022.12.28.22283666", + "rel_title": "Post-Exposure Prophylaxis with SA58 (anti-COVID-19 monoclonal antibody) Nasal Spray for the prevention of symptomatic Coronavirus Disease 2019 in healthy adult workers: A randomized, single-blind, placebo-controlled clinical study", "rel_date": "2023-01-03", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.01.01.22283267", - "rel_abs": "The beginning of the COVID-19 pandemic demonstrated how few point-of-care diagnostic tools were available that could be safely and easily operated by healthcare workers with no laboratory training. The gold-standard test, and initially the only test, used RT-PCR with nasal pharyngeal swabs (NPS). Two issues quickly emerged: 1) RT-PCR required central laboratory processing leading to significant time delays and 2) NPS collection causes discomfort, is inappropriate for ongoing repeat sampling of individuals (e.g., frontline healthcare workers) and poses difficulty when obtaining samples from some sections of the population (e.g. some elderly and young children). The Sal6830 platform is a fully self-contained, RT-PCR point-of-care device for detecting SARS-CoV-2 from saliva that takes less than thirty minutes to complete. In this study we tested the usability of the Sal6830 platform by healthcare workers unfamiliar with the instrument at two community clinics: Care 4 U Community Health Center (Miami, Florida, USA) and St. Marys Health Wagon (Wise, Virginia, USA). Staff participated in three tests: 1) determining SARS-CoV-2 status from blinded positive and negative saliva samples, 2) a clinical study comparing SARS-CoV-2 detection with a comparator point-of-care technology from the same patient and 3) completing a survey designed to measure comfort and confidence using the Sal6830 point-of-care device having received no training. Participants overwhelming found the Sal6830 platform easy and intuitive to use, successfully called SARS-CoV-2 status of contrived, blinded samples and measured a 93.3% overall percent agreement when comparing patient samples across two point-of-care technologies.", + "rel_link": "https://medrxiv.org/cgi/content/short/2022.12.28.22283666", + "rel_abs": "BACKGROUNDThis study has assessed a new Anti-COVID-19 Monoclonal Antibody Nasal Spray (SA58) for post-exposure prophylaxis (PEP) against symptomatic coronavirus disease 2019 (COVID-19).\n\nMETHODSWe conducted an efficacy study in adults aged 18 years and older within three days of exposure to a SARS-CoV-2 infected individual. Recruited participants were randomized in a ratio of 3:1 to receive SA58 or placebo. Primary endpoints were laboratory-confirmed symptomatic COVID-19 within study period.\n\nFINDINGSA total of 1,222 participants were randomized and dosed (SA58, n=901; placebo, n=321). Median of follow-up was 2{middle dot}25 days and 2{middle dot}79 days for SA58 and placebo, respectively. Adverse events occurred in 221 of 901 (25%) and 72 of 321 (22%) participants with SA58 and placebo, respectively, with no significant difference (P=0{middle dot}49). All adverse events were mild in severity. Laboratory-confirmed symptomatic COVID-19 developed in 7 of 824 participants (0{middle dot}22 per 100 person-days) in the SA58 group vs 14 of 299 (1{middle dot}17 per 100 person-days) in the placebo group, resulting in an estimated efficacy of 80 {middle dot} 82% (95%CI 52 {middle dot} 41%-92 {middle dot} 27%). There were 32 SARS-CoV-2 RT-PCR positives (1{middle dot}04 per 100 person-days) in the SA58 group vs 32 (2{middle dot}80 per 100 person-days) in the placebo group, resulting in an estimated efficacy of 61{middle dot}83% (95%CI 37{middle dot} 50%-76{middle dot} 69%). A total of 21 RT-PCR positive samples were sequenced. 21 lineages of SARS-CoV-2 variants were identified, and all were the Omicron variant BF{middle dot}7.\n\nINTERPRETATIONSA58 Nasal Spray showed favorable efficacy and safety in preventing SARS-CoV-2 infection or symptomatic COVID-19 in healthy adult workers who had exposure to SARS-CoV-2 within 72 hours.\n\nFUNDINGNo funding was received for this study.\n\nResearch in contextO_ST_ABSEvidence before this studyC_ST_ABSMonoclonal antibodies (mAbs) and the post-exposure prophylaxis (PEP) with mAbs represent a very important public health strategy against COVID-19 outbreak. SA58 Nasal Spray is a broad-spectrum anti-COVID-19 mAb, developed by Sinovac Life Sciences Ltd. for treatment and prophylaxis against COVID-19. SA58 has been shown to potently neutralize ACE2-utilizing sarbecoviruses, including most of circulating Omicron variants. We searched PubMed on Nov 21, 2022, for published clinical trials, with no language or date restrictions, using various combinations of the search terms of \"monoclonal antibodies\", \"SARS-CoV-2\", \"COVID-19\", \"prophylaxis\", and \"prevention\". Three published trials were identified. The first study reported the efficacy of AZD7442 (tixagevimab/cilgavimab) PEP against symptomatic COVID-19 in adults aged [≥]18 years over a 183-day follow-up period. The primary efficacy end point of post-exposure prevention of symptomatic COVID-19 was not met, though AZD7442 showed promising results in participants who were SARS-CoV-2 RT-PCR negative at baseline. The second study reported the efficacy and safety of bamlanivimab for COVID-19 prevention in household contacts of individuals with a SARS-CoV-2 infection in a high-risk transmission setting over a one-month efficacy assessment period. The third study reported REGEN-COV (casirivimab/imdevimab) for preventing symptomatic Covid-19 and asymptomatic SARS-CoV-2 infection in previously uninfected household contacts of infected persons. Both bamlanivimab and REGEN-COV showed satisfactory safety profile and efficacy against COVID-19 and were licensed for PEP use in the U.S. However, due to the circulating Omicron variants have developed significant escape properties, the emergency use authorization of bamlanivimab and REGEN-COV for treatment and PEP against COVID-19 has been discontinued by the U.S. Food and Drug Administration. Till the end of December 2022, no drug was available for PEP use against COVID-19.\n\nAdded value of this studyDuring a recent large outbreak of the Omicron BF{middle dot}7 sublineage in Beijing, our preliminary results in healthy adults within 72 hours of contact with SARS-CoV-2-infected individuals showed that SA58 nasal spray was highly effective in preventing symptomatic COVID-19 and SARS-CoV-2 infection caused by the sublineage, which variants have shown significant escape of immunity in previous studies. SA58 was able to significantly lower the risk of laboratory-confirmed COVID-19 by 80{middle dot}82% (95%CI 52{middle dot}41%-92{middle dot}27%) and of SARS-CoV-2 infection by 61{middle dot}83% (95%CI 37{middle dot}50%-76{middle dot}69%) in our study participants.\n\nImplications of all the available evidenceThis trial showed the ability of a nasal spray of broad-spectrum anti-COVID-19 mAb SA58 to provide satisfactory protection against one circulating Omicron strain of SARS-CoV-2. The drug had a favorable safety profile and was well tolerated by healthy adults. This newly developed mAb is resistant to SARS-CoV-2 mutations and may provide a new powerful countermeasure to tackle against the immunity-escaping variants of SARS-CoV-2 circulating in the population. The intranasal administration of SA58 is novel and has many advantages over intramuscular injections of mAbs previously licensed, as it is less invasive and more acceptable in recipients. Auto-administration with easiness of use may allow early administration, probably a key feature for prevention.", "rel_num_authors": 12, "rel_authors": [ { - "author_name": "Vanessa Mills", - "author_inst": "Care 4 U Community Health Centre, Miami, Florida, USA" + "author_name": "Rui Song", + "author_inst": "Beijing Ditan Hospital, Capital Medical University" }, { - "author_name": "Teresa Owen Tyson", - "author_inst": "St. Marys Health Wagon, Wise, Virginia, USA." + "author_name": "Gang Zeng", + "author_inst": "Sinovac Biotech, Ltd." }, { - "author_name": "Rachel Helton", - "author_inst": "St. Marys Health Wagon, Wise, Virginia, USA." + "author_name": "Jianxing Yu", + "author_inst": "Sinovac Biotech, Ltd." }, { - "author_name": "Paula Hill-Collins", - "author_inst": "St. Marys Health Wagon, Wise, Virginia, USA." + "author_name": "Xing Meng", + "author_inst": "Sinovac Biotech, Ltd." }, { - "author_name": "Sarah Hubbard", - "author_inst": "St. Marys Health Wagon, Wise, Virginia, USA." + "author_name": "Xiaoyou Chen", + "author_inst": "Beijing Ditan Hospital, Capital Medical University" }, { - "author_name": "Anchi Scott", - "author_inst": "MicroGEM, Charlottesville, Virginia, United States of America" + "author_name": "Jing Li", + "author_inst": "Sinovac Life Sciences co. Ltd." }, { - "author_name": "Jeff Hickey", - "author_inst": "MicroGEM, Charlottesville, Virginia, United States of America" + "author_name": "Xiaoliang Xie", + "author_inst": "Biomedical Pioneering Innovation Center (BIOPIC), Peking University; Changping Laboratory" }, { - "author_name": "Brian E Root", - "author_inst": "MicroGEM, Charlottesville, Virginia, United States of America" + "author_name": "Xiaojuan Lian", + "author_inst": "Sinovac Life Sciences co. Ltd." }, { - "author_name": "Rory O'Brien", - "author_inst": "MicroGEM, Charlottesville, Virginia, United States of America" + "author_name": "Zhiyun Zhang", + "author_inst": "Beijing Ditan Hospital, Capital Medical University" }, { - "author_name": "Jillian Conte", - "author_inst": "MicroGEM, Charlottesville, Virginia, United States of America" + "author_name": "Yunlong Cao", + "author_inst": "Biomedical Pioneering Innovation Center (BIOPIC), Peking University; Changping Laboratory" }, { - "author_name": "Jo-Ann L Stanton", - "author_inst": "MicroGEM, Charlottesville, Virginia, United States of America" + "author_name": "Weidong Yin", + "author_inst": "Sinovac Biotech, Ltd." }, { - "author_name": "Jeff D Chapman", - "author_inst": "MicroGEM, Charlottesville, Virginia, United States of America" + "author_name": "Ronghua Jin", + "author_inst": "Beijing Ditan Hospital, Capital Medical University" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -135908,23 +135695,55 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2022.12.27.22283962", - "rel_title": "New compartment model for COVID-19", + "rel_doi": "10.1101/2022.12.29.522182", + "rel_title": "A robust deep learning platform to predict CD8+ T-cell epitopes", "rel_date": "2022-12-29", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.12.27.22283962", - "rel_abs": "Population is separated into five compartments for COVID-19; susceptible individuals (S), pre-symptomatic patients (P), asymptomatic patients (A), quarantined patients (Q) and recovered and/or dead patients (R). The time evolution of each compartment is described by a set of ordinary differential equations. Numerical solution to the set of differential equations shows that quarantining pre-symptomatic and asymptomatic patients is effective in controlling the pandemic. It is also shown that the ratio of non-symptomatic patients to the daily confirmed new cases can be as large as 20 and that the fraction of untraceable cases in new cases can be as large as 80%, depending on the policies for social distancing and PCR test.", - "rel_num_authors": 1, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2022.12.29.522182", + "rel_abs": "T-cells play a crucial role in the adaptive immune system by inducing an anti-tumour response, defending against pathogens, and maintaining tolerance against self-antigens, which has sparked interest in the development of T-cell-based vaccines and immunotherapies. Because screening antigens driving the T-cell response is currently low-throughput and laborious, computational methods for predicting CD8+ T-cell epitopes have emerged. However, most immunogenicity algorithms struggle to learn features of peptide immunogenicity from small datasets, suffer from HLA bias and are unable to reliably predict pathology-specific CD8+ T-cell epitopes. Therefore, we developed TRAP (T-cell recognition potential of HLA-I presented peptides), a robust deep learning platform for predicting CD8+ T-cell epitopes from MHC-I presented pathogenic and self-peptides. TRAP uses transfer learning, deep learning architecture and MHC binding information to make context-specific predictions of CD8+ T-cell epitopes. TRAP also detects low-confidence predictions for peptides that differ significantly from those in the training datasets to abstain from making incorrect predictions. To estimate the immunogenicity of pathogenic peptides with low-confidence predictions, we further developed a novel metric, RSAT (relative similarity to autoantigens and tumour-associated antigens), as a complementary to dissimilarity to self from cancer studies. We used TRAP to identify epitopes from glioblastoma patients as well as SARS-CoV-2 peptides, and it outperformed other algorithms in both cancer and pathogenic settings. Thus, this study presents a novel computational platform for accurately predicting CD8+ T-cell epitopes to foster a better understanding of antigen-specific T-cell response and the development of effective clinical therapeutics.\n\nHighlightsO_LIHLA bias and out-of-distribution problem are causes of poor performance of current state-of-the-art algorithms\nC_LIO_LITransfer learning, deep learning architecture, context-specific and HLA-generalised approaches improve CD8+ T-cell epitope prediction\nC_LIO_LITRAP reports degree of correctness to improve reliability of the prediction\nC_LIO_LIA novel metric termed RSAT estimates immunogenicity of pathogenic peptides, as a complementary to dissimilarity to self from cancer studies\nC_LI", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Takashi Odagaki", - "author_inst": "Research Institute for Science Education Inc." + "author_name": "Chloe Hyung-Jung Lee", + "author_inst": "University of Oxford" + }, + { + "author_name": "Jaesung Huh", + "author_inst": "Oxford University" + }, + { + "author_name": "Paul R Buckley", + "author_inst": "Oxford University" + }, + { + "author_name": "Myeong Jun Jang", + "author_inst": "Oxford University" + }, + { + "author_name": "Mariana Pereira Pinho", + "author_inst": "Oxford University" + }, + { + "author_name": "Ricardo Fernandes", + "author_inst": "Oxford University" + }, + { + "author_name": "Agne Antanaviciute", + "author_inst": "Oxford University" + }, + { + "author_name": "Alison Simmons", + "author_inst": "Oxford University" + }, + { + "author_name": "Hashem Koohy", + "author_inst": "The University of Oxford" } ], "version": "1", "license": "cc_by_nc_nd", - "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "type": "new results", + "category": "bioinformatics" }, { "rel_doi": "10.1101/2022.12.29.522202", @@ -137738,91 +137557,87 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.12.22.22283855", - "rel_title": "Comparison of multiple whole-genome and Spike-only sequencing protocols for estimating variant frequencies via wastewater-based epidemiology", + "rel_doi": "10.1101/2022.12.23.22283921", + "rel_title": "EFFECTIVENESS OF CASIRIVIMAB-IMDEVIMAB AND SOTROVIMAB MONOCLONAL ANTIBODY TREATMENT AMONG HIGH-RISK PATIENTS WITH SARS-CoV-2 INFECTION: A REAL-WORLD EXPERIENCE", "rel_date": "2022-12-26", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.12.22.22283855", - "rel_abs": "Sequencing of SARS-CoV-2 in wastewater provides a key opportunity to monitor the prevalence of variants spatiotemporally, potentially facilitating their detection simultaneously with, or even prior to, observation through clinical testing. However, there are multiple sequencing methodologies available. This study aimed to evaluate the performance of alternative protocols for detecting SARS-CoV-2 variants. We tested the detection of two synthetic RNA SARS-CoV-2 genomes in a wide range of ratios and at two concentrations representative of those found in wastewater using whole-genome and Spike-gene-only protocols utilising Illumina and Oxford Nanopore platforms. We developed a Bayesian hierarchical model to determine the predicted frequencies of variants and the error surrounding our predictions. We found that most of the sequencing protocols detected polymorphic nucleotide frequencies at a level that would allow accurate determination of the variants present at higher concentrations. Most methodologies, including the Spike-only approach, could also predict variant frequencies with a degree of accuracy in low-concentration samples but, as expected, with higher error around the estimates. All methods were additionally confirmed to detect the same prevalent variants in a set of wastewater samples. Our results provide the first quantitative statistical comparison of a range of alternative methods that can be used successfully in the surveillance of SARS-CoV-2 variant frequencies from wastewater.\n\nImpactGenetic sequencing of SARS-CoV-2 in wastewater provides an ideal system for monitoring variant frequencies in the general population. The advantages over clinical data are that it is more cost efficient and has the potential to identify new variants before clinical testing. However, to date, there has been no direct comparison to determine which sequencing methodologies perform best at identifying the presence and prevalence of variants. Our study compares seven sequencing methods to determine which performs best. We also develop a Bayesian statistical methodology to estimate the confidence around variant frequency estimates. Our results will help monitor SARS-CoV-2 variants in wastewater, and the methodology could be adapted for other disease monitoring, including future pandemics.", - "rel_num_authors": 18, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.12.23.22283921", + "rel_abs": "BACKGROUNDSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) can evade neutralizing antibodies, raising concerns about the effectiveness of anti-spike monoclonal antibodies (mAb).\n\nMETHODSThis study reports a retrospective data analysis in Banner Health Care System. Out of 109,788 adult patients who tested positive for COVID-19, the study cohort was split into patients who received Casirivimab-Imdevimab (Cas-Imd) (N=10,836; Delta-predominant period 6/2021-11/2021) and Sotrovimab (N=998; Omicron-predominant period 12/2021-1/2022) mAb compared to propensity-matched control groups (N=10,836 and N=998), respectively. Index date was the date of mAb administration or the date of positive COVID-19 testing. The primary and secondary outcomes were the incidence of composite outcome (all-cause hospitalization and/or mortality) and ICU admission at 30-days following index date, respectively.\n\nRESULTSCompared to the propensity-matched untreated control cohort, the Cas-Imd mAb reduced the composite outcome (from 7.5% to 3.7%; difference: -3.8% [95% CI: (-4.4%, -3.2%)], p <0.01) regardless of their vaccination status, while Sotrovimab mAb did not (5.0% vs. 3.8%; difference: -1.2% [95% CI: (-3.1%, 0.7%)], p =0.22). In terms of the secondary outcome, similarly Cas-Imd mAb decreased ICU admission during the first hospitalization (from 1.5% to 0.5%; difference: -1.0% [95% CI: (-1.3%, -0.7%)], p <0.01) compared to the control group, whereas Sotrovimab mAb did not (0.9% vs. 0.6%; difference: -0.3% [95% CI: (-1.2%, 0.6%)], p =0.61). Comparing the periods, the Omicron-predominant period was associated with lower composite outcome than that during the Delta-predominant period.\n\nCONCLUSIONSCas-Imd mAb was effective against the SARS-CoV-2 Delta variant, however sotrovimab lacked efficacy in patients with SARS-CoV-2 Omicron-predominant period.\n\nKey PointsThis retrospective propensity matched analysis showed that treatment with Cas-Imd mAb was effective against the SARS-CoV-2 Delta variant to reduce the all-cause hospitalization and mortality within 30 days, by contrast sotrovimab mAb utilization lacked the efficacy against SARS-CoV-2 Omicron variant.", + "rel_num_authors": 17, "rel_authors": [ { - "author_name": "Lucy A Winder", - "author_inst": "University of Sheffield" - }, - { - "author_name": "Paul Parsons", - "author_inst": "University of Sheffield" + "author_name": "Bekir Tanriover", + "author_inst": "University of Arizona College of Medicine" }, { - "author_name": "Gavin Horsburgh", - "author_inst": "University of Sheffield" + "author_name": "Ahmet Berk Gungor", + "author_inst": "Banner University Medicine Tucson" }, { - "author_name": "Kathryn Maher", - "author_inst": "University of Sheffield" + "author_name": "Mohanad Al-Obaidi", + "author_inst": "The University of Arizona College of Medicine \u2013 Tucson: The University of Arizona College of Medicine Tucson" }, { - "author_name": "Helen Hipperson", - "author_inst": "University of Sheffield" + "author_name": "Bijin Thajudeen", + "author_inst": "Banner Health University Medicine" }, { - "author_name": "Claudia Wierzbicki", - "author_inst": "University of Liverpool" + "author_name": "Ryan Wong", + "author_inst": "Banner Health University Medicine" }, { - "author_name": "Aaron R Jeffries", - "author_inst": "University of Exeter" + "author_name": "Iyad Mansour", + "author_inst": "Banner University Medicine Tucson" }, { - "author_name": "Mathew R Brown", - "author_inst": "UK Health Security Agency" + "author_name": "Tirdad Zangeneh", + "author_inst": "The University of Arizona College of Medicine \u2013 Tucson: The University of Arizona College of Medicine Tucson" }, { - "author_name": "Aine Fairbrother-Browne", - "author_inst": "UK Health Security Agency" + "author_name": "Katherine Johnson", + "author_inst": "Banner Health University Medicine Tucson" }, { - "author_name": "Hubert Denise", - "author_inst": "UK Health Security Agency" + "author_name": "Nicole Low", + "author_inst": "Banner Health University Medicine Tucson" }, { - "author_name": "Mohammad S Khalifa", - "author_inst": "UK Health Security Agency" + "author_name": "Ruhaniyah Alam", + "author_inst": "Banner Health University Medicine Tucson" }, { - "author_name": "Irene Bassano", - "author_inst": "UK Health Security Agency" + "author_name": "Elvira Gonzalez", + "author_inst": "Banner Health University Medicine Tucson" }, { - "author_name": "Ronny van Aerle", - "author_inst": "UK Health Security Agency" + "author_name": "Burhaneddin Sandikci", + "author_inst": "Istanbul Technical University" }, { - "author_name": "Rachel Williams", - "author_inst": "Bangor University" + "author_name": "Sangeetha Muruganpandian", + "author_inst": "Banner Health University Medicine Tucson" }, { - "author_name": "Kata Farcas", - "author_inst": "Bangor University" + "author_name": "Gaurav Gupta", + "author_inst": "Virginia Commonwealth University Medical Center" }, { - "author_name": "Steve Paterson", - "author_inst": "University of Liverpool" + "author_name": "Edward Bedrick", + "author_inst": "The University of Arizona Mel and Enid Zuckerman College of Public Health" }, { - "author_name": "Paul G Blackwell", - "author_inst": "University of Sheffield" + "author_name": "Turcin Saridogan", + "author_inst": "Division of Nephrology, College of Medicine, The University of Arizona, Tucson, Arizona" }, { - "author_name": "Terry Burke", - "author_inst": "The University of Sheffield" + "author_name": "Katherine Mendoza", + "author_inst": "The University of Arizona College of Medicine \u2013 Tucson: The University of Arizona College of Medicine Tucson" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2022.12.23.22283902", @@ -139548,77 +139363,61 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.12.22.22283816", - "rel_title": "SARS-CoV-2 RNA and viable virus contamination of hospital emergency department surfaces and association with patient COVID-19 status and aerosol generating procedures", + "rel_doi": "10.1101/2022.12.21.22283785", + "rel_title": "Quantitative multi-organ proteomics of fatal COVID-19 uncovers tissue-specific effects beyond inflammation", "rel_date": "2022-12-22", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.12.22.22283816", - "rel_abs": "BackgroundInfectious aerosols and droplets generated by SARS-CoV-2-positive patient aerosol generating procedures (AGPs), coughing, or exhalation could potentially contaminate surfaces, leading to indirect SARS-CoV-2 spread via fomites. Our objective was to determine SARS-CoV-2 surface contamination frequency in Emergency Department (ED) patient rooms with respect to patient SARS-CoV-2 status and AGP receipt.\n\nMethodsSwabs were collected from fixed surfaces or equipment in the rooms of patients under investigation for COVID-19 or known to be SARS-CoV-2-positive. Environmental swabs were tested for SARS-CoV-2 RNA by RT-qPCR; RNA-positive samples were cultured in Vero E6 cells. Room contamination was also evaluated by clinical severity of COVID-19 and time since symptom onset.\n\nResultsIn total, 202 rooms were sampled: 42 SARS-CoV-2-positive AGP patient rooms, 45 non-AGP SARS-CoV-2-positive patient rooms, and 115 SARS-CoV-2-negative AGP patient rooms. SARS-CoV-2 RNA was detected on 36 (3.6%) surfaces from 29 (14.4%) rooms. RNA contamination was detected more frequently in rooms occupied by non-AGP SARS-CoV-2- positive patients than SARS-CoV-2-positive AGP patients (28.9% vs 14.3%, p=0.078). Infectious virus was cultured from one non-AGP SARS-CoV-2-positive patient room. There was no significant difference in room positivity according to COVID-19 severity or time since symptom onset.\n\nConclusionSARS-CoV-2 RNA contamination of ED room surfaces was highest and most frequent in rooms occupied by SARS-CoV-2-positive patients who did not undergo an AGP, which may be attributable to disease stage and viral shedding; however, there was no difference in room contamination according to COVID-19 severity or time since symptom onset.", - "rel_num_authors": 15, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.12.21.22283785", + "rel_abs": "SARS-CoV-2 directly damages lung tissue via its infection and replication process and indirectly due to systemic effects of the host immune system. There are few systems-wide, untargeted studies of these effects on the different tissues of the human body and nearly all of them base their conclusions on the transcriptome. Here we developed a parallelized mass spectrometry (MS)-based proteomics workflow allowing the rapid, quantitative analysis of hundreds of virus-infected and FFPE preserved tissues. The first layer of response in all tissues was dominated by circulating inflammatory molecules. To discriminated between these systemic and true tissue-specific effects, we developed an analysis pipeline revealing that proteome alterations reflect extensive tissue damage, mostly similar to non-COVID diffuse alveolar damage. The next most affected organs were kidney and liver, while the lymph-vessel system was also strongly affected. Finally, secondary inflammatory effects of the brain correlated with receptor rearrangements and the degradation of neuronal myelin. Our results establish MS-based tissue proteomics as a promising strategy to inform organ-specific therapeutic interventions following COVID-19 infections.", + "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Scott C. Roberts", - "author_inst": "Yale School of Medicine" - }, - { - "author_name": "Elliana S. Barbell", - "author_inst": "Yale School of Public Health" - }, - { - "author_name": "Doug Barber", - "author_inst": "Yale School of Medicine" - }, - { - "author_name": "Suzanne Dahlberg", - "author_inst": "Yale New Haven Hospital" - }, - { - "author_name": "Robert Heimer", - "author_inst": "Yale School of Public Health" + "author_name": "Lisa Schweizer", + "author_inst": "Department of Proteomics and Signal Transduction; Max-Planck Institute of Biochemistry; Martinsried, Bavaria, 82152; Germany" }, { - "author_name": "Karen Jubanyik", - "author_inst": "Yale School of Medicine" + "author_name": "Tina Schaller", + "author_inst": "Institute of Pathology and Molecular Diagnostics; University Medical Center Augsburg; Augsburg, Bavaria, 86156; Germany" }, { - "author_name": "Vivek Parwani", - "author_inst": "Yale School of Medicine" + "author_name": "Maximilian Zwiebel", + "author_inst": "Department of Proteomics and Signal Transduction; Max-Planck Institute of Biochemistry; Martinsried, Bavaria, 82152; Germany" }, { - "author_name": "Melinda M. Pettigrew", - "author_inst": "Yale School of Public Health" + "author_name": "Ozge Karayel", + "author_inst": "Department of Proteomics and Signal Transduction; Max-Planck Institute of Biochemistry; Martinsried, Bavaria, 82152; Germany" }, { - "author_name": "Jason M. Tanner", - "author_inst": "Yale School of Medicine" + "author_name": "Johannes Bruno Mueller-Reif", + "author_inst": "Department of Proteomics and Signal Transduction; Max-Planck Institute of Biochemistry; Martinsried, Bavaria, 82152; Germany" }, { - "author_name": "Andrew Ulrich", - "author_inst": "Yale School of Medicine" + "author_name": "Wen-Feng Zeng", + "author_inst": "Department of Proteomics and Signal Transduction; Max-Planck Institute of Biochemistry; Martinsried, Bavaria, 82152; Germany" }, { - "author_name": "Martina Wade", - "author_inst": "Yale School of Public Health" + "author_name": "Sebastian Dintner", + "author_inst": "Institute of Pathology and Molecular Diagnostics; University Medical Center Augsburg; Augsburg, Bavaria, 86156; Germany" }, { - "author_name": "Anne L. Wyllie", - "author_inst": "Yale School of Public Health" + "author_name": "Klaus Hirschbuehl", + "author_inst": "Hematology and Oncology, Medical Faculty; University of Augsburg; Augsburg, Bavaria, 86156; Germany" }, { - "author_name": "Devyn Yolda-Carr", - "author_inst": "Yale School of Public Health" + "author_name": "Bruno Maerkl", + "author_inst": "Institute of Pathology and Molecular Diagnostics; University Medical Center Augsburg; Augsburg, Bavaria, 86156; Germany" }, { - "author_name": "Richard A. Martinello", - "author_inst": "Yale School of Medicine" + "author_name": "Rainer Claus", + "author_inst": "Institute of Pathology and Molecular Diagnostics and Hematology and Oncology, Medical Faculty; University of Augsburg; Augsburg, Bavaria, 86156; Germany" }, { - "author_name": "Windy D Tanner", - "author_inst": "Yale School of Public Health" + "author_name": "Matthias Mann", + "author_inst": "Department of Proteomics and Signal Transduction; Max-Planck Institute of Biochemistry; Martinsried, Bavaria, 82152; Germany" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -141202,75 +141001,107 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.12.20.521197", - "rel_title": "Genome-based comparison between the recombinant SARS-CoV-2 XBB and its parental lineages", + "rel_doi": "10.1101/2022.12.19.521129", + "rel_title": "Rapid recall and de novo T cell responses during SARS-CoV-2 breakthrough infection", "rel_date": "2022-12-20", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.12.20.521197", - "rel_abs": "Recombination is the main contributor to RNA virus evolution, and SARS-CoV-2 during the pandemic produced several recombinants. The most recent SARS-CoV-2 recombinant is the lineage labeled XBB, also known as Gryphon, which arose from BJ.1 and BM. 1.1.1. Here we performed a genome-based survey aimed to compare the new recombinant with its parental lineages that never became dominant. Genetic analyses indicated that the recombinant XBB and its first descendant XBB.1 show an evolutionary condition typical of an evolutionary blind background with no further epidemiologically relevant descendant. Genetic variability and expansion capabilities are slightly higher than parental lineages. Bayesian Skyline Plot indicates that XBB reached its plateau around October 6, 2022 and after an initial rapid growth the viral population size did not further expand, and around November 10, 2022 its levels of genetic variability decreased. Simultaneously with the reduction of the XBB population size, an increase of the genetic variability of its first sub-lineage XBB.1 occurred, that in turn reached the plateau around November 9, 2022 showing a kind of vicariance with its direct progenitors. Structure analysis indicates that the affinity for ACE2 surface in XBB/XBB.1 RBDs is weaker than for BA.2 RBD. In conclusion, nowadays XBB and XBB.1 do not show evidence about a particular danger or high expansion capability. Genome-based monitoring must continue uninterrupted in order to individuate if further mutations can make XBB more dangerous or generate new subvariants with different expansion capability.", - "rel_num_authors": 14, + "rel_link": "https://biorxiv.org/cgi/content/short/2022.12.19.521129", + "rel_abs": "While the protective role of neutralising antibodies against COVID-19 is well-established, questions remain about the relative importance of cellular immunity. Using 6 pMHC-multimers in a cohort with early and frequent sampling we define the phenotype and kinetics of recalled and primary T cell responses following Delta or Omicron breakthrough infection. Recall of spike-specific CD4+ T cells was rapid, with cellular proliferation and extensive activation evident as early as 1 day post-symptom onset. Similarly, spike-specific CD8+ T cells were rapidly activated but showed variable levels of expansion. Strikingly, high levels of SARS-CoV-2-specific CD8+ T cell activation at baseline and peak were strongly correlated with reduced peak SARS-CoV-2 RNA levels in nasal swabs and accelerated clearance of virus. Our study demonstrates rapid and extensive recall of memory T cell populations occurs early after breakthrough infection and suggests that CD8+ T cells contribute to the control of viral replication in breakthrough SARS-CoV-2 infections.", + "rel_num_authors": 22, "rel_authors": [ { - "author_name": "Fabio Scarpa", - "author_inst": "University of Sassari" + "author_name": "Marios Koutsakos", + "author_inst": "University of Melbourne" }, { - "author_name": "Daria Sanna", - "author_inst": "Department of Biomedical Sciences, University of Sassari, Sassari, Italy" + "author_name": "Arnold Reynaldi", + "author_inst": "Kirby Institute" }, { - "author_name": "Ilenia Azzena", - "author_inst": "Department of Biomedical Sciences, University of Sassari, Sassari, Italy - Department of Veterinary Medicine, University of Sassari, Sassari, Italy;" + "author_name": "Wen Shi Lee", + "author_inst": "University of Melbourne" }, { - "author_name": "Marco Casu", - "author_inst": "Department of Veterinary Medicine, University of Sassari, Sassari, Italy;" + "author_name": "Julie Nguyen", + "author_inst": "University of Melbourne" }, { - "author_name": "Piero Cossu", - "author_inst": "Department of Veterinary Medicine, University of Sassari, Sassari, Italy;" + "author_name": "Thakshila Amarasena", + "author_inst": "University of Melbourne" }, { - "author_name": "Pier Luigi Fiori", - "author_inst": "Department of Biomedical Sciences, University of Sassari, Sassari, Italy" + "author_name": "George Taiaroa", + "author_inst": "University of Melbourne at The Peter Doherty Institute" }, { - "author_name": "Domenico Benvenuto", - "author_inst": "Unit of Medical Statistics and Molecular Epidemiology, University Campus Bio-Medico of Rome, Rome, Italy" + "author_name": "Paul Kinsella", + "author_inst": "Peter Doherty Institute" }, { - "author_name": "Elena Imperia", - "author_inst": "Unit of Medical Statistics and Molecular Epidemiology, University Campus Bio-Medico of Rome, Rome, Italy - Unit of Gastroenterology, Department of Medicine, Un" + "author_name": "Kwee Chin Liew", + "author_inst": "Peter Doherty Institute" }, { - "author_name": "Marta Giovanetti", - "author_inst": "Laboratorio de Flavivirus, Instituto Oswaldo Cruz, Fundacao Oswaldo Cruz, Rio de Janeiro, Rio de Janeiro, Brazil - Department of Science and Technology for Huma" + "author_name": "Thomas Tran", + "author_inst": "Victorian Infectious Diseases Reference Laboratory" }, { - "author_name": "Giancarlo Ceccarelli", - "author_inst": "Department of Public Health and Infectious Diseases, University Hospital Policlinico Umberto I, Sapienza University of Rome, Rome, Italy;" + "author_name": "Helen E Kent", + "author_inst": "Peter Doherty Institute for Infection and Immunity" }, { - "author_name": "Roberto Cauda", - "author_inst": "UOC Malattie Infettive, Infectious Disease Department, Fondazione Policlinico Universitario Agostino Gemelli IRCCS, 00168 Rome, Italy" + "author_name": "Hyon-Xhi Tan", + "author_inst": "University of Melbourne" }, { - "author_name": "Antonio Cassone", - "author_inst": "Center of Genomic, Genetic and Biology, 53100 Siena, Italy" + "author_name": "Louise C Rowntree", + "author_inst": "University of Melbourne" }, { - "author_name": "Stefano Pascarella", - "author_inst": "Department of Biochemical Sciences A. Rossi Fanelli, Sapienza Universita di Roma, 00185 Rome, Italy" + "author_name": "Thi H. O. Nguyen", + "author_inst": "University of Melbourne" }, { - "author_name": "Massimo Ciccozzi", - "author_inst": "Unit of Medical Statistics and Molecular Epidemiology, University Campus Bio-Medico of Rome, Rome, Italy" + "author_name": "Katherine Kedzierska", + "author_inst": "University of Melbourne" + }, + { + "author_name": "Jan Petersen", + "author_inst": "Monash University" + }, + { + "author_name": "Jamie Rossjohn", + "author_inst": "Monash University" + }, + { + "author_name": "Deborah A Williamson", + "author_inst": "Victorian Infectious Diseases Reference Laboratory" + }, + { + "author_name": "David Khoury", + "author_inst": "Kirby Institute" + }, + { + "author_name": "Miles Philip Davenport", + "author_inst": "UNSW Sydney" + }, + { + "author_name": "Stephen J. Philip Kent", + "author_inst": "University of Melbourne" + }, + { + "author_name": "Adam K Wheatley", + "author_inst": "University of Melbourne" + }, + { + "author_name": "Jennifer A Juno", + "author_inst": "University of Melbourne" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "new results", - "category": "genetics" + "category": "immunology" }, { "rel_doi": "10.1101/2022.12.19.517879", @@ -143352,35 +143183,23 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.12.15.22283533", - "rel_title": "Synthesizing evidence on the impacts of COVID-19 regulatory changes on methadone treatment for opioid use disorder: Implications for U.S. federal policy", + "rel_doi": "10.1101/2022.12.15.22283529", + "rel_title": "SARS-CoV-2-associated mortality with a principal cause other than COVID-19 during the Omicron epidemic in France and detection and treatment of Omicron infections in associated complications", "rel_date": "2022-12-16", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.12.15.22283533", - "rel_abs": "As the U.S. faces a worsening overdose crisis, improving access to evidence-based treatment for opioid use disorder (OUD) remains a central policy priority. Federal regulatory changes in response to the COVID-19 pandemic significantly expanded flexibilities on take-home doses for methadone treatment for OUD. These changes have fueled critical questions about the impact of new regulations on OUD outcomes, and the potential health impact of permanently integrating these flexibilities into treatment policy going forward. To aide US policy makers as they consider implementing permanent methadone regulatory changes, we conducted a review synthesizing peer-reviewed research evidence on the impact of the COVID-19 methadone-take-home flexibilities on methadone program operations, OUD patient and provider experiences, and patient health outcomes. We interpret this evidence in the context of the federal rulemaking process and discuss avenues by which these important findings can be incorporated and implemented into U.S. substance use treatment policy going forward.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.12.15.22283529", + "rel_abs": "BackgroundWith the emergence of the Omicron variant, an increasing proportion of SARS-CoV-2 associated deaths have a principal cause of death other than COVID-19. In France, between Nov. 1, 2021 --July 31, 2022, in addition to 33,353 deaths with the principal cause of COVID-19, there were 9,638 deaths with a confirmed SARS-CoV-2 infection with a principal cause of death other than COVID-19 (as well as SARS-CoV-2-associated deaths with an undetected SARS-CoV-2 infection).\n\nMethodsWe examined the relation between mortality for COVID-19, mortality for other causes, and ICU admissions with a SARS-CoV-2-infection in adults aged over 60y in France.\n\nResultsThe number of deaths with principal causes other than COVID-19 in France between July 2021-June 2022 was greater than the corresponding number between July 2020-June 2021 by 20,860 (95% CI (11241,30421)) after adjusting for pre-pandemic trends in mortality (compared to the increase of 3,078 in the number of deaths with a SARS-CoV-2 infection with principal causes other than COVID-19 between the two time periods). During the period of Omicron circulation (Nov. 1, 2021 - Nov. 13, 2022), there was a strong association between the rates of ICU admission with a SARS-CoV-2 infection in adults aged over 60y and (a) rates of COVID-19 deaths (correlation=0.96 (0.92,0.97)); (b) rates of mortality with principal causes other than COVID-19 (correlation=0.89 (0.82,0.94)). Proportions of ICU admissions for causes other than COVID-19 among all ICU admissions with a SARS-CoV-2 infection in older adults were lower during the periods when rates of COVID-19 disease in the community were higher.\n\nConclusionsThe significant increase in mortality with principal causes other than COVID-19, as well as the decreases in the proportions of ICU admissions for causes other than COVID-19 among all ICU admissions with a SARS-CoV-2 infection in older adults during the periods when rates of COVID-19 disease in the community were higher suggest under-detection of Omicron infections in associated complications that did not manifest themselves as COVID-19, which is related to the treatment of SARS-CoV-2 infection in those complications.", + "rel_num_authors": 1, "rel_authors": [ { - "author_name": "Noa Krawczyk", - "author_inst": "NYU Grossman School of Medicine" - }, - { - "author_name": "Bianca D. Rivera", - "author_inst": "NYU Grossman School of Medicine" - }, - { - "author_name": "Emily Levin", - "author_inst": "The George Washington University" - }, - { - "author_name": "Bridget C.E. Dooling", - "author_inst": "The George Washington University" + "author_name": "Edward Goldstein", + "author_inst": "Massachusetts Eye and Ear Hospital, Harvard Medical School" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", - "category": "addiction medicine" + "category": "epidemiology" }, { "rel_doi": "10.1101/2022.12.15.22282869", @@ -145042,83 +144861,107 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2022.12.13.22283434", - "rel_title": "Robust SARS-CoV-2 antibody and T cell immunity following three COVID-19 vaccine doses in inflammatory bowel disease patients receiving anti-TNF or alternative treatments", + "rel_doi": "10.1101/2022.12.14.520006", + "rel_title": "2-Thiouridine is a broad-spectrum antiviral nucleoside analogue against positive-strand RNA viruses", "rel_date": "2022-12-14", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.12.13.22283434", - "rel_abs": "BACKGROUND AND AIMSVaccine-mediated immune responses in patients with inflammatory bowel disease (IBD) may be influenced by IBD therapies. We investigated in-depth humoral and T-cell responses to SARS-CoV-2 vaccination in IBD patients following three COVID-19 vaccine doses.\n\nMETHODSImmune responses of 100 SARS-CoV-2-uninfected IBD patients on varying treatments were compared to healthy controls (n=35). Anti-S1/2 and anti-RBD SARS-CoV-2-specific antibodies, CD4+ and CD8+ T-cell responses were measured at baseline and at five time-points after COVID-19 vaccination.\n\nRESULTSAnti-S1/2 and anti-RBD antibody concentrations at [~]1 month after second dose vaccination were significantly lower in anti-TNF-treated patients compared to non-TNF IBD patients and healthy controls (126.4 vs 262.1 and 295.5, p<0.0001). Anti-S1/2 antibodies remained reduced in anti-TNF treated patients before and after the third dose (285.7 vs 365.3, p=0.03), although anti-RBD antibodies reached comparable titres to non-TNF patients. Anti-RBD antibodies were higher in the vedolizumab group than controls after second dose (4.2 vs 3.6, p=0.003). Anti-TNF monotherapy was associated with increased CD4+ and CD8+ T-cell activation compared to combination anti-TNF patients after second dose, but comparable after third dose. Overall, IBD patients demonstrated similar CD4+/CD8+ T-cell responses compared to healthy controls regardless of treatment regimen.\n\nCONCLUSIONSAnti-TNFs impaired antibody concentrations when compared to non-TNF patients and controls after two vaccine doses. These differences were not observed after the third vaccine dose. However, vaccine induced SARS-CoV-2-specific T cell responses are robust in anti-TNF-treated patients. Our study supports the need for timely booster vaccination particularly in anti-TNF treated patients to minimise the risk of severe SARS-CoV-2 infection.", - "rel_num_authors": 16, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2022.12.14.520006", + "rel_abs": "Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection causes significant morbidity and mortality worldwide, seriously impacting not only human health but also the global economy. Furthermore, over 1 million cases of newly emerging or re-emerging viral infections, specifically dengue virus (DENV), are known to occur annually. Because no virus-specific and fully effective treatments against these and many other viruses have been approved, they continue to be responsible for large-scale epidemics and global pandemics. Thus, there is an urgent need for novel, effective therapeutic agents. Here, we identified 2-thiouridine (s2U) as a broad-spectrum antiviral nucleoside analogue that exhibited antiviral activity against SARS-CoV-2 and its variants of concern, including the Delta and Omicron variants, as well as a number of other positive-sense single-stranded RNA (ssRNA+) viruses, including DENV. s2U inhibits RNA synthesis catalyzed by viral RNA-dependent RNA polymerase, thereby reducing viral RNA replication, which improved the survival rate of mice infected with SARS-CoV-2 or DENV in our animal models. Our findings demonstrate that s2U is a potential broad-spectrum antiviral agent not only against SARS-CoV-2 and DENV but other ssRNA+ viruses.", + "rel_num_authors": 22, "rel_authors": [ { - "author_name": "Eva Zhang", - "author_inst": "Royal Melbourne Hospital" + "author_name": "Kentaro Uemura", + "author_inst": "Hokkaido University" }, { - "author_name": "Thi O Nguyen", - "author_inst": "Peter Doherty Institute for Infection and Immunity" + "author_name": "Haruaki Nobori", + "author_inst": "Shionogi & Co., Ltd." }, { - "author_name": "Lilith Allen", - "author_inst": "Peter Doherty Institute for Infection and Immunity" + "author_name": "Akihiko Sato", + "author_inst": "Shionogi & Co., Ltd." }, { - "author_name": "Lukasz Kedzierski", - "author_inst": "Peter Doherty Institute for Infection and Immunity" + "author_name": "Shinsuke Toba", + "author_inst": "Shionogi & Co., Ltd." }, { - "author_name": "Louise C Rowntree", - "author_inst": "Peter Doherty Institute for Infection and Immunity" + "author_name": "Shinji Kusakabe", + "author_inst": "Shionogi & Co., Ltd." }, { - "author_name": "So Young Chang", - "author_inst": "Peter Doherty Institute for Infection and Immunity" + "author_name": "Michihito Sasaki", + "author_inst": "International Institute for Zoonosis Control, Hokkaido University" }, { - "author_name": "Isabelle J Foo", - "author_inst": "Peter Doherty Institute for Infection and Immunity" + "author_name": "Koshiro Tabata", + "author_inst": "Hokkaido Univeristy" }, { - "author_name": "Jennifer R Habel", - "author_inst": "Peter Doherty Institute for Infection and Immunity" + "author_name": "Keita Matsuno", + "author_inst": "Hokkaido Univeristy" }, { - "author_name": "Wuji Zhang", - "author_inst": "Peter Doherty Institute for Infection and Immunity" + "author_name": "Naoyoshi Maeda", + "author_inst": "Hokkaido Univeristy" }, { - "author_name": "Tejas Menon", - "author_inst": "Peter Doherty Institute for Infection and Immunity" + "author_name": "Shiori Ito", + "author_inst": "Hokkaido Univeristy" }, { - "author_name": "Jeni Mitchell", - "author_inst": "Royal Melbourne Hospital" + "author_name": "Mayu Tanaka", + "author_inst": "Hokkaido Univeristy" }, { - "author_name": "Rupert Leong", - "author_inst": "Macquarie University" + "author_name": "Yuki Anraku", + "author_inst": "Hokkaido Univeristy" }, { - "author_name": "Katherine Bond", - "author_inst": "Royal Melbourne Hospital" + "author_name": "Shunsuke Kita", + "author_inst": "Hokkaido Univeristy" }, { - "author_name": "Deborah A Williamson", - "author_inst": "Peter Doherty Institute for Infection and Immunity" + "author_name": "Mayumi Ishii", + "author_inst": "Univeristy of Tokyo" }, { - "author_name": "Britt Christensen", - "author_inst": "Royal Melbourne Hospital" + "author_name": "Kayoko Kanamitsu", + "author_inst": "Univeristy of Tokyo" }, { - "author_name": "Katherine Kedzierska", - "author_inst": "University of Melbourne" + "author_name": "Yasuko Orba", + "author_inst": "Hokkaido Univeristy" + }, + { + "author_name": "Yoshiharu Matsuura", + "author_inst": "Osaka University" + }, + { + "author_name": "William W. Hall", + "author_inst": "School of Medicine, University College of Dublin" + }, + { + "author_name": "Hirofumi Sawa", + "author_inst": "Hokkaido Univeristy" + }, + { + "author_name": "Hiroshi Kida", + "author_inst": "Hokkaido Univeristy" + }, + { + "author_name": "Akira Matsuda", + "author_inst": "Hokkaido Univeristy" + }, + { + "author_name": "Katsumi Maenaka", + "author_inst": "Hokkaido University" } ], "version": "1", "license": "cc_by_nc_nd", - "type": "PUBLISHAHEADOFPRINT", - "category": "gastroenterology" + "type": "new results", + "category": "microbiology" }, { "rel_doi": "10.1101/2022.12.14.520411", @@ -147111,127 +146954,119 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2022.12.12.22283387", - "rel_title": "Seroprevalence of SARS-CoV-2 antibodies and retrospective mortality in two African settings: Lubumbashi, Democratic Republic of the Congo and Abidjan, Cote dIvoire", + "rel_doi": "10.1101/2022.12.13.520255", + "rel_title": "Preclinical efficacy, safety, and immunogenicity of PHH-1V, a second-generation COVID-19 vaccine, in non-human primates", "rel_date": "2022-12-13", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.12.12.22283387", - "rel_abs": "BackgroundAlthough seroprevalence studies have demonstrated the wide circulation of SARS-COV-2 in African countries, the impact on population health in these settings is still poorly understood. Using representative samples of the general population, we evaluated retrospective mortality and seroprevalence of anti-SARS-CoV-2 antibodies in Lubumbashi and Abidjan.\n\nMethodsThe studies included retrospective mortality surveys and nested anti-SARS-CoV-2 antibody prevalence surveys. In Lubumbashi the study took place during April-May 2021 and in Abidjan the survey was implemented in two phases: July-August 2021 and October-November 2021. Crude mortality rates were stratified between pre-pandemic and pandemic periods and further investigated by age group and COVID waves. Anti-SARS-CoV-2 seroprevalence was quantified by rapid diagnostic testing (RDT) and laboratory-based testing (ELISA in Lubumbashi and ECLIA in Abidjan).\n\nResultsIn Lubumbashi, the crude mortality rate (CMR) increased from 0.08 deaths per 10 000 persons per day (pre-pandemic) to 0.20 deaths per 10 000 persons per day (pandemic period). Increases were particularly pronounced among <5 years old. In Abidjan, no overall increase was observed during the pandemic period (pre-pandemic: 0.05 deaths per 10 000 persons per day; pandemic: 0.07 deaths per 10 000 persons per day). However, an increase was observed during the third wave (0.11 deaths per 10 000 persons per day). The estimated seroprevalence in Lubumbashi was 15.7% (RDT) and 43.2% (laboratory-based). In Abidjan, the estimated seroprevalence was 17.4% (RDT) and 72.9% (laboratory-based) during the first phase of the survey and 38.8% (RDT) and 82.2% (laboratory-based) during the second phase of the survey.\n\nConclusionAlthough circulation of SARS-CoV-2 seems to have been extensive in both settings, the public health impact varied. The increases, particularly among the youngest age group, suggest indirect impacts of COVID and the pandemic on population health. The seroprevalence results confirmed substantial underdetection of cases through the national surveillance systems.", - "rel_num_authors": 27, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2022.12.13.520255", + "rel_abs": "SARS-CoV-2 emerged in December 2019 and quickly spread worldwide, continuously striking with an unpredictable evolution. Despite the success in vaccine production and mass vaccination programmes, the situation is not still completely controlled, and therefore accessible second-generation vaccines are required to mitigate the pandemic. We previously developed an adjuvanted vaccine candidate coded PHH-1V, based on a heterodimer fusion protein comprising the RBD domain of two SARS-CoV-2 variants. Here, we report data on the efficacy, safety, and immunogenicity of PHH-1V in cynomolgus macaques. PHH-1V prime-boost vaccination induces high levels of RBD-specific IgG binding and neutralising antibodies against several SARS-CoV-2 variants, as well as a balanced Th1/Th2 cellular immune response. Remarkably, PHH-1V vaccination prevents SARS-CoV-2 replication in the lower respiratory tract and significantly reduces viral load in the upper respiratory tract after an experimental infection. These results highlight the potential use of the PHH-1V vaccine in humans, currently undergoing Phase III clinical trials.", + "rel_num_authors": 25, "rel_authors": [ { - "author_name": "Erica Simons", - "author_inst": "Epicentre" - }, - { - "author_name": "Birgit Nikolay", - "author_inst": "Epicentre" - }, - { - "author_name": "Pascal Ouedraogo", - "author_inst": "Epicentre" + "author_name": "", + "author_inst": "" }, { - "author_name": "Estelle Pasquier", - "author_inst": "Epicentre" + "author_name": "", + "author_inst": "" }, { - "author_name": "Carlos Tiemeni", - "author_inst": "Medecins Sans Frontieres" + "author_name": "", + "author_inst": "" }, { - "author_name": "Ismael Adjaho", - "author_inst": "Medecins Sans Frontieres" + "author_name": "", + "author_inst": "" }, { - "author_name": "Colette Badjo", - "author_inst": "Medecins Sans Frontieres" + "author_name": "", + "author_inst": "" }, { - "author_name": "Kaouther Chamman", - "author_inst": "Epicentre" + "author_name": "", + "author_inst": "" }, { - "author_name": "Mariam Diomand\u00e9", - "author_inst": "Medecins Sans Frontieres" + "author_name": "", + "author_inst": "" }, { - "author_name": "Mireille Dosso", - "author_inst": "Institut Pasteur de C\u00f4te d'Ivoire: Institut Pasteur de Cote d'Ivoire" + "author_name": "", + "author_inst": "" }, { - "author_name": "Moussa Doumbia", - "author_inst": "Institut Pasteur in Ivory Coast: Institut Pasteur de Cote d'Ivoire" + "author_name": "", + "author_inst": "" }, { - "author_name": "Yves Asuni Izia", - "author_inst": "Medecins sans Frontieres" + "author_name": "", + "author_inst": "" }, { - "author_name": "Hugues Kakompe", - "author_inst": "Ministry of Health, Democratic Republic of the Congo" + "author_name": "", + "author_inst": "" }, { - "author_name": "Anne Marie Katsomya", - "author_inst": "Medecins Sans Frontieres" + "author_name": "", + "author_inst": "" }, { - "author_name": "Vicky Kij", - "author_inst": "Ministry of Health, Democratic Republica of the Congo" + "author_name": "", + "author_inst": "" }, { - "author_name": "Viviane Kouakou Akissi", - "author_inst": "Institut Pasteur de C\u00f4te d'Ivoire: Institut Pasteur de Cote d'Ivoire" + "author_name": "", + "author_inst": "" }, { - "author_name": "Christopher Mambula", - "author_inst": "Medecins Sans Frontieres" + "author_name": "", + "author_inst": "" }, { - "author_name": "Placide Mbala-Kingebeni", - "author_inst": "INRB: Institut National de Recherche Biomedicale" + "author_name": "", + "author_inst": "" }, { - "author_name": "Jacques Muzinga", - "author_inst": "Laboratoire National de Lubumbashi" + "author_name": "", + "author_inst": "" }, { - "author_name": "Basile Ngoy", - "author_inst": "Ministry of Health, Democratic Republic of the Congo" + "author_name": "", + "author_inst": "" }, { - "author_name": "Lou Penali", - "author_inst": "Institut Pasteur de Cote d'Ivoire" + "author_name": "", + "author_inst": "" }, { - "author_name": "Alessandro Pini", - "author_inst": "Epicentre" + "author_name": "", + "author_inst": "" }, { - "author_name": "Klaudia Porten", - "author_inst": "Epicentre" + "author_name": "", + "author_inst": "" }, { - "author_name": "Halidou Salou", - "author_inst": "Epicentre" + "author_name": "", + "author_inst": "" }, { - "author_name": "Daouda Sevede", - "author_inst": "Institut Pasteur de C\u00f4te d'Ivoire: Institut Pasteur de Cote d'Ivoire" + "author_name": "", + "author_inst": "" }, { - "author_name": "Francisco Luquero", - "author_inst": "Epicentre" + "author_name": "", + "author_inst": "" }, { - "author_name": "Etienne Gignoux", - "author_inst": "Epicentre" + "author_name": "", + "author_inst": "" } ], "version": "1", - "license": "cc_by", - "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "license": "cc_no", + "type": "new results", + "category": "immunology" }, { "rel_doi": "10.1101/2022.12.12.22283343", @@ -148653,69 +148488,201 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2022.12.06.22283183", - "rel_title": "Lack of effectiveness of Bebtelovimab Monoclonal Antibody Among High-Risk Patients with SARS-Cov-2 Omicron During BA.2, BA.2.12.1 and BA.5 Subvariants Dominated Era", + "rel_doi": "10.1101/2022.12.06.22283000", + "rel_title": "Emergence and antibody evasion of BQ and BA.2.75 SARS-CoV-2 sublineages in the face of maturing antibody breadth at the population level", "rel_date": "2022-12-07", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.12.06.22283183", - "rel_abs": "Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron subvariants are expected to be resistant to Bebtelovimab (BEB) monoclonal antibody (MAb) and the real-world experience regarding its effectiveness is scarce. This retrospective cohort study reports a data analysis in Banner Healthcare System (a large not-for-profit organization) between 4/5/2022 and 8/1/2022 and included 19,778 Coronavirus disease-19 (COVID-19) positive (by PCR or direct antigen testing) patients who were selected from Cerner-Electronic Health Record after the exclusions criteria were met. The study index date for cohort was determined as the date of BEB MAb administration or the date of the first positive COVID-19 testing. The cohort consist of COVID-19 infected patients who received BEB MAb (N=1,091) compared to propensity score (PS) matched control (N=1,091). The primary outcome was the incidence of 30-day all-cause hospitalization and/or mortality. All statistical analyses were conducted on the paired (matched) dataset. For the primary outcome, the event counts and percentages were reported. Ninety-five percent Clopper-Pearson confidence intervals for percentages were computed. The study cohorts were 1:1 propensity matched without replacement across 26 covariates using an optimal matching algorithm that minimizes the sum of absolute pairwise distance across the matched sample after fitting and using logistic regression as the distance function. The pairs were matched exactly on patient vaccination status, BMI group, age group and diabetes status. Compared to the PS matched control group (2.6%; 95% confidence interval [CI]: 1.7%, 3.7%), BEB MAb use (2.2%; 95% CI: 1.4%, 3.3%) did not significantly reduce the incidence of the primary outcome (p=0.67). In the subgroup analysis, we observed similar no-difference trends regarding the primary outcomes for the propensity rematched BEB MAb treated and untreated groups, stratified by patient vaccination status, age (<65 years or [≥]65), and immunocompromised status (patients with HIV/AIDS or solid organ transplants or malignancy including lymphoproliferative disorder). The number needed to treat (1/0.026-0.022) with BEB MAb was 250 to avoid one hospitalization and/or death over 30 days. The BEB MAb use lacked efficacy in patients with SARS-CoV-2 Omicron subvariants (mainly BA.2, BA.2.12.1, and BA.5) in the Banner Healthcare System in the Southwestern United States.", - "rel_num_authors": 13, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.12.06.22283000", + "rel_abs": "The Omicron era of the COVID-19 pandemic commenced at the beginning of 2022 and whilst it started with primarily BA.1, it was latter dominated by BA.2 and related sub-lineages. Over the course of 2022, we monitored the potency and breadth of antibody neutralization responses to many emerging variants at two levels: (i) we tracked over 420,000 U.S. plasma donors over time through various vaccine booster roll outs and Omicron waves using sequentially collected IgG pools; (ii) we mapped the antibody response in individuals using blood from strigently curated vaccine and convalescent cohorts. In pooled IgG samples, we observed the maturation of neutralization breadth to Omicron variants over time through continuing vaccine and infection waves. Importantly, in many cases we observed increased antibody breadth to variants that were yet to be in circulation. Determination of viral neutralization at the cohort level supported equivalent coverage across prior and emerging variants with emerging isolates BQ.1.1, XBB.1, BR.2.1 and XBF the most evasive. Further, these emerging variants were resistant to Evusheld, whilst neutralization resistance to Sotrovimab was restricted to BQ.1.1 and XBF. We conclude at this current point in time that dominant variants can evade antibodies at levels equivalent to their most evasive lineage counterparts but sustain an entry phenotype that continues to promote an additional outgrowth advantage. In Australia, BR2.1 and XBF share this phenotype and are dominating across NSW and Victoria.\n\nResearch in contextO_ST_ABSEvidence before this studyC_ST_ABSUp until the BA.5 wave in mid 2022, many global waves were seeded by dominant variants such as Delta, Omicron BA.1 and Omicron BA.2. Following resolution of the BA.5, was the emergence of a pool of BA.4/5 and BA.2.75 sub-lineages accumulating clusters of similar polymorphisms located with the Receptor Binding Domain (RBD) of the Spike glycoprotein. Although iterative changes in the Spike increased the ability of each variant to navigate existing neutralising antibodies, it was unclear if this alone was sufficient to provide an outgrowth advantage to any one variant to fuel major case waves in global communities with high vaccine uptake and/or infection.\n\nAdded value of this studyPrior studies on incoming variants in Australian quarantine, highlighted the potential for Australia to represent a unique mix of cocirculating variants. Following the resolution of the BA.5 Omicron wave, many globally circulating variants appeared early on and ranged from BA.2.75 lineages, recombinants XBB.1, and XBC.1 in addition to many BA.5 derived BQ.1 lineages. Two additional lineages, the recombinant XBF and the BA.2.75 derived BR.2.1 also appeared and were uniquely enriched in Australia. Using 14 primary clinical isolates covering a continuum of circulating variants in Australia, we resolved neutralisation responses of 110 donors stringently documented for their vaccine and infection status over time. In addition, we also tested the well clinical utilised clinical monoclonals Evusheld and Sotrovimab. In addition to tracking donors, we also tracked immunity at the population level, using pooled IgG samples over time. The latter samples were the sum of 420,000 US plasma donors covering time periods of high-booster uptake alongside and in addition to large case waves. Whilst the above resolved the impact of Spike changes in neutralisations, we also tested each variant with respect to the efficiency of TMPRSS2 use, as this significantly influences viral tropism across the respiratory tract.\n\nImplications of all the available evidenceAll variants analysed herein have undertaken a convergent trajectory in accumulating a similar cluster of Spike polymorphisms. Many variants, including BQ.1.1, XBB.1, XBF and BR.2.1 have accumulated key changes that now render neutralisation responses lower in all cohorts and are neutralisation resistant to Evusheld. Whilst sotrovimab retained neutralisation capacity of many variants, there was significant reduction for variants BQ.1.1 and XBF. Impact of Spike changes on TMPRSS2 use were mixed and only one variant, BQ.1.2, had equal to increased usage relative to its parent BA.5. Analysis of neutralisation at the population level over time revealed two key observations. Firstly, whilst variants converged and lowered neutralisation responses, this reduction was negated over time with increasing neutralisation breadth. Secondly, responses to a variant proceeded its appearance and global circulation. In conclusion, whilst many variants are appearing and iterative changes in the spike will challenge antibody responses, increasing breadth in the community over time has enabled sufficient coverage to presently emerging variants. Furthermore, with the exception of BQ.1.2, viral use of TMPRSS2 has not increased and as such viral tropism towards epithelial cells of the upper respiratory tract we predict will be maintained.", + "rel_num_authors": 46, "rel_authors": [ { - "author_name": "Srilekha Sridhara", - "author_inst": "The University of Arizona College of Medicine \u2013 Tucson: The University of Arizona College of Medicine Tucson" + "author_name": "Anouschka Akerman", + "author_inst": "Kirby Institute, University of New South Wales" }, { - "author_name": "Ahmet B Gungor", - "author_inst": "Banner University Medical Center Tucson" + "author_name": "Vanessa Milogiannakis", + "author_inst": "Kirby Institute, University of New South Wales" }, { - "author_name": "Halil Kutlu Erol", - "author_inst": "The University of Arizona College of Medicine \u2013 Tucson: The University of Arizona College of Medicine Tucson" + "author_name": "Tyra Jean", + "author_inst": "NSW Health Pathology" }, { - "author_name": "Mohanad Al-Obaidi", - "author_inst": "The University of Arizona College of Medicine \u2013 Tucson: The University of Arizona College of Medicine Tucson" + "author_name": "Camille Esneu", + "author_inst": "Hunter Medical Research Institute, University of Newcastle" }, { - "author_name": "Tirdad Zangeneh", - "author_inst": "The University of Arizona College of Medicine \u2013 Tucson: The University of Arizona College of Medicine Tucson" + "author_name": "Mariana Ruiz Silva", + "author_inst": "Kirby Institute, University of New South Wales" }, { - "author_name": "Edward Bedrick", - "author_inst": "The University of Arizona Mel and Enid Zuckerman College of Public Health" + "author_name": "Timothy Ison", + "author_inst": "Kirby Institute, University of New South Wales" }, { - "author_name": "Venkatesh Ariyamuthu", - "author_inst": "The University of Arizona College of Medicine \u2013 Tucson: The University of Arizona College of Medicine Tucson" + "author_name": "Christina Fichter", + "author_inst": "Kirby Institute, University of New South Wales" }, { - "author_name": "Aneesha Shetty", - "author_inst": "The University of Arizona College of Medicine \u2013 Tucson: The University of Arizona College of Medicine Tucson" + "author_name": "Deborah Chandra", + "author_inst": "Kirby Institute, University of New South Wales" }, { - "author_name": "Abd Assalam Qannus", - "author_inst": "The University of Arizona College of Medicine \u2013 Tucson: The University of Arizona College of Medicine Tucson" + "author_name": "Zin Naing", + "author_inst": "NSW Health Pathology" }, { - "author_name": "Katherine Mendoza", - "author_inst": "The University of Arizona College of Medicine \u2013 Tucson: The University of Arizona College of Medicine Tucson" + "author_name": "Gregory Walker", + "author_inst": "NSW Health Pathology" }, { - "author_name": "Sangeetha Murugapandian", - "author_inst": "The University of Arizona College of Medicine \u2013 Tucson: The University of Arizona College of Medicine Tucson" + "author_name": "Joanna Caguicla", + "author_inst": "NSW Health Pathology" }, { - "author_name": "Gaurav Gupta", - "author_inst": "Virginia Commonwealth University Medical Center" + "author_name": "daiyang Li", + "author_inst": "NSW Health Pathology" }, { - "author_name": "Bekir Tanriover", - "author_inst": "University of Arizona College of Medicine" + "author_name": "Supavadee Amatayakul-Chantler", + "author_inst": "CSL Behring, Australia" + }, + { + "author_name": "Sandro Manni", + "author_inst": "CSL Behring AG, Bern, Switzerland." + }, + { + "author_name": "Nath Roth", + "author_inst": "CSL Behring AG, Bern, Switzerland." + }, + { + "author_name": "Thomas Hauser", + "author_inst": "CSL Behring AG, Bern, Switzerland." + }, + { + "author_name": "Anna Condylios", + "author_inst": "NSW Health Pathology" + }, + { + "author_name": "Malinna Yeang", + "author_inst": "NSW Health Pathology" + }, + { + "author_name": "Maureen Wong", + "author_inst": "NSW Health Pathology" + }, + { + "author_name": "Charles S.P. Foster", + "author_inst": "NSW Health Pathology" + }, + { + "author_name": "Sharon Lee", + "author_inst": "Royal Prince Alfred Hospital" + }, + { + "author_name": "Yang Song", + "author_inst": "Westmead Hospital, WSLHD, NSW, Australia" + }, + { + "author_name": "Lijun Mao", + "author_inst": "Westmead Hospital, WSLHD, NSW, Australia" + }, + { + "author_name": "Amy Phu", + "author_inst": "Westmead Hospital, WSLHD, NSW, Australia" + }, + { + "author_name": "Allison Sigmund", + "author_inst": "Westmead Hospital, WSLHD, NSW, Australia" + }, + { + "author_name": "Ann Marie Van de More", + "author_inst": "Royal Prince Alfred Hospital, SLHD, NSW Australia" + }, + { + "author_name": "Stephanie Hunt", + "author_inst": "Royal Prince Alfred Hospital, SLHD, NSW Australia" + }, + { + "author_name": "Kerrie Sandgren", + "author_inst": "The Westmead Institute for Medical Research" + }, + { + "author_name": "Rowena Bull", + "author_inst": "Kirby Institute, University of New South Wales" + }, + { + "author_name": "Andrew Lloyd", + "author_inst": "Kirby Institute, University of New South Wales" + }, + { + "author_name": "James Triccas", + "author_inst": "The University of Sydney" + }, + { + "author_name": "Stuart Tangye", + "author_inst": "Garvan Institute of Medical Research" + }, + { + "author_name": "Anthony L Cunningham", + "author_inst": "The Westmead Institute for Medical Research" + }, + { + "author_name": "Nathan W Bartlett", + "author_inst": "Hunter Medical Research Institute, University of Newcastle" + }, + { + "author_name": "David Darley", + "author_inst": "St Vincent's Hospital" + }, + { + "author_name": "Gail Matthews", + "author_inst": "Kirby Institute, University of New South Wales" + }, + { + "author_name": "Mark Douglas", + "author_inst": "TheWestmead Institute for Medical Research" + }, + { + "author_name": "Kenta Sato", + "author_inst": "Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet, 171 77 Stockholm" + }, + { + "author_name": "Ian Caterson", + "author_inst": "The Westmead Institute for Medical Research" + }, + { + "author_name": "Ben Murrell", + "author_inst": "Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet, 171 77 Stockholm" + }, + { + "author_name": "William D Rawlinson", + "author_inst": "NSW Health Pathology" + }, + { + "author_name": "Fabienne Brilot", + "author_inst": "The University of Sydney" + }, + { + "author_name": "Damien J Stark", + "author_inst": "St Vincent's Hospital" + }, + { + "author_name": "Anthony D Kelleher", + "author_inst": "Kirby Institute, University of New South Wales" + }, + { + "author_name": "Anupriya Aggarwal", + "author_inst": "Kirby Institute, University of New South Wales" + }, + { + "author_name": "Stuart G Turville", + "author_inst": "Kirby Institute, University of New South Wales" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -150427,137 +150394,41 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.12.04.22282902", - "rel_title": "SARS-CoV-2 infection induces the production of autoantibodies in severe COVID-19 patients in an age-dependent manner", + "rel_doi": "10.1101/2022.12.01.22282932", + "rel_title": "Antibody Affinity Maturation to SARS-CoV-2 Omicron Variants in a Teachers Cohort", "rel_date": "2022-12-05", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.12.04.22282902", - "rel_abs": "Age is a significant risk factor for the coronavirus disease 2019 (COVID-19) outcomes due to immunosenescence and certain age-dependent medical conditions (e.g., obesity, cardiovascular disorder, diabetes, chronic respiratory disease). However, despite the well-known influence of age on autoantibody biology in health & disease, its impact on the risk of developing severe COVID-19 remains poorly explored. Here, we performed a cross-sectional study of autoantibodies directed against 58 targets associated with autoimmune diseases in 159 individuals with different COVID-19 outcomes (with 71 mild, 61 moderate, and 27 severe patients) and 73 healthy controls. We found that the natural production of autoantibodies increases with age and is exacerbated by SARS-CoV-2 infection, mostly in severe COVID-19 patients. Multivariate regression analysis showed that severe COVID-19 patients have a significant age-associated increase of autoantibody levels against 16 targets (e.g., amyloid {beta} peptide, {beta} catenin, cardiolipin, claudin, enteric nerve, fibulin, insulin receptor a, and platelet glycoprotein). Principal component analysis with spectrum decomposition based on these autoantibodies indicated an age-dependent stratification of severe COVID-19 patients. Random forest analysis ranked autoantibodies targeting cardiolipin, claudin, and platelet glycoprotein as the three most crucial autoantibodies for the stratification of severe elderly COVID-19 patients. Follow-up analysis using binomial regression found that anti-cardiolipin and anti-platelet glycoprotein autoantibodies indicated a significantly increased likelihood of developing a severe COVID-19 phenotype, presenting a synergistic effect on worsening COVID-19 outcomes. These findings provide new key insights to explain why elderly patients less favorable outcomes have than young individuals, suggesting new associations of distinct autoantibody levels with disease severity.", - "rel_num_authors": 30, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.12.01.22282932", + "rel_abs": "In summer of 2022, a cohort of 28 staff members were recruited from a UK primary school setting. The prevalent variants at the time were Omicron BA.1.159, BA.4/5 and BA.2: 61% of the cohort reported a lateral flow confirmed positive test for SARS-CoV-2 infection in late 2021 or 2022. A fully quantitative antibody screen for concentration and affinity was performed for spike protein variants Wuhan, Alpha, Beta, Gamma, Delta and Omicron BA.1, BA.2.75, BA.2.12.1, BA.4 and BA.5 and a pH dependent affinity was derived from disruption of the epitope-paratope complex at pH 3.2. The cohort showed a Universal positive immunity endotype, U(+), incidence of 78% (95% CI 60% - 88%) with good antibody concentrations to all ten variants; the incidence drops to 25% (95% CI 13% - 43%) when the affinity spectrum is measured. The antibody affinity profiles for each Omicron variant were all significantly better than Alpha, Beta, Gamma and Delta reflecting exposure to the antigens; we surmise either from the booster vaccines or continual contact with the virus, presenting in the school children either asymptomatically or symptomatically. Significant antibody affinity maturation was seen to the spike protein in all prevalent variants of SARS-CoV-2. Antibody concentrations were waning compared to the post-booster vaccine response. Using our hypothesised 3.4 mg/L nasal mucosal protection threshold, we postulate 46% of the cohort required boosting within 60 days and 66% within 120 days. We propose a smart boosting programme around the constant-exposure teacher cohort and parents of children could reduce community transmission.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Dennyson Leandro M. Fonseca", - "author_inst": "Interunit Postgraduate Program on Bioinformatics, Institute of Mathematics and Statistics (IME), University of Sao Paulo" - }, - { - "author_name": "Igor Salerno Filgueiras", - "author_inst": "Department of Immunology, Institute of Biomedical Sciences, University of Sao Paulo" - }, - { - "author_name": "Alexandre HC Marques", - "author_inst": "Department of Immunology, Institute of Biomedical Sciences, University of Sao Paulo" - }, - { - "author_name": "Elroy Vojdani", - "author_inst": "Regenera Medical 11860 Wilshire Blvd., Ste. 301, Los Angeles" - }, - { - "author_name": "Gilad Halpert", - "author_inst": "Ariel University, Israel" - }, - { - "author_name": "Yuri Ostrinski", - "author_inst": "Ariel University, Israel" - }, - { - "author_name": "Gabriela Crispim Baiocchi", - "author_inst": "Department of Immunology, Institute of Biomedical Sciences, University of Sao Paulo" - }, - { - "author_name": "Desiree Rodrigues Placa", - "author_inst": "Department of Clinical and Toxicological Analyses, School of Pharmaceutical Sciences, University of Sao Paulo" - }, - { - "author_name": "Paula P Freire", - "author_inst": "Department of Immunology, Institute of Biomedical Sciences, University of Sao Paulo" - }, - { - "author_name": "Shahab Zaki Pour", - "author_inst": "Laboratory of Molecular Evolution and Bioinformatics, Department of Microbiology, Biomedical Sciences Institute, University of Sao Paulo" - }, - { - "author_name": "Guido Moll", - "author_inst": "Departament of Nephrology and Internal Intensive Care Medicine, Charite University Hospital, Berlin, Germany" - }, - { - "author_name": "Rusan Catar", - "author_inst": "Departament of Nephrology and Internal Intensive Care Medicine, Charite University Hospital, Berlin, Germany" - }, - { - "author_name": "Yael Bublil Lavi", - "author_inst": "Department of Chemistry Ben Gurion University Beer-Sheva, Israel" - }, - { - "author_name": "Jonathan I. Silverberg", - "author_inst": "Department of Dermatology, George Washington University School of Medicine and Health Sciences, Washington, DC, USA" - }, - { - "author_name": "Jason Zimmerman", - "author_inst": "Maimonides Medical Center, Brooklyn, NY, USA" - }, - { - "author_name": "Gustavo Cabral de Miranda", - "author_inst": "Department of Immunology, Institute of Biomedical Sciences, University of Sao Paulo" - }, - { - "author_name": "Robson F Carvalho", - "author_inst": "Department of Structural and Functional Biology, Institute of Biosciences, Sao Paulo State University, Botucatu, Sao Paulo" - }, - { - "author_name": "Taj Ali Khan", - "author_inst": "Institute of Pathology and Diagnostic Medicine, Khyber Medical University, Peshawar, Pakistan" - }, - { - "author_name": "Harald Heidecke", - "author_inst": "CellTrend Gesellschaft mit beschrankter Haftung (GmbH), Luckenwalde, Germany" - }, - { - "author_name": "Rodrigo JS Dalmolin", - "author_inst": "Bioinformatics Multidisciplinary Environment, Federal University of Rio Grande do Norte, Natal, Brazil" - }, - { - "author_name": "Andre Ducati Luchessi", - "author_inst": "Department of Clinical and Toxicological Analyses, Federal University of Rio Grande do Norte, R.N., Brazil" - }, - { - "author_name": "Hans D. Ochs", - "author_inst": "Department of Pediatrics, University of Washington School of Medicine, and Seattle Children's Research Institute, Seattle, WA, USA" - }, - { - "author_name": "Lena F. Schimke", - "author_inst": "Department of Immunology, Institute of Biomedical Sciences, University of Sao Paulo" - }, - { - "author_name": "Howard Amital", - "author_inst": "Ariel University, Israel" - }, - { - "author_name": "Gabriela Riemekasten", - "author_inst": "Department of Rheumatology, University Medical Center Schleswig-Holstein Campus Lubeck, Lubeck, Germany" + "author_name": "Philip H James-Pemberton", + "author_inst": "University of Exeter" }, { - "author_name": "Israel Zyskind", - "author_inst": "Department of Pediatrics, NYU Langone Medical Center, New York, NY, USA" + "author_name": "Shivali Kohli", + "author_inst": "Attomarker Ltd" }, { - "author_name": "Avi Z Rosenberg", - "author_inst": "Department of Pathology, Johns Hopkins University, Baltimore, Maryland, USA" + "author_name": "Aaron Westlake", + "author_inst": "Attomarker Ltd" }, { - "author_name": "Aristo Vojdani", - "author_inst": "Department of Immunology, Immunosciences Laboratory, Inc., Los Angeles, CA, United States" + "author_name": "Alex Antill", + "author_inst": "Attomarker Ltd" }, { - "author_name": "Yehuda Shoenfeld", - "author_inst": "Zabludowicz Center for Autoimmune Diseases, Sheba Medical Center, Tel-Hashomer, Israel" + "author_name": "Rouslan Olkhov", + "author_inst": "Attomarker Ltd" }, { - "author_name": "Otavio Cabral-Marques", - "author_inst": "Department of Immunology, Institute of Biomedical Sciences, University of Sao Paulo" + "author_name": "Andrew Shaw", + "author_inst": "University of Exeter" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -152157,35 +152028,75 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.12.02.22282935", - "rel_title": "Evaluating the use of social contact data to produce age-specific forecasts of SARS-CoV-2 incidence", + "rel_doi": "10.1101/2022.12.01.22282842", + "rel_title": "Analysis of the ARTIC V4 and V4.1 SARS-CoV-2 primers and their impact on the detection of Omicron BA.1 and BA.2 lineage defining mutations", "rel_date": "2022-12-03", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.12.02.22282935", - "rel_abs": "Short-term forecasts can provide predictions of how an epidemic will change in the near future and form a central part of outbreak mitigation and control. Renewal-equation based models are increasingly popular. They infer key epidemiological parameters from historical epidemiological data and forecast future epidemic dynamics without requiring complex mechanistic assumptions. However, these models typically ignore interaction between age-groups, partly due to challenges in parameterising a time varying interaction matrix. Social contact data collected regularly by the CoMix survey during the COVID-19 epidemic in England, provide a means to inform interaction between age-groups in real-time.\n\nWe developed an age-specific forecasting framework and applied it to two age-stratified time-series: incidence of SARS-CoV-2 infection, estimated from a national infection and antibody prevalence survey; and, reported cases according to the UK national COVID-19 dashboard. Jointly fitting our model to social contact data from the CoMix study, we inferred a time-varying next generation matrix which we used to project infections and cases in the four weeks following each of 29 forecast dates between October 2021 and November 2022. We evaluated the forecasts using proper scoring rules and compared performance with three other models with alternative data and specifications alongside two naive baseline models.\n\nOverall, incorporating age-interaction improved forecasts of infections and the CoMix-data-informed model was the best performing model at time horizons between two and four weeks. However, this was not true when forecasting cases. We found that age-group-interaction was most important for predicting cases in children and older adults. The contact-data-informed models performed best during the winter months of 2020 - 2021, but performed comparatively poorly in other periods. We highlight challenges regarding the incorporation of contact data in forecasting and offer proposals as to how to extend and adapt our approach, which may lead to more successful forecasts in future.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.12.01.22282842", + "rel_abs": "The ARTIC protocol uses a multiplexed PCR approach with two primer pools tiling the entire SARS-CoV-2 genome. Primer pool updates are necessary for accurate amplicon sequencing of evolving SARS-CoV-2 variants with novel mutations. The suitability of the ARTIC V4 and updated V4.1 primer scheme was assessed using whole genome sequencing of Omicron from clinical samples using Oxford Nanopore Technology. Analysis of Omicron BA.1 genomes revealed that 93.22% of clinical samples generated improved genome coverage at 50x read depth with V4.1 primers when compared to V4 primers. Additionally, the V4.1 primers improved coverage of BA.1 across amplicons 76 and 88, which resulted in the detection of the variant defining mutations G22898A, A26530G and C26577G. The Omicron BA.2 sub-variant (VUI-22JAN-01) replaced BA.1 as the dominant variant by March 2022, and analysis of 168 clinical samples showed reduced coverage across amplicons 15 and 75. Upon further interrogation of primer binding sites, a mutation at C4321T (present in 163/168, 97% of samples) was identified as a possible cause of complete dropout of amplicon 15. Furthermore, two mutations were identified within the primer binding regions for amplicon 75: A22786C (present in 90% of samples) and C22792T (present in 12.5% of samples). Together, these mutations may result in reduced coverage of amplicon 75 and further primer updates would allow the identification of the two BA.2 defining mutations present in amplicon 75; A22688G and T22679C. This work highlights the need for ongoing surveillance of primer matches as circulating variants evolve and change.", + "rel_num_authors": 14, "rel_authors": [ { - "author_name": "James D Munday", - "author_inst": "London School of Hygiene and Tropical Medicine" + "author_name": "Fatima R Ulhuq", + "author_inst": "NHS Lothian" }, { - "author_name": "Sam Abbott", - "author_inst": "London School of Hygiene and Tropical Medicine" + "author_name": "Madhuri Barge", + "author_inst": "NHS Lothian" }, { - "author_name": "Sophie Meakin", - "author_inst": "London School of Hygiene and Tropical Medicine" + "author_name": "Kerry Falconer", + "author_inst": "NHS Lothian" }, { - "author_name": "Sebastian Funk", - "author_inst": "London School of Hygiene & Tropical Medicine" + "author_name": "Jonathan Wild", + "author_inst": "NHS Lothian" + }, + { + "author_name": "Goncalo Fernandes", + "author_inst": "NHS Lothian" + }, + { + "author_name": "Abbie Gallagher", + "author_inst": "NHS Lothian" + }, + { + "author_name": "Suzie McGinley", + "author_inst": "NHS Lothian" + }, + { + "author_name": "Ahmad Sugadol", + "author_inst": "NHS Lothian" + }, + { + "author_name": "Muhammad Tariq", + "author_inst": "NHS Lothian" + }, + { + "author_name": "Daniel Maloney", + "author_inst": "NHS Lothian, University of Edinburgh" + }, + { + "author_name": "Juliet Kenicer", + "author_inst": "NHS Lothian" + }, + { + "author_name": "Rebecca Dewar", + "author_inst": "NHS Lothian" + }, + { + "author_name": "Kate Templeton", + "author_inst": "NHS Lothian" + }, + { + "author_name": "Martin McHugh", + "author_inst": "NHS Lothian, University of St Andrews" } ], "version": "1", "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2022.12.02.22282931", @@ -154059,71 +153970,67 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.11.28.22282808", - "rel_title": "Characteristics and outcomes of patients with COVID-19 at high-risk of disease progression receiving sotrovimab, oral antivirals or no treatment in England", + "rel_doi": "10.1101/2022.11.28.22282412", + "rel_title": "Evolving SARS-CoV-2 virulence among hospital and university affiliates in Spain and Greater Boston", "rel_date": "2022-11-29", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.11.28.22282808", - "rel_abs": "IntroductionThere is limited real-world evidence surrounding the effectiveness of early, mild-to-moderate COVID-19 treatments following the emergence and dominance of Omicron SARS-CoV-2 subvariants. Here, characteristics and acute clinical outcomes are described for patients with COVID-19 treated with sotrovimab, nirmatrelvir/ritonavir or molnupiravir, or patients at highest risk per NHS criteria but who were untreated.\n\nMethodsRetrospective cohort study of non-hospitalised patients who received early treatment for, or were diagnosed with, COVID-19 between 1 December 2021 and 31 May 2022, using data from the Discover dataset in north-west London. Patients were included if aged [≥]12 years and treated with sotrovimab, nirmatrelvir/ritonavir or molnupiravir, or were untreated but expected to be eligible for early treatment per NHS highest-risk criteria at time of diagnosis. Outcomes were reported for 28 days from COVID-19 diagnosis (index). Subgroup analyses were conducted in patients with advanced renal disease, those aged 18-64 and [≥]65 years and by period of Omicron BA.1, BA.2 and BA.5 (post-hoc exploratory analysis) predominance.\n\nResultsA total of 696 patients prescribed sotrovimab, 337 prescribed nirmatrelvir/ritonavir, 470 prescribed molnupiravir and 4,044 eligible high-risk untreated patients were included. A high proportion of patients on sotrovimab had advanced renal disease (29.3%), [≥]3 high-risk comorbidities (47.6%) and were aged [≥]65 years (36.9%). In total, 5/696 (0.7%) patients on sotrovimab, <5/337 (0.3-1.2%) patients on nirmatrelvir/ritonavir, 10/470 (2.1%) patients on molnupiravir and 114/4,044 (2.8%) untreated patients were hospitalised with COVID-19 as the primary diagnosis. Similar results were observed across all subgroups and during Omicron subvariant periods.\n\nConclusionPatients who received sotrovimab appeared to show evidence of multiple comorbidities that may increase risk of severe COVID-19. Low hospitalisation rates were observed for all treated cohorts across subgroups and periods of predominant variants of concern. These descriptive results require confirmation with comparative effectiveness analyses adjusting for differences in underlying patient characteristics.\n\nKey pointsO_ST_ABSWhy carry out this study?C_ST_ABSO_LIThere is limited real-world evidence surrounding early, mild-to-moderate COVID-19 treatments, particularly during Omicron subvariant dominance periods, and the UK National Institute for Health and Care Excellence has recommended more is gathered.\nC_LIO_LIWe described patient characteristics and clinical outcomes among patients treated with sotrovimab, nirmatrelvir/ritonavir, molnupiravir or who met the highest-risk eligibility criteria but were untreated.\nC_LI\n\nWhat was learned from the study?O_LISotrovimab was often utilised amongst more elderly and at-risk patients, such as those with advanced renal disease, than patients treated with nirmatrelvir/ritonavir or molnupiravir.\nC_LIO_LIWe found that hospitalisation rates were low across all treated cohorts.\nC_LIO_LIFor patients treated with sotrovimab, clinical outcomes appeared consistent when observed across the age subgroups and Omicron subvariant periods, as well as among patients with advanced renal disease.\nC_LI", - "rel_num_authors": 13, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.11.28.22282412", + "rel_abs": "BackgroundThe COVID-19 pandemic caused by the SARS-CoV-2 virus greatly affected healthcare workers and healthcare systems. It also challenged schools and universities worldwide negatively affecting in-person education. We conducted this study is to assess the evolution of SARs-CoV-2 virulence over the course of the pandemic.\n\nMethodsA combined cohort of affiliates from the University of Navarra, two hospitals in Spain, and one healthcare system in the Greater Boston area was followed prospectively from March 8th, 2020, to January 31st, 2022 for diagnosis with COVID-19 by PCR testing and related sequelae. Follow-up time was divided into four periods according to distinct waves of infection during the pandemic. Severity of COVID-19 was measured by case-hospitalization rate. Descriptive statistics and multivariable-adjusted statistics using the Poisson mixed-effects regression model were applied.\n\nResultsFor the last two periods of the study (January 1st to December 15th, 2021 and December 16th, 2021 to January 31st, 2022) and relative to the first period (March 8th to May 31st, 2020), the incidence rate ratios (IRRs) of hospitalization were 0.08 (95% CI, 0.03-0.17) and 0.03 (95% CI, 0.01-0.15), respectively.\n\nInterpretationThe virulence of COVID-19 and immunity of our populations evolved over time, resulting in a decrease in case severity. We found the case-hospitalization rate decreased more than 90% in our cohort despite an increase in incidence.", + "rel_num_authors": 12, "rel_authors": [ { - "author_name": "Vishal Patel", - "author_inst": "GSK" - }, - { - "author_name": "Marcus J. Yarwood", - "author_inst": "Imperial College Health Partners" + "author_name": "Fares Amer", + "author_inst": "University of Navarra" }, { - "author_name": "Bethany Levick", - "author_inst": "OPEN Health Evidence & Access" + "author_name": "Fan-Yun Lan", + "author_inst": "Harvard University T.H. Chan School of Public Health" }, { - "author_name": "Daniel C. Gibbons", - "author_inst": "GSK" + "author_name": "Mario Gil-Conesa", + "author_inst": "University of Navarra" }, { - "author_name": "Myriam Drysdale", - "author_inst": "GSK" + "author_name": "Amalia Sidossis", + "author_inst": "Cambridge Health Alliance" }, { - "author_name": "William Kerr", - "author_inst": "GSK" + "author_name": "Daniel Bruque", + "author_inst": "University of Navarra" }, { - "author_name": "Jonathan D. Watkins", - "author_inst": "Imperial College Health Partners" + "author_name": "Eirini Iliaki", + "author_inst": "Cambridge Health Alliance" }, { - "author_name": "Sophie Young", - "author_inst": "Imperial College Health Partners" + "author_name": "Jane Buley", + "author_inst": "Cambridge Health Alliance" }, { - "author_name": "Benjamin F. Pierce", - "author_inst": "Imperial College Health Partners" + "author_name": "Neetha Nathan", + "author_inst": "Cambridge Health Alliance" }, { - "author_name": "Emily J. Lloyd", - "author_inst": "GSK" + "author_name": "Lou Ann Bruno-Murtha", + "author_inst": "Cambridge Health Alliance" }, { - "author_name": "Helen J. Birch", - "author_inst": "GSK" + "author_name": "Silvia Carlos-Chilleron", + "author_inst": "University of Navarra" }, { - "author_name": "Tahereh Kamalati", - "author_inst": "Imperial College Health Partners" + "author_name": "Stefanos N Kales", + "author_inst": "Cambridge Health Alliance" }, { - "author_name": "Stephen J. Brett", - "author_inst": "Department of Surgery and Cancer, Imperial College" + "author_name": "Alejandro Fernandez-Montero", + "author_inst": "Universidad de Navarra" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "public and global health" }, { "rel_doi": "10.1101/2022.11.29.518231", @@ -155865,115 +155772,55 @@ "category": "biochemistry" }, { - "rel_doi": "10.1101/2022.11.28.518175", - "rel_title": "Fc mediated pan-sarbecovirus protection after alphavirus vector vaccination", - "rel_date": "2022-11-28", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.11.28.518175", - "rel_abs": "Two group 2B {beta}-coronaviruses (sarbecoviruses) have caused regional and global epidemics in modern history. The mechanisms of cross protection driven by the sarbecovirus spike, a dominant immunogen, are less clear yet critically important for pan-sarbecovirus vaccine development. We evaluated the mechanisms of cross-sarbecovirus protective immunity using a panel of alphavirus-vectored vaccines covering bat to human strains. While vaccination did not prevent virus replication, it protected against lethal heterologous disease outcomes in both SARS-CoV-2 and clade 2 bat sarbecovirus HKU3-SRBD challenge models. The spike vaccines tested primarily elicited a highly S1-specific homologous neutralizing antibody response with no detectable cross-virus neutralization. We found non-neutralizing antibody functions that mediated cross protection in wild-type mice were mechanistically linked to FcgR4 and spike S2-binding antibodies. Protection was lost in FcR knockout mice, further supporting a model for non-neutralizing, protective antibodies. These data highlight the importance of FcR-mediated cross-protective immune responses in universal pan-sarbecovirus vaccine designs.", - "rel_num_authors": 24, + "rel_doi": "10.1101/2022.11.23.22280287", + "rel_title": "How COVID-19 pandemic impacted the students and staff physical activity? A study in a Southern Brazilian University", + "rel_date": "2022-11-27", + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2022.11.23.22280287", + "rel_abs": "Physical activity and its positive effects on coronavirus have been extensively discussed in the literature. However, there is still lack of evidence on the effects of the coronavirus pandemic on the health-related behaviors of the Brazilian university community. The aim of the present study is to describe physical activity practice during the coronavirus pandemic among students and staff of a southern Brazilian university, as well as its association with sociodemographic characteristics. This was a self-administered web-based cross-sectional study, carried out among a southern Brazilian community. The main outcome for this study was leisure time physical activity during the coronavirus pandemic. Considering only leisure-time, 21.0% and 24.0% of the students and staff, respectively, reported achieving physical activity recommendations ([≥]150 minutes per week). There was a decline of more than 15 percentage points in physical activity practice comparing pre- and during the pandemic, and those following the protocols of staying at home presented lower levels of leisure-time physical activity. Physical activity practice was mainly performed at home and without any professional help. Leisure-time physical activity prevalence during the pandemic was relatively low among students and staff, and participants that followed staying at home protocols presented lower levels of physical activity.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Lily E. Adams", - "author_inst": "University of North Carolina at Chapel Hill" - }, - { - "author_name": "Sarah R Leist", - "author_inst": "University of North Carolina" - }, - { - "author_name": "Kenneth H Dinnon III", - "author_inst": "University of North Carolina at Chapel Hill" - }, - { - "author_name": "Ande West", - "author_inst": "University of North Carolina at Chapel Hill" - }, - { - "author_name": "Kendra L Gully", - "author_inst": "University of North Carolina" - }, - { - "author_name": "Elizabeth Anderson", - "author_inst": "University of North Carolina" - }, - { - "author_name": "Jennifer F Loome", - "author_inst": "University of North Carolina" - }, - { - "author_name": "Emily Madden", - "author_inst": "University of North Carolina at Chapel Hill" - }, - { - "author_name": "John Powers", - "author_inst": "University of North Carolina at Chapel Hill" - }, - { - "author_name": "Alexandra Schaefer", - "author_inst": "University of North Carolina at Chapel Hill" - }, - { - "author_name": "Sanjay Sarkar", - "author_inst": "University of North Carolina at Chapel Hill" - }, - { - "author_name": "Izabella Castillo", - "author_inst": "The University of North Carolina at Chapel Hill School of Medicine" - }, - { - "author_name": "Jenny Maron", - "author_inst": "Ragon Institute of MGH, MIT, and Harvard University" - }, - { - "author_name": "Ryan P McNamara", - "author_inst": "Ragon Institute of MGH, MIT, and Harvard University" - }, - { - "author_name": "Harry L Bertera", - "author_inst": "Ragon Institute of MGH, MIT, and Harvard University" - }, - { - "author_name": "Mark R Zweigart", - "author_inst": "University of North Carolina" + "author_name": "Rafaela Costa Costa Martins", + "author_inst": "Federal University of Pelotas: Universidade Federal de Pelotas" }, { - "author_name": "Jaclyn S Higgins", - "author_inst": "University of North Carolina at Chapel Hill" + "author_name": "Luiza Isnardi Cardoso Ricardo", + "author_inst": "Federal University of Pelotas" }, { - "author_name": "Brea K Hampton", - "author_inst": "University of North Carolina" + "author_name": "Inacio Crochemore-Silva", + "author_inst": "Federal University of Pelotas" }, { - "author_name": "Prem Lakshmanane", - "author_inst": "University of North Carolina at Chapel Hill" + "author_name": "Flavio Fernando Demarco", + "author_inst": "Federal University of Pelotas" }, { - "author_name": "Galit Alter", - "author_inst": "Ragon Institute of MGH, MIT, and Harvard" + "author_name": "Tiago N Munhoz", + "author_inst": "Federal University of Pelotas" }, { - "author_name": "Stephanie Montgomery", - "author_inst": "Dallas Tissue Research" + "author_name": "Mateus Luz Levandowski", + "author_inst": "Federal University of Pelotas" }, { - "author_name": "Victoria Baxter", - "author_inst": "University of North Carolina at Chapel Hill" + "author_name": "Mariana Gonzalez Cademartori", + "author_inst": "Federal University of Pelotas" }, { - "author_name": "Mark T. Heise", - "author_inst": "University of North Carolina at Chapel Hill" + "author_name": "Helena Silveira Schuch", + "author_inst": "Federal University of Pelotas" }, { - "author_name": "Ralph S. Baric", - "author_inst": "University of North Carolina at Chapel Hill" + "author_name": "Pedro Hallal", + "author_inst": "Federal University of Pelotas" } ], "version": "1", "license": "cc_no", - "type": "new results", - "category": "microbiology" + "type": "PUBLISHAHEADOFPRINT", + "category": "epidemiology" }, { "rel_doi": "10.1101/2022.11.23.22282241", @@ -157839,27 +157686,31 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.11.22.22282631", - "rel_title": "Modeling COVID-19 in different countries as sequences of SI waves", + "rel_doi": "10.1101/2022.11.21.22282563", + "rel_title": "Do Public Health Efforts Matter? Explaining Cross-Country Heterogeneity in Excess Death During the COVID-19 Pandemic", "rel_date": "2022-11-22", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.11.22.22282631", - "rel_abs": "The COVID-19 pandemic has been a huge challenge worldwide for many institutions, researchers, national health organizations, and the pharmaceutical industry. As natural scientists and engineers, we attempted to contribute by calculating models and analyzing data to keep track of the pandemic.\n\nWhile a frequent goal is to predict the next pandemic wave by considering all influencing parameters, we examined methods to calculate a model course of the entire pandemic. This is done by reconstructing the course of infections into multiple model waves that sum up into a pandemic model that is close to the real course. The model wave parameters are varied by an algorithm, such as the Excel solver, to minimize the difference between the real and model courses.\n\nBy reconstructing the course of infections using the commonly known SIR model, we found that the calculated model parameters were ambiguous and difficult to interpret. In contrast, we found that sequenced SI model waves provide an astonishing precise digital representation of the pandemic course. Until November 2022, we found between six and 16 waves (depending on the country) in each of the 14 countries investigated.\n\nThe calculated parameters are easy to interpret and are comparable between different waves and countries. These wave parameters may be correlated with the virus types and measures in each country by other researchers. New waves are detectable early as they show a certain deviation from the actual model wave. After the maximum of the last real wave, the model indicates the further procedure for the pandemic course.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.11.21.22282563", + "rel_abs": "The COVID-19 pandemic has taken a devastating toll around the world. Since January 2020, the World Health Organization estimates 14.9 million excess deaths have occurred globally. Despite this grim number quantifying the deadly impact, the underlying factors contributing to COVID-19 deaths at the population level remain unclear. Prior studies indicate that demographic factors like proportion of population older than 65 and population health explain the cross-country difference in COVID-19 deaths. However, there has not been a holistic analysis including variables describing government policies and COVID-19 vaccination rate. Furthermore, prior studies focus on COVID-19 death rather than excess death to assess the impact of the pandemic. Through a robust statistical modeling framework, we analyze 80 countries and show that actionable public health efforts beyond just the factors intrinsic to each country are necessary to explain the cross-country heterogeneity in excess death.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Rainer Janssen", - "author_inst": "janssen!plan engineering office" + "author_name": "Min Woo Sun", + "author_inst": "Stanford University" }, { - "author_name": "Juergen Mimkes", - "author_inst": "Paderborn University" + "author_name": "David Troxell", + "author_inst": "Stanford University" + }, + { + "author_name": "Robert Tibshirani", + "author_inst": "Stanford University" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "health informatics" }, { "rel_doi": "10.1101/2022.11.22.517073", @@ -159705,35 +159556,27 @@ "category": "genetic and genomic medicine" }, { - "rel_doi": "10.1101/2022.11.17.22282447", - "rel_title": "Modeling analysis of COVID 19-related delays in colorectal cancer screening on simulated clinical outcomes", + "rel_doi": "10.1101/2022.11.15.22282337", + "rel_title": "Did financial interventions offset the impact of financial adversity on mental health during the COVID-19 pandemic? A longitudinal analysis of the UCL COVID-19 Social Study", "rel_date": "2022-11-18", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.11.17.22282447", - "rel_abs": "ObjectiveColorectal cancer (CRC) screening disruptions observed during the COVID-19 pandemic put patients at risk for more advanced-stage disease when diagnosed. This budget impact simulation model assessed increased use of multi-target stool DNA [mt-sDNA] or fecal immunochemical [FIT] tests to offset disruption in colonoscopy screening due to COVID-19 in adults at average-risk for CRC, from a United States payer perspective\n\nMain outcomes and measuresCompared to the base case (S0; 85% colonoscopy and 15% non-invasive tests), the estimated number of missed CRCs and advanced adenomas (AAs) were determined for four COVID-19-affected screening scenarios: S1, 9 months of CRC screening at 50% capacity, followed by 21 months at 75% capacity; S2, S1 followed by increasing stool-based testing by an average of 10% over 3-years; S3, 18 months of CRC screening at 50% capacity, followed by 12 months of 75% capacity; and S4, S3 followed by increasing stool-based testing by an average of 13% over 3-years.\n\nResultsIncreasing the proportional use of mt-sDNA improved AA detection by 6.0% (Scenario 2 versus 1) to 8.4% (Scenario 4 versus 3) and decreased the number of missed CRCs by 15.1% to 17.3%, respectively. Increasing FIT utilization improved the detection of AAs by 3.3% (Scenario 2 versus 1) to 4.6% (Scenario 4 versus 3) and decreased the number of missed CRCs by 12.9% to 14.9%, respectively. Across all scenarios, the number of AAs detected was higher for mt-sDNA than for FIT, and the number of missed CRCs was lower for mt-sDNA than for FIT.\n\nConclusions and relevanceUsing home-based stool tests for average-risk CRC screening can mitigate the consequences of reduced colonoscopy screening resulting from the COVID-19 pandemic. Use of mt-sDNA led to fewer missed CRCs and more AAs detected, compared to FIT.\n\nKey Points\n\nQuestionWhat is the impact of increasing the use of stool-based screening tests for colorectal cancer (CRC) during the COVID-19 pandemic in the United States?\n\nFindingsIn this simulation model, increasing the use of stool-based screening tests increased the number of advanced adenomas detected and decreased the number of missed CRC cases. Use of multi-target stool DNA (mt-sDNA) resulted in a higher number of advanced adenomas detected and a lower number of missed CRC cases compared to fecal immunochemical testing (FIT).\n\nMeaningIncreased use of mt-sDNA led to fewer missed CRC cases and more advanced adenomas detected, compared to FIT, when simulating reduced colonoscopy screening resulting from the COVID-19 pandemic.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.11.15.22282337", + "rel_abs": "BackgroundIt remains unclear whether financial support interventions (e.g., furlough, mortgage freezes, foodbanks, Universal Credit) provide protection against the negative impact of financial adversity on mental health.\n\nMethodsData were from adults who took part in the UCL COVID -19 Social Study between 1 April 2020 and 4 April 2022 who had variability over time in depression (N = 27,297) and anxiety symptoms (N = 26,452). Fixed-effects Poisson regressions examined the associations between an index of financial adversity (e.g., job or income loss) with depression and anxiety symptoms and controlled for other adversities and loneliness. Interaction terms between financial adversity and having used i) any, ii) charity based, iii) government based, iv) work based, and v) other forms of financial supports were examined.\n\nResultsExperiencing financial adversity had a negative impact on mental health. Only charity based support (e.g., foodbanks) consistently attenuated the impact of financial adversity on mental health, whilst work based support exacerbated the impact. Government based support only attenuated the impact of facing limited financial adversity on depression symptoms.\n\nConclusionFindings suggest that most financial interventions are insufficient for alleviating mental health difficulties resulting from financial adversity.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Lesley-Ann Miller Wilson", - "author_inst": "Exact Sciences" - }, - { - "author_name": "Vahab Vahdat", - "author_inst": "Exact Sciences" - }, - { - "author_name": "Durado Brooks", - "author_inst": "Exact Sciences" + "author_name": "Elise Paul", + "author_inst": "University College London" }, { - "author_name": "Paul Limburg", - "author_inst": "Exact Sciences" + "author_name": "Daisy Fancourt", + "author_inst": "University College London" } ], "version": "1", "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "health economics" + "category": "health policy" }, { "rel_doi": "10.1101/2022.11.16.22282396", @@ -161371,79 +161214,107 @@ "category": "medical ethics" }, { - "rel_doi": "10.1101/2022.11.15.516351", - "rel_title": "Molecularly distinct memory CD4+ T cells are induced by SARS-CoV-2 infection and mRNA vaccination", + "rel_doi": "10.1101/2022.11.16.516726", + "rel_title": "Beta-Cyclodextrins as affordable antivirals to treat coronavirus infection", "rel_date": "2022-11-16", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.11.15.516351", - "rel_abs": "Adaptive immune responses are induced by vaccination and infection, yet little is known about how CD4+ T cell memory differs when primed in these two contexts. Notably, viral infection is generally associated with higher levels of systemic inflammation than is vaccination. To assess whether the inflammatory milieu at the time of CD4+ T cell priming has long-term effects on memory, we compared Spike-specific memory CD4+ T cells in 22 individuals around the time of the participants third SARS-CoV-2 mRNA vaccination, with stratification by whether the participants first exposure to Spike was via virus or mRNA vaccine. Multimodal single-cell profiling of Spike-specific CD4+ T cells revealed 755 differentially expressed genes that distinguished infection- and vaccine-primed memory CD4+ T cells. Spike-specific CD4+ T cells from infection-primed individuals had strong enrichment for cytotoxicity and interferon signaling genes, whereas Spike-specific CD4+ T cells from vaccine-primed individuals were enriched for proliferative pathways by gene set enrichment analysis. Moreover, Spike-specific memory CD4+ T cells established by infection had distinct epigenetic landscapes driven by enrichment of IRF-family transcription factors, relative to T cells established by mRNA vaccination. This transcriptional imprint was minimally altered following subsequent mRNA vaccination or breakthrough infection, reflecting the strong bias induced by the inflammatory environment during initial memory differentiation. Together, these data suggest that the inflammatory context during CD4+ T cell priming is durably imprinted in the memory state at transcriptional and epigenetic levels, which has implications for personalization of vaccination based on prior infection history.\n\nOne Sentence SummarySARS-CoV-2 infection versus SARS-CoV-2 mRNA vaccination prime durable transcriptionally and epigenetically distinct Spike-specific CD4+ T cell memory landscapes.", - "rel_num_authors": 15, + "rel_link": "https://biorxiv.org/cgi/content/short/2022.11.16.516726", + "rel_abs": "The SARS-CoV-2 pandemic made evident that we count with few coronavirus-fighting drugs. Here we aimed to identify a cost-effective antiviral with broad spectrum activity and high safety and tolerability profiles. We began elaborating a list of 116 drugs previously used to treat other pathologies or characterized in pre-clinical studies with potential to treat coronavirus infections. We next employed molecular modelling tools to rank the 44 most promising inhibitors and tested their efficacy as antivirals against a panel of and {beta} coronavirus, e.g., the HCoV-229E and SARS-CoV-2 viruses. Four drugs, OSW-1, U18666A, hydroxypropyl-{beta}-cyclodextrin (H{beta}CD) and phytol, showed antiviral activity against both HCoV-229E (in MRC5 cells) and SARS-CoV-2 (in Vero E6 cells). The mechanism of action of these compounds was studied by transmission electron microscopy (TEM) and by testing their capacity to inhibit the entry of SARS-CoV-2 pseudoviruses in ACE2-expressing HEK-293T cells. The entry was inhibited by H{beta}CD and U18666A, yet only H{beta}CD could inhibit SARS-CoV-2 replication in the pulmonary cells Calu-3. With these results and given that cyclodextrins are widely used for drug encapsulation and can be safely administered to humans, we further tested 6 native and modified cyclodextrins, which confirmed {beta}-cyclodextrins as the most potent inhibitors of SARS-CoV-2 replication in Calu-3 cells. All accumulated data points to {beta}-cyclodextrins as promising candidates to be used in the therapeutic treatments for SARS-CoV-2 and possibly other respiratory viruses.", + "rel_num_authors": 22, "rel_authors": [ { - "author_name": "Sophie L Gray-Gaillard", - "author_inst": "Department of Medicine, New York University Grossman School of Medicine; New York, NY, USA" + "author_name": "Dalia Raich-Regue", + "author_inst": "IrsiCaixa, Badalona, Spain" }, { - "author_name": "Sabrina Solis", - "author_inst": "Department of Medicine, New York University Grossman School of Medicine; New York, NY, USA" + "author_name": "Raquel Tenorio", + "author_inst": "National Center for Biotechnology, CSIC, Madrid, Spain" }, { - "author_name": "Han Chen", - "author_inst": "Department of Medicine, New York University Grossman School of Medicine; New York, NY, USA" + "author_name": "Isabel Fernandez-de-Castro", + "author_inst": "National Center for Biotechonology, CSIC, Madrid, Spain" }, { - "author_name": "Clarice Monteiro", - "author_inst": "Department of Medicine, New York University Grossman School of Medicine; New York, NY, USA" + "author_name": "Daniel Perez-Zsolt", + "author_inst": "Irsicaixa" }, { - "author_name": "Grace Ciabattoni", - "author_inst": "Department of Microbiology, New York University School of Medicine; New York, NY, USA" + "author_name": "Jordana Munoz-Basagoiti", + "author_inst": "IrsiCaixa" }, { - "author_name": "Marie I Samanovic", - "author_inst": "Department of Medicine, New York University Grossman School of Medicine; New York, NY, USA" + "author_name": "Martin Sachse", + "author_inst": "Instituto de Salud Carlos III" }, { - "author_name": "Amber R Cornelius", - "author_inst": "Department of Medicine, New York University Grossman School of Medicine; New York, NY, USA" + "author_name": "Sara Fernandez-Sanchez", + "author_inst": "National Center for Biotechnology, CSIC, Madrid, Spain" }, { - "author_name": "Tijaana Williams", - "author_inst": "Department of Medicine, New York University Grossman School of Medicine; New York, NY, USA" + "author_name": "Marcal Gallemi", + "author_inst": "Irsicaixa" }, { - "author_name": "Emilie Geesey", - "author_inst": "Department of Medicine, New York University Grossman School of Medicine; New York, NY, USA" + "author_name": "Paula Ortega-Gonzalez", + "author_inst": "INIA" }, { - "author_name": "Miguel Rodriguez", - "author_inst": "Department of Medicine, New York University Grossman School of Medicine; New York, NY, USA" + "author_name": "Alberto Fernandez-Oliva", + "author_inst": "Rovi Pharmaceutical company" }, { - "author_name": "Mila Brum Ortigoza", - "author_inst": "Department of Medicine, New York University Grossman School of Medicine; New York, NY, USA" + "author_name": "Jose Gabaldon", + "author_inst": "UCAM, Murcia, Spain" }, { - "author_name": "Ellie N Ivanova", - "author_inst": "Department of Pathology, New York University School of Medicine; New York, NY, USA" + "author_name": "Estrella Nunez-Delicado", + "author_inst": "UCAM, Murcia, Spain" }, { - "author_name": "Sergei B Koralov", - "author_inst": "Department of Pathology, New York University School of Medicine; New York, NY, USA" + "author_name": "Josefina Casas", + "author_inst": "IQAC, Barcelona, Spain" }, { - "author_name": "Mark J Mulligan", - "author_inst": "Department of Medicine, New York University Grossman School of Medicine; New York, NY, USA" + "author_name": "Ferran Tarres", + "author_inst": "IRTA-UAB" }, { - "author_name": "Ramin Sedaghat Herati", - "author_inst": "Department of Medicine, New York University Grossman School of Medicine; New York, NY, USA" + "author_name": "Julia Vergara-Alert", + "author_inst": "IRTA-CRESA" + }, + { + "author_name": "Joaquim Segales", + "author_inst": "IRTA-CReSA" + }, + { + "author_name": "Jorge Carrillo", + "author_inst": "Institut de Recerca de la SIDA irsiCaixa" + }, + { + "author_name": "Julia Blanco", + "author_inst": "Institut de Recerca de la SIDA irsiCaixa - HIVACAT" + }, + { + "author_name": "Bonaventura Clotet", + "author_inst": "AIDS Research Institute IrsiCaixa" + }, + { + "author_name": "Jose Ceron-Carrasco", + "author_inst": "CUD, Cartagena, Spain" + }, + { + "author_name": "Nuria Izquierdo-Useros", + "author_inst": "AIDS Research Institute IrsiCaixa" + }, + { + "author_name": "Cristina Risco", + "author_inst": "Centro Nacional de Biotecnologia - CSIC" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "new results", - "category": "immunology" + "category": "microbiology" }, { "rel_doi": "10.1101/2022.11.14.516530", @@ -163025,23 +162896,239 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2022.11.09.22282122", - "rel_title": "SIR analytical model applied to 2020 Covid-19 data in Italy", + "rel_doi": "10.1101/2022.11.07.22282049", + "rel_title": "A myeloid program associated with COVID-19 severity is decreased by therapeutic blockade of IL-6 signaling", "rel_date": "2022-11-13", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.11.09.22282122", - "rel_abs": "A simple analytical Susceptible-Infectious-Recovered (SIR) model without vital dynamics is developed from basic assumptions. Based on the data available for the spread of the Covid 19 virus in Italy in 2020, the characteristic parameters of the model are estimated.", - "rel_num_authors": 1, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.11.07.22282049", + "rel_abs": "Altered myeloid inflammation and lymphopenia are hallmarks of severe infections, including SARS-CoV-2. Here, we identified a gene program, defined by correlation with EN-RAGE (S100A12) gene expression, which was up-regulated in patient airway and blood myeloid cells. The EN-RAGE program was expressed in 7 cohorts and observed in patients with both COVID-19 and acute respiratory distress syndrome (ARDS) from other causes. This program was associated with greater clinical severity and predicted future mechanical ventilation and death. EN-RAGE+ myeloid cells express features consistent with suppressor cell functionality, with low HLA-DR and high PD-L1 surface expression and higher expression of T cell-suppressive genes. Sustained EN-RAGE signature expression in airway and blood myeloid cells correlated with clinical severity and increasing expression of T cell dysfunction markers, such as PD-1. IL-6 upregulated many of the severity-associated genes in the EN-RAGE gene program in vitro, along with potential mediators of T cell suppression, such as IL-10. Blockade of IL-6 signaling by tocilizumab in a placebo-controlled clinical trial led to rapid normalization of ENRAGE and T cell gene expression. This identifies IL-6 as a key driver of myeloid dysregulation associated with worse clinical outcomes in COVID-19 patients and provides insights into shared pathophysiological mechanisms in non-COVID-19 ARDS.", + "rel_num_authors": 55, "rel_authors": [ { - "author_name": "Roberto Simeone", - "author_inst": "None" + "author_name": "Jason A. Hackney", + "author_inst": "Genentech, Inc." + }, + { + "author_name": "Haridha Shivram", + "author_inst": "Genentech, Inc." + }, + { + "author_name": "Jason Vander Heiden", + "author_inst": "Genentech, Inc." + }, + { + "author_name": "Chris Overall", + "author_inst": "Genentech, Inc." + }, + { + "author_name": "Luz Orozco", + "author_inst": "Genentech, Inc." + }, + { + "author_name": "Xia Gao", + "author_inst": "Genentech, Inc." + }, + { + "author_name": "Nathan West", + "author_inst": "Genentech, Inc." + }, + { + "author_name": "Aditi Qamra", + "author_inst": "Hoffman-La Roche Limited" + }, + { + "author_name": "Diana Chang", + "author_inst": "Genentech, Inc." + }, + { + "author_name": "Arindam Chakrabarti", + "author_inst": "Genentech, Inc." + }, + { + "author_name": "David F Choy", + "author_inst": "Genentech, Inc." + }, + { + "author_name": "Alexis J Combes", + "author_inst": "University of California San Francisco" + }, + { + "author_name": "Tristan Courau", + "author_inst": "University of California San Francisco" + }, + { + "author_name": "Gabriela K Fragiadakis", + "author_inst": "University of California San Francisco" + }, + { + "author_name": "Arjun Arkal Rao", + "author_inst": "University of California San Francisco" + }, + { + "author_name": "Arja Ray", + "author_inst": "University of California San Francisco" + }, + { + "author_name": "Jessica Tsui", + "author_inst": "University of California San Francisco" + }, + { + "author_name": "Kenneth Hu", + "author_inst": "University of California San Francisco" + }, + { + "author_name": "Nicholas F Kuhn", + "author_inst": "University of California San Francisco" + }, + { + "author_name": "Matthew F Krummel", + "author_inst": "University of California San Francisco" + }, + { + "author_name": "David J Erle", + "author_inst": "University of California San Francisco" + }, + { + "author_name": "Kirsten Kangelaris", + "author_inst": "University of California San Francisco" + }, + { + "author_name": "Aartik Sarma", + "author_inst": "University of California San Francisco" + }, + { + "author_name": "Zoe Lyon", + "author_inst": "University of California San Francisco" + }, + { + "author_name": "Carolyn S Calfee", + "author_inst": "University of California San Francisco" + }, + { + "author_name": "Prescott G Woodruff", + "author_inst": "University of California San Francisco" + }, + { + "author_name": "Rajani Ghale", + "author_inst": "University of California San Francisco" + }, + { + "author_name": "Eran Mick", + "author_inst": "University of California San Francisco" + }, + { + "author_name": "Ashley Byrne", + "author_inst": "University of California San Francisco" + }, + { + "author_name": "Beth Shoshana Zha", + "author_inst": "University of California San Francisco" + }, + { + "author_name": "Charles Langelier", + "author_inst": "University of California San Francisco" + }, + { + "author_name": "Carolyn M Hendrickson", + "author_inst": "University of California San Francisco" + }, + { + "author_name": "Monique G.P. van der Wijst", + "author_inst": "University of Groningen" + }, + { + "author_name": "George C Hartoularos", + "author_inst": "University of California San Francisco" + }, + { + "author_name": "Tianna Grant", + "author_inst": "University of California San Francisco" + }, + { + "author_name": "Raymund Bueno", + "author_inst": "University of California San Francisco" + }, + { + "author_name": "David S Lee", + "author_inst": "University of California San Francisco" + }, + { + "author_name": "John R Greenland", + "author_inst": "University of California San Francisco" + }, + { + "author_name": "Yang Sun", + "author_inst": "University of California San Francisco" + }, + { + "author_name": "Richard Perez", + "author_inst": "University of California San Francisco" + }, + { + "author_name": "Anton Ogorodnikov", + "author_inst": "University of California San Francisco" + }, + { + "author_name": "Alyssa Ward", + "author_inst": "University of California San Francisco" + }, + { + "author_name": "Chun Jimmie Ye", + "author_inst": "University of California San Francisco" + }, + { + "author_name": "- UCSF COMET Consortium", + "author_inst": "University of California San Francisco" + }, + { + "author_name": "Thiru Ramalingam", + "author_inst": "Genentech, Inc." + }, + { + "author_name": "Jacqueline M McBride", + "author_inst": "Genentech, Inc." + }, + { + "author_name": "Fang Cai", + "author_inst": "Genentech, Inc." + }, + { + "author_name": "Anastasia Teterina", + "author_inst": "Hoffman-La Roche Limited" + }, + { + "author_name": "Min Bao", + "author_inst": "Genentech, Inc." + }, + { + "author_name": "Larry Tsai", + "author_inst": "Genentech, Inc." + }, + { + "author_name": "Ivan O Rosas", + "author_inst": "Baylor College of Medicine" + }, + { + "author_name": "Aviv Regev", + "author_inst": "Genentech, Inc." + }, + { + "author_name": "Sharookh B Kapadia", + "author_inst": "Genentech, Inc." + }, + { + "author_name": "Rebecca N Bauer", + "author_inst": "Genentech, Inc." + }, + { + "author_name": "Carrie M Rosenberger", + "author_inst": "Genentech, Inc." } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2022.11.08.22281846", @@ -164835,103 +164922,31 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2022.11.10.515993", - "rel_title": "An intranasal self-amplifying RNA SARS-CoV-2 vaccine produces durable respiratory and systemic immunity", + "rel_doi": "10.1101/2022.11.10.515939", + "rel_title": "Precise identification of cell states altered indisease with healthy single-cell references", "rel_date": "2022-11-10", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.11.10.515993", - "rel_abs": "While mRNA vaccines have been effective in combating SARS-CoV-2, waning of vaccine-induced antibody responses and lack of vaccine-induced respiratory tract immunity contribute to ongoing infection and transmission. In this work, we compare and contrast intranasal (i.n.) and intramuscular (i.m.) administration of a SARS-CoV-2 self-amplifying RNA (saRNA) vaccine delivered by a nanostructured lipid carrier (NLC). Both i.m. and i.n. vaccines induce potent systemic serum neutralizing antibodies, bone marrow-resident IgG-secreting cells, and robust lymphoid tissue T cell immune responses. The i.n. vaccine additionally induces robust respiratory mucosal immune responses, including SARS-CoV-2-reactive lung-resident memory and lung-homing T cell populations. As a booster following previous i.m. vaccination, the i.n. vaccine also elicits the development of mucosal virus-specific T cells. Both the i.m. and i.n. administered vaccines protect hamsters from infection-associated morbidity upon viral challenge, significantly reducing viral loads and preventing challenged hamsters from transmitting virus to naive cagemates. This saRNA vaccines potent systemic immunogenicity, and additional mucosal immunogenicity when delivered i.n., may be key for combating SARS-CoV-2 and other respiratory pathogens.\n\nOne Sentence SummaryIntranasal SARS-CoV-2 saRNA vaccination induces systemic and mucosal immunity in mice, and prevents morbidity and blocks viral transmission in hamsters.", - "rel_num_authors": 21, + "rel_link": "https://biorxiv.org/cgi/content/short/2022.11.10.515939", + "rel_abs": "Single cell genomics is a powerful tool to distinguish altered cell states in disease tissue samples, through joint analysis with healthy reference datasets. Collections of data from healthy individuals are being integrated in cell atlases that provide a comprehensive view of cellular phenotypes in a tissue. However, it remains unclear whether atlas datasets are suitable references for disease-state identification, or whether matched control samples should be employed, to minimise false discoveries driven by biological and technical confounders. Here we quantitatively compare the use of atlas and control datasets as references for identification of disease-associated cell states, on simulations and real disease scRNA-seq datasets. We find that reliance on a single type of reference dataset introduces false positives. Conversely, using an atlas dataset as reference for latent space learning followed by differential analysis against a matched control dataset leads to precise identification of disease-associated cell states. We show that, when an atlas dataset is available, it is possible to reduce the number of control samples without increasing the rate of false discoveries. Using a cell atlas of blood cells from 12 studies to contextualise data from a case-control COVID-19 cohort, we sensitively detect cell states associated with infection, and distinguish heterogeneous pathological cell states associated with distinct clinical severities. Our analysis provides guiding principles for design of disease cohort studies and efficient use of cell atlases within the Human Cell Atlas.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Madeleine F. Jennewein", - "author_inst": "Access to Advanced Health Institute" - }, - { - "author_name": "Michael D. Schultz", - "author_inst": "University of Alabama at Birmingham" - }, - { - "author_name": "Samuel Beaver", - "author_inst": "Access to Advanced Health Institute" - }, - { - "author_name": "Peter Battisti", - "author_inst": "Access to Advanced Health Institute" - }, - { - "author_name": "Julie Bakken", - "author_inst": "Access to Advanced Health Institute" - }, - { - "author_name": "Derek Hanson", - "author_inst": "Access to Advanced Health Institute" - }, - { - "author_name": "Jobaida Akther", - "author_inst": "University of Alabama at Birmingham" - }, - { - "author_name": "Raodoh Mohamath", - "author_inst": "Access to Advanced Health Institute" - }, - { - "author_name": "Jasneet Singh", - "author_inst": "Access to Advanced Health Institute" - }, - { - "author_name": "Noah Cross", - "author_inst": "Access to Advanced Health Institute" - }, - { - "author_name": "Sierra Reed", - "author_inst": "Access to Advanced Health Institute" - }, - { - "author_name": "Davies Kalange", - "author_inst": "University of Alabama at Birmingham" - }, - { - "author_name": "Jeremy B. Foote", - "author_inst": "University of Alabama at Birmingham" - }, - { - "author_name": "R. Glenn King", - "author_inst": "University of Alabama at Birmingham" - }, - { - "author_name": "Aaron Silva-Sanchez", - "author_inst": "University of Alabama at Birmingham" - }, - { - "author_name": "Davide Botta", - "author_inst": "University of Alabama at Birmingham" - }, - { - "author_name": "Alana Gerhardt", - "author_inst": "Access to Advanced Health Institute" - }, - { - "author_name": "Corey Casper", - "author_inst": "Access to Advanced Health Institute" - }, - { - "author_name": "Troy D. Randall", - "author_inst": "University of Alabama at Birmingham" + "author_name": "Emma Dann", + "author_inst": "Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK" }, { - "author_name": "Frances E. Lund", - "author_inst": "University of Alabama at Birmingham" + "author_name": "Sarah Teichmann", + "author_inst": "Wellcome Trust Sanger Institute, Theory of Condensed Matter Group, The Cavendish Laboratory, University of Cambridge, Cambridge, UK" }, { - "author_name": "Emily A. Voigt", - "author_inst": "Access to Advanced Health Institute" + "author_name": "John Marioni", + "author_inst": "Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK, European Molecular Biology Laboratory - European Bioinformatics Institute" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nc", "type": "new results", - "category": "immunology" + "category": "genomics" }, { "rel_doi": "10.1101/2022.11.08.515589", @@ -166349,59 +166364,179 @@ "category": "health policy" }, { - "rel_doi": "10.1101/2022.11.03.22281898", - "rel_title": "Hospitalization forecast to inform COVID-19 pandemic planning and resource allocation using mathematical models", + "rel_doi": "10.1101/2022.11.03.22281912", + "rel_title": "Antibody response durability following three-dose COVID-19 vaccination in people with HIV receiving suppressive ART", "rel_date": "2022-11-05", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.11.03.22281898", - "rel_abs": "BackgroundThe COVID-19 pandemic has put tremendous pressure on hospital resources around the world. Forecasting demand for healthcare services is important generally, but crucial in epidemic contexts, both to facilitate resource planning and to inform situational awareness. There is abundant research on methods for predicting the spread of COVID-19 and even the arrival of COVID-19 patients to hospitals emergency departments. This study builds on that work to propose a hybrid tool, combining a stochastic Markov model and a discrete event simulation model to dynamically predict hospital admissions and total daily occupancy of hospital and ICU beds.\n\nMethodsThe model was developed and validated at San Juan de Alicante University Hospital from 10 July 2020 to 10 January 2022 and externally validated at Hospital Vega Baja. An admissions generator was developed using a stochastic Markov model that feeds a discrete event simulation model in R. Positive microbiological SARS-COV-2 results from the health departments catchment population were stratified by patient age to calculate the probabilities of hospital admission. Admitted patients follow distinct pathways through the hospital, which are simulated by the discrete event simulation model, allowing administrators to estimate the bed occupancy for the next week. The median absolute difference (MAD) between predicted and actual demand was used as a model performance measure.\n\nResultsWith respect to the San Juan hospital data, the admissions generator yielded a MAD of 6 admissions/week (interquartile range [IQR] 2-11). The MAD between the tools predictions and actual bed occupancy was 20 beds/day (IQR 5-43), or 5% of the hospital beds. The MAD between the intensive care unit (ICU)s predicted and actual occupancy was 4 beds/day (IQR 2-7), or 25% of the beds. When the model was further evaluated with data from Hospital Vega Baja, the admissions generator showed a MAD of 2.42 admissions/week (IQR 1.02-7.41). The MAD between the tools predictions and the actual bed occupancy was 18 beds/day (IQR 19.57-38.89), or 5.1% of the hospital beds. For ICU beds, the MAD was 3 beds/day (IQR 1-5), or 21.4% of the ICU beds.\n\nConclusionPredictions of hospital admissions, ward beds, and ICU occupancy for COVID-19 patients were very useful to hospital managers, allowing early planning of hospital resource allocation.", - "rel_num_authors": 10, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.11.03.22281912", + "rel_abs": "BackgroundLimited data exist regarding longer-term antibody responses following three-dose COVID-19 vaccination, and the impact of a first SARS-CoV-2 infection during this time, in people living with HIV (PLWH) receiving suppressive antiretroviral therapy (ART). We quantified wild-type-(WT), Omicron BA.1- and Omicron BA.5-specific responses up to six months post-third dose in 64 PLWH and 117 controls who remained COVID-19-naive or experienced their first SARS-CoV-2 infection during this time.\n\nDesignLongitudinal observational cohort.\n\nMethodsWe quantified WT- and Omicron-specific Anti-Spike receptor-binding domain IgG concentrations, ACE2 displacement activities and live virus neutralization at one, three and six months post-third vaccine dose.\n\nResultsThird doses boosted all antibody measures above two-dose levels, but BA.1-specific responses remained significantly lower than WT-specific ones, with BA.5-specific responses lower still. Serum IgG concentrations declined at similar rates in COVID-19-naive PLWH and controls post-third dose (median WT- and BA.1-specific half-lives were between 66-74 days for both groups). Antibody function also declined significantly yet comparably between groups: six months post-third dose, BA.1-specific neutralization was undetectable in >80% of COVID-19 naive PLWH and >90% of controls. Breakthrough SARS-CoV-2 infection boosted antibody concentrations and function significantly above vaccine-induced levels in both PLWH and controls, though BA.5-specific neutralization remained significantly poorer than BA.1 even post-breakthrough.\n\nConclusionsFollowing three-dose COVID-19 vaccination, antibody response durability in PLWH receiving ART is comparable to controls. PLWH also mounted strong responses to breakthrough infection. Due to temporal response declines however, COVID-19-naive individuals, regardless of HIV status, would benefit from a fourth dose within 6 months of their third.", + "rel_num_authors": 40, "rel_authors": [ { - "author_name": "Philip Erick Wikman-Jorgensen", - "author_inst": "Hospital Universitari Sant Joan d'Alacant" + "author_name": "Hope R. Lapointe", + "author_inst": "British Columbia Centre for Excellence in HIV/AIDS, Vancouver, Canada" + }, + { + "author_name": "Francis Mwimanzi", + "author_inst": "Faculty of Health Sciences, Simon Fraser University, Burnaby, Canada" + }, + { + "author_name": "Peter K. Cheung", + "author_inst": "British Columbia Centre for Excellence in HIV/AIDS, Vancouver, Canada; Faculty of Health Sciences, Simon Fraser University, Burnaby, Canada" + }, + { + "author_name": "Yurou Sang", + "author_inst": "Faculty of Health Sciences, Simon Fraser University, Burnaby, Canada" + }, + { + "author_name": "Fatima Yaseen", + "author_inst": "Department of Molecular Biology and Biochemistry, Simon Fraser University, Burnaby, Canada" + }, + { + "author_name": "Sarah Speckmaier", + "author_inst": "British Columbia Centre for Excellence in HIV/AIDS, Vancouver, Canada" + }, + { + "author_name": "Evan Barad", + "author_inst": "British Columbia Centre for Excellence in HIV/AIDS, Vancouver, Canada; Faculty of Health Sciences, Simon Fraser University, Burnaby, Canada" + }, + { + "author_name": "Nadia Moran-Garcia", + "author_inst": "British Columbia Centre for Excellence in HIV/AIDS, Vancouver, Canada" + }, + { + "author_name": "Sneha Datwani", + "author_inst": "Faculty of Health Sciences, Simon Fraser University, Burnaby, Canada" + }, + { + "author_name": "Maggie C. Duncan", + "author_inst": "British Columbia Centre for Excellence in HIV/AIDS, Vancouver, Canada; Faculty of Health Sciences, Simon Fraser University, Burnaby, Canada" + }, + { + "author_name": "Rebecca Kalikawe", + "author_inst": "Faculty of Health Sciences, Simon Fraser University, Burnaby, Canada" + }, + { + "author_name": "Siobhan Ennis", + "author_inst": "Faculty of Health Sciences, Simon Fraser University, Burnaby, Canada" + }, + { + "author_name": "Landon Young", + "author_inst": "Division of Medical Microbiology and Virology, St. Paul's Hospital, Vancouver, Canada" + }, + { + "author_name": "Bruce Ganase", + "author_inst": "AIDS Research Program, St. Paul's Hospital, Vancouver, Canada" + }, + { + "author_name": "F. Harrison Omondi", + "author_inst": "British Columbia Centre for Excellence in HIV/AIDS, Vancouver, Canada; Faculty of Health Sciences, Simon Fraser University, Burnaby, Canada" + }, + { + "author_name": "Gisele Umviligihozo", + "author_inst": "Faculty of Health Sciences, Simon Fraser University, Burnaby, Canada" + }, + { + "author_name": "Winnie Dong", + "author_inst": "British Columbia Centre for Excellence in HIV/AIDS, Vancouver, Canada" + }, + { + "author_name": "Junine Toy", + "author_inst": "British Columbia Centre for Excellence in HIV/AIDS, Vancouver, Canada" + }, + { + "author_name": "Paul Sereda", + "author_inst": "British Columbia Centre for Excellence in HIV/AIDS, Vancouver, Canada" + }, + { + "author_name": "Laura Burns", + "author_inst": "Department of Pathology and Laboratory Medicine, Providence Health Care, Vancouver, Canada" + }, + { + "author_name": "Cecilia T. Costiniuk", + "author_inst": "Division of Infectious Diseases and Chronic Viral Illness Service, McGill University Health Centre and Research Institute of the McGill University Health Centre" + }, + { + "author_name": "Curtis Cooper", + "author_inst": "Department of Medicine, University of Ottawa, Ottawa, Canada; Ottawa Hospital Research Institute, Ottawa, Canada" + }, + { + "author_name": "Aslam H. Anis", + "author_inst": "School of Population and Public Health, University of British Columbia, Vancouver, Canada; CIHR Canadian HIV Trials Network, University of British Columbia, Van" + }, + { + "author_name": "Victor Leung", + "author_inst": "Division of Medical Microbiology and Virology, St. Paul's Hospital, Vancouver, Canada; Department of Pathology and Laboratory Medicine, Providence Health Care, " + }, + { + "author_name": "Daniel T. Holmes", + "author_inst": "Department of Pathology and Laboratory Medicine, Providence Health Care, Vancouver, Canada; Department of Pathology and Laboratory Medicine, University of Briti" + }, + { + "author_name": "Mari L. DeMarco", + "author_inst": "Department of Pathology and Laboratory Medicine, Providence Health Care, Vancouver, Canada; Department of Pathology and Laboratory Medicine, University of Briti" + }, + { + "author_name": "Janet Simons", + "author_inst": "Department of Pathology and Laboratory Medicine, Providence Health Care, Vancouver, Canada; Department of Pathology and Laboratory Medicine, University of Briti" + }, + { + "author_name": "Malcolm Hedgcock", + "author_inst": "Spectrum Health, Vancouver, Canada" + }, + { + "author_name": "Natalie Prystajecky", + "author_inst": "Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, Canada; British Columbia Centre for Disease Control Public Health La" + }, + { + "author_name": "Christopher F. Lowe", + "author_inst": "Division of Medical Microbiology and Virology, St. Paul's Hospital, Vancouver, Canada; Department of Pathology and Laboratory Medicine, Providence Health Care, " }, { - "author_name": "Angel Ruiz", - "author_inst": "Laval University: Universite Laval" + "author_name": "Marc G. Romney", + "author_inst": "Division of Medical Microbiology and Virology, St. Paul's Hospital, Vancouver, Canada; Department of Pathology and Laboratory Medicine, Providence Health Care, " }, { - "author_name": "Vicente Giner-Galva\u00f1", - "author_inst": "Hospital Universitari Sant Joan d'Alacant" + "author_name": "Rolando Barrios", + "author_inst": "British Columbia Centre for Excellence in HIV/AIDS, Vancouver, Canada; 0 School of Population and Public Health, University of British Columbia, Vancouver, Cana" }, { - "author_name": "Jara Llenas-Garc\u00eda", - "author_inst": "Hospital Vega Baja" + "author_name": "Silvia Guillemi", + "author_inst": "British Columbia Centre for Excellence in HIV/AIDS, Vancouver, Canada; Department of Family Practice, Faculty of Medicine, University of British Columbia, Cana" }, { - "author_name": "Jos\u00e9 Miguel Segu\u00ed-Ripoll", - "author_inst": "Hospital Universitari Sant Joan d'Alacant" + "author_name": "Chanson J. Brumme", + "author_inst": "British Columbia Centre for Excellence in HIV/AIDS, Vancouver, Canada; Department of Medicine, University of British Columbia, Vancouver, Canada" }, { - "author_name": "Jose Mar\u00eda Salinas Serrano", - "author_inst": "Hospital Universitari Sant Joan d'Alacant" + "author_name": "Julio S.G. Montaner", + "author_inst": "British Columbia Centre for Excellence in HIV/AIDS, Vancouver, Canada; Department of Medicine, University of British Columbia, Vancouver, Canada" + }, + { + "author_name": "Mark Hull", + "author_inst": "British Columbia Centre for Excellence in HIV/AIDS, Vancouver, Canada; Department of Medicine, University of British Columbia, Vancouver, Canada" }, { - "author_name": "Emilio Borrajo", - "author_inst": "Hospital Vega Baja" + "author_name": "Marianne Harris", + "author_inst": "British Columbia Centre for Excellence in HIV/AIDS, Vancouver, Canada; Department of Family Practice, Faculty of Medicine, University of British Columbia, Canad" }, { - "author_name": "Jos\u00e9 Mar\u00eda Ibarra S\u00e1nchez", - "author_inst": "Hospital Vega Baja" + "author_name": "Masahiro Niikura", + "author_inst": "Faculty of Health Sciences, Simon Fraser University, Burnaby, Canada" }, { - "author_name": "Jos\u00e9 Pedro Garc\u00eda-Sabater", - "author_inst": "Universitat Polit\u00e8cnica de Val\u00e8ncia: Universitat Politecnica de Valencia" + "author_name": "Mark A. Brockman", + "author_inst": "Department of Molecular Biology and Biochemistry, Simon Fraser University, Burnaby, Canada; Faculty of Health Sciences, Simon Fraser University, Burnaby, Canada" }, { - "author_name": "Juan A Mar\u00edn-Garc\u00eda", - "author_inst": "Universitat Polit\u00e8cnica de Val\u00e8ncia: Universitat Politecnica de Valencia" + "author_name": "Zabrina L. Brumme", + "author_inst": "British Columbia Centre for Excellence in HIV/AIDS, Vancouver, Canada; Faculty of Health Sciences, Simon Fraser University, Burnaby, Canada" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "health systems and quality improvement" + "category": "hiv aids" }, { "rel_doi": "10.1101/2022.11.03.22281916", @@ -167963,31 +168098,23 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2022.10.31.514572", - "rel_title": "Improving the preclinical and clinical success rates of LMW drugs depends on radical revisions to the status quo scientific foundations of medicinal chemistry: a case study on COVID Mpro inhibition", + "rel_doi": "10.1101/2022.11.01.514696", + "rel_title": "Education in the Time of COVID-19: The Improvised Experiment of Virtual Assessments", "rel_date": "2022-11-02", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.10.31.514572", - "rel_abs": "The poor preclinical and clinical success rates of low molecular weight (LMW) compounds can be partially attributed to the inherent trial-and-error nature of pharmaceutical research, which is limited largely to retrospective data-driven, rather than prospective prediction-driven human relevant workflows stemming from: 1) inadequate scientific understanding of structure-activity, structure-property, and structure-free energy relationships; 2) disconnects between empirical models derived from in vitro equilibrium data (e.g., Hill and Michaelis-Menten models) vis-a-vis the native non-equilibrium cellular setting (where the pertinent metrics consist of rates, rather than equilibrium state distributions); and 3) inadequate understanding of the non-linear dynamic (NLD) basis of cellular function and disease. We argue that the limit of understanding of cellular function/dysfunction and pharmacology based on empirical principles (observation/inference) has been reached, and that further progress depends on understanding these phenomena at the first principles theoretical level. Toward that end, we have been developing and applying a theory (called \"Biodynamics\") on the general mechanisms by which: 1) cellular functions are conveyed by dynamic multi-molecular/-ionic (multi-flux) systems operating in the NLD regime; 2) cellular dysfunction results from molecular dysfunction; 3) molecular structure and function are powered by covalent/non-covalent forms of free energy; and 4) cellular dysfunction is corrected pharmacologically. Biodynamics represents a radical departure from the status quo empirical science and reduction to practice thereof, replacing: 1) the interatomic contact model of structure-free energy and structure-property relationships with a solvation free energy model; 2) equilibrium drug-target occupancy models with dynamic models accounting for time-dependent drug and target/off-target binding site buildup and decay; and 3) linear models of molecular structure-function and multi-molecular/-ionic systems conveying cellular function and dysfunction with NLD models that more realistically capture the emergent non-linear behaviors of such systems. Here, we apply our theory to COVID Mpro inhibition and overview its implications for a holistic, in vivo relevant approach to drug design.", - "rel_num_authors": 3, + "rel_link": "https://biorxiv.org/cgi/content/short/2022.11.01.514696", + "rel_abs": "One of the aspects in which the COVID-19 pandemic impacted the most was education. Teachers and students had to face a new reality for which they were not prepared adapting in an improvised way new methods and strategies to teach and to learn. Within virtual education, exams reduced in some cases to multiple choice tests while others tried to mimic traditional (pen and paper) exams. In this paper, these two kind of evaluations are compared. Although the results appear to be similar, a deeper look shows that their structure is completely different and some groups of students are unfairly harmed or benefited depending on the assessment applied. Beyond analyzing the reasons of this discrepancy, it is determined that for some type of evaluation, at least 21.1% of students maybe passing a course irregularly meanwhile, at least 5.5% could be failing a course despite their actual capabilities.", + "rel_num_authors": 1, "rel_authors": [ { - "author_name": "Robert Alan Pearlstein", - "author_inst": "Novartis Institutes for BioMedical Research" - }, - { - "author_name": "Hongbin Wan", - "author_inst": "Novartis Institutes for BioMedical Research Inc" - }, - { - "author_name": "Sarah Williams", - "author_inst": "Novartis Institutes for BioMedical Research" + "author_name": "Esteban Guevara Hidalgo", + "author_inst": "Escuela Politecnica Nacional" } ], "version": "1", - "license": "cc_no", + "license": "cc_by", "type": "new results", - "category": "pharmacology and toxicology" + "category": "scientific communication and education" }, { "rel_doi": "10.1101/2022.10.31.22281756", @@ -169288,41 +169415,77 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.10.28.22281646", - "rel_title": "Machine learning models for predicting severe COVID-19 outcomes in hospitals", + "rel_doi": "10.1101/2022.10.27.22281603", + "rel_title": "Preliminary report: Safety and immunogenicity of an inactivated SARS-CoV-2 vaccine, KD-414, in healthy adult participants: a non-randomized, open-label phase 2/3 clinical study in Japan", "rel_date": "2022-10-30", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.10.28.22281646", - "rel_abs": "The aim of this observational retrospective study is to improve early risk stratification of hospitalized Covid-19 patients by predicting in-hospital mortality, transfer to intensive care unit (ICU) and mechanical ventilation from electronic health record data of the first 24 hours after admission. Our machine learning model predicts in-hospital mortality (AUC=0.918), transfer to ICU (AUC=0.821) and the need for mechanical ventilation (AUC=0.654) from a few laboratory data of the first 24 hours after admission. Models based on dichotomous features indicating whether a laboratory value exceeds or falls below a threshold perform nearly as good as models based on numerical features. We devise completely data-driven and interpretable machine-learning models for the prediction of in-hospital mortality, transfer to ICU and mechanical ventilation for hospitalized Covid-19 patients within 24 hours after admission. Numerical values of CRP and blood sugar and dichotomous indicators for increased partial thromboplastin time (PTT) and glutamic oxaloacetic transaminase (GOT) are amongst the best predictors.", - "rel_num_authors": 7, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.10.27.22281603", + "rel_abs": "BackgroundIn the prolonged COVID-19 pandemic, there remains a high need for the development of a severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccine that can be used more safely and effectively to prevents the disease onset or severe disease. To satisfy such unmet need, we are currently developing the inactivated whole particle SARS-CoV-2 vaccine (KD-414) and conducted a phase 2/3 study in healthy adults in Japan to accumulate more immunogenicity and safety data of KD-414 using the dose selected based on the results of the phase 1/2 study.\n\nMethodsIn an open-label uncontrolled phase 2/3 study, adults aged 18 years or older without a history of COVID-19 or COVID-19 vaccination received two intramuscular doses of KD-414 at a 28-day intervals, followed by one intramuscular dose 13 weeks after the second dose as the primary immunization. Safety data were collected after the first dose of KD-414 in all participants to evaluate the safety profile. In predetermined immunogenicity analysis subjects, the neutralizing antibody titers against the pseudovirus SARS-CoV-2 (Wuhan) before the first vaccination and after each vaccination with KD-414 were evaluated.\n\nResultsA total of 2500 adults aged 18 years or older were enrolled; 2474 of them received the vaccination up to the second dose, and 2081 completed the third vaccination. Regarding the safety, no deaths or serious adverse reactions were recorded from the first vaccination until 28 days after the third vaccination with KD-414. The incidence of adverse reactions (number of participants with onsets/number of participants in the safety analysis set) was 80.6% (2015/2500). Adverse reactions with an incidence of 10% or more included injection site pain, malaise, headache, injection site erythema, myalgia, and injection site induration. A total of 11 events of grade 3 or higher adverse reactions that prevented daily activities in 9 participants. There was no increasing tendency in the incidence of adverse reactions responding to the vaccinations. To evaluate immunogenicity, 295 first comers enrolled from five age ranges were allocated to the immunogenicity analysis subjects; 291 participants received the vaccination up to the second dose, and 249 participants completed the third vaccination. The geometric mean titers (95% confidence interval [CI]) of neutralizing antibody titers against pseudovirus SARS-CoV-2 (Wuhan) 28 days after the second vaccination and 28 days after the third vaccination with KD-414 were 139.6 (118.9 - 164.0) and 285.6 (244.3 - 334.0), respectively, showing an approximately two-fold increase after the third vaccination compared to that after the second vaccination. The geometric mean titers (95% CI) of neutralizing antibody titers after the third vaccination were 327.6 (269.8 - 397.9), 272.2 (211.5 - 350.4) and 128.0 (51.6 - 317.7) in participants aged 18 to 40 years, 41 to 64 years, and 65 years or older, respectively, showing an age-dependency.\n\nConclusionThis study confirmed the favorable safety profile of KD-414 as a result of three vaccinations of KD-414 administered to over 2000 healthy Japanese participants aged 18 years or older. There were no particular differences in the types and incidences of adverse reactions between vaccinations, and no tendency of an increase in adverse reactions with an increase in the number of vaccinations. Similar to the phase 1/2 study, neutralizing antibody responses appeared to be age-dependent and the highest titers were observed in the age group of 18 - 40 years. A phase 3 study in adults aged 18 - 40 years (jRCT2031210679) and a phase 2/3 study in children aged 6 months - 18 years (jRCT2031220032) are currently ongoing.", + "rel_num_authors": 16, "rel_authors": [ { - "author_name": "Philipp Wendland", - "author_inst": "University of Applied Sciences Koblenz, Department of Mathematics and Technology" + "author_name": "Keishi Kido", + "author_inst": "KM Biologics Co., Ltd. (KM Biologics), Kumamoto, Japan" }, { - "author_name": "Vanessa Schmitt", - "author_inst": "University of Applied Sciences Koblenz, Department of Mathematics and Technology" + "author_name": "Kayo Ibaragi", + "author_inst": "KM Biologics Co., Ltd. (KM Biologics), Kumamoto, Japan" }, { - "author_name": "Joerg Zimmermann", - "author_inst": "University of Applied Sciences Koblenz, Department of Mathematics and Technology" + "author_name": "Mitsuyoshi Tanishima", + "author_inst": "KM Biologics Co., Ltd. (KM Biologics), Kumamoto, Japan" }, { - "author_name": "Lukas Haeger", - "author_inst": "University Clinic Tuebingen, Department of Internal Medicine" + "author_name": "Yosuke Muramoto", + "author_inst": "KM Biologics Co., Ltd. (KM Biologics), Kumamoto, Japan" }, { - "author_name": "Siri Goepel", - "author_inst": "University Clinic Tuebingen, Department of Internal Medicine" + "author_name": "Shun Nakayama", + "author_inst": "KM Biologics Co., Ltd. (KM Biologics), Kumamoto, Japan" }, { - "author_name": "Christof Schenkel-Haeger", - "author_inst": "University of Applied Sciences Koblenz, Department of Economics and Social Care" + "author_name": "Kohei Ata", + "author_inst": "KM Biologics Co., Ltd. (KM Biologics), Kumamoto, Japan" + }, + { + "author_name": "Kenshi Hayashida", + "author_inst": "KM Biologics Co., Ltd. (KM Biologics), Kumamoto, Japan" + }, + { + "author_name": "Hideki Nakamura", + "author_inst": "KM Biologics Co., Ltd. (KM Biologics), Kumamoto, Japan" + }, + { + "author_name": "Yasuhiko Shinmura", + "author_inst": "KM Biologics Co., Ltd. (KM Biologics), Kumamoto, Japan" + }, + { + "author_name": "Yoshiaki Oda", + "author_inst": "KM Biologics Co., Ltd. (KM Biologics), Kumamoto, Japan" }, { - "author_name": "Maik Kschischo", - "author_inst": "University of Applied Sciences Koblenz, Department of Mathematics and Technology" + "author_name": "Masafumi Endo", + "author_inst": "KM Biologics Co., Ltd. (KM Biologics), Kumamoto, Japan" + }, + { + "author_name": "Kengo Sonoda", + "author_inst": "KM Biologics Co., Ltd. (KM Biologics), Kumamoto, Japan" + }, + { + "author_name": "Yuji Sasagawa", + "author_inst": "Meiji Seika Pharma Co., Ltd., Tokyo, Japan" + }, + { + "author_name": "Yasuhiro Iwama", + "author_inst": "Meiji Seika Pharma Co., Ltd., Tokyo, Japan" + }, + { + "author_name": "Kohji Ueda", + "author_inst": "Professor emeritus, Kyushu University, Fukuoka, Japan" + }, + { + "author_name": "Takayuki Matsumoto", + "author_inst": "KM Biologics Co., Ltd. (KM Biologics), Kumamoto, Japan" } ], "version": "1", @@ -171794,75 +171957,39 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2022.10.24.22281485", - "rel_title": "Epigenetic and transcriptomic reprogramming in monocytes of severe COVID-19 patients reflects alterations in myeloid differentiation and the influence of inflammatory cytokines", + "rel_doi": "10.1101/2022.10.24.22281450", + "rel_title": "Impact of COVID-19 on the national development of countries: implications for the public health", "rel_date": "2022-10-26", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.10.24.22281485", - "rel_abs": "COVID-19 manifests with a wide spectrum of clinical phenotypes, ranging from asymptomatic and mild to severe and critical. Severe and critical COVID-19 patients are characterized by marked changes in the myeloid compartment, especially monocytes. However, little is known about the epigenetic alterations that occur in these cells during hyperinflammatory responses in severe COVID-19 patients. In this study, we obtained the DNA methylome and transcriptome of peripheral blood monocytes from severe COVID-19 patients. DNA samples extracted from CD14+CD15-monocytes of 48 severe COVID-19 patients and 11 healthy controls were hybridized on MethylationEPIC BeadChip arrays. In parallel, single-cell transcriptomics of 10 severe COVID-19 patients were generated. CellPhoneDB was used to infer changes in the crosstalk between monocytes and other immune cell types. We observed DNA methylation changes in CpG sites associated with interferon-related genes and genes associated with antigen presentation, concordant with gene expression changes. These changes significantly overlapped with those occurring in bacterial sepsis, although specific DNA methylation alterations in genes specific to viral infection were also identified. We also found these alterations to comprise some of the DNA methylation changes occurring during myeloid differentiation and under the influence of inflammatory cytokines. A progression of DNA methylation alterations in relation to the Sequential Organ Failure Assessment (SOFA) score was found to be related to interferon-related genes and T-helper 1 cell cytokine production. CellPhoneDB analysis of the single-cell transcriptomes of other immune cell types suggested the existence of altered crosstalk between monocytes and other cell types like NK cells and regulatory T cells. Our findings show the occurrence of an epigenetic and transcriptional reprogramming of peripheral blood monocytes, which could be associated with the release of aberrant immature monocytes, increased systemic levels of pro-inflammatory cytokines, and changes in immune cell crosstalk in these patients.", - "rel_num_authors": 14, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.10.24.22281450", + "rel_abs": "The article focuses on measuring the fluctuations in countries development as a result of the COVID-19 pandemic. The obtained measures make it possible to predict the extent of the impact of risks to public health on the economy, financial-budgetary, political-institutional development of states in the future, as well as the social determinants of public health. This assessment represents a new paradigm that makes it possible to effectively evaluate the manifestations of the consequences of COVID-19 and to identify the relevant determinants of the lack of resilience of the medical and social security systems to the coronavirus pandemic around the world. We picked the determinant of national development indicators of the 59 countries in order to measure the fluctuations in their economic development. In addition, we applied the binary response model for identifying the economic, financial-budgetary, and political-institutional development change with the happiness index of the countries being the dependent variable. The analysis of our empirical model made it possible for us to conclude that economic and financial-budgetary components have significantly increased the influence on well-being during the COVID-19 pandemic. In contrast, we observed the decrease in the impact of political and institutional indicators during the same period.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Gerard Godoy-Tena", - "author_inst": "Josep Carreras Research Institute (IJC)" - }, - { - "author_name": "Anis Barmada", - "author_inst": "Wellcome Sanger Institute" - }, - { - "author_name": "Octavio Morante-Palacios", - "author_inst": "Josep Carreras Research Institute (IJC)" - }, - { - "author_name": "Carlos de la Calle-Fabregat", - "author_inst": "Josep Carreras Research Institute (IJC)" - }, - { - "author_name": "Ricardo Martins-Ferreira", - "author_inst": "Josep Carreras Research Institute (IJC)" - }, - { - "author_name": "Anna G Ferrete-Bonastre", - "author_inst": "Josep Carreras Research Institute (IJC)" + "author_name": "Olha Kuzmenko", + "author_inst": "Sums'kij derzhavnij universitet" }, { - "author_name": "Laura Ciudad", - "author_inst": "Josep Carreras Resaerch Institute (IJC)" + "author_name": "Serhiy Lyeonov", + "author_inst": "Sums'kij derzhavnij universitet" }, { - "author_name": "Adolfo Ruiz-Sanmartin", - "author_inst": "Hospital Vall d'Hebron" + "author_name": "Nataliia Letunovska", + "author_inst": "Sums'kij derzhavnij universitet" }, { - "author_name": "Monica Martinez-Gallo", - "author_inst": "Hospital Vall d'Hebron" + "author_name": "Mariya Kashcha", + "author_inst": "Sums'kij derzhavnij universitet" }, { - "author_name": "Ricard Ferrer", - "author_inst": "Hospital Vall d'Hebron" - }, - { - "author_name": "Juan C Ruiz-Rodriguez", - "author_inst": "Hospital Vall d'Hebron" - }, - { - "author_name": "Javier Rodriguez-Ubreva", - "author_inst": "Josep Carreras Research Institute (IJC)" - }, - { - "author_name": "Roser Vento-Tormo", - "author_inst": "Wellcome Sanger Institute" - }, - { - "author_name": "Esteban Ballestar", - "author_inst": "Josep Carreras Research Institute (IJC)" + "author_name": "Wadm Strielkowski", + "author_inst": "Czech University of Life Sciences Prague: Ceska Zemedelska Univerzita v Praze" } ], "version": "1", - "license": "cc_no", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "genetic and genomic medicine" + "category": "health economics" }, { "rel_doi": "10.1101/2022.10.24.22281436", @@ -174152,23 +174279,63 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.10.21.22281382", - "rel_title": "Abnormal renal function tests at presentation in severe COVID 19 pneumonia and its effect on clinical outcomes", + "rel_doi": "10.1101/2022.10.21.22281343", + "rel_title": "Receipt of COVID-19 and seasonal influenza vaccines in California (USA) during the 2021-2022 influenza season", "rel_date": "2022-10-22", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.10.21.22281382", - "rel_abs": "AimTo determine the incidence of abnormal renal function tests at presentation in South Asian patients admitted with severe COVID 19 pneumonia and determine its effect on disease severity and clinical outcomes\n\nMethodsThis was a retrospective cross-sectional study conducted at the COVID Intensive care unit of a large tertiary care government hospital in Karachi, Pakistan. 190 patients admitted over five months from 1/5/2021 till 30/6/2021 were included in the study. Patient demographic characteristics, comorbidities, and clinical manifestations of COVID 19 infection were recorded. Laboratory values at the time of presentation, including Hemoglobin, NLR, platelets, blood urea nitrogen, glomerular filtration rate (GFR), inflammatory markers, liver function tests, and electrolytes were recorded. Patient outcome and need for mechanical ventilation were assessed 28 days after admission and compared with the incidence of abnormal renal functions at presentation.\n\nResultsMean GFR and BUN at presentation were 69.7 and 28.4 respectively. 109 (50.4%) patients had abnormal renal function tests at the time of presentation. 76 (40.0%) patients had low GFR and 33 (17.4%) had only raised BUN with normal GFR. Mean GFR was lower in non-survivors vs survivors (p-value 0.000) and in patients who required mechanical ventilation (p-value 0.008). Patients who had low GFR showed greater mortality than those with normal GFR (p-value 0.04) and were more likely to require mechanical ventilation (p-value 0.04).\n\nConclusionLow GFR at presentation is common in patients with severe COVID 19 pneumonia and is associated with a higher in-hospital mortality rate and need for mechanical ventilation.", - "rel_num_authors": 1, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.10.21.22281343", + "rel_abs": "BackgroundDespite lower circulation of influenza virus throughout 2020-2022 during the COVID-19 pandemic, seasonal influenza vaccination has remained a primary tool to reduce influenza-associated illness and death. The relationship between the decision to receive a COVID-19 vaccine and/or an influenza vaccine is not well understood.\n\nMethodsWe assessed predictors of receipt of 2021-2022 influenza vaccine in a secondary analysis of data from a case-control study enrolling individuals who received SARS-CoV-2 testing. We used mixed effects logistic regression to estimate factors associated with receipt of seasonal influenza vaccine. We also constructed multinomial adjusted marginal probability models of being vaccinated for COVID-19 only, seasonal influenza only, or both as compared with receipt of neither vaccination.\n\nResultsAmong 1261 eligible participants recruited between 22 October 2021 - 22 June 2022, 43% (545) were vaccinated with both seasonal influenza vaccine and [≥]1 dose of a COVID-19 vaccine, 34% (426) received [≥]1 dose of a COVID-19 vaccine only, 4% (49) received seasonal influenza vaccine only, and 19% (241) received neither vaccine. Receipt of [≥]1 COVID-19 vaccine dose was associated with seasonal influenza vaccination (adjusted odds ratio [aOR]: 3.72; 95% confidence interval [CI]: 2.15-6.43); this association was stronger among participants receiving [≥]1 COVID-19 booster dose (aOR=16.50 [10.10- 26.97]). Compared with participants testing negative for SARS-CoV-2 infection, participants testing positive had lower odds of receipt of 2021-2022 seasonal influenza vaccine (aOR=0.64 [0.50-0.82]).\n\nConclusionsRecipients of a COVID-19 vaccine were more likely to receive seasonal influenza vaccine during the 2021-2022 season. Factors associated with individuals likelihood of receiving COVID-19 and seasonal influenza vaccines will be important to account for in future studies of vaccine effectiveness against both conditions. Participants who tested positive for SARS-CoV-2 in our sample were less likely to have received seasonal influenza vaccine, suggesting an opportunity to offer influenza vaccination before or after a COVID-19 diagnosis.", + "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Naveed Iqbal", - "author_inst": "Benazir Bhutto Hospital" + "author_name": "Kristin Andrejko", + "author_inst": "University of California at Berkeley" + }, + { + "author_name": "Jennifer F Myers", + "author_inst": "California Department of Public Health" + }, + { + "author_name": "John Openshaw", + "author_inst": "California Department of Public Health" + }, + { + "author_name": "Nozomi Fukui", + "author_inst": "California Department of Public Health" + }, + { + "author_name": "Sophia Li", + "author_inst": "California Department of Public Health" + }, + { + "author_name": "James P Watt", + "author_inst": "California Department of Public Health" + }, + { + "author_name": "Erin L Murray", + "author_inst": "California Department of Public Health" + }, + { + "author_name": "Cora Hoover", + "author_inst": "California Department of Public Health" + }, + { + "author_name": "Joseph Lewnard", + "author_inst": "University of California Berkeley" + }, + { + "author_name": "Seema Jain", + "author_inst": "California Department of Public Health" + }, + { + "author_name": "Jake M Pry", + "author_inst": "University of California" } ], "version": "1", - "license": "cc_by", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2022.10.21.22281356", @@ -175994,23 +176161,31 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2022.10.20.513136", - "rel_title": "Diversity, composition, and networking of saliva microbiota distinguish the severity of COVID-19 episodes as revealed by an analysis of 16S rRNA variable V1-V3 regions sequences", - "rel_date": "2022-10-21", + "rel_doi": "10.1101/2022.10.18.512756", + "rel_title": "Endonuclease fingerprint indicates a synthetic origin of SARS-CoV-2", + "rel_date": "2022-10-20", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.10.20.513136", - "rel_abs": "BackgroundStudies on the role of the oral microbiome in SARS-CoV-2 infection and severity of the disease are limited. We aimed to characterize the bacterial communities present in the saliva of patients with varied COVID-19 severity to learn if there are differences in the characteristics of the microbiome among the clinical groups.\n\nMethodsWe included asymptomatic subjects with no previous COVID-19 infection or vaccination; patients with mild respiratory symptoms, positive or negative for SARS-CoV-2 infection; patients that required hospitalization because of severe COVID-19 with oxygen saturation below 92%, and fatal cases of COVID-19. Saliva samples collected before any treatment were tested for SARS-CoV-2 by PCR. Oral microbiota in saliva was studied by amplification and sequencing of the V1-V3 variable regions of 16S gene using a Illumina MiSeq platform.\n\nResultsWe found significant changes in diversity, composition, and networking in saliva microbiota of patients with COVID-19, as well as patterns associated with severity of disease. The presence or abundance of several commensal species and opportunistic pathogens were associated with each clinical stage. Patterns of networking were also found associated with severity of disease: a highly regulated bacterial community (normonetting) was found in healthy people whereas poorly regulated populations (disnetting) were characteristic of severe cases.\n\nConclusionsCharacterization of microbiota in saliva may offer important clues in the pathogenesis of COVID-19 and may also identify potential markers for prognosis in the severity of the disease.\n\nImportance of the workSARS-CoV-2 infection is the most severe pandemic of humankind in the last hundred years. The outcome of the infection ranges from asymptomatic or mild to severe and even fatal cases, but reasons for this remain unknown. Microbes normally colonizing the respiratory tract form communities that may mitigate the transmission, symptoms, and severity of viral infections, but very little is known on the role of these microbial communities in the severity of COVID-19. We aimed to characterize the bacterial communities in saliva of patients with different severity of COVID-19 disease, from mild to fatal cases. Our results revealed clear differences in the composition and in the nature of interactions (networking) of the bacterial species present in the different clinical groups and show community-patterns associated with disease severity. Characterization of the microbial communities in saliva may offer important clues to learn ways COVID-19 patients may suffer from different disease severities.", - "rel_num_authors": 1, + "rel_link": "https://biorxiv.org/cgi/content/short/2022.10.18.512756", + "rel_abs": "To prevent future pandemics, it is important that we understand whether SARS-CoV-2 spilled over directly from animals to people, or indirectly in a laboratory accident. The genome of SARS-COV-2 contains a peculiar pattern of unique restriction endonuclease recognition sites allowing efficient dis- and re-assembly of the viral genome characteristic of synthetic viruses. Here, we report the likelihood of observing such a pattern in coronaviruses with no history of bioengineering. We find that SARS-CoV-2 is an anomaly, more likely a product of synthetic genome assembly than natural evolution. The restriction map of SARS-CoV-2 is consistent with many previously reported synthetic coronavirus genomes, meets all the criteria required for an efficient reverse genetic system, differs from closest relatives by a significantly higher rate of synonymous mutations in these synthetic-looking recognitions sites, and has a synthetic fingerprint unlikely to have evolved from its close relatives. We report a high likelihood that SARS-CoV-2 may have originated as an infectious clone assembled in vitro.\n\nLay SummaryTo construct synthetic variants of natural coronaviruses in the lab, researchers often use a method called in vitro genome assembly. This method utilizes special enzymes called restriction enzymes to generate DNA building blocks that then can be \"stitched\" together in the correct order of the viral genome. To make a virus in the lab, researchers usually engineer the viral genome to add and remove stitching sites, called restriction sites. The ways researchers modify these sites can serve as fingerprints of in vitro genome assembly.\n\nWe found that SARS-CoV has the restriction site fingerprint that is typical for synthetic viruses. The synthetic fingerprint of SARS-CoV-2 is anomalous in wild coronaviruses, and common in lab-assembled viruses. The type of mutations (synonymous or silent mutations) that differentiate the restriction sites in SARS-CoV-2 are characteristic of engineering, and the concentration of these silent mutations in the restriction sites is extremely unlikely to have arisen by random evolution. Both the restriction site fingerprint and the pattern of mutations generating them are extremely unlikely in wild coronaviruses and nearly universal in synthetic viruses. Our findings strongly suggest a synthetic origin of SARS-CoV2.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Javier Torres", - "author_inst": "Instituto Mexicano del Seguro Social" + "author_name": "Valentin Bruttel", + "author_inst": "University Clinics of Wurzburg" + }, + { + "author_name": "Alex Washburne", + "author_inst": "Selva Analytics LLC" + }, + { + "author_name": "Antonius VanDongen", + "author_inst": "Duke University" } ], "version": "1", "license": "cc_by_nc_nd", "type": "new results", - "category": "microbiology" + "category": "bioengineering" }, { "rel_doi": "10.1101/2022.10.19.512884", @@ -178132,39 +178307,47 @@ "category": "bioinformatics" }, { - "rel_doi": "10.1101/2022.10.17.512617", - "rel_title": "Infection of primary nasal epithelial cells differentiates among lethal and seasonal human coronaviruses", - "rel_date": "2022-10-18", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.10.17.512617", - "rel_abs": "The nasal epithelium is the initial entry portal and primary barrier to infection by all human coronaviruses (HCoVs). We utilize primary nasal epithelial cells grown at air-liquid interface, which recapitulate the heterogeneous cellular population as well as mucociliary clearance functions of the in vivo nasal epithelium, to compare lethal (SARS-CoV-2 and MERS-CoV) and seasonal (HCoV-NL63 and HCoV-229E) HCoVs. All four HCoVs replicate productively in nasal cultures but diverge significantly in terms of cytotoxicity induced following infection, as the seasonal HCoVs as well as SARS-CoV-2 cause cellular cytotoxicity as well as epithelial barrier disruption, while MERS-CoV does not. Treatment of nasal cultures with type 2 cytokine IL-13 to mimic asthmatic airways differentially impacts HCoV replication, enhancing MERS-CoV replication but reducing that of SARS-CoV-2 and HCoV-NL63. This study highlights diversity among HCoVs during infection of the nasal epithelium, which is likely to influence downstream infection outcomes such as disease severity and transmissibility.", - "rel_num_authors": 5, + "rel_doi": "10.1101/2022.10.13.22281012", + "rel_title": "COVID-19 Vaccine Effectiveness against SARS-CoV-2 Infections with the Delta Variant among Ages >=12 Years in Utah", + "rel_date": "2022-10-17", + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2022.10.13.22281012", + "rel_abs": "We conducted weekly surveillance for SARS-CoV-2 infection among a sample of households with [≥]1 child aged 0-17 years from selected Utah counties. A Cox proportional hazards model approach was used to calculate infection hazard rate and vaccine effectiveness. Findings show that the recommended primary series of COVID-19 vaccine was effective against circulating variants during a Delta-predominant wave in Utah.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Clayton Otter", - "author_inst": "University of Pennsylvania" + "author_name": "Sarita Mohanty", + "author_inst": "CDC" }, { - "author_name": "Alejandra Fausto", - "author_inst": "University of Pennsylvania" + "author_name": "Fatimah S. Dawood", + "author_inst": "Centers for Disease Control and Prevention" }, { - "author_name": "Li Hui Tan", - "author_inst": "University of Pennsylvania" + "author_name": "Joseph B. Stanford", + "author_inst": "University of Utah School of Medicine" }, { - "author_name": "Noam A Cohen", - "author_inst": "Uniersity of Pennsylvania" + "author_name": "Duque Jazmin", + "author_inst": "Abt Associates" }, { - "author_name": "Susan R Weiss", - "author_inst": "University of Pennsylvania" + "author_name": "Melissa S. Stockwell", + "author_inst": "Columbia University Mailman School of Public Health" + }, + { + "author_name": "Vic Veguilla", + "author_inst": "Centers for Disease Control and Prevention" + }, + { + "author_name": "Christina A. Porucznik", + "author_inst": "University of Utah" } ], "version": "1", "license": "cc_by_nc_nd", - "type": "new results", - "category": "microbiology" + "type": "PUBLISHAHEADOFPRINT", + "category": "public and global health" }, { "rel_doi": "10.1101/2022.10.15.22281071", @@ -179966,51 +180149,59 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2022.10.12.511991", - "rel_title": "Rapid transmission and tight bottlenecks constrain the evolution of highly transmissible SARS-CoV-2 variants", + "rel_doi": "10.1101/2022.10.13.512127", + "rel_title": "SARS-CoV-2 immune complex triggers human monocyte necroptosis", "rel_date": "2022-10-14", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.10.12.511991", - "rel_abs": "Transmission bottlenecks limit the spread of novel mutations and reduce the efficiency of natural selection along a transmission chain. Many viruses exhibit tight bottlenecks, and studies of early SARS-CoV-2 lineages identified a bottleneck of 1-3 infectious virions. While increased force of infection, host receptor binding, or immune evasion may influence bottleneck size, the relationship between transmissibility and the transmission bottleneck is unclear. Here, we compare the transmission bottleneck of non-variant-of-concern (non-VOC) SARS-CoV-2 lineages to those of the Alpha, Delta, and Omicron variants. We sequenced viruses from 168 individuals in 65 multiply infected households in duplicate to high depth of coverage. In 110 specimens collected close to the time of transmission, within-host diversity was extremely low. At a 2% frequency threshold, 51% had no intrahost single nucleotide variants (iSNV), and 42% had 1-2 iSNV. In 64 possible transmission pairs with detectable iSNV, we identified a bottleneck of 1 infectious virion (95% CI 1-1) for Alpha, Delta, and Omicron lineages and 2 (95% CI 2-2) in non-VOC lineages. The latter was driven by a single iSNV shared in one non-VOC household. The tight transmission bottleneck in SARS-CoV-2 is due to low genetic diversity at the time of transmission, a relationship that may be more pronounced in rapidly transmissible variants. The tight bottlenecks identified here will limit the development of highly mutated VOC in typical transmission chains, adding to the evidence that selection over prolonged infections in immunocompromised patients may drive their evolution.", - "rel_num_authors": 8, + "rel_link": "https://biorxiv.org/cgi/content/short/2022.10.13.512127", + "rel_abs": "We analyzed the ability of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) itself and SARS-CoV-2-IgG immune complexes to trigger human monocyte necroptosis. SARS-CoV-2 was able to induce monocyte necroptosis dependently of MLKL activation. Necroptosis-associated proteins (RIPK1, RIPK3 and MLKL) were involved in SARS-CoV-2 N1 gene expression in monocytes. SARS-CoV-2 immune complexes promoted monocyte necroptosis in a RIPK3- and MLKL-dependent manner, and Syk tyrosine kinase was necessary for SARS-CoV-2 immune complex-induced monocyte necroptosis, indicating the involvement of Fc{gamma} receptors on necroptosis. Finally, we provide evidence that elevated LDH levels as a marker of lytic cell death are associated with COVID-19 pathogenesis.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Emily E. Bendall", - "author_inst": "University of Michigan" + "author_name": "Leonardo Santos", + "author_inst": "Pontifical Catholic University of Rio Grande do Sul" }, { - "author_name": "Amy Callear", - "author_inst": "University of Michigan" + "author_name": "Krist Helen Antunes", + "author_inst": "Pontifical Catholic University of Rio Grande do Sul" }, { - "author_name": "Amy Getz", - "author_inst": "University of Michigan" + "author_name": "Gisele Cassao", + "author_inst": "Pontifical Catholic University of Rio Grande do Sul" }, { - "author_name": "Kendra Goforth", - "author_inst": "University of Michigan" + "author_name": "Joao Ismael Goncalves", + "author_inst": "Pontifical Catholic University of Rio Grande do Sul" }, { - "author_name": "Drew Edwards", - "author_inst": "University of Michigan" + "author_name": "Bruno Lopes Abbadi", + "author_inst": "Pontifical Catholic University of Rio Grande do Sul" }, { - "author_name": "Arnold Monto", - "author_inst": "University of Michigan" + "author_name": "Cristiano Valim Bizarro", + "author_inst": "Pontificia Universidade Catolica do Rio Grande do Sul" }, { - "author_name": "Emily Toth Martin", - "author_inst": "University of Michigan" + "author_name": "Luiz A Basso", + "author_inst": "Pontificia Universidade Catolica do Rio Grande do Sul - PUCRS" }, { - "author_name": "Adam S. Lauring", - "author_inst": "University of Michigan" + "author_name": "Pablo Machado", + "author_inst": "Pontificia Universidade Catolica do Rio Grande do Sul" + }, + { + "author_name": "Ana Paula Duarte de Souza", + "author_inst": "PUCRS" + }, + { + "author_name": "Barbara Porto", + "author_inst": "University of Manitoba" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_no", "type": "new results", - "category": "microbiology" + "category": "immunology" }, { "rel_doi": "10.1101/2022.10.14.512216", @@ -181972,150 +182163,66 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.10.10.511571", - "rel_title": "GenSLMs: Genome-scale language models reveal SARS-CoV-2 evolutionary dynamics.", + "rel_doi": "10.1101/2022.10.10.511623", + "rel_title": "Genomic tracking of SARS-COV-2 variants in Myanmar", "rel_date": "2022-10-11", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.10.10.511571", - "rel_abs": "We seek to transform how new and emergent variants of pandemiccausing viruses, specifically SARS-CoV-2, are identified and classified. By adapting large language models (LLMs) for genomic data, we build genome-scale language models (GenSLMs) which can learn the evolutionary landscape of SARS-CoV-2 genomes. By pretraining on over 110 million prokaryotic gene sequences and finetuning a SARS-CoV-2-specific model on 1.5 million genomes, we show that GenSLMs can accurately and rapidly identify variants of concern. Thus, to our knowledge, GenSLMs represents one of the first whole genome scale foundation models which can generalize to other prediction tasks. We demonstrate scaling of GenSLMs on GPU-based supercomputers and AI-hardware accelerators utilizing 1.63 Zettaflops in training runs with a sustained performance of 121 PFLOPS in mixed precision and peak of 850 PFLOPS. We present initial scientific insights from examining GenSLMs in tracking evolutionary dynamics of SARS-CoV-2, paving the path to realizing this on large biological data.", - "rel_num_authors": 33, + "rel_link": "https://biorxiv.org/cgi/content/short/2022.10.10.511623", + "rel_abs": "BackgroundIn December 2019, the COVID-19 disease started in Wuhan, China. WHO declared a pandemic on March 12, 2020, and the disease started in Myanmar on March 23, 2020. December brought variants around the world, threatening the healthcare systems. To counter those threats, Myanmar started the COVID-19 variant surveillance program in late 2020.\n\nMethodsWhole genome sequencing was done six times between January 2021 and March 2022. We chose 83 samples with a PCR threshold cycle of less than 25. Then, we used MiSeq FGx for sequencing and Illumina DRAGEN COVIDSeq pipeline, command line interface, GISAID, and MEGA version 7 for data analysis.\n\nResult and DiscussionJanuary 2021 results showed no variant. The second run during the rise of cases in June 2021 showed multiple variants like Alpha, Delta, and Kappa. There is only Delta in the third run at the height of mortality in August, and Delta alone continued until the fourth run in December. After the world reported the Omicron variant in November, Myanmar started a surveillance program. The fifth run in January 2022 showed both Omicron and Delta variants. The sixth run in March 2022 showed only Omicron BA.2. Amino acid mutation at receptor binding domain (RBD) of Spike glycoprotein started since the second run coupling with high transmission, recurrence, and vaccine escape. We also found the mutation at the primer targets used in current RT-PCR platforms.\n\nConclusionThe occurrence of multiple variants and mutations claimed vigilance at ports of entry and preparedness for effective control measures. Genomic surveillance with the observation of evolutionary data is required to predict imminent threats of the current disease and diagnose emerging infectious diseases.", + "rel_num_authors": 12, "rel_authors": [ { - "author_name": "Max T. Zvyagin", - "author_inst": "Argonne National Laboratory" - }, - { - "author_name": "Alexander Brace", - "author_inst": "University of Chicago" - }, - { - "author_name": "Kyle Hippe", - "author_inst": "Argonne National Laboratory" - }, - { - "author_name": "Yuntian Deng", - "author_inst": "NVIDIA Inc" - }, - { - "author_name": "Bin Zhang", - "author_inst": "Cerebras Systems" - }, - { - "author_name": "Cindy Orozco Bohorquez", - "author_inst": "Cerebras Systems" - }, - { - "author_name": "Austin Clyde", - "author_inst": "University of Chicago" - }, - { - "author_name": "Bharat Kale", - "author_inst": "Northern Illinois University" - }, - { - "author_name": "Danilo Perez-Rivera", - "author_inst": "Argonne National Laboratory" - }, - { - "author_name": "Heng Ma", - "author_inst": "Argonne National Laboratory" - }, - { - "author_name": "Carla M. Mann", - "author_inst": "Argonne National Laboratory" - }, - { - "author_name": "Michael Irvin", - "author_inst": "Argonne National Laboratory" - }, - { - "author_name": "J. Gregory Pauloski", - "author_inst": "University of Chicago" - }, - { - "author_name": "Logan Ward", - "author_inst": "Argonne National Laboratory" - }, - { - "author_name": "Valerie Hayot", - "author_inst": "Argonne National Laboratory" - }, - { - "author_name": "Murali Emani", - "author_inst": "Argonne National Laboratory" + "author_name": "Khine Zaw Oo", + "author_inst": "Defence Services Medical Research Centre" }, { - "author_name": "Sam Foreman", - "author_inst": "Argonne National Laboratory" - }, - { - "author_name": "Zhen Xie", - "author_inst": "Argonne National Laboratory" - }, - { - "author_name": "Diangen Lin", - "author_inst": "University of Chicago" - }, - { - "author_name": "Maulik Shukla", - "author_inst": "Argonne National Laboratory" - }, - { - "author_name": "Weili Nie", - "author_inst": "NVIDIA Inc" - }, - { - "author_name": "Josh Romero", - "author_inst": "NVIDIA Inc" - }, - { - "author_name": "Christian Dallago", - "author_inst": "NVIDIA Inc" + "author_name": "Zaw Win Htun", + "author_inst": "Defence Services Medical Academy" }, { - "author_name": "Arash Vahdat", - "author_inst": "NVIDIA Inc" + "author_name": "Nay Myo Aung", + "author_inst": "Defence Services Medical Academy" }, { - "author_name": "Chaowei Xiao", - "author_inst": "NVIDIA Inc" + "author_name": "Ko Ko Win", + "author_inst": "Defence Services Medical Academy" }, { - "author_name": "Thomas Gibbs", - "author_inst": "NVIDIA Inc" + "author_name": "Sett Paing Htoo", + "author_inst": "Defence Services Institute of Nursing: Defence Services Medical Academy" }, { - "author_name": "Ian Foster", - "author_inst": "Argonne National Laboratory" + "author_name": "Thet Wai Oo", + "author_inst": "Defence Services Medical Academy" }, { - "author_name": "James J. Davis", - "author_inst": "Argonne National Laboratory" + "author_name": "Kyaw Zawl Linn", + "author_inst": "Defence Services Medical Academy" }, { - "author_name": "Michael E. Papka", - "author_inst": "Argonne National Laboratory" + "author_name": "Phyo Kyaw Aung", + "author_inst": "Defence Services Medical Academy" }, { - "author_name": "Thomas Brettin", - "author_inst": "Argonne National Laboratory" + "author_name": "Myo Thiha Zaw", + "author_inst": "Defence Services Medical Academy" }, { - "author_name": "Anima Anandkumar", - "author_inst": "NVIDIA Inc" + "author_name": "Kyaw Myo Tun", + "author_inst": "Defence Services Medical Academy" }, { - "author_name": "Venkatram Vishwanath", - "author_inst": "Argonne National Laboratory" + "author_name": "Kyee Myint", + "author_inst": "Defence Services Medical Academy" }, { - "author_name": "Arvind Ramanathan", - "author_inst": "Argonne National Laboratory" + "author_name": "Ko Ko Lwin", + "author_inst": "Defence Services Medical Academy" } ], "version": "1", - "license": "cc_by_nc_nd", - "type": "new results", + "license": "cc_by", + "type": "confirmatory results", "category": "bioinformatics" }, { @@ -184146,51 +184253,75 @@ "category": "pediatrics" }, { - "rel_doi": "10.1101/2022.10.08.511397", - "rel_title": "SiRNA Molecules as Potential RNAi Therapeutics to Silence RdRP Region and N-Gene of SARS-CoV-2: An In Silico Approach", + "rel_doi": "10.1101/2022.10.07.511351", + "rel_title": "Inhibition of the SARS-CoV-2 helicase at single-nucleotide resolution.", "rel_date": "2022-10-08", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.10.08.511397", - "rel_abs": "COVID-19 pandemic keeps pressing onward and effective treatment option against it is still far-off. Since the onslaught in 2020, 13 different variants of SARS-CoV-2 have been surfaced including 05 different variants of concern. Success in faster pandemic handling in the future largely depends on reinforcing therapeutics along with vaccines. As a part of RNAi therapeutics, here we developed a computational approach for predicting siRNAs, which are presumed to be intrinsically active against two crucial mRNAs of SARS-CoV-2, the RNA-dependent RNA polymerase (RdRp), and the nucleocapsid phosphoprotein gene (N gene). Sequence conservancy among the alpha, beta, gamma, and delta variants of SARS-CoV-2 was integrated in the analyses that warrants the potential of these siRNAs against multiple variants. We preliminary found 13 RdRP-targeting and 7 N gene-targeting siRNAs using the siDirect V.2.0. These siRNAs were subsequently filtered through different parameters at optimum condition including macromolecular docking studies. As a result, we selected 4 siRNAs against the RdRP and 3 siRNAs against the N-gene as RNAi candidates. Development of these potential siRNA therapeutics can significantly synergize COVID-19 mitigation by lessening the efforts, furthermore, can lay a rudimentary base for the in silico design of RNAi therapeutics for future emergencies.", - "rel_num_authors": 8, + "rel_link": "https://biorxiv.org/cgi/content/short/2022.10.07.511351", + "rel_abs": "The genome of SARS-CoV-2 encodes for a helicase called nsp13 that is essential for viral replication and highly conserved across related viruses, making it an attractive antiviral target. Here we use nanopore tweezers, a high-resolution single-molecule technique, to gain detailed insight into how nsp13 turns ATP-hydrolysis into directed motion along nucleic acid strands. We measured nsp13 both as it translocates along single-stranded DNA or unwinds short DNA duplexes. Our data confirm that nsp13 uses the inchworm mechanism to move along the DNA in single-nucleotide steps, translocating at ~1000 nt/s or unwinding at ~100 bp/s. Nanopore tweezers high spatio-temporal resolution enables observation of the fundamental physical steps taken by nsp13 even as it translocates at speeds in excess of 1000 nucleotides per second enabling detailed kinetic analysis of nsp13 motion. As a proof-of-principle for inhibition studies, we observed nsp13s motion in the presence of the ATPase inhibitor ATP{gamma}S. Our data reveals that ATP{gamma}S interferes with nsp13s action by affecting several different kinetic processes. The dominant mechanism of inhibition differs depending on the application of assisting force. These advances demonstrate that nanopore tweezers are a powerful method for studying viral helicase mechanism and inhibition.", + "rel_num_authors": 14, "rel_authors": [ { - "author_name": "Mahedi Hasan", - "author_inst": "Department of Biochemistry and Molecular Biology, School of Life Sciences, Shahjalal University of Science and Technology, Sylhet 3114, Bangladesh." + "author_name": "Sinduja K. Marx", + "author_inst": "Department of Physics, University of Washington, Seattle, WA 98195" }, { - "author_name": "Atiya Tahira Tasnim", - "author_inst": "Department of Biochemistry and Molecular Biology, School of Life Sciences, Shahjalal University of Science and Technology, Sylhet 3114, Bangladesh." + "author_name": "Keith J. Mickolajczyk", + "author_inst": "Laboratory of Chemistry and Cell Biology, The Rockefeller University, New York, New York; Department of Biochemistry and Molecular Biology, Robert Wood Johnson " }, { - "author_name": "Arafat Islam Ashik", - "author_inst": "Department of Biochemistry and Molecular Biology, School of Life Sciences, Shahjalal University of Science and Technology, Sylhet 3114, Bangladesh." + "author_name": "Jonathan M. Craig", + "author_inst": "Department of Physics, University of Washington, Seattle, WA 98195" }, { - "author_name": "Md Belal Chowdhury", - "author_inst": "Department of Biochemistry and Molecular Biology, School of Life Sciences, Shahjalal University of Science and Technology, Sylhet 3114, Bangladesh." + "author_name": "Christopher A. Thomas", + "author_inst": "Department of Physics, University of Washington, Seattle, WA 98195" }, { - "author_name": "Zakia Sultana Nishat", - "author_inst": "Department of Biochemistry and Molecular Biology, School of Life Sciences, Shahjalal University of Science and Technology, Sylhet 3114, Bangladesh." + "author_name": "Akira M. Pfeffer", + "author_inst": "Department of Physics, University of Washington, Seattle, WA 98195" }, { - "author_name": "Khandaker Atkia Fariha", - "author_inst": "Department of Biochemistry and Molecular Biology, School of Life Sciences, Shahjalal University of Science and Technology, Sylhet 3114, Bangladesh." + "author_name": "Sarah J. Abell", + "author_inst": "Department of Physics, University of Washington, Seattle, WA 98195" }, { - "author_name": "Tanvir Hossain", - "author_inst": "Department of Biochemistry and Molecular Biology, School of Life Sciences, Shahjalal University of Science and Technology, Sylhet 3114, Bangladesh." + "author_name": "Jessica D. Carrasco", + "author_inst": "Department of Physics, University of Washington, Seattle, WA 98195" }, { - "author_name": "Shamim Ahmed", - "author_inst": "Department of Biochemistry and Molecular Biology, School of Life Sciences, Shahjalal University of Science and Technology, Sylhet 3114, Bangladesh." + "author_name": "Michaela C. Franzi", + "author_inst": "Department of Physics, University of Washington, Seattle, WA 98195" + }, + { + "author_name": "Jesse R. Huang", + "author_inst": "Department of Physics, University of Washington, Seattle, WA 98195" + }, + { + "author_name": "Hwanhee C. Kim", + "author_inst": "Department of Physics, University of Washington, Seattle, WA 98195" + }, + { + "author_name": "Henry D. Brinkerhoff", + "author_inst": "Department of Physics, University of Washington, Seattle, WA 98195" + }, + { + "author_name": "Tarun M. Kapoor", + "author_inst": "Laboratory of Chemistry and Cell Biology, The Rockefeller University, New York, New York" + }, + { + "author_name": "Jens H. Gundlach", + "author_inst": "Department of Physics, University of Washington, Seattle, WA 98115" + }, + { + "author_name": "Andrew H. Laszlo", + "author_inst": "Department of Physics, University of Washington, Seattle, WA 98195" } ], "version": "1", "license": "cc_by_nc_nd", "type": "new results", - "category": "bioinformatics" + "category": "biophysics" }, { "rel_doi": "10.1101/2022.10.06.22280770", @@ -185920,27 +186051,55 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.10.04.510919", - "rel_title": "Real-time inactivation of airborne SARS-CoV-2 using ultraviolet-C", + "rel_doi": "10.1101/2022.10.05.510928", + "rel_title": "A novel antiviral formulation inhibits SARS-CoV-2 infection of human bronchial epithelium", "rel_date": "2022-10-05", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.10.04.510919", - "rel_abs": "COVID-19 is a life-threatening respiratory infection that has had a profound impact on indoor air quality awareness. Ultraviolet-C (UV-C) is a physical disinfection process that triggers microbial inactivation through creating irreversible genetic material damage. An upper room device equipped with germicidal UV-C (UR GUV) was evaluated against airborne SARS-CoV-2 for antimicrobial efficacy using a robust aerosol testing protocol. In 30 minutes, it led to a virucidal efficacy of 99.994 % in a large, room-sized chamber. UR GUV is a promising mitigation strategy for airborne pathogens.", - "rel_num_authors": 2, + "rel_link": "https://biorxiv.org/cgi/content/short/2022.10.05.510928", + "rel_abs": "A novel proprietary formulation, ViruSAL, has previously been demonstrated to inhibit diverse enveloped viral infections in vitro and in vivo. We evaluated the ability of ViruSAL to inhibit SARS-CoV-2 infectivity, using physiologically relevant models of the human bronchial epithelium, to model early infection of the upper respiratory tract. ViruSAL potently inhibited SARS-CoV-2 infection of human bronchial epithelial cells cultured as an air-liquid interface (ALI) model, in a concentration- and time-dependent manner. Viral infection was completely inhibited when ViruSAL was added to bronchial airway models prior to infection. Importantly, ViruSAL also inhibited viral infection when added to ALI models post-infection. No evidence of in vitro cellular toxicity was detected in ViruSAL treated cells at concentrations that completely abrogated viral infectivity. Moreover, intranasal instillation of ViruSAL to a rat model did not result in any toxicity or pathological changes. Together these findings highlight the potential for ViruSAL as a novel and potent antiviral for use within clinical and prophylactic settings.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Carolina Koutras", - "author_inst": "R-Zero Systems" + "author_name": "Kevin Purves", + "author_inst": "University College Dublin" + }, + { + "author_name": "Ruth Haverty", + "author_inst": "University College Dublin" + }, + { + "author_name": "David Folan", + "author_inst": "Westgate Biomedical Ltd." }, { - "author_name": "Richard L Wade", - "author_inst": "R-Zero Systems" + "author_name": "Alan W Baird", + "author_inst": "University College Dublin" + }, + { + "author_name": "Dimitri Scholz", + "author_inst": "University College Dublin" + }, + { + "author_name": "Patrick W Mallon", + "author_inst": "University College Dublin" + }, + { + "author_name": "Virginie Gautier", + "author_inst": "University College Dublin" + }, + { + "author_name": "Michael Folan", + "author_inst": "Westgate Biomedical Ltd." + }, + { + "author_name": "Nicola F Fletcher", + "author_inst": "University College Dublin" } ], "version": "1", "license": "cc_no", "type": "new results", - "category": "microbiology" + "category": "pharmacology and toxicology" }, { "rel_doi": "10.1101/2022.10.04.22280709", @@ -188014,179 +188173,79 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2022.10.03.510566", - "rel_title": "Intranasal delivery of NS1-deleted influenza virus vectored COVID-19 vaccine restrains the SARS-CoV-2 inflammatory response", + "rel_doi": "10.1101/2022.09.30.510274", + "rel_title": "Reproducibility of spatial summation of pain effect during COVID-19 pandemic", "rel_date": "2022-10-03", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.10.03.510566", - "rel_abs": "The emergence of SARS-CoV-2 (Severe Acute Respiratory Syndrome Coronavirus-2) variants and \"anatomical escape\" characteristics threaten the effectiveness of current coronavirus disease (COVID-19) vaccines. There is an urgent need to understand the immunological mechanism of broad-spectrum respiratory tract protection to guide broader vaccines development. In this study, we investigated immune responses induced by an NS1-deleted influenza virus vectored intranasal COVID-19 vaccine (dNS1-RBD) which provides broad-spectrum protection against SARS-CoV-2 variants. Intranasal delivery of dNS1-RBD induced innate immunity, trained immunity and tissue-resident memory T cells covering the upper and lower respiratory tract. It restrained the inflammatory response by suppressing early phase viral load post SARS-CoV-2 challenge and attenuating pro-inflammatory cytokine (IL-6, IL-1B, and IFN-{gamma}) levels, thereby reducing excess immune-induced tissue injury compared with the control group. By inducing local cellular immunity and trained immunity, intranasal delivery of NS1-deleted influenza virus vectored vaccine represents a broad-spectrum COVID-19 vaccine strategy to reduce disease burden.", - "rel_num_authors": 40, + "rel_link": "https://biorxiv.org/cgi/content/short/2022.09.30.510274", + "rel_abs": "The purpose of this study was to reproduce the previously observed spatial summation of pain effect (SSp) using non-laboratory procedures and commercial equipment. An additional aim was to explore the association between expectations and SSp. The Cold Pressor Task (CPT) was used to induce SSp. Healthy participants (N=68) immersed their non-dominant hands (divided into 5 segments) into cold water (Cold Pressor Task). Two conditions were used 1) gradual hand immersion (ascending condition) and 2) gradual hand withdrawal (descending condition). Pain intensity was measured on a Visual Analogue Scale (VAS). The influence of psychological factors, such as the volunteers expectations of pain intensity, on the actual perception of pain were also measured on a VAS. Results showed significant SSp ({chi}2(4) = 116.90, p < 0.001), reproduced with non-laboratory equipment in a home-based set-up. Furthermore, two novel findings were observed: i) there was a significant correlation between expectations and perceived pain, indicating a link between pain expectations and SSp, ii) spatial summation increased with the increase in duration exposure to the noxious stimulus (Wald {chi}2(2) = 157.5, p < 0.001). This study suggests that SSp is shaped by a mixture of excitatory and inhibitory mechanisms and can be influenced by the temporal summation of the nociceptive system. Moreover, this study proposes a new feasible way to induce SSp using a home-based set-up.", + "rel_num_authors": 15, "rel_authors": [ { - "author_name": "Liang Zhang", - "author_inst": "Xiamen University" + "author_name": "Jakub Nastaj", + "author_inst": "The Jerzy Kukuczka Academy of Physical Education" }, { - "author_name": "Yao Jiang", - "author_inst": "Xiamen University" + "author_name": "Jacek Skalski", + "author_inst": "The Jerzy Kukuczka Academy of Physical Education" }, { - "author_name": "Jinhang He", - "author_inst": "Xiamen University" - }, - { - "author_name": "Junyu Chen", - "author_inst": "Xiamen University" - }, - { - "author_name": "Ruoyao Qi", - "author_inst": "Xiamen University" - }, - { - "author_name": "Lunzhi Yuan", - "author_inst": "Xiamen University" - }, - { - "author_name": "Tiange Shao", - "author_inst": "Tsinghua University" + "author_name": "Aleksandra Budzisz", + "author_inst": "The Jerzy Kukuczka Academy of Physical Education" }, { - "author_name": "Congjie Chen", - "author_inst": "Xiamen University" - }, - { - "author_name": "Yaode Chen", - "author_inst": "Xiamen University" - }, - { - "author_name": "Xijing Wang", - "author_inst": "Xiamen University" - }, - { - "author_name": "Xing Lei", - "author_inst": "Xiamen University" - }, - { - "author_name": "Qingxiang Gao", - "author_inst": "Xiamen University" - }, - { - "author_name": "Chunlan Zhuang", - "author_inst": "Xiamen University" - }, - { - "author_name": "Ming Zhou", - "author_inst": "Xiamen University" - }, - { - "author_name": "Jian Ma", - "author_inst": "Xiamen University" - }, - { - "author_name": "Wei Liu", - "author_inst": "Xiamen University" - }, - { - "author_name": "Man Yang", - "author_inst": "Xiamen University" - }, - { - "author_name": "Rao Fu", - "author_inst": "Xiamen University" - }, - { - "author_name": "Yangtao Wu", - "author_inst": "Xiamen University" - }, - { - "author_name": "Feng Chen", - "author_inst": "Xiamen University" - }, - { - "author_name": "Hualong Xiong", - "author_inst": "Xiamen University" - }, - { - "author_name": "Meifeng Nie", - "author_inst": "Xiamen University" - }, - { - "author_name": "Yiyi Chen", - "author_inst": "Xiamen University" - }, - { - "author_name": "Kun Wu", - "author_inst": "Xiamen University" - }, - { - "author_name": "Mujing Fang", - "author_inst": "Xiamen University" - }, - { - "author_name": "Yingbin Wang", - "author_inst": "Xiamen University" + "author_name": "Tibor M. Szikszay", + "author_inst": "University of Luebeck" }, { - "author_name": "Zizheng Zheng", - "author_inst": "Xiamen University" + "author_name": "Sylwia Swoboda", + "author_inst": "The Jerzy Kukuczka Academy of Physical Education" }, { - "author_name": "Shoujie Huang", - "author_inst": "Xiamen University" + "author_name": "Weronika Kowalska", + "author_inst": "The Jerzy Kukuczka Academy of Physical Education" }, { - "author_name": "Shengxiang Ge", - "author_inst": "Xiamen University" + "author_name": "Daria Nowak", + "author_inst": "The Jerzy Kukuczka Academy of Physical Education" }, { - "author_name": "Shih-Chin Cheng", - "author_inst": "Xiamen University" + "author_name": "Edyta Zbroja", + "author_inst": "The Jerzy Kukuczka Academy of Physical Education" }, { - "author_name": "Huachen Zhu", - "author_inst": "The University of Hong Kong" - }, - { - "author_name": "Tong Chen", - "author_inst": "Xiamen University" + "author_name": "Natalia Kruszyna", + "author_inst": "The Jerzy Kukuczka Academy of Physical Education" }, { - "author_name": "Quan Yuan", - "author_inst": "Xiamen University" + "author_name": "Marta Jakubinska", + "author_inst": "The Jerzy Kukuczka Academy of Physical Education" }, { - "author_name": "Ting Wu", - "author_inst": "Xiamen University" + "author_name": "Dominika Grygny", + "author_inst": "The Jerzy Kukuczka Academy of Physical Education" }, { - "author_name": "Jun Zhang", - "author_inst": "Xiamen University" - }, - { - "author_name": "Yixin Chen", - "author_inst": "Xiamen University" - }, - { - "author_name": "Tianying Zhang", - "author_inst": "School of Public Health, Xiamen University" + "author_name": "Romuald Polczyk", + "author_inst": "Jagiellonian University" }, { - "author_name": "Hai Qi", - "author_inst": "Tsinghua University" + "author_name": "Andrzej Malecki", + "author_inst": "The Jerzy Kukuczka Academy of Physical Education" }, { - "author_name": "Yi Guan", - "author_inst": "The University of Hong Kong" + "author_name": "Kerstin Luedtke", + "author_inst": "University of Luebeck" }, { - "author_name": "Ningshao Xia", - "author_inst": "Xiamen University" + "author_name": "Waclaw M. Adamczyk", + "author_inst": "The Jerzy Kukuczka Academy of Physical Education" } ], "version": "1", "license": "cc_by_nc_nd", "type": "new results", - "category": "immunology" + "category": "physiology" }, { "rel_doi": "10.1101/2022.10.02.22280572", @@ -189848,53 +189907,45 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2022.09.27.509803", - "rel_title": "Activation of SARS-CoV-2 by trypsin-like proteases in the clinical specimens of patients with COVID-19", + "rel_doi": "10.1101/2022.09.27.509738", + "rel_title": "IgG3 subclass antibodies recognize antigenically drifted influenza viruses and SARS-CoV-2 variants through efficient bivalent binding", "rel_date": "2022-09-28", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.09.27.509803", - "rel_abs": "SARS-CoV-2 enters host cells through the angiotensin converting enzyme 2 (ACE2) receptor and/or transmembrane protease, serine 2 (TMPRSS2). Serine proteases, such as TMPRSS2 and trypsin, promote viral entry.\n\nIn this study, we investigated whether proteases increased SARS-CoV-2 infectivity using pseudotyped viruses and clinical specimens from patients with COVID-19. First, we investigated how trypsin increased infectivity using the pseudotyped virus. Our findings revealed that trypsin increased infectivity after the virus was adsorbed on the cells, but no increase in infectivity was observed when the virus was treated with trypsin. We examined the effect of trypsin on SARS-CoV-2 infection in clinical specimens and found that the infectivity of the SARS-CoV-2 delta variant increased 36,000-fold after trypsin treatment. By contrast, the infectivity of SARS-CoV-2 omicron variant increased to less than 20-fold in the clinical specimens. Finally, infectivity of clinical specimens containing culture supernatants of Fusobacterium necrophorum was increased from several- to 10-fold. Because SARS-CoV-2 infectivity increases in the oral cavity, which may contain anaerobic bacteria, keeping the oral cavities clean may help prevent SARS-CoV-2 infection.\n\nImportanceIn this study, we examined whether trypsin-like proteases increased the infectivity of SARS-CoV-2. We found that trypsin-like proteases increased the infectivity of both the pseudotyped viruses and the live virus in the clinical specimens. The increase in infectivity was significantly higher for the delta than the omicron variant. A large amount of protease in the oral cavity during SARS-CoV-2 infection is expected to increase infectivity. Therefore, keeping the oral cavity clean is important for preventing infection.", - "rel_num_authors": 9, + "rel_link": "https://biorxiv.org/cgi/content/short/2022.09.27.509738", + "rel_abs": "The constant domains of antibodies are important for effector functions, but less is known about how they can affect binding and neutralization of viruses. Here we evaluated a panel of human influenza virus monoclonal antibodies (mAbs) expressed as IgG1, IgG2 or IgG3. We found that many influenza virus-specific mAbs have altered binding and neutralization capacity depending on the IgG subclass encoded, and that these differences result from unique bivalency capacities of the subclasses. Importantly, subclass differences in antibody binding and neutralization were greatest when the affinity for the target antigen was reduced through antigenic mismatch. We found that antibodies expressed as IgG3 bound and neutralized antigenically drifted influenza viruses more effectively. We obtained similar results using a panel of SARS-CoV-2-specific mAbs and the antigenically advanced B.1.351 strain of SARS-CoV-2. We found that a licensed therapeutic mAb retained neutralization breadth against SARS-CoV-2 variants when expressed as IgG3, but not IgG1. These data highlight that IgG subclasses are not only important for fine-tuning effector functionality, but also for binding and neutralization of antigenically drifted viruses.\n\nSignificanceInfluenza viruses and coronaviruses undergo continuous change, successfully evading human antibodies elicited from prior infections or vaccinations. It is important to identify features that allow antibodies to bind with increased breadth. Here we examined the effect that different IgG subclasses have on monoclonal antibody binding and neutralization. We show that IgG subclass is a determinant of antibody breadth, with IgG3 affording increased neutralization of antigenically drifted variants of influenza virus and SARS-CoV-2. Future studies should evaluate IgG3 therapeutic antibodies and vaccination strategies or adjuvants that may skew antibody responses toward broadly reactive isotypes.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Emiko Igarashi", - "author_inst": "Toyama Institute of Health" - }, - { - "author_name": "Takahisa Shimada", - "author_inst": "Toyama Institute of Health" - }, - { - "author_name": "Shunsuke Yazawa", - "author_inst": "Toyama Institute of Health" + "author_name": "Marcus Bolton", + "author_inst": "Penn" }, { - "author_name": "Yumiko Saga", - "author_inst": "Toyama Institute of Health" + "author_name": "Claudia P. Arevalo", + "author_inst": "Penn" }, { - "author_name": "Masae Itamochi", - "author_inst": "Toyama Institute of Health" + "author_name": "Trevor Griesman", + "author_inst": "Penn" }, { - "author_name": "Noriko Inasaki", - "author_inst": "Toyama Institute of Health" + "author_name": "Shuk Hang Li", + "author_inst": "Penn" }, { - "author_name": "Yoshitomo Morinaga", - "author_inst": "University of Toyama" + "author_name": "Paul Bates", + "author_inst": "Penn" }, { - "author_name": "Kazunori Oishi", - "author_inst": "Toyama Institute of Health" + "author_name": "Patrick C Wilson", + "author_inst": "Weill Cornell Medicine" }, { - "author_name": "Hideki Tani", - "author_inst": "Toyama Institute of Health" + "author_name": "Scott E. Hensley", + "author_inst": "University of Pennsylvania" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "new results", "category": "microbiology" }, @@ -191842,71 +191893,87 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.09.25.22280335", - "rel_title": "Impact of cross-coronavirus immunity in post-acute sequelae of COVID-19", + "rel_doi": "10.1101/2022.09.25.22280341", + "rel_title": "Protection of homologous and heterologous boosters after primary schemes of rAd26-rAd5, ChAdOx1 nCoV-19 and BBIBP-CorV during the Omicron outbreak in adults of 50 years and older in Argentina: a test-negative case-control study.", "rel_date": "2022-09-26", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.09.25.22280335", - "rel_abs": "Beyond the unpredictable acute illness caused by SARS-CoV-2, one-fifth of infections unpredictably result in long-term persistence of symptoms despite the apparent clearance of infection. Insights into the mechanisms that underlie post-acute sequelae of COVID-19 (PASC) will be critical for the prevention and clinical management of long-term complications of COVID-19. Several hypotheses have been proposed that may account for the development of PASC, including persistence of virus or the dysregulation of immunity. Among the immunological changes noted in PASC, alterations in humoral immunity have been observed in some patient subsets. To begin to determine whether SARS-CoV-2 or other pathogen specific humoral immune responses evolve uniquely in PASC, we performed comprehensive antibody profiling against SARS-CoV-2 and a panel of endemic pathogens or routine vaccine antigens using Systems Serology in a cohort of patients with pre-existing rheumatic disease who either developed or did not develop PASC. A distinct humoral immune response was observed in individuals with PASC. Specifically, individuals with PASC harbored less inflamed and weaker Fc{gamma} receptor binding anti-SARS-CoV-2 antibodies and a significantly expanded and more inflamed antibody response against endemic Coronavirus OC43. Individuals with PASC, further, generated more avid IgM responses and developed an expanded inflammatory OC43 S2-specific Fc-receptor binding response, linked to cross reactivity across SARS-CoV-2 and common coronaviruses. These findings implicate previous common Coronavirus imprinting as a marker for the development of PASC.\n\nOne Sentence SummaryThrough high dimensional humoral immune profiling we uncovered the potential importance of previous common Coronavirus imprinting as a novel marker and potential mechanism of an endotype of PASC.", - "rel_num_authors": 13, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.09.25.22280341", + "rel_abs": "ObjectivesTo estimate the protection against laboratory-confirmed SARS-CoV-2 infection, hospitalisations, and death after homologous or heterologous third-dose (booster) in individuals with primary vaccination schemes with rAd26-rAd5, ChAdOx1nCoV-19, BBIBP-CorV or heterologous combinations, during the period of Omicron BA.1 predominance.\n\nDesignRetrospective, test-negative, case-control study, with matched analysis.\n\nSettingProvince of Buenos Aires, Argentina, between 12/1/21-4/1/21.\n\nParticipants422,144 individuals [≥]50 years who had received two or three doses of COVID-19 vaccines and were tested for SARS-CoV-2.\n\nMain outcome measures: Odds ratios of confirmed SARS-CoV-2 infection, hospitalisations and death after administering different boosters, compared to a two-dose primary scheme.\n\nResultsOf 221,933(52.5%) individuals with a positive test, 190,884(45.2%) had received a two-dose vaccination scheme and 231,260(54.8%) a three-dose scheme. The matched analysis included 127,014 cases and 180,714 controls.\n\nThe three-dose scheme reduced infections (OR 0.81[0.80-0.83]) but after 60 days protection dropped (OR 1.04[1.01-1.06]). The booster dose decreased the risk of hospitalisations and deaths after 15-59 days (ORs 0.28[0.25-0.32] and 0.25[0.22-0.28] respectively), which persisted after administration for 75[66-89] days.\n\nAdministration of a homologous booster after a primary scheme with vectored-vaccines provided low protection against infections (OR 0.94[0.92-0.97] and 1.05[1.01-1.09] before and after 60 days). Protection against hospitalisations and death was significant (OR 0.30[0.26-0.35] and 0.29[0.25-0.33] respectively) but decreased after 60 days (OR 0.59[0.47-0.74] and 0.51[0.41- 0.64] respectively).\n\nThe inoculation of a heterologous booster after a primary course with ChAdOx1 nCoV-19, rAd26-rAd5, BBIBP-CorV, or heterologous schemes, offered some protection against infection (OR 0.70[0.68-0.71]), which decreased after 60 days (OR 1.01[0.98-1.04]). The protective effect against hospitalisations and deaths (OR 0.26[0.22-0.31] and 0.22[0.18-0.25] respectively) was clear and persisted after 60 days (OR 0.43[0.35-0.53] and 0.33[0.26-0.41]).\n\nConclusionsThis study shows that, during Omicron predominance, heterologous boosters provide an enhanced protection and longer effect duration against COVID-19-related hospitalisations and death in individuals older than 50, compared to homologous boosters.", + "rel_num_authors": 17, "rel_authors": [ { - "author_name": "Jonathan D Herman", - "author_inst": "Ragon Institute of MGH, MIT, and Harvard" + "author_name": "Soledad Gonzalez", + "author_inst": "Ministry of Health of the Province of Buenos Aires, La Plata, Buenos Aires, Argentina" }, { - "author_name": "Caroline Atyeo", - "author_inst": "Ragon Institute of MGH, MIT, and Harvard" + "author_name": "Santiago Olszevicki", + "author_inst": "Ministry of Health of the Province of Buenos Aires, La Plata, Buenos Aires, Argentina" }, { - "author_name": "Yonatan Zur", - "author_inst": "Ragon Institute of MGH, MIT, and Harvard" + "author_name": "Alejandra Gaiano", + "author_inst": "Ministry of Health of the Province of Buenos Aires, La Plata, Buenos Aires, Argentina" }, { - "author_name": "Claire E Cook", - "author_inst": "Division of Rheumatology, Allergy, and Immunology, Massachusetts General Hospital" + "author_name": "Martin Salazar", + "author_inst": "Faculty of Medical Sciences, National University of La Plata, Argentina" }, { - "author_name": "Naomi J Patel", - "author_inst": "Division of Rheumatology, Allergy, and Immunology, Massachusetts General Hospital" + "author_name": "Lorena Regairaz", + "author_inst": "Immunology Unit, Childrens Hospital Sor Maria Ludovica, La Plata, Buenos Aires" }, { - "author_name": "Kathleen M Vanni", - "author_inst": "Division of Rheumatology, Inflammation, and Immunity, Brigham and Womens Hospital" + "author_name": "Ana Nina Varela Baino", + "author_inst": "Ministry of Health of the Province of Buenos Aires, La Plata, Buenos Aires, Argentina" }, { - "author_name": "Emily N Kowalski", - "author_inst": "Division of Rheumatology, Inflammation, and Immunity, Brigham and Womens Hospital" + "author_name": "Erika Bartel", + "author_inst": "Ministry of Health of the Province of Buenos Aires, La Plata, Buenos Aires, Argentina" }, { - "author_name": "Grace Qian", - "author_inst": "Division of Rheumatology, Inflammation, and Immunity, Brigham and Womens Hospital" + "author_name": "Teresa Varela", + "author_inst": "Ministry of Health of the Province of Buenos Aires, La Plata, Buenos Aires, Argentina" + }, + { + "author_name": "Veronica Gonzalez Martinez", + "author_inst": "Ministry of Health of the Province of Buenos Aires, La Plata, Buenos Aires, Argentina" }, { - "author_name": "Nancy A Shadick", - "author_inst": "Division of Rheumatology, Inflammation, and Immunity, Brigham and Womens Hospital" + "author_name": "Santiago Pesci", + "author_inst": "Ministry of Health of the Province of Buenos Aires, La Plata, Buenos Aires, Argentina" }, { - "author_name": "Douglas A Lauffenburger", - "author_inst": "Department of Biological Engineering, Massachusetts Institute of Technology" + "author_name": "Lupe Marin", + "author_inst": "Ministry of Health of the Province of Buenos Aires, La Plata, Buenos Aires, Argentina" }, { - "author_name": "Zachary S Wallace", - "author_inst": "Division of Rheumatology, Allergy, and Immunology, Massachusetts General Hospital" + "author_name": "Juan Ignacio Irassar", + "author_inst": "Ministry of Health of the Province of Buenos Aires, La Plata, Buenos Aires, Argentina" }, { - "author_name": "Jeffrey A Sparks", - "author_inst": "Division of Rheumatology, Inflammation, and Immunity, Brigham and Womens Hospital" + "author_name": "Leticia Ceriani", + "author_inst": "Ministry of Health of the Province of Buenos Aires, La Plata, Buenos Aires, Argentina" }, { - "author_name": "Galit Alter", - "author_inst": "Ragon Institute of MGH, MIT, and Harvard" + "author_name": "Enio Garcia", + "author_inst": "Ministry of Health of the Province of Buenos Aires, La Plata, Buenos Aires, Argentina" + }, + { + "author_name": "Nicolas Kreplak", + "author_inst": "Ministry of Health of the Province of Buenos Aires, La Plata, Buenos Aires, Argentina" + }, + { + "author_name": "Elisa Estenssoro", + "author_inst": "Ministry of Health of the Province of Buenos Aires, La Plata, Buenos Aires, Argentina" + }, + { + "author_name": "Franco Marsico", + "author_inst": "Faculty of Exacts and Natural Sciences, University of Buenos Aires, Argentina" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2022.09.25.22280333", @@ -194512,55 +194579,99 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2022.09.21.22280208", - "rel_title": "Less invasive SARS-CoV-2 testing for children: A comparison of saliva and a novel Anterior Nasal Swab", + "rel_doi": "10.1101/2022.09.23.22280264", + "rel_title": "Post-COVID-19 syndrome: retinal microcirculation as a potential marker for chronic fatigue", "rel_date": "2022-09-23", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.09.21.22280208", - "rel_abs": "Reducing procedural discomfort for children requiring respiratory testing for SARS-CoV-2 is important in supporting testing strategies for case identification. Alternative sampling methods to nose and throat swabs, which can be self-collected, may reduce laboratory-based testing requirements and provide rapid results for clearance to attend school or hospital settings. The aim of this study was to compare preference and diagnostic sensitivity of a novel anterior nasal swab (ANS), and saliva, with a standard combined nose and throat (CTN) swab. The three samples were self-collected by children aged 5-18 years who had COVID-19 or were a household close contact. Samples were analysed by reverse transcription polymerase chain reaction (RT-PCR) on the Allplex SARS-CoV-2 Assay. Most children and parents preferred the ANS and saliva swab over the CTN swab for future testing. The ANS was highly sensitive (sensitivity 1.000 (95% Confidence Interval (CI) 0.920, 1.000)) for SARS-CoV-2 detection, compared to saliva (sensitivity 0.886, 95% CI 0.754, 0.962). We conclude the novel ANS is a highly sensitive and more comfortable method for SARS-CoV-2 detection when compared to CTN swab.", - "rel_num_authors": 9, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.09.23.22280264", + "rel_abs": "Post-COVID-19 syndrome (PCS) summarizes persisting sequelae after infection with the severe-acute-respiratory-syndrome-Coronavirus-2 (SARS-CoV-2). PCS can affect patients of all covid-19 disease severities. As previous studies revealed impaired blood flow as a provoking factor for triggering PCS, it was the aim of the present study to investigate a potential association of self-reported chronic fatigue and retinal microcirculation in patients with PCS, potentially indicating an objective biomarker.\n\nA prospective study was performed, including 201 subjects: 173 patients with PCS and 28 controls. Retinal microcirculation was visualized by OCT-Angiography (OCT-A) and quantified by the Erlangen-Angio-Tool as macula and peripapillary vessel density (VD). Chronic Fatigue (CF) was assessed with the variables Bell score, age and gender. The VD in the superficial vascular plexus (SVP), intermediate capillary plexus (ICP) and deep capillary plexus (DCP) were analyzed considering the repetitions (12 times). Taking in account of such repetitions a mixed model was performed to detect possible differences in the least square means between different groups of analysis.\n\nAn age effect on VD was observed between patients and controls (p<0.0001). Gender analysis yielded that women with PCS showed lower VD levels in SVP compared to male patients (p=0.0015). The PCS patients showed significantly lower VD of ICP as compared to the controls (p=0.0001, [CI: 0.32; 1]). Moreover, considering PCS patients, the mixed model reveals a significant difference between chronic fatigue (CF) and without CF in VD of SVP (p=0.0033, [CI: -4.5; -0.92]). The model included age, gender and the variable Bell score, representing a subjective marker for CF. Consequently, the retinal microcirculation might be an objective biomarker in subjective-reported chronic fatigue of patients with PCS.", + "rel_num_authors": 20, "rel_authors": [ { - "author_name": "Shidan Tosif", - "author_inst": "Murdoch Childrens Research Institute" + "author_name": "Sarah Schlick", + "author_inst": "Department of Ophthalmology, Universitaetsklinikum Erlangen, Friedrich-Alexander-Universitaet Erlangen-Nuernberg" }, { - "author_name": "Lai-Yang Lee", - "author_inst": "Royal Childrens Hospital Melbourne" + "author_name": "Marianna Lucio", + "author_inst": "Research Unit Analytical BioGeoChemistry, Helmholtz Zentrum Muenchen-German Research Center for Environmental Health" }, { - "author_name": "Jill Nguyen", - "author_inst": "Murdoch Childrens Research Institute" + "author_name": "Alexander Johannes Bartsch", + "author_inst": "Department of Ophthalmology, Universitaetsklinikum Erlangen, Friedrich-Alexander-Universitaet Erlangen-Nuernberg" }, { - "author_name": "Chris Selman", - "author_inst": "Murdoch Childrens Research Institute" + "author_name": "Adam Skornia", + "author_inst": "Department of Ophthalmology, Universitaetsklinikum Erlangen, Friedrich-Alexander-Universitaet Erlangen-Nuernberg" }, { - "author_name": "Anneke Grobler", - "author_inst": "Murdoch Children's Research Institute" + "author_name": "Jakob Hoffmanns", + "author_inst": "Department of Ophthalmology, Universitaetsklinikum Erlangen, Friedrich-Alexander-Universitaet Erlangen-Nuernberg" }, { - "author_name": "Alissa McMinn", - "author_inst": "Murdoch Childrens Research Institute" + "author_name": "Charlotte Szewczykowski", + "author_inst": "Department of Ophthalmology, Universitaetsklinikum Erlangen, Friedrich-Alexander-Universitaet Erlangen-Nuernberg" }, { - "author_name": "Andrew Steer", - "author_inst": "Murdoch Childrens Research Institute" + "author_name": "Thora Schroeder", + "author_inst": "Department of Ophthalmology, Universitaetsklinikum Erlangen, Friedrich-Alexander-Universitaet Erlangen-Nuernberg" }, { - "author_name": "Andrew Daley", - "author_inst": "Royal Childrens Hospital Melbourne" + "author_name": "Franzi Raith", + "author_inst": "Department of Ophthalmology, Universitaetsklinikum Erlangen, Friedrich-Alexander-Universitaet Erlangen-Nuernberg" }, { - "author_name": "Nigel Crawford", - "author_inst": "Murdoch Childrens Research Institute" + "author_name": "Lennart Rogge", + "author_inst": "Department of Ophthalmology, Universitaetsklinikum Erlangen, Friedrich-Alexander-Universitaet Erlangen-Nuernberg" + }, + { + "author_name": "Felix Heltmann", + "author_inst": "Department of Ophthalmology, Universitaetsklinikum Erlangen, Friedrich-Alexander-Universitaet Erlangen-Nuernberg" + }, + { + "author_name": "Michael Moritz", + "author_inst": "Department of Ophthalmology, Universitaetsklinikum Erlangen, Friedrich-Alexander-Universitaet Erlangen-Nuernberg" + }, + { + "author_name": "Lorenz Beitlich", + "author_inst": "Department of Ophthalmology, Universitaetsklinikum Erlangen, Friedrich-Alexander-Universitaet Erlangen-Nuernberg" + }, + { + "author_name": "Julia Schottenhamml", + "author_inst": "Department of Ophthalmology, Universitaetsklinikum Erlangen, Friedrich-Alexander-Universitaet Erlangen-Nuernberg" + }, + { + "author_name": "Martin Herrmann", + "author_inst": "Department of Internal Medicine 3, Universitaetsklinikum Erlangen, Friedrich-Alexander-Universitaet Erlangen-Nuernberg" + }, + { + "author_name": "Thomas Harrer", + "author_inst": "Department of Internal Medicine 3, Universitaetsklinikum Erlangen, Friedrich-Alexander-Universitaet Erlangen-Nuernberg" + }, + { + "author_name": "Marion Ganslmayer", + "author_inst": "Department of Internal Medicine 1, Universitaetsklinikum of Erlangen-Nuernberg, Friedrich-Alexander-Universitaet Erlangen-Nuernberg" + }, + { + "author_name": "Friedrich E. Kruse", + "author_inst": "Department of Ophthalmology, Universitaetsklinikum Erlangen, Friedrich-Alexander-Universitaet Erlangen-Nuernberg" + }, + { + "author_name": "Robert Laemmer", + "author_inst": "Department of Ophthalmology, Universitaetsklinikum Erlangen, Friedrich-Alexander-Universitaet Erlangen-Nuernberg" + }, + { + "author_name": "Christian Mardin", + "author_inst": "Department of Ophthalmology, Universitaetsklinikum Erlangen, Friedrich-Alexander-Universitaet Erlangen-Nuernberg" + }, + { + "author_name": "Bettina Hohberger", + "author_inst": "Department of Ophthalmology, Universitaetsklinikum Erlangen, Friedrich-Alexander-Universitaet Erlangen-Nuernberg" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "pediatrics" + "category": "ophthalmology" }, { "rel_doi": "10.1101/2022.09.22.22280245", @@ -196406,131 +196517,23 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2022.09.20.508614", - "rel_title": "Parallel use of pluripotent human stem cell lung and heart models provide new insights for treatment of SARS-CoV-2", - "rel_date": "2022-09-21", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.09.20.508614", - "rel_abs": "SARS-CoV-2 primarily infects the respiratory tract, but pulmonary and cardiac complications occur in severe COVID-19. To elucidate molecular mechanisms in the lung and heart, we conducted paired experiments in human stem cell-derived lung alveolar type II (AT2) epithelial cell and cardiac cultures infected with SARS-CoV-2. With CRISPR- Cas9 mediated knock-out of ACE2, we demonstrated that angiotensin converting enzyme 2 (ACE2) was essential for SARS-CoV-2 infection of both cell types but further processing in lung cells required TMPRSS2 while cardiac cells required the endosomal pathway. Host responses were significantly different; transcriptome profiling and phosphoproteomics responses depended strongly on the cell type. We identified several antiviral compounds with distinct antiviral and toxicity profiles in lung AT2 and cardiac cells, highlighting the importance of using several relevant cell types for evaluation of antiviral drugs. Our data provide new insights into rational drug combinations for effective treatment of a virus that affects multiple organ systems.\n\nOne-sentence summaryRational treatment strategies for SARS-CoV-2 derived from human PSC models", - "rel_num_authors": 28, + "rel_doi": "10.1101/2022.09.19.22280133", + "rel_title": "Therapeutic and Interventional Bronchoscopy Performed in Critically ill COVID-19 patients: A Systematic Review", + "rel_date": "2022-09-20", + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2022.09.19.22280133", + "rel_abs": "BackgroundCoronavirus disease 2019 (COVID-19) is a highly infectious disease responsible for huge number of deaths in global population. Bronchoscopy was contraindicated for acute respiratory failure in critical patients due to possible transmission of virus to healthcare provider due to aerosol generating procedure (AGP). The safety, efficacy, complication rate, deaths, and transmission rate of virus to healthcare workers due to therapeutic and interventional bronchoscopy performed on COVID-19 patients are accessed.\n\nMethodsA systematic review of literature was performed as per PRISMA 2020 guidelines. To obtain literatures available in PubMed, MEDLINE, and Google Scholars with timeline from 1st Jan 2020 - 10th Dec 2021. Databases were searched with MeSH terms bronchoscopy and COVID-19 it fetched 7350 articles. Applying primary inclusion criteria of bronchoscopy in COVID-19 patients. Secondary inclusion criteria therapeutic and interventional bronchoscopy excluding the articles on diagnostic bronchoscopy.\n\nResultTotal 72 clinically relevant literatures were identified and included for further review. 1887/2558 patients underwent bronchoscopy for treatment of severe or critical COVID-19 pneumonia. therapeutic bronchoscopy was performed in 1241/1887 (65.8%) patients and interventional bronchoscopy was performed in 831/1887 (44.03%) patients. Overall, complications observed in 200/1887 (10.5%) patients. Total, 579/1887 (30%) patients died as per the literatures. Total 15 HCW (8%) were found infected during the studies. It led to successful completion of procedures in 924/940 (98.3%) patients. All three types of bronchoscopes were found to be safe for the patients. The safety, efficacy, complication rate to be 97.5%, and 98.3%, and 2.5% respectively in severely SARS-CoV-2 infected patients undergoing bronchoscopy.\n\nConclusionThis study suggests that bronchoscopy is a safe and effective procedure to be performed in patients suffering from COVID-19 pneumonia. Proper use of personal protective equipments (PPE) during bronchoscopic procedure reduced the risk of transmission of the virus from the patients to the healthcare provider.", + "rel_num_authors": 1, "rel_authors": [ { - "author_name": "Rajeev Rudraraju", - "author_inst": "The Department of Microbiology and Immunology, The Peter Doherty Institute for Infection and Immunity, The University of Melbourne, Melbourne, 3000, Victoria, A" - }, - { - "author_name": "Matthew J Gartner", - "author_inst": "The Department of Microbiology and Immunology, The Peter Doherty Institute for Infection and Immunity, The University of Melbourne, Melbourne, 3000, Victoria, A" - }, - { - "author_name": "Jessica A Neil", - "author_inst": "The Department of Microbiology and Immunology, The Peter Doherty Institute for Infection and Immunity, The University of Melbourne, Melbourne, 3000, Victoria, A" - }, - { - "author_name": "Elizabeth S Stout", - "author_inst": "The Novo Nordisk Foundation Centre for Stem Cell Medicine (reNEW), Murdoch Childrens Research Institute, Melbourne, 3052, Victoria, Australia" - }, - { - "author_name": "Joseph Chen", - "author_inst": "Department of Anatomy and Developmental Biology, Monash University, Clayton, Victoria, Australia" - }, - { - "author_name": "Elise J Needham", - "author_inst": "Charles Perkins Centre and School of Life and Environmental Sciences, Faculty of Science, The University of Sydney, Camperdown, NSW 2006 Australia." - }, - { - "author_name": "Michael See", - "author_inst": "The Novo Nordisk Foundation Centre for Stem Cell Medicine (reNEW), Murdoch Childrens Research Institute, Melbourne, 3052, Victoria, Australia." - }, - { - "author_name": "Charley Mackenzie-Kludas", - "author_inst": "The Department of Microbiology and Immunology, The Peter Doherty Institute for Infection and Immunity, The University of Melbourne, Melbourne, 3000, Victoria, A" - }, - { - "author_name": "Leo Yi Yang", - "author_inst": "The Department of Microbiology and Immunology, The Peter Doherty Institute for Infection and Immunity, The University of Melbourne, Melbourne, 3000, Victoria, A" - }, - { - "author_name": "Mingyang Wang", - "author_inst": "The Department of Microbiology and Immunology, The Peter Doherty Institute for Infection and Immunity, The University of Melbourne, Melbourne, 3000, Victoria, A" - }, - { - "author_name": "Hayley Pointer", - "author_inst": "The Novo Nordisk Foundation Centre for Stem Cell Medicine (reNEW), Murdoch Childrens Research Institute, Melbourne, 3052, Victoria, Australia" - }, - { - "author_name": "Kathy Karavendzas", - "author_inst": "The Novo Nordisk Foundation Centre for Stem Cell Medicine (reNEW), Murdoch Childrens Research Institute, Melbourne, 3052, Victoria, Australia" - }, - { - "author_name": "Dad Abu-Bonsrah", - "author_inst": "The Novo Nordisk Foundation Centre for Stem Cell Medicine (reNEW), Murdoch Childrens Research Institute, Melbourne, 3052, Victoria, Australia" - }, - { - "author_name": "Damien Drew", - "author_inst": "Infection and Immunity Division, The Walter and Eliza Hall Institute of Medical Research, Victoria, Australia" - }, - { - "author_name": "Yu Bo Yang Sun", - "author_inst": "Department of Anatomy and Developmental Biology, Monash University, Clayton, Victoria, Australia" - }, - { - "author_name": "Jia Ping Tan", - "author_inst": "Department of Anatomy and Developmental Biology, Monash University, Clayton, Victoria, Australia" - }, - { - "author_name": "Guizhi Sun", - "author_inst": "Department of Anatomy and Developmental Biology, Monash University, Clayton, Victoria, Australia" - }, - { - "author_name": "Abbas Salavaty", - "author_inst": "Department of Anatomy and Developmental Biology, Monash University, Clayton, Victoria, Australia" - }, - { - "author_name": "Natalie Charitakis", - "author_inst": "The Novo Nordisk Foundation Centre for Stem Cell Medicine (reNEW), Murdoch Childrens Research Institute, Melbourne, 3052, Victoria, Australia" - }, - { - "author_name": "Hieu T Nim", - "author_inst": "The Novo Nordisk Foundation Centre for Stem Cell Medicine (reNEW), Murdoch Childrens Research Institute, Melbourne, 3052, Victoria, Australia" - }, - { - "author_name": "Peter D Currie", - "author_inst": "Australian Regenerative Medicine Institute, Monash University, Clayton, Victoria, Australia" - }, - { - "author_name": "Wai-Hong Tham", - "author_inst": "Infection and Immunity Division, The Walter and Eliza Hall Institute of Medical Research, Victoria, Australia" - }, - { - "author_name": "Enzo Porrello", - "author_inst": "The Novo Nordisk Foundation Centre for Stem Cell Medicine (reNEW), Murdoch Childrens Research Institute, Melbourne, 3052, Victoria, Australia." - }, - { - "author_name": "Jose Polo", - "author_inst": "Department of Anatomy and Developmental Biology, Monash University, Clayton, Victoria, Australia" - }, - { - "author_name": "Sean J Humphrey", - "author_inst": "Charles Perkins Centre and School of Life and Environmental Sciences, Faculty of Science, The University of Sydney, Camperdown, NSW 2006 Australia" - }, - { - "author_name": "Mirana Ramialison", - "author_inst": "The Novo Nordisk Foundation Centre for Stem Cell Medicine (reNEW), Murdoch Childrens Research Institute, Melbourne, 3052, Victoria, Australia" - }, - { - "author_name": "David A Elliott", - "author_inst": "The Novo Nordisk Foundation Centre for Stem Cell Medicine (reNEW), Murdoch Childrens Research Institute, Melbourne, 3052, Victoria, Australia" - }, - { - "author_name": "Kanta Subbarao", - "author_inst": "The Peter Doherty Institute for Infection and Immunity" + "author_name": "Saikat Samadder", + "author_inst": "The Oxford College of Science" } ], "version": "1", - "license": "cc_no", - "type": "new results", - "category": "microbiology" + "license": "cc_by_nd", + "type": "PUBLISHAHEADOFPRINT", + "category": "intensive care and critical care medicine" }, { "rel_doi": "10.1101/2022.09.17.22280033", @@ -198348,77 +198351,41 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.09.15.22279958", - "rel_title": "Prevalence and risk factors for long COVID after mild disease: a longitudinal study with a symptomatic control group.", + "rel_doi": "10.1101/2022.09.15.22280010", + "rel_title": "Estimation of mRNA COVID-19 Vaccination Effectiveness in Tokyo for Omicron Variants BA.2 and BA.5 -Effect of Social Behavior-", "rel_date": "2022-09-17", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.09.15.22279958", - "rel_abs": "BackgroundThere is limited data on the prevalence and risk factors for long COVID, with a shortage of prospective studies with appropriate control groups and adequate sample size. We therefore performed a prospective study to determine the prevalence and risk factors for long COVID.\n\nMethodsWe recruited patients age [≥] 15 years who were clinically suspected of having acute SARS-CoV-2 infection from September 2020 to April 2021. Nasopharyngeal swabs were collected for RT-PCR 3-5 days post symptom onset. Clinical and sociodemographic characteristics were collected using structured questionnaires from persons positive and negative for SARS-COV-2. Follow-up was performed by telephone interview to assess early outcomes and persistent symptoms. For COVID-19 cases, 5D-3L EuroQol questionnaire was used to assess the impact of symptoms on quality of life.\n\nResultsWe followed 814 participants (412 COVD-19 positive and 402 COVID-19 negative persons) of whom the majority (741 / 814) had mild symptoms. Both the COVID-19 positive and the COVID-19 negative groups had similar sociodemographic and clinical characteristics, except for the rate of hospitalization (15.8% vs 1.5%, respectively). One month after disease onset, 122 (29.6%) individuals reported residual symptoms in the COVID-19 positive group or the long COVID group versus 24 (6%) individuals in the COVID-19 negative group. In the long COVID group, fatigue, olfactory disorder, and myalgia were the most frequent symptoms which occurred in the acute phase. Compared to recovered patients, female sex, older age and having > 5 symptoms during the acute phase were risk factors for long COVID. Quality of life was evaluated in 102 out of 122 cases of long COVID with 57 (55.9%) reporting an impact in at least one dimension of the EuroQol 5D-3L questionnaire.\n\nConclusionIn this prospective study consisting predominantly of patients with mild disease, the persistence of symptoms after acute disease was highly associated with long COVID-19 (29.6% vs 6% of COVID negative group). The risk factors for long COVID were older age, female sex, and polysymptomatic acute disease.", - "rel_num_authors": 15, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.09.15.22280010", + "rel_abs": "Variability of COVID-19 vaccination effectiveness (VE) should be assessed with a resolution of a few days assuming that VE is influenced by public behavior and social activity. Here the VE for the Omicron variants (BA.2 and BA.5) is numerically derived for Japans population for the second and third vaccination doses. We then evaluated the daily VE variation caused by our social behavior from the daily data reports for Tokyo. The vaccination effectiveness for Omicron variants (BA.1, BA.2, and BA.5) are derived from the data of Japan and Tokyo with a computational approach. In addition, the effect of different parameters regarding human behavior on VE is assessed using daily data in Tokyo. The individual VE for the Omicron BA.2 in Japan was 61% (95%CI: 57%-65%) for the vaccination second dose from our computation, whereas that for the third dose was 86% (95% CI: 84%-88%). The individual BA.5 VE for the second and third doses are 37% (95% CI: 33%-40%) and 63% (95% CI: 61%-65%). The reduction of daily VE from estimated value was close correlated to the number of tweets related to social gathering in Twitter. The number of tweets considered here would be one of new candidates for VE evaluation and surveillance affecting the viral transmission.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Ana Beatriz C Caze", - "author_inst": "Federal University of Bahia" - }, - { - "author_name": "Thiago Cerqueira Silva", - "author_inst": "LIB and LEITV Laboratories, Instituto Goncalo Moniz, Fiocruz, Salvador, Bahia, Brazil; Universidade Federal da Bahia, Salvador, Bahia, Brazil" - }, - { - "author_name": "Adriele Pinheiro Bomfim", - "author_inst": "Instituto Goncalo Muniz, Fiocruz, Salvador, Brazil; Universidade Federal da Bahia, Salvador, Bahia, Brazil" - }, - { - "author_name": "Gisley Lima de Souza", - "author_inst": "Escola de Medicina e Saude Publica da Bahia; Instituto Goncalo Moniz, Fiocruz, Salvador, Bahia, Brazil" - }, - { - "author_name": "Amanda Canario Andrade Azevedo", - "author_inst": "Hospital Santa Izabel, Santa Casa da Bahia, Salvador, Bahia, Brazil" - }, - { - "author_name": "Michelle Queiroz Aguiar Brasil", - "author_inst": "Instituto Goncalo Moniz, Fiocruz, Salvador, Bahia, Brazil; Federal University of Bahia, Salvador, Bahia, Brazil" - }, - { - "author_name": "Nara Rubia Santos", - "author_inst": "Departamento de Vigilancia em Saude/Vigilancia Epidemiologica, Campo Formoso, Bahia Brazil" - }, - { - "author_name": "Ricardo Khouri", - "author_inst": "Centro de Pesquisas Goncalo Moniz" - }, - { - "author_name": "Jennifer Dan", - "author_inst": "UCSD: University of California San Diego" - }, - { - "author_name": "Antonio Carlos Bandeira", - "author_inst": "UNI-FTC-Faculdade Tecnologia Ciencias Medical School, Bahia; Central State Laboratory LACEN-Bahia; Infectious Diseases Advisor" + "author_name": "Sachiko Kodera", + "author_inst": "Nagoya Institute of Technology" }, { - "author_name": "Luciano Pamplona de Goes Cavalcanti", - "author_inst": "Universidade Federal do Ceara, Fortaleza, Ceara, Brazil; Centro Universitario Christus, Fortaleza, Ceara, Brazil" + "author_name": "Yuki Niimi", + "author_inst": "Nagoya Institute of Technology" }, { - "author_name": "Manoel Barral Netto", - "author_inst": "LIB and LEITV Laboratories, Instituto Goncalo Moniz, Fiocruz, Salvador, Bahia, Brazil; Universidade Federal da Bahia, Salvador, Bahia, Brazil" + "author_name": "Essam A. Rashed", + "author_inst": "University of Hyogo" }, { - "author_name": "Aldina Maria Prado Barral", - "author_inst": "Instituto Goncalo Moniz, Fundacao Oswaldo Cruz, Salvador, Bahia, Brazil; Instituto de Investigacao em Imunologia, Sao Paulo, Sao Paulo, Brazil" + "author_name": "Naoki Yoshinaga", + "author_inst": "The University of Tokyo" }, { - "author_name": "Cynara Gomes Barbosa", - "author_inst": "Universidade Federal da Bahia, Salvador, Brazil" + "author_name": "Masashi Toyoda", + "author_inst": "The University of Tokyo" }, { - "author_name": "Viviane S Boaventura", - "author_inst": "Federal University of Bahia" + "author_name": "Akimasa Hirata", + "author_inst": "Nagoya Institute of Technology" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -200354,63 +200321,43 @@ "category": "respiratory medicine" }, { - "rel_doi": "10.1101/2022.09.14.22279932", - "rel_title": "Rationale, Design, and Baseline Characteristics of the VALIANT (COVID-19 in Older Adults: A Longitudinal Assessment) Cohort", - "rel_date": "2022-09-15", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.09.14.22279932", - "rel_abs": "BackgroundMost older adults hospitalized with COVID-19 survive their acute illness. The impact of COVID-19 hospitalization on patient-centered outcomes, such as physical function, cognitive function, and symptoms, is not well understood. We sought to address this knowledge gap by collecting longitudinal data about these issues from a cohort of older adult survivors of COVID-19 hospitalization.\n\nMethodsWe undertook a prospective study of community-living persons age [≥]60 years who were hospitalized with COVID-19 from June 2020 to June 2021. A baseline interview was conducted during or up to two weeks after hospitalization. Follow-up interviews occurred at one, three, and six months post-discharge. In interviews, participants completed comprehensive assessments of physical and cognitive function, symptoms, and psychosocial factors. If a participant was too impaired to complete an interview, an abbreviated assessment was performed with a proxy. Additional information was collected from the electronic health record. Baseline characteristics of the cohort are reported here.\n\nResultsAmong 341 participants, the mean age was 71.4 (SD 8.4) years, 51% were women, and 37% were of Black race or Hispanic ethnicity. Median length of hospitalization was 8 (IQR 6-12) days. All but 4% of participants required supplemental oxygen and 21% required a higher level of care in an intensive care unit or stepdown unit. Nearly half (47%) reported at least one disability in physical function, 45% demonstrated cognitive impairment, and 67% were pre-frail or frail. Participants reported a mean of 9 of 14 (SD 3) COVID-19-related symptoms.\n\nConclusionsOlder adults hospitalized with COVID-19 demonstrated high rates of baseline physical and cognitive impairment as well as high symptom burden. Longitudinal findings from this cohort will advance our understanding of outcome trajectories of great importance to older survivors of COVID-19.", - "rel_num_authors": 11, + "rel_doi": "10.1101/2022.09.13.507829", + "rel_title": "SARS-CoV-2 Protein Nsp2 Stimulates Translation Under Normal and Hypoxic Conditions", + "rel_date": "2022-09-14", + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2022.09.13.507829", + "rel_abs": "When viruses like SARS-CoV-2 infect cells, they reprogram the repertoire of cellular and viral transcripts that are being translated to optimize their strategy of replication, often targeting host translation initiation factors, particularly eIF4F complex consisting of eIF4E, eIF4G and eIF4A. A proteomic analysis of SARS-CoV-2/human proteins interaction revealed viral Nsp2 and initiation factor eIF4E2, but a role of Nsp2 in regulating translation is still controversial. HEK293T cells stably expressing Nsp2 were tested for protein synthesis rates of synthetic and endogenous mRNAs known to be translated via cap- or IRES-dependent mechanism under normal and hypoxic conditions. Both cap- and IRES-dependent translation were increased in Nsp2-expressing cells under normal and hypoxic conditions, especially mRNAs that require high levels of eIF4F. This could be exploited by the virus to maintain high translation rates of both viral and cellular proteins, particularly in hypoxic conditions as may arise in SARS-CoV-2 patients with poor lung functioning.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Andrew B Cohen", - "author_inst": "Yale School of Medicine" + "author_name": "Nadejda Korneeva", + "author_inst": "LSUHS-Shreveport" }, { - "author_name": "Gail McAvay", - "author_inst": "Yale School of Medicine" + "author_name": "MD Imtiaz Khalil", + "author_inst": "LSUHS-Shreveport" }, { - "author_name": "Mary Geda", - "author_inst": "Yale School of Medicine" + "author_name": "Ishita Ghosh", + "author_inst": "LSUHS-Shreveport" }, { - "author_name": "Sumon Chattopadhyay", - "author_inst": "University of Utah" + "author_name": "Ruping Fan", + "author_inst": "LSUHS-Shreveport" }, { - "author_name": "Seohyuk Lee", - "author_inst": "Yale School of Medicine" - }, - { - "author_name": "Denise Acampora", - "author_inst": "Yale School of Medicine" + "author_name": "Thomas Arnold", + "author_inst": "LSUHS-Shreveport" }, { - "author_name": "Katy Araujo", - "author_inst": "Yale School of Medicine" - }, - { - "author_name": "Peter Charpentier", - "author_inst": "CRI Web Tools" - }, - { - "author_name": "Thomas M Gill", - "author_inst": "Yale School of Medicine" - }, - { - "author_name": "Alexandra Hajduk", - "author_inst": "Yale School of Medicine" - }, - { - "author_name": "Lauren Ferrante", - "author_inst": "Yale School of Medicine" + "author_name": "Arrigo De Benedetti", + "author_inst": "LSUHS-Shreveport" } ], "version": "1", - "license": "cc_no", - "type": "PUBLISHAHEADOFPRINT", - "category": "geriatric medicine" + "license": "cc0_ng", + "type": "new results", + "category": "physiology" }, { "rel_doi": "10.1101/2022.09.13.507833", @@ -202124,51 +202071,83 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2022.09.11.22279823", - "rel_title": "Effects of the COVID-19 pandemic on the mental health of clinically extremely vulnerable children and children living with clinically extremely vulnerable people in Wales: A data linkage study", + "rel_doi": "10.1101/2022.09.12.22279847", + "rel_title": "Multicentre diagnostic evaluation of OnSite COVID-19 Rapid Test (CTK Biotech) among symptomatic individuals in Brazil and The United Kingdom", "rel_date": "2022-09-12", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.09.11.22279823", - "rel_abs": "ObjectivesTo determine whether clinically extremely vulnerable (CEV) children or children living with a CEV person in Wales were at greater risk of presenting with anxiety or depression in primary or secondary care during the COVID-19 pandemic compared with children in the general population, and to compare patterns of anxiety and depression during the pandemic (23rd March 2020-31st January 2021, referred to as 2020/21) and before the pandemic (March 23rd 2019-January 31st 2020, referred to as 2019/20), between CEV children and the general population.\n\nDesignPopulation-based cross-sectional cohort study using anonymised, linked, routinely collected health and administrative data held in the Secure Anonymised Information Linkage Databank. CEV individuals were identified using the COVID-19 Shielded Patient List.\n\nSettingPrimary and secondary healthcare settings covering 80% of the population of Wales.\n\nParticipantsChildren aged 2-17 in Wales: CEV (3,769); living with a CEV person (20,033); or neither (415,009).\n\nPrimary outcome measureFirst record of anxiety or depression in primary or secondary healthcare in 2019/20 and 2020/21, identified using Read and ICD-10 codes.\n\nResultsA Cox regression model adjusted for demographics and history of anxiety or depression revealed that only CEV children were at greater risk of presenting with anxiety or depression during the pandemic compared with the general population (Hazard Ratio=2.27, 95% Confidence Interval=1.94-2.66, p<0.001). Compared with the general population, the risk amongst CEV children was higher in 2020/21 (Risk Ratio 3.04) compared with 2019/20 (Risk Ratio 1.90). In 2020/21, the cumulative incidence of anxiety or depression increased slightly amongst CEV children, but declined amongst the general population.\n\nConclusionsDifferences in the cumulative incidences of recorded anxiety or depression in healthcare between CEV children and the general population were largely driven by a reduction in presentations to healthcare services by children in the general population during the pandemic.\n\nStrengths and limitations of this studyO_LIStrengths of this study include its novelty, national focus and clinical relevance; to date this is the first population-based study examining the effects of the COVID-19 pandemic on healthcare use for anxiety or depression amongst clinically extremely vulnerable (CEV) children and children living with a CEV person in Wales\nC_LIO_LIWe compared 2020/21 data with pre-pandemic 2019/20 data for CEV children and children in the general population, to place the impact of the COVID-19 pandemic in the context of longer-term patterns of healthcare use\nC_LIO_LIWe used a novel approach and linked multiple datasets to identify a cohort of children living with a CEV person in Wales during the COVID-19 pandemic\nC_LIO_LIThere was heterogeneity within the Shielded Patient List that was used to create the cohorts of children identified as CEV or living with a CEV person, in terms of the type and severity of individuals underlying conditions; the manner in which people were added to the list; the time point that people were added to the list; and the extent to which people followed the shielding guidance\nC_LIO_LIRoutinely collected healthcare data does not capture self-reported health, and is likely to underestimate the burden of common mental disorders in the population\nC_LI", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.09.12.22279847", + "rel_abs": "The COVID-19 pandemic has given rise to numerous commercially available antigen rapid diagnostic tests (Ag-RDTs). To generate and share accurate and independent data with the global community, multi-site prospective diagnostic evaluations of Ag-RDTs are required. This report describes the clinical evaluation of OnSite COVID-19 Rapid Test (CTK Biotech, California, USA) in Brazil and The United Kingdom.\n\nA total of 496 paired nasopharyngeal (NP) swabs were collected from symptomatic healthcare workers at Hospital das Clinicas in Sao Paulo, and 211 NP swabs were collected from symptomatic participants at a COVID-19 drive-through testing site in Liverpool, England. These swabs were analysed by Ag-RDT and results were compared to RT-qPCR.\n\nThe clinical sensitivity of the OnSite COVID-19 Rapid test in Brazil was 90.3% [95% Cl 75.1 - 96.7%] and in the United Kingdom was 75.3% [95% Cl 64.6 - 83.6%]. The clinical specificity in Brazil was 99.4% [95% Cl 98.1 - 99.8%] and in the United Kingdom was 95.5% [95% Cl 90.6 - 97.9%]. Analytical evaluation of the Ag-RDT was assessed using direct culture supernatant of SARS-CoV-2 strains from Wild-Type (WT), Alpha, Delta, Gamma and Omicron lineages. Analytical limit of detection was 1.0x103 pfu/mL, 1.0x103 pfu/mL, 1.0x102 pfu/mL, 5.0x103 pfu/mL and 1.0x103 pfu/mL, giving a viral copy equivalent of approximately 2.1x105 copies/mL, 2.1x104 copies/mL, 1.6x104 copies/mL, 3.5x106 copies/mL and 8.7 x 104 for the Ag-RDT, when tested on the WT, Alpha, Delta, Gamma and Omicron lineages, respectively.\n\nThis study provides comparative performance of an Ag-RDT across two different settings, geographical areas, and population. Overall, the OnSite Ag-RDT demonstrated a lower clinical sensitivity than claimed by the manufacturer... Sensitivity and specificity from the Brazil study fulfilled the performance criteria determined by the World Health Organisation but the performance obtained from the UK study failed to. Further evaluation of the use of Ag-RDTs should include harmonised protocols between laboratories to facilitate comparison between settings.", + "rel_num_authors": 16, "rel_authors": [ { - "author_name": "Laura Elizabeth Cowley", - "author_inst": "Swansea University" + "author_name": "Caitlin Rose Thompson", + "author_inst": "Liverpool School of Tropical Medicine" }, { - "author_name": "Karen Hodgson", - "author_inst": "Public Health Wales" + "author_name": "Pablo M Torres", + "author_inst": "University of S\u00e3o Paulo" }, { - "author_name": "Jiao Song", - "author_inst": "Public Health Wales" + "author_name": "Konstantina Kontogianni", + "author_inst": "LSTM" }, { - "author_name": "Tony Whiffen", - "author_inst": "Welsh Government" + "author_name": "Daisy Bengey", + "author_inst": "LSTM" }, { - "author_name": "Jacinta Tan", - "author_inst": "University of Oxford" + "author_name": "Rachel Louise Byrne", + "author_inst": "Liverpool School of Tropical Medicine" }, { - "author_name": "Ann John", - "author_inst": "Swansea University" + "author_name": "Saidy V Noguera", + "author_inst": "University of S\u00e3o Paulo" }, { - "author_name": "Amrita Bandyopadhyay", - "author_inst": "Swansea University" + "author_name": "Alessandra Luna-Muschi", + "author_inst": "University of S\u00e3o Paulo" }, { - "author_name": "Alisha R Davies", - "author_inst": "Public Health Wales" + "author_name": "P\u00e2mela S Andrade", + "author_inst": "University of S\u00e3o Paulo" + }, + { + "author_name": "Antonio dos Santos Barboza", + "author_inst": "University of S\u00e3o Paulo" + }, + { + "author_name": "Marli Nishikawara", + "author_inst": "University of S\u00e3o Paulo" + }, + { + "author_name": "Richard Body", + "author_inst": "Manchester University NHS Foundation Trust" + }, + { + "author_name": "Margaretha de Vos", + "author_inst": "Foundation for Innovative New Diagnostics" + }, + { + "author_name": "Camille Escadafal", + "author_inst": "Foundation for Innovative New Diagnostics" + }, + { + "author_name": "Emily R Adams", + "author_inst": "Liverpool School of Tropical Medicine" + }, + { + "author_name": "Silvia F Costa", + "author_inst": "University of S\u00e3o Paulo" + }, + { + "author_name": "Ana I Cubas Atienzar", + "author_inst": "LSTM" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "pediatrics" + "category": "public and global health" }, { "rel_doi": "10.1101/2022.09.09.507370", @@ -204514,49 +204493,33 @@ "category": "psychiatry and clinical psychology" }, { - "rel_doi": "10.1101/2022.09.07.22279682", - "rel_title": "Psychological factors associated with reporting side effects following COVID-19 vaccination: a prospective cohort study (CoVAccS - wave 3)", + "rel_doi": "10.1101/2022.09.05.22279616", + "rel_title": "Impact of the COVID-19 pandemic on tuberculosis notification in Brazil", "rel_date": "2022-09-09", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.09.07.22279682", - "rel_abs": "ObjectiveTo investigate symptom reporting following the first and second COVID-19 vaccine doses, attribution of symptoms to the vaccine, and factors associated with symptom reporting.\n\nMethodsProspective cohort study (T1: 13-15 January 2021, T2: 4-15 October 2021). Participants were aged 18 years or older, living in the UK. Personal, clinical, and psychological factors were investigated at T1. Symptoms were reported at T2. We used logistic regression analyses to investigate associations.\n\nResultsAfter the first COVID-19 vaccine dose, 74.1% (95% CI 71.4% to 76.7%, n=762/1028) of participants reported at least one injection-site symptom, while 65.0% (95% CI 62.0% to 67.9%, n=669/1029) reported at least one other (non-injection-site) symptom. Symptom reporting was associated with being a woman and younger. After the second dose, 52.9% (95% CI 49.8% to 56.0%, n=532/1005) of participants reported at least one injection-site symptom and 43.7% (95% CI 40.7% to 46.8%, n=440/1006) reported at least one other (non-injection-site) symptom. Symptom reporting was associated with having reported symptoms after the first dose, having an illness that put one at higher risk of COVID-19 (non-injection-site symptoms only), and not believing that one had enough information about COVID-19 to make an informed decision about vaccination (injection-site symptoms only).\n\nConclusionsWomen and younger people were more likely to report symptoms from vaccination. People who had reported symptoms from previous doses were also more likely to report symptoms subsequently, although symptom reporting following the second vaccine was lower than following the first vaccine. Few psychological factors were associated with symptom reporting.\n\nHighlightsO_LIWe measured symptom reporting and attributions from the COVID-19 vaccines.\nC_LIO_LIA prospective cohort study was used (T1: January 2021, T2: October 2021).\nC_LIO_LIWomen and younger people were more likely to report side effects.\nC_LIO_LISide effects reporting after the first and second dose was strongly associated.\nC_LI", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.09.05.22279616", + "rel_abs": "BackgroundThe COVID-19 pandemic notably impacted tuberculosis notification and detection in Brazil. We estimated the number of unnotified tuberculosis cases by group population over the first two years (2020-2021) of the pandemic.\n\nMethodsWe extracted tuberculosis case notifications from routine national surveillance records and population from Ministry of Health. We estimated trends for case notification during pre-pandemic period (2015-2019), stratified by sex, age group, and State with a mixed-effects model. We calculated the unnotified cases during 2020-2021 as the difference between expected, and reported values.\n\nResultsWe estimated 11647 (95% uncertain interval [95%UI]: 829,22466) unnotified cases for 2020; and, 6170 (95%UI: -4629,16968) for 2021; amounting 17817 unnotified cases over the two years. Of the estimated expected tuberculosis cases in 2020 and 2021, 11.2% were not notified. Across sex and age, men aged 30-59 years had the highest number of unnotified cases, and men aged 0-14 years had the highest proportion of unnotified cases. Case underreporting was significant for 13 (of the 27 States) in 2020, and for four in 2021.\n\nConclusionsTuberculosis cases notification decreased substantially during the COVID-19 pandemic in Brazil. Our analysis helped identify the most affected populations to plan strategies to mitigate the effects of the pandemic on tuberculosis control.\n\nResearch in contextO_ST_ABSEvidence before this studyC_ST_ABSA systematic review was conducted to retrieve studies that aimed the impact of the COVID-19 pandemic on tuberculosis detection in PubMed with the following terms: \"(TB or tuberculosis) and (incidence or case or notification or burden) and (COVID-19 or pandemic)\" from January 2020 to May 2022, returning 189 records. Out of these studies, we analyzed 17 that reported a decrease in tuberculosis notification during the pandemic years, and most of them with data only from the first year of the pandemic. Two studies were carried out with Brazilian data. One of them focused on the number of tuberculosis consultations at the benning of the pandemic, and the other was a government bulletin describing tuberculosis notification. As far as we know, no study has examined the tuberculosis case notification in Brazil during the two years of the pandemic, by group population. Furthermore, none of them had predicted the expected cases considering local trends in both the incidence of tuberculosis and its main determinants.\n\nAdded value of this studyUsing tuberculosis case reports from routine national surveillance registries, we estimated case notification trends during the pre-pandemic period (2015-2019), stratified by sex, age group, and State and calculated the unnotified cases during 2020-2021. Brazil lost 11647 (95% uncertain interval [95%UI]: 829,22466) tuberculosis cases in 2020; and, 6170 (95%UI: - 4629,16968) in 2021, which represents 11.2% of underreporting in both years. Across sex and age, men aged 30 to 59 years had the highest number of unnotified cases, and men aged 0 to 14 years had the highest proportion of unnotified cases. Case underreporting was significant for 13 (of the 27 States) in 2020, and for four in 2021.\n\nImplications of all the available evidenceThe COVID-19 pandemic had a catastrophic effect in tuberculosis notification in Brazil during 2020 and 2021. This resulted in a setback in progress made over decades in tuberculosis control, and highlight the threat posed by tuberculosis transmission. Several lessons learned from response to COVID-19 provide an opportunity to improve the notification of respiratory diseases.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Louise E. Smith", - "author_inst": "King's College London" + "author_name": "Daniele Maria Pelissari", + "author_inst": "Postdoc Program in Epidemiology, School of Public Health, University of Sao Paulo, Sao Paulo-SP, Brazil" }, { - "author_name": "Julius Sim", - "author_inst": "Keele University" - }, - { - "author_name": "Susan Mary Sherman", - "author_inst": "Keele University" + "author_name": "Patricia Batholomay", + "author_inst": "Chronic and Airborne Disease Surveillance Coordination, Ministry of Health, Brasilia Brazil" }, { - "author_name": "Richard Aml\u00f4t", - "author_inst": "UK Health Security Agency" + "author_name": "Fernanda Dockhorn Costa Johansen", + "author_inst": "Chronic and Airborne Disease Surveillance Coordination, Ministry of Health, Brasilia Brazil" }, { - "author_name": "Megan Cutts", - "author_inst": "Keele University" - }, - { - "author_name": "Hannah Dasch", - "author_inst": "King's College London" - }, - { - "author_name": "Nick Sevdalis", - "author_inst": "King's College London" - }, - { - "author_name": "James Rubin", - "author_inst": "King's College London" + "author_name": "Fredi Alexander Diaz-Quijano", + "author_inst": "University of Sao Paulo, School of Public Health, Department of Epidemiology. Laboratory of Causal Inference in Epidemiology (LINCE-USP). Sao Paulo, SP, Brazil" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", "category": "public and global health" }, @@ -206300,39 +206263,51 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2022.09.06.22279625", - "rel_title": "Mucosal immunity and antibody anergy in COVID-exposed Covishield vaccinees", + "rel_doi": "10.1101/2022.09.04.22279588", + "rel_title": "The prevalence of SARS-CoV-2 infection and long COVID in US adults during the BA.5 surge, June-July 2022", "rel_date": "2022-09-06", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.09.06.22279625", - "rel_abs": "Knowledge is limited on mucosal immunity induction and longitudinal responses to vaccination against SARS-CoV2. Here, we determined serum/salivary antibodies and cytokines after three Covishield vaccine doses. Sera from 205 healthcare workers (HCWs) one-month after first- dose; one-, three- and six-months after second-dose; paired sera and stimulated whole mouth fluid (SWMF) from 10 HCWs one-, three- and six-months after third-dose were tested for anti- spike SARS-CoV2 antibodies by ECLIA and for cytokines by ELISA/cytokine bead arrays. One-month after second-dose, antibodies had increased significantly (6-fold) in COVID-naive group, but declined (1.5-fold) in those previously exposed to COVID. At one-month after first- dose, IL-10 levels were statistically higher in the previously COVID-exposed group compared to COVID-naive group (p<0.02). Breakthrough infections were 44% in COVID-naive group, while re-infections were 27% in COVID-exposed group (p<0.02). Proinflammatory cytokines-IL- 17/IL-21 at one-month after first- and second-doses, and memory cytokines-IL-7/IL-15 at three- and six-months after second-dose were minimal. Antibodies spiked at one-month after third- dose and declined by three- and six-months after third-dose similar to post-second-dose. Paired sera and SWMF at one- and six-months after third-dose lacked adaptive immunity cytokine expression. Innate immunity cytokines (MIG, MCP-1, IL-8, TNF-, IL-6, IL-1{beta}) showed a declining trend in serum, but were sustained in SWMF. Thus, our findings suggest that first-dose acts as an antibody boost, while second-dose induces antibody anergy in the previously COVID- exposed group. Rapidly declining antibodies and minimal T cell cytokines raises concerns over their durability in subsequent virus exposures. Sustained innate cytokines emanating from the oral mucosa warrant further in-depth explorations.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.09.04.22279588", + "rel_abs": "Due to changes in SARS-CoV-2 testing practices, passive case-based surveillance may be an increasingly unreliable indicator for monitoring the burden of SARS-CoV-2, especially during surges.\n\nWe conducted a cross-sectional survey of a population-representative sample of 3,042 U.S. adults between June 30 and July 2, 2022, during the Omicron BA.5 surge. Respondents were asked about SARS-CoV-2 testing and outcomes, COVID-like symptoms, contact with cases, and experience with prolonged COVID-19 symptoms following prior infection. We estimated the weighted age and sex-standardized SARS-CoV-2 prevalence, during the 14-day period preceding the interview. We estimated age and gender adjusted prevalence ratios (aPR) for current SARS-CoV-2 infection using a log-binomial regression model.\n\nAn estimated 17.3% (95% CI 14.9, 19.8) of respondents had SARS-CoV-2 infection during the two-week study period-equating to 44 million cases as compared to 1.8 million per the CDC during the same time period. SARS-CoV-2 prevalence was higher among those 18-24 years old (aPR 2.2, 95% CI 1.8, 2.7) and among non-Hispanic Black (aPR 1.7, 95% CI 1.4, 2.2) and Hispanic (aPR 2.4, 95% CI 2.0, 2.9). SARS-CoV-2 prevalence was also higher among those with lower income (aPR 1.9, 95% CI 1.5, 2.3), lower education (aPR 3.7 95% CI 3.0,4.7), and those with comorbidities (aPR 1.6, 95% CI 1.4, 2.0). An estimated 21.5% (95% CI 18.2, 24.7) of respondents with a SARS-CoV-2 infection more than 4 weeks prior reported long COVID symptoms.\n\nThe inequitable distribution of SARS-CoV-2 prevalence during the BA.5 surge will likely drive inequities in the future burden of long COVID.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Priya Kannian", - "author_inst": "The Voluntary Health Services Hospital" + "author_name": "Saba Qasmieh", + "author_inst": "City University of New York School of Public Health and Health Policy" }, { - "author_name": "Pasuvaraj Mahanathi", - "author_inst": "The Voluntary Health Services Hospital, Chennai, India" + "author_name": "McKaylee Robertson", + "author_inst": "CUNY ISPH" }, { - "author_name": "Arul Gracemary", - "author_inst": "The Voluntary Health Services Hospital, Chennai, India" + "author_name": "Chloe A Teasdale", + "author_inst": "CUNY Graduate School of Public Health and Health Policy" }, { - "author_name": "Nagalingeswaran Kumarasamy", - "author_inst": "The Voluntary Health Services Hospital, Chennai, India" + "author_name": "Sarah Kulkarni", + "author_inst": "CUNY ISPH" }, { - "author_name": "Stephen J Challacombe", - "author_inst": "King's College London" + "author_name": "Heidi E Jones", + "author_inst": "CUNY School of Public Health" + }, + { + "author_name": "Margaret McNairy", + "author_inst": "Weill Cornell Medicine" + }, + { + "author_name": "Luisa N Borrell", + "author_inst": "CUNY Graduate School of Public Health" + }, + { + "author_name": "Denis Nash", + "author_inst": "City University of New York School of Public Health" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2022.09.04.22279583", @@ -208322,35 +208297,47 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2022.08.30.22279415", - "rel_title": "Spatial analysis of COVID-19 booster vaccine uptake in Scotland, and projection of future distributions", + "rel_doi": "10.1101/2022.08.31.22279432", + "rel_title": "COVID-19 disruptions of food systems and nutrition services in Ethiopia: Evidence of the impacts and policy responses", "rel_date": "2022-09-02", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.08.30.22279415", - "rel_abs": "Vaccination is a critical tool for controlling infectious diseases, with its use to protect against COVID-19 being a prime example. Where a disease is highly transmissible, even a small proportion of unvaccinated individuals can have substantial implications for disease burdens and compromise efforts for control. As socio-demographic factors such as deprivation and ethnicity have been shown to influence uptake rates, identifying how vaccine uptake varies with socio-demographic indicators is a critical step for reducing vaccine hesitancy and issues of access, and identifying plausible future uptake patterns.\n\nHere, we analyse the numbers of COVID-19 vaccinations subdivided by age, gender, date, dose and geographical location. We use publicly available socio-demographic data, and use random forest models to capture patterns of uptake at high spatial resolution, with systematic variation restricted to fine spatial scale (~ 1km in urban areas). We show that uptake of first vaccine booster doses in Scotland can be used to predict with high precision the distribution of second booster doses across deprivation deciles, age and gender despite the substantially lower uptake of second boosters compared to first.\n\nThis analysis shows that while age and gender have the greatest impact on the model fit, there is a substantial influence of several deprivation factors and the proportion of BAME residents. The high correlation amongst these factors also suggests that, should vaccine uptake decrease, the impact of deprivation is likely to increase, furthering the disproportionate impact of COVID-19 on individuals living in highly deprived areas. As our analysis is based solely on publicly available socio-demographic data and readily recorded vaccination uptake figures, it would be easily adaptable to analysing vaccination uptake data from countries where data recording is similar, and for aiding vaccination campaigns against other infectious diseases.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.08.31.22279432", + "rel_abs": "BackgroundSince its first case of COVID-19 on March 13, 2020 and Ethiopia has exerted efforts to curb the spread of the Coronavirus disease 2019 (COVID-19) without imposing a nationwide lockdown. Globally, COVID-19 related disruptions and mitigation measures have impacted livelihoods and food systems, nutrition, as well as access and use of health services.\n\nObjectiveTo develop a comprehensive understanding of the impacts of the COVID-19 pandemic on food security and maternal and child nutrition and health services and to synthesize lessons from policy responses to the COVID-19 pandemic in Ethiopia.\n\nMethodsWe conducted a review of literature and 8 key informant interviews across government agencies, donors, and non-governmental organizations (NGOs), to map the impacts of the COVID-19 pandemic on the food and health systems in Ethiopia. We summarized policy responses and identified recommendations for future actions related to the COVID-19 pandemic and other future emergencies.\n\nResultsThe impacts of the COVID-19 pandemic were felt across the food system. Disruptions were noted in inputs supply due to travel restrictions and closed borders restricting trade, reduced in-person support by agriculture extension workers, income losses, increases in food prices, and the reduction in food security and consumption of less diverse diets. Maternal and child health services were disrupted due to fear of contacting COVID-19, diversion of resources, and lack of personal protective equipment. Disruptions eased over time due to the expansion of social protection, through the Productive Safety Net Program, and the increased outreach and home service provision by the health extension workers.\n\nConclusionEthiopia experienced disruptions to food systems and expanded existing social protection and public health infrastructure and leveraged partnerships with non-state actors. Nevertheless, vulnerabilities and gaps remain and there is a need for a long-term strategy that considers the cyclical nature of COVID-19 cases.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Anthony J Wood", - "author_inst": "The University of Edinburgh" + "author_name": "Juliet McCann", + "author_inst": "Department of Global Health and Population, Harvard T.H. Chan School of Public Health, 665 Huntington Ave, Boston, USA" }, { - "author_name": "Anne Marie MacKintosh", - "author_inst": "University of Stirling" + "author_name": "Lea Sinno", + "author_inst": "Department of Nutrition, Harvard T.H. Chan School of Public Health, 677 Huntington Ave, Boston, USA" }, { - "author_name": "Martine Stead", - "author_inst": "University of Stirling" + "author_name": "Eki Ramadhan", + "author_inst": "Harvard Kennedy School, 79 John F. Kennedy Street, Cambridge, MA" }, { - "author_name": "Rowland Raymond Kao", - "author_inst": "University of Edinburgh" + "author_name": "Nega Assefa", + "author_inst": "College of Health and Medical Sciences, School of Public Health, Haramaya University, Harar, Ethiopia" + }, + { + "author_name": "Hanna Y Berhane", + "author_inst": "Department of Nutrition and Behavioral Sciences, Addis Continental Institute of Public Health, Addis Ababa, Ethiopia" + }, + { + "author_name": "Isabel Madzorera", + "author_inst": "Department of Global Health and Population, Harvard T.H. Chan School of Public Health, 665 Huntington Ave, Boston, USA" + }, + { + "author_name": "Wafaie Fawzi", + "author_inst": "Department of Epidemiology, Harvard T.H. Chan School of Public Health, Harvard University, Boston, USA" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "public and global health" }, { "rel_doi": "10.1101/2022.08.31.22279265", @@ -210092,127 +210079,31 @@ "category": "systems biology" }, { - "rel_doi": "10.1101/2022.08.29.22279359", - "rel_title": "Prophylactic Treatment of COVID-19 in Care Homes Trial (PROTECT-CH)", - "rel_date": "2022-08-31", + "rel_doi": "10.1101/2022.08.25.22279235", + "rel_title": "How Important Are Study Designs? A Simulation Assessment of Vaccine Effectiveness Estimation Bias with Time-Varying Vaccine Coverage, and Heterogeneous Testing and Baseline Attack Rates", + "rel_date": "2022-08-30", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.08.29.22279359", - "rel_abs": "BackgroundCoronavirus disease 2019 (COVID-19) is associated with significant mortality and morbidity in care homes. Novel or repurposed antiviral drugs may reduce infection and disease severity through reducing viral replication and inflammation.\n\nObjectiveTo compare the safety and efficacy of antiviral agents (ciclesonide, niclosamide) for preventing SARS-CoV-2 infection and COVID-19 severity in care home residents.\n\nDesignCluster-randomised open-label blinded endpoint platform clinical trial testing antiviral agents in a post-exposure prophylaxis paradigm.\n\nSettingCare homes across all four United Kingdom member countries.\n\nParticipantsCare home residents 65 years of age or older.\n\nInterventionsCare homes were to be allocated at random by computer to 42 days of antiviral agent plus standard care versus standard of care and followed for 60 days after randomisation.\n\nMain outcome measuresThe primary four-level ordered categorical outcome with participants classified according to the most serious of all-cause mortality, all-cause hospitalisation, SARS-CoV-2 infection and no infection. Analysis using ordinal logistic regression was by intention to treat. Other outcomes included the components of the primary outcome and transmission.\n\nResultsDelays in contracting between NIHR and the manufacturers of potential antiviral agents significantly delayed any potential start date. Having set up the trial (protocol, approvals, insurance, website, database, routine data algorithms, training materials), the trial was stopped in September 2021 prior to contracting of care homes and general practitioners in view of the success of vaccination in care homes with significantly reduced infections, hospitalisations and deaths. As a result, the sample size target (based on COVID-19 rates and deaths occurring in February-June 2020) became unfeasible.\n\nLimitationsCare home residents were not approached about the trial and so were not consented and did not receive treatment. Hence, the feasibility of screening, consent, treatment and data acquisition, and potential benefit of post exposure prophylaxis were never tested. Further, contracting between the University of Nottingham and the PIs, GPs and care homes was not completed, so the feasibility of contracting with all the different groups at the scale needed was not tested.\n\nConclusionsThe role of post exposure prophylaxis of COVID-19 in care home residents was not tested because of changes in COVID-19 incidence, prevalence and virulence as a consequence of the vaccination programme that rendered the study unfeasible. Significant progress was made in describing and developing the infrastructure necessary for a large scale Clinical Trial of Investigational Medicinal Products in care homes in all four UK nations.\n\nFuture workThe role of post-exposure prophylaxis of COVID-19 in care home residents remains to be defined. Significant logistical barriers to conducting research in care homes during a pandemic need to be removed before such studies are possible in the required short timescale.", - "rel_num_authors": 27, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.08.25.22279235", + "rel_abs": "ObjectiveWe studied how commonly used vaccine effectiveness (VE) study designs (variations of cohorts, and test-negative designs) perform under epidemiological nuances more prominent in the COVID-19 era, specifically time-varying vaccine coverage, and heterogeneous testing behaviour and baseline attack rates with selection on willingness to vaccinate.\n\nMethodologyWe simulated data from a multi-parameter conceptual model of the epidemiological environment using 888125 parameter sets. Four configurations of cohorts, and two test-negative designs, were conducted on the simulated data, from which estimation bias is computed. Finally, stratified and fixed effects linear regressions were estimated to quantify the sensitivity of estimation bias to model parameters.\n\nFindingsIrrespective of study designs, dynamic vaccine coverage, and heterogeneous testing behaviour and baseline attack rates are important determinants of bias. Study design choices have non-trivial effects on VE estimation bias even if these factors are absent. The importance of these sources of bias differ across study designs.\n\nConclusionA re-benchmarking of methodology, especially for studying COVID-19 VE, and implementation of vaccine-preventable disease surveillance systems that minimise these sources of bias, are warranted.\n\nHighlightsO_LIThis paper simulated a theoretical model with frictions in vaccination, testing, baseline disease risks, and heterogeneous vaccine effectiveness to evaluate estimation bias across four cohort and two test-negative designs.\nC_LIO_LIIn theory, bias depends on behavioural asymmetries (in testing, and baseline risk) between the vax-willing and vax-unwilling, and the speed of vaccination rollout.\nC_LIO_LIThere is intrinsic estimation bias across all study designs, with the direction and magnitude contingent on specific conditions.\nC_LIO_LIIn scenarios that may be reflective of past SARS-CoV-2 waves, the degree of bias can be substantial, attributable to variation in assumed testing and baseline risk frictions.\nC_LIO_LIA regression-based decomposition indicates that study designs have visibly different primary sources of estimation bias, and degree of robustness in general.\nC_LIO_LIThis study warrants a re-benchmarking of methodology and reporting checklists for VE research, and informs the design of cost-effective surveillance by quantifying part of the bias-implementation cost trade-off.\nC_LI", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Philip M Bath", - "author_inst": "University of Nottingham" - }, - { - "author_name": "Jonathan Ball", - "author_inst": "University of Nottingham" - }, - { - "author_name": "Matthew Boyd", - "author_inst": "University of Nottingham" - }, - { - "author_name": "Heather Gage", - "author_inst": "University of Surrey" - }, - { - "author_name": "Matthew Glover", - "author_inst": "University of Surrey" - }, - { - "author_name": "Maureen Godfrey", - "author_inst": "Private person" - }, - { - "author_name": "Bruce Guthrie", - "author_inst": "University of Edinburgh" - }, - { - "author_name": "Jonathan Hewitt", - "author_inst": "Llandough Hospital" - }, - { - "author_name": "Robert Howard", - "author_inst": "University College London" - }, - { - "author_name": "Thomas Jaki", - "author_inst": "University of Cambridge" - }, - { - "author_name": "Edmund Juszczak", - "author_inst": "University of Nottingham" - }, - { - "author_name": "Daniel Lasserson", - "author_inst": "University of Warwick" - }, - { - "author_name": "Paul Leighton", - "author_inst": "University of Nottingham" - }, - { - "author_name": "Val Leyland", - "author_inst": "Private person" - }, - { - "author_name": "Wei Shen Lim", - "author_inst": "Nottingham University Hospitals NHS Trust" - }, - { - "author_name": "Pip Logan", - "author_inst": "University of Nottingham" - }, - { - "author_name": "Garry Meakin", - "author_inst": "University of Nottingham" - }, - { - "author_name": "Alan Montgomery", - "author_inst": "University of Nottingham" - }, - { - "author_name": "Reuben Ogollah", - "author_inst": "University of Nottingham" - }, - { - "author_name": "Peter Passmore", - "author_inst": "Queen's University Belfast" - }, - { - "author_name": "Philip Quinlan", - "author_inst": "University of Nottingham" - }, - { - "author_name": "Caroline Rick", - "author_inst": "University of Nottingham" - }, - { - "author_name": "Simon Royal", - "author_inst": "Cripps Health Centre" - }, - { - "author_name": "Susan D Shenkin", - "author_inst": "University of Edinburgh" - }, - { - "author_name": "Clare Upton", - "author_inst": "University of Nottingham" + "author_name": "Jing Lian Suah", + "author_inst": "Research and Modelling Unit, Central Bank of Malaysia" }, { - "author_name": "Adam L Gordon", - "author_inst": "University of Nottingham" + "author_name": "Naor Bar-Zeev", + "author_inst": "Bloomberg School of Public Health, Johns Hopkins University" }, { - "author_name": "- PROTECT-CH Trialists", - "author_inst": "" + "author_name": "Maria Deloria Knoll", + "author_inst": "Bloomberg School of Public Health, Johns Hopkins University" } ], "version": "1", "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2022.08.26.22279284", @@ -211746,43 +211637,55 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.08.25.505365", - "rel_title": "Antimicrobial copper as an effective and practical deterrent to surface transmission of SARS-CoV-2", + "rel_doi": "10.1101/2022.08.25.22279195", + "rel_title": "Are female-specific cancers long-term sequelae of COVID-19? Evidence from a large-scale genome-wide cross-trait analysis", "rel_date": "2022-08-27", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.08.25.505365", - "rel_abs": "The aerosols are critical for SARS-CoV-2 transmission, however in areas with high confluence of people the contaminated surfaces take an important role that we could attack using antimicrobial surfaces including copper. In this study, we wanted to challenge infectious SARS-CoV-2 with two samples of copper surfaces and one plastic surface as control at different direct times contact. To evaluate and quantify virucidal activity of copper against SARS-CoV-2, two methods of experimental infection were performed, TCID50 and plaque assays on VeroE6 cells, showing significant inactivation of high titer of SARS-CoV-2 within minutes reaching 99.9 % of inactivation of infectivity on both copper surfaces. Daily high demand surfaces contamination is an issue that we have to worry about not only during the actual pandemic time but also for future, where copper or its alloys will have a pivotal role.\n\nImportanceQuantitative data obtained of TCID50 and plaque assay with infectious SARS-CoV-2 virus showed that after direct contact with copper or copper alloys, viruses were inactivated within minutes. Notably, the SARS-CoV-2 virus used in these assays was in high titer (106 PFU/mL) showing strong copper inactivation of the infectious SARS-CoV-2.", - "rel_num_authors": 6, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2022.08.25.22279195", + "rel_abs": "BackgroundLittle is known regarding the long-term adverse effects of COVID-19 on female-specific cancers due to the restricted length of observational time, nor the shared genetic influences underlying these conditions.\n\nMethodsLeveraging summary statistics from the hitherto largest genome-wide association studies conducted in each trait, we performed a comprehensive genome-wide cross-trait analysis to investigate the shared genetic architecture and the putative genetic associations between COVID-19 with three main female-specific cancers: breast cancer (BC), epithelial ovarian cancer (EOC), and endometrial cancer (EC). Three phenotypes were selected to represent COVID-19 susceptibility (SARS-CoV-2 infection) and severity (COVID-19 hospitalization, COVID-19 critical illness).\n\nResultsFor COVID-19 susceptibility, we found no evidence of a genetic correlation with any of the female-specific cancers. For COVID-19 severity, we identified a significant genome-wide genetic correlation with EC for both hospitalization (rg=0.19, P=0.01) and critical illness (rg =0.29, P=3.00x10-4). Mendelian randomization demonstrated no valid association of COVID-19 with any cancer of interest, except for suggestive associations of genetically predicted hospitalization (ORIVW=1.09, 95%CI=1.01-1.18, P=0.04) and critical illness (ORIVW=1.06, 95%CI=1.00-1.11, P=0.04) with EC risk, none withstanding multiple correction. No reverse association was found. Cross-trait meta-analysis identified multiple pleiotropic SNPs between COVID-19 and female-specific cancers, including 20 for BC, 15 for EOC, and 5 for EC. Transcriptome-wide association studies revealed shared genes, mostly enriched in the hematologic, cardiovascular, and nervous systems.\n\nConclusionsOur genetic analysis highlights an intrinsic link underlying female-specific cancers and COVID-19 - while COVID-19 is not likely to elevate the immediate risk of the examined female-specific cancers, it appears to share mechanistic pathways with these conditions. These findings may provide implications for future therapeutic strategies and public health actions.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Jorge Vera-Otarola", - "author_inst": "Pontificia Universidad Catolica de Chile" + "author_name": "Xunying Zhao", + "author_inst": "Department of Epidemiology and Biostatistics and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospit" }, { - "author_name": "Nicolas Mendez", - "author_inst": "The Clean Copper Company, LLC" + "author_name": "Xueyao Wu", + "author_inst": "Department of Epidemiology and Biostatistics and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospit" }, { - "author_name": "Constanza Mart\u00ednez-Valdebenito", - "author_inst": "Pontificia Universidad Catolica de Chile" + "author_name": "Jinyu Xiao", + "author_inst": "Department of Epidemiology and Biostatistics and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospit" }, { - "author_name": "Rodolfo Mannheim", - "author_inst": "Universidad de Santiago de Chile" + "author_name": "Li Zhang", + "author_inst": "West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China" }, { - "author_name": "Kenneth Lu", - "author_inst": "University of California" + "author_name": "Yu Hao", + "author_inst": "Department of Epidemiology and Biostatistics and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospit" }, { - "author_name": "Steve Rhodes", - "author_inst": "The Clean Copper Company, LLC" + "author_name": "Chenghan Xiao", + "author_inst": "Department of Maternal, Child and Adolescent Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China" + }, + { + "author_name": "Ben Zhang", + "author_inst": "Department of Epidemiology and Biostatistics and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospit" + }, + { + "author_name": "Jiayuan Li", + "author_inst": "Department of Epidemiology and Biostatistics and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospit" + }, + { + "author_name": "Xia Jiang", + "author_inst": "Department of Epidemiology and Biostatistics and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospit" } ], "version": "1", - "license": "cc_by_nd", - "type": "confirmatory results", - "category": "microbiology" + "license": "cc_by_nc_nd", + "type": "PUBLISHAHEADOFPRINT", + "category": "epidemiology" }, { "rel_doi": "10.1101/2022.08.15.22278583", @@ -213824,79 +213727,23 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2022.08.25.22279225", - "rel_title": "Multisystem Inflammatory Syndrome in Children Managed in the Outpatient Setting: An EHR-based cohort study from the RECOVER program", + "rel_doi": "10.1101/2022.08.23.504944", + "rel_title": "COVID-19 Contact Tracing Analysis with Bluetooth Technology Using Raspberry Pis", "rel_date": "2022-08-25", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.08.25.22279225", - "rel_abs": "Using electronic health record data combined with primary chart review, we identified 7 children across 8 pediatric medical centers with a diagnosis of Multisystem Inflammatory Syndrome in Children (MIS-C) who were managed as outpatients. These findings should prompt a discussion about modifying the case definition to allow for such a possibility.", - "rel_num_authors": 15, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2022.08.23.504944", + "rel_abs": "Contact tracing, a method for detecting and preventing the spread of a disease, can become more efficient by becoming automated, rather than being done manually. Bluetooth based contact tracing is a potential method for creating an automated method for contact tracing. However, Bluetooth signals cannot always predict something with complete accuracy due to many subtle obstructions. Received signal strength indicator (RSSI), a value produced when Bluetooth devices send and receive signals, generated from Raspberry Pis can predict the distance between the two devices. By running many experiments with variations of obstructions, I was able to successfully create models to correlate RSSI values and distance with a potential success rate of 91.973%. For my research, a success is determined to be anything but a false negative. Despite the limitations when conducting my research, the inaccuracies of my results prove Bluetooth based contact tracing to not be a reliable method for determining people who have been in contact with an index case in the real world.", + "rel_num_authors": 1, "rel_authors": [ { - "author_name": "Ravi Jhaveri", - "author_inst": "Ann & Robert H. Lurie Children's Hospital of Chicago" - }, - { - "author_name": "Ryan Webb", - "author_inst": "Children's Hospital of Philadelphia" - }, - { - "author_name": "Hanieh Razzaghi", - "author_inst": "Children's Hospital of Philadelphia" - }, - { - "author_name": "Julia Schurchard", - "author_inst": "Children's Hospital of Philadelphia" - }, - { - "author_name": "Asuncion Mejias", - "author_inst": "Nationwide Children's Hospital" - }, - { - "author_name": "Tellen D Bennett", - "author_inst": "University of Colorado School of Medicine" - }, - { - "author_name": "Pei-Ni Jone", - "author_inst": "Children's Hospital of Colorado" - }, - { - "author_name": "Deepika Thacker", - "author_inst": "Nemours" - }, - { - "author_name": "Grant R. Schulert", - "author_inst": "Cincinnati Children's Hospital & Medical Center" - }, - { - "author_name": "Colin Rogerson", - "author_inst": "Riley Children's Hospital" - }, - { - "author_name": "Jonathan D. Cogen", - "author_inst": "Seattle Children's Hospital" - }, - { - "author_name": "L. Charles Bailey", - "author_inst": "Children's Hospital of Philadelphia" - }, - { - "author_name": "Christopher B. Forrest", - "author_inst": "Children's Hospital of Philadelphia" - }, - { - "author_name": "Grace M. Lee", - "author_inst": "Stanford Children's Hospital" - }, - { - "author_name": "Suchitra Rao", - "author_inst": "University of Colorado School of Medicine" + "author_name": "Dean Y. Zhang", + "author_inst": "MIT Lincoln Laboratory Beaver Works" } ], "version": "1", - "license": "cc_no", - "type": "PUBLISHAHEADOFPRINT", - "category": "pediatrics" + "license": "cc_by_nc_nd", + "type": "confirmatory results", + "category": "bioinformatics" }, { "rel_doi": "10.1101/2022.08.22.22278973", @@ -215594,27 +215441,71 @@ "category": "molecular biology" }, { - "rel_doi": "10.1101/2022.08.22.504823", - "rel_title": "Effective Matrix Designs for COVID-19 Group Testing", + "rel_doi": "10.1101/2022.08.23.503528", + "rel_title": "An outbreak of SARS-CoV-2 in big hairy armadillos (Chaetophractus villosus) associated with Gamma variant in Argentina three months after being undetectable in humans", "rel_date": "2022-08-23", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.08.22.504823", - "rel_abs": "BackgroundGrouping samples with low prevalence of positives into pools and testing these pools can achieve considerable savings in testing resources compared with individual testing in the context of COVID-19. We review published pooling matrices, which encode the assignment of samples into pools and describe decoding algorithms, which decode individual samples from pools. Based on the findings we propose new one-round pooling designs with high compression that can efficiently be decoded by combinatorial algorithms. This expands the admissible parameter space for the construction of pooling matrices compared to current methods.\n\nResultsBy arranging samples in a grid and using polynomials to construct pools, we develop direct formulas for an Algorithm (Polynomial Pools (PP)) to generate assignments of samples into pools. Designs from PP guarantee to correctly decode all samples with up to a specified number of positive samples. PP includes recent combinatorial methods for COVID-19, and enables new constructions that can result in more effective designs.\n\nConclusionFor low prevalences of COVID-19, group tests can save resources when compared to individual testing. Constructions from the recent literature on combinatorial methods have gaps with respect to the designs that are available. We develop a method (PP), which generalizes previous constructions and enables new designs that can be advantageous in various situations.", - "rel_num_authors": 2, + "rel_link": "https://biorxiv.org/cgi/content/short/2022.08.23.503528", + "rel_abs": "The present pandemic produced by SARS-CoV-2 and its variants represents an example of the one health concept in which humans and animals are components of the same epidemiologic chain. Animal reservoirs of these viruses are thus the focus of surveillance programs to monitor their circulation and evolution in potentially new hosts and reservoirs. In this work, we report the detection of SARS-CoV-2 Gamma variant infection in four specimens of Chaetophractus villosus (big hairy armadillo/armadillo peludo) in Argentina. In addition to the finding of a new wildlife species susceptible to SARS-CoV-2 infection, the identification of the Gamma variant three months after its last detection in humans is a noteworthy result, raising the question of potential unidentified viral reservoirs.", + "rel_num_authors": 13, "rel_authors": [ { - "author_name": "David Brust", - "author_inst": "German Aerospace Center (DLR)" + "author_name": "Franco Exequiel Lucero Arteaga", + "author_inst": "Consejo Nacional de Investigaciones Cientificas y Tecnicas, CONICET,Facultad De Ciencias Veterinarias UNLPam, La Pampa, Argentina" }, { - "author_name": "Johannes J Brust", - "author_inst": "University of California San Diego" + "author_name": "Mercedes Nabaes Jodar", + "author_inst": "Consejo Nacional de Investigaciones Cientificas y Tecnicas, CONICET,Laboratorio de Virologia Hospital de Ninos Ricardo Gutierrez, Buenos Aires, Argentina" + }, + { + "author_name": "Mariela Mondino", + "author_inst": "Facultad De Ciencias Veterinarias UNLPam, La Pampa, Argentina." + }, + { + "author_name": "Ana Portu", + "author_inst": "Facultad De Ciencias Veterinarias UNLPam, La Pampa, Argentina" + }, + { + "author_name": "Monica Boeris", + "author_inst": "Facultad De Ciencias Veterinarias UNLPam, La Pampa, Argentina" + }, + { + "author_name": "Ana Jolly", + "author_inst": "Facultad De Ciencias Veterinarias UBA INPA Conicet, Buenos Aires, Argentina" + }, + { + "author_name": "Ana Maria Jar", + "author_inst": "Facultad De Ciencias Veterinarias UBA INPA Conicet, Buenos Aires, Argentina" + }, + { + "author_name": "Silvia Leonor Mundo", + "author_inst": "Facultad De Ciencias Veterinarias UBA INPA Conicet, Buenos Aires, Argentina" + }, + { + "author_name": "Eliana Castro", + "author_inst": "Consejo Nacional de Investigaciones Cientificas y Tecnicas, CONICET,Instituto de Investigaciones Biotecnologicas, Universidad de San Martin(UNSAM)" + }, + { + "author_name": "Diego Alvarez", + "author_inst": "Consejo Nacional de Investigaciones Cientificas y Tecnicas, CONICET,Instituto de Investigaciones Biotecnologicas, Universidad de San Martin(UNSAM)" + }, + { + "author_name": "Carolina Torres", + "author_inst": "Consejo Nacional de Investigaciones Cientificas y Tecnicas, CONICET, Universidad de Buenos Aires, Facultad de Farmacia y Bioquimica, Instituto de Investigacione" + }, + { + "author_name": "Mariana Viegas", + "author_inst": "Consejo Nacional de Investigaciones Cientificas y Tecnicas, CONICET,Laboratorio de Virologia Hospital de Ninos Ricardo Gutierrez, Buenos Aires, Argentina" + }, + { + "author_name": "Ana Bratanich", + "author_inst": "Facultad De Ciencias Veterinarias UBA INPA Conicet, Buenos Aires, Argentina" } ], "version": "1", "license": "cc_by", "type": "new results", - "category": "bioinformatics" + "category": "microbiology" }, { "rel_doi": "10.1101/2022.08.23.504908", @@ -217324,99 +217215,87 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.08.21.22279031", - "rel_title": "Neutrophil proteomics identifies temporal changes and hallmarks of delayed recovery in COVID19", + "rel_doi": "10.1101/2022.08.22.504819", + "rel_title": "The butterfly effect: mutational bias of SARS-CoV-2 affects its pattern of molecular evolution on synonymous and nonsynonymous levels", "rel_date": "2022-08-22", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.08.21.22279031", - "rel_abs": "RationaleNeutrophils are important in the pathophysiology of COVID19 but the molecular changes contributing to altered neutrophil phenotypes following SARS-CoV-2 infection are not fully understood.\n\nObjectivesTo use quantitative mass spectrometry-based proteomics to explore neutrophil phenotypes following acute SARS-CoV-2 infection and during recovery.\n\nMethodsProspective observational study of hospitalised patients with PCR-confirmed SARS-CoV-2 infection (May 2020-December 2020). Patients were enrolled within 96 hours of admission, with longitudinal sampling up to 29 days. Control groups comprised non-COVID19 acute lower respiratory tract infection (LRTI) and age-matched non-infected controls. Neutrophils isolated from peripheral blood were processed for mass spectrometry. COVID19 severity and recovery were defined using the WHO ordinal scale.\n\nMeasurements and Main Results84 COVID19 patients were included and compared to 91 LRTI patients and 42 controls. 5,800 neutrophil proteins were identified and 1,748 proteins were significantly different (q-value<0.05) in neutrophils from COVID19 patients compared to those of non-infected controls, including a robust interferon response at baseline, which was lost in severe patients one week after enrolment. Neutrophil changes associated with COVID19 disease severity and prolonged illness were characterized and candidate targets for modulation of neutrophil function were identified. Delayed recovery from COVID19 was associated with changes in metabolic and signalling proteins, complement, chemokine and leukotriene receptors, integrins and inhibitory receptors.\n\nConclusionsSARS-CoV-2 infection results in the sustained presence of recirculating neutrophils with distinct metabolic profiles and altered capacities to respond to migratory signals and cues from other immune cells, pathogens or cytokines.\n\nScientific Knowledge on the SubjectInflammation is the primary driver of morbidity and mortality in severe COVID19. Type I interferon responses, T-cell exhaustion, cytokine storm, emergency myelopoiesis, myeloid compartment dysregulation and procoagulant pathway activation are well established contributors to COVID19 disease severity. Neutrophils play an important role in COVID19, with elevated neutrophil-to-lymphocyte ratios and the emergence of a circulating immature neutrophil population in individuals with severe symptoms. Neutrophil infiltration in the lungs coupled with the release of neutrophil extracellular traps has also been reported in severe and fatal COVID19. The aim of this study was to quantitatively map the proteomes of peripheral blood neutrophils from a cohort of hospitalised COVID19 patients to understand how SARS-CoV-2 infection changes neutrophil phenotypes and functional capacity.\n\nWhat this study adds to the fieldHigh-resolution mass spectrometry was used to characterise the proteomes of peripheral blood neutrophils from >200 individuals at different stages of disease. This work has comprehensively mapped neutrophil molecular changes associated with mild and severe COVID19 and identified significant quantitative changes in more than 1700 proteins in neutrophils from patients hospitalised with COVID19 versus patients with non-COVID19 acute respiratory infections. The study identifies neutrophil protein signatures associated with COVID19 disease severity. The data also show that alterations in neutrophil proteomes can persist in fully recovered patients and identify distinct neutrophil proteomes in recovered versus non recovered patients. Our study provides novel insights into neutrophil responses during acute COVID19 and reveals that altered neutrophil phenotypes persist in convalescent COVID19 patients.", - "rel_num_authors": 20, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2022.08.22.504819", + "rel_abs": "Evolution is a function of mutagenesis and selection. To analyse the role of mutagenesis on the structure of the SARS-CoV-2 genome, we reconstructed the mutational spectrum, which was highly C>U and G>U biased. This bias forces the SARS-CoV-2 genome to become increasingly U-rich unless selection cancels it. We analysed the consequences of this bias on the composition of the most neutral (four-fold degenerate synonymous substitutions) and the least neutral positions (nonsynonymous substitutions). The neutral nucleotide composition is already highly saturated by U and, according to our model, it is at equilibrium, suggesting that in the future, we dont expect any more increase in U. However, nonsynonymous changes continue slowly evolve towards equilibrium substituting CG-rich amino-acids (\"losers\") with U-rich ones (\"gainers\"). This process is universal for all genes of SARS-CoV-2 as well as for other coronaviridae species. In line with the direction mutation pressure hypothesis, we show that viral-specific amino acid content is associated with the viral-specific mutational spectrum due to the accumulation of effectively neutral slightly deleterious variants (losers to gainers) during the molecular evolution. The tuning of a protein space by the mutational process is expected to be typical for species with relaxed purifying selection, suggesting that the purging of slightly-deleterious variants in the SARS-CoV-2 population is not very effective, probably due to the fast expansion of the viral population during the pandemic. Understanding the mutational process can help to design more robust vaccines, based on gainer-rich motifs, close to the mutation-selection equilibrium.", + "rel_num_authors": 17, "rel_authors": [ { - "author_name": "Merete B Long", - "author_inst": "University of Dundee" + "author_name": "Alexandr Voronka", + "author_inst": "Center for Mitochondrial Functional Genomics, Immanuel Kant Baltic Federal University, Russia" }, { - "author_name": "Andrew JM Howden", - "author_inst": "University of Dundee" + "author_name": "Bogdan Efimenko", + "author_inst": "Center for Mitochondrial Functional Genomics, Immanuel Kant Baltic Federal University, Russia" }, { - "author_name": "Holly R Keir", - "author_inst": "University of Dundee" + "author_name": "Sergey Oreshkov", + "author_inst": "Center for Mitochondrial Functional Genomics, Immanuel Kant Baltic Federal University, Kaliningrad, Russian Federation" }, { - "author_name": "Christina M Rollings", - "author_inst": "University of Dundee" + "author_name": "Melissa Franco", + "author_inst": "Northeastern University, Massachusetts, USA" }, { - "author_name": "Yan Hui Giam", - "author_inst": "University of Dundee" + "author_name": "Zoe Fleischmann", + "author_inst": "Northeastern University, Massachusetts, USA" }, { - "author_name": "Thomas Pembridge", - "author_inst": "University of Dundee" + "author_name": "Valerian Yurov", + "author_inst": "Center for Mitochondrial Functional Genomics, Immanuel Kant Baltic Federal University, Kaliningrad, Russian Federation" }, { - "author_name": "Hani Abo-Leyah", - "author_inst": "University of Dundee" + "author_name": "Arina Trufanova", + "author_inst": "Center for Mitochondrial Functional Genomics, Immanuel Kant Baltic Federal University, Kaliningrad, Russian Federation" }, { - "author_name": "Amy Lloyd", - "author_inst": "University of Dundee" + "author_name": "Valeria Timonina", + "author_inst": "School of Life Sciences, Ecole Polytechnique Federale de Lausanne, Lausanne, Switzerland" }, { - "author_name": "Gabriel Sollberger", - "author_inst": "Max Planck Institute for infection biology" + "author_name": "Natalia Ree", + "author_inst": "Center for Mitochondrial Functional Genomics, Immanuel Kant Baltic Federal University, Kaliningrad, Russian Federation" }, { - "author_name": "Rebecca Hull", - "author_inst": "University of Sheffield" + "author_name": "Arthur Zalevsky", + "author_inst": "University of California San Francisco, California, United States" }, { - "author_name": "Amy Gilmour", - "author_inst": "University of Dundee" + "author_name": "Emma Penfrat", + "author_inst": "School of Life Sciences, Ecole Polytechnique Federale de Lausanne, Lausanne, Switzerland" }, { - "author_name": "Chloe Hughes", - "author_inst": "University of Dundee" - }, - { - "author_name": "Benjamin JM New", - "author_inst": "NHS Tayside" - }, - { - "author_name": "Diane Cassidy", - "author_inst": "University of Dundee" - }, - { - "author_name": "Amelia Shoemark", - "author_inst": "University of Dundee" + "author_name": "Thomas Junier", + "author_inst": "School of Life Sciences, Ecole Polytechnique Federale de Lausanne, Lausanne, Switzerland" }, { - "author_name": "Hollian Richardson", - "author_inst": "University of Dundee" + "author_name": "Alexey Agranovsky", + "author_inst": "Faculty of Biology, Lomonosov Moscow State University, Moscow, Russian Federation" }, { - "author_name": "Angus I Lamond", - "author_inst": "University of Dundee" + "author_name": "Konstantin Khrapko", + "author_inst": "Northeastern University, Massachusetts, USA" }, { - "author_name": "Doreen Cantrell", - "author_inst": "University of Dundee" + "author_name": "Konstantin Gunbin", + "author_inst": "Center for Mitochondrial Functional Genomics, Immanuel Kant Baltic Federal University, Kaliningrad, Russian Federation" }, { - "author_name": "James Chalmers", - "author_inst": "University of Dundee" + "author_name": "Jacques Fellay", + "author_inst": "School of Life Sciences, Ecole Polytechnique Federale de Lausanne, Lausanne, Switzerland" }, { - "author_name": "Alejandro J Brenes", - "author_inst": "University of Dundee" + "author_name": "Konstantin Popadin", + "author_inst": "School of Life Sciences, Ecole Polytechnique Federale de Lausanne, Lausanne, Switzerland" } ], "version": "1", "license": "cc_no", - "type": "PUBLISHAHEADOFPRINT", - "category": "respiratory medicine" + "type": "new results", + "category": "evolutionary biology" }, { "rel_doi": "10.1101/2022.08.17.22278807", @@ -219070,65 +218949,17 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2022.08.15.22278787", - "rel_title": "The impact of the Covid-19 pandemic on Italian population-based cancer screening activities and test coverage: results from national cross-sectional repeated surveys", + "rel_doi": "10.1101/2022.08.15.22278703", + "rel_title": "Long-term changes in human mobility responses to COVID-19-related information in Japan", "rel_date": "2022-08-17", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.08.15.22278787", - "rel_abs": "BackgroundIn Italy, population-based screening programs for breast, cervical and colorectal cancers are mandatory, and Regions are in charge of their delivery. From March to May 2020, a severe lockdown was imposed due to the Covid-19 pandemic by the Italian Ministry of Health, with the suspension of screening programs. This paper describes the impact of the pandemic on Italian screening activities and test coverage in 2020.\n\nMethodsThe regional number of subjects invited and of screening tests performed in 2020 were compared with those in 2019. Invitation and examination coverage were also calculated. PASSI surveillance system, through telephone interviews, investigated the population screening test coverage, before and during the pandemic, accordingly to educational attainment, perceived economic difficulties and citizenship.\n\nResultsA reduction of subjects invited and tests performed, with differences among periods and geographic macro areas, was observed in 2020 vs. 2019. The reduction in examination coverage was larger than that in invitation coverage for all screening campaigns. From the second half of 2020, the trend for test coverage showed a decrease in all the macro areas for all the screening campaigns. Compared with the pre-pandemic period, there was a greater difference according to level of education in the odds of having had a test last year vs. never having been screened or not being up to date with screening tests. In addition, foreigners had less access to screening than Italians did.\n\nConclusionsThe lockdown and the ongoing Covid-19 emergency caused an important delay in screening activities. This increased the pre-existing individual and geographical inequalities in access. The opportunistic screening did not mitigate the pandemic impact.\n\nFundingThis study was partially supported by Italian Ministry of Health - Ricerca Corrente Annual Program 2023.", - "rel_num_authors": 13, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.08.15.22278703", + "rel_abs": "How human behaviour has changed over the long term in response to COVID-19-related information, such as the number of COVID-19-infected cases and non-pharmaceutical interventions (NPIs), is under-researched. It is also unclear how increasing vaccination rates have affected human mobility. We estimate human mobility responses to such COVID-19-related information via the interactive effects model, using publicly available daily data on human mobility for retail and recreation and residential spent time in each Japanese prefecture. The results show that Japanese citizens were generally fearful in the first wave of unknown infection; however, they gradually became habituated to similar infection information during the subsequent waves. Nevertheless, the level of habituation decreased in response to different infection information: new variants. In contrast, as for NPIs, it is more plausible to consider that human mobility responds to varying requests rather than habituating them. We also find that rapid vaccination promotion reassures people to go out. Furthermore, we are the first to identify the spatial spillovers of infection information on human mobility responses, as well as heterogeneous responses during different phases of infection. A rapid vaccination policy and detailed monitoring of human mobilities will be useful during long-term pandemics. Long-term analysis is crucial for evidence-based policymaking.", + "rel_num_authors": 1, "rel_authors": [ { - "author_name": "Paolo Giorgi Rossi", - "author_inst": "Azienda Sanitaria Unit\u00e0 Locale di Reggio Emilia" - }, - { - "author_name": "Giuliano Carrozzi", - "author_inst": "Azienda Unit\u00e0 Sanitaria Locale - Modena" - }, - { - "author_name": "Patrizia Falini", - "author_inst": "Institute for cancer research, prevention and clinical network (ISPRO), Florence, Italy" - }, - { - "author_name": "Letizia Sampaolo", - "author_inst": "Azienda Unit\u00e0 Sanitaria Locale - Modena" - }, - { - "author_name": "Giuseppe Gorini", - "author_inst": "Institute for cancer research, prevention and clinical network (ISPRO), Florence, Italy" - }, - { - "author_name": "Manuel Zorzi", - "author_inst": "Registro Tumori del Veneto, Azienda Zero" - }, - { - "author_name": "Paola Armaroli", - "author_inst": "Centro di Prevenzione Oncologica, Azienda Ospedaliero-Universitaria Citt\u00e0 della Salute e della Scienza di Torino" - }, - { - "author_name": "Carlo Senore", - "author_inst": "Centro di Prevenzione Oncologica, Azienda Ospedaliero-Universitaria Citt\u00e0 della Salute e della Scienza di Torino" - }, - { - "author_name": "Priscilla Sassoli de Bianchi", - "author_inst": "Servizio Prevenzione Collettiva e Sanit\u00e0 Pubblica, Direzione Generale Cura della Persona, Salute e Welfare, Regione Emilia-Romagna" - }, - { - "author_name": "Maria Masocco", - "author_inst": "Istituto Superiore di Sanita, Rome" - }, - { - "author_name": "Marco Zappa", - "author_inst": "Retired, Institute for cancer research, prevention and clinical network (ISPRO), Florence, Italy" - }, - { - "author_name": "Francesca Battisti", - "author_inst": "Institute for cancer research, prevention and clinical network (ISPRO), Florence, Italy" - }, - { - "author_name": "Paola Mantellini", - "author_inst": "Institute for cancer research, prevention and clinical network (ISPRO), Florence, Italy" + "author_name": "Shinya Fukui", + "author_inst": "Osaka Metropolitan University" } ], "version": "1", @@ -220864,63 +220695,31 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2022.08.12.503750", - "rel_title": "Sphingosine kinases promote Ebola virus infection and can be targeted to inhibit filoviruses, coronaviruses, and arenaviruses using late endocytic trafficking to enter cells", + "rel_doi": "10.1101/2022.08.12.22278708", + "rel_title": "Estimation of the Total Number of Infected Cases in the 5th Wave of COVID-19 in Hong Kong", "rel_date": "2022-08-12", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.08.12.503750", - "rel_abs": "Entry of enveloped viruses in host cells requires the fusion of the viral and host cell membranes, a process that is facilitated by viral fusion proteins protruding from the viral envelope. For fusion, viral fusion proteins need to be triggered by host factors and for some viruses, such as Ebola virus (EBOV) and Lassa fever virus, this event occurs inside endosomes and/or lysosomes. Consequently, these late-penetrating viruses must be internalized and delivered to entry-conducive intracellular vesicles. Because endocytosis and vesicular trafficking are tightly regulated cellular processes, late penetrating viruses also depend on specific host factors, such as signaling molecules, for efficient viral delivery to the site of fusion, suggesting that these could be targeted for antiviral therapy. In this study, we investigated a role for sphingosine kinases (SKs) in viral entry and found that chemical inhibition of sphingosine kinase 1 (SK1) and/or SK2 and knockdown of SK1 or SK2, inhibited entry of EBOV into host cells. Mechanistically, inhibition of SK1 and/or SK2 prevented EBOV from reaching late-endosomes and lysosomes that are positive for the EBOV receptor, Niemann Pick C1 (NPC1). Furthermore, we present evidence that suggests the trafficking defect caused by SK1/2 inhibition occurs independently of S1P signaling through cell-surface S1PRs. Lastly, we found that chemical inhibition of SKs prevents entry of other late-penetrating viruses, including arenaviruses and coronaviruses, in addition to inhibiting infection by replication competent EBOV and SARS-CoV-2 in Huh7.5 cells. In sum, our results highlight an important role played by SKs in endocytic trafficking which can be targeted to inhibit entry of late-penetrating viruses. SK inhibitors could serve as a starting point for the development of broad-spectrum antiviral therapeutics.", - "rel_num_authors": 11, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2022.08.12.22278708", + "rel_abs": "The total number of infected cases in a region in an epidemic is an important measure of the severity of the disease. With the increase in the number of infected people, the number of susceptible people will be reduced, and the recovery number is increased. The present study attempts to estimate the total number of infected cases in the 5th wave of COVID-19 in Hong Kong based on the daily additional cases supplied by the government based on two test schemes. Scheme 1 covers citizens suspected to be infected as referred by medical professionals, or requested or reported by citizens themselves, those returning from overseas, and those in close contact with the infected persons. Scheme 2 covers residents in buildings with a high concentration of virus in sewage. Polymerase chain reaction (PCR) test and then rapid antigen test (RAT) after 26 February 2022 were accepted by the Hong Kong Special Administrative Government in confirming infected cases. The number of infected cases in these two schemes were compared.\n\nA prediction model on infection case was proposed based on the transient daily infection curves. The averaged recovery number was estimated by assuming a 10-day infection period, including an incubation period of 5 days, and another 5 days for recovery. The transient number of infected, susceptible, recovered people were then presented. An adjustment factor to extend the scenario to the whole population of 7 million in Hong Kong was estimated and applied to study infection number in Hong Kong. Further, it appears that the infection number at the later stage of the 5th wave is weak around end July 2022. However, the number stayed at a constant value in comparing with rapid rise at the early stage in February 2022, even though the gathering activities were kept normal.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Corina M Stewart", - "author_inst": "University of Ottawa" - }, - { - "author_name": "Yuxia Bo", - "author_inst": "University of Ottawa" - }, - { - "author_name": "Kathy Fu", - "author_inst": "University of Ottawa" - }, - { - "author_name": "Mable Chan", - "author_inst": "University of Manitoba" - }, - { - "author_name": "Robert Kozak", - "author_inst": "Sunnybrook Health Sciences Center" - }, - { - "author_name": "Kim Yang-Ping Apperley", - "author_inst": "University of Ottawa" - }, - { - "author_name": "Genevieve Laroche", - "author_inst": "University of Ottawa" - }, - { - "author_name": "Andre Beauchemin", - "author_inst": "University of Ottawa" - }, - { - "author_name": "Gary Kobinger", - "author_inst": "University of Texas Medical Branch" + "author_name": "W.K. Chow", + "author_inst": "The Hong Kong Polytechnic Unversity" }, { - "author_name": "Darwyn Kobasa", - "author_inst": "University of Manitoba" + "author_name": "C.L. Chow", + "author_inst": "City University of Hong Kong" }, { - "author_name": "Marceline Cote", - "author_inst": "University of Ottawa" + "author_name": "C.H. Cheng", + "author_inst": "City University of Hong Kong" } ], "version": "1", - "license": "cc_by_nc", - "type": "new results", - "category": "microbiology" + "license": "cc_by_nc_nd", + "type": "PUBLISHAHEADOFPRINT", + "category": "health policy" }, { "rel_doi": "10.1101/2022.08.11.22278682", @@ -223282,57 +223081,21 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.08.09.22278505", - "rel_title": "Safety and Immunogenicity of Intradermal Administration of Fractional Dose CoronaVac(R), ChAdOx1 nCoV-19 and BNT162b2 as Primary Series Vaccination", + "rel_doi": "10.1101/2022.08.09.22278555", + "rel_title": "What rate of air filtration (ACH) can emulate protection of an N95 respirator in an unventilated room and how can it be checked?", "rel_date": "2022-08-10", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.08.09.22278505", - "rel_abs": "There is a limited supply of COVID-19 vaccines, with less than 20% of eligible populations in low-income countries having received one dose. Intradermal delivery of fractional dose vaccines is one way to improve global vaccine access, but no studies have reported data on intradermal delivery of COVID-19 primary series vaccination. We conducted a pilot study to examine the safety and immunogenicity of three intradermal primary series regimens - heterologous regimen of CoronaVac and ChAdOx1 (CoronaVac-ChAdOx1), homologous regimen of ChAdOx1 (ChAdOx1-ChAdOx1), and homologous regimen of BNT162b2 (BNT162b2-BNT162b2). Each dose was 1/5th or 1/6th of the standard dose. Two additional exploratory arms of intradermal vaccination for the second dose following an intramuscular first dose of ChAdOx1 and BNT162b2 were included. Intradermal vaccination was found to be immunogenic and safe. The antibody responses generated by the intradermal primary series were highest in the BNT162b2 arms. The anti-receptor binding domain (anti-RBD) IgG concentration following fractional dose intradermal vaccination was similar to that of standard dose intramuscular vaccination of the same regimen, except for BNT162b2. The BNT162b2 intradermal series generated a lower antibody concentration than the reference intramuscular series, despite generating the highest antibody concentration of all three intradermal primary series regimens. Neutralizing antibody responses against the SARS-CoV-2 ancestral strain were consistent with what was observed for anti-RBD IgG, with lower titers for SARS-CoV-2 variants. The FRNT50 titers were lowest against the omicron variant, being undetectable (GMT[≤]10) in about a quarter of study participants. T-cell responses against spike- and nucleocapsid-membrane-open reading frame proteins were also detected following intradermal vaccination. Adverse effects following intradermal vaccination were generally comparable with post-intramuscular vaccination effects. Taken together, our data suggest that intradermal vaccination using 1/5th or 1/6th of standard COVID-19 intramuscular vaccination dosing generates similar immune responses with tendency of lower systemic adverse reactions than intramuscular vaccination. Our findings have implications in settings where COVID-19 vaccines are in shortage.", - "rel_num_authors": 10, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.08.09.22278555", + "rel_abs": "There is an immediate need for efficient networks to detect and control novel/emerging bioaerosol threats. In 2022, the Pentagon Force Protection Agency (PFPA) found detection of emerging bioaerosol threats to be \"not feasible for daily operations\" due to cost of reagents used for metagenomics, cost of sequencing instruments, and time/cost for labor (subject matter expertise) to analyze bioinformatics. If the Pentagon experiences these operational difficulties, they may also extend to many of the 280,000 buildings (2.3 billion square feet) at 5000 secure US DoD military sites, 250 US Navy ships, and beyond in civilian buildings around the world. These economic barriers can still be addressed in a threat-agnostic manner by dynamically pooling samples from a network of dry filter units (DFUs) to detect spatio-temporally correlated \"spikes\" in novel pathogen concentrations, termed Spike Triggered Virtualization (STV). In STV, pooling and sequencing depth are automatically modulated in the next cycle in response to novel potential biothreats in the sequencing output of the previous sequencing cycle. By running at a high pooling factor and lower depth unless triggered by a potential pathogen spike, average daily and annual cost per DFU can be reduced by one to two orders of magnitude depending on chosen trigger thresholds. Artificial intelligence (AI) can further enhance sensitivity of STV triggers. Risk of infection remains during the 12-24 hour window between a bioaerosol incident and its detection, but can in some cases be reduced by 80% or potentially more with high-speed indoor air cleaning exceeding 10 air changes per hour (10 ACH) similar to passenger airplanes (Airbus A319, A321 and a Boeing 737-Max8/9) that were tested in flight. Costs of 4 ACH or higher are expected to rise non-linearly with ACH using central HVAC systems and be cost-prohibitive. Whereas 10 ACH or more can be achieved economically by recycling the air in rooms with low-noise, portable air filtration systems tested herein for which costs scale linearly with ACH. For typical ceiling heights (< 10 ), the cost per square foot cost for low-noise air filtration exceeding 10 ACH was found to be approximately $0.5 to $1 for Do-It-Yourself (DIY) and $2 to $5 for HEPA.", + "rel_num_authors": 1, "rel_authors": [ { - "author_name": "Somruedee Chatsiricharoenkul", - "author_inst": "Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand" - }, - { - "author_name": "Suvimol Niyomnaitham", - "author_inst": "Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand" - }, - { - "author_name": "H. Joshua Posen", - "author_inst": "Division of Infectious Diseases, Hospital for Sick Children, Toronto, Canada" - }, - { - "author_name": "Zheng Quan Toh", - "author_inst": "Murdoch Children Research Institute, Parkville, Victoria, Australia" - }, - { - "author_name": "Paul V Licciardi", - "author_inst": "Murdoch Children's Research Institute" - }, - { - "author_name": "Patimaporn Wongprompitak", - "author_inst": "Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand" - }, - { - "author_name": "Thaneeya Duangchinda", - "author_inst": "Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand" - }, - { - "author_name": "Pattarakul Pakchotanon", - "author_inst": "Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand" - }, - { - "author_name": "Warangkana Chantima", - "author_inst": "Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand" - }, - { - "author_name": "Kulkanya Chokephaibulkit", - "author_inst": "Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand" + "author_name": "Devabhaktuni Srikrishna", + "author_inst": "Patient Knowhow, Inc." } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -225340,31 +225103,63 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.08.06.503019", - "rel_title": "Evolutionary progression of collective mutations in Omicron sub-lineages towards efficient RBD-hACE2: allosteric communications between and within viral and human proteins", + "rel_doi": "10.1101/2022.08.06.503050", + "rel_title": "The Defenders of the Alveolus Succumb in COVID-19 Pneumonia to SARS-CoV-2, Necroptosis, Pyroptosis and Panoptosis", "rel_date": "2022-08-08", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.08.06.503019", - "rel_abs": "The interaction between the Spike (S) protein of SARS-CoV-2 and the human angiotensin converting enzyme 2 (hACE2) is essential for infection, and is a target for neutralizing antibodies. Consequently, selection of mutations in the S protein is expected to be driven by the impact on the interaction with hACE2 and antibody escape. Here, for the first time, we systematically characterized the collective effects of mutations in each of the Omicron sub-lineages (BA.1, BA.2, BA.3 and BA.4) on both the viral S protein receptor binding domain (RBD) and the hACE2 protein using post molecular dynamics studies and dynamic residue network (DRN) analysis. Our analysis suggested that Omicron sub-lineage mutations result in altered physicochemical properties that change conformational flexibility compared to the reference structure, and may contribute to antibody escape. We also observed changes in the hACE2 substrate binding groove in some sub-lineages. Notably, we identified unique allosteric communication paths in the reference protein complex formed by the DRN metrics betweenness centrality and eigencentrality hubs, originating from the RBD core traversing the receptor binding motif of the S protein and the N-terminal domain of the hACE2 to the active site. We showed allosteric changes in residue network paths in both the RBD and hACE2 proteins due to Omicron sub-lineage mutations. Taken together, these data suggest progressive evolution of the Omicron S protein RBD in sub-lineages towards a more efficient interaction with the hACE2 receptor which may account for the increased transmissibility of Omicron variants.", - "rel_num_authors": 3, + "rel_link": "https://biorxiv.org/cgi/content/short/2022.08.06.503050", + "rel_abs": "The alveolar type II (ATII) pneumocyte has been called the defender of the alveolus because, amongst the cells many important roles, repair of lung injury is particularly critical. We investigated the extent to which SARS-CoV-2 infection incapacitates the ATII reparative response in fatal COVID-19 pneumonia, and describe massive infection and destruction of ATI and ATII cells. We show that both type I interferon-negative infected ATII and type I-interferon-positive uninfected ATII cells succumb to TNF-induced necroptosis, BTK-induced pyroptosis and a new PANoptotic hybrid form of inflammatory cell death that combines apoptosis, necroptosis and pyroptosis in the same cell. We locate pathway components of these cell death pathways in a PANoptosomal latticework that mediates emptying and disruption of ATII cells and destruction of cells in blood vessels associated with microthrombi. Early antiviral treatment combined with inhibitors of TNF and BTK could preserve ATII cell populations to restore lung function and reduce hyperinflammation from necroptosis, pyroptosis and panoptosis.\n\nGraphic\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=125 SRC=\"FIGDIR/small/503050v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (28K):\norg.highwire.dtl.DTLVardef@8bf28dorg.highwire.dtl.DTLVardef@1e1335eorg.highwire.dtl.DTLVardef@1f3a0e2org.highwire.dtl.DTLVardef@1c77c62_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIIn fatal COVID-19 pneumonia, the initial destruction of Type II alveolar cells by SARS-CoV-2 infection is amplified by infection of the large numbers of spatially contiguous Type II cells supplied by the proliferative reparative response.\nC_LIO_LIInterferon-negative infected cells and interferon-positive uninfected cells succumb to inflammatory forms of cell death, TNF-induced necroptosis, BTK-induced pyroptosis, and PANoptosis.\nC_LIO_LIAll of the cell death pathway components, including a recently identified NINJ1 component, are localized in a PANoptosome latticework that empties in distinctive patterns to generate morphologically distinguishable cell remnants.\nC_LIO_LIEarly combination treatment with inhibitors of SARS-CoV-2 replication, TNF and BTK could reduce the losses of Type II cells and preserve a reparative response to regenerate functional alveoli.\nC_LI", + "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Victor Barozi", - "author_inst": "Rhodes University" + "author_name": "Luca Schifanella", + "author_inst": "University of Minnesota" }, { - "author_name": "Adrienne L Edkins", - "author_inst": "Rhodes University" + "author_name": "Jodi Anderson", + "author_inst": "University of Minnesota" }, { - "author_name": "Ozlem Tastan Bishop", - "author_inst": "Rhodes University" + "author_name": "Garritt Wieking", + "author_inst": "University of Minnesota" + }, + { + "author_name": "Peter J Southern", + "author_inst": "University of Minnesota" + }, + { + "author_name": "Spinello Antinori", + "author_inst": "University of Milan" + }, + { + "author_name": "Masssimo Galli", + "author_inst": "University of Milan" + }, + { + "author_name": "Mario Corbellino", + "author_inst": "University of Milan" + }, + { + "author_name": "Alessia Lai", + "author_inst": "University of Milan" + }, + { + "author_name": "Nichole Klatt", + "author_inst": "University of Minnesota" + }, + { + "author_name": "Timothy Schacker", + "author_inst": "University of Minnesota" + }, + { + "author_name": "Ashley T. Haase", + "author_inst": "University of Minnesota" } ], "version": "1", "license": "cc_by_nc_nd", "type": "new results", - "category": "bioinformatics" + "category": "immunology" }, { "rel_doi": "10.1101/2022.08.08.503075", @@ -227578,37 +227373,77 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.08.03.22278013", - "rel_title": "Spatio-temporal characteristics of the SARS-CoV-2 Omicron variant spread at fine geographical scales, and comparison to earlier variants", + "rel_doi": "10.1101/2022.08.02.22278212", + "rel_title": "One Health Genomic Surveillance and Response to a University-Based Outbreak of the SARS-CoV-2 Delta AY.25 Lineage, Arizona, 2021", "rel_date": "2022-08-04", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.08.03.22278013", - "rel_abs": "For the long term control of an infectious disease such as COVID-19, it is crucial to identify the most likely individuals to become infected and the role that differences in demographic characteristics play in the observed patterns of infection. As high-volume surveillance winds down, testing data from earlier periods are invaluable for studying risk factors for infection in detail. Observed changes in time during these periods may then inform how stable the pattern will be in the long term.\n\nTo this end we analyse the distribution of cases of COVID-19 across Scotland in 2021, where the location (census areas of order 500-1,000 residents) and reporting date of cases are known. We consider over 450,000 individually recorded cases, in two infection waves triggered by different lineages: B.1.1.529 (\"Omicron\") and B.1.617.2 (\"Delta\"). We use random forests, informed by measures of geography, demography, testing and vaccination. We show that the distributions are only adequately explained when considering multiple explanatory variables, implying that case heterogeneity arose from a combination of individual behaviour, immunity, and testing frequency.\n\nDespite differences in virus lineage, time of year, and interventions in place, we find the risk factors remained broadly consistent between the two waves. Many of the observed smaller differences could be reasonably explained by changes in control measures.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.08.02.22278212", + "rel_abs": "Large scale outbreaks of the SARS-CoV-2 Delta variant have occurred in numerous settings, including universities. An outbreak of the SARS-CoV-2 Delta AY.25 lineage associated with a university campus with multiple transmission events was identified; genomic analyses characterized this outbreak and complemented contract tracing and wastewater surveillance strategies that strengthened overall public health response actions.\n\nEpidemiologic and clinical data routinely gathered through contact tracing and public health investigations were matched to genomic sequencing of SARS-CoV-2 positive samples belonging to a suspect cluster identified through ongoing phylogenomic analyses. Continued phylogenetic analyses were conducted to describe the AY.25 outbreak. Wastewater collected twice weekly from sites across campus was tested for SARS-CoV-2 by RT-qPCR, and subsequently sequenced to identify variants.\n\nThe AY.25 outbreak was defined by a single mutation (C18804T) and comprised 379 genomes from SARS-CoV-2 positive cases associated with the university and community. Several undergraduate student gatherings and congregate living settings on campus likely contributed to the rapid spread of COVID-19 across the university with secondary transmission into the community. The clade defining mutation was also found in wastewater samples collected from around student dormitories during \"move-in\", a week before the semester began, and 9 days before cases were identified.\n\nGenomic, epidemiologic, and wastewater surveillance provided evidence that an AY.25 clone was likely imported into the university setting just prior to the onset of the Fall 2021 semester, rapidly spread through a subset of the student population, and then subsequent spillover occurred in the surrounding community. The university and local public health department worked closely together to facilitate timely reporting of cases, identification of close contacts, and other necessary response and mitigation strategies. The emergence of new SARS-CoV-2 variants and potential threat of other infectious disease outbreaks on university campuses presents an opportunity for future comprehensive One Health genomic data driven, targeted interventions.", + "rel_num_authors": 15, "rel_authors": [ { - "author_name": "Anthony J Wood", - "author_inst": "The Roslin Institute, University of Edinburgh" + "author_name": "Hayley Yaglom", + "author_inst": "Translational Genomics Research Institute" }, { - "author_name": "Aeron R Sanchez", - "author_inst": "The Roslin Institute, University of Edinburgh" + "author_name": "Matthew Maurer", + "author_inst": "Coconino County Health and Human Services" }, { - "author_name": "Paul R Bessell", - "author_inst": "The Roslin Institute, University of Edinburgh" + "author_name": "Brooke Collins", + "author_inst": "Coconino County Health and Human Services" }, { - "author_name": "Rebecca Wightman", - "author_inst": "Edinburgh Medical School, University of Edinburgh" + "author_name": "Jacob D Hojnacki", + "author_inst": "Coconino County Health and Human Services" }, { - "author_name": "Rowland R Kao", - "author_inst": "Royal (Dick) School of Veterinary Studies, University of Edinburgh" + "author_name": "Juan Monroy-Nieto", + "author_inst": "Translational Genomics Research Institute" + }, + { + "author_name": "Jolene R Bowers", + "author_inst": "Translational Genomics Research Institute" + }, + { + "author_name": "Samuel D Packard", + "author_inst": "Coconino County Health and Human Services" + }, + { + "author_name": "Daryn E. Erickson", + "author_inst": "Translational Genomics Research Institute" + }, + { + "author_name": "Zachary A Barrand", + "author_inst": "Translational Genomics Research Institute" + }, + { + "author_name": "Kyle M Simmons", + "author_inst": "Translational Genomics Research Institute" + }, + { + "author_name": "Breezy N Brock", + "author_inst": "Translational Genomics Research Institute" + }, + { + "author_name": "Efrem S Lim", + "author_inst": "Arizona State University" + }, + { + "author_name": "Sandra Smith", + "author_inst": "Northern Arizona University" + }, + { + "author_name": "Crystal M Hepp", + "author_inst": "Translational Genomics Research Institute" + }, + { + "author_name": "David M Engelthaler", + "author_inst": "Translational Genomics Research Institute" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -229444,47 +229279,75 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2022.08.01.22278262", - "rel_title": "An integrated epidemiologic and economic model to assess optimal COVID-19 pandemic policy", + "rel_doi": "10.1101/2022.08.02.22277351", + "rel_title": "Development, testing and validation of a SARS-CoV-2 multiplex panel for detection of the five major variants of concern on a portable PCR platform", "rel_date": "2022-08-02", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.08.01.22278262", - "rel_abs": "AO_SCPLOWBSTRACTC_SCPLOWO_ST_ABSBackgroundC_ST_ABSIdentifying optimal COVID-19 policies is challenging. For Victoria, Australia (6.6 million people), we evaluated 104 policy packages (two levels of stringency of public health and social measures [PHSMs], by two levels each of mask-wearing and respirator provision during large outbreaks, by 13 vaccination schedules) for nine future SARS-CoV-2 variant scenarios.\n\nMethodsWe used an agent-based model to estimate morbidity, mortality, and costs over 12 months from October 2022 for each scenario. The 104 policies (each averaged over the nine future variant scenarios) were ranked based on four evenly weighted criteria: cost-effectiveness from (a) health system only and (b) health system plus GDP perspectives, (c) deaths and (d) days exceeding hospital occupancy thresholds.\n\nFindingsMore compared to less stringent PHSMs reduced cumulative infections, hospitalisations and deaths but also increased time in stage [≥]3 PHSMs. Any further vaccination from October 2022 decreased hospitalisations and deaths by 12% and 27% respectively compared to no further vaccination and was usually a cost-saving intervention from a health expenditure plus GDP perspective. High versus low vaccine coverage decreased deaths by 15% and reduced time in stage [≥]3 PHSMs by 20%. The modelled mask policies had modest impacts on morbidity, mortality, and health system pressure. The highest-ranking policy combination was more stringent PHSMs, two further vaccine doses (an Omicron-targeted vaccine followed by a multivalent vaccine) for [≥]30-year-olds with high uptake, and promotion of increased mask wearing (but not Government provision of respirators).\n\nInterpretationOngoing vaccination and PHSMs continue to be key components of the COVID-19 pandemic response. Integrated epidemiologic and economic modelling, as exemplified in this paper, can be rapidly updated and used in pandemic decision making.\n\nFundingAnonymous donation, University of Melbourne funding.\n\nAO_SCPLOWBSTRACTC_SCPLOW\n\nBackgroundIdentifying optimal COVID-19 policies is challenging. For Victoria, Australia (6.6 million people), we evaluated 104 policy packages: (a) two levels of stringency of public health and social measures (PHSMs; lower, higher), by (b) two levels each of mask wearing (low, high) and Government respirator provision (nil, yes) during large outbreaks (defined as when the projected number of people in hospital reached >270 or >130 per million population for lower and higher stringency PHSM settings respectively), by (c) 13 vaccination schedules (nil, and four combinations of low/high coverage for [≥]30/60-year-olds, each with an Omicron-targeted (OT) booster in the last quarter of 2022 followed by one of: nil, another OT booster in the second quarter of 2023, or a multivalent booster in the second quarter of 2023). These policies were modelled in the setting of nine future SARS-CoV-2 variant scenarios (no major new variant of concern and one of eight variants arriving in November 2022 with different virulence, antigenic, and immune escape profiles).\n\nMethodsWe used an agent-based model to estimate morbidity, mortality, and costs over 12 months from October 2022 for each scenario. The 104 policies (each averaged over the nine future variant scenarios) were ranked based on four evenly weighted criteria: cost-effectiveness from (a) health system only and (b) health system plus GDP perspectives (HALYs valued at AUD 70,000; discount rate 3%), (c) deaths and (d) days exceeding hospital occupancy thresholds.\n\nFindingsMore compared to less stringent PHSMs reduced cumulative infections, hospitalisations and deaths by an average of 25%, 24% and 24% respectively across 468 policy comparisons (other policy and variant scenarios held constant), but also increased time in stage [≥]3 (out of 5) PHSMs by an average of 42 days (23 days for low virulence and 70 days for high virulence variants).\n\nAny further vaccination from October 2022 decreased hospitalisations and deaths by 12% and 27% respectively compared to no further vaccination, however the cumulative number of infections increased by 10% due to vaccination preferentially decreasing hospitalisation rates that were used to dynamically set PHSM stages. Any further vaccination was of marginal cost-effectiveness from a health system perspective (an average of AUD 77,500 per HALY gained for vaccinating [≥]60-year-olds, and AUD 41,600 for 30- to 59-year-olds incremental to [≥]60-year-olds), but vaccination also resulted in 36% fewer days in Stage [≥]3 PHSMs usually making it a cost-saving intervention from a health expenditure plus GDP perspective. High versus low vaccine coverage reduced deaths by 15% and reduced time in Stage [≥]3 PHSMs by 20%.\n\nPromotion to increase mask wearing or government provision of respirators during large outbreaks reduced cumulative infections, hospitalisations and deaths over the 12 months by 1% to 2%, and reduced days with hospital occupancy exceeding 750 COVID-19 patients by 2% (4% to 5% in the context of highly virulent variants).\n\nThe highest-ranking policy combination was more stringent PHSMs, two further vaccine doses (an Omicron-targeted vaccine followed by a multivalent vaccine) for [≥]30-year-olds with high uptake, and promotion of increased mask wearing (but not Government provision of respirators).\n\nInterpretationOngoing vaccination and PHSMs continue to be key components of the COVID-19 pandemic response. Integrated epidemiologic and economic modelling, as exemplified in this paper, can be rapidly updated and used in pandemic decision making.\n\nFundingAnonymous donation, University of Melbourne funding.\n\nRO_SCPLOWESEARCHC_SCPLOWO_SCPCAP C_SCPCAPO_SCPLOWINC_SCPLOWO_SCPCAP C_SCPCAPO_SCPLOWCONTEXTC_SCPLOW\n\nEvidence before this studyWe searched Ovid MEDLINE to 28 July 2022 for studies using the terms (economic evaluation.mp. OR cost effectiveness.mp. OR health economic*.mp.) AND (simulation.mp. OR model*.mp.) AND pandemic*.mp. to identify existing simulation modelling analyses of pandemic preparedness and response that incorporated cost effectiveness considerations. All identified literature examined pandemic influenza and COVID-19 and was highly heterogeneous in terms of modelled interventions (which included school closures, masks, hand hygiene, vaccination, testing strategies, antiviral medication, physical distancing measures, indoor ventilation, and personal protective equipment), quality, context, model structure, and economic evaluation approach.\n\nSystematic reviews of COVID-19 modelling studies that include a health economic component generally indicate that SARS-CoV-2 testing, personal protective equipment, masks, and physical distancing measures are cost-effective. However, few prior studies consider optimal packages of interventions (as opposed to standalone interventions), and none explicitly account for ongoing viral evolution or accurately capture the complexities of vaccine- or natural infection-derived immunity to SARS-CoV-2.\n\nFor example, a previous study integrating a dynamic SARS-CoV-2 transmission model with an economic analysis using a net monetary benefit approach published in early 2021 emphasized the combined public health and economic advantages of COVID-19 vaccination combined with physical distancing measures in the UK. However, considering current knowledge regarding the substantial waning of vaccine effectiveness and relatively low protection against infection conferred by vaccination (compared to more severe clinical outcomes), this model likely over-estimated the impact of COVID-19 vaccination on viral transmission. Scenarios that considered the emergence of SARS-CoV-2 variants of concern and thus associated changes in viral transmissibility, immune escape capacity (which has, in the case of the Omicron variant, greatly reduced protection following vaccination and prior infection) or virulence were also not modelled.\n\nAdded value of this studyTo our knowledge, our study is the first that utilises a dynamic disease transmission model combined with an integrated economic evaluation framework to systematically compare COVID-19 policy intervention packages while accounting for ongoing SARS-CoV-2 evolution and waning population immunity. At a high-level, we found that a considerable degree of COVID-19 disease burden should be expected in the future, with modelled interventions only able to partly mitigate pandemic-associated morbidity and mortality in the medium-term.\n\nAcross nine plausible future SARS-CoV-2 variant scenarios, higher stringency PHSMs notably reduced cumulative infections, hospitalisations and deaths in the 12-month period modelled but had the tradeoff of higher expected societal economic losses. Increasing community mask-wearing and substituting cloth and surgical masks for government supplied respirators during periods of high SARS-CoV-2 morbidity both reduced the number of days with hospital occupancy exceeding 750 COVID-19 patients by 2% on average across scenarios, and minimally reduced the cumulative infection, hospitalization and death burden. Compared to no further vaccines, the modelled vaccination schedules (with next-generation vaccines; one or two further doses) reduced hospitalisations by an average of 12%, and deaths by 27%. Vaccinating [≥]30-year-olds was modestly superior to just vaccinating [≥]60-year-olds (reducing cumulative deaths, for example, by 3.1%).\n\nConsidering all policy options together, and ranking by optimality on cost-effectiveness, health system pressure and deaths, the highest ranking policy combinations tended to be a mix of higher stringency PHSMs, promotion to increase mask wearing but no Government-funded respirator provision during large outbreaks, and the administration of two booster vaccine doses within the 12-month period to [≥]30-year-olds with associated high coverage (noting gains from vaccinating [≥]30-year-olds compared to [≥]60-year-olds were modest).\n\nImplications of all the available evidenceThe policy implications of this study are three-fold. Firstly, it reinforces the cost-effectiveness of ongoing vaccination of the public to mitigate morbidity and mortality associated with COVID-19. Secondly, the characteristics of emerging SARS-CoV-2 variants, outside the control of policy makers, will likely substantially influence public health outcomes associated with the pandemic in the future. Finally, at a phase of the pandemic characterised by growing intervention options urgently requiring prioritisation by decision makers alongside a large degree of ongoing uncertainty about future variants, this study provides a framework within which to systematically compare the health and economic benefits and burdens of packages of interventions that can be rapidly updated with new information (such as estimated effectiveness and waning kinetics of newly-developed vaccines) to support policy making.", - "rel_num_authors": 7, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.08.02.22277351", + "rel_abs": "Many SARS-CoV-2 variants have emerged during the course of the COVID-19 pandemic. These variants have acquired mutations conferring phenotypes such as increased transmissibility or virulence, or causing diagnostic, therapeutic, or immune escape. Detection of Alpha and the majority of Omicron sublineages by PCR relied on the so-called S gene target failure due to the deletion of six nucleotides coding for amino acids 69-70 in the spike (S) protein. Detection of hallmark mutations in other variants present in samples relied on whole genome sequencing. However, whole genome sequencing as a diagnostic tool is still in its infancy due to geographic inequities in sequencing capabilities, higher cost compared to other molecular assays, longer turnaround time from sample to result, and technical challenges associated with producing complete genome sequences from samples that have low viral load and/or high background. Hence, there is a need for rapid genotyping assays. In order to rapidly generate information on the presence of a variant in a given sample, we have created a panel of four triplex RT-qPCR assays targeting 12 mutations to detect and differentiate all five variants of concern: Alpha, Beta, Gamma, Delta and Omicron. We also developed an expanded pentaplex assay that can reliably distinguish among the major sublineages (BA.1-BA.5) of Omicron. In silico, analytical and clinical testing of the variant panel indicate that the assays overall exhibit high sensitivity and specificity. This variant panel can be used as a Research Use Only screening tool for triaging SARS-CoV-2 positive samples prior to whole genome sequencing.", + "rel_num_authors": 14, "rel_authors": [ { - "author_name": "Joshua Szanyi", - "author_inst": "Melbourne School of Population and Global Health, The University of Melbourne" + "author_name": "Bryce J Stanhope", + "author_inst": "Biomeme" }, { - "author_name": "Tim Wilson", - "author_inst": "Melbourne School of Population and Global Health, The University of Melbourne" + "author_name": "Brittany Peterson", + "author_inst": "MRIGlobal" }, { - "author_name": "Samantha Howe", - "author_inst": "Melbourne School of Population and Global Health, The University of Melbourne" + "author_name": "Brittany Knight", + "author_inst": "MRIGlobal" }, { - "author_name": "Jessie Zeng", - "author_inst": "Melbourne School of Population and Global Health, The University of Melbourne" + "author_name": "Ray Decadiz", + "author_inst": "Naval Health Research Center (NHRC)" }, { - "author_name": "Hassan Andrabi", - "author_inst": "Melbourne School of Population and Global Health, The University of Melbourne" + "author_name": "Roger Pan", + "author_inst": "Naval Health Research Center (NHRC)" }, { - "author_name": "Shania Rossiter", - "author_inst": "Melbourne School of Population and Global Health, The University of Melbourne" + "author_name": "Phillip Davis", + "author_inst": "MRIGlobal" }, { - "author_name": "Tony Blakely", - "author_inst": "Melbourne School of Population and Global Health, The University of Melbourne" + "author_name": "Anne Fraser", + "author_inst": "Naval Health Research Center (NHRC)" + }, + { + "author_name": "Manunya Nuth", + "author_inst": "Biomeme" + }, + { + "author_name": "Jesse vanWestrienen", + "author_inst": "Biomeme" + }, + { + "author_name": "Erik Wendlandt", + "author_inst": "Integrated DNA Technologies (IDT)" + }, + { + "author_name": "Bruce G Goodwin", + "author_inst": "Joint Program Executive Office for Chemical, Biological, Radiological and Nuclear Defense (JPEO-CBRND), Enabling Biotechnologies" + }, + { + "author_name": "Christopher Myers", + "author_inst": "Naval Health Research Center (NHRC)" + }, + { + "author_name": "Jennifer J Stone", + "author_inst": "MRIGlobal" + }, + { + "author_name": "Shanmuga Sozhamannan", + "author_inst": "JPEO (CBRND), JPL-Enabling Biotechnologies" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2022.08.01.22278278", @@ -231186,77 +231049,57 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.07.28.22278142", - "rel_title": "Priority age targets for COVID-19 vaccination in Ethiopia under limited vaccine supply", + "rel_doi": "10.1101/2022.07.28.22278141", + "rel_title": "Seroprevalence of anti-SARS-CoV-2 IgG antibodies in Tyrol, Austria: Updated analysis involving 22,607 blood donors covering the period October 2021 to April 2022", "rel_date": "2022-07-31", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.07.28.22278142", - "rel_abs": "BackgroundThe worldwide inequitable access to vaccination claims for a re-assessment of policies that could minimize the COVID-19 burden in low-income countries. An illustrative example is what occurred in Ethiopia, where nine months after the launch of the national vaccination program in March 2021, only 3% of the population received two doses of COVID-19 vaccine. In the meantime, a new wave of cases caused by the emergence of Delta variant of SARS-CoV-2 was observed between July and November 2021.\n\nMethodsWe used a SARS-CoV-2 transmission model to estimate the level of immunity accrued before the launch of vaccination in the Southwest Shewa Zone (SWSZ) and to evaluate the impact of alternative age priority vaccination targets in a context of limited vaccine supply. The model was informed with available epidemiological evidence and detailed contact data collected across different socio-demographic settings.\n\nResultsWe found that, during the first year of the pandemic, 46.1-58.7% of SARS-CoV-2 infections and 24.9-48% of critical cases occurred in SWSZ were likely associated with infectors under 30 years of age. During the Delta wave, the contribution of this age group in causing critical cases was estimated to increase to 66.7-70.6%. However, our findings suggest that, when considering the vaccine product available at the time (ChAdOx1 nCoV-19; 65% efficacy against infection after 2 doses), prioritizing the elderly for vaccination remained the best strategy to minimize the disease burden caused by Delta, irrespectively to the number of available doses. Vaccination of all individuals aged 50{square}years or older would have averted 40 (95%CI: 18-60), 90 (95%CI: 61-111), and 62 (95%CI: 21-108) critical cases per 100,000 residents in urban, rural, and remote areas, respectively. Vaccination of all individuals aged 30{square}years or more would have averted an average of 86-152 critical cases per 100,000 individuals, depending on the setting considered.\n\nConclusionsDespite infections among children and young adults likely caused 70% of critical cases during the Delta wave in SWSZ, most vulnerable ages should remain a key priority target for vaccination against COVID-19.", - "rel_num_authors": 15, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.07.28.22278141", + "rel_abs": "BackgroundBecause a large proportion of the Austrian population has been infected with SARS-CoV-2 during high incidence periods in winter 2021/2022, up-to-date estimates of seroprevalence of anti-SARS-CoV-2 antibodies are required to inform upcoming public health policies.\n\nMethodsWe quantified anti-Spike IgG antibody levels in 22,607 individuals that donated blood between October 2021 and April 2022 across Tyrol, Austria (participation rate: 96.0%).\n\nResultsMedian age of participants was 45.3 years (IQR: 30.9-55.1); 41.9% were female. From October 2021 to April 2022, seropositivity increased from 84.9% (95% CI: 83.8-86.0%) to 95.8% (94.9-96.4%) and the geometric mean anti-Spike IgG levels among seropositive participants increased from 283 (95% CI: 271-296) to 1437 (1360-1518) BAU/mL. The percentages of participants in categories with undetectable levels, and detectable levels at <500, 500-<1000, 1000-<2000, 2000-<3000, and [≥]3,000 BAU/mL were 15%, 54%, 15%, 10%, 3%, and 3% in October 2021 vs. 4%, 18%, 17%, 18%, 11%, and 32% in April 2022. Of 2711 participants that had repeat measurements taken a median 4.2 months apart, 61.8% moved to a higher, 13.9% to a lower, and 24.4% remained in the same category. Among seropositive participants, antibody levels were 16.8-fold in vaccinated individuals compared to unvaccinated individuals (95% CI: 14.2-19.9; p-value < 0.001).\n\nConclusionAnti-SARS-CoV-2 seroprevalence in terms of seropositivity and average antibody levels has increased markedly during the winter 2021/2022 SARS-CoV-2 waves in Tyrol, Austria.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Margherita Galli", - "author_inst": "Fondazione Bruno Kessler" - }, - { - "author_name": "Agnese Zardini", - "author_inst": "Fondazione Bruno Kessler" - }, - { - "author_name": "Worku Nigussa Gamshie", - "author_inst": "Doctors with Africa CUAMM" - }, - { - "author_name": "Stefano Santini", - "author_inst": "Doctors with Africa CUAMM" - }, - { - "author_name": "Ademe Tsegaye", - "author_inst": "Doctors with Africa CUAMM" - }, - { - "author_name": "Filippo Trentini", - "author_inst": "Bocconi University" + "author_name": "Lisa Seekircher", + "author_inst": "Clinical Epidemiology Team, Medical University of Innsbruck, Innsbruck, Austria" }, { - "author_name": "Valentina Marziano", - "author_inst": "Fondazione Bruno Kessler" + "author_name": "Anita Siller", + "author_inst": "Central Institute for Blood Transfusion and Immunology, Tirol Kliniken GmbH, Innsbruck, Austria" }, { - "author_name": "Giorgio Guzzetta", - "author_inst": "Fondazione Bruno Kessler" + "author_name": "Manfred Astl", + "author_inst": "Central Institute for Blood Transfusion and Immunology, Tirol Kliniken GmbH, Innsbruck, Austria" }, { - "author_name": "Mattia Manica", - "author_inst": "Fondazione Bruno Kessler" + "author_name": "Lena Tschiderer", + "author_inst": "Clinical Epidemiology Team, Medical University of Innsbruck, Innsbruck, Austria" }, { - "author_name": "Valeria d'Andrea", - "author_inst": "Fondazione Bruno Kessler" + "author_name": "Gregor A Wachter", + "author_inst": "Central Institute for Blood Transfusion and Immunology, Tirol Kliniken GmbH, Innsbruck, Austria" }, { - "author_name": "Giovanni Putoto", - "author_inst": "Doctors with Africa CUAMM" + "author_name": "Bernhard Pfeifer", + "author_inst": "Tyrolean Federal Institute for Integrated Care, Tirol Kliniken GmbH, Innsbruck, Austria, and Division for Healthcare Network and Telehealth, UMIT-Private Univer" }, { - "author_name": "Fabio Manenti", - "author_inst": "Doctors with Africa CUAMM" + "author_name": "Andreas Huber", + "author_inst": "Tyrolean Federal Institute for Integrated Care, Tirol Kliniken GmbH, Innsbruck, Austria" }, { - "author_name": "Marco Ajelli", - "author_inst": "Indiana University School of Public Health, Bloomington, US" + "author_name": "Manfred Gaber", + "author_inst": "Blood donor service Tyrol of the Austrian Red Cross, Rum, Austria" }, { - "author_name": "Piero Poletti", - "author_inst": "Bruno Kessler Foundation" + "author_name": "Harald Schennach", + "author_inst": "Central Institute for Blood Transfusion and Immunology, Tirol Kliniken GmbH, Innsbruck, Austria" }, { - "author_name": "Stefano Merler", - "author_inst": "Fondazione Bruno Kessler" + "author_name": "Peter Willeit", + "author_inst": "Clinical Epidemiology Team, Medical University of Innsbruck, Innsbruck, Austria, and Department of Public Health and Primary Care, University of Cambridge, Camb" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -232988,39 +232831,87 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2022.07.28.22278138", - "rel_title": "An agent-based modelling framework for assessing SARS-CoV-2 indoor airborne transmission risk", + "rel_doi": "10.1101/2022.07.29.502072", + "rel_title": "Infection- or vaccine mediated immunity reduces SARS-CoV-2 transmission, but increases competitiveness of Omicron in hamsters", "rel_date": "2022-07-29", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.07.28.22278138", - "rel_abs": "We develop a framework for modelling the risk of infection from airborne Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) in well-mixed environments in the presence of interventions designed to reduce infection risk. Our framework allows development of models that are highly tailored to the specifics of complex indoor environments, including layout, people movements, and ventilation. We explore its utility through case studies, two of which are based on actual sites.\n\nOur results reflect previously quantified benefits of masks and vaccinations. We also produce quantitative estimates of the effects of air filters, and reduced indoor occupancy for which we cannot find quantitative estimates but for which positive benefits have been postulated.\n\nWe find that increased airflow reduces risk due to dilution, even if that airflow is via recirculation in a large space. Our case studies have identified interventions which seem to generalise, and others which seem to be dependent on site-specific factors, such as occupant density.", - "rel_num_authors": 5, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2022.07.29.502072", + "rel_abs": "Omicron has demonstrated a competitive advantage over Delta in vaccinated people. To understand this, we designed a transmission chain experiment using naive, intranasally (IN) or intramuscularly (IM) vaccinated, and previously infected (PI) hamsters. Vaccination and previous infection protected animals from disease and virus replication after Delta and Omicron dual challenge. A gradient in transmission blockage was observed: IM vaccination displayed moderate transmission blockage potential over three airborne chains (approx. 70%), whereas, IN vaccination and PI blocked airborne transmission in >90%. In naive hamsters, Delta completely outcompeted Omicron within and between hosts after dual infection in onward transmission. Although Delta also outcompeted Omicron in the vaccinated and PI transmission chains, an increase in Omicron competitiveness was observed in these groups. This correlated with the increase in the strength of the humoral response against Delta, with the strongest response seen in PI animals. These data highlight the continuous need to assess the emergence and spread of novel variants in populations with pre-existing immunity and address the additional evolutionary pressure this may exert on the virus.", + "rel_num_authors": 17, "rel_authors": [ { - "author_name": "Simon O Knapp", - "author_inst": "CSIRO" + "author_name": "Julia R Port", + "author_inst": "Laboratory of Virology, Division of Intramural Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Hamilton, MT, USA" }, { - "author_name": "Rob Dunne", - "author_inst": "CSIRO" + "author_name": "Claude Kwe Yinda", + "author_inst": "Laboratory of Virology, Division of Intramural Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Hamilton, MT, USA" }, { - "author_name": "Bruce Tabor", - "author_inst": "CSIRO" + "author_name": "Jade C Riopelle", + "author_inst": "Laboratory of Virology, Division of Intramural Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Hamilton, MT, USA" }, { - "author_name": "Roslyn I Hickson", - "author_inst": "CSIRO" + "author_name": "Zachary A Weishampel", + "author_inst": "Laboratory of Virology, Division of Intramural Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Hamilton, MT, USA" }, { - "author_name": "Simon Dunstall", - "author_inst": "CSIRO" + "author_name": "Taylor A Saturday", + "author_inst": "Laboratory of Virology, Division of Intramural Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Hamilton, MT, USA" + }, + { + "author_name": "Victoria A Avanzato", + "author_inst": "Laboratory of Virology, Division of Intramural Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Hamilton, MT, USA" + }, + { + "author_name": "Jonathan E Schukz", + "author_inst": "Laboratory of Virology, Division of Intramural Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Hamilton, MT, USA" + }, + { + "author_name": "Myndi G Holbrook", + "author_inst": "Laboratory of Virology, Division of Intramural Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Hamilton, MT, USA" + }, + { + "author_name": "Kent Barbian", + "author_inst": "Genomics Research Section, Research Technologies Branch, Division of Intramural Research, National Institute of Allergy and Infectious Diseases, National Instit" + }, + { + "author_name": "Rose Perry-Gottschalk", + "author_inst": "Rocky Mountain Visual and Medical Arts Unit, Research Technologies Branch, Division of Intramural Research, National Institute of Allergy and Infectious Disease" + }, + { + "author_name": "Elaine Haddock", + "author_inst": "Laboratory of Virology, Division of Intramural Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Hamilton, MT, USA" + }, + { + "author_name": "Criag Martens", + "author_inst": "Genomics Research Section, Research Technologies Branch, Division of Intramural Research, National Institute of Allergy and Infectious Diseases, National Instit" + }, + { + "author_name": "Carl I Shaia", + "author_inst": "Rocky Mountain Veterinary Branch, Division of Intramural Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Hamilto" + }, + { + "author_name": "Teresa Lambe", + "author_inst": "The Jenner Institute, Nuffield Department of Medicine, University of Oxford, Oxford, UK" + }, + { + "author_name": "Sarah C Gilbert", + "author_inst": "The Jenner Institute, Nuffield Department of Medicine, University of Oxford, Oxford, UK" + }, + { + "author_name": "Neeltje van Doremalen", + "author_inst": "Laboratory of Virology, Division of Intramural Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Hamilton, MT, USA" + }, + { + "author_name": "Vincent J Munster", + "author_inst": "Laboratory of Virology, Division of Intramural Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Hamilton, MT, USA" } ], "version": "1", - "license": "cc_by", - "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "license": "cc0", + "type": "new results", + "category": "microbiology" }, { "rel_doi": "10.1101/2022.07.29.502045", @@ -234754,105 +234645,45 @@ "category": "hematology" }, { - "rel_doi": "10.1101/2022.07.25.22278025", - "rel_title": "Plasma proteomics of SARS-CoV-2 infection and severity reveals impact on Alzheimer and coronary disease pathways", + "rel_doi": "10.1101/2022.07.25.22277980", + "rel_title": "Lowered quality of life in Long COVID is strongly predicted by affective symptoms and chronic fatigue syndrome which are associated with inflammatory processes during the acute infectious phase and consequent neuroimmunotoxic pathways.", "rel_date": "2022-07-25", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.07.25.22278025", - "rel_abs": "Identification of the plasma proteomic changes of Coronavirus disease 2019 (COVID-19) is essential to understanding the pathophysiology of the disease and developing predictive models and novel therapeutics. We performed plasma deep proteomic profiling from 332 COVID-19 patients and 150 controls and pursued replication in an independent cohort (297 cases and 76 controls) to find potential biomarkers and causal proteins for three COVID-19 outcomes (infection, ventilation, and death). We identified and replicated 1,449 proteins associated with any of the three outcomes (841 for infection, 833 for ventilation, and 253 for death) that can be query on a web portal (https://covid.proteomics.wustl.edu/). Using those proteins and machine learning approached we created and validated specific prediction models for ventilation (AUC>0.91), death (AUC>0.95) and either outcome (AUC>0.80). These proteins were also enriched in specific biological processes, including immune and cytokine signaling (FDR [≤] 3.72x10-14), Alzheimers disease (FDR [≤] 5.46x10-10) and coronary artery disease (FDR [≤] 4.64x10-2). Mendelian randomization using pQTL as instrumental variants nominated BCAT2 and GOLM1 as a causal proteins for COVID-19. Causal gene network analyses identified 141 highly connected key proteins, of which 35 have known drug targets with FDA-approved compounds. Our findings provide distinctive prognostic biomarkers for two severe COVID-19 outcomes (ventilation and death), reveal their relationship to Alzheimers disease and coronary artery disease, and identify potential therapeutic targets for COVID-19 outcomes.", - "rel_num_authors": 22, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.07.25.22277980", + "rel_abs": "The physio-affective phenome of Long COVID-19 is predicted by a) immune- inflammatory biomarkers of the acute infectious phase, including peak body temperature (PBT) and oxygen saturation (SpO2), and b) the subsequent activation of immune and oxidative stress pathways during Long COVID. The purpose of this study was to delineate the effects of PBT and SpO2 during acute infection, as well as increased neurotoxicity on the physical, psychological, social and environmental domains of health-related quality of life (HR-QoL) in people with Long COVID. We recruited 86 participants with Long COVID and 39 normal controls, assessed the WHO-QoL-BREF (World Health Organization Quality of Life Instrument-Abridged Version) and the physio-affective phenome of Long Covid (comprising depression, anxiety and fibromyalgia-fatigue rating scales) and measured PBT and SpO2 during acute infection, and neurotoxicity (NT, comprising serum interleukin (IL)-1{beta}, IL-18 and caspase-1, advanced oxidation protein products and myeloperoxidase, calcium and insulin resistance) in Long COVID. We found that 70.3% of the variance in HR-QoL was explained by the regression on the physio-affective phenome, lowered calcium and increased NT, whilst 61.5% of the variance in the physio-affective phenome was explained by calcium, NT, increased PBT, lowered SpO2, female sex and vaccination with Astra-Zeneca and Pfizer. The effects of PBT and SpO2 on lowered HR-QoL were mediated by increased NT and lowered calcium yielding increased severity of the physio-affective phenome which largely affects HR- QoL. In conclusion, lowered HR-Qol in Long COVID is largely predicted by the severity of neuro-immune and neuro-oxidative pathways during acute and Long COVID.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Carlos Cruchaga", - "author_inst": "Washington University School of Medicine, St Louis, MO, USA" - }, - { - "author_name": "Lihua Wang", - "author_inst": "Washington University School of Medicine, St Louis, MO, USA" - }, - { - "author_name": "Yun Ju Sung", - "author_inst": "Washington University School of Medicine, St Louis, MO, USA" - }, - { - "author_name": "Dan Western", - "author_inst": "Washington University School of Medicine, St Louis, MO, USA" - }, - { - "author_name": "Jigyasha Timsina", - "author_inst": "Washington University School of Medicine, St Louis, MO, USA" - }, - { - "author_name": "Charlie Repaci", - "author_inst": "Washington University School of Medicine, St Louis, MO, USA" - }, - { - "author_name": "Won-Min Song", - "author_inst": "Icahn Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, New York, USA" - }, - { - "author_name": "Joanne Norton", - "author_inst": "Washington University School of Medicine, St Louis, MO, USA" - }, - { - "author_name": "Pat Kohlfeld", - "author_inst": "Washington University School of Medicine, St Louis, MO, USA" - }, - { - "author_name": "John Budde", - "author_inst": "Washington University School of Medicine, St Louis, MO, USA" - }, - { - "author_name": "Sharlee Climer", - "author_inst": "University of Missouri-St. Louis, St. Louis, MO, USA" - }, - { - "author_name": "Omar H. Bbut", - "author_inst": "Washington University School of Medicine, St Louis, MO, USA" - }, - { - "author_name": "Daniel A Jacobson", - "author_inst": "Oak Ridge National Laboratory" - }, - { - "author_name": "Michael R Garvin", - "author_inst": "UT-BATTELLE, LLC-OAK RIDGE NATIONAL LAB" - }, - { - "author_name": "Alan R. Templeton", - "author_inst": "Washington University School of Medicine, St Louis, MO, USA" - }, - { - "author_name": "Shawn Campagna", - "author_inst": "University of Tennessee, Knoxville, TN, USA" + "author_name": "Michael Maes", + "author_inst": "Chulalongkorn University" }, { - "author_name": "Jane O'Halloran", - "author_inst": "Washington University in St. Louis School of Medicine" + "author_name": "Haneen Tahseen Al-Rubaye", + "author_inst": "Imam Ja'afar Al-Sadiq University, Najaf" }, { - "author_name": "Rachel Presti", - "author_inst": "Washington University School of Medicine, St Louis, MO, USA" + "author_name": "Abbas F. Almulla", + "author_inst": "Chulalongkorn university" }, { - "author_name": "Charles William Goss", - "author_inst": "Washington University in St. Louis School of Medicine" + "author_name": "Dhurgham Shihab Al-Hadrawi", + "author_inst": "Al-Najaf Center for Cardiac Surgery and Transcatheter Therapy" }, { - "author_name": "Philip A Mudd", - "author_inst": "Washington University School of Medicine" + "author_name": "Kristina Stoyanova", + "author_inst": "Medical University Plovdiv" }, { - "author_name": "Beau M. Ances", - "author_inst": "Washington University School of Medicine, St Louis, MO, USA" + "author_name": "Marta Kubera", + "author_inst": "Polish Academy of Sciences" }, { - "author_name": "Bin Zhang", - "author_inst": "Icahn School of Medicine at Mount Sinai, New York, New York, USA" + "author_name": "Hussein K Al-Hakeim", + "author_inst": "Kufa University" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -236640,37 +236471,45 @@ "category": "pediatrics" }, { - "rel_doi": "10.1101/2022.07.21.22277909", - "rel_title": "Early COVID-19 Pandemic Response in Western Visayas, Philippines", + "rel_doi": "10.1101/2022.07.19.22277801", + "rel_title": "How the Malian press treated hydroxychloroquine at the beginning of the COVID-19 pandemic", "rel_date": "2022-07-22", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.07.21.22277909", - "rel_abs": "The COVID-19 pandemic has burdened the public health system in the Philippines since January 2020. In Western Visayas (Region 6), Philippines, issues have been raised on the limitations of the governments response on testing, contact tracing, and augmentation of healthcare facilities. Using data from the Western Visayas - Regional Epidemiologic Surveillance Unit (WV - RESU) from March 20 - June 20, 2020, the following observations were made: 1) Of the 6 provinces, Iloilo had the highest % tests done per capita which may be linked to the presence of the only regional COVID-19 testing facility in the province at that time, 2) There were delays in the overall processing times for specimens from Antique and Negros Occidental which may be linked to transport logistics and/or laboratory processing, 3) Contact tracing and testing were de-linked - tracing was adequate (3,420/3,503, 97.63%), but less than 50% of these (1,668/3,420) were tested, 4) Hospital and quarantine facility capacities were still adequate, but their utilization rates needed to be monitored continuously for further augmentation, if needed. This data shows the challenges of establishing a pandemic response in one of the regions in the Philippines.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.07.19.22277801", + "rel_abs": "BackgroundThe global debate on the efficacy of hydroxychloroquine (HCQ) on COVID-19 has gone far beyond the scientific framework and has been highly politicized. These issues immediately invested the debate on HCQ and made it an object of particular crystallization. This study analyzes, through the Malian press, the echo of this debate in the national background.\n\nMethodsMixed methods design, based on a review of 452 articles about COVID-19 published by six major Malian newspapers, from January 1st to July 31st 2020. Results of a content analysis with WORDSTAT8 software were further explained by a thematic qualitative analysis using and deductive-indictive approach.\n\nResultsThe debate on HCQ has had very little echo in the Malian press despite some interest, because of a lack of anchoring and thus of a \"response\" at the national level. The national health authorities, who adopted the treatment as part of clinical trials, and the press, stayed away from both the medical and the \"ideological\" components of the debate, despite these a priori directly involved a country like Mali.\n\nConclusionsThe paper sheds light on the issues at stake in the HCQ debate based on a case study of an atypical country in terms of impacts of Covid-19. The governance of COVID helped crystallize political opposition to the presidential regime leading to a coup in August.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Pia Regina Fatima Zamora", - "author_inst": "University of San Agustin" + "author_name": "Fabrice Olivier Escot", + "author_inst": "Miseli Research Association" + }, + { + "author_name": "Kate Zinszer", + "author_inst": "Universite de Montreal" }, { - "author_name": "Jonathan Adam Rico", - "author_inst": "University of San Agustin" + "author_name": "Krystelle Abalovi", + "author_inst": "School of Public Health, University of Montreal" }, { - "author_name": "Dominic Karl Bolinas", - "author_inst": "University of the Philippines Manila" + "author_name": "Nathan Peiffer-Smadja", + "author_inst": "National Institute for Health Research Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, Imperial College London" }, { - "author_name": "Jesus Emmanuel Sevilleja", - "author_inst": "National Center for Mental Health" + "author_name": "Abdourahmane Coulibaly", + "author_inst": "Miseli Research Association" }, { - "author_name": "Romulo de Castro", - "author_inst": "University of San Agustin" + "author_name": "Adrien Saucier", + "author_inst": "School of Public Health, University of Montreal" + }, + { + "author_name": "Valery Ridde", + "author_inst": "Centre Population et Developpement (Ceped), Institut de recherche pour le developpement (IRD) Universite de Paris, ERL INSERM SAGESUD" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", "category": "public and global health" }, @@ -238342,63 +238181,59 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2022.07.19.22277798", - "rel_title": "Co-designing an intervention to strengthen vaccine uptake in Congolese migrants in the UK (LISOLO MALAMU): a participatory study protocol", + "rel_doi": "10.1101/2022.07.18.22277769", + "rel_title": "Impact of SARS-Cov-2 on Clinical Trial Unit Staff: The EPIC Observational Study", "rel_date": "2022-07-19", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.07.19.22277798", - "rel_abs": "IntroductionAdult migrants are at risk of under-immunisation and are likely to need catch-up vaccination to bring them in line with the UK schedule. The COVID-19 pandemic has highlighted and exacerbated inequities in vaccine uptake, with migrants facing additional barriers to information, low vaccine confidence, and access to vaccine services. There is a need for participatory and theory-based research that meaningfully engages underserved migrant groups to make sense of their experiences and beliefs about vaccination and uses these insights to co-produce tailored interventions which can increase uptake. COVID-19 vaccination provides a unique entry-point and opportunity to explore these issues in tandem with addressing routine immunisation gaps and developing more culturally-sensitive routine vaccination services.\n\nMethods and analysisLISOLO MALAMU ( Good Talk) is a community-based participatory research study which uses co-design, design thinking and behaviour change theory to engage adult Congolese migrants in developing a tailored intervention to increase vaccine uptake. A community-academic coalition will lead and co-design the study. The study will involve i) in-depth interviews with adult Congolese migrants (foreign-born, >18 years), ii-iii) interviews and consensus workshops with clinical, public health and community stakeholders, and iv) co-design workshops with adult Congolese migrants. Qualitative data will be analysed iteratively, using Thematic Analysis, and mapped to the Theoretical Domains Framework, with participation from the coalition in discussing and interpreting findings and selecting intervention functions to guide the co-design workshops. Sociodemographic data of interview participants will be summarised using descriptive statistics. The study will run from approximately November 2021-November 2022.\n\nEthics and disseminationEthics approval has been granted by the St Georges University Research Ethics Committee (REC reference 2021.0128). Study findings will be widely disseminated by the coalition through local community organisations in Hackney and broader academic and policy stakeholders, including a final celebration event. Recommendations for a future larger scale study and testing of prototyped interventions will be made.\n\nStrengths and limitations of this study\n\nStrengthsO_LIThis study will directly respond to ongoing calls for community-centred and participatory approaches to engaging migrants in routine and COVID-19 vaccination, by implementing a value-driven and reciprocal approach to conducting a study addressing the needs of an underserved community.\nC_LIO_LIThe target population was selected following a comprehensive systematic review of the evidence (1) and pre-engagement scoping work conducted with migrant community representatives in London, UK. (2, 3)\nC_LIO_LIIt aims to co-produce a tailored intervention to address specific barriers to, and strengthen, vaccine uptake for COVID-19 and routine vaccines in adult Congolese migrants (including MMR, Td/IPV, and HPV) as set out by UKHSA guidance (4), and has been co-designed with, and will be co-delivered by, a coalition formed of academic researchers, a council for voluntary service (a local charity which offers services and support for local voluntary and community organisations), and a Congolese community-based organisation.\nC_LI\n\nLimitationsO_LIAs this study is tailored to the Congolese migrant population, other migrants who also face barriers to vaccine uptake are not included. Whilst we can draw some conclusions about the experiences of other Black migrants who face similar historical and cultural barriers to uptake of routine and COVID-19 vaccines, our ability to generalise the findings to all migrant communities might be limited.\nC_LIO_LICo-designed intervention prototypes will not be formally implemented and evaluated in this study, however recommendations will be made so that this can be done in a future phase.\nC_LI", - "rel_num_authors": 11, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.07.18.22277769", + "rel_abs": "IntroductionClinical Trials Units (CTUs) are a key component of delivering non-commercial and commercial clinical research globally. Within the UK, CTUs are seen as a specialist and independent entity available to all researchers requiring support to setup, conduct and deliver clinical trials. Therefore, an involvement of a CTU is highly recommended by national regulators and positively accepted by funders, especially for drug and/or medical device and/or complex intervention trials.\n\nAimThis study aims to determine the challenges associated with the management of Covid-19 research managed via the CTU workforce, including the challenges associated with quality assurance, trial setup and data management. Additionally, this study will explore the by-stander effect on trial staff by way of evaluating the mental and physical health impact.\n\nMethods/ DesignThis is a mixed methods study. An online novel questionnaire survey study will be conducted among the UK CTU workforce. Quantitative data will be collected using the Qualtrics XM platform. We aim to recruit up to 1,500 CTU staff across the UK workforce. A subgroup sample will be randomly invited to take part in semi-structured interviews. Therefore, this survey will generate both quantitative and qualitative data inclusive of demographic data.\n\nResultsThe findings will inform current initiatives and identify key themes for prioritising in further research to develop robust approaches to support CTU staff, including the development of a start-re-start framework for CTUs for any future pandemics relevant to developing and delivering communicable diseases and non-communicable diseases-based research.\n\nStrengths/LimitationsThe validation of the EPIC impact questionnaire used qualitative and quantitative methods which is a strength of the study. However, the study has a single timepoint to obtain data with the secondary outcome measures to be completed at two timepoints as this is an exploratory study attempting to obtain a wider data pool.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Alison F Crawshaw Ms", - "author_inst": "St George's, University of London" - }, - { - "author_name": "Caroline Hickey Ms", - "author_inst": "Hackney CVS" + "author_name": "Peter Phiri", + "author_inst": "Southern Health NHS Foundation" }, { - "author_name": "Laura Muzinga Lutumba", - "author_inst": "Hackney Congolese Women Support Group" + "author_name": "Lucy Yardley", + "author_inst": "University of Southampton" }, { - "author_name": "Lusau Mimi Kitoko", - "author_inst": "Hackney Congolese Women Support Group" + "author_name": "Kathryn Elliot", + "author_inst": "Southern Health NHS Foundation Trust" }, { - "author_name": "Sarah Luti Nkembi", - "author_inst": "Hackney Congolese Women Support Group" + "author_name": "katharine Barnard-Kelly", + "author_inst": "Barnard Health Ltd" }, { - "author_name": "Felicity Knights", - "author_inst": "St George's, University of London" + "author_name": "Vanessa Raymont", + "author_inst": "University of Oxford" }, { - "author_name": "Yusuf Ciftci", - "author_inst": "Doctors of the World UK" + "author_name": "Shanaya Rathod", + "author_inst": "Southern Health NHS Foundation Trust" }, { - "author_name": "Lucy P Goldsmith", - "author_inst": "St George's, University of London" + "author_name": "Jington Hu", + "author_inst": "Southern University of Science and Technology" }, { - "author_name": "Tushna Vandrevala", - "author_inst": "Kingston University and St George's" + "author_name": "Heitor Cavalini", + "author_inst": "Southern Health NHS Foundation Trust" }, { - "author_name": "Alice S Forster", - "author_inst": "Our Future Health" + "author_name": "Jian Shi", + "author_inst": "Southern University of Science and Technology" }, { - "author_name": "Sally Hargreaves", - "author_inst": "St George's, University of London" + "author_name": "Gayathri Delanerolle", + "author_inst": "University of Oxford" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "health systems and quality improvement" }, { "rel_doi": "10.1101/2022.07.19.500639", @@ -240248,45 +240083,33 @@ "category": "health systems and quality improvement" }, { - "rel_doi": "10.1101/2022.07.15.22276814", - "rel_title": "Assessment of COVID-19 hospitalization risk during SARS-CoV-2 Omicron relative to Delta variant predominance, New York City, August 2021-January 2022", + "rel_doi": "10.1101/2022.07.16.22277702", + "rel_title": "Extended compartmental model for modeling COVID-19 epidemic in Slovenia", "rel_date": "2022-07-17", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.07.15.22276814", - "rel_abs": "ImportanceAssessing relative disease severity of SARS-CoV-2 variants in populations with varied vaccination and infection histories can help characterize emerging variants and support healthcare system preparedness.\n\nObjectiveTo assess COVID-19 hospitalization risk for patients infected with Omicron (BA.1 and sublineages) compared with Delta SARS-CoV-2 variants.\n\nDesignObservational cohort study.\n\nSettingNew York City Department of Health and Mental Hygiene population-based COVID-19 disease registry, linked with laboratory results, immunization registry, and supplemental hospitalization data sources.\n\nParticipantsNew York City residents with positive laboratory-based SARS-CoV-2 tests during August 2021-January 2022. A secondary analysis restricted to patients with whole-genome sequencing results, comprising 1%-18% of weekly confirmed cases.\n\nExposuresDiagnosis during periods when [≥]98% of sequencing results were Delta (August-November 2021) or Omicron (January 2022). A secondary analysis defined variant exposure using patient-level sequencing results.\n\nMain outcomes and measuresCOVID-19 hospitalization, defined as a positive SARS-CoV-2 test 14 days before or 3 days after hospital admission.\n\nResultsAmong 646,852 persons with a positive laboratory-based SARS-CoV-2 test, hospitalization risk was lower for patients diagnosed when Omicron predominated (16,025/488,053, 3.3%) than when Delta predominated (8,268/158,799, 5.2%). In multivariable analysis adjusting for demographic characteristics and prior diagnosis and vaccination status, patients diagnosed when Omicron relative to Delta predominated had 0.72 (95% confidence interval [CI]: 0.63, 0.82) times the hospitalization risk. In a secondary analysis of 55,138 patients with sequencing results, hospitalization risk was similar for patients infected with Omicron (2,042/29,866, 6.8%) relative to Delta (1,780/25,272, 7.0%) and higher among those who received two mRNA vaccine doses (adjusted relative risk 1.64, 95% CI: 1.44, 1.87).\n\nConclusions and relevanceIllness severity was lower for patients diagnosed when Omicron (BA.1 and sublineages) relative to Delta predominated. This finding was consistent after adjusting for prior diagnosis and vaccination status, suggesting intrinsic virologic properties, not population-based immunity, accounted for the lower severity. A secondary analysis demonstrated collider bias from the sequencing sampling frame changing over time in ways associated with disease severity. Investing in representative data collection is necessary to avoid bias in assessing relative disease severity as new variants emerge, immunity wanes, and additional COVID-19 vaccines are administered.", - "rel_num_authors": 7, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.07.16.22277702", + "rel_abs": "In the absence of a systematic approach to epidemiological modeling in Slovenia, various isolated mathematical epidemiological models emerged shortly after the outbreak of the COVID-19 epidemic. We present an epidemiological model adapted to the COVID-19 situation in Slovenia. The standard SEIR model was extended to distinguish between age groups, symptomatic or asymptomatic disease progression, and vaccinated or unvaccinated populations. Evaluation of the model forecasts for 2021 showed the expected behavior of epidemiological modeling: our model adequately predicts the situation up to 4 weeks in advance; the changes in epidemiologic dynamics due to the emergence of a new viral variant in the population or the introduction of new interventions cannot be predicted by the model, but when the new situation is incorporated into the model, the forecasts are again reliable. Comparison with ensemble forecasts for 2022 within the European Covid-19 Forecast Hub showed better performance of our model, which can be explained by a model architecture better adapted to the situation in Slovenia, in particular a refined structure for vaccination, and better parameter tuning enabled by the more comprehensive data for Slovenia. Our model proved to be flexible, agile, and, despite the limitations of its compartmental structure, heterogeneous enough to provide reasonable and prompt short-term forecasts and possible scenarios for various public health strategies. The model has been fully operational on a daily basis since April 2020, served as one of the models for decision-making during the COVID-19 epidemic in Slovenia, and is part of the European Covid-19 Forecast Hub.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Sharon K. Greene", - "author_inst": "New York City Department of Health and Mental Hygiene" - }, - { - "author_name": "Alison K. Levin-Rector", - "author_inst": "New York City Department of Health and Mental Hygiene" - }, - { - "author_name": "Elizabeth Luoma", - "author_inst": "New York City Department of Health and Mental Hygiene" - }, - { - "author_name": "Helly Amin", - "author_inst": "New York City Department of Health and Mental Hygiene" + "author_name": "Miha Fosnaric", + "author_inst": "University of Ljubljana, Faculty of Health Sciences" }, { - "author_name": "Emily McGibbon", - "author_inst": "New York City Department of Health and Mental Hygiene" + "author_name": "Tina Kamensek", + "author_inst": "University of Ljubljana, Faculty of Health Sciences" }, { - "author_name": "Robert W. Mathes", - "author_inst": "New York City Department of Health and Mental Hygiene" + "author_name": "Jerneja Gros", + "author_inst": "Alpineon, d.o.o." }, { - "author_name": "Shama D. Ahuja", - "author_inst": "New York City Department of Health and Mental Hygiene" + "author_name": "Janez Zibert", + "author_inst": "University of Ljubljana" } ], "version": "1", - "license": "cc0", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -242438,53 +242261,53 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.07.12.22277539", - "rel_title": "Vaccine, Booster and Natural Antibody Binding to SARS-CoV-2 Omicron (BA.1) Spike Protein and Vaccine Efficacy", + "rel_doi": "10.1101/2022.07.13.22277580", + "rel_title": "Procalcitonin for Antimicrobial Stewardship Among Cancer Patients Admitted with COVID-19", "rel_date": "2022-07-15", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.07.12.22277539", - "rel_abs": "The SARS-CoV-2 Omicron variant (BA.1) has 25 unique mutations to the Spike glycoprotein, suggesting the efficacy of current vaccines against the new variant may be seriously degraded. A fully quantitative antibody binding study was performed for Spike Omicron (SO) and original Spike (S) proteins simultaneously on three cohorts of patients: convalescent following RT-PCR-confirmed infection in early 2020, double-vaccinated at [≥]2 weeks, and vaccine boosters. The average (mode) of the booster cohort response distributions were 15.1 mg/L and 13.4 mg/L for S and SO, respectively, compared with the significantly lower double-vaccinated average, S=2.4 mg/L, SO=2.0 mg/L, and natural infections average S=2.0 mg/L, SO = 1.8 mg/L. A preliminary epitope degradation screen was performed for a panel of antibodies raised to the S1 and S2 regions of the original S protein. The panel showed significant degradation to antibody epitopes in the S1 region. Differential antibody binding of the vaccine response to S and SO suggests vaccine efficacy may be reduced by up to 50% against the Omicron variant.", + "rel_link": "https://medrxiv.org/cgi/content/short/2022.07.13.22277580", + "rel_abs": "BackgroundProcalcitonin (PCT) has been used to guide antibiotic therapy in bacterial infections. We aimed to determine the role of PCT in decreasing the duration of empiric antibiotic therapy among cancer patients admitted with COVID-19.\n\nMethodsThis retrospective study included cancer patients admitted to our institution for COVID-19 between March 1, 2020, and June 28, 2021, with a PCT test done within 72 hours after admission. Patients were divided into 2 groups: PCT <0.25 ng/ml and PCT [≥]0.25 ng/ml. We assessed pertinent cultures, antibacterial use, and duration of empiric antibacterial therapy.\n\nResultsThe study included 530 patients (median age, 62 years [range, 13-91]). All the patients had [≥]1 culture test within 7 days following admission. Patients with PCT <0.25 ng/ml were less likely to have a positive culture than were those with PCT [≥]0.25 ng/ml (6% [20/358] vs 17% [30/172]; p<0.0001). PCT <0.25 ng/ml had a high negative predictive value for bacteremia and 30-day mortality. Patients with PCT <0.25 ng/ml were less likely to receive intravenous (IV) antibiotics for >72 hours than were patients with PCT [≥]0.25 ng/ml (45% [162/358] vs 69% [119/172]; p<0.0001). Among patients with PCT <0.25 ng/ml and negative cultures, 30-day mortality was similar between those who received IV antibiotics for [≥]72 hours and those who received IV antibiotics for shorter durations (2% [2/111] vs 3% [5/176], p=0.71).\n\nConclusionsAmong cancer patients with COVID-19, PCT level <0.25 ng/ml is associated with lower likelihood of bacterial co-infection and greater likelihood of a shorter antibiotic course. In patients with PCT level <0.25 ng/ml and negative cultures, an antibiotic course of > 72 hours is unnecessary. PCT could be useful in enhancing antimicrobial stewardship in cancer patients with COVID-19.", "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Philip H James-Pemberton", - "author_inst": "University of Exeter" + "author_name": "Hiba Dagher", + "author_inst": "UT MD Anderson Cancer Center" }, { - "author_name": "Mark W Helliwell", - "author_inst": "Attomarker Ltd" + "author_name": "Anne-Marie Chaftari", + "author_inst": "UT MD Anderson Cancer Center" }, { - "author_name": "Rouslan V Olkhov", - "author_inst": "Attomarker Ltd" + "author_name": "Patricia Mulanovich", + "author_inst": "UT MD Anderson Cancer Center" }, { - "author_name": "Shivali Kohli", - "author_inst": "Attomarker Ltd" + "author_name": "Ying Jiang", + "author_inst": "UT MD Anderson Cancer Center" }, { - "author_name": "Aaron C Westlake", - "author_inst": "Attomarker Ltd" + "author_name": "Ray Hachem", + "author_inst": "UT MD Anderson Cancer Center" }, { - "author_name": "Benjamin M Farrar", - "author_inst": "Attomarker Ltd" + "author_name": "Alexandre E Malek", + "author_inst": "UT MD Anderson Cancer Center" }, { - "author_name": "Ben J Sutton", - "author_inst": "Attomarker Ltd" + "author_name": "Jovan Borjan", + "author_inst": "UT MD Anderson Cancer Center" }, { - "author_name": "Nicholas D Ager", - "author_inst": "Attomarker Ltd" + "author_name": "George M Viola", + "author_inst": "UT MD Anderson Cancer Center" }, { - "author_name": "Andrew M Shaw", - "author_inst": "University of Exeter" + "author_name": "Issam I Raad", + "author_inst": "UT MD Anderson Cancer Center" } ], "version": "1", - "license": "cc_no", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -243984,35 +243807,51 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2022.07.13.499586", - "rel_title": "Structural basis for the enhanced infectivity and immune evasion of Omicron subvariants", + "rel_doi": "10.1101/2022.07.13.499346", + "rel_title": "Nitazoxanide is a potent inhibitor of human seasonal coronaviruses acting at postentry level: effect on viral spike glycoprotein", "rel_date": "2022-07-13", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.07.13.499586", - "rel_abs": "The Omicron variants of SARS-CoV-2 have recently become the globally dominant variants of concern in the COVID-19 pandemic. At least five major Omicron sub-lineages have been characterized: BA.1, BA.2, BA.3, BA.4 and BA.5. They all possess over 30 mutations on the Spike (S) protein. Here we report the cryo-EM structures of the trimeric S proteins from the five subvariants, of which BA.4 and BA.5 share the same mutations of S protein, each in complex with the surface receptor ACE2. All three receptor binding domains of S protein from BA.2 and BA.4/BA.5 are \"up\", while the BA.1 S protein has two \"up\" and one \"down\". The BA.3 S protein displays increased heterogeneity, with the majority in the all \"up\" RBD state. The differentially preferred conformations of the S protein are consistent with their varied transmissibilities. Analysis of the well defined S309 and S2K146 epitopes reveals the underlie immune evasion mechanism of Omicron subvariants.", - "rel_num_authors": 4, + "rel_link": "https://biorxiv.org/cgi/content/short/2022.07.13.499346", + "rel_abs": "Coronaviridae is recognized as one of the most rapidly evolving virus family as a consequence of the high genomic nucleotide substitution rates and recombination. The family comprises a large number of enveloped, positive-sense single-stranded RNA viruses, causing an array of diseases of varying severity in animals and humans. To date, seven human coronaviruses (HCoV) have been identified, namely HCoV-229E, HCoV-NL63, HCoV-OC43 and HCoV-HKU1, which are globally circulating in the human population (seasonal HCoV, sHCoV), and the highly pathogenic SARS-CoV, MERS-CoV and SARS-CoV-2. Seasonal HCoV are estimated to contribute to 15-30% of common cold cases in humans; although diseases are generally self-limiting, sHCoV can sometimes cause severe lower respiratory infections, as well as enteric and neurological diseases. No specific treatment is presently available for sHCoV infections. Herein we show that the anti-infective drug nitazoxanide has a potent antiviral activity against three human endemic coronaviruses, the Alpha-coronaviruses HCoV-229E and HCoV-NL63, and the Beta-coronavirus HCoV-OC43 in cell culture with IC50 ranging between 0.05 and 0.15 g/ml and high selectivity indexes. We found that nitazoxanide does not affect HCoV adsorption, entry or uncoating, but acts at postentry level and interferes with the spike glycoprotein maturation, hampering its terminal glycosylation at an endoglycosidase H-sensitive stage. Altogether the results indicate that nitazoxanide, due to its broad-spectrum anti-coronavirus activity, may represent a readily available useful tool in the treatment of seasonal coronavirus infections.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Yaning Li", - "author_inst": "School of Life Sciences, Westlake University, Hangzhou 310024, Zhejiang Province, China. School of Life Sciences, Tsinghua University, Beijing 100084, China." + "author_name": "Sara Piacentini", + "author_inst": "University of Rome Tor Vergata" }, { - "author_name": "Yaping Shen", - "author_inst": "School of Life Sciences, Westlake University, Hangzhou 310024, Zhejiang Province, China." + "author_name": "Anna Riccio", + "author_inst": "University of Rome Tor Vergata" }, { - "author_name": "Yuanyuan Zhang", - "author_inst": "School of Life Sciences, Westlake University, Hangzhou 310024, Zhejiang Province, China." + "author_name": "Silvia Santopolo", + "author_inst": "University of Rome Tor Vergata" }, { - "author_name": "Renhong Yan", - "author_inst": "School of Life Sciences, Westlake University, Hangzhou 310024, Zhejiang Province, China" + "author_name": "Silvia Pauciullo", + "author_inst": "University of Rome Tor Vergata" + }, + { + "author_name": "Simone La Frazia", + "author_inst": "University of Rome Tor Vergata" + }, + { + "author_name": "Antonio Rossi", + "author_inst": "2Institute of Translational Pharmacology, CNR, Rome, Italy" + }, + { + "author_name": "Jean-Francois Rossignol", + "author_inst": "Romark Lc." + }, + { + "author_name": "Maria Gabriella Santoro", + "author_inst": "University of Rome Tor Vergata" } ], "version": "1", "license": "cc_no", "type": "new results", - "category": "biochemistry" + "category": "microbiology" }, { "rel_doi": "10.1101/2022.07.10.22277465", @@ -246062,105 +245901,109 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.07.07.22277353", - "rel_title": "Assessing the impact of SARS-CoV-2 lineages and mutations on patient survival", + "rel_doi": "10.1101/2022.07.07.22277128", + "rel_title": "SARS-CoV-2 Omicron BA.5: Evolving tropism and evasion of potent humoral responses and resistance to clinical immunotherapeutics relative to viral variants of concern.", "rel_date": "2022-07-10", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.07.07.22277353", - "rel_abs": "After more than two years of COVID-19 pandemic, SARS-CoV-2 still remains a global public health problem. Successive waves of infection have produced new SARS-CoV-2 variants with new mutations whose impact on COVID-19 severity and patient survival is uncertain. A total of 764 SARS-CoV-2 genomes sequenced from COVID-19 patients, hospitalized from 19th February 2020 to 30st April 2021, along with their clinical data, were used for survival analysis. A significant association of B.1.1.7, the alpha lineage, with patient mortality (Log Hazard ratio LHR=0.51, C.I.=[0.14,0.88]) was found upon adjustment by all the covariates known to affect COVID-19 prognosis. Moreover, survival analysis of mutations in the SARS-CoV-2 genome rendered 27 of them significantly associated with higher mortality of patients. Most of these mutations were located in the S, ORF8 and N proteins. This study illustrates how a combination of genomic and clinical data provide solid evidence on the impact of viral lineage on patient survival.", - "rel_num_authors": 22, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.07.07.22277128", + "rel_abs": "Genetically distinct viral variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have been recorded since January 2020. Over this time global vaccine programs have been introduced, contributing to lower COVID-19 hospitalisation and mortality rates, particularly in developed countries. In late 2021, the Omicron BA.1 variant emerged, with substantially different genetic differences and clinical effects from other variants of concern (VOC). This variant demonstrated higher numbers of polymorphisms in the gene encoding the Spike (S) protein, and it has displaced the previously dominant Delta variant. Shortly after dominating global spread in early 2022, BA.1 was supplanted by the genetically distinct Omicron lineage BA.2. A sub-lineage of BA.2, designated BA.5 has now started to dominate globally, with the potential to supplant BA.2. To address the relative threat of BA.5, we determined infectivity to particle ratios in primary nasopharyngeal samples and expanded low passage isolates in a well characterised, genetically engineered ACE2/TMPRSS2 cell line. We then assessed the impact of BA.5 infection on humoral neutralisation in vitro, in vaccinated and convalescent cohorts, using concentrated human IgG pooled from thousands of plasma donors, and licensed monoclonal antibody therapies. The infectivity of virus in primary swabs and expanded isolates revealed that whilst BA.1 and BA.2 are attenuated through ACE2/TMPRSS2, BA.5 infectivity is equivalent to that of an early 2020 circulating clade and has greater sensitivity to the TMPRSS2 inhibitor Nafamostat. As with BA.1, we observed BA.5 to significantly reduce neutralisation titres across all donors. Concentrated pooled human IgG from convalescent and vaccinated donors had greater breadth of neutralisation, although the potency was still reduced 7-fold with BA.5. Of all therapeutic antibodies tested, we observed a 14.3-fold reduction using Evusheld and 16.8-fold reduction using Sotrovimab when neutralising a Clade A versus BA.5 isolate. These results have implications for ongoing tracking and management of Omicron waves globally.", + "rel_num_authors": 23, "rel_authors": [ { - "author_name": "Carlos Loucera", - "author_inst": "Computational Medicine, Andalusian Public Foundation Progress and Health-FPS, Sevilla, 41013, Spain" + "author_name": "Anupriya Aggarwal", + "author_inst": "The Kirby Institute, University of New South Wales, New South Wales, Australia." }, { - "author_name": "Javier Perez-Florido", - "author_inst": "Computational Medicine, Andalusian Public Foundation Progress and Health-FPS, Sevilla, 41013, Spain" + "author_name": "Anouschka Akerman", + "author_inst": "The Kirby Institute, University of New South Wales, New South Wales, Australia." }, { - "author_name": "Carlos S Casimiro-Soriguer", - "author_inst": "Computational Medicine, Andalusian Public Foundation Progress and Health-FPS, Sevilla, 41013, Spain" + "author_name": "Vanessa Milogiannakis", + "author_inst": "The Kirby Institute, University of New South Wales, New South Wales, Australia." }, { - "author_name": "Francisco M Ortuno", - "author_inst": "Department of Computer Architecture and Computer Technology, University of Granada, 18011, Granada, Spain" + "author_name": "Mariana Ruiz Silva", + "author_inst": "The Kirby Institute, University of New South Wales, New South Wales, Australia." }, { - "author_name": "Rosario Carmona", - "author_inst": "Computational Medicine, Andalusian Public Foundation Progress and Health-FPS, Sevilla, 41013, Spain" + "author_name": "Gregory J Walker", + "author_inst": "University of New South Wales" }, { - "author_name": "Gerrit Bostelmann", - "author_inst": "Computational Medicine, Andalusian Public Foundation Progress and Health-FPS, Sevilla, 41013, Spain" + "author_name": "Andrea Kindinger", + "author_inst": "The Kirby Institute, University of New South Wales, New South Wales, Australia." }, { - "author_name": "Luis Javier Martinez-Gonzalez", - "author_inst": "GENYO. Centre for Genomics and Oncological Research, Pfizer/University of Granada/Andalusian Regional Government, PTS Granada, 18016 Granada, Spain" + "author_name": "Thomas Angelovich", + "author_inst": "School of Health and Biomedical Sciences, RMIT University, Bundoora, Australia" }, { - "author_name": "Dolores Dolores Munoyerro-Muniz", - "author_inst": "Subdireccion Tecnica Asesora de Gestion de la Informacion. Servicio Andaluz de Salud, 41001, Sevilla, Spain." + "author_name": "Melissa Churchill", + "author_inst": "School of Health and Biomedical Sciences, RMIT University, Bundoora, Australia" }, { - "author_name": "Roman Villegas", - "author_inst": "Subdireccion Tecnica Asesora de Gestion de la Informacion. Servicio Andaluz de Salud, 41001, Sevilla, Spain." + "author_name": "Emily Waring", + "author_inst": "RMIT" }, { - "author_name": "Jesus Rodriguez-Bano", - "author_inst": "Unidad Clinica de Enfermedades Infecciosas, Microbiologia y Medicina Preventiva, Hospital Universitario Virgen Macarena, 41009, Sevilla, Spain." + "author_name": "Supavadee Amatayakul-Chantler", + "author_inst": "Department of Bioanalytical Sciences, Plasma Product Development, Research & Development, CSL Behring AG, Bern, Switzerland." }, { - "author_name": "Manuel Romero-Gomez", - "author_inst": "Servicio de Aparato Digestivo. Hospital Universitario Virgen del Rocio. 41013, Sevilla. Spain." + "author_name": "Nathan Roth", + "author_inst": "Department of Bioanalytical Sciences, Plasma Product Development, Research & Development, CSL Behring AG, Bern, Switzerland." }, { - "author_name": "Nicola Lorusso", - "author_inst": "Direccion General de Salud Publica. Consejeria de Salud y Familias. Junta de Andalucia. 41020, Sevilla, Spain" + "author_name": "Germano Coppola", + "author_inst": "Department of Bioanalytical Sciences, Plasma Product Development, Research & Development, CSL Behring AG, Bern, Switzerland." + }, + { + "author_name": "Malinna Yeang", + "author_inst": "Serology and Virology Division (SAViD), NSW Health Pathology, Randwick, Australia." }, { - "author_name": "Javier Garcia-Leon", - "author_inst": "Departamento de Metafisica y Corrientes Actuales de la Filosofia, Etica y Filosofia Politica. Universidad de Sevilla, 41004, Sevilla, Spain" + "author_name": "Tyra Jean", + "author_inst": "Serology and Virology Division (SAViD), NSW Health Pathology, Randwick, Australia." }, { - "author_name": "Jose M Navarro-Mari", - "author_inst": "Servicio de Microbiologia, Hospital Virgen de las Nieves, 18014, Granada, Spain." + "author_name": "Charles S.P. Foster", + "author_inst": "University of New South Wales" }, { - "author_name": "Pedro Camacho-Martinez", - "author_inst": "Servicio de Microbiologia. Unidad Clinica Enfermedades Infecciosas, Microbiologia y Medicina Preventiva. Hospital Universitario Virgen del Rocio. 41013. Sevilla" + "author_name": "Alexandra Carey Hoppe", + "author_inst": "The Kirby Institute, University of New South Wales, New South Wales, Australia." }, { - "author_name": "Laura Merino-Diaz", - "author_inst": "Servicio de Microbiologia. Unidad Clinica Enfermedades Infecciosas, Microbiologia y Medicina Preventiva. Hospital Universitario Virgen del Rocio. 41013. Sevilla" + "author_name": "Mee Ling Munier", + "author_inst": "The Kirby Institute, University of New South Wales, New South Wales, Australia." }, { - "author_name": "Adolfo de Salazar", - "author_inst": "Servicio de Microbiologia. Hospital Universitario San Cecilio. 18016, Granada, Spain." + "author_name": "Daniel Christ", + "author_inst": "Garvan Institute" }, { - "author_name": "Laura Vinuela", - "author_inst": "Servicio de Microbiologia. Hospital Universitario San Cecilio. 18016, Granada, Spain." + "author_name": "David Ross Darley", + "author_inst": "St Vincent's Hospital, Sydney, New South Wales, Australia." }, { - "author_name": "- The Andalusian COVID-19 sequencing initiative", - "author_inst": "" + "author_name": "Gail Matthews", + "author_inst": "St Vincent's Hospital, Sydney, New South Wales, Australia." }, { - "author_name": "Jose A Lepe", - "author_inst": "Servicio de Microbiologia. Unidad Clinica Enfermedades Infecciosas, Microbiologia y Medicina Preventiva. Hospital Universitario Virgen del Rocio. 41013. Sevilla" + "author_name": "William D Rawlinson", + "author_inst": "Prince of Wales Hospital" }, { - "author_name": "Federico Garcia", - "author_inst": "Servicio de Microbiologia. Hospital Universitario San Cecilio. 18016, Granada, Spain." + "author_name": "Anthony D Kelleher", + "author_inst": "The Kirby Institute, University of New South Wales, New South Wales, Australia." }, { - "author_name": "Joaquin Dopazo", - "author_inst": "Computational Medicine, Andalusian Public Foundation Progress and Health-FPS, Sevilla, 41013, Spain" + "author_name": "Stuart G Turville", + "author_inst": "The Kirby Institute, University of New South Wales, New South Wales, Australia." } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -248312,53 +248155,33 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.07.06.22277066", - "rel_title": "Association between nursing home crowding and outbreak-associated respiratory infection and death prior to the COVID-19 pandemic between 2014 and 2019 in Ontario, Canada", + "rel_doi": "10.1101/2022.07.06.22277341", + "rel_title": "Prevalence and factors associated with antigen test positivity following SARS-CoV-2 infection among healthcare workers in Los Angeles", "rel_date": "2022-07-07", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.07.06.22277066", - "rel_abs": "ImportanceResident crowding in nursing homes is associated with larger SARS-CoV-2 outbreaks. However, this association has not been previously documented for non-SARS-CoV-2 respiratory infections.\n\nObjectiveWe sought to measure the association between nursing home crowding and respiratory infections in Ontario nursing homes prior to the COVID-19 pandemic.\n\nDesign, Setting, and ParticipantsWe conducted a retrospective cohort study of nursing home residents in Ontario, Canada over a five-year period prior to the COVID-19 pandemic, between September 2014 and August 2019.\n\nExposureUsing administrative data, we estimated the crowding index equal to the mean number of residents per bedroom and bathroom (residents / [0.5*bedrooms+0.5*bathrooms]).\n\nOutcomesThe incidence of outbreak-associated infections and mortality per 100 nursing home residents per year. We also examined infection and mortality outcomes for outbreaks due to 7 specific pathogens: coronaviruses (OC43, 229E, NL63, HKU1), influenza A, influenza B, human metapneumovirus, parainfluenza virus, respiratory syncytial virus, rhinovirus/enterovirus.\n\nResultsThere was one or more respiratory outbreak in 93.9% (588/626) nursing homes in Ontario. There were 4,921 outbreaks involving 64,829 cases of respiratory infection, and 1,969 deaths. Outbreaks attributable to a single identified pathogen were principally caused by influenza A (29%), rhinovirus (11.7%), influenza B (8.1%), and respiratory syncytial virus (6.1%). Among homes, 42.7% (251/588) homes had a high crowding index ([≥] 2.0). After adjustment, more crowded homes had higher outbreak-associated respiratory infection incidence (aRR 1.89; 95% 1.64-2.18) and mortality incidence (aRR 2.28; 95% 1.84-2.84). More crowded homes had higher adjusted estimates of the incidence of infection and mortality for each of the 7 respiratory pathogens examined.\n\nConclusions and RelevanceResidents of crowded nursing homes experienced more respiratory-outbreak infections and mortality due to influenza and other non-SARS-CoV-2 respiratory pathogens. Decreasing crowding in nursing homes is an important patient safety target beyond the COVID-19 pandemic.", - "rel_num_authors": 9, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.07.06.22277341", + "rel_abs": "Surges of SARS-CoV-2 infections among healthcare workers (HCWs) have led to critical staffing shortages. From January 4 to February 4, 2022, we implemented a return-to-work antigen testing program for HCWs and 870 HCWs participated. Antigen test positivity was 60.5% for those [≤]5 days from symptom onset or positive PCR and 47.4% were positive at day 7. Antigen positivity was associated with receiving a booster vaccination and being [≤]6 days from symptom onset or PCR test, but not age or a symptomatic infection. Rapid antigen testing can be a useful tool to guide return-to-work and isolation precautions for HCWs following infection.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Pamela Leece", - "author_inst": "Public Health Ontario" - }, - { - "author_name": "Michael Whelan", - "author_inst": "Public Health Ontario" - }, - { - "author_name": "Andrew P Costa", - "author_inst": "McMaster University" - }, - { - "author_name": "Nick Daneman", - "author_inst": "Public Health Ontario" - }, - { - "author_name": "Jennie Johnstone", - "author_inst": "Mount Sinai Hospital" - }, - { - "author_name": "Allison McGeer", - "author_inst": "Mount Sinai Hospital" + "author_name": "Paul C Adamson", + "author_inst": "David Geffen School of Medicine at UCLA" }, { - "author_name": "Paula Rochon", - "author_inst": "Womens College Hospital" + "author_name": "Judith S Currier", + "author_inst": "University of California Los Angeles, David Geffen School of Medicine" }, { - "author_name": "Kevin L Schwartz", - "author_inst": "Public Health Ontario" + "author_name": "Daniel Z Uslan", + "author_inst": "University of California Los Angeles, David Geffen School of Medicine" }, { - "author_name": "Kevin Antoine Brown", - "author_inst": "Public Health Ontario" + "author_name": "Omai B Garner", + "author_inst": "University of California Los Angeles, David Geffen School of Medicine" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -250246,67 +250069,31 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2022.07.02.22277186", - "rel_title": "Inferring the differences in incubation-period and generation-interval distributions of the Delta and Omicron variants of SARS-CoV-2", + "rel_doi": "10.1101/2022.07.02.22277179", + "rel_title": "Using machine learning probabilities to identify effects of COVID-19", "rel_date": "2022-07-05", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.07.02.22277186", - "rel_abs": "Estimating the differences in the incubation-period, serial-interval, and generation-interval distributions of SARS-CoV-2 variants is critical to understanding their transmission and control. However, the impact of epidemic dynamics is often neglected in estimating the timing of infection and transmission--for example, when an epidemic is growing exponentially, a cohort of infected individuals who developed symptoms at the same time are more likely to have been infected recently. Here, we re-analyze incubation-period and serial-interval data describing transmissions of the Delta and Omicron variants from the Netherlands at the end of December 2021. Previous analysis of the same data set reported shorter mean observed incubation period (3.2 days vs 4.4 days) and serial interval (3.5 days vs 4.1 days) for the Omicron variant, but the number of infections caused by the Delta variant decreased during this period as the number of Omicron infections increased. When we account for growth-rate differences of two variants during the study period, we estimate similar mean incubation periods (3.8-4.5 days) for both variants but a shorter mean generation interval for the Omicron variant (3.0 days; 95% CI: 2.7-3.2 days) than for the Delta variant (3.8 days; 95% CI: 3.7-4.0 days). We further note that the differences in estimated generation intervals may be driven by the \"network effect\"--higher effective transmissibility of the Omicron variant can cause faster susceptible depletion among contact networks, which in turn prevents late transmission (therefore shortening realized generation intervals). Using up-to-date generation-interval distributions is critical to accurately estimating the reproduction advantage of the Omicron variant.\n\nSignificanceRecent studies suggest that individuals infected with the Omicron variant develop symptoms earlier (shorter incubation period) and transmit faster (shorter generation interval) than those infected with the Delta variant. However, these studies typically neglect population-level effects: when an epidemic is growing, a greater proportion of current cases were infected recently, biasing us toward observing faster transmission events. Accounting for this dynamical bias, we find that Omicron infections from the Netherlands at the end of December 2021 had similar incubation periods, but shorter generation intervals, compared to Delta infections from the same period. Shorter generation intervals of the Omicron variant might be due to its higher effective reproduction number, which can cause faster local susceptible depletion around the contact network.", - "rel_num_authors": 12, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.07.02.22277179", + "rel_abs": "COVID-19, the disease caused by the SARS-CoV-2 virus, has had and continues to have extensive economic, social and public health impacts in the United States and around the world. To date, there have been more than 500 million reported cases of SARS-CoV-2 infection worldwide with more than 6 million reported deaths, more than 80 million of those cases and more than 1 million of those deaths have been reported in the United States. Retrospective analysis throughout the pandemic, which identified comorbidities, risk factors and treatments, has underpinned the response COVID-19. As the situation transitions from a pandemic to an endemic, retrospective analyses using electronic health records will be increasingly important to identify long term effects of COVID-19. However, these analyses can be complicated by the incompleteness of electronic health records, which in turns makes it difficult to differentiate visits where the patient has COVID-19. To address this, we trained a random forest classifier to assign a probability of a patient having been diagnosed with COVID-19 during each visit using demographic data, temporal data and visit-specific diagnoses (Training AUROC = 0.9867, Training OOB AUROC = 0.8957, Evaluation AUROC = 0.8958). Using these probabilities, we identified conditions associated with higher COVID-19 probabilities irrespective of clinical history and when accounting for previous diagnosis and estimated the hazards ratio for myocardial infarction (Hazards ratio = 121.736 (87.375, 169.611), p = 3.796E-177 and Hazards ratio = 80.262 (4.134, 4.637), p = 4.543E-256, respectively), urinary tract infection (Hazards ratio = 72.021 (58.116 - 89.253), p < 2.225E-308 and Hazards ratio = 61.380 (51.273 - 73.479), p < 2.225E-308, respectively), acute renal failure (Hazards ratio = 1.264E4 (9.278E4 - 1.724E4), p < 2.225E-308 and Hazards ratio = 6.333E3 (4.947E3 - 8.108E3), p < 2.225E-308, respectively) and type 2 diabetes (Hazards ratio = 345.730 (283.180 - 422.098), p < 2.225E-308 and Hazards ratio = 217.271 (187.898 - 251.235), p = 1.39E-22, respectively) when accounting for demographics and the ten most common clinical conditions.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Sang Woo Park", - "author_inst": "Princeton University" - }, - { - "author_name": "Kaiyuan Sun", - "author_inst": "National Institutes of Health" - }, - { - "author_name": "Sam Abbott", - "author_inst": "London School of Hygiene & Tropical Medicine" - }, - { - "author_name": "Ron Sender", - "author_inst": "Weizmann Institute of Science" - }, - { - "author_name": "Yinon M. Bar-On", - "author_inst": "Weizmann Institute of Science" - }, - { - "author_name": "Joshua S Weitz", - "author_inst": "Georgia Institute of Technology" - }, - { - "author_name": "Sebastian Funk", - "author_inst": "London School of Hygiene & Tropical Medicine" - }, - { - "author_name": "Bryan Grenfell", - "author_inst": "Princeton University" - }, - { - "author_name": "Jantien A. Backer", - "author_inst": "National Institute for Public Health and the Environment" - }, - { - "author_name": "Jacco Wallinga", - "author_inst": "National Institute for Public Health and the Environment" + "author_name": "Vijendra Ramlall", + "author_inst": "Columbia University" }, { - "author_name": "Cecile Viboud", - "author_inst": "National Institutes of Health" + "author_name": "Benjamin May", + "author_inst": "Columbia University" }, { - "author_name": "Jonathan Dushoff", - "author_inst": "McMaster University" + "author_name": "Nicholas P Tatonetti", + "author_inst": "Columbia University" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "health informatics" }, { "rel_doi": "10.1101/2022.07.03.22277183", @@ -253336,111 +253123,127 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.07.01.22277137", - "rel_title": "The decline of COVID-19 severity and lethality over two years of pandemic", + "rel_doi": "10.1101/2022.06.30.22277079", + "rel_title": "Rucaparib blocks SARS-CoV-2 virus binding to cells and interleukin-6 release in a model of COVID-19", "rel_date": "2022-07-02", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.07.01.22277137", - "rel_abs": "Undernotification of SARS-CoV-2 infections has been a major obstacle to the tracking of critical quantities such as infection attack rates and the probability of severe and lethal outcomes. We use a model of SARS-CoV-2 transmission and vaccination informed by epidemiological and genomic surveillance data to estimate the number of daily infections occurred in Italy in the first two years of pandemic. We estimate that the attack rate of ancestral lineages, Alpha, and Delta were in a similar range (10-17%, range of 95% CI: 7-23%), while that of Omicron until February 20, 2022, was remarkably higher (51%, 95%CI: 33-70%). The combined effect of vaccination, immunity from natural infection, change in variant features, and improved patient management massively reduced the probabilities of hospitalization, admission to intensive care, and death given infection, with 20 to 40-fold reductions during the period of dominance of Omicron compared to the initial acute phase.", - "rel_num_authors": 23, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.06.30.22277079", + "rel_abs": "Coronavirus disease 2019 (COVID-19), caused by SARS-CoV-2 virus, is a major global health challenge, as there is no efficient treatment for the moderate to severe disease. ADP-ribosylation events are involved in regulating the life cycle of coronaviruses and the inflammatory reactions of the host, hence we assessed the repurposing of registered PARP inhibitors for the treatment of COVID-19. We detected high levels of oxidative stress and strong PARylation in all cell types in the lungs of COVID-19 patients. Interestingly, rucaparib, unlike other PARP inhibitors, reduced SARS-CoV-2 infection rate through binding to the conserved 493-498 amino acid region located in the spike-ACE2 interface in the spike protein and prevented viruses from binding to ACE2. In addition, the spike protein-induced overexpression of IL-6, a key cytokine in COVID-19, was inhibited by rucaparib at pharmacologically relevant concentrations. These findings build a case for repurposing rucaparib for treating COVID-19 disease.", + "rel_num_authors": 27, "rel_authors": [ { - "author_name": "Valentina Marziano", - "author_inst": "Bruno Kessler Foundation" + "author_name": "Henrietta Papp Ms.", + "author_inst": "University of Pecs, Pecs, Hungary" }, { - "author_name": "Giorgio Guzzetta", - "author_inst": "Bruno Kessler Foundation" + "author_name": "Judit Bovari-Biri Ms.", + "author_inst": "University of Pecs, Pecs, Hungary" }, { - "author_name": "Francesco Menegale", - "author_inst": "University of Trento" + "author_name": "Krisztina Banfai-Biri Ms.", + "author_inst": "University of Pecs, Pecs, Hungary" }, { - "author_name": "Chiara Sacco", - "author_inst": "Istituto Superiore di Sanita" + "author_name": "Peter Juhasz Dr.", + "author_inst": "University of Debrecen, Debrecen, Hungary" }, { - "author_name": "Daniele Petrone", - "author_inst": "Istituto Superiore di Sanita" + "author_name": "Mohamed Mahdi Dr.", + "author_inst": "University of Debrecen, Debrecen, Hungary" }, { - "author_name": "Alberto Mateo Urdiales", - "author_inst": "Istituto Superiore di Sanita" + "author_name": "Lilian Christina Russo Dr.", + "author_inst": "Department of Biochemistry, Institute of Chemistry, University of Sao Paulo, Sao Paulo, Brazil" }, { - "author_name": "Martina Del Manso", - "author_inst": "Istituto Superiore di Sanita" + "author_name": "David Bajusz Dr.", + "author_inst": "Medicinal Chemistry Research Group, Research Centre for Natural Sciences, 1117, Budapest, Hungary" }, { - "author_name": "Antonino Bella", - "author_inst": "Istituto Superiore di Sanita" + "author_name": "Adrienn Sipos Dr.", + "author_inst": "University of Debrecen, Debrecen, Hungary" }, { - "author_name": "Massimo Fabiani", - "author_inst": "Istituto Superiore di Sanita" + "author_name": "Laszlo Petri Mr.", + "author_inst": "Medicinal Chemistry Research Group, Research Centre for Natural Sciences, 1117, Budapest, Hungary" }, { - "author_name": "Maria Fenicia Vescio", - "author_inst": "Istituto Superiore di Sanita" + "author_name": "Agnes Kemeny Dr.", + "author_inst": "University of Pecs, Pecs, Hungary" }, { - "author_name": "Flavia Riccardo", - "author_inst": "Istituto Superiore di Sanita" + "author_name": "Monika Madai Dr.", + "author_inst": "University of Pecs, Pecs, Hungary" }, { - "author_name": "Piero Poletti", - "author_inst": "Bruno Kessler Foundation" + "author_name": "Anett Kuczmog Dr.", + "author_inst": "University of Pecs, Pecs, Hungary" }, { - "author_name": "Mattia Manica", - "author_inst": "Bruno Kessler Foundation" + "author_name": "Gyula Batta Prof.", + "author_inst": "University of Debrecen, Debrecen, Hungary" }, { - "author_name": "Agnese Zardini", - "author_inst": "Bruno Kessler Foundation" + "author_name": "Orsolya Mozner Ms.", + "author_inst": "Institute of Enzymology, Research Centre for Natural Sciences, 1117, Budapest, Hungary" }, { - "author_name": "Valeria d'Andrea", - "author_inst": "Bruno Kessler Foundation" + "author_name": "Dorottya Vasko Ms.", + "author_inst": "Department of Organic Chemistry and Technology, Faculty of Chemical Technology and Biotechnology, Budapest University of Technology and Economics, 1111, Budapes" }, { - "author_name": "Filippo Trentini", - "author_inst": "Bocconi University" + "author_name": "Edit Hirsch Dr.", + "author_inst": "Department of Organic Chemistry and Technology, Faculty of Chemical Technology and Biotechnology, Budapest University of Technology and Economics, 1111, Budapes" }, { - "author_name": "Paola Stefanelli", - "author_inst": "Istituto Superiore di Sanita" + "author_name": "Peter Bohus Dr.", + "author_inst": "Erzsebet Hospital, Satoraljaujhely, 3980, Hungary" }, { - "author_name": "Giovanni Rezza", - "author_inst": "Ministry of Health" + "author_name": "Gabor Mehes Prof.", + "author_inst": "University of Debrecen, Debrecen, Hungary" }, { - "author_name": "Anna Teresa Palamara", - "author_inst": "Istituto Superiore di Sanita" + "author_name": "Jozsef Tozser Prof.", + "author_inst": "University of Debrecen, Debrecen, Hungary" }, { - "author_name": "Silvio Brusaferro", - "author_inst": "Istituto Superiore di Sanita" + "author_name": "Nicola J. Curtin Prof.", + "author_inst": "Translational and Clinical Research Institute, Newcastle University Centre for Cancer, Faculty of Medical Sciences, Newcastle University, NE2 4HH, Newcastle upo" }, { - "author_name": "Marco Ajelli", - "author_inst": "Indiana University School of Public Health" + "author_name": "Zsuzsanna Helyes Prof.", + "author_inst": "University of Pecs, Pecs, Hungary" }, { - "author_name": "Patrizio Pezzotti", - "author_inst": "Istituto Superiore di Sanita" + "author_name": "Attila Toth Prof.", + "author_inst": "University of Debrecen, Debrecen, Hungary" }, { - "author_name": "Stefano Merler", - "author_inst": "Bruno Kessler Foundation" + "author_name": "Nicolas Hoch Prof.", + "author_inst": "Department of Biochemistry, Institute of Chemistry, University of Sao Paulo, Sao Paulo, Brazil" + }, + { + "author_name": "Ferenc Jakab Prof.", + "author_inst": "University of Pecs, Pecs, Hungary" + }, + { + "author_name": "Gyorgy Keseru Prof.", + "author_inst": "Medicinal Chemistry Research Group, Research Centre for Natural Sciences, 1117, Budapest, Hungary" + }, + { + "author_name": "Judit E. Pongracz Prof.", + "author_inst": "University of Pecs, Pecs, Hungary" + }, + { + "author_name": "Peter Bai Prof.", + "author_inst": "University of Debrecen, Debrecen, Hungary" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "pharmacology and therapeutics" }, { "rel_doi": "10.1101/2022.06.30.22277115", @@ -254822,141 +254625,41 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2022.06.28.22276303", - "rel_title": "Effectiveness of vaccines in preventing hospitalization due to COVID-19: A multicenter hospital-based case-control study, Germany, June 2021 to January 2022", + "rel_doi": "10.1101/2022.06.28.22277028", + "rel_title": "Masks Do No More Than Prevent Transmission:Theory and Data Undermine the Variolation Hypothesis", "rel_date": "2022-06-29", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.06.28.22276303", - "rel_abs": "We included 852 patients in a prospectively recruiting multicenter matched case-control study in Germany to assess vaccine effectiveness (VE) in preventing COVID-19-associated hospitalization (Delta-variant dominance). Two-dose VE was 89% (95%CI 84-93%) overall, 79% in patients with >2 comorbidities and 77% in adults aged 60-75 years. A third dose increased VE to >93% in all patient-subgroups.", - "rel_num_authors": 31, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.06.28.22277028", + "rel_abs": "BackgroundMasking serves an important role in reducing the transmission of respiratory viruses, including SARS-CoV-2. During the COVID-19 pandemic, several perspective and review articles have also argued that masking reduces the risk of developing severe disease by reducing the inoculum dose received by the contact. This hypothesis - known as the variolation hypothesis - has gained considerable traction since its development.\n\nMethodsTo assess the plausibility of this hypothesis, we develop a quantitative framework for understanding the relationship between (i) inoculum dose and the risk of infection and (ii) inoculum dose and the risk of developing severe disease. We parameterize the mathematical models underlying this framework with parameters relevant for SARS-CoV-2 to quantify these relationships empirically and to gauge the range of inoculum doses in natural infections. We then identify and analyze relevant experimental studies of SARS-CoV-2 to ascertain the extent of empirical support for the proposed framework.\n\nResultsMathematical models, when simulated under parameter values appropriate for SARS-CoV-2, indicate that the risk of infection and the risk of developing severe disease both increase with an increase in inoculum dose. However, the risk of infection increases from low to almost certain infection at low inoculum doses (with <1000 initially infected cells). In contrast, the risk of developing severe disease is only sensitive to dose at very high inoculum levels, above 106 initially infected cells. By drawing on studies that have estimated transmission bottleneck sizes of SARS-CoV-2, we find that inoculum doses are low in natural SARS-CoV-2 infections. As such, reductions in inoculum dose through masking or greater social distancing are expected to reduce the risk of infection but not the risk of developing severe disease conditional on infection. Our review of existing experimental studies support this finding.\n\nConclusionsWe find that masking and other measures such as distancing that act to reduce inoculum doses in natural infections are highly unlikely to impact the contacts risk of developing severe disease conditional on infection. However, in support of existing empirical studies, we find that masking and other mitigation measures that reduce inoculum dose are expected to reduce the risk of infection with SARS-CoV-2. Our findings therefore undermine the plausibility of the variolation hypothesis, underscoring the need to focus on other factors such as comorbidities and host age for understanding the heterogeneity in disease outcomes for SARS-CoV-2.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Anna Stoliaroff", - "author_inst": "Robert Koch-Institute" - }, - { - "author_name": "Caroline Peine", - "author_inst": "Robert Koch-Institute" - }, - { - "author_name": "Tim Herath", - "author_inst": "Robert Koch-Institute" - }, - { - "author_name": "Johannes Lachmann", - "author_inst": "Robert Koch-Institute" - }, - { - "author_name": "Achim Doerre", - "author_inst": "Robert Koch-Institute" - }, - { - "author_name": "Delphine Perriat", - "author_inst": "Robert Koch-Institute" - }, - { - "author_name": "Andreas Nitsche", - "author_inst": "Robert Koch Institute" - }, - { - "author_name": "Janine Michel", - "author_inst": "Robert Koch-Institute" - }, - { - "author_name": "Thomas Rinner", - "author_inst": "Robert Koch-Institute" - }, - { - "author_name": "Daniel Stern", - "author_inst": "Robert Koch-Institute" - }, - { - "author_name": "Fridolin Treindl", - "author_inst": "Robert Koch-Institute" - }, - { - "author_name": "Natalie Hofmann", - "author_inst": "Robert Koch-Institute" - }, - { - "author_name": "Marica Grossegesse", - "author_inst": "Robert Koch Institute" - }, - { - "author_name": "Claudia Kohl", - "author_inst": "Robert Koch-Institute" - }, - { - "author_name": "Annika Brinkmann", - "author_inst": "Robert Koch-Institute" - }, - { - "author_name": "Tanja Meyer", - "author_inst": "Robert Koch-Institute" - }, - { - "author_name": "Brigitte Dorner", - "author_inst": "Robert Koch-Institute" - }, - { - "author_name": "Sascha Hein", - "author_inst": "Paul-Ehrlich-Institute" - }, - { - "author_name": "Laura Werel", - "author_inst": "Paul-Ehrlich-Institute" - }, - { - "author_name": "Eberhard Hildt", - "author_inst": "Paul-Ehrlich-Institute" - }, - { - "author_name": "Sven Glaeser", - "author_inst": "Vivantes Netzwerk fuer Gesundheit GmbH" - }, - { - "author_name": "Helmut Schuehlen", - "author_inst": "Vivantes Netzwerk fuer Gesundheit GmbH" - }, - { - "author_name": "Caroline Isner", - "author_inst": "Vivantes Netzwerk fuer Gesundheit GmbH" - }, - { - "author_name": "Alexander Peric", - "author_inst": "Vivantes Netzwerk fuer Gesundheit GmbH" - }, - { - "author_name": "Ammar Ghouzi", - "author_inst": "Schoen Klinik Duesseldorf" - }, - { - "author_name": "Annette Reichardt", - "author_inst": "Helios Klinikum Berlin-Buch" + "author_name": "Katia Koelle", + "author_inst": "Emory University" }, { - "author_name": "Matthias Janneck", - "author_inst": "Albertinen Krankenhaus Hamburg" + "author_name": "Jack Lin", + "author_inst": "Emory University" }, { - "author_name": "Guntram Lock", - "author_inst": "Albertinen Krankenhaus Hamburg" + "author_name": "Huisheng Zhu", + "author_inst": "Emory University" }, { - "author_name": "Lars Schaade", - "author_inst": "Robert Koch-Institute" + "author_name": "Rustom Antia", + "author_inst": "Emory University" }, { - "author_name": "Ole Wichmann", - "author_inst": "Robert Koch-Institute" + "author_name": "Anice Lowen", + "author_inst": "Emory University" }, { - "author_name": "Thomas Harder", - "author_inst": "Robert Koch-Institute" + "author_name": "Daniel Weissman", + "author_inst": "Emory University" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -256860,31 +256563,87 @@ "category": "rehabilitation medicine and physical therapy" }, { - "rel_doi": "10.1101/2022.06.24.22276853", - "rel_title": "Algorithmic Fairness and Bias Mitigation for Clinical Machine Learning: A New Utility for Deep Reinforcement Learning", + "rel_doi": "10.1101/2022.06.23.22276827", + "rel_title": "HIV and SARS-CoV-2 infection in postpartum Kenyan women and their infants", "rel_date": "2022-06-27", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.06.24.22276853", - "rel_abs": "As machine learning-based models continue to be developed for healthcare applications, greater effort is needed in ensuring that these technologies do not reflect or exacerbate any unwanted or discriminatory biases that may be present in the data. In this study, we introduce a reinforcement learning framework capable of mitigating biases that may have been acquired during data collection. In particular, we evaluated our model for the task of rapidly predicting COVID-19 for patients presenting to hospital emergency departments, and aimed to mitigate any site-specific (hospital) and ethnicity-based biases present in the data. Using a specialized reward function and training procedure, we show that our method achieves clinically-effective screening performances, while significantly improving outcome fairness compared to current benchmarks and state-of-the-art machine learning methods. We performed external validation across three independent hospitals, and additionally tested our method on a patient ICU discharge status task, demonstrating model generalizability.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.06.23.22276827", + "rel_abs": "BackgroundHIV may increase SARS-CoV-2 infection risk and COVID-19 severity generally, but data are limited about its impact on postpartum women and their infants. As such, we characterized SARS-CoV-2 infection among mother-infant pairs in Nairobi, Kenya.\n\nMethodsWe conducted a nested study of 53 HIV-uninfected and 51 healthy women living with HIV, as well as their HIV-exposed uninfected (N=41) and HIV-unexposed (N=48) infants, participating in a prospective cohort. SARS-CoV-2 serology was performed on plasma collected between 1 May-31 December 2020 to determine the incidence, risk factors, and symptoms of infection. SARS-CoV-2 RNA PCR and sequencing was also performed on stool samples from seropositive participants.\n\nResultsSARS-CoV-2 seropositivity was found in 38% of the 104 mothers and in 17% of the 89 infants. There was no significant association between SARS-CoV-2 infection and maternal HIV (Hazard Ratio [HR]=1.51, 95% CI: 0.780-2.94) or infant HIV exposure (HR=1.48, 95% CI: 0.537-4.09). Maternal SARS-CoV-2 was associated with a >10-fold increased risk of infant infection (HR=10.3, 95% CI: 2.89-36.8). Twenty percent of participants had symptoms, but no participant experienced severe COVID-19 or death. Seroreversion occurred in [~]30% of mothers and infants. SARS-CoV-2 sequences obtained from stool were related to contemporaneously circulating variants.\n\nConclusionsThese data indicate that postpartum Kenyan women and their infants were at high risk for SARS-CoV-2 infection in 2020, and that antibody responses waned rapidly. However, most cases were asymptomatic and healthy women living with HIV did not have a substantially increased risk of infection or severe COVID-19.", + "rel_num_authors": 17, "rel_authors": [ { - "author_name": "Jenny Yang", - "author_inst": "The University of Oxford" + "author_name": "Emily R Begnel", + "author_inst": "University of Washington" }, { - "author_name": "Andrew AS Soltan", - "author_inst": "University of Oxford" + "author_name": "Bhavna H Chohan", + "author_inst": "University of Washington, Kenya Medical Research Institute" }, { - "author_name": "David A Clifton", - "author_inst": "The University of Oxford" + "author_name": "Ednah Ojee", + "author_inst": "University of Nairobi" + }, + { + "author_name": "Judith Adhiambo", + "author_inst": "University of Nairobi" + }, + { + "author_name": "Prestone Owiti", + "author_inst": "University of Nairobi" + }, + { + "author_name": "Vincent Ogweno", + "author_inst": "University of Nairobi" + }, + { + "author_name": "LaRinda A Holland", + "author_inst": "Arizona State University" + }, + { + "author_name": "Carolyn S Fish", + "author_inst": "Fred Hutchinson Cancer Research Center" + }, + { + "author_name": "Barbra A Richardson", + "author_inst": "University of Washington" + }, + { + "author_name": "Adam K Khan", + "author_inst": "Arizona State University" + }, + { + "author_name": "Rabia Maqsood", + "author_inst": "Arizona State University" + }, + { + "author_name": "Efrem Lim", + "author_inst": "Arizona State University" + }, + { + "author_name": "Dara A Lehman", + "author_inst": "Fred Hutchinson Cancer Research Center" + }, + { + "author_name": "Jennifer Slyker", + "author_inst": "University of Washington" + }, + { + "author_name": "John Kinuthia", + "author_inst": "University of Washington, Kenyatta National Hospital" + }, + { + "author_name": "Dalton Wamalwa", + "author_inst": "University of Washington, University of Nairobi" + }, + { + "author_name": "Soren Gantt", + "author_inst": "Universite de Montreal" } ], "version": "1", - "license": "cc_by", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "health informatics" + "category": "hiv aids" }, { "rel_doi": "10.1101/2022.06.23.22276825", @@ -258382,79 +258141,43 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2022.06.22.22276690", - "rel_title": "Long-term immune persistence induced by two-dose BBIBP-CorV vaccine with different intervals, and immunogenicity and safety of a homologous booster dose in high-risk occupational population. Secondary Study Based on a Randomized Clinical Trial", + "rel_doi": "10.1101/2022.06.24.22276867", + "rel_title": "The mental wellbeing of prison staff in England during the COVID-19 pandemic: a cross-sectional study", "rel_date": "2022-06-26", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.06.22.22276690", - "rel_abs": "BackgroundBBIBP-CorV vaccine with two doses and an interval of 3-4 weeks had been proved to have good immunogenicity and efficacy as well as an acceptable safety profile according to our initial research and other similar studies. Maintaining adequate neutralizing antibody levels is also necessary for long-term protection, especially in the midst of the COVID-19 pandemic. Our aim was to evaluate the immune persistence of neutralizing antibody elicited by BBIBP-CorV vaccines with day 0-14, 0-21 and 0-28 schedule, and assess the immunogenicity and safety of a homologous booster dose in the high-risk occupational population aged 18-59 years.\n\nMethodsA total of 809 eligible participants, aged 18-59 years, were recruited and randomly allocated to receive BBIBP-CorV vaccine with day 0-14, 0-21 or 0-28 schedule respectively between January and May 2021 in Taiyuan City, Shanxi Province, China among the public security officers and the airport ground staff in initial study. In this secondary study, the responders (GMT [≥] 16) at day 28 after priming two-dose vaccine were followed up at months 3, 6 and 10 to evaluate the immune persistence of three two-dose schedules. At month 10, eligible participants of three two-dose schedules were received a homologous booster dose respectively (hereafter abbreviated as 0-14d-10m group, 0-21d-10m group and 0-28d-10m group), and followed up at day 28 post-booster to assess the safety and immunogenicity of the booster dose. The contents of follow-up included the blood samples, oropharyngeal/nasal swabs, and adverse reactions collection. The main outcomes of the study included geometric mean titers (GMT) of neutralizing antibody to live SARS-CoV-2, the positive rates of different criteria and the constituent ratio of GMT of neutralizing antibodies at different follow-up point. Meanwhile, we explored the kinetics of antibody levels of different vaccination regimens by generalized estimating equations (GEE) and used exponent curve model to predict the duration of maintaining protected antibody after the booster dose. We also determined predictors of maintaining protected antibody level within 10 months after the second dose by Cox proportional hazards regression model and nomogram. The trial was registered with ChiCTR.org.cn (ChiCTR2100041705, ChiCTR2100041706).\n\nResultsThe number of 241, 247 and 256 responders (GMT [≥] 16) at day 28 after two-dose BBIBP-CorV vaccine in 0-14d, 0-21d and 0-28d schedule were followed-up at months 3, 6, and 10 for immune persistence evaluation. At month 10, a total of 390 participants were eligible and received a booster dose with 130 participants in the 0-14d-10m, 0-21d-10m and 0-28d-10m group respectively, of whom 74.1% (289/390) were male, with a mean age of 37.1{+/-}10.3 years. The GMT of neutralizing antibody in 0-28d-10m and 0-21d-10m group were significantly higher than 0-14d-10m group at month 3 (GMT: 71.6 & 64.2 vs 46.4, P<0.0001), month 6 (GMT: 47.1 & 42.8 vs 30.5, P < 0.0001) and month 10 (GMT: 32.4 vs 20.3, P < 0.0001; 28.8 vs 20.3, P=0.0004) after the second dose. A sharply decrease by 4.85-fold (GMT: 94.4-20.3), 4.67-fold (GMT: 134.4-28.8) and 4.49-fold (GMT: 145.5-32.4) was observed from day 28 to month 10 after the second dose in 0-14d-10m, 0-21d-10m and 0-28d-10m group, respectively, and they had similar decline kinetics (P=0.67). At 28 days after booster dose, a remarkable rebound in neutralizing antibody (GMT: 246.2, 277.5 and 288.6) were observed in three groups, respectively. Notably, the GMT after booster dose was not affected by priming two-dose schedule. The predictive duration of neutralizing antibody declining to the cutoff level of positive antibody response may be 18.08 months, 18.83 months and 19.08 months after booster dose in three groups, respectively. Long-term immune persistence within 10 months after the second dose was associated with age<40, female, and history of influenza vaccination. All adverse reactions were mild after the booster injection. None of the participants were infected SARS-CoV-2 during the trial period.\n\nConclusionsThe priming two-dose BBIBP-CorV vaccine with 0-28 days and 0-21 days schedule could lead a longer persistence of neutralizing antibody than 0-14 days schedule. Maintaining long-term immune persistence was also associated with age<40, female, and history of influenza vaccination. Regardless of priming two-doses vaccination regimens, a homologous booster dose led to a strong rebound in neutralizing antibody and might elicit satisfactory persistent immunity.", - "rel_num_authors": 15, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.06.24.22276867", + "rel_abs": "ObjectivesTo examine the mental wellbeing of prison staff in England within the pandemic, and determine factors associated with wellbeing.\n\nDesignCross-sectional study, with self-completed hardcopy and online surveys.\n\nSetting26 prisons across England, chosen to be representative of the wider closed prison estate in England\n\nParticipantsAll staff within the 26 prisons from 20th July 2020 and 2nd October 2020 were eligible.\n\nPrimary outcome measureWellbeing, measured using the Short-version of Warwick-Edinburgh Wellbeing Scale (SWEMWBS). Staff wellbeing was compared to that of the English population using indirectly standardised data from the Health Survey for England 2010-13 and a one-sample t-test. Multivariate linear regression modelling explored associations with mental wellbeing score.\n\nResults2534 individuals were included (response rate 22.2%). The mean age was 44 years, 53% were female, and 93% were white. The sample mean SWEMWBS score was 23.84 and the standardised population mean score was 23.57. The difference in means was statistically significant (95% CI 0.09 to 0.46), but not of at a clinically meaningful level. The multivariate linear regression model was adjusted for age category, sex, ethnicity, smoking status, presence of comorbidities, occupation, and HMPPS region. Higher wellbeing was significantly associated with older age, male sex, Black/Black British ethnicity, never having smoked, working within the health staff team, and working in certain prison regions. The overall model had a low predictive value (adjusted R2 = 0.0345).\n\nConclusionsUnexpectedly, prison staff wellbeing as measured by SWEMWBS was similar to that of the general population. Reasons for this are unclear but could include the reduction in violence within prisons since the start of the pandemic. Qualitative research across a diverse sample of prison settings would enrich understanding of staff wellbeing within the pandemic.\n\nStrengths and limitations of this studyO_LIThis is the largest study to date to explore the mental wellbeing of prison staff in the UK (n=2534) and the first peer-reviewed study examining this during the COVID-19 pandemic.\nC_LIO_LIThe sampling frame used (all staff at 26 prisons in England) is more likely to be representative of the prison staff population than other studies which have measured prison staff wellbeing and recruited through trade union channels\nC_LIO_LIWellbeing was measured using SWEMWBS, which has been validated within the UK population\nC_LIO_LIResponse rate was low (22.2%) and a number of variables adjusted for in the regression model were self-reported which could lead to a degree of bias\nC_LI", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Tian Yao", - "author_inst": "First Hospital/First Clinical Medical College of Shanxi Medical University" - }, - { - "author_name": "Xiaohong Zhang", - "author_inst": "Shanxi Provincial Center for Disease Control and Prevention" - }, - { - "author_name": "Shengcai Mu", - "author_inst": "Shanxi Provincial Center for Disease Control and Prevention" - }, - { - "author_name": "Yana Guo", - "author_inst": "School of Public Health, Shanxi Medical University" - }, - { - "author_name": "Xiuyang Xu", - "author_inst": "School of Public Health, Shanxi Medical University" - }, - { - "author_name": "Junfeng Huo", - "author_inst": "Shanxi Provincial Center for Disease Control and Prevention" - }, - { - "author_name": "Zhiyun Wei", - "author_inst": "Shanxi Provincial Center for Disease Control and Prevention" - }, - { - "author_name": "Ling Liu", - "author_inst": "Shanxi Provincial Center for Disease Control and Prevention" - }, - { - "author_name": "Xiaoqing Li", - "author_inst": "Shanxi Provincial Center for Disease Control and Prevention" - }, - { - "author_name": "Hong Li", - "author_inst": "Shanxi Provincial Center for Disease Control and Prevention" + "author_name": "Luke Johnson", + "author_inst": "School of Primary Care, Population Sciences and Medical Education, University of Southampton, Southampton, SO17 1BJ, UK" }, { - "author_name": "Rongqin Xing", - "author_inst": "Outpatient Department of Shanxi Aviation Industry Group Co. LTD" + "author_name": "Maciej Czachorowski", + "author_inst": "Vulnerable People and Inclusion Health Directorate, UK Health Security Agency" }, { - "author_name": "Yongliang Feng", - "author_inst": "School of Public Health, Shanxi Medical University" + "author_name": "Kerry Gutridge", + "author_inst": "Centre for Womens Mental Health, Division of Psychology and Mental Health, University of Manchester" }, { - "author_name": "Jing Chen", - "author_inst": "Shanxi Provincial Center for Disease Control and Prevention" + "author_name": "Nuala McGrath", + "author_inst": "School of Primary Care, Population Sciences and Medical Education, University of Southampton, Southampton, SO17 1BJ, UK" }, { - "author_name": "Lizhong Feng", - "author_inst": "Shanxi Provincial Center for Disease Control and Prevention" + "author_name": "Julie Parkes", + "author_inst": "School of Primary Care, Population Sciences and Medical Education, University of Southampton, Southampton, SO17 1BJ, UK" }, { - "author_name": "Suping Wang", - "author_inst": "School of Public Health, Shanxi Medical University" + "author_name": "Emma Plugge", + "author_inst": "School of Primary Care, Population Sciences and Medical Education, University of Southampton, Southampton, SO17 1BJ, UK" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "public and global health" }, { "rel_doi": "10.1101/2022.06.24.22276878", @@ -260376,27 +260099,31 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2022.06.23.22276812", - "rel_title": "On the impacts of the COVID-19 pandemic on mortality: Lost years or lost days?", + "rel_doi": "10.1101/2022.06.22.22276789", + "rel_title": "Association of physical activity and the risk of COVID-19 hospitalization: a dose-response meta-analysis", "rel_date": "2022-06-23", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.06.23.22276812", - "rel_abs": "ObjectiveTo quantify the (direct and indirect) impacts of the COVID-19 pandemic on mortality for actual populations of persons living in 12 European countries in 2020.\n\nMethodBased on demographic and mortality data, as well as remaining life expectancies found in the Human Mortality Database, we calculated a \"population life lost\" in 2020 for men and women living in Belgium, Croatia, Denmark, Finland, Hungary, Lithuania, Luxembourg, Norway, Portugal, Spain, Sweden and Switzerland. This quantity was obtained by dividing the total number of years lost in 2020 (estimated from all-cause mortality data and attributed directly or indirectly to COVID-19) by the size of the population.\n\nResultsA significant population life loss was found in 8 countries in 2020, with men losing an average of 8.7, 5.0, 4.4, 4.0, 3.7, 3.4, 3.1 and 2.7 days in Lithuania, Spain, Belgium, Hungary, Croatia, Portugal, Switzerland and Sweden, respectively. For women, this loss was 5.5, 4.3, 3.7, 3.7, 3.1, 2.4, 1.6 and 1.4 days, respectively. No significant losses were found in Finland, Luxembourg, Denmark and Norway. Life loss was highly dependent on age, reaching 40 days at the age of 90 in some countries, while only a few significant losses occurred under the age of 60. Even in countries with a significant population life loss in 2020, it was on average about 30 times lower than in 1918, at the time of the Spanish flu.\n\nConclusionsOur results based on the concept of population life loss were consistent with those based on the classical concept of life expectancy, confirming the significant impact of COVID-19 on mortality in 8 European countries in 2020. However, while life expectancy losses were typically counted in months or years, population life losses could be counted in days, a potentially useful piece of information from a public health perspective.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.06.22.22276789", + "rel_abs": "BackgroundMany people have experienced a high burden due to the spread of the coronavirus disease (COVID-19) and its serious consequences for health and everyday life. Prior studies have reported that physical activity (PA) may lower the risk of COVID-19 hospitalization. The present meta-analysis (PROSPERO registration number: CRD42022339672) explored the dose- response relationship between PA and the risk of COVID-19 hospitalization.\n\nMethodsEpidemiological observational studies on the relationship between PA and the risk of COVID-19 hospitalization were included. Categorical dose-response relationships between PA and the risk of COVID-19 hospitalization were assessed using random effect models. Robust error meta-regression models assessed the continuous relationship between PA (metabolic equivalent [MET]-h/week) and COVID-19 hospitalization risk across studies reporting quantitative PA estimates.\n\nResultsSeventeen observational studies (cohort\\case-control\\cross-section) met the criteria for inclusion in the meta-analysis. Categorical dose-relationship analysis showed a 40% (risk ratio (RR) 0.60, 95% confidence intervals (CI): 0.48-0.71) reduction in the risk of COVID-19 hospitalization compared to the lowest dose of PA. The results of the continuous dose-response relationship showed a non-linear inverse relationship (Pnon-linearity < 0.05) between PA and the risk of COVID-19 hospitalization. When total PA was less than or greater than 10 Met-h/week, an increase of 4 Met-h/week was associated with a 14% (RR = 0.83, 95%CI: 0.85-0.87) and 11% (RR = 0.89, 95%CI: 0.87-0.90) reduction in the risk of COVID-19 hospitalization, respectively.\n\nConclusionsThere was an inverse non-linear dose-response relationship between PA level and the risk of COVID-19 hospitalization. Doses of the guideline-recommended minimum PA levels by WTO may be required for more substantial reductions in the COVID-19 hospitalization risk.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Valentin Rousson", - "author_inst": "University of Lausanne" + "author_name": "Dan Li", + "author_inst": "Wuhan University of Science and Technology" }, { - "author_name": "Isabella Locatelli", - "author_inst": "Unisante (University of Lausanne)" + "author_name": "Shengzhen Jin", + "author_inst": "Wuhan Sports University" + }, + { + "author_name": "Songtao Lu", + "author_inst": "Wuhan University of Science and Technology" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "sports medicine" }, { "rel_doi": "10.1101/2022.06.21.22276696", @@ -262266,43 +261993,23 @@ "category": "genetic and genomic medicine" }, { - "rel_doi": "10.1101/2022.06.19.22276620", - "rel_title": "Emotions in the time of COVID-19: A sentiment analysis of tweets during the nationwide lockdown in India", + "rel_doi": "10.1101/2022.06.16.22276531", + "rel_title": "Vaccination and testing as a means of ending the COVID-19 pandemic: comparative and statistical analysis", "rel_date": "2022-06-21", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.06.19.22276620", - "rel_abs": "BackgroundCOVID-19 pandemic is unprecedented in terms of burden, nature and quantum of control measures and public reactions. We report trends in public emotions and sentiments before and during the nation-wide lockdown implemented since 25th March 2020 in India.\n\nMethodsWe collected a sample of tweets containing the keywords coronavirus or COVID-19 published between 12th March and 14th April in India. After pre-processing, the tweets were subjected to sentiment analysis using natural language processing algorithms.\n\nResultsOur analysis of 226170 tweets revealed a positive public sentiment (mean sentiment score=0.25). Tweets expressing a given sentiment showed significant (p<0.001) waning of negativity; negative tweets decreased (39.3% to 35.9%) and positive tweets increased (49.8% to 51.8%). Trust (0.85 words/tweet/day) and fear (0.66 words/tweet/day) were the dominant positive and negative emotions, respectively.\n\nConclusionsPositive sentiments dominated during the COVID-19 lockdown in India. A surveillance system monitoring public sentiments on public health interventions for COVID-19 should be established.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.06.16.22276531", + "rel_abs": "BackgroundRecord numbers of new cases and deaths registered in Japan and European countries in early 2022 once again proved that existing vaccines cannot stop the new infections and deaths caused by SARS-CoV-2 and aroused new questions about methods of overcoming the pandemic.\n\nAim of the studyto compare the pandemic waves in Japan, Ukraine, USA, Hong Kong, mainland China, European and African countries in 2020, 2021, 2022 and to investigate the influence of testing and vaccination levels.\n\nMethodsThe smoothed daily numbers of new cases and deaths per capita, the ratio of these characteristics and the non-linear correlation with the tests per case ratio were used.\n\nResultsAs in other countries, the deaths per case ratio in Japan decreases with the increase of the vaccination level. Non-linear correlation revealed, that the daily number of new cases drastically decreases with the increase of the tests per case ratio.\n\nConclusionsIncreasing the level of testing (especially for people who may have contact with infected persons) and adhering to quarantine restrictions for the entire population, including vaccinated people, may be recommended to end the pandemic.", + "rel_num_authors": 1, "rel_authors": [ { - "author_name": "Rizwan Suliankatchi Abdulkader", - "author_inst": "ICMR-National Institute of Epidemiology" - }, - { - "author_name": "Kathiresan Jeyashree", - "author_inst": "ICMR-National Institute of Epidemiology" - }, - { - "author_name": "Deneshkumar Venugopal", - "author_inst": "Manonmaniam Sundaranar University" - }, - { - "author_name": "K Senthamarai Kannan", - "author_inst": "Manonmaniam Sundaranar University" - }, - { - "author_name": "Manickam Ponnaiah", - "author_inst": "ICMR-National Institute of Epidemiology" - }, - { - "author_name": "Manoj Murhekar", - "author_inst": "ICMR-National Insitute of Epidemiology" + "author_name": "Igor Nesteruk", + "author_inst": "Institute of Hydromechanics National Academy of sciences of Ukraine" } ], "version": "1", "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "health informatics" + "category": "epidemiology" }, { "rel_doi": "10.1101/2022.06.19.22276608", @@ -264020,103 +263727,99 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2022.06.16.496375", - "rel_title": "An S1 subunit vaccine and combination adjuvant (COVAC-1) elicits robust protection against SARS-CoV-2 challenge in African green monkeys", + "rel_doi": "10.1101/2022.06.16.22276514", + "rel_title": "High Mortality among Older Patients Hospitalized with COVID-19 during the First Pandemic Wave", "rel_date": "2022-06-17", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.06.16.496375", - "rel_abs": "Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the agent responsible for the ongoing global pandemic. With over 500 million cases and more than 6 million deaths reported globally, the need for access to effective vaccines is clear. An ideal SARS-CoV-2 vaccine will prevent pathology in the lungs and prevent virus replication in the upper respiratory tract, thus reducing transmission. Here, we assessed the efficacy of an adjuvanted SARS-CoV-2 S1 subunit vaccine, called COVAC-1, in an African green monkey (AGM) model. AGMs immunized and boosted with COVAC-1 were protected from SARS-CoV-2 challenge compared to unvaccinated controls based on reduced pathology and reduced viral RNA levels and infectious virus in the respiratory tract. Both neutralizing antibodies and antibodies capable of mediating antibody-dependent cell-mediated cytotoxicity (ADCC) were observed in vaccinated animals prior to the challenge. COVAC-1 induced effective protection, including in the upper respiratory tract, thus supporting further development and utility for determining the mechanism that confers this protection.\n\nAUTHOR SUMMARYVaccines that can prevent the onward transmission of SARS-CoV-2 and prevent disease are highly desirable. Whether this can be accomplished without mucosal immunization by a parenterally administered subunit vaccine is not well established. Here we demonstrate that following two vaccinations, a protein subunit vaccine containing the S1 portion of the SARS-CoV-2 spike glycoprotein and the novel adjuvant TriAdj significantly reduces the amount of virus in the lungs and also mediates rapid clearance of the virus from the upper respiratory tract. Further support of the effectiveness of COVAC-1 was the observation of reduced pathology in the lungs and viral RNA being largely absent from tissues, blood, and rectal swabs. Thus COVAC-1 appears promising at mediating protection in both the upper and lower respiratory tract and may be capable of reducing subsequent transmission of SARS-CoV-2. Further investigation into the mechanism of protection in the upper respiratory tract and the initial immune response that supports this would be warranted.", - "rel_num_authors": 21, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2022.06.16.22276514", + "rel_abs": "BackgroundUnderstanding the local epidemiology, including mortality, of COVID-19 is important for guiding optimal mitigation strategies such as vaccine implementation, need for study of more effective treatment, and redoubling of focused infection control measures.\n\nMethodsA retrospective observational cohort study design was utilized. We included adult patients diagnosed in the hospital or emergency department with COVID-19 from March 8, 2020 through May 17, 2020 at Grady Memorial Hospital (Atlanta, GA). Medical chart data abstraction was performed to collect clinical, laboratory and outcome data. Death, defined as inpatient mortality or discharge to hospice, was the primary outcome.\n\nResultsAmong 360 persons with laboratory-confirmed COVID-19, 50% were [≥] 60 years, and most (80%) were Black and had a BMI [≥]25 kg/m2 (64%). A total of 53 patients (15%) had an outcome of death with the majority (n=46, 88%) occurring in persons [≥] 60 years. Persons [≥] 60 years were less likely to have typical COVID-19 symptoms while more likely to have multiple comorbidities, multifocal pneumonia, and to be admitted to intensive care. The death rate was 27% among persons [≥]60 years versus 4% in those <60 years (p<.01). Furthermore, most deaths (n=40, 75%) occurred among residents of long-term care facilities (LCFs).\n\nConclusionsWe describe early COVID-19 cases among predominantly Black and older patients from a single center safety net hospital. COVID-19 related mortality occurred predominantly among older patients from LCFs highlighting the need for improved preparedness and supporting prioritization of vaccination efforts in such settings.", + "rel_num_authors": 20, "rel_authors": [ { - "author_name": "Lauren Garnett", - "author_inst": "University of Manitoba Max Rady College of Medicine" - }, - { - "author_name": "Kaylie Tran", - "author_inst": "National Microbiology Laboratory" + "author_name": "Russell R Kempker", + "author_inst": "Emory University School of Medicine, Department of Medicine, Division of Infectious Diseases, Atlanta, GA, USA" }, { - "author_name": "Mable Chan", - "author_inst": "National Microbiology Laboratory" + "author_name": "Paulina Alejandra Rebolledo", + "author_inst": "Emory University School of Medicine, Department of Medicine, Division of Infectious Diseases, Atlanta, GA, USA" }, { - "author_name": "Kevin Tierney", - "author_inst": "National Microbiology Laboratory" + "author_name": "Francois Rollin", + "author_inst": "Emory University School of Medicine, Department of Medicine, Division of Internal Medicine, Atlanta, GA" }, { - "author_name": "Zachary Schiffman", - "author_inst": "National Microbiology Laboratory" + "author_name": "Saumya Gurbani", + "author_inst": "Emory University, School of Medicine, Atlanta, GA" }, { - "author_name": "Jonathan Audet", - "author_inst": "National Microbiology Laboratory" + "author_name": "Marcos C Schechter", + "author_inst": "Emory University School of Medicine, Department of Medicine, Division of Infectious Diseases, Atlanta, GA, USA" }, { - "author_name": "Jocelyne Lew", - "author_inst": "University of Saskatchewan" + "author_name": "David A Wilhoite", + "author_inst": "Emory University, School of Medicine, Atlanta, GA" }, { - "author_name": "Courtney Meilleur", - "author_inst": "National Microbiology Laboratory" + "author_name": "Sherri N Bogard", + "author_inst": "Emory University School of Medicine, Department of Medicine, Division of Hospitalist Medicine, Atlanta, GA" }, { - "author_name": "Michael Chan", - "author_inst": "National Microbiology Laboratory" + "author_name": "Stacey Watkins", + "author_inst": "Emory University School of Medicine, Department of Medicine, Division of Hospitalist Medicine, Atlanta, GA" }, { - "author_name": "Kathy Manguiat", - "author_inst": "National Microbiology Laboratory" + "author_name": "Aarti Duggal", + "author_inst": "Emory University School of Medicine, Department of Medicine, Division of Hospitalist Medicine, Atlanta, GA" }, { - "author_name": "Nikesh Tailor", - "author_inst": "National Microbiology Laboratory" + "author_name": "Nova John", + "author_inst": "Emory University School of Medicine, Department of Medicine, Division of Hospitalist Medicine, Atlanta, GA" }, { - "author_name": "Robert Vendramelli", - "author_inst": "National Microbiology Laboratory" + "author_name": "Malavika Kapuria", + "author_inst": "Emory University School of Medicine, Department of Medicine, Division of Hospitalist Medicine, Atlanta, GA" }, { - "author_name": "Yvon Deschambault", - "author_inst": "National Microbiology Laboratory" + "author_name": "Charles Terry", + "author_inst": "Division of Pulmonary, Allergy, Critical Care, and Sleep Medicine, Department of Medicine, Emory University School of Medicine, Atlanta, Georgia, USA" }, { - "author_name": "Guillaume Beaudoin-Bussi\u00e8res", - "author_inst": "University of Montreal: Universite de Montreal" + "author_name": "Philip Yang", + "author_inst": "Division of Pulmonary, Allergy, Critical Care, and Sleep Medicine, Department of Medicine, Emory University School of Medicine, Atlanta, Georgia, USA" }, { - "author_name": "Jonathan Richard", - "author_inst": "University of Montreal: Universite de Montreal" + "author_name": "Gordon Dale", + "author_inst": "Emory University, School of Medicine, Atlanta, GA" }, { - "author_name": "Andr\u00e9s Finzi", - "author_inst": "University of Montreal: Universite de Montreal" + "author_name": "Ariana Mora", + "author_inst": "Emory University, School of Medicine, Atlanta, GA" }, { - "author_name": "Rick Higgins", - "author_inst": "University of Manitoba Max Rady College of Medicine" + "author_name": "Jessica Preslar", + "author_inst": "Emory University, School of Medicine, Atlanta, GA" }, { - "author_name": "Sylvia van den Hurk", - "author_inst": "University of Saskatchewan" + "author_name": "Katilin Sandor", + "author_inst": "Emory University, School of Medicine, Atlanta, GA" }, { - "author_name": "Volker Gerdts", - "author_inst": "University of Saskatchewan" + "author_name": "Yun F Wang", + "author_inst": "Emory University School of Medicine" }, { - "author_name": "James Strong", - "author_inst": "National Microbiology Laboratory" + "author_name": "Michael H Woodworth", + "author_inst": "Emory University School of Medicine, Department of Medicine, Division of Infectious Diseases, Atlanta, GA, USA" }, { - "author_name": "Darryl Falzarano", - "author_inst": "University of Saskatchewan" + "author_name": "Jordan A Kempker", + "author_inst": "Division of Pulmonary, Allergy, Critical Care, and Sleep Medicine, Department of Medicine, Emory University School of Medicine, Atlanta, Georgia, USA" } ], "version": "1", - "license": "cc_by", - "type": "new results", - "category": "microbiology" + "license": "cc_no", + "type": "PUBLISHAHEADOFPRINT", + "category": "infectious diseases" }, { "rel_doi": "10.1101/2022.06.16.22276483", @@ -266062,35 +265765,59 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.06.14.22276401", - "rel_title": "Persistent circulating SARS-CoV-2 spike is associated with post-acute COVID-19 sequelae", + "rel_doi": "10.1101/2022.06.16.22276476", + "rel_title": "Moral injury and psychological wellbeing in UK healthcare staff", "rel_date": "2022-06-16", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.06.14.22276401", - "rel_abs": "The diagnosis and management of post-acute sequelae of COVID-19 (PASC) poses an ongoing medical challenge. Identifying biomarkers associated with PASC would immensely improve the classification of PASC patients and provide the means to evaluate treatment strategies. We analyzed plasma samples collected from a cohort of PASC and COVID-19 patients (n = 63) to quantify circulating viral antigens and inflammatory markers. Strikingly, we detect SARS-CoV-2 spike antigen in a majority of PASC patients up to 12 months post-diagnosis, suggesting the presence of an active persistent SARS-CoV-2 viral reservoir. Furthermore, temporal antigen profiles for many patients show the presence of spike at multiple time points over several months, highlighting the potential utility of the SARS-CoV-2 full spike protein as a biomarker for PASC.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.06.16.22276476", + "rel_abs": "BackgroundPotentially morally injurious events (PMIEs) can negatively impact mental health. The COVID-19 pandemic may have placed healthcare staff at risk of moral injury.\n\nAimTo examine the impact of PMIE on healthcare staff wellbeing.\n\nMethod12,965 healthcare staff (clinical and non-clinical) were recruited from 18 NHS-England trusts into a survey of PMIE exposure and wellbeing.\n\nResultsPMIEs were significantly associated with adverse mental health symptoms across healthcare staff. Specific work factors were significantly associated with experiences of moral injury, including being redeployed, lack of PPE, and having a colleague die of COVID-19. Nurses who reported symptoms of mental disorders were more likely to report all forms of PMIEs than those without symptoms (AOR 2.7; 95% CI 2.2, 3.3). Doctors who reported symptoms were only more likely to report betrayal events, such as breach of trust by colleagues (AOR 2.7, 95% CI 1.5, 4.9).\n\nConclusionsA considerable proportion of NHS healthcare staff in both clinical and non-clinical roles report exposure to PMIEs during the COVID-19 pandemic. Prospective research is needed to identify the direction of causation between moral injury and mental disorder as well as continuing to monitor the longer term outcomes of exposure to PMIEs.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Zoe Swank", - "author_inst": "Brigham and Women's Hospital, Harvard Medical School" + "author_name": "Victoria Williamson", + "author_inst": "King's College London" }, { - "author_name": "Yasmeen Senussi", - "author_inst": "Brigham and Women's Hospital, Harvard Medical School" + "author_name": "Danielle Lamb", + "author_inst": "UCL" }, { - "author_name": "Galit Alter", - "author_inst": "Ragon Institute of MGH, MIT and Harvard" + "author_name": "Matthew Hotopf", + "author_inst": "King's College London" }, { - "author_name": "David R. Walt", - "author_inst": "Brigham and Women's Hospital/Harvard Medical School" + "author_name": "Rosalind Raine", + "author_inst": "King's College London" + }, + { + "author_name": "Sharon Stevelink", + "author_inst": "King's College London" + }, + { + "author_name": "Simon Wessely", + "author_inst": "King's College London" + }, + { + "author_name": "Mary Jane Docherty", + "author_inst": "South London and Maudsley NHS Foundation Trust" + }, + { + "author_name": "Ira Madan", + "author_inst": "Guy's and St Thomas' NHS Foundation Trust" + }, + { + "author_name": "Dominic Murphy", + "author_inst": "King's College London" + }, + { + "author_name": "Neil Greenberg", + "author_inst": "King's College London" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", - "category": "pathology" + "category": "psychiatry and clinical psychology" }, { "rel_doi": "10.1101/2022.06.12.22276300", @@ -268224,45 +267951,149 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.06.11.22276248", - "rel_title": "Assessing COVID-19 vaccination strategies in varied demographics using an individual-based model", + "rel_doi": "10.1101/2022.06.11.22276266", + "rel_title": "Stratifying elicited antibody dynamics after two doses of SARS-CoV-2 vaccine in a community-based cohort in Fukushima, Japan", "rel_date": "2022-06-14", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.06.11.22276248", - "rel_abs": "BackgroundNew variants of SARS-CoV-2 are constantly discovered. Administration of COVID-19 vaccines and booster doses, combined with applications of non-pharmaceutical interventions (NPIs), is often used to prevent outbreaks of emerging variants. Such outbreak dynamics are further complicated by the populations behavior and demographic composition. Hence, realistic simulations are needed to estimate the efficiency of proposed vaccination strategies in conjunction with NPIs.\n\nMethodsWe developed an individual-based model of COVID-19 dynamics that considers age-dependent parameters such as contact matrices, probabilities of symptomatic and severe disease, and households age distribution. As a case study, we simulate outbreak dynamics under the demographic compositions of two Israeli cities with different household sizes and age distributions. We compare two vaccination strategies: vaccinate individuals in a currently prioritized age group, or dynamically prioritize neighborhoods with a high estimated reproductive number. Total infections and hospitalizations are used to compare the efficiency of the vaccination strategies under the two demographic structures, in conjunction with different NPIs.\n\nResultsWe demonstrate the effectiveness of vaccination strategies targeting highly infected localities and of NPIs actively detecting asymptomatic infections. We further show that there are different optimal vaccination strategies for each demographic composition of sub-populations, and that their application is superior to a uniformly applied strategy.\n\nConclusionOur study emphasizes the importance of tailoring vaccination strategies to subpopulations infection rates and to the unique characteristics of their demographics (e.g., household size and age distributions). The presented simulation framework and our findings can help better design future responses against the following emerging variants.", - "rel_num_authors": 7, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.06.11.22276266", + "rel_abs": "Recent studies have provided insights into the effect of vaccine boosters on recall immunity. Given the limited global supply of COVID-19 vaccines, identifying vulnerable populations with lower sustained vaccine-elicited antibody titers is important for targeting individuals for booster vaccinations. Here we investigated longitudinal data in a cohort of 2,526 people in Fukushima, Japan, from April 2021 to December 2021. Antibody titers following two doses of a COVID-19 vaccine were repeatedly monitored and information on lifestyle habits, comorbidities, adverse reactions, and medication use was collected. Using mathematical modeling and machine learning, we stratified the time-course patterns of antibody titers and identified vulnerable populations with low sustained antibody titers. Moreover, we showed that only 5.7% of the participants in our cohort were part of the \"durable\" population with high sustained antibody titers, which suggests that this durable population might be overlooked in small cohorts. We also found large variation in antibody waning within our cohort. There is a potential usefulness of our approach for identifying the neglected vulnerable population.", + "rel_num_authors": 33, "rel_authors": [ { - "author_name": "Noam Ben-Zuk", - "author_inst": "Tel Aviv University" + "author_name": "Naotoshi Nakamura", + "author_inst": "interdisciplinary Biology Laboratory(iBLab), Division of Natural Science, Graduate School of Science, Nagoya University, Nagoya, Japan." }, { - "author_name": "Yair Daon", - "author_inst": "Tel Aviv University" + "author_name": "Yurie Kobashi", + "author_inst": "Department of Radiation Health Management, Fukushima Medical University School of Medicine, Fukushima, Japan. Department of General Internal Medicine, Hirata Ce" }, { - "author_name": "Amit Sasson", - "author_inst": "Tel Aviv University" + "author_name": "Kwang Su Kim", + "author_inst": "interdisciplinary Biology Laboratory(iBLab), Division of Natural Science, Graduate School of Science, Nagoya University, Nagoya, Japan. Department of Science Sy" }, { - "author_name": "Dror Ben-Adi", - "author_inst": "Tel Aviv University" + "author_name": "Yuta Tani", + "author_inst": "Medical Governance Research Institute,Tokyo, Japan." }, { - "author_name": "Amit Huppert", - "author_inst": "Tel Aviv University" + "author_name": "Yuzo Shimazu", + "author_inst": "Department of Radiation Health Management, Fukushima Medical University School of Medicine, Fukushima, Japan." }, { - "author_name": "Daniel Nevo", - "author_inst": "Tel Aviv University" + "author_name": "Tianchen Zhao", + "author_inst": "Department of Radiation Health Management, Fukushima Medical University School of Medicine, Fukushima, Japan." }, { - "author_name": "Uri Obolski", - "author_inst": "Tel Aviv University" + "author_name": "Yoshitaka Nishikawa", + "author_inst": "Department of General Internal Medicine, Hirata Central Hospital, Fukushima, Japan." + }, + { + "author_name": "Fumiya Omata", + "author_inst": "Department of General Internal Medicine, Hirata Central Hospital, Fukushima, Japan." + }, + { + "author_name": "Moe Kawashima", + "author_inst": "Department of Radiation Health Management, Fukushima Medical University School of Medicine, Fukushima, Japan." + }, + { + "author_name": "Makoto Yoshida", + "author_inst": "Medical Governance Research Institute,Tokyo, Japan." + }, + { + "author_name": "Toshiki Abe", + "author_inst": "Department of Radiation Health Management, Fukushima Medical University School of Medicine, Fukushima, Japan." + }, + { + "author_name": "Yoshika Saito", + "author_inst": "Medical Governance Research Institute,Tokyo, Japan." + }, + { + "author_name": "Yuki Senoo", + "author_inst": "Medical Governance Research Institute,Tokyo, Japan." + }, + { + "author_name": "Saori Nonaka", + "author_inst": "Department of Radiation Health Management, Fukushima Medical University School of Medicine, Fukushima, Japan." + }, + { + "author_name": "Morihito Takita", + "author_inst": "Department of Radiation Health Management, Fukushima Medical University School of Medicine, Fukushima, Japan." + }, + { + "author_name": "Chika Yamamoto", + "author_inst": "Department of Radiation Health Management, Fukushima Medical University School of Medicine, Fukushima, Japan." + }, + { + "author_name": "Takeshi Kawamura", + "author_inst": "Proteomics Laboratory, Isotope Science Center, The University of Tokyo, Tokyo, Japan. Laboratory for Systems Biology and Medicine, Research Center for Advanced " + }, + { + "author_name": "Akira Sugiyama", + "author_inst": "Proteomics Laboratory, Isotope Science Center, The University of Tokyo, Tokyo, Japan." + }, + { + "author_name": "Aya Nakayama", + "author_inst": "Proteomics Laboratory, Isotope Science Center, The University of Tokyo, Tokyo, Japan." + }, + { + "author_name": "Yudai Kaneko", + "author_inst": "Laboratory for Systems Biology and Medicine, Research Center for Advanced Science and Technology, The University of Tokyo, Tokyo, Japan. Medical & Biological La" + }, + { + "author_name": "Hyeongi Park", + "author_inst": "interdisciplinary Biology Laboratory(iBLab), Division of Natural Science, Graduate School of Science, Nagoya University, Nagoya, Japan." + }, + { + "author_name": "Yong Dam Jeong", + "author_inst": "interdisciplinary Biology Laboratory(iBLab), Division of Natural Science, Graduate School of Science, Nagoya University, Nagoya, Japan. Department of Mathematic" + }, + { + "author_name": "Daiki Tatematsu", + "author_inst": "interdisciplinary Biology Laboratory(iBLab), Division of Natural Science, Graduate School of Science, Nagoya University, Nagoya, Japan." + }, + { + "author_name": "Marwa Akao", + "author_inst": "interdisciplinary Biology Laboratory(iBLab), Division of Natural Science, Graduate School of Science, Nagoya University, Nagoya, Japan." + }, + { + "author_name": "Yoshitaka Sato", + "author_inst": "Department of Virology, Nagoya University Graduate School of Medicine, Nagoya, Japan." + }, + { + "author_name": "Shoya Iwanami", + "author_inst": "interdisciplinary Biology Laboratory(iBLab), Division of Natural Science, Graduate School of Science, Nagoya University, Nagoya, Japan." + }, + { + "author_name": "Yasuhisa Fujita", + "author_inst": "interdisciplinary Biology Laboratory(iBLab), Division of Natural Science, Graduate School of Science, Nagoya University, Nagoya, Japan." + }, + { + "author_name": "Masatoshi Wakui", + "author_inst": "Department of Laboratory Medicine, Keio University School of Medicine, Tokyo, Japan." + }, + { + "author_name": "Kazuyuki Aihara", + "author_inst": "International Research Center for Neurointelligence, The University of Tokyo Institutes for Advanced Study, The University of Tokyo, Tokyo, Japan." + }, + { + "author_name": "Tatsuhiko Kodama", + "author_inst": "Laboratory for Systems Biology and Medicine, Research Center for Advanced Science and Technology, The University of Tokyo, Tokyo, Japan." + }, + { + "author_name": "Kenji Shibuya", + "author_inst": "Soma Medical Center for vaccination for COVID-19, Fukushima, Japan. Tokyo Foundation for Policy Research, Tokyo, Japan." + }, + { + "author_name": "Shingo Iwami", + "author_inst": "interdisciplinary Biology Laboratory(iBLab), Division of Natural Science, Graduate School of Science, Nagoya University, Nagoya, Japan. Institute of Mathematics" + }, + { + "author_name": "Masaharu Tsubokura", + "author_inst": "Department of Radiation Health Management, Fukushima Medical University School of Medicine, Fukushima, Japan. Department of General Internal Medicine, Hirata Ce" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -270134,27 +269965,75 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2022.06.13.495792", - "rel_title": "Antigenic escape accelerated by the presence of immunocompromised hosts", + "rel_doi": "10.1101/2022.06.14.496021", + "rel_title": "Protective efficacy of COVAXIN(R) against Delta and Omicron variants in hamster model", "rel_date": "2022-06-14", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.06.13.495792", - "rel_abs": "The repeated emergence of SARS-CoV-2 escape mutants from host immunity has obstructed the containment of the current pandemic and poses a serious threat to humanity. Prolonged infection in immunocompromised patients has received increasing attention as a driver of immune escape, and accumulating evidence suggests that viral genomic diversity and emergence of immune-escape mutants are promoted in immunocompromised patients. However, because immunocompromised patients comprise a small proportion of the host population, whether they have a significant impact on antigenic evolution at the population level is unknown. We used an evolutionary epidemiological model combining antigenic evolution and epidemiological dynamics in host populations with heterogeneity in immune competency to determine the impact of immunocompromised patients on the pathogen evolutionary dynamics of antigenic escape from host immunity. We derived analytical formulae of the speed of antigenic evolution in heterogeneous host populations and found that even a small number of immunocompromised hosts in the population significantly accelerates antigenic evolution. Our results demonstrate that immunocompromised hosts play a key role in viral adaptation at the population level and emphasize the importance of critical care and surveillance of immunocompromised hosts.", - "rel_num_authors": 2, + "rel_link": "https://biorxiv.org/cgi/content/short/2022.06.14.496021", + "rel_abs": "The immunity acquired after natural infection or vaccinations against SARS-CoV-2 tend to wane with time. Vaccine effectiveness also varies with the variant of infection. Here, we compared the protective efficacy of COVAXIN(R) following 2 and 3 dose immunizations against the Delta variant and also studied the efficacy of COVAXIN(R) against Omicron variants in a Syrian hamster model. The antibody response, clinical observations, viral load reduction and lung disease severity after virus challenge were studied. Protective response in terms of the reduction in lung viral load and lung lesions were observed in both the 2 dose as well as 3 doses COVAXIN(R) immunized group when compared to placebo group following the Delta variant challenge. In spite of the comparable neutralizing antibody response against the homologous vaccine strain in both the 2 dose and 3 dose immunized groups, considerable reduction in the lung disease severity was observed in the 3 dose immunized group post Delta variant challenge indicating the involvement of cell mediated immune response also in protection. In the vaccine efficacy study against the Omicron variants i.e., BA.1 and BA.2, lesser virus shedding, lung viral load and lung disease severity were observed in the immunized groups in comparison to the placebo groups. The present study shows that administration of COVAXIN(R) booster dose will enhance the vaccine effectiveness against the Delta variant infection and give protection against the Omicron variants BA.1.1 and BA.2.", + "rel_num_authors": 14, "rel_authors": [ { - "author_name": "Ryuichi Kumata", - "author_inst": "The Graduate University of Advanced Studies" + "author_name": "Pragya Yadav", + "author_inst": "ICMR_National Institute of Virology" }, { - "author_name": "Akira Sasaki", - "author_inst": "Department of Evolutionary Studies of Biosystems, The Graduate University of Advanced Studies, SOKENDAI, Hayama, Kanagawa 2400139, Japan" + "author_name": "Sreelekshmy Mohandas", + "author_inst": "ICMR-National Institute of Virology, Pune" + }, + { + "author_name": "Anita Shete", + "author_inst": "ICMR-National Institute of Virology, Pune" + }, + { + "author_name": "Gajanan Sapkal", + "author_inst": "Indian Council of Medical Research-National Institute of Virology, Pune" + }, + { + "author_name": "Gururaj Deshpande", + "author_inst": "ICMR-NIV, Pune" + }, + { + "author_name": "Abhimanyu Kumar", + "author_inst": "ICMR-NIV, Pune" + }, + { + "author_name": "Kundan Wakchaure", + "author_inst": "ICMR-NIV, Pune" + }, + { + "author_name": "Hitesh Dighe", + "author_inst": "ICMR-NIV, Pune" + }, + { + "author_name": "Rajlaxmi Jain", + "author_inst": "ICMR-NIV, Pune" + }, + { + "author_name": "Brunda Ganneru", + "author_inst": "Bharat Biotech International Limited, Telangana" + }, + { + "author_name": "Jyoti Yemul", + "author_inst": "ICMR-NIV, Pune" + }, + { + "author_name": "Pranita Gawande", + "author_inst": "ICMR-NIV, Pune" + }, + { + "author_name": "Krishna Mohan Vadrevu", + "author_inst": "BHarat Biotech International Limited, Telangana" + }, + { + "author_name": "Priya Abraham", + "author_inst": "ICMR-NIV, Pune" } ], "version": "1", "license": "cc_by_nc_nd", "type": "new results", - "category": "evolutionary biology" + "category": "immunology" }, { "rel_doi": "10.1101/2022.06.14.22276389", @@ -271616,69 +271495,53 @@ "category": "biophysics" }, { - "rel_doi": "10.1101/2022.06.09.495472", - "rel_title": "Tracking infectious entry routes of SARS-CoV-2", + "rel_doi": "10.1101/2022.06.09.495433", + "rel_title": "A cellular assay for spike/ACE2 fusion: quantification of fusion-inhibitory antibodies after COVID-19 and vaccination", "rel_date": "2022-06-09", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.06.09.495472", - "rel_abs": "SARS-CoV-2 cell entry starts with membrane attachment and ends with spike-protein (S) catalyzed membrane fusion depending on two cleavage steps, one usually by furin in producing cells and the second by TMPRSS2 on target cells. Endosomal cathepsins can carry out both. Using real-time 3D single virion tracking, we show fusion and genome penetration requires virion exposure to an acidic milieu of pH 6.2-6.8, even when furin and TMPRSS2 cleavages have occurred. We detect the sequential steps of S1-fragment dissociation, fusion, and content release from the cell surface in TMPRRS2 overexpressing cells only when exposed to acidic pH. We define a key role of an acidic environment for successful infection, found in endosomal compartments and at the surface of TMPRSS2 expressing cells in the acidic milieu of the nasal cavity.\n\nSignificance StatementInfection by SARS-CoV-2 depends upon the S large spike protein decorating the virions and is responsible for receptor engagement and subsequent fusion of viral and cellular membranes allowing release of virion contents into the cell. Using new single particle imaging tools, to visualize and track the successive steps from virion attachment to fusion, combined with chemical and genetic perturbations of the cells, we provide the first direct evidence for the cellular uptake routes of productive infection in multiple cell types and their dependence on proteolysis of S by cell surface or endosomal proteases. We show that fusion and content release always require the acidic environment from endosomes, preceded by liberation of the S1 fragment which depends on ACE2 receptor engagement.\n\nOne sentence summaryDetailed molecular snapshots of the productive infectious entry pathway of SARS-CoV-2 into cells", - "rel_num_authors": 13, + "rel_link": "https://biorxiv.org/cgi/content/short/2022.06.09.495433", + "rel_abs": "Not all antibodies against SARS-CoV-2 inhibit viral entry and hence infection. Neutralizing antibodies are more likely to reflect real immunity, however certain of these tests investigate protein/protein interaction rather than the fusion event. Viral and pseudoviral entry assays detect functionally active antibodies, however they are cumbersome and burdened by biosafety and standardization issues. We have developed a Spike/ACE2-dependant cell-to-cell fusion assay, based on a split luciferase. Hela cells stably transduced with Spike and a large fragment of luciferase were co-cultured with Hela cells transduced with ACE2 and the complementary small fragment of luciferase. Within 24h, cell fusion occured allowing the measurement of luminescence. Light emission was abolished in the absence of Spike and reduced in the presence of an inhibitor of Spike-processing proteases. Serum samples from COVID-19-negative, non-vaccinated individuals, or sera from patients at the moment of first symptoms did not lead to a significant reduction of fusion. In contrast, sera from COVID-19-positive patients as well as sera from vaccinated individuals reduced the fusion. In conclusion, we report a new method measuring fusion-inhibitory antibodies in serum, combining the advantage of a functional full Spike/ACE2 interaction with a high degree of standardization, easily allowing automation in a standard bio-safety environment.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Louis-Marie Bloyet", - "author_inst": "Washington University in St Louis" - }, - { - "author_name": "Spencer Stumpf", - "author_inst": "Washington University in St Louis" - }, - { - "author_name": "Zhuoming Liu", - "author_inst": "Washington University in St. Louis" - }, - { - "author_name": "Ravi Ojha", - "author_inst": "University of Helsinki" - }, - { - "author_name": "Markku T Patjas", - "author_inst": "University of Helsinki" + "author_name": "Fabien Abdul", + "author_inst": "faculty of medicine, university of Geneva" }, { - "author_name": "Ahmed Geneid", - "author_inst": "University of Helsinki" + "author_name": "Pascale Ribaux", + "author_inst": "faculty of medicine, university of Geneva" }, { - "author_name": "Catherine A Doyle", - "author_inst": "University of Virginia" + "author_name": "Aurelie Caillon", + "author_inst": "faculty of medicine, university of Geneva" }, { - "author_name": "Sanna Toppila-Salmi", - "author_inst": "University of Helsinki" + "author_name": "Astrid Malezieux", + "author_inst": "Geneva University Hospitals" }, { - "author_name": "Antti Makitie", - "author_inst": "University of Helsinki" + "author_name": "Virginie Prendki", + "author_inst": "Geneva University Hospitals" }, { - "author_name": "Volker Kiessling", - "author_inst": "University of Virginia" + "author_name": "Nicolay Zhukovsky", + "author_inst": "Neurix SA" }, { - "author_name": "Olli Vapalahti", - "author_inst": "University of Helsinki" + "author_name": "Flavien Delhaes", + "author_inst": "faculty of medicine, university of Geneva" }, { - "author_name": "Sean P. J. Whelan", - "author_inst": "Washington University in Saint Louis" + "author_name": "Karl-Heinz Krause", + "author_inst": "faculty of medicine, university of Geneva" }, { - "author_name": "Giuseppe Balistreri", - "author_inst": "University of Helsinki" + "author_name": "Olivier Preynat-Seauve", + "author_inst": "Geneva University Hospitals, faculty of medicine" } ], "version": "1", - "license": "cc_no", + "license": "cc_by", "type": "new results", "category": "microbiology" }, @@ -273794,51 +273657,31 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2022.06.04.22275989", - "rel_title": "Predictors of second COVID-19 booster dose or new COVID-19 vaccine hesitancy among nurses: a cross-sectional study", + "rel_doi": "10.1101/2022.06.06.22276032", + "rel_title": "Understanding COVID-19 admissions in the UK; Analysis of Freedom of Information Requests", "rel_date": "2022-06-06", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.06.04.22275989", - "rel_abs": "Aims and objectivesTo assess the levels of second COVID-19 booster dose or new COVID-19 vaccine hesitancy among nurses and explore the potential predictors of vaccine hesitancy.\n\nBackgroundCOVID-19 full vaccination seems to be highly effective against highly contagious variants of SARS-CoV-2. Healthcare workers are a high-risk group since they have experienced high levels of COVID-19-associated morbidity and mortality.\n\nMethodsAn on-line cross-sectional study was carried out in Greece in May 2022, using a self-administered questionnaire. The study population included nurses in healthcare services who were fully vaccinated against COVID-19 at the time of study. We considered socio-demographic characteristics, COVID-19-related variables, and attitudes toward COVID-19 vaccination and pandemic as potential predictors of vaccine hesitancy.\n\nResultsAmong 795 nurses, 30.9% were hesitant toward a second booster dose or a new COVID-19 vaccine. Independent predictors of hesitancy included lower educational level, absence of a chronic condition, good/very good self-perceived physical health, lack of flu vaccination during 2021, front-line nurses that provided healthcare to COVID-19 patients during the pandemic, nurses that had not been diagnosed with COVID-19 during the pandemic, and nurses that had at least one relative/friend that has died from COVID-19. Moreover, increased compliance with hygiene measures, increased fear of a second booster dose/new COVID-19 vaccine, and decreased trust in COVID-19 vaccination were associated with increased hesitancy.\n\nConclusionsOur study shows that a significant percentage of nurses are hesitant toward a second booster dose/new COVID-19 vaccine. This initial hesitancy could be a barrier to efforts to control the COVID-19 pandemic. There is a need to communicate COVID-19 vaccine science in a way that is accessible to nurses in order to decrease COVID-19 vaccine hesitancy.", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.06.06.22276032", + "rel_abs": "BackgroundThe progression and severity of the COVID 19 pandemic have been measured based on the daily and total numbers of cases, hospitalisations and deaths. We focused on the nature of hospitalisations from 2020 to 2022.\n\nMethodsWe analysed the role played by SARS-CoV-2 in the pandemic in the UK; we lodged FOI requests to Public Health Wales (PHW), Scotland (PHS), and Northern Ireland (PHA NI), the UK Health Security Agency (UKHSA) and NHS England. We asked for all-cause hospital admission monthly numbers reported by days of positivity to SARS-CoV-2 since admission from March 2020. We grouped replies by respondents. We considered any positive tests acquired from day 8 post admission as evidence of in hospital transmission.\n\nResultsPHW, PHS and PHA NI, provided data within two months. The proportion of people admitted who became positive after eight or more days was 33% in Northern Ireland, 24% in Scotland and 45% in Wales. There are seasonal fluctuations reflecting community admissions but no evidence that the proportion of those infected in hospitals reduced over time. No authorities had viral load or symptoms data relating to their datasets. Given the limitations in PCR reporting, it is impossible to know how many \"positive\" cases were active. UKHSA did not hold the data, and NHS England did not clarify the content of its website.\n\nConclusionAggregate data of \"cases of Covid\" in hospitals should not be used to inform policy of decision-makers until coordination, and proper interpretation of the dataset are instigated.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Petros A Galanis", - "author_inst": "National and Kapodistrian University of Athens" - }, - { - "author_name": "Irene Vraka", - "author_inst": "P. and A. Kyriakou Childrens Hospital" - }, - { - "author_name": "Aglaia Katsiroumpa", - "author_inst": "Faculty of Nursing, National and Kapodistrian University of Athens" - }, - { - "author_name": "Olga Siskou", - "author_inst": "University of Piraeus" - }, - { - "author_name": "Olympia Konstantakopoulou", - "author_inst": "Faculty of Nursing, National and Kapodistrian University of Athens" - }, - { - "author_name": "Theodoros Katsoulas", - "author_inst": "Faculty of Nursing, National and Kapodistrian University of Athens" + "author_name": "Tom Jefferson", + "author_inst": "University of Oxford" }, { - "author_name": "Theodoros Mariolis-Sapsakos", - "author_inst": "Faculty of Nursing, National and Kapodistrian University of Athens" + "author_name": "Jon Brassey", + "author_inst": "Trip Database Ltd" }, { - "author_name": "Daphne Kaitelidou", - "author_inst": "Faculty of Nursing, National and Kapodistrian University of Athens" + "author_name": "Carl Heneghan", + "author_inst": "University of Oxford" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2022.06.05.22276016", @@ -275584,23 +275427,67 @@ "category": "bioinformatics" }, { - "rel_doi": "10.1101/2022.06.03.494608", - "rel_title": "Taxonium: a web-based tool for exploring large phylogenetic trees", + "rel_doi": "10.1101/2022.06.02.493651", + "rel_title": "Distinct antibody responses to endemic coronaviruses pre- and post-SARS-CoV-2 infection in Kenyan infants and mothers", "rel_date": "2022-06-03", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.06.03.494608", - "rel_abs": "The COVID-19 pandemic has resulted in a step change in the scale of sequencing data, with more genomes of SARS-CoV-2 having been sequenced than any other organism on earth. These sequences reveal key insights when represented as a phylogenetic tree, which captures the evolutionary history of the virus, and allows the identification of transmission events and the emergence of new variants. However, existing web-based tools for exploring phylogenies do not scale to the size of datasets now available for SARS-CoV-2. We have developed Taxonium, a new tool that uses WebGL to allow the exploration of trees with tens of millions of nodes in the browser for the first time. Taxonium links each node to associated metadata and supports mutation-annotated trees, which are able to capture all known genetic variation in a dataset. It can either be run entirely locally in the browser, from a server-based backend, or as a desktop application. We describe insights that analysing a tree of five million sequences can provide into SARS-CoV-2 evolution, and provide a tool at cov2tree.org for exploring a public tree of more than five million SARS-CoV-2 sequences. Taxonium can be applied to any tree, and is available at taxonium.org, with source code at github.com/theosanderson/taxonium.", - "rel_num_authors": 1, + "rel_link": "https://biorxiv.org/cgi/content/short/2022.06.02.493651", + "rel_abs": "Pre-existing antibodies that bind endemic human coronaviruses (eHCoVs) can cross-react with SARS-CoV-2, the betacoronavirus that causes COVID-19, but whether these responses influence SARS-CoV-2 infection is still under investigation and is particularly understudied in infants. In this study, we measured eHCoV and SARS-CoV-1 IgG antibody titers before and after SARS-CoV-2 seroconversion in a cohort of Kenyan women and their infants. Pre-existing eHCoV antibody binding titers were not consistently associated with SARS-CoV-2 seroconversion in infants or mothers, though we observed a very modest association between pre-existing HCoV-229E antibody levels and lack of SARS-CoV-2 seroconversion in infants. After seroconversion to SARS-CoV-2, antibody binding titers to endemic betacoronaviruses HCoV-OC43 and HCoV-HKU1, and the highly pathogenic betacoronavirus SARS-CoV-1, but not endemic alphacoronaviruses HCoV-229E and HCoV-NL63, increased in mothers. However, eHCoV antibody levels did not increase following SARS-CoV-2 seroconversion in infants, suggesting the increase seen in mothers was not simply due to cross-reactivity to naively generated SARS-CoV-2 antibodies. In contrast, the levels of antibodies that could bind SARS-CoV-1 increased after SARS-CoV-2 seroconversion in both mothers and infants, both of whom are unlikely to have had a prior SARS-CoV-1 infection, supporting prior findings that SARS-CoV-2 responses cross-react with SARS-CoV-1. In summary, we find evidence for increased eHCoV antibody levels following SARS-CoV-2 seroconversion in mothers but not infants, suggesting eHCoV responses can be boosted by SARS-CoV-2 infection when a prior memory response has been established, and that pre-existing cross-reactive antibodies are not strongly associated with SARS-CoV-2 infection risk in mothers or infants.", + "rel_num_authors": 12, "rel_authors": [ { - "author_name": "Theo Sanderson", - "author_inst": "Francis Crick Institute" + "author_name": "Caitlin I Stoddard", + "author_inst": "Fred Hutchinson Cancer Research Center" + }, + { + "author_name": "Kevin Sung", + "author_inst": "Fred Hutchinson Cancer Research Center" + }, + { + "author_name": "Ednah Ojee", + "author_inst": "University of Nairobi" + }, + { + "author_name": "Judith Adhiambo", + "author_inst": "University of Nairobi" + }, + { + "author_name": "Emily R Begnel", + "author_inst": "University of Washington" + }, + { + "author_name": "Jennifer Slyker", + "author_inst": "University of Washington" + }, + { + "author_name": "Soren Gantt", + "author_inst": "Universite de Montreal" + }, + { + "author_name": "Frederick A Matsen IV", + "author_inst": "Fred Hutchinson Cancer Research Center" + }, + { + "author_name": "John Kinuthia", + "author_inst": "University of Washington" + }, + { + "author_name": "Dalton Wamalwa", + "author_inst": "University of Nairobi" + }, + { + "author_name": "Julie Overbaugh", + "author_inst": "Fred Hutchinson Cancer Research Center" + }, + { + "author_name": "Dara A Lehman", + "author_inst": "Fred Hutchinson Cancer Research Center" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "new results", - "category": "bioinformatics" + "category": "microbiology" }, { "rel_doi": "10.1101/2022.06.03.494642", @@ -277406,33 +277293,21 @@ "category": "intensive care and critical care medicine" }, { - "rel_doi": "10.1101/2022.05.31.22275831", - "rel_title": "WAVES (Web-based tool for Analysis and Visualization of Environmental Samples) - a web application for visualization of wastewater pathogen sequencing results", + "rel_doi": "10.1101/2022.06.01.22275842", + "rel_title": "The spread of infectious diseases from a physics perspective", "rel_date": "2022-06-02", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.05.31.22275831", - "rel_abs": "Environmental monitoring of pathogens provides an accurate and timely source of information for public health authorities and policymakers. In the last two years, wastewater sequencing proved to be an effective way of detection and quantification of SARS-CoV-2 variants circulating in population. Wastewater sequencing produces substantial amounts of geographical and genomic data. Proper visualization of spatial and temporal patterns in this data is crucial for the assessment of the epidemiological situation and forecasting. Here, we present a web-based dashboard application for visualization and analysis of data obtained from sequencing of environmental samples. The dashboard provides multi-layered visualization of geographical and genomic data. It allows to display frequencies of detected pathogen variants as well as individual mutation frequencies. The features of WAVES for early tracking and detection of novel variants in the wastewater are demonstrated in an example of BA.1 variant and the signature Spike mutation S:E484A. WAVES dashboard is easily customized through the editable configuration file and can be used for different types of pathogens and environmental samples.\n\nAvailabilityWAVES source code is freely available at https://github.com/ptriska/WavesDash under MIT license.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.06.01.22275842", + "rel_abs": "This paper presents a theoretical investigation of the spread of infectious diseases (including Covid-19) in a population network. The central idea is that a population can actually be considered as a network of interlinked nodes. The nodes represent the members of the population, the edges between the nodes the social contacts linking 2 population members. Infections spread throughout the population along these network edges. The actual spread of infections is described within the framework of the SIR compartmental model. Special emphasis is laid on understanding and on the interpretation of phenomena in terms of concepts borrowed from condensed-matter and statistical physics. To obtain a mathematical framework that deals with the influence of the network structure and topology, the original SIR model by Kermack and McKendrick was augmented, leading to a system of differential equations that is in principle exact, but the solution of which appears to be intractable. Therefore, combined algebraic/numerical solutions are presented for simplified (approximative) cases that nevertheless capture the essentials of the effect of the network details on the spread of an infection. Solutions of this kind were successfully tested against the results of direct statistical simulations based on Monte-Carlo methods, indicating the appropriateness of the model. Expressions for the (basic) reproduction numbers in terms of the model parameters are presented, and justify some mild criticisms on the widely spread interpretation of reproduction numbers as being the number of secondary infections due to a single active infection. Throughout the entire paper, special attention is paid to the concept of herd-immunity, its nature and its definition. The model allows for obtaining an exact (algebraic) criterion for the most relevant form of herd-immunity to occur in unvaccinated populations. Analysis of the effects of vaccination leads to an even more general version of this criterion in terms of not only the model parameters but also the effectiveness of the vaccine(s) and the vaccination rate(s). This general criterion is also exact within the context of the SIR model. Furthermore it is shown that the onset of herd-immunity can be considered as a 2nd-order phase transition of the kind that is known from thermodynamics and statistical physics, thus offering a fundamentally new viewpoint on the phenomenon. The role of percolation is highlighted and extensively investigated. It is shown that the herd-immunity transition is actually related to a percolation transition, and marks therewith the transition from a regime where the cumulative infections grow into a large macroscopic cluster that spans a major part of the population, towards a regime were the cumulative infections only occur in smaller secondary clusters of limited size. It appears that percolation phenomena become particularly important in the case of (strict) lock-downs. It is also demonstrated how a system of differential equations can be obtained that accounts for the presence of such percolation phenomena. The analyses presented in this paper also provide insight in how various measures to prevent an epidemic spread of an infection work, how they can be optimised and what potentially deceptive issues have to be considered when such measures are either implemented or scaled down. Herd-immunity appears to be a particularly tricky concept in this respect. Phenomena such as a saturation of the cumulative infection number or a fade-out of the number of active infections may easily be mistaken for a stable case of herd-immunity setting in, whereas in reality such phenomena may be no more than an artefact of protective or contact-reducing measures taken, without any meaning for the vulnerability of a population at large under normal (social) conditions. On the other hand, the paper also highlights and explains the theoretical possibility of \"smothering\" an epidemic via very restrictive measures that prevent it from developing out of a limited number of initial seed-infections.", + "rel_num_authors": 1, "rel_authors": [ { - "author_name": "Petr Triska", - "author_inst": "CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences" - }, - { - "author_name": "Fabian Amman", - "author_inst": "CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences" - }, - { - "author_name": "Lukas Endler", - "author_inst": "CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences" - }, - { - "author_name": "Andreas Bergthaler", - "author_inst": "Medical University of Vienna" + "author_name": "Jan H.V.J. Brabers", + "author_inst": "Formerly at van der Waals-Zeeman Institute (UvA), Max Planck Institut fuer Metall/Festkoerperforschung" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -279128,31 +279003,71 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2022.05.30.22275757", - "rel_title": "Young age, student status and reported non-binary gender associate strongly with decreased functioning during Covid-19 pandemic in a university community.", + "rel_doi": "10.1101/2022.05.25.22275569", + "rel_title": "Modelling patterns of SARS-CoV-2 circulation in the Netherlands, August 2020-February 2022, revealed by a nationwide sewage surveillance program", "rel_date": "2022-05-30", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.05.30.22275757", - "rel_abs": "BackgroundCovid-19 pandemic has had detrimental effects on physical and mental well-being whereas there are fewer studies on Covid-19 effects on everyday functioning.\n\nAimsWe aimed to investigate effects of Covid-19 on functioning and related factors in a university community.\n\nMethodIn all, 2004 students and university personnel responded to a Webropol survey in May 2021, when the measures for preventing Covid-19 infections had sustained about a year and a half. Functioning included Visual Analog Scale (0 to 10) assessments on ability to function and ability to work.\n\nResultsYoung age, reported non-binary gender, being student, low resilience, loneliness, received mental care and minor physical exercise, as well as depressive symptoms associated with inferior functioning and negative effects of Covid-19 on functioning. Good school performance at adolescence associated with better, while childhood adversities associated with poorer functioning.\n\nConclusionsIn the university community, young age and non-binary gender associated with decreased functioning during Covid-19 pandemic. Functioning of students was lower than in that of the university personnel. The need for therapeutic counselling and interventions is greatest among young students.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.05.25.22275569", + "rel_abs": "BackgroundSurveillance of SARS-CoV-2 in wastewater offers an unbiased and near real-time tool to track circulation of SARS-CoV-2 at a local scale, next to other epidemic indicators such as hospital admissions and test data. However, individual measurements of SARS-CoV-2 in sewage are noisy, inherently variable, and can be left-censored.\n\nAimWe aimed to infer latent virus loads in a comprehensive sewage surveillance program that includes all sewage treatment plants (STPs) in the Netherlands and covers 99.6% of the Dutch population.\n\nMethodsA multilevel Bayesian penalized spline model was developed and applied to estimate time- and STP-specific virus loads based on water flow adjusted SARS-CoV-2 qRT-PCR data from 1-4 sewage samples per week for each of the >300 STPs.\n\nResultsThe model provided an adequate fit to the data and captured the epidemic upsurges and downturns in the Netherlands, despite substantial day-to-day measurement variation. Estimated STP virus loads varied by more than two orders of magnitude, from approximately 1012 (virus particles per 100,000 persons per day) in the epidemic trough in August 2020 to almost 1015 in many STPs in January 2022. Epidemics at the local levels were slightly shifted between STPs and municipalities, which resulted in less pronounced peaks and troughs at the national level.\n\nConclusionAlthough substantial day-to-day variation is observed in virus load measurements, wastewater-based surveillance of SARS-CoV-2 can track long-term epidemic progression at a local scale in near real-time, especially at high sampling frequency.", + "rel_num_authors": 13, "rel_authors": [ { - "author_name": "Raimo K. R. Salokangas", - "author_inst": "University of Turku" + "author_name": "Michiel van Boven", + "author_inst": "National Institute for Public Health and the Environment" }, { - "author_name": "Tiina From", - "author_inst": "University of Turku" + "author_name": "Wouter A Hetebrij", + "author_inst": "National Institute for Public Health and the Environment" + }, + { + "author_name": "Arno M Swart", + "author_inst": "National Institute for Public Health and the Environment" + }, + { + "author_name": "Erwin Nagelkerke", + "author_inst": "National Institute for Public Health and the Environment" + }, + { + "author_name": "Rudolf FHJ van der Beek", + "author_inst": "National Institute for Public Health and the Environment" + }, + { + "author_name": "Sjors Stouten", + "author_inst": "National Institute for Public Health and the Environment" + }, + { + "author_name": "Rudolf T Hoogeveen", + "author_inst": "National Institute for Public Health and the Environment" + }, + { + "author_name": "Fuminari Miura", + "author_inst": "National Institute for Public Health and the Environment" + }, + { + "author_name": "Astrid Kloosterman", + "author_inst": "National Institute for Public Health and the Environment" + }, + { + "author_name": "Anne-Merel R van der Drift", + "author_inst": "National Institute for Public Health and the Environment" }, { - "author_name": "Jarmo Hietala", - "author_inst": "University of Turku and Turku University Hospital" + "author_name": "Anne Welling", + "author_inst": "National Institute for Public Health and the Environment" + }, + { + "author_name": "Willemijn J Lodder", + "author_inst": "National Institute for Public Health and the Environment" + }, + { + "author_name": "Ana M de Roda Husman", + "author_inst": "National Institute for Public Health and the Environment" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2022.05.27.493767", @@ -280566,147 +280481,107 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.05.25.22274904", - "rel_title": "Immunogenicity and Safety of Beta Adjuvanted Recombinant Booster Vaccine", + "rel_doi": "10.1101/2022.05.27.493569", + "rel_title": "Spike mutation resilient scFv76 antibody counteracts SARS-CoV-2 lung damage upon aerosol delivery", "rel_date": "2022-05-27", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.05.25.22274904", - "rel_abs": "BackgroundVariant-adaptated vaccines against coronavirus disease 2019 (COVID-19) as boosters are needed to increase a broader protection against SARS CoV-2 variants. New adjuvanted recombinant protein vaccines as heterologous boosters could maximize the response.\n\nMethodsIn this randomized, single-blinded, multicenter trial, adults who had received two doses of Pfizer-BioNTech mRNA vaccine (BNT162b2) 3 to7 months before were randomly assigned to receive a boost of BNT162b2, Sanofi/GSK SARS-CoV-2 adjuvanted recombinant protein MV D614 (monovalent parental formulation) or SARS-CoV-2 adjuvanted recombinant protein MV B.1.351 vaccine (monovalent Beta formulation). The primary endpoint was the percentage of subjects with a [≥]10-fold increase in neutralizing antibody titers for the Wuhan (D614) and B.1.351 (Beta) SARS-CoV-2 viral strains between day 0 and day 15.\n\nFindingsThe percentages of participants whose neutralizing antibody titers against the Wuhan (D614) SARS-CoV-2 strain increased by a factor [≥]10 between day 0 and day 15 was 55.3% (95% CI 43.4-66.7) in MV D614 group (n=76), 76.1% (64.5-85.4) in MV B.1.351 (Beta) group (n=71) and 63.2% (51.3-73.9) in BNT162b2 group (n=76). These percentages were 44.7% (33.3-56.6), 84.5% (74.0-92.0) and 51.3% (39.6-63.0) for the B.1.351 (Beta) viral strain, respectively. Higher neutralizing antibodies rates against Delta and Omicron BA.1 variants were also elicited after Sanofi/GSK MV Beta vaccine compared to the other vaccines. Comparable reactogenicity profile was observed with the three vaccines.\n\nInterpretationHeterologous boosting with the Sanofi/GSK Beta formulation vaccine resulted in a higher neutralizing antibody response against Beta variant but also the original strain and Delta and Omicron BA.1 variants, compared with mRNA BNT162b2 vaccine or the Sanofi/GSK MVD614 formulation. New vaccines containing Beta spike protein may represent an interesting strategy for broader protection against SARS CoV-2 variants.\n\nFundingFrench Ministries of Solidarity and Health and Research and Sanofi\n\nTrial registration numberClinicalTrials.gov identifier NCT05124171; EudraCT identifier 2021-004550-33.", - "rel_num_authors": 32, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2022.05.27.493569", + "rel_abs": "Uneven worldwide vaccination coverage against SARS-CoV-2 and emergence of variants escaping immunity call for broadly-effective and easily-deployable therapeutics. We previously described the human single-chain scFv76 antibody, which recognizes SARS-CoV-2 Alfa, Beta, Gamma and Delta variants. We now show that scFv76 also neutralizes infectivity and fusogenic activity of Omicron BA.1 and BA.2 variants. Cryo-EM analysis reveals that scFv76 binds to a well-conserved SARS-CoV-2 spike epitope, providing the structural basis for its broad-spectrum activity. Moreover, we demonstrate that nebulized scFv76 exhibits therapeutic efficacy in a severe hACE2 transgenic mouse model of COVID-19 pneumonia, as shown by body weight and pulmonary viral load data. Counteraction of infection correlates with the inhibition of lung inflammation observed by histopathology and expression of inflammatory cytokines and chemokines. Biomarkers of pulmonary endothelial damage were also significantly reduced in scFv76-treated mice. Altogether the results support the use of nebulized scFv76 for COVID-19 induced by any SARS-CoV-2 variants emerged so far.", + "rel_num_authors": 22, "rel_authors": [ { - "author_name": "Odile LAUNAY", - "author_inst": "AP-HP, H\u00f4pital Cochin; Inserm CIC 1417, Paris, France, Universit\u00e9 Paris Cit\u00e9, Facult\u00e9 de m\u00e9decine, Paris, France, F-CRIN, I REIVAC/COVIREIVAC, France" - }, - { - "author_name": "Marine Cachanado", - "author_inst": "Department of Clinical Pharmacology and Clinical Research Platform Paris-East (URCEST-CRC-CRB), APHP, H\u00f4pital St Antoine, Paris, France" - }, - { - "author_name": "Liem Binh Luong Ng\u0169yen", - "author_inst": "AP-HP, H\u00f4pital Cochin; Inserm CIC 1417, Paris, France; F-CRIN, I REIVAC/COVIREIVAC, France" - }, - { - "author_name": "Laetitia Ninove", - "author_inst": "Unit\u00e9 des Virus \u00c9mergents, UVE: Aix Marseille Univ, IRD 190, INSERM 1207, Marseille, France" - }, - { - "author_name": "Marie Lach\u00e2tre", - "author_inst": "AP-HP, H\u00f4pital Cochin; Inserm CIC 1417, Paris, France; F-CRIN, I REIVAC/COVIREIVAC, France" - }, - { - "author_name": "In\u00e8s Ben Ghezala", - "author_inst": "Inserm, CIC 1432, Clinical Investigation Center, Clinical Epidemiology/Clinical Trials Unit, University Hospital, Dijon, France" - }, - { - "author_name": "Marc Bardou", - "author_inst": "Inserm, CIC 1432, Clinical Investigation Center, Clinical Epidemiology/Clinical Trials Unit, University Hospital, Dijon, France; F-CRIN, I REIVAC/COVIREIVAC, Fr" - }, - { - "author_name": "Catherine Schmidt -Mutter", - "author_inst": "CIC Inserm 1434, H\u00f4pitaux Universitaires de Strasbourg, France, F-CRIN, I REIVAC/COVIREIVAC, France" - }, - { - "author_name": "Renaud Felten", - "author_inst": "CIC Inserm 1434, H\u00d4pitaux Universitaires de Strasbourg, France; F-CRIN, I REIVAC/COVIREIVAC, France" - }, - { - "author_name": "Karine Lacombe", - "author_inst": "Sorbonne Universit\u00e9, IPLESP Inserm UMR-S1136, H\u00f4pital St Antoine, AP-HP, Paris, France; F-CRIN, I REIVAC/COVIREIVAC, France" - }, - { - "author_name": "Laure Surgers", - "author_inst": "Sorbonne Universit\u00e9, IPLESP Inserm UMR-S1136, H\u00d4pital St Antoine, AP-HP, Paris, France; F-CRIN, I REIVAC/COVIREIVAC, France" + "author_name": "Ferdinando Maria Milazzo", + "author_inst": "Alfasigma" }, { - "author_name": "Fabrice Laine", - "author_inst": "INSERM, CIC1414, CHU Rennes, Rennes, France; F-CRIN, I REIVAC/COVIREIVAC, France" + "author_name": "Antonio Chaves-Sanjuan", + "author_inst": "Department of Biosciences and Cryo-EM Lab Pediatric Research Center Fondazione Romeo e Enrica Invernizzi University of Milan" }, { - "author_name": "Jean-Sebastien Allain", - "author_inst": "INSERM, CIC1414, CHU Rennes, Rennes, France; F-CRIN, I REIVAC/COVIREIVAC, France" + "author_name": "Olga Minenkova", + "author_inst": "Alfasigma" }, { - "author_name": "Elisabeth Botelho-Nevers", - "author_inst": "Service d infectiologie, CIC1408, Inserm, CHU de Saint-Etienne, 42055 Saint-Etienne, France; F-CRIN, I REIVAC/COVIREIVAC, France" + "author_name": "Daniela Santapaola", + "author_inst": "Alfasigma" }, { - "author_name": "Marie-Pierre Tavolacci", - "author_inst": "Normandie Univ, UNIROUEN, U1073, CHU Rouen, and CIC-CRB 1404, F-76000 Rouen, France; F-CRIN, I REIVAC/COVIREIVAC, France" + "author_name": "Anna Maria Anastasi", + "author_inst": "Alfasigma" }, { - "author_name": "christian Chidiac", - "author_inst": "Maladies Infectieuses, GHN Croix Rousse, Hospices Civils de Lyon, UFR de M\u00e9decine et Ma&eutique Lyon Sud Universit\u00e9 Claude Bernard Lyon1, Universit&ea de Lyon, " + "author_name": "Gianfranco Battistuzzi", + "author_inst": "Alfasigma" }, { - "author_name": "Patricia Pavese", - "author_inst": "Maladies infectieuses et tropicales, CHU de Grenoble Alpes, France; F-CRIN, I REIVAC/COVIREIVAC, France" + "author_name": "Caterina Chiapparino", + "author_inst": "Alfasigma" }, { - "author_name": "Bertrand Dussol", - "author_inst": "CIC 14-09, INSERM - Aix Marseille Universit\u00e9 H\u00f4pitaux Universitaires de Marseille; F-CRIN, I REIVAC/COVIREIVAC, France" + "author_name": "Antonio Rosi", + "author_inst": "Alfasigma" }, { - "author_name": "Stephane Priet", - "author_inst": "Unit\u00e9 des Virus \u00c9mergents, UVE: Aix Marseille Univ, IRD 190, INSERM 1207, Marseille, France" + "author_name": "Emilio Merlo Pich", + "author_inst": "Alfasigma" }, { - "author_name": "Dominique Deplanque", - "author_inst": "Univ. Lille, Inserm, CHU Lille, CIC 1403 Centre d investigation clinique, F- 59000 Lille, France; F-CRIN, I REIVAC/COVIREIVAC, France" + "author_name": "Claudio Albertoni", + "author_inst": "Studio E Roma" }, { - "author_name": "Amel Touati", - "author_inst": "Department of Clinical Pharmacology and Clinical Research Platform Paris-East (URCEST-CRC-CRB), APHP, H\u00f4pital St Antoine, Paris, France" + "author_name": "Emanuele Marra", + "author_inst": "Takis" }, { - "author_name": "Laureen Curci", - "author_inst": "AP-HP, H\u00f4pital Cochin; Inserm CIC 1417, Paris, France; F-CRIN, I REIVAC/COVIREIVAC, France" + "author_name": "Laura Luberto", + "author_inst": "Takis" }, { - "author_name": "Eleine Konate", - "author_inst": "AP-HP, H\u00f4pital Cochin; Inserm CIC 1417, Paris, France; F-CRIN, I REIVAC/COVIREIVAC, France" + "author_name": "C\u00e9cile Viollet", + "author_inst": "Texcell" }, { - "author_name": "Nadine Ben Hamouda", - "author_inst": "Service Immunologie Biologique, APHP, H\u00f4pital Europ\u00e9en Georges Pompidou, 75015 Paris, France ; PARCC, INSERM U970, Universit\u00e9 de Paris, 75006 Paris, France" + "author_name": "Luigi Giusto Spagnoli", + "author_inst": "Histo-Cyto Service" }, { - "author_name": "Anissa Besbes", - "author_inst": "Service Immunologie Biologique, APHP, H\u00f4pital Europ\u00e9en Georges Pompidou, 75015 Paris, France ; PARCC, INSERM U970, Universit\u00e9 de Paris, 75006 Paris, France" + "author_name": "Anna Riccio", + "author_inst": "University of Rome Tor Vergata" }, { - "author_name": "Eunice Nubret", - "author_inst": "APHP, Direction de la Recherche Clinique et de l Innovation (DRCI), Paris, France" + "author_name": "Antono Rossi", + "author_inst": "CNR" }, { - "author_name": "Florence Capelle", - "author_inst": "D\u00e9partement des Essais Cliniques de l AGEPS, DRCI-APHP, Paris, France" + "author_name": "M. Gabriella Santoro", + "author_inst": "University of Rome Tor Vergata and CNR" }, { - "author_name": "Laurence Berard", - "author_inst": "Department of Clinical Pharmacology and Clinical Research Platform Paris-East (URCEST-CRC-CRB), APHP, H\u00f4pital St Antoine, Paris, France" + "author_name": "Federico Ballabio", + "author_inst": "University of Milan" }, { - "author_name": "Alexandra Rousseau", - "author_inst": "Department of Clinical Pharmacology and Clinical Research Platform Paris-East (URCEST-CRC-CRB), APHP, H\u00d4pital St Antoine, Paris, France" + "author_name": "Cristina Paissoni", + "author_inst": "University of Milan" }, { - "author_name": "Eric Tartour", - "author_inst": "Service d Immunologie Biologique, APHP, H\u00f4pital Europ\u00e9en Georges Pompidou, 75015 Paris, France ; PARCC, INSERM U970, Universit\u00e9 de Paris, 75006 Paris, France" + "author_name": "Carlo Camilloni", + "author_inst": "University of Milan" }, { - "author_name": "Tabassome Simon", - "author_inst": "Department of Clinical Pharmacology and Clinical Research Platform Paris-East (URCEST-CRC-CRB), APHP, H\u00f4pital St Antoine, Paris, France" + "author_name": "Martino Bolognesi", + "author_inst": "University of Milan" }, { - "author_name": "Xavier De Lamballerie", - "author_inst": "Unit\u00e9 des Virus \u00c9mergents, UVE: Aix Marseille Univ, IRD 190, INSERM 1207, Marseille, France" + "author_name": "Rita De Santis", + "author_inst": "Alfasigma" } ], "version": "1", "license": "cc_by_nc_nd", - "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "type": "new results", + "category": "microbiology" }, { "rel_doi": "10.1101/2022.05.25.22275517", @@ -283076,59 +282951,27 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.05.25.22275300", - "rel_title": "Limited induction of lung-resident memory T cell responses against SARS-CoV-2 by mRNA vaccination", + "rel_doi": "10.1101/2022.05.25.22275487", + "rel_title": "Modelling the impacts of public health interventions and weather on SARS-CoV-2 Omicron outbreak in Hong Kong", "rel_date": "2022-05-26", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.05.25.22275300", - "rel_abs": "Resident memory T cells (TRM) present at the respiratory tract may be essential to enhance early SARS-CoV-2 viral clearance, thus limiting viral infection and disease. While long-term antigen (Ag)-specific TRM are detectable beyond 11 months in the lung of convalescent COVID-19 patients after mild and severe infection, it is unknown if mRNA vaccination encoding for the SARS-CoV-2 S-protein can induce this frontline protection. We found that the frequency of CD4+ T cells secreting interferon (IFN){gamma} in response to S-peptides was variable but overall similar in the lung of mRNA-vaccinated patients compared to convalescent-infected patients. However, in vaccinated patients, lung responses presented less frequently a TRM phenotype compared to convalescent infected individuals and polyfunctional CD107a+ IFN{gamma}+ TRM were virtually absent. Thus, a robust and broad TRM response established in convalescent-infected individuals may be advantageous in limiting disease if the virus is not blocked by initial mechanisms of protection, such as neutralization. Still, mRNA vaccines might induce responses within the lung parenchyma, potentially contributing to the overall disease control.", - "rel_num_authors": 10, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.05.25.22275487", + "rel_abs": "BackgroundHong Kong, has operated under a zero-Covid policy in the past few years. As a result, population immunity from natural infections has been low. The fifth wave in Hong Kong, caused by the Omicron variant, grew substantially in February 2022 during the transition from winter into spring. The daily number of reported cases began to decline quickly in a few days after social distancing regulations were tightened and rapid antigen test (RAT) kits were largely distributed. How the non-pharmaceutical interventions (NPIs) and seasonal factors (temperature and relative humidity) could affect the spread of Omicron remains unknown.\n\nMethodsWe developed a model with stratified immunity, to incorporate antibody responses, together with changes in mobility and seasonal factors. After taking into account the detection rates of PCR test and RAT, we fitted the model to the daily number of reported cases between 1 February and 31 March, and quantified the associated effects of individual NPIs and seasonal factors on infection dynamics.\n\nFindingsAlthough NPIs and vaccine boosters were critical in reducing the number of infections, temperature was associated with a larger change in transmissibility. Cold days appeared to drive Re from about 2-3 sharply to 10.6 (95%CI: 9.9-11.4). But this number reduced quickly below one a week later when the temperature got warmer. The model projected that if weather in March maintained as Februarys average level, the estimated cumulative incidence could increase double to about 80% of total population.\n\nInterpretationTemperature should be taken into account when making public health decisions (e.g. a more relaxed (or tightened) social distancing during a warmer (or colder) season).", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Daan K.J. Pieren", - "author_inst": "Vall d'Hebron Research Institute (VHIR)" - }, - { - "author_name": "Sebasti\u00e1n G. Kuguel", - "author_inst": "Vall d'Hebron Research Institute (VHIR)" - }, - { - "author_name": "Joel Rosado", - "author_inst": "Vall d'Hebron Research Institute (VHIR)" - }, - { - "author_name": "Alba G. Robles", - "author_inst": "Vall d'Hebron Research Institute (VHIR)" - }, - { - "author_name": "Joan Rey-Cano", - "author_inst": "Vall d'Hebron Research Institute (VHIR)" - }, - { - "author_name": "Cristina Mancebo", - "author_inst": "Vall d'Hebron Research Institute (VHIR)" - }, - { - "author_name": "Juliana Esperalba", - "author_inst": "Vall d'Hebron Research Institute (VHIR)" - }, - { - "author_name": "Vicen\u00e7 Falc\u00f3", - "author_inst": "Vall d'Hebron Research Institute (VHIR)" - }, - { - "author_name": "Mar\u00eda J. Buz\u00f3n", - "author_inst": "Vall d'Hebron Research Institute (VHIR)" + "author_name": "Hsiang-Yu Yuan", + "author_inst": "City University of Hong Kong" }, { - "author_name": "Meritxell Genesc\u00e0", - "author_inst": "Vall d'Hebron Research Institute (VHIR)" + "author_name": "Jingbo LIANG", + "author_inst": "City University of Hong Kong" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "public and global health" }, { "rel_doi": "10.1101/2022.05.26.493539", @@ -284942,139 +284785,79 @@ "category": "neurology" }, { - "rel_doi": "10.1101/2022.05.24.22275398", - "rel_title": "Generalizable Long COVID Subtypes: Findings from the NIH N3C and RECOVER Programs", + "rel_doi": "10.1101/2022.05.24.22275498", + "rel_title": "Health workers Perspective on the Feasibility and Acceptability of the Introduction of AgRDT for COVID-19 in Kisumu County, Western Kenya", "rel_date": "2022-05-25", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.05.24.22275398", - "rel_abs": "Accurate stratification of patients with post-acute sequelae of SARS-CoV-2 infection (PASC, or long COVID) would allow precision clinical management strategies. However, the natural history of long COVID is incompletely understood and characterized by an extremely wide range of manifestations that are difficult to analyze computationally. In addition, the generalizability of machine learning classification of COVID-19 clinical outcomes has rarely been tested. We present a method for computationally modeling PASC phenotype data based on electronic healthcare records (EHRs) and for assessing pairwise phenotypic similarity between patients using semantic similarity. Our approach defines a nonlinear similarity function that maps from a feature space of phenotypic abnormalities to a matrix of pairwise patient similarity that can be clustered using unsupervised machine learning procedures. Using k-means clustering of this similarity matrix, we found six distinct clusters of PASC patients, each with distinct profiles of phenotypic abnormalities. There was a significant association of cluster membership with a range of pre-existing conditions and with measures of severity during acute COVID-19. Two of the clusters were associated with severe manifestations and displayed increased mortality. We assigned new patients from other healthcare centers to one of the six clusters on the basis of maximum semantic similarity to the original patients. We show that the identified clusters were generalizable across different hospital systems and that the increased mortality rate was consistently observed in two of the clusters. Semantic phenotypic clustering can provide a foundation for assigning patients to stratified subgroups for natural history or therapy studies on PASC.", - "rel_num_authors": 30, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.05.24.22275498", + "rel_abs": "COVID-19 pandemic remains a major global public health challenge also in Low- and Middle-Income Countries (LMIC), due to fragile health systems, limited resources and personnel, low testing and counseling capacity, community perceptions, among others. In Kisumu County of Western Kenya, a unique Public Private Partnership (PPP) was rolled-out to increase testing and capacity building by linking private facilities to the ongoing public sector efforts in combating COVID-19. It became increasingly clear that centralized PCR testing for COVID-19 was too labor-intensive, expensive, prone to machine breakdowns and stock-outs of essential reagents, resulting in long turn-around times and sometimes even adaptations of patient selection criteria. A clear need was identified for rapid point-of-care COVID-19 testing (AgRDT). After successful field evaluation, RDT for COVID-19 was offered through the PPP. This paper aimed to understand the health workers perspective on the feasibility and acceptability of the introduction of the AgRDT in Kisumu County.\n\nIn-Depth Interviews were conducted with selected health workers (n=23) from the participating facilities and analyzed using Nvivo 11 The health workers accepted the use of AgRDT as it enabled the strengthening of the existing health system, increased testing capacity and provided capacity building opportunities. Challenges included poor management of results discrepant with PCR gold standard.\n\nThe health workers applauded the introduction of AgRDT with the Kisumu County Department of Health as a more realistic and user-friendly approach, leading to fast turn-around times and increased personal safety experience.", + "rel_num_authors": 15, "rel_authors": [ { - "author_name": "Justin Reese", - "author_inst": "Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA" - }, - { - "author_name": "Hannah Blau", - "author_inst": "The Jackson Laboratory for Genomic Medicine, 10 Discovery Drive, Farmington, CT, USA" - }, - { - "author_name": "Timothy Bergquist", - "author_inst": "Sage Bionetworks. Seattle, WA, USA" - }, - { - "author_name": "Johanna J. Loomba", - "author_inst": "The Integrated Translational Health Research Institute of Virginia (iTHRIV), University of Virginia, Charlottesville, Virginia, USA." - }, - { - "author_name": "Tiffany Callahan", - "author_inst": "Department of Biomedical Informatics, Columbia University, New York, NY, USA" - }, - { - "author_name": "Bryan Laraway", - "author_inst": "University of Colorado Anschutz Medical Campus, Aurora, CO, USA" - }, - { - "author_name": "Corneliu Antonescu", - "author_inst": "University of Arizona - Banner Health, Phoenix, AZ" + "author_name": "Mevis Corrie Omollo", + "author_inst": "CGHR: Centre for Global Health Research" }, { - "author_name": "Elena Casiraghi", - "author_inst": "AnacletoLab, Dipartimento di Informatica, Universita degli Studi di Milano, Italy" + "author_name": "I.A Odero", + "author_inst": "CGHR: Centre for Global Health Research" }, { - "author_name": "Ben Coleman", - "author_inst": "The Jackson Laboratory for Genomic Medicine, 10 Discovery Drive, Farmington, CT, USA" + "author_name": "H.C. Barsosio", + "author_inst": "CGHR: Centre for Global Health Research" }, { - "author_name": "Michael Gargano", - "author_inst": "The Jackson Laboratory for Genomic Medicine, 10 Discovery Drive, Farmington, CT, USA" + "author_name": "S. Kariuki", + "author_inst": "CGHR: Centre for Global Health Research" }, { - "author_name": "Kenneth Wilkins", - "author_inst": "Biostatistics Program, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD, USA." + "author_name": "F. Ter Kuile", + "author_inst": "LSTM: Liverpool School of Tropical Medicine" }, { - "author_name": "Luca Cappelletti", - "author_inst": "AnacletoLab, Dipartimento di Informatica, Universita degli Studi di Milano, Italy" + "author_name": "S.O Okello", + "author_inst": "CGHR: Centre for Global Health Research" }, { - "author_name": "Tommaso Fontana", - "author_inst": "AnacletoLab, Dipartimento di Informatica, Universita degli Studi di Milano, Italy" + "author_name": "K. Oyoo", + "author_inst": "CGHR: Centre for Global Health Research" }, { - "author_name": "Nariman Ammar", - "author_inst": "University of Tennessee Health Science Center, Memphis, TN, USA" + "author_name": "A. K'Oloo", + "author_inst": "CGHR: Centre for Global Health Research" }, { - "author_name": "Blessy Antony", - "author_inst": "Department of Computer Science, Virginia Tech, Blacksburg, VA, USA." + "author_name": "S. Van Duijn", + "author_inst": "Achmea" }, { - "author_name": "T. M. Murali", - "author_inst": "Department of Computer Science, Virginia Tech, Blacksburg, VA, USA." + "author_name": "N. Houben", + "author_inst": "Achmea" }, { - "author_name": "Guy Karlebach", - "author_inst": "The Jackson Laboratory for Genomic Medicine, 10 Discovery Drive, Farmington, CT, USA" + "author_name": "E. Milimo", + "author_inst": "Achmea" }, { - "author_name": "Julie A. McMurry", - "author_inst": "University of Colorado Anschutz Medical Campus, Aurora, CO, USA" + "author_name": "R. Aroka", + "author_inst": "Achmea" }, { - "author_name": "Andrew Williams", - "author_inst": "Tufts Medical Center Clinical and Translational Science Institute, Tufts Medical Center, Boston, MA, USA" - }, - { - "author_name": "Richard Moffitt", - "author_inst": "Stony Brook University Department of Biomedical Informatics and Stony Brook Cancer Center, Stony Brook, NY, USA" - }, - { - "author_name": "Jineta Banerjee", - "author_inst": "Sage Bionetworks. Seattle, WA, USA" - }, - { - "author_name": "Anthony E. Solomonides", - "author_inst": "NorthShore University HealthSystem Research Institute, Evanston, IL" - }, - { - "author_name": "Hannah Davis", - "author_inst": "Patient-Led Research Collaborative, NY, USA" - }, - { - "author_name": "Kristin Kostka", - "author_inst": "Northeastern University, OHDSI Center at the Roux Institute, Boston, MA, USA" - }, - { - "author_name": "Giorgio Valentini", - "author_inst": "AnacletoLab, Dipartimento di Informatica, Universita degli Studi di Milano, Italy" - }, - { - "author_name": "David Sahner", - "author_inst": "Axle Informatics, Rockville, MD, USA" - }, - { - "author_name": "Christopher G. Chute", - "author_inst": "Schools of Medicine, Public Health, and Nursing, Johns Hopkins University, Baltimore, MD" - }, - { - "author_name": "Charisse Madlock-Brown", - "author_inst": "University of Tennessee Health Science Center, Memphis, TN, USA" + "author_name": "A. Odhiambo", + "author_inst": ": Ministry of Health" }, { - "author_name": "Melissa A. Haendel", - "author_inst": "University of Colorado Anschutz Medical Campus, Aurora, CO, USA" + "author_name": "S.N Onsongo", + "author_inst": "Aga Khan Health Services" }, { - "author_name": "Peter N. Robinson", - "author_inst": "The Jackson Laboratory for Genomic Medicine, 10 Discovery Drive, Farmington, CT, USA" + "author_name": "T.F Rinke de Wit", + "author_inst": "Achmea" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "public and global health" }, { "rel_doi": "10.1101/2022.05.18.22275112", @@ -287112,167 +286895,67 @@ "category": "primary care research" }, { - "rel_doi": "10.1101/2022.05.19.22275214", - "rel_title": "Antibody levels following vaccination against SARS-CoV-2: associations with post-vaccination infection and risk factors", - "rel_date": "2022-05-22", + "rel_doi": "10.1101/2022.05.20.22275359", + "rel_title": "Targeting SARS-CoV-2 superspreading infections could dramatically improve the efficiency of epidemic control strategies in resource-limited contexts", + "rel_date": "2022-05-21", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.05.19.22275214", - "rel_abs": "SARS-CoV-2 antibody levels can be used to assess humoral immune responses following SARS-CoV-2 infection or vaccination, and may predict risk of future infection. From cross-sectional antibody testing of 9,361 individuals from TwinsUK and ALSPAC UK population-based longitudinal studies (jointly in April-May 2021, and TwinsUK only in November 2021-January 2022), we tested associations between antibody levels following vaccination and: (1) SARS-CoV-2 infection following vaccination(s); (2) health, socio-demographic, SARS-CoV-2 infection and SARS-CoV-2 vaccination variables.\n\nWithin TwinsUK, single-vaccinated individuals with the lowest 20% of anti-Spike antibody levels at initial testing had 3-fold greater odds of SARS-CoV-2 infection over the next six to nine months, compared to the top 20%. In TwinsUK and ALSPAC, individuals identified as at increased risk of COVID-19 complication through the UK \"Shielded Patient List\" had consistently greater odds (2 to 4-fold) of having antibody levels in the lowest 10%. Third vaccination increased absolute antibody levels for almost all individuals, and reduced relative disparities compared with earlier vaccinations.\n\nThese findings quantify the association between antibody level and risk of subsequent infection, and support a policy of triple vaccination for the generation of protective antibodies.\n\nLay summaryIn this study, we analysed blood samples from 9,361 participants from two studies in the UK: an adult twin registry, TwinsUK (4,739 individuals); and the Avon Longitudinal Study of Parents and Children, ALSPAC (4,622 individuals). We did this work as part of the UK Government National Core Studies initiative researching COVID-19. We measured blood antibodies which are specific to SARS-CoV-2 (which causes COVID-19). Having a third COVID-19 vaccination boosted antibody levels. More than 90% of people from TwinsUK had levels after third vaccination that were greater than the average level after second vaccination. Importantly, this was the case even in individuals on the UK \"Shielded Patient List\". We found that people with lower antibody levels after first vaccination were more likely to report having COVID-19 later on, compared to people with higher antibody levels. People on the UK \"Shielded Patient List\", and individuals who reported that they had poorer general health, were more likely to have lower antibody levels after vaccination. In contrast, people who had had a previous COVID-19 infection were more likely to have higher antibody levels following vaccination compared to people without infection. People receiving the Oxford/AstraZeneca rather than the Pfizer BioNTech vaccine had lower antibody levels after one or two vaccinations. However, after a third vaccination, there was no difference in antibody levels between those who had Oxford/AstraZeneca and Pfizer BioNTech vaccines for their first two doses. These findings support having a third COVID-19 vaccination to boost antibodies.", - "rel_num_authors": 37, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.05.20.22275359", + "rel_abs": "Targeted surveillance allows public health authorities to implement testing and isolation strategies when diagnostic resources are limited. When transmission patterns are determined by social contact rates, the consideration of social network topologies in testing schemes is one avenue for targeted surveillance, specifically by prioritizing those individuals likely to contribute disproportionately to onward transmission. Yet, it remains unclear how to implement such surveillance and control when network data is unavailable, as is often the case in resource-limited settings. We evaluated the efficiency of a testing strategy that targeted individuals based on their degree centrality on a social network compared to a random testing strategy in the context of low testing capacity. We simulated SARS-CoV-2 dynamics on two contact networks from rural Madagascar and measured the epidemic duration, infection burden, and tests needed to end the epidemics. In addition, we examined the robustness of this approach when individuals true degree centralities were unknown and were instead estimated via readily-available socio-demographic variables (age, gender, marital status, educational attainment, and household size). Targeted testing reduced the infection burden by between 5 - 50% at low testing capacities, while requiring up to 28% fewer tests than random testing. Further, targeted tested remained more efficient when the true network topology was unknown and prioritization was based on socio-demographic characteristics, demonstrating the feasibility of this approach under realistic conditions. Incorporating social network topology into epidemic control strategies is an effective public health strategy for health systems suffering from low testing capacity and can be implemented via socio-demographic proxies when social networks are unknown.\n\n*French abstract available in Supplemental Materials", + "rel_num_authors": 12, "rel_authors": [ { - "author_name": "Nathan J Cheetham", - "author_inst": "King's College London" - }, - { - "author_name": "Milla Kibble", - "author_inst": "University of Cambridge" - }, - { - "author_name": "Andrew Wong", - "author_inst": "University College London" - }, - { - "author_name": "Richard J Silverwood", - "author_inst": "University College London" - }, - { - "author_name": "Anika Knuppel", - "author_inst": "University College London" - }, - { - "author_name": "Dylan M Williams", - "author_inst": "University College London" - }, - { - "author_name": "Olivia K L Hamilton", - "author_inst": "University of Glasgow" - }, - { - "author_name": "Paul H Lee", - "author_inst": "University of Leicester" - }, - { - "author_name": "Charis Bridger Staatz", - "author_inst": "University College London" - }, - { - "author_name": "Giorgio Di Gessa", - "author_inst": "University College London" - }, - { - "author_name": "Jingmin Zhu", - "author_inst": "University College London" - }, - { - "author_name": "Srinivasa Vittal Katikireddi", - "author_inst": "University of Glasgow" - }, - { - "author_name": "George B Ploubidis", - "author_inst": "University College London" - }, - { - "author_name": "Ellen J Thompson", - "author_inst": "King's College London" - }, - { - "author_name": "Ruth C E Bowyer", - "author_inst": "King's College London" - }, - { - "author_name": "Xinyuan Zhang", - "author_inst": "King's College London" - }, - { - "author_name": "Golboo Abbasian", - "author_inst": "King's College London" - }, - { - "author_name": "Maria Paz Garcia", - "author_inst": "King's College London" - }, - { - "author_name": "Deborah Hart", - "author_inst": "King's College London" - }, - { - "author_name": "Jeffrew Seow", - "author_inst": "King's College London" - }, - { - "author_name": "Carl Graham", - "author_inst": "King's College London" - }, - { - "author_name": "Neophytos Kouphou", - "author_inst": "King's College London" - }, - { - "author_name": "Sam Acors", - "author_inst": "King's College London" - }, - { - "author_name": "Michael H Malim", - "author_inst": "King's College London" - }, - { - "author_name": "Ruth E Mitchell", - "author_inst": "University of Bristol" - }, - { - "author_name": "Kate Northstone", - "author_inst": "University of Bristol" + "author_name": "Michelle V Evans", + "author_inst": "Institute de Recherche pour le Developpement" }, { - "author_name": "Daniel Major-Smith", - "author_inst": "University of Bristol" + "author_name": "Tanjona Ramiadantsoa", + "author_inst": "University of Fianarantsoa" }, { - "author_name": "Sarah Matthews", - "author_inst": "University of Bristol" + "author_name": "Andres Garchitorena", + "author_inst": "Institut de Recherche pour le Developpement" }, { - "author_name": "Thomas Breeze", - "author_inst": "University of Bristol" + "author_name": "Kayla Kaffman", + "author_inst": "University of California - Santa Barbara" }, { - "author_name": "Michael Crawford", - "author_inst": "University of Bristol" + "author_name": "James Moody", + "author_inst": "Duke University" }, { - "author_name": "Lynn Molloy", - "author_inst": "University of Bristol" + "author_name": "Charles Nunn", + "author_inst": "Duke University" }, { - "author_name": "Alex Siu Fung Kwong", - "author_inst": "University of Bristol" + "author_name": "Jean Yves Rabezara", + "author_inst": "University of Antsiranana" }, { - "author_name": "Katie J Doores", - "author_inst": "King's College London" + "author_name": "Prisca Raharimalala", + "author_inst": "Andapa" }, { - "author_name": "Nishi Chaturvedi", - "author_inst": "University College London" + "author_name": "Toky M Randriamoria", + "author_inst": "Association Vahatra" }, { - "author_name": "Emma L Duncan", - "author_inst": "King's College London" + "author_name": "Voahangy Soarimalala", + "author_inst": "University of Fianarantsoa" }, { - "author_name": "Nicholas J Timpson", - "author_inst": "University of Bristol" + "author_name": "Georgia Titcomb", + "author_inst": "University ofCalifornia - Santa Barbara" }, { - "author_name": "Claire J Steves", - "author_inst": "King's College London" + "author_name": "Benjamin Roche", + "author_inst": "Institut de Recherche pour le Developpement" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "public and global health" }, { "rel_doi": "10.1101/2022.05.18.22275242", @@ -288986,51 +288669,51 @@ "category": "primary care research" }, { - "rel_doi": "10.1101/2022.05.18.22275203", - "rel_title": "Prevalence and determinants of mental well-being and satisfaction with life among university students amidst COVID-19 pandemic", + "rel_doi": "10.1101/2022.05.20.22275350", + "rel_title": "Parents' intention to vaccinate their child for COVID-19: a cross-sectional survey (CoVAccS - wave 3)", "rel_date": "2022-05-20", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.05.18.22275203", - "rel_abs": "BackgroundThe COVID-19 pandemic has caused a slew of mental illnesses due to a lack of cures and vaccinations, as well as concerns about students well-being and satisfaction with life, resulting in psychological symptoms and dissatisfaction with their lives. As students are highly susceptible to mental health issues, researchers discovered that perceived SWL and MWB decreased. The present study investigated the prevalence and determinants of mental well-being and satisfaction with life among university students in Bangladesh.\n\nMethodsAn e-survey based cross-sectional study was carried out from February to April 2021 among 660 students. A purposive sampling technique was utilized in the study. Self-reported mental well-being and satisfaction with life psychological tools were also used. The e-questionnaire survey was conducted with informed consent and questions were related to socio-demographics, satisfaction with life, and mental well-being scales. Descriptive statistics and multiple regression analysis were performed. The data were rechecked and analyzed with the R programming language\n\nResultsThe prevalence estimates of mental well-being and satisfaction with life were 27% and 13%, respectively. In a total of 660 participants, 58.2% of them were male and the rest of them were female (41.8%). Among the participants, 22.5% suffer the worst conditions regarding their financial conditions, and 16.5% badly seek a job for livelihood.\n\nConclusionThe present findings revealed that the COVID-19 pandemic and longtime educational institution closure significantly affect the students mental health. Students mental well-being was in vulnerable conditions and their satisfaction with life was extremely poor. A comprehensive student psychological support service should be expanded to help students mental health.", + "rel_link": "https://medrxiv.org/cgi/content/short/2022.05.20.22275350", + "rel_abs": "ObjectivesTo investigate UK parents vaccination intention at a time when COVID-19 vaccination was available to some children.\n\nStudy designData reported are from the second wave of a prospective cohort study.\n\nMethodsOnline survey of 270 UK parents (conducted 4-15 October 2021). At this time, vaccination was available to 16- and 17-year-olds and had become available to 12- to 15- year-olds two weeks prior. We asked participants whose child had not yet been vaccinated how likely they were to vaccinate their child for COVID-19. Linear regression analyses were used to investigate factors associated with intention. Parents were also asked for their main reasons behind vaccination intention. Open-ended responses were analysed using content analysis.\n\nResultsParental vaccination intention was mixed (likely: 39.3%, 95% CI 32.8%, 45.7%; uncertain: 33.9%, 27.7%, 40.2%; unlikely: 26.8%, 20.9%, 32.6%). Intention was associated with: parental COVID-19 vaccination status; greater perceived necessity and social norms regarding COVID-19 vaccination; greater COVID-19 threat appraisal; and lower vaccine safety and novelty concerns. In those who intended to vaccinate their child, the main reasons for doing so were to protect the child and others. In those who did not intend to vaccinate their child, the main reason was safety concerns.\n\nConclusionsParent COVID-19 vaccination and psychological factors explained a large percentage of the variance in vaccination intention for ones child. How fluctuating infection rates, more children being vaccinated, and the UKs reliance on vaccination as a strategy to live with COVID-19 may impact parents intention to vaccinate their child requires further study.", "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Md. Safaet Hossain Sujan", - "author_inst": "Department of Public Health and Informatics, Jahangirnagar University, Savar, Dhaka-1342, Bangladesh bCentre for Advanced Research Excellence in Public Health" + "author_name": "Louise E Smith", + "author_inst": "King's College London" }, { - "author_name": "Atefehsadat Haghighathoseini Haghighathoseini", - "author_inst": "Department of Health Administration and Policy, George Mason University" + "author_name": "Susan M Sherman", + "author_inst": "Keele University" }, { - "author_name": "Rafia Tasnim", - "author_inst": "Department of Public Health and Informatics, Jahangirnagar University, Savar, Dhaka-1342, Bangladesh bCentre for Advanced Research Excellence in Public Health, " + "author_name": "Julius Sim", + "author_inst": "Keele University" }, { - "author_name": "Rezaul Karim Ripon", - "author_inst": "Department of Public Health and Informatics, Jahangirnagar University, Savar, Dhaka-1342, Bangladesh" + "author_name": "Richard Amlot", + "author_inst": "UK Health Security Agency" }, { - "author_name": "Sayem Ahmed Ripon", - "author_inst": "Department of Geography and Environmental studies. University of Chittagong" + "author_name": "Megan Cutts", + "author_inst": "Keele University" }, { - "author_name": "Mohammad Mohiuddin Hasan", - "author_inst": "Hospital Services Management, DGHS, Mohakhali, Dhaka-1212, Bangladesh" + "author_name": "Hannah Dasch", + "author_inst": "King's College London" }, { - "author_name": "Muhammad Ramiz Uddin", - "author_inst": "Department of Chemistry and Biochemistry, The university of Oklahoma, Norman, USA" + "author_name": "Nick Sevdalis", + "author_inst": "King's College London" }, { - "author_name": "Most. Zannatul Ferdous", - "author_inst": "Jahangirnagar University" + "author_name": "G James Rubin", + "author_inst": "King's College London" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "psychiatry and clinical psychology" + "category": "public and global health" }, { "rel_doi": "10.1101/2022.05.18.22275293", @@ -290704,67 +290387,43 @@ "category": "pharmacology and toxicology" }, { - "rel_doi": "10.1101/2022.05.16.22274439", - "rel_title": "Neuropathic symptoms with SARS-CoV-2 vaccination", + "rel_doi": "10.1101/2022.05.12.22274953", + "rel_title": "Racial differences in vaccine acceptance in a rural southern US state", "rel_date": "2022-05-17", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.05.16.22274439", - "rel_abs": "Background and ObjectivesVarious peripheral neuropathies, particularly those with sensory and autonomic dysfunction may occur during or shortly after acute COVID-19 illnesses. These appear most likely to reflect immune dysregulation. If similar manifestations can occur with the vaccination remains unknown.\n\nResultsIn an observational study, we studied 23 patients (92% female; median age 40years) reporting new neuropathic symptoms beginning within 1 month after SARS-CoV-2 vaccination. 100% reported sensory symptoms comprising severe face and/or limb paresthesias, and 61% had orthostasis, heat intolerance and palpitations. Autonomic testing in 12 identified seven with reduced distal sweat production and six with positional orthostatic tachycardia syndrome. Among 16 with lower-leg skin biopsies, 31% had diagnostic/subthreshold epidermal neurite densities ([≤]5%), 13% were borderline (5.01-10%) and 19% showed abnormal axonal swelling. Biopsies from randomly selected five patients that were evaluated for immune complexes showed deposition of complement C4d in endothelial cells. Electrodiagnostic test results were normal in 94% (16/17). Together, 52% (12/23) of patients had objective evidence of small-fiber peripheral neuropathy. 58% patients (7/12) treated with oral corticosteroids had complete or near-complete improvement after two weeks as compared to 9% (1/11) of patients who did not receive immunotherapy having full recovery at 12 weeks. At 5-9 months post-symptom onset, 3 non-recovering patients received intravenous immunoglobulin with symptom resolution within two weeks.\n\nConclusionsThis observational study suggests that a variety of neuropathic symptoms may manifest after SARS-CoV-2 vaccinations and in some patients might be an immune-mediated process.", - "rel_num_authors": 12, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.05.12.22274953", + "rel_abs": "IntroductionTo assess vaccine acceptance among adults living in a largely rural Southern state.\n\nMethodsData were collected between October 3 and October 17, 2020 using random digit dialing. Participants included residents aged 18+, able to understand English or Spanish, and provide informed consent. The primary outcome was a multi-dimensional COVID-19 vaccine acceptance measure. Scores varied between -3 to +3.\n\nResultsThe sample (n=1,164) was weighted to be representative of the states population. Black participants had the lowest overall vaccine acceptance (0.5) compared to White participants (1.2). Hispanic participants had the highest scores (1.4). In adjusted models, Black participants had 0.81 points lower acceptance than White participants, and Hispanic participants had 0.35 points higher acceptance. Hispanic participants had the highest scores for all five vaccine acceptance dimensions, relatively equivalent to White participants. Black participants had consistently lower scores, especially perceived vaccine safety (mean -0.2, SD 0.1).\n\nConclusionsThe lowest vaccine acceptance rates were among Black participants particularly on perceived vaccine safety. While Black participants had the lowest acceptance scores, Hispanic participants had the highest. This variability shows the value of a multi-dimensional vaccine acceptance measure to inform COVID-19 vaccination campaign strategies.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Farinaz Safavi", - "author_inst": "NINDS,NIH" - }, - { - "author_name": "Lindsey Gustafson", - "author_inst": "NINDS, NIH" - }, - { - "author_name": "Brian Walitt", - "author_inst": "National Institutes of Health" - }, - { - "author_name": "Tanya Lehky", - "author_inst": "NINDS, NIH" - }, - { - "author_name": "Sara Dehbashi", - "author_inst": "Jefferson University" - }, - { - "author_name": "Amanda Wiebold", - "author_inst": "NINDS, NIH" - }, - { - "author_name": "Yair Mina", - "author_inst": "NINDS, NIH" + "author_name": "Benjamin C. Amick III", + "author_inst": "University of Arkansas for Medical Sciences" }, { - "author_name": "Susan Shin", - "author_inst": "Ichan School of Medicine at Mt Sinai" + "author_name": "Jaimi L. Allen", + "author_inst": "University of Arkansas for Medical Sciences" }, { - "author_name": "Baohan Pan", - "author_inst": "Johns Hopkins University" + "author_name": "Clare C. Brown", + "author_inst": "University of Arkansas for Medical Sciences" }, { - "author_name": "Michael Polydefkis", - "author_inst": "Johns Hopkins University" + "author_name": "Anthony Goudie", + "author_inst": "University of Arkansas for Medical Sciences" }, { - "author_name": "Anne Louise Oaklander", - "author_inst": "Massachusetts General Hospital" + "author_name": "Mick Tilford", + "author_inst": "University of Arkansas for Medical Sciences" }, { - "author_name": "Avindra Nath", - "author_inst": "National Institutes of Health" + "author_name": "Mark Williams", + "author_inst": "University of Arkansas for Medical Sciences" } ], "version": "1", - "license": "cc0", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", - "category": "neurology" + "category": "public and global health" }, { "rel_doi": "10.1101/2022.05.16.492112", @@ -292370,97 +292029,33 @@ "category": "transplantation" }, { - "rel_doi": "10.1101/2022.05.12.22274799", - "rel_title": "A Universal Day Zero Infectious Disease Testing Strategy Leveraging CRISPR-based Sample Depletion and Metagenomic Sequencing", + "rel_doi": "10.1101/2022.05.12.22274991", + "rel_title": "Elevated expression of RGS2 may underlie reduced olfaction in COVID-19 patients", "rel_date": "2022-05-16", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.05.12.22274799", - "rel_abs": "The lack of preparedness for detecting the highly infectious SARS-CoV-2 pathogen, the pathogen responsible for the COVID-19 disease, has caused enormous harm to public health and the economy. It took [~]60 days for the first reverse transcription quantitative polymerase chain reaction (RT-qPCR) tests for SARS-CoV-2 infection developed by the United States Centers for Disease Control (CDC) to be made publicly available. It then took >270 days to deploy 800,000 of these tests at a time when the estimated actual testing needs required over 6 million tests per day. Testing was therefore limited to individuals with symptoms or in close contact with confirmed positive cases. Testing strategies deployed on a population scale at Day Zero i.e., at the time of the first reported case, would be of significant value. Next Generation Sequencing (NGS) has such Day Zero capabilities with the potential for broad and large-scale testing. However, it has limited detection sensitivity for low copy numbers of pathogens which may be present. Here we demonstrate that by using CRISPR-Cas9 to remove abundant sequences that do not contribute to pathogen detection, NGS detection sensitivity of COVID-19 is comparable to RT-qPCR. In addition, we show that this assay can be used for variant strain typing, co-infection detection, and individual human host response assessment, all in a single workflow using existing open-source analysis pipelines. This NGS workflow is pathogen agnostic, and therefore has the potential to transform how both large-scale pandemic response and focused clinical infectious disease testing are pursued in the future.\n\nSIGNIFICANCE STATEMENTThe lack of preparedness for detecting infectious pathogens has had a devastating effect on the global economy and society. Thus, a Day Zero testing strategy, that can be deployed at the first reported case and expanded to population scale, is required. Next generation sequencing enables Day Zero capabilities but is inadequate for detecting low levels of pathogen due to abundant sequences of little biological interest. By applying the CRISPR-Cas system to remove these sequences in vitro, we show sensitivity of pathogen detection equivalent to RT-qPCR. The workflow is pathogen agnostic, and enables detection of strain types, co-infections and human host response with a single workflow and open-source analysis tools. These results highlight the potential to transform future large-scale pandemic response.", - "rel_num_authors": 20, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.05.12.22274991", + "rel_abs": "Anosmia is common in COVID-19 patients, lasting for weeks or months following recovery. The biological mechanism underlying olfactory deficiency in COVID-19 does not involve direct damage to nasal olfactory neurons, which do not express the proteins required for SARS-CoV-2 infection. A recent study suggested that anosmia results from downregulation of olfactory receptors. We hypothesized that anosmia in COVID-19 may also reflect SARS-CoV-2 infection-driven elevated expression of regulator of G protein signaling 2 (RGS2), a key regulator odorant receptor, thereby silencing their signaling. To test our hypothesis, we analyzed gene expression of nasopharyngeal swabs from SARS-CoV-2 positive patients and non-infected controls (two published RNA-sequencing datasets, 580 individuals). Our analysis found upregulated RGS2 expression in SARS-CoV-2 positive patients (FC=14.5, Padj=1.69e-05 and FC=2.4; Padj=0.001, per dataset). Additionally, RGS2 expression was strongly correlated with PTGS2, IL1B, CXCL8, NAMPT and other inflammation markers with substantial upregulation in early infection. These observations suggest that upregulated expression of RGS2 may underlie anosmia in COVID-19 patients. As a regulator of numerous G-protein coupled receptors, RGS2 may drive further neurological symptoms of COVID-19. Studies are required for clarifying the cellular mechanisms by which SARS-CoV-2 infection drives the upregulation of RGS2 and other genes implicated in inflammation. Insights on these pathways may assist in understanding anosmia and additional neurological symptoms reported in COVID-19 patients.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Agnes P Chan", - "author_inst": "The Translational Genomics Research Institute (TGen)" - }, - { - "author_name": "Azeem Siddique", - "author_inst": "Jumpcode Genomics" - }, - { - "author_name": "Yvain Desplat", - "author_inst": "Jumpcode Genomics" - }, - { - "author_name": "Yongwook Choi", - "author_inst": "TGen" - }, - { - "author_name": "Sridhar Ranganathan", - "author_inst": "Jumpcode Genomics" - }, - { - "author_name": "Kumari Sonal Choudhary", - "author_inst": "Jumpcode Genomics" - }, - { - "author_name": "Josh Diaz", - "author_inst": "Jumpcode Genomics" - }, - { - "author_name": "Jon Bezney", - "author_inst": "Jumpcode Genomics" - }, - { - "author_name": "Dante DeAscanis", - "author_inst": "Jumpcode Genomics" - }, - { - "author_name": "Zenas George", - "author_inst": "Jumpcode Genomics" - }, - { - "author_name": "Shukmei Wong", - "author_inst": "TGen" - }, - { - "author_name": "William Selleck", - "author_inst": "TGen" - }, - { - "author_name": "Jolene Bowers", - "author_inst": "TGen" - }, - { - "author_name": "Victoria Zismann", - "author_inst": "TGen" - }, - { - "author_name": "Lauren Reining", - "author_inst": "TGen" - }, - { - "author_name": "Sarah Highlander", - "author_inst": "TGen" - }, - { - "author_name": "Yaron Hakak", - "author_inst": "Jumpcode Genomics" + "author_name": "Eden Avnat", + "author_inst": "Tel Aviv University, Tel Aviv, Israel" }, { - "author_name": "Keith Brown", - "author_inst": "Jumpcode Genomics" + "author_name": "Guy Shapira", + "author_inst": "Tel Aviv University, Tel Aviv, Israel" }, { - "author_name": "Jon Armstrong", - "author_inst": "Jumpcode Genomics" + "author_name": "David Gurwitz", + "author_inst": "Tel Aviv University, Tel Aviv, Israel" }, { - "author_name": "Nicholas J Schork", - "author_inst": "The Translational Genomics Research Institute (TGen)" + "author_name": "Noam Shomron", + "author_inst": "Tel Aviv University, Tel Aviv, Israel" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -294056,135 +293651,27 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2022.05.13.491770", - "rel_title": "Structural insights for neutralization of BA.1 and BA.2 Omicron variants by a broadly neutralizing SARS-CoV-2 antibody", - "rel_date": "2022-05-13", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.05.13.491770", - "rel_abs": "The SARS-CoV-2 BA.1 and BA.2 (Omicron) variants contain more than 30 mutations within the spike protein and evade therapeutic monoclonal antibodies (mAbs). Here, we report a receptor-binding domain (RBD) targeting human antibody (002-S21F2) that effectively neutralizes live viral isolates of SARS-CoV-2 variants of concern (VOCs) including Alpha, Beta, Gamma, Delta, and Omicron (BA.1 and BA.2) with IC50 ranging from 0.02 - 0.05 g/ml. This near germline antibody 002-S21F2 has unique genetic features that are distinct from any reported SARS-CoV-2 mAbs. Structural studies of the full-length IgG in complex with spike trimers (Omicron and WA.1) reveal that 002-S21F2 recognizes an epitope on the outer face of RBD (class-3 surface), outside the ACE2 binding motif and its unique molecular features enable it to overcome mutations found in the Omicron variants. The discovery and comprehensive structural analysis of 002-S21F2 provide valuable insight for broad and potent neutralization of SARS-CoV-2 Omicron variants BA.1 and BA.2.", - "rel_num_authors": 29, + "rel_doi": "10.1101/2022.04.02.22273339", + "rel_title": "Factors Related to Stress in Children with Online Media Learning Methods during a Pandemic at Jaya Mulya 1 Elementary School, Karawang-Indonesia", + "rel_date": "2022-05-12", + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2022.04.02.22273339", + "rel_abs": "Stress on students is a condition that occurs when there is pressure at school that makes students feel burdened. This study aims to determine the factors related to stress in students who attend school with online media during the covid-19 pandemic at SDN Jayamulya 1 Kab. Karawang. This study uses a descriptive analytic design with a cross sectional approach with a population of 57 respondents and the sample used is 57 respondents. The results of this study there is a relationship between high achievement pressure factors and stress with a p-value of 0.022 < 0.05, a busy schedule factor with stress with a p-value of 0.012 < 0.05, academic achievement factors with stress with a p-value of 0.000 <0.05, physical demands factor with stress with p-value 0.036 < 0.05.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Sanjeev Kumar", - "author_inst": "ICGEB-Emory Vaccine Center, International Center for Genetic Engineering and Biotechnology, New Delhi, 110067, India" - }, - { - "author_name": "Anamika Patel", - "author_inst": "Department of Biochemistry, Emory University School of Medicine, Atlanta, GA 30322, USA." - }, - { - "author_name": "Lilin Lai", - "author_inst": "Department of Pediatrics, Emory University School of Medicine, Emory University, Atlanta, GA 30322, USA" - }, - { - "author_name": "Chennareddy Chakravarthy", - "author_inst": "Department of Microbiology and Immunology, Emory University School of Medicine, Emory University, Atlanta, GA 30322, USA; Emory Vaccine Center, Emory University" - }, - { - "author_name": "Rajesh Valanparambil", - "author_inst": "Department of Microbiology and Immunology, Emory University School of Medicine, Emory University, Atlanta, GA 30322, USA; Emory Vaccine Center, Emory University" - }, - { - "author_name": "Meredith E. Davis-Gardner", - "author_inst": "Department of Pediatrics, Emory University School of Medicine, Emory University, Atlanta, GA 30322, USA" - }, - { - "author_name": "Venkata Viswanadh Edara", - "author_inst": "Department of Pediatrics, Emory University School of Medicine, Emory University, Atlanta, GA 30322, USA" - }, - { - "author_name": "Susanne Linderman", - "author_inst": "Department of Microbiology and Immunology, Emory University School of Medicine, Emory University, Atlanta, GA 30322, USA; Emory Vaccine Center, Emory University" - }, - { - "author_name": "Elluri Seetharami Reddy", - "author_inst": "ICGEB-Emory Vaccine Center, International Center for Genetic Engineering and Biotechnology, New Delhi, 110067, India; Kusuma School of Biological Sciences, Indi" - }, - { - "author_name": "Kamalvishnu Gottimukkala", - "author_inst": "ICGEB-Emory Vaccine Center, International Center for Genetic Engineering and Biotechnology, New Delhi, 110067, India" - }, - { - "author_name": "Kaustuv Nayak", - "author_inst": "ICGEB-Emory Vaccine Center, International Center for Genetic Engineering and Biotechnology, New Delhi, 110067, India" - }, - { - "author_name": "Prashant Bajpai", - "author_inst": "ICGEB-Emory Vaccine Center, International Center for Genetic Engineering and Biotechnology, New Delhi, 110067, India" - }, - { - "author_name": "Vanshika Singh", - "author_inst": "ICGEB-Emory Vaccine Center, International Center for Genetic Engineering and Biotechnology, New Delhi, 110067, India" - }, - { - "author_name": "Filipp Frank", - "author_inst": "Department of Biochemistry, Emory University School of Medicine, Atlanta, GA 30322, USA." - }, - { - "author_name": "Narayanaiah Cheedarla", - "author_inst": "Department of Pathology and Laboratory Medicine, Emory University School of Medicine, Atlanta, GA 30322, USA" - }, - { - "author_name": "Hans Verkerke", - "author_inst": "Department of Pathology and Laboratory Medicine, Emory University School of Medicine, Atlanta, GA 30322, USA; Department of Pathology, Brigham and Womens Hospit" - }, - { - "author_name": "Andrew S. Neish", - "author_inst": "Department of Pathology and Laboratory Medicine, Emory University School of Medicine, Atlanta, GA 30322, USA" - }, - { - "author_name": "John D. Roback", - "author_inst": "Department of Pathology and Laboratory Medicine, Emory University School of Medicine, Atlanta, GA 30322, USA" - }, - { - "author_name": "Grace Mantus", - "author_inst": "Department of Pediatrics, Emory University School of Medicine, Emory University, Atlanta, GA 30322, USA; Emory Vaccine Center, Emory University, Atlanta, GA 303" - }, - { - "author_name": "Pawan Kumar Goel", - "author_inst": "Shaheed Hasan Khan Mewat Government Medical College, Haryana, India" - }, - { - "author_name": "Manju Rahi", - "author_inst": "Division of Epidemiology and Communicable Diseases, Indian Council of Medical Research, New Delhi, 110029, India" - }, - { - "author_name": "Carl W. Davis", - "author_inst": "Department of Microbiology and Immunology, Emory University School of Medicine, Emory University, Atlanta, GA 30322, USA; Emory Vaccine Center, Emory University" - }, - { - "author_name": "Jens Wrammert", - "author_inst": "Department of Pediatrics, Emory University School of Medicine, Emory University, Atlanta, GA 30322, USA; Emory Vaccine Center, Emory University, Atlanta, GA 303" - }, - { - "author_name": "Mehul S. Suthar", - "author_inst": "Department of Pediatrics, Emory University School of Medicine, Emory University, Atlanta, GA 30322, USA" - }, - { - "author_name": "Rafi Ahmed", - "author_inst": "Department of Microbiology and Immunology, Emory University School of Medicine, Emory University, Atlanta, GA 30322, USA; Emory Vaccine Center, Emory University" - }, - { - "author_name": "Eric Ortlund", - "author_inst": "Department of Biochemistry, Emory University School of Medicine, Atlanta, GA 30322, USA." + "author_name": "Ratih Bayuningsih", + "author_inst": "STIKes Mitra Keluarga" }, { - "author_name": "Amit Sharma", - "author_inst": "ICMR-National Institute of Malaria Research, Dwarka, New Delhi, 110077, India; Structural Parasitology Group, International Center for Genetic Engineering and B" - }, - { - "author_name": "Kaja Murali Krishna", - "author_inst": "ICGEB-Emory Vaccine Center, International Center for Genetic Engineering and Biotechnology, New Delhi, 110067, India; Emory Vaccine Center and Department of Ped" - }, - { - "author_name": "Anmol Chandele", - "author_inst": "ICGEB-Emory Vaccine Center, International Center for Genetic Engineering and Biotechnology, New Delhi, 110067, India" + "author_name": "Fajar Sidik", + "author_inst": "STIKes Horizon Karawang" } ], "version": "1", "license": "cc_by_nc_nd", - "type": "new results", - "category": "immunology" + "type": "PUBLISHAHEADOFPRINT", + "category": "nursing" }, { "rel_doi": "10.1101/2022.05.12.22274823", @@ -295846,79 +295333,71 @@ "category": "intensive care and critical care medicine" }, { - "rel_doi": "10.1101/2022.05.06.22274739", - "rel_title": "PixelPrint: Three-dimensional printing of realistic patient-specific lung phantoms for validation of computed tomography post-processing and inference algorithms", + "rel_doi": "10.1101/2022.05.08.22274817", + "rel_title": "High but Short-lived anti-SARS-CoV2 neutralizing, IgM, IgA, and IgG levels among mRNA-vaccinees compared to naturally-infected participants", "rel_date": "2022-05-10", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.05.06.22274739", - "rel_abs": "BackgroundRadiomics and other modern clinical decision-support algorithms are emerging as the next frontier for diagnostic and prognostic medical imaging. However, heterogeneities in image characteristics due to variations in imaging systems and protocols hamper the advancement of reproducible feature extraction pipelines. There is a growing need for realistic patient-based phantoms that accurately mimic human anatomy and disease manifestations to provide consistent ground-truth targets when comparing different feature extraction or image cohort normalization techniques.\n\nMaterials and MethodsPixelPrint was developed for 3D-printing lifelike lung phantoms for computed tomography (CT) by directly translating clinical images into printer instructions that control the density on a voxel-by-voxel basis. CT datasets of three COVID-19 pneumonia patients served as input for 3D-printing lung phantoms. Five radiologists rated patient and phantom images for imaging characteristics and diagnostic confidence in a blinded reader study. Linear mixed models were utilized to evaluate effect sizes of evaluating phantom as opposed to patient images. Finally, PixelPrints reproducibility was evaluated by producing four phantoms from the same clinical images.\n\nResultsEstimated mean differences between patient and phantom images were small (0.03-0.29, using a 1-5 scale). Effect size assessment with respect to rating variabilities revealed that the effect of having a phantom in the image is within one-third of the inter- and intra-reader variabilities. PixelPrints production reproducibility tests showed high correspondence among four phantoms produced using the same patient images, with higher similarity scores between high-dose scans of the different phantoms than those measured between clinical-dose scans of a single phantom.\n\nConclusionsWe demonstrated PixelPrints ability to produce lifelike 3D-printed CT lung phantoms reliably. These can provide ground-truth targets for validating the generalizability of inference-based decision-support algorithms between different health centers and imaging protocols, as well as for optimizing scan protocols with realistic patient-based phantoms.", - "rel_num_authors": 15, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.05.08.22274817", + "rel_abs": "1.BackgroundWaning of protection against emerging SARS-CoV-2 variants by pre-existing antibodies elicited due to current vaccination or natural infection is a global concern. Whether this is due to waning of immunity to SARS-COV-2 remains unclear.\n\nAimWe aimed to investigate dynamics of antibody isotype responses among vaccinated naive (VN) and naturally infected (NI) individuals.\n\nMethodsWe followed up antibody levels in COVID-19 mRNA-vaccinated subjects without prior infection (VN, n=100) at two phases: phase-I (P-I) at [~]1.4 and phase-II (P-II) at [~]5.3 months. Antibody levels were compared to those of unvaccinated and naturally infected subjects (NI, n=40) at [~]1.7 (P-1) and 5.2 (P-II) months post-infection. Neutralizing antibodies (NTAb), anti-S-RBD-IgG, -IgM, and anti-S-IgA isotypes were measured.\n\nResultsVN group produced significantly greater antibody responses (p<0.001) than NI group at P-I except for IgM. In VN group, a significant waning in antibody response was observed in all isotypes. There was about [~] a 4-fold decline in NTAb levels (p<0.001), anti-S-RBD-IgG ([~]5-folds, p<0.001), anti-S-RBD-IgM ([~]6-folds, p<0.001), and anti-S1-IgA (2-folds, p<0.001). In NI group, a significant but less steady decline was notable in NTAb ([~]1-folds, p<0.001), anti-S-RBD IgG ([~]1-fold, p=0.005), and S-RBD-IgM ([~]2-folds, p<0.001). Unlike VN group, NI group mounted a lasting anti-S1-IgA response with no significant decline. Anti-S1-IgA levels which were [~]3 folds higher in VN subjects compared to NI in P-1 (p<0.001), dropped to almost same levels, with no significant difference observed between the two groups in P-II.\n\nConclusionWhile double dose mRNA vaccination boosted antibody levels, this \"boost\" was relatively short-lived in vaccinated individuals.", + "rel_num_authors": 13, "rel_authors": [ { - "author_name": "Nadav Shapira", - "author_inst": "University of Pennsylvania" - }, - { - "author_name": "Kevin Donovan", - "author_inst": "University of Pennsylvania" - }, - { - "author_name": "Kai Mei", - "author_inst": "University of Pennsylvania" + "author_name": "Haissam Abou Saleh", + "author_inst": "Qatar University" }, { - "author_name": "Michael Geagan", - "author_inst": "University of Pennsylvania" + "author_name": "Bushra Abo Halawa", + "author_inst": "Qatar University" }, { - "author_name": "Leonid Roshkovan", - "author_inst": "University of Pennsylvania" + "author_name": "Salma Younes", + "author_inst": "Qatar University" }, { - "author_name": "Grace Gang", - "author_inst": "John Hopkins University" + "author_name": "Nadin Younes", + "author_inst": "Qatar University" }, { - "author_name": "Mohammed Abed", - "author_inst": "Ibn Sina University of Medical and Pharmaceutical Sciences" + "author_name": "Duaa Al-Sadeq", + "author_inst": "Qatar University" }, { - "author_name": "Nathaniel B Linna", - "author_inst": "University of Pennsylvania" + "author_name": "Farah Shurrab", + "author_inst": "Qatar University" }, { - "author_name": "Coulter P Cranston", - "author_inst": "University of Pennsylvania" + "author_name": "Na Liu", + "author_inst": "Shenzhen Mindray Bio-Medical Electronics Co., Ltd.," }, { - "author_name": "Ali H Dhanaliwala", - "author_inst": "University of Pennsylvania" + "author_name": "Hamda Qotba", + "author_inst": "Primary Health Care Centers" }, { - "author_name": "Despina Kontos", - "author_inst": "University of Pennsylvania" + "author_name": "Nader AlDewik", + "author_inst": "Hamad Medical Corporation" }, { - "author_name": "Harold I Litt", - "author_inst": "University of Pennsylvania" + "author_name": "Ahmed Ismail", + "author_inst": "Medical Commission Department, Ministry of Public Health" }, { - "author_name": "J Webster Stayman", - "author_inst": "John Hopkins University" + "author_name": "HADI M. YASSINE", + "author_inst": "Qatar University" }, { - "author_name": "Russell T Shinohara", - "author_inst": "University of Pennsylvania" + "author_name": "Laith J Abu-Raddad", + "author_inst": "Weill Cornell Medicine-Qatar" }, { - "author_name": "Peter B No\u00ebl", - "author_inst": "University of Pennsylvania" + "author_name": "Gheyath Nasrallah", + "author_inst": "Qatar University" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "radiology and imaging" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2022.05.10.22274890", @@ -297864,35 +297343,67 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2022.05.06.490962", - "rel_title": "The bacterial lysate Lantigen B reduces the expression of ACE2 on primary oropharyngeal cells", + "rel_doi": "10.1101/2022.05.07.491038", + "rel_title": "Simultaneous and sequential multi-species coronavirus vaccination", "rel_date": "2022-05-08", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.05.06.490962", - "rel_abs": "Angiotensin-converting enzyme2 (ACE2) is the main cell surface receptor of the SARS-CoV-2 spike protein and is expressed in a variety of cell types, including cells of the respiratory tract. A bacterial lysate used for the prophylaxis of respiratory infections (OM-85), was recently shown to downregulate the expression of ACE2 in epithelial cells, suggesting its possible role as a prophylaxis of the onset of COVID19. Another bacterial lysate (Lantigen B, administered sublingually) is used in the prophylaxis of recurrent respiratory tract infections. It contains antigens obtained by chemical lysis from the most representative microbes of the respiratory tract. In this in vitro study, the capacity of Lantigen B to decrease ACE2 in human oropharyngeal cells was evaluated. The study was carried out in 40 healthy donors undergoing oropharyngeal swab for routine SARS-CoV-2 detection. Cells were treated in vitro with a 1:2 of Lantigen B. ACE2 expression was evaluated using a fluorescent anti-ACE2 monoclonal antibody and flow cytometry. A reduction in the number of positive cells was observed in 72% of the patients, while a modulation of ACE2 expression was observed in 62% of the samples. As a control, the expression of the CD54 rhinovirus receptor in the same cells was unaffected. To evaluate the functional effects of down regulation, in a subset of samples, the same oropharynx cells were incubated with Lantigen B and infected with wild-type SARS-CoV-2. After 24 hours, viral RNA, as assessed by rt-PCR, was significantly lower in samples treated with Lantigen B. In conclusion, this study demonstrates that Lantigen B, at a pharmacological dose, modulates the expression of the main SARS-CoV-2 receptor in oropharyngeal cells, and reduces viral yield. This activity could be synergistic with other approaches (vaccination and therapy) by reducing the number of potentially infected cells and thus reducing the effects of SARS-CoV-2 infection.", - "rel_num_authors": 4, + "rel_link": "https://biorxiv.org/cgi/content/short/2022.05.07.491038", + "rel_abs": "Although successful COVID-19 vaccines have been developed, multiple pathogenic coronavirus species exist, urging for development of multi-species coronavirus vaccines. Here we developed prototype LNP-mRNA vaccine candidates against SARS-CoV-2 (Delta variant), SARS-CoV and MERS-CoV, and test how multiplexing of these LNP-mRNAs can induce effective immune responses in animal models. A triplex scheme of LNP-mRNA vaccination induced antigen-specific antibody responses against SARS-CoV-2, SARS-CoV and MERS-CoV, with a relatively weaker MERS-CoV response in this setting. Single cell RNA-seq profiled the global systemic immune repertoires and the respective transcriptome signatures of multiplexed vaccinated animals, which revealed a systemic increase in activated B cells, as well as differential gene expression signatures across major adaptive immune cells. Sequential vaccination showed potent antibody responses against all three species, significantly stronger than simultaneous vaccination in mixture. These data demonstrated the feasibility, antibody responses and single cell immune profiles of multi-species coronavirus vaccination. The direct comparison between simultaneous and sequential vaccination offers insights on optimization of vaccination schedules to provide broad and potent antibody immunity against three major pathogenic coronavirus species.\n\nOne sentence summaryMultiplexed mRNA vaccination in simultaneous and sequential modes provide broad and potent immunity against pathogenic coronavirus species.", + "rel_num_authors": 12, "rel_authors": [ { - "author_name": "Caterina Pizzimenti", - "author_inst": "Department of Research and Development, Bruschettini Ltd, Via Isonzo 6, 16147, Genova, Italy" + "author_name": "Lei Peng", + "author_inst": "Yale University" + }, + { + "author_name": "Zhenhao Fang", + "author_inst": "Yale University" + }, + { + "author_name": "Paul A Renauer", + "author_inst": "Yale University" + }, + { + "author_name": "Andrew McNamara", + "author_inst": "Yale University" + }, + { + "author_name": "Jonathan J Park", + "author_inst": "Yale University" }, { - "author_name": "Paola Pirrello", - "author_inst": "Department of Research and Development, Bruschettini Ltd, Via Isonzo 6, 16147, Genova, Italy" + "author_name": "Qianqian Lin", + "author_inst": "Yale University" }, { - "author_name": "Alessia Ruiba", - "author_inst": "Klinik fur Medicinische Onkologie und Hamatologie, Kantonsspital St. Gallen, Rorschacher Strasse 95, 9007 St Gallen" + "author_name": "Xiaoyu Zhou", + "author_inst": "Yale University" }, { - "author_name": "Giovanni Melioli", - "author_inst": "Laboratory Medicine, Albaro Site, Alliance Medical Diagnostic Ltd, Via Boselli 30, 16146, Genova, Italy" + "author_name": "Matthew B Dong", + "author_inst": "Yale University" + }, + { + "author_name": "Biqing Zhu", + "author_inst": "Yale University" + }, + { + "author_name": "Hongyu Zhao", + "author_inst": "Yale University" + }, + { + "author_name": "Craig B Wilen", + "author_inst": "Yale University" + }, + { + "author_name": "Sidi Chen", + "author_inst": "Yale University" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "new results", - "category": "cell biology" + "category": "immunology" }, { "rel_doi": "10.1101/2022.05.07.22274789", @@ -299550,71 +299061,35 @@ "category": "cell biology" }, { - "rel_doi": "10.1101/2022.05.06.490867", - "rel_title": "SARS-CoV-2 evolution and patient immunological history shape the breadth and potency of antibody-mediated immunity", - "rel_date": "2022-05-06", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.05.06.490867", - "rel_abs": "Since the emergence of SARS-CoV-2, humans have been exposed to distinct SARS-CoV-2 antigens, either by infection with different variants, and/or vaccination. Population immunity is thus highly heterogeneous, but the impact of such heterogeneity on the effectiveness and breadth of the antibody-mediated response is unclear. We measured antibody-mediated neutralisation responses against SARS-CoV-2Wuhan, SARS-CoV-2, SARS-CoV-2{delta} and SARS-CoV-2o pseudoviruses using sera from patients with distinct immunological histories, including naive, vaccinated, infected with SARS-CoV-2Wuhan, SARS-CoV-2 or SARS-CoV-2{delta}, and vaccinated/infected individuals. We show that the breadth and potency of the antibody-mediated response is influenced by the number, the variant, and the nature (infection or vaccination) of exposures, and that individuals with mixed immunity acquired by vaccination and natural exposure exhibit the broadest and most potent responses. Our results suggest that the interplay between host immunity and SARS-CoV-2 evolution will shape the antigenicity and subsequent transmission dynamics of SARS-CoV-2, with important implications for future vaccine design.\n\nAuthor SummaryNeutralising antibodies provide protection against viruses and are generated because of vaccination or prior infections. The main target of anti-SARS-CoV-2 neutralising antibodies is a protein called Spike, which decorates the viral particle and mediates viral entry into cells. As SARS-CoV-2 evolves, mutations accumulate in the spike protein, allowing the virus to escape antibody-mediated immunity and decreasing vaccine effectiveness. Multiple SARS-CoV-2 variants have appeared since the start of the COVID-19 pandemic, causing various waves of infection through the population and infecting-in some cases-people that had been previously infected or vaccinated. Since the antibody response is highly specific, individuals infected with different variants are likely to have different repertoires of neutralising antibodies. We studied the breadth and potency of the antibody-mediated response against different SARS-CoV-2 variants using sera from vaccinated people as well as from people infected with different variants. We show that potency of the antibody response against different SARS-CoV-2 variants depends on the particular variant that infected each person, the exposure type (infection or vaccination) and the number and order of exposures. Our study provides insight into the interplay between virus evolution and immunity, as well as important information for the development of better vaccination strategies.", - "rel_num_authors": 13, + "rel_doi": "10.1101/2022.05.02.22273554", + "rel_title": "Longitudinal analyses of depression and anxiety highlight greater prevalence during COVID-19 lockdowns in the Dutch general population and a continuing increase in suicidal ideation in young adults", + "rel_date": "2022-05-05", + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2022.05.02.22273554", + "rel_abs": "ObjectiveThe pandemic of the coronavirus disease 2019 (COVID-19) has led to an increased burden on mental health. This study therefore investigated the development of major depressive disorder (MDD), generalized anxiety disorder (GAD), and suicidal ideation in the Netherlands during the first fifteen months of the pandemic and three nation-wide lockdowns.\n\nMethodsParticipants of the Lifelines Cohort Study -a Dutch population-based sample-reported current symptoms of MDD and GAD, including suicidal ideation, according to DSM-IV criteria using a digital structured questionnaire. Between March 2020 and June 2021, 36,106 participants (aged 18-96) filled out a total of 629,811 questionnaires across 23 time points. Trajectories over time were estimated using generalized additive models and analyzed in relation to age, sex, and lifetime history of MDD/GAD to identify groups at risk.\n\nResultsWe found non-linear trajectories for MDD and GAD with a higher number of symptoms and prevalence rates during periods of lockdown. The point prevalence of MDD and GAD peaked during the third hard lockdown at 2.88% (95% CI: 2.71%-3.06%) and 2.92% (95% CI: 2.76%-3.08%), respectively, in March 2021. Women, younger adults, and participants with a history of MDD/GAD reported significantly more symptoms. For suicidal ideation, we found a linear increase over time in younger participants which continued even after the lockdowns ended. For example, 4.63% (95% CI: 3.09%-6.96%) of 20-year-old participants reported suicidal ideation at our last measured time point in June 2021, which represents a 4.14x increase since the start of the pandemic.\n\nConclusionsOur study showed greater prevalence of MDD and GAD during COVID-19 lockdowns suggesting that the pandemic and government enacted restrictions impacted mental health in the population. We furthermore found a continuing increase in suicidal ideation in young adults. This warrants for alertness in clinical practice and prioritization of mental health in public health policy.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Maria Manali", - "author_inst": "MRC-University of Glasgow Centre for Virus Research" - }, - { - "author_name": "Laura A Bissett", - "author_inst": "MRC-University of Glasgow Centre for Virus Research" - }, - { - "author_name": "Julien Amat", - "author_inst": "MRC-University of Glasgow Centre for Virus Research" - }, - { - "author_name": "Nicola Logan", - "author_inst": "MRC-University of Glasgow Centre for Virus Research" - }, - { - "author_name": "Sam Scott", - "author_inst": "MRC-University of Glasgow Centre for Virus Research" - }, - { - "author_name": "Ellen Hughes", - "author_inst": "MRC-University of Glasgow Centre for Virus Research" - }, - { - "author_name": "William Harvey", - "author_inst": "MRC-University of Glasgow Centre for Virus Research" - }, - { - "author_name": "Richard Orton", - "author_inst": "MRC-University of Glasgow Centre for Virus Research" - }, - { - "author_name": "Emma Thomson", - "author_inst": "MRC-University of Glasgow Centre for Virus Research" - }, - { - "author_name": "Rory Gunson", - "author_inst": "NHS Greater Glasgow and Clyde" + "author_name": "Anil PS Ori", + "author_inst": "University of Groningen, University Medical Center Groningen" }, { - "author_name": "Mafalda Viana", - "author_inst": "University of Glasgow" + "author_name": "Martijn Wieling", + "author_inst": "University of Groningen" }, { - "author_name": "Brian Willett", - "author_inst": "MRC-University of Glasgow Centre for Virus Research" + "author_name": "- Lifelines Corona Research Initiative", + "author_inst": "-" }, { - "author_name": "Pablo Ramiro Murcia", - "author_inst": "MRC-University of Glasgow Centre for Virus Research" + "author_name": "Hanna M van Loo", + "author_inst": "University of Groningen, University Medical Center Groningen" } ], "version": "1", - "license": "cc_by", - "type": "new results", - "category": "microbiology" + "license": "cc_no", + "type": "PUBLISHAHEADOFPRINT", + "category": "psychiatry and clinical psychology" }, { "rel_doi": "10.1101/2022.04.11.22272364", @@ -301608,51 +301083,151 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2022.05.03.490409", - "rel_title": "Sensitivity of novel SARS-CoV-2 Omicron subvariants, BA.2.11, BA.2.12.1, BA.4 and BA.5 to therapeutic monoclonal antibodies", + "rel_doi": "10.1101/2022.05.03.22274602", + "rel_title": "Accident and emergency (AE) attendance in England following infection with SARS-CoV-2 Omicron or Delta", "rel_date": "2022-05-03", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.05.03.490409", - "rel_abs": "As of May 2022, Omicron BA.2 variant is the most dominant variant in the world. Thereafter, Omicron subvariants have emerged and some of them began outcompeting BA.2 in multiple countries. For instance, Omicron BA.2.11, BA.2.12.1 and BA.4/5 subvariants are becoming dominant in France, the USA and South Africa, respectively. In this study, we evaluated the sensitivity of these new Omicron subvariants (BA.2.11, BA.2.12.1 and BA.4/5) to eight therapeutic monoclonal antibodies (bamlanivimab, bebtelovimab, casirivimab, cilgavimab, etesevimab, imdevimab, sotrovimab and tixagevimab). Notably, we showed that although cilgavimab is antiviral against BA.2, BA.4/5 exhibits higher resistance to this antibody compared to BA.2. Since mutations are accumulated in the spike proteins of newly emerging SARS-CoV-2 variants, we suggest the importance of rapid evaluation of the efficiency of therapeutic monoclonal antibodies against novel SARS-CoV-2 variants.", - "rel_num_authors": 8, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2022.05.03.22274602", + "rel_abs": "The SARS-CoV-2 Omicron variant is increasing in prevalence around the world. Accurate estimation of disease severity associated with Omicron is critical for pandemic planning. We found lower risk of accident and emergency (AE) attendance following SARS-CoV-2 infection with Omicron compared to Delta (HR: 0.39 (95% CI: 0.30 - 0.51; P<.0001). For AE attendances that lead to hospital admission, Omicron was associated with an 85% lower hazard compared with Delta (HR: 0.14 (95% CI: 0.09 - 0.24; P<.0001)).\n\nConflicts of InterestsNothing to declare.\n\nFunding statementThis work was supported by the Medical Research Council MR/V015737/1. TPP provided technical expertise and infrastructure within their data centre pro bono in the context of a national emergency. Rosalind Eggo is funded by HDR UK (grant: MR/S003975/1), MRC (grant: MC_PC 19065), NIHR (grant: NIHR200908).", + "rel_num_authors": 33, "rel_authors": [ { - "author_name": "Daichi Yamasoba", - "author_inst": "The University of Tokyo" + "author_name": "Daniel J Grint", + "author_inst": "London School of Hygiene and Tropical Medicine" }, { - "author_name": "Yusuke Kosugi", - "author_inst": "The University of Tokyo" + "author_name": "Kevin Wing", + "author_inst": "London School of Hygiene and Tropical Medicine" }, { - "author_name": "Izumi Kimura", - "author_inst": "The University of Tokyo" + "author_name": "Hamish P Gibbs", + "author_inst": "London School of Hygiene and Tropical Medicine" }, { - "author_name": "Shigeru Fujita", - "author_inst": "The University of Tokyo" + "author_name": "Stephen JW Evans", + "author_inst": "London School of Hygiene and Tropical Medicine" }, { - "author_name": "Keiya Uriu", - "author_inst": "The University of Tokyo" + "author_name": "Elizabeth J Williamson", + "author_inst": "London School of Hygiene and Tropical Medicine" }, { - "author_name": "Jumpei Ito", - "author_inst": "The Institute of Medical Science, The University of Tokyo" + "author_name": "Krishnan Bhaskaran", + "author_inst": "London School of Hygiene and Tropical Medicine" }, { - "author_name": "Kei Sato", - "author_inst": "Institute of Medical Science, The University of Tokyo" + "author_name": "Helen I McDonald", + "author_inst": "London School of Hygiene and Tropical Medicine" }, { - "author_name": "- The Genotype to Phenotype Japan (G2P-Japan) Consortium", - "author_inst": "-" + "author_name": "Alex J Walker", + "author_inst": "University of Oxford" + }, + { + "author_name": "David Evans", + "author_inst": "University of Oxford" + }, + { + "author_name": "George Hickman", + "author_inst": "University of Oxford" + }, + { + "author_name": "Rohini Mathur", + "author_inst": "London School of Hygiene and Tropical Medicine" + }, + { + "author_name": "Anna Schultze", + "author_inst": "London School of Hygiene and Tropical Medicine" + }, + { + "author_name": "Christopher T Rentsch", + "author_inst": "London School of Hygiene and Tropical Medicine" + }, + { + "author_name": "John Tazare", + "author_inst": "London School of Hygiene and Tropical Medicine" + }, + { + "author_name": "Ian J Douglas", + "author_inst": "London School of Hygiene and Tropical Medicine" + }, + { + "author_name": "Helen J Curtis", + "author_inst": "University of Oxford" + }, + { + "author_name": "Caroline E Morton", + "author_inst": "University of Oxford" + }, + { + "author_name": "Sebastian CJ Bacon", + "author_inst": "University of Oxford" + }, + { + "author_name": "Simon Davy", + "author_inst": "University of Oxford" + }, + { + "author_name": "Brian MacKenna", + "author_inst": "University of Oxford" + }, + { + "author_name": "Peter Inglesby", + "author_inst": "University of Oxford" + }, + { + "author_name": "Richard Croker", + "author_inst": "University of Oxford" + }, + { + "author_name": "John Parry", + "author_inst": "TPP" + }, + { + "author_name": "Frank Hester", + "author_inst": "TPP" + }, + { + "author_name": "Sam Harper", + "author_inst": "TPP" + }, + { + "author_name": "Nicholas J DeVito", + "author_inst": "University of Oxford" + }, + { + "author_name": "William J Hulme", + "author_inst": "University of Oxford" + }, + { + "author_name": "Christopher Bates", + "author_inst": "TPP" + }, + { + "author_name": "Jonathan Cockburn", + "author_inst": "TPP" + }, + { + "author_name": "Amir Mehrkar", + "author_inst": "University of Oxford" + }, + { + "author_name": "Ben Goldacre", + "author_inst": "University of Oxford" + }, + { + "author_name": "Rosalind M Eggo", + "author_inst": "London School of Hygiene and Tropical Medicine" + }, + { + "author_name": "Laurie Tomlinson", + "author_inst": "London School of Hygiene and Tropical Medicine" } ], "version": "1", - "license": "cc_by_nc_nd", - "type": "new results", - "category": "microbiology" + "license": "cc_by", + "type": "PUBLISHAHEADOFPRINT", + "category": "infectious diseases" }, { "rel_doi": "10.1101/2022.04.28.22274421", @@ -303626,81 +303201,53 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2022.04.29.22274455", - "rel_title": "Protection against Omicron re-infection conferred by prior heterologous SARS-CoV-2 infection, with and without mRNA vaccination", + "rel_doi": "10.1101/2022.04.27.22274270", + "rel_title": "Clinical Features and Outcomes of COVID-19 at a Teaching Hospital in Kingston, Jamaica", "rel_date": "2022-04-29", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.04.29.22274455", - "rel_abs": "ImportanceOmicron is phylogenetically- and antigenically-distinct from earlier SARS-CoV-2 variants and the original vaccine strain. Protection conferred by prior SARS-CoV-2 infection against Omicron re-infection, and the added value of vaccination, require quantification.\n\nObjectiveTo estimate protection against Omicron re-infection and hospitalization conferred by prior heterologous SARS-CoV-2 (non-Omicron) infection and/or up to three doses of (ancestral, Wuhan-like) mRNA vaccine.\n\nDesignTest-negative study between December 26 (epi-week 52), 2021 and March 12 (epi-week 10), 2022.\n\nSettingPopulation-based, province of Quebec, Canada\n\nParticipantsCommunity-dwelling [≥]12-year-olds tested for SARS-CoV-2.\n\nExposuresPrior laboratory-confirmed infection with/without mRNA vaccination.\n\nOutcomesLaboratory-confirmed SARS-CoV-2 re-infection and hospitalization, presumed Omicron by genomic surveillance. The odds of prior non-Omicron infection with/without vaccination were compared among Omicron cases/hospitalizations versus test-negative controls (single randomly-selected per individual). Adjusted odds ratios controlled for age, sex, testing-indication and epi-week. Analyses were stratified by severity and time since last non-Omicron infection or vaccine dose.\n\nResultsWithout vaccination, prior non-Omicron infection reduced the Omicron re-infection risk by 44% (95%CI:38-48), decreasing from 66% (95%CI:57-73) at 3-5 months to 35% (95%CI:21-47) at 9-11 months post-infection and <30% thereafter. The more severe the prior infection, the greater the risk reduction: 8% (95%CI:17-28), 43% (95%CI:37-49) and 68% (95%CI:51-80) for prior asymptomatic, symptomatic ambulatory or hospitalized infections. mRNA vaccine effectiveness against Omicron infection was consistently significantly higher among previously-infected vs. non-infected individuals at 65% (95%CI:63-67) vs. 20% (95%CI:16-24) for one-dose; 68% (95%CI:67-70) vs. 42% (95%CI:41-44) for two doses; and 83% (95%CI:81-84) vs. 73% (95%CI:72-73) for three doses.\n\nInfection-induced protection against Omicron hospitalization was 81% (95%CI: 66-89) increasing to 86% (95%CI:77-99) with one, 94% (95%CI:91-96) with two and 97%(95%CI:94-99) with three mRNA vaccine doses. Two-dose effectiveness against hospitalization among previously-infected individuals did not wane across 11 months and did not significantly differ from three-dose effectiveness despite longer follow-up (median 158 and 27 days, respectively).\n\nConclusions and relevancePrior heterologous SARS-CoV-2 infection provided substantial and sustained protection against Omicron hospitalization, greatest among those also vaccinated. In the context of program goals to prevent severe outcomes and preserve healthcare system capacity, >2 doses of ancestral Wuhan-like vaccine may be of marginal incremental value to previously-infected individuals.", - "rel_num_authors": 16, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.04.27.22274270", + "rel_abs": "ObjectiveWe examined the demographic, clinical characteristics and indicators of poor outcomes among hospitalized adults with COVID-19 at the University Hospital of the West Indies, Jamaica.\n\nMethodsA retrospective medical record review between March 10 and December 31, 2020 analyzed data for 362 participants.\n\nResultsThere were 218 males (mean age 59.5 years) and 144 females (mean age 55.7 years). Hypertension, diabetes mellitus, cardiovascular disease, obesity and chronic kidney disease were the most common comorbidities. Cough, shortness of breath, fever and malaise were the most common presenting complaints. Fifty-one percent of patients were moderately to severely ill on admission; 11% were critically ill; 18% were admitted to the Intensive Care Unit (ICU). Death occurred in 62 (17%) patients (95% CI 13.6-21.4%). Among obese participants, there were increased odds of developing respiratory failure (OR 5.2, p < 0.001), acute kidney injury (OR 4.7, p < 0.001), sepsis (OR 2.9, p =0.013) and the need for ICU care (OR 3.7, p < 0.001). Factors independently associated with increased odds of death were age (OR 1.03 per year, p = 0.013) and obesity (OR 2.26, p = 0.017). Mortality also correlated significantly with D-dimer > 1000 ng/ml (OR 2.78; p = 0.03), serum albumin < 40 g/L (OR 3.54; p = 0.03) and serum LDH > 485 U/L OR 1.92, p = 0.11).\n\nConclusionsTargeted interventions among these high-risk patient subgroups may reduce in-patient morbidity and mortality.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Sara Carazo", - "author_inst": "Biological and occupational risks unit. Institut national de sant\u00e9 publique du Qu\u00e9bec, Quebec city, Quebec, Canada" - }, - { - "author_name": "Danuta M Skowronski", - "author_inst": "BC Centre for Disease Control, Vancouver, British Columbia, Canada" - }, - { - "author_name": "Marc Brisson", - "author_inst": "Centre Hospitalier Universitaire (CHU) de Qu\u00e9bec Universit\u00e9 Laval Research Center, Quebec city, Quebec, Canada" - }, - { - "author_name": "Chantal Sauvageau", - "author_inst": "Biological and occupational risks unit. Institut national de sant\u00e9 publique du Qu\u00e9bec, Quebec city, Quebec, Canada" - }, - { - "author_name": "Nicholas Brousseau", - "author_inst": "Biological and occupational risks unit. Institut national de sant\u00e9 publique du Qu\u00e9bec, Quebec city, Quebec, Canada" - }, - { - "author_name": "Rodica Gilca", - "author_inst": "Biological and occupational risks unit. Institut national de sant\u00e9 publique du Qu\u00e9bec, Quebec city, Quebec, Canada" - }, - { - "author_name": "Manale Ouakki", - "author_inst": "Biological and occupational risks unit. Institut national de sant\u00e9 publique du Qu\u00e9bec, Quebec city, Quebec, Canada" - }, - { - "author_name": "Sapha Barkati", - "author_inst": "Department of Medicine, Division of infectious diseases, McGill University Health Center, McGill University, Montreal, Quebec, Canada" + "author_name": "Tamara K Thompson", + "author_inst": "University Of The West Indies, Department of Medicine, Mona, Jamaica" }, { - "author_name": "Judith Fafard", - "author_inst": "Laboratoire de Sant\u00e9 Publique du Qu\u00e9bec, Institut national de sant\u00e9 publique du Qu\u00e9bec, Sainte-Anne-de-Bellevue, Quebec, Canada" + "author_name": "Yvonne Dawkins", + "author_inst": "University of The West Indies, Department of Medicine, Mona, Jamaica" }, { - "author_name": "Denis Talbot", - "author_inst": "Centre Hospitalier Universitaire (CHU) de Qu\u00e9bec Universit\u00e9 Laval Research Center, Quebec city, Quebec, Canada" + "author_name": "Swane Rowe-Gardener", + "author_inst": "University of The West Indies, Department of Medicine, Mona, Jamaica" }, { - "author_name": "Vladimir Gilca", - "author_inst": "Biological and occupational risks unit. Institut national de sant\u00e9 publique du Qu\u00e9bec, Quebec city, Quebec, Canada" + "author_name": "Lisa Chin-Harty", + "author_inst": "University of The West Indies, Department of Medicine, Mona, Jamaica" }, { - "author_name": "Genevi\u00e8ve Deceuninck", - "author_inst": "Centre Hospitalier Universitaire (CHU) de Qu\u00e9bec Universit\u00e9 Laval Research Center, Quebec city, Quebec, Canada" + "author_name": "Kyaw Kyaw Hoe", + "author_inst": "University of The West Indies, Department of Medicine, Mona, Jamaica" }, { - "author_name": "Christophe Garenc", - "author_inst": "Biological and occupational risks unit. Institut national de sant\u00e9 publique du Qu\u00e9bec, Quebec city, Quebec, Canada" + "author_name": "Kelvin Ehikhametalor", + "author_inst": "University of the West Indies, Department of Surgery, Radiology, Anesthesia and Intensive Care, Mona, Jamaica" }, { - "author_name": "Alex Carignan", - "author_inst": "Department of microbiology and infectious diseases, Sherbrook University, Sherbrook, Quebec, Canada" + "author_name": "Trevor S Ferguson", + "author_inst": "Caribbean Institute for Health Research, The University of the West Indies; Department of Medicine, University of The West Indies, Mona, Jamaica" }, { - "author_name": "Philippe De Wals", - "author_inst": "Biological and occupational risks unit. Institut national de sant\u00e9 publique du Qu\u00e9bec, Quebec city, Quebec, Canada" + "author_name": "Kelly-Ann Gordon-Johnson", + "author_inst": "Centers for Disease Control and Prevention, Caribbean Regional Office (CDC/CRO)" }, { - "author_name": "Gaston De Serres", - "author_inst": "Biological and occupational risks unit. Institut national de sant\u00e9 publique du Qu\u00e9bec, Quebec city, Quebec, Canada" + "author_name": "Varough Deyde", + "author_inst": "Centers for Disease Control and Prevention, Caribbean Regional Office (CDC/CRO)" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -305644,111 +305191,23 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.04.25.22274187", - "rel_title": "Partial ORF1ab Gene Target Failure with Omicron BA.2.12.1", + "rel_doi": "10.1101/2022.04.26.22274335", + "rel_title": "Incorporating Vaccination into Compartment Models for Infectious Diseases", "rel_date": "2022-04-28", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.04.25.22274187", - "rel_abs": "Mutations in the viral genome of SARS-CoV-2 can impact the performance of molecular diagnostic assays. In some cases, such as S gene target failure, the impact can serve as a unique indicator of a particular SARS-CoV-2 variant and provide a method for rapid detection. Here we describe partial ORF1ab gene target failure (pOGTF) on the cobas(R) SARS-CoV-2 assays, defined by a [≥]2 thermocycles delay in detection of the ORF1ab gene compared to the E gene. We demonstrate that pOGTF is 97% sensitive and 99% specific for SARS-CoV-2 lineage BA.2.12.1, an emerging variant in the United States with spike L452Q and S704L mutations that may impact transmission, infectivity, and/or immune evasion. Increasing rates of pOGTF closely mirrored rates of BA.2.12.1 sequences uploaded to public databases, and, importantly increasing local rates of pOGTF also mirrored increasing overall test positivity. Use of pOGTF as a proxy for BA.2.12.1 provides faster tracking of the variant than whole-genome sequencing and can benefit laboratories without sequencing capabilities.", - "rel_num_authors": 23, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.04.26.22274335", + "rel_abs": "The standard way of incorporating mass vaccination into a compartment model for an infectious disease is as a spontaneous transition process that applies to the entire susceptible class. The large degree of COVID-19 vaccine refusal, hesitancy, and ineligibility, and initial limitations of supply and distribution require reconsideration of this standard treatment. In this paper, we address these issues for models on endemic and epidemic time scales. On an endemic time scale, we partition the susceptible class into prevaccinated and unprotected subclasses and show that vaccine refusal/hesitancy/ineligibility has a significant impact on endemic behavior, particularly for diseases where immunity is short-lived. On an epidemic time scale, we develop a supply-limited Holling type 3 vaccination model and show that it is an excellent fit to vaccination data. We also extend the Holling model to a COVID-19 scenario in which the population is divided into two risk classes, with the highrisk class being prioritized for vaccination. For both cases with and without stratification by risk, we see significant differences in epidemiological outcomes between the Holling vaccination model and naive models. Finally, we use the new model to explore implications for public health policies in future pandemics.", + "rel_num_authors": 1, "rel_authors": [ { - "author_name": "Kyle G Rodino", - "author_inst": "University of Pennsylvania Perelman School of Medicine" - }, - { - "author_name": "David R. Peaper", - "author_inst": "Yale University" - }, - { - "author_name": "Brendan J Kelly", - "author_inst": "University of Pennsylvania Perelman School of Medicine" - }, - { - "author_name": "Frederic Bushman", - "author_inst": "University of Pennsylvania" - }, - { - "author_name": "Andrew Marques", - "author_inst": "University of Pennsylvania Perelman School of Medicine" - }, - { - "author_name": "Hriju Adhikari", - "author_inst": "University of Pennsylvania Perelman School of Medicine" - }, - { - "author_name": "Zheng Jin Tu", - "author_inst": "Cleveland Clinic" - }, - { - "author_name": "Rebecca Marrero Rolon", - "author_inst": "Weill Cornell Medicine" - }, - { - "author_name": "Lars F Westblade", - "author_inst": "Weill Cornell Medicine" - }, - { - "author_name": "Daniel Green", - "author_inst": "Columbia University Irving Medical Center" - }, - { - "author_name": "Gregory J Berry", - "author_inst": "Columbia University Medical Center" - }, - { - "author_name": "Fann Wu", - "author_inst": "Columbia University Irving Medical Center" - }, - { - "author_name": "Medini K Annavajhala", - "author_inst": "Columbia University Irving Medical Center" - }, - { - "author_name": "Anne-Catrin Uhlemann", - "author_inst": "Columbia University Medical Center" - }, - { - "author_name": "Bijal A Parikh", - "author_inst": "Washington University School of Medicine" - }, - { - "author_name": "Tracy McMillen", - "author_inst": "Memorial Sloan Kettering Cancer Center" - }, - { - "author_name": "Krupa Jani", - "author_inst": "Memorial Sloan Kettering Cancer Center" - }, - { - "author_name": "N. Esther Babady", - "author_inst": "Memorial Sloan Kettering Cancer Center" - }, - { - "author_name": "Anne M Hahn", - "author_inst": "Yale School of Public Health" - }, - { - "author_name": "Robert T Koch", - "author_inst": "Yale School of Public Health" - }, - { - "author_name": "Nathan D Grubaugh", - "author_inst": "Yale School of Public Health" - }, - { - "author_name": "- Yale SARS-CoV-2 Genomic Surveillance Initiative", - "author_inst": "" - }, - { - "author_name": "Daniel D Rhoads", - "author_inst": "Cleveland Clinic" + "author_name": "Glenn Ledder", + "author_inst": "University of Nebraska-Lincoln" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2022.04.26.22274256", @@ -307354,35 +306813,55 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.04.26.22274244", - "rel_title": "The impact of COVID-19 pandemic on bronchiolitis (lower respiratory tract infection) due to respiratory syncytial virus: A systematic review and meta-analysis", + "rel_doi": "10.1101/2022.04.26.489630", + "rel_title": "P681 mutations within the polybasic motif of spike dictate fusogenicity and syncytia formation of SARS CoV-2 variants", "rel_date": "2022-04-27", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.04.26.22274244", - "rel_abs": "BackgroundThe COVID-19 pandemic has changed the epidemiology of RSV infection which accounts for most bronchiolitis cases and viral pneumonias in infants.\n\nAimThis systematic review and meta-analysis aimed to quantitatively assess the effect of COVID-19 pandemic on respiratory syncytial virus (RSV) associated bronchiolitis among hospitalised infants globally.\n\nMethodsThe study protocol was registered in the PROSPERO database (CRD42022314000) and was designed based on PRISMA guidelines updated in May 2020. An electronic search of PubMed/MEDLINE, Scopus and Google Scholar was carried out for articles regarding the impact of the COVID-19 pandemic on bronchiolitis or lower respiratory tract infection due to the respiratory syncytial virus in English published between January 2019 and March 2022. The meta-analysis component was modified appropriately to synthesise the pooled proportion of infants having RSV-associated bronchiolitis before the COVID-19 pandemic in 2019 and during the pandemic with 95% confidence interval (CI).\n\nResultsWe screened 189 articles and systematically reviewed fifty studies reporting RSV-associated bronchiolitis cases in infants before the pandemic in 2019 and during the pandemic in 2020/2021. Eight qualified studies from Europe and China, which reported RSV-bronchiolitis both in 2019 and in 2020/21 were pooled by random-effects meta-analysis. These studies comprised 109,186 symptomatic cases of bronchiolitis before the pandemic in 2019 and 61,982 cases in 2020-2021. The quantitative analysis included laboratory-confirmed RSV infection in 7691 infants with bronchiolitis reported before the pandemic in 2019. Meanwhile, during the pandemic, 4964 bronchiolitis cases were associated with RSV infection. The pooled proportion of RSV-associated bronchiolitis cases before the pandemic in 2019 was 16.74% (95% CI 11.73, 22.43%, 95% prediction interval 0.032, 34.16). The pooled proportion of confirmed RSV cases during the pandemic in 2020/2021 was 19.20 % (95% CI 12.01, 27.59%, 95% prediction interval 0.046, 42.35).\n\nConclusionThere was an increase in RSV activity after the relaxation of stringent public health measures during the COVID-19 pandemic.\n\nKey Messages (Provide appropriate messages of about 35-50 words to be printed in centre box)O_LIThis systematic review and meta-analysis reports the pooled proportion of RSV associated bronchiolitis cases in 2019 (before the COVID-19 pandemic) and during the pandemic.\nC_LIO_LIEight observational studies from China and Europe were qualified for the meta-analysis.\nC_LIO_LIA decline in reported cases of bronchiolitis was observed during the COVID-19 pandemic which might be attributed to non-pharmaceutical measures and a fall in the hospitalisation rates of respiratory non-SARS-CoV-2 infections.\nC_LIO_LIThe pooled proportion of RSV positivity rate among bronchiolitis cases was more during the COVID-19 pandemic.\nC_LI", - "rel_num_authors": 4, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2022.04.26.489630", + "rel_abs": "The rapid spread and dominance of the Omicron SARS-CoV-2 over its Delta variant has posed severe global challenges. While extensive research on the role of the Receptor Binding Domain on viral infectivity and vaccine sensitivity has been documented, the role of the spike 681PRRAR/SV687 polybasic motif is less clear. Here we monitored infectivity and vaccine sensitivity of Omicron SARS-CoV-2 pseudovirus against sera samples that were drawn four months post administration of the third dose of BNT162b2 mRNA vaccine. Our findings show that relative to Wuhan-Hu and Delta SARS-CoV-2, Omicron displayed enhanced infectivity and a sharp decline in its sensitivity to vaccine-induced neutralizing antibodies. Furthermore, while the spike proteins form Wuhan-Hu (P681), Omicron (H681) and BA.2 (H681) pseudoviruses modestly promoted cell fusion and syncytia formation, Delta spike (P681R) displayed enhanced fusogenic activity and syncytia formation capability. Live-viruses plaque formation assays confirmed these findings and demonstrated that relatively to the Wuhan-Hu and Omicron SARS-CoV-2, Delta formed more plaques that were smaller in size. Introducing a single P681R point mutation within the Wuhan-Hu spike, or H681R within Omicron spike, restored fusion potential to similar levels observed for Delta spike. Conversely, a R681P point mutation within Delta spike efficiency abolished fusion potential. We conclude that over time, the efficiency of the third dose of the Pfizer vaccine against SARS CoV-2 is waned, and cannot neutralize Omicron. We further verify that the P681 position of the viral spike dictates fusogenicity and syncytia formation.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Sasidharanpillai Sabeena", - "author_inst": "Independent Researcher" + "author_name": "Alona Kuzmina", + "author_inst": "Ben-Gurion University of the Negev" }, { - "author_name": "Nagaraja Ravishankar", - "author_inst": "Vallabhbhai Patel Chest Institute, New Delhi" + "author_name": "Nofar Atari", + "author_inst": "Central Virology Laboratory, Public Health Services, Ministry of Health and Sheba Medical" }, { - "author_name": "Sudandiradas Robin", - "author_inst": "Manipal Academy of Higher Education" + "author_name": "Aner Ottolenghi", + "author_inst": "Ben Gurion University of the Negev" }, { - "author_name": "Sabitha Sasidharan Pillai", - "author_inst": "Warren Alpert Medical School of Brown University, Providence, USA" + "author_name": "Dina Korovin", + "author_inst": "Ben-Gurion University of the Negev" + }, + { + "author_name": "Ido Cohen Lass", + "author_inst": "Ben-Gurion University of the Negev" + }, + { + "author_name": "Benyamin Rosental", + "author_inst": "Ben Gurion University of the Negev" + }, + { + "author_name": "Eli Rosenberg", + "author_inst": "Soroka Medical Center" + }, + { + "author_name": "Michal Mandelboim", + "author_inst": "Chaim Sheba Medical Center" + }, + { + "author_name": "Ran Taube", + "author_inst": "Ben-Gurion University of the Negev" } ], "version": "1", - "license": "cc_by_nc_nd", - "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "license": "cc_no", + "type": "new results", + "category": "microbiology" }, { "rel_doi": "10.1101/2022.04.23.22273730", @@ -309164,35 +308643,39 @@ "category": "health economics" }, { - "rel_doi": "10.1101/2022.04.22.22274137", - "rel_title": "A within-host model of SARS-CoV-2 infection", + "rel_doi": "10.1101/2022.04.22.22274163", + "rel_title": "Predicting past and future SARS-CoV-2-related sick leave using discrete time Markov modelling", "rel_date": "2022-04-22", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.04.22.22274137", - "rel_abs": "Within-host models have been used to successfully describe the dynamics of multiple viral infections, however, the dynamics of SARS-CoV-2 virus infection remain poorly understood. A greater understanding of how the virus interacts with the host can contribute to more realistic epidemiological models and help evaluate the effect of antiviral therapies and vaccines. Here, we present a within-host model to describe SARS-CoV-2 viral dynamics in the upper respiratory tract of individuals enrolled in the UK COVID-19 Human Challenge Study. Using this model, we investigate the viral dynamics and provide timescales of infection that independently verify key epidemiological parameters important in the management of an epidemic. In particular, we estimate that an infected individual is first capable of transmitting the virus after approximately 2.1 days, remains infectious for a further 8.3 days, but can continue to test positive using a PCR test for up to 27 days.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.04.22.22274163", + "rel_abs": "BackgroundPrediction of SARS-CoV-2-induced sick leave among healthcare workers (HCWs) is essential for being able to plan the healthcare response to the epidemic.\n\nMethodsDuring first wave of the SARS-Cov-2 epidemic (April 23rd to June 24th, 2020), the HCWs in the greater Stockholm region in Sweden were invited to a study of past or present SARS-CoV-2 infection. We develop a discrete time Markov model using a cohort of 9449 healthcare workers (HCWs) who had complete data on SARS-CoV-2 RNA and antibodies as well as sick leave data for the calendar year 2020. The one-week and standardized longer term transition probabilities of sick leave and the ratios of the standardized probabilities for the baseline covariate distribution were compared with the referent period (an independent period when there were no SARS-CoV-2 infections) in relation to PCR results, serology results and gender.\n\nResultsThe one-week probabilities of transitioning from healthy to partial sick leave or full sick leave during the outbreak as compared to after the outbreak were highest for healthy HCWs testing positive for large amounts of virus (3.69, (95% confidence interval, CI: 2.44-5.59) and 6.67 (95% CI: 1.58-28.13), respectively). The proportion of all sick leaves attributed to COVID-19 during outbreak was at most 55% (95% CI: 50%-59%).\n\nConclusionsA robust Markov model enabled use of simple SARS-CoV-2 testing data for quantifying past and future COVID-related sick leave among HCWs, which can serve as a basis for planning of healthcare during outbreaks.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Jonathan Carruthers", - "author_inst": "United Kingdom Health Security Agency" + "author_name": "Jiayao Lei", + "author_inst": "Karolinska Institutet" }, { - "author_name": "Jingsi Xu", - "author_inst": "University of Manchester" + "author_name": "Mark Clements", + "author_inst": "Karolinska Institute: Karolinska Institutet" }, { - "author_name": "Thomas James Ronald Finnie", - "author_inst": "United Kingdom Health Security Agency" + "author_name": "Miriam Elfstr\u00f6m", + "author_inst": "Karolinska Institutet" }, { - "author_name": "Ian Hall", - "author_inst": "University of Manchester" + "author_name": "Kalle Conneryd Lundgren", + "author_inst": "Karolinska Hospital: Karolinska Universitetssjukhuset" + }, + { + "author_name": "Joakim Dillner", + "author_inst": "Karolinska Universitetssjukhuset" } ], "version": "1", "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2022.04.19.22274028", @@ -312414,45 +311897,93 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2022.04.18.22273880", - "rel_title": "Changes of LipoxinA4 Levels Following Early Hospital Management of Patients with Non-Severe COVID-19: A Pilot Study", + "rel_doi": "10.1101/2022.04.19.22274056", + "rel_title": "Effectiveness of Primary and Booster COVID-19 mRNA Vaccination against Infection Caused by the SARS-CoV-2 Omicron Variant in People with a Prior SARS-CoV-2 Infection", "rel_date": "2022-04-20", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.04.18.22273880", - "rel_abs": "LipoxinA4 (LXA4) is an anti-inflammatory biomarker participating in the active process of inflammation resolution, which is suggested to be effective on infectious and inflammatory diseases like COVID-19. In this study, we hypothesized that LXA4 levels may increase following COVID-19 treatment and are even more accurate than commonly used inflammatory markers such as erythrocyte sedimentation rate (ESR), c-reactive protein (CRP), and ferritin. To test this hypothesis, a pilot study was conducted with 31 adult hospitalized patients with non-severe COVID-19. LXA4 levels were measured at the baseline and 48-72 hours later. Accordingly, ESR and CRP levels were collected on the first day of hospitalization. Moreover, the maximum serum ferritin levels were collected during the five days. LXA4 levels significantly increased at 48-72 hours compared to the baseline. ESR, CRP, and ferritin levels were positively correlated with the increased LXA4. In contrast, aging was shown to negatively correlate with the increased LXA4 levels. LXA4 may be known as a valuable marker to assess the treatment response among non-elderly patients with non-severe COVID-19. Furthermore, LXA4 could be considered as a potential treatment option under inflammatory conditions. Further studies are necessary to clarify LXA4 role in COVID-19 pathogenesis, as well as the balance between such pro-resolving mediators and inflammatory parameters.", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.04.19.22274056", + "rel_abs": "BackgroundThe benefit of vaccination in people who experienced a prior SARS-CoV-2 infection remains unclear.\n\nObjectiveTo estimate the effectiveness of primary (two-dose) and booster (third dose) vaccination against Omicron infection among people with a prior documented infection.\n\nDesignTest-negative case-control study.\n\nSettingYale New Haven Health System facilities.\n\nParticipantsVaccine eligible people who received SARS-CoV-2 RT-PCR testing between November 1, 2021, and January 31, 2022.\n\nMeasurementsWe conducted two analyses, each with an outcome of Omicron BA.1 infection (S-gene target failure defined) and each stratified by prior SARS-CoV-2 infection status. We estimated the effectiveness of primary and booster vaccination. To test whether booster vaccination reduced the risk of infection beyond that of the primary series, we compared the odds among boosted and booster eligible people.\n\nResultsOverall, 10,676 cases and 119,397 controls were included (6.1% and 7.8% occurred following a prior infection, respectively). The effectiveness of primary vaccination 14-149 days after 2nd dose was 36.1% (CI, 7.1% to 56.1%) for people with and 28.5% (CI, 20.0% to 36.2%) without prior infection. The odds ratio comparing boosted and booster eligible people with prior infection was 0.83 (CI, 0.56 to 1.23), whereas the odds ratio comparing boosted and booster eligible people without prior infection was 0.51 (CI, 0.46 to 0.56).\n\nLimitationsMisclassification, residual confounding, reliance on TaqPath assay analyzed samples.\n\nConclusionWhile primary vaccination provided protection against BA.1 infection among people with and without prior infection, booster vaccination was only associated with additional protection in people without prior infection. These findings support primary vaccination in people regardless of prior infection status but suggest that infection history should be considered when evaluating the need for booster vaccination.\n\nPrimary Funding SourceBeatrice Kleinberg Neuwirth and Sendas Family Funds, Merck and Co through their Merck Investigator Studies Program, and the Yale Schools of Public Health and Medicine.", + "rel_num_authors": 20, "rel_authors": [ { - "author_name": "Farzaneh Jamali", - "author_inst": "Tehran University of Medical Sciences" + "author_name": "Margaret Lind", + "author_inst": "Yale University" }, { - "author_name": "Bita Shahrami", - "author_inst": "Tehran University of Medical Sciences" + "author_name": "Alexander James Robertson", + "author_inst": "Yale University" }, { - "author_name": "Amirmahdi Mojtahedzadeh", - "author_inst": "Semmelweis University" + "author_name": "Julio Silva", + "author_inst": "Yale School of Medicine" }, { - "author_name": "Farhad Najmeddin", - "author_inst": "Tehran University of Medical Sciences" + "author_name": "Frederick Warner", + "author_inst": "Yale University" }, { - "author_name": "Amir Ahmad Arabzadeh", - "author_inst": "Ardabil University of Medical Sciences" + "author_name": "Andreas C. Coppi", + "author_inst": "Yale University" }, { - "author_name": "Azar Hadadi", - "author_inst": "Tehran University of Medical Sciences" + "author_name": "Nathaniel Price", + "author_inst": "Yale New Haven Health System" }, { - "author_name": "Mohammad Sharifzadeh", - "author_inst": "Tehran University of Medical Sciences" + "author_name": "Chelsea Duckwall", + "author_inst": "Yale University" }, { - "author_name": "Mojtaba Mojtahedzadeh", - "author_inst": "Tehran University of Medical Sciences" + "author_name": "Peri Sosensky", + "author_inst": "Yale University" + }, + { + "author_name": "Erendira C Di Giuseppe", + "author_inst": "Yale University" + }, + { + "author_name": "Ryan Borg", + "author_inst": "Yale University" + }, + { + "author_name": "Mariam O Fofana", + "author_inst": "Yale University" + }, + { + "author_name": "Otavio T Ranzani", + "author_inst": "Barcelona Institute for Global Health" + }, + { + "author_name": "Natalie E Dean", + "author_inst": "Emory University" + }, + { + "author_name": "Jason R Andrews", + "author_inst": "Stanford University" + }, + { + "author_name": "Julio Croda", + "author_inst": "Oswaldo Cruz Foundation" + }, + { + "author_name": "Akiko Iwasaki", + "author_inst": "Yale University School of Medicine" + }, + { + "author_name": "Derek A.T. Cummings", + "author_inst": "University of Florida" + }, + { + "author_name": "Albert Ko", + "author_inst": "Yale University School of Public Health" + }, + { + "author_name": "Matt DT Hitchings", + "author_inst": "University of Florida" + }, + { + "author_name": "Wade L Schulz", + "author_inst": "Yale School of Medicine" } ], "version": "1", @@ -314196,39 +313727,55 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2022.04.18.488640", - "rel_title": "BCG vaccination of Diversity Outbred mice induces cross-reactive antibodies to SARS-CoV-2 spike protein", + "rel_doi": "10.1101/2022.04.19.488806", + "rel_title": "The Spike protein of SARS-CoV-2 impairs lipid metabolism and increases susceptibility to lipotoxicity: implication for a role of Nrf2", "rel_date": "2022-04-19", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.04.18.488640", - "rel_abs": "The Bacillus Calmette-Guerin (BCG) vaccine, the only vaccine against tuberculosis, induces cross-protection against pathogens unrelated to Mycobacterium, including viruses. Epidemiological studies have identified potential benefits of BCG vaccination against SARS-CoV-2 infection. While BCGs heterologous effects have been widely attributable to trained immunity, we hypothesized BCG vaccination could induce cross-reactive antibodies against the spike protein of SARS-CoV-2 Wuhan-Hu-1. The concentration of IgG reactive to SARS-CoV-2 spike protein from the sera of BCG-vaccinated, Diversity Outbred (DO) mice and C57BL/6J inbred mice was measured using ELISA. Sera from 10/15 BCG-vaccinated DO mice possessed more IgG reactive to recombinant spike protein than sera from BCG-vaccinated C57BL/6J mice and unvaccinated DO mice. Amino acid sequences common to BCG cell wall/membrane proteins and SARS-CoV-2 spike protein were identified as potential antigen candidates for future study. These results imply a humoral mechanism, influenced by genotype, by which BCG vaccination could confer immunity to SARS-CoV-2.\n\nGraphic Abstract\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=80 SRC=\"FIGDIR/small/488640v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (23K):\norg.highwire.dtl.DTLVardef@1ff9d16org.highwire.dtl.DTLVardef@a2302dorg.highwire.dtl.DTLVardef@8ee2borg.highwire.dtl.DTLVardef@4c7b55_HPS_FORMAT_FIGEXP M_FIG C_FIG", - "rel_num_authors": 5, + "rel_link": "https://biorxiv.org/cgi/content/short/2022.04.19.488806", + "rel_abs": "Background/objectivesCoronavirus disease 2019 (COVID-19) patients exhibit lipid metabolic alterations, but the mechanism remains unknown. In this study, we aimed to investigate whether the Spike protein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) impairs lipid metabolism in host cells.\n\nMethodsA Spike cell line in HEK293 was generated using the pcDNA vector carrying the Spike gene expression cassette. A control cell line was generated using the empty pcDNA vector. Gene expression profiles related to lipid metabolic, autophagic, and ferroptotic pathways were investigated. Palmitic acid (PA)-overload was used to assess lipotoxicity-induced necrosis.\n\nResultsAs compared with controls, the Spike cells showed a significant increase in lipid depositions on cell membranes as well as dysregulation of expression of a panel of molecules involved lipid metabolism, autophagy, and ferroptosis. The Spike cells showed an upregulation of nuclear factor erythroid 2-related factor 2 (Nrf2), a multifunctional transcriptional factor, in response to PA. Furthermore, the Spike cells exhibited increased necrosis in response to PA-induced lipotoxicity compared to control cells in a time- and dose-dependent manner via ferroptosis, which could be attenuated by the Nrf2 inhibitor trigonelline.\n\nConclusionsThe Spike protein impairs lipid metabolic and autophagic pathways in host cells, leading to increased susceptibility to lipotoxicity via ferroptosis which can be suppressed by a Nrf2 inhibitor. This data also suggests a central role of Nrf2 in Spike-induced lipid metabolic impairments.\n\nHighlightsO_LIThe Spike protein increases lipid deposition in host cell membranes\nC_LIO_LIThe Spike protein impairs lipid metabolic and autophagic pathways\nC_LIO_LIThe Spike protein exaggerates PA-induced lipotoxicity in host cells via ferroptosis\nC_LIO_LINrf2 inhibitor Trigonelline can mitigate the Spike protein-induced necrosis\nC_LI", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Aubrey G. Specht", - "author_inst": "Department of Infectious Disease and Global Health, Cummings SVM at Tufts University, North Grafton, MA, USA" + "author_name": "Vi Nguyen", + "author_inst": "University of South Carolina" + }, + { + "author_name": "Yuping Zhang", + "author_inst": "University of South Carolina" }, { - "author_name": "Sherry L. Kurtz", - "author_inst": "Center for Biologics Evaluation and Research, Food and Drug Administration, Silver Spring, MD, USA" + "author_name": "Chao Gao", + "author_inst": "University of South Carolina" }, { - "author_name": "Karen L. Elkins", - "author_inst": "Center for Biologics Evaluation and Research, Food and Drug Administration, Silver Spring, MD, USA" + "author_name": "Xiaoling Cao", + "author_inst": "University of South Carolina" }, { - "author_name": "Harrison Specht", - "author_inst": "Department of Bioengineering and Barnett Institute, Northeastern University, Boston, MA, USA" + "author_name": "Yan Tian", + "author_inst": "University of South Carolina" }, { - "author_name": "Gillian Beamer", - "author_inst": "Department of Infectious Disease and Global Health, Cummings SVM at Tufts University, North Grafton, MA, USA" + "author_name": "Wayne Carver", + "author_inst": "University of South Carolina" + }, + { + "author_name": "Hippokratis Kiaris", + "author_inst": "University of South Carolina" + }, + { + "author_name": "Taixing Cui", + "author_inst": "University of South Carolina" + }, + { + "author_name": "Wenbin Tan", + "author_inst": "University of South Carolina, School of Medicine" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nd", "type": "new results", - "category": "immunology" + "category": "cell biology" }, { "rel_doi": "10.1101/2022.04.19.488067", @@ -315966,43 +315513,47 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2022.04.13.22273200", - "rel_title": "Pre-procedural testing improves estimated COVID-19 prevalence and trends", + "rel_doi": "10.1101/2022.04.14.22273896", + "rel_title": "COVID-19 vaccine effectiveness against severe disease from the Omicron BA.1 and BA.2 subvariants: surveillance results from southern Sweden, December 2021 to March 2022", "rel_date": "2022-04-18", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.04.13.22273200", - "rel_abs": "BackgroundCOVID-19 positivity rates reported to the public may provide a distorted view of community trends because they tend to be inflated by high-risk groups, such as symptomatic patients and individuals with known exposures to COVID-19. This positive bias within high-risk groups has also varied over time, depending on testing capability and indications for being tested. In contrast, throughout the pandemic, routine COVID-19 screening tests for elective procedures and operations unrelated to COVID-19 risk have been administered by medical facilities to reduce transmission to medical staffing and other patients. We propose the use of these pre-procedural COVID-19 patient datasets to reduce biases in community trends and better understand local prevalence.\n\nMethodsUsing patient data from the Maui Medical Group clinic, we analyzed 12,640 COVID-19 test results from May 1, 2020 to March 16, 2021, divided into two time periods corresponding with Mauis outbreak.\n\nResultsMean positivity rates were 0.1% for the pre-procedural group, 3.9% for the symptomatic group, 4.2% for the exposed group, and 2.0% for the total study population. Post-outbreak, the mean positivity rate of the pre-procedural group was significantly lower than the aggregate group (all other clinic groups combined). The positivity rates of both pre-procedural and aggregate groups increased over the study period, although the pre-procedural group showed a smaller rise in rate.\n\nConclusionsPre-procedural groups may produce different trends compared to high-risk groups and are sufficiently robust to detect small changes in positivity rates. Considered in conjunction with high-risk groups, pre-procedural marker groups used to monitor understudied, low-risk subsets of a community may improve our understanding of community COVID-19 prevalence and trends.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.04.14.22273896", + "rel_abs": "We compared vaccine effectiveness (VE) against severe COVID-19 during calendar periods from December 2021 to March 2022 when Omicron BA.1 and BA.2, respectively, were the dominating virus variants in Scania county, Sweden. We used continuous density case-control sampling matched for sex and age, and with further adjustment for differences in comorbidities and prior infection. VE remained relatively stable after the transition from BA.1 to BA.2 among people with at least three doses but decreased markedly among those with only two doses. Protection from prior infection was also lower after the transition to BA.2. These findings suggest that booster vaccination is needed to maintain sufficient protection against severe COVID-19.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "GENEVIEVE C. PANG", - "author_inst": "Hawaii Department of Health" + "author_name": "Jonas Bjork", + "author_inst": "Lund University" }, { - "author_name": "Amy T. Hou", - "author_inst": "Maui Medical Group" + "author_name": "Carl Bonander", + "author_inst": "University of Gothenburg" }, { - "author_name": "Krizhna L. Bayudan", - "author_inst": "Hawaii State Department of Health" + "author_name": "Mahnaz Moghaddassi", + "author_inst": "Lund University" }, { - "author_name": "Ethan A. Frank", - "author_inst": "Hawaii State Department of Health" + "author_name": "Magnus Rasmussen", + "author_inst": "Lund University" }, { - "author_name": "Jennifer Pastiglione", - "author_inst": "Maui Medical Group" + "author_name": "Ulf Malmqvist", + "author_inst": "Skane University Hospital" }, { - "author_name": "Lorrin W. Pang", - "author_inst": "Hawaii State Department of Health" + "author_name": "Malin Inghammar", + "author_inst": "Lund University" + }, + { + "author_name": "Fredrik Kahn", + "author_inst": "Lund University" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2022.04.14.22273865", @@ -317652,29 +317203,29 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.04.11.22273644", - "rel_title": "COVID-19 vaccine coverage among immigrants and refugees in Alberta: a population-based cross-sectional study", + "rel_doi": "10.1101/2022.04.07.22273578", + "rel_title": "Disentangling the rhythms of human activity in the built environment for airborne transmission risk", "rel_date": "2022-04-16", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.04.11.22273644", - "rel_abs": "IntroductionStudies have shown that immigrants have lower vaccination rates than the Canadian-born population. We sought to assess COVID-19 vaccine coverage and factors associated with uptake among foreign-born immigrants relative to the non-immigrant population in Alberta, Canada.\n\nMethodsIn this cross-sectional study, we analyzed population-based linked administrative health data from Alberta to examine vaccine coverage for 3,931,698 Albertans, of which 731,217 were immigrants. We calculated COVID-19 vaccination coverage as the proportion of eligible Albertans with a record of receiving at least one dose of a COVID-19 vaccine as of November 29, 2021. We used multivariable logistic regression to examine the association of vaccine coverage with migration status (immigrants: four categories based on time since migration and non-immigrants) adjusting for socio-demographic variables.\n\nResultsOverall, COVID-19 vaccination coverage was higher among immigrants (78.2%; 95% CI: 78.1%-78.3%) compared to non-immigrants (76.0%; 95% CI: 75.9%-76.0%). Coverage among immigrants differed by continent of origin, with North America, Oceania, and Europe having the lowest coverage. Although vaccine coverage was relatively uniform across neighborhood income quintiles for immigrants, immigrants living in rural areas had lower vaccine coverage compared to non-immigrants living in rural areas. Multivariable logistic regression analysis showed a significant interaction between age category and migration status. While immigrants below 50 years of age generally had significantly higher vaccine coverage compared to non-immigrants, there was some variation based on time since migration. Immigrants above 50 years of age showed significantly lower coverage compared to non-immigrants of the same age.\n\nConclusionPublic health interventions should focus on older immigrants, immigrants living in rural areas, and immigrants from specific continental backgrounds in order to improve COVID-19 vaccination coverage.", + "rel_link": "https://medrxiv.org/cgi/content/short/2022.04.07.22273578", + "rel_abs": "BackgroundSince the outset of the COVID-19 pandemic, substantial public attention has focused on the role of seasonality in impacting transmission. Misconceptions have relied on seasonal mediation of respiratory diseases driven solely by environmental variables. However, seasonality is expected to be driven by host social behavior, particularly in highly susceptible populations. A key gap in understanding the role of social behavior in respiratory disease seasonality is our incomplete understanding of the seasonality of indoor human activity.\n\nMethodsWe leverage a novel data stream on human mobility to characterize activity in indoor versus outdoor environments in the United States. We use an observational mobile app-based location dataset encompassing over 5 million locations nationally. We classify locations as primarily indoor (e.g. stores, offices) or outdoor (e.g. playgrounds, farmers markets), disentangling location-specific visits into indoor and outdoor, to arrive at a fine-scale measure of indoor to outdoor human activity across time and space.\n\nResultsWe find the proportion of indoor to outdoor activity during a baseline year is seasonal, peaking in winter months. The measure displays a latitudinal gradient with stronger seasonality at northern latitudes and an additional summer peak in southern latitudes. We statistically fit this baseline indoor-outdoor activity measure to inform the incorporation of this complex empirical pattern into infectious disease dynamic models. However, we find that the disruption of the COVID-19 pandemic caused these patterns to shift significantly from baseline, and the empirical patterns are necessary to predict spatiotemporal heterogeneity in disease dynamics.\n\nConclusionsOur work empirically characterizes, for the first time, the seasonality of human social behavior at a large scale with high spatiotemporal resolution, and provides a parsimonious parameterization of seasonal behavior that can be included in infectious disease dynamics models. We provide critical evidence and methods necessary to inform the public health of seasonal and pandemic respiratory pathogens and improve our understanding of the relationship between the physical environment and infection risk in the context of global change.\n\nFundingResearch reported in this publication was supported by the National Institute of General Medical Sciences of the National Institutes of Health under award number R01GM123007.", "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Shannon E MacDonald", - "author_inst": "University of Alberta" + "author_name": "Zachary Susswein", + "author_inst": "Georgetown University" }, { - "author_name": "Yuba Raj Paudel", - "author_inst": "University of Alberta" + "author_name": "Eva C Rest", + "author_inst": "Georgetown University" }, { - "author_name": "Crystal Du", - "author_inst": "University of Alberta" + "author_name": "Shweta Bansal", + "author_inst": "Georgetown University" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -319154,79 +318705,47 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/105437", - "rel_title": "The Arabidopsis Framework Model version 2 predicts the organism-level effects of circadian clock gene mis-regulation", - "rel_date": "2022-04-14", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/105437", - "rel_abs": "Predicting a multicellular organisms phenotype quantitatively from its genotype is challenging, as genetic effects must propagate across scales. Circadian clocks are intracellular regulators that control temporal gene expression patterns and hence metabolism, physiology and behaviour. Here we explain and predict canonical phenotypes of circadian timing in a multicellular, model organism. We used diverse metabolic and physiological data to combine and extend mathematical models of rhythmic gene expression, photoperiod-dependent flowering, elongation growth and starch metabolism within a Framework Model for the vegetative growth of Arabidopsis thaliana, sharing the model and data files in a structured, public resource. The calibrated model predicted the effect of altered circadian timing upon each particular phenotype in clock-mutant plants under standard laboratory conditions. Altered night-time metabolism of stored starch accounted for most of the decrease in whole-plant biomass, as previously proposed. Mobilisation of a secondary store of malate and fumarate was also mis-regulated, accounting for any remaining biomass defect. We test three candidate mechanisms for the accumulation of these organic acids. Our results link genotype through specific processes to higher-level phenotypes, formalising our understanding of a subtle, pleiotropic syndrome at the whole-organism level, and validating the systems approach to understand complex traits starting from intracellular circuits.\n\nThis work updates the first biorXiv version, February 2017, https://doi.org/10.1101/105437, with an expanded description and additional analysis of the same core data sets and the same FMv2 model, summary tables and supporting, follow-on data from three further studies with further collaborators. This biorXiv revision constitutes the second version of this report.", - "rel_num_authors": 15, + "rel_doi": "10.1101/2022.04.08.22273322", + "rel_title": "Correlations between kidney and heart function bioindicators and the expressions of Toll-Like, ACE2, and NRP-1 receptors in COVID-19", + "rel_date": "2022-04-13", + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2022.04.08.22273322", + "rel_abs": "BackgroundCOVID-19 impacts the cardiovascular system resulting in myocardial damage and also affects the kidneys leading to renal dysfunction. This effect is mostly through the binding with angiotensin-converting enzyme-2 (ACE2) and Neuropilin-1(NRP-l) receptors. Toll-Like Receptors (TLRs) typically combine with microbial pathogens and provoke an inflammatory response.\n\nAimThis work aims to compare the changes in kidney and heart function bioindicators and expressions of TLRs (TLR2 and TLR2) as well as ACE2 and NRP-l receptors in moderate and severe COVID-19 patients. The correlations between kidney and heart function bioindicators and expressions of these receptors are also studied.\n\nPatients and MethodsIn this study, 50 healthy control and 100 COVID-19 patients (55 male and 45 female) were enrolled. According to WHO guidelines, these participants were divided into severe (50 cases) and moderate (50 cases). Serum creatinine, blood urea, CKMB, LDH, and Troponin I were estimated. We measured the gene expression for Toll-Like Receptors (TLR2, TLR4), ACE2, and NRP-1 in the blood samples using quantitative real-time PCR (qRT -PCR).\n\nResultsIn comparison with the healthy group, all patients exhibited a significant elevation in the serum creatinine, blood urea, cardiac enzymes, and CRP. As well, all studied patients revealed a significant elevation in the expression levels of TLR2, TLR4, ACE2, and NRP-1 mRNA. In all patients, CKMB, ACE2, and NRP-1 mRNA expression levels were positively correlated to both TLR2 and TLR4 expression levels. Moreover, serum creatinine and blood urea were positively correlated to both TLR2 and TLR 4 expression levels in the severe group only.\n\nConclusionsOur study concluded that expression levels for TLR2, TLR4, ACE2, and NRP-1 mRNA in both severe and moderate patients were positively correlated with renal biomarkers and cardiac enzymes. Innate immune markers can be important because they correlate with the severity of illness in COVID-19.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Abigail Vanderheiden", - "author_inst": "Emory University" + "author_name": "Rabab Hussein Soltan", + "author_inst": "Beni Suef University- Faculty of Postgraduate Studies for Advanced Sciences" }, { - "author_name": "Philipp Ralfs", - "author_inst": "Emory University" + "author_name": "Maged Salah Abdallah", + "author_inst": "Cairo University- Kasr Alainy Hospital" }, { - "author_name": "Tatiana Chirkova", - "author_inst": "Emory University" + "author_name": "Tarek Mohamed Ali", + "author_inst": "Taif Univesity - College of Medicin" }, { - "author_name": "Amit A Upadhyay", - "author_inst": "Emory University" + "author_name": "Amr EL Said Ahmed", + "author_inst": "Beni Suef University- Faculty of Postgraduate Studies for Advanced Science" }, { - "author_name": "Matthew G Zimmerman", - "author_inst": "Emory University" + "author_name": "Hebatallah Hany Assal", + "author_inst": "Cairo University- Kasr Alaini Hospital" }, { - "author_name": "Shamika Bedoya", - "author_inst": "Emory University" + "author_name": "Basem Hassan Elesawy", + "author_inst": "Taif Univesity- College of Medicine" }, { - "author_name": "Hadj Aoued", - "author_inst": "Emory University" - }, - { - "author_name": "Gregory K Tharp", - "author_inst": "Emory University" - }, - { - "author_name": "Kathryn Pellegrini", - "author_inst": "Emory University" - }, - { - "author_name": "Anice C Lowen", - "author_inst": "Emory University School of Medicine" - }, - { - "author_name": "Vineet D. Menachery", - "author_inst": "University of Texas Medical Branch at Galveston" - }, - { - "author_name": "Larry J Anderson", - "author_inst": "University of Emory School of Medicine" - }, - { - "author_name": "Arash Grakoui", - "author_inst": "Emory University School of Medicine" - }, - { - "author_name": "Steven E. Bosinger", - "author_inst": "Emory University" - }, - { - "author_name": "Mehul S Suthar", - "author_inst": "Emory University" + "author_name": "Osama Mohamed Ahmed", + "author_inst": "Beni Suef University- Faculty of Science" } ], - "version": "2", + "version": "1", "license": "cc_no", - "type": "new results", - "category": "plant biology" + "type": "PUBLISHAHEADOFPRINT", + "category": "infectious diseases" }, { "rel_doi": "10.1101/2022.04.11.22273327", @@ -321155,18 +320674,18 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.04.10.22273660", - "rel_title": "Lowered oxygen saturation and increased body temperature in acute COVID-19 largely predict chronic fatigue syndrome and affective symptoms due to LONG COVID: a precision nomothetic approach", + "rel_doi": "10.1101/2022.04.11.22273729", + "rel_title": "Intensity and longevity of SARS-CoV-2 vaccination response and efficacy of adjusted vaccination schedules in patients with immune-mediated inflammatory disease", "rel_date": "2022-04-12", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.04.10.22273660", - "rel_abs": "BackgroundLong coronavirus disease 2019 (LC) is a chronic sequel of acute COVID-19. The exact pathophysiology of the affective, chronic fatigue and physiosomatic symptoms (labeled as \"physio-affective phenome\") of LC has remained elusive.\n\nObjectiveThe current study aims to delineate the effects of oxygen saturation (SpO2) and body temperature during the acute phase on the physio-affective phenome of LC.\n\nMethodWe recruited 120 LC patients and 36 controls. For all participants, we assessed the lowest SpO2 and peak body temperature during acute COVID-19, and the Hamilton Depression and Anxiety Rating Scale (HAMD/HAMA) and Fibro Fatigue (FF) scales 3 to 4 months later.\n\nResultsLowered SpO2 and increased body temperature during the acute phase and female sex predict 60.7% of the variance in the physio-affective phenome of LC. Using unsupervised learning techniques we were able to delineate a new endophenotype class, which comprises around 26.7% of the LC patients and is characterized by very low SpO2 and very high body temperature, and depression, anxiety, chronic fatigue, and autonomic and gastro-intestinal symptoms scores. Single latent vectors could be extracted from both biomarkers, depression, anxiety and FF symptoms or from both biomarkers, insomnia, chronic fatigue, gastro-intestinal and autonomic symptoms.\n\nConclusionThe newly constructed endophenotype class and pathway phenotypes indicate that the physio-affective phenome of LC is at least in part the consequence of the pathophysiology of acute COVID-19, namely the combined effects of lowered SpO2, increased body temperature and the associated immune-inflammatory processes and lung lesions.", + "rel_link": "https://medrxiv.org/cgi/content/short/2022.04.11.22273729", + "rel_abs": "ObjectivesTo investigate the intensity and longevity of SARS-CoV-2 vaccination response in patients with immune-mediated inflammatory disease (IMID) by diagnosis, treatment and adapted vaccination schedules.\n\nMethodsSARS-CoV-2 IgG antibody response after SARS-CoV-2 vaccination was measured longitudinally in a large prospective cohort of healthy controls (HC) and IMID patients between December 2020 and 2021. Demographic and disease-specific data were recorded. Humoral response was compared across treatment and disease groups, and with respect to receipt of booster vaccinations. Age and sex adjusted SARS-CoV-2 antibody response was modelled over time. Marginal mean antibody levels and marginal risks of poor response were calculated at weekly intervals starting from week-8 after the first vaccination up to week 40.\n\nResultsAmong 5076 individuals registered, 2535 IMID patients and 1198 HC were eligible for this analysis. Mean antibody levels were higher in HC compared to IMIDs at all-time points, with peak antibody response in HC more than twice that in IMIDs (12.48 (11.52-13.52) vs. 5.71 (5.46-5.97)). Poor response to vaccination was observed in IMID patients treated with agents affecting B- and T-cell functions. Mean differences in antibody response between IMID diseases were small. After additional vaccinations, IMID patients could achieve higher antibody levels than HC vaccinated according to the two-dose schedule, even-though initial antibody levels were lower.\n\nConclusionsIMID patients show a lower and less durable SARS-CoV-2 vaccination response and are at risk to lose humoral immune protection. Adjusted vaccination schedules with earlier boosters and/or more frequent re-doses could better protect IMID patients.", "rel_num_authors": 0, "rel_authors": null, "version": "1", "license": "", "type": "PUBLISHAHEADOFPRINT", - "category": "psychiatry and clinical psychology" + "category": "rheumatology" }, { "rel_doi": "10.1101/2022.04.11.22273754", @@ -322451,21 +321970,97 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2022.04.08.22273628", - "rel_title": "Implications of red state/blue state differences in COVID-19 death rates", + "rel_doi": "10.1101/2022.04.06.22273535", + "rel_title": "Effectiveness of 2 and 3 mRNA COVID-19 Vaccines Doses against Omicron and Delta-Related Outpatient Illness among Adults, October 2021 - February 2022", "rel_date": "2022-04-10", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.04.08.22273628", - "rel_abs": "The study objective was to explore state death rates pre- and post- 4/19/2021 (date vaccines were assumed available) and the relative contributions of 3 factors to state death rates post- 4/19/2021: 1) vaccination rates, 2) prevalence of obesity, hypertension, diabetes, COPD, cardiovascular disease, and asthma and 3) red vs. blue states, to better understand options for reducing deaths. The ratio of red to blue state deaths/million was 1.6 pre-4/19/2021 and 2.3 between 4/19 and 2/28/2022 resulting in >222,000 extra deaths in red states or 305/ day. Adjusted betas from linear regression showed state vaccination rates had the strongest effect on death rates while red vs. blue states explained more of the difference in state death rates (60% vs. 46% for vaccination rates) with mean vaccination rates ~10% higher in blue states. Results suggest that increasing vaccination rates in red states could potentially save thousands of lives as the pandemic continues.", - "rel_num_authors": 1, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.04.06.22273535", + "rel_abs": "BackgroundWe estimated SARS-CoV-2 Delta and Omicron-specific effectiveness of 2 and 3 mRNA COVID-19 vaccine doses in adults against symptomatic illness in US outpatient settings.\n\nMethodsBetween October 1, 2021, and February 12, 2022, research staff consented and enrolled eligible participants who had fever, cough, or loss of taste or smell and sought outpatient medical care or clinical SARS-CoV-2 testing within 10 days of illness onset. Using the test-negative design, we compared the odds of receiving 2 or 3 mRNA COVID-19 vaccine doses among SARS-CoV-2 cases versus controls using logistic regression. Regression models were adjusted for study site, age, onset week, and prior SARS-CoV-2 infection. Vaccine effectiveness (VE) was calculated as (1 - adjusted odds ratio) x 100%.\n\nResultsAmong 3847 participants included for analysis, 574 (32%) of 1775 tested positive for SARS-CoV-2 during the Delta predominant period and 1006 (56%) of 1794 participants tested positive during the Omicron predominant period. When Delta predominated, VE against symptomatic illness in outpatient settings was 63% (95% CI: 51% to 72%) among mRNA 2-dose recipients and 96% (95% CI: 93% to 98%) for 3-dose recipients. When Omicron predominated, VE was 21% (95% CI: -6% to 41%) among 2-dose recipients and 62% (95% CI: 48% to 72%) among 3-dose recipients.\n\nConclusionsIn this adult population, 3 mRNA COVID-19 vaccine doses provided substantial protection against symptomatic illness in outpatient settings when the Omicron variant became the predominant cause of COVID-19 in the U.S. These findings support the recommendation for a 3rd mRNA COVID-19 vaccine dose.", + "rel_num_authors": 20, "rel_authors": [ { - "author_name": "Mary Adams", - "author_inst": "On Target Health Data LLC" + "author_name": "Sara Kim", + "author_inst": "Centers for Disease Control and Prevention" + }, + { + "author_name": "Jessie Chung", + "author_inst": "US Centers for Disease Control and Prevention" + }, + { + "author_name": "Keipp Talbot", + "author_inst": "Vanderbilt University Medical Center" + }, + { + "author_name": "Carlos G Grijalva", + "author_inst": "Vanderbilt University Medical Center" + }, + { + "author_name": "Karen Wernli", + "author_inst": "Kaiser Permanente Washington Research Institute" + }, + { + "author_name": "Erika Kiniry", + "author_inst": "Kaiser Permanente Washington Research Institute" + }, + { + "author_name": "Emily Toth Martin", + "author_inst": "University of Michigan-Ann Arbor" + }, + { + "author_name": "Arnold Monto", + "author_inst": "University of Michigan-Ann Arbor" + }, + { + "author_name": "Edward Belongia", + "author_inst": "Marshfield Clinic Research Institute" + }, + { + "author_name": "Huong Q McLean", + "author_inst": "Marshfield Clinic Research Institute" + }, + { + "author_name": "Manjusha Gaglani", + "author_inst": "Baylor Scott and White Health, Texas A&M University College of Medicine" + }, + { + "author_name": "Mufaddal Mamawala", + "author_inst": "Baylor Scott and White Health" + }, + { + "author_name": "Mary Patricia Nowalk", + "author_inst": "University of Pittsburgh" + }, + { + "author_name": "Krissy Moehling Geffel", + "author_inst": "University of Pittsburgh" + }, + { + "author_name": "Sara Tartof", + "author_inst": "Kaiser Permanente Southern California" + }, + { + "author_name": "Ana Florea", + "author_inst": "Kaiser Permanente Southern California" + }, + { + "author_name": "Justin S Lee", + "author_inst": "Centers for Disease Control and Prevention" + }, + { + "author_name": "Mark W Tenforde", + "author_inst": "Centers for Disease Control and Prevention" + }, + { + "author_name": "Manish Patel", + "author_inst": "Centers for Disease Control and Prevention" + }, + { + "author_name": "Brendan Flannery", + "author_inst": "Centers for Disease Control and Prevention" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc0", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -324401,57 +323996,69 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.03.30.22271928", - "rel_title": "Multiplexed biosensor for point-of-care COVID-19 monitoring: CRISPR-powered unamplified RNA diagnostics and protein-based therapeutic drug management", + "rel_doi": "10.1101/2022.04.05.22273453", + "rel_title": "Unsuppressed HIV infection impairs T cell responses to SARS-CoV-2 infection and abrogates T cell cross-recognition", "rel_date": "2022-04-06", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.03.30.22271928", - "rel_abs": "In late 2019 SARS-CoV-2 rapidly spread to become a global pandemic, therefore, measures to attenuate chains of infection, such as high-throughput screenings and isolation of carriers were taken. Prerequisite for a reasonable and democratic implementation of such measures, however, is the availability of sufficient testing opportunities (beyond reverse transcription PCR, the current gold standard). We, therefore, propose an electrochemical, microfluidic multiplexed biosensor in combination with CRISPR/Cas-powered assays for point-of-care nucleic acid testing. In this study, we simultaneously screen for and identify SARS-CoV-2 infections (Omicron-variant) in clinical specimens (Sample-to-result time: [~]30 min), employing LbuCas13a, whilst bypassing reverse transcription as well as target amplification of the viral RNA, both of which are necessary for detection via PCR and multiple other methods. In addition, we demonstrate the feasibility of combining assays based on different classes of biomolecules, in this case protein-based antibiotic detection, on the same device. The programmability of the effector and multiplexing capacity (up to six analytes) of our platform, in combination with a miniaturized measurement setup, including a credit card sized near field communication (NFC) potentiostat and a microperistaltic pump, provide a promising on-site tool for identifying individuals infected with variants of concern and monitoring their disease progression alongside other potential biomarkers or medication clearance.", - "rel_num_authors": 10, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.04.05.22273453", + "rel_abs": "HIV infection has been identified as one of the major risk factors for severe COVID-19 disease, but the mechanisms underpinning this susceptability are still unclear. Here, we assessed the impact of HIV infection on the quality and epitope specificity of SARS-CoV-2 T cell responses in the first wave and second wave of the COVID-19 epidemic in South Africa. Flow cytometry was used to measure T cell responses following PBMC stimulation with SARS-CoV-2 peptide pools. Culture expansion was used to determine T cell immunodominance hierarchies and to assess potential SARS-CoV-2 escape from T cell recognition. HIV-seronegative individuals had significantly greater CD4+ and CD8+ T cell responses against the Spike protein compared to the viremic PLWH. Absolute CD4 count correlated positively with SARS-CoV-2 specific CD4+ and CD8+ T cell responses (CD4 r= 0.5, p=0.03; CD8 r=0.5, p=0.001), whereas T cell activation was negatively correlated with CD4+ T cell responses (CD4 r= -0.7, p=0.04). There was diminished T cell cross-recognition between the two waves, which was more pronounced in individuals with unsuppressed HIV infection. Importantly, we identify four mutations in the Beta variant that resulted in abrogation of T cell recognition. Together, we show that unsuppressed HIV infection markedly impairs T cell responses to SARS-Cov-2 infection and diminishes T cell cross-recognition. These findings may partly explain the increased susceptibility of PLWH to severe COVID-19 and also highlights their vulnerability to emerging SARS-CoV-2 variants of concern.\n\nOne sentence summaryUnsuppressed HIV infection is associated with muted SARS-CoV-2 T cell responses and poorer recognition of the Beta variant.", + "rel_num_authors": 13, "rel_authors": [ { - "author_name": "Midori Johnston", - "author_inst": "University of Freiburg" + "author_name": "Zaza Mtine Ndhlovu", + "author_inst": "Ragon Institute of MGH, MIT and Harvard" }, { - "author_name": "H. Ceren Ates", - "author_inst": "University of Freiburg" + "author_name": "Thandeka Nkosi", + "author_inst": "Africa Health Research Institute" }, { - "author_name": "Regina T. Glatz", - "author_inst": "University of Freiburg" + "author_name": "Anele Mbatha", + "author_inst": "HIV Pathogenesis Programme. University of KwaZulu-Natal" }, { - "author_name": "Hasti Mohsenin", - "author_inst": "University of Freiburg" + "author_name": "Mza Nsimbi", + "author_inst": "Africa Health Research Institute" }, { - "author_name": "Rosanne Schmachtenberg", - "author_inst": "University of Freiburg" + "author_name": "Andrea O Papadopoulos", + "author_inst": "Africa Health Research Institute" }, { - "author_name": "Nathalie G\u00f6ppert", - "author_inst": "University of Freiburg" + "author_name": "Tiza Nguni", + "author_inst": "Africa Health Research Institute" }, { - "author_name": "Daniela Huzly", - "author_inst": "University of Freiburg" + "author_name": "Farina Karim", + "author_inst": "Africa Health Research Institute" }, { - "author_name": "Gerald A. Urban", - "author_inst": "University of Freiburg" + "author_name": "Mohomed Yunus S Moosa", + "author_inst": "Africa Health Research Institute" }, { - "author_name": "Wilfried Weber", - "author_inst": "University of Freiburg" + "author_name": "Inbal Gazy", + "author_inst": "KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), Nelson R Mandela School of Medicine, University of KwaZulu-Natal" }, { - "author_name": "Can Dincer", - "author_inst": "University of Freiburg" + "author_name": "Kondwani Jambo", + "author_inst": "Malawi-Liverpool-Wellcome Trust Clinical Research Programme" + }, + { + "author_name": "- COMMIT-KZN", + "author_inst": "-" + }, + { + "author_name": "Willem Hanekom", + "author_inst": "Africa Health Research Institute" + }, + { + "author_name": "Alex Sigal", + "author_inst": "Africa Health Research Institute" } ], "version": "1", - "license": "cc_by", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -326159,61 +325766,81 @@ "category": "genetic and genomic medicine" }, { - "rel_doi": "10.1101/2022.04.03.22273268", - "rel_title": "Classification of Omicron BA.1, BA.1.1 and BA.2 sublineages by TaqMan assay consistent with whole genome analysis data", + "rel_doi": "10.1101/2022.04.04.22273429", + "rel_title": "Viral dynamics of Omicron and Delta SARS-CoV-2 variants with implications for timing of release from isolation: a longitudinal cohort study", "rel_date": "2022-04-05", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.04.03.22273268", - "rel_abs": "ObjectiveRecently, the Omicron strain of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has spread and replaced the previously dominant Delta strain. Several Omicron sublineages (BA.1, BA.1.1 and BA.2) have been identified, with in vitro and preclinical reports showing that the pathogenicity and therapeutic efficacy differs between BA.1 and BA.2. We sought to develop a TaqMan assay to identify these subvariants.\n\nMethodsA TaqMan assay was constructed for rapid identification and genotyping of Omicron sublineages. We analyzed three characteristic mutations of the spike gene, {Delta}69-70, G339D and Q493R, by TaqMan assay. The accuracy of the TaqMan assay was examined by comparing its results with the results of whole genome sequencing (WGS) analysis.\n\nResultsA total of 169 SARS-CoV-2 positive samples were analyzed by WGS and TaqMan assay. The 127 samples determined as BA.1/BA.1.1 by WGS were all positive for {Delta}69-70, G339D and Q493R by TaqMan assay. Forty-two samples determined as BA.2 by WGS were negative for {Delta}69-70 but positive for G339D and Q493R by TaqMan. The concordance rate between WGS and the TaqMan assay was 100% (169/169).\n\nConclusionTaqMan assays targeting characteristic mutations are useful for identification and discrimination of Omicron sublineages.", - "rel_num_authors": 12, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.04.04.22273429", + "rel_abs": "BackgroundIn January 2022, United States guidelines shifted to recommend isolation for 5 days from symptom onset, followed by 5 days of mask wearing. However, viral dynamics and variant and vaccination impact on culture conversion are largely unknown.\n\nMethodsWe conducted a longitudinal study on a university campus, collecting daily anterior nasal swabs for at least 10 days for RT-PCR and culture, with antigen rapid diagnostic testing (RDT) on a subset. We compared culture positivity beyond day 5, time to culture conversion, and cycle threshold trend when calculated from diagnostic test, from symptom onset, by SARS-CoV-2 variant, and by vaccination status. We evaluated sensitivity and specificity of RDT on days 4-6 compared to culture.\n\nResultsAmong 92 SARS-CoV-2 RT-PCR positive participants, all completed the initial vaccine series, 17 (18.5%) were infected with Delta and 75 (81.5%) with Omicron. Seventeen percent of participants had positive cultures beyond day 5 from symptom onset with the latest on day 12. There was no difference in time to culture conversion by variant or vaccination status. For the 14 sub-study participants, sensitivity and specificity of RDT were 100% and 86% respectively.\n\nConclusionsThe majority of our Delta- and Omicron-infected cohort culture-converted by day 6, with no further impact of booster vaccination on sterilization or cycle threshold decay. We found that rapid antigen testing may provide reassurance of lack of infectiousness, though masking for a full 10 days is necessary to prevent transmission from the 17% of individuals who remain culture positive after isolation.\n\nMain PointBeyond day 5, 17% of our Delta and Omicron-infected cohort were culture positive. We saw no significant impact of booster vaccination on within-host Omicron viral dynamics. Additionally, we found that rapid antigen testing may provide reassurance of lack of infectiousness.", + "rel_num_authors": 17, "rel_authors": [ { - "author_name": "Yosuke Hirotsu", - "author_inst": "Yamanashi Central Hospital" + "author_name": "Tara C Bouton", + "author_inst": "Boston Medical Center, Boston University School of Medicine" }, { - "author_name": "Makoto Maejima", - "author_inst": "Yamanashi Central Hospital" + "author_name": "Joseph Atarere", + "author_inst": "Boston Medical Center" }, { - "author_name": "Masahiro Shibusawa", - "author_inst": "Yamanashi Central Hospital" + "author_name": "Jacquelyn Turcinovic", + "author_inst": "Boston University" }, { - "author_name": "Yume Natori", - "author_inst": "Yamanashi Central Hospital" + "author_name": "Scott Seitz", + "author_inst": "Boston University" }, { - "author_name": "Yuki Nagakubo", - "author_inst": "Yamanashi Central Hospital" + "author_name": "Cole Sher-Jan", + "author_inst": "Boston University" }, { - "author_name": "Kazuhiro Hosaka", - "author_inst": "Yamanashi Central Hospital" + "author_name": "Madison Gilbert", + "author_inst": "Boston University" }, { - "author_name": "Hitomi Sueki", - "author_inst": "Yamanashi Central Hospital" + "author_name": "Laura White", + "author_inst": "Boston University" }, { - "author_name": "Hitoshi Mochizuki", - "author_inst": "Yamanashi Central Hospital" + "author_name": "Zhenwei Zhou", + "author_inst": "Boston University" }, { - "author_name": "Toshiharu Tsutsui", - "author_inst": "Yamanashi Central Hospital" + "author_name": "Mohammad M. Hossain", + "author_inst": "Boston University" }, { - "author_name": "Yumiko Kakizaki", - "author_inst": "Yamanashi Central Hospital" + "author_name": "Victoria Overbeck", + "author_inst": "Boston University" }, { - "author_name": "Yoshihiro Miyashita", - "author_inst": "Yamanashi Central Hospital" + "author_name": "Lynn Doucette-Stamm", + "author_inst": "Boston University" }, { - "author_name": "Masao Omata", - "author_inst": "Yamanashi Central Hospital" + "author_name": "Judy Platt", + "author_inst": "Boston University" + }, + { + "author_name": "Hannah E Landsberg", + "author_inst": "Boston University" + }, + { + "author_name": "Davidson H Hamer", + "author_inst": "Boston University School of Public Health" + }, + { + "author_name": "Catherine M. Klapperich", + "author_inst": "Boston University College of Engineering" + }, + { + "author_name": "Karen R Jacobson", + "author_inst": "Boston Medical Center and Boston University" + }, + { + "author_name": "John H Connor", + "author_inst": "Boston University" } ], "version": "1", @@ -328005,67 +327632,75 @@ "category": "intensive care and critical care medicine" }, { - "rel_doi": "10.1101/2022.04.02.486853", - "rel_title": "Dietary \u03b1KG inhibits SARS CoV-2 infection and rescues inflamed lungs to restore normal O2 saturation in animals", + "rel_doi": "10.1101/2022.04.03.486854", + "rel_title": "Conformational Flexibility in Neutralization of SARS-CoV-2 by Naturally Elicited Anti-SARS-CoV-2 Antibodies", "rel_date": "2022-04-03", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.04.02.486853", - "rel_abs": "Our recent works described the rescue effect of -ketoglutarate (KG, a metabolite of Krebs cycle) on thrombosis and inflammation in animals. KG augments activity of prolyl hydroxylase 2 (PHD2), which in turn degrades proline residues of substrates like phosphorylated Akt (pAkt) and hypoxia inducible factor (HIF). Here we describe the inhibitory effect of octyl KG on pAkt as well as on HIF1/HIF2, and in turn decreasing SARS CoV-2 replication in Vero E6 cells. KG failed to inhibit the viral replication and Akt phosphorylation in PHD2-knockdown U937 cells transiently expressing ACE2. Contrastingly, triciribine (TCN, an Akt-inhibitor) inhibited viral replication alongside a downmodulation of pAkt in PHD2-KD cells. Dietary KG significantly inhibited viral infection and rescued hamsters from thrombus formation and inflammation in lungs, the known causes of acute respiratory distress syndrome (ARDS) in COVID-19. KG supplementation also reduced the apoptotic death of lung tissues in infected animals, alongside a downmodulation of pAkt and HIF2. KG supplementation neither affected IgG levels against SARS CoV-2 RBD protein nor altered the neutralization antibody response against SARS CoV-2. It did not interfere with the percentage of interferon-{gamma} positive (IFN{gamma}+) CD4+ and IFN{gamma}+CD8+ T cells in infected animals. The extended work in balb/c mice transiently expressing ACE2 showed a similar effect of KG in reducing accumulation of inflammatory immune cells and cytokines, including IL6, IL1{beta} and TNF, in lungs as well as in circulation of infected animals. Pro-thrombotic markers like platelet microparticles and platelet-leukocyte aggregates were reduced significantly in infected mice after KG supplementation. Importantly, KG supplementation restored the O2 saturation (SpO2) in circulation of SARS CoV-2 infected hamsters and mice, suggesting a potential therapeutic role of this metabolite in COVID-19 treatment.", - "rel_num_authors": 12, + "rel_link": "https://biorxiv.org/cgi/content/short/2022.04.03.486854", + "rel_abs": "As new variants of SARS-CoV-2 continue to emerge, it is important to assess the neutralizing capabilities of naturally elicited antibodies against SARS-CoV-2. In the present study, we evaluated the activity of nine anti-SARS-CoV-2 monoclonal antibodies (mAbs), previously isolated from convalescent donors infected with the Wuhan-Hu-1 strain, against the SARS-CoV-2 variants of concern (VOC) Alpha, Beta, Gamma, Delta and Omicron. By testing an array of mutated spike receptor binding domain (RBD) proteins, cell-expressed spike proteins from VOCs, and neutralization of SARS-CoV-2 VOCs as pseudoviuses, or as the authentic viruses in culture, we show that mAbs directed against the ACE2 binding site (ACE2bs) are far more sensitive to viral evolution compared to anti-RBD non-ACE2bs mAbs, two of which kept their potency against all VOCs tested. At the second part of our study, we reveal the neutralization mechanisms at high molecular resolution of two anti-SARS-CoV-2 neutralizing mAbs by structural characterization. We solved the structures of the Delta-neutralizing ACE2bs mAb TAU-2303 with the SARS-CoV-2 spike trimer and RBD at 4.5 [A] and 2.42 [A], respectively, revealing a similar mode of binding to that between the RBD and the ACE2 receptor. Furthermore, we provide five additional structures (at resolutions of 5.54 [A], 7.76 [A], 6.47 [A], 3.45 [A], and 7.32 [A]) of a second antibody, non-ACE2bs mAb TAU-2212, complexed with the SARS-CoV-2 spike trimer. TAU-2212 binds an exclusively quaternary epitope, and exhibits a unique, flexible mode of neutralization that involves transitioning between five different conformations, with both arms of the antibody recruited for cross linking intra- and inter-spike RBD subunits. Our study provides new mechanistic insights about how antibodies neutralize SARS-CoV-2 and its emerging variants and provides insight about the likelihood of reinfections.", + "rel_num_authors": 14, "rel_authors": [ { - "author_name": "Sakshi Agarwal", - "author_inst": "Regional Centre for Biotechnology, National Capital Region Biotech Science Cluster, Faridabad, India" + "author_name": "Ruofan Li", + "author_inst": "Tsinghua University" }, { - "author_name": "Simrandeep Kaur", - "author_inst": "Regional Centre for Biotechnology, National Capital Region Biotech Science Cluster, Faridabad, India" + "author_name": "Michael Mor", + "author_inst": "Tel Aviv University" }, { - "author_name": "Tejeswara Rao Asuru", - "author_inst": "Regional Centre for Biotechnology, National Capital Region Biotech Science Cluster, Faridabad, India" + "author_name": "Bingting Ma", + "author_inst": "Tsinghua University" }, { - "author_name": "Garima Joshi", - "author_inst": "Regional Centre for Biotechnology, National Capital Region Biotech Science Cluster, Faridabad, India" + "author_name": "Alex E Clark", + "author_inst": "University of California San Diego" }, { - "author_name": "Nishith M Shrimali", - "author_inst": "Regional Centre for Biotechnology, National Capital Region Biotech Science Cluster, Faridabad, India" + "author_name": "Joel Alter", + "author_inst": "Bar Ilan University" }, { - "author_name": "Anamika Singh", - "author_inst": "Regional Centre for Biotechnology, National Capital Region Biotech Science Cluster, Faridabad, India" + "author_name": "Michal Werbner", + "author_inst": "Bar Ilan University" }, { - "author_name": "Oinam N Singh", - "author_inst": "Translational Health Science Technology Institute, National Capital Region Biotech Science Cluster, Faridabad, India." + "author_name": "Jamie Lee", + "author_inst": "University of California San Diego" }, { - "author_name": "Puneet Srivastva", - "author_inst": "Translational Health Science Technology Institute, National Capital Region Biotech Science Cluster, Faridabad, India." + "author_name": "Sandra L Leibel", + "author_inst": "University of California San Diego" }, { - "author_name": "Tripti Shrivastava", - "author_inst": "Translational Health Science Technology Institute, National Capital Region Biotech Science Cluster, Faridabad, India." + "author_name": "Aaron F Carlin", + "author_inst": "University of California San Diego" }, { - "author_name": "Sudhanshu Vrati", - "author_inst": "Regional Centre for Biotechnology, National Capital Region Biotech Science Cluster, Faridabad, India" + "author_name": "Moshe Dassau", + "author_inst": "Bar Ilan University" }, { - "author_name": "Milan Surjit", - "author_inst": "Translational Health Science Technology Institute, National Capital Region Biotech Science Cluster, Faridabad, India." + "author_name": "Meital Gal-Tanamy", + "author_inst": "Bar Ilan University" + }, + { + "author_name": "Ben A Croker", + "author_inst": "University of California San Diego" }, { - "author_name": "Prasenjit Guchhait", - "author_inst": "Regional Centre for Biotechnology, National Capital Region Biotech Science Cluster, Faridabad, India;" + "author_name": "Ye Xiang", + "author_inst": "Tsinghua University" + }, + { + "author_name": "Natalia T Freund", + "author_inst": "Tel Aviv University" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by_nc_nd", "type": "new results", - "category": "pathology" + "category": "immunology" }, { "rel_doi": "10.1101/2022.04.03.486864", @@ -329811,33 +329446,33 @@ "category": "allergy and immunology" }, { - "rel_doi": "10.1101/2022.04.01.22273316", - "rel_title": "Modeling and Global Sensitivity Analysis of Strategies to Mitigate Covid-19 Transmission on a Structured College Campus", + "rel_doi": "10.1101/2022.04.01.22273281", + "rel_title": "Effectiveness of COVID-19 vaccines against Omicron and Delta hospitalisation: test negative case-control study", "rel_date": "2022-04-01", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.04.01.22273316", - "rel_abs": "In response to the COVID-19 pandemic, many higher educational institutions moved their courses on-line in hopes of slowing disease spread. The advent of multiple highly-effective vaccines offers the promise of a return to \"normal\" in-person operations, but it is not clear if--or for how long--campuses should employ non-pharmaceutical interventions such as requiring masks or capping the size of in-person courses. In this study, we develop and fine-tune a model of COVID-19 spread to UC Merceds student and faculty population. We perform a global sensitivity analysis to consider how both pharmaceutical and non-pharmaceutical interventions impact disease spread. Our work reveals that vaccines alone may not be sufficient to eradicate disease dynamics and that significant contact with an infectious surrounding community will maintain infections on-campus. Our work provides a foundation for higher-education planning allowing campuses to balance the benefits of in-person instruction with the ability to quarantine/isolate infectious individuals.", + "rel_link": "https://medrxiv.org/cgi/content/short/2022.04.01.22273281", + "rel_abs": "BackgroundThe omicron (B.1.1.529) variant has been associated with reduced vaccine effectiveness (VE) against infection and mild disease with rapid waning, even after a third dose, nevertheless omicron has also been associated with milder disease than previous variants. With previous variants protection against severe disease has been substantially higher than protection against infection.\n\nMethodsWe used a test-negative case-control design to estimate VE against hospitalisation with the omicron and delta variants using community and in hospital testing linked to hospital records. As a milder disease, there may be an increasing proportion of hospitalised individuals with Omicron as an incidental finding. We therefore investigated the impact of using more specific and more severe hospitalisation indicators on VE.\n\nResultsAmong 18-64 year olds using all Covid-19 cases admitted via emergency care VE after a booster peaked at 82.4% and dropped to 53.6% by 15+ weeks after the booster; using all admissions for >= 2 days stay with a respiratory code in the primary diagnostic field VE ranged from 90.9% down to 67.4%; further restricting to those on oxygen/ventilated/on intensive care VE ranged from 97.1% down to 75.9%. Among 65+ year olds the equivalent VE estimates were 92.4% down to 76.9%; 91.3% down to 85.3% and 95.8% down to 86.8%.\n\nConclusionsWith generally milder disease seen with Omicron, in particular in younger adults, contamination of hospitalisations with incidental cases is likely to reduce VE estimates against hospitalisation. VE estimates improve and waning and waning is more limited when definitions of hospitalisation that are more specific to severe respiratory disease are used.", "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Lihong Zhao", - "author_inst": "University of California Merced" + "author_name": "Julia Stowe", + "author_inst": "UK Health Security Agency" }, { - "author_name": "Fabian Santiago", - "author_inst": "University of California, Merced" + "author_name": "Nick Andrews", + "author_inst": "UK Health Security Agency" }, { - "author_name": "Erica M. Rutter", - "author_inst": "University of California, Merced" + "author_name": "Freja Kirsebom", + "author_inst": "UK Health Security Agency" }, { - "author_name": "Shilpa Khatri", - "author_inst": "University of California, Merced" + "author_name": "Mary Ramsay", + "author_inst": "UK Health Security Agency" }, { - "author_name": "Suzanne Sindi", - "author_inst": "University of California, Merced" + "author_name": "Jamie Lopez Bernal", + "author_inst": "UK Health Security Agency" } ], "version": "1", @@ -331793,131 +331428,47 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.03.24.22272732", - "rel_title": "Transcriptomic profiling of cardiac tissues from SARS-CoV-2 patients identifies DNA damage", + "rel_doi": "10.1101/2022.03.27.22273007", + "rel_title": "Global Reports of Myocarditis Following COVID-19 Vaccination: A Systematic Review and Meta-Analysis", "rel_date": "2022-03-31", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.03.24.22272732", - "rel_abs": "The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is known to present with pulmonary and extra-pulmonary organ complications. In comparison with the 2009 pandemic (pH1N1), SARS-CoV-2 infection is likely to lead to more severe disease, with multi-organ effects, including cardiovascular disease. SARS-CoV-2 has been associated with acute and long-term cardiovascular disease, but the molecular changes govern this remain unknown.\n\nIn this study, we investigated the landscape of cardiac tissues collected at rapid autopsy from SARS-CoV-2, pH1N1, and control patients using targeted spatial transcriptomics approaches. Although SARS-CoV-2 was not detected in cardiac tissue, host transcriptomics showed upregulation of genes associated with DNA damage and repair, heat shock, and M1-like macrophage infiltration in the cardiac tissues of COVID-19 patients. The DNA damage present in the SARS-CoV-2 patient samples, were further confirmed by {gamma}-H2Ax immunohistochemistry. In comparison, pH1N1 showed upregulation of Interferon-stimulated genes (ISGs), in particular interferon and complement pathways, when compared with COVID-19 patients.\n\nThese data demonstrate the emergence of distinct transcriptomic profiles in cardiac tissues of SARS-CoV-2 and pH1N1 influenza infection supporting the need for a greater understanding of the effects on extra-pulmonary organs, including the cardiovascular system of COVID-19 patients, to delineate the immunopathobiology of SARS-CoV-2 infection, and long term impact on health.", - "rel_num_authors": 28, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.03.27.22273007", + "rel_abs": "In December 2020, the FDA granted emergency approval to Pfizer-BioNTech (BNT162b2) and Moderna (mRNA-1273) COVID-19 vaccines. There have been recent media reports of myocarditis after receiving COVID-19 vaccines, particularly the messenger RNA (mRNA) vaccines, causing public concern. This review summarizes information from published case series and case reports, with a strong emphasis on reporting patient and disease characteristics, investigation, and clinical outcome, to provide a comprehensive picture of the condition. Forty studies, including 147 cases, participated in this systematic review. The median age was 28.9 years; 93.9% were male and 6.1% were female. 72.1% of patients received the Pfizer-BioNTech (BNT162b2) vaccine, 24.5% of patients received the Moderna COVID-19 Vaccine (mRNA-1273), and the rest of the 3.3% received other types of vaccines. Furthermore, most myocarditis cases (87.1%) occurred after the second vaccine dose, after a median time interval of 3.3 days. The most frequently reported symptoms were chest pain, myalgia/body aches and fever. Troponin levels were consistently elevated in 98.6%. The admission ECG was abnormal in 88.5% of cases, and the left LVEF was lower than 50% in 26.5% of cases. The vast majority of patients (93.2%) resolved symptoms and recovered, and only 3 patients died. These findings may help public health policy to consider myocarditis in the context of the benefits of COVID-19 vaccination as well as to assess the cardiac condition before the choice of vaccine, which is offered to male adults. In addition, it must be carefully weighed against the very substantial benefit of vaccination.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Arutha Kulasinghe", - "author_inst": "The University of Queensland" - }, - { - "author_name": "Ning Liu", - "author_inst": "The Walter and Eliza Hall Institute" - }, - { - "author_name": "Chin Wee Tan", - "author_inst": "The Walter and Eliza Hall Institute" - }, - { - "author_name": "James Monkman", - "author_inst": "The University of Queensland Diamantina Institute" - }, - { - "author_name": "Jane E Sinclair", - "author_inst": "The University of Queensland" - }, - { - "author_name": "Dharmesh D Bhuva", - "author_inst": "The Walter and Eliza Hall Institute" - }, - { - "author_name": "David Godbolt", - "author_inst": "The Prince Charles Hospital" - }, - { - "author_name": "Liuliu Pan", - "author_inst": "Nanostring Technologies" - }, - { - "author_name": "Andy Nam", - "author_inst": "Nanostring Technologies" - }, - { - "author_name": "Habib Sadeghirad", - "author_inst": "The University of Queensland Diamantina Institute" - }, - { - "author_name": "Kei Sato", - "author_inst": "The University of Queensland" - }, - { - "author_name": "Gianluigi Li Bassi", - "author_inst": "University of Queensland" - }, - { - "author_name": "Ken O'Byrne", - "author_inst": "Princess Alexandra Hospital" - }, - { - "author_name": "Camila Hartmann", - "author_inst": "Pontifical Catholic University of Parana" - }, - { - "author_name": "Anna Flavia Ribeiro dos Santos Miggiolaro", - "author_inst": "Pontifical Catholic University of Parana" - }, - { - "author_name": "Gustavo Lenci Marques", - "author_inst": "Pontifical Catholic University of Parana" - }, - { - "author_name": "Lidia Zytynski Moura", - "author_inst": "Pontifical Catholic University of Parana" - }, - { - "author_name": "Derek Richard", - "author_inst": "Queensland University of Technology" - }, - { - "author_name": "Mark N Adams", - "author_inst": "Queensland University of Technology" - }, - { - "author_name": "Lucia Noronha", - "author_inst": "Pontifical Catholic University of Parana" - }, - { - "author_name": "Cristina Pellegrino Baena", - "author_inst": "Pontifical Catholic University of Parana" - }, - { - "author_name": "Jacky Suen", - "author_inst": "The University of Queensland" + "author_name": "Sirwan Khalid Ahmed", + "author_inst": "Department of Emergency, Rania Teaching Hospital, Rania 46012, Kurdistan region-Iraq." }, { - "author_name": "Rakesh Arora", - "author_inst": "The University of Manitoba" + "author_name": "Mona Gamal Mohamed", + "author_inst": "Department of Adult Nursing, RAK Medical and Health Sciences University, Ras Al Khaimah, UAE" }, { - "author_name": "Gabrielle T Belz", - "author_inst": "The University of Queensland" + "author_name": "Rawand Abdulrahman Essa", + "author_inst": "Department of Cardiothoracic and Vascular Surgery, Rania Medical City Hospital, Rania, Sulaimani, Kurdistan-Region, Iraq" }, { - "author_name": "Kirsty Short", - "author_inst": "University of Queensland" + "author_name": "Eman Abdelazizi Ahmed Rashad", + "author_inst": "Department of Adult Nursing, RAK Medical and Health Sciences University, Ras Al Khaimah, UAE" }, { - "author_name": "Melissa J Davis", - "author_inst": "The Walter and Eliza Hall Institute" + "author_name": "Peshraw Khdir Ibrahim", + "author_inst": "Department of Nursing, University of Raparin, Sulaimani, Rania, Kurdistan-region, Iraq" }, { - "author_name": "Fernando SF Guimaraes", - "author_inst": "The University of Queensland Diamantina Institute" + "author_name": "Awat Alla Khdir", + "author_inst": "Department of Emergency, Rania Teaching Hospital, Rania 46012, Kurdistan region-Iraq" }, { - "author_name": "John F Fraser", - "author_inst": "The University of Queensland" + "author_name": "Zhiar Hussen Wsu", + "author_inst": "Department of Emergency, Rania Teaching Hospital, Rania 46012, Kurdistan region-Iraq" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "cardiovascular medicine" }, { "rel_doi": "10.1101/2022.03.31.22273230", @@ -334387,59 +333938,43 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2022.03.25.22272948", - "rel_title": "Labor market position and depression during the COVID-19 epidemic among young adults (18 to 30 years): a nationally representative study in France.", + "rel_doi": "10.1101/2022.03.28.22273029", + "rel_title": "Healthcare workers perceptions and medically approved COVID-19 infection risk: understanding the mental health dimension of the pandemic. A German hospital case study", "rel_date": "2022-03-30", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.03.25.22272948", - "rel_abs": "ObjectiveTo examine the relationship between young adults labor force participation and depression in the context of the COVID-19 pandemic.\n\nDesign, Setting, ParticipantsData come from the nationally-representative EPICOV cohort study set up in France, and were collected in 2020 and 2021 (3 waves of online or telephone interviews) among 2217 participants aged 18-30 years. Participants with prior mental health disorder (n=50) were excluded from the statistical analyses.\n\nResultsUsing Generalized Estimating Equation (GEE) models controlled for participants socio-demographic and health characteristics and weighted to be nationally-representative, we found that compared to young adults who were employed, those who were studying or unemployed were significantly more likely to experience depression assessed using the PHQ-9 (multivariate ORs respectively: OR: 1.29, 95% CI 1.05-1.60 and OR: 1.50, 1.13-1.99). Stratifying the analyses by age, we observed than unemployment was more strongly associated with depression among participants 25-30 years than among those who were 18-24 years (multivariate ORs respectively 1.78, 95% CI 1.17-2.71 and 1.41, 95% CI 0.96-2.09). Being out of the labor force was, to the contrary, more significantly associated with depression among participants 18-24 years (multivariate OR: 1.71, 95% CI 1.04-2.82, vs. 1.00, 95% CI 0.53-1.87 among participants 25-30 years). Stratifying the analyses by sex, we found no significant differences in the relationships between labor market characteristics and depression (compared to participants who were employed, multivariate ORs associated with being a student: men: 1.33, 95% CI 1.01-1.76; women: 1.19, 95% CI 0.85-1.67, multivariate ORs associated with being unemployed: men: 1.60, 95% CI 1.04-2.45; women: 1.47, 95% CI 1.01-2.15).\n\nConclusions and relevanceOur study shows that in addition to students, young adults who are unemployed also experience elevated levels of depression in the context of the COVID-19 pandemic. These two groups should be the focus of specific attention in terms of prevention and mental health treatment. Supporting employment could also be a propitious way of reducing the burden of the Covid-19 pandemic on the mental health of young adults.\n\nKey PointsO_ST_ABSQuestionC_ST_ABSIs labor force participation associated with young adults likelihood of depression during the COVID-19 pandemic?\n\nFindingsIn a nationally-representative cohort study in France, compared to young adults who are employed, those who are studying or experience unemployment had elevated odds of depression in 2020 and 2021.\n\nMeaningYoung people are experiencing the highest burden of mental health problems in the context of the COVID-19 epidemic - our study implies that those who are studying or are unemployed are at especially high risk and should be the focus of attention in terms of prevention and treatment.", - "rel_num_authors": 10, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.03.28.22273029", + "rel_abs": "IntroductionThis study analyses how healthcare workers (HCWs) perceived risks, protection and preventive measures during the COVID-19 pandemic in relation to medically approved risks and organisational measures. The aim is to explore blind spots of pandemic protection and make mental health needs of HCWs visible.\n\nMethodsWe have chosen an optimal-case scenario of a high-income country with a well-resourced hospital sector and low HCW infection rate at the organisational level to explore governance gaps in HCW protection. A German multi-method hospital study at Hannover Medical School served as empirical case; document analysis, expert information and survey data (n=1163) were collected as part of a clinical study into SARS-CoV-2 serology testing during the second wave of the pandemic (November 2020-February 2021). Selected survey items included perceptions of risks, protection and preventive measures. Descriptive statistical analysis and regression were undertaken for gender, profession and COVID-19 patient care.\n\nResultsThe results reveal a low risk of 1% medically approved infections among participants, but a much higher mean personal risk estimate of 15%. The majority (68.4%) expressed some to very strong fear of acquiring infection at the workplace. Individual protective behaviour and compliance with protective workplace measures were estimated as very high. Yet only about half of the respondents felt strongly protected by the employer; 12% even perceived no or little protection. Gender and contact with COVID-19 patients had no significant effect on the estimations of infection risks and protective workplace behaviour, but nursing was correlated with higher levels of personal risk estimations and fear of infection.\n\nConclusionsA strong mismatch between low medically approved risk and personal risk perceptions of HCWs brings stressors and threats into view, that may be preventable through better information and risk communication and through investment in mental health and inclusion in pandemic preparedness plans.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Maria Melchior", - "author_inst": "INSERM" - }, - { - "author_name": "Aline-Marie Florence", - "author_inst": "INSERM" - }, - { - "author_name": "Camille Davisse-Paturet", - "author_inst": "INSERM" - }, - { - "author_name": "Bruno Falissard", - "author_inst": "Paris Saclay" - }, - { - "author_name": "Cedric Galera", - "author_inst": "Bordeaux University" + "author_name": "Ellen Kuhlmann", + "author_inst": "Medizinische Hochschule Hannover" }, { - "author_name": "Jean-Baptiste Hazo", - "author_inst": "Ministry of Health" + "author_name": "Georg Behrens", + "author_inst": "Hannover Medical School" }, { - "author_name": "Cecile Vuillermoz", - "author_inst": "INSERM" + "author_name": "Anne Cossmann", + "author_inst": "Medizinische Hochschule Hannover" }, { - "author_name": "Josiane WARSZAWSKI", - "author_inst": "INSERM CESP Universite Paris-Saclay, Service de sante publique, AP-HP" + "author_name": "Stefanie Homann", + "author_inst": "Medizinische Hochschule Hannover" }, { - "author_name": "Fallou Dione", - "author_inst": "INSERM" + "author_name": "Christine Happle", + "author_inst": "Medizinische Hochschule Hannover" }, { - "author_name": "Alexandra Rouquette", - "author_inst": "Paris Saclay" + "author_name": "Alexandra Dopfer-Jablonka", + "author_inst": "Hannover Medical School" } ], "version": "1", "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "rheumatology" }, { "rel_doi": "10.1101/2022.03.28.22273077", @@ -336809,99 +336344,71 @@ "category": "gastroenterology" }, { - "rel_doi": "10.1101/2022.03.23.22270017", - "rel_title": "Serological Response to Three, Four and Five Doses of SARS-CoV-2 Vaccine in Kidney Transplant Recipients", + "rel_doi": "10.1101/2022.03.24.22272871", + "rel_title": "Detection and prevalence of SARS-CoV-2 co-infections during the Omicron variant circulation, France, December 2021 - February 2022", "rel_date": "2022-03-27", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.03.23.22270017", - "rel_abs": "Mortality from COVID-19 among kidney transplant recipients (KTR) is high, and their response to three vaccinations against SARS-CoV-2 is strongly impaired.\n\nWe retrospectively analyzed serological response of up to five doses of SARS-CoV-2 vaccine in KTR from December 27, 2020, until December 31, 2021. Particularly, the influence of different dose adjustment regimens for mycophenolic acid (MPA) on serological response to fourth vaccination was analyzed.\n\nIn total, 4.277 vaccinations against SARS-CoV-2 in 1.478 patients were analyzed. Serological response was 19.5% after 1.203 basic immunizations, and increased to 29.4%, 55.6%, and 57.5% in response to 603 third, 250 fourth and 40 fifth vaccinations, resulting in a cumulative response rate of 88.7%.\n\nIn patients with calcineurin inhibitor and MPA maintenance immunosuppression, pausing MPA and adding 5 mg prednisolone equivalent before the fourth vaccination increased serological response rate to 75% in comparison to no dose adjustment (52%) or dose reduction (46%). Belatacept-treated patients had a response rate of 8.7% (4/46) after three vaccinations and 12.5% (3/25) after four vaccinations.\n\nExcept for belatacept-treated patients, repeated SARS-CoV-2 vaccination of up to five times effectively induces serological response in kidney transplant recipients. It can be enhanced by pausing MPA at the time of vaccination.", - "rel_num_authors": 20, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.03.24.22272871", + "rel_abs": "In Dec 2021-Feb 2022, an intense and unprecedented co-circulation of SARS-CoV-2 variants with high genetic diversity raised the question of possible co-infections between variants and how to detect them. Using 11 mixes of Delta:Omicron isolates at different ratios, we evaluated the performance of 4 different sets of primers used for whole-genome sequencing and we developed an unbiased bioinformatics method which can detect all co-infections irrespective of the SARS-CoV-2 lineages involved. Applied on 21,387 samples collected between weeks 49-2021 and 08-2022 from random genomic surveillance in France, we detected 53 co-infections between different lineages. The prevalence of Delta and Omicron (BA.1) co-infections and Omicron lineages BA.1 and BA.2 co-infections were estimated at 0.18% and 0.26%, respectively. Among 6,242 hospitalized patients, the intensive care unit (ICU) admission rates were 1.64%, 4.81% and 15.38% in Omicron, Delta and Delta/Omicron patients, respectively. No BA.1/BA.2 co-infections were reported among ICU admitted patients. Although SARS-CoV-2 co-infections were rare in this study, their proper detection is crucial to evaluate their clinical impact and the risk of the emergence of potential recombinants.", + "rel_num_authors": 13, "rel_authors": [ { - "author_name": "Bilgin Osmanodja", - "author_inst": "Department of Nephrology and Medical Intensive Care, Charite Berlin, Berlin, Germany" - }, - { - "author_name": "Simon Ronicke", - "author_inst": "Department of Nephrology and Medical Intensive Care, Charite Berlin, Berlin, Germany" - }, - { - "author_name": "Klemens Budde", - "author_inst": "Department of Nephrology and Medical Intensive Care, Charite Berlin, Berlin, Germany" - }, - { - "author_name": "Annika Jens", - "author_inst": "Department of Nephrology and Medical Intensive Care, Charite Berlin, Berlin, Germany" - }, - { - "author_name": "Charlotte Hammett", - "author_inst": "Department of Nephrology and Medical Intensive Care, Charite Berlin, Berlin, Germany" - }, - { - "author_name": "Nadine Koch", - "author_inst": "Department of Nephrology and Medical Intensive Care, Charite Berlin, Berlin, Germany" - }, - { - "author_name": "Evelyn Seelow", - "author_inst": "Department of Nephrology and Medical Intensive Care, Charite Berlin, Berlin, Germany" - }, - { - "author_name": "Johannes Waiser", - "author_inst": "Department of Nephrology and Medical Intensive Care, Charite Berlin, Berlin, Germany" + "author_name": "Antonin Bal", + "author_inst": "Hospices Civils de Lyon" }, { - "author_name": "Bianca Zukunft", - "author_inst": "Department of Nephrology and Medical Intensive Care, Charite Berlin, Berlin, Germany" + "author_name": "Bruno Simon", + "author_inst": "Hospices Civils de Lyon" }, { - "author_name": "Friederike Bachmann", - "author_inst": "Department of Nephrology and Medical Intensive Care, Charite Berlin, Berlin, Germany" + "author_name": "Gregory Destras", + "author_inst": "Institut des Agents Infectieux - Hospices Civils de Lyon" }, { - "author_name": "Mira Choi", - "author_inst": "Department of Nephrology and Medical Intensive Care, Charite Berlin, Berlin, Germany" + "author_name": "Richard Chalvignac", + "author_inst": "Hospices Civils de Lyon" }, { - "author_name": "Ulrike Weber", - "author_inst": "Department of Nephrology and Medical Intensive Care, Charite Berlin, Berlin, Germany" + "author_name": "Quentin Semanas", + "author_inst": "Hospices Civils de Lyon" }, { - "author_name": "Bettina Ebersp\u00e4cher", - "author_inst": "Labor Berlin-Charite Vivantes GmbH, Berlin, Germany" + "author_name": "Antoine Oblette", + "author_inst": "Hospices Civils de Lyon" }, { - "author_name": "J\u00f6rg Hofmann", - "author_inst": "Labor Berlin-Charite Vivantes GmbH, Berlin, Germany" + "author_name": "Gregory Queromes", + "author_inst": "Hospices Civils de Lyon" }, { - "author_name": "Fritz Grunow", - "author_inst": "Department of Nephrology and Medical Intensive Care, Charite Berlin, Berlin, Germany" + "author_name": "Remi Fanget", + "author_inst": "Hospices Civils de Lyon" }, { - "author_name": "Michael Mikhailov", - "author_inst": "Department of Nephrology and Medical Intensive Care, Charite Berlin, Berlin, Germany" + "author_name": "Hadrien Regue", + "author_inst": "Hospices Civils de Lyon" }, { - "author_name": "Lutz Liefeldt", - "author_inst": "Department of Nephrology and Medical Intensive Care, Charite Berlin, Berlin, Germany" + "author_name": "Florence Morfin", + "author_inst": "Hospices Civils de Lyon" }, { - "author_name": "Kai-Uwe Eckardt", - "author_inst": "Department of Nephrology and Medical Intensive Care, Charite Berlin, Berlin, Germany" + "author_name": "Martine Valette", + "author_inst": "Hospices Civils de Lyon" }, { - "author_name": "Fabian Halleck", - "author_inst": "Department of Nephrology and Medical Intensive Care, Charite Berlin, Berlin, Germany" + "author_name": "Bruno Lina", + "author_inst": "Hospices Civils de Lyon" }, { - "author_name": "Eva Schrezenmeier", - "author_inst": "Department of Nephrology and Medical Intensive Care, Charite Berlin, Berlin, Germany" + "author_name": "Laurence Josset", + "author_inst": "Hospices Civils de Lyon" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "nephrology" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2022.03.24.22272768", @@ -338447,63 +337954,59 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2022.03.22.485425", - "rel_title": "Influenza infection in ferrets with SARS-CoV-2 infection history", + "rel_doi": "10.1101/2022.03.24.485596", + "rel_title": "Differences in neuroinflammation in the olfactory bulb between D614G, Delta and Omicron BA.1 SARS-CoV-2 variants in the hamster model", "rel_date": "2022-03-24", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.03.22.485425", - "rel_abs": "Non-pharmaceutical interventions (NPIs) to contain the SARS-CoV-2 pandemic drastically reduced human-to-human interactions, decreasing the circulation of other respiratory viruses as well. As a consequence, influenza virus circulation - normally responsible for 3-5 million hospitalizations per year globally - was significantly reduced. With downscaling the NPI countermeasures, there is a concern for increased influenza disease, particularly in individuals suffering from post-acute effects of SARS-CoV-2 infection. To investigate this possibility, we performed a sequential influenza H1N1 infection 4 weeks after an initial SARS-CoV-2 infection in the ferret model. Upon H1N1 infection, ferrets that were previously infected with SARS-CoV-2 showed an increased tendency to develop clinical symptoms compared to the control H1N1 infected animals. Histopathological analysis indicated only a slight increase for type II pneumocyte hyperplasia and bronchitis. The effects of the sequential infection thus appeared minor. However, ferrets were infected with B.1.351-SARS-CoV-2, the beta variant of concern, which replicated poorly in our model. The histopathology of the respiratory organs was mostly resolved 4 weeks after SARS-CoV-2 infection, with only reminiscent histopathological features in the upper respiratory tract. Nevertheless, SARS-CoV-2 specific cellular and humoral responses were observed, confirming an established infection. Thus, there may likely be a SARS-CoV-2 variant-dependent effect on the severity of disease upon a sequential influenza infection as we observed mild effects upon a mild infection. It, however, remains to be determined what the impact is of more virulent SARS-CoV-2 variants.\n\nImportanceDuring the COVID-19 pandemic, the use of face masks, social distancing and isolation were not only effective in decreasing the circulation of SARS-CoV-2, but also in reducing other respiratory viruses such as influenza. With less restrictions, influenza is slowly returning. In the meantime, people still suffering from long-COVID, could be more vulnerable to an influenza virus infection and develop more severe influenza disease. This study provides directions to the effect of a previous SARS-CoV-2 exposure on influenza disease severity in the ferret model. This model is highly valuable to test sequential infections under controlled settings for translation to humans. We could not induce clear long-term COVID-19 effects as SARS-CoV-2 infection in ferrets was mild. However, we still observed a slight increase in influenza disease severity compared to ferrets that had not encountered SARS-CoV-2 before. It may therefore be advisable to include long-COVID patients as a risk group for influenza vaccination.", - "rel_num_authors": 11, + "rel_link": "https://biorxiv.org/cgi/content/short/2022.03.24.485596", + "rel_abs": "Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is associated with various neurological complications. SARS-CoV-2 infection induces neuroinflammation in the central nervous system (CNS), whereat the olfactory bulb seems to be involved most frequently. Here we show differences in the neuroinvasiveness and neurovirulence among SARS-CoV-2 variants in the hamster model five days post inoculation. Replication in the olfactory mucosa was observed in all hamsters, but most prominent in D614 inoculated hamsters. We observed neuroinvasion into the CNS via the olfactory nerve in D614G-, but not Delta (B.1.617.2)- or Omicron BA.1 (B.1.1.529) inoculated hamsters. Neuroinvasion was associated with neuroinflammation in the olfactory bulb of hamsters inoculated with D614G but hardly in Delta or Omicron BA.1. Altogether, this indicates that there are differences in the neuroinvasive and neurovirulent potential among SARS-CoV-2 variants in the acute phase of the infection in the hamster model.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Caroline Vilas Boas de Melo", - "author_inst": "National Institute for Public Health and the Environment" - }, - { - "author_name": "Florence Peters", - "author_inst": "National Institute for Public Health and the Environment" + "author_name": "Lisa Bauer", + "author_inst": "Erasmus Medical Center" }, { - "author_name": "Harry van Dijken", - "author_inst": "National Institute for Public Health and the Environment" + "author_name": "Melanie Rissmann", + "author_inst": "Erasmus Medical Center" }, { - "author_name": "Stefanie Lenz", - "author_inst": "National Institute for Public Health and the Environment" + "author_name": "Feline Benavides", + "author_inst": "Erasmus Medical Center" }, { - "author_name": "Koen van de Ven", - "author_inst": "National Institute for Public Health and the Environment" + "author_name": "Lonneke Leijten", + "author_inst": "Erasmus Medical Center" }, { - "author_name": "Lisa Wijsman", - "author_inst": "National Institute for Public Health and the Environment" + "author_name": "Lineke Begeman", + "author_inst": "Erasmus MC" }, { - "author_name": "Ang\u00e9la Gommersbach", - "author_inst": "Poonawalla Science Park" + "author_name": "Edwin Veldhuis Kroeze", + "author_inst": "Erasmus MC" }, { - "author_name": "Tanja Schouten", - "author_inst": "Poonawalla Sciencepark" + "author_name": "Peter van Run", + "author_inst": "Erasmus MC" }, { - "author_name": "Puck B van Kasteren", - "author_inst": "National Institute for Public Health and the Environment (RIVM)" + "author_name": "Marion P.G Koopmans", + "author_inst": "Erasmus Medical Center" }, { - "author_name": "Judith M.A. van den Brand", - "author_inst": "University of Utrecht" + "author_name": "Barry Rockx", + "author_inst": "Erasmus University Medical Center" }, { - "author_name": "Jorgen de Jonge", - "author_inst": "National Institute for Public Health and the Environment" + "author_name": "Debby van Riel", + "author_inst": "Erasmus University Medical Center" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "new results", - "category": "pathology" + "category": "microbiology" }, { "rel_doi": "10.1101/2022.03.24.485614", @@ -340317,65 +339820,25 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.03.22.22272773", - "rel_title": "Risk of SARS-CoV-2 transmission by fomites: a clinical observational study in highly infectious COVID-19 patients", + "rel_doi": "10.1101/2022.03.22.22272758", + "rel_title": "Mathematical modelling of COVID-19 transmission dynamics with vaccination: A case study in Ethiopia", "rel_date": "2022-03-23", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.03.22.22272773", - "rel_abs": "BackgroundThe contribution of droplet-contaminated surfaces for virus transmission has been discussed controversially in the context of the current Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) pandemic. Importantly, the risk of fomite-based transmission has not been systematically addressed.\n\nMethodsWe initiated this single-center observational study to evaluate whether hospitalized COVID-19 patients can contaminate stainless steel carriers by coughing or intensive moistening with saliva and to assess the risk of SARS-CoV-2 transmission upon detection of viral loads and infectious virus in cell culture. Fifteen hospitalized patients with a high baseline viral load (CT value [≤] 25) shortly after admission were included. We documented clinical and laboratory parameters and used patient samples to perform virus culture, quantitative PCR and virus sequencing.\n\nResultsNasopharyngeal and oropharyngeal swabs of all patients were positive for viral RNA on the day of the study. Infectious SARS-CoV-2 could be isolated from 6 patient swabs (46.2 %). While after coughing, no infectious virus could be recovered, intensive moistening with saliva resulted in successful viral recovery from steel carriers of 5 patients (38.5 %).\n\nConclusionsTransmission of infectious SARS-CoV-2 via fomites is possible upon extensive moistening, but unlikely to occur in real-life scenarios and from droplet-contaminated fomites.", - "rel_num_authors": 13, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.03.22.22272758", + "rel_abs": "Mathematical modelling is important for better understanding of disease dynamics and developing strategies to manage rapidly spreading infectious diseases. In this work, we consider a mathematical model of COVID-19 transmission with double-dose vaccination strategy to control the disease. For the analytical analysis purpose we divided the model into two, model with vaccination and without vaccination. Analytical and numerical approach is employed to investigate the results. In the analytical study of the model we have shown the local and global stability of disease-free equilibrium, existence of the endemic equilibrium and its local stability, positivity of the solution, invariant region of the solution, transcritical bifurcation of equilibrium and sensitivity analysis of the model is conducted. From these analyses, for the full model (model with vaccination) we found that the disease-free equilibrium is globally asymptotically stable for Rv < 1 and is unstable for Rv > 1. A locally stable endemic equilibrium exists for Rv > 1, which shows the persistence of the disease if the reproduction parameter is greater than unity. The model is fitted to cumulative daily infected cases and vaccinated individuals data of Ethiopia from May 01, 2021 to January 31, 2022. The unknown parameters are estimated using the least square method with the MATLAB built-in function lsqcurvefit. The basic reproduction number, R0 and controlled reproduction number Rv are calculated to be R0 = 1.17 and Rv = 1.15 respectively. Finally, we performed different simulations using MATLAB. From the simulation results, we found that it is important to reduce the transmission rate, infectivity factor of asymptomatic cases and, increase the vaccination coverage and quarantine rate to control the disease transmission.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Toni Luise Meister", - "author_inst": "Ruhr University Bochum" - }, - { - "author_name": "Marielen Dreismeier", - "author_inst": "Ruhr University Bochum" - }, - { - "author_name": "Elena Vidal Blanco", - "author_inst": "Ruhr University Bochum" - }, - { - "author_name": "Yannick Brueggemann", - "author_inst": "Ruhr University Bochum" - }, - { - "author_name": "Natalie Heinen", - "author_inst": "Ruhr University Bochum" - }, - { - "author_name": "Guenter Kampf", - "author_inst": "University Medicine Greifswald" - }, - { - "author_name": "Daniel Todt", - "author_inst": "Ruhr University Bochum" - }, - { - "author_name": "Huu Phuc Nguyen", - "author_inst": "Ruhr University Bochum" - }, - { - "author_name": "Joerg Steinmann", - "author_inst": "Paracelsus Medical University" - }, - { - "author_name": "Wolfgang Ekkehard Schmidt", - "author_inst": "Ruhr University Bochum" - }, - { - "author_name": "Eike Steinmann", - "author_inst": "Ruhr University Bochum" + "author_name": "Sileshi Sintayehu Sharbayta", + "author_inst": "Addis Ababa University" }, { - "author_name": "Daniel Robert Quast", - "author_inst": "Ruhr University Bochum" + "author_name": "Henok Desalegn Desta", + "author_inst": "Addis Ababa University" }, { - "author_name": "Stephanie Pfaender", - "author_inst": "Ruhr University Bochum" + "author_name": "Tadesse Abdi", + "author_inst": "Addis Ababa University" } ], "version": "1", @@ -342339,47 +341802,27 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2022.03.18.22272462", - "rel_title": "A fast and sensitive absolute quantification assay for the detection of SARS-CoV-2 peptides using Parallel Reaction Monitoring Mass Spectrometry", + "rel_doi": "10.1101/2022.03.21.22272687", + "rel_title": "Cost-effectiveness of antigen testing for ending COVID-19 isolation", "rel_date": "2022-03-21", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.03.18.22272462", - "rel_abs": "The on-going SARS-CoV-2 (COVID-19) pandemic has called for an urgent need for rapid and high-throughput methods for mass testing for early detection, prevention and surveillance of the disease. Here, we tested if targeted parallel reaction monitoring (PRM) quantification using high resolution Orbitrap instruments can provide the sensitivity and speed required for a high-throughput method that could be used for clinical diagnosis. Here we report a high-throughput and sensitive PRM-MS assay that enables absolute quantification of SARS-CoV-2 nucleocapsid peptides with short turn-around times. Concatenated peptides (QconCAT) synthesized using isotopically labelled SARS-CoV-2 were used for absolute quantification. We developed a fast and high-throughput S-trap-based sample preparation method, which was then successfully utilized for testing 25 positive and 25 negative heat-inactivated nasopharyngeal swab samples for SARS-CoV-2 detection. The method was able to differentiate between negative and positive patients accurately within its limits of detection. Moreover, extrapolating from the QconCAT absolute quantification, our data show that patients with Ct values as low as 17.5 have NCAP protein amounts of around 7.5 pmol in swab samples. The present high-throughput method could potentially be utilized in specialized clinics as an alternative tool for detection of SARS-CoV-2.", - "rel_num_authors": 7, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.03.21.22272687", + "rel_abs": "BackgroundThe Omicron variant of SARS-CoV-2 led to a steep rise in transmissions. Recently, as public tolerance for isolation abated, CDC guidance on duration of at-home isolation of COVID-19 cases was shortened to five days if no symptoms, with no lab test requirement, despite more cautious approaches advocated by other federal experts.\n\nMethodsWe conducted a decision tree analysis of alternative protocols for ending COVID-19 isolation, estimating net costs (direct and productivity), secondary infections, and incremental cost-effectiveness ratios. Sensitivity analyses assessed the impact of input uncertainty.\n\nResultsPer 100 individuals, five-day isolation had 23 predicted secondary infections and a net cost of $33,000. Symptom check on day five (CDC guidance) yielded a 23% decrease in secondary infections (to 17.8), with a net cost of $45,000. Antigen testing on day six yielded 2.9 secondary infections and $63,000 in net costs. This protocol, compared to the next best protocol of antigen testing on day five of a maximum eight-day isolation, cost an additional $1,300 per secondary infection averted. Antigen or polymerase chain reaction testing on day five were dominated (more expensive and less effective) versus antigen testing on day six. Results were qualitatively robust to uncertainty in key inputs.\n\nConclusionsA six-day isolation with antigen testing to confirm the absence of contagious virus appears the most effective and cost-effective de-isolation protocol to shorten at-home isolation of individuals with COVID-19.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Akshada Gajbhiye", - "author_inst": "Newcastle University" - }, - { - "author_name": "Atakan Nalbant", - "author_inst": "Newcastle University" - }, - { - "author_name": "Tiaan Heunis", - "author_inst": "Newcastle University" - }, - { - "author_name": "Frances Sidgwick", - "author_inst": "Newcastle University" - }, - { - "author_name": "Andrew Porter", - "author_inst": "Newcastle University" - }, - { - "author_name": "Yusri Taha", - "author_inst": "The Newcastle upon Tyne Hospitals NHS Foundation Trust" + "author_name": "Sigal Maya", + "author_inst": "University of California San Francisco" }, { - "author_name": "Matthias Trost", - "author_inst": "Newcastle University" + "author_name": "James G. Kahn", + "author_inst": "University of California San Francisco" } ], "version": "1", "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "health economics" }, { "rel_doi": "10.1101/2022.03.20.485050", @@ -344453,35 +343896,75 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2022.03.18.484954", - "rel_title": "Peptidome Surveillance Across Evolving SARS-CoV-2 Lineages Reveals HLA Binding Conservation in Nucleocapsid Among Variants With Most Potential for T-Cell Epitope Loss In Spike", + "rel_doi": "10.1101/2022.03.18.484956", + "rel_title": "Human Galectin-9 Potently Enhances SARS-CoV-2 Replication and Inflammation in Airway Epithelial Cells", "rel_date": "2022-03-20", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.03.18.484954", - "rel_abs": "To provide a unique global view of the relative potential for evasion of CD8+ and CD4+ T cells by SARS-CoV-2 lineages as they evolve over time, we performed a comprehensive analysis of predicted HLA-I and HLA-II binding peptides in spike (S) and nucleocapsid (N) protein sequences of all available SARS-CoV-2 genomes as provided by NIH NCBI at a bi-monthly interval between March and December of 2021. A data supplement of all B.1.1.529 (Omicron) genomes from GISAID in early December was also used to capture the rapidly spreading variant. A key finding is that throughout continued viral evolution and increasing rates of mutations occurring at T-cell epitope hotspots, protein instances with worst case binding loss did not become the most frequent for any Variant of Concern (VOC) or Variant of Interest (VOI) lineage; suggesting T-cell evasion is not likely to be a dominant evolutionary pressure on SARS-CoV-2. We also determined that throughout the course of the pandemic in 2021, there remained a relatively steady ratio of viral variants that exhibit conservation of epitopes in the N protein, despite significant potential for epitope loss in S relative to other lineages. We further localized conserved regions in N with high epitope yield potential, and illustrated HLA-I binding heterogeneity across the S protein consistent with empirical observations. Although Omicrons high volume of mutations caused it to exhibit more epitope loss potential than most frequently observed versions of proteins in almost all other VOCs, epitope candidates across its most frequent N proteins were still largely conserved. This analysis adds to the body of evidence suggesting that N may have merit as an additional antigen to elicit immune responses to vaccination with increased potential to provide sustained protection against COVID-19 disease in the face of emerging variants.", - "rel_num_authors": 4, + "rel_link": "https://biorxiv.org/cgi/content/short/2022.03.18.484956", + "rel_abs": "The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has caused a global economic and health crisis. Recently, plasma levels of galectin-9 (Gal-9), a {beta}-galactoside-binding lectin involved in immune regulation and viral immunopathogenesis, were reported to be elevated in the setting of severe COVID-19 disease. However, the impact of Gal-9 on SARS-CoV-2 infection and immunopathology remained to be elucidated. Here, we demonstrate that Gal-9 treatment potently enhances SARS-CoV-2 replication in human airway epithelial cells (AECs), including primary AECs in air-liquid interface (ALI) culture. Gal-9-glycan interactions promote SARS-CoV-2 attachment and entry into AECs in an ACE2-dependent manner, enhancing the binding affinity of the viral spike protein to ACE2. Transcriptomic analysis revealed that Gal-9 and SARS-CoV-2 infection synergistically induce the expression of key pro-inflammatory programs in AECs including the IL-6, IL-8, IL-17, EIF2, and TNF signaling pathways. Our findings suggest that manipulation of Gal-9 should be explored as a therapeutic strategy for SARS-CoV-2 infection.\n\nImportanceCOVID-19 continues to have a major global health and economic impact. Identifying host molecular determinants that modulate SARS-CoV-2 infectivity and pathology is a key step in discovering novel therapeutic approaches for COVID-19. Several recent studies have revealed that plasma concentrations of the human {beta}-galactoside-binding protein galectin-9 (Gal-9) are highly elevated in COVID-19 patients. In this study, we investigated the impact of Gal-9 on SARS-CoV-2 pathogenesis ex vivo in airway epithelial cells (AECs), the critical initial targets of SARS-CoV-2 infection. Our findings reveal that Gal-9 potently enhances SARS-CoV-2 replication in AECs, interacting with glycans to enhance the binding between viral particles and entry receptors on the target cell surface. Moreover, we determined that Gal-9 accelerates and exacerbates several virus-induced pro-inflammatory programs in AECs that are established signature characteristics of COVID-19 disease and SARS-CoV-2-induced acute respiratory distress syndrome (ARDS). Our findings suggest that Gal-9 is a promising pharmacological target for COVID-19 therapies.", + "rel_num_authors": 14, "rel_authors": [ { - "author_name": "Kamil Wnuk", - "author_inst": "ImmunityBio, Inc." + "author_name": "Li Du", + "author_inst": "Vitalant Research Institute" }, { - "author_name": "Jeremi Sudol", - "author_inst": "ImmunityBio, Inc." + "author_name": "Mohamed S. Bouzidi", + "author_inst": "Vitalant Research Institute" }, { - "author_name": "Patricia R Spilman", - "author_inst": "ImmunityBio, Inc." + "author_name": "Akshay Gala", + "author_inst": "Vitalant Research Institute" }, { - "author_name": "Patrick Soon-Shiong", - "author_inst": "ImmunityBio, Inc" + "author_name": "Fred Deiter", + "author_inst": "University of California, San Francisco" + }, + { + "author_name": "Jean-Noel Billaud", + "author_inst": "QIAGEN Digital Insights" + }, + { + "author_name": "Stephen Yeung", + "author_inst": "Weill Cornell Medicine" + }, + { + "author_name": "Prerna Dabral", + "author_inst": "Vitalant Research Institute" + }, + { + "author_name": "Jing Jin", + "author_inst": "Vitalant Research Institute" + }, + { + "author_name": "Graham Simmons", + "author_inst": "Vitalant Research Institute" + }, + { + "author_name": "Zain Dossani", + "author_inst": "Vitalant Research Institute" + }, + { + "author_name": "Toshiro Niki", + "author_inst": "Kagawa University" + }, + { + "author_name": "Lishomwa Ndhlovu", + "author_inst": "Weill Cornell Medicine" + }, + { + "author_name": "John Greenland", + "author_inst": "University of California, San Francisco" + }, + { + "author_name": "Satish K Pillai", + "author_inst": "Vitalant Research Institute" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "new results", - "category": "immunology" + "category": "microbiology" }, { "rel_doi": "10.1101/2022.03.18.484178", @@ -346371,41 +345854,45 @@ "category": "allergy and immunology" }, { - "rel_doi": "10.1101/2022.03.16.22272521", - "rel_title": "The decay of coronavirus in sewage pipes and the development of a predictive model for the estimation of SARS-CoV-2 infection cases based on wastewater surveillance", + "rel_doi": "10.1101/2022.03.16.22272497", + "rel_title": "Variant-specific burden of SARS-CoV-2 in Michigan: March 2020 through November 2021", "rel_date": "2022-03-18", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.03.16.22272521", - "rel_abs": "Wastewater surveillance serves as a promising approach to elucidate the silent transmission of SARS-CoV-2 in a given community by detecting the virus in wastewater treatment facilities. This study monitored the viral RNA abundance at one WWTP and three communities during the COVID-19 outbreak in the Yanta district of Xian city from December 2021 to January 2022. To further understand the decay of the coronavirus in sewage pipes, avian infectious bronchitis virus (IBV) was seeded in two recirculating water systems and operated for 90 days. Based on the viral abundance in the wastewater of Xian and the above data regarding the decay of coronavirus in sewage pipes, Monte Carol simulations were performed to estimate the infectious cases in Xian. The results suggested that the delta variant was first detected on Dec-10, five days earlier than the reported date of clinical samples. SARS-CoV-2 was detected on December 18 in the monitored community two days earlier than the first case and was consecutively detected in the following two sampling times. In pipelines without biofilms, the results showed that high temperature significantly reduced the viral RNA abundance by 2.18 log10 GC/L after experiencing 20 km travel distance, while only a 1.68 log10 GC/L reduction was observed in the pipeline with a low water temperature. After 90 days of operation, the biofilm matured in the pipeline in both systems. Reductions of viral RNA abundance of 2.14 and 4.79 log10 GC/L were observed in low- and high-temperature systems with mature biofilms, respectively. Based on the above results, we adjusted the input parameters for Monte Carol simulation and estimated 23.3, 50.1, 127.3 and 524.2 infected persons in December 14, 18, 22 and 26, respectively, which is largely consistent with the clinical reports. This work highlights the viability of wastewater surveillance for the early warning of COVID-19 at both the community and city levels, which represents a valuable complement to clinical approaches.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.03.16.22272497", + "rel_abs": "Accurate estimates of total burden of SARS-CoV-2 are needed to inform policy, planning and response. We sought to quantify SARS-CoV-2 cases, hospitalizations, and deaths by age in Michigan. COVID-19 cases reported to the Michigan Disease Surveillance System were multiplied by age and time-specific adjustment factors to correct for under-detection. Adjustment factors were estimated in a model fit to incidence data and seroprevalence estimates. Age-specific incidence of SARS-CoV-2 hospitalization, death, and vaccination, and variant proportions were estimated from publicly available data. We estimated substantial under-detection of infection that varied by age and time. Accounting for under-detection, we estimate cumulative incidence of infection in Michigan reached 75% by mid-November 2021, and over 87% of Michigan residents were estimated to have had [≥]1 vaccination dose and/or previous infection. Comparing pandemic waves, the relative burden among children increased over time. Adults [≥]80 years were more likely to be hospitalized or die if infected in fall 2020 than if infected during later waves. Our results highlight the ongoing risk of periods of high SARS-CoV-2 incidence despite widespread prior infection and vaccination. This underscores the need for long-term planning for surveillance, vaccination, and other mitigation measures amidst continued response to the acute pandemic.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Songzhe Fu", - "author_inst": "Dalian Ocean University" + "author_name": "Joshua G Petrie", + "author_inst": "Marshfield Clinic Research Institute" }, { - "author_name": "Qingyao Wang", - "author_inst": "Dalian Ocean University" + "author_name": "Marisa C Eisenberg", + "author_inst": "University of Michigan School of Public Health" }, { - "author_name": "Fenglan He", - "author_inst": "Nanchang Center for Disease Control and Prevention" + "author_name": "Adam S. Lauring", + "author_inst": "University of Michigan" }, { - "author_name": "Can Zhou", - "author_inst": "Dalian Ocean University" + "author_name": "Julie Gilbert", + "author_inst": "University of Michigan School of Public Health" }, { - "author_name": "Jin Zhang", - "author_inst": "Dalian Ocean University" + "author_name": "Samantha M Harrison", + "author_inst": "University of Michigan School of Public Health" }, { - "author_name": "Wen Xia", - "author_inst": "Nanchang Center for Disease Control and Prevention" + "author_name": "Peter M DeJonge", + "author_inst": "Wisconsin Department of Health Services" + }, + { + "author_name": "Emily Toth Martin", + "author_inst": "University of Michigan School of Public Health" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -348137,91 +347624,23 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2022.03.15.484379", - "rel_title": "Hypoxia inducible factors regulate infectious SARS-CoV-2, epithelial damage and respiratory symptoms in a hamster COVID-19 model.", + "rel_doi": "10.1101/2022.03.15.484404", + "rel_title": "Omicron variant of SARS-COV-2 gains new mutations in New Zealand and Hong Kong", "rel_date": "2022-03-15", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.03.15.484379", - "rel_abs": "Understanding the host pathways that define susceptibility to SARS-CoV-2 infection and disease are essential for the design of new therapies. Oxygen levels in the microenvironment define the transcriptional landscape, however the influence of hypoxia on virus replication and disease in animal models is not well understood. In this study, we identify a role for the hypoxic inducible factor (HIF) signalling axis to inhibit SARS-CoV-2 infection, epithelial damage and respiratory symptoms in Syrian hamsters. Pharmacological activation of HIF with the prolyl-hydroxylase inhibitor FG-4592 significantly reduced the levels of infectious virus in the upper and lower respiratory tract. Nasal and lung epithelia showed a reduction in SARS-CoV-2 RNA and nucleocapsid expression in treated animals. Transcriptomic and pathological analysis showed reduced epithelial damage and increased expression of ciliated cells. Our study provides new insights on the intrinsic antiviral properties of the HIF signalling pathway in SARS-CoV-2 replication that may be applicable to other respiratory pathogens and identifies new therapeutic opportunities.", - "rel_num_authors": 18, + "rel_link": "https://biorxiv.org/cgi/content/short/2022.03.15.484404", + "rel_abs": "Disclaimer statementThe authors have withdrawn this manuscript because an issue was raised about the SARS- COV-2 genome sequence data used in the study. Therefore, the authors do not wish this work to be cited as reference for the project. If you have any questions, please contact the corresponding author.", + "rel_num_authors": 1, "rel_authors": [ { - "author_name": "Peter AC Wing", - "author_inst": "University of Oxford" - }, - { - "author_name": "Maria Prange-Barczynska", - "author_inst": "University of Oxford" - }, - { - "author_name": "Amy Cross", - "author_inst": "University of Oxford" - }, - { - "author_name": "Stefania Crotta", - "author_inst": "Francis Crick Institute" - }, - { - "author_name": "Claudia Orbegozo Rubio", - "author_inst": "University of Oxford" - }, - { - "author_name": "Xiaotong Cheng", - "author_inst": "University of Oxford" - }, - { - "author_name": "James M Harris", - "author_inst": "University of Oxford" - }, - { - "author_name": "Xiaodong Zhuang", - "author_inst": "University of Oxford" - }, - { - "author_name": "Rachel L Johnson", - "author_inst": "United Kingdom Health Security Agency" - }, - { - "author_name": "Kathryn A Ryan", - "author_inst": "United Kingdom Health Security Agency" - }, - { - "author_name": "Yper Hall", - "author_inst": "United Kingdom Health Security Agency" - }, - { - "author_name": "Miles W Carroll", - "author_inst": "University of Oxford" - }, - { - "author_name": "Fadi Issa", - "author_inst": "University of Oxford" - }, - { - "author_name": "Peter Balfe", - "author_inst": "University of Oxford" - }, - { - "author_name": "Andreas Wack", - "author_inst": "Francis Crick Institute" - }, - { - "author_name": "Tammie Bishop", - "author_inst": "University of Oxford" - }, - { - "author_name": "Francisco J Salguero", - "author_inst": "United Kingdom Health Security Agency" - }, - { - "author_name": "Jane A. McKeating", - "author_inst": "University of Oxford" + "author_name": "Xiang-Jiao Yang", + "author_inst": "McGill University" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "new results", - "category": "microbiology" + "category": "genomics" }, { "rel_doi": "10.1101/2022.03.15.484421", @@ -350003,75 +349422,59 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.03.14.22272283", - "rel_title": "Migrants' primary care utilisation before and during the COVID-19 pandemic in England: An interrupted time series", + "rel_doi": "10.1101/2022.03.11.484006", + "rel_title": "Dual inhibition of vacuolar ATPase and TMPRSS2 is required for complete blockade of SARS-CoV-2 entry into cells", "rel_date": "2022-03-14", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.03.14.22272283", - "rel_abs": "BackgroundHow international migrants access and use primary care in England is poorly understood. We aimed to compare primary care consultation rates between international migrants and non-migrants in England before and during the COVID-19 pandemic (2015- 2020).\n\nMethodsUsing linked data from the Clinical Practice Research Datalink (CPRD) GOLD and the Office for National Statistics, we identified migrants using country-of-birth, visa-status or other codes indicating international migration. We ran a controlled interrupted time series (ITS) using negative binomial regression to compare rates before and during the pandemic.\n\nFindingsIn 262,644 individuals, pre-pandemic consultation rates per person-year were 4.35 (4.34-4.36) for migrants and 4.6 (4.59-4.6) for non-migrants (RR:0.94 [0.92-0.96]). Between 29 March and 26 December 2020, rates reduced to 3.54 (3.52-3.57) for migrants and 4.2 (4.17-4.23) for non-migrants (RR:0.84 [0.8-0.88]). Overall, this represents an 11% widening of the pre-pandemic difference in consultation rates between migrants and non-migrants during the first year of the pandemic (RR:0.89, 95%CI:0.84-0.94). This widening was greater for children, individuals whose first language was not English, and individuals of White British, White non-British and Black/African/Caribbean/Black British ethnicities.\n\nInterpretationMigrants were less likely to use primary care before the pandemic and the first year of the pandemic exacerbated this difference. As GP practices retain remote and hybrid models of service delivery, they must improve services and ensure they are accessible and responsive to migrants healthcare needs.\n\nFundingThis study was funded by the Medical Research Council (MR/V028375/1) and Wellcome Clinical Research Career Development Fellowship (206602).", - "rel_num_authors": 14, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2022.03.11.484006", + "rel_abs": "An essential step in the infection life cycle of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the proteolytic activation of the viral spike (S) protein, which enables membrane fusion and entry into the host cell. Two distinct classes of host proteases have been implicated in the S protein activation step: cell-surface serine proteases, such as the cell-surface transmembrane protease, serine 2 (TMPRSS2), and endosomal cathepsins, leading to entry through either the cell-surface route or the endosomal route, respectively. In cells expressing TMPRSS2, inhibiting endosomal proteases using non-specific cathepsin inhibitors such as E64d or lysosomotropic compounds such as hydroxychloroquine fails to prevent viral entry, suggesting that the endosomal route of entry is unimportant; however, mechanism-based toxicities and poor efficacy of these compounds confound our understanding of the importance of the endosomal route of entry. Here, to identify better pharmacological agents to elucidate the role of the endosomal route of entry, we profiled a panel of molecules identified through a high throughput screen that inhibit endosomal pH and/or maturation through different mechanisms. Among the three distinct classes of inhibitors, we found that inhibiting vacuolar-ATPase using the macrolide bafilomycin A1 was the only agent able to potently block viral entry without associated cellular toxicity. Using both pseudotyped and authentic virus, we showed that bafilomycin A1 inhibits SARS-CoV-2 infection both in the absence and presence of TMPRSS2. Moreover, synergy was observed upon combining bafilomycin A1 with Camostat, a TMPRSS2 inhibitor, in neutralizing SARS-CoV-2 entry into TMPRSS2-expressing cells. Overall, this study highlights the importance of the endosomal route of entry for SARS-CoV-2 and provides a rationale for the generation of successful intervention strategies against this virus that combine inhibitors of both entry pathways.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Claire X Zhang", - "author_inst": "UCL" - }, - { - "author_name": "Yamina Boukari", - "author_inst": "University College London" - }, - { - "author_name": "Neha Pathak", - "author_inst": "University College London" - }, - { - "author_name": "Rohini Mathur", - "author_inst": "London School of Hygiene and Tropical Medicine" - }, - { - "author_name": "Srinivasa Vittal Katikireddi", - "author_inst": "University of Glasgow" + "author_name": "Simoun Icho", + "author_inst": "The Hospital for Sick Children and University of Toronto" }, { - "author_name": "Parth Patel", - "author_inst": "University College London" + "author_name": "Edurne Rujas", + "author_inst": "The Hospital for Sick Children and University of Toronto" }, { - "author_name": "In\u00eas Campos-Matos", - "author_inst": "Department of Health and Social Care" + "author_name": "Krithika Muthuraman", + "author_inst": "The Hospital for Sick Children and University of Toronto" }, { - "author_name": "Dan Lewer", - "author_inst": "University College London" + "author_name": "John Tam", + "author_inst": "The Hospital for Sick Children and University of Toronto" }, { - "author_name": "Vincent Nguyen", - "author_inst": "University College London" + "author_name": "Huazhu Liang", + "author_inst": "The Hospital for Sick Children and University of Toronto" }, { - "author_name": "Greg Hugenholtz", - "author_inst": "University College London" + "author_name": "Shelby Harms", + "author_inst": "Vaccine and Infectious Disease Organization" }, { - "author_name": "Rachel Burns", - "author_inst": "University College London" + "author_name": "Minming Liao", + "author_inst": "Vaccine and Infectious Disease Organization" }, { - "author_name": "Amy R Mulick", - "author_inst": "London School of Hygiene and Tropical Medicine" + "author_name": "Darryl Falzarano", + "author_inst": "Vaccine and Infectious Disease Organization" }, { - "author_name": "Alasdair Henderson", - "author_inst": "London School of Hygiene and Tropical Medicine" + "author_name": "Jean-Philippe Julien", + "author_inst": "The Hospital for Sick Children and University of Toronto" }, { - "author_name": "Robert W Aldridge", - "author_inst": "UCL" + "author_name": "Roman Melnyk", + "author_inst": "The Hospital for Sick Children and University of Toronto" } ], "version": "1", - "license": "cc_by_nc_nd", - "type": "PUBLISHAHEADOFPRINT", - "category": "primary care research" + "license": "cc_by_nd", + "type": "new results", + "category": "cell biology" }, { "rel_doi": "10.1101/2022.03.12.484092", @@ -351789,107 +351192,31 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2022.03.13.22272176", - "rel_title": "Vaccination against SARS-CoV-2 in UK school-aged children and young people decreases infection rates and reduces COVID-19 symptoms", + "rel_doi": "10.1101/2022.03.12.22272300", + "rel_title": "Did COVID-19 Vaccines Go to the Whitest Neighborhoods First? Racial Inequities in Six Million Phase 1 Doses Shipped to Pennsylvania", "rel_date": "2022-03-13", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.03.13.22272176", - "rel_abs": "BackgroundWe aimed to explore the effectiveness of one-dose BNT162b2 vaccination upon SARS-CoV-2 infection, its effect on COVID-19 presentation, and post-vaccination symptoms in children and young people (CYP) in the UK during periods of Delta and Omicron variant predominance.\n\nMethodsIn this prospective longitudinal cohort study, we analysed data from 115,775 CYP aged 12-17 years, proxy-reported through the Covid Symptom Study (CSS) smartphone application. We calculated post-vaccination infection risk after one dose of BNT162b2, and described the illness profile of CYP with post-vaccination SARS- CoV-2 infection, compared to unvaccinated CYP, and post-vaccination side-effects.\n\nFindingsBetween August 5, 2021 and February 14, 2022, 25,971 UK CYP aged 12-17 years received one dose of BNT162b2 vaccine. Vaccination reduced (proxy-reported) infection risk (-80{middle dot}4% and -53{middle dot}7% at 14-30 days with Delta and Omicron variants respectively, and -61{middle dot}5% and -63{middle dot}7% after 61-90 days). The probability of remaining infection-free diverged soon after vaccination, and was greater in CYP with prior SARS-CoV-2 infection. Vaccinated CYP who contracted SARS-CoV-2 during the Delta period had milder disease than unvaccinated CYP; during the Omicron period this was only evident in children aged 12-15 years. Overall disease profile was similar in both vaccinated and unvaccinated CYP. Post-vaccination local side-effects were common, systemic side-effects were uncommon, and both resolved quickly.\n\nInterpretationOne dose of BNT162b2 vaccine reduced risk of SARS-CoV-2 infection for at least 90 days in CYP aged 12-17 years. Vaccine protection varied for SARS-CoV-2 variant type (lower for Omicron than Delta variant), and was enhanced by pre-vaccination SARS-CoV-2 infection. Severity of COVID-19 presentation after vaccination was generally milder, although unvaccinated CYP also had generally mild disease. Overall, vaccination was well-tolerated.\n\nFundingUK Government Department of Health and Social Care, Chronic Disease Research Foundation, The Wellcome Trust, UK Engineering and Physical Sciences Research Council, UK Research and Innovation London Medical Imaging & Artificial Intelligence Centre for Value Based Healthcare, UK National Institute for Health Research, UK Medical Research Council, British Heart Foundation and Alzheimers Society, and ZOE Limited.\n\nResearch in context\n\nEvidence before this studyWe searched PubMed database for peer-reviewed articles and medRxiv for preprint papers, published between January 1, 2021 and February 15, 2022 using keywords (\"SARS-CoV-2\" OR \"COVID-19\") AND (child* OR p?ediatric* OR teenager*) AND (\"vaccin*\" OR \"immunization campaign\") AND (\"efficacy\" OR \"effectiveness\" OR \"symptoms\") AND (\"delta\" or \"omicron\" OR \"B.1.617.2\" OR \"B.1.1.529\"). The PubMed search retrieved 36 studies, of which fewer than 30% specifically investigated individuals <18 years.\n\nEleven studies explored SARS-CoV-2 viral transmission: seroprevalence in children (n=4), including age-dependency of susceptibility to SARS-CoV-2 infection (n=1), SARS-CoV-2 transmission in schools (n=5), and the effect of school closure on viral transmission (n=1).\n\nEighteen documents reported clinical aspects, including manifestation of infection (n=13), symptomatology, disease duration, and severity in children. Other studies estimated emergency department visits, hospitalization, need for intensive care, and/or deaths in children (n=4), and explored prognostic factors (n=1).\n\nThirteen studies explored vaccination-related aspects, including vaccination of children within specific paediatric co-morbidity groups (e.g., children with Down syndrome, inflammatory bowel disease, and cancer survivors, n=4), mRNA vaccine efficacy in children and adolescents from the general population (n=7), and the relation between vaccination and severity of disease and hospitalization cases (n=2). Four clinical trials were conducted using mRNA vaccines in minors, also exploring side effects. Sixty percent of children were found to have side effects after BNT162b2 vaccination, and especially after the second dose; however, most symptoms were mild and transient apart from rare uncomplicated skin ulcers. Two studies focused on severe adverse effects and safety of SARS-CoV-2 vaccines in children, reporting on myocarditis episodes and two cases of Guillain-Barre syndrome. All other studies were beyond the scope of our research.\n\nAdded value of this studyWe assessed multiple components of the UK vaccination campaign in a cohort of children and young people (CYP) aged 12-17 years drawn from a large UK community-based citizen-science study, who received a first dose of BNT162b2 vaccine. We describe a variant-dependent protective effect of the first dose against both Delta and Omicron, with additional protective effect of pre-vaccination SARS- CoV-2 infection on post-vaccination re-infection. We compare the illness profile in CYP infected post-vaccination with that of unvaccinated CYP, demonstrating overall milder disease with fewer symptoms for vaccinated CYP. We describe local and systemic side-effects during the first week following first-dose vaccination, confirming that local symptoms are common, systemic symptoms uncommon, and both usually transient.\n\nImplications of all the available evidenceOur data confirm that first dose BNT162b2 vaccination in CYP reduces risk of infection by SARS-CoV-2 variants, with generally local and brief side-effects. If infected after vaccination, COVID-19 is milder, if manifest at all. The study aims to contribute quantitative evidence to the risk-benefit evaluation of vaccination in CYP to inform discussion regarding rationale for their vaccination and the designing of national immunisation campaigns for this age group; and applies citizen-science approaches in the conduct of epidemiological surveillance and data collection in the UK community.\n\nImportantly, this study was conducted during Delta and Omicron predominance in UK; specificity of vaccine efficacy to variants is also illustrated; and results may not be generalizable to future SARS-CoV-2 strains.", - "rel_num_authors": 22, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.03.12.22272300", + "rel_abs": "Research on racial disparities in COVID-19 vaccination rates has focused primarily on vaccine hesitancy. However, vaccine hesitancy research is increasingly unable to account for racial disparities in vaccination rates in the U.S., which have shrunk rapidly over the past year. This and other evidence suggests that inequities in vaccine allocation and access may have contributed to vaccination rate disparities in the U.S. But to our knowledge, no previously published research has examined whether the geographic distribution of COVID-19 vaccines has led to greater access for White Americans than for Black Americans.\n\nHere, we link neighborhood-level data on vaccine allocation to data on racial demographics to show that in the first 17 weeks of Pennsylvanias COVID-19 vaccine rollout (Phase 1), White people were 25% more likely than Black people to live in neighborhoods (census tracts) that received vaccine shipments. In the 17 weeks of Pennsylvanias de jure restrictions on vaccine eligibility, de facto geographic restrictions on vaccine access disproportionately disadvantaged Black people and favored White people. In revealing these vaccine inequities, our work builds on prior work to develop a theory-driven, evidence-based, reproducible framework for studying racial inequities in the distribution of COVID-19 vaccines.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Erika Molteni", - "author_inst": "King's College London" - }, - { - "author_name": "Liane S Canas", - "author_inst": "King's College London" - }, - { - "author_name": "Kerstin Klaser", - "author_inst": "King's College London" - }, - { - "author_name": "Jie Deng", - "author_inst": "King's College London" - }, - { - "author_name": "Sunil S Bhopal", - "author_inst": "Newcastle University" - }, - { - "author_name": "Robert C Hughes", - "author_inst": "London School of Hygiene & Tropical Medicine, London" - }, - { - "author_name": "Liyuan Chen", - "author_inst": "King's College London" - }, - { - "author_name": "Benjamin Murray", - "author_inst": "King's College London" - }, - { - "author_name": "Eric Kerfoot", - "author_inst": "King's College London" - }, - { - "author_name": "Michela Antonelli", - "author_inst": "King's College London" - }, - { - "author_name": "Carole Helene Sudre", - "author_inst": "King's College London" - }, - { - "author_name": "Joan Capdevila Pujol", - "author_inst": "Zoe Limited, London, UK" - }, - { - "author_name": "Lorenzo Polidori", - "author_inst": "Zoe Limited, London, UK" - }, - { - "author_name": "Anna May", - "author_inst": "Zoe Limited, London, UK" - }, - { - "author_name": "Alexander Hammers", - "author_inst": "King's College London" - }, - { - "author_name": "Jonathan Wolf", - "author_inst": "Zoe Limited, London, UK" - }, - { - "author_name": "Timothy Spector", - "author_inst": "King's College London" - }, - { - "author_name": "Claire J Steves", - "author_inst": "King's College London" - }, - { - "author_name": "Sebastien Ourselin", - "author_inst": "King's College London" - }, - { - "author_name": "Michael Absoud", - "author_inst": "King's College London" + "author_name": "Geoffrey S Holtzman", + "author_inst": "Boston University" }, { - "author_name": "Marc Modat", - "author_inst": "King's College London" + "author_name": "Yukun Yang", + "author_inst": "Boston University" }, { - "author_name": "Emma L Duncan", - "author_inst": "King's College London" + "author_name": "Pierce Louis", + "author_inst": "Boston University" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "public and global health" }, { "rel_doi": "10.1101/2022.03.11.483930", @@ -354039,171 +353366,47 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2022.03.07.22272026", - "rel_title": "Trends, regional variation and clinical characteristics of recipients of antivirals and neutralising monoclonal antibodies for non-hospitalised COVID-19: a descriptive cohort study of 23.4 million people in OpenSAFELY", + "rel_doi": "10.1101/2022.03.07.22272028", + "rel_title": "Short-term drop in antibody titer after the third dose of SARS-CoV-2 BNT162b2 vaccine in adults", "rel_date": "2022-03-10", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.03.07.22272026", - "rel_abs": "ObjectivesAscertain patient eligibility status and describe coverage of antivirals and neutralising monoclonal antibodies (nMAB) as treatment for COVID-19 in community settings in England.\n\nDesignCohort study, approved by NHS England.\n\nSettingRoutine clinical data from 23.4m people linked to data on COVID-19 infection and treatment, within the OpenSAFELY-TPP database.\n\nParticipantsNon-hospitalised COVID-19 patients at high-risk of severe outcomes.\n\nInterventionsNirmatrelvir/ritonavir (Paxlovid), sotrovimab, molnupiravir, casirivimab or remdesivir, administered in the community by COVID-19 Medicine Delivery Units.\n\nResultsWe identified 102,170 non-hospitalised patients with COVID-19 between 11th December 2021 and 28th April 2022 at high-risk of severe outcomes and therefore potentially eligible for antiviral and/or nMAB treatment. Of these patients, 18,210 (18%) received treatment; sotrovimab, 9,340 (51%); molnupiravir, 4,500 (25%); Paxlovid, 4,290 (24%); casirivimab, 50 (<1%); and remdesivir, 20 (<1%). The proportion of patients treated increased from 8% (180/2,380) in the first week of treatment availability to 22% (420/1870) in the latest week. The proportion treated varied by high risk group, lowest in those with Liver disease (12%; 95% CI 11 to 13); by treatment type, with sotrovimab favoured over molnupiravir/Paxlovid in all but three high risk groups: Down syndrome (36%; 95% CI 31 to 40), Rare neurological conditions (46%; 95% CI 44 to 48), and Primary immune deficiencies (49%; 95% CI 48 to 51); by ethnicity, from Black (10%; 95% CI 9 to 11) to White (18%; 95% CI 18 to 19); by NHS Region, from 11% (95% CI 10 to 12) in Yorkshire and the Humber to 23% (95% CI 22 to 24) in the East of England); and by deprivation level, from 12% (95% CI 12 to 13) in the most deprived areas to 21% (95% CI 21 to 22) in the least deprived areas. There was also lower coverage among unvaccinated patients (5%; 95% CI 4 to 7), those with dementia (5%; 95% CI 4 to 6) and care home residents (6%; 95% CI 5 to 6).\n\nConclusionsUsing the OpenSAFELY platform we were able to identify patients who were potentially eligible to receive treatment and assess the coverage of these new treatments amongst these patients. Targeted activity may be needed to address apparent lower treatment coverage observed among certain groups, in particular (at present): different NHS regions, socioeconomically deprived areas, and care homes.\n\nWhat is already known about this topicSince the emergence of COVID-19, a number of approaches to treatment have been tried and evaluated. These have mainly consisted of treatments such as dexamethasone, which were used in UK hospitals,from early on in the pandemic to prevent progression to severe disease. Until recently (December 2021), no treatments have been widely used in community settings across England.\n\nWhat this study addsFollowing the rollout of antiviral medicines and neutralising monoclonal antibodies (nMABs) as treatment for patients with COVID-19, we were able to identify patients who were potentially eligible to receive antivirals or nMABs and assess the coverage of these new treatments amongst these patients, in as close to real-time as the available data flows would support. While the proportion of the potentially eligible patients receiving treatment increased over time, rising from 8% (180/2,380) in the first week of the roll out to 22% (420/1870) in the last week of April 2022, there were variations in coverage between key clinical, geographic, and demographic subgroup.\n\nHow this study might affect research, practice, or policyTargeted activity may therefore be needed to address lower treatment rates observed among certain geographic areas and key groups including ethnic minorities, people living in areas of higher deprivation, and in care homes.", - "rel_num_authors": 38, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.03.07.22272028", + "rel_abs": "Little is known about the longevity of antibodies after a third dose of BNT162b2 (BioNTech/Pfizer). Therefore, the serum antibody levels were evaluated after the third dose of BNT162b2 which dropped significantly within 11 weeks from 4155.59 {+/-} 2373.65 BAU/ml to 2389.10 {+/-} 1433.90 BAU/ml, p-value <0.001 but remained higher than after the second dose.\n\nThese data underline the positive effect of third dose of BNT162b2 but shows a rapid and significant drop of antibodies within a short span of time.\n\nTrial RegistrationThis trial was prospectively registered in the German Clinical Trial Register (DRKS00021270).", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Amelia CA Green", - "author_inst": "University of Oxford" - }, - { - "author_name": "Helen J Curtis", - "author_inst": "University of Oxford" - }, - { - "author_name": "Rose Higgins", - "author_inst": "University of Oxford" - }, - { - "author_name": "Rebecca Smith", - "author_inst": "University of Oxford" - }, - { - "author_name": "Amir Mehrkar", - "author_inst": "University of Oxford" - }, - { - "author_name": "Peter Inglesby", - "author_inst": "University of Oxford" - }, - { - "author_name": "Viyaasan Mahalingasivam", - "author_inst": "London School of Hygiene and Tropical Medicine" - }, - { - "author_name": "Henry Drysdale", - "author_inst": "University of Oxford" - }, - { - "author_name": "Nicholas DeVito", - "author_inst": "University of Oxford" - }, - { - "author_name": "Richard Croker", - "author_inst": "University of Oxford" - }, - { - "author_name": "Christopher T Rentsch", - "author_inst": "London School of Hygiene and Tropical Medicine" - }, - { - "author_name": "Krishnan Bhaskaran", - "author_inst": "London School of Hygiene and Tropical Medicine" - }, - { - "author_name": "Colm D Andrews", - "author_inst": "University of Oxford" - }, - { - "author_name": "Sebastian CJ Bacon", - "author_inst": "University of Oxford" - }, - { - "author_name": "Simon Davy", - "author_inst": "University of Oxford" - }, - { - "author_name": "Iain Dillingham", - "author_inst": "University of Oxford" - }, - { - "author_name": "David Evans", - "author_inst": "University of Oxford" - }, - { - "author_name": "Louis Fisher", - "author_inst": "University of Oxford" - }, - { - "author_name": "George Hickman", - "author_inst": "University of Oxford" - }, - { - "author_name": "Lisa E M Hopcroft", - "author_inst": "University of Oxford" - }, - { - "author_name": "William J Hulme", - "author_inst": "University of Oxford" - }, - { - "author_name": "Jon Massey", - "author_inst": "University of Oxford" - }, - { - "author_name": "Jessica Morley", - "author_inst": "University of Oxford" - }, - { - "author_name": "Caroline E Morton", - "author_inst": "University of Oxford" - }, - { - "author_name": "Robin Y Park", - "author_inst": "University of Oxford" - }, - { - "author_name": "Alex J Walker", - "author_inst": "University of Oxford" - }, - { - "author_name": "Tom Ward", - "author_inst": "University of Oxford" - }, - { - "author_name": "Milan Wiedemann", - "author_inst": "University of Oxford" - }, - { - "author_name": "Christopher Bates", - "author_inst": "TPP" - }, - { - "author_name": "Jonathan Cockburn", - "author_inst": "TPP" - }, - { - "author_name": "John Parry", - "author_inst": "TPP" - }, - { - "author_name": "Frank Hester", - "author_inst": "TPP" + "author_name": "Jonas Herzberg", + "author_inst": "Krankenhaus Reinbek St. Adolf-Stift" }, { - "author_name": "Sam Harper", - "author_inst": "TPP" + "author_name": "Bastian Fischer", + "author_inst": "Herz- und Diabeteszentrum NRW" }, { - "author_name": "Ian J Douglas", - "author_inst": "London School of Hygiene and Tropical Medicine" + "author_name": "Heiko Becher", + "author_inst": "University Medical Center Hamburg-Eppendorf" }, { - "author_name": "Stephen JW Evans", - "author_inst": "London School of Hygiene and Tropical Medicine" + "author_name": "Ann-Kristin Becker", + "author_inst": "Asklepios Klinik Harburg" }, { - "author_name": "Laurie Tomlinson", - "author_inst": "London School of Hygiene and Tropical Medicine" + "author_name": "Human Honarpisheh", + "author_inst": "Krankenhaus Reinbek St. Adolf-Stift" }, { - "author_name": "Brian MacKenna", - "author_inst": "University of Oxford" + "author_name": "Tim Strate", + "author_inst": "Krankenhaus Reinbek St. Adolf-Stift" }, { - "author_name": "Ben Goldacre", - "author_inst": "University of Oxford" + "author_name": "Cornelius Knabbe", + "author_inst": "Herz- und Diabeteszentrum NRW" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "primary care research" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2022.03.08.22270920", @@ -356205,67 +355408,35 @@ "category": "emergency medicine" }, { - "rel_doi": "10.1101/2022.03.07.22271699", - "rel_title": "Severity of maternal SARS-CoV-2 infection and perinatal outcomes during the Omicron variant dominant period: UK Obstetric Surveillance System national cohort study.", + "rel_doi": "10.1101/2022.03.07.22272051", + "rel_title": "Impact of long-term COVID on workers: a systematic review protocol", "rel_date": "2022-03-09", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.03.07.22271699", - "rel_abs": "ObjectivesTo describe the severity of maternal infection when the Omicron SARS-CoV-2 variant was dominant (15/12/21-14/01/22) and compare outcomes among groups with different vaccination status.\n\nDesignProspective cohort study\n\nSettingUK consultant-led maternity units\n\nParticipantsPregnant women hospitalised with a positive SARS-CoV-2 PCR test up to 7 days prior to admission and/or during admission up to 2 days after giving birth.\n\nMain outcome measuresSymptomatic or asymptomatic infection. Vaccination status. Severity of maternal infection (moderate or severe infection according to modified WHO criteria). Mode of birth and perinatal outcomes.\n\nResultsOut of 1561 women admitted to hospital with SARS-CoV-2 infection, 449 (28.8%) were symptomatic. Among symptomatic women admitted, 86 (19.2%) had moderate to severe infection; 51 (11.4%) had pneumonia on imaging, 62 (14.3%) received respiratory support, and 19 (4.2%) were admitted to the intensive care unit (ICU). Three women died (0.7%). Vaccination status was known for 383 symptomatic women (85.3%) women; 249 (65.0%) were unvaccinated, 45 (11.7%) had received one vaccine dose, 76 (19.8%) had received two doses and 13 (3.4%) had received three doses. 59/249 (23.7%) unvaccinated women had moderate to severe infection, compared to 10/45 (22.2%) who had one dose, 9/76 (11.8%) who had two doses and 0/13 (0%) who had three doses. Among the 19 symptomatic women admitted to ICU, 14 (73.7%) were unvaccinated, 3 (15.8%) had received one dose, 1 (5.3%) had received two doses, 0 (0%) had received 3 doses and 1 (5.3%) had unknown vaccination status.\n\nConclusionThe risk of severe respiratory disease amongst unvaccinated pregnant women admitted with symptomatic SARS-CoV-2 infection during the Omicron dominance period was comparable to that observed during the period the wildtype variant was dominant. Most women with severe disease were unvaccinated. Vaccine coverage among pregnant women admitted with SARS-CoV-2 was low compared to the overall pregnancy population and very low compared to the general population. Ongoing action to prioritise and advocate for vaccine uptake in pregnancy is essential.\n\nO_TEXTBOXSUMMARY BOX\n\nWhat is already known on this topic\n\nO_LIIn non-pregnant adults, growing evidence indicates a lower risk of severe respiratory disease with the Omicron SARS-CoV-2 Variant of Concern (VOC).\nC_LIO_LIPregnant women admitted during the periods in which the Alpha and Delta VOC were dominant were at increased risk of moderate to severe SARS-CoV-2 infection compared to the period when the original wildtype infection was dominant.\nC_LIO_LIMost women admitted to hospital with symptomatic SARS-CoV-2 infection have been unvaccinated.\nC_LI\n\nWhat this study adds\n\nO_LIOne in four women who had received no vaccine or a single dose had moderate to severe infection, compared with one in eight women who had received two doses and no women who had received three doses\nC_LIO_LIThe proportional rate of moderate to severe infection in unvaccinated pregnant women during the Omicron dominance period is similar to the rate observed during the wildtype dominance period\nC_LIO_LIOne in eight symptomatic admitted pregnant women needed respiratory support during the period when Omicron was dominant\nC_LI\n\nC_TEXTBOX", - "rel_num_authors": 12, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.03.07.22272051", + "rel_abs": "IntroductionPart of the patients infected by COVID-19 have at least one lasting sequel of the disease and may be framed in the concept of long Covid. These sequelae can compromise the quality of life, increase dependence on other people for personal care, impair the performance of activities of daily living, thus compromising work activities and harming the health of the worker. This protocol aims to critically synthesize the scientific evidence on the effects of Covid-19 among workers and its impact on their health status and professional life.\n\nMethodSearches will be performed in MEDLINE via PubMed, EMBASE, Cochrane Library, Web of Science, Scopus, LILACS and Epistemonikos. Included studies will be those that report the prevalence of long-term signs and symptoms in workers and/or the impact on their health status and work performance, which may be associated with Covid-19 infection. Data extraction will be conducted by 3 reviewers independently. For data synthesis, a results report will be carried out, based on the main outcome of this study.\n\nDiscussionThis review will provide evidence to support health surveillance to help decision makers (i.e. healthcare providers, stakeholders and governments) regarding long-term Covid.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Hilde Marie Engjom", - "author_inst": "Norwegian Institute of Public Health" - }, - { - "author_name": "Rema Ramakrishnan", - "author_inst": "National Perinatal Epidemiology Unit, Nuffield Department of Population Health, University of Oxford" - }, - { - "author_name": "Nicola Vousden", - "author_inst": "National Perinatal Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, UK, OX3 7LF" - }, - { - "author_name": "Kathryn Bunch", - "author_inst": "National Perinatal Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, UK, OX3 7LF" - }, - { - "author_name": "Edvard P Morris", - "author_inst": "Royal College of Obstetricians and Gynaecologists, London, UK, SE1 1SZ" - }, - { - "author_name": "Nigel Simpson", - "author_inst": "Department of Women's and Children's Health, School of Medicine, University of Leeds, UK, LS2 9JT" - }, - { - "author_name": "Christopher Gale", - "author_inst": "Imperial College London" - }, - { - "author_name": "Pat OBrien", - "author_inst": "Institute for Womens Health, University College London, London, UK" - }, - { - "author_name": "Maria Quigley", - "author_inst": "National Perinatal Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, UK, OX3 7LF" + "author_name": "Camila Bruneli do Prado", + "author_inst": "Universidade Federal do Esp\u00edrito Santo" }, { - "author_name": "Peter Brocklehurst", - "author_inst": "Birmingham Clinical Trials Unit, Institute of Applied Health Research, University of Birmingham, UK" + "author_name": "Giselly Storch Emerick", + "author_inst": "Federal University of Espirito Santo: Universidade Federal do Espirito Santo" }, { - "author_name": "Jennifer J Kurinczuk", - "author_inst": "National Perinatal Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, UK, OX3 7LF" + "author_name": "Luciana Bicalho Cevolani Pires", + "author_inst": "Federal University of Espirito Santo: Universidade Federal do Espirito Santo" }, { - "author_name": "Marian Knight", - "author_inst": "National Perinatal Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, UK, OX3 7LF" + "author_name": "Luciane Bresciani Salaroli", + "author_inst": "Federal University of Espirito Santo: Universidade Federal do Espirito Santo" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "public and global health" }, { "rel_doi": "10.1101/2022.03.08.22272091", @@ -358383,21 +357554,17 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2022.03.07.483258", - "rel_title": "Intragenomic rearrangements of SARS-CoV-2 and other \u03b2-coronaviruses", + "rel_doi": "10.1101/2022.03.05.483145", + "rel_title": "Predicted binding interface between coronavirus nsp3 and nsp4", "rel_date": "2022-03-07", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.03.07.483258", - "rel_abs": "Variation of the betacoronavirus SARS-CoV-2 has been the bane of COVID-19 control. Documented variation includes point mutations, deletions, insertions, and recombination among closely or distantly related coronaviruses. Here, we describe yet another aspect of genome variation by beta- and alphacoronaviruses. Specifically, we report numerous genomic insertions of 5-untranslated region sequences into coding regions of SARS-CoV-2, other betacoronaviruses, and alphacoronaviruses. To our knowledge this is the first systematic description of such insertions. In many cases, these insertions change viral protein sequences and further foster genomic flexibility and viral adaptability through insertion of transcription regulatory sequences in novel positions within the genome. Among human Embecorivus betacoronaviruses, for instance, from 65% to all of the surveyed sequences in publicly available databases contain 5-UTR-derived inserted sequences. In limited instances, there is mounting evidence that these insertions alter the fundamental biological properties of mutant viruses. Intragenomic rearrangements add to our appreciation of how variants of SARS-CoV-2 and other beta- and alphacoronaviruses may arise.\n\nSignificanceUnderstanding mechanisms of variation in coronaviruses is vital to control of their associated diseases. Beyond point mutations, insertions, deletions and recombination, we here describe for the first time intragenomic rearrangements and their relevance to changes in transmissibility, immune escape and/or virulence documented during the SARS-CoV-2 pandemic.", - "rel_num_authors": 2, + "rel_link": "https://biorxiv.org/cgi/content/short/2022.03.05.483145", + "rel_abs": "Double membrane vesicles (DMVs) in coronavirus-infected cells feature pores that span both membranes. DMV pores were observed to have six-fold symmetry and include the nsp3 protein. Co-expression of SARS-CoV nsp3 and nsp4 induces DMV formation, and elements of nsp3 and nsp4 have been identified that are essential for membrane disruption. I describe a predicted luminal binding interface between nsp3 and nsp4 that is membrane-associated, conserved in SARS-CoV-2 during the COVID-19 pandemic and in diverse coronaviruses, and stable in molecular dynamics simulation. Combined with structure predictions for the full-length nsp4 monomer and cryo-EM data, this suggests a DMV pore model in which nsp4 spans both membranes with nsp3 and nsp4 inserted into the same bilayer. This approach may be able to identify additional protein-protein interactions between coronavirus proteins.", + "rel_num_authors": 1, "rel_authors": [ { - "author_name": "Roberto Patarca", - "author_inst": "ACCESS Health International" - }, - { - "author_name": "William A Haseltine", - "author_inst": "ACCES Health International" + "author_name": "Zach Hensel", + "author_inst": "ITQB NOVA" } ], "version": "1", @@ -359761,91 +358928,187 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.03.02.22271106", - "rel_title": "Proteome reveals antiviral host response and NETosis during acute COVID-19 in high-risk patients", + "rel_doi": "10.1101/2022.03.03.22271860", + "rel_title": "Sero-surveillance for IgG to SARS-CoV-2 at antenatal care clinics in three Kenyan referral hospitals: repeated cross-sectional surveys 2020-21", "rel_date": "2022-03-06", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.03.02.22271106", - "rel_abs": "SARS-CoV-2 remains an acute threat to human health, endangering hospital capacities worldwide. Many studies have aimed at informing pathophysiologic understanding and identification of disease indicators for risk assessment, monitoring, and therapeutic guidance. While findings start to emerge in the general population, observations in high-risk patients with complex pre-existing conditions are limited.\n\nTo this end, we biomedically characterized quantitative proteomics in a hospitalized cohort of COVID-19 patients with mild to severe symptoms suffering from different (co)-morbidities in comparison to both healthy individuals and patients with non-COVID related inflammation. Deep clinical phenotyping enabled the identification of individual disease trajectories in COVID-19 patients. By the use of this specific disease phase assignment, proteome analysis revealed a severity dependent general type-2 centered host response side-by-side with a disease specific antiviral immune reaction in early disease. The identification of phenomena such as neutrophil extracellular trap (NET) formation and a pro-coagulatory response together with the regulation of proteins related to SARS-CoV-2-specific symptoms by unbiased proteome screening both confirms results from targeted approaches and provides novel information for biomarker and therapy development.\n\nGraphical AbstractSars-CoV-2 remains a challenging threat to our health care system with many pathophysiological mechanisms not fully understood, especially in high-risk patients. Therefore, we characterized a cohort of hospitalized COVID-19 patients with multiple comorbidities by quantitative plasma proteomics and deep clinical phenotyping. The individual patients disease progression was determined and the subsequently assigned proteome profiles compared with a healthy and a chronically inflamed control cohort. The identified disease phase and severity specific protein profiles revealed an antiviral immune response together with coagulation activation indicating the formation of NETosis side-by-side with tissue remodeling related to the inflammatory signature.\n\n\n\nO_FIG O_LINKSMALLFIG WIDTH=197 HEIGHT=200 SRC=\"FIGDIR/small/22271106v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (50K):\norg.highwire.dtl.DTLVardef@1e791faorg.highwire.dtl.DTLVardef@20d3d6org.highwire.dtl.DTLVardef@1339e42org.highwire.dtl.DTLVardef@1db3710_HPS_FORMAT_FIGEXP M_FIG C_FIG", - "rel_num_authors": 18, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.03.03.22271860", + "rel_abs": "IntroductionThe high proportion of SARS-CoV-2 infections that have remained undetected presents a challenge to tracking the progress of the pandemic and estimating the extent of population immunity.\n\nMethodsWe used residual blood samples from women attending antenatal care services at three hospitals in Kenya between August 2020 and October 2021and a validated IgG ELISA for SARS-Cov-2 spike protein and adjusted the results for assay sensitivity and specificity. We fitted a two-component mixture model as an alternative to the threshold analysis to estimate of the proportion of individuals with past SARS-CoV-2 infection.\n\nResultsWe estimated seroprevalence in 2,981 women; 706 in Nairobi, 567 in Busia and 1,708 in Kilifi. By October 2021, 13% of participants were vaccinated (at least one dose) in Nairobi, 2% in Busia. Adjusted seroprevalence rose in all sites; from 50% (95%CI 42-58) in August 2020, to 85% (95%CI 78-92) in October 2021 in Nairobi; from 31% (95%CI 25-37) in May 2021 to 71% (95%CI 64-77) in October 2021 in Busia; and from 1% (95% CI 0-3) in September 2020 to 63% (95% CI 56-69) in October 2021 in Kilifi. Mixture modelling, suggests adjusted cross-sectional prevalence estimates are underestimates; seroprevalence in October 2021 could be 74% in Busia and 72% in Kilifi.\n\nConclusionsThere has been substantial, unobserved transmission of SARS-CoV-2 in Nairobi, Busia and Kilifi Counties. Due to the length of time since the beginning of the pandemic, repeated cross-sectional surveys are now difficult to interpret without the use of models to account for antibody waning.", + "rel_num_authors": 42, "rel_authors": [ { - "author_name": "Alina Bauer", - "author_inst": "Helmholtz Zentrum Muenchen, Computational Health Department, Member of the German Center for Lung Research (DZL), 85764 Munich, Germany" + "author_name": "R. K Lucinde", + "author_inst": "KEMRI-Wellcome Trust Research Programme: Centre for Geographic Medicine Research Coast" }, { - "author_name": "Elisabeth Pachl", - "author_inst": "Helmholtz Zentrum Muenchen, Computational Health Department, Member of the German Center for Lung Research (DZL), 85764 Munich, Germany; Fraunhofer IKS, Fraunho" + "author_name": "D. Mugo", + "author_inst": "KEMRI-Wellcome Trust Research Programme: Centre for Geographic Medicine Research Coast" }, { - "author_name": "Johannes C. Hellmuth", - "author_inst": "Department of Medicine III, University Hospital, LMU Munich, Munich, Germany" + "author_name": "C. Bottomley", + "author_inst": "London School of Hygiene & Tropical Medicine" }, { - "author_name": "Nikolaus Kneidinger", - "author_inst": "Institute of Lung Biology and Disease and Comprehensive Pneumology Center with the CPC-M bioArchive, Helmholtz Zentrum Muenchen, Member of the DZL, Munich, Germ" + "author_name": "A. Karani", + "author_inst": "KEMRI-Wellcome Trust Research Programme: Centre for Geographic Medicine Research Coast" }, { - "author_name": "Marion Frankenberger", - "author_inst": "Institute of Lung Biology and Disease and Comprehensive Pneumology Center with the CPC-M bioArchive, Helmholtz Zentrum Muenchen, Member of the German Center for" + "author_name": "E Gardiner", + "author_inst": "KEMRI-Wellcome Trust Research Programme: Centre for Geographic Medicine Research Coast" }, { - "author_name": "Hans C. Stubbe", - "author_inst": "Department of Medicine II, University Hospital, LMU Munich, Munich, Germany; Institute of Lung Biology and Disease and Comprehensive Pneumology Center with the " + "author_name": "R Aziza", + "author_inst": "University of Warwick" }, { - "author_name": "Bernhard Ryffel", - "author_inst": "Laboratory of Experimental and Molecular Immunology and Neurogenetics (INEM), UMR 7355 CNRS-University of Orleans and Artimmune, Orleans, France" + "author_name": "J. Gitonga", + "author_inst": "KEMRI-Wellcome Trust Research Programme: Centre for Geographic Medicine Research Coast" }, { - "author_name": "Agnese Petrera", - "author_inst": "Metabolomics and Proteomics Core, Helmholtz Zentrum Muenchen, Munich, Germany" + "author_name": "H. Karanja", + "author_inst": "KEMRI-Wellcome Trust Research Programme: Centre for Geographic Medicine Research Coast" }, { - "author_name": "Stefanie M. Hauck", - "author_inst": "Metabolomics and Proteomics Core, Helmholtz Zentrum Muenchen, Munich, Germany" + "author_name": "J Nyagwange", + "author_inst": "KEMRI-Wellcome Trust Research Programme: Centre for Geographic Medicine Research Coast" }, { - "author_name": "J\u00fcrgen Behr", - "author_inst": "Institute of Lung Biology and Disease and Comprehensive Pneumology Center with the CPC-M bioArchive, Helmholtz Zentrum Muenchen, Germany" + "author_name": "J. Tuju", + "author_inst": "KEMRI-Wellcome Trust Research Programme: Centre for Geographic Medicine Research Coast" }, { - "author_name": "Rainer Kaiser", - "author_inst": "Medizinische Klinik und Poliklinik I, University Hospital, LMU Munich, Munich, Germany, DZHK (German Center for Cardiovascular Research), Partner Site Munich He" + "author_name": "P. Wanjiku", + "author_inst": "KEMRI-Wellcome Trust Research Programme: Centre for Geographic Medicine Research Coast" }, { - "author_name": "Clemens Scherer", - "author_inst": "Medizinische Klinik und Poliklinik I, University Hospital, LMU Munich, Munich, Germany, DZHK (German Center for Cardiovascular Research), Partner Site Munich He" + "author_name": "E. Nzomo", + "author_inst": "Kilifi County Hospital" }, { - "author_name": "Li Deng", - "author_inst": "Helmholtz Zentrum Muenchen, Computational Health Department, Member of the German Center for Lung Research (DZL), 85764 Munich, Germany; Institute of Virology, " + "author_name": "E. Kamuri", + "author_inst": "Kenyatta National Hospital" }, { - "author_name": "Daniel Teupser", - "author_inst": "Institute of Laboratory Medicine, University Hospital, LMU Munich, Munich, Germany" + "author_name": "K. Thuranira", + "author_inst": "Kenyatta National Hospital" }, { - "author_name": "Narges Ahmidi", - "author_inst": "Fraunhofer IKS, Fraunhofer Institute for Cognitive Systems IKS, 80686 Munich, Germany" + "author_name": "S. Agunda", + "author_inst": "Kenyatta National Hospital" }, { - "author_name": "Maximilian Muenchhoff", - "author_inst": "Max von Pettenkofer Institute and Gene Center, Virology, National Reference Center for Retroviruses, LMU Muenchen, Munich, Germany; German Center for Infection " + "author_name": "G. Nyutu", + "author_inst": "KEMRI-Wellcome Trust Research Programme: Centre for Geographic Medicine Research Coast" }, { - "author_name": "Benjamin Schubert", - "author_inst": "Helmholtz Zentrum Muenchen, Computational Health Department, Member of the German Center for Lung Research (DZL), 85764 Munich, Germany; Department of Mathemati" + "author_name": "A. Etyang", + "author_inst": "KEMRI-Wellcome Trust Research Programme: Centre for Geographic Medicine Research Coast" }, { - "author_name": "Anne Hilgendorff", - "author_inst": "Institute of Lung Biology and Disease and Comprehensive Pneumology Center with the CPC-M bioArchive, Helmholtz Ze; Center for Comprehensive Developmental Care (" + "author_name": "I. M. O. Adetifa", + "author_inst": "KEMRI-Wellcome Trust Research Programme: Centre for Geographic Medicine Research Coast" + }, + { + "author_name": "E. Kagucia", + "author_inst": "KEMRI-Wellcome Trust Research Programme: Centre for Geographic Medicine Research Coast" + }, + { + "author_name": "S. Uyoga", + "author_inst": "KEMRI-Wellcome Trust Research Programme: Centre for Geographic Medicine Research Coast" + }, + { + "author_name": "M. Otiende", + "author_inst": "KEMRI-Wellcome Trust Research Programme: Centre for Geographic Medicine Research Coast" + }, + { + "author_name": "E. Otieno", + "author_inst": "KEMRI-Wellcome Trust Research Programme: Centre for Geographic Medicine Research Coast" + }, + { + "author_name": "L. Ndwiga", + "author_inst": "KEMRI-Wellcome Trust Research Programme: Centre for Geographic Medicine Research Coast" + }, + { + "author_name": "C. N. Agoti", + "author_inst": "KEMRI-Wellcome Trust Research Programme: Centre for Geographic Medicine Research Coast" + }, + { + "author_name": "R. A. Aman", + "author_inst": "Kenya Ministry of Health" + }, + { + "author_name": "M. Mwangangi", + "author_inst": "Kenya Ministry of Health" + }, + { + "author_name": "P. Amoth", + "author_inst": "Kenya Ministry of Health" + }, + { + "author_name": "K. Kasera", + "author_inst": "Kenya Ministry of Health" + }, + { + "author_name": "A. Nyaguara", + "author_inst": "KEMRI-Wellcome Trust Research Programme: Centre for Geographic Medicine Research Coast" + }, + { + "author_name": "W. Ng\u2019ang\u2019a", + "author_inst": "Government of Kenya" + }, + { + "author_name": "L. B. Ochola", + "author_inst": "IPR: Institute of Primate Research" + }, + { + "author_name": "E. Namdala", + "author_inst": "Busia County Teaching & Referral Hospital" + }, + { + "author_name": "O Gaunya", + "author_inst": "Busia County Teaching & Referral Hospital" + }, + { + "author_name": "R Okuku", + "author_inst": "Busia County Teaching & Referral Hospital" + }, + { + "author_name": "E. Barasa", + "author_inst": "KEMRI-Wellcome Trust Research Programme Nairobi" + }, + { + "author_name": "P. Bejon", + "author_inst": "KEMRI-Wellcome Trust Research Programme: Centre for Geographic Medicine Research Coast" + }, + { + "author_name": "B. Tsofa", + "author_inst": "KEMRI-Wellcome Trust Research Programme: Centre for Geographic Medicine Research Coast" + }, + { + "author_name": "L. I. Ochola-Oyier", + "author_inst": "KEMRI-Wellcome Trust Research Programme: Centre for Geographic Medicine Research Coast" + }, + { + "author_name": "G. M. Warimwe", + "author_inst": "KEMRI-Wellcome Trust Research Programme: Centre for Geographic Medicine Research Coast" + }, + { + "author_name": "A. Agweyu", + "author_inst": "KEMRI-Wellcome Trust Research Programme: Centre for Geographic Medicine Research Coast" + }, + { + "author_name": "J. A. G. Scott", + "author_inst": "KEMRI-Wellcome Trust Research Programme: Centre for Geographic Medicine Research Coast" + }, + { + "author_name": "Katherine E. Gallagher", + "author_inst": "London School of Hygiene and Tropical Medicine Faculty of Infectious and Tropical Diseases" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "respiratory medicine" + "category": "epidemiology" }, { "rel_doi": "10.1101/2022.03.03.22271313", @@ -361451,39 +360714,119 @@ "category": "biochemistry" }, { - "rel_doi": "10.1101/2022.03.03.22271835", - "rel_title": "Acute and long-term impacts of COVID-19 on economic vulnerability: a population-based longitudinal study (COVIDENCE UK)", - "rel_date": "2022-03-04", + "rel_doi": "10.1101/2022.03.02.22271759", + "rel_title": "SARS-CoV-2 IgG seroprevalence in the Okinawa Main Island and remote islands in Okinawa, Japan, 2020-2021.", + "rel_date": "2022-03-03", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.03.03.22271835", - "rel_abs": "BackgroundSocio-economic deprivation is well recognised as a risk factor for developing COVID-19. However, the impact of COVID-19 on economic vulnerability has not previously been characterised.\n\nObjectiveTo determine whether COVID-19 has a significant impact on adequacy of household income to meet basic needs (primary outcome) and work absence due to sickness (secondary outcome), both at the onset of illness (acutely) and subsequently (long-term).\n\nDesignMultivariate mixed regression analysis of self-reported data from monthly on-line questionnaires, completed 1st May 2020 to 28th October 2021, adjusting for baseline characteristics including age, sex, socioeconomic status and self-rated health.\n\nSetting and ParticipantsParticipants (n=16,910) were UK residents aged 16 years or over participating in a national longitudinal study of COVID-19 (COVIDENCE UK).\n\nResultsIncident COVID-19 was independently associated with increased odds of participants reporting household income as being inadequate to meet their basic needs, both acutely (adjusted odds ratio [aOR) 1.39, 95% confidence interval [CI] 1.12 to 1.73) and in the long-term (aOR 1.15, 95% CI 1.00 to 1.33). Exploratory analysis revealed the long-term association to be restricted to those who reported long COVID, defined as the presence of symptoms lasting more than 4 weeks after the acute episode (aOR 1.39, 95% CI 1.10 to 1.77). Incident COVID-19 associated with increased odds of reporting sickness absence from work in the long-term (aOR 5.29, 95% CI 2.76 to 10.10) but not acutely (aOR 1.34, 95% CI 0.52 to 3.49).\n\nConclusionsWe demonstrate an independent association between COVID-19 and increased risk of economic vulnerability, both acutely and in the long-term. Taking these findings together with pre-existing research showing that socio-economic disadvantage increases the risk of developing COVID-19, this may generate a vicious cycle of impaired health and poor economic outcomes.\n\nTrial registrationNCT04330599\n\nSummary BoxO_ST_ABSWhat is already known on this topicC_ST_ABSO_LISocioeconomic deprivation is recognised as a major risk factor for incidence and severity of COVID-19 disease, mediated via factors including increased occupational and household exposure to SARS-CoV-2 and greater physical vulnerability due to comorbidities\nC_LIO_LIThe potential for COVID-19 to act as a cause, rather than a consequence, of economic vulnerability has not previously been characterised.\nC_LI\n\nWhat this study addsO_LIWe demonstrate an independent association between incident COVID-19 and subsequent self-report of household income being inadequate to meet basic needs, both acutely and in the long term\nC_LIO_LIIncident COVID-19 was also associated with increased odds of subsequent self-report of sickness absence from work in the long-term.\nC_LI", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.03.02.22271759", + "rel_abs": "We estimated the seroprevalence of anti-SARS-COV-2 IgG in different island groups in Okinawa and described its changes over time. A cross-sectional sero-survey was repeated in three distinct periods between July 2020 and February 2021. A total of 2683 serum samples were collected from six referral medical centers, each covering a separate region in Okinawa. Patients who visited the emergency department for any reason and underwent blood collection were eligible for the study. Samples were analyzed using an FDA-authorized two-step enzyme-linked immunosorbent assay (ELISA) protocol. The case detection ratio was computed by dividing the seroprevalence by the attack rate obtained from publicly available surveillance data. In the main island, the seroprevalence was 0.0% (0/392, 95% CI: 0.0-0.9), 0.6% (8/1448, 0.2-1.1), and 1.4% (8/582, 0.6-2.7) at the 1st, 2nd, and 3rd sero-survey, respectively. In the remote islands, the seroprevalence was 0.0% (0/144, 95% CI: 0.0-2.5) and 1.6% (2/123, 0.2-5.8) at the 2nd and 3rd survey, respectively. The overall case detection ratios at the 3rd survey were 2.7 (95% CI: 1.3-5.3) in the main island and 2.8 (0.7-11.1) in the remote islands. The highest age-specific case detection ratio was observed in people aged 20-29 years (8.3, 95% CI: 3.3-21.4) in the main island and in those aged 50-59 years (14.1, 2.1-92.7) in the remote islands. The low seroprevalence at the latest survey suggested that a large-scale epidemic had not yet occurred in Okinawa by February 2021. The case detection ratios imply that the cumulative number of incident cases in Okinawa should be 2-3 times higher than that reported by routine surveillance. The ratio was particularly high in young people probably due to a frequent asymptomatic/mild COVID-19 disease in this age group. To accurately measure the scale of the COVID-19 epidemic, it is crucially important to conduct a sero-survey targeting the young.", + "rel_num_authors": 25, "rel_authors": [ { - "author_name": "Anne E Williamson", - "author_inst": "Blizard Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London" + "author_name": "Kenji Mizumoto", + "author_inst": "Kyoto Daigaku" }, { - "author_name": "Florence Tydeman", - "author_inst": "Blizard Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London" + "author_name": "Yusuke Shimakawa", + "author_inst": "Institut Pasteur" }, { - "author_name": "Alec Miners", - "author_inst": "Department of Health Services Research and Policy, London School of Hygiene and Tropical Medicine" + "author_name": "Yoshiaki Aizawa", + "author_inst": "Public Kumejima Hospital" }, { - "author_name": "Kate Pyper", - "author_inst": "Department of Mathematics and Statistics, University of Strathclyde" + "author_name": "Christian Butcher", + "author_inst": "Okinawa Institute of Science and Technology: Gakko Hojin Okinawa Kagaku Gijutsu Daigakuin Daigaku Gakuen" }, { - "author_name": "Adrian R Martineau", - "author_inst": "Institute of Population Health Sciences, Barts and The London School of Medicine and Dentistry, Queen Mary University of London" + "author_name": "Naomi Chibana", + "author_inst": "Naha City Hospital" + }, + { + "author_name": "Mary Collins", + "author_inst": "Okinawa Institute of Science and Technology: Gakko Hojin Okinawa Kagaku Gijutsu Daigakuin Daigaku Gakuen" + }, + { + "author_name": "Kohei Kameya", + "author_inst": "OKinawa Prefectural Yaeyama Hospital" + }, + { + "author_name": "Tae Gyun Kim", + "author_inst": "Okinawa Institute of Science and Technology: Gakko Hojin Okinawa Kagaku Gijutsu Daigakuin Daigaku Gakuen" + }, + { + "author_name": "Satoshi Koyama", + "author_inst": "Okinawa Miyako Hospital: Okinawa Kenritsu Miyako Byoin" + }, + { + "author_name": "Ryota Matsuyama", + "author_inst": "Hiroshima University: Hiroshima Daigaku" + }, + { + "author_name": "Melissa M. Matthews", + "author_inst": "Okinawa Institute of Science and Technology: Gakko Hojin Okinawa Kagaku Gijutsu Daigakuin Daigaku Gakuen" + }, + { + "author_name": "Tomoari Mori", + "author_inst": "Okinawa Institute of Science and Technology: Gakko Hojin Okinawa Kagaku Gijutsu Daigakuin Daigaku Gakuen" + }, + { + "author_name": "Tetsuharu Nagamoto", + "author_inst": "Kyoto University: Kyoto Daigaku" + }, + { + "author_name": "Masashi Narita", + "author_inst": "Okinawa Prefectural Chubu Hospital: Okinawa Kenritsu Chubu Byoin" + }, + { + "author_name": "Ryosuke Omori", + "author_inst": "Hokkaido University: Hokkaido Daigaku" + }, + { + "author_name": "Noriko Shibata", + "author_inst": "Okinawa Institute of Science and Technology: Gakko Hojin Okinawa Kagaku Gijutsu Daigakuin Daigaku Gakuen" + }, + { + "author_name": "Satoshi Shibata", + "author_inst": "Okinawa Institute of Science and Technology: Gakko Hojin Okinawa Kagaku Gijutsu Daigakuin Daigaku Gakuen" + }, + { + "author_name": "Souichi Shiiki", + "author_inst": "Okinawa Prefectural Chubu Hospital: Okinawa Kenritsu Chubu Byoin" + }, + { + "author_name": "Syunichi Takakura", + "author_inst": "Okinawa Prefectural Chubu Hospital: Okinawa Kenritsu Chubu Byoin" + }, + { + "author_name": "Naoki Toyozato", + "author_inst": "Okinawa Prefectural Chubu Hospital: Okinawa Kenritsu Chubu Byoin" + }, + { + "author_name": "Hiroyuki Tsuchiya", + "author_inst": "Okinawa Prefectural Nambu Medical Center & Children's Mecical Center" + }, + { + "author_name": "Matthias Wolf", + "author_inst": "Okinawa Institute of Science and Technology: Gakko Hojin Okinawa Kagaku Gijutsu Daigakuin Daigaku Gakuen" + }, + { + "author_name": "Shuhei Yokoyama", + "author_inst": "Okinawa Prefectural Chubu Hospital: Okinawa Kenritsu Chubu Byoin" + }, + { + "author_name": "Sho Yonaha", + "author_inst": "Public Kumejima Hospital" + }, + { + "author_name": "Yoshihiro Takayama", + "author_inst": "Okinawa Prefectural Chubu Hospital: Okinawa Kenritsu Chubu Byoin" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "health economics" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2022.03.03.482788", @@ -363597,57 +362940,45 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2022.03.01.482536", - "rel_title": "Discovery of compounds that inhibit SARS-CoV-2 Mac1-ADP-ribose binding by high-throughput screening", + "rel_doi": "10.1101/2022.03.02.480688", + "rel_title": "Flipped Over U: Structural Basis for dsRNA Cleavage by the SARS-CoV-2 Endoribonuclease", "rel_date": "2022-03-02", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.03.01.482536", - "rel_abs": "The emergence of several zoonotic viruses in the last twenty years, especially the pandemic outbreak of SARS-CoV-2, has exposed a dearth of antiviral drug therapies for viruses with pandemic potential. Developing a diverse drug portfolio will be critical for our ability to rapidly respond to novel coronaviruses (CoVs) and other viruses with pandemic potential. Here we focus on the SARS-CoV-2 conserved macrodomain (Mac1), a small domain of non-structural protein 3 (nsp3). Mac1 is an ADP-ribosylhydrolase that cleaves mono-ADP-ribose (MAR) from target proteins, protects the virus from the anti-viral effects of host ADP-ribosyltransferases, and is critical for the replication and pathogenesis of CoVs. In this study, a luminescent-based high-throughput assay was used to screen [~]38,000 small molecules for those that could inhibit Mac1-ADP-ribose binding. We identified 5 compounds amongst 3 chemotypes that inhibit SARS-CoV-2 Mac1-ADP-ribose binding in multiple assays with IC50 values less than 100{micro}M, inhibit ADP-ribosylhydrolase activity, and have evidence of direct Mac1 binding. These chemotypes are strong candidates for further derivatization into highly effective Mac1 inhibitors.", - "rel_num_authors": 10, + "rel_link": "https://biorxiv.org/cgi/content/short/2022.03.02.480688", + "rel_abs": "Coronaviruses generate double-stranded (ds) RNA intermediates during viral replication that can activate host immune sensors. To evade activation of the host pattern recognition receptor MDA5, coronaviruses employ Nsp15, which is uridine-specific endoribonuclease. Nsp15 is proposed to associate with the coronavirus replication-transcription complex within double-membrane vesicles to cleave these dsRNA intermediates. How Nsp15 recognizes and processes dsRNA is poorly understood because previous structural studies of Nsp15 have been limited to small single-stranded (ss) RNA substrates. Here we present cryo-EM structures of SARS-CoV-2 Nsp15 bound to a 52nt dsRNA. We observed that the Nsp15 hexamer forms a platform for engaging dsRNA across multiple protomers. The structures, along with site-directed mutagenesis and RNA cleavage assays revealed critical insight into dsRNA recognition and processing. To process dsRNA Nsp15 utilizes a base-flipping mechanism to properly orient the uridine within the active site for cleavage. Our findings show that Nsp15 is a distinctive endoribonuclease that can cleave both ss- and dsRNA effectively.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Anu Roy", - "author_inst": "University of Kansas" - }, - { - "author_name": "Yousef M Alhammad", - "author_inst": "University of Kansas" - }, - { - "author_name": "Peter McDonald", - "author_inst": "University of Kansas" - }, - { - "author_name": "David K Johnson", - "author_inst": "University of Kansas" + "author_name": "Meredith N Frazier", + "author_inst": "National Institute of Environmental Health Sciences" }, { - "author_name": "Junlin Zhuo", - "author_inst": "Johns Hopkins University" + "author_name": "Isha M Wilson", + "author_inst": "NIEHS/NIH" }, { - "author_name": "Sarah Wazir", - "author_inst": "Oulu University" + "author_name": "Juno M Krahn", + "author_inst": "NIEHS/NIH" }, { - "author_name": "Dana V Ferraris", - "author_inst": "McDaniel College" + "author_name": "Kevin John Butay", + "author_inst": "NIEHS/NIH" }, { - "author_name": "Lari Lehti\u00f6", - "author_inst": "University of Oulu" + "author_name": "Lucas B Dillard", + "author_inst": "NIEHS/NIH" }, { - "author_name": "Anthony Leung", - "author_inst": "Johns Hopkins University" + "author_name": "Mario J. N Borgnia", + "author_inst": "National Institute of Health" }, { - "author_name": "Anthony R Fehr", - "author_inst": "University of Kansas" + "author_name": "Robin E Stanley", + "author_inst": "NIEHS/NIH" } ], "version": "1", - "license": "cc_no", + "license": "cc0", "type": "new results", "category": "biochemistry" }, @@ -365459,47 +364790,83 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2022.02.28.22271643", - "rel_title": "Myocarditis and Pericarditis following COVID-19 Vaccination: Evidence Syntheses on Incidence, Risk Factors, Natural History, and Hypothesized Mechanisms", + "rel_doi": "10.1101/2022.02.27.482162", + "rel_title": "Stable nebulization and muco-trapping properties of Regdanvimab/IN-006 support its development as a potent, dose-saving inhaled therapy for COVID-19", "rel_date": "2022-03-01", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.02.28.22271643", - "rel_abs": "ObjectivesMyocarditis and pericarditis are adverse events of special interest after vaccination for COVID-19. Evidence syntheses were conducted on incidence rates, risk factors for myocarditis and pericarditis after COVID-19 mRNA vaccination, clinical presentation and short- and longer-term outcomes of cases, and proposed mechanisms and their supporting evidence.\n\nDesignSystematic reviews and evidence reviews.\n\nData sourcesMedline, Embase and the Cochrane Library were searched from October 2020 to January 10, 2022; reference lists and grey literature (to January 13, 2021).\n\nReview methodsLarge (>10,000) or population-based/multisite observational studies and surveillance data (incidence and risk factors) reporting on confirmed myocarditis or pericarditis after COVID-19 vaccination; case series (n[≥]5, presentation, short-term clinical course and longer-term outcomes); opinions/letters/reviews/primary studies focused on describing or supporting hypothesized mechanisms. A single reviewer completed screening and another verified 50% of exclusions, using a machine-learning program to prioritize records. A second reviewer verified all exclusions at full text, extracted data, and (for incidence and risk factors) risk of bias assessments using modified Joanna Briggs Institute tools. Team consensus determined certainty of evidence ratings for incidence and risk factors using GRADE.\n\nResults46 studies were included (14 on incidence, 7 on risk factors, 11 on characteristics and short-term course, 3 on longer term outcomes, and 21 on mechanisms). Incidence of myocarditis after mRNA vaccines is highest in male adolescents and young adults (12-17y: range 50-139 cases per million [low certainty] and 18-29y: range 28-147 per million [moderate certainty]). For 5-11 year-old males and females and females 18-29 years of age, incidence of myocarditis after vaccination with Pfizer may be fewer than 20 cases per million (low certainty). There was very low certainty evidence for incidence after a third dose of an mRNA vaccine. For 18-29 year-old males and females, incidence of myocarditis is probably higher after vaccination with Moderna compared to Pfizer (moderate certainty). Among 12-17, 18-29 and 18-39 year-olds, incidence of myocarditis/pericarditis after dose 2 of an mRNA vaccine may be lower when administered [≥]31 days compared to [≤]30 days after dose 1 (low certainty). Data specific to males aged 18-29 indicated that the dosing interval may need to increase to [≥]56 days to substantially drop incidence. For clinical course and short-term outcomes only one small series (n=8) was found for 5-11 year olds. In cases of adolescents and adults, the majority (>90%) of myocarditis cases involved 20-30 year-old males with symptom onset 2 to 4 days after second dose (71-100%). Most cases were hospitalized ([≥]84%) for a short duration (2-4 d). For pericarditis, data is limited but more variation has been reported in patient age, sex, onset timing and rate of hospitalization. Case series with longer-term (3 mo; n=38) follow-up suggest persistent ECG abnormalities, as well as ongoing symptoms and/or a need for medications or restriction from activities in >50% of patients. 16 hypothesized mechanisms are described, with little direct supporting or refuting evidence.\n\nConclusionsAdolescent and young adult males are at the highest risk of myocarditis after mRNA vaccination. Pfizer over Moderna and waiting more than 30 days between doses may be preferred for this population. Incidence of myocarditis in children aged 5-11 may be very rare but certainty was low. Data on clinical risk factors was very limited. Clinical course of mRNA related myocarditis appears to be benign although longer term follow-up data is limited. Prospective studies with appropriate testing (e.g., biopsy, tissue morphology) will enhance understanding of mechanism(s).\n\nFunding and Registration noThis project was funded in part by the Canadian Institutes of Health Research (CIHR) through the COVID-19 Evidence Network to support Decision-making (COVID-END) at McMaster University. Not registered.\n\nSummary boxWhat is already known about this topic?\n\nCase reports and surveillance signals of myocarditis (inflammation of the heart muscle) and pericarditis (inflammation of the two-layered sac surrounding the heart) after COVID-19 vaccination appeared as early as April 2021.\n\nThese have prompted ongoing surveillance and research of these complications to investigate their incidence, possible attribution to the vaccines, and clinical course.\n\nWhat this study adds\n\nThis review critically appraises and synthesizes the available evidence to-date on the incidence of and risk factors for myocarditis and pericarditis after COVID-19 vaccination in multiple countries. It summarizes the presentation and clinical course of over 8000 reported cases and describes some initial reports of longer term outcomes. Further, many possible mechanisms are outlined and discussed.\n\nThough low, the incidence of myocarditis is probably the highest in young males aged 12-29 years and is probably higher with Moderna than Pfizer mRNA vaccines. Longer dosing intervals may be beneficial. Most cases are mild and self-limiting, though data in 5-11 year-olds is very limited. Continued active surveillance with longer term follow-up is warranted.", - "rel_num_authors": 7, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2022.02.27.482162", + "rel_abs": "The respiratory tract represents the key target for antiviral delivery in early interventions to prevent severe COVID-19. While neutralizing monoclonal antibodies (mAb) possess considerable efficacy, their current reliance on parenteral dosing necessitates very large doses and places a substantial burden on the healthcare system. In contrast, direct inhaled delivery of mAb therapeutics offers the convenience of self-dosing at home, as well as much more efficient mAb delivery to the respiratory tract. Here, building on our previous discovery of Fc-mucin interactions crosslinking viruses to mucins, we showed that regdanvimab, a potent neutralizing mAb already approved for COVID-19 in several countries around the world, can effectively trap SARS-CoV-2 virus-like-particles in fresh human airway mucus. IN-006, a reformulation of Regdanvimab, was stably nebulized across a wide range of concentrations, with no loss of activity and no formation of aggregates. Finally, nebulized delivery of IN-006 resulted in 100-fold greater mAb levels in the lungs of rats compared to serum, in marked contrast to intravenously dosed mAbs. These results not only support our current efforts to evaluate the safety and efficacy of IN-006 in clinical trials, but more broadly substantiate nebulized delivery of human antiviral mAbs as a new paradigm in treating SARS-CoV-2 and other respiratory pathologies.", + "rel_num_authors": 16, "rel_authors": [ { - "author_name": "Jennifer Pillay", - "author_inst": "University of Alberta" + "author_name": "Morgan D McSweeney", + "author_inst": "Inhalon Biopharma, Inc" }, { - "author_name": "Lindsay Gaudet", - "author_inst": "University of Alberta" + "author_name": "Ian Stewart", + "author_inst": "RTI International" }, { - "author_name": "Aireen Wingert", - "author_inst": "University of Alberta" + "author_name": "Zach Richardson", + "author_inst": "Inhalon Biopharma, Inc." }, { - "author_name": "Liza Bialy", - "author_inst": "University of Alberta" + "author_name": "Hyunah Kang", + "author_inst": "Biotechnology Research Institute, Celltrion Inc" }, { - "author_name": "Andrew S Mackie", - "author_inst": "University of Alberta" + "author_name": "Yoona Park", + "author_inst": "Biotechnology Research Institute, Celltrion Inc" }, { - "author_name": "Ian Paterson", - "author_inst": "University of Alberta" + "author_name": "Cheolmin Kim", + "author_inst": "Biotechnology Research Institute, Celltrion Inc" }, { - "author_name": "Lisa Hartling", - "author_inst": "University of Alberta" + "author_name": "Karthik Tiruthani", + "author_inst": "University of North Carolina, Chapel Hill" + }, + { + "author_name": "Whitney Wolf", + "author_inst": "University of North Carolina, Chapel Hill" + }, + { + "author_name": "Alison Schaefer", + "author_inst": "University of North Carolina, Chapel Hill" + }, + { + "author_name": "Priya Kumar", + "author_inst": "University of North Carolina, Chapel Hill" + }, + { + "author_name": "Harendra Aurora", + "author_inst": "University of North Carolina, Chapel Hill" + }, + { + "author_name": "Jeff Hutchins", + "author_inst": "Inhalon Biopharma, Inc" + }, + { + "author_name": "Jong Moon Cho", + "author_inst": "Biotechnology Research Institute, Celltrion Inc." + }, + { + "author_name": "Anthony J Hickey", + "author_inst": "RTI International" + }, + { + "author_name": "Soo Young Lee", + "author_inst": "Biotechnology Research Institute, Celltrion Inc" + }, + { + "author_name": "Samuel K Lai", + "author_inst": "University of North Carolina, Chapel Hill" } ], "version": "1", - "license": "cc_by_nc", - "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "license": "cc_no", + "type": "new results", + "category": "bioengineering" }, { "rel_doi": "10.1101/2022.03.01.22271644", @@ -367409,83 +366776,51 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.02.26.22271546", - "rel_title": "Genomics of Post-Vaccination SARS-CoV-2 Infections During the Delta Dominated Second Wave of COVID-19 Pandemic, from Mumbai Metropolitan Region (MMR), India", - "rel_date": "2022-02-27", + "rel_doi": "10.1101/2022.02.25.22271277", + "rel_title": "Rapid genome surveillance of SARS-CoV-2 and study of risk factors using shipping container laboratories and portable DNA sequencing technology", + "rel_date": "2022-02-26", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.02.26.22271546", - "rel_abs": "Vaccination against SARS-CoV-2 was launched in India in January 2021. Though vaccination reduced hospitalization and mortality due to COVID-19, vaccine breakthrough infections have become common. The present study was initiated in May 2021 to understand the proportion of predominant variants in post-vaccination infections during the Delta dominated second wave of COVID-19 in the Mumbai Metropolitan Region (MMR) in India and to understand any mutations selected in the post-vaccination infections or showing association with any patient demographics. We collected samples (n=166) from severe/moderate/mild COVID-19 patients who were either vaccinated (COVISHIELD/COVAXIN - partial/fully vaccinated) or unvaccinated, from a city hospital and from home isolation patients in MMR. A total of 150 viral genomes were sequenced by Oxford Nanopore sequencing (using MinION) and the data of 136 viral genomes were analyzed for clade/lineage and for identifying mutations in all the genomes. The sequences belonged to three clades (21A, 21I and 21J) and their lineage was identified as either Delta (B.1.617.2) or Delta+ (B.1.617.2 + K417N) or sub-lineages of Delta variant (AY.120/AY.38/AY.99). A total of 620 mutations were identified of which 10 mutations showed an increase in trend with time (May-Oct 2021). Associations of 6 mutations (2 in spike, 3 in orf1a and 1 in nucleocapsid) were shown with milder forms of the disease and one mutation (in orf1a) with partial vaccination status. The results indicate a trend towards reduction in disease severity as the wave progressed.", - "rel_num_authors": 16, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.02.25.22271277", + "rel_abs": "In this paper we report on genome sequencing of 154 SARS-CoV-2 samples between June and July 2021 (Summer outbreak) in the Bailiwick of Jersey, a UK channel island. We have analysed extensive data collected on 598,155 RT-qPCR tests that identified 8,950 positive cases as part of public health surveillance from September 2020 to August 2021. Our study implemented an amplicon-based sequencing approach using the Oxford Nanopore Technology (ONT) portable device. This revealed the emergence of twelve AY sublineages and were clustered into the Delta sub-clades 21I and 21J. This was integrated alongside an existing RT-qPCR diagnostic laboratory to provide a sample-to-sequence turnaround time of approximately 30 hours with significant scope for optimisation. Owing to the geographic remoteness of the island from large scale sequencing infrastructure, this presents an opportunity to provide policy makers with near real-time sequencing findings. Our analysis suggests that age and sex remained a substantial risk factor for mortality. We observe viral loads are higher in advanced ages and unvaccinated individuals. The median age of SARS-CoV-2 positive individuals was higher during winter than the summer outbreak, and the contact tracing program showed that younger individuals stayed positive for longer.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Kayzad S Nilgiriwala", - "author_inst": "The Foundation for Medical Research" - }, - { - "author_name": "Pratibha Kadam", - "author_inst": "The Foundation for Medical Research" - }, - { - "author_name": "Grishma Patel", - "author_inst": "The Foundation for Medical Research" - }, - { - "author_name": "Ambreen Shaikh", - "author_inst": "The Foundation for Medical Research" - }, - { - "author_name": "Tejal Mestry", - "author_inst": "The Foundation for Medical Research" - }, - { - "author_name": "Smriti Vaswani", - "author_inst": "The Foundation for Medical Research" - }, - { - "author_name": "Shalini Sakthivel", - "author_inst": "The Foundation for Medical Research" - }, - { - "author_name": "Aruna Poojary", - "author_inst": "Breach Candy Hospital" - }, - { - "author_name": "Bhavesh Gandhi", - "author_inst": "Breach Candy Hospital" + "author_name": "SARA FARAHI BILOOEI", + "author_inst": "OpenCell.bio, Shepherd's Bush, London W12 8LH, United Kingdom" }, { - "author_name": "Seema Rohra", - "author_inst": "Breach Candy Hospital" + "author_name": "Dejana Jovicevic", + "author_inst": "OpenCell.bio, Shepherd's Bush, London W12 8LH, United Kingdom" }, { - "author_name": "Zarir Udwadia", - "author_inst": "Breach Candy Hospital" + "author_name": "Arash Iranzadeh", + "author_inst": "Computational Biology Division, Department of Integrative Biomedical Sciences, University of Cape Town, Cape Town, South Africa" }, { - "author_name": "Vikas Oswal", - "author_inst": "Vikas Nursing Home" + "author_name": "Cynthia Mpofu", + "author_inst": "OpenCell.bio, Shepherd's Bush, London W12 8LH, United Kingdom" }, { - "author_name": "Daksha Shah", - "author_inst": "Municipal Corporation of Greater Mumbai" + "author_name": "Ivan Muscat", + "author_inst": "Departments of Infection Sciences and Public Health, The Parade, St Helier, JE1 3QS, Jersey" }, { - "author_name": "Mangala Gomare", - "author_inst": "Municipal Corporation of Greater Mumbai" + "author_name": "Anthony Thomas", + "author_inst": "OpenCell.bio, Shepherd's Bush, London W12 8LH, United Kingdom" }, { - "author_name": "Kalpana Sriraman", - "author_inst": "The Foundation for Medical Research" + "author_name": "Helene Steiner", + "author_inst": "OpenCell.bio, Shepherd's Bush, London W12 8LH, United Kingdom" }, { - "author_name": "Nerges Mistry", - "author_inst": "The Foundation for Medical Research" + "author_name": "Thomas Meany", + "author_inst": "OpenCell.bio, Shepherd's Bush, London W12 8LH, United Kingdom" } ], "version": "1", "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2022.02.24.22271262", @@ -369019,75 +368354,175 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2022.02.16.22271092", - "rel_title": "Presence of Symptoms 6 Weeks After COVID-19 Among Vaccinated and Unvaccinated U.S. Healthcare Personnel", + "rel_doi": "10.1101/2022.02.22.481551", + "rel_title": "Highly divergent white-tailed deer SARS-CoV-2 with potential deer-to-human transmission", "rel_date": "2022-02-25", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.02.16.22271092", - "rel_abs": "AO_SCPLOWBSTRACTC_SCPLOWO_ST_ABSImportanceC_ST_ABSAlthough COVID-19 vaccines protect against infection and severe disease, the role of vaccination in preventing prolonged symptoms in those with subsequent infection is unclear.\n\nObjectiveTo determine differences in symptoms stratified by prior vaccination reported by healthcare personnel (HCP) 6 weeks after onset of COVID-19, and whether there were differences in timing of return to work.\n\nDesignNested cohort study within a multicenter vaccine effectiveness study. HCP with COVID-19 between December 2020 and August 2021 were followed up 6 weeks after illness onset.\n\nSettingHealth systems in 12 U.S. states.\n\nParticipantsHCP participating in a vaccine effectiveness study were eligible for inclusion if they had confirmed COVID-19 with either verified mRNA vaccination (symptom onset [≥]14 days after two doses) or no prior COVID-19 vaccination. Among 681 eligible participants, 419 (61%) completed a follow-up survey approximately 6 weeks after illness onset.\n\nExposuresTwo doses of a COVID-19 mRNA vaccine compared with no COVID-19 vaccine.\n\nMain outcomes and measuresPresence of symptoms 6 weeks after onset of COVID-19 illness and days to return to work after COVID-19 illness.\n\nResultsAmong 419 HCP with confirmed COVID-19, 298 (71%) reported one or more COVID-like symptoms 6 weeks after illness onset, with a lower prevalence among vaccinated participants (60.6%) compared with unvaccinated participants (60.6% vs. 79.1%; aRR 0.70, 95% CI 0.58-0.84). Vaccinated HCP returned to work a median 2.0 days (95% CI 1.0-3.0) sooner than unvaccinated HCP (aHR 1.37; 95% CI, 1.04-1.79).\n\nConclusionsA history of two doses of COVID-19 mRNA vaccine among HCP with COVID-19 illness was associated with decreased risk of COVID-like symptoms at 6 weeks and earlier to return to work. Vaccination is associated with improved recovery from COVID-19, in addition to preventing symptomatic infection.\n\nKEY POINTSO_ST_ABSQuestionC_ST_ABSDoes vaccination lead to improved recovery of symptoms and return to work following COVID-19?\n\nFindingsIn this nested cohort study of healthcare personnel, participants with COVID-19 who had received two doses of a COVID-19 mRNA vaccine were less likely to report symptoms 6 weeks after illness onset than participants with COVID-19 who were unvaccinated. Return to work was sooner if previously vaccinated.\n\nMeaningVaccination is associated with improved recovery from COVID-19, in addition to prevention of infection and disease.", - "rel_num_authors": 14, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2022.02.22.481551", + "rel_abs": "Wildlife reservoirs of SARS-CoV-2 may enable viral adaptation and spillback from animals to humans. In North America, there is evidence of unsustained spillover of SARS-CoV-2 from humans to white-tailed deer (Odocoileus virginianus), but no evidence of transmission from deer to humans. Through a biosurveillance program in Ontario, Canada we identified a new and highly divergent lineage of SARS-CoV-2 in white-tailed deer. This lineage is the most divergent SARS-CoV-2 lineage identified to date, with 76 consensus mutations (including 37 previously associated with non-human animal hosts) and signatures of considerable evolution and transmission within wildlife. Phylogenetic analysis also revealed an epidemiologically linked human case. Together, our findings represent the first clear evidence of sustained evolution of SARS-CoV-2 in white-tailed deer and of deer-to-human transmission.", + "rel_num_authors": 39, "rel_authors": [ { - "author_name": "Nicholas M. Mohr", - "author_inst": "University of Iowa Carver College of Medicine" + "author_name": "Brad Pickering", + "author_inst": "Canadian Food Inspection Agency" }, { - "author_name": "Ian D Plumb", - "author_inst": "CDC/DDID/NCIRD/DVD" + "author_name": "Oliver Lung", + "author_inst": "Canadian Food Inspection Agency" }, { - "author_name": "Karisa K Harland", - "author_inst": "University of Iowa" + "author_name": "Finlay Maguire", + "author_inst": "Dalhousie University" }, { - "author_name": "Tamara Pilishvili", - "author_inst": "CDC" + "author_name": "Peter Kruczkiewicz", + "author_inst": "Canadian Food Inspection Agency" }, { - "author_name": "Katherine E Flemming-Dutra", - "author_inst": "CDC/DDID/NCIRD/DBD" + "author_name": "Jonathon D Kotwa", + "author_inst": "Sunnybrook Research Institute" }, { - "author_name": "Anusha Krishnadasan", - "author_inst": "University of California, Los Angeles" + "author_name": "Tore Buchanan", + "author_inst": "Ontario Ministry of Northern Development, Mines, Natural Resources and Forestry" }, { - "author_name": "Karin F Hoth", - "author_inst": "University of Iowa" + "author_name": "Marianne Gagnier", + "author_inst": "Quebec Ministere des Forets, de la Faune et des Parcs" }, { - "author_name": "Sharon H Saydah", - "author_inst": "CDC/DDI/NCIRD/DVD" + "author_name": "Jennifer Guthrie", + "author_inst": "Public Health Ontario" }, { - "author_name": "Zachary Mankoff", - "author_inst": "Thomas Jefferson University Hospital" + "author_name": "Claire Jardine", + "author_inst": "University of Guelph" }, { - "author_name": "John P Haran", - "author_inst": "University of Massachusetts" + "author_name": "Alex Marchand-Austin", + "author_inst": "Public Health Ontario" }, { - "author_name": "Melissa Briggs-Hagen", - "author_inst": "CDC/DDI/NCIRD/DVD" + "author_name": "Ariane Mass\u00e9", + "author_inst": "Quebec Ministere des Forets, de la Faune et des Parcs" }, { - "author_name": "Eliezer Santos Leon", - "author_inst": "University of Iowa" + "author_name": "Heather McClinchey", + "author_inst": "Ontario Ministry of Health" }, { - "author_name": "David A Talan", - "author_inst": "University of California, Los Angeles" + "author_name": "Kuganya Nirmalarajah", + "author_inst": "University of Toronto" }, { - "author_name": "- Project PREVENT Network", - "author_inst": "" + "author_name": "Patryk Aftanas", + "author_inst": "Sunnybrook Research Institute" + }, + { + "author_name": "Juliette Blais-Savoie", + "author_inst": "Sunnybrook Research Institute" + }, + { + "author_name": "Hsien-Yao Chee", + "author_inst": "Sunnybrook Research Institute" + }, + { + "author_name": "Emily Chien", + "author_inst": "University of Toronto" + }, + { + "author_name": "Winfield Yim", + "author_inst": "University of Toronto" + }, + { + "author_name": "Andra Banete", + "author_inst": "Sunnybrook Research Institute" + }, + { + "author_name": "Bryan D. Griffin", + "author_inst": "Sunnybrook Research Institute" + }, + { + "author_name": "Lily Yip", + "author_inst": "Sunnybrook Research Institute" + }, + { + "author_name": "Melissa Goolia", + "author_inst": "Canadian Food Inspection Agency" + }, + { + "author_name": "Matthew Suderman", + "author_inst": "Canadian Food Inspection Agency" + }, + { + "author_name": "Mathieu Pinette", + "author_inst": "Canadian Food Inspection Agency" + }, + { + "author_name": "Greg Smith", + "author_inst": "Canadian Food Inspection Agency" + }, + { + "author_name": "Daniel Sullivan", + "author_inst": "Canadian Food Inspection Agency" + }, + { + "author_name": "Josip Rudar", + "author_inst": "Canadian Food Inspection Agency" + }, + { + "author_name": "Elizabeth Adey", + "author_inst": "Ontario Ministry of Northern Development, Mines, Natural Resources and Forestry" + }, + { + "author_name": "Michelle Nebroski", + "author_inst": "Canadian Food Inspection Agency" + }, + { + "author_name": "Guillaume Goyette", + "author_inst": "CRCHUM" + }, + { + "author_name": "Andr\u00e9s Finzi", + "author_inst": "Universit\u00e9 de Montr\u00e9al" + }, + { + "author_name": "Genevi\u00e8ve Laroche", + "author_inst": "University of Ottawa" + }, + { + "author_name": "Ardeshir Ariana", + "author_inst": "University of Ottawa" + }, + { + "author_name": "Brett Vahkal", + "author_inst": "University of Ottawa" + }, + { + "author_name": "Marceline C\u00f4t\u00e9", + "author_inst": "University of Ottawa" + }, + { + "author_name": "Allison McGeer", + "author_inst": "Mount Sinai Hospital" + }, + { + "author_name": "Larissa Nituch", + "author_inst": "Ontario Ministry of Northern Development, Mines, Natural Resources and Forestry" + }, + { + "author_name": "Samira Mubareka", + "author_inst": "Sunnybrook Research Institute and University of Toronto" + }, + { + "author_name": "Jeff Bowman", + "author_inst": "Ontario Ministry of Northern Development, Mines, Natural Resources and Forestry" } ], "version": "1", - "license": "cc_no", - "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "license": "cc_by_nc_nd", + "type": "new results", + "category": "microbiology" }, { "rel_doi": "10.1101/2022.02.24.22271478", @@ -370661,101 +370096,105 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2022.02.23.481644", - "rel_title": "Omicron BA.1 and BA.2 are antigenically distinct SARS-CoV-2 variants", + "rel_doi": "10.1101/2022.02.23.481658", + "rel_title": "Bacterial metatranscriptomes in wastewater can differentiate virally infected human populations", "rel_date": "2022-02-24", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.02.23.481644", - "rel_abs": "The emergence and rapid spread of SARS-CoV-2 variants may impact vaccine efficacy significantly1. The Omicron variant termed BA.2, which differs genetically substantially from BA.1, is currently replacing BA.1 in several countries, but its antigenic characteristics have not yet been assessed2,3. Here, we used antigenic cartography to quantify and visualize antigenic differences between SARS-CoV-2 variants using hamster sera obtained after primary infection. Whereas early variants are antigenically similar, clustering relatively close to each other in antigenic space, Omicron BA.1 and BA.2 have evolved as two distinct antigenic outliers. Our data show that BA.1 and BA.2 both escape (vaccine-induced) antibody responses as a result of different antigenic characteristics. Close monitoring of the antigenic changes of SARS-CoV-2 using antigenic cartography can be helpful in the selection of future vaccine strains.", - "rel_num_authors": 21, + "rel_link": "https://biorxiv.org/cgi/content/short/2022.02.23.481658", + "rel_abs": "Monitoring wastewater samples at building-level resolution screens large populations for SARS-CoV-2, prioritizing testing and isolation efforts. Here we perform untargeted metatranscriptomics on virally-enriched wastewater samples from 10 locations on the UC San Diego campus, demonstrating that resulting bacterial taxonomic and functional profiles discriminate SARS-CoV-2 status even without direct detection of viral transcripts. Our proof-of-principle reveals emergent threats through changes in the human microbiome, suggesting new approaches for untargeted wastewater-based epidemiology.", + "rel_num_authors": 22, "rel_authors": [ { - "author_name": "Anna Z Mykytyn", - "author_inst": "Erasmus Medical Centre" + "author_name": "Rodolfo A. Salido", + "author_inst": "UC San Diego" }, { - "author_name": "Melanie Rissmann", - "author_inst": "Erasmus MC" + "author_name": "Cameron Martino", + "author_inst": "UC San Diego" }, { - "author_name": "Adinda Kok", - "author_inst": "Erasmus MC" + "author_name": "Smruthi Karthikeyan", + "author_inst": "UC San Diego" }, { - "author_name": "Miruna Rosu", - "author_inst": "Erasmus MC" + "author_name": "Shi Huang", + "author_inst": "UC San Diego" }, { - "author_name": "Debby Schipper", - "author_inst": "Erasmus MC" + "author_name": "Gibraan Rahman", + "author_inst": "UC San Diego" }, { - "author_name": "Tim I Breugem", - "author_inst": "Erasmus MC" + "author_name": "Antonio Gonzalez", + "author_inst": "UC San Diego" }, { - "author_name": "Petra B van den Doel", - "author_inst": "Erasmus University Medical Center" + "author_name": "Livia S. Zaramela", + "author_inst": "UC San Diego" }, { - "author_name": "Felicity Chandler", - "author_inst": "Erasmus MC" + "author_name": "Kristen L. Beck", + "author_inst": "IBM Research - Almaden" }, { - "author_name": "Theo Bestebroer", - "author_inst": "Erasmus MC" + "author_name": "Shrikant Bhute", + "author_inst": "UC San Diego" }, { - "author_name": "Maurice de Wit", - "author_inst": "Erasmus MC" + "author_name": "Kalen Cantrell", + "author_inst": "UC San Diego" }, { - "author_name": "Martin E. van Royen", - "author_inst": "Erasmus MC" + "author_name": "Anna Paola Carrieri", + "author_inst": "IBM Research Europe - Daresbury" }, { - "author_name": "Richard Molenkamp", - "author_inst": "Erasmus University Medical Center" + "author_name": "Sawyer Farmer", + "author_inst": "UC San Diego" }, { - "author_name": "Bas Oude Munnink", - "author_inst": "ErasmusMC" + "author_name": "Niina Haiminen", + "author_inst": "IBM T.J Watson Research Center" }, { - "author_name": "Rory Dylan de Vries", - "author_inst": "Erasmus MC" + "author_name": "Greg Humphrey", + "author_inst": "UC San Diego" }, { - "author_name": "Corine GeurtsvanKessel", - "author_inst": "Erasmus MC" + "author_name": "Ho-Cheol Kim", + "author_inst": "IBM Research - Almaden" }, { - "author_name": "Derek J Smith", - "author_inst": "University of Cambridge" + "author_name": "Laxmi Parida", + "author_inst": "IBM T.J Watson Research Center" }, { - "author_name": "Marion Koopmans", - "author_inst": "Erasmus Medical Center" + "author_name": "R. Alexander Richter", + "author_inst": "UC San Diego" }, { - "author_name": "Barry Rockx", - "author_inst": "Erasmus University Medical Center" + "author_name": "Yoshiki Vazquez-Baeza", + "author_inst": "UC San Diego" }, { - "author_name": "Mart Matthias Lamers", - "author_inst": "Erasmus MC" + "author_name": "Karsten Zengler", + "author_inst": "UC San Diego" }, { - "author_name": "Ron Fouchier", - "author_inst": "Erasmus MC" + "author_name": "Austin Swafford", + "author_inst": "UC San Diego" }, { - "author_name": "Bart Haagmans", - "author_inst": "Erasmus Medical Center" + "author_name": "Andrew Bartko", + "author_inst": "UC San Diego" + }, + { + "author_name": "Rob Knight", + "author_inst": "UC San Diego" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "new results", "category": "microbiology" }, @@ -372211,129 +371650,145 @@ "category": "health systems and quality improvement" }, { - "rel_doi": "10.1101/2022.02.17.22271138", - "rel_title": "Influenza vaccination reveals and partly reverses sex dimorphic immune imprints associated with prior mild COVID-19", + "rel_doi": "10.1101/2022.02.19.22271112", + "rel_title": "Occurrence and significance of Omicron BA.1 infection followed by BA.2 reinfection", "rel_date": "2022-02-22", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.02.17.22271138", - "rel_abs": "Viral infections can have profound and durable functional impacts on the immune system. There is an urgent need to characterize the long-term immune effects of SARS-CoV-2 infection given the persistence of symptoms in some individuals and the continued threat of novel variants. Here we use systems immunology, including longitudinal multimodal single cell analysis (surface proteins, transcriptome, and V(D)J sequences) from 33 previously healthy individuals after recovery from mild, non-hospitalized COVID-19 and 40 age- and sex-matched healthy controls with no history of COVID-19 to comparatively assess the post-infection immune status (mean: 151 days after diagnosis) and subsequent innate and adaptive responses to seasonal influenza vaccination. Identification of both sex-specific and -independent temporally stable changes, including signatures of T-cell activation and repression of innate defense/immune receptor genes (e.g., Toll-like receptors) in monocytes, suggest that mild COVID-19 can establish new post-recovery immunological set-points. COVID-19-recovered males had higher innate, influenza-specific plasmablast, and antibody responses after vaccination compared to healthy males and COVID-19-recovered females, partly attributable to elevated pre-vaccination frequencies of a GPR56 expressing CD8+ T-cell subset in male recoverees that are \"poised\" to produce higher levels of IFN{gamma} upon inflammatory stimulation. Intriguingly, by day 1 post-vaccination in COVID-19-recovered subjects, the expression of the repressed genes in monocytes increased and moved towards the pre-vaccination baseline of healthy controls, suggesting that the acute inflammation induced by vaccination could partly reset the immune states established by mild COVID-19. Our study reveals sex-dimorphic immune imprints and in vivo functional impacts of mild COVID-19 in humans, suggesting that prior COVID-19, and possibly respiratory viral infections in general, could change future responses to vaccination and in turn, vaccines could help reset the immune system after COVID-19, both in an antigen-agnostic manner.", - "rel_num_authors": 28, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.02.19.22271112", + "rel_abs": "The newly found Omicron SARS-CoV-2 variant of concern has rapidly spread worldwide. Omicron carries numerous mutations in key regions and is associated with increased transmissibility and immune escape. The variant has recently been divided into four subvariants with substantial genomic differences, in particular between Omicron BA.1 and BA.2. With the surge of Omicron subvariants BA.1 and BA.2, a large number of reinfections from earlier cases has been observed, raising the question of whether BA.2 specifically can escape the natural immunity acquired shortly after a BA.1 infection.\n\nTo investigate this, we selected a subset of samples from more than 1,8 million cases of infections in the period from November 22, 2021, until February 11, 2022. Here, individuals with two positive samples, more than 20 and less than 60 days apart, were selected. From a total of 187 reinfection cases, we identified 47 instances of BA.2 reinfections shortly after a BA.1 infection, mostly in young unvaccinated individuals with mild disease not resulting in hospitalization or death.\n\nIn conclusion, we provide evidence that Omicron BA.2 reinfections do occur shortly after BA.1 infections but are rare.", + "rel_num_authors": 32, "rel_authors": [ { - "author_name": "Rachel Sparks", - "author_inst": "Multiscale Systems Biology Section, Laboratory of Immune System Biology, NIAID, NIH, Bethesda, MD, USA" + "author_name": "Marc Stegger", + "author_inst": "Statens Serum Institut" }, { - "author_name": "William W Lau", - "author_inst": "Multiscale Systems Biology Section, Laboratory of Immune System Biology, NIAID, NIH, Bethesda, MD, USA" + "author_name": "Sofie Marie Edslev", + "author_inst": "Statens Serum Institut" }, { - "author_name": "Can Liu", - "author_inst": "Multiscale Systems Biology Section, Laboratory of Immune System Biology, NIAID, NIH, Bethesda, MD, USA; Graduate Program in Biological Sciences, University of M" + "author_name": "Raphael Niklaus Sieber", + "author_inst": "Statens Serum Institut" }, { - "author_name": "Kyu Lee Han", - "author_inst": "NIH Center for Human Immunology, NIAID, NIH, Bethesda, MD, USA" + "author_name": "Anna Cacilia Ingham", + "author_inst": "Statens Serum Institut" }, { - "author_name": "Kiera L Vrindten", - "author_inst": "Multiscale Systems Biology Section, Laboratory of Immune System Biology, NIAID, NIH, Bethesda, MD, USA" + "author_name": "Kim Lee Ng", + "author_inst": "Statens Serum Institut" }, { - "author_name": "Guangping Sun", - "author_inst": "Multiscale Systems Biology Section, Laboratory of Immune System Biology, NIAID, NIH, Bethesda, MD, USA; Division of Intramural Research, NIAID, NIH, Bethesda, M" + "author_name": "Man-Hung Eric Tang", + "author_inst": "Statens Serum Institut" }, { - "author_name": "Milann Cox", - "author_inst": "Multiscale Systems Biology Section, Laboratory of Immune System Biology, NIAID, NIH, Bethesda, MD, USA" + "author_name": "Soren Alexandersen", + "author_inst": "Statens Serum Institut" }, { - "author_name": "Sarah F Andrews", - "author_inst": "Vaccine Research Center, NIAID, NIH, Bethesda, MD, USA" + "author_name": "Jannik Fonager", + "author_inst": "Statens Serum Institut" }, { - "author_name": "Neha Bansal", - "author_inst": "Multiscale Systems Biology Section, Laboratory of Immune System Biology, NIAID, NIH, Bethesda, MD, USA" + "author_name": "Rebecca Legarth", + "author_inst": "Statens Serum Institut" }, { - "author_name": "Laura E Failla", - "author_inst": "Multiscale Systems Biology Section, Laboratory of Immune System Biology, NIAID, NIH, Bethesda, MD, USA" + "author_name": "Magdalena Utko", + "author_inst": "Statens Serum Institut" }, { - "author_name": "Jody Manischewitz", - "author_inst": "Division of Viral Products, Center for Biologics Evaluation and Research (CBER), FDA, Silver Spring, MD, USA" + "author_name": "Bartlomiej Wilkowski", + "author_inst": "Statens Serum Institut" }, { - "author_name": "Gabrielle Grubbs", - "author_inst": "Division of Viral Products, Center for Biologics Evaluation and Research (CBER), FDA, Silver Spring, MD, USA" + "author_name": "Vithiagaran Gunalan", + "author_inst": "Statens Serum Institut" }, { - "author_name": "Lisa R King", - "author_inst": "Division of Viral Products, Center for Biologics Evaluation and Research (CBER), FDA, Silver Spring, MD, USA" + "author_name": "Marc Bennedbaek", + "author_inst": "Statens Serum Institut" }, { - "author_name": "Galina Koroleva", - "author_inst": "NIH Center for Human Immunology, NIAID, NIH, Bethesda, MD, USA" + "author_name": "Jonas Byberg-Grauholm", + "author_inst": "Statens Serum Institut" }, { - "author_name": "Stephanie Leimenstoll", - "author_inst": "Laboratory of Clinical Immunology and Microbiology, NIAID, NIH, Bethesda, MD, USA" + "author_name": "Camilla Holten Moeller", + "author_inst": "Statens Serum Institut" }, { - "author_name": "LaQuita Snow", - "author_inst": "Laboratory of Clinical Immunology and Microbiology, NIAID, NIH, Bethesda, MD, USA" + "author_name": "Lasse Engbo Christiansen", + "author_inst": "Technical University of Denmark" }, { - "author_name": "- OP11 Clinical Staff", - "author_inst": "" + "author_name": "Christina Wiid Svarrer", + "author_inst": "Statens Serum Institut" }, { - "author_name": "Jinguo Chen", - "author_inst": "NIH Center for Human Immunology, NIAID, NIH, Bethesda, MD, USA" + "author_name": "Kirsten Ellegaard", + "author_inst": "Statens Serum Institut" }, { - "author_name": "Juanjie Tang", - "author_inst": "Division of Viral Products, Center for Biologics Evaluation and Research (CBER), FDA, Silver Spring, MD, USA" + "author_name": "Sharmin Baig", + "author_inst": "Statens Serum Institut" + }, + { + "author_name": "Thor Bech Johannesen", + "author_inst": "Statens Serum Institut" }, { - "author_name": "Amrita Mukherjee", - "author_inst": "NIH Center for Human Immunology, NIAID, NIH, Bethesda, MD, USA" + "author_name": "Laura Espenhain", + "author_inst": "Statens Serum Institut" }, { - "author_name": "Brain A Sellers", - "author_inst": "NIH Center for Human Immunology, NIAID, NIH, Bethesda, MD, USA" + "author_name": "Robert Skov", + "author_inst": "Statens Serum Institut" }, { - "author_name": "Richard Apps", - "author_inst": "NIH Center for Human Immunology, NIAID, NIH, Bethesda, MD, USA" + "author_name": "Arieh Sierra Cohen", + "author_inst": "Statens Serum Institut" }, { - "author_name": "Adrian B McDermott", - "author_inst": "Vaccine Research Center, NIAID, NIH, Bethesda, MD, USA" + "author_name": "Nicolai Balle Larsen", + "author_inst": "Statens Serum Institut" }, { - "author_name": "Andrew J Martins", - "author_inst": "Multiscale Systems Biology Section, Laboratory of Immune System Biology, NIAID, NIH, Bethesda, MD, USA" + "author_name": "Karina Meden Soerensen", + "author_inst": "Statens Serum Institut" }, { - "author_name": "Evan M Bloch", - "author_inst": "Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD, USA" + "author_name": "Emeily Dibba White", + "author_inst": "Statens Serum Institut" }, { - "author_name": "Hana Golding", - "author_inst": "Division of Viral Products, Center for Biologics Evaluation and Research (CBER), FDA, Silver Spring, MD, USA" + "author_name": "Troels Lillebaek", + "author_inst": "Statens Serum Institut" }, { - "author_name": "Surender Khurana", - "author_inst": "Division of Viral Products, Center for Biologics Evaluation and Research (CBER), FDA, Silver Spring, MD, USA" + "author_name": "Henrik Ullum", + "author_inst": "Statens Serum Institut" + }, + { + "author_name": "Tyra Grove Krause", + "author_inst": "Statens Serum Institut" + }, + { + "author_name": "Anders Fomsgaard", + "author_inst": "Statens Serum Institut" + }, + { + "author_name": "Steen Ethelberg", + "author_inst": "Statens Serum Institut" }, { - "author_name": "John S Tsang", - "author_inst": "Multiscale Systems Biology Section, Laboratory of Immune System Biology, NIAID, NIH, Bethesda, MD, USA; NIH Center for Human Immunology, NIAID, NIH, Bethesda, M" + "author_name": "Morten Rasmussen", + "author_inst": "Statens Serum Institut" } ], "version": "1", - "license": "cc0", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -374196,43 +373651,255 @@ "category": "rehabilitation medicine and physical therapy" }, { - "rel_doi": "10.1101/2022.02.16.22271059", - "rel_title": "Genomic monitoring unveils a high prevalence of SARS-CoV 2 Omicron Variant in vaccine breakthrough cases in Bahia, Brazil", + "rel_doi": "10.1101/2022.02.16.22271064", + "rel_title": "An open-label randomized, controlled trial of the effect of lopinavir/ritonavir, lopinavir/ritonavir plus IFN-beta-1a and hydroxychloroquine in hospitalized patients with COVID-19 - Final results from the DisCoVeRy trial", "rel_date": "2022-02-21", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.02.16.22271059", - "rel_abs": "Genome sequencing proved to be an excellent tool to monitor the molecular epidemiology of the disease caused by SARS-CoV-2, i.e., coronavirus disease (COVID-19). Some reports of infected, vaccinated individuals have aroused great interest because they are primarily being infected with circulating variants of concern (VOCs). To investigate the cases of infected, vaccinated individuals in Salvador, Bahia, Brazil, we performed genomic monitoring to estimate the magnitude of the different VOCs in these cases. Nasopharyngeal swabs from infected (symptomatic and asymptomatic), fully vaccinated individuals (n=29) who were of varying age and had RT-qPCR Ct values of [≤]30 were subjected to viral sequencing using Nanopore technology. Our analysis revealed that the Omicron variant was found in 99% of cases and that only one case was due to the Delta variant. Infected, fully vaccinated patients have a favorable clinical prognosis; however, within the community, they become viral carriers with the aggravating factor of viral dissemination of VOCs not neutralized by the vaccines.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.02.16.22271064", + "rel_abs": "ObjectivesWe evaluated the clinical, virological and safety outcomes of lopinavir/ritonavir, lopinavir/ritonavir-interferon (IFN)-{beta}-1a, hydroxychloroquine or remdesivir in comparison to standard of care (control) in COVID-19 inpatients requiring oxygen and/or ventilatory support. While preliminary results were previously published, we present here the final results, following completion of the data monitoring.\n\nMethodsWe conducted a phase 3 multi-centre open-label, randomized 1:1:1:1:1, adaptive, controlled trial (DisCoVeRy), add-on trial to Solidarity (NCT04315948, EudraCT2020-000936-23). The primary outcome was the clinical status at day 15, measured by the WHO 7-point ordinal scale. Secondary outcomes included SARS-CoV-2 quantification in respiratory specimens, pharmacokinetic and safety analyses. We report the results for the lopinavir/ritonavir-containing arms and for the hydroxychloroquine arm, which were stopped prematurely.\n\nResultsThe intention-to-treat population included 593 participants (lopinavir/ritonavir, n=147; lopinavir/ritonavir-IFN-{beta}-1a, n=147; hydroxychloroquine, n=150; control, n=149), among whom 421 (71.0%) were male, the median age was 64 years (IQR, 54-71) and 214 (36.1%) had a severe disease. The day 15 clinical status was not improved with investigational treatments: lopinavir/ritonavir versus control, adjusted odds ratio (aOR) 0.82, (95% confidence interval [CI] 0.54-1.25, P=0.36); lopinavir/ritonavir-IFN-{beta}-1a versus control, aOR 0.69 (95%CI 0.45-1.05, P=0.08); hydroxychloroquine versus control, aOR 0.94 (95%CI 0.62-1.41, P=0.76). No significant effect of investigational treatment was observed on SARS-CoV-2 clearance. Trough plasma concentrations of lopinavir and ritonavir were higher than those expected, while those of hydroxychloroquine were those expected with the dosing regimen. The occurrence of Serious Adverse Events was significantly higher in participants allocated to the lopinavir/ritonavir-containing arms.\n\nConclusionIn adults hospitalized for COVID-19, lopinavir/ritonavir, lopinavir/ritonavir-IFN-{beta}-1a and hydroxychloroquine did not improve the clinical status at day 15, nor SARS-CoV-2 clearance in respiratory tract specimens.", + "rel_num_authors": 59, "rel_authors": [ { - "author_name": "Gubio Soares Campos", - "author_inst": "Universidade Federal da Bahia" + "author_name": "Florence ADER", + "author_inst": "CHU Lyon" }, { - "author_name": "Marta Giovanetti", - "author_inst": "Fundacao Oswaldo Cruz" + "author_name": "Nathan PEIFFER-SMADJA", + "author_inst": "CHU Bichat" }, { - "author_name": "Laise de Moraes", - "author_inst": "Fundacao Oswaldo Cruz" + "author_name": "Julien POISSY", + "author_inst": "CHU Lille" }, { - "author_name": "Helena S da Hora", - "author_inst": "Universidade Federal da Bahia" + "author_name": "Maude BOUSCAMBERT-DUCHAMP", + "author_inst": "CHU Lyon" }, { - "author_name": "Keila Motta Alcantara", - "author_inst": "Universidade Federal da Bahia" + "author_name": "Drifa BELHADI", + "author_inst": "CHU Bichat" }, { - "author_name": "Silvia Ines Sardi", - "author_inst": "Universidade Federal da Bahia" + "author_name": "Alpha DIALLO", + "author_inst": "ANRS" + }, + { + "author_name": "Christelle DELMAS", + "author_inst": "ANRS" + }, + { + "author_name": "Juliette SAILLARD", + "author_inst": "Inserm" + }, + { + "author_name": "Aline DECHANET", + "author_inst": "CHU Bichat" + }, + { + "author_name": "Noemie MERCIER", + "author_inst": "ANRS" + }, + { + "author_name": "Axelle DUPONT", + "author_inst": "CHU Bichat" + }, + { + "author_name": "Toni ALFAIATE", + "author_inst": "CHU Bichat" + }, + { + "author_name": "Francois-Xavier LESCURE", + "author_inst": "CHU Bichat" + }, + { + "author_name": "Francois RAFFI", + "author_inst": "CHU Nantes" + }, + { + "author_name": "Francois GOEHRINGER", + "author_inst": "CHU Nancy" + }, + { + "author_name": "Antoine KIMMOUN", + "author_inst": "CHU Nancy" + }, + { + "author_name": "Stephane JAUREGUIBERRY", + "author_inst": "CHU Bicetre" + }, + { + "author_name": "Jean REIGNIER", + "author_inst": "CHU Nantes" + }, + { + "author_name": "Saad NSEIR", + "author_inst": "CHU Lille" + }, + { + "author_name": "Francois DANION", + "author_inst": "CHU Strasbourg" + }, + { + "author_name": "Raphael CLERE-JEHL", + "author_inst": "CHU Strasbourg" + }, + { + "author_name": "Kevin BOUILLER", + "author_inst": "CHU Besancon" + }, + { + "author_name": "Jean-Christophe NAVELLOU", + "author_inst": "CHU Besancon" + }, + { + "author_name": "Violaine TOLSMA", + "author_inst": "CH Annecy Gennevois" + }, + { + "author_name": "Andre CABIE", + "author_inst": "CHU Fort de France" + }, + { + "author_name": "Clement DUBOST", + "author_inst": "HIA Begin" + }, + { + "author_name": "Johan COURJON", + "author_inst": "CHU Nice" + }, + { + "author_name": "Sylvie LEROY", + "author_inst": "CHU Nice" + }, + { + "author_name": "Joy MOOTIEN", + "author_inst": "CH Mulhouse" + }, + { + "author_name": "Rostane GACI", + "author_inst": "CHR Mets-Thionville" + }, + { + "author_name": "Bruno MOURVILLIER", + "author_inst": "CHU Reims" + }, + { + "author_name": "Emmanuel FAURE", + "author_inst": "CHU Lille" + }, + { + "author_name": "Valerie POURCHER", + "author_inst": "CHU Pitie-Salpetriere" + }, + { + "author_name": "Sebastien GALLIEN", + "author_inst": "CHU Mondor" + }, + { + "author_name": "Odile LAUNAY", + "author_inst": "CHU Cochin" + }, + { + "author_name": "Karine LACOMBE", + "author_inst": "CHU Saint Antoine" + }, + { + "author_name": "Jean-Philippe LANOIX", + "author_inst": "CHU Amiens" + }, + { + "author_name": "Alain MAKINSON", + "author_inst": "CHU Montpellier" + }, + { + "author_name": "Guillaume MARTIN-BLONDEL", + "author_inst": "CHU Toulouse" + }, + { + "author_name": "Lila BOUADMA", + "author_inst": "CHU Bichat" + }, + { + "author_name": "elisabeth BOTELHO-NEVERS", + "author_inst": "CHU Saint Etienne" + }, + { + "author_name": "Amandine GAGNEUX-BRUNON", + "author_inst": "CHU Saint Etienne" + }, + { + "author_name": "Olivier EPAULARD", + "author_inst": "CHU Grenoble" + }, + { + "author_name": "Lionel PIROTH", + "author_inst": "CHU Dijon" + }, + { + "author_name": "Florent WALLET", + "author_inst": "CHU Lyon" + }, + { + "author_name": "Jean-Christophe RICHARD", + "author_inst": "CHU Lyon" + }, + { + "author_name": "Jean REUTER", + "author_inst": "CHU Luxembourg" + }, + { + "author_name": "Therese STAUB", + "author_inst": "CHU Luxembourg" + }, + { + "author_name": "Bruno LINA", + "author_inst": "CHU Lyon" + }, + { + "author_name": "Marion NORET", + "author_inst": "CH Annecy Gennevois" + }, + { + "author_name": "Claire ANDREJAK", + "author_inst": "CHU Amiens" + }, + { + "author_name": "Minh-Patrick LE", + "author_inst": "CHU Bichat" + }, + { + "author_name": "Gilles PEYTAVIN", + "author_inst": "CHU Bichat" + }, + { + "author_name": "Maya HITES", + "author_inst": "CHU Erasme" + }, + { + "author_name": "Dominique COSTAGLIOLA", + "author_inst": "Inserm" + }, + { + "author_name": "Yazdan YAZDANPANAH", + "author_inst": "CHU Bichat" + }, + { + "author_name": "Charles BURDET", + "author_inst": "CHU Bichat" + }, + { + "author_name": "France MENTRE", + "author_inst": "CHU Bichat" + }, + { + "author_name": "- DisCoVeRy study group", + "author_inst": "" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2022.02.18.22271188", @@ -376022,47 +375689,59 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2022.02.17.480819", - "rel_title": "Metagenomic analysis reveals the abundance and diversity of opportunistic fungal pathogens in the nasopharyngeal tract of COVID-19 patients", + "rel_doi": "10.1101/2022.02.17.480826", + "rel_title": "Genomic Characterization of Sars-Cov-2 from Islamabad Pakistan by Rapid Nanopore Sequencing", "rel_date": "2022-02-18", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.02.17.480819", - "rel_abs": "The nasopharyngeal tract (NT) of human is a habitat of a diverse microbial community that work together with other gut microbes to maintain the host immunity. In our previous study, we reported that SARS-CoV-2 infection reduces human nasopharyngeal commensal microbiome (bacteria, archaea and commensal respiratory viruses) but increases the abundance of pathobionts. This study aimed to assess the possible changes in the resident fungal diversity by the inclusion of opportunistic fungi due to the infection of SARS-CoV-2 in the NT of humans. Twenty-two (n = 22) nasopharyngeal swab samples (including COVID-19 = 8, Recovered = 7, and Healthy = 7) were collected for RNAseq-based metagenomics analyses. Our results indicate that SARS-CoV-2 infection significantly increased (p < 0.05, Wilcoxon test) the population and diversity of NT fungi with a high inclusion of opportunistic pathogens. We detected 863 fungal species including 533, 445, and 188 species in COVID-19, Recovered, and Healthy individuals, respectively that indicate a distinct microbiome dysbiosis due to the SARS-CoV-2 infection. Remarkably, 37% of the fungal species were exclusively associated with SARS-CoV-2 infection, where S. cerevisiae (88.62%) and Phaffia rhodozyma (10.30%) were two top abundant species in the NT of COVID-19 patients. Importantly, 16% commensal fungal species found in the Healthy control were not detected in either COVID-19 patients or when they were recovered from the COVID-19. Pairwise Spearmans correlation test showed that several altered metabolic pathways had significant positive correlations (r > 0.5, p < 0.01) with dominant fungal species detected in three metagenomes. Taken together, our results indicate that SARS-CoV-2 infection causes significant dysbiosis of fungal microbiome and alters some metabolic pathways and expression of genes in the NT of human. Findings of our study might be helpful for developing microbiome-based diagnostics, and also devising appropriate therapeutic regimens including antifungal drugs for prevention and control of concurrent fungal coinfections in COVID-19 patients.\n\nAuthor summaryThe SARS-CoV-2 is a highly transmissible and pathogenic betacoronavirus that primarily enters into the human body through NT to cause fearsome COVID-19 disease. Recent high throughput sequencing and downstream bioinformatic analyses revealed that microbiome dysbiosis associated with SARS-CoV-2 infection are not limited to bacteria, and fungi are also implicated in COVID-19 development in susceptible individuals. This study demonstrates that SARS-CoV-2 infection results in remarkable depletion of NT commensal fungal microbiomes with inclusion of various opportunistic fungal pathogens. We discussed the role of these altered fungal microbiomes in the pathophysiology of the SARS-CoV-2 infection. Our results suggest that dysbiosis in fungal microbiomes and associated altered metabolic functional pathways (or genes) possibly play a determining role in the progression of SARS-CoV-2 pathogenesis. Thus, the identifiable changes in the diversity and composition of the NT fungal population and their related genomic features demonstrated in this study might lay a foundation for better understanding of the underlying mechanism of co-pathogenesis, and the ongoing development of therapeutic agents including antifungal drugs for the resolution of COVID-19 pandemic.", - "rel_num_authors": 7, + "rel_link": "https://biorxiv.org/cgi/content/short/2022.02.17.480826", + "rel_abs": "Since the start of COVID-19 pandemic, Pakistan has experienced four waves of pandemic. The fourth wave ended in October, 2021 while the fifth wave of pandemic starts in January, 2022. The data regarding the circulating strains after the fourth wave of pandemic from Pakistan is not available. The current study explore the genomic diversity of SARS-CoV-2 after fourth wave and before fifth wave of pandemic through whole genome sequencing. The results showed the circulation of different strains of SARS-CoV-2 during November-December, 2021. We have Omicron BA.1 (n=4), Lineage A (n=2) and delta AY.27 (n=1) variants of SARS-CoV-2 in the population of Islamabad. All the isolates harbors characteristics mutations of omicron and delta variant in the genome. The lineage A isolate harbors a nine amino acid (68-76) and a ten amino acid (679-688) deletion in the genome. The circulation of omicron in the population before the fifth wave of pandemic and subsequent upsurges of COVID-19 positive cases in Pakistan highlights the importance of genomic surveillance.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "M. Nazmul Hoque", - "author_inst": "Bangabandhu Sheikh Mujibur Rahman Agricultural University" + "author_name": "Nazish Badar", + "author_inst": "National Institute of Health" }, { - "author_name": "M. Shaminur Rahman", - "author_inst": "Jessore Science and Technology University: Jessore University of Science and Technology" + "author_name": "Aamir Ikram", + "author_inst": "National Institute of Health" }, { - "author_name": "Md. Murshed Hasan Sarkar", - "author_inst": "Bangladesh Council of Scientific and Industrial Research" + "author_name": "Muhammad Salman", + "author_inst": "National Institute of Health" }, { - "author_name": "Md Ahashan Habib", - "author_inst": "Bangladesh Council of Scientific and Industrial Research" + "author_name": "Massab Umair", + "author_inst": "National Institute of Health" }, { - "author_name": "M. Anwar Hossain", - "author_inst": "Jessore University of Science and Technology" + "author_name": "Zaira Rehman", + "author_inst": "National Institute of Health" }, { - "author_name": "M. Salim Khan", - "author_inst": "Bangladesh Council of Scientific and Industrial Research" + "author_name": "Abdul Ahad", + "author_inst": "National Institute of Health" }, { - "author_name": "Tofazzal Islam", - "author_inst": "Bangabandhu Sheikh Mujibur Rahman Agricultural University" + "author_name": "Hamza ahmed Mirza", + "author_inst": "National Institute of Health" + }, + { + "author_name": "Masroor Alam", + "author_inst": "National Institute of Health" + }, + { + "author_name": "Nayyab Mehmood", + "author_inst": "National Institute of Health" + }, + { + "author_name": "Uzma Bashir aamir", + "author_inst": "World Health Organisation Pakistan" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nd", "type": "new results", - "category": "microbiology" + "category": "molecular biology" }, { "rel_doi": "10.1101/2022.02.18.480994", @@ -377916,91 +377595,71 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2022.02.16.480524", - "rel_title": "Experimental infection of mink with SARS-COV-2 Omicron (BA.1) variant leads to symptomatic disease with lung pathology and transmission", - "rel_date": "2022-02-16", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.02.16.480524", - "rel_abs": "We report an experimental infection of American mink with SARS-CoV-2 Omicron variant and show that minks remain virus RNA positive for days, develop clinical signs and histopathological changes, and transmit the virus to uninfected recipients warranting further studies and preparedness.", - "rel_num_authors": 18, + "rel_doi": "10.1101/2022.02.11.22270848", + "rel_title": "Strength and durability of antibody responses to BNT162b2 and CoronaVac", + "rel_date": "2022-02-15", + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2022.02.11.22270848", + "rel_abs": "We studied 2780 adults in Hong Kong who received CoronaVac inactivated virus vaccine (Sinovac) and BNT162b2 mRNA vaccine (\"Comirnaty\", BioNTech/Fosun Pharma). We found stronger and more durable antibody responses to two doses of the mRNA vaccine, and slightly stronger initial antibody responses to each vaccine in younger adults and women.", + "rel_num_authors": 13, "rel_authors": [ { - "author_name": "Jenni Virtanen", - "author_inst": "University of Helsinki" - }, - { - "author_name": "Kirsi Aaltonen", - "author_inst": "University of Helsinki" - }, - { - "author_name": "Kristel Kegler", - "author_inst": "University of Helsinki" - }, - { - "author_name": "Vinaya Venkat", - "author_inst": "University of Helsinki" - }, - { - "author_name": "Thanakorn Niamsap", - "author_inst": "University of Helsinki" - }, - { - "author_name": "Lauri Kareinen", - "author_inst": "University of Helsinki" + "author_name": "Benjamin J. Cowling", + "author_inst": "The University of Hong Kong" }, { - "author_name": "Rasmus Malmgren", - "author_inst": "University of Helsinki" + "author_name": "Irene O. L. Wong", + "author_inst": "The University of Hong Kong" }, { - "author_name": "Olga Kivela", - "author_inst": "University of Helsinki" + "author_name": "Eunice Y. C. Shiu", + "author_inst": "The University of Hong Kong" }, { - "author_name": "Nina Atanasova", - "author_inst": "University of Helsinki and Finnish Meteorological Institute" + "author_name": "Amber Y. T. Lai", + "author_inst": "The University of Hong Kong" }, { - "author_name": "Pamela Osterlund", - "author_inst": "Finnish Institute for Health and Welfare" + "author_name": "Samuel M. S. Cheng", + "author_inst": "The University of Hong Kong" }, { - "author_name": "Teemu Smura", - "author_inst": "University of Helsinki" + "author_name": "Sara Chaothai", + "author_inst": "The University of Hong Kong" }, { - "author_name": "Antti Sukura", - "author_inst": "University of Helsinki" + "author_name": "Kelvin K. H. Kwan", + "author_inst": "The University of Hong Kong" }, { - "author_name": "Tomas Strandin", - "author_inst": "University of Helsinki" + "author_name": "Mario Martin-Sanchez", + "author_inst": "The University of Hong Kong" }, { - "author_name": "Lara Dutra", - "author_inst": "University of Helsinki" + "author_name": "Leo L. M. Poon", + "author_inst": "The University of Hong Kong" }, { - "author_name": "Olli Vapalahti", - "author_inst": "University of Helsinki" + "author_name": "Dennis K. M. Ip", + "author_inst": "The University of Hong Kong" }, { - "author_name": "Heli Nordgren", - "author_inst": "University of Helsinki" + "author_name": "Gabriel M. Leung", + "author_inst": "The University of Hong Kong" }, { - "author_name": "Ravi Kant", - "author_inst": "University of Helsinki" + "author_name": "Nancy H. L. Leung", + "author_inst": "The University of Hong Kong" }, { - "author_name": "Tarja Sironen", - "author_inst": "Haartman Institute, University of Helsinki" + "author_name": "Malik Peiris", + "author_inst": "The University of Hong Kong" } ], "version": "1", - "license": "cc_no", - "type": "new results", - "category": "microbiology" + "license": "cc_by_nd", + "type": "PUBLISHAHEADOFPRINT", + "category": "infectious diseases" }, { "rel_doi": "10.1101/2022.02.13.22270825", @@ -380042,89 +379701,57 @@ "category": "transplantation" }, { - "rel_doi": "10.1101/2022.02.14.480460", - "rel_title": "A live-attenuated SARS-CoV-2 vaccine candidate with accessory protein deletions", + "rel_doi": "10.1101/2022.02.14.480430", + "rel_title": "A global lipid map reveals host dependency factors conserved across SARS-CoV-2 variants", "rel_date": "2022-02-15", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.02.14.480460", - "rel_abs": "We report a live-attenuated SARS-CoV-2 vaccine candidate with (i) re-engineered viral transcriptional regulator sequences and (ii) deleted open-reading-frames (ORF) 3, 6, 7, and 8 ({Delta}3678). The {Delta}3678 virus replicates about 7,500-fold lower than wild-type SARS-CoV-2 on primary human airway cultures, but restores its replication on interferon-deficient Vero-E6 cells that are approved for vaccine production. The {Delta}3678 virus is highly attenuated in both hamster and K18-hACE2 mouse models. A single-dose immunization of the {Delta}3678 virus protects hamsters from wild-type virus challenge and transmission. Among the deleted ORFs in the {Delta}3678 virus, ORF3a accounts for the most attenuation through antagonizing STAT1 phosphorylation during type-I interferon signaling. We also developed an mNeonGreen reporter {Delta}3678 virus for high-throughput neutralization and antiviral testing. Altogether, the results suggest that {Delta}3678 SARS-CoV-2 may serve as a live-attenuated vaccine candidate and a research tool for potential biosafety level-2 use.", - "rel_num_authors": 18, + "rel_link": "https://biorxiv.org/cgi/content/short/2022.02.14.480430", + "rel_abs": "A comprehensive understanding of host dependency factors for SARS-CoV-2 remains elusive. We mapped alterations in host lipids following SARS-CoV-2 infection using nontargeted lipidomics. We found that SARS-CoV-2 rewires host lipid metabolism, altering 409 lipid species up to 64-fold relative to controls. We correlated these changes with viral protein activity by transfecting human cells with each viral protein and performing lipidomics. We found that lipid droplet plasticity is a key feature of infection and that viral propagation can be blocked by small-molecule glycerolipid biosynthesis inhibitors. We found that this inhibition was effective against the main variants of concern (alpha, beta, gamma, and delta), indicating that glycerolipid biosynthesis is a conserved host dependency factor that supports this evolving virus.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Yang Liu", - "author_inst": "UTMB" - }, - { - "author_name": "Xianwen Zhang", - "author_inst": "UTMB" - }, - { - "author_name": "Jianying Liu", - "author_inst": "UTMB" - }, - { - "author_name": "Hongjie Xia", - "author_inst": "UTMB" - }, - { - "author_name": "Jing Zou", - "author_inst": "UTMB" - }, - { - "author_name": "Antonio E. Muruato", - "author_inst": "UTMB" - }, - { - "author_name": "Sivakumar Periasamy", - "author_inst": "UTMB" - }, - { - "author_name": "Jessica A. Plante", - "author_inst": "UTMB" - }, - { - "author_name": "Nathen E. Bopp", - "author_inst": "UTMB" + "author_name": "Scotland E Farley", + "author_inst": "Oregon Health and Science University" }, { - "author_name": "Chaitanya Kurhade", - "author_inst": "UTMB" + "author_name": "Jennifer Kyle", + "author_inst": "Pacific Northwest National Laboratories" }, { - "author_name": "Alexander Bukreyev", - "author_inst": "UTMB" + "author_name": "Hans Leier", + "author_inst": "Oregon Health and Science University" }, { - "author_name": "Ping Ren", - "author_inst": "UTMB" + "author_name": "Lisa M Bramer", + "author_inst": "Pacific Northwest National Laboratories" }, { - "author_name": "Tian Wang", - "author_inst": "UTMB" + "author_name": "Jules Weinstein", + "author_inst": "Oregon Health and Science University" }, { - "author_name": "Vineet D. Menachery", - "author_inst": "UTMB" + "author_name": "Timothy A Bates", + "author_inst": "Oregon Health & Science University" }, { - "author_name": "Kenneth S. Plante", - "author_inst": "UTMB" + "author_name": "Joon-Yong Lee", + "author_inst": "Pacific Northwest National Laboratory" }, { - "author_name": "Xuping Xie", - "author_inst": "UTMB" + "author_name": "Thomas O Metz", + "author_inst": "Pacific Northwest National Laboratories" }, { - "author_name": "Scott C. Weaver", - "author_inst": "UTMB" + "author_name": "Carsten Schultz", + "author_inst": "OHSU" }, { - "author_name": "Pei-Yong Shi", - "author_inst": "UTMB" + "author_name": "Fikadu Tafesse", + "author_inst": "Oregon Health and Science University" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "new results", "category": "microbiology" }, @@ -381976,143 +381603,111 @@ "category": "rheumatology" }, { - "rel_doi": "10.1101/2022.02.10.22270471", - "rel_title": "POST-ACUTE SEQUELAE AND ADAPTIVE IMMUNE RESPONSES IN PEOPLE LIVING WITH HIV RECOVERING FROM SARS-COV-2 INFECTION", + "rel_doi": "10.1101/2022.02.13.22270896", + "rel_title": "Comprehensive humoral and cellular immune responses to SARS-CoV-2 variants in diverse Chinese populations: A benefit perspective of national vaccination", "rel_date": "2022-02-14", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.02.10.22270471", - "rel_abs": "BackgroundLimited data are available on the long-term clinical and immunologic consequences of SARS-CoV-2 infection in people with HIV (PWH).\n\nMethodsWe measured SARS-CoV-2 specific humoral and cellular responses in people with and without HIV recovering from COVID-19 (n=39 and n=43, respectively) using binding antibody, surrogate virus neutralization, intracellular cytokine staining, and inflammatory marker assays. We identified individuals experiencing post-acute sequelae of SARS-CoV-2 infection (PASC) and evaluated immunologic parameters. We used linear regression and generalized linear models to examine differences by HIV status in the magnitude of inflammatory and virus-specific antibody and T cell responses, as well as differences in the prevalence of PASC.\n\nResultsAmong PWH, we found broadly similar SARS-CoV-2-specific antibody and T cell responses as compared with a well-matched group of HIV-negative individuals. PWH had 70% lower relative levels of SARS-CoV-2 specific memory CD8+ T cells (p=0.007) and 53% higher relative levels of PD-1+ SARS-CoV-2 specific CD4+ T cells (p=0.007). Higher CD4/CD8 ratio was associated with lower PD-1 expression on SARS-CoV-2 specific CD8+ T cells (0.34-fold effect, p=0.02). HIV status was strongly associated with PASC (odds ratio 4.01, p=0.008), and levels of certain inflammatory markers (IL-6, TNF-alpha, and IP-10) were associated with persistent symptoms.\n\nConclusionsWe identified potentially important differences in SARS-CoV-2 specific CD4+ and CD8+ T cells in PWH and HIV-negative participants that might have implications for long-term immunity conferred by natural infection. HIV status strongly predicted the presence of PASC. Larger and more detailed studies of PASC in PWH are urgently needed.", - "rel_num_authors": 31, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.02.13.22270896", + "rel_abs": "The emerging SARS-CoV-2 variants have made great challenges to current vaccine and pandemic control strategies. B.1.1.529 (Omicron), which was classified as a variant of concern (VOC) by the World Health Organization on November 26th, 2021, has quickly become the dominant circulating variant and causing waves of infections. It is urgent to understand the current immune status of the general population given that pre-existing immunity has been established by national vaccination or exposure to past variants. Using sera from 85 individuals (including 21 convalescents of natural infection, 15 cases suffered a breakthrough infection after vaccination, and 49 vaccinated participants without infection history), we showed that the cross-neutralizing activity against VOCs such as Omicron can be detected in 53 (62.4%) cases, although less potent than against the Wuhan-1 strain (WT), with a 3.9-fold reduction in geometric mean neutralizing titer (GMT) (130.7, 95% CI 88.4-193.3 vs 506, 355.8-719.7, respectively). Subgroup analysis revealed significantly enhanced neutralizing activity against WT and VOCs in Delta convalescent sera. The neutralizing antibodies against Omicron were detectable in 75% of convalescents and 44.9% of healthy donors (p = 0.006), with a GMT of 289.5, 180.9-463.3 and 42.6, 31.3-59, respectively. However, the protective effect against VOCs was weaker in young convalescents (aged < 18y), with a detectable rate of 50% and a GMT of 46.4 against Omicron, similar to vaccinees. The pan-sarbecovirus neutralizing activities were not observed in vaccinated SARS-CoV-1 survivors. A booster dose significantly increased the breadth and magnitude of neutralization against WT and VOCs to different degrees than full vaccination. In addition, we showed that COVID-19 inactivated vaccines can elicit Omicron-specific T cell responses. The positive rates of ELISpot reactions were 26.7% (4/15) and 43.8% (7/16) in the full vaccination group and the booster vaccination group, respectively. The neutralizing antibody titers declined while T-cell responses remain robust over 6 months. These findings will inform the optimization of public health vaccination and intervention strategies to protect diverse populations against SARS-CoV-2 variants.", + "rel_num_authors": 23, "rel_authors": [ { - "author_name": "Michael J Peluso", - "author_inst": "University of California, San Francisco" - }, - { - "author_name": "Matthew A Spinelli", - "author_inst": "University of California, San Francisco" - }, - { - "author_name": "Tyler-Marie Deveau", - "author_inst": "University of California, San Francisco" - }, - { - "author_name": "Carrie A Forman", - "author_inst": "University of California, San Francisco" - }, - { - "author_name": "Sadie E Munter", - "author_inst": "University of California, San Francisco" - }, - { - "author_name": "Sujata Mathur", - "author_inst": "University of California, San Francisco" - }, - { - "author_name": "Alex F Tang", - "author_inst": "University of California, San Francisco" + "author_name": "Jiwei Li", + "author_inst": "Department of Respiratory, Critical Care and Sleep Medicine, Xiang'an Hospital of Xiamen University, Xiamen, Fujian, China; School of Medicine, Xiamen Universit" }, { - "author_name": "Scott Lu", - "author_inst": "University of California, San Francisco" + "author_name": "Jing Wu", + "author_inst": "Department of Respiratory, Critical Care and Sleep Medicine, Xiang'an Hospital of Xiamen University, Xiamen, Fujian, China; School of Medicine, Xiamen Universit" }, { - "author_name": "Sarah A Goldberg", - "author_inst": "University of California, San Francisco" + "author_name": "Qiuyue Long", + "author_inst": "Department of Respiratory, Critical Care and Sleep Medicine, Xiang'an Hospital of Xiamen University, Xiamen, Fujian, China; School of Medicine, Xiamen Universit" }, { - "author_name": "Mireya I Arreguin", - "author_inst": "University of California, San Francisco" + "author_name": "Yanan Wu", + "author_inst": "Department of Clinical Laboratory, Xiang'an Hospital of Xiamen University, Xiamen, Fujian, China" }, { - "author_name": "Rebecca Hoh", - "author_inst": "University of California, San Francisco" + "author_name": "Xiaoyi Hu", + "author_inst": "Department of Respiratory, Critical Care and Sleep Medicine, Xiang'an Hospital of Xiamen University, Xiamen, Fujian, China; School of Medicine, Xiamen Universit" }, { - "author_name": "Viva Tai", - "author_inst": "University of California, San Francisco" + "author_name": "Yukun He", + "author_inst": "Department of Respiratory and Critical Care Medicine, Peking University People's Hospital, Beijing, China" }, { - "author_name": "Jessica Y Chen", - "author_inst": "University of California, San Francisco" - }, - { - "author_name": "Enrique O. Martinez", - "author_inst": "University of California, San Francisco" - }, - { - "author_name": "Ahmed Chenna", - "author_inst": "Monogram Biosciences" + "author_name": "Mingzheng Jiang", + "author_inst": "Department of Respiratory, Critical Care and Sleep Medicine, Xiang'an Hospital of Xiamen University, Xiamen, Fujian, China; School of Medicine, Xiamen Universit" }, { - "author_name": "John W Winslow", - "author_inst": "Monogram Biosciences" + "author_name": "Jia Li", + "author_inst": "Department of Respiratory and Critical Care Medicine, Peking University People's Hospital, Beijing, China" }, { - "author_name": "Christos J Petropoulos", - "author_inst": "Monogram Biosciences" + "author_name": "Lili Zhao", + "author_inst": "Department of Respiratory and Critical Care Medicine, Peking University People's Hospital, Beijing, China" }, { - "author_name": "Alessandro Sette", - "author_inst": "University of California, San Diego" + "author_name": "Shuoqi Yang", + "author_inst": "School of Medicine, Xiamen University, Xiamen, Fujian, China; Department of Thoracic Surgery, Xiang'an Hospital of Xiamen University, Xiamen, Fujian, China" }, { - "author_name": "Daniella Weiskopf", - "author_inst": "University of California, San Diego" + "author_name": "Xiaoyong Chen", + "author_inst": "Department of Respiratory, Critical Care and Sleep Medicine, Xiang'an Hospital of Xiamen University, Xiamen, Fujian, China" }, { - "author_name": "Nitasha Kumar", - "author_inst": "University of California, San Francisco" + "author_name": "Minghui Wang", + "author_inst": "Department of Respiratory, Critical Care and Sleep Medicine, Xiang'an Hospital of Xiamen University, Xiamen, Fujian, China" }, { - "author_name": "Kara L Lynch", - "author_inst": "University of California, San Francisco" + "author_name": "Jianshi Zheng", + "author_inst": "Department of Respiratory, Critical Care and Sleep Medicine, Xiang'an Hospital of Xiamen University, Xiamen, Fujian, China" }, { - "author_name": "Peter W Hunt", - "author_inst": "University of California, San Francisco" + "author_name": "Fangfang Wu", + "author_inst": "Department of Respiratory, Critical Care and Sleep Medicine, Xiang'an Hospital of Xiamen University, Xiamen, Fujian, China" }, { - "author_name": "Matthew S Durstenfeld", - "author_inst": "University of California, San Francisco" + "author_name": "Ruiliang Wu", + "author_inst": "Department of Respiratory, Critical Care and Sleep Medicine, Xiang'an Hospital of Xiamen University, Xiamen, Fujian, China" }, { - "author_name": "Priscilla Y Hsue", - "author_inst": "University of California, San Francisco" + "author_name": "Lihong Ren", + "author_inst": "Department of Pediatrics, Xiang'an Hospital of Xiamen University, Xiamen, Fujian, China" }, { - "author_name": "J Daniel Kelly", - "author_inst": "University of California, San Francisco" + "author_name": "Liang Bu", + "author_inst": "Department of Thoracic Surgery, Xiang'an Hospital of Xiamen University, Xiamen, Fujian, China" }, { - "author_name": "Jeffrey N Martin", - "author_inst": "University of California, San Francisco" + "author_name": "Houzhao Wang", + "author_inst": "Department of Clinical Laboratory, Xiang'an Hospital of Xiamen University, Xiamen, Fujian, China" }, { - "author_name": "David V Glidden", - "author_inst": "University of California, San Francisco" + "author_name": "Ke Li", + "author_inst": "Department of Critical Care Medicine, Xiang'an Hospital of Xiamen University, Xiamen, Fujian, China" }, { - "author_name": "Monica Gandhi", - "author_inst": "University of California, San Francisco" + "author_name": "Lijuan Fu", + "author_inst": "Department of Infectious Diseases, Xiang'an Hospital of Xiamen University, Xiamen, Fujian, China" }, { - "author_name": "Steven G Deeks", - "author_inst": "University of California, San Francisco" + "author_name": "Guojun Zhang", + "author_inst": "Cancer Research Center and the Department of Breast-Thyroid-Surgery, Xiang'an Hospital of Xiamen University, Xiamen, Fujian, China" }, { - "author_name": "Rachel L Rutishauser", - "author_inst": "University of California, San Francisco" + "author_name": "Yali Zheng", + "author_inst": "Department of Respiratory, Critical Care and Sleep Medicine, Xiang'an Hospital of Xiamen University, Xiamen, Fujian, China" }, { - "author_name": "Timothy J Henrich", - "author_inst": "University of California, San Francisco" + "author_name": "Zhancheng Gao", + "author_inst": "Department of Respiratory, Critical Care and Sleep Medicine, Xiang'an Hospital of Xiamen University, Xiamen, Fujian, China; Department of Respiratory and Critic" } ], "version": "1", "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "hiv aids" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2022.02.10.22270789", @@ -383898,31 +383493,43 @@ "category": "bioinformatics" }, { - "rel_doi": "10.1101/2022.02.11.480029", - "rel_title": "Omicron (BA.1) and Sub-Variants (BA.1, BA.2 and BA.3) of SARS-CoV-2 Spike Infectivity and Pathogenicity: A Comparative Sequence and Structural-based Computational Assessment", + "rel_doi": "10.1101/2022.02.10.22270782", + "rel_title": "Impact of COVID-19 pandemic and anti-pandemic measures on tuberculosis, viral hepatitis, HIV/AIDS and malaria - a systematic review", "rel_date": "2022-02-11", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.02.11.480029", - "rel_abs": "The Omicron variant of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has now spread throughout the world. We used computational tools to assess the spike infectivity, transmission, and pathogenicity of Omicron (BA.1) and sub-variants (BA.1.1, BA.2, and BA.3) in this study. BA.1 has 39 mutations, BA.1.1 has 40 mutations, BA.2 has 31 mutations, and BA.3 has 34 mutations, with 21 shared mutations between all. We observed 11 common mutations in Omicrons receptor-binding domain and sub-variants. In pathogenicity analysis, the Y505H, N786K, T95I, N211I, N856K, and V213R mutations in omicron and sub-variants are predicted to be deleterious. Due to the major effect of the mutations characterising, in the receptor-binding domain (RBD), we found that Omicron and sub-variants had a higher positive electrostatic surface potential. This could increase interaction between RBD and electronegative human angiotensin-converting enzyme 2 (hACE2). Omicron and sub-variants had a higher affinity for hACE2 and the potential for increased transmission when compared to the wild type. Among Omicron sub-lineages, BA.2 and BA.3 have a higher transmission potential than BA.1 and BA.1.1. We predicted that mutated residues in BA.1.1 (K478), BA.2 (R400, R490, R495), and BA.3 (R397 and H499) formation of new salt bridges and hydrogen bonds. Omicron and sub-variant mutations at Receptor-binding Motif (RBM) residues such as Q493R, N501Y, Q498, T478K, and Y505H all contribute significantly to binding affinity with human ACE2. Interactions with Omicron variant mutations at residues 493, 496, 498, and 501 seem to restore ACE2 binding effectiveness lost due to other mutations like K417N and Y505H.", - "rel_num_authors": 3, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2022.02.10.22270782", + "rel_abs": "COVID-19 pandemic puts an enormous strain on health care systems worldwide and may have a detrimental effect on prevention, treatment and outcomes of tuberculosis (TB), viral hepatitis, HIV/AIDS and malaria, whose ending is part of the United Nations 2030 Agenda for Sustainable Development. We conducted a systematic review of scientific and grey literature in order to collect wide-ranging evidence with emphasis on quantification of the projected and actual indirect impacts of COVID-19 on the four infectious diseases with a global focus. We followed PRISMA guidelines and the protocol registered for malaria (CRD42021234974). We searched PubMed, Scopus, preView (last search: January 13, 2021) and websites of main (medical) societies and leading NGOs related to each of the four considered infectious diseases. The identified modelling studies warned about under-diagnosis (TB), anti-retroviral therapy interruption/decrease in viral load suppression (HIV), disruptions of insecticide-treated nets (ITN) distribution and access to effective treatment (malaria), and treatment delays and vaccination interruptions (viral hepatitis). The reported disruptions were very heterogeneous both between and within countries. If observed at several points in time, the initial drops (partly dramatic, e.g. TB notifications/cases, or HIV testing volumes decreased up to -80%) were followed by a gradual recovery. However, the often-missing assessment of the changes against the usual pre-pandemic fluctuations hampered the interpretation of less severe ones. Given the recurring waves of the pandemic and the unknown mid- to long-term effects of adaptation and normalisation, the real consequences for the fight against leading infectious diseases will only manifest over the coming years.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Suresh Kumar", - "author_inst": "Management & Science University" + "author_name": "Barbora Kessel", + "author_inst": "Helmholtz Centre for Infection Research" }, { - "author_name": "Kalimuthu Karuppanan", - "author_inst": "University of Oxford, UK" + "author_name": "Torben Heinsohn", + "author_inst": "Helmholtz Centre for Infection Research" }, { - "author_name": "Gunasekaran Subramaniam", - "author_inst": "University of Oxford, Oxford, UK" + "author_name": "J\u00f6rdis J Ott", + "author_inst": "Helmholty centre for Infection Research and Hannover Medical School (MHH)" + }, + { + "author_name": "Jutta Wolff", + "author_inst": "Hannover Medical School (MHH)" + }, + { + "author_name": "Max J Hassenstein", + "author_inst": "Helmholtz Centre for Infection research and PhD Programme \"Epidemiology\" Braunschweig-Hannover" + }, + { + "author_name": "Berit Lange", + "author_inst": "Helmholtz Centre for Infection Research and German Center for Infection research (DZIF), partner site Hannover-Braunschweig" } ], "version": "1", - "license": "cc_by_nc_nd", - "type": "new results", - "category": "bioinformatics" + "license": "cc_by_nc", + "type": "PUBLISHAHEADOFPRINT", + "category": "public and global health" }, { "rel_doi": "10.1101/2022.02.10.480017", @@ -385683,39 +385290,63 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2022.02.07.22270640", - "rel_title": "The interaction effect between hemoglobin and hypoxemia on COVID-19 mortality in a sample from Bogota, Colombia: An exploratory study.", + "rel_doi": "10.1101/2022.02.08.22270666", + "rel_title": "Monitoring SARS-CoV-2 in wastewater during New York City's second wave of COVID-19: Sewershed-level trends and relationships to publicly available clinical testing data", "rel_date": "2022-02-09", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.02.07.22270640", - "rel_abs": "PurposeWe aimed to assess the effect of hemoglobin (Hb) concentration and oxygenation index on COVID-19 patients mortality risk.\n\nPatients and methodsWe retrospectively reviewed sociodemographic and clinical characteristics, laboratory findings, and clinical outcomes from patients admitted to a tertiary care hospital in Bogota, Colombia. We assessed exploratory associations between oxygenation index and Hb concentration at admission and clinical outcomes. We used a generalized additive model (GAM) to evaluate the nonlinear relations observed and the classification and regression trees (CART) algorithm to assess the interaction effects found.\n\nResultsFrom March to July 2020, 643 patients were admitted, of which 52% were male. The median age was 60 years old, and the most frequent comorbidity was hypertension (35.76%). The median value of SpO2/FiO2 was 419, and the median Hb concentration was 14.8 g/dL. The mortality was 19.1% (123 patients). Age, sex, and history of hypertension were independently associated with mortality. We described a nonlinear relationship between SpO2/FiO2, Hb concentration and neutrophil-to-lymphocyte ratio with mortality and an interaction effect between SpO2/FiO2 and Hb concentration. Patients with a similar oxygenation index had different mortality likelihoods based upon their Hb at admission. CART showed that patients with SpO2/FiO2 < 324, who were older than 62 years, and had an Hb of [≥] 16 g/dl had the highest mortality risk (96%). Additionally, patients with SpO2/FiO2 > 324 but Hb of < 12 and neutrophil-to-lymphocyte ratio of > 4 had a higher mortality likelihood (57%). In contrast, patients with SpO2/FiO2 > 324 and Hb of > 12 g/dl had the lowest mortality risk (10%).\n\nConclusionWe found that a decreased SpO2/FiO2 increased mortality risk. Extreme values of Hb, either low or high, showed an increase in likelihood of mortality. However, Hb concentration modified the SpO2/FiO2 effect on mortality; the likelihood of death in patients with low SpO2/FiO2 increased as Hb increased.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.02.08.22270666", + "rel_abs": "New York Citys ongoing wastewater monitoring program tracked trends in sewershed-level SARS-CoV-2 loads starting in the fall of 2020, just before the start of the Citys second wave of the COVID-19 outbreak. During a five-month study period, from November 8, 2020 to April 11, 2021, viral loads in influent wastewater from each of New York Citys 14 wastewater treatment plants were measured and compared to new laboratory-confirmed COVID-19 cases for the populations in each corresponding sewershed, estimated from publicly available clinical testing data. We found significant positive correlations between viral loads in wastewater and new COVID-19 cases. The strength of the correlations varied depending on the sewershed, with Spearmans rank correlation coefficients ranging between 0.38 and 0.81 (mean = 0.55). Based on a linear regression analysis of a combined data set for New York City, we found that a 1 log10 change in the SARS-CoV-2 viral load in wastewater corresponded to a 0.6 log10 change in the number of new laboratory-confirmed COVID-19 cases/day in a sewershed. An estimated minimum detectable case rate between 2 - 8 cases/day/100,000 people was associated with the method limit of detection in wastewater. This work offers a preliminary assessment of the relationship between wastewater monitoring data and clinical testing data in New York City. While routine monitoring and method optimization continue, information on the development of New York Citys ongoing wastewater monitoring program may provide insights for similar wastewater-based epidemiology efforts in the future.", + "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Andr\u00e9s Felipe Pati\u00f1o-Aldana", - "author_inst": "Universidad del Rosario: Universidad Del Rosario" + "author_name": "Catherine Hoar", + "author_inst": "Department of Civil and Urban Engineering, New York University Tandon School of Engineering Brooklyn, NY, USA" }, { - "author_name": "\u00c1ngela Mar\u00eda Ru\u00edz Sternberg", - "author_inst": "Universidad Del Rosario Escuela de Medicina y Ciencias de la Salud" + "author_name": "Francoise Chauvin", + "author_inst": "New York City Department of Environmental Protection, New York, NY, USA" }, { - "author_name": "Angela Maria Pinzon-Rondon", - "author_inst": "Universidad Del Rosario" + "author_name": "Alexander Clare", + "author_inst": "New York City Department of Environmental Protection, New York, NY, USA" }, { - "author_name": "Nicolas Molano-Gonz\u00e1lez", - "author_inst": "Universidad del Rosario: Universidad Del Rosario" + "author_name": "Hope McGibbon", + "author_inst": "New York City Department of Environmental Protection, New York, NY, USA" }, { - "author_name": "David Ren\u00e9 Rodr\u00edguez-Lima", - "author_inst": "M\u00e9deri: Hospital Universitario Mayor" + "author_name": "Esmeraldo Castro", + "author_inst": "New York City Department of Environmental Protection, New York, NY, USA" + }, + { + "author_name": "Samantha Patinella", + "author_inst": "New York City Department of Environmental Protection, New York, NY, USA" + }, + { + "author_name": "Dimitrios Katehis", + "author_inst": "New York City Department of Environmental Protection, New York, NY, USA" + }, + { + "author_name": "John J Dennehy Jr.", + "author_inst": "Biology Department, Queens College, The City University of New York, Queens, NY USA; Biology Doctoral Program, The Graduate Center, The City University of New Y" + }, + { + "author_name": "Monica Trujillo", + "author_inst": "Department of Biology, Queensborough Community College, The City University of New York, Bayside, NY, USA" + }, + { + "author_name": "Davida S. Smyth", + "author_inst": "Department of Natural Sciences and Mathematics, Eugene Lang College of Liberal Arts at The New School, New York, NY, USA; present affiliation: Department of Lif" + }, + { + "author_name": "Andrea I. Silverman", + "author_inst": "Department of Civil and Urban Engineering, New York University Tandon School of Engineering Brooklyn, NY, USA" } ], "version": "1", - "license": "cc_by", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2022.02.08.22270636", @@ -387869,29 +387500,29 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.02.07.22270490", - "rel_title": "Effectiveness of Covid-19 Vaccines against the SARS-COV-2-Delta (B.1.617.2) in China-A Real World Study", + "rel_doi": "10.1101/2022.02.05.22269707", + "rel_title": "Acoustic Epidemiology in Pulmonary Tuberculosis & Covid19 leveraging Explainable AI/ML", "rel_date": "2022-02-08", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.02.07.22270490", - "rel_abs": "AbstractsO_ST_ABSBackgroundC_ST_ABSSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) delta (B.1.617.2) variant is highly transmissible and has contributed to a surge in cases globally. This study aimed to explore the potential of vaccines against SARS-CoV-2 delta (B.1.617.2) variant in China.\n\nMethodsIn this real-world study, all data were extracted from Xian Chest Hospital. Confirmed cases infected with Delta VOC with exact date of positive viral testing were included for analysis. Patients meeting the study criteria were divided into unvaccinated and partially vaccinated (one dose), full vaccinated (two doses), and booster vaccination of COVID-19.\n\nResultsA total of 455 cases were enrolled in this study. Proportion of severe and critical cases in full vaccinated cases (1.82%) and cases with booster vaccination (1.35%) of COVID-19 were much lower than that of unvaccinated and partially vaccinated cases (8.16%). In addition, cases with booster vaccination (12.78 days) and full vaccinated cases (12.59 days) showed shorter duration of viral shedding than that in unvaccinated and partially vaccinated cases (13.87 days).\n\nConclusionThis is the first real world study indicating that Covid-19 vaccines showed much powerful effectiveness against the SARS-COV-2-Delta (B.1.617.2) in China, including lowing the proportion of severe illness and shorting the virus shedding time.", + "rel_link": "https://medrxiv.org/cgi/content/short/2022.02.05.22269707", + "rel_abs": "Involuntary cough is a prominent symptom for many a Lung Ailments ranging from Infectious to non-Infectious diseases. Early research around human cough established that the spectral signatures do not vary between Involuntary and Voluntary coughs. The study aimed at evaluating voluntary human cough sounds recorded under a stringent clinical protocol. Indias ambitious goal to eliminate and eradicate TB by 2025 shall be facilitated by Machine Learning tools that address subjectivity in that the healthcare worker can now take the solution as a screening modality to the last mile as a part of outreach programs without having to rely on infrastructure & connectivity. In this paper we present the findings of Clinical Trials for Pulmonary TB registered at CTRI/2019/02/017672 conducted independently and included Covid19 during the pandemic as a part of Bi-Directional screening modality. The reference standards used were CBNAAT (Cartridge based nucleic acid amplification test) & CXR (Chest X-Ray) for TB while for Covid19; RT-PCR was used as the reference standard. As a non-invasive and contactless screening modality, a sophisticated third party Microphone Array was used to record the cough under a stringent infection control protocol. Sensitivity achieved across the sites for TB ranged between 80% - 83% and Specificity was to the tune of 92% while using CBNAAT as a reference standard. CXR when used as a reference standard for TB achieved a sensitivity and specificity of 59% and 60% respectively. Covid19 achieved a sensitivity & specificity of 92% and 96% while using RT-PCR as the reference standard. The study was primarily focused on the Frequency domain that paved way for feature extraction and explainable Machine Learning Models operating upon lossless WAV files hypothesizing acoustic theory and demographic inputs. The solution titled \"TimBre\" can now be added to the healthcare workers arsenal in situations where a RT-PCR or CXR is not available and seamlessly conduct bi-directional screening with a single recording of cough and also offer insights into Non-Communicable diseases as a part of differential diagnosis.", "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Xinge Ma", - "author_inst": "The First Affiliated Hospital of Xi'an Jiaotong University" + "author_name": "rahul pathri", + "author_inst": "docturnal" }, { - "author_name": "Jianfeng Han", - "author_inst": "The First Affiliated Hospital of Xi'an Jiaotong University" + "author_name": "Shekhar Jha", + "author_inst": "Docturnal" }, { - "author_name": "Hongxia Li", - "author_inst": "The First Affiliated Hospital of Xi'an Jiaotong University" + "author_name": "samarth tandon", + "author_inst": "Docturnal" }, { - "author_name": "Chang Liu", - "author_inst": "The First Affiliated Hospital of Xi'an Jiaotong University" + "author_name": "Suryakanth Gangashetty", + "author_inst": "KL University" } ], "version": "1", @@ -389887,39 +389518,35 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.02.07.22270614", - "rel_title": "Chronic Disease and Workforce Participation Among Medicaid Enrollees Over 50: The Potential Impact of Medicaid Work Requirements Post-COVID-19", - "rel_date": "2022-02-08", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.02.07.22270614", - "rel_abs": "As the COVID-19 pandemic wanes, states may reintroduce Medicaid work requirements to reduce enrollment. Using the Health and Retirement Study, we evaluated chronic disease burden among beneficiaries aged >50 (n=1460) who might be impacted by work requirements (i.e. working <20 hours per week). Seven of eight chronic conditions evaluated were associated with reduced workforce participation, including history of stroke (OR: 7.35; 95% CI: 2.98-18.14) and lung disease (OR: 4.39; 95% CI: 2.97-7.47). Those with more severe disease were also more likely to work fewer hours. Medicaid work requirements would likely have great impact on older beneficiaries with significant disease burden.\n\nKey PointsO_LIChronic disease linked to reduced work among older Medicaid beneficiaries.\nC_LIO_LIWork requirements would greatly impact those aged >50 with chronic conditions.\nC_LIO_LICoverage loss would have negative implications for long-term disease management.\nC_LI", - "rel_num_authors": 5, + "rel_doi": "10.1101/2022.02.04.479209", + "rel_title": "Comparative analysis of cell-cell communication at single-cell resolution", + "rel_date": "2022-02-07", + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2022.02.04.479209", + "rel_abs": "Inference of cell-cell communication (CCC) from single-cell RNA-sequencing data is a powerful technique to uncover putative axes of multicellular coordination, yet existing methods perform this analysis at the level of the cell type or cluster, discarding single-cell level information. Here we present Scriabin - a flexible and scalable framework for comparative analysis of CCC at single-cell resolution. We leverage multiple published datasets to show that Scriabin recovers expected CCC edges and use spatial transcriptomic data, genetic perturbation screens, and direct experimental manipulation of receptor-ligand interactions to validate that the recovered edges are biologically meaningful. We then apply Scriabin to uncover co-expressed programs of CCC from atlas-scale datasets, validating known communication pathways required for maintaining the intestinal stem cell niche and revealing species-specific communication pathways. Finally, we utilize single-cell communication networks calculated using Scriabin to follow communication pathways that operate between timepoints in longitudinal datasets, highlighting bystander cells as important initiators of inflammatory reactions in acute SARS-CoV-2 infection. Our approach represents a broadly applicable strategy to leverage single-cell resolution data maximally toward uncovering CCC circuitry and rich niche-phenotype relationships in health and disease.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Rodlescia Sneed", - "author_inst": "Michigan State University" - }, - { - "author_name": "Alexander Stubblefield", - "author_inst": "Michigan State University" + "author_name": "Aaron James Wilk", + "author_inst": "Stanford University" }, { - "author_name": "Graham Gardner", - "author_inst": "Michigan State University" + "author_name": "Alex K Shalek", + "author_inst": "MIT" }, { - "author_name": "Tamara Jordan", - "author_inst": "Michigan State University" + "author_name": "Susan P Holmes", + "author_inst": "Stanford University" }, { - "author_name": "Briana Mezuk", - "author_inst": "University of Michigan" + "author_name": "Catherine A Blish", + "author_inst": "Stanford University" } ], "version": "1", "license": "cc_no", - "type": "PUBLISHAHEADOFPRINT", - "category": "health policy" + "type": "new results", + "category": "cell biology" }, { "rel_doi": "10.1101/2022.02.04.479134", @@ -392185,67 +391812,47 @@ "category": "neurology" }, { - "rel_doi": "10.1101/2022.02.07.22270575", - "rel_title": "COVID-19 outbreaks in Australia during a period of high epidemic control, 2020", - "rel_date": "2022-02-07", + "rel_doi": "10.1101/2022.02.04.22270473", + "rel_title": "Minimizing school disruption under high incidence conditions due to the Omicron variant in early 2022", + "rel_date": "2022-02-06", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.02.07.22270575", - "rel_abs": "To describe characteristics of COVID-19 outbreaks in Australia to guide policy development for mitigation of future outbreaks, we conducted a retrospective analysis of COVID-19 outbreaks affecting two or more people reported to COVID-Net--an Australian national surveillance network--from 28 January until 27 December 2020. The COVID-Net surveillance network covered all Australian states and territories, with an estimated population of 25,649,985 persons as at 31 June 2020. We reported the epidemiology of COVID-19 outbreaks in Australia, including the setting in which they occurred, size, and duration.\n\n853 outbreaks of COVID-19 were reported; associated with 13,957 confirmed cases, of whom 2,047 were hospitalised, and 800 died. The pattern of outbreaks followed a similar trend to the epidemic in Australia, defined by two distinct peaks in mid-March and July. Victoria reported the greatest number of outbreaks across all settings aligned with the second wave of infections. Outbreaks most commonly occurred in the workplace/industry setting (22%, 190/853), followed by education (14%, 122/853), residential aged care (13%, 114/853) and hospitals (10%, 83/853). The majority (40%, 340/853) of outbreaks had 6 to 24 cases, and the median outbreak duration increased in proportion with the number of associated cases.\n\nThis report summarising COVID-19 outbreaks in Australia identifies settings of highest risk. Surveillance of outbreaks informs our understanding of transmission dynamics in Australia relative to national and jurisdictional interventions. For settings that are high risk for COVID-19, it is important to prioritise planning, surveillance, and implementation of control measures.", - "rel_num_authors": 12, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.02.04.22270473", + "rel_abs": "As record cases due to the Omicron variant are currently registered in Europe, schools remain a vulnerable setting suffering large disruption. Extending previous modeling of SARS-CoV-2 transmission in schools in France, we estimate that at high incidence rates reactive screening protocols (as currently applied in France) require comparable test resources as weekly screening (as currently applied in some Swiss cantons), for considerably lower control. Our findings can be used to define incidence levels triggering school protocols and optimizing their cost-effectiveness.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Freya G Hogarth", - "author_inst": "Australian Government Department of Health" - }, - { - "author_name": "Rachel Nye", - "author_inst": "Australian Government Department of Health" - }, - { - "author_name": "Nevada Pingault", - "author_inst": "Western Australia Department of Health: Government of Western Australia Department of Health" - }, - { - "author_name": "Simon Crouch", - "author_inst": "Victorian Department of Health" - }, - { - "author_name": "Cushla Coffey", - "author_inst": "Queensland Health" - }, - { - "author_name": "Kylie Smith", - "author_inst": "Tasmanian Health Service THS: Tasmania Department of Health" + "author_name": "Elisabetta Colosi", + "author_inst": "INSERM, Sorbonne Universit\u00e9, Pierre Louis Institute of Epidemiology and Public Health, Paris, France" }, { - "author_name": "Rowena Boyd", - "author_inst": "Northern Territory Department of Health and Community Services: Northern Territory Department of Health" + "author_name": "Giulia Bassignana", + "author_inst": "INSERM, Sorbonne Universit\u00e9, Pierre Louis Institute of Epidemiology and Public Health, Paris, France" }, { - "author_name": "Catherine Kelaher", - "author_inst": "Australian Government Department of Health" + "author_name": "Alain Barrat", + "author_inst": "Aix Marseille Univ, Universit\u00e9 de Toulon, CNRS, CPT, Turing Center for Living Systems, Marseille, France" }, { - "author_name": "Tracie Reinten", - "author_inst": "NSW Health: New South Wales Ministry of Health" + "author_name": "Bruno Lina", + "author_inst": "National Reference Center for Respiratory Viruses, Department of Virology, Infective Agents Institute, Croix-Rousse Hospital, Hospices Civils de Lyon, Lyon, Fra" }, { - "author_name": "Moira C Hewitt", - "author_inst": "Australian Government Department of Health" + "author_name": "Philippe Vanhems", + "author_inst": "Service d'Hygi\u00e8ne, \u00c9pid\u00e9miologie, Infectiovigilance et Pr\u00e9vention, Hospices Civils de Lyon, Lyon, France" }, { - "author_name": "Ben Polkinghorne", - "author_inst": "Australian National University" + "author_name": "Julia Bielicki", + "author_inst": "Paediatric Infectious Diseases, University of Basel Children's Hospital, Spitalstrasse 33, 4056, Basel, Switzerland" }, { - "author_name": "Martyn Kirk", - "author_inst": "Australian National University" + "author_name": "Vittoria Colizza", + "author_inst": "INSERM, Sorbonne Universit\u00e9, Pierre Louis Institute of Epidemiology and Public Health, Paris, France" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2022.02.04.22270413", @@ -394247,283 +393854,35 @@ "category": "bioinformatics" }, { - "rel_doi": "10.1101/2022.02.03.479037", - "rel_title": "mRNA-1273 or mRNA-Omicron boost in vaccinated macaques elicits comparable B cell expansion, neutralizing antibodies and protection against Omicron", + "rel_doi": "10.1101/2022.02.02.478897", + "rel_title": "Primary human macrophages exhibit a modest inflammatory response early in SARS-CoV-2 infection", "rel_date": "2022-02-04", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.02.03.479037", - "rel_abs": "SARS-CoV-2 Omicron is highly transmissible and has substantial resistance to antibody neutralization following immunization with ancestral spike-matched vaccines. It is unclear whether boosting with Omicron-specific vaccines would enhance immunity and protection. Here, nonhuman primates that received mRNA-1273 at weeks 0 and 4 were boosted at week 41 with mRNA-1273 or mRNA-Omicron. Neutralizing antibody titers against D614G were 4760 and 270 reciprocal ID50 at week 6 (peak) and week 41 (pre-boost), respectively, and 320 and 110 for Omicron. Two weeks after boost, titers against D614G and Omicron increased to 5360 and 2980, respectively, for mRNA-1273 and 2670 and 1930 for mRNA-Omicron. Following either boost, 70-80% of spike-specific B cells were cross-reactive against both WA1 and Omicron. Significant and equivalent control of virus replication in lower airways was observed following either boost. Therefore, an Omicron boost may not provide greater immunity or protection compared to a boost with the current mRNA-1273 vaccine.", - "rel_num_authors": 66, + "rel_link": "https://biorxiv.org/cgi/content/short/2022.02.02.478897", + "rel_abs": "Involvement of macrophages in the SARS-CoV-2-associated cytokine storm, the excessive secretion of inflammatory/anti-viral factors leading to the acute respiratory distress syndrome (ARDS) in COVID-19 patients, is unclear. In this study, we sought to characterize the interplay between the virus and primary human monocyte-derived macrophages (MDM). MDM were stimulated with recombinant IFN- and/or infected with either live or UV-inactivated SARS-CoV-2 or with two reassortant influenza viruses containing external genes from the H1N1 PR8 strain and heterologous internal genes from a highly pathogenic avian H5N1 or a low pathogenic human seasonal H1N1 strain. Virus replication was monitored by qRT-PCR for the E viral gene for SARS-CoV-2 or M gene for influenza and TCID50 or plaque assay, and cytokine levels were assessed semiquantitatively with qRT-PCR and a proteome cytokine array. We report that MDM are not susceptible to SARS-CoV-2 whereas both influenza viruses replicated in MDM, albeit abortively. We observed a modest cytokine response in SARS-CoV-2 infected MDM with notable absence of IFN-{beta} induction, which was instead strongly induced by the influenza viruses. Pre-treatment of MDM with IFN- enhanced proinflammatory cytokine expression upon infection. Together, the findings concur that the hyperinflammation observed in SARS-CoV-2 infection is not driven by macrophages.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Matthew Gagne", - "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, 20892, United States of Ameri" - }, - { - "author_name": "Juan I. Moliva", - "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, 20892, United States of Ameri" - }, - { - "author_name": "Kathryn E. Foulds", - "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, 20892, United States of Ameri" - }, - { - "author_name": "Shayne F. Andrew", - "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, 20892, United States of Ameri" - }, - { - "author_name": "Barbara J. Flynn", - "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, 20892, United States of Ameri" - }, - { - "author_name": "Anne P. Werner", - "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, 20892, United States of Ameri" - }, - { - "author_name": "Danielle A. Wagner", - "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, 20892, United States of Ameri" - }, - { - "author_name": "I-Ting Teng", - "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, 20892, United States of Ameri" - }, - { - "author_name": "Bob C. Lin", - "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, 20892, United States of Ameri" - }, - { - "author_name": "Christopher Moore", - "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, 20892, United States of Ameri" - }, - { - "author_name": "Nazaire Jean-Baptiste", - "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, 20892, United States of Ameri" - }, - { - "author_name": "Robin Carroll", - "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, 20892, United States of Ameri" - }, - { - "author_name": "Stephanie L. Foster", - "author_inst": "Department of Pediatrics, Emory Vaccine Center, Yerkes National Primate Research Center, Emory University School of Medicine, Atlanta, Georgia, 30322, United St" - }, - { - "author_name": "Mit Patel", - "author_inst": "Department of Pediatrics, Emory Vaccine Center, Yerkes National Primate Research Center, Emory University School of Medicine, Atlanta, Georgia, 30322, United St" - }, - { - "author_name": "Madison Ellis", - "author_inst": "Department of Pediatrics, Emory Vaccine Center, Yerkes National Primate Research Center, Emory University School of Medicine, Atlanta, Georgia, 30322, United St" - }, - { - "author_name": "Venkata-Viswanadh Edara", - "author_inst": "Department of Pediatrics, Emory Vaccine Center, Yerkes National Primate Research Center, Emory University School of Medicine, Atlanta, Georgia, 30322, United St" - }, - { - "author_name": "Nahara Vargas Maldonado", - "author_inst": "Department of Pediatrics, Emory Vaccine Center, Yerkes National Primate Research Center, Emory University School of Medicine, Atlanta, Georgia, 30322, United St" - }, - { - "author_name": "Mahnaz Minai", - "author_inst": "Infectious Disease Pathogenesis Section, Comparative Medicine Branch, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Rock" - }, - { - "author_name": "Lauren McCormick", - "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, 20892, United States of Ameri" - }, - { - "author_name": "Christopher Cole Honeycutt", - "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, 20892, United States of Ameri" - }, - { - "author_name": "Bianca M. Nagata", - "author_inst": "Infectious Disease Pathogenesis Section, Comparative Medicine Branch, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Rock" - }, - { - "author_name": "Kevin W. Bock", - "author_inst": "Infectious Disease Pathogenesis Section, Comparative Medicine Branch, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Rock" - }, - { - "author_name": "Caitlyn N. M. Dulan", - "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, 20892, United States of Ameri" - }, - { - "author_name": "Jamilet Cordon", - "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, 20892, United States of Ameri" - }, - { - "author_name": "John-Paul M. Todd", - "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, 20892, United States of Ameri" - }, - { - "author_name": "Elizabeth McCarthy", - "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, 20892, United States of Ameri" - }, - { - "author_name": "Laurent Pessaint", - "author_inst": "Bioqual, Inc., Rockville, Maryland, 20850, United States of America" - }, - { - "author_name": "Alex Van Ry", - "author_inst": "Bioqual, Inc., Rockville, Maryland, 20850, United States of America" - }, - { - "author_name": "Brandon Narvaez", - "author_inst": "Bioqual, Inc., Rockville, Maryland, 20850, United States of America" - }, - { - "author_name": "Daniel Valentin", - "author_inst": "Bioqual, Inc., Rockville, Maryland, 20850, United States of America" - }, - { - "author_name": "Anthony Cook", - "author_inst": "Bioqual, Inc., Rockville, Maryland, 20850, United States of America" - }, - { - "author_name": "Alan Dodson", - "author_inst": "Bioqual, Inc., Rockville, Maryland, 20850, United States of America" - }, - { - "author_name": "Katelyn Steingrebe", - "author_inst": "Bioqual, Inc., Rockville, Maryland, 20850, United States of America" - }, - { - "author_name": "Dillon R. Flebbe", - "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, 20892, United States of Ameri" - }, - { - "author_name": "Saule T. Nurmukhambetova", - "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, 20892, United States of Ameri" - }, - { - "author_name": "Sucheta Godbole", - "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, 20892, United States of Ameri" - }, - { - "author_name": "Amy R. Henry", - "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, 20892, United States of Ameri" - }, - { - "author_name": "Farida Laboune", - "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, 20892, United States of Ameri" - }, - { - "author_name": "Jesmine Roberts-Torres", - "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, 20892, United States of Ameri" - }, - { - "author_name": "Cynthia G. Lorang", - "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, 20892, United States of Ameri" - }, - { - "author_name": "Shivani Amin", - "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, 20892, United States of Ameri" - }, - { - "author_name": "Jessica Trost", - "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, 20892, United States of Ameri" - }, - { - "author_name": "Mursal Naisan", - "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, 20892, United States of Ameri" - }, - { - "author_name": "Manjula Basappa", - "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, 20892, United States of Ameri" - }, - { - "author_name": "Jacquelyn Willis", - "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, 20892, United States of Ameri" - }, - { - "author_name": "Lingshu Wang", - "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, 20892, United States of Ameri" - }, - { - "author_name": "Wei Shi", - "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, 20892, United States of Ameri" - }, - { - "author_name": "Nicole A. Doria-Rose", - "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, 20892, United States of Ameri" - }, - { - "author_name": "Adam S. Olia", - "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, 20892, United States of Ameri" - }, - { - "author_name": "Cuiping Liu", - "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, 20892, United States of Ameri" - }, - { - "author_name": "Darcy R. Harris", - "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, 20892, United States of Ameri" - }, - { - "author_name": "Andrea Carfi", - "author_inst": "Moderna Inc., Cambridge, MA, 02139, United States of America" - }, - { - "author_name": "John R. Mascola", - "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, 20892, United States of Ameri" - }, - { - "author_name": "Peter D. Kwong", - "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, 20892, United States of Ameri" - }, - { - "author_name": "Darin K. Edwards", - "author_inst": "Moderna Inc., Cambridge, MA, 02139, United States of America" - }, - { - "author_name": "Hanne Andersen", - "author_inst": "Bioqual, Inc., Rockville, Maryland, 20850, United States of America" - }, - { - "author_name": "Mark G. Lewis", - "author_inst": "Bioqual, Inc., Rockville, Maryland, 20850, United States of America" - }, - { - "author_name": "Kizzmekia S. Corbett", - "author_inst": "Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, 02115, United States of America" - }, - { - "author_name": "Martha C. Nason", - "author_inst": "Biostatistics Research Branch, Division of Clinical Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Ma" - }, - { - "author_name": "Adrian B. McDermott", - "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, 20892, United States of Ameri" - }, - { - "author_name": "Mehul S. Suthar", - "author_inst": "Department of Pediatrics, Emory Vaccine Center, Yerkes National Primate Research Center, Emory University School of Medicine, Atlanta, Georgia, 30322, United St" - }, - { - "author_name": "Ian N. Moore", - "author_inst": "Division of Pathology, Yerkes National Primate Research Center, Emory University School of Medicine, Atlanta, Georgia, 30329, United States of America" - }, - { - "author_name": "Mario Roederer", - "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, 20892, United States of Ameri" + "author_name": "Ziyun Zhang", + "author_inst": "Imperial College London" }, { - "author_name": "Nancy J. Sullivan", - "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, 20892, United States of Ameri" + "author_name": "Rebecca Penn", + "author_inst": "Imperial College London" }, { - "author_name": "Daniel C. Douek", - "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, 20892, United States of Ameri" + "author_name": "Wendy S S Barclay", + "author_inst": "Imperial College London" }, { - "author_name": "Robert A. Seder", - "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, 20892, United States of Ameri" + "author_name": "Efstathios S Giotis", + "author_inst": "Imperial College London & University of Essex" } ], "version": "1", "license": "cc_no", - "type": "new results", - "category": "immunology" + "type": "confirmatory results", + "category": "microbiology" }, { "rel_doi": "10.1101/2022.02.03.479080", @@ -396393,27 +395752,47 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2022.02.02.478873", - "rel_title": "Unraveling the Enzymatic Mechanism of the SARS-CoV-2 RNA-Dependent-RNA-Polymerase. An Unusual Active Site Leading to High Replication Rates.", + "rel_doi": "10.1101/2022.02.03.22270390", + "rel_title": "Private Equity Acquisition in Ophthalmology and Optometry: A Time Series Analysis of the Pre-COVID, COVID Pre-Vaccine, and COVID Post-Vaccine Eras", "rel_date": "2022-02-03", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.02.02.478873", - "rel_abs": "Viral infection relies on the hijacking of cellular machineries to enforce the reproduction of the infecting virus and its subsequent diffusion. In this context the replication of the viral genome is a key step performed by specific enzymes, i.e. polymerases. The replication of SARS-CoV-2, the causative agent of the COVID-19 pandemics, is based on the duplication of its RNA genome, an action performed by the viral RNA-dependent-RNA polymerase. In this contribution, for the first time and by using two-dimensional enhanced sampling quantum mechanics/ molecular mechanics, we have determined the chemical mechanisms leading to the inclusion of a nucleotide in the nascent viral RNA strand. We prove the high efficiency of the polymerase, which lowers the activation free energy to less than 10 kcal/mol. Furthermore, the SARS-CoV-2 polymerase active site is slightly different from those found usually found in other similar enzymes, and particularly it lacks the possibility to enforce a proton shuttle via a nearby histidine. Our simulations show that this absence is partially compensate by lysine, whose proton assist the reaction opening up an alternative, but highly efficient, reactive channel. Our results present the first mechanistic resolution of SARS-CoV-2 genome replication and shed light on unusual enzymatic reactivity paving the way for future rational design of antivirals targeting emerging RNA viruses.", - "rel_num_authors": 2, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2022.02.03.22270390", + "rel_abs": "ObjectiveTo identify temporal and geographic trends in private equity (PE) backed acquisitions of ophthalmology and optometry practices in the United States from 2012 to 2021.\n\nDesignCross-sectional time series analysis using acquisition data from 10/21/2019 to 9/1/2021 compared to previously published data from 1/1/2012-10/20/2019. Acquisition data was compiled from 6 financial databases, 5 industry news outlets, and publicly available press releases. Linear regression models were used to compare rates of acquisition.\n\nSubjects245 PE acquisitions of ophthalmology and optometry practices in the United States between 10/21/2019 and 9/1/2021.\n\nMeasuresNumber of total acquisitions, practice type, locations, provider details, and geographic footprint.\n\nResults245 practices associated with 614 clinical locations and 948 ophthalmologists or optometrists were acquired by 30 PE-backed platform companies. 18 of 30 platform companies were new compared to our prior study. Of these acquisitions from 10/21/2019 - 9/1/2021, 127, 29, and 89 were comprehensive, retina, and optometry practices, respectively. From 2012 to 2021, monthly acquisitions increased by 0.947 acquisitions per year (p<0.001*). Texas, Florida, Michigan, and New Jersey were the states with the greatest number of PE acquisitions with 55, 48, 29, 28 clinic acquisitions, respectively. Average monthly PE acquisitions were 5.71 per month from 1/1/2019 - 2/29/2020 (pre-COVID), 5.30 per month 3/1/2020-12/31/2020 (COVID pre-vaccine, p=0.8072), and were 8.78/month 1/1/2021-9/1/2021 (COVID post-vaccine, p=0.1971).\n\nConclusionPE acquisitions increased from 2012-2021 as companies continue to utilize both regionally focused and multi-state models of add-on acquisitions.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Emmanuelle Bignon", - "author_inst": "Universite de Lorraine" + "author_name": "Sachi A Patil", + "author_inst": "Department of Ophthalmology New York University Grossman School of Medicine" }, { - "author_name": "Antonio Monari", - "author_inst": "Universite de Paris and CNRS, ITODYS" + "author_name": "Daniel Garrett Vail", + "author_inst": "Department of Ophthalmology, Icahn School of Medicine at Mount Sinai, New York Eye and Ear Infirmary of Mount Sinai" + }, + { + "author_name": "Jacob Tanner Cox", + "author_inst": "Department of Ophthalmology, Massachusetts Eye and Ear" + }, + { + "author_name": "Evan M Chen", + "author_inst": "Department of Ophthalmology, University of California San Francisco" + }, + { + "author_name": "Prithvi Mruthyunjaya", + "author_inst": "Byers Eye Institute, Department of Ophthalmology, Stanford University School of Medicine" + }, + { + "author_name": "James C Tsai", + "author_inst": "Department of Ophthalmology, Icahn School of Medicine at Mount Sinai, New York Eye and Ear Infirmary of Mount Sinai" + }, + { + "author_name": "Ravi Parikh", + "author_inst": "Department of Ophthalmology New York University Grossman School of Medicine; Manhattan Retina and Eye Consultants" } ], "version": "1", "license": "cc_by_nc_nd", - "type": "new results", - "category": "biophysics" + "type": "PUBLISHAHEADOFPRINT", + "category": "ophthalmology" }, { "rel_doi": "10.1101/2022.02.02.22269653", @@ -398331,57 +397710,113 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.02.02.22270302", - "rel_title": "Durability of Omicron-neutralizing serum activity following mRNA booster immunization in elderly individuals", + "rel_doi": "10.1101/2022.02.01.22270279", + "rel_title": "Rapid, high throughput, automated detection of SARS-CoV-2 neutralizing antibodies against native-like vaccine and delta variant spike trimers", "rel_date": "2022-02-02", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.02.02.22270302", - "rel_abs": "Elderly individuals are at high risk for severe COVID-19. Due to modest vaccine responses compared to younger individuals and the time elapsed since prioritized vaccinations, the emerging immune-evasive Omicron variant of SARS-CoV-2 is a particular concern for the elderly. Here we longitudinally determined SARS-CoV-2-neutralizing serum activity against different variants in a cohort of 37 individuals with a median age of 82 years. Participants were followed for 10 months after an initial two-dose BNT162b2 vaccination and up to 4.5 months after a BNT162b2 booster. Detectable Omicron-neutralizing activity was nearly absent after two vaccinations but elicited in 89% of individuals by the booster immunization. Neutralizing titers against the Wu01, Delta, and Omicron variants showed similar post-boost declines and 81% of individuals maintained detectable activity against Omicron. Our study demonstrates the mRNA booster effectiveness in inducing Omicron neutralizing activity and provides critical information on vaccine response durability in the highly vulnerable elderly population.", - "rel_num_authors": 11, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.02.01.22270279", + "rel_abs": "Traditional cellular and live-virus methods for detection of SARS-CoV-2 neutralizing antibodies (nAbs) are labor- and time-intensive, and thus not suited for routine use in the clinical lab to predict vaccine efficacy and natural immune protection. Here, we report the development and validation of a rapid, high throughput method for measuring SARS-CoV-2 nAbs against native-like trimeric spike proteins. This assay uses a blockade of hACE-2 binding (BoAb) approach in an automated digital immunoassay on the Quanterix HD-X platform. BoAb assays using vaccine and delta variant viral strains showed strong correlation with cell-based pseudovirus and live-virus neutralization activity. Importantly, we were able to detect similar patterns of delta variant resistance to neutralization in samples with paired vaccine and delta variant BoAb measurements. Finally, we screened clinical samples from patients with or without evidence of SARS-CoV-2 exposure by a single-dilution screening version of our assays, finding significant nAb activity only in exposed individuals. In principle, these assays offer a rapid, robust, and scalable alternative to time-, skill-, and cost-intensive standard methods for measuring SARS-CoV-2 nAb levels.", + "rel_num_authors": 25, "rel_authors": [ { - "author_name": "Kanika Vanshylla", - "author_inst": "Laboratory of Experimental Immunology, Institute of Virology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany" + "author_name": "Narayanaiah Cheedarla", + "author_inst": "Department of Pathology and Laboratory Medicine, Emory University School of Medicine, Atlanta, GA 30322, USA" }, { - "author_name": "Pinkus Tober-Lau", - "author_inst": "Department of Infectious Diseases and Respiratory Medicine, Charite-Universitaetsmedizin Berlin, Freie Universitaet Berlin and Humboldt-Universitaet zu Berlin, " + "author_name": "Hans Verkerke", + "author_inst": "Emory" }, { - "author_name": "Henning Gruell", - "author_inst": "Laboratory of Experimental Immunology, Institute of Virology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany" + "author_name": "Sindhu Potlapalli", + "author_inst": "Department of Pathology and Laboratory Medicine, Emory University School of Medicine, Atlanta, GA 30322, USA" }, { - "author_name": "Friederike Muenn", - "author_inst": "Department of Infectious Diseases and Respiratory Medicine, Charite-Universitaetsmedizin Berlin, Freie Universitaet Berlin and Humboldt-Universitaet zu Berlin, " + "author_name": "Kaleb Benjamin McLendon", + "author_inst": "Department of Pathology and Laboratory Medicine, Emory University School of Medicine, Atlanta, GA 30322, USA" }, { - "author_name": "Ralf Eggeling", - "author_inst": "Methods in Medical Informatics, Department of Computer Science, University of Tuebingen, Tuebingen, Germany" + "author_name": "Anamika B Patel", + "author_inst": "Department of Biochemistry, Emory University School of Medicine, Atlanta, GA 30322, USA." }, { - "author_name": "Nico Pfeifer", - "author_inst": "Methods in Medical Informatics, Department of Computer Science, University of Tuebingen, Tuebingen, Germany" + "author_name": "Filipp Frank", + "author_inst": "Department of Biochemistry, Emory University School of Medicine, Atlanta, GA 30322, USA." }, { - "author_name": "N. Han Le", - "author_inst": "Department of Infectious Diseases and Respiratory Medicine, Charite-Universitaetsmedizin Berlin, Freie Universitaet Berlin and Humboldt-Universitaet zu Berlin, " + "author_name": "Gregory L Damhorst", + "author_inst": "Department of Medicine, Division of infectious diseases, Emory University, Atlanta, GA 30322, USA." }, { - "author_name": "Irmgard Landgraf", - "author_inst": "Hausarztpraxis am Agaplesion Bethanien Sophienhaus, Berlin, Germany" + "author_name": "Huixia Wu", + "author_inst": "Department of Pathology and Laboratory Medicine, Emory University School of Medicine, Atlanta, GA 30322, USA" }, { - "author_name": "Florian Kurth", - "author_inst": "Department of Infectious Diseases and Respiratory Medicine, Charite-Universitaetsmedizin Berlin, Freie Universitaet Berlin and Humboldt-Universitaet zu Berlin, " + "author_name": "William Henry O'Sick", + "author_inst": "Department of Pathology and Laboratory Medicine, Emory University School of Medicine, Atlanta, GA 30322, USA" }, { - "author_name": "Leif Erik Sander", - "author_inst": "Department of Infectious Diseases and Respiratory Medicine, Charite-Universitaetsmedizin Berlin, Freie Universitaet Berlin and Humboldt-Universitaet zu Berlin, " + "author_name": "Daniel Graciaa", + "author_inst": "Department of Medicine, Division of infectious diseases, Emory University, Atlanta, GA 30322, USA." }, { - "author_name": "Florian Klein", - "author_inst": "Laboratory of Experimental Immunology, Institute of Virology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany" + "author_name": "Fuad Hudaib", + "author_inst": "Department of Pathology and Laboratory Medicine, Emory University School of Medicine, Atlanta, GA 30322, USA" + }, + { + "author_name": "David N Alter", + "author_inst": "Department of Pathology and Laboratory Medicine, Emory University School of Medicine, Atlanta, GA 30322, USA" + }, + { + "author_name": "Jeannette Bryksin", + "author_inst": "Department of Pathology and Laboratory Medicine, Emory University School of Medicine, Atlanta, GA 30322, USA" + }, + { + "author_name": "Eric A Ortlund", + "author_inst": "Department of Biochemistry, Emory University School of Medicine, Atlanta, GA 30322, USA." + }, + { + "author_name": "Jeannette Guarner", + "author_inst": "Department of Pathology and Laboratory Medicine, Emory University School of Medicine, Atlanta, GA 30322, USA" + }, + { + "author_name": "Sara Auld", + "author_inst": "Department of Medicine, Division of infectious diseases, Emory University, Atlanta, GA 30322, USA." + }, + { + "author_name": "Sarita Shah", + "author_inst": "Rollins School of Public Health, Emory University, Atlanta, GA 30322, USA" + }, + { + "author_name": "Wilbur Lam", + "author_inst": "Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, USA" + }, + { + "author_name": "Dawn Mattoon", + "author_inst": "Quanterix" + }, + { + "author_name": "Joseph M Johnson", + "author_inst": "Quanterix" + }, + { + "author_name": "Wilson David", + "author_inst": "Quanterix Corporation, 900 Middlesex Turnpike, Billerica, MA 01821" + }, + { + "author_name": "Madhav V Dhodapkar", + "author_inst": "Department of Hematology/Medical Oncology, Emory University, Atlanta, GA" + }, + { + "author_name": "Sean R Stowell", + "author_inst": "Harvard" + }, + { + "author_name": "Andrew S Neish", + "author_inst": "Department of Pathology and Laboratory Medicine, Emory University School of Medicine, Atlanta, GA 30322, USA" + }, + { + "author_name": "John D Roback", + "author_inst": "Department of Pathology and Laboratory Medicine, Emory University School of Medicine, Atlanta, GA 30322, USA" } ], "version": "1", @@ -399937,35 +399372,95 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2022.01.31.22270058", - "rel_title": "Analysis of COVID-19 infection amongst healthcare workers in Rivers State, Nigeria", + "rel_doi": "10.1101/2022.01.31.22270203", + "rel_title": "Blood transcriptomes of SARS-CoV-2 infected kidney transplant recipients demonstrate immune insufficiency", "rel_date": "2022-02-01", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.31.22270058", - "rel_abs": "Background/aimsHealthcare workers (HCWs) are at an increased risk of infection and mortality associated with the COVID-19 pandemic. This study determined the illness severity and mortality amongst COVID-19 infected healthcare workers.\n\nMethodsThe current study was a retrospective cohort study using population-level data. Secondary analysis was conducted on collated data from the Public Health Emergency Operations Centre (PHEOC) at the State Ministry of Health. The cohort included all documented healthcare workers with confirmed COVID-19 infection (diagnosed by Polymerase Chain Reaction). Data were gathered from the COVID-19 patient database of the PHEOC, on demographics, place of work, illness severity and outcome. Descriptive statistics were reported on the cohort characteristics. Adjusted odds ratio was used to report the measure of association between illness severity and risk factors.\n\nResultsThe mean age was 43 years and 50.5% of the cohort were female. Of the 301 healthcare workers, 187 patients were symptomatic with 32 requiring hospitalisation. From the available data, seven infected HCWs died of their COVID-19 infection, resulting in a case fatality ratio of 2.3%. A subgroup analysis was conducted on the health professionals infected -doctors (71.7%), nurses (27.3%), others (1%). Symptomatic cases were more inclined to progress to severe illness. Predictors of mortality assessed included age, sex, case class and illness severity. The logistic regression model was statistically significant,{chi} 2(9) = 16.965, = 0.049.\n\nConclusionFrontline healthcare workers are at an increased risk of exposure to COVID-19 infections. In Nigeria, there is a higher risk of experiencing a severe disease if symptomatic while infected with COVID-19. It is imperative that preventive strategies, proper education, and awareness are put in place to protect healthcare workers.\n\nSummary BoxHealthcare workers as first responders, are vulnerable to workplace infections. It is manifest in the COVID-19 pandemic where deaths of healthcare workers resulted in further shortage of the already compromised human resource; consequently compromising effective healthcare delivery. As the pandemic progresses, studies have been conducted globally on this topic and scientific evidence continues to show higher mortality and disease severity of COVID-19. Nevertheless, it is important to understand the effect of COVID-19 on healthcare workers in Nigeria-a developing country.\n\nThis study highlights the illness severity and mortality associated with COVID-19 among the study population; its results presented a higher case fatality rate than both national and subnational rates. The results also further emphasises the need to protect healthcare workers; ensure they are knowledgable in both infection prevention and control, and that the healthcare space is safe against nosocomial infections\n\nThe study adds to the scientific evidence on the severity and mortality associated with COVID-19 in Nigeria. A national research is needed to extrapolate the findings from this study to the nation. Hence, expatiate on the global fight against coronaviruses such as COVID-19.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.31.22270203", + "rel_abs": "BackgroundKidney transplant recipients (KTRs) with COVID-19 have poor outcomes compared to non-KTRs. To provide insight into management of immunosuppression during acute illness, we studied immune signatures from the peripheral blood during and after COVID-19 infection from a multicenter KTR cohort.{square}\n\nMethodsClinical data were collected by chart review. PAXgene blood RNA was poly-A selected and RNA sequencing was performed to evaluate transcriptome changes.\n\nResultsA total of 64 cases of COVID-19 in KTRs were enrolled, including 31 acute cases (< 4 weeks from diagnosis) and 33 post-acute cases (>4 weeks). In the blood transcriptome of acute cases, we identified differentially expressed genes (DEGs) in positive or negative association COVID-19 severity scores. Functional enrichment analyses showed upregulation of neutrophil and innate immune pathways, but downregulation of T-cell and adaptive immune-activation pathways proportional to severity score. This finding was independent of lymphocyte count and despite reduction in immunosuppression (IS) in most KTRs. Comparison with post-acute cases showed \"normalization\" of these enriched pathways after >4 weeks, suggesting recovery of adaptive immune system activation despite reinstitution of IS. The latter analysis was adjusted for COVID-19 severity score and lymphocyte count. DEGs associated with worsening disease severity in a non-KTR cohort with COVID-19 (GSE152418) showed significant overlap with KTRs in these identified enriched pathways.\n\nConclusionBlood transcriptome of KTRs affected by COVID-19 shows decrease in T-cell and adaptive immune activation pathways during acute disease that associate with severity despite IS reduction and show recovery after acute illness.\n\nSignificance statementKidney transplant recipients (KTRs) are reported to have worse outcomes with COVID-19, and empiric reduction of maintenance immunosuppression is pursued. Surprisingly, reported rates of acute rejection have been low despite reduced immunosuppression. We evaluated the peripheral blood transcriptome of 64 KTRs either during or after acute COVID-19. We identified transcriptomic signatures consistent with suppression of adaptive T-cell responses which significantly associated with disease severity and showed evidence of recovery after acute disease, even after adjustment for lymphocyte number. Our transcriptomic findings of immune-insufficiency during acute COVID-19 provide an explanation for the low rates of acute rejection in KTRs despite reduced immunosuppression. Our data support the approach of temporarily reducing T -cell-directed immunosuppression in KTRs with acute COVID-19.", + "rel_num_authors": 19, "rel_authors": [ { - "author_name": "Chidinma Eze-Emiri", - "author_inst": "University of Port Harcourt, River State, Nigeria" + "author_name": "Zeguo Sun", + "author_inst": "Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Foster Patrick", - "author_inst": "University of Port Harcourt, Rivers State, Nigeria" + "author_name": "Zhongyang Zhang", + "author_inst": "Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Ezinne Igwe", - "author_inst": "University of Wollongong, NSW, Australia" + "author_name": "Khadijia Banu", + "author_inst": "Yale University school of Medicine" }, { - "author_name": "Golden Owhonda", - "author_inst": "Rivers State Ministry of Health, Port Harcourt, Rivers State, Nigeria" + "author_name": "Yorg AI Azzi", + "author_inst": "Albert Einstein College of Medicine" + }, + { + "author_name": "Anand Reghuvaran", + "author_inst": "Yale University school of Medicine" + }, + { + "author_name": "Samuel Fredericks", + "author_inst": "Icahn School of Medicine at Mount Sinai" + }, + { + "author_name": "Marina Planoutene", + "author_inst": "Icahn School of Medicine at Mount Sinai" + }, + { + "author_name": "Susan Hartzell", + "author_inst": "Icahn School of Medicine at Mount Sinai" + }, + { + "author_name": "John Pell", + "author_inst": "Yale University school of Medicine" + }, + { + "author_name": "Gregory Tietjen", + "author_inst": "Yale University school of Medicine" + }, + { + "author_name": "William Asch", + "author_inst": "Yale University school of Medicine" + }, + { + "author_name": "Sanjay Kulkarni", + "author_inst": "Yale University school of Medicine" + }, + { + "author_name": "Richard Formica", + "author_inst": "Yale University school of Medicine" + }, + { + "author_name": "Meenakshi Rana", + "author_inst": "Icahn School of Medicine at Mount Sinai" + }, + { + "author_name": "Weijia Zhang", + "author_inst": "Icahn School of Medicine at Mount Sinai" + }, + { + "author_name": "Enver Akalin", + "author_inst": "Albert Einstein College of Medicine" + }, + { + "author_name": "Paolo Cravedi", + "author_inst": "Icahn School of Medicine at Mount Sinai" + }, + { + "author_name": "Peter Heeger", + "author_inst": "Icahn School of Medicine at Mount Sinai" + }, + { + "author_name": "Madhav C Menon", + "author_inst": "Yale School of Medicine" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "nephrology" }, { "rel_doi": "10.1101/2022.01.31.22270206", @@ -401735,91 +401230,35 @@ "category": "biophysics" }, { - "rel_doi": "10.1101/2022.01.30.478343", - "rel_title": "High Frequencies of PD-1+TIM3+TIGIT+CTLA4+ Functionally Exhausted SARS-CoV-2-Specific CD4+ and CD8+ T Cells Associated with Severe Disease in Critically ill COVID-19 Patients", + "rel_doi": "10.1101/2022.01.27.477964", + "rel_title": "Virucidal activity and mechanism of action of cetylpyridinium chloride against SARS-CoV-2", "rel_date": "2022-01-31", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.01.30.478343", - "rel_abs": "SARS-CoV-2-specific memory T cells that cross-react with common cold coronaviruses (CCCs) are present in both healthy donors and COVID-19 patients. However, whether these cross-reactive T cells play a role in COVID-19 pathogenesis versus protection remain to be fully elucidated. In this study, we characterized cross-reactive SARS-CoV-2-specific CD4+ and CD8+ T cells, targeting genome-wide conserved epitopes in a cohort of 147 non-vaccinated COVID-19 patients, divided into six groups based on the degrees of disease severity. We compared the frequency, phenotype, and function of these SARS-CoV-2-specific CD4+ and CD8+ T cells between severely ill and asymptomatic COVID-19 patients and correlated this with -CCCs and {beta}-CCCs co-infection status. Compared with asymptomatic COVID-19 patients, the severely ill COVID-19 patients and patients with fatal outcomes: (i) Presented a broad leukocytosis and a broad CD4+ and CD8+ T cell lymphopenia; (ii) Developed low frequencies of functional IFN-{gamma}-producing CD134+CD138+CD4+ and CD134+CD138+CD8+ T cells directed toward conserved epitopes from structural, non-structural and regulatory SARS-CoV-2 proteins; (iii) Displayed high frequencies of SARS-CoV-2-specific functionally exhausted PD-1+TIM3+TIGIT+CTLA4+CD4+ and PD-1+TIM3+TIGIT+CTLA4+CD8+ T cells; and (iv) Displayed similar frequencies of co-infections with {beta}-CCCs strains but significantly fewer co-infections with -CCCs strains. Interestingly, the cross-reactive SARS-CoV-2 epitopes that recalled the strongest CD4+ and CD8+ T cell responses in unexposed healthy donors (HD) were the most strongly associated with better disease outcome seen in asymptomatic COVID-19 patients. Our results demonstrate that, the critically ill COVID-19 patients displayed fewer co-infection with -CCCs strain, presented broad T cell lymphopenia and higher frequencies of cross-reactive exhausted SARS-CoV-2-specific CD4+ and CD8+ T cells. In contrast, the asymptomatic COVID-19 patients, appeared to present more co-infections with -CCCs strains, associated with higher frequencies of functional cross-reactive SARS-CoV-2-specific CD4+ and CD8+ T cells. These findings support the development of broadly protective, T-cell-based, multi-antigen universal pan-Coronavirus vaccines.\n\nKEY POINTSO_LIA broad lymphopenia and lower frequencies of SARS-CoV-2-specific CD4+ and CD8+ T-cells were associated with severe disease onset in COVID-19 patients.\nC_LIO_LIHigh frequencies of phenotypically and functionally exhausted SARS-CoV-2-specific CD4+ and CD8+ T cells, co-expressing multiple exhaustion markers, and targeting multiple structural, non-structural, and regulatory SARS-CoV-2 protein antigens, were detected in severely ill COVID-19 patients.\nC_LIO_LICompared to severely ill COVID-19 patients and to patients with fatal outcomes, the (non-vaccinated) asymptomatic COVID-19 patients presented more functional cross-reactive CD4+ and CD8+ T cells targeting conserved epitopes from structural, non-structural, and regulatory SARS-CoV-2 protein antigens.\nC_LIO_LIThe cross-reactive SARS-CoV-2 epitopes that recalled the strongest CD4+ and CD8+ T cell responses in unexposed healthy donors (HD) were the most strongly associated with better disease outcomes seen in asymptomatic COVID-19 patients.\nC_LIO_LICompared to severely ill COVID-19 patients and to patients with fatal outcomes, the (non-vaccinated) asymptomatic COVID-19 patients presented higher rates of co-infection with the -CCCs strains.\nC_LIO_LICompared to patients with mild or asymptomatic COVID-19, severely ill symptomatic patients and patients with fatal outcomes had more exhausted SARS-CoV-2-speccific CD4+ and CD8+ T cells that preferentially target cross-reactive epitopes that share high identity and similarity with the {beta}-CCCs strains.\nC_LI", - "rel_num_authors": 18, + "rel_link": "https://biorxiv.org/cgi/content/short/2022.01.27.477964", + "rel_abs": "ObjectiveSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the pathogen causing the coronavirus disease 2019 (COVID-19) global pandemic. Recent studies have shown the importance of the throat and salivary glands as sites of virus replication and transmission. The viral host receptor, angiotensin-converting enzyme 2 (ACE2), is broadly enriched in epithelial cells of the salivary glands and oral mucosae. Oral care products containing cetylpyridinium chloride (CPC) as a bactericidal ingredient are known to exhibit antiviral activity against SARS-CoV-2 in vitro. However, the exact mechanism of action remains unknown.\n\nMethodsThis study examined the antiviral activity of CPC against SARS-CoV-2 and its inhibitory effect on the interaction between the viral spike (S) protein and ACE2 using an enzyme-linked immunosorbent assay.\n\nResultsCPC (0.05%, 0.1% and 0.3%) effectively inactivated SARS-CoV-2 within the contact times (20 and 60 s) in directions for use of oral care products in vitro. The binding ability of both the S protein and ACE2 were reduced by CPC.\n\nConclusionsOur results suggest that CPC inhibits the interaction between S protein and ACE2, and thus, reduces infectivity of SARS-CoV-2 and suppresses viral adsorption.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Pierre-Gregoire A Coulon", - "author_inst": "Laboratory of Cellular and Molecular Immunology, Gavin Herbert Eye Institute, University of California Irvine, School of Medicine, Irvine, CA 92697" - }, - { - "author_name": "Swayam Prakash", - "author_inst": "Laboratory of Cellular and Molecular Immunology, Gavin Herbert Eye Institute, University of California Irvine, School of Medicine, Irvine, CA 92697" - }, - { - "author_name": "Nisha R Dhanushkodi", - "author_inst": "Laboratory of Cellular and Molecular Immunology, Gavin Herbert Eye Institute, University of California Irvine, School of Medicine, Irvine, CA 92697" - }, - { - "author_name": "Ruchi Srivastava", - "author_inst": "Laboratory of Cellular and Molecular Immunology, Gavin Herbert Eye Institute, University of California Irvine, School of Medicine, Irvine, CA 92697" - }, - { - "author_name": "Latifa Zayou", - "author_inst": "Laboratory of Cellular and Molecular Immunology, Gavin Herbert Eye Institute, University of California Irvine, School of Medicine, Irvine, CA 92697" - }, - { - "author_name": "Delia F Tifrea", - "author_inst": "Department of Pathology and Laboratory Medicine, School of Medicine, Irvine, CA 92697" - }, - { - "author_name": "Robert A Edwards", - "author_inst": "Department of Pathology and Laboratory Medicine, School of Medicine, Irvine, CA 92697" - }, - { - "author_name": "Cesar J Figueroa", - "author_inst": "Department of Surgery, Divisions of Trauma, Burns & Critical Care, School of Medicine, Irvine, CA 92697" - }, - { - "author_name": "Sebastian D Schubl", - "author_inst": "Department of Surgery, Divisions of Trauma, Burns & Critical Care, School of Medicine, Irvine, CA 92697" - }, - { - "author_name": "Lanny Hsieh", - "author_inst": "Department of Medicine, Division of Infectious Diseases and Hospitalist Program, School of Medicine, Irvine, CA 92697" + "author_name": "Nako Okamoto", + "author_inst": "R&D, Sunstar Inc., 1-35-10, Kawanishi-cho, Takatsuki, Osaka, 569-1133, Japan" }, { - "author_name": "Anthony B Nesburn", - "author_inst": "Laboratory of Cellular and Molecular Immunology, Gavin Herbert Eye Institute, University of California Irvine, School of Medicine, Irvine, CA 92697" - }, - { - "author_name": "Baruch D Kuppermann", - "author_inst": "Laboratory of Cellular and Molecular Immunology, Gavin Herbert Eye Institute, University of California Irvine, School of Medicine, Irvine, CA 92697" - }, - { - "author_name": "Elmostafa BAHRAOUI", - "author_inst": "INFINITY, INSERM, University Toulouse III" - }, - { - "author_name": "Hawa Vahed", - "author_inst": "Department of Vaccines and Immunotherapies, TechImmune, LLC, University Lab Partners, Irvine, CA 92660" - }, - { - "author_name": "Daniel Gil", - "author_inst": "Department of Vaccines and Immunotherapies, TechImmune, LLC, University Lab Partners, Irvine, CA 92660" - }, - { - "author_name": "Trevor M Jones", - "author_inst": "Department of Vaccines and Immunotherapies, TechImmune, LLC, University Lab Partners, Irvine, CA 92660" + "author_name": "Akatsuki Saito", + "author_inst": "Department of Veterinary Science, Faculty of Agriculture, University of Miyazaki, Miyazaki, Japan" }, { - "author_name": "Jeffrey B Ulmer", - "author_inst": "Department of Vaccines and Immunotherapies, TechImmune, LLC, University Lab Partners, Irvine, CA 92660" + "author_name": "Tamaki Okabayashi", + "author_inst": "Department of Veterinary Science, Faculty of Agriculture, University of Miyazaki, Miyazaki, Japan" }, { - "author_name": "LBACHIR BENMOHAMED", - "author_inst": "UC Irvine, School of Medicine" + "author_name": "Akihiko Komine", + "author_inst": "R&D, Sunstar Inc., 1-35-10, Kawanishi-cho, Takatsuki, Osaka, 569-1133, Japan" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_by_nc_nd", "type": "new results", - "category": "immunology" + "category": "microbiology" }, { "rel_doi": "10.1101/2022.01.28.22270043", @@ -403697,57 +403136,113 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2022.01.28.22270006", - "rel_title": "A mixed methods analysis of participation in social contact surveys", + "rel_doi": "10.1101/2022.01.27.22269965", + "rel_title": "Outbreak.info genomic reports: scalable and dynamic surveillance of SARS-CoV-2 variants and mutations", "rel_date": "2022-01-29", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.28.22270006", - "rel_abs": "BackgroundSocial contact survey data forms a core component of modern epidemic models: however, there has been little assessment of the potential biases in such data.\n\nMethodsWe conducted focus groups with university students who had (n=13) and had not (n=14) completed a social contact survey during the COVID-19 pandemic. Qualitative findings were explored quantitatively by analysing participation data.\n\nResultsThe opportunity to contribute to COVID-19 research, to be heard and feel useful were frequently reported motivators for participating in the contact survey. Reductions in survey engagement following lifting of COVID-19 restrictions may have occurred because the research was perceived to be less critical and/ or because the participants were busier and had more contacts. Having a high number of contacts to report, uncertainty around how to report each contact, and concerns around confidentiality were identified as factors leading to inaccurate reporting. Focus groups participants thought that financial incentives or provision of study results would encourage participation.\n\nConclusionsIncentives could improve engagement with social contact surveys. Qualitative research can inform the format, timing, and wording of surveys to optimise completion and accuracy.\n\nGraphical abstract\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=113 SRC=\"FIGDIR/small/22270006v2_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (47K):\norg.highwire.dtl.DTLVardef@10a3dd4org.highwire.dtl.DTLVardef@1616032org.highwire.dtl.DTLVardef@1f2aab8org.highwire.dtl.DTLVardef@a62043_HPS_FORMAT_FIGEXP M_FIG C_FIG", - "rel_num_authors": 11, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.27.22269965", + "rel_abs": "The emergence of SARS-CoV-2 variants of concern has prompted the need for near real-time genomic surveillance to inform public health interventions. In response to this need, the global scientific community, through unprecedented effort, has sequenced and shared over 10 million genomes through GISAID, as of May 2022. This extraordinarily high sampling rate provides a unique opportunity to track the evolution of the virus in near real-time. Here, we present outbreak.info, a platform that currently tracks over 40 million combinations of PANGO lineages and individual mutations, across over 7,000 locations, to provide insights for researchers, public health officials, and the general public. We describe the interpretable and opinionated visualizations in the variant and location focussed reports available in our web application, the pipelines that enable the scalable ingestion of heterogeneous sources of SARS-CoV-2 variant data, and the server infrastructure that enables widespread data dissemination via a high performance API that can be accessed using an R package. We present a case study that illustrates how outbreak.info can be used for genomic surveillance and as a hypothesis generation tool to understand the ongoing pandemic at varying geographic and temporal scales. With an emphasis on scalability, interactivity, interpretability, and reusability, outbreak.info provides a template to enable genomic surveillance at a global and localized scale.", + "rel_num_authors": 25, "rel_authors": [ { - "author_name": "Emily J Nixon", - "author_inst": "University of Bristol" + "author_name": "Karthik Gangavarapu", + "author_inst": "University of California, Los Angeles" }, { - "author_name": "Taru Silvonen", - "author_inst": "University of Bristol" + "author_name": "Alaa Abdel Latif", + "author_inst": "The Scripps Research Institute" }, { - "author_name": "Antoine Barreaux", - "author_inst": "CIRAD" + "author_name": "Julia Mullen", + "author_inst": "The Scripps Research Institute" }, { - "author_name": "Rachel Kwiatkowska", - "author_inst": "University of Bristol" + "author_name": "Manar Alkuzweny", + "author_inst": "University of Notre Dame" }, { - "author_name": "Adam Trickey", - "author_inst": "University of Bristol" + "author_name": "Emory Hufbauer", + "author_inst": "The Scripps Research Institute" }, { - "author_name": "Amy C Thomas", - "author_inst": "University of Bristol" + "author_name": "Ginger Tsueng", + "author_inst": "The Scripps Research Institute" }, { - "author_name": "Becky Ali", - "author_inst": "University of Bristol" + "author_name": "Emily Haag", + "author_inst": "The Scripps Research Institute" }, { - "author_name": "Georgia Treneman-evans", - "author_inst": "University of Bristol" + "author_name": "Mark Zeller", + "author_inst": "The Scripps Research Institute" }, { - "author_name": "Hannah Christensen", - "author_inst": "University of Bristol" + "author_name": "Christine M. Aceves", + "author_inst": "The Scripps Research Institute" }, { - "author_name": "Ellen Brooks Pollock", - "author_inst": "University of Bristol" + "author_name": "Karina Zaiets", + "author_inst": "The Scripps Research Institute" }, { - "author_name": "Sarah Denford", - "author_inst": "University of Bristol" + "author_name": "Marco Cano", + "author_inst": "The Scripps Research Institute" + }, + { + "author_name": "Jerry Zhou", + "author_inst": "The Scripps Research Institute" + }, + { + "author_name": "Zhongchao Qian", + "author_inst": "The Scripps Research Institute" + }, + { + "author_name": "Rachel Sattler", + "author_inst": "The Scripps Research Institute" + }, + { + "author_name": "Nathaniel L Matteson", + "author_inst": "The Scripps Research Institute" + }, + { + "author_name": "Joshua I. Levy", + "author_inst": "The Scripps Research Institute" + }, + { + "author_name": "Raphael TC Lee", + "author_inst": "GISAID Global Data Science Initiative" + }, + { + "author_name": "Lucas Freitas", + "author_inst": "GISAID Global Data Science Initiative" + }, + { + "author_name": "Sebastian Maurer-Stroh", + "author_inst": "GISAID Global Data Science Initiative" + }, + { + "author_name": "- GISAID core and curation team", + "author_inst": "GISAID Global Data Science Initiative" + }, + { + "author_name": "Marc A. Suchard", + "author_inst": "University of California, Los Angeles" + }, + { + "author_name": "Chunlei Wu", + "author_inst": "The Scripps Research Institute" + }, + { + "author_name": "Andrew I. Su", + "author_inst": "The Scripps Research Institute" + }, + { + "author_name": "Kristian G. Andersen", + "author_inst": "The Scripps Research Institute" + }, + { + "author_name": "Laura D. Hughes", + "author_inst": "The Scripps Research Institute" } ], "version": "1", @@ -405467,131 +404962,139 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.01.26.22269848", - "rel_title": "mRNA vaccine boosting enhances antibody responses against SARS-CoV-2 Omicron variant in patients with antibody deficiency syndromes", + "rel_doi": "10.1101/2022.01.27.22269787", + "rel_title": "Early introduction and rise of the Omicron SARS-CoV-2 variant in highly vaccinated university populations", "rel_date": "2022-01-28", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.26.22269848", - "rel_abs": "Patients with primary antibody deficiency syndromes (PAD) have poor humoral immune responses requiring immunoglobulin replacement therapy. We followed PAD patients after SARS-CoV-2 vaccination by evaluating their immunoglobulin replacement products and serum for anti-spike binding, Fc{gamma}R binding, and neutralizing activities. Immunoglobulin replacement products had low anti-spike and receptor binding domain (RBD) titers and neutralizing activity. In COVID-19-naive PAD patients, anti-spike and RBD titers increased after mRNA vaccination but decreased to pre-immunization levels by 90 days. Patients vaccinated after SARS-CoV-2 infection developed higher responses comparable to healthy donors. Most vaccinated PAD patients had serum neutralizing antibody titers above an estimated correlate of protection against ancestral SARS-CoV-2 and Delta virus but not against Omicron virus, although this was improved by boosting. Thus, currently used immunoglobulin replacement products likely have limited protective activity, and immunization and boosting of PAD patients with mRNA vaccines should confer at least short-term immunity against SARS-CoV-2 variants, including Omicron.", - "rel_num_authors": 28, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.27.22269787", + "rel_abs": "The Omicron variant of SARS-CoV-2 is transmissible in vaccinated and unvaccinated populations. Here, we describe the rapid dominance of Omicron following its introduction to three Massachusetts universities with asymptomatic surveillance programs. We find that Omicron was established and reached fixation earlier on these campuses than in Massachusetts or New England as a whole, rapidly outcompeting Delta despite its association with lower viral loads. These findings highlight the transmissibility of Omicron and its propensity to fixate in small populations, as well as the ability of robust asymptomatic surveillance programs to offer early insights into the dynamics of pathogen arrival and spread.", + "rel_num_authors": 30, "rel_authors": [ { - "author_name": "Ofer Zimmerman", - "author_inst": "Washington University School of Medicine" + "author_name": "Brittany A Petros", + "author_inst": "Broad Institute of MIT and Harvard" }, { - "author_name": "Alexa Michelle Altman Doss", - "author_inst": "Washington University School of Medicine" + "author_name": "Jacquelyn Turcinovic", + "author_inst": "Boston University" }, { - "author_name": "Paulina Kaplonek", - "author_inst": "Ragon Institute" + "author_name": "Nicole Welch", + "author_inst": "Broad Institute of MIT and Harvard" }, { - "author_name": "Laura A. VanBlargan", - "author_inst": "Washington University School of Medicine" + "author_name": "Laura White", + "author_inst": "Boston University" }, { - "author_name": "Chieh-Yu Liang", - "author_inst": "Washington University School of Medicine" + "author_name": "Eric Kolaczyk", + "author_inst": "Boston University" }, { - "author_name": "Rita E. Chen", - "author_inst": "Washington University School of Medicine" + "author_name": "Matthew Bauer", + "author_inst": "Broad Institute of MIT and Harvard" }, { - "author_name": "Jennifer Marie Monroy", - "author_inst": "Washington University School of Medicine" + "author_name": "Michael Cleary", + "author_inst": "Harvard University Clinical Laboratory" }, { - "author_name": "H. James Wedner", - "author_inst": "Washington University School of Medicine" + "author_name": "Sabrina Dobbins", + "author_inst": "Broad Institute of MIT and Harvard" }, { - "author_name": "Anthony Kulczycki", - "author_inst": "Washington University School of Medicine" + "author_name": "Lynn Doucette-Stamm", + "author_inst": "Boston University Clinical Testing Laboratory" }, { - "author_name": "Tarisa L. Mantia", - "author_inst": "Washington University School of Medicine" + "author_name": "Mitch Gore", + "author_inst": "Integrated DNA Technologies, Inc." }, { - "author_name": "Caitlin C. O'Shaughnessy", - "author_inst": "Washington University School of Medicine" + "author_name": "Parvathy Nair", + "author_inst": "Howard Hughes Medical Institute" }, { - "author_name": "Hannah G. Davis-Adams", - "author_inst": "Washington University School of Medicine" + "author_name": "Tien Nguyen", + "author_inst": "Broad Institute of MIT and Harvard" }, { - "author_name": "Harry L. Bertera", - "author_inst": "Ragon Institute" + "author_name": "Scott Rose", + "author_inst": "Integrated DNA Technologies, Inc." }, { - "author_name": "Lucas J. Adams", - "author_inst": "Washington University School of Medicine" + "author_name": "Bradford Taylor", + "author_inst": "Harvard T.H. Chan School of Public Health" }, { - "author_name": "Saravanan Raju", - "author_inst": "Washington University School of Medicine" + "author_name": "Daniel Tsang", + "author_inst": "Integrated DNA Technologies, Inc." }, { - "author_name": "Fang R. Zhao", - "author_inst": "Washington University School of Medicine" + "author_name": "Erik Wendlandt", + "author_inst": "Integrated DNA Technologies, Inc." }, { - "author_name": "Christopher J. Rigell", - "author_inst": "Washington University School of Medicine" + "author_name": "Michele Hope", + "author_inst": "Harvard University Clinical Laboratory" }, { - "author_name": "Tiffany Biason Dy", - "author_inst": "Washington University School of Medicine" + "author_name": "Judy Platt", + "author_inst": "Boston University" }, { - "author_name": "Andrew L. Kau", - "author_inst": "Washington University School of Medicine" + "author_name": "Karen Jacobson", + "author_inst": "Boston University School of Medicine" }, { - "author_name": "Zhen Ren", - "author_inst": "Washington University School of Medicine" + "author_name": "Tara Bouton", + "author_inst": "Boston Medical Center, Boston University School of Medicine" }, { - "author_name": "Jackson Turner", - "author_inst": "Washington University School of Medicine" + "author_name": "Seyho Yune", + "author_inst": "Northeastern University" }, { - "author_name": "Jane A. O'Halloran", - "author_inst": "Washington University in St. Louis School of Medicine" + "author_name": "Jared Auclair", + "author_inst": "Northeastern University" }, { - "author_name": "Rachel Presti", - "author_inst": "Washington University School of Medicine" + "author_name": "Lena Landaverde", + "author_inst": "Boston University" }, { - "author_name": "Daved H. Fremont", - "author_inst": "Washington University School of Medicine" + "author_name": "Catherine M. Klapperich", + "author_inst": "Boston University College of Engineering" }, { - "author_name": "Peggy L. Kendall", - "author_inst": "Washington University School of Medicine" + "author_name": "Davidson H Hamer", + "author_inst": "Boston University School of Public Health" }, { - "author_name": "Ali H. Ellebedy", - "author_inst": "Washington University School of Medicine" + "author_name": "William P Hanage", + "author_inst": "Harvard T.H. Chan School of Public Health" }, { - "author_name": "Galit Alter", - "author_inst": "Ragon Institute of MGH, MIT, and Harvard" + "author_name": "Bronwyn MacInnis", + "author_inst": "Broad Institute" }, { - "author_name": "Michael S. Diamond", - "author_inst": "Washington University School of Medicine" + "author_name": "Pardis Sabeti", + "author_inst": "Harvard University; The Broad Institute or MIT and Harvard; Howard Hughes Medical Institute" + }, + { + "author_name": "John H Connor", + "author_inst": "Boston University School of Medicine" + }, + { + "author_name": "Michael Springer", + "author_inst": "Harvard Medical School" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "allergy and immunology" + "category": "epidemiology" }, { "rel_doi": "10.1101/2022.01.26.22269908", @@ -407557,33 +407060,45 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2022.01.26.477969", - "rel_title": "Effect of SARS-CoV-2 spike mutations on its activation by TMPRSS2 and TMPRSS13", + "rel_doi": "10.1101/2022.01.26.477774", + "rel_title": "The P132H mutation in the main protease of Omicron SARS-CoV-2 decreases thermal stability without compromising catalysis or small-molecule drug inhibition", "rel_date": "2022-01-27", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.01.26.477969", - "rel_abs": "The continuous emergence of new SARS-CoV-2 variants urges better understanding of the functional motifs in the spike (S) protein and their tolerance towards mutations. We here focus on the S2 motif which, during virus entry, requires cleavage by a cell surface protease to release the fusion peptide. Though belonging to an immunogenic region, the SARS-CoV-2 S2 motif (811-KPSKR-815) has shown hardly any variation, with its three basic (K/R) residues being >99.99% conserved thus far. By creating a series of mutant S-pseudotyped viruses, we show that K814, which precedes the scissile R815 residue, is dispensable for SARS-CoV-2 spike activation by TMPRSS2 but not TMPRSS13. The latter protease lost its activity towards SARS-CoV-2 S when the S2 motif was swapped with that of the low pathogenic 229E coronavirus (685-RVAGR-689) and also the reverse effect was seen. This swap had no impact on TMPRSS2 activation. Also in the MERS-CoV spike, introducing a dibasic scissile motif was fully accepted by TMPRSS13 but less so by TMPRSS2. Our findings are the first to demonstrate which S2 residues are important for SARS-CoV-2 spike activation by these two airway proteases, with TMPRSS13 exhibiting higher preference for K/R rich motifs than TMPRSS2. This preemptive insight can help to estimate the impact of S2 motif changes as they may appear in new SARS-CoV-2 variants.\n\nIMPORTANCESince the start of the COVID-19 pandemic, SARS-CoV-2 is undergoing worldwide selection with frequent appearance of new variants. The surveillance would benefit from proactive characterization of the functional motifs in the spike protein, the most variable viral factor. This is linked to immune evasion but also influences spike functioning in a direct manner. Remarkably, though located in a strong immunogenic region, the S2 cleavage motif has, thus far, remained highly conserved. This suggests that its amino acid sequence is critical for spike activation by airway proteases. To investigate this, we assessed which S2 site mutations affect processing by TMPRSS2 and TMPRSS13, two main activators of the SARS-CoV-2 spike. Being the first in its kind, our study will help to assess the biological impact of S2 site variations as soon as they are detected during variant surveillance.", - "rel_num_authors": 5, + "rel_link": "https://biorxiv.org/cgi/content/short/2022.01.26.477774", + "rel_abs": "The ongoing SARS-CoV-2 pandemic continues to be a significant threat to global health. First reported in November 2021, the Omicron variant (B.1.1.529) is more transmissible and can evade immunity better than previous SARS-CoV-2 variants, fueling an unprecedented surge in cases. To produce functional proteins from this polyprotein, SARS-CoV-2 relies on the cysteine proteases Nsp3/papain-like protease (PLpro) and Nsp5/Main Protease (Mpro)/3C-like protease to cleave at three and more than 11 sites, respectively.1 Therefore, Mpro and PLpro inhibitors are considered to be some of the most promising SARS-CoV-2 antivirals. On December 22, 2021, the Food and Drug Administration (FDA) issued an Emergency Use Authorization (EUA) for PAXLOVID, a ritonavir-boosted formulation of nirmatrelvir. Nirmatrelvir is a first-in-class orally bioavailable SARS-CoV-2 Mpro inhibitor.2 Thus, the scientific community must vigilantly monitor potential mechanisms of drug resistance, especially because SARS-CoV-2 is naive to Mpro inhibitors. Mutations have been well identified in variants to this point.3 Notably, Omicron Mpro (OMpro) harbors a single mutation- P132H. In this study we characterize the enzymatic activity, drug inhibition, and structure of OMpro while evaluating the past and future implications of Mpro mutations.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Annelies Stevaert", - "author_inst": "Rega Institute for Medical Research, KU Leuven - University of Leuven" + "author_name": "Michael D Sacco", + "author_inst": "University of South Florida" }, { - "author_name": "Ria Van Berwaer", - "author_inst": "Rega Institute for Medical Research, KU Leuven - University of Leuven" + "author_name": "Yanmei Hu", + "author_inst": "Rutgers University" }, { - "author_name": "Valerie Raeymaekers", - "author_inst": "Rega Institute for Medical Research, KU Leuven - University of Leuven" + "author_name": "Maura V Gongora", + "author_inst": "University of South Florida" }, { - "author_name": "Manon Laporte", - "author_inst": "Icahn School of Medicine at Mount Sinai" + "author_name": "Flora Meilleur", + "author_inst": "Oak Ridge National Laboratory" + }, + { + "author_name": "M Trent Kemp", + "author_inst": "University of South Florida" }, { - "author_name": "Lieve M.J. Naesens", - "author_inst": "Rega Institute for Medical Research, KU Leuven - University of Leuven" + "author_name": "Xiujun Zhang", + "author_inst": "University of South Florida" + }, + { + "author_name": "Jun Wang", + "author_inst": "Rutgers University" + }, + { + "author_name": "Yu Chen", + "author_inst": "University of South Florida" } ], "version": "1", @@ -409859,99 +409374,35 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2022.01.25.477673", - "rel_title": "Despite the odds: formation of the SARS-CoV-2 methylation complex.", + "rel_doi": "10.1101/2022.01.25.477753", + "rel_title": "The SARS-CoV-2 protein NSP2 impairs the microRNA-induced silencing capacity of human cells", "rel_date": "2022-01-26", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.01.25.477673", - "rel_abs": "Coronaviruses protect their single-stranded RNA genome with a methylated cap during replication. The capping process is initiated by several nonstructural proteins (nsp) encoded in the viral genome. The methylation is performed by two methyltransferases, nsp14 and nsp16 where nsp10 acts as a co-factor to both. Aditionally, nsp14 carries an exonuclease domain, which operates in the proofreading system during RNA replication of the viral genome. Both nsp14 and nsp16 were reported to independently bind nsp10, but the available structural information suggests that the concomitant interaction between these three proteins should be impossible due to steric clashes. Here, we show that nsp14, nsp10, and nsp16 can form a heterotrimer complex. This interaction is expected to encourage formation of mature capped viral mRNA, modulating the nsp14s exonuclease activity, and protecting the viral RNA. Our findings show that nsp14 is amenable to allosteric regulation and may serve as a novel target for therapeutic approaches.", - "rel_num_authors": 20, + "rel_link": "https://biorxiv.org/cgi/content/short/2022.01.25.477753", + "rel_abs": "The coronavirus SARS-CoV-2 is the cause of the ongoing pandemic of COVID-19. Given the absence of effective treatments against SARS-CoV-2, there is an urgent need for a molecular understanding of how the virus influences the machineries of the host cell. The SARS-CoV-2 generates 16 Non-Structural Proteins (NSPs) through proteolytic cleavage of a large precursor protein. In the present study, we focused our attention on the SARS-CoV-2 protein NSP2, whose role in the viral pathogenicity is poorly understood. Recent proteomic studies shed light on the capacity of NSP2 to bind the 4EHP-GIGYF2 complex, a key factor involved in microRNA-mediated silencing of gene expression in human cells. In order to gain a better understanding of the function of NSP2, we attempted to identify the molecular basis of its interaction with 4EHP-GIGYF2. Our data demonstrate that NSP2 physically associates with the endogenous 4EHP-GIGYF2 complex in the cytoplasm. Using co-immunoprecipitation and in vitro interaction assays, we identified both 4EHP and a central segment in GIGYF2 as binding sites for NSP2. We also provide functional evidence that NSP2 impairs the function of GIGYF2 in mediating mRNA silencing using reporter-based assays, thus leading to a reduced activity of microRNAs. Altogether, these data reveal the profound impact of NSP2 on the post-transcriptional silencing of gene expression in human cells, pointing out 4EHP-GIGYF2 targeting as a possible strategy of SARS-CoV-2 to take over the silencing machinery and to suppress host defenses.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Alex Matsuda", - "author_inst": "Jagiellonian University" - }, - { - "author_name": "Jacek Plewka", - "author_inst": "Jagiellonian University" - }, - { - "author_name": "Yuliya Chykunova", - "author_inst": "Jagiellonian University" - }, - { - "author_name": "Alisha N. Jones", - "author_inst": "Helmholtz Zentrum Munchen" - }, - { - "author_name": "Magdalena Pachota", - "author_inst": "Jagiellonian University" - }, - { - "author_name": "Michal Rawski", - "author_inst": "Jagiellonian University" - }, - { - "author_name": "Andre Mourao", - "author_inst": "Helmholtz Zentrum Munchen" - }, - { - "author_name": "Abdulkarim Karim", - "author_inst": "Jagiellonian University" - }, - { - "author_name": "Leanid Kresik", - "author_inst": "Jagiellonian University" - }, - { - "author_name": "Kinga Lis", - "author_inst": "Jagiellonian University" - }, - { - "author_name": "Igor Minia", - "author_inst": "Berlin Institute for Medical Systems Biology" - }, - { - "author_name": "Kinga Hartman", - "author_inst": "AGH University of Science and Technology" - }, - { - "author_name": "Ravi Sonani", - "author_inst": "Jagiellonian University" - }, - { - "author_name": "Grzegorz Dubin", - "author_inst": "Jagiellonian University" - }, - { - "author_name": "Michael Sattler", - "author_inst": "Helmholtz Zentrum Munchen" - }, - { - "author_name": "Piotr Suder", - "author_inst": "AGH University of Science and Technology" - }, - { - "author_name": "Pawel Mak", - "author_inst": "Jagiellonian University" + "author_name": "Limei Zou", + "author_inst": "Laboratoire de Biologie Structurale de la Cellule (BIOC), CNRS, Ecole polytechnique, IP Paris" }, { - "author_name": "Grzegorz Popowicz", - "author_inst": "Helmholtz Zentrum Munchen" + "author_name": "Clara Moch", + "author_inst": "Laboratoire de Biologie Structurale de la Cellule (BIOC), CNRS, Ecole polytechnique, IP Paris" }, { - "author_name": "Krzysztof Pyrc", - "author_inst": "Jagiellonian University" + "author_name": "Marc GRAILLE", + "author_inst": "Ecole Polytechnique, CNRS-UMR7654" }, { - "author_name": "Anna Czarna", - "author_inst": "Jagiellonian University" + "author_name": "Clement Chapat", + "author_inst": "Laboratoire de Biologie Structurale de la Cellule (BIOC), CNRS, Ecole polytechnique, IP Paris" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "new results", - "category": "microbiology" + "category": "cell biology" }, { "rel_doi": "10.1101/2022.01.25.477784", @@ -411449,27 +410900,59 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2022.01.25.477671", - "rel_title": "Structural insight into antibody evasion of SARS-CoV-2 omicron variant", + "rel_doi": "10.1101/2022.01.24.22269676", + "rel_title": "Projection of Healthcare Demand in Germany and Switzerland Urged by Omicron Wave (January-March 2022)", "rel_date": "2022-01-25", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.01.25.477671", - "rel_abs": "The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) continues to mutate and evolve with the emergence of omicron (B.1.1.529) as the new variant of concern. The rapid spread of this variant regionally and globally could be an allusion to increased infectivity, transmissibility, and antibody resistance. The omicron variant has a large set of mutations in its spike protein, specifically in the receptor binding domain (RBD), reflecting their significance in ACE2 interaction and antibody recognition. We have carried out the present study to understand how these mutations structurally impact the binding of the antibodies to their target epitope. We have computationally evaluated the binding of different classes of RBD targeted antibodies, namely, CB6 (etesevimab), REGN10933 (casirivimab), S309 (sotrovimab), and S2X259 to the omicron mutation-induced RBD. Molecular dynamics simulations and binding free energy calculations unveil the binding affinity and stability of the antibody-RBD complexes. All the four antibodies show reduced binding affinity towards the omicron RBD. The therapeutic antibody CB6 aka etesevimab was substantially affected due to numerous omicron mutations occurring in its target epitope. This study provides a structural insight into the reduced efficacy of RBD targeting antibodies against the SARS-CoV-2 omicron variant.", - "rel_num_authors": 2, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.24.22269676", + "rel_abs": "After the implementation of broad vaccination programs, there is an urgent need to understand how the population immunity affects the dynamics of the COVID-19 pandemic in presence of the protection waning and of the emergence of new vari-ants of concern. In the current Omicron wave that is propagating across Europe, assessing the risk of saturation of the healthcare systems is crucial for pandemic management, as it allows us to support the transition towards the endemic course of SARS-CoV-2 and implement more refined mitigation strategies that shield the most vulnerable groups and protect the healthcare systems. We investigated the current pandemic dynamics by means of compartmental models that describe the age-stratified social-mixing, and consider vaccination status, vaccine types, and their waning efficacy. Our goal is to provide insight into the plausible scenarios that are likely to be seen in Switzerland and Germany in the coming weeks and help take informed decisions. Despite the huge numbers of new positive cases, our results suggest that the current wave is unlikely to create an overwhelming health-care demand: owing to the lower hospitalization rate of the novel variant and the effectiveness of the vaccines. Our findings are robust with respect to the plausible variability of the main parameters that govern the severity and the progression of the Omicron infection. In a broader context, our framework can be applied also to future endemic scenarios, offering quantitative support for refined public health interventions in response to recurring COVID-19 waves.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Jyoti Verma", - "author_inst": "Jawaharlal Nehru University" + "author_name": "Hossein Gorji", + "author_inst": "Empa" }, { - "author_name": "Naidu Subbarao", - "author_inst": "Jawaharlal Nehru University" + "author_name": "No\u00e9 Stauffer", + "author_inst": "Empa" + }, + { + "author_name": "Ivan Lunati", + "author_inst": "Empa" + }, + { + "author_name": "Alexa Caduff", + "author_inst": "Department of Justice, Security and Health, Canton Grisons, Switzerland" + }, + { + "author_name": "Martin B\u00fchler", + "author_inst": "\u00fc" + }, + { + "author_name": "Doortje Engel", + "author_inst": "Department of Justice, Security and Health, Canton Grisons, Switzerland" + }, + { + "author_name": "Ho Ryun Chung", + "author_inst": "Philipps University Marburg" + }, + { + "author_name": "Orestis Loukas", + "author_inst": "Philipps University Marburg" + }, + { + "author_name": "Sabine Feig", + "author_inst": "Philipps University Marburg" + }, + { + "author_name": "Harald Renz", + "author_inst": "Philipps University Marburg" } ], "version": "1", "license": "cc_by_nc_nd", - "type": "new results", - "category": "bioinformatics" + "type": "PUBLISHAHEADOFPRINT", + "category": "epidemiology" }, { "rel_doi": "10.1101/2022.01.25.22269717", @@ -413199,75 +412682,39 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2022.01.22.22269701", - "rel_title": "Effectiveness of BBV152 vaccine against SARS-CoV-2 infections, hospitalizations, and deaths among healthcare workers in the setting of high delta variant transmission in New Delhi, India", + "rel_doi": "10.1101/2022.01.23.22269719", + "rel_title": "Should healthcare workers with SARS-CoV-2 household exposures work? A Cohort Study.", "rel_date": "2022-01-24", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.22.22269701", - "rel_abs": "BackgroundDelta variant transmission resulted in surge of SARS CoV-2 cases in New Delhi, India during the early half of year 2021. Health Care Workers (HCWs) received vaccines on priority for prevention of infection. Real life effectiveness of BBV152 vaccine against severe disease including hospitalization and death was not known.\n\nObjectiveTo estimate effectiveness of BBV152 vaccine among HCWs against SARS CoV-2 infection, hospitalization or death\n\nDesignObservational study\n\nSettinga multi -speciality tertiary care public funded hospital in New Delhi, India.\n\nParticipants12,237 HCWs\n\nInterventionsBBV152 vaccine (Covaxin, Bharat Biotech limited, Hyderabad, India); whole virion inactivated vaccine; two doses four weeks apart\n\nMeasurementsvaccine effectiveness after receipt of two doses of BBV152 protecting against any SARS CoV-2 infection, symptomatic infections or hospitalizations or deaths, and hospitalizations or deaths.\n\nResultsThe mean age of HCWs was 36({+/-}11) years, 66% were men and 16% had comorbidity. After adjusting for potential covariates viz age, sex, health worker type category, body mass index, and comorbidity, the vaccine effectiveness (95% Confidence Interval) in fully vaccinated HCWs and [≥]14 days elapsed after the receipt of second dose was 44% (37 to 51, p<0.001) against symptomatic infection, hospitalization or death due to SARS CoV-2, and 61% (37 to 76, p<0.001) against hospitalization or death, respectively.\n\nConclusionsBBV152 vaccine with complete two doses offer a modest response to SARS CoV-2 infection in real life situations against a backdrop of high delta variant community transmission. Efforts in maximizing receipt of full vaccines should be invested for HCWs, who are at higher occupational risk for infection.", - "rel_num_authors": 14, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.23.22269719", + "rel_abs": "ImportanceDue to high community transmission of the Omicron variant, healthcare workers (HCWs) have been increasingly reporting household exposures to confirmed COVID-19 cases. Quebec (Canada) provincial guidelines required to quarantine these HCWs. Facing the risk of staffing shortages, our hospital decided to allow them to work.\n\nObjectiveTo evaluate the risk for HCWs, who were household contacts, to become positive for COVID-19 by RT-PCR and evaluate the risk of nosocomial COVID-19 transmission.\n\nDesignCohort of HCWs with a history of household exposure to a confirmed case of COVID-19.\n\nSettingCHU Sainte-Justine, a tertiary care mother and child center in Montreal (QC) Canada\n\nParticipantsConsecutive HCWs who contacted OHS between December 20, 2021 and January 17, 2022 for a history of household exposure to COVID-19.\n\nExposureConfirmed case of COVID-19 in the household\n\nMain outcome and measuresThe main outcome was a positive RT-PCR for SARS-CoV-2. Outbreaks and nosocomial cases were identified through daily analysis of COVID-19 cases, by sector and part of the usual Infection Prevention and Control surveillance process.\n\nResultsOverall, 237 of 475 (50%) HCWs who declared a known household contact with a confirmed COVID-19 case remained negative. Of those who became positive, 196 (82.4%) were positive upon initial testing and were quarantined. Only 42 (15%) of 279 HCWs who were allowed to work became positive, a median of 4 days after the initial test. The absence of symptoms at initial evaluation (OR 3.8, 95% CI 2.5-5.7) and having received a third vaccine dose more than 7 days before (OR 1.88, 95% CI 1.3 - 2.8) were associated with an increased odds of remaining negative. There was no outbreak among HCWs and no nosocomial transmission to patients from a HCW that was allowed to work, while a known household contact.\n\nConclusion and relevanceMeasures taken to protect the health care environment from COVID-19 must be cautiously balanced with the risk of staffing shortage. Allowing vaccinated asymptomatic HCWs who are known household contacts of confirmed COVID-19 cases to work is likely a safe alternative, when staff shortage is anticipated.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Sumit Malhotra", - "author_inst": "All India Institute of Medical Sciences, New Delhi" - }, - { - "author_name": "Kalaivani Mani", - "author_inst": "All India Institute of Medical Sciences, New Delhi" - }, - { - "author_name": "Rakesh Lodha", - "author_inst": "All India Institute of Medical Sciences, New Delhi" - }, - { - "author_name": "Sameer Bakhshi", - "author_inst": "All India Institute of Medical Sciences, New Delhi" - }, - { - "author_name": "Vijay Prakash Mathur", - "author_inst": "All India Institute of Medical Sciences, New Delhi" - }, - { - "author_name": "Pooja Gupta", - "author_inst": "All India Institute of Medical Sciences, New Delhi" - }, - { - "author_name": "Saurabh Kedia", - "author_inst": "All India Institute of Medical Sciences, New Delhi" - }, - { - "author_name": "Jeeva Sankar", - "author_inst": "All India Institute of Medical Sciences, New Delhi" - }, - { - "author_name": "Parmeshwar Kumar", - "author_inst": "All India Institute of Medical Sciences, New Delhi" - }, - { - "author_name": "Arvind Kumar", - "author_inst": "All India Institute of Medical Sciences, New Delhi" + "author_name": "Caroline Quach", + "author_inst": "University of Montreal" }, { - "author_name": "Vineet Ahuja", - "author_inst": "All India Institute of Medical Sciences, New Delhi" + "author_name": "Ana C. Blanchard", + "author_inst": "University of Montreal" }, { - "author_name": "Subrata Sinha", - "author_inst": "All India Institute of Medical Sciences, New Delhi" + "author_name": "Josee Lamarche", + "author_inst": "CHU Sainte-Justine" }, { - "author_name": "Randeep Guleria", - "author_inst": "All India Institute of Medical Sciences, New Delhi" + "author_name": "Nathalie Audy", + "author_inst": "CHU Sainte-Justine" }, { - "author_name": "- COVID Reinfection AIIMS Consortium", - "author_inst": "" + "author_name": "Valerie Lamarre", + "author_inst": "CHU Sainte-Justine" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "occupational and environmental health" }, { "rel_doi": "10.1101/2022.01.23.22269706", @@ -415109,69 +414556,81 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2022.01.19.22269391", - "rel_title": "COVID-19 and its clinical severity are associated with alterations of plasma sphingolipids and enzyme activities of sphingomyelinase and ceramidase", + "rel_doi": "10.1101/2022.01.14.22269289", + "rel_title": "Serological study of CoronaVac vaccine and booster doses in Chile: immunogenicity and persistence of anti-SARS-CoV-2 S antibodies", "rel_date": "2022-01-23", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.19.22269391", - "rel_abs": "In the current pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2; COVID-19), a better understanding of the underlying mechanisms is essential to reduce morbidity and mortality and treat post-COVID-19 disease. Here, we analyzed alterations of sphingolipids and their metabolizing enzymes in 125 men and 74 women tested positive for SARS-CoV-2 and hospitalized with mild, moderate or severe symptoms or after convalescence.\n\nThe activities of acid and neutral sphingomyelinases (ASM, NSM), which hydrolyze sphingomyelin to ceramide, were significantly increased in COVID-19 patients, while the activity of neutral ceramidase (NC), which hydrolyzes ceramide to sphingosine, was reduced. These alterations could each contribute to elevated ceramide levels in patients. Accordingly, liquid chromatography tandem-mass spectrometry (LC-MS/MS) yielded increased levels of ceramides 16:0 and 18:0 with highest levels in severely affected patients and similar effects for dihydroceramides 16:0 and 18:0, whereas levels of (dihydro-)ceramides 24:0 were reduced. Furthermore, sphingomyelin 20:0; 22:0 and 24:0 as substrates of ASM and NSM as well as their dihydrosphingomyelin counterparts were reduced in patients as well as sphingosine-1-phosphate further downstream of NC activity. Effects of NSM, NC, ceramides and sphingomyelins remained significant after Bonferroni correction. SARS-CoV-2 antibody levels in convalescent patients were associated with age but none of the sphingolipid parameters. Based on our data, COVID-19 is associated with a dysregulation of sphingolipid homeostasis in a severity-dependent manner, particularly focused around a reduction of sphingomyelins and an accumulation of ceramides by increased enzyme activities leading to ceramide elevation (ASM, NSM) combined with a decreased activity of enzymes (NC) reducing ceramide levels. The potential of a combined sphingolipid/enzyme pattern as a diagnostic and prognostic marker and therapeutic target deserves further exploration.", - "rel_num_authors": 13, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.14.22269289", + "rel_abs": "BackgroundChile was severely affected by COVID19 outbreaks but was also one of the first countries to start a nationwide program to vaccinate against the disease. Furthermore, Chile became one of the fastest countries to inoculate a high percentage of the target population and implemented homologous and heterologous booster schemes in late 2021 to prevent potential immunological waning. The aim of this study is to compare the immunogenicity and time course of the humoral response elicited by the CoronaVac vaccine in combination with homologous versus heterologous boosters.\n\nMethods and FindingsWe compared the immunogenicity of two doses of CoronaVac and BNT162b2 vaccines and studied the effect of different booster regimes in the Chilean population. Our results demonstrate that a two-dose vaccination scheme with CoronaVac induces lower levels of anti-SARS-CoV-2 S antibodies than BNT162b2 in a broad age range. Furthermore, antibody production declines with time in individuals vaccinated with CoronaVac and less noticeably, with BNT162b2. Remarkably, analysis of booster schemes revealed that individuals vaccinated with two doses of CoronaVac generate immunological memory against the SARS-CoV-2 ancestral strain, which can be re-activated with homologous or heterologous (BNT162b2 and ChAdOx1) boosters. Nevertheless, the magnitude of the antibody response with the heterologous booster regime was considerably higher and persistent (over 100 days) than the responses induced by the homologous scheme.\n\nConclusionsTwo doses of CoronaVac induces antibody titers against the SARS-CoV-2 ancestral strain which are lower in magnitude than those induced by the BNT162b2 vaccine. However, the response induced by CoronaVac can be greatly potentiated with a heterologous booster scheme with BNT162b2 or ChAdOx1 vaccines. Furthermore, the heterologous booster regimes induce a durable antibody response which does not show signs of decay 3 months after the booster dose.", + "rel_num_authors": 16, "rel_authors": [ { - "author_name": "Christiane M\u00fchle", - "author_inst": "Universit\u00e4tsklinikum Erlangen and Friedrich-Alexander University Erlangen-N\u00fcrnberg (FAU)" + "author_name": "Leonardo Vargas", + "author_inst": "Laboratory of Immunology, Biology Department, Faculty of Sciences, Universidad de Chile." }, { - "author_name": "Andreas Kremer", - "author_inst": "Department of Medicine 1, Universit\u00e4tsklinikum Erlangen and Friedrich-Alexander University Erlangen-N\u00fcrnberg (FAU), Germany and Department of Gastroenterology a" + "author_name": "Nicolas Valdivieso", + "author_inst": "Laboratory of Immunology, Biology Department, Faculty of Sciences, Universidad de Chile" }, { - "author_name": "Marcel Vetter", - "author_inst": "Department of Medicine 1, Universit\u00e4tsklinikum Erlangen and Friedrich-Alexander University Erlangen-N\u00fcrnberg (FAU)" + "author_name": "Fabian Tempio", + "author_inst": "Laboratory of Cancer Immunoediting, Immunology Program, Institute of Biomedical Sciences, Faculty of Medicine, Universidad de Chile." }, { - "author_name": "Jonas Schmid", - "author_inst": "Department of Medicine 1, Universit\u00e4tsklinikum Erlangen and Friedrich-Alexander University Erlangen-N\u00fcrnberg (FAU)" + "author_name": "Valeska Simon", + "author_inst": "Laboratory of Immunology, Biology Department, Faculty of Sciences, Universidad de Chile." }, { - "author_name": "Susanne Achenbach", - "author_inst": "Department of Transfusion Medicine, Universit\u00e4tsklinikum Erlangen and Friedrich-Alexander University Erlangen-N\u00fcrnberg (FAU), German" + "author_name": "Daniela Sauma", + "author_inst": "Laboratory of Immunology, Biology Department, Faculty of Sciences, Universidad de Chile." }, { - "author_name": "Fabian Schumacher", - "author_inst": "Freie Universit\u00e4t Berlin, Institute of Pharmacy, K\u00f6nigin-Luise-Str. 2+4, 14195 Berlin, Germany" + "author_name": "Lucia Valenzuela", + "author_inst": "Immunogastroenterology Lab., Gastroenterology Unit, Hospital Clinico Universidad de Chile, Facullty of Medicine, Universidad de Chile" }, { - "author_name": "Bernd Lenz", - "author_inst": "Department of Addictive Behavior and Addiction Medicine, Central Institute of Mental Health (CIMH), Medical Faculty Mannheim, Heidelberg University, Germany" + "author_name": "Caroll Beltran", + "author_inst": "Immunogastroenterology Lab., Gastroenterology Unit, Hospital Clinico Universidad de Chile, Facullty of Medicine, Universidad de Chile" }, { - "author_name": "C\u00e9line Cougoule", - "author_inst": "Institut de Pharmacologie et de Biologie Structurale, IPBS, Universit\u00e9 de Toulouse, Toulouse, France" + "author_name": "Loriana Castillo-Delgado", + "author_inst": "Hospital Clinico Metropolitano La Florida Dra. Eloisa Diaz I." }, { - "author_name": "Nicolas Hoertel", - "author_inst": "Universit\u00e9 de Paris, AP-HP, H\u00f4pital Corentin-Celton, DMU Psychiatrie et Addictologie, D\u00e9partement de Psychiatrie, INSERM, Institut de Psychiatrie et Neuroscienc" + "author_name": "Ximena Contreras-Benavides", + "author_inst": "Hospital Clinico Metropolitano La Florida Dra. Eloisa Diaz I." }, { - "author_name": "Alexander Carpinteiro", - "author_inst": "Department of Hematology and Stem Cell Transplantation, University Hospital Essen, University of Duisburg-Essen, Essen, Germany and Institute for Molecular Biol" + "author_name": "Monica L. Acevedo", + "author_inst": "Laboratory of Molecular and Cellular Virology, Virology Program, Institute of Biomedical Sciences, Faculty of Medicine, Universidad de Chile." }, { - "author_name": "Erich Gulbins", - "author_inst": "Institute for Molecular Biology, University Medicine Essen, University of Duisburg- Essen, Essen, Germany" + "author_name": "Fernando Valiente-Echeverria", + "author_inst": "Laboratory of Molecular and Cellular Virology, Virology Program, Institute of Biomedical Sciences, Faculty of Medicine, Universidad de Chile." }, { - "author_name": "Burkhard Kleuser", - "author_inst": "Freie Universit\u00e4t Berlin, Institute of Pharmacy, K\u00f6nigin-Luise-Str. 2+4, 14195 Berlin, Germany" + "author_name": "Ricardo Soto-Rifo", + "author_inst": "Laboratory of Molecular and Cellular Virology, Virology Program, Institute of Biomedical Sciences, Faculty of Medicine, Universidad de Chile." }, { - "author_name": "Johannes Kornhuber", - "author_inst": "Department of Psychiatry and Psychotherapy, Universit\u00e4tsklinikum Erlangen and Friedrich-Alexander University Erlangen-N\u00fcrnberg (FAU), Germany" + "author_name": "Rafael I Gonzalez", + "author_inst": "Centro de Nanotecnologia Aplicada, Universidad Mayor, Santiago, Chile. Center for the Development of Nanoscience and Nanotechnology, CEDENNA." + }, + { + "author_name": "Mercedes Lopez", + "author_inst": "Laboratory of Cancer Immunoediting, Immunology Program, Institute of Biomedical Sciences, Faculty of Medicine, Universidad de Chile." + }, + { + "author_name": "Fabiola Osorio", + "author_inst": "Laboratory of Immunology and Cellular Stress, Immunology Program, Institute of Biomedical Sciences, Faculty of Medicine, University of Chile." + }, + { + "author_name": "Maria Rosa Bono", + "author_inst": "Laboratory of Immunology, Biology Department, Faculty of Sciences, Universidad de Chile." } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -417131,93 +416590,49 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.01.18.22269501", - "rel_title": "Seroprevalence of anti-SARS coronavirus 2 antibodies in Thai adults during the first three epidemic waves", + "rel_doi": "10.1101/2022.01.18.22269330", + "rel_title": "Effectiveness of COVID-19 Vaccines in preventing Infectiousness, Hospitalization and Mortality: A Historical Cohort Study Using Iranian Registration Data During Vaccination program", "rel_date": "2022-01-21", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.18.22269501", - "rel_abs": "This study sought to determine the anti-SARS-CoV-2 antibody status of 4111 Thai people from May 2020 to April 2021, a period which spanned the first two and part of the third epidemic wave of the COVID-19 in Thailand. Participants comprised 142 COVID-19 patients, 2113 individuals at risk due to their occupations [health personnel, airport officers, public transport drivers, and workers in entertainment venues (pubs, bars and massage parlors)], 1856 individuals at risk due to sharing workplaces or living communities with COVID-19 patients, and 553 Thai citizens returning after extended periods in countries with a high disease prevalence. All sera were tested in a microneutralization assay and a chemiluminescence immunoassay (CLIA) for IgG against the N protein. Furthermore, we performed an immunofluorescence assay to resolve discordant results between the two assays. Antibody responses developed in 88% (15 of 17) of COVID-19 patients at 8 days and in 94-100% between 15 and 60 days after disease onset. Neutralizing antibodies persisted for at least 8 months, longer than the IgG did, against the N protein. None of the health providers, airport officers, and public transport drivers were seropositive, while the antibodies were present in 0.44% of entertainment workers. This study showed the seropositivity of 1.9, 1.5, and 7.5% during the 3 epidemic waves, respectively, in Bangkok residents who were at risk due to sharing workplaces or communities with COVID-19 patients. Also, antibody prevalence was 1.3% in Chiang Mai people during the first epidemic wave, and varied between 6.5 and 47.0% in Thais returning from high-risk countries. This serosurveillance study found a low infection rate of SARS-CoV-2 in Thailand before the emergence of the Delta variant in late May 2021. The findings support the Ministry of Public Healths data, which are based on numbers of patients and contact tracing.", - "rel_num_authors": 19, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.18.22269330", + "rel_abs": "BackgroundThere are some concerns about the effectiveness of the inactivated and vector-based vaccines against SARS-CoV-2 in the real-world settings with the emergence of new mutations, especially variants of concern. Data derived from administrative repositories during mass-vaccination campaigns or programs are of interest to study vaccine effectiveness (VE).\n\nMethodsUsing 4-repository administrative data linkage, we conducted a historical cohort study on a target population of 3,628,857 inhabitants aged at least 18 years residing in Southern Iran.\n\nResultsWe estimated 71.9% [95% CI: 70.7-73.1%], 81.5% [95% CI: 79.5-83.4%], 67.5% [95% CI: 59.5-75.6%], and 86.4% [95% CI: 84.1-88.8%] hospitalization reduction for those who received the full vaccination schedule of BIBP-CorV, ChAdOx1-S/nCoV-19, rAd26-rAd5, and BIV1-CovIran vaccines, respectively. A high reduction in mortality - at least 85% - was observed in all age subgroups of fully immunized population.\n\nConclusionThe pragmatic implementation of a vaccination plan including all available vaccine options in the Iranian population was associated with a significant reduction in documented COVID-19 infection, hospitalization, and death associated with COVID-19.\n\nKey pointsThe mass vaccination program with implementing a group of vaccines, that even for some of them (rAd26-rAd5, and BIV1-CovIran vaccines) have been only regionally authorized for emergency use, has been associated with a dramatic reduction in documented COVID-19 infection, as well as in hospitalization and deaths related to the COVID-19 diagnosis.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Hatairat Lerdsamran", - "author_inst": "Mahidol University" - }, - { - "author_name": "Anek Mungaomklang", - "author_inst": "Royal Thai Government Ministry of Public Health" - }, - { - "author_name": "Sopon Iamsirithaworn", - "author_inst": "Royal Thai Government Ministry of Public Health" - }, - { - "author_name": "Jarunee Prasertsopon", - "author_inst": "Mahidol University" - }, - { - "author_name": "Witthawat Wiriyarat", - "author_inst": "Mahidol University" - }, - { - "author_name": "Suthee Saritsiri", - "author_inst": "Bangkok Metropolitan Administration" - }, - { - "author_name": "Ratikorn Anusorntanawat", - "author_inst": "Royal Thai Government Ministry of Public Health" + "author_name": "Alireza Mirahmadizadeh", + "author_inst": "Non-communicable Diseases Research Center, Shiraz University of Medical Sciences, Shiraz, Iran" }, { - "author_name": "Nirada Siriyakorn", - "author_inst": "Royal Thai Government Ministry of Public Health" - }, - { - "author_name": "Poj Intalapaporn", - "author_inst": "Royal Thai Government Ministry of Public Health" - }, - { - "author_name": "Somrak Sirikhetkon", - "author_inst": "Royal Thai Government Ministry of Public Health" + "author_name": "Alireza Heiran", + "author_inst": "Non-communicable Diseases Research Center, Shiraz University of Medical Sciences, Shiraz, Iran" }, { - "author_name": "Kantima Sangsiriwut", - "author_inst": "Mahidol University" + "author_name": "Kamran Bagheri Lankarani", + "author_inst": "Health Policy Research Center, Shiraz University of Medical Sciences, Shiraz, Iran" }, { - "author_name": "Worawat Dangsakul", - "author_inst": "Royal Thai Government Ministry of Public Health" + "author_name": "Mohammadreza Serati", + "author_inst": "Statistics and Information Technology Management, Shiraz University of Medical Sciences, Shiraz, Iran" }, { - "author_name": "Suteema Sawadpongpan", - "author_inst": "Mahidol University" - }, - { - "author_name": "Nattakan Thinpan", - "author_inst": "Mahidol University" - }, - { - "author_name": "Pilailuk Okada", - "author_inst": "Royal Thai Government Ministry of Public Health" - }, - { - "author_name": "Ranida Techasuwanna", - "author_inst": "Royal Thai Government Ministry of Public Health" + "author_name": "Mohammad Habibi", + "author_inst": "Statistics and Information Technology Management, Shiraz University of Medical Sciences, Shiraz, Iran" }, { - "author_name": "Noparat Mongkalangoon", - "author_inst": "Royal Thai Government Ministry of Public Health" + "author_name": "Owrang Eilami", + "author_inst": "Shiraz University of Medical Sciences, Shiraz, Iran (O. Eilami); Medis Holding, Shiraz, Iran" }, { - "author_name": "Kriengkrai Prasert", - "author_inst": "Royal Thai Government Ministry of Public Health" + "author_name": "Fatemeh Heiran", + "author_inst": "University of Isfahan, Isfahan, Iran" }, { - "author_name": "Pilaipan Puthavathana", - "author_inst": "Mahidol University Faculty of Medical Technology" + "author_name": "Mohsen Moghadami", + "author_inst": "Health Policy Research Center, Shiraz University of Medical Sciences, Shiraz, Iran" } ], "version": "1", - "license": "cc_by", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -418997,67 +418412,79 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2022.01.19.477009", - "rel_title": "Computation of Antigenicity Predicts SARS-CoV-2 Vaccine Breakthrough Variants", + "rel_doi": "10.1101/2022.01.18.476864", + "rel_title": "Longitudinal Assessment of SARS-CoV-2 Specific T Cell Cytokine-Producing Responses for 1 Year Reveals Persistence of Multi-Cytokine Proliferative Responses, with Greater Immunity Associated with Disease Severity", "rel_date": "2022-01-20", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.01.19.477009", - "rel_abs": "It has been reported that multiple SARS-CoV-2 variants of concerns (VOCs) including B.1.1.7 (Alpha), B.1.351 (Beta), P.1 (Gamma), and B.1.617.2 (Delta) can reduce neutralisation by antibodies, resulting in vaccine breakthrough infections. Virus-antiserum neutralisation assays are typically performed to monitor potential vaccine breakthrough strains. However, such experimental-based methods are slow and cannot instantly validate whether newly emerging variants can break through current vaccines or therapeutic antibodies. To address this, we sought to establish a computational model to predict the antigenicity of SARS-CoV-2 variants by sequence alone and in real time. In this study, we firstly identified the relationship between the antigenic difference transformed from the amino acid sequence and the antigenic distance from the neutralisation titres. Based on this correlation, we obtained a computational model for the receptor binding domain (RBD) of the spike protein to predict the fold decrease in virus-antiserum neutralisation titres with high accuracy (~0.79). Our predicted results were comparable with experimental neutralisation titres of variants, including B.1.1.7 (Alpha), B.1.351 (Beta), B.1.617.2 (Delta), B.1.429 (Epsilon), P.1 (Gamma), B.1.526 (Iota), B.1.617.1 (Kappa), and C.37 (Lambda), as well as SARS-CoV. Here, we firstly predicted the fold of decrease of B.1.1.529 (Omicron) as 17.4-fold less susceptible to neutralisation. We visualised all 1521 SARS-CoV-2 lineages to indicate variants including B.1.621 (Mu), B.1.630, B.1.633, B.1.649, and C.1.2, which can induce vaccine breakthrough infections in addition to reported VOCs B.1.351 (Beta), P.1 (Gamma), B.1.617.2 (Delta), and B.1.1.529 (Omicron). Our study offers a quick approach to predict the antigenicity of SARS-CoV-2 variants as soon as they emerge. Furthermore, this approach can facilitate future vaccine updates to cover all major variants. An online version can be accessed at http://jdlab.online.", - "rel_num_authors": 12, + "rel_link": "https://biorxiv.org/cgi/content/short/2022.01.18.476864", + "rel_abs": "Cellular-mediated immunity is critical for long-term protection against most viral infections, including coronaviruses. We studied 23 SARS-CoV-2-infected survivors over a one year post symptom onset (PSO) interval by ex vivo cytokine ELISpot assay. All subjects demonstrated SARS-CoV-2-specific IFN-{gamma}, IL-2, and Granzyme B (GzmB) T cell responses at presentation, with greater frequencies in severe disease. Cytokines, mainly produced by CD4+ T cells, targeted all structural proteins (Nucleocapsid, Membrane, Spike) except Envelope, with GzmB > IL-2 > IFN-{gamma}. Mathematical modeling predicted that: 1) cytokine responses peaked at 6 days for IFN-{gamma}, 36 days for IL-2, and 7 days for GzmB, 2) severe illness was associated with reduced IFN-{gamma} and GzmB, but increased IL-2 production rates, 3) males displayed greater production of IFN-{gamma}, whereas females produced more GzmB. Ex vivo responses declined over time with persistence of IL-2 in 86% and of IFN-{gamma} and GzmB in 70% of subjects at a median of 336 days PSO. The average half-life of SARS-CoV-2-specific cytokine-producing cells was modelled to be 139 days ([~]4.6 months). Potent T cell proliferative responses persisted throughout observation, were CD4 dominant, and were capable of producing all 3 cytokines. Several immunodominant CD4 and CD8 epitopes identified in this study were shared by seasonal coronaviruses or SARS-CoV-1 in the Nucleocapsid and Membrane regions. Both SARS-CoV-2-specific CD4+ and CD8+ T cell clones were able to kill target cells, though CD8 tended to be more potent.\n\nImportanceOur findings highlight the relative importance of SARS-CoV-2-specific GzmB-producing T cell responses in SARS-CoV-2 control, shared CD4 and CD8 immunodominant epitopes in seasonal coronaviruses or SARS-CoV-1, and indicate robust persistence of T cell memory at least one year after infection. Our findings should inform future strategies to induce T cell vaccines against SARS-CoV-2 and other coronaviruses.", + "rel_num_authors": 15, "rel_authors": [ { - "author_name": "Ye-fan Hu", - "author_inst": "The University of Hong Kong" + "author_name": "Jonah Lin", + "author_inst": "University of Toronto" }, { - "author_name": "Jing-chu Hu", - "author_inst": "Shenzhen Institutes of Advanced Technology" + "author_name": "Ryan Law", + "author_inst": "University of Toronto" }, { - "author_name": "Hua-Rui Gong", - "author_inst": "The University of Hong Kong" + "author_name": "Chapin Korosec", + "author_inst": "York University" }, { - "author_name": "Antoine Danchin", - "author_inst": "CNRS / Institut Pasteur" + "author_name": "Christine Zhou", + "author_inst": "University of Toronto" }, { - "author_name": "Ren Sun", - "author_inst": "The University of Hong Kong" + "author_name": "Wan Han Koh", + "author_inst": "University of Toronto" }, { - "author_name": "Hin Chu", - "author_inst": "The University of Hong Kong" + "author_name": "Mohammad Sajjad Ghaemi", + "author_inst": "National Research Council Canada" }, { - "author_name": "Ivan Fan-Ngai Hung", - "author_inst": "The University of Hong Kong" + "author_name": "Philip Samaan", + "author_inst": "University of Toronto" }, { - "author_name": "Kwok Yung Yuen", - "author_inst": "The University of Hong Kong" + "author_name": "Hsu Kiang Ooi", + "author_inst": "National Research Council Canada" }, { - "author_name": "Kelvin Kai-Wang To", - "author_inst": "University of Hong Kong" + "author_name": "Feng-Yun Yue", + "author_inst": "University of Toronto" }, { - "author_name": "Bao-Zhong Zhang", - "author_inst": "Shenzhen Institutes of Advanced Technology" + "author_name": "Anne-Claude Gingras", + "author_inst": "Samuel Lunenfeld Research Institute at Mount Sinai Hospital" }, { - "author_name": "Thomas Yau", - "author_inst": "The University of Hong Kong" + "author_name": "Samira Mubareka", + "author_inst": "Sunnybrook Health Science Centre" }, { - "author_name": "Jian-Dong Huang", - "author_inst": "The University of Hong Kong" + "author_name": "Allison McGeer", + "author_inst": "Mount Sinai Hospital" + }, + { + "author_name": "Jerome Leis", + "author_inst": "SunnybrookHealth Sciences Centre" + }, + { + "author_name": "Jane M. Heffernan", + "author_inst": "York University" + }, + { + "author_name": "Mario Ostrowski", + "author_inst": "University of Toronto" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by_nc_nd", "type": "new results", - "category": "evolutionary biology" + "category": "immunology" }, { "rel_doi": "10.1101/2022.01.20.477038", @@ -421081,12 +420508,12 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2022.01.17.22269421", - "rel_title": "Estimation of the COVID-19 Average Incubation Time:Systematic Review, Meta-analysis and SensitivityAnalyses", + "rel_doi": "10.1101/2022.01.17.22269222", + "rel_title": "The value of vaccine booster doses to mitigate the global impact of the Omicron SARS-CoV-2 variant", "rel_date": "2022-01-18", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.17.22269421", - "rel_abs": "ObjectivesWe aim to provide sensible estimates of the average incubation time of COVID-19 by capitalizing available estimates reported in the literature and explore different ways to accommodate heterogeneity involved with the reported studies.\n\nMethodsWe search through online databases to collect the studies about estimates of the average incubation time and conduct meta-analyses to accommodate heterogeneity of the studies and the publication bias. Cochrans heterogeneity statistic Q and Higgins & Thompsons I2 statistic are employed. Subgroup analyses are conducted using mixed effects models and publication bias is assessed using the funnel plot and Eggers test.\n\nResultsUsing all those reported mean incubation estimates, the average incubation time is estimated to be 6.43 days with a 95% confidence interval (CI) (5.90, 6.96), and using all those reported mean incubation estimates together with those transformed median incubation estimates, the estimated average incubation time is 6.07 days with a 95% CI (5.70,6.45).\n\nConclusionsProviding sensible estimates of the average incubation time for COVID-19 is important yet complex, and the available results vary considerably due to many factors including heterogeneity and publication bias. We take different angles to estimate the mean incubation time, and our analyses provide estimates to range from 5.68 days to 8.30 days.", + "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.17.22269222", + "rel_abs": "Vaccines have played a central role in mitigating severe disease and death from COVID-19 in the past 12 months. However, efficacy wanes over time and this loss of protection is being compounded by the emergence of the Omicron variant. By fitting an immunological model to population-level vaccine effectiveness data, we estimate that neutralizing antibody titres for Omicron are reduced by 3.9-fold (95% CrI 2.9-5.5) compared to the Delta variant. Under this model, we predict that 90 days after boosting with the Pfizer-BioNTech vaccine, efficacy against severe disease (admission to hospital) declines to 95.9% (95% CrI 95.4%-96.3%) against the Delta variant and 78.8% (95% CrI 75.0%-85.1%) against the Omicron variant. Integrating this immunological model within a model of SARS-CoV-2 transmission, we demonstrate that the size of the Omicron wave will depend on the degree of past exposure to infection across the population, with relatively small Omicron waves in countries that previously experienced a large Delta wave. We show that booster doses can have a major impact in mitigating the epidemic peak, although in many settings it remains possible that healthcare capacity could still be challenged. This is particularly the case in \"zero-COVID\" countries where there is little prior infection-induced immunity and therefore epidemic peaks will be higher. Where dose supply is limited, targeting boosters to the highest risk groups to ensure continued high protection in the face of waning immunity is of greater benefit than giving these doses as primary vaccination to younger age-groups. In many settings it is likely that health systems will be stretched, and it may therefore be necessary to maintain and/or reintroduce some level of NPIs to mitigate the worst impacts of the Omicron variant as it replaces the Delta variant.", "rel_num_authors": 0, "rel_authors": null, "version": "1", @@ -422685,73 +422112,37 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.01.14.21267836", - "rel_title": "Generation of novel SARS-CoV-2 variants on B.1.1.7 lineage in three patients with advanced HIV disease", + "rel_doi": "10.1101/2022.01.14.22269270", + "rel_title": "Validation of a clinical and genetic model for predicting severe COVID-19", "rel_date": "2022-01-15", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.14.21267836", - "rel_abs": "The emergence of new SARS-COV-2 variants is of public health concern in case of vaccine escape. Described are three patients with advanced HIV-1 and chronic SARS-CoV-2 infection in whom there is evidence of selection and persistence of novel mutations which are associated with increased transmissibility and immune escape.", - "rel_num_authors": 14, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.14.22269270", + "rel_abs": "Using nested case-control data from the Lifelines COVID-19 cohort, we undertook a validation study of a clinical and genetic model to predict the risk of severe COVID-19 in people with confirmed COVID-19 and in people with confirmed or self-reported COVID-19. The model performed well in terms of discrimination of cases and controls for all ages (area under the receiver operating characteristic curve [AUC] = 0.680 for confirmed COVID-19 and AUC = 0.689 for confirmed and self-reported COVID-19) and in the age group in which the model was developed (50 years and older; AUC = 0.658 for confirmed COVID-19 and AUC= 0.651 for confirmed and self-reported COVID-19). There was no evidence of over- or under-dispersion of risk scores but there was evidence of overall over-estimation of risk in all analyses (all P < 0.0001). In the light of large numbers of people worldwide remaining unvaccinated and continuing uncertainty regarding vaccine efficacy over time and against variants of concern, identification of people at high risk of severe COVID-19 may encourage the uptake of vaccinations (including boosters) and the use of non-pharmaceutical inventions.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Anna C Riddell", - "author_inst": "Barts Health NHS Trust" - }, - { - "author_name": "Beatrix Kele", - "author_inst": "Barts Health NHS Trust" - }, - { - "author_name": "Kathryn Harris", - "author_inst": "Barts Health NHS Trust" - }, - { - "author_name": "Jon Bible", - "author_inst": "Barts Health NHS Trust" - }, - { - "author_name": "Maurice Murphy", - "author_inst": "Barts Health NHS Trust" - }, - { - "author_name": "Subathira Dakshina", - "author_inst": "Barts Health NHS Trust" - }, - { - "author_name": "Nathaniel Storey", - "author_inst": "Great Ormond Street Hospital for Children NHS Foundation Trust" - }, - { - "author_name": "Dola Owoyemi", - "author_inst": "Barts Health NHS Trust" - }, - { - "author_name": "Corinna Pade", - "author_inst": "Barts and The London School of Medicine and Dentistry Blizard Institute" - }, - { - "author_name": "Joseph M Gibbons", - "author_inst": "Barts and The London School of Medicine and Dentistry Blizard Institute" + "author_name": "Gillian S Dite", + "author_inst": "Genetic Technologies Limited." }, { - "author_name": "David Harrington", - "author_inst": "Barts Health NHS Trust" + "author_name": "Nicholas M Murphy", + "author_inst": "Genetic Technologies Limited" }, { - "author_name": "Eliza Alexander", - "author_inst": "Barts Health NHS Trust" + "author_name": "Erika Spaeth", + "author_inst": "Phenogen Sciences Inc" }, { - "author_name": "\u00c1ine McKnight", - "author_inst": "Barts and The London School of Medicine and Dentistry Blizard Institute" + "author_name": "Richard Allman", + "author_inst": "Genetic Technologies Limited" }, { - "author_name": "Teresa Cutino-Moguel", - "author_inst": "Barts Health NHS Trust" + "author_name": "- Lifelines Corona Research Initiative", + "author_inst": "" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -424495,43 +423886,63 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2022.01.13.22269198", - "rel_title": "Seasonal Prediction of Omicron Pandemic", + "rel_doi": "10.1101/2022.01.10.22269041", + "rel_title": "Evidence of early community transmission of Omicron (B1.1.529) in Delhi- A city with very high seropositivity and past exposure!", "rel_date": "2022-01-13", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.13.22269198", - "rel_abs": "The ongoing coronavirus disease 2019 (COVID-19) pandemic has pushed the world in the face of another huge outbreak. In order to have a better understanding on the fast transmission of Omicron variant, we made seasonal predictions on the development of Omicron pandemic globally, as well as 11 key countries. The results demonstrated that the pandemic has an exponential-like growth rate at the initial stage of the outbreak, and will have small resurgences around April and June in north hemisphere countries and south hemisphere countries, respectively.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.10.22269041", + "rel_abs": "BackgroundSince identification, infections by new SARS-CoV-2 variant Omicron are rapidly increasing worldwide. There is huge gap of knowledge regarding virus behaviour in the population from low and middle income countries. Delhi being unique population with a high seropositivity and vaccination rate against COVID-19 infection. We aimed to study the epidemiological and clinical presentations of few early cases of community spread of Omicron infection in the state.\n\nMethodsThis is a prospective study where respiratory specimen from all RT-PCR confirmed positive cases between November 25th-December 23rd 2021 collected from five districts of Delhi were subjected to whole genome sequencing. Complete demographic and clinical details were recorded. We also analyzed the formation of local and familial clusters and eventual community transmission.\n\nFindingsOut of the 264 cases included during study period, 68.9% (n=182)were identified as Delta and its sub-lineages while 31.06% (n=82) were Omicron with BA.1 as the predominant sub-lineage (73.1%). Most of the Omicron cases were asymptomatic (n=50,61%) and not requiring any hospitalizations. A total of 72 (87.8%) cases were fully vaccinated. 39.1% (n=32) had a history of travel and/or contacts while 60.9 (n=50) showed a community transmission. A steep increase in the daily progression of Omicron cases with its preponderance in the community was observed from 1.8% to 54%.\n\nInterpretationThis study is among the first from India to provide the evidence of community transmission of Omicron with significantly increased breakthrough infections, decreased hospitalization rates, and lower rate of symptomatic infections among individuals with high seropositivity against SARS-CoV-2 infections.", + "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Jianping Huang Sr.", - "author_inst": "Lanzhou University" + "author_name": "Rahul Garg", + "author_inst": "Institute of Liver and Biliary Sciences, New Delhi, India." }, { - "author_name": "Yingjie Zhao", - "author_inst": "Collaborative Innovation Centre for West Ecological Safety (CIWES), Lanzhou University" + "author_name": "Pramod Gautam", + "author_inst": "Institute of Liver and Biliary Sciences, New Delhi, India." }, { - "author_name": "Li Zhang", - "author_inst": "College of Atmospheric Sciences, Lanzhou University" + "author_name": "Varun Suroliya", + "author_inst": "Institute of Liver and Biliary Sciences, New Delhi, India." }, { - "author_name": "Xu Li", - "author_inst": "College of Atmospheric Sciences, Lanzhou University" + "author_name": "Reshu Agarwal", + "author_inst": "Institute of Liver and Biliary Sciences, New Delhi, India." + }, + { + "author_name": "Arjun Bhugra", + "author_inst": "Institute of Liver and Biliary Sciences, New Delhi, India." }, { - "author_name": "Shuoyuan Gao", - "author_inst": "College of Atmospheric Sciences, Lanzhou University" + "author_name": "Urvinder S. Kaur", + "author_inst": "Institute of Liver and Biliary Sciences, New Delhi, India." }, { - "author_name": "Xiaodong Song", - "author_inst": "Collaborative Innovation Centre for West Ecological Safety (CIWES), Lanzhou University" + "author_name": "Santanu Das", + "author_inst": "Institute of Liver and Biliary Sciences, New Delhi, India." + }, + { + "author_name": "Chhagan Bihari", + "author_inst": "Institute of Liver and Biliary Sciences, New Delhi, India." + }, + { + "author_name": "Anil Agarwal", + "author_inst": "Institute of Liver and Biliary Sciences, New Delhi, India." + }, + { + "author_name": "S. K. Sarin", + "author_inst": "Institute of Liver and Biliary Sciences, New Delhi, India." + }, + { + "author_name": "Ekta Gupta", + "author_inst": "Institute of Liver and Biliary Sciences, New Delhi, India." } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "public and global health" }, { "rel_doi": "10.1101/2022.01.13.22269203", @@ -426769,27 +426180,23 @@ "category": "bioinformatics" }, { - "rel_doi": "10.1101/2022.01.11.475877", - "rel_title": "GenomeBits insight into omicron and delta variants of coronavirus pathogen", + "rel_doi": "10.1101/2022.01.07.475397", + "rel_title": "Investigation of the Effects of N-Linked Glycans on the Stability of the Spike Protein in SARS-CoV-2 by Molecular Dynamics Simulations", "rel_date": "2022-01-12", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.01.11.475877", - "rel_abs": "We apply the new GenomeBits method to uncover underlying genomic features of omicron and delta coronavirus variants. This is a statistical algorithm whose salient feature is to map the nucleotide bases into a finite alternating ({+/-}) sum series of distributed terms of binary (0,1) indicators. We show how by this method, distinctive signals can be uncovered out of the intrinsic data organization of amino acid progressions along their base positions. Results reveal a sort of ordered (or constant) to disordered (or peaked) transition around the coronavirus S-spike protein region. Together with our previous results for past variants of coronavirus: Alpha, Beta, Gamma, Epsilon and Eta, we conclude that the mapping into GenomeBits strands of omicron and delta variants can help to characterize mutant pathogens.", - "rel_num_authors": 2, + "rel_link": "https://biorxiv.org/cgi/content/short/2022.01.07.475397", + "rel_abs": "We perform all-atom molecular dynamics simulations to study the effects of the N-linked glycans on the stability of the spike glycoprotein in SARS-CoV-2. After a 100 ns of simulation on the spike proteins without and with the N-linked glycans, we found that the presence of glycans increases the local stability in their vicinity; even though their effect on the full structure is negligible.\n\nGraphical Abstract\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=95 SRC=\"FIGDIR/small/475397v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (32K):\norg.highwire.dtl.DTLVardef@cb1c1dorg.highwire.dtl.DTLVardef@a2ecbeorg.highwire.dtl.DTLVardef@64db68org.highwire.dtl.DTLVardef@180a1aa_HPS_FORMAT_FIGEXP M_FIG C_FIG", + "rel_num_authors": 1, "rel_authors": [ { - "author_name": "Enrique Canessa Sr.", - "author_inst": "ICTP, Trieste" - }, - { - "author_name": "Livio Tenze Sr.", - "author_inst": "ICTP, Trieste" + "author_name": "Emine Deniz Tekin", + "author_inst": "University of Turkish Aeronautical Association" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_by_nd", "type": "new results", - "category": "bioinformatics" + "category": "biophysics" }, { "rel_doi": "10.1101/2022.01.11.22269050", @@ -428695,63 +428102,47 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.01.11.22269068", - "rel_title": "The impact of post-hospital remote monitoring of COVID-19 patients using pulse oximetry: a national observational study using hospital activity data", + "rel_doi": "10.1101/2022.01.10.475725", + "rel_title": "A single-cell atlas reveals shared and distinct immune responses and metabolism during SARS-CoV-2 and HIV-1 infections", "rel_date": "2022-01-11", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.11.22269068", - "rel_abs": "BackgroundThere was a national roll out of COVID Virtual Wards (CVW) during Englands second COVID-19 wave (Autumn 2020 - Spring 2021). These services used remote pulse oximetry monitoring for COVID-19 patients following discharge from hospital. A key aim was to enable rapid detection of patient deterioration. It was anticipated that the services would support early discharge and avoid readmissions, reducing pressure on beds. This study is an evaluation of the impact of the CVW services on hospital activity.\n\nMethodsUsing retrospective patient-level hospital admissions data, we built multivariate models to analyse the relationship between the implementation of CVW services and hospital activity outcomes: length of COVID-19 related stays and subsequent COVID-19 readmissions within 28 days. We used data from more than 98% of recorded COVID-19 hospital stays in England, where the patient was discharged alive between mid-August 2020 and late February 2021.\n\nFindingsWe found a longer length of stay for COVID-19 patients discharged from hospitals where a CVW was available, when compared to patients discharged from hospitals where there was no CVW (adjusted IRR 1{middle dot}05, 95% CI 1{middle dot}01 to 1{middle dot}09). We found no evidence of a relationship between the availability of CVW and subsequent rates of readmission for COVID-19 (adjusted OR 0{middle dot}95, 95% CI 0{middle dot}89 to 1{middle dot}02).\n\nInterpretationWe found no evidence of early discharges or reduced readmissions associated with the roll out of COVID Virtual Wards across England. Our analysis made pragmatic use of national-scale hospital data, but it is possible that a lack of specific data (for example, on which patients were enrolled) may have meant that true impacts, especially at a local level, were not ultimately discernible.\n\nFundingThis is independent research funded by the National Institute for Health Research, Health Services & Delivery Research programme and NHSEI.\n\nResearch in contextO_ST_ABSEvidence before this studyC_ST_ABSPost-hospital virtual wards have been found to have a positive impact on patient outcomes when focussed on patients with specific diseases, for example those with heart disease. There has been less evidence of impact for more heterogenous groups of patients. While these services have been rolled out at scale in England, there has been little evidence thus far that post-hospital virtual wards (using pulse oximetry monitoring) have helped to reduce the length of stay of hospitalised COVID-19 patients, or rates of subsequent readmissions for COVID-19.\n\nAdded value of this studyThis national-scale study provides evidence that the rollout of post-hospital discharge virtual ward services for COVID-19 patients in England did not reduce lengths of stay in hospital, or rates of readmission.\n\nImplications of all the available evidenceWhile there is currently an absence of evidence of positive impacts for COVID-19 patients discharged to a virtual ward, our study emphasises the need for quality data to be collected as part of future service implementation.", - "rel_num_authors": 11, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2022.01.10.475725", + "rel_abs": "SARS-CoV-2 and HIV-1 are RNA viruses that have killed millions of people worldwide. Understanding the similarities and differences between these two infections is critical for understanding disease progression and for developing effective vaccines and therapies, particularly for 38 million HIV-1+ individuals who are vulnerable to SARS-CoV-2 co-infection. Here, we utilized single-cell transcriptomics to perform a systematic comparison of 94,442 PBMCs from 7 COVID-19 and 9 HIV-1+ patients in an integrated immune atlas, in which 27 different cell types were identified using an accurate consensus single-cell annotation method. While immune cells in both cohorts show shared inflammation and disrupted mitochondrial function, COVID-19 patients exhibit stronger humoral immunity, broader IFN-I signaling, elevated Rho GTPase and mTOR pathway activities, and downregulated mitophagy. Our results elucidate transcriptional signatures associated with COVID-19 and HIV-1 that may reveal insights into fundamental disease biology and potential therapeutic targets to treat these viral infections.\n\nHighlightsO_LICOVID-19 and HIV-1+ patients show disease-specific inflammatory immune signatures\nC_LIO_LICOVID-19 patients show more productive humoral responses than HIV-1+ patients\nC_LIO_LISARS-CoV-2 elicits more enriched IFN-I signaling relative to HIV-I\nC_LIO_LIDivergent, impaired metabolic programs distinguish SARS-CoV-2 and HIV-1 infections\nC_LI", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Theo Georghiou", - "author_inst": "Nuffield Trust" - }, - { - "author_name": "Chris Sherlaw-Johnson", - "author_inst": "Nuffield Trust" - }, - { - "author_name": "Efthalia Massou", - "author_inst": "Department of Public Health and Primary Care, University of Cambridge" - }, - { - "author_name": "Stephen Morris", - "author_inst": "Department of Public Health & Primary Care, University of Cambridge" - }, - { - "author_name": "Nadia E Crellin", - "author_inst": "Nuffield Trust" + "author_name": "Tony Pan", + "author_inst": "University of Chicago" }, { - "author_name": "Lauren Herlitz", - "author_inst": "Department of Applied Health Research, University College London" + "author_name": "Guoshuai Cao", + "author_inst": "University of Chicago" }, { - "author_name": "Manbinder S Sidhu", - "author_inst": "Health Services Management Centre, University of Birmingham" + "author_name": "Erting Tang", + "author_inst": "University of Chicago" }, { - "author_name": "Sonila M Tomini", - "author_inst": "Department of Applied Health Research, University College London" + "author_name": "Yu Zhao", + "author_inst": "University of Chicago" }, { - "author_name": "Cecilia Vindrola-Padros", - "author_inst": "Department of Targeted Intervention, University College London" + "author_name": "Pablo Penaloza-MacMaster", + "author_inst": "Northwestern University" }, { - "author_name": "Holly Walton", - "author_inst": "Department of Applied Health Research, University College London" + "author_name": "Yun Fang", + "author_inst": "University of Chicago" }, { - "author_name": "Naomi J Fulop", - "author_inst": "Department of Applied Health Research, University College London" + "author_name": "Jun Huang", + "author_inst": "The University of Chicago" } ], "version": "1", - "license": "cc_by_nc", - "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "license": "cc_no", + "type": "new results", + "category": "bioinformatics" }, { "rel_doi": "10.1101/2022.01.11.475820", @@ -430593,39 +429984,18 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.01.10.22268799", - "rel_title": "Quantifying behavior change during the first year of the COVID-19 pandemic in the United States", + "rel_doi": "10.1101/2022.01.07.475453", + "rel_title": "Mild respiratory SARS-CoV-2 infection can cause multi-lineage cellular dysregulation and myelin loss in the brain", "rel_date": "2022-01-10", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.10.22268799", - "rel_abs": "BackgroundDuring the first year of the COVID-19 pandemic, the most effective way to reduce transmission and to protect oneself was to reduce contact with others. However, it is unclear how behavior changed, despite numerous surveys about peoples attitudes and actions during the pandemic and public health efforts to influence behavior.\n\nMethodsWe used two sources of data to quantify changes in behavior at the county level during the first year of the pandemic in the United States: aggregated mobile device (smartphone) location data to approximate the fraction of people staying at home each day and digital invitation data to capture the number and size of social gatherings.\n\nResultsBetween mid-March to early April 2020, the number of events fell and the fraction of devices staying at home peaked, independently of when states issued emergency orders or stay-at-home recommendations. Activity began to recover in May or June, with later rebounds in counties that suffered an early spring wave of reported COVID-19 cases. Counties with high incidence in the summer had more events, higher mobility, and less stringent state-level COVID-related restrictions the month before than counties with low incidence. Counties with high incidence in early fall stayed at home less and had less stringent state-level COVID-related restrictions in October, when cases began to rise in some parts of the US. During the early months of the pandemic, the number of events was inversely correlated with the fraction of devices staying at home, but after the fall of 2020 mobility appeared to stay constant as the number of events fell. Greater changes in behavior were observed in counties where a larger fraction voted for Biden in the 2020 US Presidential election. The number of people invited per event dropped gradually throughout the first year of the pandemic.\n\nConclusionsThe mobility and events datasets uncovered different kinds of behavioral responses to the pandemic. Our results indicate that people did in fact change their behavior in ways that likely reduced COVID exposure and transmission, though the degree of change appeared to be affected by political views. Though the mobility data captured the initial massive behavior changes in the first months of the pandemic, the digital invitation data, presented here for the first time, continued to show large changes in behavior later in the first year of the pandemic.", - "rel_num_authors": 5, - "rel_authors": [ - { - "author_name": "Dennis L Chao", - "author_inst": "Bill & Melinda Gates Foundation" - }, - { - "author_name": "Victor Cho", - "author_inst": "Evite, Inc" - }, - { - "author_name": "Amanda S Izzo", - "author_inst": "Bill & Melinda Gates Foundation" - }, - { - "author_name": "Joshua L Proctor", - "author_inst": "Bill & Melinda Gates Foundation" - }, - { - "author_name": "Marita Zimmermann", - "author_inst": "Bill & Melinda Gates Foundation" - } - ], + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2022.01.07.475453", + "rel_abs": "Survivors of Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) infection frequently experience lingering neurological symptoms, including impairment in attention, concentration, speed of information processing and memory. This long-COVID cognitive syndrome shares many features with the syndrome of cancer therapy-related cognitive impairment (CRCI). Neuroinflammation, particularly microglial reactivity and consequent dysregulation of hippocampal neurogenesis and oligodendrocyte lineage cells, is central to CRCI. We hypothesized that similar cellular mechanisms may contribute to the persistent neurological symptoms associated with even mild SARS-CoV-2 respiratory infection. Here, we explored neuroinflammation caused by mild respiratory SARS-CoV-2 infection - without neuroinvasion - and effects on hippocampal neurogenesis and the oligodendroglial lineage. Using a mouse model of mild respiratory SARS-CoV-2 infection induced by intranasal SARS-CoV-2 delivery, we found white matter-selective microglial reactivity, a pattern observed in CRCI. Human brain tissue from 9 individuals with COVID-19 or SARS-CoV-2 infection exhibits the same pattern of prominent white matter-selective microglial reactivity. In mice, pro-inflammatory CSF cytokines/chemokines were elevated for at least 7-weeks post-infection; among the chemokines demonstrating persistent elevation is CCL11, which is associated with impairments in neurogenesis and cognitive function. Humans experiencing long-COVID with cognitive symptoms (48 subjects) similarly demonstrate elevated CCL11 levels compared to those with long-COVID who lack cognitive symptoms (15 subjects). Impaired hippocampal neurogenesis, decreased oligodendrocytes and myelin loss in subcortical white matter were evident at 1 week, and persisted until at least 7 weeks, following mild respiratory SARS-CoV-2 infection in mice. Taken together, the findings presented here illustrate striking similarities between neuropathophysiology after cancer therapy and after SARS-CoV-2 infection, and elucidate cellular deficits that may contribute to lasting neurological symptoms following even mild SARS-CoV-2 infection.", + "rel_num_authors": 0, + "rel_authors": null, "version": "1", - "license": "cc_by_nd", - "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "license": "", + "type": "new results", + "category": "neuroscience" }, { "rel_doi": "10.1101/2022.01.10.475532", @@ -432667,61 +432037,33 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.01.07.22268891", - "rel_title": "COVID-19 impact on routine immunisations for vaccine-preventable diseases: Projecting the effect of different routes to recovery", + "rel_doi": "10.1101/2022.01.07.22268886", + "rel_title": "Estimation of excess all-cause mortality due to COVID-19 in Thailand", "rel_date": "2022-01-07", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.07.22268891", - "rel_abs": "AO_SCPLOWBSTRACTC_SCPLOWO_ST_ABSIntroductionC_ST_ABSOver the past two decades, vaccination programmes for vaccine-preventable diseases (VPDs) have expanded across low- and middle-income countries (LMICs). However, the rise of COVID-19 resulted in global disruption to routine immunisation (RI) activities. Such disruptions could have a detrimental effect on public health, leading to more deaths from VPDs, particularly without mitigation efforts. Hence, as RIs resume, it is important to estimate the effectiveness of different approaches for recovery.\n\nMethodsWe apply an impact extrapolation method developed by the Vaccine Impact Modelling Consortium to estimate the impact of COVID-19-related disruptions with different recovery scenarios for ten VPDs across 112 LMICs. We focus on deaths averted due to RIs occurring in the years 2020-2030 and investigate two recovery scenarios relative to a no-COVID-19 scenario. In the recovery scenarios, we assume a 10% COVID-19-related drop in RI coverage in the year 2020. We then linearly interpolate coverage to the year 2030 to investigate two routes to recovery, whereby the immunization agenda (IA2030) targets are reached by 2030 or fall short by 10%.\n\nResultsWe estimate that falling short of the IA2030 targets by 10% leads to 11.26% fewer fully vaccinated persons (FVPs) and 11.34% more deaths over the years 2020-2030 relative to the no-COVID-19 scenario, whereas, reaching the IA2030 targets reduces these proportions to 5% fewer FVPs and 5.22% more deaths. The impact of the disruption varies across the VPDs with diseases where coverage expands drastically in future years facing a smaller detrimental effect.\n\nConclusionOverall, our results show that drops in RI coverage could result in more deaths due to VPDs. As the impact of COVID-19-related disruptions is dependent on the vaccination coverage that is achieved over the coming years, the continued efforts of building up coverage and addressing gaps in immunity are vital in the road to recovery.\n\nSUMMARYO_ST_ABSWhat is already known?C_ST_ABSO_LIThe impact of vaccination programmes without COVID-19-related disruption has been assessed by the Vaccine Impact Modelling Consortium.\nC_LIO_LIThe COVID-19 pandemic has disrupted vaccination programmes resulting in a decline in coverage in the year 2020, the ramifications of this is unclear.\nC_LI\n\nWhat are the new findings?O_LIWe estimate the impact of disruptions to routine immunisation coverage and different routes to recovery. We compare to a scenario without COVID-19-related disruptions (assuming no drops in immunisation coverage).\nC_LIO_LIWe estimate that reaching the Immunization Agenda (IA2030) targets leads to 5% fewer FVPs and 5.22% more deaths over the years 2020 to 2030 relative to the scenario with no COVID-19-related disruptions, whereas falling short of the IA2030 targets by 10% leads to 11.26% fewer fully vaccinated persons (FVPs) and 11.34% more deaths.\nC_LIO_LIThe impact of the disruption varies across the vaccine-preventable diseases with those forecasted to have vast expansions in coverage post-2020 able to recover more.\nC_LI\n\nWhat do the new findings imply?O_LIA drop in vaccination coverage results in fewer vaccinated individuals and thus more deaths due to vaccine-preventable diseases. To mitigate this, building up coverage of routine immunisations and addressing immunity gaps with activities such as catch-up campaigns are vital in the road to recovery.\nC_LI", - "rel_num_authors": 11, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.07.22268886", + "rel_abs": "Thailand has experienced the most prominent COVID-19 outbreak, resulting in a new record for COVID-19 cases and deaths in 2021. To assess the influence of the COVID-19 outbreak on mortality, we estimated excess all-cause and pneumonia mortality in Thailand during the COVID-19 outbreak from April to October 2021. We used the previous five years mortality to estimate the baseline number of deaths using generalized linear mixed models (GLMMs). The models were adjusted for seasonality and demographics. We found that the estimated cumulative excess death was 14.3% (95% CI: 8.6%-18.8%) higher than the baseline. The results also showed that the excess deaths in males were higher than in females by approximately 26.3%. The excess deaths directly caused by the COVID-19 infections accounted for approximately 75.0% of the all-cause excess deaths. Furthermore, excess pneumonia deaths were also found to be 26.2% (95% CI: 4.8%-46.0%) above baseline. There was a significant rise in excess fatalities, especially in the older age groups. Therefore, the age and sex structure of the population are essential to assessing the mortality impact of COVID-19. Our modeling results could potentially provide insights into the COVID-19 outbreaks and provide a guide for outbreak control and intervention.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Jaspreet Toor", - "author_inst": "Imperial College London" - }, - { - "author_name": "Xiang Li", - "author_inst": "Imperial College London" - }, - { - "author_name": "Mark Jit", - "author_inst": "London School of Hygiene & Tropical Medicine" - }, - { - "author_name": "Caroline Trotter", - "author_inst": "University of Cambridge" - }, - { - "author_name": "Susy Echeverria-Londono", - "author_inst": "Imperial College London" - }, - { - "author_name": "Anna-Maria Hartner", - "author_inst": "Imperial College London" - }, - { - "author_name": "Jeremy Roth", - "author_inst": "Imperial College London" - }, - { - "author_name": "Allison Portnoy", - "author_inst": "Harvard T.H. Chan School of Public Health" + "author_name": "Chaiwat Wilasang", + "author_inst": "Mahidol University" }, { - "author_name": "Kaja Abbas", - "author_inst": "London School of Hygiene & Tropical Medicine" + "author_name": "Thanchanok Lincharoen", + "author_inst": "Mahidol University" }, { - "author_name": "Neil M Ferguson", - "author_inst": "Imperial College London" + "author_name": "Charin Modchang", + "author_inst": "Mahidol University" }, { - "author_name": "Katy A M Gaythorpe", - "author_inst": "Imperial College London" + "author_name": "Sudarat Chadsuthi", + "author_inst": "Naresuan University" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", "category": "public and global health" }, @@ -434556,45 +433898,37 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.01.04.22268721", - "rel_title": "Preliminary modeling estimates of the relative transmissibility and immune escape of the Omicron SARS-CoV-2 variant of concern in South Africa", + "rel_doi": "10.1101/2022.01.01.21268131", + "rel_title": "Bayesian Estimation of real-time Epidemic Growth Rates using Gaussian Processes: local dynamics of SARS-CoV-2 in England", "rel_date": "2022-01-05", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.04.22268721", - "rel_abs": "We develop a stochastic, multi-strain, compartmental epidemic model to estimate the relative transmissibility and immune escape of the Omicron variant of concern (VOC) in South Africa. The model integrates population, non-pharmaceutical interventions, vaccines, and epidemiological data and it is calibrated in the period May 1st, 2021 - November 23rd, 2021. We explore a parameter space of relative transmissibility with respect to the Delta variant and immune escape for Omicron by assuming an initial seeding, from unknown origin, in the first week of October 2021. We identify a region of the parameter space where combinations of relative transmissibility and immune escape are compatible with the growth of the epidemic wave. We also find that changes in the generation time associated with Omicron infections strongly affect the results concerning its relative transmissibility. The presented results are informed by current knowledge of Omicron and subject to changes.", - "rel_num_authors": 7, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.01.21268131", + "rel_abs": "Quantitative assessments of the recent state of an epidemic and short-term projections into the near future are key public health tools that have substantial policy impacts, helping to determine if existing control measures are sufficient or need to be strengthened. Key to these quantitative assessments is the ability to rapidly and robustly measure the speed with which the epidemic is growing or decaying. Frequently, epidemiological trends are addressed in terms of the (time-varying) reproductive number R. Here, we take a more parsimonious approach and calculate the exponential growth rate, r, using a Bayesian hierarchical model to fit a Gaussian process to the epidemiological data. We show how the method can be employed when only case data from positive tests are available, and the improvement gained by including the total number of tests as a measure of heterogeneous testing effort. Although the methods are generic, we apply them to SARS-CoV-2 cases and testing in England, making use of the available high-resolution spatio-temporal data to determine long-term patterns of national growth, highlight regional growth and spatial heterogeneity.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Nicol\u00f2 Gozzi", - "author_inst": "Networks and Urban Systems Centre, University of Greenwich, UK" - }, - { - "author_name": "Matteo Chinazzi", - "author_inst": "Laboratory for the Modeling of Biological and Socio-technical Systems, Northeastern University, Boston, MA USA" - }, - { - "author_name": "Jessica T. Davis", - "author_inst": "Laboratory for the Modeling of Biological and Socio-technical Systems, Northeastern University, Boston, MA USA" + "author_name": "Laura Marcela Guzman Rincon", + "author_inst": "University of Warwick" }, { - "author_name": "Kunpeng Mu", - "author_inst": "Laboratory for the Modeling of Biological and Socio-technical Systems, Northeastern University, Boston, MA USA" + "author_name": "Edward M Hill", + "author_inst": "University of Warwick" }, { - "author_name": "Ana Pastore y Piontti", - "author_inst": "Laboratory for the Modeling of Biological and Socio-technical Systems, Northeastern University, Boston, MA USA" + "author_name": "Louise Dyson", + "author_inst": "University of Warwick" }, { - "author_name": "Alessandro Vespignani", - "author_inst": "Laboratory for the Modeling of Biological and Socio-technical Systems, Northeastern University, Boston, MA USA" + "author_name": "Michael J Tildesley", + "author_inst": "University of Warwick" }, { - "author_name": "Nicola Perra", - "author_inst": "Networks and Urban Systems Centre, University of Greenwich, UK" + "author_name": "Matt J Keeling", + "author_inst": "University of Warwick" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -436218,93 +435552,25 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.01.04.22268758", - "rel_title": "Containment of a multi-index B.1.1.7 outbreak on a university campus through a genomically-informed public health response", + "rel_doi": "10.1101/2022.01.04.22268760", + "rel_title": "Differential Effects of Race/Ethnicity and Social Vulnerability on COVID-19 Positivity, Hospitalization, and Death in the San Francisco Bay Area", "rel_date": "2022-01-05", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.04.22268758", - "rel_abs": "The first cluster of SARS-CoV-2 cases with lineage B.1.1.7 in the state of Michigan was identified through intensive university-led surveillance sampling and targeted sequencing. A collaborative investigation and response was conducted by the local and state health departments, and the campus and athletic medicine COVID-19 response teams, using S-gene target failure screening and rapid genomic sequencing to inform containment strategies. A total of 50 cases of B.1.1.7-lineage SARS-CoV-2 were identified in this outbreak, which was due to three coincident introductions of B.1.1.7-lineage SARS-CoV-2, all of which were genetically distinct from lineages which later circulated in the broader community. This investigation demonstrates the successful implementation of a genomically-informed outbreak response which can be extended to university campuses and other settings at high risk for rapid emergence of new variants.", - "rel_num_authors": 19, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.04.22268760", + "rel_abs": "BACKGROUNDHigher COVID-19 incidence and morbidity have been documented for US Black and Hispanic populations but not as clearly for other racial and ethnic groups. Efforts to elucidate the mechanisms underlying racial health disparities can be confounded by the relationship between race/ethnicity and socioeconomic status.\n\nOBJECTIVEExamine race/ethnicity and social vulnerability effects on COVID-19 out-comes in the San Francisco Bay Area, an ethnically and socioeconomically diverse region, using geocoded patient records from 2020 in the University of California, San Francisco Health system.\n\nKEY RESULTSHigher social vulnerability, but not race/ethnicity, was associated with less frequent testing yet a higher likelihood of testing positive. Asian hospitalization rates (11.5%) were double that of White patients (5.4%) and exceeded the rates for Black (9.3%) and Hispanic patients (6.9%). A modest relationship between higher hospitalization rates and increasing social vulnerability was evident only for White patients. Hispanic patients had the highest years of expected life lost due to COVID-19.\n\nCONCLUSIONSCOVID-19 outcomes were not consistently explained by greater social vulnerability. Asian individuals showed disproportionately high rates of hospitalization regardless of social vulnerability status. Study of the San Francisco Bay Area population not only provides valuable insights into the differential contributions of race/ethnicity and social determinants of health to COVID-19 outcomes but also emphasizes that all racial groups have experienced the toll of the pandemic, albeit in different ways and to varying degrees.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Emily Toth Martin", - "author_inst": "University of Michigan-Ann Arbor" - }, - { - "author_name": "Adam S Lauring", - "author_inst": "Department of Internal Medicine, University of Michigan School of Medicine" - }, - { - "author_name": "JoLynn P Montgomery", - "author_inst": "EpiStudies, LLC" - }, - { - "author_name": "Andrew L Valesano", - "author_inst": "Department of Internal Medicine, University of Michigan School of Medicine" - }, - { - "author_name": "Marisa C Eisenberg", - "author_inst": "Department of Epidemiology, University of Michigan School of Public Health" - }, - { - "author_name": "Danielle Sheen", - "author_inst": "Environmental Health & Safety, University of Michigan" - }, - { - "author_name": "Jennifer Nord", - "author_inst": "Environmental Health & Safety, University of Michigan" - }, - { - "author_name": "Robert D Ernst", - "author_inst": "Department of Internal Medicine, University of Michigan School of Medicine" - }, - { - "author_name": "Lindsey Y Mortenson", - "author_inst": "University Health Service, University of Michigan;" - }, - { - "author_name": "Riccardo Valdez", - "author_inst": "Department of Pathology, University of Michigan Medical School" - }, - { - "author_name": "Yashar Niknafs", - "author_inst": "LynxDx, Inc." - }, - { - "author_name": "Darryl Conway", - "author_inst": "Athletics, University of Michigan" - }, - { - "author_name": "Sami F Rifat", - "author_inst": "Athletic Medicine, University of Michigan" - }, - { - "author_name": "Natasha Bagdasarian", - "author_inst": "Michigan Department of Health and Human Services" - }, - { - "author_name": "Sarah Lyon-Callo", - "author_inst": "Michigan Department of Health and Human Services" - }, - { - "author_name": "Jim Collins", - "author_inst": "Michigan Department of Health and Human Services" - }, - { - "author_name": "Heather Blakenship", - "author_inst": "Michigan Department of Health and Human Services" - }, - { - "author_name": "Marty Soehnlen", - "author_inst": "Michigan Department of Health and Human Services" + "author_name": "Wendy K. Tam Cho", + "author_inst": "University of Illinois at Urbana-Champaign" }, { - "author_name": "Juan Marquez", - "author_inst": "Washtenaw County Health Department" + "author_name": "David G. Hwang", + "author_inst": "University of California San Francisco" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -438148,35 +437414,31 @@ "category": "cell biology" }, { - "rel_doi": "10.1101/2022.01.03.474721", - "rel_title": "Hydrodynamics of spike proteins dictate a transport-affinity competition for SARS-CoV-2 and other enveloped viruses", + "rel_doi": "10.1101/2021.12.30.474602", + "rel_title": "Integrated Autolysis, DNA Hydrolysis and Precipitation Enables an Improved Bioprocess for Q-Griffithsin, a Broad-Spectrum Antiviral and Clinical-Stage anti-COVID-19 Candidate", "rel_date": "2022-01-03", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.01.03.474721", - "rel_abs": "Many viruses, such as SARS-CoV-2 or Influenza, possess spike-decorated envelopes. Depending on the virus type, a large variability is present in spikes number, morphology and reactivity, which remains generally unexplained. Since viruses transmissibility depend on features beyond their genetic sequence, new tools are required to discern the effects of spikes functionality, interaction, and morphology. Here, we postulate the relevance of hydrodynamic interactions in the viral infectivity of enveloped viruses and propose micro-rheological characterization as a platform for viruses differentiation. To understand how the spikes affect virion mobility and infectivity, we investigate the diffusivity of spike-decorate structures using mesoscopic-hydrodynamic simulations. Furthermore, we explored the interplay between affinity and passive viral transport. Our results revealed that the diffusional mechanism of SARS-CoV-2 is strongly influenced by the size and distribution of its spikes. We propose and validate a universal mechanism to explain the link between optimal virion structure and maximal infectivity for many virus families.", - "rel_num_authors": 4, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.12.30.474602", + "rel_abs": "Across the biomanufacturing industry, innovations are needed to improve efficiency and flexibility, especially in the face of challenges such as the COVID-19 pandemic. Here we report an improved bioprocess for Q-Griffithsin, a broad-spectrum antiviral currently in clinical trials for COVID-19. Q-Griffithsin is produced at high titer in E. coli and purified to anticipated clinical grade without conventional chromatography or the need for any fixed downstream equipment. The process is thus both low-cost and highly flexible, facilitating low sales prices and agile modifications of production capacity, two key features for pandemic response. The simplicity of this process is enabled by a novel unit operation that integrates cellular autolysis, autohydrolysis of nucleic acids, and contaminant precipitation, giving essentially complete removal of host cell DNA as well as reducing host cell proteins and endotoxin by 3.6 and 2.4 log10 units, respectively. This unit operation can be performed rapidly and in the fermentation vessel, such that Q-GRFT is obtained with 100% yield and >99.9% purity immediately after fermentation and requires only a flow-through membrane chromatography step for further contaminant removal. Using this operation or variations of it may enable improved bioprocesses for a range of other high-value proteins in E. coli.\n\nHighlightsO_LIIntegrating autolysis, DNA hydrolysis and precipitation enables process simplification\nC_LIO_LIAutolysis reduces endotoxin release and burden to purification\nC_LIO_LIQ-Griffithsin recovered from fermentation vessel at >99.9% purity and 100% yield\nC_LIO_LIQ-Griffithsin purified to anticipated clinical grade without conventional chromatography\nC_LIO_LIThe resulting bioprocess is 100% disposables-compatible, scalable, and low-cost\nC_LI", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Nicolas Moreno", - "author_inst": "Basque Center for Applied Mathematics" - }, - { - "author_name": "Daniela Moreno-Chaparro", - "author_inst": "Basque Center for Applied Mathematics" + "author_name": "John S Decker", + "author_inst": "Duke University" }, { - "author_name": "Florencio Balboa Usabiaga", - "author_inst": "Basque Center for Applied Mathematics" + "author_name": "Romel Menacho-Melgar", + "author_inst": "Duke University" }, { - "author_name": "Marco Ellero", - "author_inst": "Basque Center for Applied Mathematics" + "author_name": "Michael D Lynch", + "author_inst": "Duke University" } ], "version": "1", "license": "cc_no", "type": "new results", - "category": "biophysics" + "category": "synthetic biology" }, { "rel_doi": "10.1101/2021.12.30.474561", @@ -440158,71 +439420,115 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.12.30.21267140", - "rel_title": "EARLY LENZILUMAB TREATMENT OF COVID-19 PATIENTS USING C-REACTIVE PROTEIN AS A BIOMARKER IMPROVES EFFICACY: RESULTS FROM THE PHASE 3 LIVE-AIR TRIAL", + "rel_doi": "10.1101/2021.12.30.21268308", + "rel_title": "Cross reactivity of spike glycoprotein induced antibody against delta and omicron variants before and after third SARS-CoV-2 vaccine dose", "rel_date": "2022-01-01", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.30.21267140", - "rel_abs": "ObjectiveThe LIVE-AIR trial demonstrated that the anti-GM-CSF monoclonal antibody, lenzilumab improved the likelihood of survival without invasive mechanical ventilation (SWOV) in COVID-19 patients; with greatest effect in those with baseline CRP below the median baseline value of 79 mg/L. Similar to GM-CSF, C-reactive protein (CRP) levels are correlated with COVID-19 severity. This current analysis assessed the utility of baseline CRP levels to guide treatment with lenzilumab.\n\nDesignLIVE-AIR was a phase 3, double-blind, placebo-controlled trial. Participants were randomized 1:1 and stratified according to age and disease severity, to receive lenzilumab or placebo on Day 0, were followed through Day 28.\n\nSettingSecondary and tertiary care hospitals in the US and Brazil.\n\nParticipants520 hospitalized COVID-19 participants with SpO2[≤] 94% on room air or required supplemental oxygen but not invasive mechanical ventilation were included.\n\nInterventionsLenzilumab (1800mg; divided as 3 doses, q8h) or placebo infusion alongside standard treatments including corticosteroids and remdesivir.\n\nMain outcome measuresA multi-variate logistic regression analysis assessed key baseline risk factors for progression to IMV or death. The primary endpoint, SWOV, and key secondary endpoints were analyzed according to baseline CRP levels in all participants with CRP values.\n\nResultsThe multi-variate analysis demonstrated that elevated baseline plasma CRP was the most predictive feature for progression to IMV or death. SWOV was achieved in 152 (90%; 95%CI: 85to 94) lenzilumab and 183 (79%; 72 to 84) placebo participants with baseline CRP<150 mg/L and its likelihood was greater with lenzilumab than placebo (HR: 2.54; 95%CI, 1.46 to 4.41; p=0.0009) but not in participants with CRP[≥]150 mg/L at baseline. CRP as a covariate in the overall analysis demonstrated a statistically significant interaction with lenzilumab treatment (p=0.044). Grade [≥] 3 adverse events in participants with baseline CRP<150 mg/L were reported in 18% and 28% in lenzilumab or placebo, respectively. No treatment-emergent serious adverse events were attributable to lenzilumab.\n\nConclusionThese finding suggest that COVID-19 participants with low baseline CRP levels achieve the greatest clinical benefit from lenzilumab and that baseline CRP levels may be a useful biomarker to guide therapeutic intervention.\n\nTrial RegistrationClinicalTrials.gov NCT04351152\n\nWHAT IS ALREADY KNOWN ON THIS TOPICGM-CSF is one of the early upstream mediators and orchestrators of the hyperinflammatory immune response following SARS-CoV-2 infection. Baseline levels of GM-CSF and CRP have each been shown to correlate with COVID-19 disease progression. Increases in CRP are driven by elevations of IL-6 during the hyperinflammatory response following SARS-CoV-2 infection. In the phase 3, randomized, double-blind, placebo-controlled LIVE-AIR study, GM-CSF neutralization with lenzilumab significantly improved the likelihood of survival without invasive mechanical ventilation (SWOV, primary endpoint, also referred to as ventilator-free survival) vs. placebo (HR:1.54; 95% CI, 1.02 to 2.32; p=0.0403), which included standard supportive care including corticosteroids and remdesivir. No treatment-emergent serious adverse events attributable to lenzilumab have been reported to date.\n\nWHAT THIS STUDY ADDSA comprehensive analysis of LIVE -AIR CRP data provides evidence for the utility of baseline CRP to predict progression to IMV and death. Baseline CRP was identified to be the strongest predictor of SWOV in this study. Patients with baseline CRP<150 mg/L represented 78% of the study population and demonstrated the greatest clinical benefit with lenzilumab, including SWOV through day 28 (HR: 2.54; 95%CI; 1.46-4.41; nominal p=0.0009). A biomarker-driven approach using baseline CRP levels to guide therapeutic intervention may improve outcomes in those hospitalized with COVID-19. Participants with baseline CRP levels above 150 mg/L were described as experiencing COVID-19-associated hyperinflammation and were at risk of imminent escalation of respiratory support or death. Elevated baseline plasma CRP was the most predictive feature for progression to IMV or death (OR, 0.15; 95%CI, 0.07-0.29; nominal p<0.001). These findings suggest that baseline CRP may be a useful biomarker in determining which participants may be most successfully treated with lenzilumab.", - "rel_num_authors": 13, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.30.21268308", + "rel_abs": "Variants of SARS-CoV-2 may evade natural and vaccine induced immunity and monoclonal antibody immunotherapeutics. There is an urgent need to know how well antibodies, induced by healthy and Clinically Extremely Vulnerable (CEV) patients, will bind and thus help reduce transmission and severity of infection from variants of concern (VOC). This study determines the cross-reactive binding of serum antibodies obtained prior to and 28 days after a third vaccination in three cohorts; a health care worker cohort who received three doses of Pfizer-BioNtech (PPP), a cohort of CEV patients received two doses of the AstraZeneca-ChAdOx1-nCoV-19 (AAP) vaccine, followed by a third PFZ vaccine and a haemodialysis cohort that had a mixture of two AZ or PFZ vaccines followed by a PFZ booster. Six months post second vaccine there was evidence of antibody waning with 58.9% of individuals in the HD cohort seropositive against Wuhan, 34.4% Delta and 62.2% Omicron strains. For the AAP cohort, equivalent figures were 62.5%, 45.8% and 91.7% and the PPP cohort 92.2%, 90% and 91.1%. Post third dose vaccination there were universal increases in seropositivity and median optical density. For the HD cohort, 98.8% were seropositive to the Wuhan strain, 97.6% against Delta and 100% against Omicron strains. For the PPP and AAP cohorts, 100% were seropositive against all 3 strains. Lastly, we examined the WHO NIBSC 20/136 standard and there was no loss of antibody binding to either VOC. Similarly, a dilution series of Sotrovimab (GSK) found this therapeutic monoclonal antibody bound similarly to all VOC.\n\nHighlightsO_LIIgG anti-SARS-CoV-2 Omicron spike glycoprotein antibody levels were high in 100% of health care workers (HCW), a general practice population considered clinically extremely vulnerable (CEV) and haemodialysis patients (HD) 4 weeks after a third SARS-CoV-2 vaccine dose (Pfizer-BioNtech-PFZ).\nC_LIO_LIFor both Delta and Omicron variant spike glycoproteins these antibody levels were highest in the CEV cohort who had previously received two doses of AstraZeneca ChAdOx1 nCoV-19 vaccine (AAP), lower in HCW who had previously received two doses of PFZ (PPP) and lowest in HD who had a mix of vaccines for the first and second dose\nC_LIO_LIPrior to this third vaccine dose and 6 months post second vaccine dose there was evidence of significant waning of antibodies against VOC.\nC_LI", + "rel_num_authors": 24, "rel_authors": [ { - "author_name": "Zelalem Temesgen", - "author_inst": "Mayo Clinic, Division of Infectious Disease, Rochester, MN" + "author_name": "Sian E Faustini", + "author_inst": "Institute of Immunology and Immunotherapy, University of Birmingham" }, { - "author_name": "Colleen F. Kelley", - "author_inst": "Division of Infectious Diseases, Emory University School of Medicine, Grady Memorial Hospital, Atlanta, GA" + "author_name": "Adrian M Shields", + "author_inst": "Institute of Immunology and Immunotherapy, University of Birmingham" }, { - "author_name": "Frank Cerasoli", - "author_inst": "RxMedical Dynamics, New York, NY" + "author_name": "Gemma Banham", + "author_inst": "Institute of Clinical Sciences, University of Birmingham" }, { - "author_name": "Adrian Kilcoyne", - "author_inst": "Humanigen, Inc., Burlingame, CA" + "author_name": "Nadezhda Wall", + "author_inst": "Institute of Clinical Sciences, University of Birmingham" }, { - "author_name": "Dale Chappell", - "author_inst": "Humanigen, Inc., Burlingame, CA" + "author_name": "Saly Al-Taei", + "author_inst": "Institute of Immunology and Immunotherapy, University of Birmingham" }, { - "author_name": "Cameron Durrant", - "author_inst": "Humanigen, Inc., Burlingame, CA" + "author_name": "Chloe Tanner", + "author_inst": "Institute of Immunology and Immunotherapy, University of Birmingham" }, { - "author_name": "Omar Ahmed", - "author_inst": "Humanigen, Inc., Burlingame, CA" + "author_name": "Zahra Ahmed", + "author_inst": "Institute of Immunology and Immunotherapy, University of Birmingham" }, { - "author_name": "Gabrielle Chappell", - "author_inst": "Humanigen, Inc., Burlingame, CA" + "author_name": "Elena Efstathiou", + "author_inst": "Institute of Immunology and Immunotherapy, University of Birmingham" }, { - "author_name": "Victoria Catterson", - "author_inst": "BioSymetrics, Inc., New York, NY" + "author_name": "Neal Townsend", + "author_inst": "Institute of Immunology and Immunotherapy, University of Birmingham" }, { - "author_name": "Christopher Polk", - "author_inst": "Atrium Health, Charlotte, NC" + "author_name": "Ruth Price", + "author_inst": "Biomedical Sciences Research Institute, Ulster University, Northern Ireland" }, { - "author_name": "Andrew D. Badley", - "author_inst": "Mayo Clinic, Division of Infectious Disease and Department of Molecular Medicine, Rochester, MN" + "author_name": "Grace Curry", + "author_inst": "Biomedical Sciences Research Institute, Ulster University, Northern Ireland" }, { - "author_name": "Vincent Marconi", - "author_inst": "Division of Infectious Diseases, Emory University School of Medicine, Rollins School of Public Health, and Emory Vaccine Center, Atlanta, GA" + "author_name": "Louise Robertson", + "author_inst": "Biomedical Sciences Research Institute, Ulster University, Northern Ireland" + }, + { + "author_name": "Andrew Nesbit", + "author_inst": "Biomedical Sciences Research Institute, Ulster University, Northern Ireland" + }, + { + "author_name": "Amy Black", + "author_inst": "Biomedical Sciences Research Institute, Ulster University, Northern Ireland" + }, + { + "author_name": "JULIE MOORE", + "author_inst": "Biomedical Sciences Research Institute, Ulster University, Northern Ireland" + }, + { + "author_name": "James McLaughlin", + "author_inst": "Nanotechnology and Integrated Bioengineering Centre, Ulster University, Northern Ireland" }, { - "author_name": "- the LIVE-AIR Study Group", + "author_name": "John Farnan", + "author_inst": "The Group Surgery, 257 North Queen Street, Belfast, Northern Ireland" + }, + { + "author_name": "- COVID-HD Birmingham Study Group", + "author_inst": "" + }, + { + "author_name": "- PITCH consortium", "author_inst": "" + }, + { + "author_name": "Adam F Cunningham", + "author_inst": "Immunology and Immunotherapy, University of Birmingham" + }, + { + "author_name": "Lorraine Harper", + "author_inst": "Institute of Inflammation and Ageing, University of Birmingham" + }, + { + "author_name": "Tara Moore", + "author_inst": "Biomedical Sciences Research Institute, Ulster University, Northern Ireland" + }, + { + "author_name": "Mark T Drayson", + "author_inst": "Institute of Immunology and Immunotherapy, University of Birmingham" + }, + { + "author_name": "Alex G Richter", + "author_inst": "Institute of Immunology and Immunotherapy, University of Birmingham" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "intensive care and critical care medicine" + "category": "allergy and immunology" }, { "rel_doi": "10.1101/2021.12.30.21268236", @@ -442272,55 +441578,51 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.12.29.21268511", - "rel_title": "COVID-19 vaccine effectiveness among immunocompromised populations: a targeted literature review of real-world studies", + "rel_doi": "10.1101/2021.12.27.21268264", + "rel_title": "Immunomodulation by intravenous omega-3 fatty acid treatment in older subjects hospitalized for COVID-19: a single-blind randomized controlled trial", "rel_date": "2021-12-31", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.29.21268511", - "rel_abs": "IntroductionFrom July through October of 2021, several countries issued recommendations for increased COVID-19 vaccine protection for individuals with one or more immunocompromised (IC) conditions. It is critically important to understand the vaccine effectiveness (VE) of COVID-19 vaccines among IC populations as recommendations are updated over time in response to the evolving COVID-19 pandemic.\n\nAreas coveredA targeted literature review was conducted to identify real-world studies that assessed COVID-19 VE in IC populations between December 2020 and September 2021. A total of 10 studies from four countries were identified and summarized in this review.\n\nExpert opinion/commentaryVE of the widely available COVID-19 vaccines, including BNT162b2 (Pfizer/BioNTech), mRNA-1273 (Moderna), Ad26.COV2.S (Janssen), and ChAdOx1 nCoV-19 (Oxford/AstraZeneca), ranged from 64%-90% against SARS-CoV-2 infection, 73%-84% against symptomatic illness, 70%-100% against severe illness, and 63%-100% against COVID-19-related hospitalization among the fully vaccinated IC populations included in the studies. COVID-19 VE for most outcomes in the IC populations included in these studies was lower than in the general populations. These findings provide preliminary evidence that the IC population requires greater protective measures to prevent COVID-19 infection and associated illness, hence should be prioritized while implementing recommendations of additional COVID-19 vaccine doses.", - "rel_num_authors": 9, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.27.21268264", + "rel_abs": "Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes coronavirus disease 2019 (COVID-19) with respiratory distress and systemic hyperinflammation. The primary objective of this single-blind randomized controlled proof-of-concept clinical trial was to establish the effects of intravenous (i.v.) omega-3 (n-3) polyunsaturated fatty acid (PUFA) treatment compared to placebo on inflammatory markers in COVID-19, represented by leukocytes as well as inflammatory protein and lipid mediators. Here we also present an exploratory analysis of the mechanisms of action to elucidate the potential to resolve the COVID-19 hyperinflammation through interfering with lipid mediators. Inclusion criteria were COVID-19 diagnosis and clinical status requiring hospitalization. Randomization was 1:1 to a once daily i.v. infusion (2 mL/kg) of either n-3 PUFA emulsion containing 10g of fish oil per 100 mL or placebo (NaCl) for 5 days. Results from 22 older subjects (mean age 81{+/-}6.1 years) were analyzed. The neutrophil to lymphocyte ratio was significantly decreased after n-3 PUFA administration. Liquid chromatography-mass spectrometry (LC-MS/MS) -based lipid metabolite analysis established increased proresolving lipid mediator precursor levels and decreased formation of leukotoxin and isoleukotoxin diols by n-3 PUFA treatment. The mechanistic exploration revealed decreased immunothrombosis and preserved interferon-response. Finally, n-3 PUFA treatment may serve to limit cortisone-induced immunosuppression, including preserving leukocyte phagocytic capacity. In conclusion, i.v. n-3 PUFA administration was safe and feasible during hospitalization of multimorbid older subjects for COVID-19. The results identified n-3 PUFA treatment mediated lipid signature of increased proresolving precursor levels and decreased leukotoxin diols in parallel to beneficial immune responses. EudraCT: 2020-002293-28; clinicaltrials.gov: NCT04647604.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Manuela Di Fusco", - "author_inst": "Pfizer Inc." - }, - { - "author_name": "Jay Lin", - "author_inst": "Novosys Health" + "author_name": "Hildur Arnardottir", + "author_inst": "Karolinska Institutet" }, { - "author_name": "Shailja Vaghela", - "author_inst": "HealthEcon Consulting Inc." + "author_name": "Sven-Christian Pawelzik", + "author_inst": "Karolinska Institutet" }, { - "author_name": "Melissa Lingohr-Smith", - "author_inst": "Novosys Health" + "author_name": "Philip Sarajlic", + "author_inst": "Karolinska Institutet" }, { - "author_name": "Jennifer L Nguyen", - "author_inst": "Pfizer, Inc." + "author_name": "Alessandro Quaranta", + "author_inst": "Karolinska Institutet" }, { - "author_name": "Thomas Scassellati Sforzolini", - "author_inst": "Pfizer, Inc." + "author_name": "Johan Kolmert", + "author_inst": "Karolinska Institutet" }, { - "author_name": "Jennifer Judy", - "author_inst": "Pfizer, Inc." + "author_name": "Dorota Religa", + "author_inst": "Karolinska Institutet" }, { - "author_name": "Alejandro Cane", - "author_inst": "Pfizer, Inc." + "author_name": "Craig E Wheelock", + "author_inst": "Karolinska Institutet" }, { - "author_name": "Mary M Moran", - "author_inst": "Pfizer, Inc." + "author_name": "Magnus Back", + "author_inst": "Karolinska Institutet" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "pharmacology and therapeutics" + "category": "respiratory medicine" }, { "rel_doi": "10.1101/2021.12.29.21268487", @@ -444318,79 +443620,87 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.12.28.474336", - "rel_title": "A Novel CRISPR-Engineered, Stem Cell-Derived Cellular Vaccine", + "rel_doi": "10.1101/2021.12.29.474432", + "rel_title": "mRNA-1273 and Ad26.COV2.S vaccines protect against the B.1.621 variant of SARS-CoV-2", "rel_date": "2021-12-29", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.12.28.474336", - "rel_abs": "COVID-19 has forced rapid clinical translation of novel vaccine technologies, principally mRNA vaccines, that have resulted in meaningful efficacy and adequate safety in response to the global pandemic. Notwithstanding this success, there remains an opportunity for innovation in vaccine technology to address current limitations and meet the challenges of inevitable future pandemics. We describe a universal vaccine cell (UVC) rationally designed to mimic the natural physiologic immunity induced post viral infection of host cells. Induced pluripotent stem cells were CRISPR engineered to delete MHC-I expression and simultaneously overexpress a NK Ligand adjuvant to increase rapid cellular apoptosis which was hypothesized to enhance viral antigen presentation in the resulting immune microenvironment leading to a protective immune response. Cells were further engineered to express the parental variant WA1/2020 SARS-CoV-2 spike protein as a representative viral antigen prior to irradiation and cryopreservation. The cellular vaccine was then used to immunize non-human primates in a standard 2-dose, IM injected prime + boost vaccination with 1e8 cells per 1 ml dose resulting in robust neutralizing antibody responses (1e3 nAb titers) with decreasing levels at 6 months duration. Similar titers generated in this established NHP model have translated into protective human neutralizing antibody levels in SARS-Cov-2 vaccinated individuals. Animals vaccinated with WA1/2020 spike antigens were subsequently challenged with 1.0 x 105 TCID50 infectious Delta (B.1.617.2) SARS-CoV-2 in a heterologous challenge which resulted in an approximately 3-log order decrease in viral RNA load in the lungs. These heterologous viral challenge results reflect the ongoing real-world experience of original variant WA1/2020 spike antigen vaccinated populations exposed to rapidly emerging variants like Delta and now Omicron. This cellular vaccine is designed to be a rapidly scalable cell line with a modular poly-antigenic payload to allow for practical, large-scale clinical manufacturing and use in an evolving viral variant environment. Human clinical translation of the UVC is being actively explored for this and potential future pandemics.", - "rel_num_authors": 15, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.12.29.474432", + "rel_abs": "Since the emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in 2019, viral variants with greater transmissibility or immune evasion properties have arisen, which could jeopardize recently deployed vaccine and antibody-based countermeasures. Here, we evaluated in mice and hamsters the efficacy of preclinical non-GMP Moderna mRNA vaccine (mRNA-1273) and the Johnson & Johnson recombinant adenoviral-vectored vaccine (Ad26.COV2.S) against the B.1.621 (Mu) South American variant of SARS-CoV-2, which contains spike mutations T95I, Y144S, Y145N, R346K, E484K, N501Y, D614G, P681H, and D950N. Immunization of 129S2 and K18-human ACE2 transgenic mice with mRNA-1273 vaccine protected against weight loss, lung infection, and lung pathology after challenge with B.1.621 or WA1/2020 N501Y/D614G SARS-CoV-2 strain. Similarly, immunization of 129S2 mice and Syrian hamsters with a high dose of Ad26.COV2.S reduced lung infection after B.1.621 virus challenge. Thus, immunity induced by mRNA-1273 or Ad26.COV2.S vaccines can protect against the B.1.621 variant of SARS-CoV-2 in multiple animal models.", + "rel_num_authors": 17, "rel_authors": [ { - "author_name": "Krishnendu Chakraborty", - "author_inst": "Intima Bioscience" + "author_name": "Tamarand L Darling", + "author_inst": "Washington University in St Louis" }, { - "author_name": "Abishek Chandrashekar", - "author_inst": "Beth Israel Deaconess Medical Center" + "author_name": "Boaling Ying", + "author_inst": "Washington University in St Louis" }, { - "author_name": "Adam Sidaway", - "author_inst": "Intima Bioscience" + "author_name": "Bradley Whitener", + "author_inst": "Washington University in St Louis" }, { - "author_name": "Elizabeth Latta", - "author_inst": "Intima Bioscience" + "author_name": "Laura VanBlargan", + "author_inst": "Washington University in St Louis" }, { - "author_name": "Jingyou Yu", - "author_inst": "Beth Israel Deaconess Medical Center" + "author_name": "Traci L Bricker", + "author_inst": "Washington University in St Louis" }, { - "author_name": "Katherine McMahan", - "author_inst": "Beth Israel Deaconess Medical Center" + "author_name": "Chieh-Yu Liang", + "author_inst": "Washington University in St Louis" }, { - "author_name": "Cordelia Manickam", - "author_inst": "BIDMC/Harvard Medical School" + "author_name": "Astha Joshi", + "author_inst": "Washington University in St Louis" }, { - "author_name": "Kyle Kroll", - "author_inst": "BIDMC/Harvard Medical School" + "author_name": "Gayan Bamunuarachchi", + "author_inst": "Washington University in St Louis" }, { - "author_name": "Matthew Mosher", - "author_inst": "BIDMC/Harvard Medical School" + "author_name": "Kuljeet Seehra", + "author_inst": "Washington University in St Louis" }, { - "author_name": "R. Keith Reeves", - "author_inst": "BIDMC/Harvard Medical School" + "author_name": "Aaron Schmitz", + "author_inst": "Washington University in St Louis" }, { - "author_name": "Rihab Gam", - "author_inst": "Intima Bioscience" + "author_name": "Peter Halfmann", + "author_inst": "University of Wisconsin-Madison" }, { - "author_name": "Elisa Arthofer", - "author_inst": "Intima Bioscience" + "author_name": "Yoshihiro Kawaoka", + "author_inst": "University of Wisconsin-Madison" }, { - "author_name": "Modassir Choudhry", - "author_inst": "Intima Bioscience" + "author_name": "Sayda Elbashir", + "author_inst": "Moderna Inc" }, { - "author_name": "Dan H. Barouch", - "author_inst": "Beth Israel Deaconess Medical Center" + "author_name": "Darin K Edwards", + "author_inst": "Moderna Inc" }, { - "author_name": "Tom Henley", - "author_inst": "Intima Bioscience" + "author_name": "Larissa Thackray", + "author_inst": "Washington University in St Louis" + }, + { + "author_name": "Michael Diamond", + "author_inst": "Washington University School of Medicine" + }, + { + "author_name": "Adrianus Boon", + "author_inst": "Washington University in St Louis" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "new results", - "category": "immunology" + "category": "microbiology" }, { "rel_doi": "10.1101/2021.12.27.474288", @@ -446332,55 +445642,187 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.12.27.21268456", - "rel_title": "Seroprevalence, waning, and correlates of anti-SARS-CoV-2 IgG antibodies in Tyrol, Austria: Large-scale study of 35,193 blood donors conducted between June 2020 and September 2021", - "rel_date": "2021-12-29", + "rel_doi": "10.1101/2021.12.26.21268380", + "rel_title": "SARS-CoV-2 spike T cell responses induced upon vaccination or infection remain robust against Omicron", + "rel_date": "2021-12-28", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.27.21268456", - "rel_abs": "BackgroundThere is uncertainty about the seroprevalence of anti-SARS-CoV-2 antibodies in the general population of Austria, and about the extent to which antibodies elicited by vaccination or infection wane over time.\n\nAimTo estimate seroprevalence, waning, and correlates of anti-SARS-CoV-2 IgG antibodies in the Federal State of Tyrol, Austria.\n\nMethodsWe conducted a seroepidemiological study between June 2020 and September 2021, enrolling blood donors aged 18-70 years across Tyrol, Austria (participation rate 84.0%). We analysed serum samples for antibodies against spike or nucleocapsid proteins of SARS-CoV-2 with Abbott SARS-CoV-2 IgG assays.\n\nResultsWe performed 47,363 serological tests among 35,193 individuals (median age 43.1 years [IQR: 29.3-53.7], 45.3% women, 10.0% with prior SARS-CoV-2 infection). Seroprevalence increased from 3.4% (95% CI: 2.8-4.2%) in June 2020 to 82.7% (95% CI: 81.4-83.8%) in September 2021, largely due to vaccination. Anti-spike IgG seroprevalence was 99.6% (99.4-99.7%) among fully vaccinated individuals, 90.4% (88.8-91.7%) among unvaccinated with prior infection, and 11.5% (10.8-12.3%) among unvaccinated without known prior infection. Anti-spike IgG levels were reduced by 44.0% (34.9-51.7%) at 5-6 months compared to 0-3 months after infection. In fully vaccinated individuals, they decreased by 31.7% (29.4-33.9%) per month. In multivariable adjusted analyses, both seropositivity among unvaccinated and antibody levels among fully vaccinated individuals were higher at young age (<25 years), higher with a known prior infection, and lower in current smokers.\n\nConclusionSeroprevalence in Tyrol increased to 82.7% in September 2021, with the bulk of seropositivity stemming from vaccination. Antibody levels substantially and gradually declined after vaccination or infection.", - "rel_num_authors": 9, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.26.21268380", + "rel_abs": "The SARS-CoV-2 Omicron variant has multiple Spike (S) protein mutations that contribute to escape from the neutralizing antibody responses, and reducing vaccine protection from infection. The extent to which other components of the adaptive response such as T cells may still target Omicron and contribute to protection from severe outcomes is unknown. We assessed the ability of T cells to react with Omicron spike in participants who were vaccinated with Ad26.CoV2.S or BNT162b2, and in unvaccinated convalescent COVID-19 patients (n = 70). We found that 70-80% of the CD4 and CD8 T cell response to spike was maintained across study groups. Moreover, the magnitude of Omicron cross-reactive T cells was similar to that of the Beta and Delta variants, despite Omicron harbouring considerably more mutations. Additionally, in Omicron-infected hospitalized patients (n = 19), there were comparable T cell responses to ancestral spike, nucleocapsid and membrane proteins to those found in patients hospitalized in previous waves dominated by the ancestral, Beta or Delta variants (n = 49). These results demonstrate that despite Omicrons extensive mutations and reduced susceptibility to neutralizing antibodies, the majority of T cell response, induced by vaccination or natural infection, cross-recognises the variant. Well-preserved T cell immunity to Omicron is likely to contribute to protection from severe COVID-19, supporting early clinical observations from South Africa.", + "rel_num_authors": 42, "rel_authors": [ { - "author_name": "Anita Siller", - "author_inst": "Central Institute for Blood Transfusion and Immunology, Tirol Kliniken GmbH, Innsbruck, Austria" + "author_name": "Roanne Keeton", + "author_inst": "Institute of Infectious Disease and Molecular Medicine, University of Cape Town, Observatory, South Africa; Division of Medical Virology, Department of Patholo" }, { - "author_name": "Lisa Seekircher", - "author_inst": "Clinical Epidemiology Team, Medical University of Innsbruck, Innsbruck, Austria" + "author_name": "Marius B Tincho", + "author_inst": "Institute of Infectious Disease and Molecular Medicine, University of Cape Town, Observatory, South Africa; Division of Medical Virology, Department of Patholo" }, { - "author_name": "Gregor A Wachter", - "author_inst": "Central Institute for Blood Transfusion and Immunology, Tirol Kliniken GmbH, Innsbruck, Austria" + "author_name": "Amkele Ngomti", + "author_inst": "Institute of Infectious Disease and Molecular Medicine, University of Cape Town, Observatory, South Africa; Division of Medical Virology, Department of Patholo" }, { - "author_name": "Manfred Astl", - "author_inst": "Central Institute for Blood Transfusion and Immunology, Tirol Kliniken GmbH, Innsbruck, Austria" + "author_name": "Richard Baguma", + "author_inst": "Institute of Infectious Disease and Molecular Medicine, University of Cape Town, Observatory, South Africa; Division of Medical Virology, Department of Patholo" }, { - "author_name": "Lena Tschiderer", - "author_inst": "Clinical Epidemiology Team, Medical University of Innsbruck, Innsbruck, Austria" + "author_name": "Ntombi Benede", + "author_inst": "Institute of Infectious Disease and Molecular Medicine, University of Cape Town, Observatory, South Africa; Division of Medical Virology, Department of Patholo" }, { - "author_name": "Bernhard Pfeifer", - "author_inst": "Department of Clinical Epidemiology, Tyrolean Federal Institute for Integrated Care, Tirol Kliniken GmbH, Innsbruck, Austria, and Division for Healthcare Networ" + "author_name": "Akiko Suzuki", + "author_inst": "Institute of Infectious Disease and Molecular Medicine, University of Cape Town, Observatory, South Africa; Division of Medical Virology, Department of Patholo" }, { - "author_name": "Manfred Gaber", - "author_inst": "Blood donor service Tyrol of the Austrian Red Cross, Rum, Austria" + "author_name": "Khadija Khan", + "author_inst": "Africa Health Research Institute, Durban, South Africa; School of Laboratory Medicine and Medical Sciences, University of KwaZulu-Natal, Durban, South Africa" }, { - "author_name": "Harald Schennach", - "author_inst": "Central Institute for Blood Transfusion and Immunology, Tirol Kliniken GmbH, Innsbruck, Austria" + "author_name": "Sandile Cele", + "author_inst": "Africa Health Research Institute, Durban, South Africa; School of Laboratory Medicine and Medical Sciences, University of KwaZulu-Natal, Durban, South Africa" }, { - "author_name": "Peter Willeit", - "author_inst": "Clinical Epidemiology Team, Medical University of Innsbruck, Innsbruck, Austria, and Department of Public Health and Primary Care, University of Cambridge, Camb" + "author_name": "Mallory Bernstein", + "author_inst": "Africa Health Research Institute, Durban, South Africa; School of Laboratory Medicine and Medical Sciences, University of KwaZulu-Natal, Durban, South Africa" + }, + { + "author_name": "Farina Karim", + "author_inst": "Africa Health Research Institute, Durban, South Africa; School of Laboratory Medicine and Medical Sciences, University of KwaZulu-Natal, Durban, South Africa" + }, + { + "author_name": "Sharon V Madzorera", + "author_inst": "National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa; SA MRC Antibody Immunity Research Unit, Scho" + }, + { + "author_name": "Thandeka Moyo-Gwete", + "author_inst": "National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa; SA MRC Antibody Immunity Research Unit, Scho" + }, + { + "author_name": "Mathilda Mennen", + "author_inst": "Department of Medicine, University of Cape Town and Groote Schuur Hospital, Observatory, South Africa" + }, + { + "author_name": "Sango Skelem", + "author_inst": "Department of Medicine, University of Cape Town and Groote Schuur Hospital, Observatory, South Africa" + }, + { + "author_name": "Marguerite Adriaanse", + "author_inst": "Department of Medicine, University of Cape Town and Groote Schuur Hospital, Observatory, South Africa" + }, + { + "author_name": "Daniel Mutithu", + "author_inst": "Department of Medicine, University of Cape Town and Groote Schuur Hospital, Observatory, South Africa" + }, + { + "author_name": "Olukayode Aremu", + "author_inst": "Department of Medicine, University of Cape Town and Groote Schuur Hospital, Observatory, South Africa" + }, + { + "author_name": "Cari Stek", + "author_inst": "Institute of Infectious Disease and Molecular Medicine, University of Cape Town, Observatory, South Africa; Department of Medicine, University of Cape Town and " + }, + { + "author_name": "Elsa du Bruyn", + "author_inst": "Institute of Infectious Disease and Molecular Medicine, University of Cape Town, Observatory, South Africa; Department of Medicine, University of Cape Town and " + }, + { + "author_name": "Mieke Van Der Mescht", + "author_inst": "Department of Immunology, University of Pretoria, Pretoria, South Africa" + }, + { + "author_name": "Zelda de Beer", + "author_inst": "Tshwane District Hospital, Tshwane, South Africa" + }, + { + "author_name": "Talita R de Villiers", + "author_inst": "Tshwane District Hospital, Tshwane, South Africa" + }, + { + "author_name": "Annie Bodenstein", + "author_inst": "Tshwane District Hospital, Tshwane, South Africa" + }, + { + "author_name": "Gretha van den Berg", + "author_inst": "Tshwane District Hospital, Tshwane, South Africa" + }, + { + "author_name": "Adriano Mendes", + "author_inst": "Centre for Viral Zoonoses, Department of Virology, University of Pretoria, Pretoria, South Africa" + }, + { + "author_name": "Amy Strydom", + "author_inst": "Centre for Viral Zoonoses, Department of Virology, University of Pretoria, Pretoria, South Africa" + }, + { + "author_name": "Marietjie Venter", + "author_inst": "Centre for Viral Zoonoses, Department of Virology, University of Pretoria, Pretoria, South Africa" + }, + { + "author_name": "Alba Grifoni", + "author_inst": "Center for Infectious Disease and Vaccine Research, La Jolla Institute for Immunology, La Jolla, California, USA" + }, + { + "author_name": "Daniela Weiskopf", + "author_inst": "Center for Infectious Disease and Vaccine Research, La Jolla Institute for Immunology, La Jolla, California, USA" + }, + { + "author_name": "Alessandro Sette", + "author_inst": "Center for Infectious Disease and Vaccine Research, La Jolla Institute for Immunology, La Jolla, California, USA; Department of Medicine, Division of Infectious" + }, + { + "author_name": "Robert J Wilkinson", + "author_inst": "Institute of Infectious Disease and Molecular Medicine, University of Cape Town, Observatory, South Africa; Department of Medicine, University of Cape Town and " + }, + { + "author_name": "Linda-Gail Bekker", + "author_inst": "Institute of Infectious Disease and Molecular Medicine, University of Cape Town, Observatory, South Africa; Department of Medicine, University of Cape Town and " + }, + { + "author_name": "Glenda Gray", + "author_inst": "South African Medical Research Council, Cape Town, South Africa" + }, + { + "author_name": "Veronica Ueckermann", + "author_inst": "Department of Internal Medicine, University of Pretoria and Steve Biko Academic Hospital, Pretoria, South Africa" + }, + { + "author_name": "Theresa Rossouw", + "author_inst": "Department of Immunology, University of Pretoria, Pretoria, South Africa" + }, + { + "author_name": "Michael T Boswell", + "author_inst": "Department of Internal Medicine, University of Pretoria and Steve Biko Academic Hospital, Pretoria, South Africa" + }, + { + "author_name": "Jinal Bihman", + "author_inst": "National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa; SA MRC Antibody Immunity Research Unit, Scho" + }, + { + "author_name": "Penny Moore", + "author_inst": "Institute of Infectious Disease and Molecular Medicine, University of Cape Town, Observatory, South Africa; National Institute for Communicable Diseases of the " + }, + { + "author_name": "Alex Sigal", + "author_inst": "Africa Health Research Institute, Durban, South Africa; School of Laboratory Medicine and Medical Sciences, University of KwaZulu-Natal, Durban, South Africa; M" + }, + { + "author_name": "Ntobeko A. B. Ntusi", + "author_inst": "Institute of Infectious Disease and Molecular Medicine, University of Cape Town, Observatory, South Africa; Department of Medicine, University of Cape Town and " + }, + { + "author_name": "Wendy A Burgers", + "author_inst": "Institute of Infectious Disease and Molecular Medicine, University of Cape Town, Observatory, South Africa; Division of Medical Virology, Department of Patholo" + }, + { + "author_name": "Catherine Riou", + "author_inst": "Institute of Infectious Disease and Molecular Medicine, University of Cape Town, Observatory, South Africa; Division of Medical Virology, Department of Patholo" } ], "version": "1", "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2021.12.28.474244", @@ -448546,31 +447988,95 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2021.12.21.21268173", - "rel_title": "Post COVID-19 1st Dose Vaccination Common Symptoms among SE Asia College Students", + "rel_doi": "10.1101/2021.12.27.21268278", + "rel_title": "SARS-CoV-2 Omicron VOC Transmission in Danish Households", "rel_date": "2021-12-27", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.21.21268173", - "rel_abs": "In the second year of the COVID-19 epidemic in the Southeast Asia (SE) regions, there is a plan to reopen the school, including the campus. Among students in Indonesia, college students have a population of almost 8.3 million. Considering the massive numbers of college students, school reopening should be supported by adequate COVID-19 vaccination. As a result, the first dose of the inactivated virus COVID-19 vaccine has been administered, including to college students aged over 18 years old. While COVID-19 vaccination is widely available, there is still a scarcity of information on post-vaccination symptoms. As reported from other locations, post vaccination has been reported. Then, this study aims to assess the common symptoms of COVID-19 1st dose vaccinations among the following groups: gender (male and female college students), age, body weight, and height. The observed symptoms include sore arms, fatigue, headache, fever with a body temperature above 38 {degrees}C, nausea, shivering, and muscle joint pain. Participants in this study were students at the university. They were considered eligible for this study if they were currently enrolled at university, were at least 19 years of age, and provided informed consent. The data was recorded using a standardized online questionnaire. The answers were collected in an online database. At the beginning of the questionnaire, subjects or students were informed that data would be collected anonymously. Based on the results, the symptoms were different between female and male students. In fact, female students have experienced more symptoms than male students. While male students only suffered sore arms (68%) followed by headache symptoms (32%). Similar to male students, sore arms are the most common symptom observed among female students. Among female students, from the most to the least common symptoms observed from 20 years of age in this study are sore arms at site reaction > headache > fatigue > fever > muscle joint pain > shivering > nausea. A higher risk of presenting fatigue and headache symptoms was found in those with a non-overweight status with weight ranges of 50-60 kg.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.27.21268278", + "rel_abs": "1The Omicron variant of concern (VOC) is a rapidly spreading variant of SARS-CoV-2 that is likely to overtake the previously dominant Delta VOC in many countries by the end of 2021.\n\nWe estimated the transmission dynamics following the spread of Omicron VOC within Danish households during December 2021. We used data from Danish registers to estimate the household secondary attack rate (SAR).\n\nAmong 11,937 households (2,225 with the Omicron VOC), we identified 6,397 secondary infections during a 1-7 day follow-up period. The SAR was 31% and 21% in households with the Omicron and Delta VOC, respectively. We found an increased transmission for unvaccinated individuals, and a reduced transmission for booster-vaccinated individuals, compared to fully vaccinated individuals. Comparing households infected with the Omicron to Delta VOC, we found an 1.17 (95%-CI: 0.99-1.38) times higher SAR for unvaccinated, 2.61 times (95%-CI: 2.34-2.90) higher for fully vaccinated and 3.66 (95%-CI: 2.65-5.05) times higher for booster-vaccinated individuals, demonstrating strong evidence of immune evasiveness of the Omicron VOC.\n\nOur findings confirm that the rapid spread of the Omicron VOC primarily can be ascribed to the immune evasiveness rather than an inherent increase in the basic transmissibility.", + "rel_num_authors": 19, "rel_authors": [ { - "author_name": "Andri Wibowo", - "author_inst": "Universitas Indonesia" + "author_name": "Frederik Plesner Lyngse", + "author_inst": "University of Copenhagen" + }, + { + "author_name": "Laust Hvas Mortensen", + "author_inst": "Statistics Denmark" + }, + { + "author_name": "Matthew J. Denwood", + "author_inst": "University of Copenhagen" + }, + { + "author_name": "Lasse Engbo Christiansen", + "author_inst": "DTU" }, { - "author_name": "Natasya O Yostyadiananda", - "author_inst": "Universitas Indonesia" + "author_name": "Camilla Holten M\u00f8ller", + "author_inst": "Statens Serum Institut" }, { - "author_name": "Gabriella RA Gunawan", - "author_inst": "Universitas Indonesia" + "author_name": "Robert Leo Skov", + "author_inst": "Statens Serum Institut" + }, + { + "author_name": "Katja Spiess", + "author_inst": "Statens Serum Institut" + }, + { + "author_name": "Anders Fomsgaard", + "author_inst": "Statens Serum Institut" + }, + { + "author_name": "Ria Lassauniere", + "author_inst": "Statens Serum Institut" + }, + { + "author_name": "Morten Rasmussen", + "author_inst": "Statens Serum Institut" + }, + { + "author_name": "Marc Stegger", + "author_inst": "Statens Serum Institut" + }, + { + "author_name": "Claus Nielsen", + "author_inst": "Statens Serum Institut" + }, + { + "author_name": "Raphael Niklaus Sieber", + "author_inst": "Statens Serum Institut" + }, + { + "author_name": "Arieh Sierra Cohen", + "author_inst": "Statens Serum Institut" + }, + { + "author_name": "Frederik Trier M\u00f8ller", + "author_inst": "Statens Serum Institut" + }, + { + "author_name": "Maria Overvad", + "author_inst": "Statens Serum Institut" + }, + { + "author_name": "K\u00e5re M\u00f8lbak", + "author_inst": "Statens Serum Institut" + }, + { + "author_name": "Tyra Grove Krause", + "author_inst": "Statens Serum Institut" + }, + { + "author_name": "Carsten Thure Kirkeby", + "author_inst": "University of Copenhagen" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "health informatics" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2021.12.26.21268420", @@ -450828,63 +450334,27 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.12.24.21268387", - "rel_title": "The Canadian COVID-19 Experiences Survey: Study Protocol", + "rel_doi": "10.1101/2021.12.22.21268212", + "rel_title": "Dying from COVID-19 or with COVID-19: a definitive answer through a retrospective analysis of mortality in Italy", "rel_date": "2021-12-27", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.24.21268387", - "rel_abs": "IntroductionVaccine hesitancy and inconsistent mitigation behavior performance have been significant challenges throughout the COVID-19 pandemic. In Canada, despite relatively high vaccine availability and uptake, willingness to accept booster shots and maintain mitigation behaviors in the post-acute phase of COVID-19 remain uncertain. The aim of the Canadian COVID-19 Experiences Project (CCEP) is two-fold: 1) to identify social-cognitive and neurocognitive correlates of vaccine hesitancy and mitigation behaviors, and 2) to identify optimal communication strategies to promote vaccination and mitigation behaviors into the post-acute phase of the pandemic.\n\nMethods and analysesThe CCEP is comprised of two components: a conventional population survey (Study 1) and a functionally interconnected laboratory study (Study 2). Study 1 will involve 3 waves of data collection. Wave 1, completed between 28 September and 21 October, 2021, recruited 1,958 vaccine-hesitant (49.8%) and fully vaccinated (50.2%) adults using quota sampling to ensure maximum statistical power. Measures included a variety of social cognitive (e.g., beliefs, intentions) and neurocognitive (e.g., delay discounting) measures, followed by an opportunity to view and rate a set of professionally produced COVID-19 public service announcement (PSA) videos for perceived efficacy. Study 2 employs the same survey items and PSAs but coupled with lab-based eye tracking and functional brain imaging to directly quantify neural indicators of attention capture and self-reflection in a smaller community sample. In the final phase of the project, subjective impressions and neural indicators of PSA efficacy will be compared and used to inform recommendations for construction of COVID-19 PSAs into the post-acute phase of the pandemic.\n\nEthics and disseminationThe CCEP has received ethical review and approval by the University of Waterloo Office of Research Ethics. Findings will be disseminated through peer-reviewed publications and presentations at scientific meetings.", - "rel_num_authors": 11, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.22.21268212", + "rel_abs": "BackgroundCOVID-19 mortality was associated with several reasons, including conspiracy theories and infodemic phenomena. However, little is known about the potential endogenous reasons for the increase in COVID-19 associated mortality in Italy.\n\nObjectiveThis study aimed to search the potential endogenous reasons for the increase in COVID-19 mortality recorded in Italy during the year 2020 and evaluate the statistical significance of the latter.\n\nMethodsWe analyzed all the trends in the timelapse 2011-2019 related to deaths by age, sex, region, and cause of death in Italy and compared them with those of 2020. Ordinary least squares (OLS) linear regressions and ARIMA (p, d, q) models were applied to investigate the predictions of death in 2020 as compared to death reported in the same year. Grubbs and Iglewicz-Hoaglin tests were used to identify the statistical differences between the predicted and observed deaths. The relationship between mortality and predictive variables was assessed using OLS multiple regression models.\n\nResultsBoth ARIMA and OLS linear regression models predicted the number of deaths in Italy during 2020 to be between 640,000 and 660,000 (95% confidence intervals range: 620,000 - 695,000) and these values were far from the observed deaths reported (above 750,000). Significant difference in deaths at national level (P = 0.003), and higher male mortality than women (+18% versus +14%, P < 0.001 versus P = 0.01) was observed. Finally, higher mortality was strongly and positively correlated with latitude (R = 0.82, P < 0.001).\n\nConclusionsOur findings support the absence of historical endogenous reasons capable of justifying the increase in deaths and mortality observed in Italy in 2020. Together with the current knowledge on the novel coronavirus 2019, these findings provide decisive evidence on the devastating impact of COVID-19 in Italy. We suggest that this research be leveraged by government, health, and information authorities to furnish proof against conspiracy hypotheses. Moreover, given the marked concordance between the predictions of the ARIMA and OLS regression models, we suggest that these models be exploited to predict mortality trends.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Peter Hall", - "author_inst": "University of Waterloo" - }, - { - "author_name": "Geoffrey Fong", - "author_inst": "University of Waterloo" - }, - { - "author_name": "Sara Hitchman", - "author_inst": "University of Zurich" - }, - { - "author_name": "Anne Quah", - "author_inst": "University of Waterloo" - }, - { - "author_name": "Thomas Agar", - "author_inst": "University of Waterloo" - }, - { - "author_name": "Gang Meng", - "author_inst": "University of Waterloo" - }, - { - "author_name": "Hasan Ayaz", - "author_inst": "Drexel University" - }, - { - "author_name": "Bruce Dore", - "author_inst": "McGill University" - }, - { - "author_name": "Mohammad Nazmus Sakib", - "author_inst": "University of Waterloo" - }, - { - "author_name": "Anna Hudson", - "author_inst": "University of Waterloo" + "author_name": "Alessandro Rovetta", + "author_inst": "R&C Research" }, { - "author_name": "Christian Boudreau", - "author_inst": "University of Waterloo" + "author_name": "Akshaya Srikanth Bhagavathula", + "author_inst": "Institute of Public Health, College of Medicine and Health Sciences, UAE University, Al Ain 17666, Abu Dhabi, United Arab Emirates." } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2021.12.26.21268434", @@ -452798,107 +452268,27 @@ "category": "primary care research" }, { - "rel_doi": "10.1101/2021.12.22.21268252", - "rel_title": "Rapid increase in Omicron infections in England during December 2021: REACT-1 study", + "rel_doi": "10.1101/2021.12.21.470882", + "rel_title": "COVID-19: Salient Aspects of Coronavirus Infection, Vaccines and Vaccination Testing and their Implications", "rel_date": "2021-12-24", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.22.21268252", - "rel_abs": "BackgroundThe highest-ever recorded numbers of daily severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections in England has been observed during December 2021 and have coincided with a rapid rise in the highly transmissible Omicron variant despite high levels of vaccination in the population. Although additional COVID-19 measures have been introduced in England and internationally to contain the epidemic, there remains uncertainty about the spread and severity of Omicron infections among the general population.\n\nMethodsThe REal-time Assessment of Community Transmission-1 (REACT-1) study has been monitoring the prevalence of SARS-CoV-2 infection in England since May 2020. REACT-1 obtains self-administered throat and nose swabs from a random sample of the population of England at ages 5 years and over. Swabs are tested for SARS-CoV-2 infection by reverse transcription polymerase chain reaction (RT-PCR) and samples testing positive are sent for viral genome sequencing. To date 16 rounds have been completed, each including [~]100,000 or more participants with data collected over a period of 2 to 3 weeks per month. Socio-demographic, lifestyle and clinical information (including previous history of COVID-19 and symptoms prior to swabbing) is collected by online or telephone questionnaire. Here we report results from round 14 (9-27 September 2021), round 15 (19 October - 05 November 2021) and round 16 (23 November - 14 December 2021) for a total of 297,728 participants with a valid RT-PCR test result, of whom 259,225 (87.1%) consented for linkage to their NHS records including detailed information on vaccination (vaccination status, date). We used these data to estimate community prevalence and trends by age and region, to evaluate vaccine effectiveness against infection in children ages 12 to 17 years, and effect of a third (booster) dose in adults, and to monitor the emergence of the Omicron variant in England.\n\nResultsWe observed a high overall prevalence of 1.41% (1.33%, 1.51%) in the community during round 16. We found strong evidence of an increase in prevalence during round 16 with an estimated reproduction number R of 1.13 (1.06, 1.09) for the whole of round 16 and 1.27 (1.14, 1.40) when restricting to observations from 1 December onwards. The reproduction number in those aged 18-54 years was estimated at 1.23 (1.14, 1.33) for the whole of round 16 and 1.41 (1.23, 1.61) from 1 December. Our data also provide strong evidence of a steep increase in prevalence in London with an estimated R of 1.62 (1.34, 1.93) from 1 December onwards and a daily prevalence reaching 6.07% (4.06%, 9.00%) on 14 December 2021. As of 1 to 11 December 2021, of the 275 lineages determined, 11 (4.0%) corresponded to the Omicron variant. The first Omicron infection was detected in London on 3 December, and subsequent infections mostly appeared in the South of England. The 11 Omicron cases were all aged 18 to 54 years, double-vaccinated (reflecting the large numbers of people who have received two doses of vaccine in this age group) but not boosted, 9 were men, 5 lived in London and 7 were symptomatic (5 with classic COVID-19 symptoms: loss or change of sense of smell or taste, fever, persistent cough), 2 were asymptomatic, and symptoms were unknown for 2 cases. The proportion of Omicron (vs Delta or Delta sub-lineages) was found to increase rapidly with a daily increase of 66.0% (32.7%, 127.3%) in the odds of Omicron (vs. Delta) infection, conditional on swab positivity. Highest prevalence of swab positivity by age was observed in (unvaccinated) children aged 5 to 11 years (4.74% [4.15%, 5.40%]) similar to the prevalence observed at these ages in round 15. In contrast, prevalence in children aged 12 to 17 years more than halved from 5.35% (4.78%, 5.99%) in round 15 to 2.31% (1.91%, 2.80%) in round 16. As of 14 December 2021, 76.6% children at ages 12 to 17 years had received at least one vaccine dose; we estimated that vaccine effectiveness against infection was 57.9% (44.1%, 68.3%) in this age group. In addition, the prevalence of swab positivity in adults aged 65 years and over fell by over 40% from 0.84% (0.72%, 0.99%) in round 15 to 0.48% (0.39%,0.59%) in round 16 and for those aged 75 years and over it fell by two-thirds from 0.63% (0.48%,0.82%) to 0.21% (0.13%,0.32%). At these ages a high proportion of participants (>90%) had received a third vaccine dose; we estimated that adults having received a third vaccine dose had a three- to four-fold lower risk of testing positive compared to those who had received two doses.\n\nConclusionA large fall in swab positivity from round 15 to round 16 among 12 to 17 year olds, most of whom have been vaccinated, contrasts with the continuing high prevalence among 5 to 11 year olds who have largely not been vaccinated. Likewise there were large falls in swab positivity among people aged 65 years and over, the vast majority of whom have had a third (booster) vaccine dose; these results reinforce the importance of the vaccine and booster campaign. However, the rapidly increasing prevalence of SARS-CoV-2 infections in England during December 2021, coincident with the rapid rise of Omicron infections, may lead to renewed pressure on health services. Additional measures beyond vaccination may be needed to control the current wave of infections and prevent health services (in England and other countries) from being overwhelmed.\n\nSummaryThe unprecedented rise in SARS-CoV-2 infections is concurrent with rapid spread of the Omicron variant in England and globally. We analysed prevalence of SARS-CoV-2 and its dynamics in England from end of November to mid-December 2021 among almost 100,000 participants from the REACT-1 study. Prevalence was high during December 2021 with rapid growth nationally and in London, and of the proportion of infections due to Omicron. We observed a large fall in swab positivity among mostly vaccinated older children (12-17 years) compared with unvaccinated younger children (5-11 years), and in adults who received a third vs. two doses of vaccine. Our results reiterate the importance of vaccination and booster campaigns; however, additional measures may be needed to control the rapid growth of the Omicron variant.", - "rel_num_authors": 22, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2021.12.21.470882", + "rel_abs": "In the present study, three basic aspects related to COVID-19 are presented.\n\nO_LIThe occurrence of coronavirus infection is analyzed statistically as number of coronaviruses infected alveolar cells compared to normal alveolar cells in human lungs. The mole concept is used to estimate the number of normal alveolar cells per human lung. The number of coronavirus infections in infected alveolar cells is estimated from the published Lower Respiratory Tract (LRT) load data. The Poisson probability distribution is aptly applied to imply the incubation period of the coronavirus infection to be within day-3 to day-7, with the cumulative probability of 75%. The incubation period within day-0 to day-10 has a cumulative probability of 98%. It implies a 10-day quarantine to isolate an uninfected individual as a precautionary measure.\nC_LIO_LIThree vaccines to combat COVID-19, which adopt distinct paradigms while preparing them, are analyzed. These are Modernas mRNA-1273, Oxford-AstraZenecas ChAdOx1 nCoV-19 and Bharat BioTechs COVAXIN. The mole concept is used to estimate the antigen mass density per dose of each of these vaccines as 10 g cm-3, 0.1 g cm-3 and 1 g cm-3, respectively. The vaccines are deemed to be compatible to neutralize the infection.\nC_LIO_LIA statistical analysis is performed of the Modernas mRNA-1273 vaccine efficacy of 94.1% and Oxfords ChAdOx1 nCoV-19 vaccine efficacy of 62.1% in terms of groups of volunteers testing negative to vaccine by chance. In the Moderna vaccination testing scenario, since the probability of negative response of vaccine is small, the Poisson probability distribution for 95% cumulative probability is used to describe the vaccination testing in 300 samples of 47 volunteers each. Thus, 87% of samples have average group of 3 volunteers testing negative to vaccine. About 6% of samples have all volunteers testing positive to vaccine. In the Oxford vaccination testing scenario, since the probability of negative response of vaccine is finite, the Gaussian probability distribution for 95% probability is used to describe the vaccination testing in 75 samples of 120 volunteers each. Thus, 68% of samples have average group of 45 volunteers testing negative to vaccine. No sample has all volunteers testing positive to vaccine. A vaccine, irrespective of its efficacy being high or low, is necessary for mass immunization.\nC_LI", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Paul Elliott", - "author_inst": "School of Public Health, Imperial College London, UKImperial College Healthcare NHS Trust, UKNational Institute for Health Research Imperial Biomedical Research" - }, - { - "author_name": "Barbara Bodinier", - "author_inst": "School of Public Health, Imperial College London, UK" - }, - { - "author_name": "Oliver Eales", - "author_inst": "School of Public Health, Imperial College London, UKMRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergency" - }, - { - "author_name": "Haowei Wang", - "author_inst": "School of Public Health, Imperial College London, UKMRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergency" - }, - { - "author_name": "David Haw", - "author_inst": "School of Public Health, Imperial College London, UKMRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergency" - }, - { - "author_name": "Joshua Elliott", - "author_inst": "Imperial College London" - }, - { - "author_name": "Matthew Whitaker", - "author_inst": "School of Public Health, Imperial College London, UK" + "author_name": "Pradeep K. Pasricha", + "author_inst": "National Physical Laboratory CSIR (Retired)" }, { - "author_name": "Jakob Jonnerby", - "author_inst": "School of Public Health, Imperial College London, UKMRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergency" - }, - { - "author_name": "David Tang", - "author_inst": "Imperial College London" - }, - { - "author_name": "Caroline E. Walters", - "author_inst": "School of Public Health, Imperial College London, UKMRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergency" - }, - { - "author_name": "Christina Atchinson", - "author_inst": "School of Public Health, Imperial College London, UK" - }, - { - "author_name": "Peter J. Diggle", - "author_inst": "CHICAS, Lancaster Medical School, Lancaster University, UK and Health Data Research, UK" - }, - { - "author_name": "Andrew J. Page", - "author_inst": "Quadram Institute, Norwich, UK" - }, - { - "author_name": "Alex Trotter", - "author_inst": "Quadram Institute Bioscience" - }, - { - "author_name": "Deborah Ashby", - "author_inst": "School of Public Health, Imperial College London, UK" - }, - { - "author_name": "Wendy Barclay", - "author_inst": "Department of Infectious Disease, Imperial College London, UK" - }, - { - "author_name": "Graham Taylor", - "author_inst": "Department of Infectious Disease, Imperial College London, UK" - }, - { - "author_name": "Helen Ward", - "author_inst": "School of Public Health, Imperial College London, UKImperial College Healthcare NHS Trust, UKNational Institute for Health Research Imperial Biomedical Research" - }, - { - "author_name": "Ara Darzi", - "author_inst": "Imperial College Healthcare NHS Trust, UKNational Institute for Health Research Imperial Biomedical Research Centre, UKInstitute of Global Health Innovation at " - }, - { - "author_name": "Graham Cooke", - "author_inst": "Department of Infectious Disease, Imperial College London, UKImperial College Healthcare NHS Trust, UKNational Institute for Health Research Imperial Biomedical" - }, - { - "author_name": "Marc Chadeau-Hyam", - "author_inst": "School of Public Health, Imperial College London, UK" - }, - { - "author_name": "Christl A Donnelly", - "author_inst": "School of Public Health, Imperial College London, UKMRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergency" + "author_name": "Arun K. Upadhayaya", + "author_inst": "National Physical Laboratory CSIR" } ], "version": "1", - "license": "cc_by_nc_nd", - "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "license": "cc_no", + "type": "new results", + "category": "scientific communication and education" }, { "rel_doi": "10.1101/2021.12.21.473733", @@ -454952,18 +454342,67 @@ "category": "evolutionary biology" }, { - "rel_doi": "10.1101/2021.12.21.473702", - "rel_title": "Tutorial: Investigating SARS-CoV-2 evolution and phylogeny using MNHN-Tree-Tools", + "rel_doi": "10.1101/2021.12.22.472458", + "rel_title": "Computational Mapping of the Human-SARS-CoV-2 Protein-RNA Interactome", "rel_date": "2021-12-23", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.12.21.473702", - "rel_abs": "The Covid-19 pandemic has caused at more than 3 million deaths by Mai this year [1]. It had a significant impact on the daily life and the global economy [2]. The virus has since its first recorded outbreak in China [3] mutated into new strains [4]. The Nextstrain [5] project has so far been monitoring the evolution of the virus. At the same time we were developing in our lab the MNHN-Tree-Tools [6] toolkit, primarily for the investigation of DNA repeat sequences. We have further extended MNHN-Tree-Tools [6] to guide phylogenetics. As such the toolkit has evolved into a high performance code, allowing for a fast investigation of millions of sequences. Given the context of the pandemic it became evident that we will use our versatile tool to investigate the evolution of SARS-CoV-2 sequences. Our efforts have cumulated in this tutorial that we share with the scientific community.", - "rel_num_authors": 0, - "rel_authors": null, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.12.22.472458", + "rel_abs": "Strong evidence suggests that human human RNA-binding proteins (RBPs) are critical factors for viral infection, yet there is no feasible experimental approach to map exact binding sites of RBPs across the SARS-CoV-2 genome systematically at a large scale. We investigated the role of RBPs in the context of SARS-CoV-2 by constructing the first in silico map of human RBP / viral RNA interactions at nucleotide-resolution using two deep learning methods (pysster and DeepRiPe) trained on data from CLIP-seq experiments. We evaluated conservation of RBP binding between 6 other human pathogenic coronaviruses and identified sites of conserved and differential binding in the UTRs of SARS-CoV-1, SARS-CoV-2 and MERS. We scored the impact of variants from 11 viral strains on protein-RNA interaction, identifying a set of gain-and loss of binding events. Lastly, we linked RBPs to functional data and OMICs from other studies, and identified MBNL1, FTO and FXR2 as potential clinical biomarkers. Our results contribute towards a deeper understanding of how viruses hijack host cellular pathways and are available through a comprehensive online resource (https://sc2rbpmap.helmholtz-muenchen.de).", + "rel_num_authors": 12, + "rel_authors": [ + { + "author_name": "Marc Horlacher", + "author_inst": "Computational Health Center, Helmholtz Center Munich, Germany" + }, + { + "author_name": "Svitlana Oleshko", + "author_inst": "Computational Health Center, Helmholtz Center Munich, Germany" + }, + { + "author_name": "Yue Hu", + "author_inst": "Computational Health Center, Helmholtz Center Munich, Germany" + }, + { + "author_name": "Giulia Cantini", + "author_inst": "Computational Health Center, Helmholtz Center Munich, Germany" + }, + { + "author_name": "Patrick Schinke", + "author_inst": "Computational Health Center, Helmholtz Center Munich, Germany" + }, + { + "author_name": "Mahsa Ghanbari", + "author_inst": "Berlin Institute for Medical Systems Biology, Max Delbruck Center for Molecular Medicine, Berlin, Germany" + }, + { + "author_name": "Ernesto Elorduy Vergara", + "author_inst": "Computational Health Center, Helmholtz Center Munich, Germany" + }, + { + "author_name": "Florian Bittner", + "author_inst": "Knowing01 GmbH, Munich, Germany" + }, + { + "author_name": "Nikola Mueller", + "author_inst": "Knowing01 GmbH, Munich, Germany" + }, + { + "author_name": "Uwe Ohler", + "author_inst": "Berlin Institute for Medical Systems Biology, Max Delbruck Center for Molecular Medicine, Berlin, Germany" + }, + { + "author_name": "Lambert Moyon", + "author_inst": "Computational Health Center, Helmholtz Center Munich, Germany" + }, + { + "author_name": "Annalisa Marsico", + "author_inst": "Computational Health Center, Helmholtz Center Munich, Germany" + } + ], "version": "1", - "license": "cc_by_nd", - "type": "confirmatory results", - "category": "genetics" + "license": "cc_no", + "type": "new results", + "category": "bioinformatics" }, { "rel_doi": "10.1101/2021.12.22.473892", @@ -456957,53 +456396,53 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2021.12.20.473447", - "rel_title": "Blockade of TMPRSS2-mediated priming of SARS-CoV-2 by the N-terminal peptide of lactoferrin", + "rel_doi": "10.1101/2021.12.20.473421", + "rel_title": "Virus-like particles (VLPs) are efficient tools for boosting mRNA-induced antibodies", "rel_date": "2021-12-22", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.12.20.473447", - "rel_abs": "In addition to vaccines, there is an urgent need for supplemental antiviral therapeutics to dampen the persistent COVID-19 pandemic caused by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). The transmembrane protease serine 2 (TMPRSS2), which is responsible for the proteolytic processing of the SARS-CoV-2 spike protein as virus priming for cell entry, appears as a rational therapeutic target for the clearance of SARS-CoV-2 infection. Accordingly, selective inhibitors of TMPRSS2 represent potential tools for prevention and treatment of COVID-19. Here, we tested the inhibitory capacities of the human milk glycoprotein lactoferrin and its N-terminal peptide pLF1, which we identified as inhibitors of plasminogen, a serine protease homologous to TMPRSS2. In vitro proteolysis assays revealed that, unlike full-length lactoferrin, pLF1 significantly inhibited the proteolytic activity of TMPRSS2. pLF1 inhibited both the proteolytic processing of the SARS-CoV-2 spike protein and the SARS-CoV-2 infection of simian Vero cells. Because lactoferrin is a natural product and several biologically active peptides, such as the N-terminally derived lactoferricins, are produced naturally by pepsin-mediated digestion, natural or synthetic peptides from lactoferrin represent well-achievable candidates for supporting prevention and treatment of COVID-19.", + "rel_link": "https://biorxiv.org/cgi/content/short/2021.12.20.473421", + "rel_abs": "mRNA based vaccines against COVID-19 have proven most successful at keeping the SARS-CoV-2 pandemic at bay in many countries. Recently, there is an increased interest in heterologous prime-boost vaccination strategies for COVID-19 to maintain antibody response for the control of continuously emerging SARS-CoV-2 variants of concern (VoCs) and to overcome other obstacles such as supply shortage, costs and reduced safety issues or inadequate induced immune-response. In this study, we investigate the antibody responses induced by heterologous prime-boost with vaccines based on mRNA and virus-like particles (VLPs). The VLP-based mCuMVTT-RBM vaccine candidate and the approved mRNA-1273 vaccine were used for this purpose. We find that homologous prime boost regimens with either mRNA or VLP induced high levels of high avidity antibodies. Optimal antibody responses were, however, induced by heterologous regimens both for priming with mRNA and boosting with VLP and vice versa, priming with VLP and boosting with mRNA. Thus, heterologous prime boost strategies may be able to optimize efficacy and economics of novel vaccine strategies.", "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Anna Ohradanova-Repic", - "author_inst": "MUW" + "author_name": "Anne-Cathrine Sarah Vogt", + "author_inst": "Inselspital University Hospital Bern: Inselspital Universitatsspital Bern" }, { - "author_name": "Laura Gebetsberger", - "author_inst": "MUW" + "author_name": "Lukas J\u00f6rg", + "author_inst": "Inselspital University Hospital Bern: Inselspital Universitatsspital Bern" }, { - "author_name": "Gabor Tajti", - "author_inst": "MUW" + "author_name": "Byron Martina", + "author_inst": "Erasmus Medical Centre: Erasmus MC" }, { - "author_name": "Gabriela Ondrovicova", - "author_inst": "SAS" + "author_name": "Pascal S. Krenger", + "author_inst": "Inselspital University Hospital Bern: Inselspital Universitatsspital Bern" }, { - "author_name": "Romana Prazenicova", - "author_inst": "SAS" + "author_name": "Xinyue Chang", + "author_inst": "Inselspital University Hospital Bern: Inselspital Universitatsspital Bern" }, { - "author_name": "Rostislav Skrabana", - "author_inst": "SAS" + "author_name": "Andris Zeltins", + "author_inst": "Latvian Biomedical Research and Study Centre: Latvijas Biomedicinas petijumu un studiju centrs" }, { - "author_name": "Peter Barath", - "author_inst": "SAS" + "author_name": "Monique Vogel", + "author_inst": "Inselspital University Hospital Bern: Inselspital Universitatsspital Bern" }, { - "author_name": "Hannes Stockinger", - "author_inst": "MUW" + "author_name": "Mona O. Mohsen", + "author_inst": "Inselspital University Hospital Bern: Inselspital Universitatsspital Bern" }, { - "author_name": "Vladimir Leksa", - "author_inst": "SAS" + "author_name": "Martin F. Bachmann", + "author_inst": "Inselspital University Hospital Bern: Inselspital Universitatsspital Bern" } ], "version": "1", - "license": "cc_no", + "license": "cc_by", "type": "new results", "category": "immunology" }, @@ -459283,51 +458722,43 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.12.20.21267918", - "rel_title": "Keeping doors open: A cross-sectional survey of family physician practice patterns during COVID-19, needs, and intentions", + "rel_doi": "10.1101/2021.12.18.21268039", + "rel_title": "Comparative effectiveness of the BNT162b2 vs ChAdOx1 vaccine against Covid-19", "rel_date": "2021-12-21", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.20.21267918", - "rel_abs": "ObjectiveTo determine the extent to which family physicians closed their doors altogether or for in-person visits during the pandemic, their future practice intentions, and related factors.\n\nMethodsBetween March and June 2021, we conducted a cross-sectional survey using email, fax, and phone of 1,186 family doctors practicing comprehensive family medicine in Toronto, Ontario. We asked about practice patterns in January 2021, use of virtual care, and practice intentions.\n\nResultsOf the 1,016 (86%) that responded to the survey, 99.7% (1001/1004) indicated their practice was open in January 2021 with 94.8% (928/979) seeing patients in-person and 30.8% (264/856) providing in-person care to patients reporting COVID-19 symptoms. Respondents estimated spending 58.2% of clinical care time on phone visits and an additional 5.8% on video and 7.5% on email. 17.2% (77/447) were planning to close their current practice in the next five years. There was a higher proportion of physicians who worked alone in a clinic among those who did not see patients in-person (27.6% no vs 12.4% yes, p<0.05), did not see symptomatic patients (15.6% no vs 6.5 % yes, p<0.001), and those who planned to close their practice in the next 5 years (28.9% yes vs 13.9% no, p<0.01).\n\nInterpretationThe vast majority of family physicians in Toronto were open to in-person care in January 2021 but almost one-fifth are considering closing their practice in the next five years. Policy-makers need to prepare for a growing family physician shortage and better understand factors that support recruitment and retention.", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.18.21268039", + "rel_abs": "Although pivotal trials with varying populations and study methods suggest higher efficacy for mRNA than adenoviral Covid-19 vaccines, no direct evidence is available. Here, we conducted a head-to-head comparison of BNT162b2 versus ChAdOx1 against Covid-19. We analysed 235,181 UK Biobank participants aged 50 years or older and vaccinated with one or two doses of BNT162b2 or ChAdOx1. People were followed from the vaccination date until 18/10/2021. Inverse probability weighting was used to minimise confounding and the Cox models to derive hazard ratio. We found that, compared with two doses of ChAdOx1, vaccination with BNT162b2 was associated with 30% lower risks of both SARS-CoV-2 infection and related hospitalisation during the period dominated by the delta variant. Also, this comparative effectiveness was consistent across several subgroups and persisted for at least six months, suggesting no differential waning between the two vaccines. Our findings can inform evidence-based Covid-19 vaccination campaigns and booster strategies.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Tara Kiran", - "author_inst": "St. Michael's Hospital" - }, - { - "author_name": "Ri Wang", - "author_inst": "St. Michael's Hospital" - }, - { - "author_name": "Curtis Handford", - "author_inst": "St. Michael's Hospital" + "author_name": "Junqing Xie", + "author_inst": "Centre for Statistics in Medicine, NDORMS, University of Oxford, Oxford, UK" }, { - "author_name": "Nadine Laraya", - "author_inst": "University of Toronto" + "author_name": "shuo feng", + "author_inst": "Oxford Vaccine Group, Department of Paediatrics, University of Oxford, UK" }, { - "author_name": "Azza Eissa", - "author_inst": "University of Toronto" + "author_name": "Xintong Li", + "author_inst": "University of Oxford" }, { - "author_name": "Pauline Pariser", - "author_inst": "University of Toronto" + "author_name": "Ester Gea Mallorqui", + "author_inst": "Nuffield Department of Clinical Medicine, University of Oxford, Oxford, UK" }, { - "author_name": "Rebecca Brown", - "author_inst": "St. Michael's Hospital" + "author_name": "Albert Prats-Uribe", + "author_inst": "University of Oxford" }, { - "author_name": "Cheryl Pedersen", - "author_inst": "St. Michael's Hospital" + "author_name": "DANIEL PRIETO-ALHAMBRA", + "author_inst": "University of Oxford" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc0_ng", "type": "PUBLISHAHEADOFPRINT", - "category": "primary care research" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2021.12.17.21268009", @@ -461264,59 +460695,43 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2021.12.21.21268155", - "rel_title": "Variability in physical inactivity responses of university students during COVID-19 pandemic: A monitoring of daily step counts using a smartphone application", + "rel_doi": "10.1101/2021.12.20.21268081", + "rel_title": "Economic burden and catastrophic health expenditure associated with COVID-19 hospitalisations in Kerala, South India", "rel_date": "2021-12-21", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.21.21268155", - "rel_abs": "This study investigated the changes in physical inactivity of university students during the COVID-19 pandemic, with reference to their academic calendar. We used the daily step counts recorded by a smartphone application (iPhone Health App) from April 2020 to January 2021 (287 days) for 603 students. The data for 287 days were divided into five periods based on their academic calendar. The median value of daily step counts across each period was calculated. A k-means clustering analysis was performed to classify the 603 participants into subgroups to demonstrate the variability in the physical inactivity responses. The median daily step counts, with a 7-days moving average, dramatically decreased from 5,000 to 2,000 steps/day in early April. It remained at a lower level (less than 2,000 steps/day) during the first semester, then increased to more than 5,000 steps/day at the start of summer vacation. The clustering analysis demonstrated the variability in physical inactivity responses. Independent of the academic calendar, many inactive students did not recover their original daily step counts after its dramatic decrement. Consequently, promoting physical activity is recommended for inactive university students over the course of the whole semester.", - "rel_num_authors": 10, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.20.21268081", + "rel_abs": "IntroductionCatastrophic health expenditure during COVID-19 hospitalization has altered the economic picture of households especially in low resource settings with high rates of COVID-19 infection. This study aimed to estimate the Out of Pocket (OOP) expenditure and the proportion of households that incurred catastrophic health expenditures due to COVID-19 hospitalisation in Kerala, South India.\n\nMaterials and MethodsA cross-sectional study was conducted among a representative sample of 155 COVID-19 hospitalised patients in Kottayam district over four months, using a pretested interview schedule. The direct medical and non-medical costs incurred by the study participant during hospitalisation and the total monthly household expenditure were obtained from the respective COVID-19 affected households. Catastrophic health expenditure was defined as direct medical expenditure exceeding 40% of effective household income.\n\nResultsFrom the study, median and mean Out of Pocket (OOP) expenditures were obtained as USD 93.57 and USD 502.60 respectively. The study revealed that 49.7% of households had Catastrophic health expenditure, with 32.9% having incurred Distress financing. Multivariate analysis revealed being Below poverty line, hospitalisation in private healthcare facility and presence of co-morbid conditions as significant determinants of Catastrophic health expenditure.\n\nConclusionHigh levels of Catastrophic health expenditure and distress financing revealed by the study unveils major unaddressed challenges in the road to Universal health coverage.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Shoji Konda", - "author_inst": "Osaka University" - }, - { - "author_name": "Issei Ogasawara", - "author_inst": "Osaka University" - }, - { - "author_name": "Kazuki Fujita", - "author_inst": "Osaka University" - }, - { - "author_name": "Chisa Aoyama", - "author_inst": "Osaka University" + "author_name": "Ronnie Thomas", + "author_inst": "Government Medical College, Kottayam" }, { - "author_name": "Teruki Yokoyama", - "author_inst": "Osaka University" + "author_name": "Quincy Mariam Jacob", + "author_inst": "Government Medical College, Kottayam" }, { - "author_name": "Takuya Magome", - "author_inst": "Otemon Gakuin University, Osaka University" + "author_name": "Sharon Raj Eliza", + "author_inst": "Pushpagiri Institute of Medical Sciences and Research Centre" }, { - "author_name": "Chen Yulong", - "author_inst": "Osaka University" + "author_name": "Malathi Mini", + "author_inst": "Government Medical College, Kottayam" }, { - "author_name": "Ken Hashizume", - "author_inst": "Osaka University" + "author_name": "Jobinse Jose", + "author_inst": "Kasturba Medical College, Mangalore" }, { - "author_name": "Tomoyuki Matsuo", - "author_inst": "Osaka University" - }, - { - "author_name": "Ken Nakata", - "author_inst": "Osaka University" + "author_name": "Sobha A", + "author_inst": "Government Medical College, Kottayam" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "sports medicine" + "category": "health economics" }, { "rel_doi": "10.1101/2021.12.20.21267978", @@ -463390,43 +462805,67 @@ "category": "evolutionary biology" }, { - "rel_doi": "10.1101/2021.12.17.473260", - "rel_title": "A Computational Dissection of Spike protein of SARS-CoV-2 Omicron Variant", + "rel_doi": "10.1101/2021.12.17.473265", + "rel_title": "Evidence for a Potential Pre-Pandemic SARS-like Coronavirus Among Animals in North America", "rel_date": "2021-12-20", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.12.17.473260", - "rel_abs": "The emergence of SARS-CoV-2 omicron variant in late November, 2021 and its rapid spread to different countries, warns the health authorities to take initiative to work on containing its spread. The omicron SARS-CoV-2 variant is unusual from the other variants of concerns reported earlier as it harbors many novel mutations in its genome particularly with >30 mutations in the spike glycoprotein alone. The current study investigated the variation in binding mechanism which it carries compared to the wild type. The study also explored the interaction profile of spike-omicron with human ACE2 receptor. The structure of omicron spike glycoprotein was determined though homology modeling. The interaction analysis was performed through docking using HADDOCK followed by binding affinity calculation. Finally, the comparison of interactions were performed among spike-ACE2 complex of wild type, delta and omicron variants. The interaction analysis has revealed the involvement of highly charged and polar residues (H505, Arg498, Ser446, Arg493, and Tyr501) in the interactions. The important novel interactions in the spike-ACE2-omicron complex was observed as S494:H34, S496:D38, R498:Y41, Y501:K353, and H505:R393 and R493:D38. Moreover, the binding affinity of spike-ACE2-omicron complex (-17.6Kcal/mol) is much higher than wild type-ACE2 (-13.2Kcal/mol) and delta-ACE2 complex (-13.3Kcal/mol). These results indicate that the involvement of polar and charged residues in the interactions with ACE2 may have an impact on increased transmissibility of omicron variant.", - "rel_num_authors": 6, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.12.17.473265", + "rel_abs": "In late 2019, a novel coronavirus began circulating within humans in central China. It was designated SARS-CoV-2 because of its genetic similarities to the 2003 SARS coronavirus (SARS-CoV). Now that SARS-CoV-2 has spread worldwide, there is a risk of it establishing new animal reservoirs and recombination with native circulating coronaviruses. To screen local animal populations in the United States for exposure to SARS-like coronaviruses, we developed a serological assay using the receptor binding domain (RBD) from SARS-CoV-2. SARS-CoV-2s RBD is antigenically distinct from common human and animal coronaviruses allowing us to identify animals previously infected with SARS-CoV or SARS-CoV-2. Using an indirect ELISA for SARS-CoV-2s RBD, we screened serum from wild and domestic animals for the presence of antibodies against SARS-CoV-2s RBD. Surprisingly pre-pandemic feline serum samples submitted to the University of Tennessee Veterinary Hospital were [~]50% positive for anti-SARS RBD antibodies. Some of these samples were serologically negative for feline coronavirus (FCoV), raising the question of the etiological agent generating anti-SARS-CoV-2 RBD cross-reactivity. We also identified several white-tailed deer from South Carolina with anti-SARS-CoV-2 antibodies. These results are intriguing as cross-reactive antibodies towards SARS-CoV-2 RBD have not been reported to date. The etiological agent responsible for seropositivity was not readily apparent, but finding seropositive cats prior to the current SARS-CoV-2 pandemic highlights our lack of information about circulating coronaviruses in other species.\n\nImportanceWe report cross-reactive antibodies from pre-pandemic cats and post-pandemic South Carolina white-tailed deer that are specific for that SARS-CoV RBD. There are several potential explanations for this cross-reactivity, each with important implications to coronavirus disease surveillance. Perhaps the most intriguing possibility is the existence and transmission of an etiological agent (such as another coronavirus) with similarity to SARS-CoV-2s RBD region. However, we lack conclusive evidence of pre-pandemic transmission of a SARS-like virus. Our findings provide impetus for the adoption of a One Health Initiative focusing on infectious disease surveillance of multiple animal species to predict the next zoonotic transmission to humans and future pandemics.", + "rel_num_authors": 12, "rel_authors": [ { - "author_name": "Zaira Rehman", - "author_inst": "National Institute of Health (Pakistan)" + "author_name": "Trevor J Hancock", + "author_inst": "University of Tennessee at Knoxville" }, { - "author_name": "Massab Umair", - "author_inst": "National Institute of Health" + "author_name": "Peyton Hickman", + "author_inst": "University of Tennessee at Knoxville" }, { - "author_name": "Aamer Ikram", - "author_inst": "National Institute of Health" + "author_name": "Niloo Kazerooni", + "author_inst": "University of Tennessee" }, { - "author_name": "Muhammad Salman", - "author_inst": "National Institute of Health" + "author_name": "Melissa Kennedy", + "author_inst": "University of Tennessee at Knoxville" }, { - "author_name": "Syed Adnan Haider", - "author_inst": "National Institute of Health" + "author_name": "Stephen Anthony Kania", + "author_inst": "University of Tennessee at Knoxville" }, { - "author_name": "Muhmmad Ammar", - "author_inst": "National Institute of Health" + "author_name": "Michelle Dennis", + "author_inst": "University of Tennessee at Knoxville" + }, + { + "author_name": "Nicole Szafranski", + "author_inst": "University of Tennessee Institute of Agriculture" + }, + { + "author_name": "Richard W Gerhold", + "author_inst": "University of Tennessee Institute of Agriculture" + }, + { + "author_name": "Chunlei Su", + "author_inst": "University of Tennessee at Knoxville" + }, + { + "author_name": "Thomas J Masi", + "author_inst": "University of Tennessee" + }, + { + "author_name": "Stephen Smith", + "author_inst": "MEDIC Regional Blood Center" + }, + { + "author_name": "Tim E Sparer", + "author_inst": "University of Tennessee at Knoxville" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by_nc_nd", "type": "new results", - "category": "bioinformatics" + "category": "immunology" }, { "rel_doi": "10.1101/2021.12.17.473223", @@ -464900,27 +464339,27 @@ "category": "pediatrics" }, { - "rel_doi": "10.1101/2021.12.16.21267914", - "rel_title": "The impact of shielding during the COVID-19 pandemic on mental health: Evidence from the English Longitudinal Study of Ageing", + "rel_doi": "10.1101/2021.12.17.21267941", + "rel_title": "Predictors of uncertainty and unwillingness to receive the COVID-19 booster vaccine in a sample of 22,139 fully vaccinated adults in the UK", "rel_date": "2021-12-17", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.16.21267914", - "rel_abs": "BackgroundDuring the COVID-19 pandemic, older and clinically vulnerable people were instructed to shield or stay at home to save lives. Policies restricting social contact and human interaction pose a risk to mental health, but we know very little about the impact of shielding and stay at home orders on the mental health of older people.\n\nAimsUnderstand the extent to which shielding contributes to poorer mental health.\n\nMethodExploiting longitudinal data from Wave 9 (2018/19) and two COVID-19 sub-studies (June/July 2020; November/December 2020) of the English Longitudinal Study of Ageing we use logistic and linear regression models to investigate associations between patterns of shielding during the pandemic and mental health, controlling for socio-demographic characteristics, pre-pandemic physical and mental health, and social isolation measures.\n\nResultsBy December 2020, 70% of older people were still shielding or staying at home, with 5% shielding throughout the first 9 months of the pandemic. Respondents who shielded experienced worse mental health. Although prior characteristics and lack of social interactions explain some of this association, even controlling for all covariates, those shielding throughout had higher odds of reporting elevated depressive symptoms (OR=1.87, 95%CI=1.22;2.87) and reported lower quality of life (B=-1.28, 95%CI=-2.04;-0.52) than those who neither shielded nor stayed at home. Shielding was also associated with increased anxiety.\n\nConclusionsShielding itself seems associated with worse mental health among older people, highlighting the need for policymakers to address the mental health needs of those who shielded, both in emerging from the current pandemic and for the future.", + "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.17.21267941", + "rel_abs": "BackgroundThe continued success of the COVID-19 vaccination programme in the UK will depend on widespread uptake of booster vaccines. However, there is evidence of hesitancy and unwillingness to receive the booster vaccine, even in fully vaccinated adults. Identifying factors associated with COVID-19 booster vaccine intentions specifically in this population is therefore critical.\n\nMethodsWe used data from 22,139 fully vaccinated adults who took part in the UCL COVID-19 Social Study. Multinomial logistic regression examined predictors of uncertainty and unwillingness (versus willingness) to receive a COVID-19 booster vaccine (measured 22 November 2021 to 6 December 2021), including (i) socio-demographic factors, (ii) COVID-19 related factors (e.g., having been infected with COVID-19), and (iii) initial intent to receive a COVID-19 vaccine in the four months following the announcement in the UK that the vaccines had been approved (2 December 2020 to 31 March 2021).\n\nFindings4% of the sample reported that they were uncertain about receiving a COVID-19 booster vaccine, and a further 4% unwilling. Initial uncertainty and unwillingness to accept the first COVID-19 vaccine in 2020-21 were each associated with over five times the risk of being uncertain about and unwilling to accept a booster vaccine. Healthy adults (those without a pre-existing physical health condition) were also more likely to be uncertain or unwilling to receive a booster vaccine. In addition, low levels of current stress about catching or becoming seriously ill from COVID-19, consistently low compliance with COVID-19 government guidelines during periods of strict restrictions (e.g., lockdowns), lower levels of educational qualification, lower socio-economic position, and age below 45 years were all associated with uncertainty and unwillingness.\n\nInterpretationOur findings highlight that there are a range of factors that predict booster intentions, with the strongest predictor being previous uncertainty and unwillingness. Two other concerning patterns also emerged from our results. First, administration of booster vaccinations may increase social inequalities in experiences of COVID-19 as adults from lower socio-economic backgrounds are also most likely to be uncertain or unwilling to accept a booster vaccine as well as most likely to be seriously affected by the virus. Second, some of those most likely to spread COVID-19 (i.e., those with poor compliance with guidelines) are most likely to be uncertain and unwilling. Public health messaging should be tailored specifically to these groups.\n\nFundingThe Nuffield Foundation [WEL/FR-000022583], the MARCH Mental Health Network funded by the Cross-Disciplinary Mental Health Network Plus initiative supported by UK Research and Innovation [ES/S002588/1], and the Wellcome Trust [221400/Z/20/Z and 205407/Z/16/Z].", "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Giorgio Di Gessa", + "author_name": "Elise Paul", "author_inst": "University College London" }, { - "author_name": "Debora Price", - "author_inst": "University of Manchester" + "author_name": "Daisy Fancourt", + "author_inst": "University College London" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "psychiatry and clinical psychology" + "category": "public and global health" }, { "rel_doi": "10.1101/2021.12.16.21267811", @@ -467114,39 +466553,59 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2021.12.15.21267849", - "rel_title": "Neurodevelopmental outcomes at one year in offspring of mothers who test positive for SARS-CoV-2 during pregnancy", + "rel_doi": "10.1101/2021.12.14.21267778", + "rel_title": "Efficient control of IL-6, CRP and Ferritin in Covid-19 patients with two variants of Beta-1,3-1,6 glucans in combination, within 15 days in an open-label prospective clinical trial", "rel_date": "2021-12-16", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.15.21267849", - "rel_abs": "ImportanceEpidemiologic studies suggest maternal immune activation during pregnancy may be associated with neurodevelopmental effects in offspring.\n\nObjectiveTo determine whether in utero exposure to the novel coronavirus SARS-CoV-2 is associated with risk for neurodevelopmental disorders in the first 12 months after birth.\n\nDesignRetrospective cohort\n\nParticipantsLive offspring of all mothers who delivered between March and September 2020 at one of six Massachusetts hospitals across two health systems.\n\nExposureSARS-CoV-2 infection confirmed by PCR during pregnancy\n\nMain Outcome and MeasuresNeurodevelopmental disorders determined from ICD-10 diagnostic codes over 12 months; sociodemographic and clinical features of mothers and offspring; all drawn from the electronic health record.\n\nResultsThe cohort included 7,772 live births (7,466 pregnancies, 96% singleton, 222 births to SARS-CoV-2 positive mothers), with mean maternal age of 32.9 years; offspring were 9.9% Asian, 8.4% Black, and 69.0% white; 15.1% were of Hispanic ethnicity. Preterm delivery was more likely among exposed mothers (14% versus 8.7%; p=.003). Maternal SARS-CoV-2 positivity during pregnancy was associated with greater rate of neurodevelopmental diagnoses (crude OR 2.17 [95% CI 1.24-3.79, p=0.006]) as well as models adjusted for race, ethnicity, insurance status, offspring sex, maternal age, and preterm status (adjusted OR 1.86 [95% CI 1.03-3.36, p=0.04]). Third-trimester infection was associated with effects of larger magnitude (adjusted OR 2.34, 95% CI 1.23-4.44, p=0.01)\n\nConclusion and RelevanceOur results provide preliminary evidence that maternal SARS-CoV-2 may be associated with neurodevelopmental sequelae in some offspring. Prospective studies with longer follow-up duration will be required to exclude confounding and confirm these effects.\n\nTrial RegistrationNA\n\nKey PointsO_ST_ABSQuestionC_ST_ABSDoes COVID-19 exposure in utero increase the risk for neurodevelopmental disorders in the first year of life?\n\nFindingsIn a cohort of babies delivered during COVID-19, those born to mothers with a positive SARS-CoV-2 PCR test during pregnancy were more likely to receive a neurodevelopmental diagnosis in the first 12 months after delivery, even after accounting for preterm delivery.\n\nMeaningThese preliminary findings suggest that COVID-19 exposure may impact neurodevelopment, and highlight the need for prospective investigation of outcomes in children exposed to COVID-19 in utero.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.14.21267778", + "rel_abs": "ObjectiveIn this study, we evaluated the efficiency of the combination of two variants AFO-202 and N-163 strains of Aureobasidium Pullulans produced in comparison with the control arm, which underwent a conventional regimen of treatment alone, for a shorter duration of 15 days.\n\nMethodsA total of 40 RT-PCR positive Covid-19 patients divided into two groups (Gr): Gr. 1 control (n=22) - Standard treatment; Gr. 2 (n =18) - Standard treatment + combination of AFO-202 and N-163 beta glucans for 15 days. Biomarkers of relevance to cytokine storm and coagulopathy were evaluated at baseline on Day 7 and Day 15.\n\nResultsThe C-reactive protein (CRP), which declined from 33.95 mg/l to 5.07 mg/l in control and from 33.95 mg/l to 5.64 mg/l in the treatment arm on Day 7, increased to 14.6 mg/l in the former while it continued to be under control in the treatment arm at 5.68 mg/l on Day 15. The same trend was observed in Ferritin, whose values were 560.58 ng/ml at baseline to 261.44 ng/ml (day-7) and 182.40 ng/ml (day-15) in the treatment group, while it was 535.24 ng/ml at baseline, 116.66 ng/ml on day 7 and 291.95 ng/ml on day 15 in the control group. IL-6 showed a higher decrease in treatment group compared to the control group. The difference between day 7 and day 15 values were statically significant.\n\nConclusionA statistically significant control of IL-6, CRP and Ferritin in Covid-19 patients who orally consumed AFO-202 and N-163 strains of Aureobasidium Pullulans produced Beta glucans together in 15 days make us recommend this safe food supplement be consumed by Covid-19 patients along with conventional treatments, especially to the vulnerable population, as a prophylaxis amidst the prolonged pandemic with evolution of mutated strains of SARS-COV2.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Andrea G. Edlow", - "author_inst": "Massachusetts General Hospital" + "author_name": "Subramanian Pushkala", + "author_inst": "The Tamil Nadu Dr. M.G.R. Medical University" }, { - "author_name": "Victor M Castro", - "author_inst": "Mass General Brigham" + "author_name": "Sudha Seshayyan", + "author_inst": "The Tamil Nadu Dr. M.G.R. Medical University" }, { - "author_name": "Lydia Shook", - "author_inst": "Massachusetts General Hospital" + "author_name": "Ethirajan Theranirajan", + "author_inst": "Rajiv Gandhi Government General Hospital, Madras Medical College" }, { - "author_name": "Anjali J Kaimal", - "author_inst": "Massachusetts General Hospital" + "author_name": "Doraisamy Sudhakar", + "author_inst": "Rajiv Gandhi Government General Hospital, Madras Medical College" }, { - "author_name": "Roy H Perlis", - "author_inst": "Massachusetts General Hospital" + "author_name": "Kadalraja Raghavan", + "author_inst": "Jesuit Antonyraj memorial Inter-disciplinary Centre for Advanced Rehabilitation and Education (JAICARE)" + }, + { + "author_name": "Vidyasagar Devaprasad Dedeepiya", + "author_inst": "Nichi-In Centre for Regenerative Medicine (NCRM" + }, + { + "author_name": "Nobunao Ikewaki", + "author_inst": "Kyushu University of Health and Welfare" + }, + { + "author_name": "Masaru Iwasaki", + "author_inst": "University of Yamanashi - School of Medicine" + }, + { + "author_name": "Senthilkumar Preethy", + "author_inst": "Nichi-In Centre for Regenerative Medicine (NCRM)" + }, + { + "author_name": "Samuel JK Abraham", + "author_inst": "Yamanashi University-Faculty of Medicine" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "neurology" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2021.12.16.21267862", @@ -469227,63 +468686,147 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2021.12.14.472547", - "rel_title": "From Deer-to-Deer: SARS-CoV-2 is efficiently transmitted and presents broad tissue tropism and replication sites in white-tailed deer", + "rel_doi": "10.1101/2021.12.14.472630", + "rel_title": "Considerable escape of SARS-CoV-2 variant Omicron to antibody neutralization", "rel_date": "2021-12-15", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.12.14.472547", - "rel_abs": "Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of coronavirus disease 2019 (COVID-19) in humans, has a broad host range, and is able to infect domestic and wild animal species. Notably, white-tailed deer (WTD, Odocoileus virginianus), the most widely distributed cervid species in the Americas, were shown to be highly susceptible to SARS-CoV-2 in challenge studies and reported natural infection rates approaching 40% in free-ranging WTD in the U.S. Thus, understanding the infection and transmission dynamics of SARS-CoV-2 in WTD is critical to prevent future zoonotic transmission to humans and for implementation of effective disease control measures. Here, we demonstrated that following intranasal inoculation with SARS-CoV-2, WTD fawns shed infectious virus up to day 5 post-inoculation (pi), with high viral loads shed in nasal and oral secretions. This resulted in efficient deer-to-deer transmission on day 3 pi. Consistent a with lack of infectious SARS-CoV-2 shedding after day 5 pi, no transmission was observed to contact animals added on days 6 and 9 pi. We have also investigated the tropism and sites of SARS-CoV-2 replication in adult WTD. Infectious virus was recovered from respiratory-, lymphoid-, and central nervous system tissues, indicating broad tissue tropism and multiple sites of virus replication. The study provides important insights on the infection and transmission dynamics of SARS-CoV-2 in WTD, a wild animal species that is highly susceptible to infection and with the potential to become a reservoir for the virus in the field.\n\nAuthor summaryThe high susceptibility of white-tailed deer (WTD) to SARS-CoV-2, their ability to transmit the virus to other deer, and the recent findings suggesting widespread SARS-CoV-2 infection in wild WTD populations in the U.S. underscore the need for a better understanding of the infection and transmission dynamics of SARS-CoV-2 in this potential reservoir species. Here we investigated the transmission dynamics of SARS-CoV-2 over time and defined the major sites of virus replication during the acute phase of infection. Additionally, we assessed the evolution of the virus as it replicated and transmitted between animals. The work provides important information on the infection dynamics of SARS-CoV-2 in WTD, an animal species that - if confirmed as a new reservoir of infection - may provide many opportunities for exposure and potential zoonotic transmission of the virus back to humans.", - "rel_num_authors": 11, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.12.14.472630", + "rel_abs": "The SARS-CoV-2 Omicron variant was first identified in November 2021 in Botswana and South Africa1,2. It has in the meantime spread to many countries and is expected to rapidly become dominant worldwide. The lineage is characterized by the presence of about 32 mutations in the Spike, located mostly in the N-terminal domain (NTD) and the receptor binding domain (RBD), which may enhance viral fitness and allow antibody evasion. Here, we isolated an infectious Omicron virus in Belgium, from a traveller returning from Egypt. We examined its sensitivity to 9 monoclonal antibodies (mAbs) clinically approved or in development3, and to antibodies present in 90 sera from COVID-19 vaccine recipients or convalescent individuals. Omicron was totally or partially resistant to neutralization by all mAbs tested. Sera from Pfizer or AstraZeneca vaccine recipients, sampled 5 months after complete vaccination, barely inhibited Omicron. Sera from COVID-19 convalescent patients collected 6 or 12 months post symptoms displayed low or no neutralizing activity against Omicron. Administration of a booster Pfizer dose as well as vaccination of previously infected individuals generated an anti-Omicron neutralizing response, with titers 5 to 31 fold lower against Omicron than against Delta. Thus, Omicron escapes most therapeutic monoclonal antibodies and to a large extent vaccine-elicited antibodies.", + "rel_num_authors": 32, "rel_authors": [ { - "author_name": "Mathias Martins", - "author_inst": "Cornell University College of Veterinary Medicine" + "author_name": "Delphine Planas", + "author_inst": "Institut Pasteur" }, { - "author_name": "Paola M. Boggiatto", - "author_inst": "USDA Agricultural Research Service" + "author_name": "Nell Saunders", + "author_inst": "Institut Pasteur" }, { - "author_name": "Alexandra Buckley", - "author_inst": "USDA Agricultural Research Service" + "author_name": "Piet Maes", + "author_inst": "KU Leuven" }, { - "author_name": "Eric D. Cassmann", - "author_inst": "USDA Agricultural Research Service" + "author_name": "Florence Guivel Benhassine", + "author_inst": "Institut Pasteur" }, { - "author_name": "Shollie Falkenberg", - "author_inst": "USDA Agricultural Research Service" + "author_name": "Cyril Planchais", + "author_inst": "Institut Pasteur" }, { - "author_name": "Leonardo C. Caserta", - "author_inst": "Cornell University College of Veterinary Medicine" + "author_name": "Francoise Porrot", + "author_inst": "Institut Pasteur" }, { - "author_name": "Maureen H.V. Fernandes", - "author_inst": "Cornell University College of Veterinary Medicine" + "author_name": "Isabelle Staropoli", + "author_inst": "Institut Pasteur" }, { - "author_name": "Carly Kanipe", - "author_inst": "USDA Agricultural Research Service" + "author_name": "Frederic Lemoine", + "author_inst": "Institut Pasteur" }, { - "author_name": "Kelly Lager", - "author_inst": "USDA Agricultural Research Service" + "author_name": "Helene Pere", + "author_inst": "APHP" }, { - "author_name": "Mitchell V. Palmer", - "author_inst": "USDA Agricultural Research Service" + "author_name": "David Veyer", + "author_inst": "APHP" }, { - "author_name": "Diego G. Diel", - "author_inst": "Cornell University College of Veterinary Medicine" + "author_name": "Julien Puech", + "author_inst": "APHP" + }, + { + "author_name": "Julien Rodary", + "author_inst": "APHP" + }, + { + "author_name": "William Henry Bolland", + "author_inst": "Institut Pasteur" + }, + { + "author_name": "Julian Buchrieser", + "author_inst": "Institut Pasteur" + }, + { + "author_name": "Guy Baele", + "author_inst": "KU Leuven" + }, + { + "author_name": "Simon Dellicour", + "author_inst": "KU Leuven" + }, + { + "author_name": "Joren Raymenants", + "author_inst": "KU Leuven" + }, + { + "author_name": "Sarah Gorissen", + "author_inst": "KU Leuven" + }, + { + "author_name": "Caspar Geenen", + "author_inst": "KU Leuven" + }, + { + "author_name": "Bert Vanmechelen", + "author_inst": "KU Leuven" + }, + { + "author_name": "Tony Wawina", + "author_inst": "KU Leuven" + }, + { + "author_name": "Joan Marti", + "author_inst": "KU Leuven" + }, + { + "author_name": "Lize Cuypers", + "author_inst": "UZ Leuven" + }, + { + "author_name": "Aymeric Seve", + "author_inst": "CHR Orleans" + }, + { + "author_name": "Laurent Hocqueloux", + "author_inst": "CHR Orleans" + }, + { + "author_name": "Thierry Prazuck", + "author_inst": "CHR Orleans" + }, + { + "author_name": "Etienne Simon Loriere", + "author_inst": "Institut Pasteur" + }, + { + "author_name": "Felix REY", + "author_inst": "Institut Pasteur" + }, + { + "author_name": "Timothee Bruel", + "author_inst": "Institut Pasteur" + }, + { + "author_name": "Hugo Mouquet", + "author_inst": "Institut Pasteur" + }, + { + "author_name": "Emmanuel Andre", + "author_inst": "UZ Leuven" + }, + { + "author_name": "Olivier Schwartz", + "author_inst": "Institut Pasteur" } ], "version": "1", - "license": "cc0", + "license": "cc_by_nc_nd", "type": "new results", - "category": "microbiology" + "category": "immunology" }, { "rel_doi": "10.1101/2021.12.14.472622", @@ -471509,53 +471052,69 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.12.13.21267509", - "rel_title": "Microarray-based detection of antibodies against SARS-CoV-2 proteins, common respiratory viruses and type I interferons", + "rel_doi": "10.1101/2021.12.09.21267566", + "rel_title": "Oral antiviral clevudine compared with placebo in Korean COVID-19 patients with moderate severity", "rel_date": "2021-12-14", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.13.21267509", - "rel_abs": "A microarray-based assay to detect IgG and IgM antibodies against betacoronaviruses (SARS-CoV-2, SARS, MERS, OC43, and HKU1), other respiratory viruses and type I interferons (IFN-Is) was developed. This multiplex assay was applied to track antibody cross-reactivity due to previous contact with similar viruses and to identify antibodies against IFN-Is as the markers for severe COVID-19. In total, 278 serum samples from convalescent plasma donors, COVID-19 patients in the intensive care unit (ICU) and patients who recovered from mild/moderate COVID-19, vaccine recipients, prepandemic and pandemic patients with autoimmune endocrine disorders, and a heterogeneous prepandemic cohort including healthy individuals and chronically ill patients were analyzed. The anti-SARS-CoV-2 microarray results agreed well with the ELISA results. Regarding ICU patients, autoantibodies against IFN-Is were detected in 10.5% of samples, and 10.5% of samples were found to simultaneously contain IgM antibodies against more than two different viruses. Cross-reactivity between IgG against the SARS-CoV-2 nucleocapsid and IgG against the OC43 and HKU1 spike proteins was observed, resulting in positive signals for the SARS-CoV-2 nucleocapsid in prepandemic samples from patients with autoimmune endocrine disorders. The presence of IgG against the SARS-CoV-2 nucleocapsid in the absence of IgG against the SARS-CoV-2 spike RBD should be interpreted with caution.", - "rel_num_authors": 9, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.09.21267566", + "rel_abs": "BackgroundClevudine, an antiviral drug for chronic hepatitis B virus infection, is expected to inhibit the replication of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus. Therefore, we conducted a prospective, single-blind, proof of concept clinical study to examine the antiviral efficacy and safety of clevudine compared to placebo in Korean corona virus disease 19 (COVID-19) patients with moderate severity.\n\nMethodsAdults with confirmed SARS-CoV-2 infection and symptom onset within 7 days were randomized 2:1 to 120 mg clevudine or placebo to receive one of treatments orally once-daily for 14 days. Antiviral efficacy outcomes were the proportion of patients with real-time reverse transcription polymerase chain reaction (RT-PCR) negative result for SARS-CoV-2 infection and cycle threshold (Ct) value changes from baseline. Clinical efficacy outcomes included proportion of patients who showed improvement in lung involvement by imaging tests, proportion of patients with normal body temperature, proportion of patients with normal oxygen saturation, and the changes in C-reactive protein (CRP) from baseline. Safety outcomes included changes in clinical laboratory tests, vital signs measurement, and physical examination from baseline, and incidence of adverse events.\n\nResultsThe proportion of patients with real-time RT-PCR negative test and Ct value changes showed no significant difference between clevudine group and placebo group. The changes in Ct value from baseline were significantly greater in clevudine group compared to placebo group in patients with hypertension, and patients who underwent randomization during the first 5 and 7 days after the onset of symptoms. All clinical efficacy outcomes had no significant difference between clevudine group and placebo group. Clevudine was well tolerated and there was no significant difference in safety profile between two treatment groups.\n\nConclusionsThis is the first clinical study to compare the antiviral efficacy and safety of clevudine to placebo in Korean COVID-19 patients with moderate severity. The study has demonstrated a possible favorable outcome for the reduction of SARS-CoV-2 replication, with acceptable safety profile, when COVID-19 patients were treated with clevudine. Further large-scale clinical studies, preferably with various clinical endpoints and virus titer evaluation, are required to better understand the effectiveness of using clevudine in COVID-19 treatment. Considering recent trend in clinical development for antiviral drugs, we need to design a clinical study aiming for reducing clinical risk of COVID-19 in mild to moderate patients with at least one risk factor for serious illness.", + "rel_num_authors": 13, "rel_authors": [ { - "author_name": "Elena Savvateeva", - "author_inst": "Center for Precision Genome Editing and Genetic Technologies for Biomedicine, Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, Moscow, Ru" + "author_name": "Joon-Young Song", + "author_inst": "Division of Infectious Diseases, Department of Internal Medicine, Korea University College of Medicine" }, { - "author_name": "Marina Filippova", - "author_inst": "Center for Precision Genome Editing and Genetic Technologies for Biomedicine, Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, Moscow, Ru" + "author_name": "Yeon-Sook Kim", + "author_inst": "Division of Infectious Diseases, Department of Internal Medicine, Chungnam National University School of Medicine" }, { - "author_name": "Vladimir Valuev-Elliston", - "author_inst": "Center for Precision Genome Editing and Genetic Technologies for Biomedicine, Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, Moscow, Ru" + "author_name": "Joong-Sik Eom", + "author_inst": "Division of Infectious Diseases, Department of Internal Medicine, Gil Medical Center, Gachon University School of Medicine" + }, + { + "author_name": "Jin-Yong Kim", + "author_inst": "Division of Infectious Diseases, Department of Internal Medicine, Incheon Medical Center" }, { - "author_name": "Nurana Nuralieva", - "author_inst": "Endocrinology Research Centre, Ministry of Health of Russia, Moscow, Russia" + "author_name": "Jin-Soo Lee", + "author_inst": "Division of Infectious Diseases, Department of Internal Medicine, Inha University School of Medicine" }, { - "author_name": "Marina Yukina", - "author_inst": "Endocrinology Research Centre, Ministry of Health of Russia, Moscow, Russia" + "author_name": "Jacob Lee", + "author_inst": "Division of Infectious Disease, Department of Internal Medicine, Kangnam Sacred Heart Hospital, Hallym University College of Medicine" }, { - "author_name": "Ekaterina Troshina", - "author_inst": "Endocrinology Research Centre, Ministry of Health of Russia, Moscow, Russia" + "author_name": "Won-Suk Choi", + "author_inst": "Division of Infectious Diseases, Department of Internal Medicine, Korea University College of Medicine, Ansan Hospital" }, { - "author_name": "Vladimir Baklaushev", - "author_inst": "Federal Scientific and Clinical Center of Specialized Types of Medical Care and Medical Technologies of the Federal Medical and Biological Agency of Russia, Mos" + "author_name": "Jung-Yeon Heo", + "author_inst": "Department of Infectious Diseases, Ajou University School of Medicine" }, { - "author_name": "Alexander Ivanov", - "author_inst": "Center for Precision Genome Editing and Genetic Technologies for Biomedicine, Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, Moscow, Ru" + "author_name": "Jang-Wook Sohn", + "author_inst": "Division of Infectious Diseases, Department of Internal Medicine, Korea University College of Medicine" }, { - "author_name": "Dmitry Gryadunov", - "author_inst": "Center for Precision Genome Editing and Genetic Technologies for Biomedicine, Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, Moscow, Ru" + "author_name": "Ki-Deok Lee", + "author_inst": "Department of Infectious Diseases, Myongji Hospital, Hanyang university medical center" + }, + { + "author_name": "Donghui Cho", + "author_inst": "Department of Surgery, Seoul Medical Center" + }, + { + "author_name": "IlYoung Cho", + "author_inst": "Regulatory Affairs, Bukwang Pharm. Co. Ltd." + }, + { + "author_name": "Woo-Joo Kim", + "author_inst": "Division of Infectious Diseases, Department of Internal Medicine, Korea University College of Medicine" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -473379,55 +472938,67 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.12.13.21267718", - "rel_title": "Mental Health During COVID-19: A Qualitative Study with Ethnically Diverse Healthcare Workers in the United Kingdom", + "rel_doi": "10.1101/2021.12.13.21267717", + "rel_title": "Comparative efficacy of tocilizumab and baricitinib in COVID-19 treatment: a retrospective cohort study", "rel_date": "2021-12-14", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.13.21267718", - "rel_abs": "IntroductionHealthcare workers are experiencing deterioration in their mental health due to COVID-19. Ethnic minority populations in the United Kingdom are disproportionately affected by COVID-19, with a higher death rate and poorer physical and mental health outcomes. It is important that healthcare organisations consider the specific context and mental, as well as physical, health needs of an ethnically diverse healthcare workforce in order to better support them during, and after, the COVID-19 pandemic.\n\nMethodsWe undertook a qualitative work package as part of the United Kingdom Research study into Ethnicity and COVID-19 outcomes among healthcare workers (UK-REACH). As part of the qualitative research, we conducted focus group discussions with healthcare workers between December 2020 and July 2021, and covered topics such as their experiences, fears and concerns, and perceptions about safety and protection, while working during the pandemic. The purposive sample included ancillary health workers, doctors, nurses, midwives and allied health professionals from diverse ethnic backgrounds. We conducted discussions using Microsoft Teams. Recordings were transcribed and thematically analysed.\n\nFindingsWe carried out 16 focus groups with a total of 61 participants. Several factors were identified which contributed to, and potentially exacerbated, the poor mental health of ethnic minority healthcare workers during this period including anxiety (due to inconsistent protocols and policy); fear (of infection); trauma (due to increased exposure to severe illness and death); guilt (of potentially infecting loved ones); and stress (due to longer working hours and increased workload).\n\nConclusionCOVID-19 has affected the mental health of healthcare workers. We identified a number of factors which may be contributing to a deterioration in mental health across diverse ethnic groups. Healthcare organisations should consider developing strategies to counter the negative impact of these factors. This paper will help employers of healthcare workers and other relevant policy makers better understand the wider implications and potential risks of COVID-19 and assist in developing strategies to safeguard the mental health of these healthcare workers going forward, and reduce ethnic disparities.\n\nKey messagesO_ST_ABSWhat is already known about this subjectC_ST_ABSO_LIHealthcare Workers (HCWs) are experiencing deterioration of their mental health due to COVID-19\nC_LIO_LIEthnic minority populations and HCWs are disproportionately affected by COVID-19\nC_LIO_LIMore research is needed on the specific factors influencing the mental health of ethnically diverse healthcare workforces\nC_LI\n\nWhat are the new findingsProminent factors influencing the mental health and emotional wellbeing of this population include:\n\nO_LIanxiety (due to inconsistent protocols and policy)\nC_LIO_LIfear (of infection)\nC_LIO_LItrauma (due to increased exposure to severe illness and death)\nC_LIO_LIguilt (of potentially infecting loved ones)\nC_LIO_LIstress (due to longer working hours and increased workload)\nC_LI\n\nHow might this impact on policy or clinical practice in the foreseeable futureO_LIHealthcare organisations should consider the specific circumstances of these staff and develop strategies to counter the negative impact of these factors and help safeguard the mental health of their staff\nC_LI", - "rel_num_authors": 9, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.13.21267717", + "rel_abs": "BackgroundAlthough biological agents, tocilizumab and baricitinib, have been shown to improve the outcomes of patients with COVID-19, a comparative evaluation has not been performed.\n\nMethodsA retrospective, single-center study was conducted using the data of patients with COVID-19 admitted to the Hokkaido University hospital between April 2020 and September 2021, who were treated with tocilizumab or baricitinib. The clinical characteristics of patients who received each drug were compared. Univariate and multivariate logistic regression models were performed against the outcomes of all-cause mortality and the improvement in respiratory status. The development of secondary infection events was analyzed using the Kaplan-Meier analysis and the log-rank test.\n\nResultsThe use of tocilizumab or baricitinib was not associated with all-cause mortality and the improvement in respiratory status within 28 days of drug administration. Age, chronic renal disease, and comorbid respiratory disease were independent prognostic factors for all-cause mortality, while anti-viral drug use and severity of COVID-19 at baseline were associated with the improvement in respiratory status. There was no significant difference in the infection-free survival between patients treated with tocilizumab and those with baricitinib.\n\nConclusionThere were no differences in efficacy and safety between tocilizumab and baricitinib for the treatment of COVID-19.", + "rel_num_authors": 12, "rel_authors": [ { - "author_name": "Irtiza Qureshi", - "author_inst": "University of Nottingham" + "author_name": "Yuichi Kojima", + "author_inst": "Faculty of Medicine, Hokkaido University" }, { - "author_name": "Mayuri Gogoi", - "author_inst": "University of Leicester" + "author_name": "Sho Nakakubo", + "author_inst": "Faculty of Medicine , Hokkaido University" }, { - "author_name": "Amani Al-Oraibi", - "author_inst": "University of Nottingham" + "author_name": "Nozomu Takei", + "author_inst": "Faculty of Medicine, Hokkaido University" }, { - "author_name": "Fatimah Wobi", - "author_inst": "University of Leicester" + "author_name": "Keisuke Kamada", + "author_inst": "Faculty of Medicine, Hokkaido University" }, { - "author_name": "Jonathan Chaloner", - "author_inst": "University of Nottingham" + "author_name": "Yu Yamashita", + "author_inst": "Faculty of Medicine, Hokkaido University" }, { - "author_name": "Laura Gray", - "author_inst": "University of Leicester" + "author_name": "Junichi Nakamura", + "author_inst": "Faculty of Medicine, Hokkaido University" }, { - "author_name": "Anna Louise Guyatt", - "author_inst": "University of Leicester" + "author_name": "Munehiro Matsumoto", + "author_inst": "Faculty of Medicine, Hokkaido University" }, { - "author_name": "Laura Nellums", - "author_inst": "University of Nottingham" + "author_name": "Kazuki Sato", + "author_inst": "Faculty of Medicine, Hokkaido University" }, { - "author_name": "Manish Pareek", - "author_inst": "University of Leicester" + "author_name": "Hiroshi Horii", + "author_inst": "Faculty of Medicine, Hokkaido University" + }, + { + "author_name": "Hideki Shima", + "author_inst": "Faculty of Medicine, Hokkaido University" + }, + { + "author_name": "Masaru Suzuki", + "author_inst": "Faculty of Medicine, Hokkaido University" + }, + { + "author_name": "Satoshi Konno", + "author_inst": "Faculty of Medicine, Hokkaido University" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "occupational and environmental health" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2021.12.12.21267663", @@ -475121,39 +474692,75 @@ "category": "cell biology" }, { - "rel_doi": "10.1101/2021.12.10.472102", - "rel_title": "Mutations in RBD of SARS-CoV-2 Omicron variant result stronger binding to human ACE2 protein", + "rel_doi": "10.1101/2021.12.10.472134", + "rel_title": "SARS-CoV2 variant-specific replicating RNA vaccines protect from disease and pathology and reduce viral shedding following challenge with heterologous SARS-CoV2 variants of concern", "rel_date": "2021-12-13", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.12.10.472102", - "rel_abs": "The COVID-19 pandemic caused by the SARS-CoV-2 virus has led to more than 270 million infections and 5.3 million of deaths worldwide. Several major variants of SARS-CoV-2 have emerged and posed challenges in controlling the pandemic. The recently occurred Omicron variant raised serious concerns about reducing the efficacy of vaccines and neutralization antibodies due to its vast mutations. We have modelled the complex structure of the human ACE2 protein and the receptor binding domain (RBD) of Omicron Spike protein (S-protein), and conducted atomistic molecular dynamics simulations to study the binding interactions. The analysis shows that the Omicron RBD binds more strongly to the human ACE2 protein than the original strain. The mutations at the ACE2-RBD interface enhance the tight binding by increasing hydrogen bonding interaction and enlarging buried solvent accessible surface area.", - "rel_num_authors": 5, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.12.10.472134", + "rel_abs": "Despite mass public health efforts, the SARS-CoV2 pandemic continues as of late-2021 with resurgent case numbers in many parts of the world. The emergence of SARS-CoV2 variants of concern (VoC) and evidence that existing vaccines that were designed to protect from the original strains of SARS-CoV-2 may have reduced potency for protection from infection against these VoC is driving continued development of second generation vaccines that can protect against multiple VoC. In this report, we evaluated an alphavirus-based replicating RNA vaccine expressing Spike proteins from the original SARS-CoV-2 Alpha strain and recent VoCs delivered in vivo via a lipid inorganic nanoparticle. Vaccination of both mice and Syrian Golden hamsters showed that vaccination induced potent neutralizing titers against each homologous VoC but reduced neutralization against heterologous challenges. Vaccinated hamsters challenged with homologous SARS-CoV2 variants exhibited complete protection from infection. In addition, vaccinated hamsters challenged with heterologous SARS-CoV-2 variants exhibited significantly reduced shedding of infectious virus. Our data demonstrate that this vaccine platform elicits significant protective immunity against SARS-CoV2 variants and supports continued development of this platform.", + "rel_num_authors": 14, "rel_authors": [ { - "author_name": "Cecylia Severin Lupala", - "author_inst": "Beijing Computational Science Research Center" + "author_name": "David W Hawman", + "author_inst": "NIAID/NIH" }, { - "author_name": "Yongjin Ye", - "author_inst": "Beijing Computational Science Research Center" + "author_name": "Kimberly Meade-White", + "author_inst": "NIAID/NIH" }, { - "author_name": "Hong Chen", - "author_inst": "Peking University" + "author_name": "Jacob Archer", + "author_inst": "HDT Bio" }, { - "author_name": "Xiaodong Su", - "author_inst": "Peking University" + "author_name": "Shanna Leventhal", + "author_inst": "NIAID/NIH" }, { - "author_name": "Haiguang Liu", - "author_inst": "Beijing Computational Science Research Center" + "author_name": "Drew Wilson", + "author_inst": "NIAID/NIH" + }, + { + "author_name": "Carl Shaia", + "author_inst": "NIAID/NIH" + }, + { + "author_name": "Samantha Randall", + "author_inst": "University of Washington" + }, + { + "author_name": "Amit P Khandhar", + "author_inst": "HDT Bio" + }, + { + "author_name": "Tien-Ying Hsiang", + "author_inst": "The University of Washington" + }, + { + "author_name": "Michael Gale Jr.", + "author_inst": "University of Washington" + }, + { + "author_name": "Peter Berglund", + "author_inst": "HDT Bio" + }, + { + "author_name": "Deborah Heydenburg Fuller", + "author_inst": "University of Washington" + }, + { + "author_name": "Heinz Feldmann", + "author_inst": "NIAID/NIH" + }, + { + "author_name": "Jesse Erasmus", + "author_inst": "HDT Bio" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc0", "type": "new results", - "category": "bioinformatics" + "category": "microbiology" }, { "rel_doi": "10.1101/2021.12.10.472112", @@ -477075,191 +476682,111 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2021.12.09.21267548", - "rel_title": "Proteomic Characterization of Acute Kidney Injury in Patients Hospitalized with SARS-CoV2 Infection", + "rel_doi": "10.1101/2021.12.09.21267513", + "rel_title": "Contribution of endogenous and exogenous antibodies to clearance of SARS-CoV-2 during convalescent plasma therapy", "rel_date": "2021-12-11", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.09.21267548", - "rel_abs": "Acute kidney injury (AKI) is a known complication of COVID-19 and is associated with an increased risk of in-hospital mortality. Unbiased proteomics using biological specimens can lead to improved risk stratification and discover pathophysiological mechanisms. Using measurements of [~]4000 plasma proteins in two cohorts of patients hospitalized with COVID-19, we discovered and validated markers of COVID-associated AKI (stage 2 or 3) and long-term kidney dysfunction. In the discovery cohort (N= 437), we identified 413 higher plasma abundances of protein targets and 40 lower plasma abundances of protein targets associated with COVID-AKI (adjusted p <0.05). Of these, 62 proteins were validated in an external cohort (p <0.05, N =261). We demonstrate that COVID-AKI is associated with increased markers of tubular injury (NGAL) and myocardial injury. Using estimated glomerular filtration (eGFR) measurements taken after discharge, we also find that 25 of the 62 AKI-associated proteins are significantly associated with decreased post-discharge eGFR (adjusted p <0.05). Proteins most strongly associated with decreased post-discharge eGFR included desmocollin-2, trefoil factor 3, transmembrane emp24 domain-containing protein 10, and cystatin-C indicating tubular dysfunction and injury. Using clinical and proteomic data, our results suggest that while both acute and long-term COVID-associated kidney dysfunction are associated with markers of tubular dysfunction, AKI is driven by a largely multifactorial process involving hemodynamic instability and myocardial damage.", - "rel_num_authors": 43, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.09.21267513", + "rel_abs": "Neutralizing antibodies are considered a key correlate of protection by current SARS-CoV-2 vaccines. The ability of antibody-based therapies, including convalescent plasma, to affect established disease remains to be elucidated. Only few monoclonal therapies and only when used at a very early stage of infection have shown efficacy. Here, we conducted a proof-of-principle study of convalescent plasma therapy in a phase I trial in 30 COVID-19 patients including immunocompromised individuals hospitalized early after onset of symptoms. A comprehensive longitudinal monitoring of the virologic, serologic, and disease status of recipients in conjunction with detailed post-hoc seroprofiling of transfused convalescent plasma, allowed deciphering of parameters on which plasma therapy efficacy depends. Plasma therapy was safe and had a significant effect on viral clearance depending on neutralizing and spike SARS-CoV-2 antibody levels in the supplied convalescent plasma. Endogenous immunity had strong effects on virus control. Lack of endogenous neutralizing activity at baseline was associated with a higher risk of systemic viremia. The onset of endogenous neutralization had a noticeable effect on viral clearance but, importantly, even after adjusting for their endogenous neutralization status recipients benefitted from therapy with high neutralizing antibody containing plasma.\n\nIn summary, our data demonstrate a clear impact of exogenous antibody therapy on the rapid clearance of viremia in the early stages of infection and provide directions for improved efficacy evaluation of current and future SARS-CoV-2 therapies beyond antibody-based interventions. Incorporating an assessment of the endogenous immune response and its dynamic interplay with viral production is critical for determining therapeutic effects.\n\nOne Sentence SummaryThis study demonstrates the impact of exogenous antibody therapy by convalescent plasma containing high neutralizing titers on the rapid clearance of viremia in the early stages of SARS-CoV-2 infection.", + "rel_num_authors": 23, "rel_authors": [ { - "author_name": "Ishan Paranjpe", - "author_inst": "The Mount Sinai Clinical Intelligence Center (MSCIC), Icahn School of Medicine at Mount Sinai, New York, NY, USA" - }, - { - "author_name": "Pushkala Jayaraman", - "author_inst": "Mount Sinai Clinical Intelligence Center(MSCIC), The Charles Bronfman Institute of Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY," - }, - { - "author_name": "Chen-Yang Su", - "author_inst": "Lady Davis Institute, Jewish General Hospital, McGill University, Montreal, Quebec, Canada" - }, - { - "author_name": "Sirui Zhou", - "author_inst": "Lady Davis Institute, Jewish General Hospital, McGill University, Montreal, Quebec, Canada" - }, - { - "author_name": "Steven Chen", - "author_inst": "The Precision Immunology Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA." - }, - { - "author_name": "Ryan Thompson", - "author_inst": "The Mount Sinai Clinical Intelligence Center (MSCIC), Icahn School of Medicine at Mount Sinai, New York, NY, USA" - }, - { - "author_name": "Diane Marie Del Valle", - "author_inst": "The Mount Sinai Clinical Intelligence Center (MSCIC), Icahn School of Medicine at Mount Sinai, New York, NY, USA" - }, - { - "author_name": "Ephraim Kenigsberg", - "author_inst": "Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA" - }, - { - "author_name": "Shan Zhao", - "author_inst": "Department of Anesthesiology, Perioperative and Pain Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America" - }, - { - "author_name": "Suraj Jaladanki", - "author_inst": "The Mount Sinai Clinical Intelligence Center (MSCIC), Icahn School of Medicine at Mount Sinai, New York, NY, USA" - }, - { - "author_name": "Kumardeep Chaudhary", - "author_inst": "The Mount Sinai Clinical Intelligence Center (MSCIC), Icahn School of Medicine at Mount Sinai, New York, NY, USA" - }, - { - "author_name": "Steven Ascolillo", - "author_inst": "The Mount Sinai Clinical Intelligence Center (MSCIC), Icahn School of Medicine at Mount Sinai, New York, NY, USA" - }, - { - "author_name": "Akhil Vaid", - "author_inst": "The Mount Sinai Clinical Intelligence Center (MSCIC), Icahn School of Medicine at Mount Sinai, New York, NY, USA" - }, - { - "author_name": "Arvind Kumar", - "author_inst": "The Mount Sinai Clinical Intelligence Center (MSCIC), Icahn School of Medicine at Mount Sinai, New York, NY, USA" - }, - { - "author_name": "Edgar Gonzalez-Kozlova", - "author_inst": "The Mount Sinai Clinical Intelligence Center(MSCIC), Icahn School of Medicine at Mount Sinai, New York, NY, USA" - }, - { - "author_name": "Manish Paranjpe", - "author_inst": "Division of Health Sciences and Technology, Harvard Medical School, Boston, MA, USA" - }, - { - "author_name": "Ross O Hagan", - "author_inst": "The Mount Sinai Clinical Intelligence Center (MSCIC), Icahn School of Medicine at Mount Sinai, New York, NY, USA" - }, - { - "author_name": "Samir Kamat", - "author_inst": "The Mount Sinai Clinical Intelligence Center (MSCIC), Icahn School of Medicine at Mount Sinai, New York, NY, USA" - }, - { - "author_name": "Faris F. Gulamali", - "author_inst": "The Mount Sinai Clinical Intelligence Center (MSCIC), Icahn School of Medicine at Mount Sinai, New York, NY, USA" - }, - { - "author_name": "Justin Kauffman", - "author_inst": "The Mount Sinai Clinical Intelligence Center(MSCIC), Icahn School of Medicine at Mount Sinai, New York, NY, USA" - }, - { - "author_name": "Hui Xie", - "author_inst": "Human Immune Monitoring Center, Icahn School of Medicine at Mount Sinai, New York, NY, USA" + "author_name": "Maddalena Marconato", + "author_inst": "Department of Medical Oncology and Hematology, University Hospital and University of Zurich and Comprehensive Cancer Center Zurich, Switzerland" }, { - "author_name": "Joceyln Harris", - "author_inst": "Human Immune Monitoring Center, Icahn School of Medicine at Mount Sinai, New York, NY, USA" + "author_name": "Irene A Abela", + "author_inst": "Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, Switzerland/ Institute of Medical Virology, University of Zurich, Switzer" }, { - "author_name": "Manishkumar Patel", - "author_inst": "Human Immune Monitoring Center, Icahn School of Medicine at Mount Sinai, New York, NY, USA" + "author_name": "Anthony Hauser", + "author_inst": "Institute of Medical Virology, University of Zurich, Switzerland" }, { - "author_name": "Kimberly Argueta", - "author_inst": "Human Immune Monitoring Center, Icahn School of Medicine at Mount Sinai, New York, NY, USA" + "author_name": "Magdalena Schwarzmueller", + "author_inst": "Institute of Medical Virology, University of Zurich, Switzerland" }, { - "author_name": "Craig Batchelor", - "author_inst": "Human Immune Monitoring Center, Icahn School of Medicine at Mount Sinai, New York, NY, USA" + "author_name": "Rheliana Katzensteiner", + "author_inst": "Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, Switzerland" }, { - "author_name": "Kai Nie", - "author_inst": "Human Immune Monitoring Center, Icahn School of Medicine at Mount Sinai, New York, NY, USA" + "author_name": "Dominique L Braun", + "author_inst": "Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, Switzerland" }, { - "author_name": "Sergio Dellepiane", - "author_inst": "Department of Medicine, Division of Nephrology, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America" + "author_name": "Selina Epp", + "author_inst": "Institute of Medical Virology, University of Zurich, Switzerland" }, { - "author_name": "Leisha Scott", - "author_inst": "Human Immune Monitoring Center, Icahn School of Medicine at Mount Sinai, New York, NY, USA" + "author_name": "Annette Audige", + "author_inst": "Institute of Medical Virology, University of Zurich, Switzerland" }, { - "author_name": "Matthew A Levin", - "author_inst": "The Mount Sinai Clinical Intelligence Center (MSCIC), Icahn School of Medicine at Mount Sinai, New York, NY, USA" + "author_name": "Jacqueline Weber", + "author_inst": "Institute of Medical Virology, University of Zurich, Switzerland" }, { - "author_name": "John Cijiang He", - "author_inst": "Department of Medicine, Division of Nephrology, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America" + "author_name": "Peter Rusert", + "author_inst": "Institute of Medical Virology, University of Zurich, Switzerland" }, { - "author_name": "Mayte Suarez-Farinas", - "author_inst": "Department of Biostatistics, Icahn School of Medicine, Mount Sinai, NY" + "author_name": "Emery Schindler", + "author_inst": "Blood Transfusion Service Zurich, Switzerland" }, { - "author_name": "Steven G Coca", - "author_inst": "Department of Medicine, Division of Nephrology, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America" + "author_name": "Chloe Pasin", + "author_inst": "Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, Switzerland/Institute of Medical Virology, University of Zurich, Switzerl" }, { - "author_name": "Lili Chan", - "author_inst": "Department of Medicine, Division of Nephrology, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America" + "author_name": "Emily West", + "author_inst": "Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, Switzerland" }, { - "author_name": "Evren U Azeloglu", - "author_inst": "Department of Medicine, Division of Nephrology, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America" + "author_name": "Juerg Boeni", + "author_inst": "Institute of Medical Virology, University of Zurich, Switzerland" }, { - "author_name": "Eric Schadt", - "author_inst": "Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA" + "author_name": "Verena Kufner", + "author_inst": "Institute of Medical Virology, University of Zurich, Switzerland" }, { - "author_name": "Noam Beckmann", - "author_inst": "The Mount Sinai Clinical Intelligence Center (MSCIC), Icahn School of Medicine at Mount Sinai, New York, NY, USA" + "author_name": "Michael Huber", + "author_inst": "Institute of Medical Virology, University of Zurich, Switzerland" }, { - "author_name": "Sacha Gnjatic", - "author_inst": "Department of Oncological Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA." + "author_name": "Maryam Zaheri", + "author_inst": "Institute of Medical Virology, University of Zurich, Switzerland" }, { - "author_name": "Miram Merad", - "author_inst": "The Precision Immunology Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA." + "author_name": "Stefan Schmutz", + "author_inst": "Institute of Medical Virology, University of Zurich, Switzerland" }, { - "author_name": "Seunghee Kim-Schulze", - "author_inst": "The Precision Immunology Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA." + "author_name": "Beat M Frey", + "author_inst": "Blood Transfusion Service Zurich, Switzerland" }, { - "author_name": "Brent Richards", - "author_inst": "Lady Davis Institute, Jewish General Hospital, McGill University, Montreal, Quebec, Canada" + "author_name": "Roger D Kouyos", + "author_inst": "Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, Switzerland" }, { - "author_name": "Benjamin S Glicksberg", - "author_inst": "The Mount Sinai Clinical Intelligence Center (MSCIC), Icahn School of Medicine at Mount Sinai, New York, NY, USA" + "author_name": "Huldrych F Gunthard", + "author_inst": "Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, Switzerland" }, { - "author_name": "Alexander W Charney", - "author_inst": "The Mount Sinai Clinical Intelligence Center (MSCIC), Icahn School of Medicine at Mount Sinai, New York, NY, USA" + "author_name": "Markus G Manz", + "author_inst": "Department of Medical Oncology and Hematology, University Hospital and University of Zurich and Comprehensive Cancer Center Zurich, Switzerland" }, { - "author_name": "Girish N Nadkarni", - "author_inst": "The Mount Sinai Clinical Intelligence Center (MSCIC), Icahn School of Medicine at Mount Sinai, New York, NY, USA" + "author_name": "Alexandra Trkola", + "author_inst": "Institute of Medical Virology, University of Zurich, Switzerland" } ], "version": "1", "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "nephrology" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2021.12.09.21267278", @@ -479221,61 +478748,33 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2021.12.07.471597", - "rel_title": "Deep Mutational Engineering of broadly-neutralizing and picomolar affinity nanobodies to accommodate SARS-CoV-1 & 2 antigenic polymorphism", + "rel_doi": "10.1101/2021.12.08.471688", + "rel_title": "Mutations in the spike RBD of SARS-CoV-2 omicron variant may increase infectivity without dramatically altering the efficacy of current multi-dosage vaccinations", "rel_date": "2021-12-09", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.12.07.471597", - "rel_abs": "We report in this study the molecular engineering of nanobodies that bind with picomolar affinity to both SARS-CoV-1 and SARS-CoV-2 Receptor Binding Domains (RBD) and are highly neutralizing. We applied Deep Mutational Engineering to VHH72, a nanobody initially specific for SARS-CoV-1 RBD with little cross-reactivity to SARS-CoV-2 antigen. We first identified all the individual VHH substitutions that increase binding to SARS-CoV-2 RBD and then screened highly focused combinatorial libraries to isolate engineered nanobodies with improved properties. The corresponding VHH-Fc molecules show high affinities for SARS-CoV-2 antigens from various emerging variants and SARS-CoV-1, block the interaction between ACE2 and RBD and neutralize the virus with high efficiency. Its rare specificity across sarbecovirus relies on its peculiar epitope outside the immunodominant regions. The engineered nanobodies share a common motif of three amino acids, which contribute to the broad specificity of recognition. These nanobodies appears as promising therapeutic candidates to fight SARS-CoV-2 infection.", - "rel_num_authors": 11, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.12.08.471688", + "rel_abs": "With the continuous evolution of SARS-CoV-2, variants of concern (VOCs) and their mutations are a focus of rapid assessment. Vital mutations in the VOC are found in spike protein, particularly in the receptor binding domain (RBD), which directly interacts with ACE2 on the host cell membrane, a key determinant of the binding affinity and cell entry. With the reporting of the most recent VOC, omicron, we performed amino acid sequence alignment of the omicron spike protein with that of the wild type and other VOCs. Although it shares several conserved mutations with other variants, we found that omicron has a large number of unique mutations. We applied the Hopp-Woods scale to calculate the hydrophilicity scores of the amino acid stretches of the RBD and the entire spike protein, and found 3 new hydrophilic regions in the RBD of omicron, implying exposure to water, with the potential to bind proteins such as ACE2 increasing transmissibility and infectivity. However, careful analysis reveals that most of the exposed domains of spike protein can serve as antigenic epitopes for generating B cell and T cell-mediated immune responses. This suggests that in the collection of polyclonal antibodies to various epitopes generated after multiple doses of vaccination, some can likely still bind to the omicron spike protein and the RBD to prevent severe clinical disease. In summary, while the omicron variant might result in more infectivity, it can still bind to a reasonable repertoire of antibodies generated by multiple doses of current vaccines likely preventing severe disease. Effective vaccines may not universally prevent opportunistic infections but can prevent the sequelae of severe disease, as observed for the delta variant. This might still be the case with the omicron variant, albeit, with increased frequency of infection.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Adrien Laroche", - "author_inst": "Universite Paris-Saclay, CEA, INRAE, Medicines and Healthcare Technologies Department, SIMoS, Gif-sur-Yvette" - }, - { - "author_name": "Maria Lucia Orsini Delgado", - "author_inst": "Universite Paris-Saclay, CEA, INRAE, Medicines and Healthcare Technologies Department, SPI, Gif-sur-Yvette, France" - }, - { - "author_name": "Philippe Cuniasse", - "author_inst": "Universite Paris-Saclay, CNRS, CEA, Institute for Integrative Biology of the Cell (I2BC), Gif-sur-Yvette, France" - }, - { - "author_name": "Steven Dubois", - "author_inst": "Universite Paris-Saclay, CEA, INRAE, Medicines and Healthcare Technologies Department, SIMoS, Gif-sur-Yvette" - }, - { - "author_name": "Raphael Sierocki", - "author_inst": "Deeptope SAS, Massy, France" - }, - { - "author_name": "Fabrice Gallais", - "author_inst": "Universite Paris Saclay, CEA, INRAE, Departement Medicaments et Technologies pour la Sante (DMTS), SPI, 30200 Bagnols-sur-Ceze, France" - }, - { - "author_name": "Stephanie Debroas", - "author_inst": "Universite Paris Saclay, CEA, INRAE, Departement Medicaments et Technologies pour la Sante (DMTS), SPI, 30200 Bagnols-sur-Ceze, France" - }, - { - "author_name": "Laurent Bellanger", - "author_inst": "Universite Paris Saclay, CEA, INRAE, Departement Medicaments et Technologies pour la Sante (DMTS), SPI, 30200 Bagnols-sur-Ceze, France" + "author_name": "Bingrui Li", + "author_inst": "UT MD Anderson Cancer Center" }, { - "author_name": "Stephanie Simon", - "author_inst": "Universite Paris-Saclay, CEA, INRAE, Medicines and Healthcare Technologies Department, SPI, Gif-sur-Yvette, France" + "author_name": "Xin Luo", + "author_inst": "UT MD Anderson Cancer Center" }, { - "author_name": "Bernard Maillere", - "author_inst": "Universite Paris-Saclay, CEA, INRAE, Medicines and Healthcare Technologies Department, SIMoS, Gif-sur-Yvette, France" + "author_name": "Kathleen M McAndrews", + "author_inst": "UT MD Anderson Cancer Center" }, { - "author_name": "Herv\u00e9 Nozach", - "author_inst": "Universite Paris-Saclay, CEA, INRAE, Medicines and Healthcare Technologies Department, SIMoS, Gif-sur-Yvette" + "author_name": "Raghu Kalluri", + "author_inst": "UT MD Anderson Cancer Center" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "new results", "category": "biochemistry" }, @@ -480747,55 +480246,75 @@ "category": "bioinformatics" }, { - "rel_doi": "10.1101/2021.12.06.471421", - "rel_title": "Metabolic dysregulation induces impaired lymphocyte memory formation during severe SARS-CoV-2 infection", + "rel_doi": "10.1101/2021.12.06.471528", + "rel_title": "The cellular characterisation of SARS-CoV-2 spike protein in virus-infected cells using Receptor Binding Domain-binding specific human monoclonal antibodies.", "rel_date": "2021-12-08", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.12.06.471421", - "rel_abs": "Cellular metabolic dysregulation is a consequence of COVID-19 infection that is a key determinant of disease severity. To understand the mechanisms underlying these cellular changes, we performed high-dimensional immune cell profiling of PBMCs from COVID-19-infected patients, in combination with single cell transcriptomic analysis of COVID-19 BALFs. Hypoxia, a hallmark of COVID-19 ARDS, was found to elicit a global metabolic reprogramming in effector lymphocytes. In response to oxygen and nutrient-deprived microenvironments, these cells shift from aerobic respiration to increase their dependence on anaerobic processes including glycolysis, mitophagy, and glutaminolysis to fulfill their bioenergetic demands. We also demonstrate metabolic dysregulation of ciliated lung epithelial cells is linked to significant increase of proinflammatory cytokine secretion and upregulation of HLA class 1 machinery. Augmented HLA class-1 antigen stimulation by epithelial cells leads to cellular exhaustion of metabolically dysregulated CD8 and NK cells, impairing their memory cell differentiation. Unsupervised clustering techniques revealed multiple distinct, differentially abundant CD8 and NK memory cell states that are marked by high glycolytic flux, mitochondrial dysfunction, and cellular exhaustion, further highlighting the connection between disrupted metabolism and impaired memory cell function in COVID-19. Our findings provide novel insight on how SARS-CoV-2 infection affects host immunometabolism and anti-viral response during COVID-19.\n\nGraphical Abstract\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=85 SRC=\"FIGDIR/small/471421v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (32K):\norg.highwire.dtl.DTLVardef@18bff7borg.highwire.dtl.DTLVardef@31f46borg.highwire.dtl.DTLVardef@1a5ad50org.highwire.dtl.DTLVardef@1577a0_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIHypoxia and anaerobic glycolysis drive CD8, NK, NKT dysfunction\nC_LIO_LIHypoxia and anaerobic glycolysis impair memory differentiation in CD8 and NK cells\nC_LIO_LIHypoxia and anaerobic glycolysis cause mitochondrial dysfunction in CD8, NK, NKT cells\nC_LI", - "rel_num_authors": 9, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.12.06.471528", + "rel_abs": "A human monoclonal antibody panel (PD4, PD5, PD7, SC23 and SC29) was isolated from the B cells of convalescent patients and used to examine the S protein in SARS-CoV-2- infected cells. While all five antibodies bound conformational-specific epitopes within SARS-CoV-2 Spike (S) protein, only PD5, PD7, and SC23 were able to bind to the Receptor Binding Domain (RBD). Immunofluorescence microscopy was used to examine the S protein RBD in cells infected with the Singapore isolates SARS-CoV-2/0334 and SARS-CoV-2/1302. The RBD-binders exhibited a distinct cytoplasmic staining pattern that was primarily localised within the Golgi complex and was distinct from the diffuse cytoplasmic staining pattern exhibited by the non-RBD binders (PD4 and SC29). These data indicated that the S protein adopted a conformation in the Golgi complex that enabled the RBD recognition by the RBD-binders. The RBD-binders also recognised the uncleaved S protein indicating that S protein cleavage was not required for RBD recognition. Electron microscopy indicated high levels of cell-associated virus particles, and multiple cycle virus infection using RBD-binder staining provided evidence for direct cell-to-cell transmission for both isolates. Although similar levels of RBD-binder staining was demonstrated for each isolate, the SARS-CoV-2/1302 exhibited slower rates of cell-to-cell transmission. These data suggest that a conformational change in the S protein occurs during its transit through the Golgi complex that enables RBD recognition by the RBD-binders, and suggests that these antibodies can be used to monitor S protein RBD formation during the early stages of infection.\n\nImportanceThe SARS CoV-2 spike (S) protein receptor binding domain (RBD) mediates the attachment of SARS CoV-2 to the host cell. This interaction plays an essential role in initiating virus infection and the S protein RBD is therefore a focus of therapeutic and vaccine interventions. However, new virus variants have emerged with altered biological properties in the RBD that can potentially negate these interventions. Therefore an improved understanding of the biological properties of the RBD in virus-infected cells may offer future therapeutic strategies to mitigate SARS CoV-2 infection. We used physiologically relevant antibodies that were isolated from the B cells of convalescent COVID19 patients to monitor the RBD in cells infected with SARS CoV-2 clinical isolates. These immunological reagents specifically recognise the correctly folded RBD and were used to monitor the appearance of the RBD in SARS CoV-2-infected cells and identified the site where the RDB first appears.", + "rel_num_authors": 14, "rel_authors": [ { - "author_name": "Hung Nguyen", - "author_inst": "University of Central Florida" + "author_name": "Conrad En-Zuo Chan", + "author_inst": "DSO National Laboratories" }, { - "author_name": "Sanjeev Gurshaney", - "author_inst": "University of Central Florida" + "author_name": "Ching-Ging Ng", + "author_inst": "DSO National Laboratories" }, { - "author_name": "Anamaria Morales Alvarez", - "author_inst": "University of Central Florida" + "author_name": "Angeline P. C. Lim", + "author_inst": "National University of Singapore" }, { - "author_name": "Kevin Ezhakunnel", - "author_inst": "University of Central Florida" + "author_name": "Shirley Gek-Kheng Seah", + "author_inst": "DSO National Laboratories" }, { - "author_name": "Andrew Manalo", - "author_inst": "University of Central Florida" + "author_name": "De Hoe Chye", + "author_inst": "Defense Medical and Environmental Research Institute, DSO National Laboratories" }, { - "author_name": "Thien-Huong Huynh", - "author_inst": "University of Central Florida" + "author_name": "Steven K. K. Wong", + "author_inst": "Defense Medical and Environmental Research Institute, DSO National Laboratories" }, { - "author_name": "Nhat -Tu Le", - "author_inst": "Houston Methodist" + "author_name": "Jie-Hui Lim", + "author_inst": "DMERI" }, { - "author_name": "Daniel Lupu", - "author_inst": "AdventHealth" + "author_name": "Vanessa Zi-Yun Lim", + "author_inst": "Nanyang Technological University" }, { - "author_name": "Stephen Gardell", - "author_inst": "AdventHealth" + "author_name": "Soak Kuan Lai", + "author_inst": "Nanyang Technological University" + }, + { + "author_name": "Pui-San Wong", + "author_inst": "DSO National Laboratories" + }, + { + "author_name": "Kok-Mun Leong", + "author_inst": "DSO National Laboratories" + }, + { + "author_name": "Yichun Liu", + "author_inst": "Defence Medical and Environmental Research Institute" + }, + { + "author_name": "Richard Sugrue", + "author_inst": "Nanyang Technological University" + }, + { + "author_name": "Boon Huan Tan", + "author_inst": "DSO National Laboratories" } ], "version": "1", "license": "cc_no", "type": "new results", - "category": "immunology" + "category": "microbiology" }, { "rel_doi": "10.1101/2021.12.06.471464", @@ -482629,31 +482148,23 @@ "category": "pharmacology and toxicology" }, { - "rel_doi": "10.1101/2021.11.29.21266774", - "rel_title": "Stressors, Manifestations and Course of COVID-19 Related Distress Among Nurses and Midwives in Tasmania", + "rel_doi": "10.1101/2021.11.30.21267096", + "rel_title": "Statistical Inferences and Analysis based on the COVID-19 data from the United States", "rel_date": "2021-12-07", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.29.21266774", - "rel_abs": "The deleterious effects relating to the COVID-19 pandemic on the mental health of healthcare workers has now been widely established. Understanding how COVID-19 affects their work and life is complex and multidimensional. This study describes the critical stressors and how they manifest within both the work and larger social environment for nurses and midwives in Tasmania, Australia.\n\nA longitudinal, descriptive survey was designed to explore the trajectory of the psychological health of Tasmanian public sector nurses and midwives during the COIVD-19 pandemic. The survey was distributed at 3 timepoints over a 12-month period and consisted of a battery of psychological tests which included the Patient Health Questionnaire, General Anxiety Disorder, Insomnia Severity Index, and the Impact of Events Scale-Revised, together with free text comments.\n\nThe associations between outcome and predictor variables were assessed using mixed effects linear regression and linear mixed model analyses. Free text comments were themed.\n\nHigh levels of stress and mental exhaustion were attributed to threatened workplace team culture; compromised quality of patient care; the impact on family, home, financial and economic domains; lack of clear communication; issues surrounding personal protective equipment; and female gender. Study data show younger nurses and midwives suffered higher levels of stress and mental exhaustion than older.\n\nThis study highlights the need for stable and functional relationships at home and at work for nurses and midwives.\n\nFactors which will help preserve the mental health of nurses and midwives include strong workplace culture with ongoing processes to monitor organisational burnout; building resilience, particularly among younger nurses and midwives; protection of healthcare worker safety; clear communication processes and supporting stable and functional relationships at home. The health service has an imperative to ensure optimum service delivery by safeguarding staff, despite the inevitable health stress imposed by the nature of the work.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.30.21267096", + "rel_abs": "This paper investigates the mortality statistics of the COVID-19 pandemic from the United States perspective. We bring out several exciting and glaring aspects of the pandemic, otherwise hidden, using empirical data analysis and statistical inference tools. First, specific patterns seen in demographics such as race/ethnicity are analyzed qualitatively and quantitatively. We looked at the role of factors such as population density in mortality rates. A detailed study of the connections between COVID-19 and other respiratory diseases is also covered. Finally, we examine the temporal dynamics of the COVID-19 outbreak and vaccines stellar impact in controlling the pandemic. Statistical inference such as the ones gathered in this paper would be helpful for better scientific understanding, policy preparation, and thus adequately preparing, should a similar situation arise in the future.", + "rel_num_authors": 1, "rel_authors": [ { - "author_name": "Kathryn M Marsden", - "author_inst": "Tasmanian Health Service South" - }, - { - "author_name": "Julie M Porter", - "author_inst": "Tasmanian Health Service South" - }, - { - "author_name": "I.K. Robertson", - "author_inst": "University of Tasmania" + "author_name": "Nivedita Rethnakar", + "author_inst": "Palomar College" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "nursing" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2021.12.06.21267354", @@ -484559,35 +484070,47 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.12.05.21267334", - "rel_title": "Association of regional Covid-19 mortality with indicators of indoor ventilation, including temperature and wind: insights into the upcoming winter: Update Dec. 5, 2021", + "rel_doi": "10.1101/2021.12.07.21267398", + "rel_title": "In-hospital mortality due to breakthrough COVID-19 among recipients of COVISHIELD (ChAdOx nCoV-19) and COVAXIN (BBV152)", "rel_date": "2021-12-07", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.05.21267334", - "rel_abs": "BackgroundOutdoor environmental variables, such as cold temperatures and low wind speed, have been correlated with incidence and mortality from Covid-19 (caused by the SARS-CoV-2 virus). However, as Covid-19 predominantly spreads indoors, the degree to which outdoor environmental variables might directly cause disease spread is unclear.\n\nMethodsWorld regions were considered to have reliable data if the excess mortality did not greatly exceed reported Covid-19 mortality. The relative risk of Covid-19 mortality for 142 regions as a function of median weekly temperature and wind speed was determined. For instance, Covid-19 mortality following warm weeks in a country was compared with mortality following cold weeks in the same country.\n\nResultsCovid-19 mortality increases with cooling from 20 C to close to freezing (0 to 4 C, p<0.001). The relation of Covid-19 mortality with temperature demonstrates a maximum close to freezing. Below -5 C, the decrease in mortality with further cooling was statistically significant (p<0.01). With warming above room temperature (20 to 24 C), there is a nonsignificant trend for mortality to increase again. A literature review demonstrated that window opening and indoor ventilation tend to increase with warming in the range from freezing to room temperature.\n\nConclusionThe steep decline in Covid-19 mortality with warming in the range from freezing to room temperature may relate to window opening and less indoor crowding when it is comfortable outside. Below freezing, all windows are closed, and further cooling increases stack ventilation (secondary to indoor-outdoor temperature differences) and thereby tends to decrease Covid-19 mortality. Opening windows and other tools for improving indoor ventilation may decrease the spread of Covid-19.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.07.21267398", + "rel_abs": "BackgroundMultiple vaccines have received emergency-use authorization in different countries in the fight against the COVID-19 pandemic. India had started its vaccination campaign using the COVISHIELD (ChAdOx nCoV-19) and the COVAXIN (BBV152) vaccines. However, there is a lack of head-to-head comparisons of the different vaccines.\n\nMethodsWe performed a retrospective cohort study during the second wave of the pandemic in India with predominant circulation of the delta strain of SARS-CoV-2. We enrolled adult patients who were hospitalized with breakthrough COVID-19 infection after vaccination. We compared in-hospital outcomes between patients who had received the COVISHIELD (n=181) or COVAXIN vaccines.\n\nResultsBetween April and June 2021, a total of 353 patients were enrolled, among whom 181 (51.3%) received COVAXIN (156 partially vaccinated and 25 fully vaccinated) and 172 (48.7%) received COVISHIELD (155 partially vaccinated and 17 fully vaccinated). The in-hospital mortality did not differ between the recipients of COVISHIELD or COVAXIN in either the fully vaccinated [2 deaths (11.8%) vs 0 deaths (0%), respectively p=0.08] or the partially vaccinated cohorts [31 deaths (20%) vs 28 deaths (17.9%), respectively, p=0.65].\n\nConclusionsPatients who are hospitalized with breakthrough COVID-19 had similar in-hospital outcome irrespective of whether they received COVISHIELD or COVAXIN.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Christopher T Leffler", - "author_inst": "Virginia Commonwealth University" + "author_name": "Tejas M Suri", + "author_inst": "AIIMS" }, { - "author_name": "Joseph D. Lykins V", - "author_inst": "Virginia Commonwealth University" + "author_name": "Tamoghna Ghosh", + "author_inst": "All India Institute of Medical Sciences, New Delhi" }, { - "author_name": "Brandon I Fram", - "author_inst": "Virginia Commonwealth University" + "author_name": "Arunachalam M", + "author_inst": "AIIMS" }, { - "author_name": "Edward Yang", - "author_inst": "Virginia Commonwealth University" + "author_name": "Rohit Vadala", + "author_inst": "AIIMS" + }, + { + "author_name": "Saurabh Vig", + "author_inst": "AIIMS" + }, + { + "author_name": "Sushma Bhatnagar", + "author_inst": "AIIMS" + }, + { + "author_name": "Anant Mohan", + "author_inst": "All India Institute of Medical Sciences" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "allergy and immunology" }, { "rel_doi": "10.1101/2021.12.06.21267375", @@ -486341,159 +485864,55 @@ "category": "nephrology" }, { - "rel_doi": "10.1101/2021.12.03.21266112", - "rel_title": "Brain Injury in COVID-19 is Associated with Autoinflammation and Autoimmunity", + "rel_doi": "10.1101/2021.12.04.21267231", + "rel_title": "A mixed-methods study of risk factors and experiences of healthcare workers tested for the novel coronavirus in Canada", "rel_date": "2021-12-05", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.03.21266112", - "rel_abs": "COVID-19 has been associated with many neurological complications including stroke, delirium and encephalitis. Furthermore, many individuals experience a protracted post-viral syndrome which is dominated by neuropsychiatric symptoms, and is seemingly unrelated to COVID-19 severity. The true frequency and underlying mechanisms of neurological injury are unknown, but exaggerated host inflammatory responses appear to be a key driver of severe COVID-19 more broadly.\n\nWe sought to investigate the dynamics of, and relationship between, serum markers of brain injury (neurofilament light [NfL], Glial Fibrillary Acidic Protein [GFAP] and total Tau) and markers of dysregulated host response including measures of autoinflammation (proinflammatory cytokines) and autoimmunity. Brain injury biomarkers were measured using the Quanterix Simoa HDx platform, cytokine profiling by Luminex (R&D) and autoantibodies by a custom protein microarray.\n\nDuring hospitalisation, patients with COVID-19 demonstrated elevations of NfL and GFAP in a severity-dependant manner, and there was evidence of ongoing active brain injury at follow-up 4 months later. Raised NfL and GFAP were associated with both elevations of pro-inflammatory cytokines and the presence of autoantibodies; autoantibodies were commonly seen against lung surfactant proteins as well as brain proteins such as myelin associated glycoprotein, but reactivity was seen to a large number of different antigens.\n\nFurthermore, a distinct process characterised by elevation of serum total Tau was seen in patients at follow-up, which appeared to be independent of initial disease severity and was not associated with dysregulated immune responses in the same manner as NfL and GFAP.", - "rel_num_authors": 35, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.04.21267231", + "rel_abs": "ObjectivesWe aimed to investigate the contribution of occupational and non-work-related factors to the risk of novel coronavirus (SARS-CoV-2) infection among healthcare workers (HCWs) in Vancouver Coastal Health, British Columbia, Canada. We also aimed to examine how HCWs described their experiences.\n\nMethodsWe conducted a matched case-control study using data from online and phone questionnaires with optional open-ended questions completed by HCWs who sought SARS-CoV-2 testing between March 2020 and March 2021. Conditional logistic regression and thematic analysis were utilized.\n\nResultsData from 1340 HCWs were included. Free-text responses were provided by 257 respondents. Adjusting for age, gender, race, occupation, and number of weeks since pandemic was declared, community exposure to a known COVID-19 case (adjusted odds ratio -aOR: 2.45; 95% CI 1.67-3.59), and difficulty accessing personal protective equipment -PPE- (aOR: 1.84; 95% CI 1.07-3.17) were associated with higher infection odds. Care-aides/licensed practical nurses had substantially higher risk (aOR: 2.92; 95% CI 1.49-5.70) than medical staff who had the lowest risk. Direct COVID-19 patient care was not associated with elevated risk. HCWs experiences reflected the phase of the pandemic when they were tested. Suboptimal communication, mental stress, and situations perceived as unsafe were common sources of dissatisfaction.\n\nConclusionsCommunity exposures and occupation were important determinants of infection among HCWs in our study. The availability of PPE and clear communication enhanced a sense of safety. Varying levels of risk between occupational groups call for wider targeting of infection prevention measures. Strategies for mitigating community exposure and supporting HCW resilience are required.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Edward J Needham", - "author_inst": "Department of Clinical Neurosciences, University of Cambridge, UK" - }, - { - "author_name": "Alex L Ren", - "author_inst": "Division of Anaesthesia, Department of Medicine, University of Cambridge, UK." - }, - { - "author_name": "Richard J Digby", - "author_inst": "Division of Anaesthesia, Department of Medicine, University of Cambridge, UK." - }, - { - "author_name": "Joanne G Outtrim", - "author_inst": "Division of Anaesthesia, Department of Medicine, University of Cambridge, UK." - }, - { - "author_name": "Dorothy A Chatfield", - "author_inst": "Division of Anaesthesia, Department of Medicine, University of Cambridge, UK." - }, - { - "author_name": "Virginia FJ Newcombe", - "author_inst": "Division of Anaesthesia, Department of Medicine, University of Cambridge, UK." - }, - { - "author_name": "Rainer Doffinger", - "author_inst": "Department of Clinical Biochemistry and Immunology, Addenbrooke's Hospital, Cambridge, UK." - }, - { - "author_name": "Gabriela Barcenas-Morales", - "author_inst": "Department of Clinical Biochemistry and Immunology, Addenbrooke's Hospital, Cambridge, UK." - }, - { - "author_name": "Claudia Fonseca", - "author_inst": "Cambridge Protein Arrays Ltd, Babraham Research Campus, Cambridge, UK" - }, - { - "author_name": "Michael J Taussig", - "author_inst": "Cambridge Protein Arrays Ltd, Babraham Research Campus, Cambridge, UK" - }, - { - "author_name": "Rowan M Burnstein", - "author_inst": "Division of Anaesthesia, Department of Medicine, University of Cambridge, UK." - }, - { - "author_name": "Cordelia Dunai", - "author_inst": "Clinical Infection Microbiology and Neuroimmunology, Institute of Infection, Veterinary and Ecological Science, Liverpool, UK." - }, - { - "author_name": "Nyarie Sithole", - "author_inst": "Department of Infectious Diseases, Cambridge University NHS Hospitals Foundation Trust, Cambridge, UK." - }, - { - "author_name": "Nicholas J Ashton", - "author_inst": "Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, the Sahlgrenska Academy at the University of Gothenburg, Molndal, Sweden." - }, - { - "author_name": "Henrik Zetterberg", - "author_inst": "Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, the Sahlgrenska Academy at the University of Gothenburg, Molndal, Sweden; C" - }, - { - "author_name": "Magnus Gisslen", - "author_inst": "Department of Infectious Diseases, Institute of Biomedicine, the Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden; Region Vastra Gotaland" - }, - { - "author_name": "Eden Arvid", - "author_inst": "Department of Infectious Diseases, Institute of Biomedicine, the Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden; Region Vastra Gotaland" - }, - { - "author_name": "Emelie Marklund", - "author_inst": "Department of Infectious Diseases, Institute of Biomnedicine, the Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden; Region Vastra Gotalan" - }, - { - "author_name": "Michael J Griffiths", - "author_inst": "Institute of Infection, Veterinary & Ecological Sciences, University of Liverpool, Liverpool, UK." - }, - { - "author_name": "Jonathan Cavanagh", - "author_inst": "Centre for Immunobiology, Institute of Infection, Immunity and Inflammation, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, U" - }, - { - "author_name": "Gerome Breen", - "author_inst": "Department of Social Genetic and Developmental Psychiatry, King's College London, London, UK." - }, - { - "author_name": "Sarosh R Irani", - "author_inst": "Oxford Autoimmune Neurology Group, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK; Department of Neurology, Oxford University H" - }, - { - "author_name": "Anne Elmer", - "author_inst": "Cambridge Clinical Research Centre, NIHR Clinical Research Facility, Cambridge University Hospitals NHS Foundation Trust, Addenbrooke's Hospital, Cambridge, UK " - }, - { - "author_name": "Nathalie Kingston", - "author_inst": "NIHR BioResource, Cambridge University Hospitals NHS Foundation, Cambridge Biomedical Campus, Cambridge, UK." - }, - { - "author_name": "John R Bradley", - "author_inst": "NIHR BioResource, Cambridge University Hospitals NHS Foundation, Cambridge Biomedical Campus, Cambridge, UK; Department of Medicine, University of Cambridge, Ad" - }, - { - "author_name": "Leonie S Taams", - "author_inst": "Centre for Inflammation Biology and Cancer Immunology and Dept Inflammation Biology, School of Immunology and Microbial Sciences, Kings College London, Guys Cam" - }, - { - "author_name": "Benedict D michael", - "author_inst": "Clinical Infection Microbiology and Neuroimmunology, Institute of Infection, Veterinary and Ecological Science, Liverpool, UK." + "author_name": "Arnold Ikedichi Okpani", + "author_inst": "University of British Columbia, Vancouver, Canada" }, { - "author_name": "Edward T Bullmore", - "author_inst": "Department of Psychiatry, University of Cambridge, Herchel Smith Building for Brain and Mind Sciences, Cambridge Biomedical Campus, Cambridge, UK." + "author_name": "Stephen Barker", + "author_inst": "University of British Columbia, Vancouver, Canada" }, { - "author_name": "Kenneth GC Smith", - "author_inst": "Department of Medicine, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK; Cambridge Institute of Therapeutic Immunology and Infectious Disease, Je" + "author_name": "Karen Lockhart", + "author_inst": "University of British Columbia, Vancouver, Canada" }, { - "author_name": "Paul A Lyons", - "author_inst": "Department of Medicine, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK; Cambridge Institute of Therapeutic Immunology and Infectious Disease, Je" + "author_name": "Jennifer M. Grant", + "author_inst": "Department of Pathology and Laboratory Medicine, Vancouver Coastal Health (VCH), Vancouver, Canada" }, { - "author_name": "Alasdair JC Coles", - "author_inst": "Department of Clinical Neurosciences, University of Cambridge, UK" + "author_name": "Jorge Andres Delgado-Ron", + "author_inst": "University of British Columbia, Canada" }, { - "author_name": "David K Menon", - "author_inst": "Division of Anaesthesia, Department of Medicine, University of Cambridge, UK." + "author_name": "Muzimkhulu Zungu", + "author_inst": "National Institute for Occupational Health (NIOH), National Health Laboratory Service (NHLS), Johannesburg, South Africa" }, { - "author_name": "- Cambridge NeuroCOVID Group", - "author_inst": "" + "author_name": "Nisha Naicker", + "author_inst": "National Institute for Occupational Health (NIOH), National Health Laboratory Service (NHLS), Johannesburg, South Africa" }, { - "author_name": "- NIHR Cambridge Covid BioResource", - "author_inst": "" + "author_name": "Rodney Ehrlich", + "author_inst": "Department of Environmental Health, University of Johannesburg, Johannesburg, South Africa" }, { - "author_name": "- NIHR Cambridge Clinical Research Facility", - "author_inst": "" + "author_name": "Annalee Yassi", + "author_inst": "The University of British Columbia, Vancouver, Canada" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "neurology" + "category": "occupational and environmental health" }, { "rel_doi": "10.1101/2021.12.03.21267172", @@ -488323,47 +487742,23 @@ "category": "pediatrics" }, { - "rel_doi": "10.1101/2021.12.02.21267165", - "rel_title": "The Impact of COVID-19 on NO2 and PM2.5 Levels and Their Associations with Human Mobility Patterns in Singapore", + "rel_doi": "10.1101/2021.12.04.21267300", + "rel_title": "Price-performance comparison of HEPA air purifiers and lower-cost MERV 13/14 filters with box fans for filtering out SARS-Cov-2 and other particulate aerosols in indoor community settings", "rel_date": "2021-12-05", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.02.21267165", - "rel_abs": "The decline in NO2 and PM2.5 pollutant levels were observed during COVID-19 around the world, especially during lockdowns. Previous studies explained such observed decline with the decrease in human mobility, whilst overlooking the meteorological changes (e.g., rainfall, wind speed) that could mediate air pollution level simultaneously. This pitfall could potentially lead to over-or under-estimation of the effect of COVID-19 on air pollution. Consequently, this study aims to re-evaluate the impact of COVID-19 on NO2 and PM2.5 pollutant level in Singapore, by incorporating the effect of meteorological parameters in predicting NO2 and PM2.5 baseline in 2020 using machine learning methods. The results found that NO2 and PM2.5 declined by a maximum of 38% and 36%, respectively, during lockdown period. As two proxies for change in human mobility, taxi availability and carpark availability were found to increase and decrease by a maximum of 12.6% and 9.8%, respectively, in 2020 from 2019 during lockdown. To investigate how human mobility influenced air pollutant level, two correlation analyses were conducted: one between PM2.5 and carpark availability changes at regional scale and the other between NO2 and taxi availability changes at a spatial resolution of 0.01{degrees}. The NO2 variation was found to be more associated with the change in human mobility, with the correlation coefficients vary spatially across Singapore. A cluster of stronger correlations were found in the South and East Coast of Singapore. Contrarily, PM2.5 and carpark availability had a weak correlation, which could be due to the limit of regional analyses. Drawing to the wider context, the high association between human mobility and NO2 in the South and East Coast area can provide insights into future NO2 reduction policy in Singapore.\n\nGraphical Abstract\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=80 SRC=\"FIGDIR/small/21267165v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (29K):\norg.highwire.dtl.DTLVardef@1e0ea3aorg.highwire.dtl.DTLVardef@131be31org.highwire.dtl.DTLVardef@bda881org.highwire.dtl.DTLVardef@181dec5_HPS_FORMAT_FIGEXP M_FIG C_FIG", - "rel_num_authors": 7, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.04.21267300", + "rel_abs": "Public health departments such as CDC and California Department of Public Health (CA-DPH) advise HEPA-purifiers to limit transmission of SARS-CoV-2 indoor spaces. CA-DPH recommends air exchanges per hour (ACH) of 4-6 air for rooms with marginal ventilation and 6-12 in classrooms often necessitating multiple HEPA-purifiers per room, unaffordable in under-resourced community settings. Pressure to seek cheap, rapid air filtration resulted in proliferation of lower-cost, Do-It-Yourself (DIY) air purifiers whose performance is not well characterized compared to HEPA-purifiers. Primary metrics are clean air delivery rate (CADR), noise generated (dBA), and affordability ($$). CADR measurement often requires hard-to-replicate laboratory experiments with generated aerosols. We use simplified, low-cost measurement tools of ambient aerosols enabling scalable evaluation of aerosol filtration efficiencies (0.3 to 10 microns), estimated CADR, and noise generation to compare 3 HEPA-purifiers and 9 DIY purifier designs. DIY purifiers consist of one or two box fans coupled to single MERV 13-16 filters (1\"-5\" thick) or quad filters in a cube. Accounting for reduced filtration efficiency of MERV 13-16 filters (versus HEPA) at the most penetrating particle size of 0.3 microns, estimated CADR of DIY purifiers using 2\" (67%), 4\" (66%), and 5\" (85%) filters at lowest fan speed was 293 cfm ($35), 322 cfm ($58), and 405 cfm ($120) comparable to best-in-class, low-noise generating HEPA-purifier running at maximum speed with at 282 cfm ($549). Quad filter designs, popularly known Corsi-Rosenthal boxes, achieved gains in estimated CADR below 80% over single filter designs, less than the 100% gain by adding a second DIY purifier. Replacing one of the four filters with a second fan resulted in gains of 125%-150% in estimated CADR. Tested DIY alternatives using lower-efficiency, single filters compare favorably to tested HEPA-purifiers in estimated CADR, noise generated at five to ten times lower cost, enabling cheap, rapid aerosol removal indoors.", + "rel_num_authors": 1, "rel_authors": [ { - "author_name": "Yangyang Li", - "author_inst": "National University of Singapore" - }, - { - "author_name": "Yihan Zhu", - "author_inst": "National University of Singapore" - }, - { - "author_name": "Jia Yu Karen Tan", - "author_inst": "National University of Singapore" - }, - { - "author_name": "Hoong Chen Teo", - "author_inst": "National University of Singapore" - }, - { - "author_name": "Andrea Law", - "author_inst": "National University of Singapore" - }, - { - "author_name": "Dezhan Qu", - "author_inst": "Northeast Normal University" - }, - { - "author_name": "Wei Luo", - "author_inst": "National University of Singapore" + "author_name": "Devabhaktuni Srikrishna", + "author_inst": "Patient Knowhow, Inc." } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2021.12.01.21267115", @@ -490021,43 +489416,55 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.11.30.470550", - "rel_title": "Direct lysis RT-qPCR of SARS-CoV-2 in cell culture supernatant allows for fast and accurate quantification of virus, opening a vast array of applications", + "rel_doi": "10.1101/2021.11.30.470521", + "rel_title": "SARS-CoV-2 Delta derivatives impact on neutralization of Covishield recipient sera", "rel_date": "2021-12-02", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.11.30.470550", - "rel_abs": "An enormous global effort is being made to study SARS-CoV-2 and develop safe and effective treatments. Studying the entire virus replication cycle of SARS-CoV-2 is essential to identify host factors and treatments to combat the infection. However, quantification of released virus often requires lengthy procedures, such as endpoint dilution assays or reinfection with engineered reporter viruses. Quantification of viral RNA in cell supernatant is faster and can be performed on clinical isolates. However, viral RNA purification is expensive in time and resources and often unsuitable for high-throughput screening. Here, we show a direct lysis RT-qPCR method allowing sensitive, accurate, fast, and cheap quantification of SARS-CoV-2 in culture supernatant. During lysis, the virus is completely inactivated, allowing further processing in low containment areas. This protocol facilitates a wide array of high- and low-throughput applications from basic quantification to studying the biology of SARS-CoV-2 and to identify novel antiviral treatments in vitro.", - "rel_num_authors": 6, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.11.30.470521", + "rel_abs": "The emergence of SARS-CoV-2 Delta variant and its derivatives has created grave public health problem worldwide. The high transmissibility associated with this variant has led to daily increase in the number of SARS-CoV-2 infections. Delta variant has slowly dominated the other variants of concern. Subsequently, Delta has further mutated to Delta AY.1 to Delta AY.126. Of these, Delta AY.1 has been reported from several countries including India and considered to be highly infectious and probable escape mutant. Considering the possible immune escape, we had already evaluated the efficacy of the BBV152 against Delta and Delta AY.1 variants. Here, we have evaluated the neutralizing potential of sera of COVID-19 naive vaccinees (CNV) immunized with two doses of vaccine, COVID-19 recovered cases immunized with two doses of vaccine (CRV) and breakthrough infections (BTI) post immunization with two doses of vaccine against Delta, Delta AY.1 and B.1.617.3 using 50% plaque reduction neutralization test (PRNT50). Our study observed low NAb titer in CNV group against all the variants compared to CRV and BTI groups. Delta variant has shown highest reduction of 27.3-fold in NAb titer among CNV group compared to other groups and variants. Anti-S1-RBD IgG immune response among all the groups was also substantiated with NAb response. Compromised neutralization was observed against Delta and Delta AY.1 compared B.1 in all three groups. However, it provided protection against severity of the disease and fatality.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Nicky Craig", - "author_inst": "The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Easter Bush, Midlothian, UK" + "author_name": "Rima Sahay", + "author_inst": "Indian Council of Medical Research-National Institute of Virology, Pune, Maharashtra, India, Pin-411021" }, { - "author_name": "Sarah Louise Fletcher", - "author_inst": "The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Easter Bush, Midlothian, UK" + "author_name": "Deepak Y Patil", + "author_inst": "Indian Council of Medical Research-National Institute of Virology, Pune, Maharashtra, India, Pin-411021" }, { - "author_name": "Alison Daniels", - "author_inst": "The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Easter Bush, Midlothian, UK & Division of Infection Medicine, Unive" + "author_name": "Gajanan N Sapkal", + "author_inst": "Indian Council of Medical Research-National Institute of Virology, Pune, Maharashtra, India, Pin-411021" + }, + { + "author_name": "Gururaj R Deshpande", + "author_inst": "Indian Council of Medical Research-National Institute of Virology, Pune, Maharashtra, India, Pin-411021" }, { - "author_name": "Caitlin Newman", - "author_inst": "The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Easter Bush, Midlothian, UK" + "author_name": "Anita M Shete", + "author_inst": "Indian Council of Medical Research-National Institute of Virology, Pune, Maharashtra, India, Pin-411021" }, { - "author_name": "Amanda Warr", - "author_inst": "The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Easter Bush, Midlothian, UK" + "author_name": "Dimpal Nyayanit", + "author_inst": "Indian Council of Medical Research-National Institute of Virology, Pune, Maharashtra, India, Pin-411021" }, { - "author_name": "Christine Tait-Burkard", - "author_inst": "The University Of Edinburgh" + "author_name": "Sanjay Kumar", + "author_inst": "Department of Neurosurgery, AMC, Pune, India 411040" + }, + { + "author_name": "Shanta Dutta", + "author_inst": "ICMR-NICED, Kolkatta, India - 700010" + }, + { + "author_name": "Pragya D Yadav", + "author_inst": "Indian Council of Medical Research-National Institute of Virology, Pune, Maharashtra, India, Pin-411021" } ], "version": "1", "license": "cc_by_nc_nd", "type": "new results", - "category": "microbiology" + "category": "molecular biology" }, { "rel_doi": "10.1101/2021.11.30.21266810", @@ -491539,127 +490946,39 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2021.11.30.21266756", - "rel_title": "Association of subcutaneous or intravenous route of administration of casirivimab and imdevimab monoclonal antibodies with clinical outcomes in COVID-19.", + "rel_doi": "10.1101/2021.11.30.470470", + "rel_title": "SARS-CoV-2 variants impact RBD conformational dynamics and ACE2 accessibility", "rel_date": "2021-12-01", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.30.21266756", - "rel_abs": "ImportanceMonoclonal antibody (mAb) treatment decreases hospitalization and death in outpatients with mild to moderate COVID-19; however, only intravenous administration has been evaluated in randomized clinical trials of treatment. Subcutaneous administration may expand outpatient treatment capacity and qualified staff available to administer treatment, but association with patient outcomes is understudied.\n\nObjectiveTo evaluate whether or not, i.) subcutaneous casirivimab and imdevimab treatment is associated with reduced 28-day hospitalization/death than non-treatment among mAb-eligible patients, and ii.) subcutaneous casirivimab and imdevimab treatment is clinically and statistically similar to intravenous casirivimab and imdevimab treatment.\n\nDesign, Setting, and ParticipantsProspective cohort study of outpatients in a learning health system in the United States with mild to moderate COVID-19 symptoms from July 14 to October 26, 2021 who were eligible for mAb treatment under emergency use authorization. A nontreated control group of eligible patients was also selected.\n\nInterventionSubcutaneous injection or intravenous administration of the combined single dose of casirivimab 600mg and imdevimab 600mg.\n\nMain Outcomes and MeasuresThe primary outcome was the 28-day adjusted risk ratio or adjusted risk difference for hospitalization or death. Secondary outcomes included 28-day adjusted risk ratios/differences of hospitalization, death, composite endpoint of ED admission and hospitalization, and rates of adverse events.\n\nResultsAmong 1,956 matched adults with mild to moderate COVID-19, patients who received casirivimab and imdevimab subcutaneously had a 28-day rate of hospitalization/death of 3.4% (n=652) compared to 7.8% (n=1,304) in nontreated controls [risk ratio 0.44 (95% confidence interval: 0.28 to 0.68, p < .001)]. Among 2,185 patients treated with subcutaneous (n=969) or intravenous (n=1,216) casirivimab and imdevimab, the 28-day rate of hospitalization/death was 2.8% vs. 1.7%, respectively which resulted in an adjusted risk difference of 1.5% (95% confidence interval: -0.5% to 3.5%, p=.14). The 28-day adjusted risk differences (subcutaneous - intravenous) for death, ICU admission, and mechanical ventilation were 0.3% or less, although the 95% confidence intervals were wide.\n\nConclusions and RelevanceSubcutaneously administered casirivimab-imdevimab is associated with reduced risk-adjusted hospitalization or death amongst outpatients with mild to moderate COVID-19 compared to no treatment and indicates low adjusted risk difference compared to patients treated intravenously.\n\nKey PointsO_ST_ABSQuestionC_ST_ABSAmong outpatients with mild to moderate COVID-19, is subcutaneously administered casirivimab and imdevimab associated with improved risk-adjusted 28-day clinical outcomes compared to non-treatment with monoclonal antibodies, and clinically similar association compared to intravenously administered casirivimab and imdevimab?\n\nFindingsAmong 1,956 propensity-matched adults, outpatients who received casirivimab and imdevimab subcutaneously had a 28-day rate of hospitalization or death of 3.4% (n=652) compared to 7.8% (n=1,304) in non-treated controls [risk ratio 0.44 (95% confidence interval: 0.28 to 0.68, p < .001)]. Among 2,185 outpatients who received subcutaneous (n=969) or intravenous (n=1,216) casirivimab and imdevimab, the 28-day rate of hospitalization/death was 2.8% vs. 1.7%, respectively, which resulted in an adjusted risk difference of 1.5% (95% confidence interval: -0.5% to 3.5%, p=.14). The 28-day adjusted risk differences comparing subcutaneous to intravenous route for death, ICU admission, and mechanical ventilation were 0.3% or less, although the 95% confidence intervals were wide.\n\nMeaningSubcutaneously administered casirivimab and imdevimab is associated with reduced hospitalization or death amongst outpatients with mild to moderate COVID-19 compared to no treatment, and has a small, adjusted risk difference compared to patients treated intravenously.", - "rel_num_authors": 27, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2021.11.30.470470", + "rel_abs": "The coronavirus disease 2019 (COVID-19) pandemic, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has killed over 5 million people and is causing a devastating social and economic impact all over the world. The rise of new variants of concern (VOCs) represents a difficult challenge due to the loss vaccine and natural immunity, and increased transmissibility. All circulating VOCs contain mutations in the spike glycoprotein, which mediates fusion between the viral and host cell membranes, via its receptor binding domain (RBD) that binds to angiotensin-converting enzyme 2 (ACE2). In an attempt to understand the effect of RBD mutations in circulating VOCs, a lot of attention has been given to the RBD-ACE2 interaction. However, this type of analysis is limited, since it ignores more indirect effects, such as the conformational dynamics of the RBD itself. Observing that some VOCs mutations occur in residues that are not in direct contact with ACE2, we hypothesized that they could affect RBD conformational dynamics. To test this, we performed long atomistic (AA) molecular dynamics (MD) simulations to investigate the structural dynamics of wt RBD, and that of three circulating VOCs (alpha, beta, and delta). Our results show that in solution, wt RBD presents two distinct conformations: an \"open\" conformation where it is free to bind ACE2; and a \"closed\" conformation, where the RBM ridge blocks the binding surface. The alpha and beta variants significantly impact the open/closed equilibrium, shifting it towards the open conformation by roughly 20%. This shift likely increases ACE2 binding affinity. Simulations of the currently predominant delta variant RBD were extreme in this regard, in that a closed conformation was never observed. Instead, the system alternated between the before mentioned open conformation and an alternative \"reversed\" one, with a significantly changed orientation of the RBM ridge flanking the RBD. This alternate conformation could potentially provide a fitness advantage not only due to increased availability for ACE2 binding, but also by aiding antibody escape through epitope occlusion. These results support the hypothesis that VOCs, and particularly the delta variant, impact RBD conformational dynamics in a direction that simultaneously promotes efficient binding to ACE2 and antibody escape.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Erin K. McCreary", - "author_inst": "University of Pittsburgh School of Medicine" - }, - { - "author_name": "J. Ryan Bariola", - "author_inst": "University of Pittsburgh School of Medicine" - }, - { - "author_name": "Richard J. Wadas", - "author_inst": "University of Pittsburgh School of Medicine" - }, - { - "author_name": "Judith A. Shovel", - "author_inst": "University of Pittsburgh Medical Center" - }, - { - "author_name": "Mary K. Wisniewski", - "author_inst": "University of Pittsburgh Medical Center" - }, - { - "author_name": "Michelle Adam", - "author_inst": "University of Pittsburgh Medical Center" - }, - { - "author_name": "Debbie Albin", - "author_inst": "University of Pittsburgh Medical Center" - }, - { - "author_name": "Tami E. Minnier", - "author_inst": "University of Pittsburgh Medical Center" - }, - { - "author_name": "Mark Schmidhofer", - "author_inst": "University of Pittsburgh School of Medicine" - }, - { - "author_name": "Russell Meyers", - "author_inst": "University of Pittsburgh School of Medicine" - }, - { - "author_name": "Oscar C. Marroquin", - "author_inst": "University of Pittsburgh Medical Center" - }, - { - "author_name": "Kevin Collins", - "author_inst": "University of Pittsburgh Medical Center" - }, - { - "author_name": "William Garrard", - "author_inst": "University of Pittsburgh Medical Center" - }, - { - "author_name": "Lindsay R. Berrry", - "author_inst": "Berry Consultants, LLC" - }, - { - "author_name": "Scott Berry", - "author_inst": "Berry Consultants, LLC" - }, - { - "author_name": "Amy M. Crawford", - "author_inst": "Berry Consultants, LLC" - }, - { - "author_name": "Anna McGlothlin", - "author_inst": "Berry Consultants, LLC" - }, - { - "author_name": "Kelsey Linstrum", - "author_inst": "University of Pittsburgh Medical Center" - }, - { - "author_name": "Anna Nakayama", - "author_inst": "University of Pittsburgh Medical Center" - }, - { - "author_name": "Stephanie K. Montgomery", - "author_inst": "University of Pittsburgh Medical Center" - }, - { - "author_name": "Graham M. Snyder", - "author_inst": "University of Pittsburgh Medical Center" + "author_name": "Mariana Fidalgo Valerio", + "author_inst": "Instituto de Tecnologia Quimica e Biologica Antonio Xavier, Universidade Nova de Lisboa, Oeiras 2780-157, Portugal" }, { - "author_name": "Donald M. Yealy", - "author_inst": "University of Pittsburgh School of Medicine" + "author_name": "Luis Borges-Araujo", + "author_inst": "iBB-Institute for Bioengineering and Biosciences, Instituto Superior Tecnico, Universidade de Lisboa, Lisbon, Portugal" }, { - "author_name": "Derek C. Angus", - "author_inst": "University of Pittsburgh Medical Center" + "author_name": "Manuel N. Melo", + "author_inst": "Instituto de Tecnologia Quimica e Biologica Antonio Xavier, Universidade Nova de Lisboa, Oeiras 2780-157, Portugal" }, { - "author_name": "Paula L. Kip", - "author_inst": "University of Pittsburgh Medical Center" - }, - { - "author_name": "Christopher W. Seymour", - "author_inst": "University of Pittsburgh School of Medicine" - }, - { - "author_name": "David T. Huang", - "author_inst": "University of Pittsburgh School of Medicine" + "author_name": "Diana Lousa", + "author_inst": "Instituto de Tecnologia Quimica e Biologica Antonio Xavier, Universidade Nova de Lisboa, Oeiras 2780-157, Portugal" }, { - "author_name": "Kevin E. Kip", - "author_inst": "University of Pittsburgh Medical Center" + "author_name": "Claudio M. Soares", + "author_inst": "Instituto de Tecnologia Quimica e Biologica Antonio Xavier, Universidade Nova de Lisboa, Oeiras 2780-157, Portugal" } ], "version": "1", "license": "cc_by_nc_nd", - "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "type": "new results", + "category": "biophysics" }, { "rel_doi": "10.1101/2021.11.30.470568", @@ -493909,57 +493228,21 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2021.11.30.21266889", - "rel_title": "Normalisation of SARS-CoV-2 concentrations in wastewater: the use of flow, conductivity and CrAssphages", + "rel_doi": "10.1101/2021.11.29.21267004", + "rel_title": "Phase Shift Between Age-Specific COVID-19 Incidence Curves Points to a Potential Epidemic Driver Function of Kids and Juveniles in Germany", "rel_date": "2021-11-30", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.30.21266889", - "rel_abs": "Over the course of the COVID-19 pandemic in 2020-2021, monitoring of SARS-CoV-2 RNA in wastewater has rapidly evolved into a supplementary surveillance instrument for public health. Short term trends (2 weeks) are used as a basis for policy and decision making on measures for dealing with the pandemic. Normalization is required to account for the varying dilution rates of the domestic wastewater, that contains the shedded virus RNA. The dilution rate varies due to runoff, industrial discharges and extraneous waters. Three normalization methods using flow, conductivity and CrAssphage, have been investigated on 9 monitoring locations between Sep 2020 and Aug 2021, rendering 1071 24-hour flow-proportional samples. In addition, 221 stool samples have been analyzed to determine the daily CrAssphage load per person. Results show that flow normalization supported by a quality check using conductivity monitoring is the advocated normalization method in case flow monitoring is or can be made available. Although Crassphage shedding rates per person vary greatly, the CrAssphage loads were very consistent over time and space and direct CrAssphage based normalization can be applied reliably for populations of 5600 and above.", - "rel_num_authors": 10, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.29.21267004", + "rel_abs": "Mutual phase shifts between three German COVID-19 incidence curves corresponding to the age classes of children, juveniles and adults, respectively, are calculated by means of delay-cross-correlations. At the country level, a phase shift of -5 weeks during the first half of the epidemic between the incidence curves corresponding to the juvenile age class and the curve corresponding to the adult class is observed. The childrens incidence curve is shifted by -3 weeks with respect to the adults curve. On the regional level of the 411 German districts (Landkreise) the distributions of observed time lags are inclined towards negative values. Regarding the incidence time series of the juvenile sub-population, 20% of the German districts exhibit negative phase shifts and only 3% show positive shifts versus the incidence curves of the adult sub-population. Similarly for the children with 6% positive shifts. Thus, childrens and juveniles epidemic activity is ahead of the adults activity. The correlation coefficients of shifted curves are large (> 0.9 for juveniles versus adults on the country level) which indicates that aside from the phase shift the sub-populations follow a similar epidemic dynamics. Negative phase shifts of the childrens incidence curves during the first and second epidemic waves are predictors for high incidences during the current fourth wave with respect to the corresponding districts.", + "rel_num_authors": 1, "rel_authors": [ { - "author_name": "Jeroen Langeveld", - "author_inst": "TU Delft" - }, - { - "author_name": "Remy Schilperoort", - "author_inst": "partners4urbanwater" - }, - { - "author_name": "Leo Heijnen", - "author_inst": "KWR, Water Research Institute" - }, - { - "author_name": "goffe elsinga", - "author_inst": "kwr water research institute" - }, - { - "author_name": "claudia schapendonk", - "author_inst": "Erasmus MC" - }, - { - "author_name": "ewout fanoy", - "author_inst": "GGD Rotterdam" - }, - { - "author_name": "evelien de schepper", - "author_inst": "erasmus MC" - }, - { - "author_name": "Marion Koopmans", - "author_inst": "Erasmus Medical Center" - }, - { - "author_name": "Miranda de Graaf", - "author_inst": "Erasmus MC" - }, - { - "author_name": "Gertjan Medema", - "author_inst": "KWR Water Research Institute" + "author_name": "Hans H. Diebner", + "author_inst": "Ruhr-University Bochum, Germany" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -495543,53 +494826,117 @@ "category": "genetic and genomic medicine" }, { - "rel_doi": "10.1101/2021.11.26.21266918", - "rel_title": "DEVELOPMENT AND TESTING OF A LOW-COST INACTIVATION BUFFER THAT ALLOWS DIRECT SARS-COV-2 DETECTION IN SALIVA", + "rel_doi": "10.1101/2021.11.25.21266298", + "rel_title": "Management and containment of a SARS-CoV-2 Beta variant outbreak at the Malawi University of Science and Technology", "rel_date": "2021-11-28", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.26.21266918", - "rel_abs": "Massive testing is a cornerstone in efforts to effectively track infections and stop COVID-19 transmission, including places where good vaccination coverage has been achieved. However, SARS-CoV-2 testing by RT-qPCR requires specialized personnel, protection equipment, commercial kits, and dedicated facilities, which represent significant challenges for massive testing implementation in resource-limited settings. It is therefore important to develop testing protocols that facilitate implementation and are inexpensive, fast, and sufficiently sensitive. In this work, we optimized the composition of a buffer (PKTP) containing a protease, a detergent, and an RNase inhibitor, that is compatible with the RT-qPCR chemistry, allowing for direct testing of SARS-CoV-2 from saliva in an RNA extraction-independent manner. This buffer is compatible with heat-inactivation reducing the biohazard risk of handling the samples. We assessed the PKTP buffer performance in comparison to the RNA-extraction-based protocol of the US Centers for Disease Control and Prevention in saliva samples from 70 COVID-19 patients finding a good sensitivity (82.2% for the N1 and 84.4% for the N2 target, respectively) and correlations (R=0.77, p<0.001 for N1, and R=0.78, p<0.001 for N2). We also propose an auto-collection protocol for saliva samples and a multiplex reaction to reduce the number of PCR reactions per patient and further reduce overall costs while maintaining diagnostic standards in favor of massive testing.", - "rel_num_authors": 9, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.25.21266298", + "rel_abs": "Outbreaks of COVID at university campuses can spread rapidly and threaten the broader community. We describe the management of an outbreak at a Malawian university in April-May 2021 during Malawis second wave. Classes were suspended following detection of infections by routine testing and campus-wide PCR mass testing was conducted. Fifty seven cases were recorded, 55 among students, two among staff. Classes resumed 28 days after suspension following two weeks without cases. Just 6.3% of full-time staff and 87.4% of outsourced staff tested while 65% of students at the main campus and 74% at the extension campus were tested. Final year students had significantly higher positivity and lower testing coverage compared to freshmen. All viruses sequenced were beta variant and at least four separate virus introductions onto campus were observed. These findings are useful for development of campus outbreak responses and indicate the need to emphasize staff, males and senior students in testing.\n\nArticle Summary LineSuccessful management of a campus outbreak using test trace and isolate approach with resumption within a month following suspension of all in-person classes. Trends in voluntary testing by gender, age and year of study that can help in formation of future management approaches.", + "rel_num_authors": 25, "rel_authors": [ { - "author_name": "Brandon Bustos-Garcia", - "author_inst": "Institute of Cellular Physiology (IFC), National Autonomous University of Mexico (UNAM)" + "author_name": "Gama Petulo Bandawe", + "author_inst": "Malawi University of Science and Technology" }, { - "author_name": "Sylvia Garza-Manero", - "author_inst": "Institute of Cellular Physiology (IFC), National Autonomous University of Mexico (UNAM)" + "author_name": "Petros Chigwechokha", + "author_inst": "Malawi University of Science and Technology" }, { - "author_name": "Nallely Cano-Dominguez", - "author_inst": "Institute of Cellular Physiology (IFC), National Autonomous University of Mexico" + "author_name": "Precious Kunyenje", + "author_inst": "Malawi University of Science and Technology" }, { - "author_name": "Dulce Maria Lopez Sanchez", - "author_inst": "Centre for Research in Infectious Diseases of the National Institute of Respiratory Diseases (CIENI/INER)" + "author_name": "Yohane Kazembe", + "author_inst": "Malawi University of Science and Technology" }, { - "author_name": "Gonzalo Salgado-Montes de Oca", - "author_inst": "Centre for Research in Infectious Diseases of the National Institute of Respiratory Diseases (CIENI/INER)" + "author_name": "Jeverson Mwale", + "author_inst": "Malawi University of Science and Technology" }, { - "author_name": "Alfonso Salgado-Aguayo", - "author_inst": "Centre for Research in Infectious Diseases of the National Institute of Respiratory Diseases (CIENI/INER)" + "author_name": "Maladalitso Kamaliza", + "author_inst": "Malawi University of Science and Technology" }, { - "author_name": "Felix Recillas-Targa", - "author_inst": "Institute of Cellular Physiology (IFC), National Autonomous University of Mexico" + "author_name": "Mtisunge Mpakati", + "author_inst": "Malawi University of Science and Technology" }, { - "author_name": "Santiago Avila-Rios", - "author_inst": "National Institute of Respiratory Diseases" + "author_name": "Yanjanani Nyakanyaka", + "author_inst": "Malawi University of Science and Technology" + }, + { + "author_name": "Charles Makamo", + "author_inst": "Malawi University of Science and Technology" + }, + { + "author_name": "Saizi Kimu", + "author_inst": "Malawi University of Science and Technology" + }, + { + "author_name": "Mwayiwawo Madanitsa", + "author_inst": "Malawi University of Science and Technology" + }, + { + "author_name": "Joseph Bitilinyu-Bangoh", + "author_inst": "Ministry of Health, Malawi" + }, + { + "author_name": "Tonney Nyirenda", + "author_inst": "Kamuzu University of Health Sciences" + }, + { + "author_name": "Richard Luhanga", + "author_inst": "DREAM Molecular Laboratory, Blantyre, Malawi" + }, + { + "author_name": "Martha Sambani", + "author_inst": "Malawi University of Science and Technology" + }, + { + "author_name": "Bernard Mvula", + "author_inst": "Public Health Institute of Malawi" + }, + { + "author_name": "Jennifer Giandhari", + "author_inst": "University of KwaZulu-Natal, Durban, South Africa" + }, + { + "author_name": "Sureshnee Pillay", + "author_inst": "University of KwaZulu-Natal, Durban, South Africa" + }, + { + "author_name": "Yashnee Naidoo", + "author_inst": "University Of KwaZulu-Natal, Durban, South Africa" + }, + { + "author_name": "Upasana Ramphal", + "author_inst": "University of KwaZulu-Natal, Durban, South Africa" }, { - "author_name": "Julian Valdes", - "author_inst": "Institute of Cellular Physiology (IFC), National Autonomous University of Mexico" + "author_name": "Emmanuel James San", + "author_inst": "University of KwaZulu-Natal, Durban, South Africa" + }, + { + "author_name": "Houriiyah Tegally", + "author_inst": "University of KwaZulu-Natal, Durban, South Africa" + }, + { + "author_name": "Eduan Wilkinson", + "author_inst": "University of KwaZulu-Natal, Durban, South Africa" + }, + { + "author_name": "Tulio de Oliveira", + "author_inst": "University of KwaZulu-Natal" + }, + { + "author_name": "Address Malata", + "author_inst": "Malawi University of Science and Technology" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -497349,51 +496696,35 @@ "category": "nephrology" }, { - "rel_doi": "10.1101/2021.11.23.21266761", - "rel_title": "Higher Limbic and Basal Ganglia volumes in surviving COVID-negative patients and the relations to fatigue.", + "rel_doi": "10.1101/2021.11.22.21266712", + "rel_title": "Human phospho-signaling networks of SARS-CoV-2 infection are rewired by population genetic variants", "rel_date": "2021-11-24", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.23.21266761", - "rel_abs": "BackgroundAmong systemic abnormalities caused by the novel coronavirus, little is known about the critical attack on the central nervous system (CNS). Few studies have shown cerebrovascular pathologies that indicate CNS involvement in acute patients. However, replication studies are necessary to verify if these effects persist in COVID-19 survivors more conclusively. Furthermore, recent studies indicate fatigue is highly prevalent among long-COVID patients. How morphometry in each group relate to work-related fatigue need to be investigated.\n\nMethodCOVID survivors were MRI scanned two weeks after hospital discharge. We hypothesized, these survivors will demonstrate altered gray matter volume (GMV) and experience higher fatigue levels when compared to healthy controls, leading to stronger correlation of GMV with fatigue. Voxel-based morphometry was performed on T1-weighted MRI images between 46 survivors and 30 controls. Unpaired two-sample t-test and multiple linear regression were performed to observe group differences and correlation of fatigue with GMV.\n\nResultsThe COVID group experienced significantly higher fatigue levels and GMV of this group was significantly higher within the Limbic System and Basal Ganglia when compared to healthy controls. Moreover, while a significant positive correlation was observed across the whole group between GMV and self-reported fatigue, COVID subjects showed stronger effects within the Posterior Cingulate, Precuneus and Superior Parietal Lobule.\n\nConclusionBrain regions with GMV alterations in our analysis align with both single case acute patient reports and current group level neuroimaging findings. We also newly report a stronger positive correlation of GMV with fatigue among COVID survivors within brain regions associated with fatigue, indicating a link between structural abnormality and brain function in this cohort.", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.22.21266712", + "rel_abs": "SARS-CoV-2 infection hijacks signaling pathways and induces protein-protein interactions between human and viral proteins. Human genetic variation may impact SARS-CoV-2 infection and COVID-19 pathology; however, the role of genetic variation in these signaling networks remains uncharacterized. We studied human single nucleotide variants (SNVs) affecting phosphorylation sites modulated by SARS-CoV-2 infection, using machine learning to identify amino acid changes altering kinase-bound sequence motifs. We found 2033 infrequent phosphorylation-associated SNVs (pSNVs) that are enriched in sequence motif alterations, potentially reflecting the evolution of signaling networks regulating host defenses. Proteins with pSNVs are involved in viral life cycle processes and host responses, including regulators of RNA splicing and interferon response, as well as glucose homeostasis pathways with potential associations with COVID-19 co-morbidities. Certain pSNVs disrupt CDK and MAPK substrate motifs and replace these with motifs recognized by Tank Binding Kinase 1 (TBK1) involved in innate immune responses, indicating consistent rewiring of infection signaling networks. Our analysis highlights potential genetic factors contributing to the variation of SARS-CoV-2 infection and COVID-19 and suggests leads for mechanistic and translational studies.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Rakibul Hafiz", - "author_inst": "New Jersey Institute of Technology" - }, - { - "author_name": "Tapan Kumar Gandhi", - "author_inst": "Indian Institute of Technology (IIT), Delhi, India" - }, - { - "author_name": "Sapna Mishra", - "author_inst": "Indian Institute of Technology (IIT), Delhi, India" - }, - { - "author_name": "Alok Prasad", - "author_inst": "Metro Heart Institute With Multispecialty" - }, - { - "author_name": "Vidur Mahajan", - "author_inst": "Indian Institute of Technology (IIT), Delhi, India" + "author_name": "Diogo Pellegrina", + "author_inst": "Ontario Institute for Cancer Research" }, { - "author_name": "Xin Di", - "author_inst": "New Jersey Institute of Technology (NJIT)" + "author_name": "Alexander T Bahcheli", + "author_inst": "University of Toronto" }, { - "author_name": "Benjamin H. Natelson", - "author_inst": "Icahn School of Medicine at Mount Sinai, Mount Sinai Hospital" + "author_name": "Michal Krassowski", + "author_inst": "University of Oxford" }, { - "author_name": "Bharat B. Biswal", - "author_inst": "New Jersey Institute of Technology (NJIT)" + "author_name": "J\u00fcri Reimand", + "author_inst": "University of Toronto" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "neurology" + "category": "genetic and genomic medicine" }, { "rel_doi": "10.1101/2021.11.23.21266747", @@ -499259,35 +498590,27 @@ "category": "molecular biology" }, { - "rel_doi": "10.1101/2021.11.24.21266779", - "rel_title": "Severe COVID-19 induces molecular signatures of aging in the human brain", + "rel_doi": "10.1101/2021.11.24.21266741", + "rel_title": "A genome-wide association study of COVID-19 related hospitalization in Spain reveals genetic disparities among sexes", "rel_date": "2021-11-24", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.24.21266779", - "rel_abs": "Coronavirus disease 2019 (COVID-19) is predominantly an acute respiratory disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and remains a significant threat to public health. COVID-19 is accompanied by neurological symptoms and cognitive decline, but the molecular mechanisms underlying this effect remain unclear. As aging induces distinct molecular signatures in the brain associated with cognitive decline in healthy populations, we hypothesized that COVID-19 may induce molecular signatures of aging. Here, we performed whole transcriptomic analysis of human frontal cortex, a critical area for cognitive function, in 12 COVID-19 cases and age- and sex-matched uninfected controls. COVID-19 induces profound changes in gene expression, despite the absence of detectable virus in brain tissue. Pathway analysis shows downregulation of genes involved in synaptic function and cognition and upregulation of genes involved in immune processes. Comparison with five independent transcriptomic datasets of aging human frontal cortex reveals striking similarities between aged individuals and severe COVID-19 patients. Critically, individuals below 65 years of age exhibit profound transcriptomic changes not observed among older individuals in our patient cohort. Our data indicate that severe COVID-19 induces molecular signatures of aging in the human brain and emphasize the value of neurological follow-up in recovered individuals.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.24.21266741", + "rel_abs": "AbstractWe describe the results of the Spanish Coalition to Unlock Research on Host Genetics on COVID-19 (SCOURGE). In sex-disaggregated genome-wide studies of COVID-19 hospitalization, we found two known loci associated among males (SLC6A20-LZTFL1 and IFNAR2), and a novel one among females (TLE1). Meta-analyses with independent studies revealed two novel associations (AQP3 and ARHGAP33) and replicated ELF5. A genetic risk score predicted COVID-19 severity, especially among younger males. We found less SNP-heritability and larger heritability differences by age (<60/[≥]60 years) among males than females. Inbreeding depression was associated with COVID-19 hospitalization and severity, and the effect was stronger among older males.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Maria Mavrikaki", - "author_inst": "Beth Israel Deaconess Medical Center, Harvard Medical School" - }, - { - "author_name": "Jonathan D. Lee", - "author_inst": "Beth Israel Deaconess Medical Center, Harvard Medical School" - }, - { - "author_name": "Isaac H. Solomon", - "author_inst": "Brigham and Women's Hospital, Harvard Medical School" + "author_name": "- Spanish COalition to Unlock Research on host GEnetics on COVID-19 (SCOURGE)", + "author_inst": "" }, { - "author_name": "Frank J. Slack", - "author_inst": "Beth Israel Deaconess Medical Center, Harvard Medical School" + "author_name": "Angel Carracedo", + "author_inst": "University of Santiago de Compostela" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "neurology" + "category": "genetic and genomic medicine" }, { "rel_doi": "10.1101/2021.11.23.21266767", @@ -501229,35 +500552,43 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2021.11.18.469065", - "rel_title": "Immune escape facilitation by mutations of epitope residues in RdRp of SARS-CoV-2", + "rel_doi": "10.1101/2021.11.19.469335", + "rel_title": "Acute SARS-CoV-2 infection in pregnancy is associated with placental ACE-2 shedding", "rel_date": "2021-11-22", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.11.18.469065", - "rel_abs": "SARS-CoV-2 has considerably higher mutation rate. SARS-CoV-2 possesses a RNA dependent RNA polymerase (RdRp) which helps to replicate its genome. The mutation P323L in RdRp is associated with the loss of a particular epitope (321-327) from this protein which may influence the pathogenesis of the concern SARS-CoV-2 through the development of antibody escape variants. We consider the effect of mutations in some of the epitope regions including the naturally occurring mutation P323L on the structure of the epitope and their interface with paratope using all-atom molecular dynamics (MD) simulation studies. P323L mutations cause conformational changes in the epitope region by opening up the region associated with increase in the radius of gyration and intramolecular hydrogen bonds, making the region less accessible. Moreover, the fluctuations in the dihedral angles in the epitope:paratope (IgG) interface increase which destabilize the interface. Such mutations may help in escaping antibody mediated immunity of the host.", - "rel_num_authors": 4, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.11.19.469335", + "rel_abs": "Human placental tissues have variable rates of SARS-CoV-2 invasion resulting in consistently low rates of fetal transmission suggesting a unique physiologic blockade against SARS-CoV-2. Angiotensin-converting enzyme (ACE)-2, the main receptor for SARS-CoV-2, is expressed as cell surface and soluble forms regulated by a metalloprotease cleavage enzyme, ADAM17. ACE-2 is expressed in the human placenta, but the regulation of placental ACE-2 expression in relation to timing of maternal SARS-CoV-2 infection in pregnancy is not well understood. In this study, we evaluated ACE-2 expression, ADAM17 activity and serum ACE-2 abundance in a cohort of matched villous placental and maternal serum samples from Control pregnancies (SARS-CoV-2 negative, n=8) and pregnancies affected by symptomatic maternal SARS-CoV-2 infections in the 2nd trimester (\"2ndTri COVID\", n=8) and 3rd trimester (\"3rdTri COVID\", n=8). In 3rdTri COVID as compared to control and 2ndTri-COVID villous placental tissues ACE-2 mRNA expression was remarkably elevated, however, ACE-2 protein expression was significantly decreased with a parallel increase in ADAM17 activity. Soluble ACE-2 was also significantly increased in the maternal serum from 3rdTri COVID infections as compared to control and 2ndTri-COVID pregnancies. These data suggest that in acute maternal SARS-CoV-2 infections, decreased placental ACE-2 protein may be the result of ACE-2 shedding. Overall, this work highlights the importance of ACE-2 for ongoing studies on SARS-CoV-2 responses at the maternal-fetal interface.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Aayatti Mallick Gupta", - "author_inst": "S N Bose National Centre for Basic Sciences" + "author_name": "Elizabeth S Taglauer", + "author_inst": "Department of Pediatrics, Boston University School of Medicine" }, { - "author_name": "Sasthi Charan Mandal", - "author_inst": "S N Bose National Centre for Basic Sciences" + "author_name": "Elisha M Wachman", + "author_inst": "Department of Pediatrics, Boston University School of Medicine" }, { - "author_name": "Jaydeb Chakrabarti", - "author_inst": "S N Bose National Centre for Basic Sciences" + "author_name": "Qiong Wang", + "author_inst": "Department of Surgery, Johns Hopkins University School of Medicine" }, { - "author_name": "Sukhendu Mandal", - "author_inst": "University of Calcutta" + "author_name": "Asuka Ishiyama", + "author_inst": "Department of Surgery, Johns Hopkins University School of Medicine" + }, + { + "author_name": "David J Hackam", + "author_inst": "Department of Surgery, Johns Hopkins University School of Medicine" + }, + { + "author_name": "Hongpeng Jia", + "author_inst": "Department of Surgery, Johns Hopkins University School of Medicine" } ], "version": "1", "license": "cc_no", "type": "new results", - "category": "bioinformatics" + "category": "pathology" }, { "rel_doi": "10.1101/2021.11.19.469276", @@ -502787,63 +502118,43 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.11.17.21266473", - "rel_title": "ROLE OF BODY MASS AND PHYSICAL ACTIVITY IN AUTONOMIC FUNCTION MODULATION ON POST-COVID-19 CONDITION: AN OBSERVATIONAL SUBANALYSIS OF FIT-COVID STUDY", + "rel_doi": "10.1101/2021.11.19.468693", + "rel_title": "The Effect of COVID-19 on the Postdoctoral Experience: a comparison of pre-pandemic and pandemic surveys.", "rel_date": "2021-11-21", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.17.21266473", - "rel_abs": "The harmful effects of coronavirus disease 2019 (COVID-19) can reach the autonomic nervous system (ANS) and endothelial function. Therefore, the detrimental multiorgan effects of COVID-19 could be induced by deregulations in ANS that may persist after the acute SARS-CoV-2 infection. Additionally, investigating the differences in ANS response in overweight/obese, and physically inactive participants who had COVID-19 compared to those who did not have the disease is necessary. The aim of the study was to analyze the autonomic function of young adults after mild-to-moderate infection with COVID-19 and to assess whether body mass index (BMI) and levels of physical activity modulates autonomic function in participants with and without COVID-19. Patients previously infected with COVID-19 and healthy controls were recruited for this cross-sectional observational study. A general anamnesis was taken and BMI and physical activity levels were assessed. The ANS was evaluated through heart rate variability. A total of 57 subjects were evaluated. Sympathetic nervous system activity in post-COVID-19 group was increased (stress index; p=0.0273). They also presented lower values of parasympathetic activity (p<0.05). Overweight/obese subjects in the post-COVID-19 group presented significantly lower parasympathetic activity and reduced global variability compared to non-obese in control group (p<0.05). Physically inactive subjects in post-COVID-19 group presented significantly higher sympathetic activity than active subjects in control group. Parasympathetic activity was significantly increased in physically active subjects in control group compared to the physically inactive post-COVID-19 group (p<0.05). COVID-19 promotes changes in the ANS of young adults, and these changes are modulated by Overweight/obesity and physical activity levels.\n\nKey Points- Our main finding is that even in mild and moderate infections, young adults who had COVID-19 had greater sympathetic activity, less parasympathetic activity, and global variability when compared to uninfected individuals.\n- In participants who were overweight and obese and/or physically inactive, cardiac autonomic modulation showed worse indices.\n- Our study provides new insights regarding the role of body mass index and physical activity status on post-COVID-19 infection autonomic deregulation that may contribute to the understand of pathophysiology and treatment of of post-acute sequelae SARS-CoV-2 infection.", - "rel_num_authors": 11, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2021.11.19.468693", + "rel_abs": "In the interest of advocating for the postdoctoral community in the United States, we present results from survey data collected before and during the COVID-19 pandemic on the same population of postdocs. In 2019, 5,929 postdocs in the US completed a comprehensive survey, and in 2020, a subset completed a follow-up survey several months into the pandemic. The results show that the pandemic has substantially impacted postdocs mental health and wellness irrespective of gender, race, citizenship, or other identities. Postdocs also reported a significant impact on their career trajectories and progression, reduced confidence in achieving career goals, and negative perceptions of the job market compared to pre-COVID-19. International postdocs also reported experiencing distinct stressors due to the changes in immigration policy. Notably, having access to Postdoctoral Associations and Postdoctoral Offices positively impacted postdocs overall well-being and helped mitigate the personal and professional stresses and career uncertainties caused by the pandemic.\n\nGraphical Abstract\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=137 SRC=\"FIGDIR/small/468693v2_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (56K):\norg.highwire.dtl.DTLVardef@174d7e3org.highwire.dtl.DTLVardef@9893dorg.highwire.dtl.DTLVardef@114470org.highwire.dtl.DTLVardef@1a4278f_HPS_FORMAT_FIGEXP M_FIG Graphical Abstract of survey responses to: Why or how has your research been disrupted or not disrupted due to the pandemic? Overall, postdocs responded with feelings of loss of control as the pandemic was acting upon them and taking away their ability to complete their work.\n\nC_FIG", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Ana Paula Figueira Freire", - "author_inst": "Universidade do Oeste Paulista" - }, - { - "author_name": "Fabio Santos de Lira", - "author_inst": "Universidade Estadual Paulista" - }, - { - "author_name": "Ana Elisa von Ah Morano", - "author_inst": "Universidade Estadual Paulista" - }, - { - "author_name": "Telmo Pereira", - "author_inst": "University of Coimbra" - }, - { - "author_name": "Manuel-Joao Coelho Silva", - "author_inst": "University of Coimbra" - }, - { - "author_name": "Armando Caseiro", - "author_inst": "University of Coimbra" + "author_name": "Andr\u00e9anne Morin", + "author_inst": "University of Chicago" }, { - "author_name": "Diego Giulliano Destro Christofaro", - "author_inst": "Universidade Estadual Paulista" + "author_name": "Britney A Helling", + "author_inst": "University of Chicago" }, { - "author_name": "Osmar Marchioto Jr.", - "author_inst": "Universidade Estadual Paulista" + "author_name": "Seetha Krishnan", + "author_inst": "University of Chicago" }, { - "author_name": "Gilson Pires Dorneles", - "author_inst": "Universidade Federal de Ciencias da Saude de Porto Alegre" + "author_name": "Laurie E Risner", + "author_inst": "University of Chicago" }, { - "author_name": "Ricardo Aurino Pinho", - "author_inst": "Pontificia Universidade Catolica Do Parana" + "author_name": "Nykia D Walker", + "author_inst": "University of Chicago" }, { - "author_name": "Bruna Spolador de Alencar Silva", - "author_inst": "Universidade Estadual Paulista" + "author_name": "Nancy B Schwartz", + "author_inst": "University of Chicago" } ], "version": "1", "license": "cc_by_nc_nd", - "type": "PUBLISHAHEADOFPRINT", - "category": "cardiovascular medicine" + "type": "new results", + "category": "scientific communication and education" }, { "rel_doi": "10.1101/2021.11.17.21266457", @@ -504517,25 +503828,65 @@ "category": "health policy" }, { - "rel_doi": "10.1101/2021.11.19.21266532", - "rel_title": "Monitoring of SARS-CoV-2 Antibodies Using Dried Blood Spot for At-Home Collection", + "rel_doi": "10.1101/2021.11.19.21266552", + "rel_title": "Low neutralizing antibody titers against the Mu variant of SARS-CoV-2 in BNT162b2 vaccinated individuals", "rel_date": "2021-11-19", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.19.21266532", - "rel_abs": "The utilization of vaccines to fight the spread of SARS-CoV-2 has led to a growing need for expansive serological testing. To address this, an EUA approved immunoassay for detection of antibodies to SARS-CoV-2 in venous serum samples was investigated for use with dried blood spot (DBS) samples. Results from self-collected DBS samples demonstrated a 98.1% categorical agreement to venous serum with a correlation (R) of 0.9600 while professionally collected DBS samples demonstrated a categorical agreement of 100.0% with a correlation of 0.9888 to venous serum. Additional studies were performed to stress aspects of at-home DBS collection, including shipping stability, interference effects, and other sample-specific robustness studies. These studies demonstrated a categorical agreement of at least 95.0% and a mean bias less than {+/-}20.0%. Furthermore, the ability to track antibody levels following vaccination with the BioNTech/Pfizer vaccine was demonstrated with self-collected DBS samples from pre-dose (Day 0) out to 19 weeks.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.19.21266552", + "rel_abs": "BackgroundGlobal surveillance programs for the virus that causes COVID-19 are showing the emergence of variants with mutations in the Spike protein, including the Mu variant, recently declared a Variant of Interest (VOI) by the World Health Organization. Genomic and laboratory surveillance is important in these types of variants because they may be more infectious or less susceptible to antiviral treatments and vaccine-induced antibodies.\n\nObjectivesTo evaluate the sensitivity of the Mu variant (B.1.621) to neutralizing antibodies induced by the BNT162b2 vaccine.\n\nStudy designThree of the most predominant SARS-CoV-2 variants in Colombia during the epidemiological peaks of 2021 were isolated. Microneutralization assays were performed by incubating 120 TCDI50 of each SARS-CoV-2 isolate with five 2-fold serial dilutions of sera from 14 BNT162b2 vaccinated volunteers. The MN50 titer was calculated by the Reed-Muench formula\n\nResultsThe three isolated variants were Mu, a Variant of Interest (VOI), Gamma, a variant of concern (VOC), and B.1.111 that lacks genetic markers associated with greater virulence. At the end of August, the Mu and Gamma variants were widely distributed in Colombia. Mu was predominant (49%), followed by Gamma (25%). In contrast, B.1.111 became almost undetectable. The evaluation of neutralizing antibodies suggests that patients vaccinated with BNT162-2 generate neutralizing antibody titers against the Mu variant at significantly lower concentrations relative to B.1.111 and Gamma.\n\nConclusionsThis study shows the importance of continuing with surveillance programs of emerging variants as well as the need to evaluate the neutralizing antibody response induced by other vaccines circulating in the country against Mu and other variants with high epidemiological impact.\n\nHighlightsO_LIMu and Gamma variants represented 49% and 25% of cases in Colombia by August 2021.\nC_LIO_LIIncreased proportion of SARS-COV-2 cases were mostly associated with Mu variant, despite being detected simultaneously with the VOC Gamma\nC_LIO_LIThe Mu variant remarkably escapes from neutralizing antibodies elicited by the BNT162b2-vaccine\nC_LIO_LILaboratory studies of neutralizing antibodies are useful to determine the efficacy of SARS-CoV-2 vaccines against VOC and VOI.\nC_LI", + "rel_num_authors": 13, "rel_authors": [ { - "author_name": "Peyton K Miesse", - "author_inst": "Laboratory Corporation of America Holdings" + "author_name": "Diego Alejandro Alvarez-Diaz", + "author_inst": "Instituto Nacional de Salud" + }, + { + "author_name": "Ana L Munoz", + "author_inst": "Fundacion Banco Nacional de Sangre Hemolife" + }, + { + "author_name": "Pilar Tavera-Rodriguez", + "author_inst": "Instituto Nacional de Salud" + }, + { + "author_name": "Maria T Herrera-Sepulveda", + "author_inst": "Instituto Nacional de Salud" + }, + { + "author_name": "Hector A Ruiz-Moreno", + "author_inst": "Instituto Nacional de Salud" + }, + { + "author_name": "Katherine Laiton-Donato", + "author_inst": "Instituto Nacional de Salud" + }, + { + "author_name": "Carlos Franco-Munoz", + "author_inst": "Instituto Nacional de Salud" }, { - "author_name": "Bradley B Collier", - "author_inst": "Laboratory Corporation of America Holdings" + "author_name": "Dioselina Pelaez-Carvajal", + "author_inst": "Instituto Nacional de Salud" + }, + { + "author_name": "Diego Cuellar", + "author_inst": "Instituto Nacional de Salud" + }, + { + "author_name": "Alejandra M Munoz-Ramirez", + "author_inst": "Instituto Nacional de Salud" }, { - "author_name": "Russell P Grant", - "author_inst": "Laboratory Corporation of America Holdings" + "author_name": "Marisol Galindo", + "author_inst": "Instituto Nacional de Salud" + }, + { + "author_name": "Edgar J Arias-Ramirez", + "author_inst": "Instituto Nacional de Salud" + }, + { + "author_name": "Marcela M Reyes", + "author_inst": "Instituto Nacional de Salud" } ], "version": "1", @@ -506215,103 +505566,31 @@ "category": "intensive care and critical care medicine" }, { - "rel_doi": "10.1101/2021.11.15.21266264", - "rel_title": "Association of COVID-19 employment disruption with mental and social wellbeing: evidence from nine UK longitudinal studies", + "rel_doi": "10.1101/2021.11.16.21266383", + "rel_title": "High COVID-19 vaccine coverage allows for a re-opening of European universities", "rel_date": "2021-11-16", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.15.21266264", - "rel_abs": "BackgroundThe COVID-19 pandemic has led to major economic disruptions. In March 2020, the UK implemented the Coronavirus Job Retention Scheme - known as furlough - to minimize the impact of job losses. We investigate associations between change in employment status and mental and social wellbeing during the early stages of the pandemic.\n\nMethodsData were from 25,670 respondents, aged 17 to 66, across nine UK longitudinal studies. Furlough and other employment changes were defined using employment status pre-pandemic and during the first lockdown (April-June 2020). Mental and social wellbeing outcomes included psychological distress, life satisfaction, self-rated health, social contact, and loneliness. Study-specific modified Poisson regression estimates, adjusting for socio-demographic characteristics and pre-pandemic mental and social wellbeing measures, were pooled using meta-analysis.\n\nResultsCompared to those who remained working, furloughed workers were at greater risk of psychological distress (adjusted risk ratio, ARR=1.12; 95% CI: 0.97, 1.29), low life satisfaction (ARR=1.14; 95% CI: 1.07, 1.22), loneliness (ARR=1.12; 95% CI: 1.01, 1.23), and poor self-rated health (ARR=1.26; 95% CI: 1.05, 1.50), but excess risk was less pronounced than that of those no longer employed (e.g., ARR for psychological distress=1.39; 95% CI: 1.21, 1.59) or in stable unemployment (ARR=1.33; 95% CI: 1.09, 1.62).\n\nConclusionsDuring the early stages of the pandemic, those furloughed had increased risk for poor mental and social wellbeing. However, their excess risk was lower in magnitude than that of those who became or remained unemployed, suggesting that furlough may have partly mitigated poorer outcomes.", - "rel_num_authors": 21, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.16.21266383", + "rel_abs": "Returning universities to full on-campus operations while the COVID-19 pandemic is ongoing has been a controversial discussion in many countries. The risk of large outbreaks in dense course settings is contrasted by the benefits of in-person teaching. Transmission risk depends on a range of parameters, such as vaccination coverage, number of contacts and adoption of non-pharmaceutical intervention measures (NPIs). Due to the generalised academic freedom in Europe, many universities are asked to autonomously decide on and implement intervention measures and regulate on-campus operations. In the context of rapidly changing vaccination coverage and parameters of the virus, universities often lack the scientific facts to base these decisions on. To address this problem, we analyse a calibrated, data-driven simulation of transmission dynamics of 10755 students and 974 faculty in a medium-sized university. We use a co-location network reconstructed from student enrolment data and calibrate transmission risk based on outbreak size distributions in other Austrian education institutions. We focus on actionable interventions that are part of the already existing decision-making process of universities to provide guidance for concrete policy decisions. Here we show that with the vaccination coverage of about 80% recently reported for students in Austria, universities can be safely reopened if they either mandate masks or reduce lecture hall occupancy to 50%. Our results indicate that relaxing NPIs within an organisation based on the vaccination coverage of its sub-population can be a way towards limited normalcy, even if nation wide vaccination coverage is not sufficient to prevent large outbreaks yet.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Jacques Wels", - "author_inst": "University College London" - }, - { - "author_name": "Charlotte Booth", - "author_inst": "University College London" - }, - { - "author_name": "Bozena Wielgoszewska", - "author_inst": "University College London" - }, - { - "author_name": "Michael J Green", - "author_inst": "University of Glasgow" - }, - { - "author_name": "Giorgio Di Gessa", - "author_inst": "University College London" - }, - { - "author_name": "Charlotte F Huggins", - "author_inst": "University of Edinburgh" - }, - { - "author_name": "Gareth J Griffith", - "author_inst": "University of Bristol" - }, - { - "author_name": "Alex Siu Fung Kwong", - "author_inst": "University of Bristol" - }, - { - "author_name": "Ruth C E Bowyer", - "author_inst": "King's College London" - }, - { - "author_name": "Jane Maddock", - "author_inst": "University College London" - }, - { - "author_name": "Praveetha Patalay", - "author_inst": "University College London" - }, - { - "author_name": "Richard J Silverwood", - "author_inst": "University College London" - }, - { - "author_name": "Emla Fitzsimons", - "author_inst": "University College London" - }, - { - "author_name": "Richard John Shaw", - "author_inst": "University of Glasgow" - }, - { - "author_name": "Ellen J Thompson", - "author_inst": "Kings College London" - }, - { - "author_name": "Andrew Steptoe", - "author_inst": "University College London" - }, - { - "author_name": "Alun Hughes", - "author_inst": "University College London" - }, - { - "author_name": "Nishi Chaturvedi", - "author_inst": "University College London" - }, - { - "author_name": "Claire J Steves", - "author_inst": "King's College London" + "author_name": "Jana Lasser", + "author_inst": "Graz University of Technology" }, { - "author_name": "Srinivasa Vittal Katikireddi", - "author_inst": "University of Glasgow" + "author_name": "Timotheus Hell", + "author_inst": "Graz University of Technology" }, { - "author_name": "George B Ploubidis", - "author_inst": "University College London" + "author_name": "David Garcia", + "author_inst": "Graz University of Technology" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "psychiatry and clinical psychology" + "category": "public and global health" }, { "rel_doi": "10.1101/2021.11.15.21266377", @@ -508229,129 +507508,145 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2021.11.14.21266294", - "rel_title": "Inactivated virus vaccine BBV152/Covaxin elicits robust cellular immune memory to SARS-CoV-2 and variants of concern", + "rel_doi": "10.1101/2021.11.14.21266309", + "rel_title": "Safety and Immunogenicity of anti-SARS CoV-2 vaccine SOBERANA 02 in homologous or heterologous scheme.", "rel_date": "2021-11-15", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.14.21266294", - "rel_abs": "The characteristics of immune memory established in response to inactivated SARS-CoV-2 vaccines remains unclear. We determined the magnitude, quality and persistence of cellular and humoral memory responses up to 6 months after vaccination with BBV152/Covaxin. Here, we show that the quantity of vaccine-induced spike- and nucleoprotein-antibodies is comparable to that following natural infection and the antibodies are detectable up to 6 months. The RBD-specific antibodies decline in the range of 3 to 10-fold against the SARS-CoV-2 variants in the order of alpha (B.1.1.7) > delta (B.1.617.2) > beta (B.1.351), with no observed impact of gamma (P.1) and kappa (B.1.617.1) variant. We found that the vaccine induces memory B cells, similar to natural infection, which are impacted by virus variants in the same order as antibodies. The vaccine further induced antigen-specific functionally potent multi-cytokine expressing CD4+ T cells in [~]85% of the subjects, targeting spike and nucleoprotein of SARS-CoV-2. Marginal [~]1.3 fold-reduction was observed in vaccine-induced CD4+ T cells against the beta variant, with no significant impact of the alpha and the delta variants. The antigen-specific CD4+ T cells were populated in the central memory compartment and persisted up to 6 months of vaccination. Importantly the vaccine generated Tfh cells that are endowed with B cell help potential, similar to the Tfh cells induced after natural infection. Altogether, these findings establish that the inactivated virus vaccine BBV152 induces robust immune memory to SARS-CoV-2 and variants of concern, which persist for at least 6 months after vaccination. This study provides insight into the attributes of BBV152-elicited immune memory, and has implication for future vaccine development, guidance for use of inactivated virus vaccine, and booster immunization.", - "rel_num_authors": 28, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.14.21266309", + "rel_abs": "BackgroundSOBERANA 02 is a COVID-19 conjugate vaccine candidate based on SARS-CoV-2 recombinant RBD conjugated to tetanus toxoid. SOBERANA Plus antigen is dimeric-RBD. Here we report safety, reactogenicity and immunogenicity from phase I and IIa clinical trials using two-doses SOBERANA 02 (homologous protocol) and three-doses (homologous) or heterologous (with SOBERANA Plus) protocols.\n\nMethodWe performed an open-label, monocentric, sequential and adaptive phase I for evaluating safety, reactogenicity and exploring immunogenicity of SOBERANA 02 in two formulations (15 and 25 g) in 40 subjects, 19-59 years old. Phase IIa was open-label including 100 volunteers 19-80 years, receiving two doses of SOBERANA 02-25 g. In both trials, half of volunteers received a third dose of SOBERANA 02, half received a heterologous dose of SOBERANA Plus-50 g. Primary outcomes were safety and reactogenicity. The secondary outcome was vaccine immunogenicity evaluated by anti-RBD IgG ELISA, molecular neutralization test of RBD:hACE2 interaction, live-virus neutralization test and specific T-cells response.\n\nResultsThe most frequent AE was local pain, other AEs had frequencies [≤] 5%. No serious related AEs were reported. Phase IIa confirmed the safety results in 60-80 years subjects. In phase-I SOBERANA 02-25{micro}g elicited higher immune response than SOBERANA 02-15 {micro}g; in consequence, the higher dose progressed to phase IIa. Phase IIa results confirmed the immunogenicity of SOBERANA 02-25 g even in 60-80 age range. Two doses of SOBERANA02-25 g elicited an immune response similar to that of the Cuban Convalescent Serum Panel; it was higher after both the homologous and heterologous third doses; the heterologous scheme showing a higher immunological response.\n\nConclusionsSOBERANA 02 was safe and immunogenic in persons aged 19-80 years, eliciting neutralizing antibodies and specific T cell response. Highest immune responses were obtained in the heterologous three doses protocol. Trial registry: https://rpcec.sld.cu/trials/RPCEC00000340 and https://rpcec.sld.cu/trials/RPCEC00000347", + "rel_num_authors": 32, "rel_authors": [ { - "author_name": "Rajesh Vikkurthi", - "author_inst": "Vaccine Immunology Laboratory, National Institute of Immunology, New Delhi, 110067, India" + "author_name": "Maria Eugenia Toledo-Romani", + "author_inst": "Pedro KouriTropical Medicine Institute" }, { - "author_name": "Asgar Ansari", - "author_inst": "Vaccine Immunology Laboratory, National Institute of Immunology, New Delhi, 110067, India" + "author_name": "Leslihana Verdecia Sanchez", + "author_inst": "Clinic 1" }, { - "author_name": "Anupama R Pai", - "author_inst": "Vaccine Immunology Laboratory, National Institute of Immunology, New Delhi, 110067, India" + "author_name": "Meybis Rodriguez Gonzalez", + "author_inst": "Finlay Vaccine Institute" }, { - "author_name": "Someshwar Nath Jha", - "author_inst": "Vaccine Immunology Laboratory, National Institute of Immunology, New Delhi, 110067, India" + "author_name": "Laura Rodriguez Noda", + "author_inst": "Finlay Vaccine Institute" }, { - "author_name": "Shilpa Sachan", - "author_inst": "Vaccine Immunology Laboratory, National Institute of Immunology, New Delhi, 110067, India" + "author_name": "Carmen Valenzuela Silva", + "author_inst": "Cybernetics, Mathematics and Physics Institute" }, { - "author_name": "Suvechchha Pandit", - "author_inst": "Vaccine Immunology Laboratory, National Institute of Immunology, New Delhi, 110067, India" + "author_name": "Beatriz Paredes Moreno", + "author_inst": "Finlay Vaccine Institute" }, { - "author_name": "Bhushan Nikam", - "author_inst": "Vaccine Immunology Laboratory, National Institute of Immunology, New Delhi, 110067, India" + "author_name": "Belinda Sanchez Ramirez", + "author_inst": "Centre of Molecular Immunology" }, { - "author_name": "Anurag Kalia", - "author_inst": "Vaccine Immunology Laboratory, National Institute of Immunology, New Delhi, 110067, India" + "author_name": "Rocmira Perez Nicado", + "author_inst": "Finlay Vaccine Institute" }, { - "author_name": "Bimal Prasad Jit", - "author_inst": "Department of Biochemistry, All India Institute of Medical Sciences, New Delhi, 110029, India" + "author_name": "Raul Gonzalez Mugica", + "author_inst": "Finlay Vaccine Institute" }, { - "author_name": "Hilal Ahmad Parray", - "author_inst": "Translational Health Science and Technology Institute, Faridabad, 121001, India" + "author_name": "Tays Hernandez Garcia", + "author_inst": "Centre of Molecular Immunology" }, { - "author_name": "Savita Singh", - "author_inst": "Translational Health Science and Technology Institute, Faridabad, 121001, India" + "author_name": "Gretchen Bergado Baez", + "author_inst": "Centre of Molecular Immunology" }, { - "author_name": "Pallavi Kshetrapal", - "author_inst": "Translational Health Science and Technology Institute, Faridabad, 121001, India" + "author_name": "Franciscary Pi Estopinan", + "author_inst": "Centre of Molecular Immunology" }, { - "author_name": "Nitya Wadhwa", - "author_inst": "Translational Health Science and Technology Institute, Faridabad, 121001, India" + "author_name": "Otto Cruz Sui", + "author_inst": "National Civil Defense Research Laboratory" }, { - "author_name": "Tripti Shrivastava", - "author_inst": "Translational Health Science and Technology Institute, Faridabad, 121001, India" + "author_name": "Anitza Fraga Quintero", + "author_inst": "National Civil Defense Research Laboratory" }, { - "author_name": "Poonam Coshic", - "author_inst": "Department of Transfusion Medicine, All India Institute of Medical Sciences, New Delhi, 110029, India" + "author_name": "Majela Garcia Montero", + "author_inst": "National Civil Defense Research Laboratory" }, { - "author_name": "Suresh Kumar", - "author_inst": "Maulana Azad Medical College and Lok Nayak Hospital, New Delhi, 110002, India" + "author_name": "Ariel Palenzuela Diaz", + "author_inst": "Centre for Immunoassays" }, { - "author_name": "Pragya Sharma", - "author_inst": "Maulana Azad Medical College and Lok Nayak Hospital, New Delhi, 110002, India" + "author_name": "Gerardo Baro Roman", + "author_inst": "Centre for Immunoassays" }, { - "author_name": "Nandini Sharma", - "author_inst": "Maulana Azad Medical College and Lok Nayak Hospital, New Delhi, 110002, India" + "author_name": "Ivis Mendoza Hernandez", + "author_inst": "National Clinical Trials Coordinating Center" }, { - "author_name": "Juhi Taneja", - "author_inst": "ESIC Medical College and Hospital, Faridabad, 121012, India" + "author_name": "Sonsire Fernandez Castillo", + "author_inst": "Finlay Vaccine Institute" }, { - "author_name": "Anil K Pandey", - "author_inst": "ESIC Medical College and Hospital, Faridabad, 121012, India" + "author_name": "Yanet Climent Ruiz", + "author_inst": "Finlay Vaccine Institute" }, { - "author_name": "Ashok Sharma", - "author_inst": "Department of Biochemistry, All India Institute of Medical Sciences, New Delhi, 110029, India" + "author_name": "Darielys Santana Mederos", + "author_inst": "Finlay Vaccine Institute" }, { - "author_name": "Ramachandran Thiruvengadam", - "author_inst": "Translational Health Science and Technology Institute, Faridabad, 121001, India" + "author_name": "Ubel Ramirez Gonzalez", + "author_inst": "Finlay Vaccine Institute" }, { - "author_name": "Alba Grifoni", - "author_inst": "Center for Infectious Disease and Vaccine Research, La Jolla Institute for Immunology, La Jolla, CA, 92037, USA" + "author_name": "Yanelda Garcia Vega", + "author_inst": "Centre of Molecular Immunology" }, { - "author_name": "Shinjini Bhatnagar", - "author_inst": "Translational Health Science and Technology Institute, Faridabad, 121001, India" + "author_name": "Beatriz Perez Masson", + "author_inst": "Centre of Molecular Immunology" }, { - "author_name": "Daniela Weiskopf", - "author_inst": "Center for Infectious Disease and Vaccine Research, La Jolla Institute for Immunology, La Jolla, CA, 92037, USA" + "author_name": "Guang Wu Chen", + "author_inst": "Chengdu Olisynn Biotech. Co. Ltd., and State Key Laboratory of Biotherapy and Cancer Center" }, { - "author_name": "Alessandro Sette", - "author_inst": "Center for Infectious Disease and Vaccine Research, La Jolla Institute for Immunology, La Jolla, CA, 92037, USA" + "author_name": "Tammy Boggiano Ayo", + "author_inst": "Centre of Molecular Immunology" }, { - "author_name": "Pramod Kumar Garg", - "author_inst": "Translational Health Science and Technology Institute, Faridabad, 121001, India" + "author_name": "Eduardo Ojito Magaz", + "author_inst": "Centre of Molecular Immunology" }, { - "author_name": "Nimesh Gupta", - "author_inst": "Vaccine Immunology Laboratory, National Institute of Immunology, New Delhi, 110067, India" + "author_name": "Daniel G. Rivera", + "author_inst": "Laboratory of Synthetic and Biomolecular Chemistry, Faculty of Chemistry, University of Havana" + }, + { + "author_name": "Yury Valdes Balbin", + "author_inst": "Finlay Vaccine Institute" + }, + { + "author_name": "Dagmar Garcia Rivera", + "author_inst": "Finlay Vaccine Institute" + }, + { + "author_name": "vicente Verez Bencomo", + "author_inst": "Finlay Vaccine Institute" + }, + { + "author_name": "- SOBERANA Research Group", + "author_inst": "" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -510079,37 +509374,41 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.11.11.21266237", - "rel_title": "An outbreak inside an outbreak: rising incidence of carbapenem-resistant isolates during the COVID-19 pandemic. Report from a tertiary care center in Argentina.", - "rel_date": "2021-11-12", + "rel_doi": "10.1101/2021.11.09.21265517", + "rel_title": "Ultrafast RNA extraction-free SARS-CoV-2 detection by direct RT-PCR using a rapid thermal cycling approach", + "rel_date": "2021-11-11", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.11.21266237", - "rel_abs": "IntroductionCOVID-19 outbreaks have left us to deal with an aftermath on many fronts. In particular, disproportionate use of antibiotics, high ICU burden and longer in-hospital stays during the pandemic have been proposed to aggravate the emergency posed by carbapenem-resistant isolates (CRI), specially through carbapenemase production. However, there have been few reports worldwide regarding changes in CRI incidence and little latinamerican literature.\n\nObjectiveWe set out to determine whether the incidence of CRI rose in a tertiary care center in Santa Fe, Argentina during the time period with active cases of COVID-19.\n\nMethodsAnalytic epidemiologic study retrospectively designed. Two time periods were defined: P1 (without active cases of COVID-19) from September, 2019 to August, 2020 and P2 (starting at the onset of the first wave of COVID-19 in this institution) from September, 2020 to June 2021. All clinically-relevant microbiological samples -those meant for diagnostic purposes-taken during the study period from patients in the Internal Medicine and Surgical wards as well as the Intensive Care Units were included. Incidence was calculated by dividing the number of CRI during each time frame by the count of patient-day during that same period, multiplied by a hundred.\n\nResults9,135 hospitalizations, 50,145 patient-days of analysis. A total of 7285 clinical samples were taken, with an overall positivity for CRI of 12.1% (n=883). Overall CRI incidence during P2 was 2.5 times higher than in P1 (2.52 vs 0.955/100 patient-days, p <0.001). ICU CRI incidence raised from 6.78 to 8.69/100 patient-days in P2 (p=0.006).\n\nConclusionWe found alarming rates of CRI in our center, 2.5 times higher than previous to the first COVID-19 wave, similar to other reports worldwide. To our knowledge, this is one of the few Latin-American reports on the effect of the COVID-19 pandemic on CRI incidence.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.09.21265517", + "rel_abs": "The surging COVID19 pandemic has underlined the need for quick, sensitive, and high-throughput SARS-CoV-2 detection assays. Although many different methods to detect SARS-CoV-2 particles in clinical material have been developed, none of these assays are successful in combining all three of the above characteristics into a single, easy-to-use method that is suitable for large-scale use. Here we report the development of a direct RT-PCR SARS-CoV-2 detection method that can reliably detect minute quantities of SARS-CoV-2 gRNA in nasopharyngeal swab samples as well as the presence of human genomic DNA. An extraction-less validation protocol was carried out to determine performance characteristics of the assay in both synthetic SARS-CoV-2 RNA as well as clinical specimens. Feasibility of the assay and analytical sensitivity was first determined by testing a dilution series of synthetic SARS-CoV-2 RNA in two different solvents (water and AMIES VTM), revealing a high degree of linearity and robustness in fluorescence readouts. Following analytical performance using synthetic RNA, the limit of detection was determined at equal to or less than 1 SARS-CoV-2 copy/ul of sample in a commercially available sample panel that contains surrogate clinical samples with varying SARS-CoV-2 viral load. Lastly, we benchmarked our method against a reference qPCR method by testing 87 nasopharyngeal swab samples. The direct endpoint ultra-fast RT-PCR method exhibited a positive percent agreement score of 98.5% and a negative percent agreement score of 100% as compared to the reference method, while RT-PCR cycling was completed in 27 minutes/sample as opposed to 60 minutes/sample in the reference qPCR method. In summary, we describe a rapid direct RT-PCR method to detect SARS-CoV-2 material in clinical specimens which can be completed in significantly less time as compared to conventional RT-PCR methods, making it an attractive option for large-scale SARS-CoV-2 screening applications.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Maximiliano Gabriel Castro", - "author_inst": "Hospital Dr. JB Iturraspe (Sta Fe, Arg)" + "author_name": "Robin Struijk", + "author_inst": "Molecular Biology Systems" + }, + { + "author_name": "Anton van den Ouden", + "author_inst": "Molecular Biology Systems" }, { - "author_name": "Lucia Ines Ubiergo", - "author_inst": "Dr. JB Iturraspe Hospital" + "author_name": "Brian McNally", + "author_inst": "Molecular Biology Systems" }, { - "author_name": "Macarena Vicino", - "author_inst": "Dr. JB Iturraspe Hospital" + "author_name": "Theun de Groot", + "author_inst": "Canisius Wilhelmina Hospital" }, { - "author_name": "Gisel Cuevas", - "author_inst": "Dr. JB Iturraspe Hospital" + "author_name": "Bert Mulder", + "author_inst": "Canisius Wilhelmina Hospital" }, { - "author_name": "Fernanda Argarana", - "author_inst": "Dr. JB Iturraspe Hospital" + "author_name": "Gert de Vos", + "author_inst": "Molecular Biology Systems" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -512061,31 +511360,55 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.11.09.21264627", - "rel_title": "ChAdOx1 n-COV-19 Vaccine Side Effects Among Health Care Workers in Trinidad and Tobago", + "rel_doi": "10.1101/2021.11.09.467862", + "rel_title": "Mice infected with Mycobacterium tuberculosis are resistant to secondary infection with SARS-CoV-2", "rel_date": "2021-11-10", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.09.21264627", - "rel_abs": "BackgroundThe pharmaceutical firms have been lauded for the swift development, trial, approval, and rollout of various Covid-19 vaccines. However, a key issue in the vaccination campaign relates to vaccine hesitancy due to concerns on Covid-19 vaccines safety.\n\nMethodA retrospective longitudinal study was carried out via a telephone validated questionnaire. The questionnaire domains included demographic data, medical and COVID-19 related anamneses, and local and systemic side effects 48 hours after receiving the first dose of the vaccine and 48 hours after receiving the second dose of the vaccine.\n\nResultsThe questionnaire was administered to a sample of 687 healthcare workers (Male = 275; Female = 412). The results indicated that the incidence of reported fever, body pain, chills, nausea, myalgia, headache, malaise, fatigue and other systemic symptoms declined significantly 48 hours after administration of the second dose compared to the first dose. The Chi-square test and multiple logistics regression results were consistent in demonstrating that younger vaccine recipients were more likely to report fever, body pain, chills, nausea, myalgia, headache, fatigue and other symptoms compared to older vaccine recipients. The multiple logistics regression indicate that female vaccine recipients had greater odds of reporting headache, fatigue, discomfort and less likely to report no symptoms compared to male vaccine recipients, 48 hours after receiving both doses.\n\nConclusionsThe findings indicate that on average, vaccine recipients reported fewer number of local and systemic side effects within 48 hours after receiving the second dose compared to 48 hours after receiving the first dose. The findings have implications on public health policy efforts to lower vaccine hesitancy.", - "rel_num_authors": 3, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2021.11.09.467862", + "rel_abs": "Mycobacterium tuberculosis (Mtb) and SARS-CoV-2 (CoV2) are the leading causes of death due to infectious disease. Although Mtb and CoV2 both cause serious and sometimes fatal respiratory infections, the effect of Mtb infection and its associated immune response on secondary infection with CoV2 is unknown. To address this question we applied two mouse models of COVID19, using mice which were chronically infected with Mtb. In both model systems, Mtb-infected mice were resistant to secondary CoV2 infection and its pathological consequences, and CoV2 infection did not affect Mtb burdens. Single cell RNA sequencing of coinfected and monoinfected lungs demonstrated the resistance of Mtb-infected mice is associated with expansion of T and B cell subsets upon viral challenge. Collectively, these data demonstrate that Mtb infection conditions the lung environment in a manner that is not conducive to CoV2 survival.\n\nAUTHOR SUMMARYMycobacterium tuberculosis (Mtb) and SARS-CoV-2 (CoV2) are distinct organisms which both cause lung disease. We report the surprising observation that Mtb-infected mice are resistant to secondary infection with CoV2, with no impact on Mtb burden and resistance associating with lung T and B cell expansion.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Chavin D Gopaul", - "author_inst": "The North Central Regional Health Authority" + "author_name": "Oscar Rosas Mejia", + "author_inst": "The Ohio State University" + }, + { + "author_name": "Erin Gloag", + "author_inst": "The Ohio State University" }, { - "author_name": "Dale Ventour", - "author_inst": "The University of the West Indies Trinidad and Tobago" + "author_name": "Jianying Li", + "author_inst": "The Ohio State University" }, { - "author_name": "Davlin Thomas", - "author_inst": "The North Central Regional Health Authority" + "author_name": "Marisa Ruane-Foster", + "author_inst": "The Ohio State University" + }, + { + "author_name": "Tiffany A. Claeys", + "author_inst": "The Ohio State University" + }, + { + "author_name": "Daniela Farkas", + "author_inst": "The Ohio State University" + }, + { + "author_name": "Laszlo Farkas", + "author_inst": "The Ohio State University" + }, + { + "author_name": "Gang Xin", + "author_inst": "The Ohio State University" + }, + { + "author_name": "Richard Robinson", + "author_inst": "Ohio State University College of Medicine" } ], "version": "1", - "license": "cc_by_nd", - "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "license": "cc_by", + "type": "new results", + "category": "immunology" }, { "rel_doi": "10.1101/2021.11.09.21265912", @@ -513770,109 +513093,61 @@ "category": "health systems and quality improvement" }, { - "rel_doi": "10.1101/2021.11.08.21266069", - "rel_title": "De novo emergence of a remdesivir resistance mutation during treatment of persistent SARS-CoV-2 infection in an immunocompromised patient: A case report", + "rel_doi": "10.1101/2021.11.05.21265911", + "rel_title": "Compassionate Use of REGEN-COV(R) in Patients with COVID-19 and Immunodeficiency-Associated Antibody Disorders", "rel_date": "2021-11-09", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.08.21266069", - "rel_abs": "SARS-CoV-2 remdesivir resistance mutations have been generated in vitro but have not been reported in patients receiving treatment with the antiviral agent. We present a case of an immunocompromised patient with acquired B-cell deficiency who developed an indolent, protracted course of SARS-CoV-2 infection. Remdesivir therapy alleviated symptoms and produced a transient virologic response, but her course was complicated by recrudescence of high-grade viral shedding. Whole genome sequencing identified a mutation, E802D, in the nsp12 RNA-dependent RNA polymerase, which was not present in pre-treatment specimens. In vitro experiments demonstrated that the mutation conferred a [~]6-fold increase in remdesivir IC50 but resulted in a fitness cost in the absence of remdesivir. Sustained clinical and virologic response was achieved after treatment with casirivimab-imdevimab. Although the fitness cost observed in vitro may limit the risk posed by E802D, this case illustrates the importance of monitoring for remdesivir resistance and the potential benefit of combinatorial therapies in immunocompromised patients with SARS-CoV-2 infection.", - "rel_num_authors": 23, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.05.21265911", + "rel_abs": "BackgroundPatients with immunodeficiency-associated antibody disorders are at a higher risk of prolonged/persistent COVID-19 infection, having no viable treatment options.\n\nMethodsThis is a retrospective analysis of patients with primary and/or secondary immunodeficiency-associated antibody disorders who received casirivimab and imdevimab (REGEN-COV(R)) under emergency compassionate use. The objectives were to describe safety and response to REGEN-COV, with a focus on the subset of patients who had COVID-19 duration [≥]21 days prior to treatment. Quantitative (change in oxygenation status and/or viral load) and/or qualitative (physician-reported clinical status) patient outcomes data are reported.\n\nResultsOutcome data are available from 64 patients who received REGEN-COV. Improvement in [≥]1 outcome measure was observed in 90.6% of the overall patient group. Thirty-seven of these patients had COVID-19 duration [≥]21 days prior to treatment, with a median time from RT-PCR diagnosis to REGEN-COV administration of 60.5 days. Of the 29 patients with COVID-19 duration [≥]21 days prior to treatment who had available outcome data, 96.6% showed improvement in [≥]1 outcome measure evaluated following use of REGEN-COV. In the 14 patients who had post-treatment RT-PCR results available, 11 (78.6%) reported a negative RT-PCR following treatment with REGEN-COV, with 5 patients (45.5%) reporting a negative RT-PCR within 5 days of treatment and 8 (72.7%) reporting a negative RT-PCR within 21 days of treatment.\n\nConclusionsIn this retrospective analysis of immunodeficient patients who were granted REGEN-COV under the compassionate use program, REGEN-COV treatment was associated with rapid viral clearance and clinical improvement in the evaluable patients with long-standing COVID-19.\n\nSummaryPatients with immunodeficiency-associated antibody disorders are at a higher risk of prolonged/persistent COVID-19 infection. In this retrospective analysis, compassionate use of REGEN-COV in such patients was associated with rapid viral clearance and/or clinical improvement in the evaluable patients.", + "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Shiv Gandhi", - "author_inst": "Yale University School of Medicine" - }, - { - "author_name": "Jonathan Klein", - "author_inst": "Yale University School of Medicine" - }, - { - "author_name": "Alexander Robertson", - "author_inst": "Yale School of Public Health" - }, - { - "author_name": "Mario A. Pena-Hernandez", - "author_inst": "Yale University School of Medicine" - }, - { - "author_name": "Michelle J Lin", - "author_inst": "University of Washington School of Medicine" - }, - { - "author_name": "Pavitra Roychoudhury", - "author_inst": "University of Washington School of Medicine" - }, - { - "author_name": "Peiwen Lu", - "author_inst": "Yale University School of Medicine" - }, - { - "author_name": "John Fournier", - "author_inst": "Yale University School of Medicine" - }, - { - "author_name": "David Ferguson", - "author_inst": "Yale New Haven Hospital" - }, - { - "author_name": "Shah A. Mohamed Bakhash", - "author_inst": "University of Washington School of Medicine" - }, - { - "author_name": "M. Catherine Muenker", - "author_inst": "Yale School of Public Health" - }, - { - "author_name": "Ariktha Srivathsan", - "author_inst": "Yale School of Public Health" - }, - { - "author_name": "Elsio A. Wunder Jr.", - "author_inst": "Yale School of Public Health" + "author_name": "David Stein", + "author_inst": "Regeneron Pharmaceuticals, Inc., Tarrytown, NY, USA" }, { - "author_name": "Nicholas Kerantzas", - "author_inst": "Yale University School of Medicine" + "author_name": "Ernesto Oviedo-Orta", + "author_inst": "Regeneron Pharmaceuticals, Inc., Tarrytown, NY, USA" }, { - "author_name": "Wenshuai Wang", - "author_inst": "Yale University" + "author_name": "Wendy A. Kampman", + "author_inst": "Regeneron Pharmaceuticals, Inc., Tarrytown, NY, USA" }, { - "author_name": "Brett Lindenbach", - "author_inst": "Yale University School of Medicine" + "author_name": "Jennifer McGinniss", + "author_inst": "Regeneron Pharmaceuticals, Inc., Tarrytown, NY, USA" }, { - "author_name": "Anna Pyle", - "author_inst": "Yale University" + "author_name": "George Betts", + "author_inst": "Regeneron Pharmaceuticals, Inc., Tarrytown, NY, USA" }, { - "author_name": "Craig B. Wilen", - "author_inst": "Yale University School of Medicine" + "author_name": "Margaret McDermott", + "author_inst": "Regeneron Pharmaceuticals, Inc., Tarrytown, NY, USA" }, { - "author_name": "Onyema Ogbuagu", - "author_inst": "Yale University School of Medicine" + "author_name": "Beth Holly", + "author_inst": "Regeneron Pharmaceuticals, Inc., Tarrytown, NY, USA" }, { - "author_name": "Alexander L. Greninger", - "author_inst": "University of Washington School of Medicine" + "author_name": "Johnathan M. Lancaster", + "author_inst": "Regeneron Pharmaceuticals, Inc., Tarrytown, NY, USA" }, { - "author_name": "Akiko Iwasaki", - "author_inst": "Yale University School of Medicine" + "author_name": "Ned Braunstein", + "author_inst": "Regeneron Pharmaceuticals, Inc., Tarrytown, NY, USA" }, { - "author_name": "Wade L. Schulz", - "author_inst": "Yale University School of Medicine" + "author_name": "George D. Yancopoulos", + "author_inst": "Regeneron Pharmaceuticals, Inc., Tarrytown, NY, USA" }, { - "author_name": "Albert I. Ko", - "author_inst": "Yale School of Public Health" + "author_name": "David M. Weinreich", + "author_inst": "Regeneron Pharmaceuticals, Inc., Tarrytown, NY, USA" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -515264,77 +514539,101 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.11.06.21265632", - "rel_title": "SARS-CoV-2 specific T cell and humoral immune responses upon vaccination with BNT162b2", + "rel_doi": "10.1101/2021.11.05.21265712", + "rel_title": "A need of COVID19 vaccination for children aged <12 years: Comparative evidence from the clinical characteristics in patients during a recent Delta surge (B.1.617.2)", "rel_date": "2021-11-08", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.06.21265632", - "rel_abs": "IntroductionThe humoral and cellular immune responses against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) upon coronavirus disease 2019 (COVID-19) vaccination remain to be clarified. Hence, we aimed to investigate the long-term chronological changes in SARS-CoV-2 specific IgG antibody, neutralizing antibody, and T cell responses during and after receiving the BNT162b2 vaccine.\n\nMethodsWe performed serological, neutralization, and T cell assays among 100 hospital workers aged 22-73 years who received the vaccine. We conducted seven surveys up to eight months after the second vaccination dose.\n\nResultsSARS-CoV-2 spike protein-specific IgG (IgG-S) titers and T cell responses increased significantly following the first vaccination dose. The highest titers were observed on day 29 and decreased gradually until the end of the follow-up period. There was no correlation between IgG-S and T cell responses. Notably, T cell responses were detected on day 15, earlier than the onset of neutralizing activity.\n\nConclusionsThis study demonstrated that both IgG-S and T cell responses were detected before acquiring sufficient levels of SARS-CoV-2 neutralizing antibodies. These immune responses are sustained for approximately six-ten weeks but not for seven months or later following the second vaccination, indicating the need for the booster dose (i.e., third vaccination).", - "rel_num_authors": 15, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.05.21265712", + "rel_abs": "ObjectiveTo evaluate the necessity of Covid-19 vaccination in children aged < 12 y by comparing the clinical characteristics in unvaccinated children aged < 12 y with vaccinated patients aged [≥] 12y during the Delta surge (B.1.617.2) in Putian, Fujian, China.\n\nMethodsA total of 226 patients with SARS-Cov-2 Delta variant (B.1.167.2; confirmed by Realtime PCR positive and sequencing) were enrolled from Sep 10th to Oct 20th, 2021, including 77 unvaccinated children (aged < 12y) and 149 people aged [≥] 12y, mostly vaccinated. The transmission route was explored and the clinical data of two groups were compared; the effect factors for the time of the nucleic acid negativization (NAN) were examined by R statistical analysis.\n\nResultsThe Delta surge in Putian spread from children in schools to factories, mostly through family contact. Compared with those aged [≥] 12y, patients aged < 12y accounted for 34.07% of the total and showed milder fever, less cough and fatigue; they reported higher peripheral blood lymphocyte counts [1.84(1.32,2.71)x10^9/L vs. 1.31(0.94,1.85)x10^9/L; p<0.05), higher normal CRP rate (92.21% vs. 57.72%), lower IL-6 levels [5.28(3.31,8.13) vs. 9.10(4.37,15.14); p< 0.05]. Upon admission, their COVID19 antibodies (IgM and IgG) and IgG in convalescence were lower [0.13(0.00,0.09) vs. 0.12(0.03,0.41), p<0.05; 0.02(0.00,0.14) vs. 1.94(0.54,6.40), p <0.05; 5.46(2.41,9.26) vs. 73.63 (54.63,86.55), p<0.05, respectively], but longer NAN time (18 days vs. 16 days, p=0.13).\n\nConclusionChildren aged < 12y may be critical hidden spreaders, which indicates an urgent need of vaccination for this particular population.", + "rel_num_authors": 21, "rel_authors": [ { - "author_name": "Junko S Takeuchi", - "author_inst": "National Center for Global Health and Medicine" + "author_name": "Hongru Li", + "author_inst": "Fujian Provincial Hospital" }, { - "author_name": "Ami Fukunaga", - "author_inst": "National Center for Global Health and Medicine" + "author_name": "Haibin Lin", + "author_inst": "Affiliated Hospital of Putian University" }, { - "author_name": "Shohei Yamamoto", - "author_inst": "National Center for Global Health and Medicine" + "author_name": "Xiaoping Chen", + "author_inst": "Fujian Normal University" }, { - "author_name": "Akihito Tanaka", - "author_inst": "National Center for Global Health and Medicine" + "author_name": "Hang Li", + "author_inst": "Affiliated Hospital of Putian University" }, { - "author_name": "Kouki Matsuda", - "author_inst": "National Center for Global Health and Medicine" + "author_name": "Hong Li", + "author_inst": "Fujian Provincial Hospital" }, { - "author_name": "Moto Kimura", - "author_inst": "National Center for Global Health and Medicine" + "author_name": "Sheng Lin", + "author_inst": "Fujian Provincial Hospital" }, { - "author_name": "Azusa Kamikawa", - "author_inst": "National Center for Global Health and Medicine" + "author_name": "Liping Huang", + "author_inst": "Fujian Provincial Hospital" }, { - "author_name": "Yumiko Kito", - "author_inst": "National Center for Global Health and Medicine" + "author_name": "Gongping Chen", + "author_inst": "The First Affiliated Hospital of Fujian Medical University" }, { - "author_name": "Kenji Maeda", - "author_inst": "National Center For Global Health and Medicine" + "author_name": "Guilin Zheng", + "author_inst": "Fujian Provincial Hospital" }, { - "author_name": "Gohzoh Ueda", - "author_inst": "Abbott Japan LLC" + "author_name": "Shibiao Wang", + "author_inst": "Fujian Provincial Maternity and Child Health Hospital" }, { - "author_name": "Tetsuya Mizoue", - "author_inst": "National Center for Global Health and Medicine" + "author_name": "Xiaowei Hu", + "author_inst": "Shanghai Children's Medical Center Fujian Hospital" }, { - "author_name": "Mugen Ujiie", - "author_inst": "National Center for Global Health and Medicine" + "author_name": "Handong Huang", + "author_inst": "Affiliated Hospital of Putian University" }, { - "author_name": "Hiroaki Mitsuya", - "author_inst": "National Center for Global Health and Medicine" + "author_name": "Haijian Tu", + "author_inst": "Affiliated Hospital of Putian University" }, { - "author_name": "Norio Ohmagari", - "author_inst": "National Center for Global Health and Medicine" + "author_name": "Xiaoqin Li", + "author_inst": "Fujian Provincial Hospital" }, { - "author_name": "Wataru Sugiura", - "author_inst": "National Center for Global Health and Medicine" + "author_name": "Yuejiao Ji", + "author_inst": "Fujian Normal University" + }, + { + "author_name": "Wen Zhong", + "author_inst": "Fujian Provincial Hospital" + }, + { + "author_name": "Qing Li", + "author_inst": "Fujian Provincial Hospital" + }, + { + "author_name": "Jiabin Fang", + "author_inst": "Fujian Provincial Hospital" + }, + { + "author_name": "Qunying Lin", + "author_inst": "Affiliated Hospital of Putian University" + }, + { + "author_name": "Rongguo Yu", + "author_inst": "Fujian Provincial Hospital" + }, + { + "author_name": "Baosong Xie", + "author_inst": "Fujian Provincial Hospital, Fujian Shengli medical college" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -517362,43 +516661,71 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2021.11.03.21265201", - "rel_title": "Optimising the quarantining and response sequence towards SARS-CoV-2 outbreaks on board cargo vessels", + "rel_doi": "10.1101/2021.11.05.21265569", + "rel_title": "Evaluation of patients treated by telemedicine in the COVID-19 pandemic by a private clinic in Sao Paulo, Brazil: A non-randomized clinical trial preliminary study", "rel_date": "2021-11-05", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.03.21265201", - "rel_abs": "The Coronavirus Disease (COVID-19) pandemic has brought significant impact onto the maritime activities worldwide, including disruption to global trade and supply chains. The ability to predict the evolution and duration of a COVID-19 outbreak on cargo vessels would inform a more nuanced response to the event and provide a more precise return-to-trade date. A SEIQ(H)R (Susceptibility--Exposed-Infected--Quarantine--(Hospitalisation)--Removed/Recovered) model is developed and fit-tested to simulate the transmission dynamics of COVID-19 on board cargo vessels of up to 60 crew. Due to specific living and working circumstances on board cargo vessels, instead of utilising the reproduction number, we consider the highest fraction of crew members who share the same nationality to quantify the transmissibility of the disease. The performance of the model is verified using case studies based on data collected during COVID-19 outbreaks on three cargo vessels in Western Australia during 2020. The simulations show that the model can forecast the time taken for the transmission dynamics on each vessel to reach their equilibriums, providing informed predictions on the evolution of the outbreak, including hospitalisation rates and duration. The model demonstrates that (a) all crew members are susceptible to infection; (b) their roles on board is a determining factor in the evolution of the outbreak; (c) an unmitigated outbreak could affect the entire crew and continue on for many weeks. The ability to model the evolution of an outbreak, both in duration and severity, is essential to predict outcomes and to plan for the best response strategy. At the same time, it offers a higher degree of certainty regarding the return to trade, which is of significant importance to multiple stakeholders.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.05.21265569", + "rel_abs": "IntroductionAs a result of the coronavirus disease 2019 (COVID-19) pandemic the year 2020 brought major changes on the delivery of health care and face to face physician patient communication was significantly reduced and the practice of remote telehealth care using computer technology is assuming a standard of care, particularly, with COVID-19 patients with attempts to reduce viral spread.\n\nObjectiveTo describe the clinical practice experience using telemedicine towards COVID-19 and the respective clinical outcomes.\n\nMethodsWe performed a pilot open-label non-randomized, controlled clinical trial. The patients were divided into four groups, according severity of symptoms: (1) asymptomatic, (2) mild symptoms, (3) moderate symptoms and (4) severe symptoms, and were followed up for five days, counted from the beginning of the symptoms. A drug intervention was performed in group 3, for which the protocol followed as suggested by the International Pulmonology Societys consensus for adults with moderate symptoms: first day (attack phase) hydroxychloroquine sulfate 400 mg 12/12h; second to fifth day (maintenance phase) 200 mg (half pill) 12/12h. The medication was associated with azithromycin 500mg once a day for five days. For children with moderate symptoms were used: hydroxychloroquine sulfate 6.5 mg/kg/dose every 12 hours in the first day and 3.25 mg/kg/dose every 12 hours from day 2 to 5. The therapeutic response was telemonitored. Group 4 patients were directly oriented to seek hospital care. During the use of the drugs, the patients were telemonitored daily.\n\nResultsOne hundred eighty-seven patients were seen with mean age of 37,6 years ({+/-}15,6). The most frequent symptom was cough (57,6%), followed by malaise (60,3%), fever (41,1%), headache (56,0%), muscle pain (51,1%). Of all the patients that sought telemedicine service in our center, 23% were asymptomatic despite contact with people with probable diagnostic of COVID-19; 29,4% reported mild symptoms, 43,9% moderate symptoms, and 3,7% severe symptoms. It was possible to observe in patients treated their symptoms of COVID-19 (group 3) with hydroxychloroquine and azithromycin for five days, presented statistically better improvement of the symptoms when compared to those that did not follow the protocol (p = 0.039). Three patients were hospitalized and discharged after recovery.\n\nConclusionsOur study showed that patients with COVID-19 who had delivery of health care through telemedicine initiated in early stages of the disease presented satisfactory clinical response, reducing the need of face-to-face consultations and hospitalizations. Our results indicate that the use of telemedicine with diagnosis and drug treatment protocols is a safe and effective strategy to reduce overload of health services and the exposure of healthcare providers and the general population to infected patients in a pandemic situation.\n\nTrial registrationRBR-658khm\n\nHuman Research Ethics Committee number: 30246520.0.0000.0069", + "rel_num_authors": 13, "rel_authors": [ { - "author_name": "Kok Yew Ng", - "author_inst": "Ulster University" + "author_name": "Michelle Chechter", + "author_inst": "Centro Medico Mazzei, Sao Paulo, Brazil" }, { - "author_name": "Tudor A Codreanu", - "author_inst": "State Health Incident Coordination Centre, Department of Health Western Australia, Perth, Western Australia, Australia." + "author_name": "Gustavo Maximiliano Dutra da Silva", + "author_inst": "Sao Francisco University (USF), Braganca Paulista, Brazil" }, { - "author_name": "Meei Mei Gui", - "author_inst": "Queen's University Belfast" + "author_name": "Thomas Gabriel Miklos", + "author_inst": "Department of Obstetrics and Gynecology - Santa Casa of Sao Paulo Medical School, Sao Paulo (FCMSCSP), Brazil." }, { - "author_name": "Pardis Biglarbeigi", - "author_inst": "Flowminder Foundation" + "author_name": "Marta Maria Kemp", + "author_inst": "Kemp Institute of Integrative Health, Sao Paulo Brazil" }, { - "author_name": "Dewar Finlay", - "author_inst": "Ulster University" + "author_name": "Nilzio Antonio da Silva", + "author_inst": "Federal University of Goias, Medical School, Department of Medical Clinic, Goiania, Brazil" }, { - "author_name": "James McLaughlin", - "author_inst": "Ulster University" + "author_name": "Gabriel Lober Lober", + "author_inst": "Laboratory DASA, Sao Paulo, Brazil" + }, + { + "author_name": "Marcela Ferreira Tavares Zanut", + "author_inst": "Instituto CEMA, Sao Paulo, Brazil" + }, + { + "author_name": "Rute Alves Pereira e Costa", + "author_inst": "Sociedade Brasileira de Valorizacao das Sociedades Medicas SOBEMED, Sao Paulo, Brazil" + }, + { + "author_name": "Aline Pinheiro dos Santos Cortada", + "author_inst": "Clinical Research Center of Associacao de Assistencia a Crianca Deficiente, Sao Paulo, Brazil" + }, + { + "author_name": "Luciana de Nazare Lima da Cruz", + "author_inst": "Centro Medico Mazzei, Sao Paulo, Brazil" + }, + { + "author_name": "Paulo Macio Porto de Melo", + "author_inst": "Departamento de Neurocirurgia, Hospital Militar de Area de Sao Paulo, Brazil" + }, + { + "author_name": "Bruno Campello de Souza", + "author_inst": "Departamento de Ciencias, Universidade Federal de Pernambuco, Recife, Brazil" + }, + { + "author_name": "Morton Aaron Scheinberg", + "author_inst": "Hospital Israelita Albert Einstein, Sao Paulo, Brazil" } ], "version": "1", "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2021.11.05.466755", @@ -519000,49 +518327,29 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.11.03.21265819", - "rel_title": "Effectiveness of COVID-19 Vaccines and Post-vaccination SARS-COV 2 Infection, Hospitalization, and Mortality: a Systematic Review and Meta-analysis of Observational Studies", + "rel_doi": "10.1101/2021.11.02.21265826", + "rel_title": "The basic reproduction number of COVID-19 across Africa", "rel_date": "2021-11-03", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.03.21265819", - "rel_abs": "Introduction & ObjectiveVaccination is one of the most important and effective ways of preventing infectious diseases, and has recently been used in the COVID-19 epidemic and pandemic. The present meta-analysis study aimed to evaluate the effectiveness of COVID-19 vaccines in reducing the incidence of infection, hospitalization, and mortality in observational studies.\n\nMaterials and MethodsA systematic search was performed independently in Scopus, PubMed, ProQuest, and Google Scholar electronic databases as well as Preprint servers using the keywords under study. The heterogeneity of the studies was assessed using I2 and {chi}2 statistics, according to which the I2 of > 50% and P -value <0.1 was reported as heterogeneity of the studies. In addition, the Pooled Vaccine Effectiveness (PVE) obtained from the studies was calculated by converting (1-Pooled estimate x 100%) based on the type of outcome.\n\nResultsA total of 54 records were included in this meta-analysis. The rate of PVE against SARS-COV 2 infection was about 71% (OR = 0.29, 95% CI: 0.23-0.36) in the first dose and 87% (OR = 0.13, 95% CI: 0.08-0.21) in the second, and the highest effectiveness in the first and second doses was that of BNT162b2 mRNA and combined studies. The PVE versus COVID-19-associated hospitalization was 73% (OR = 0.27, 95% CI: 0.18-0.41) in the first dose and 89% (OR = 0.11, 95% CI: 0.07-0.17) in the second. mRNA-1273 and combined studies in the first dose and ChAdOx1 and mRNA-1273 in the second dose had the highest effectiveness. Regarding the COVID-19-related mortality, PVE was about 28% (HR = 0.39, 95% CI: 0.23-0.45) in the first dose and 89% (HR = 0.11, 95% CI: 0.03-0.43) in the second.\n\nConclusionThe evidence obtained from this study showed that the effectiveness of BNT162b2 mRNA, mRNA-1273, and ChAdOx1 in the first and second doses, and even combined studies were associated with increased effectiveness against SARS-COV2 infection, hospitalization, and death from COVID-19. In addition, considering that the second dose was significantly more efficient than the first one, a booster dose injection could be effective in high-risk individuals. On the other hand, it was important to observe other prevention considerations in the first days after taking the first dose.", - "rel_num_authors": 9, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.02.21265826", + "rel_abs": "The pandemic of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) took the world by surprise. Following the first outbreak of COVID-19 in December 2019, several models have been developed to study and understand its transmission dynamics. Although the spread of COVID-19 is being slowed down by vaccination and other interventions, there is still a need to have a clear understanding of the evolution of the pandemic across countries, states and communities. To this end, there is a need to have a clearer picture of the initial spread of the disease in different regions. In this project, we used a simple SEIR model and a Bayesian inference framework to estimate the basic reproduction number of COVID-19 across Africa. Our estimates vary between 1.98 (Sudan) and 9.66 (Mauritius), with a median of 3.67 (90% CrI: 3.31 - 4.12). The estimates provided in this paper will help to inform COVID-19 modeling in the respective countries/regions.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Kazem Rahmani", - "author_inst": "Iran Unoversity of medical sciences" - }, - { - "author_name": "Rasoul Shavaleh", - "author_inst": "Iran University of Medical Sciences" - }, - { - "author_name": "Mahtab Forouhi", - "author_inst": "Shahid Beheshti University of Medical Sciences" - }, - { - "author_name": "Hamideh Feiz Disfani", - "author_inst": "Mashhad University of Medical Sciences" - }, - { - "author_name": "Mostafa Kamandi", - "author_inst": "Mashhad Universityof Medical Sciences" - }, - { - "author_name": "Aram Asareh Zadegan Dezfuli", - "author_inst": "Ahvaz Jundishapour University of Medical Sciences" + "author_name": "Sarafa Adewale Iyaniwura", + "author_inst": "The University of British Columbia" }, { - "author_name": "Rozita Khatamian Oskooi", - "author_inst": "Birjand University of Medical Sciences" + "author_name": "Muhammad Rabiu Musa", + "author_inst": "university of KwaZulu-Natal" }, { - "author_name": "Molood Foogerdi", - "author_inst": "Birjand University of Medical Sciences" + "author_name": "Jummy F. David", + "author_inst": "York University" }, { - "author_name": "Moslem Soltani", - "author_inst": "Mashhad University of Medical sciences" + "author_name": "Jude Dzevela Kong", + "author_inst": "York University" } ], "version": "1", @@ -521530,51 +520837,43 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2021.10.31.21265672", - "rel_title": "Chest X-ray Severity and its Association with Outcomes in Patients with COVID-19 Presenting to the Emergency Department", + "rel_doi": "10.1101/2021.10.31.21265711", + "rel_title": "Cross-border transmissions of delta substrain AY.29 during Olympic and Paralympic Games", "rel_date": "2021-11-01", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.31.21265672", - "rel_abs": "BackgroundSeverity of radiographic abnormalities on chest X-ray (CXR) in patients with COVID-19 has been shown to be associated with worse outcomes, but studies are limited by different scoring systems, sample size, patient age and study duration. Data regarding the longitudinal evolution of radiographic abnormalities and its association with outcomes is scarce. We sought to evaluate these questions using a well-validated scoring system (the Radiographic Assessment of Lung Edema [RALE] score) using data over 6 months from a large, multi-hospital healthcare system.\n\nMethodsWe collected clinical and demographic data and quantified radiographic edema on CXRs obtained in the emergency department (ED) as well as on days 1-2 and 3-5 (in those admitted) in patients with a nasopharyngeal swab positive for SARS-CoV-2 PCR visiting the ED for COVID-19-related complaints between March and September 2020. We examined the association of baseline and longitudinal evolution of radiographic edema with severity of hypoxemia and clinical outcomes.\n\nResults870 patients were included (median age 53.6, 50.8% female). Inter-rate agreement for RALE scores was excellent (ICC = 0.84, 95% CI 0.82 - 0.87, p < 0.0001). RALE scores correlated with hypoxemia as quantified by SpO2-FiO2 ratio (r = -0.42, p < 0.001). Admitted patients had higher RALE scores than those discharged (6 [2, 11] vs 0 [0, 3], p < 0.001). An increase of RALE score of 4 or more was associated with worse 30-day survival (p < 0.01). Larger increases in the RALE score were associated with worse survival.\n\nConclusionsThe RALE score is reproducible and easily implementable in adult patients presenting to the ED with COVID-19. Its association with physiologic parameters and outcomes at baseline and longitudinally makes it a readily available tool for prognostication and early ICU triage, particularly in patients with worsening radiographic edema.", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.31.21265711", + "rel_abs": "Tokyo Olympic and Paralympic Games, postponed for COVID-19 pandemic, were finally held in summer of 2021. Just before the games, alpha variant was being replaced with more contagious delta variant (B.1.617.2). AY.4 substrain AY.29, which harbors two additional characteristic mutations of 5239C>T (NSP3 Y840Y) and 5514T>C (NSP3 V932A), emerged in Japan and became the dominant strain in Tokyo by the time of the Olympic Games. As of October 18, 98 AY.29 samples are identified in 16 countries outside of Japan. Phylogenetic analysis and ancestral searches identified 46 distinct introductions of AY.29 strains into those 16 countries. United States has 44 samples with 10 distinct introductions, and United Kingdom has 13 distinct AY.29 strains introduced in 16 samples. Other countries or regions with multiple introductions of AY.29 are Canada, Germany, South Korea, and Hong Kong while Italy, France, Spain, Sweden, Belgium, Peru, Australia, New Zealand, and Indonesia have only one distinct strain introduced. There exists no unambiguous evidence that Olympic and Paralympic Games induced cross-border transmission of the delta substrain AY.29. Since most of unvaccinated countries are also under sampled for genome analysis with longer lead time for data sharing, it will take longer to capture the whole picture of cross-border transmissions of AY.29.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Daniel Kotok", - "author_inst": "Cleveland Clinic Florida" - }, - { - "author_name": "Jose Rivera Robles", - "author_inst": "Cleveland Clinic Florida" - }, - { - "author_name": "Christine Girard", - "author_inst": "Cleveland Clinic Florida" + "author_name": "Takahiko Koyama", + "author_inst": "IBM T. J. Watson Research Center" }, { - "author_name": "Shruti Shettigar", - "author_inst": "Cleveland Clinic Florida" + "author_name": "Reitaro Tokumasu", + "author_inst": "IBM Research - Tokyo" }, { - "author_name": "Allen Lavina", - "author_inst": "Cleveland Clinic Florida" + "author_name": "Kotoe Katayama", + "author_inst": "The Institute of Medical Science, The University of Tokyo" }, { - "author_name": "Samantha Gillenwater", - "author_inst": "Cleveland Clinic Florida" + "author_name": "Ayumu Saito", + "author_inst": "The Institute of Medical Science, The University of Tokyo" }, { - "author_name": "Andrew Kim", - "author_inst": "Cleveland Clinic Florida" + "author_name": "Michiharu Kudo", + "author_inst": "IBM Research - Tokyo" }, { - "author_name": "Anas Hadeh", - "author_inst": "Cleveland Clinic Florida" + "author_name": "Seiya Imoto", + "author_inst": "The Institute of Medical Science, The University of Tokyo" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "respiratory medicine" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2021.10.29.21265555", @@ -523336,33 +522635,45 @@ "category": "respiratory medicine" }, { - "rel_doi": "10.1101/2021.10.29.21265691", - "rel_title": "Assessment of the fatality rate and transmissibility taking account of undetected cases during an unprecedented COVID-19 surge in Taiwan", + "rel_doi": "10.1101/2021.10.29.21265628", + "rel_title": "Contributions of occupation characteristics and educational attainment to racial/ethnic inequities in COVID-19 mortality", "rel_date": "2021-10-30", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.29.21265691", - "rel_abs": "BackgroundDuring the COVID-19 outbreak in Taiwan between May 11 and June 20, 2021, the observed fatality rate (FR) was 5.3%, higher than the global average at 2.1%. The high number of reported deaths suggests that hospital capacity was insufficient. However, many unexplained deaths were subsequently identified as cases, indicating that there were a few undetected cases, hence resulting in a higher estimate of FR. Estimating the number of total infected cases or knowing how to reduce the undetected cases can allow an accurate estimation of the fatality rate (FR) and effective reproduction number (Rt).\n\nMethodsAfter adjusting for reporting delays, we estimated the number of undetected cases using reported deaths that were and were not previously detected. The daily FR and Rt were calculated using the number of total cases (i.e. including undetected cases). A logistic regression model was developed to predict the detection ratio among deaths using selected predictors from daily testing and tracing data.\n\nResultsThe estimated true daily case number at the peak of the outbreak on May 22 was 897, which was 24.3% higher than the reported number, but the difference became less than 4% on June 9 and afterward. After taking account of undetected cases, our estimated mean FR (4.7%) was still high but the daily rate showed a large decrease from 6.5% on May 19 to 2.8% on June 6. Rt reached a maximum value of 6.4 on May 11, compared to 6.0 estimated using the reported case number. The decreasing proportion of undetected cases was associated with the increases in the ratio of the number of tests conducted to reported cases, and the proportion of cases that are contact-traced before symptom onset.\n\nConclusionsIncreasing testing capacity and tracing efficiency can lead to a reduction of hidden cases and hence improvement in epidemiological parameter estimation.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.29.21265628", + "rel_abs": "BackgroundRacial/ethnic inequities in COVID-19 mortality are hypothesized to be driven by education and occupation, but limited empirical evidence has assessed these mechanisms.\n\nObjectiveTo quantify the extent to which educational attainment and occupation explain racial/ethnic inequities in COVID-19 mortality.\n\nDesignObservational cohort.\n\nSettingCalifornia.\n\nParticipantsCalifornians aged 18-65 years.\n\nMeasurementsWe linked all COVID-19-confirmed deaths in California through February 12, 2021 (N=14,783), to population estimates within strata defined by race/ethnicity, sex, age, USA nativity, region of residence, education, and occupation. We characterized occupations using measures related to COVID-19 exposure including essential sector, telework-ability, and wages. Using sex-stratified regressions, we predicted COVID-19 mortality by race/ethnicity if all races/ethnicities had the same education and occupation distribution as White people and if all people held the safest educational/occupational positions.\n\nResultsCOVID-19 mortality per 100,000 ranged from 15 for White and Asian females to 139 for Latinx males. Accounting for differences in age, nativity, and region, if all races/ethnicities had the education and occupation distribution of Whites, COVID-19 mortality would be reduced for Latinx males (-22%) and females (-23%), and Black males (-1%) and females (-8%), but increased for Asian males (+22%) and females (+23%). Additionally, if all individuals had the COVID-19 mortality associated with the safest educational and occupational position (Bachelors degree, non-essential, telework, highest wage quintile), there would have been 57% fewer COVID-19 deaths.\n\nConclusionEducational and occupational disadvantage are important risk factors for COVID-19 mortality across all racial/ethnic groups, especially Latinx individuals. Eliminating avoidable excess risk associated with low-education, essential, on-site, and low-wage jobs may reduce COVID-19 mortality and inequities, but is unlikely to be sufficient to achieve equity.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Hsiang-Yu Yuan", - "author_inst": "City University of Hong Kong" + "author_name": "Ellicott C. Matthay", + "author_inst": "University of California, San Francisco" }, { - "author_name": "M. Pear Hossain", - "author_inst": "City University of Hong Kong" + "author_name": "Kate A. Duchowny", + "author_inst": "University of California, San Francisco" }, { - "author_name": "Tzai-Hung Wen", - "author_inst": "National Taiwan University" + "author_name": "Alicia R Riley", + "author_inst": "University of California, Santa Cruz" }, { - "author_name": "Ming-Jiuh Wang", - "author_inst": "National Taiwan University Hospital" + "author_name": "Marilyn Thomas", + "author_inst": "University of California, San Francisco" + }, + { + "author_name": "Yea-Hung Chen", + "author_inst": "University of California, San Francisco" + }, + { + "author_name": "Kirsten Bibbins-Domingo", + "author_inst": "University of California, San Francisco" + }, + { + "author_name": "M. Maria Maria Glymour", + "author_inst": "University of California, San Francisco" } ], "version": "1", - "license": "cc0_ng", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -525218,35 +524529,35 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2021.10.27.466182", - "rel_title": "Efficacy of anti-microbial gel vapours against aerosolised coronavirus, bacteria, and fungi", + "rel_doi": "10.1101/2021.10.28.466298", + "rel_title": "Identification of COVID-19 and COPD common key genes and pathways using a protein-protein interaction approach", "rel_date": "2021-10-29", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.10.27.466182", - "rel_abs": "BackgroundThe urban population spends up to 90% of their time indoors. The indoor environment harbours a diverse microbial population including viruses, bacteria, and fungi. Pathogens present in the indoor environment can be transmitted to humans through aerosols.\n\nAimThis study evaluated the efficacy of an antimicrobial gel containing a mix of essential oils against aerosols of bacteria, fungi, and coronavirus.\n\nMethodsThe antimicrobial gel was allowed to vapourize inside a glass chamber for 10 or 20 minutes. Microbial aerosols of Escerichia coli, Aspergillus flavus spores or murine hepatitis virus MHV 1, a surrogate of SARS CoV-2 was passed through the gel vapours and then collected on a 6-stage Andersen sampler. The number of viable microbes present in the aerosols collected in the different stages were enumerated and compared to number of viable microbes in control microbial aerosols that were not exposed to the gel vapours.\n\nResultsVaporizing the antimicrobial gel for 10 and 20 minutes resulted in a 48% (p = 0.002 Vs. control) and 53% (p = 0.001 Vs. control) reduction in the number of MHV-1 in the aerosols, respectively. The antimicrobial gel vaporised for 10 minutes, reduced the number of viable E. coli by 51% (p = 0.032 Vs. control) and Aspergillus flavus spores by 72% (p=0.008 Vs. control) in the aerosols.\n\nConclusionsThe antimicrobial gel may be able to reduce aerosol transmission of microbes.", + "rel_link": "https://biorxiv.org/cgi/content/short/2021.10.28.466298", + "rel_abs": "Coronavirus disease (COVID-19) is an extremely contagious and cognitive disease that could cause immense hypoxemia. The rise in critically ill patients in epidemic regions has put enormous pressure on hospitals. There is a need to define extreme COVID-19 clinical determinants to optimize clinical diagnosis and the management system is strong. Chronic obstructive pulmonary disease (COPD) is linked to a rapidly increasing risk of death rates in population pneumonia. In this research, a network of protein-protein interaction (PPI) was developed using constructed datasets of COVID-19 and COPD genes to define the interrelationship between COVID-19 and COPD, how it affects each other, and the genes that are responsible for the process. The PPI network shows the top 10 common overlapping genes, which include IL10, TLR4, TNF, IL6, CXCL8, IL4, ICAM1, IFNG, TLR2, and IL18. These are the genes that COVID-19 and high-risk COPD patients are known to be expressed. These important genes shared by COVID-19 and COPD are involved in pathways such as malaria, African trypanosomiasis, inflammatory bowel disease, Chagas disease, influenza, and tuberculosis.", "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Parthasarathi Kalaiselvan", - "author_inst": "University of New South Wales" + "author_name": "Thiviya S. Thambiraja", + "author_inst": "Faculty of Health and Life Sciences, Management and Science University, Seksyen 13, 40100 Shah Alam, Selangor, Malaysia" }, { - "author_name": "Muhammad Yasir", - "author_inst": "University of New South Wales" + "author_name": "Kalimuthu Karuppanan", + "author_inst": "Division of Cardiovascular Medicine, Radcliffe Department of Medicine, Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK" }, { - "author_name": "Mark D. P. Willcox", - "author_inst": "University of New South Wales" + "author_name": "Gunasekaran Subramaniam", + "author_inst": "Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford, UK" }, { - "author_name": "Ajay Kumar Vijay", - "author_inst": "University of New South Wales" + "author_name": "Suresh Kumar", + "author_inst": "Faculty of Health and Life Sciences, Management and Science University, Seksyen 13, 40100 Shah Alam, Selangor, Malaysia" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by_nc_nd", "type": "new results", - "category": "microbiology" + "category": "bioinformatics" }, { "rel_doi": "10.1101/2021.10.26.466019", @@ -526964,39 +526275,59 @@ "category": "nephrology" }, { - "rel_doi": "10.1101/2021.10.20.21265103", - "rel_title": "The Relationship Between Food Security and Dietary Patterns Status with COVID-19 in Northeastern Iran: Protocol for a Case-Control Study", + "rel_doi": "10.1101/2021.10.19.21265200", + "rel_title": "Preclinical and clinical validation of a novel injected molded swab for molecular assay detection of SARS-CoV-2 virus", "rel_date": "2021-10-26", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.20.21265103", - "rel_abs": "BackgroundFood insecurity is defined as the limited or uncertain availability of enough food for a consistently active and healthy life. COVID-19 is a highly transmissible viral infection with high mortality due to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and, or the uncommon severe pneumonia. This study assesses the relationship between food security and dietary patterns status with COVID-19 in the North Khorasan province, Iran.\n\nMethodsThis case-control study will be conducted in the men and women aged 20-60 years improved from COVID-19 infection. The cases (n=124) and controls (n=124) were selected according to the eligibility criteria, including recently improved COVID-19 according to the positive COVID-19 PCR test. People referred to public and private laboratories or employees of public and private factories, offices, and departments of hospitals and universities (for the cases) and negative PCR tests without any clinical signs of COVID-19 infection (for the controls). The North Khorasan province was the target place. The groups are matched for age, sex, and body mass index (BMI). The assessments will include anthropometric measurements and general demographic, USDA 18-item food security (18item-FSSM), and 147-item food frequency (FFQ) questionnaires. Finally, the determination of the relationship between food security and dietary patterns status and associated socioeconomic factors with COVID-19 is done. P-value will be <0.05.\n\nDiscussionThis study would be the first assessment of the relationship between food security and dietary patterns status with COVID-19 disease. It may help planners and policymakers to manage food insecurity and unhealthy dietary patterns and later increasing the immune system and decreasing the incidence of COVID-19. Further studies are suggested.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.19.21265200", + "rel_abs": "During the COVID-19 public health emergency, many actions have been undertaken to help ensure that patients and health care providers had timely and continued access to high-quality medical devices to respond effectively. The development and validation of new testing supplies and equipment, including collection swab, help expand the availability and capability for various diagnostic, therapeutic, and protective medical devices in high demand during the COVID-19 emergency. Here, we report the validation of a new injection-molded anterior nasal swab, ClearTip, that was experimentally validated in a laboratory setting as well as in independent clinical studies in comparison to gold standard flocked swabs. We have also developed an in vitro anterior nasal tissue model, that offers an efficient and clinically relevant validation tool to replicate with high fidelity the clinical swabbing workflow, while being accessible, safe, reproducible, time and cost effective. ClearTip displayed a greater efficiency of release of inactivated virus in the benchtop model, confirmed by greater ability to report positive samples in a clinical study in comparison to flocked swabs. We also quantified in multi-center pre-clinical and clinical studies the detection of biological materials, as proxy for viral material, that showed a statistically significant difference in one study and a slight reduction in performance in comparison to flocked swabs. Taken together these results underscore the compelling benefits of non-absorbent injected molded anterior nasal swab for COVID-19 detection, comparable to standard flocked swabs. Injection-molded swabs, as ClearTip, could have the potential to support future swab shortage, due to its manufacturing advantages, while offering benefits in comparison to highly absorbent swabs in terms comfort, limited volume collection, and potential multiple usage.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Sepideh Badri-Fariman", - "author_inst": "Tabriz University of Medical Sciences" + "author_name": "Chiara Elia Ghezzi", + "author_inst": "University of Massachusetts Lowell" }, { - "author_name": "Bahram Pourghassem-Gargari", - "author_inst": "Tabriz University of Medical Sciences, Tabriz" + "author_name": "Devon R Hartigan", + "author_inst": "University of Massachusetts Lowell" }, { - "author_name": "Mahtab Badri-Fariman", - "author_inst": "Tehran University of Medical Sciences" + "author_name": "Justin Hardick", + "author_inst": "John Hopkins University School of Medicine" }, { - "author_name": "Mohammad Pourfridoni", - "author_inst": "Jiroft University of Medical Sciences" + "author_name": "Rebecca Gore", + "author_inst": "University of Massachusetts Lowell" + }, + { + "author_name": "Miryam Adelfio", + "author_inst": "University of Massachusetts Lowell" }, { - "author_name": "Milad Daneshi-Maskooni", - "author_inst": "Jiroft University of Medical Sciences" + "author_name": "Anyelo R Diaz", + "author_inst": "University of Massachusetts Lowell" + }, + { + "author_name": "Pamela D McGuiness", + "author_inst": "University of Massachusetts Lowell" + }, + { + "author_name": "Matthew L Robinson", + "author_inst": "John Hopkins University School of Medicine" + }, + { + "author_name": "Bryan O Buchholz", + "author_inst": "University of Massachusetts Lowell" + }, + { + "author_name": "Yukari C L Manabe", + "author_inst": "Johns Hopkins University School of Medicine" } ], "version": "1", "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "nutrition" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2021.10.19.21265177", @@ -528790,55 +528121,55 @@ "category": "health systems and quality improvement" }, { - "rel_doi": "10.1101/2021.10.25.21265422", - "rel_title": "Limited impact of Delta variants mutations in the effectiveness of neutralization conferred by natural infection or COVID-19 vaccines in a Latino population", + "rel_doi": "10.1101/2021.10.26.21265525", + "rel_title": "COVCOG 1: Factors predicting Cognitive Symptoms in Long COVID. A First Publication from the COVID and Cognition Study.", "rel_date": "2021-10-26", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.25.21265422", - "rel_abs": "The SARS-CoV-2 pandemic has impacted public health systems all over the world. The Delta variant seems to possess enhanced transmissibility, but no clear evidence suggests it has increased virulence. Our data shows that pre-exposed individuals had similar neutralizing activity against the authentic COVID-19 strain and the Delta and Epsilon variants. After one vaccine dose, the neutralization capacity expands to all tested variants. Healthy vaccinated individuals showed a limited breadth of neutralization. One vaccine dose induced similar neutralizing antibodies against the Delta compared to the authentic strain. However, even after two doses, this capacity only expanded to the Epsilon variant.", + "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.26.21265525", + "rel_abs": "Since its first emergence in December 2019, coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has evolved into a global pandemic. Whilst often considered a respiratory disease, a large proportion of COVID-19 patients report neurological symptoms, and there is accumulating evidence for neural damage in some individuals, with recent studies suggesting loss of gray matter in multiple regions, particularly in the left hemisphere. There are a number of mechanisms by which COVID-19 infection may lead to neurological symptoms and structural and functional changes in the brain, and it is reasonable to expect that many of these may translate into cognitive problems. Indeed, cognitive problems are one of the most commonly reported symptoms in those suffering from \"Long COVID\"--the chronic illness following COVID-19 infection that affects between 10-25% of sufferers. The COVID and Cognition Study is a part cross-sectional, part longitudinal, study documenting and aiming to understand the cognitive problems in Long COVID. In this first paper from the study, we document the characteristics of our sample of 181 individuals who had suffered COVID-19 infection, and 185 who had not. We explore which factors may be predictive of ongoing symptoms and their severity, as well as conducting an in-depth analysis of symptom profiles. Finally, we explore which factors predict the presence and severity of cognitive symptoms, both throughout the ongoing illness and at the time of testing. The main finding from this first analysis is that that severity of initial illness is a significant predictor of the presence and severity of ongoing symptoms, and that some symptoms during the acute illness--particularly limb weakness--may be more common in those that have more severe ongoing symptoms. Symptom profiles can be well described in terms of 5 or 6 factors, reflecting the variety of this highly heterogenous condition suffered by the individual. Specifically, we found that neurological and fatigue symptoms during the initial illness, and that neurological, gastro-intestinal, and cardiopulmonary symptoms during the ongoing illness, predicted experience of cognitive symptoms.", "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Carlos A Sariol", - "author_inst": "Unit of Comparative Medicine, Medical Sciences Campus, University of Puerto Rico," + "author_name": "Panyuan Guo", + "author_inst": "University of Cambridge" }, { - "author_name": "Crisanta Serrano", - "author_inst": "UPR-MSC" + "author_name": "Alvaro Benito Ballesteros", + "author_inst": "University of Cambridge" }, { - "author_name": "Edwin J. Ortiz", - "author_inst": "Unit of Comparative Medicine, School of Medicine, University of Puerto Rico" + "author_name": "Sabine P Yeung", + "author_inst": "University of Cambridge" }, { - "author_name": "Petraleigh Pantoja", - "author_inst": "Unit of Comparative Medicine, School of Medicine, University of Puerto Rico" + "author_name": "Ruby Liu", + "author_inst": "University of Cambridge" }, { - "author_name": "Lorna Cruz", - "author_inst": "University of Puerto Rico, Medical Sciences Campus" + "author_name": "Arka Saha", + "author_inst": "University of Cambridge" }, { - "author_name": "Teresa Arana", - "author_inst": "Department of Microbiology, School of Medicine, University of Puerto Rico" + "author_name": "Lyn Curtis", + "author_inst": "University of Exeter" }, { - "author_name": "Dianne Atehortua", - "author_inst": "Puerto Rico Science, Technology and Research Trust" + "author_name": "Muzaffer Kaser", + "author_inst": "University of Cambridge" }, { - "author_name": "Christina Pabon-Carrero", - "author_inst": "Puerto Rico Science, Technology and Research Trust" + "author_name": "Mark P Haggard", + "author_inst": "University of Cambridge" }, { - "author_name": "Ana M Espino", - "author_inst": "University of Puerto Rico Medical Sciences Campus" + "author_name": "Lucy G Cheke", + "author_inst": "University of Cambridge" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2021.10.25.21265504", @@ -530820,91 +530151,67 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2021.10.25.21265324", - "rel_title": "Safety and Immunogenicity of the COVID-19 Vaccine BNT162b2 in Patients Undergoing Chemotherapy for Solid Cancer", + "rel_doi": "10.1101/2021.10.24.21265455", + "rel_title": "Vaccine hesitancy for coronavirus SARS-CoV-2 in North India", "rel_date": "2021-10-25", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.25.21265324", - "rel_abs": "BackgroundAlthough COVID-19 severity in cancer patients is high, the safety and immunogenicity of the BNT162b2 mRNA COVID-19 vaccine in patients undergoing chemotherapy for solid cancers in Japan have not been reported.\n\nMethodsWe investigated the safety and immunogenicity of BNT162b2 in 41 patients undergoing chemotherapy for solid cancers and in healthy volunteers who received 2 doses of BNT162b2. We evaluated serum IgG antibody titers for S1 protein by ELISA at pre-vaccination, prior to the second dose and 14 days after the second vaccination in 24 cancer patients undergoing cytotoxic chemotherapy (CC group), 17 cancer patients undergoing immune checkpoint inhibitor therapy (ICI group) and 12 age-matched healthy volunteers (HV group). Additionally, inflammatory cytokine levels were compared between the HV and ICI groups at pre and the next day of each vaccination.\n\nResultsAnti-S1 antibody levels were significantly lower in the ICI and CC groups than in the HV group after the second dose (median optimal density: 0.241 [0.063-1.205] and 0.161 [0.07-0.857] vs 0.644 [0.259-1.498], p = 0.0024 and p < 0.0001, respectively). Adverse effect profile did not differ among the three groups, and no serious adverse event occurred. There were no differences in vaccine-induced inflammatory cytokines between the HV and ICI groups.\n\nConclusionAlthough there were no significant differences in adverse events in three groups, antibody titers were significantly lower in the ICI and CC groups than in the HV group. Further protection strategies should be considered in cancer patients undergoing CC or ICI.\n\nMini abstractTiters of anti-S1 antibody after the second dose of BNT162b2 were significantly lower in patients with solid tumors undergoing active anticancer treatment than in the healthy volunteers.", - "rel_num_authors": 18, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.24.21265455", + "rel_abs": "With the roll-out of worlds largest vaccine drive for Severe Acute Respiratory Syndrome coronavirus 2 (SARS-CoV-2) by Government of India on January 16 2021, India has targeted to vaccinate its entire population by the end of year 2021. Struggling with vaccine procurement and production earlier, India came up with these hurdles but the Indian population still did not seem to be mobilizing swiftly towards vaccination centers. With the initial hesitancy, as soon as the vaccination started to speedup, India was hit severely by the second wave. The severe second wave has slowed down the vaccination pace and also it was one of the major contributing factor of vaccine hesitancy. To understand the nature of vaccine hesitancy and factors underlying it, we conducted an extensive online and offline surveys in Varanasi and adjoining regions using structured questions. Majority of respondents though were students (0.633), respondents from other occupations such as government officials (0.10) were also included in the study. We observed several intriguing opinions on our eleven questions. It is interesting to note that the majority of the people (0.75) relied on fake news and did not take COVID-19 seriously. Most importantly, we noticed that a substantial proportion of respondents (relative frequency 0.151; mean age 24.8 years) reported that they are still not interested in vaccination. People who have neither been vaccinated nor have ever been infected may become the medium for spreading the virus and creating new variants. This could also lead to a resistant variant of the vaccine in the future. We expect that this extensive survey may help the government to upgrade their vaccination policies for COVID-19 in North India.", + "rel_num_authors": 12, "rel_authors": [ { - "author_name": "Yohei Funakoshi", - "author_inst": "Division of Medical Oncology/Hematology, Department of Medicine, Kobe University Hospital and Graduate School of Medicine, Kobe, Japan" - }, - { - "author_name": "Kimikazu Yakushijin", - "author_inst": "Division of Medical Oncology/Hematology, Department of Medicine, Kobe University Hospital and Graduate School of Medicine, Kobe, Japan" - }, - { - "author_name": "Goh Ohji", - "author_inst": "Division of Infection Disease Therapeutics, Department of Microbiology and Infectious Diseases, Kobe University Hospital and Graduate School of Medicine, Kobe, " - }, - { - "author_name": "Wataru Hojo", - "author_inst": "R&D, Cellspect Co., Ltd., Morioka, Japan" - }, - { - "author_name": "Hironori Sakai", - "author_inst": "R&D, Cellspect Co., Ltd., Morioka, Japan" - }, - { - "author_name": "Ryo Takai", - "author_inst": "Division of Gastrointestinal Surgery, Department of Surgery, Kobe University Hospital and Graduate School of Medicine, Kobe, Japan" + "author_name": "Utkarsh Srivastav", + "author_inst": "Department of Anthropology, Faculty of Social Sciences, Banaras Hindu University, Varanasi, India-221005" }, { - "author_name": "Taku Nose", - "author_inst": "Division of Medical Oncology/Hematology, Department of Medicine, Kobe University Hospital and Graduate School of Medicine, Kobe, Japan" + "author_name": "Avanish Kumar Tripathi", + "author_inst": "Department of Anthropology, Faculty of Social Sciences, Banaras Hindu University, Varanasi, India-221005" }, { - "author_name": "Shinya Ohata", - "author_inst": "Division of Medical Oncology/Hematology, Department of Medicine, Kobe University Hospital and Graduate School of Medicine, Kobe, Japan" + "author_name": "Jagjeet Kaur", + "author_inst": "Department of Anthropology, Faculty of Social Sciences, Banaras Hindu University, Varanasi, India-221005" }, { - "author_name": "Yoshiaki Nagatani", - "author_inst": "Division of Medical Oncology/Hematology, Department of Medicine, Kobe University Hospital and Graduate School of Medicine, Kobe, Japan" + "author_name": "Sabita Devi", + "author_inst": "Department of Anthropology, Faculty of Social Sciences, Banaras Hindu University, Varanasi, India-221005" }, { - "author_name": "Taiji Koyama", - "author_inst": "Division of Medical Oncology/Hematology, Department of Medicine, Kobe University Hospital and Graduate School of Medicine, Kobe, Japan" - }, - { - "author_name": "Akihito Kitao", - "author_inst": "Division of Medical Oncology/Hematology, Department of Medicine, Kobe University Hospital and Graduate School of Medicine, Kobe, Japan" + "author_name": "Shipra Verma", + "author_inst": "Department of Anthropology, Faculty of Social Sciences, Banaras Hindu University, Varanasi, India-221005" }, { - "author_name": "Meiko Nishimura", - "author_inst": "Division of Medical Oncology/Hematology, Department of Medicine, Kobe University Hospital and Graduate School of Medicine, Kobe, Japan" + "author_name": "Vanya Singh", + "author_inst": "Cytogenetics laboratory, Department of Zoology, Banaras Hindu University, Varanasi, India- 221005" }, { - "author_name": "Yoshinori Imamura", - "author_inst": "Division of Medical Oncology/Hematology, Department of Medicine, Kobe University Hospital and Graduate School of Medicine, Kobe, Japan" + "author_name": "Debashruti Das", + "author_inst": "Cytogenetics laboratory, Department of Zoology, Banaras Hindu University, Varanasi, India- 221005" }, { - "author_name": "Naomi Kiyota", - "author_inst": "Division of Medical Oncology/Hematology, Department of Medicine, Kobe University Hospital and Graduate School of Medicine, Kobe, Japan" + "author_name": "Prajjval Pratap Singh", + "author_inst": "Cytogenetics laboratory, Department of Zoology, Banaras Hindu University, Varanasi, India- 221005" }, { - "author_name": "Kenichi Harada", - "author_inst": "Division of Urology, Department of Surgery, Kobe University Hospital and Graduate School of Medicine, Kobe, Japan" + "author_name": "Pradeep Kumar", + "author_inst": "Department of Biotechnology, VBS Purvanchal University, Jaunpur, India-222001" }, { - "author_name": "Yugo Tanaka", - "author_inst": "Division of Thoracic Surgery, Department of Surgery, Kobe University Hospital and Graduate School of Medicine, Kobe, Japan" + "author_name": "Vandana Rai", + "author_inst": "Department of Biotechnology, VBS Purvanchal University, Jaunpur, India-222001" }, { - "author_name": "Yasuko Mori", - "author_inst": "Division of Clinical Virology, Center for Infectious Diseases, Kobe University Graduate School of Medicine, Kobe, Japan" + "author_name": "Rakesh Pandey", + "author_inst": "Department of Psychology, Banaras Hindu University, Varanasi-221005, India" }, { - "author_name": "Hironobu Minami", - "author_inst": "Division of Medical Oncology/Hematology, Department of Medicine, Kobe University Hospital and Graduate School of Medicine, Kobe, Japan" + "author_name": "Gyaneshwer Chaubey", + "author_inst": "Cytogenetics laboratory, Department of Zoology, Banaras Hindu University, Varanasi, India- 221005" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "oncology" + "category": "health systems and quality improvement" }, { "rel_doi": "10.1101/2021.10.20.21265301", @@ -533066,47 +532373,59 @@ "category": "occupational and environmental health" }, { - "rel_doi": "10.1101/2021.10.19.21265193", - "rel_title": "Use and impact of virtual primary care on quality and safety: public perspectives during the COVID-19 pandemic", + "rel_doi": "10.1101/2021.10.19.21265190", + "rel_title": "Can the Rapid Antigen Test for COVID-19 Replace RT-PCR: A Meta-analysis of Test Agreement", "rel_date": "2021-10-22", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.19.21265193", - "rel_abs": "BackgroundWith the onset of COVID-19, primary care has swiftly transitioned from face-to-face to virtual care, yet it remains largely unknown how this has impacted on the quality and safety of care.\n\nAimTo evaluate patient use of virtual primary care models during COVID-19 in terms of change in uptake, perceived impact on the quality and safety of care, and willingness of future use.\n\nDesign and settingAn online cross-sectional survey was administered to the public across the United Kingdom, Sweden, Italy and Germany.\n\nMethodsMcNemar tests were conducted to test pre- and post pandemic differences in uptake for each technology. One-way analysis of variance was conducted to examine patient experience ratings and perceived impacts on healthcare quality and safety across demographic characteristics.\n\nResultsRespondents (N=6,326) reported an increased use of telephone consultations (+6.3%, P<.001), patient-initiated services (+1.5%, n=98, p<0.001), video consultations (+1.4%, P<.001), remote triage (+1.3, p<0.001), and secure messaging systems (+0.9%, P=.019). Experience rates using virtual care technologies were higher for men (2.39{+/-}0.96 vs 2.29{+/-}0.92, P<.001), those with higher literacy (2.75{+/-}1.02 vs 2.29{+/-}0.92, P<.001), and participants from Germany (2.54{+/-}0.91, P<.001). Healthcare timeliness and efficiency were the quality dimensions most often reported as being positively impacted by virtual technologies (60.2%, n=2,793 and 55.7%, n=2,401, respectively), followed by effectiveness (46.5%, n=1,802), safety (45.5%, n=1,822), patient-centredness (45.2%, n=45.2) and equity (42.9%, n=1,726). Interest in future use was highest for telephone consultations (55.9%), followed by patient-initiated digital services (56.1%), secure messaging systems (43.4%), online triage (35.1%), video consultations (37.0%), and chat consultations (30.1%), although significant variation was observed between countries and patient characteristics.\n\nConclusionFuture work must examine the drivers and determinants of positive experiences using remote care to co-create a supportive environment that ensures equitable adoption and use across different patient groups. Comparative analysis between countries and health systems offers the opportunity for policymakers to learn from best practices internationally.", - "rel_num_authors": 7, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.19.21265190", + "rel_abs": "BackgroundSeveral studies have compared the performance of reverse transcription-polymerase chain reaction (RT-PCR) and antigen rapid diagnostic tests (Ag-RDTs) as tools to diagnose SARS-CoV-2 disease (COVID-19). As the performance of Ag-RDT may vary among different products and viral load scenarios, the clinical utility of the Ag-RDT remains unclear. Our aim is to assess the diagnostic agreement between Ag-RDTs and RT-PCR in testing for COVID-19 across different products and cycle threshold (Ct) values.\n\nMethodsAn evidence synthesis and meta-analysis of Positive Percent Agreement (PPA) and Negative Percent Agreement (NPA) was conducted after an exhaustive search of five databases to locate published studies that compared Ag-RDT to RT-PCR and reported quantitative comparison results. After the screening, quality assessment, and data extraction, the synthesis of pooled estimates was carried out utilizing the quality-effects (QE) model and Freeman-Tukey double arcsine transformation (FTT) for variance stabilization. Subgroup analysis was also conducted to evaluate the tests diagnostic agreement across distinctive products and Ct-value thresholds.\n\nFindingsA total of 420 studies were screened by title and abstract, of which 39 were eventually included in the analysis. The overall NPA was 99.4% (95%CI 98.8-99.8, I2=91.40%). The PPA was higher in lower Ct groups such as groups with Ct <20 and Ct <25, which had an overall PPA of 95.9% (95%CI 92.7-98.2, I2=0%) and 96.8% (95%CI 95.2-98.0, I2=50.1%) respectively. This is in contrast to groups with higher Ct values, which had relatively lower PPA. Panbio and Roche Ag-RDTs had the best consistent overall PPA across different Ct groups especially in groups with Ct <20 and Ct <25.\n\nInterpretationThe findings of our meta-analysis support the use of Ag-RDTs in lieu of RT-PCR for decision making regarding COVID-19 control measures, since the enhanced capacity of RT-PCR to detect disease in those that are Ag-RDT negative will be unlikely to have much public health utility. This step will drastically reduce the cost and time in testing for COVID-19.\n\nFundingThis research did not receive any specific funding.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Ana Luisa Neves", - "author_inst": "NIHR Patient Safety Translational Research Centre, Imperial College" + "author_name": "Ibrahim Mohamed Elmakaty Sr.", + "author_inst": "Qatar University, College of Medicine" }, { - "author_name": "Jackie van Dael", - "author_inst": "NIHR Patient Safety Translational Research Centre, Imperial College" + "author_name": "Abdelrahman Ahmed Elsayed Sr.", + "author_inst": "Qatar University, College of Medicine" }, { - "author_name": "Niki O'Brien", - "author_inst": "Institute of Global Health Innovation, Imperial College" + "author_name": "Rama Ghassan Hommos", + "author_inst": "Qatar University, College of Medicine" }, { - "author_name": "Kelsey Flott", - "author_inst": "NIHR Patient Safety Translational Research Centre, Imperial College" + "author_name": "Ruba Shakib Abdo", + "author_inst": "Qatar University, College of Medicine" }, { - "author_name": "Saira Ghafur", - "author_inst": "Institute of Global Health Innovation, Imperial College" + "author_name": "Amira Gamal Mohamed", + "author_inst": "Qatar University, College of Medicine" }, { - "author_name": "Ara Darzi", - "author_inst": "Institute of Global Health Innovation, Imperial College" + "author_name": "Zahra Badreldien Yousif", + "author_inst": "Qatar University, College of Medicine" }, { - "author_name": "Erik Mayer", - "author_inst": "NIHR Patient Safety Translational Research Centre, Imperial College" + "author_name": "Maryam Mohammed Fakhroo", + "author_inst": "Qatar University, College of Medicine" + }, + { + "author_name": "Abdulrahman Ahmed Alansari", + "author_inst": "Qatar University, College of Medicine" + }, + { + "author_name": "Peter V. Coyle", + "author_inst": "Hamad Medical Corporation" + }, + { + "author_name": "Suhail A. R. Doi", + "author_inst": "Department of Population Medicine, College of Medicine, QU Health, Qatar University" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "health systems and quality improvement" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2021.10.19.21265187", @@ -535139,41 +534458,49 @@ "category": "pharmacology and toxicology" }, { - "rel_doi": "10.1101/2021.10.19.464951", - "rel_title": "Preparation of ingestible antibodies to neutralize the binding of SarsCoV2 RBD (receptor binding domain) to human ACE2 Receptor", + "rel_doi": "10.1101/2021.10.19.463727", + "rel_title": "Neutralization of Mu and C.1.2 SARS-CoV-2 Variants by Vaccine-elicited Antibodies in Individuals With and Without Previous History of Infection", "rel_date": "2021-10-20", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.10.19.464951", - "rel_abs": "COVID19 continues to be a serious threat to human health and mortality. There is dire need for new solutions to combat this pandemic especially for those individuals who are not vaccinated or unable to be vaccinated and continue to be exposed to the SARSCoV2. In addition, the emergence of new more transmissible variants such as delta pose additional threat from this virus.\n\nTo explore another solution for prevention and treatment of COVID 19, we have produced chicken egg derived IgY antibodies against the Receptor binding domain (RBD) of SARSCoV2 spike protein which is involved in binding to human cell ACE2 receptors. The - RBD IgY effectively neutralize the binding of RBD to ACE2 and prevent pseudovirus entry in a PRNT assay. Importantly our anti-RBD IgY also neutralize the binding of Sars CoV2 delta variant RBD to ACE2. Given that chicken egg derived IgY are safe and permissible for human consumption, we plan to develop these ingestible antibodies for prevention of viral entry in the oropharyngeal and digestive tract in humans as passive immunotherapy.", - "rel_num_authors": 6, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.10.19.463727", + "rel_abs": "Recently identified SARS-CoV-2 variants Mu and C.1.2 have mutations in the receptor binding domain and N- and C-terminal domains that might confer resistance to natural and vaccine-elicited antibody. Analysis with pseudotyped lentiviruses showed that viruses with the Mu and C.1.2 spike proteins were partially resistant to neutralization by antibodies in convalescent sera and those elicited by mRNA and adenoviral vector-based vaccine-elicited antibodies. Virus with the C.1.2 variant spike, which is heavily mutated, was more neutralization-resistant than that of any of variants of concern. The resistance of the C.1.2 spike was caused by a combination of the RBD mutations N501Y, Y449H and E484K and the NTD mutations. Although Mu and C.1.2 were partially resistant to neutralizing antibody, neutralizing titers elicited by mRNA vaccination remained above what is found in convalescent sera and thus are likely to remain protective against severe disease. The neutralizing titers of sera from infection-experienced BNT162b2-vaccinated individuals, those with a history of previous SARS-CoV-2 infection, were as much as 15-fold higher than those of vaccinated individuals without previous infection and effectively neutralized all of the variants. The findings demonstrate that individuals can raise a broadly neutralizing humoral response by generating a polyclonal response to multiple spike protein epitopes that should protect against current and future variants.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Gopi Kadiyala", - "author_inst": "Kyntox Bio Private Limited" + "author_name": "Takuya Tada", + "author_inst": "NYU Grossman School of Medicine" }, { - "author_name": "Subramanian Iyer", - "author_inst": "ProdIgY Bio" + "author_name": "Hao Zhou", + "author_inst": "NYU Grossman School of Medicine" }, { - "author_name": "Kranti Meher", - "author_inst": "Reagene Biosciences Private Limited" + "author_name": "Belinda M Dcosta", + "author_inst": "NYU Grossman School of Medicine" }, { - "author_name": "Subhramanyam Vangala", - "author_inst": "Reagene Biosciences Private Limited" + "author_name": "Marie I Samanovic", + "author_inst": "NYU Grossman School of Medicine" }, { - "author_name": "Satish Chandran", - "author_inst": "ProdIgY Bio" + "author_name": "Amber Cornelius", + "author_inst": "NYU Grossman School of Medicine" }, { - "author_name": "Uday Saxena", - "author_inst": "Reagene Biosciences Private Limited" + "author_name": "Ramin Herati", + "author_inst": "NYU Grossman School of Medicine" + }, + { + "author_name": "Mark J Mulligan", + "author_inst": "New York University Grossman School of Medicine" + }, + { + "author_name": "Nathaniel R Landau", + "author_inst": "NYU Grossman School of Medicine" } ], "version": "1", - "license": "cc_by", + "license": "cc_no", "type": "new results", "category": "immunology" }, @@ -536909,59 +536236,27 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.10.18.464882", - "rel_title": "Rapid and Effective Inactivation of SARS-CoV-2 by a Cationic Conjugated Oligomer with Visible Light: Studies of Antiviral Activity in Solutions and on Supports", + "rel_doi": "10.1101/2021.10.18.21265128", + "rel_title": "The effect of circulating zinc, selenium, copper and vitamin K1 on COVID-19 outcomes: a Mendelian randomization study", "rel_date": "2021-10-19", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.10.18.464882", - "rel_abs": "This paper presents results of a study of a new cationic oligomer that contains end groups and a chromophore affording inactivation of SARS-Cov-2 by visible light irradiation in solution or as a solid coating on wipes paper and glass fiber filtration substrates. A key finding of this study is that the cationic oligomer with a central thiophene ring and imidazolium charged groups give outstanding performance in both killing of E. coli bacterial cells and inactivation of the virus at very short times. Our introduction of cationic N-Methyl Imidazolium groups enhances the light-activation process for both E. coli and SARS-Cov-2 but dampens the dark killing of the bacteria and eliminates the dark inactivation of the virus. For the studies with this oligomer in solution at concentration of 1 g/mL and E. coli we obtain 3 log killing of the bacteria with 10 min irradiation with LuzChem cool white lights (mimicking indoor illumination). With the oligomer in solution at a concentration of 10 g/mL, we observe 4 logs inactivation (99.99 %) in 5 minutes of irradiation and total inactivation after 10 min. The oligomer is quite active against E. coli on oligomer-coated wipes papers and glass fiber filter supports. The SARS-Cov-2 is also inactivated by the oligomer coated glass fiber filter papers. This study indicates that these oligomer-coated materials may be very useful as wipes and filtration materials.", - "rel_num_authors": 10, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.18.21265128", + "rel_abs": "BackgroundPrevious results from observational, interventional studies and in vitro experiments suggest that certain micronutrients have anti-viral and immunomodulatory activities. In particular, it has been hypothesized that zinc, selenium, copper and vitamin K1 have strong potential for prophylaxis and treatment of COVID-19.\n\nObjectivesWe aimed to test whether genetically predicted Zn, Se, Cu or vitamin K1 levels have a causal effect on COVID-19 related outcomes: risk of infection, hospitalization and critical illness.\n\nMethodsWe employed two-sample Mendelian Randomization (MR) analysis. Our genetic variants derived from European-ancestry GWAS reflected circulating levels of Zn, Cu, Se in red blood cells as well as Se and vitamin K1 in serum/plasma. For the COVID-19 outcome GWAS, we used infection, hospitalization or critical illness. Our inverse-variance weighted (IVW) MR analysis was complemented by sensitivity analyses: more liberal selection of variants at genome-wide subsignificant threshold, MR-Egger and weighted median/mode tests.\n\nResultsCirculating micronutrient levels show limited evidence of association with COVID-19 infection with odds ratio [OR] ranging from 0.97 (95% CI: 0.87-1.08, p-value=0.55) for zinc to 1.07 (95% CI: 1.00-1.14, p-value=0.06) - ie. no beneficial effect for copper, per 1 SD increase in exposure. Similarly minimal evidence was obtained for the hospitalization and critical illness outcomes with OR from 0.98 (95% CI: 0.87-1.09, p-value=0.66) for vitamin K1 to 1.07 (95% CI: 0.88-1.29, p-value=0.49) for copper, and from 0.93 (95% CI: 0.72-1.19, p-value=0.55) for vitamin K1 to 1.21 (95% CI: 0.79-1.86, p-value=0.39) for zinc, respectively.\n\nConclusionsThis study does not provide evidence that supplementation with zinc, selenium, copper or vitamin K1 can prevent SARS-CoV-2 infection, critical illness or hospitalization for COVID-19.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Kemal Kaya", - "author_inst": "University of New Mexico" - }, - { - "author_name": "Mohammed I Khalil", - "author_inst": "University of New Mexico" - }, - { - "author_name": "Benjamin Fetrow", - "author_inst": "University of New Mexico" - }, - { - "author_name": "Hugh Fritz", - "author_inst": "University of New Mexico" - }, - { - "author_name": "Pradeepkumar Jagadesan", - "author_inst": "University of Texas at San Antonio" - }, - { - "author_name": "Virginie Bondu", - "author_inst": "University of New Mexico" - }, - { - "author_name": "Linea Ista", - "author_inst": "University of New Mexico" - }, - { - "author_name": "Eva Y Chi", - "author_inst": "University of New Mexico" - }, - { - "author_name": "David Whitten", - "author_inst": "University of New Mexico" + "author_name": "Maria K Sobczyk", + "author_inst": "University of Bristol" }, { - "author_name": "Kirk S Schanze", - "author_inst": "University of Texas at San Antonio" + "author_name": "Tom R Gaunt", + "author_inst": "University of Bristol" } ], "version": "1", - "license": "cc_no", - "type": "new results", - "category": "biochemistry" + "license": "cc_by_nd", + "type": "PUBLISHAHEADOFPRINT", + "category": "epidemiology" }, { "rel_doi": "10.1101/2021.10.19.21263786", @@ -538506,147 +537801,59 @@ "category": "hiv aids" }, { - "rel_doi": "10.1101/2021.10.16.21265087", - "rel_title": "Durability of antibody responses and frequency of clinical and subclinical SARS-CoV-2 infection six months after BNT162b2 COVID-19 vaccination in healthcare workers", + "rel_doi": "10.1101/2021.10.15.21264137", + "rel_title": "COVID-19 is associated with higher risk of venous thrombosis, but not arterial thrombosis, compared with influenza: Insights from a large US cohort", "rel_date": "2021-10-18", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.16.21265087", - "rel_abs": "Antibodies against SARS-CoV-2 decay but persist six months post-vaccination, with lower levels of neutralizing titers against Delta than wild-type. Only 2 of 227 vaccinated healthcare workers experienced outpatient symptomatic breakthrough infections despite 59 of 227 exhibiting serological evidence of exposure to SARS-CoV-2 as defined by development of anti-nucleocapsid protein antibodies.", - "rel_num_authors": 32, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.15.21264137", + "rel_abs": "IntroductionInfection with SARS-CoV-2 is typically compared with influenza to contextualize its health risks. SARS-CoV-2 has been linked with coagulation disturbances including arterial thrombosis, leading to considerable interest in antithrombotic therapy for Coronavirus Disease 2019 (COVID-19). However, the independent thromboembolic risk of SARS-CoV-2 infection compared with influenza remains incompletely understood. We evaluated the adjusted risks of thromboembolic events after a diagnosis of COVID-19 compared with influenza in a large retrospective cohort.\n\nMethodsWe used a US-based electronic health record (EHR) dataset linked with insurance claims to identify adults diagnosed with COVID-19 between April 1, 2020 and October 31, 2020. We identified influenza patients diagnosed between October 1, 2018 and April 31, 2019. Primary outcomes [venous composite of pulmonary embolism (PE) and acute deep vein thrombosis (DVT); arterial composite of ischemic stroke and myocardial infarction (MI)] and secondary outcomes were assessed 90 days post-diagnosis. Propensity scores (PS) were calculated using demographic, clinical, and medication variables. PS-adjusted hazard ratios (HRs) were calculated using Cox proportional hazards regression.\n\nResultsThere were 417,975 COVID-19 patients (median age 57y, 61% women), and 345,934 influenza patients (median age 47y, 66% women). Compared with influenza, patients with COVID-19 had higher venous thromboembolic risk (HR 1.53, 95% CI 1.38-1.70), but not arterial thromboembolic risk (HR 1.02, 95% CI 0.95-1.10). Secondary analyses demonstrated similar risk for ischemic stroke (HR 1.11, 95% CI 0.98-1.25) and MI (HR 0.93, 95% CI 0.85-1.03) and higher risk for DVT (HR 1.36, 95% CI 1.19-1.56) and PE (HR 1.82, 95% CI 1.57-2.10) in patients with COVID-19.\n\nConclusionIn a large retrospective US cohort, COVID-19 was independently associated with higher 90-day risk for venous thrombosis, but not arterial thrombosis, as compared with influenza. These findings may inform crucial knowledge gaps regarding the specific thromboembolic risks of COVID-19.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Eric D Laing", - "author_inst": "Uniformed Services University, Bethesda, MD, USA" - }, - { - "author_name": "Carol D Weiss", - "author_inst": "US Food and Drug Administration, Silver Spring, MD, USA" - }, - { - "author_name": "Emily C Samuels", - "author_inst": "Uniformed Services University, Bethesda, MD, USA; Henry M. Jackson Foundation for the Advancement of Military Medicine, Bethesda, MD, USA" - }, - { - "author_name": "Si'Ana A Coggins", - "author_inst": "Uniformed Services University, Bethesda, MD, USA; Henry M. Jackson Foundation for the Advancement of Military Medicine, Bethesda, MD, USA" - }, - { - "author_name": "Wei Wang", - "author_inst": "US Food and Drug Administration, Silver Spring, MD, USA" - }, - { - "author_name": "Richard Wang", - "author_inst": "US Food and Drug Administration, Silver Spring, MD, USA" - }, - { - "author_name": "Russell Vassell", - "author_inst": "US Food and Drug Administration, Silver Spring, MD, USA" - }, - { - "author_name": "Spencer L Sterling", - "author_inst": "Uniformed Services University, Bethesda, MD, USA; Henry M. Jackson Foundation for the Advancement of Military Medicine, Bethesda, MD, USA" - }, - { - "author_name": "Marana A Tso", - "author_inst": "Uniformed Services University, Bethesda, MD, USA" - }, - { - "author_name": "Tonia Conner", - "author_inst": "Uniformed Services University, Bethesda, MD, USA" - }, - { - "author_name": "Emilie Goguet", - "author_inst": "Uniformed Services University, Bethesda, MD, USA; Henry M. Jackson Foundation for the Advancement of Military Medicine, Bethesda, MD, USA" - }, - { - "author_name": "Belinda M Jackson-Thompson", - "author_inst": "Uniformed Services University, Bethesda, MD, USA; Henry M. Jackson Foundation for the Advancement of Military Medicine, Bethesda, MD, USA" - }, - { - "author_name": "Luca Illinik", - "author_inst": "Naval Medical Research Center, Silver Spring, MD; Henry M. Jackson Foundation for the Advancement of Military Medicine, Bethesda, MD, USA" - }, - { - "author_name": "Julian Davies", - "author_inst": "Naval Medical Research Center, Silver Spring, MD; Henry M. Jackson Foundation for the Advancement of Military Medicine, Bethesda, MD, USA" - }, - { - "author_name": "Orlando Ortega", - "author_inst": "Naval Medical Research Center, Silver Spring, MD; Henry M. Jackson Foundation for the Advancement of Military Medicine, Bethesda, MD, USA" - }, - { - "author_name": "Edward Parmelee", - "author_inst": "Uniformed Services University, Bethesda, MD, USA; Henry M. Jackson Foundation for the Advancement of Military Medicine, Bethesda, MD, USA" - }, - { - "author_name": "Monique Hollis-Perry", - "author_inst": "Naval Medical Research Center, Silver Spring, MD" - }, - { - "author_name": "Santina E Maiolatesi", - "author_inst": "Naval Medical Research Center, Silver Spring, MD; Henry M. Jackson Foundation for the Advancement of Military Medicine, Bethesda, MD, USA" - }, - { - "author_name": "Gregory Wang", - "author_inst": "Naval Medical Research Center, Silver Spring, MD; General Dynamics Information Technology, Falls Church, VA" - }, - { - "author_name": "Kathleen F Ramsey", - "author_inst": "Naval Medical Research Center, Silver Spring, MD; General Dynamics Information Technology, Falls Church, VA" - }, - { - "author_name": "Anatalio E Reyes", - "author_inst": "Naval Medical Research Center, Silver Spring, MD; General Dynamics Information Technology, Falls Church, VA" - }, - { - "author_name": "Yolanda Alcorta", - "author_inst": "Naval Medical Research Center, Silver Spring, MD; General Dynamics Information Technology, Falls Church, VA" - }, - { - "author_name": "Mimi A Wong", - "author_inst": "Naval Medical Research Center, Silver Spring, MD; General Dynamics Information Technology, Falls Church, VA" + "author_name": "Andrew Ward", + "author_inst": "HealthPals" }, { - "author_name": "Alyssa R Lindrose", - "author_inst": "Uniformed Services University, Bethesda, MD, USA; Henry M. Jackson Foundation for the Advancement of Military Medicine, Bethesda, MD, USA" + "author_name": "Ashish Sarraju", + "author_inst": "Stanford University School of Medicine" }, { - "author_name": "Christopher A Duplessis", - "author_inst": "Naval Medical Research Center, Silver Spring, MD" + "author_name": "Donghyun Lee", + "author_inst": "HealthPals" }, { - "author_name": "David R Tribble", - "author_inst": "Uniformed Services University, Bethesda, MD, USA" + "author_name": "Kanchan Bhasin", + "author_inst": "HealthPals" }, { - "author_name": "Allison MW Malloy", - "author_inst": "Uniformed Services University, Bethesda, MD, USA" + "author_name": "Sanchit Gad", + "author_inst": "HealthPals" }, { - "author_name": "Timothy H Burgess", - "author_inst": "Uniformed Services University, Bethesda, MD, USA" + "author_name": "Robert Beetel", + "author_inst": "HealthPals" }, { - "author_name": "Simon D Pollett", - "author_inst": "Uniformed Services University, Bethesda, MD, USA; Henry M. Jackson Foundation for the Advancement of Military Medicine, Bethesda, MD, USA" + "author_name": "Stella Chang", + "author_inst": "Veradigm" }, { - "author_name": "Cara H Olsen", - "author_inst": "Uniformed Services University, Bethesda, MD, USA" + "author_name": "Mac Bonafede", + "author_inst": "Veradigm" }, { - "author_name": "Christopher C Broder", - "author_inst": "Uniformed Services University, Bethesda, MD, USA" + "author_name": "Fatima Rodriguez", + "author_inst": "Stanford University School of Medicine" }, { - "author_name": "Edward Mitre", - "author_inst": "Uniformed Services University, Bethesda, MD, USA" + "author_name": "Rajesh Dash", + "author_inst": "Stanford University School of Medicine" } ], "version": "1", - "license": "cc0", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "public and global health" }, { "rel_doi": "10.1101/2021.10.13.21264957", @@ -540343,31 +539550,27 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.10.11.21264845", - "rel_title": "Willingness to take the Covid-19 vaccines and associated factors at a tertiary institution community in Johannesburg, South Africa", + "rel_doi": "10.1101/2021.10.10.21264809", + "rel_title": "A novel framework based on deep learning and ANOVA feature selection method for diagnosis of COVID-19 cases from chest X-ray Images", "rel_date": "2021-10-14", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.11.21264845", - "rel_abs": "BackgroundSA is aiming to achieve herd immunity against Covid-19 by the first quarter of 2022. The success of the Covid-19 vaccination roll-out depends primarily on the willingness of the population to take the vaccines.\n\nAimThis study examined the willingness to take the Covid-19 vaccine, along with the factors of concern, efficacy, and preferences of the individual which may increase the willingness to be vaccinated.\n\nSettingThis study was conducted at the University of the Witwatersrand, Johannesburg, amongst adult students and academic and professional staff.\n\nMethodsWe conducted a cross-sectional online study from 27 July - 14 August 2021. We performed descriptive and inferential analysis to determine the factors associated with willingness to take the Covid-19 vaccine.\n\nResults2364 participants responded to a survey link and 82% were students, 66.8% were in the 18-29 years age band, females represented 64.0% and 49.2% were black people. 1965 (83.3%) were willing to receive a Covid-19 vaccine, the most preferred vaccines were Pfizer (41%) and J&J (23%), local pharmacy (29%) and GP (17%) were the preferred places for vaccination and the trusted sources of information on Covid-19 vaccines were the general practitioners (40.6%) and specialists (19,2%). Perceptions that vaccines are safe (aOR=31.56, 95%CI: 16.02-62.12 for affirmative agreement) and effective (aOR=5.92, 95%CI: 2.87-12.19 for affirmative agreement) were the main determinants for willingness to taking a COVID-19 vaccine\n\nConclusionIt is imperative to reinforce the message of Covid-19 vaccine safety and efficacy and to include the GPs and the community pharmacies in the vaccination roll-out in SA.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.10.21264809", + "rel_abs": "The new coronavirus (known as COVID-19) was first identified in Wuhan and quickly spread worldwide, wreaking havoc on the economy and peoples everyday lives. Fever, cough, sore throat, headache, exhaustion, muscular aches, and difficulty breathing are all typical symptoms of COVID-19. A reliable detection technique is needed to identify affected individuals and care for them in the early stages of COVID-19 and reduce the viruss transmission. The most accessible method for COVID-19 identification is RT-PCR; however, due to its time commitment and false-negative results, alternative options must be sought. Indeed, compared to RT-PCR, chest CT scans and chest X-ray images provide superior results. Because of the scarcity and high cost of CT scan equipment, X-ray images are preferable for screening. In this paper, a pre-trained network, DenseNet169, was employed to extract features from X-ray images. Features were chosen by a feature selection method (ANOVA) to reduce computations and time complexity while overcoming the curse of dimensionality to improve predictive accuracy. Finally, selected features were classified by XGBoost. The ChestX-ray8 dataset, which was employed to train and evaluate the proposed method. This method reached 98.72% accuracy for two-class classification (COVID-19, healthy) and 92% accuracy for three-class classification (COVID-19, healthy, pneumonia).", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Bhadrashil H Modi", - "author_inst": "University of Witwatersrand" - }, - { - "author_name": "Deidre Pretorius", - "author_inst": "University of Witwatersrand" + "author_name": "Hamid Nasiri", + "author_inst": "Amirkabir University of Technology" }, { - "author_name": "Joel M Francis", - "author_inst": "University of Witwatersrand" + "author_name": "Seyyed Ali Alavi", + "author_inst": "Semnan University" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "radiology and imaging" }, { "rel_doi": "10.1101/2021.10.11.21264835", @@ -542573,37 +541776,57 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.10.14.21264474", - "rel_title": "Deep phylogenetic-based clustering analysis uncovers new and shared mutations in SARS-CoV-2 variants as a result of directional and convergent evolution", + "rel_doi": "10.1101/2021.10.14.21264988", + "rel_title": "Modelling airborne transmission of SARS-CoV-2 using CARA: Risk assessment for enclosed spaces", "rel_date": "2021-10-14", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.14.21264474", - "rel_abs": "Nearly two decades after the last epidemic caused by a severe acute respiratory syndrome coronavirus (SARS-CoV), newly emerged SARS-CoV-2 quickly spread in 2020 and precipitated an ongoing global public health crisis. Both the continuous accumulation of point mutations, owed to the naturally imposed genomic plasticity of SARS-CoV-2 evolutionary processes, as well as viral spread over time, allow this RNA virus to gain new genetic identities, spawn novel variants and enhance its potential for immune evasion. Here, through an in-depth phylogenetic clustering analysis of upwards of 200,000 whole-genome sequences, we reveal the presence of not previously reported and hitherto unidentified mutations and recombination breakpoints in Variants of Concern (VOC) and Variants of Interest (VOI) from Brazil, India (Beta, Eta and Kappa) and the USA (Beta, Eta and Lambda). Additionally, we identify sites with shared mutations under directional evolution in the SARS-CoV-2 Spike-encoding protein of VOC and VOI, tracing a heretofore-undescribed correlation with viral spread in South America, India and the USA. Our evidence-based analysis provides well-supported evidence of similar pathways of evolution for such mutations in all SARS-CoV-2 variants and sub-lineages. This raises two pivotal points: the co-circulation of variants and sub-lineages in close evolutionary environments, which sheds light onto their trajectories into convergent and directional evolution (i), and a linear perspective into the prospective vaccine efficacy against different SARS-CoV-2 strains (ii).\n\nAuthor summaryIn this study, through analysis of very robust and comprehensive datasets, we identify a plethora of mutations in the SARS-CoV-2 Spike cell surface protein of several variants of concern and multiple variants of interest. We trace an association of such mutations with viral spread in different countries. We further infer the presence of new SARS-CoV-2 sublineages and show that the vast majority of mutations identified in the SARS-CoV-2 Spike protein are under convergent evolution. If we consider every color of a Rubiks cubes face to represent a different mutation of a particular variant, evolutionary convergence can be achieved only when all composite pieces of a single face are of the same color and every face has one unique color. Overall, this raises two important points: we provide insight into the presence of SARS-CoV-2 variants and sub-lineages circulating in very close evolutionary environments and our analyses can serve to facilitate an outlook into the prospective vaccine efficacy against different SARS-CoV-2 strains.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.14.21264988", + "rel_abs": "The global crisis triggered by the COVID-19 pandemic has highlighted the need for a proper risk assessment of respiratory pathogens in indoor settings. This paper documents the COVID Airborne Risk Assessment (CARA) methodology, to assess the potential exposure of airborne SARS-CoV-2 viruses, with an emphasis on the effect of certain virological and immunological factors in the quantification of the risk. The proposed model is the result of a multidisciplinary approach linking physical, mechanical and biological domains, benchmarked with clinical and experimental data, enabling decision makers or facility managers to perform risk assessments against airborne transmission. The model was tested against two benchmark outbreaks, showing good agreement. The tool was also applied to several everyday-life settings, in particular for the cases of a shared office, classroom and ski cabin. We found that 20% of infected hosts can emit approximately 2 orders of magnitude more viral-containing particles, suggesting the importance of super-emitters in airborne transmission. The use of surgical-type masks provides a 5-fold reduction in viral emissions. Natural ventilation through the opening of windows at all times are effective strategies to decrease the concentration of virions and slightly opening a window in the winter has approximately the same effect as a full window opening during the summer. Although vaccination is an effective protection measure, non-pharmaceutical interventions, which significantly reduce the viral density in the air (ventilation, masks), should be actively supported and included early in the risk assessment process. We propose a critical threshold value approach which could be used to define an acceptable risk level in a given indoor setting.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Danilo Rosa Nunes", - "author_inst": "Federal University of Sao Paulo (UNIFESP)" + "author_name": "Andre Henriques", + "author_inst": "CERN" }, { - "author_name": "Carla Torres Braconi", - "author_inst": "Federal University of Sao Paulo (UNIFESP)" + "author_name": "Nicolas Mounet", + "author_inst": "CERN" }, { - "author_name": "Louisa Ludwig-Begall", - "author_inst": "University of Liege" + "author_name": "Luis Aleixo", + "author_inst": "CERN" }, { - "author_name": "Clarice Weis Arns", - "author_inst": "University of Campinas (UNICAMP)" + "author_name": "Philip Elson", + "author_inst": "CERN" }, { - "author_name": "Ricardo Duraes-Carvalho", - "author_inst": "University of Campinas" + "author_name": "James Devine", + "author_inst": "CERN" + }, + { + "author_name": "Gabriella Azzopardi", + "author_inst": "CERN" + }, + { + "author_name": "Marco Andreini", + "author_inst": "CERN" + }, + { + "author_name": "Markus Rognlien", + "author_inst": "NTNU" + }, + { + "author_name": "Nicola Tarocco", + "author_inst": "CERN" + }, + { + "author_name": "Julian Tang", + "author_inst": "Respiratory Sciences, University of Leicester" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -544431,39 +543654,43 @@ "category": "molecular biology" }, { - "rel_doi": "10.1101/2021.10.09.21264758", - "rel_title": "The military as a neglected pathogen transmitter and its implications for COVID-19: A systematic review", + "rel_doi": "10.1101/2021.10.11.463956", + "rel_title": "SARS-CoV-2 variants exhibit increased kinetic stability of open spike conformations as an evolutionary strategy", "rel_date": "2021-10-12", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.09.21264758", - "rel_abs": "BackgroundThe risk of outbreaks escalating into pandemics has soared with globalization. Therefore, understanding transmission mechanisms of infectious diseases has become critical to formulating global public health policy. This systematic review assessed evidence in the medical and public health literature for the military as a disease vector.\n\nMethodsWe searched 3 electronic databases without temporal restrictions. Two researchers independently extracted study data using a standardized form. Through team discussions, studies were grouped according to their type of transmission mechanism and direct quotes were extracted to generate themes and sub-themes. A content analysis was later performed and frequency distributions for each theme were generated.\n\nResultsOf 6477 studies, 210 met our inclusion criteria and provided evidence, spanning over two centuries (1810 - 2020), for the military as a pathogen transmitter, within itself or between it and civilians. Biological mechanisms driving transmission included person-to-person transmission, contaminated food and water, vector-borne, and airborne routes. Contaminated food and/or water were the most common biological transmission route. Social mechanisms facilitating transmission included crowded living spaces, unhygienic conditions, strenuous working, training conditions, absent or inadequate vaccination programs, pressure from military leadership, poor compliance with public health advice, contractor mismanagement, high-risk behaviours, and occupation-specific freedom of movement. Living conditions were the most common social transmission mechanism, with young, low ranking military personnel repeatedly reported as the most affected group. Selected social mechanisms, such as employment-related freedom of movement, were unique to the military as a social institution. While few studies explicitly studied civilian populations, considerably more contained information that implied that civilians were likely impacted by outbreaks described in the military.\n\nConclusionsThis study identified features of the military that pose a significant threat to global health, especially to civilian health in countries with substantial military presence or underdeveloped health systems. While biological transmission mechanisms are shared by other social groups, selected social transmission mechanisms are unique to the military. As an increasingly interconnected world faces the challenges of COVID-19 and future infectious diseases, the identified features of the military may exacerbate current and similar challenges and impair attempts to implement successful and equitable global public health policies.", - "rel_num_authors": 5, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2021.10.11.463956", + "rel_abs": "SARS-CoV-2 variants of concern harbor mutations in the Spike (S) glycoprotein that confer more efficient transmission and dampen the efficacy of COVID-19 vaccines and antibody therapies. S mediates virus entry and is the primary target for antibody responses. Structural studies of soluble S variants have revealed an increased propensity towards conformations accessible to receptor human Angiotensin-Converting Enzyme 2 (hACE2). However, real-time observations of conformational dynamics that govern the structural equilibriums of the S variants have been lacking. Here, we report single-molecule Forster Resonance Energy Transfer (smFRET) studies of S variants containing critical mutations, including D614G and E484K, in the context of virus particles. Investigated variants predominantly occupied more open hACE2-accessible conformations, agreeing with previous structures of soluble trimers. Additionally, these S variants exhibited decelerated transitions in hACE2-accessible/bound states. Our finding of increased S kinetic stability in the open conformation provides a new perspective on SARS-CoV-2 adaptation to the human population.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Claudia Chaufan", - "author_inst": "Faculty of Health, York University, Canada" + "author_name": "Ziwei Yang", + "author_inst": "Yale University School of Medicine, New Haven, CT, USA" }, { - "author_name": "Ilinca A. Dutescu", - "author_inst": "Faculty of Health, York University, Canada" + "author_name": "Yang Han", + "author_inst": "University of Texas Health Science Center, Tyler, TX, USA" }, { - "author_name": "Hanah Fekre", - "author_inst": "Faculty of Health, York University, Canada" + "author_name": "Shilei Ding", + "author_inst": "Universit\u00e9 de Montr\u00e9al, Montreal, QC, Canada." }, { - "author_name": "Saba Marzabadi", - "author_inst": "Faculty of Health, York University, Canada" + "author_name": "Andr\u00e9s Finzi", + "author_inst": "Universit\u00e9 de Montr\u00e9al, Montreal, QC, Canada." }, { - "author_name": "K.J. Noh", - "author_inst": "Independent Scholar, USA" + "author_name": "Walther Mothes", + "author_inst": "Yale University School of Medicine, New Haven, CT, USA" + }, + { + "author_name": "Maolin Lu", + "author_inst": "University of Texas Health Science Center, Tyler, TX, USA" } ], "version": "1", - "license": "cc_by_nc_nd", - "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "license": "cc_no", + "type": "new results", + "category": "microbiology" }, { "rel_doi": "10.1101/2021.10.11.463936", @@ -545896,115 +545123,203 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2021.10.08.21264519", - "rel_title": "Immunogenicity of the Ad26.CoV2.S vaccine in people living with HIV", + "rel_doi": "10.1101/2021.10.08.21264302", + "rel_title": "Safety and immunogenicity of a SARS-CoV-2 recombinant protein vaccine with AS03 adjuvant in healthy adults: interim findings from a phase 2, randomised, dose-finding, multi-centre study", "rel_date": "2021-10-10", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.08.21264519", - "rel_abs": "BackgroundPeople living with HIV (PLWH) have been reported to have an increased risk of more severe COVID-19 disease outcome and an increased risk of death relative to HIV-uninfected individuals. Here we assessed the ability of the Johnson and Johnson Ad26.CoV2.S vaccine to elicit neutralizing antibodies to the Delta variant in PLWH relative to HIV-uninfected individuals. We also compared the neutralization after vaccination to neutralization elicited by SARS-CoV-2 infection only in HIV-uninfected, suppressed HIV PLWH, and PLWH with detectable HIV viremia.\n\nMethodsWe enrolled 26 PLWH and 73 HIV-uninfected participants from the SISONKE phase 3b open label South African clinical trial of the Ad26.CoV2.S vaccine in health care workers (HCW). Enrollment was a median 56 days (range 19-98 days) post-vaccination and PLWH in this group had well controlled HIV infection. We also enrolled unvaccinated participants previously infected with SARS-CoV-2. This group consisted of 34 PLWH and 28 HIV-uninfected individuals. 10 of the 34 (29%) SARS-CoV-2 infected only PLWH had detectable HIV viremia. We used records of a positive SARS-CoV-2 qPCR result, or when a positive result was absent, testing for SARS-CoV-2 nucleocapsid antibodies, to determine which vaccinated participants were SARS-CoV-2 infected prior to vaccination. Neutralization capacity was assessed using participant plasma in a live virus neutralization assay of the Delta SARS-CoV-2 variant currently dominating infections in South Africa. This study was approved by the Biomedical Research Ethics Committee at the University of KwaZulu-Natal (reference BREC/00001275/2020).\n\nFindingsThe majority (68%) of Ad26.CoV2.S vaccinated HCW were found to be previously infected with SARS-CoV-2. In this group, Delta variant neutralization was 9-fold higher compared to the infected only group (GMT=306 versus 36, p<0.0001) and 26-fold higher relative to the vaccinated only group (GMT=12, p<0.0001). No significant difference in Delta variant neutralization capacity was observed in vaccinated and previously SARS-CoV-2 infected PLWH relative to vaccinated and previously SARS-CoV-2 infected, HIV-uninfected participants (GMT=307 for HIV-uninfected, 300 for PLWH, p=0.95). SARS-CoV-2 infected, unvaccinated PLWH showed 7-fold reduced neutralization of the Delta variant relative to HIV-uninfected participants (GMT=105 for HIV-uninfected, 15 for PLWH, p=0.001). There was a higher frequency of non-responders in PLWH relative to HIV-uninfected participants in the SARS-CoV-2 infected unvaccinated group (27% versus 0%, p=0.0029) and 60% of HIV viremic versus 13% of HIV suppressed PLWH were non-responders (p=0.0088). In contrast, the frequency of non-responders was low in the vaccinated/infected group, and similar between HIV-uninfected and PLWH. Vaccinated only participants showed a low neutralization of the Delta variant, with a stronger response in PLWH (GMT=6 for HIV-uninfected, 73 for PLWH, p=0.02).\n\nInterpretationThe neutralization response of the Delta variant following Ad26.CoV2.S vaccination in PLWH with well controlled HIV was not inferior to HIV-uninfected study participants. In SARS-CoV-2 infected and non-vaccinated participants, the presence of HIV infection reduced the neutralization response to SARS-CoV-2 infection, and this effect was strongest in PLWH with detectable HIV viremia\n\nFundingSouth African Medical Research Council, The Bill & Melinda Gates Foundation.", - "rel_num_authors": 24, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.08.21264302", + "rel_abs": "BackgroundThis study evaluated the safety and immunogenicity of an AS03-adjuvanted SARS-CoV-2 recombinant protein candidate vaccine, CoV2 preS dTM.\n\nMethodsThis Phase 2, modified double-blind, parallel-group study (NCT04762680) was conducted in adults, including those at increased risk of severe COVID-19. Participants were randomised 1:1:1, stratified by age (18-59/[≥]60 years), rapid serodiagnostic test (positive/negative) and high-risk medical conditions (yes/no), to receive two injections (day [D]1 and D22) of 5g, 10g or 15g of CoV2 preS dTM antigen with fixed AS03 content. Interim safety and reactogenicity results (to D43) and neutralising antibodies (NAbs) against the D614G variant are presented (primary objectives).\n\nFindingsOf 722 participants enrolled and randomised between 24 February and 8 March 2021, 721 received [≥]1 injections (5g, n=240; 10g, n=239; 15g, n=242). Four participants reported unsolicited immediate adverse events (AEs), two were vaccine-related (investigator assessment). Five participants reported seven vaccine-related medically-attended AEs. No vaccine-related serious AEs and no AEs of special interest were reported. Solicited reactions (local and systemic) were reported at similar frequencies between study groups; these were mostly mild to moderate and transient, with higher frequency and intensity post-injection 2 than post-injection 1. In SARS-CoV-2 naive participants at D36, 96{middle dot}9%, 97.0% and 97{middle dot}6% of participants had [≥]4-fold-rise in NAb titres from baseline in the 5g-, 10g- and 15g-dose groups, respectively. NAb titres increased with antigen dose in younger (GMTs: 2954, 3951 and 5142 for 5g-, 10g- and 15g-dose groups) but not older adults (GMTs: 1628, 1393 and 1736, respectively). NAb titres in non-naive adults after one injection were higher than titres after two injections in naive adults.\n\nInterpretationTwo injections of CoV2 preS dTM-AS03 demonstrated acceptable safety and reactogenicity, and robust immunogenicity in SARS-CoV-2 naive and non-naive adults. These results informed antigen dose selection for progression to Phase 3 evaluation of primary and booster vaccination.", + "rel_num_authors": 46, "rel_authors": [ { - "author_name": "Khadija Khan", - "author_inst": "Africa Health Research Institute; School of Laboratory Medicine and Medical Sciences, University of KwaZulu-Natal" + "author_name": "Saranya Sridhar", + "author_inst": "Sanofi Pasteur, Reading, UK" }, { - "author_name": "Gila Lustig", - "author_inst": "Centre for the AIDS Programme of Research in South Africa" + "author_name": "Joaquin Arnel", + "author_inst": "Charles R. Drew University of Medicine and Science, Los Angeles, CA, USA" }, { - "author_name": "Mallory Bernstein", - "author_inst": "Africa Health Research Institute" + "author_name": "Matthew I Bonaparte", + "author_inst": "Sanofi Pasteur, Swiftwater, PA, USA" }, { - "author_name": "Derseree Archary", - "author_inst": "Centre for the AIDS Programme of Research in South Africa; Department of Medical Microbiology, University of KwaZulu-Natal" + "author_name": "Agustin Bueso", + "author_inst": "Demedica, San Pedro Sula, Honduras" }, { - "author_name": "Sandile Cele", - "author_inst": "Africa Health Research Institute; School of Laboratory Medicine and Medical Sciences, University of KwaZulu-Natal" + "author_name": "Anne-Laure Chabanon", + "author_inst": "Sanofi Pasteur, Lyon, France" }, { - "author_name": "Farina Karim", - "author_inst": "Africa Health Research Institute; School of Laboratory Medicine and Medical Sciences, University of KwaZulu-Natal" + "author_name": "Aiying Chen", + "author_inst": "Sanofi Pasteur, Swiftwater, PA, USA" }, { - "author_name": "Muneerah Smith", - "author_inst": "Department of Integrative Biomedical Sciences" + "author_name": "Roman M Chicz", + "author_inst": "Sanofi Pasteur, Cambridge, MA, USA" }, { - "author_name": "Yashica Ganga", - "author_inst": "Africa Health Research Institute" + "author_name": "David Diemert", + "author_inst": "The George Washington School of Medicine and Health Sciences, Washington, DC, USA" }, { - "author_name": "Zesuliwe Jule", - "author_inst": "Africa Health Research Institute" + "author_name": "Brandon J Essink", + "author_inst": "Meridian Clinical Research, Omaha, NE, USA" }, { - "author_name": "Kajal Reedoy", - "author_inst": "Africa Health Research Institute" + "author_name": "Bo Fu", + "author_inst": "Sanofi Pasteur, Swiftwater, PA, USA" }, { - "author_name": "Yoliswa Miya", - "author_inst": "Africa Health Research Institute" + "author_name": "Nicole A Grunenberg", + "author_inst": "Fred Hutchinson Cancer Research Center, Seattle, WA, USA" }, { - "author_name": "Ntombifuthi Mthabela", - "author_inst": "Africa Health Research Institute" + "author_name": "Helene Janosczyk", + "author_inst": "Sanofi Pasteur, Swiftwater, PA, USA" }, { - "author_name": "- COMMIT-KZN Team", - "author_inst": "" + "author_name": "Michael C Keefer", + "author_inst": "University of Rochester, School of Medicine and Dentistry, Rochester, NY, USA" }, { - "author_name": "Richard Lessells", - "author_inst": "School of Laboratory Medicine and Medical Sciences, University of KwaZulu-Natal, Durban, South Africa; Centre for the AIDS Programme of Research in South Africa" + "author_name": "Doris M Rivera M", + "author_inst": "INVERIME S.A, Tegucigalpa, Honduras" }, { - "author_name": "Tulio de Oliveira", - "author_inst": "School of Laboratory Medicine and Medical Sciences, University of KwaZulu-Natal, Durban, South Africa; Centre for the AIDS Programme of Research in South Africa" + "author_name": "Ya Meng", + "author_inst": "Sanofi Pasteur, Swiftwater, PA, USA" }, { - "author_name": "Bernadett Gosnell", - "author_inst": "Department of Infectious Diseases, Nelson R. Mandela School of Clinical Medicine, University of KwaZulu-Natal" + "author_name": "Nelson L Michael", + "author_inst": "Walter Reed Army Institute of Research, MD, USA" }, { - "author_name": "Salim Abdool Karim", - "author_inst": "Centre for the AIDS Programme of Research in South Africa" + "author_name": "Sonal S Munsiff", + "author_inst": "University of Rochester, School of Medicine and Dentistry, Rochester, NY, USA" }, { - "author_name": "Nigel Garrett", - "author_inst": "Centre for the AIDS Programme of Research in South Africa; Discipline of Public Health Medicine, School of Nursing and Public Health, University of KwaZulu-Nata" + "author_name": "Onyema Ogbuagu", + "author_inst": "Yale University School of Medicine, New Haven, Connecticut, USA" }, { - "author_name": "Willem Hanekom", - "author_inst": "Africa Health Research Institute; Division of Infection and Immunity, University College London" + "author_name": "Vanessa N Raabe", + "author_inst": "New York University Grossman School of Medicine, New York, New York, USA" }, { - "author_name": "Linda Gail Bekker", - "author_inst": "Institute of Infectious Disease and Molecular Medicine; Desmond Tutu HIV Centre" + "author_name": "Randall Severance", + "author_inst": "Synexus Clinical Research Limited, Tempe, AZ, USA" }, { - "author_name": "Glenda Gray", - "author_inst": "South African Medical Research Council" + "author_name": "Enrique Rivas", + "author_inst": "Sanofi Pasteur, Ciudad de Mexico, Mexico" }, { - "author_name": "Jonathan M Blackburn", - "author_inst": "Department of Integrative Biomedical Sciences; Institute of Infectious Disease and Molecular Medicine; Sengenics Corporation, Kuala Lumpur, Malaysia" + "author_name": "Natalya Romanyak", + "author_inst": "Sanofi Pasteur, Swiftwater, PA, USA" }, { - "author_name": "Mahomed-Yunus S Moosa", - "author_inst": "Department of Infectious Diseases, Nelson R. Mandela School of Clinical Medicine, University of KwaZulu-Natal" + "author_name": "Nadine G Rouphael", + "author_inst": "Emory University School of Medicine, Atlanta, GA, USA" }, { - "author_name": "Alex Sigal", - "author_inst": "Africa Health Research Institute" + "author_name": "Lode Schuerman", + "author_inst": "GlaxoSmithKline Vaccines, Wavre, Belgium" + }, + { + "author_name": "Lawrence D Sher", + "author_inst": "Peninsula Research Associates, Rolling Hills Estates, CA, USA" + }, + { + "author_name": "Stephen R Walsh", + "author_inst": "Harvard Medical School, Boston, MA, USA" + }, + { + "author_name": "Judith White", + "author_inst": "Accelerated Enrollment Solutions, Horsham, PA, USA" + }, + { + "author_name": "Dalia von Barbier", + "author_inst": "Sanofi Pasteur, Swiftwater, PA, USA" + }, + { + "author_name": "Guy de Bruyn", + "author_inst": "Sanofi Pasteur, Swiftwater, PA, USA" + }, + { + "author_name": "Richard Canter", + "author_inst": "Sanofi Pasteur, Swiftwater, PA, USA" + }, + { + "author_name": "Marie-Helene Grillet", + "author_inst": "Sanofi Pasteur, Lyon, France" + }, + { + "author_name": "Maryam Keshtkar-Jahromi", + "author_inst": "National Institute of Health, Rockville, Maryland; John Hopkins University School of Medicine, Baltimore, Maryland" + }, + { + "author_name": "Marguerite Koutsoukos", + "author_inst": "GlaxoSmithKline Vaccines, Wavre, Belgium" + }, + { + "author_name": "Denise Lopez", + "author_inst": "Sanofi Pasteur, Swiftwater, PA, USA" + }, + { + "author_name": "Roger Masotti", + "author_inst": "Sanofi Pasteur, Swiftwater, PA, USA" + }, + { + "author_name": "Sandra Mendoza", + "author_inst": "Sanofi Pasteur, Bogota, Colombia" + }, + { + "author_name": "Catherine Moreau", + "author_inst": "Sanofi Pasteur, Marcy l'Etoile, France" + }, + { + "author_name": "Maria Angeles Ceregido", + "author_inst": "GlaxoSmithKline Vaccines, Wavre, Belgium" + }, + { + "author_name": "Shelly Ramirez", + "author_inst": "Fred Hutchinson Cancer Research Center, Seattle, WA, USA" + }, + { + "author_name": "Ansoyta Said", + "author_inst": "Sanofi Pasteur, Marcy l'Etoile, France" + }, + { + "author_name": "Fernanda Tavares-Da-Silva", + "author_inst": "GlaxoSmithKline Vaccines, Wavre, Belgium" + }, + { + "author_name": "Jiayuan Shi", + "author_inst": "TechData Service Company LLC, PA, USA" + }, + { + "author_name": "Tina Tong", + "author_inst": "Vaccine Translational Research Branch, NIAID, NIH, MD, USA" + }, + { + "author_name": "John Treanor", + "author_inst": "Biomedical Advanced Research and Development Authority (BARDA), Washington, DC, USA" + }, + { + "author_name": "Carlos A Diazgranados", + "author_inst": "Sanofi Pasteur, Swiftwater, PA, USA" + }, + { + "author_name": "Stephen Savarino", + "author_inst": "Sanofi Pasteur, Swiftwater, PA, USA" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "hiv aids" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2021.10.08.21264742", @@ -547674,45 +546989,161 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.10.04.21264542", - "rel_title": "Postvaccination SARS-CoV-2 infection among healthcare workers: A Systematic Review and meta-analysis", + "rel_doi": "10.1101/2021.10.05.21262783", + "rel_title": "Is the infection of the SARS-CoV-2 Delta variant associated with the outcomes of COVID-19 patients?", "rel_date": "2021-10-07", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.04.21264542", - "rel_abs": "INTRODUCTIONHealthcare workers (HCWs) remain on the front line of the battle against SARS-CoV-2 and COVID-19 infection, and are among the highest groups at risk of infection during this raging pandemic. We conducted a systematic review and meta-analysis to assess incidence of postvaccination SARS-CoV-2 infection among vaccinated HCWs.\n\nMETHODSWe searched multiple databases from inception through August 2021 to identify studies that reported on incidence of postvaccination SARS-CoV-2 infection among HCWs. Meta-analysis was performed to determine pooled proportions of COVID-19 infection in partially and fully vaccinated individuals.\n\nRESULTSEighteen studies with 228,873 HCWs were included in the final analysis. Total number of partially vaccinated, fully vaccinated, and unvaccinated HCWs were 132,922, 155,673 and 17505, respectively. Overall pooled proportion of COVID-19 infections among partially/fully vaccinated and unvaccinated HCWs was 2.1% (95% CI 1.2-3.5). Among partially vaccinated, fully vaccinated and unvaccinated HCWs, pooled proportion of COVID-19 infections was 3.7% (95% CI 1.8-7.3), 1.3% (95% CI 0.6-2.9), and 10.1% (95% CI 4.5-19.5), respectively.\n\nDISCUSSIONOur analysis shows the risk of COVID-19 infection in both partially and fully vaccinated HCWs remains exceedingly low when compared to unvaccinated individuals. There remains an urgent need for all frontline HCWs to be vaccinated against SARS-CoV-2 infection.", - "rel_num_authors": 7, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.05.21262783", + "rel_abs": "BackgroundSARS-CoV-2 Delta variant (B.1.617.2) has been responsible for the current increase in COVID-19 infectivity rate worldwide. We compared the impact of the Delta variant and non-Delta variant on the COVID-19 outcomes in patients from Yogyakarta and Central Java provinces, Indonesia.\n\nMethodsWe ascertained 161 patients, 69 with the Delta variant and 92 with the non-Delta variant. The Illumina MiSeq next-generation sequencer was used to perform the whole genome sequences of SARS-CoV-2.\n\nResultsThe mean age of patients with Delta and the non-Delta variant was 27.3 {+/-} 20.0 and 43.0 {+/-} 20.9 (p=3x10-6). The patients with Delta variant consisted of 23 males and 46 females, while the patients with the non-Delta variant involved 56 males and 36 females (p=0.001). The Ct value of the Delta variant (18.4 {+/-} 2.9) was significantly lower than the non-Delta variant (19.5 {+/-} 3.8) (p=0.043). There was no significant difference in the hospitalization and mortality of patients with Delta and non-Delta variants (p=0.80 and 0.29, respectively). None of the prognostic factors was associated with the hospitalization, except diabetes with an OR of 3.6 (95% CI=1.02-12.5; p=0.036). Moreover, the patients with the following factors have been associated with higher mortality rate than patients without the factors: age [≥]65 years, obesity, diabetes, hypertension, and cardiovascular disease with the OR of 11 (95% CI=3.4-36; p=8x10-5), 27 (95% CI=6.1-118; p=1x10-5), 15.6 (95% CI=5.3-46; p=6x10-7), 12 (95% CI=4-35.3; p=1.2x10-5), and 6.8 (95% CI=2.1-22.1; p=0.003), respectively. Multivariate analysis showed that age [≥]65 years, obesity, diabetes, and hypertension were the strong prognostic factors for the mortality of COVID-19 patients with the OR of 3.6 (95% CI=0.58-21.9; p=0.028), 16.6 (95% CI=2.5-107.1; p=0.003), 5.5 (95% CI=1.3-23.7; p=0.021), and 5.8 (95% CI=1.02-32.8; p=0.047), respectively.\n\nConclusionsWe show that the patients infected by the SARS-CoV-2 Delta variant have a lower Ct value than the patients infected by the non-Delta variant, implying that the Delta variant has a higher viral load, which might cause a more transmissible virus among humans. However, the Delta variant does not affect the COVID-19 outcomes in our patients. Our study also confirms the older age and comorbidity increase the mortality rate of COVID-19 patients.", + "rel_num_authors": 36, "rel_authors": [ { - "author_name": "Saurabh Chandan", - "author_inst": "CHI Health Creighton University Medical Center" + "author_name": "Gunadi", + "author_inst": "Pediatric Surgery Division, Department of Surgery/Genetics Working Group, Faculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada, Yogyakarta, I" }, { - "author_name": "Shahab R. Khan", - "author_inst": "Brigham and Womens Hospital, Harvard Medical School" + "author_name": "Mohamad Saifudin Hakim", + "author_inst": "Department of Microbiology, Faculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada, Yogyakarta, Indonesia" }, { - "author_name": "Smit Deliwala", - "author_inst": "Hurley Medical Center" + "author_name": "Hendra Wibawa", + "author_inst": "Disease Investigation Center, Wates, Yogyakarta, Ministry of Agriculture Indonesia;" }, { - "author_name": "Babu P. Mohan", - "author_inst": "University of Utah Health" + "author_name": "Marcellus", + "author_inst": "Genetics Working Group, Faculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada, Yogyakarta, Indonesia" }, { - "author_name": "Daryl Ramai", - "author_inst": "University of Utah Health" + "author_name": "Vivi Setiawaty", + "author_inst": "National Institute of Health Research and Development, Ministry of Health, Jakarta, Indonesia" }, { - "author_name": "Ojasvini C. Chandan", - "author_inst": "Childrens Hospital of Omaha" + "author_name": "Slamet", + "author_inst": "National Institute of Health Research and Development, Ministry of Health, Jakarta, Indonesia" }, { - "author_name": "Antonio Facciorusso", - "author_inst": "University of Foggia" + "author_name": "Ika Trisnawati", + "author_inst": "Pulmonology Division, Department of Internal Medicine, Faculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada/Dr. Sardjito Hospital, Yogyakarta" + }, + { + "author_name": "Endah Supriyati", + "author_inst": "Centre of Tropical Medicine, Faculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada, Yogyakarta, Indonesia" + }, + { + "author_name": "Riat El Khair", + "author_inst": "Department of Clinical Pathology and Laboratory Medicine, Faculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada/Dr. Sardjito Hospital, Yogyaka" + }, + { + "author_name": "Kristy Iskandar", + "author_inst": "Department of Child Health/Genetics Working Group, Faculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada/ UGM Academic Hospital, Yogyakarta, I" + }, + { + "author_name": "Afiahayati", + "author_inst": "Department of Computer Science and Electronics Faculty of Mathematics and Natural Sciences, Universitas Gadjah Mada, Yogyakarta, Indonesia" + }, + { + "author_name": "Siswanto", + "author_inst": "Department of Physiology, Faculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada/UGM Academic Hospital, Yogyakarta, Indonesia" + }, + { + "author_name": "Irene", + "author_inst": "Balai Besar Teknik Kesehatan Lingkungan dan Pengendalian Penyakit, Yogyakarta, Yogyakarta, Indonesia" + }, + { + "author_name": "Nungki Anggorowati", + "author_inst": "Department of Anatomical Pathology/Genetics Working Group, Faculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada, Yogyakarta, Indonesia" + }, + { + "author_name": "Edwin Widyanto Daniwijaya", + "author_inst": "Department of Microbiology, Faculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada/UGM Academic Hospital, Yogyakarta, Indonesia" + }, + { + "author_name": "Dwi Aris Agung Nugrahaningsih", + "author_inst": "Department of Pharmacology and Therapy/Genetics Working Group, Faculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada, Yogyakarta, Indonesia" + }, + { + "author_name": "Yunika Puspadewi", + "author_inst": "Department of Clinical Pathology and Laboratory Medicine, Faculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada/Dr. Sardjito Hospital, Yogyaka" + }, + { + "author_name": "Dyah Ayu Puspitarani", + "author_inst": "Genetics Working Group, Faculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada, Yogyakarta, Indonesia" + }, + { + "author_name": "Irene Tania", + "author_inst": "Genetics Working Group, Faculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada, Yogyakarta, Indonesia" + }, + { + "author_name": "Khanza Adzkia Vujira", + "author_inst": "Genetics Working Group, Faculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada, Yogyakarta, Indonesia" + }, + { + "author_name": "Muhammad Buston Ardlyamustaqim", + "author_inst": "Genetics Working Group, Faculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada, Yogyakarta, Indonesia" + }, + { + "author_name": "Gita Christy Gabriela", + "author_inst": "Genetics Working Group, Faculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada, Yogyakarta, Indonesia" + }, + { + "author_name": "Laudria Stella Eryvinka", + "author_inst": "Genetics Working Group, Faculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada, Yogyakarta, Indonesia" + }, + { + "author_name": "Bunga Citta Nirmala", + "author_inst": "Genetics Working Group, Faculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada, Yogyakarta, Indonesia" + }, + { + "author_name": "Esensi Tarian Geometri", + "author_inst": "Genetics Working Group, Faculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada, Yogyakarta, Indonesia" + }, + { + "author_name": "Abirafdi Amajida Darutama", + "author_inst": "Genetics Working Group, Faculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada, Yogyakarta, Indonesia" + }, + { + "author_name": "Anisa Adityarini Kuswandani", + "author_inst": "Genetics Working Group, Faculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada, Yogyakarta, Indonesia" + }, + { + "author_name": "Lestari", + "author_inst": "Disease Investigation Center, Wates, Yogyakarta, Ministry of Agriculture Indonesia" + }, + { + "author_name": "Sri Handayani Irianingsih", + "author_inst": "Disease Investigation Center, Wates, Yogyakarta, Ministry of Agriculture Indonesia" + }, + { + "author_name": "Siti Khoiriyah", + "author_inst": "RSUD Dr. Loekmono Hadi, Kudus, Central Java, Indonesia" + }, + { + "author_name": "Ina Lestari", + "author_inst": "RSUD Dr. Loekmono Hadi, Kudus, Central Java, Indonesia" + }, + { + "author_name": "Nur Rahmi Ananda", + "author_inst": "Pulmonology Division, Department of Internal Medicine, Faculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada/Dr. Sardjito Hospital, Yogyakarta" + }, + { + "author_name": "Eggi Arguni", + "author_inst": "Department of Child Health, Faculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada/Dr. Sardjito Hospital, Yogyakarta, Indonesia" + }, + { + "author_name": "Titik Nuryastuti", + "author_inst": "Department of Microbiology, Faculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada, Yogyakarta, Indonesia" + }, + { + "author_name": "Tri Wibawa", + "author_inst": "Department of Microbiology, Faculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada, Yogyakarta, Indonesia" + }, + { + "author_name": "- Yogyakarta-Central Java COVID-19 study group", + "author_inst": "-" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -549980,79 +549411,91 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2021.10.07.463234", - "rel_title": "High-throughput Activity Assay for Screening Inhibitors of the SARS-CoV-2 Mac1 Macrodomain", + "rel_doi": "10.1101/2021.10.03.21264490", + "rel_title": "Assessment of Post COVID-19 Health Problems and its Determinants in North India: A descriptive cross section study", "rel_date": "2021-10-07", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.10.07.463234", - "rel_abs": "Macrodomains are a class of conserved ADP-ribosylhydrolases expressed by viruses of pandemic concern, including coronaviruses and alphaviruses. Viral macrodomains are critical for replication and virus-induced pathogenesis; therefore, these enzymes are a promising target for antiviral therapy. However, no potent or selective viral macrodomain inhibitors currently exist, in part due to the lack of a high-throughput assay for this class of enzymes. Here, we developed a high-throughput ADP-ribosylhydrolase assay using the SARS-CoV-2 macrodomain Mac1. We performed a pilot screen which identified dasatinib and dihydralazine as ADP-ribosylhydrolase inhibitors. Importantly, dasatinib does not inhibit MacroD2, the closest Mac1 homolog in humans. Our study demonstrates the feasibility of identifying selective inhibitors based on ADP-ribosylhydrolase activity, paving the way for screening large compound libraries to identify improved macrodomain inhibitors and explore their potential as antiviral therapies for SARS-CoV-2 and future viral threats.", - "rel_num_authors": 15, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.03.21264490", + "rel_abs": "With millions of people getting affected with COVID-19 pandemic caused by a novel severe acute respiratory syndrome corona virus 2 (SARS-CoV-2), people living with post COVID-19 Symptoms (PCS) are expected to rise in the future{middle dot} The present study aimed at assessing PCS comprehensively and its associated factors among COVID-19 recovered adult population in north India.\n\nMethodsIn a tertiary health centre at Delhi, an online based cross-sectional study was conducted using a semi-structured questionnaire, developed by employing a nominal group technique, in aged 18 years and above who were SARS-CoV-2 positive during the month of January to April 2021. Socio-demographic, various potential risk factors, including pre-existing morbidities, vaccination status, and severity of acute COVID-19 illness, information on acute illness for management and a spectrum of PCS were collected between June 16 to July 28, 2021. Each participant was contacted telephonically before sending the survey link. PCS were presented as relative frequency; chi-square test, odds ratio, including adjusted, were calculated to rule out association between PCS and potential predictors.\n\nResultsA total of 773 of 1801 COVID recovered participants responded to the link reaching a participation rate of 42{middle dot}9%, with a median age of 34 years (IQR 27 to 44). Male respondents were 56{middle dot}4%. Around 33{middle dot}2% of them had PCS at four or more weeks, affecting almost all body organ systems. The most prevalent PCS were fatigue (79{middle dot}3%), pain in the joins (33{middle dot}4%), muscle (29{middle dot}9%), hair loss (28{middle dot}0%), headache (27{middle dot}2%), breathlessness (25{middle dot}3%), sleep disturbance (25{middle dot}3%) and cough (24{middle dot}9%). The prevalence of PCS was reduced to 12{middle dot}8% at 12 weeks after positive test. Factor such as female gender, older age, oxygen supplementation during the acute illness, working in healthcare care facilities, the severity of acute illness, and pre-existing co-morbid were risk factors for PCS. Further, vaccination (second dose) reduced the odds of developing PCS by 45% compared to unvaccinated participants (aOR 0{middle dot}65; 95%CI 0{middle dot}45-0{middle dot}96). Finally, 8{middle dot}3% of participants rated their overall health status was either poor or very poor following COVID-19 illness.\n\nConclusionsThe PCS involves almost all organ systems, regardless of the severity of acute COVID-19 illness. Two doses of vaccine help to reduce development of PCS.\n\nResearch in ContextO_ST_ABSEvidence before this studyC_ST_ABSAlthough the evidence is mounting in prolonged COVID-19 symptoms among COVID-19 survivors, to date, the full range of such post-COVID-19 symptoms (PCS) is not yet fully understood. There is a lack of studies that assessed PCS comprehensively among persons who have recovered from the COVID-19illness. For example, limited data are available on psychosocial, behavioral, and oral manifestations related to PCS. Further, there is a paucity of studies that included a wide range of determinants of PCS and the association of vaccination with the development of PCS across the world. Our study is the first such study conducted among COVID-19 recovered persons who with a majority of them employed in a tertiary health care institute of north India.\n\nAdded value of this studyOur study, for the first time, investigated a wide range of post-COVID-19 manifestations among COVID-19 recovered persons in organ-specific and psychosocial behavioral aspects, making this the largest categorization of PCS currently (in total 16). The study included telephonic calls to each eligible candidate which helped in ensuring the COVID-19 status at the time of the study. Since the participants either were employees in the hospital or their dependents that enhance the accuracy of reporting PCS. The most prevalent symptom was unspecific PCS (85.6%), e.g., fatigue, followed by musculoskeletal manifestations (49{middle dot}8%), Ear, Nose and Throat symptoms (47{middle dot}5%), neurological (47{middle dot}0%), cardio-respiratory (42{middle dot}4%, gastrointestinal (36{middle dot}2%), ocular symptoms (31{middle dot}9%), dermatological symptoms (31{middle dot}5%), and cardio-vascular (24{middle dot}5%) symptoms, and mental health symptoms (23{middle dot}7%). The rest of the organ specific symptoms were observed in less than 20% of the respondents. Older age, female gender, pre-existing co-morbid, oxygen supplementation during acute illness, the severity of illness, working in health care institutions were associated with PCS. Vaccination after the second dose was protective against PCS compared to non-vaccinated participants. Further, our study also reported a rating of the overall health status among COVID survivors, whereby around 8.3% of them reported being a poor or very poor health.\n\nImplications of all the available evidencePCS affects a multi-organ organ system, irrespective of the severity of acute-phase COVID-19 illness and hospitalization. Such persistent COVID-19 symptoms, compounded by its heterogeneity among COVID survivors can pose a substantial burden to the affected individuals and their families and additional challenges for healthcare delivery and public health service. The current study shows that one in three individuals experience persistent COVID-19 symptoms. Since the COVID pandemic is still ongoing across the world, therefore, the number of people experiencing PCS is likely to be increased substantially further. An integrated PCS care strategy, but not limited to organ-specific healthcare disciplines, others such as psychosocial support, including counseling and education, rehabilitation, community-based rehabilitation programs will be required for management. Prioritization of PCS care to elder and co-morbid patients should be recommended. Expediting the vaccination drive will be helpful to reduce the development of persistent COVID-19 symptoms. Research, collaborative and multidisciplinary, is required to understand the underlying pathophysiology mechanism for PCS.", + "rel_num_authors": 18, "rel_authors": [ { - "author_name": "Morgan A Dasovich", - "author_inst": "Johns Hopkins University" + "author_name": "Suraj Singh Senjam", + "author_inst": "Dr. R.P.Centre for Ophthalmic Sciences, AIIMS, New Delhi" }, { - "author_name": "Junlin Zhuo", - "author_inst": "Johns Hopkins University" + "author_name": "Balhara Yatan Pal Singh", + "author_inst": "Department of Psychiatry, National Drug Dependence Treatment Centre, All India Institute of Medical Sciences, New Delhi, India" }, { - "author_name": "Ajit G Thomas", - "author_inst": "Johns Hopkins University" + "author_name": "Kumar Parmeshwar", + "author_inst": "Department of Hospital Administration, All India Institute of Medical Sciences, New Delhi, India" }, { - "author_name": "Jack A Goodman", - "author_inst": "Johns Hopkins University" + "author_name": "Neeraj Nichal", + "author_inst": "Department of Medicine, All India Institute of Medical Sciences, New Delhi" }, { - "author_name": "Robert Lyle McPherson", - "author_inst": "Massachusetts Institute of Technology" + "author_name": "Souvik Manna", + "author_inst": "1.\tDr. Rajendra Prasad Centre for Ophthalmic Sciences, All India Institute of Medical Sciences, New Delhi, India" }, { - "author_name": "Aravinth Kumar Jayabalan", - "author_inst": "Johns Hopkins University" + "author_name": "Karan Madan", + "author_inst": "Department of Pulmonary, Critical Care and Sleep Medicine, All India Institute of Medical Sciences, New Delhi, India." }, { - "author_name": "Veronica F. Busa", - "author_inst": "Johns Hopkins University" + "author_name": "Nishat Hussain Ahmed", + "author_inst": "Dr. Rajendra Prasad Centre for Ophthalmic Sciences, All India Institute of Medical Sciences, New Delhi, India" }, { - "author_name": "Shang-Jung Cheng", - "author_inst": "Johns Hopkins University" + "author_name": "Noopur Gupta", + "author_inst": "Dr. Rajendra Prasad Centre for Ophthalmic Sciences, All India Institute of Medical Sciences, New Delhi, India" }, { - "author_name": "Brennan Murphy", - "author_inst": "Johns Hopkins University" + "author_name": "Rajesh Sharma", + "author_inst": "Dr. Rajendra Prasad Centre for Ophthalmic Sciences, All India Institute of Medical Sciences, New Delhi, India" }, { - "author_name": "Karli R Redinger", - "author_inst": "Case Western Reserve University" + "author_name": "Yashdeep Gupta", + "author_inst": "Department of Endocrinology and Metabolism, All India Institute of Medical Sciences, New Delhi, India" }, { - "author_name": "Takashi Tsukamoto", - "author_inst": "Johns Hopkins University" + "author_name": "Animesh Ray", + "author_inst": "Department of Medicine, All India Institute of Medical Sciences, New Delhi" }, { - "author_name": "Barbara S Slusher", - "author_inst": "Johns Hopkins University" + "author_name": "Vivek Gupta", + "author_inst": "Dr. Rajendra Prasad Centre for Ophthalmic Sciences, All India Institute of Medical Sciences, New Delhi, India" }, { - "author_name": "Jurgen Bosch", - "author_inst": "Case Western Reserve University" + "author_name": "Praveen Vashist", + "author_inst": "Dr. Rajendra Prasad Centre for Ophthalmic Sciences, All India Institute of Medical Sciences, New Delhi, India" }, { - "author_name": "Jack Wei", - "author_inst": "Johns Hopkins University" + "author_name": "Atul Kumar", + "author_inst": "Dr. Rajendra Prasad Centre for Ophthalmic Sciences, All India Institute of Medical Sciences, New Delhi, India" }, { - "author_name": "Anthony Leung", - "author_inst": "Johns Hopkins University" + "author_name": "Lalit Dar", + "author_inst": "Department of Micrology, All India Institute of Medical Sciences, New Delhi, India" + }, + { + "author_name": "Jeevan Singh Titiyal", + "author_inst": "Dr. Rajendra Prasad Centre for Ophthalmic Sciences, All India Institute of Medical Sciences, New Delhi, India" + }, + { + "author_name": "Radhika Tandon", + "author_inst": "Dr. Rajendra Prasad Centre for Ophthalmic Sciences, All India Institute of Medical Sciences, New Delhi, India" + }, + { + "author_name": "Randeep Gulleira", + "author_inst": "Department of Pulmonary, Critical Care and Sleep Medicine, All India Institute of Medical Sciences, New Delhi, India." } ], "version": "1", "license": "cc_no", - "type": "new results", - "category": "biochemistry" + "type": "PUBLISHAHEADOFPRINT", + "category": "public and global health" }, { "rel_doi": "10.1101/2021.10.04.21264507", @@ -552358,35 +551801,127 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2021.10.04.463014", - "rel_title": "Genetic association of TMPRSS2 rs2070788 polymorphism with COVID-19 Case Fatality Rate among Indian populations", + "rel_doi": "10.1101/2021.10.05.463212", + "rel_title": "TREM2+ and interstitial macrophages orchestrate airway inflammation in SARS-CoV-2 infection in rhesus macaques", "rel_date": "2021-10-05", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.10.04.463014", - "rel_abs": "SARS-CoV2, the causative agent for COVID-19, an ongoing pandemic, engages the ACE2 receptor to enter the host cell through S protein priming by a serine protease, TMPRSS2. Variation in the TMPRSS2 gene may account for the difference in population disease susceptibility. The haplotype-based genetic sharing and structure of TMPRSS2 among global populations have not been studied so far. Therefore, in the present work, we used this approach with a focus on South Asia to study the haplotypes and their sharing among various populations worldwide. We have used next-generation sequencing data of 393 individuals and analysed the TMPRSS2 gene. Our analysis of genetic relatedness for this gene showed a closer affinity of South Asians with the West Eurasian populations therefore, host disease susceptibility and severity particularly in the context of TMPRSS2 will be more akin to West Eurasian instead of East Eurasian. This is in contrast to our prior study on ACE2 gene which shows South Asian haplotypes have a strong affinity towards West Eurasians. Thus ACE2 and TMPRSS2 have an antagonistic genetic relatedness among South Asians. We have also tested the SNPs frequencies of this gene among various Indian state populations with respect to the case fatality rate. Interestingly, we found a significant positive association between the rs2070788 SNP (G Allele) and the case fatality rate in India. It has been shown that the GG genotype of rs2070788 allele tends to have a higher expression of TMPRSS2 in the lung compared to the AG and AA genotypes, thus it might play a vital part in determining differential disease vulnerability. We trust that this information will be useful in underscoring the role of the TMPRSS2 variant in COVID-19 susceptibility and using it as a biomarker may help to predict populations at risk.", - "rel_num_authors": 4, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.10.05.463212", + "rel_abs": "The COVID-19 pandemic remains a global health crisis, yet, the immunopathological mechanisms driving the development of severe disease remain poorly defined. Here, we utilize a rhesus macaque (RM) model of SARS-CoV-2 infection to delineate perturbations in the innate immune system during acute infection using an integrated systems analysis. We found that SARS-CoV-2 initiated a rapid infiltration (two days post infection) of plasmacytoid dendritic cells into the lower airway, commensurate with IFNA production, natural killer cell activation, and induction of interferon-stimulated genes. At this early interval, we also observed a significant increase of blood CD14-CD16+ monocytes. To dissect the contribution of lung myeloid subsets to airway inflammation, we generated a novel compendium of RM-specific lung macrophage gene expression using a combination of sc-RNA-Seq data and bulk RNA-Seq of purified populations under steady state conditions. Using these tools, we generated a longitudinal sc-RNA-seq dataset of airway cells in SARS-CoV-2-infected RMs. We identified that SARS-CoV-2 infection elicited a rapid recruitment of two subsets of macrophages into the airway: a C206+MRC1-population resembling murine interstitial macrophages, and a TREM2+ population consistent with CCR2+ infiltrating monocytes, into the alveolar space. These subsets were the predominant source of inflammatory cytokines, accounting for ~75% of IL6 and TNF production, and >90% of IL10 production, whereas the contribution of CD206+MRC+ alveolar macrophages was significantly lower. Treatment of SARS-CoV-2 infected RMs with baricitinib (Olumiant(R)), a novel JAK1/2 inhibitor that recently received Emergency Use Authorization for the treatment of hospitalized COVID-19 patients, was remarkably effective in eliminating the influx of infiltrating, non-alveolar macrophages in the alveolar space, with a concomitant reduction of inflammatory cytokines. This study has delineated the major subsets of lung macrophages driving inflammatory and anti-inflammatory cytokine production within the alveolar space during SARS-CoV-2 infection.\n\nOne sentence summaryMulti-omic analyses of hyperacute SARS-CoV-2 infection in rhesus macaques identified two population of infiltrating macrophages, as the primary orchestrators of inflammation in the lower airway that can be successfully treated with baricitinib", + "rel_num_authors": 27, "rel_authors": [ { - "author_name": "RUDRA KUMAR PANDEY", - "author_inst": "BANARAS HINDU UNIVERSITY" + "author_name": "Amit A. Upadhyay", + "author_inst": "Emory University" }, { - "author_name": "Anshika Srivastava", - "author_inst": "BANARAS HINDU UNIVERSITY" + "author_name": "Timothy N. Hoang", + "author_inst": "Emory University" }, { - "author_name": "Prajjval Pratap Singh", - "author_inst": "BANARAS HINDU UNIVERSITY" + "author_name": "Maria Pino", + "author_inst": "Emory University" }, { - "author_name": "Gyaneshwer Chaubey", - "author_inst": "BANARAS HINDU UNIVERSITY" + "author_name": "Arun K. Boddapati", + "author_inst": "Emory University" + }, + { + "author_name": "Elise G. Viox", + "author_inst": "Emory University" + }, + { + "author_name": "Michelle Y.H. Lee", + "author_inst": "Emory University" + }, + { + "author_name": "Jacqueline Corry", + "author_inst": "University of Pittsburgh" + }, + { + "author_name": "Zachary Strongin", + "author_inst": "Emory University" + }, + { + "author_name": "David A. Cowan", + "author_inst": "Emory University" + }, + { + "author_name": "Elizabeth N. Beagle", + "author_inst": "Emory University" + }, + { + "author_name": "Tristan R. Horton", + "author_inst": "Emory University" + }, + { + "author_name": "Sydney Hamilton", + "author_inst": "Emory University" + }, + { + "author_name": "Hadj Aoued", + "author_inst": "Emory University" + }, + { + "author_name": "Justin L. Harper", + "author_inst": "Emory University" + }, + { + "author_name": "Kevin Nguyen", + "author_inst": "Emory University" + }, + { + "author_name": "Kathryn L. Pellegrini", + "author_inst": "Emory University" + }, + { + "author_name": "Gregory K. Tharp", + "author_inst": "Emory University" + }, + { + "author_name": "Anne Piantadosi", + "author_inst": "Emory University" + }, + { + "author_name": "Rebecca D. Levit", + "author_inst": "Emory University" + }, + { + "author_name": "Rama R. Amara", + "author_inst": "Emory University" + }, + { + "author_name": "Simon M. Barratt-Boyes", + "author_inst": "University of Pittsburgh" + }, + { + "author_name": "Susan P. Ribeiro", + "author_inst": "Emory University" + }, + { + "author_name": "Rafick P. Sekaly", + "author_inst": "Emory University" + }, + { + "author_name": "Thomas H. Vanderford", + "author_inst": "Emory University" + }, + { + "author_name": "Raymond F. Schinazi", + "author_inst": "Emory University" + }, + { + "author_name": "Mirko Paiardini", + "author_inst": "Emory University" + }, + { + "author_name": "Steven E. Bosinger", + "author_inst": "Emory University" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "new results", - "category": "genetics" + "category": "microbiology" }, { "rel_doi": "10.1101/2021.10.05.463185", @@ -553876,55 +553411,51 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2021.09.30.21264343", - "rel_title": "Genomic diversity of SARS-CoV-2 in Pakistan during fourth wave of pandemic", + "rel_doi": "10.1101/2021.10.01.21264349", + "rel_title": "Humoral cross-reactivity towards SARS-CoV-2 in young children with acute respiratory infection with low-pathogenicity coronaviruses", "rel_date": "2021-10-03", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.30.21264343", - "rel_abs": "The emergence of different variants of concern of SARS-CoV-2 has resulted in upsurges of COVID positive cases around the globe. Pakistan is also experiencing fourth wave of COVID-19 with increasing number of positive cases. In order to understand the genomic diversity of circulating SARS-CoV-2 strains during fourth wave of pandemic in Pakistan, the current study was designed. The samples from 89 COVID-19 positive patients were subjected to whole genome sequencing using GeneStudio S5. The results showed that 99% (n=88) of isolates belonged to delta variant and only one isolate belonged to alpha variant. Among delta variant cases 26.1% (n=23) isolates were showing B.1.617.2 while 74% of isolates showing AY.4 lineage. Islamabad was found to be the most affected city with 54% (n=48) of cases, followed by Karachi (28%, n=25), and Rawalpindi (10%, n=9). AY.4 has slight difference in mutation profile compared to B.1.617.2. E156del, G142D and V26I mutations in spike and T181I in NSP6 were present in B.1.617.2 but not in AY.4. Interestingly, A446V mutation in NSP4 has been only observed in AY.4. The current study highlights the circulation of primarily delta variant (B.1.617.2 and AY.4) during fourth wave of pandemic in Pakistan.", - "rel_num_authors": 9, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.01.21264349", + "rel_abs": "SARS-CoV-2 infection in children frequently leads to only asymptomatic and mild infections. It has been suggested that frequent infections due to low-pathogenicity coronaviruses in children, imparts immunity against SARS-CoV-2 in this age group. From a prospective birth cohort study prior to the pandemic, we identified children (n=42) with proven low-pathogenicity coronavirus infections. Convalescent sera from these samples had antibodies against the respective seasonal CoVs as demonstrated by immunofluorescence assay. We tested these samples for neutralization of SARS-CoV-2 using virus microneutralization assay. Forty serum samples showed no significant neutralization of SARS-CoV-2, while 2 samples showed inconclusive results. These findings suggest that the antibodies generated in low-pathogenicity coronavirus infections offer no protection from SARS-CoV-2 infection in young children.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Massab Umair", - "author_inst": "National Institute of Health" - }, - { - "author_name": "Aamer Ikram", - "author_inst": "National Institute of Health" + "author_name": "Nitin Dhochak", + "author_inst": "All India Institute of Medical Sciences, New Delhi, India" }, { - "author_name": "Zaira Rehman", - "author_inst": "National Institute of Health (Pakistan)" + "author_name": "Tanvi Agrawal", + "author_inst": "Translational Health Science and Technology Institute, Faridabad, Haryana, India." }, { - "author_name": "Adnan Haider", - "author_inst": "National Institute of Health" + "author_name": "Heena Shaman", + "author_inst": "Translational Health Science and Technology Institute, Faridabad, Haryana, India" }, { - "author_name": "Nazish Badar", - "author_inst": "National Institute of Health" + "author_name": "Naseem Ahmed Khan", + "author_inst": "Translational Health Science and Technology Institute, Faridabad, Haryana, India" }, { - "author_name": "Muhammad Ammar", - "author_inst": "National Institute of Health" + "author_name": "Prawin Kumar", + "author_inst": "All India Institute of Medical Sciences, Jodhpur, India" }, { - "author_name": "Abdul Ahad", - "author_inst": "National Institute of Health" + "author_name": "Sushil K Kabra", + "author_inst": "All India Institute of Medical Sciences, New Delhi, India" }, { - "author_name": "Rana Suleman", - "author_inst": "National Institute of Health" + "author_name": "Guruprasad R Medigeshi", + "author_inst": "Translational Health Science and Technology Institute" }, { - "author_name": "Muhammad Salman", - "author_inst": "National Institute of Health" + "author_name": "Rakesh Lodha", + "author_inst": "All India Institute of Medical Sciences, New Delhi, India" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2021.09.30.21264377", @@ -555698,45 +555229,77 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.10.01.21264373", - "rel_title": "Longitudinal SARS-CoV-2 testing is punctuated by intermittent positivity and variable rates of cycle-threshold decline", + "rel_doi": "10.1101/2021.09.29.21264089", + "rel_title": "Immune Memory Response After a Booster Injection of mRNA-1273 for Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2)", "rel_date": "2021-10-01", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.01.21264373", - "rel_abs": "The COVID-19 pandemic is complicated by cases of vaccine-breakthrough, re-infection, and widespread transmission of variants of concern (VOC). Consequently, the need to interpret longitudinal positive SARS-CoV-2 (SCV-2) tests is crucial in guiding clinical decisions regarding infection control precautions and treatment. Although quantitative tests are not routinely used diagnostically, standard diagnostic RT-PCR tests yield Ct values that are inversely correlated with RNA quantity. In this study, we performed a retrospective review of 72,217 SCV-2 PCR positive tests and identified 264 patients with longitudinal positivity prior to vaccination and VOC circulation. Patients with longitudinal positivity fell into two categories: short-term (207, 78%) or prolonged (57, 22%) positivity, defined as <= 28 (range 1-28, median 16) days and >28 (range 29-152, median 41) days, respectively. In general, Ct values declined over time in both groups; however, 11 short-term positive patients had greater amounts of RNA detected at their terminal test compared to the first positive, and 5 patients had RNA detected at Ct < 35 at least 40 days after initial infection. Oscillating positive and negative results occurred in both groups, although oscillation was seen three times more frequently in prolonged-positive patients. Patients with prolonged positivity had diverse clinical characteristics but were often critically ill and were discharged to high-level care or deceased (22%). Overall, this study demonstrates that caution must be emphasized when interpreting Ct values as a proxy for infectivity, predictor of severity, or a guide for patient care decisions in the absence of additional clinical context.", - "rel_num_authors": 7, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.29.21264089", + "rel_abs": "Rising breakthrough infections of coronavirus-2 (SARS-CoV-2) in previously immunized individuals has raised concerns for a booster to combat suspected waning immunity and new variants. Participants immunized 6-8 months earlier with a primary series of two doses of 50 or 100 {micro}g of mRNA-1273 were administered a booster injection of 50 {micro}g of mRNA-1273. Neutralizing antibody levels against wild-type virus and the Delta variant at one month after the booster were 1.7-fold and 2.1-fold higher, respectively, than those 28 days post primary series second injection indicating an immune memory response. The reactogenicity after the booster dose was similar to that after the second dose in the primary series of two doses of mRNA-1273 (50 or 100 {micro}g) with no serious adverse events reported in the one-month follow-up period. These results demonstrate that a booster injection of mRNA-1273 in previously immunized individuals stimulated an immune response greater than the primary vaccination series.", + "rel_num_authors": 15, "rel_authors": [ { - "author_name": "Shawn E. Hawken", - "author_inst": "UNC Medical Center" + "author_name": "Laurence Chu", + "author_inst": "Benchmark Research" }, { - "author_name": "Subhashini A. Sellers", - "author_inst": "UNC School of Medicine" + "author_name": "David Montefiori", + "author_inst": "Duke University" }, { - "author_name": "Jason R. Smedberg", - "author_inst": "UNC Medical Center" + "author_name": "Wenmei Huang", + "author_inst": "Moderna, Inc." }, { - "author_name": "Jeremy D. Ward", - "author_inst": "University of North Carolina at Chapel Hill" + "author_name": "Biliana Nestorova", + "author_inst": "Moderna, Inc." }, { - "author_name": "Herbert C. Whinna", - "author_inst": "UNC School of Medicine" + "author_name": "Ying Chang", + "author_inst": "Moderna, Inc." }, { - "author_name": "William A. Fischer II", - "author_inst": "University of North Carolina at Chapel Hill" + "author_name": "Andrea Carfi", + "author_inst": "Moderna, Inc." }, { - "author_name": "Melissa B. Miller", - "author_inst": "UNC School of Medicine" + "author_name": "Darin K Edwards", + "author_inst": "Moderna Inc" + }, + { + "author_name": "Judy Oestreicher", + "author_inst": "Moderna, Inc." + }, + { + "author_name": "Holly Legault", + "author_inst": "Moderna, Inc." + }, + { + "author_name": "Bethany Girard", + "author_inst": "Moderna, Inc." + }, + { + "author_name": "Rolando Pajon", + "author_inst": "Moderna, Inc." + }, + { + "author_name": "Jacqueline M Miller", + "author_inst": "Moderna, Inc." + }, + { + "author_name": "Rituparna Das", + "author_inst": "Moderna, Inc." + }, + { + "author_name": "Brett Leav", + "author_inst": "Moderna, Inc." + }, + { + "author_name": "Roderick McPhee", + "author_inst": "Moderna" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -558004,39 +557567,31 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.09.28.21264066", - "rel_title": "How well does SARS-CoV-2 spread in hospitals?", + "rel_doi": "10.1101/2021.09.28.21264259", + "rel_title": "Persistence of neuropsychiatric symptoms associated with SARS-CoV-2 positivity among a cohort of children and adolescents", "rel_date": "2021-09-29", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.28.21264066", - "rel_abs": "Covid-19 poses significant risk of nosocomial transmission, and preventing this requires good estimates of the basic reproduction number R0 in hospitals and care facilities, but these are currently lacking. Such estimates are challenging due to small population sizes in these facilities and inconsistent testing practices.\n\nWe estimate the patient-to-patient R0 and daily transmission rate of SARS-CoV-2 using data from a closely monitored hospital outbreak in Paris 2020 during the first wave. We use a realistic epidemic model which accounts for progressive stages of infection, stochastic effects and a large proportion of asymptomatic infections. Innovatively, we explicitly include changes in testing capacity over time, as well as the evolving sensitivity of PCR testing at different stages of infection. We conduct rigorous statistical inference using iterative particle filtering to fit the model to the observed patient data and validate this methodology using simulation.\n\nWe provide estimates for R0 across the entire hospital (2.6) and in individual wards (from 3 to 15), possibly reflecting heterogeneity in contact patterns or control measures. An obligatory mask-wearing policy introduced during the outbreak is likely to have changed the R0, and we estimate values before (8.7) and after (1.3) its introduction, corresponding to a policy efficacy of 85%.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.28.21264259", + "rel_abs": "BackgroundPost-acute sequelae of COVID-19 are common among adults. The prevalence of such syndromes among community samples of children and adolescents remains less well characterized.\n\nMethodWe identified all individuals age 5-18 across 2 New England health systems who had a positive SARS-CoV-2 PCR test between 3/12/2020 and 4/18/2021 and at least 90 days of follow-up visits documented in electronic health records. We identified neuropsychiatric symptoms in intervals prior to, and following, this testing using a previously-derived set of ICD-10 codes and natural language processing terms. Primary analysis examined sociodemographic features associated with presence of at least one incident (i.e., new-onset) neuropsychiatric symptom between 90 and 150 days after an initial positive test for COVID-19.\n\nResultsAmong 5058 children (50% female, 2.9% Asian, 6.3% Black, and 63% White; 30% Hispanic; mean age was 12.4 (IQR 8.9-15.6), 366 (7.2%) exhibited at least one new-onset neuropsychiatric symptom between 90 and 150 days following initial SARS-CoV-2 test positivity. The most common incident symptoms at 90-150 days were headache (2.4%), mood and anxiety symptoms (2.4%), cognitive symptoms (2.3%), and fatigue (1.1%). In regression models, older children, girls, those with Hispanic ethnicity, those with public versus private insurance, and those with greater overall burden of medical comorbidity were more likely to exhibit subsequent symptoms.\n\nConclusionThe prevalence of neuropsychiatric symptoms between 3- and 5-months following SARS-CoV-2 test positivity is similar to that observed in the period prior to infection. Prospective controlled studies will be needed to further refine these estimates.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "George Shirreff", - "author_inst": "Laboratoire MESuRS, Conservatoire National des Arts et M\u00e9tiers, Paris, France ; Institut Pasteur, Epidemiology and Modelling of Antibiotic Evasion unit, P" - }, - { - "author_name": "Jean-Ralph Zahar", - "author_inst": "Infection Control Unit, H\u00f4pital Avicenne, Groupe Hospitalier Paris Seine Saint Denis, AP-HP, 93000 Bobigny, France" - }, - { - "author_name": "Simon Cauchemez", - "author_inst": "Mathematical Modelling of Infectious Diseases Unit, Institut Pasteur, UMR2000, CNRS, Paris, France." + "author_name": "Victor M Castro", + "author_inst": "Mass General Brigham" }, { - "author_name": "Laura Temime", - "author_inst": "Laboratoire MESuRS, Conservatoire National des Arts et M\u00e9tiers, Paris, France ; PACRI Unit, Institut Pasteur, Conservatoire national des Arts et M\u00e9tiers, Paris," + "author_name": "Faith M Gunning", + "author_inst": "Weill Cornell Medicine" }, { - "author_name": "Lulla Opatowski", - "author_inst": "Institut Pasteur, Epidemiology and Modelling of Antibiotic Evasion unit, Paris, France ; University of Versailles Saint-Quentin-en-Yvelines, Montigny-le-Bretonn" + "author_name": "Roy H Perlis", + "author_inst": "Massachusetts General Hospital" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "psychiatry and clinical psychology" }, { "rel_doi": "10.1101/2021.09.27.21264003", @@ -560030,63 +559585,83 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2021.09.29.462326", - "rel_title": "Metabolic snapshot of plasma samples reveals new pathways implicated in SARS-CoV-2 pathogenesis", + "rel_doi": "10.1101/2021.09.28.462270", + "rel_title": "Data-driven approaches for genetic characterization of SARS-CoV-2 lineages", "rel_date": "2021-09-29", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.09.29.462326", - "rel_abs": "Despite of the scientific and human efforts to understand COVID-19, there are questions still unanswered. Variations in the metabolic reaction to SARS-CoV-2 infection could explain the striking differences in the susceptibility to infection and the risk of severe disease. Here, we used untargeted metabolomics to examine novel metabolic pathways related to SARS-CoV-2 susceptibility and COVID-19 clinical severity using capillary electrophoresis coupled to a time-of-flight mass spectrometer (CE-TOF-MS) in plasma samples. We included 27 patients with confirmed COVID-19 early after symptom onset who were prospectively followed and 29 healthcare workers heavily exposed to SARS-CoV-2 but with low susceptibility to infection ( nonsusceptible). We found that the metabolite profile was predictive of the study group. We identified a total of 55 metabolites as biomarkers of SARS-CoV-2 susceptibility or COVID-19 clinical severity. We report the discovery of new plasma biomarkers for COVID-19 that provide mechanistic explanations for the clinical consequences of SARS-CoV-2, including mitochondrial and liver dysfunction as a consequence of hypoxemia (citrulline, citrate, and BAIBA), energy production and amino acid catabolism (L-glycine, L-alanine, L-serine, L-proline, L-aspartic acid and L-histidine), endothelial dysfunction and thrombosis (citrulline, L-ADMA, 2-AB, and Neu5Ac), and we found interconnections between these pathways. In summary, in this first report of the metabolomic profile of individuals with severe COVID-19 and SARS-CoV-2 susceptibility by CE-MS, we define several metabolic pathways implicated in SARS-CoV-2 susceptibility and COVID-19 clinical progression that could be developed as biomarkers of COVID-19.", - "rel_num_authors": 11, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.09.28.462270", + "rel_abs": "The genome of the Severe Acute Respiratory Syndrome coronavirus 2 (SARS-CoV-2), the pathogen that causes coronavirus disease 2019 (COVID-19), has been sequenced at an unprecedented scale, leading to a tremendous amount of viral genome sequencing data. To understand the evolution of this virus in humans, and to assist in tracing infection pathways and designing preventive strategies, we present a set of computational tools that span phylogenomics, population genetics and machine learning approaches. To illustrate the utility of this toolbox, we detail an in depth analysis of the genetic diversity of SARS-CoV-2 in first year of the COVID-19 pandemic, using 329,854 high-quality consensus sequences published in the GISAID database during the pre-vaccination phase. We demonstrate that, compared to standard phylogenetic approaches, haplotype networks can be computed efficiently on much larger datasets, enabling real-time analyses. Furthermore, time series change of Tajimas D provides a powerful metric of population expansion. Unsupervised learning techniques further highlight key steps in variant detection and facilitate the study of the role of this genomic variation in the context of SARS-CoV-2 infection, with Multiscale PHATE methodology identifying fine-scale structure in the SARS-CoV-2 genetic data that underlies the emergence of key lineages. The computational framework presented here is useful for real-time genomic surveillance of SARS-CoV-2 and could be applied to any pathogen that threatens the health of worldwide populations of humans and other organisms.", + "rel_num_authors": 16, "rel_authors": [ { - "author_name": "Oihane E. Alb\u00f3niga", - "author_inst": "CEU San Pablo University: Universidad CEU San Pablo" + "author_name": "Fatima Mostefai", + "author_inst": "Universite de Montreal" + }, + { + "author_name": "Isabel Gamache", + "author_inst": "Universite de Montreal" }, { - "author_name": "Daniel Jim\u00e9nez", - "author_inst": "IRYCIS: Instituto Ramon y Cajal de Investigacion Sanitaria" + "author_name": "Jessie Huang", + "author_inst": "Yale University" }, { - "author_name": "Matilde S\u00e1nchez-Conde", - "author_inst": "IRYCIS: Instituto Ramon y Cajal de Investigacion Sanitaria" + "author_name": "Justin Pelletier", + "author_inst": "Universite de Montreal" }, { - "author_name": "Pilar Vizcarra", - "author_inst": "IRYCIS: Instituto Ramon y Cajal de Investigacion Sanitaria" + "author_name": "Ahmad Pesaranghader", + "author_inst": "McGill University" }, { - "author_name": "Raquel Ron", - "author_inst": "IRYCIS: Instituto Ramon y Cajal de Investigacion Sanitaria" + "author_name": "David Hamelin", + "author_inst": "Universite de Montreal" }, { - "author_name": "Sabina Herrera", - "author_inst": "IRYCIS: Instituto Ramon y Cajal de Investigacion Sanitaria" + "author_name": "Carmen Lia Murall", + "author_inst": "McGill University" }, { - "author_name": "Javier Mart\u00ednez-Sanz", - "author_inst": "IRYCIS: Instituto Ramon y Cajal de Investigacion Sanitaria" + "author_name": "Raphael Poujol", + "author_inst": "Institut de Cardiologie de Montreal" }, { - "author_name": "Elena Moreno", - "author_inst": "IRYCIS: Instituto Ramon y Cajal de Investigacion Sanitaria" + "author_name": "Jean-Christophe Grenier", + "author_inst": "Institut de Cardiologie de Montreal" }, { - "author_name": "Santiago Moreno", - "author_inst": "IRYCIS: Instituto Ramon y Cajal de Investigacion Sanitaria" + "author_name": "Martin Smith", + "author_inst": "Universite de Montreal" }, { - "author_name": "Coral Barbas", - "author_inst": "CEU San Pablo University: Universidad CEU San Pablo" + "author_name": "Etienne Caron", + "author_inst": "Universite de Montreal" }, { - "author_name": "Sergio Serrano-Villar", - "author_inst": "University Hospital Ram\u00f3n y Cajal and IRYCIS" + "author_name": "Morgan Craig", + "author_inst": "Universite de Montreal" + }, + { + "author_name": "Jesse Shapiro", + "author_inst": "McGill University" + }, + { + "author_name": "Guy Wolf", + "author_inst": "Universite de Montreal" + }, + { + "author_name": "Smita Krishnaswamy", + "author_inst": "Yale University" + }, + { + "author_name": "Julie Hussin", + "author_inst": "Universite de Montreal" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nd", "type": "new results", - "category": "biochemistry" + "category": "bioinformatics" }, { "rel_doi": "10.1101/2021.09.29.462344", @@ -561532,75 +561107,103 @@ "category": "systems biology" }, { - "rel_doi": "10.1101/2021.09.21.21258385", - "rel_title": "Using genomic epidemiology of SARS-CoV-2 to support contact tracing and public health surveillance in rural Humboldt County, California.", + "rel_doi": "10.1101/2021.09.21.21263740", + "rel_title": "The Pandemic Brain: neuroinflammation in healthy, non-infected individuals during the COVID-19 pandemic", "rel_date": "2021-09-27", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.21.21258385", - "rel_abs": "During the COVID-19 pandemic within the United States, much of the responsibility for diagnostic testing and epidemiologic response has relied on the action of county-level departments of public health. Here we describe the integration of genomic surveillance into epidemiologic response within Humboldt County, a rural county in northwest California. Through a collaborative effort, 853 whole SARS-CoV-2 genomes were generated, representing [~]58% of the 1,449 SARS-CoV-2-positive cases detected in Humboldt County as of mid-March 2021. Phylogenetic analysis of these data was used to develop a comprehensive understanding of SARS-CoV-2 introductions to the county and to support contact tracing and epidemiologic investigations of all large outbreaks in the county. In the case of an outbreak on a commercial farm, viral genomic data were used to validate reported epidemiologic links and link additional cases within the community who did not report a farm exposure to the outbreak. During a separate outbreak within a skilled nursing facility, genomic surveillance data were used to rule out the putative index case, detect the emergence of an independent Spike:N501Y substitution, and verify that the outbreak had been brought under control. These use cases demonstrate how developing genomic surveillance capacity within local public health departments can support timely and responsive deployment of genomic epidemiology for surveillance and outbreak response based on local needs and priorities.", - "rel_num_authors": 14, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.21.21263740", + "rel_abs": "SummaryO_ST_ABSBackgroundC_ST_ABSThe impact of COVID-19 on human health extends beyond the morbidity and death toll directly caused by the SARS-CoV-2 virus. In fact, accumulating evidence indicates a global increase in the incidence of fatigue, brain fog and depression, including among non-infected, since the pandemic onset. Motivated by previous evidence linking those symptoms to neuroimmune activation in other pathological contexts, we hypothesized that subjects examined after the enforcement of lockdown/stay-at-home measures would demonstrate increased neuroinflammation.\n\nMethodsWe performed simultaneous brain Positron Emission Tomography / Magnetic Resonance Imaging in healthy volunteers either before (n=57) or after (n=15) the 2020 Massachusetts lockdown, using [11C]PBR28, a radioligand for the glial marker 18 kDa translocator protein (TSPO). First, we compared [11C]PBR28 signal across pre- and post-lockdown cohorts. Then, we evaluated the link between neuroinflammatory signals and scores on a questionnaire assessing mental and physical impacts of the pandemic. Further, we investigated multivariate associations between the spatial pattern of [11C]PBR28 post-lockdown changes and constitutive brain gene expression in post-mortem brains (Allen Human Brain Atlas). Finally, in a subset (n=13 pre-lockdown; n=11 post-lockdown), we also used magnetic resonance spectroscopy to quantify brain (thalamic) levels of myoinositol (mIns), another neuroinflammatory marker.\n\nFindingsBoth [11C]PBR28 and mIns signals were overall stable pre-lockdown, but markedly elevated after lockdown, including within brain regions previously implicated in stress, depression and \"sickness behaviors\". Moreover, amongst the post-lockdown cohort, subjects endorsing higher symptom burden showed higher [11C]PBR28 PET signal compared to those reporting little/no symptoms. Finally, the post-lockdown [11C]PBR28 signal changes were spatially aligned with the constitutive expression of several genes highly expressed in glial/immune cells and/or involved in neuroimmune signaling.\n\nInterpretationOur results suggest that pandemic-related stressors may have induced sterile neuroinflammation in healthy individuals that were not infected with SARS-CoV-2. This work highlights the possible impact of the COVID-19 pandemic-related lifestyle disruptions on human brain health.\n\nFundingR01-NS094306-01A1, R01-NS095937-01A1, R01-DA047088-01, The Landreth Family Foundation.", + "rel_num_authors": 21, "rel_authors": [ { - "author_name": "Gunnar Stoddard", - "author_inst": "Humboldt County Department of Health and Human Services - Public Health, Eureka, California, USA" + "author_name": "Ludovica Brusaferri", + "author_inst": "Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA" }, { - "author_name": "Allison Black", - "author_inst": "Chan Zuckerberg Initiative" + "author_name": "Zeynab Alshelh", + "author_inst": "Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA" }, { - "author_name": "Patrick Ayscue", - "author_inst": "Chan Zuckerberg Biohub" + "author_name": "Daniel Martins", + "author_inst": "Department of Neuroimaging, King's College London, London, UK" }, { - "author_name": "Dan Lu", - "author_inst": "Chan Zuckerberg Initiative" + "author_name": "Minhae Kim", + "author_inst": "Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA" }, { - "author_name": "Jack Kamm", - "author_inst": "Chan Zuckerberg Biohub" + "author_name": "Akila Weerasekera", + "author_inst": "Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA" }, { - "author_name": "Karan Bhatt", - "author_inst": "Chan Zuckerberg Biohub" + "author_name": "Hope Housman", + "author_inst": "Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA" }, { - "author_name": "Lienna Chan", - "author_inst": "Chan Zuckerberg Biohub" + "author_name": "Erin J Morrisey", + "author_inst": "Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA" }, { - "author_name": "Amy L Kistler", - "author_inst": "Chan Zuckerberg Biohub" + "author_name": "Paulina C Knight", + "author_inst": "Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA" }, { - "author_name": "Joshua Batson", - "author_inst": "Public Health Company" + "author_name": "Kelly A Castro-Blanco", + "author_inst": "Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA" }, { - "author_name": "Angela Detweiler", - "author_inst": "Chan Zuckerberg Biohub" + "author_name": "Daniel S Albrecht", + "author_inst": "Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA" }, { - "author_name": "Michelle Tan", - "author_inst": "Chan Zuckerberg Biohub" + "author_name": "Chieh-En Tseng", + "author_inst": "Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA" }, { - "author_name": "Norma Neff", - "author_inst": "Chan Zuckerberg Biohub" + "author_name": "Nicole R Zurcher", + "author_inst": "Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA" }, { - "author_name": "Joseph L DeRisi", - "author_inst": "Chan Zuckerberg Biohub" + "author_name": "Eva-Maria Ratai", + "author_inst": "Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA" }, { - "author_name": "Jeremy Corrigan", - "author_inst": "Humboldt County Public Health Laboratory, Eureka, California, USA" + "author_name": "Oluwaseun Johnson-Akeju", + "author_inst": "Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA" + }, + { + "author_name": "Nathaniel D Mercaldo", + "author_inst": "Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA" + }, + { + "author_name": "Nouchine Hadjikhani", + "author_inst": "Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA" + }, + { + "author_name": "Mattia Veronese", + "author_inst": "Department of Neuroimaging, King's College London, London, UK" + }, + { + "author_name": "Federico Turkheimer", + "author_inst": "Department of Neuroimaging, King's College London, London, UK" + }, + { + "author_name": "Bruce R Rosen", + "author_inst": "Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA" + }, + { + "author_name": "Jacob M Hooker", + "author_inst": "Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA" + }, + { + "author_name": "Marco L Loggia", + "author_inst": "Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "public and global health" }, { "rel_doi": "10.1101/2021.09.25.21264097", @@ -563618,87 +563221,95 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.09.18.21263550", - "rel_title": "Persistent while declined neutralizing antibody responses in the convalescents of COVID-19 across clinical spectrum during the 16 months follow up", + "rel_doi": "10.1101/2021.09.23.21263948", + "rel_title": "Demographic characteristics of SARS-CoV-2 B.1.617.2 (Delta) variant infections in Indian population", "rel_date": "2021-09-26", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.18.21263550", - "rel_abs": "Elucidation the kinetics of neutralizing antibody response in the coronavirus disease 2019 (COVID-19) convalescents is crucial for the future control of the COVID-19 pandemic and vaccination strategies. Here we tested 411 sequential plasma samples collected up to 480 days post symptoms onset (d.a.o) from 214 convalescents of COVID-19 across clinical spectrum without re-exposure history after recovery and vaccination of SARS-CoV-2, using authentic SARS-CoV-2 microneutralization (MN) assays. COVID-19 convalescents free of re-exposure and vaccination could maintain relatively stable anti-RBD IgG and MN titers during 400[~]480 d.a.o after the peak at around 120 d.a.o and the subsequent decrease. Undetectable neutralizing activity started to occur in mild and asymptomatic infections during 330 to 480 d.a.o with an overall rate of 14.29% and up to 50% for the asymptomatic infections. Significant decline in MN titers was found in 91.67% COVID-19 convalescents with [≥] 50% decrease in MN titers when comparing the available peak and current MN titers ([≥] 300 d.a.o). Antibody-dependent immunity could also provide protection against most of circulating variants after one year, while significantly decreased neutralizing activities against the Beta, Delta and Lambda variants were found in most of individuals. In summary, our results indicated that neutralizing antibody responses could last at least 480 days in most COVID-19 convalescents despite of the obvious decline of neutralizing activity, while the up to 50% undetectable neutralizing activity in the asymptomatic infections is of great concern.", - "rel_num_authors": 17, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.23.21263948", + "rel_abs": "ImportanceHigher risks of contracting infection, developing severe illness and mortality are known facts in aged and male sex if exposed to the wild type SARS-CoV-2 strains (Wuhan and B.1 strains). Now, accumulating evidence suggests greater involvement of lower age and narrowing the age and sex based differences for the severity of symptoms in infections with emerging SARS-CoV-2 variants. Delta variant (B.1.617.2) is now a globally dominant SARS-CoV-2 strain, however, current evidence on demographic characteristics for this variant are limited. Recently, delta variant caused a devastating second wave of COVID-19 in India. We performed a demographic characterization of COVID-19 cases in Indian population diagnosed with SARS-CoV-2 genomic sequencing for delta variant.\n\nObjectiveTo determine demographic characteristics of delta variant in terms of age and sex, severity of the illness and mortality rate, and post-vaccination infections.\n\nDesignA cross sectional study\n\nSettingDemographic characteristics, including vaccination status (for two complete doses) and severity of the illness and mortality rate, of COVID-19 cases caused by wild type strain (B.1) and delta variant (B.1.617.2) of SARS-CoV-2 in Indian population were studied.\n\nParticipantsCOVID-19 cases for which SARS-CoV-2 genomic sequencing was performed and complete demographic details (age, sex, and location) were available, were included.\n\nExposuresSARS-CoV-2 infection with Delta (B.1.617.2) variant and wild type (B.1) strain.\n\nMain Outcomes and MeasuresThe patient metadata containing details for demographic and vaccination status (two complete doses) of the COVID-19 patients with confirmed delta variant and WT (B.1) infections were analyzed [total number of cases (N) =9500, Ndelta=6238, NWT=3262]. Further, severity of the illness and mortality were assessed in subsets of patients. Final data were tabulated and statistically analyzed to determine age and sex based differences in chances of getting infection and the severity of illness, and post-vaccination infections were compared between wild type and delta variant strains. Graphs were plotted to visualize the trends.\n\nResultsWith delta variant, in comparison to wild type (B.1) strain, higher proportion of lower age groups, particularly <20 year (0-9 year: 4.47% vs. 2.3%, 10-19 year: 9% vs. 7%) were affected. The proportion of women contracting infection were increased (41% vs. 36%). The higher proportion of total young (0-19 year, 10% vs. 4%) (p=.017) population and young (14% vs. 3%) as well as adult (20-59 year, 75% vs. 55%) women developed symptoms/hospitalized with delta variant in comparison to B.1 infection (p< .00001). The mean age of contracting infection [Delta, men=37.9 ({+/-}17.2) year, women=36.6 ({+/-}17.6) year; B.1, men=39.6 ({+/-}16.9) year and women= 40.1 ({+/-}17.4) year (p< .001)] as well as developing symptoms/hospitalization [Delta, men=39.6({+/-} 17.4) year, women=35.6 ({+/-}16.9) year; B.1, men=47({+/-}18) year and women= 49.5({+/-}20.9) year (p< .001)] was considerably lower. The total mortality was about 1.8 times higher (13% vs. 7%). Risk of death increased irrespective of the sex (Odds ratio: 3.034, 95% Confidence Interval: 1.7-5.2, p<0.001), however, increased proportion of women (32% vs. 25%) were died. Further, multiple incidences of delta infections were noted following complete vaccination.\n\nConclusions and RelevanceThe increased involvement of young (0-19 year) and women, lower mean age for contracting infection and symptomatic illness/hospitalization, higher mortality, and frequent incidences of post-vaccination infections with delta variant compared to wild type strain raises significant epidemiological concerns.\n\nKey PointsO_ST_ABSQuestionC_ST_ABSDid SARS-CoV-2 B.1.617.2 (Delta) variant infections show varied demographic characteristics in comparison to wild type strains?\n\nFindingsIn this cross sectional study viral genomic sequences of 9500 COVID-19 patients were analyzed. As the key findings, increased involvement of young (0-19 year) and women, lower mean age for contracting infection and symptomatic illness/hospitalization, higher mortality, and frequent incidences of post-vaccination infections with delta variant in comparison to wild type (WT) strain (B.1) were observed.\n\nMeaningThe findings of this study suggest that delta variant has varied demographic characteristics reflecting increased involvement of the young and women, and increased lethality in comparison to wild type strains.", + "rel_num_authors": 19, "rel_authors": [ { - "author_name": "Yang Yang", - "author_inst": "Shenzhen Third People's Hospital" + "author_name": "Ashutosh Kumar", + "author_inst": "All India Institute of Medical Sciences-Patna, Bihar, India" }, { - "author_name": "Minghui Yang", - "author_inst": "Shenzhen third people's hospital" + "author_name": "Adil Asghar", + "author_inst": "All India Institute of Medical Sciences-Patna, Bihar, India" }, { - "author_name": "Yun Peng", - "author_inst": "Shenzhen Third People's Hospital" + "author_name": "Khursheed Raza", + "author_inst": "All India Institute of Medical Sciences- Deoghar, Jharkhand, India" }, { - "author_name": "Yanhua Liang", - "author_inst": "Shenzhen Third People's Hospital" + "author_name": "Ravi K. Narayan", + "author_inst": "Andaman and Nicobar Islands Institute of Medical Sciences, Port Blair, Andaman and Nicobar Islands, India" }, { - "author_name": "Jinli Wei", - "author_inst": "Shenzhen Third People's Hospital" + "author_name": "Rakesh K. Jha", + "author_inst": "All India Institute of Medical Sciences-Patna, Bihar, India" }, { - "author_name": "Li Xing", - "author_inst": "Shenzhen Third People's Hospital" + "author_name": "Abhigyan Satyam", + "author_inst": "All India Institute of Medical Sciences-Patna, Bihar, India" }, { - "author_name": "Liping Guo", - "author_inst": "Shenzhen Third People's Hospital" + "author_name": "Gopichand Kumar", + "author_inst": "All India Institute of Medical Sciences-Patna, Bihar, India" }, { - "author_name": "Xiaohe Li", - "author_inst": "Shenzhen Third People's Hospital" + "author_name": "Prakhar Dwivedi", + "author_inst": "All India Institute of Medical Sciences-Patna, Bihar, India" }, { - "author_name": "Jie Li", - "author_inst": "Shenzhen Third People's Hospital" + "author_name": "Chetan Sahni", + "author_inst": "Institute of Medical Sciences, Banaras Hindu University (BHU), Varanasi, Uttar Pradesh, India" }, { - "author_name": "Jun Wang", - "author_inst": "Shenzhen Third People's Hospital" + "author_name": "Chiman Kumari", + "author_inst": "Postgraduate Institute of Medical Education and Research, Chandigarh, India" }, { - "author_name": "Mianhuan Li", - "author_inst": "Shenzhen Third People's Hospital" + "author_name": "Maheswari Kulandhasamy", + "author_inst": "Maulana Azad Medical College (MAMC), New Delhi, India" }, { - "author_name": "Zhixiang Xu", - "author_inst": "Shenzhen Third People's Hospital" + "author_name": "Rohini Motwani", + "author_inst": "All India Institute of Medical Sciences-Bibinagar, Telangna, India" }, { - "author_name": "Mingxia Zhang", - "author_inst": "Shenzhen Third People's Hospital" + "author_name": "Gurjot Kaur", + "author_inst": "School of Pharmaceutical Sciences, Shoolini University, Solan, Himachal Pradesh, India" }, { - "author_name": "Fuxiang Wang", - "author_inst": "Shenzhen Third People's Hospital" + "author_name": "Hare Krishna", + "author_inst": "All India Institute of Medical Sciences-Jodhpur, Rajasthan, India" }, { - "author_name": "Yi Shi", - "author_inst": "CAS Key Laboratory of Pathogenic Microbiology and Immunology, Institute of 12 Microbiology, Chinese Academy of Sciences, Beijing, China" + "author_name": "Kishore Sesham", + "author_inst": "All India Institute of Medical Sciences-Mangalagiri, Andhra Pradesh, India" }, { - "author_name": "Jing Yuan", - "author_inst": "Shenzhen Third People's Hospital" + "author_name": "Sada N. Pandey", + "author_inst": "Department of Zoology, Banaras Hindu University (BHU), Varanasi, India" }, { - "author_name": "Yingxia Liu", - "author_inst": "Shenzhen Third People's Hospital" + "author_name": "Rakesh Parashar", + "author_inst": "India Health Lead, Oxford Policy Management Limited, Oxford, UK" + }, + { + "author_name": "Kamla Kant", + "author_inst": "All India Institute of Medical Sciences-Bathinda, Punjab, India" + }, + { + "author_name": "Sujeet Kumar", + "author_inst": "Center for Proteomics and Drug Discovery, Amity Institute of Biotechnology, Amity University, Maharashtra, India" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2021.09.21.21263915", @@ -565348,31 +564959,83 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.09.22.21263977", - "rel_title": "COVID-19 mortality risk correlates inversely with vitamin D3 status, and a mortality rate close to zero could theoretically be achieved at 50 ng/ml 25(OH)D3: Results of a systematic review and meta-analysis", + "rel_doi": "10.1101/2021.09.24.461759", + "rel_title": "Protein Vaccine Induces a Durable, More Broadly Neutralizing Antibody Response in Macaques than Natural Infection with SARS-CoV-2 P.1", "rel_date": "2021-09-25", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.22.21263977", - "rel_abs": "BackgroundMuch research shows that blood calcidiol (25(OH)D3) levels correlate strongly with SARS-CoV-2 infection severity. There is open discussion regarding whether low D3 is caused by the infection or if deficiency negatively affects immune defense. The aim of this study was to collect further evidence on this topic.\n\nMethodsSystematic literature search was performed to identify retrospective cohort as well as clinical studies on COVID-19 mortality rates versus D3 blood levels. Mortality rates from clinical studies were corrected for age, sex and diabetes. Data were analyzed using correlation and linear regression.\n\nResultsOne population study and seven clinical studies were identified, which reported D3 blood levels pre-infection or on the day of hospital admission. They independently showed a negative Pearson correlation of D3 levels and mortality risk (r(17)=-.4154, p=.0770/r(13)=-.4886, p=.0646). For the combined data, median (IQR) D3 levels were 23.2 ng/ml (17.4 - 26.8), and a significant Pearson correlation was observed (r(32)=-.3989, p=.0194). Regression suggested a theoretical point of zero mortality at approximately 50 ng/ml D3.\n\nConclusionsThe two datasets provide strong evidence that low D3 is a predictor rather than a side effect of the infection. Despite ongoing vaccinations, we recommend raising serum 25(OH)D levels to above 50 ng/ml to prevent or mitigate new outbreaks due to escape mutations or decreasing antibody activity.\n\nTrial registrationNot applicable.", - "rel_num_authors": 3, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2021.09.24.461759", + "rel_abs": "FDA-approved and Emergency Use Authorized (EUA) vaccines using new mRNA and viral-vector technology are highly effective in preventing moderate to severe disease, however, information on their long-term efficacy and protective breadth against SARS-CoV-2 Variants of Concern (VOCs) is currently scarce. Here we describe the durability and broad-spectrum VOC immunity of a prefusion-stabilized spike (S) protein adjuvanted with liquid or lyophilized CoVaccine HT in cynomolgus macaques. This recombinant subunit vaccine is highly immunogenic and induces robust spike-specific and broadly neutralizing antibody responses effective against circulating VOCs (B.1.351 [Beta], P.1 [Gamma], B.1.617 [Delta]) for at least 3 months after the final boost. Protective efficacy and post-exposure immunity were evaluated using a heterologous P.1 challenge nearly 3 months after the last immunization. Our results indicate that while immunization with both high and low S doses shorten and reduce viral loads in the upper and lower respiratory tract, a higher antigen dose is required to provide durable protection against disease as vaccine immunity wanes. Histologically, P.1 infection causes similar COVID-19-like lung pathology as seen with early pandemic isolates. Post-challenge IgG concentrations were restored to peak immunity levels and vaccine-matched and cross-variant neutralizing antibodies were significantly elevated in immunized macaques indicating an efficient anamnestic response. Only low levels of P.1-specific neutralizing antibodies with limited breadth were observed in control (non-vaccinated but challenged) macaques suggesting that natural infection may not prevent reinfection by other VOCs. Overall, these results demonstrate that a properly dosed and adjuvanted recombinant subunit vaccine can provide long-lasting and protective immunity against circulating VOCs.\n\nOne Sentence SummaryA recombinant subunit protein formulated with CoVaccine HT adjuvant induces superior immunity than natural infection and reduces viral load while protecting cynomolgus macaques from COVID-19-like disease caused by late SARS-CoV-2 P.1 (Gamma) challenge.", + "rel_num_authors": 16, "rel_authors": [ { - "author_name": "Lorenz Borsche", - "author_inst": "Independent Researcher" + "author_name": "Albert To", + "author_inst": "University of Hawaii at Manoa" }, { - "author_name": "Bernd Glauner", - "author_inst": "Independent Researcher" + "author_name": "Teri Ann S Wong", + "author_inst": "University of Hawaii at Manoa" + }, + { + "author_name": "Michael M Lieberman", + "author_inst": "University of Hawaii at Manoa" + }, + { + "author_name": "Karen S Thompson", + "author_inst": "University of Hawaii at Manoa" + }, + { + "author_name": "Laurent Pessaint", + "author_inst": "Bioqual Inc" + }, + { + "author_name": "Jack Greenhouse", + "author_inst": "Bioqual Inc." + }, + { + "author_name": "Nisrine Daham", + "author_inst": "Bioqual Inc." + }, + { + "author_name": "Anthony Cook", + "author_inst": "Bioqual Inc." + }, + { + "author_name": "Brandon Narvaez", + "author_inst": "Bioqual Inc." + }, + { + "author_name": "Zack Flinchbaugh", + "author_inst": "Bioqual Inc." }, { - "author_name": "Julian von Mendel", - "author_inst": "IU International University of Applied Sciences" + "author_name": "Alex Van Ry", + "author_inst": "Bioqual Inc." + }, + { + "author_name": "Jake Yalley-Ogunro", + "author_inst": "Bioqual Inc." + }, + { + "author_name": "Hanne Andersen", + "author_inst": "Bioqual Inc." + }, + { + "author_name": "Chih-Yun Lai", + "author_inst": "University of Hawaii at Manoa" + }, + { + "author_name": "Oreola Donini", + "author_inst": "Soligenix, Inc" + }, + { + "author_name": "Axel T Lehrer", + "author_inst": "University of Hawaii at Manoa" } ], "version": "1", - "license": "cc_by_nc_nd", - "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "license": "cc_no", + "type": "new results", + "category": "immunology" }, { "rel_doi": "10.1101/2021.09.19.21262615", @@ -567034,39 +566697,31 @@ "category": "oncology" }, { - "rel_doi": "10.1101/2021.09.22.21263984", - "rel_title": "Consequences of COVID-19 vaccine allocation inequity in Chicago", + "rel_doi": "10.1101/2021.09.22.21263488", + "rel_title": "Monoclonal antibodies therapy for Covid-19 - Experiences at a regional hospital.", "rel_date": "2021-09-23", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.22.21263984", - "rel_abs": "During Chicagos initial COVID-19 vaccine rollout, the city disproportionately allocated vaccines to zip codes with high incomes and predominantly White populations. However, the impact of this inequitable distribution on COVID-19 outcomes is unknown. This observational study determined the association between zip-code level vaccination rate and COVID-19 mortality in residents of 52 Chicago zip codes. After controlling for age distribution and recovery from infection, a 10% higher vaccination rate by March 28, 2021, was associated with a 39% lower relative risk of death during the peak of the spring wave of COVID-19. Using a difference-in-difference analysis, Chicago could have prevented an estimated 72% of deaths in the least vaccinated quartile of the city (vaccination rates of 17.8 - 26.9%) if it had had the same vaccination rate as the most vaccinated quartile (39.9 - 49.3%). Inequitable vaccine allocation in Chicago likely exacerbated existing racial disparities in COVID-19 mortality.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.22.21263488", + "rel_abs": "Applying monoclonal antibodies against Covid-19 is a promising treatment option for avoiding severe outcomes. However, real life data, especially in regional hospitals are still scarce. We here report on our first results with this therapy in a retrospective, observational study. Indeed, compared to a risk-factor matched reference group, hospitalisation time was reduced but survival rate and kinetics of SARS-CoV-2 RT-PCR results remained apparently unaffected.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Sharon Zeng", - "author_inst": "University of Chicago" - }, - { - "author_name": "Kenley M Pelzer", - "author_inst": "University of Chicago" + "author_name": "Judith Pannier", + "author_inst": "Dessau Medical Centre" }, { - "author_name": "Robert D Gibbons", - "author_inst": "University of Chicago" - }, - { - "author_name": "Monica E Peek", - "author_inst": "University of Chicago" + "author_name": "Norbert Nass", + "author_inst": "Dessau Mecial Centre" }, { - "author_name": "William Fiske Parker", - "author_inst": "University of Chicago" + "author_name": "Gerhard Behre", + "author_inst": "Dessau Medical Centre" } ], "version": "1", "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "health policy" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2021.09.22.21263998", @@ -569056,45 +568711,25 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.09.20.21263865", - "rel_title": "Vitamin D and socioeconomic deprivation mediate COVID-19 ethnic health disparities", + "rel_doi": "10.1101/2021.09.20.21263509", + "rel_title": "Real-world clinical performance of SARS-CoV-2 point-of-care diagnostic tests: a systematic review of available trials as per April, 4, 2021", "rel_date": "2021-09-22", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.20.21263865", - "rel_abs": "Ethnic minorities in developed countries suffer a disproportionately high burden of COVID-19 morbidity and mortality, and COVID-19 ethnic disparities have been attributed to social determinants of health. Vitamin D has been proposed as a modifiable risk factor that could mitigate COVID-19 health disparities. We investigated the relationship between vitamin D and COVID-19 susceptibility and severity using the UK Biobank, a large progressive cohort study of the United Kingdom population. Structural equation modelling was used to evaluate the ability of vitamin D, socioeconomic deprivation, and other known risk factors to mediate COVID-19 ethnic health disparities. Asian ethnicity is associated with higher COVID-19 susceptibility, compared to the majority White population, and Asian and Black ethnicity are both associated with higher COVID-19 severity. Socioeconomic deprivation mediates all three ethnic disparities and shows the highest overall signal of mediation for any COVID-19 risk factor. Vitamin supplements, including vitamin D, mediate the Asian disparity in COVID-19 susceptibility, and serum 25-hydroxyvitamin D (calcifediol) levels mediate Asian and Black COVID-19 severity disparities. Several measures of overall health also mediate COVID-19 ethnic disparities, underscoring the importance of comorbidities. Our results support ethnic minorities use of vitamin D as both a prophylactic and a supplemental therapeutic for COVID-19.", - "rel_num_authors": 7, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.20.21263509", + "rel_abs": "Point-of-care assays offer a decentralized and fast solution to the diagnosis of SARS-CoV-2, providing benefits for patients, healthcare workers and healthcare facilities. This technology has the potential to prevent outbreaks, enable fast adoption of potentially life-saving measures and improve hospital workflow. While reviews regarding the laboratory performance of those assays exist, a review focused on the real-life clinical performance and true point-of-care feasibility of those platforms is missing. Therefore, the objective of this study is to help clinicians, healthcare providers and organizations to understand the real-life performance of point-of-care assays, aiding in their implementation in decentralised, true point-of-care facilities, or inside hospitals. 1246 studies were screened in 3 databases and 87 studies were included, evaluating 27 antigen tests and 11 nucleic-acid amplification platforms deemed feasible for true point-of-care placement. We excluded studies that used processed samples, pre-selected populations, archived samples and laboratory-only evaluations and strongly favored prospective trial designs. We also investigated package inserts, instructions for use, comments on published studies and manufacturers websites in order to assess feasibility of point-of-care placement and additional information of relevance to the end-user. Apart from performance in the form of sensitivity and specificity, we present information on time to results, hands-on time, kit storage, machine operating conditions and regulatory status. To the best of our knowledge, this is the first review to systematically compare point-of-care test performance in real-life clinical practice. We found the performance of tests in clinical practice to be markedly different from the manufacturers reported performance and laboratory- only evaluations in the majority of scenarios. Our findings may help in the decision-making process related to SARS-CoV-2 test in real-life clinical settings.\n\nRationale for the reviewA review focused on the real-life clinical performance and point-of-care feasibility of SARS-CoV-2 diagnostic platforms is missing, impairing the ability of individuals, healthcare providers and test providers to make informed decisions.\n\nObjective(s) or question(s) the review addressesThe objective of this study is to help clinicians, healthcare providers and organizations to understand the real-life performance of point-of-care assays, aiding in their implementation in decentralised, true point-of-care facilities or in complex healthcare environments.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Leonardo Marino-Ramirez", - "author_inst": "National Institute on Minority Health and Health Disparities, National Institutes of Health" - }, - { - "author_name": "Maria Ahmad", - "author_inst": "National Institute on Minority Health and Health Disparities, National Institutes of Health" - }, - { - "author_name": "Lavanya Rishishwar", - "author_inst": "National Institute on Minority Health and Health Disparities, National Institutes of Health" - }, - { - "author_name": "Shashwat Deepali Nagar", - "author_inst": "Georgia Institute of Technology" - }, - { - "author_name": "Kara K. Lee", - "author_inst": "Georgia Institute of Technology" - }, - { - "author_name": "Emily T. Norris", - "author_inst": "National Institute on Minority Health and Health Disparities, National Institutes of Health" + "author_name": "Gabriel Henrique Hawthorne", + "author_inst": "Cambridge University Hospitals" }, { - "author_name": "I. King King Jordan", - "author_inst": "Georgia Institute of Technology" + "author_name": "Adam Harvey", + "author_inst": "Diagnostics For the Real World" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -570531,71 +570166,79 @@ "category": "occupational and environmental health" }, { - "rel_doi": "10.1101/2021.09.16.21263693", - "rel_title": "The longitudinal kinetics of antibodies in COVID-19 recovered patients over 14 months", + "rel_doi": "10.1101/2021.09.16.21263692", + "rel_title": "Immunogenicity of a third dose viral-vectored COVID-19 vaccine after receiving two-dose inactivated vaccines in healthy adults", "rel_date": "2021-09-21", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.16.21263693", - "rel_abs": "Here, we describe the longitudinal kinetics of the serological response in COVID-19 recovered patients over the period of 14 months. The antibody kinetics in a cohort of 200 recovered patients with 89 follow up samples at 2-4 visits reveal that RBD-specific antibodies decay over the period of 14 month following the onset of symptoms. The decay rate is associated with the robustness of the response thus, recovered patients that exhibit elevated antibody levels at the first visit, experience faster decay. We further explored the longitudinal kinetics differences between recovered patients and naive BNT162b2 vaccinees. We found a significantly faster decay in naive vaccinees compared to recovered patients suggesting that the serological memory following natural infection is more robust compared to vaccination. Our data highlights the differences between serological memory induced by natural infection vs. vaccination, facilitating the decision making in Israel regarding the 3rd dose vaccination.", - "rel_num_authors": 13, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.16.21263692", + "rel_abs": "In June 2021, Thailand was hit by the delta variant of SARS-CoV-2 resulting in the biggest wave of COVID-19. Due to the widespread delta variant, more than 600 healthcare workers had COVID-19 despite completion of two-dose CoronaVac. The Ministry of Public Health recommended that healthcare workers received a third dose of AZD1222 to increase level of protection against SARS-CoV-2. However, immune response after the third vaccination with AZD1222 are limited. In this study, sera from those who received a booster of AZD1222 in June-July 2021 were tested for SARS-CoV-2 spike receptor-binding-domain (RBD) IgG, anti-RBD total immunoglobulins and anti-spike protein 1 (S1) IgA. The neutralizing activities in a subset of serum samples were tested against the wild type and variants of concern (B.1.1.7, B.1.617.2, and B.1.351) using an enzyme-linked immunosorbent assay-based surrogate virus neutralization test. Participants who received the booster of AZD1222 possessed higher levels of spike RBD-specific IgG, total immunoglobulins, and anti-S1 IgA than that two-dose vaccines (p < 0.001). They also elicited higher neutralizing activity against the wild type and all variants of concern than those in the recipients of the two-dose vaccines. This study demonstrated a high immunogenicity of the AZD1222 booster who completed the two-dose inactivated vaccines.", + "rel_num_authors": 15, "rel_authors": [ { - "author_name": "Tsuf Eyran", - "author_inst": "Tel-Aviv university" + "author_name": "Ritthideach Yorsaeng", + "author_inst": "Center of Excellence in Clinical Virology, Faculty of Medicine, Chulalongkorn University, Bangkok, 10330, Thailand" }, { - "author_name": "Anna Vaisman-Mentesh", - "author_inst": "Tel-Aviv University" + "author_name": "Nungruthai Suntronwong", + "author_inst": "Center of Excellence in Clinical Virology, Faculty of Medicine, Chulalongkorn University, Bangkok, 10330, Thailand" }, { - "author_name": "Yeal Dror", - "author_inst": "Tel-Aviv University" + "author_name": "Harit Phowatthanasathian", + "author_inst": "Center of Excellence in Clinical Virology, Faculty of Medicine, Chulalongkorn University, Bangkok, 10330, Thailand" }, { - "author_name": "Ligal Aizik", - "author_inst": "Tel-Aviv University" + "author_name": "Suvichada Assawakosri", + "author_inst": "Center of Excellence in Clinical Virology, Faculty of Medicine, Chulalongkorn University, Bangkok, 10330, Thailand" }, { - "author_name": "Aya Kigel", - "author_inst": "Tel-Aviv University" + "author_name": "Sitthichai Kanokudom", + "author_inst": "Center of Excellence in Clinical Virology, Faculty of Medicine, Chulalongkorn University, Bangkok, 10330, Thailand" }, { - "author_name": "Shai Rosenstein", - "author_inst": "Tel-Aviv University" + "author_name": "Thanunrat Thongmee", + "author_inst": "Excellence in Clinical Virology, Faculty of Medicine, Chulalongkorn University, Bangkok, 10330, Thailand" }, { - "author_name": "Yeal Bahar", - "author_inst": "Tel-Aviv University" + "author_name": "Preeyaporn Vichaiwattana", + "author_inst": "Center of Excellence in Clinical Virology, Faculty of Medicine, Chulalongkorn University, Bangkok, 10330, Thailand" }, { - "author_name": "David Taussig", - "author_inst": "Tel-Aviv University" + "author_name": "Chompoonut Auphimai", + "author_inst": "Center of Excellence in Clinical Virology, Faculty of Medicine, Chulalongkorn University, Bangkok, 10330, Thailand" }, { - "author_name": "Ran Tur-Kaspa", - "author_inst": "Department of Medicine D and the Liver Institute, Rabin Medical Center, Beilinson Hospital, Molecular Hepatology Research Laboratory, Felsenstein Medical Resear" + "author_name": "Lakkhana Wongsrisang", + "author_inst": "Center of Excellence in Clinical Virology, Faculty of Medicine, Chulalongkorn University, Bangkok, 10330, Thailand" }, { - "author_name": "Tatiana Kournos", - "author_inst": "Internal Medicine D, Hasharon Hospital-Rabin Medical Center, Petach Tikva, Israel" + "author_name": "Donchida Srimuan", + "author_inst": "Center of Excellence in Clinical Virology, Faculty of Medicine, Chulalongkorn University, Bangkok, 10330, Thailand" }, { - "author_name": "Dana Markovitch", - "author_inst": "Internal Medicine D, Hasharon Hospital-Rabin Medical Center, Petach Tikva, Israel" + "author_name": "Thaksaporn Thatsanatorn", + "author_inst": "Center of Excellence in Clinical Virology, Faculty of Medicine, Chulalongkorn University, Bangkok, 10330, Thailand" }, { - "author_name": "Dror Dicker", - "author_inst": "Internal Medicine D, Hasharon Hospital-Rabin Medical Center, Petach Tikva, Israel" + "author_name": "Sirapa Klinfueng", + "author_inst": "Center of Excellence in Clinical Virology, Faculty of Medicine, Chulalongkorn University, Bangkok, 10330, Thailand" }, { - "author_name": "Yariv Wine", - "author_inst": "Tel Aviv University" + "author_name": "Natthinee Sudhinaraset", + "author_inst": "Center of Excellence in Clinical Virology, Faculty of Medicine, Chulalongkorn University, Bangkok, 10330, Thailand" + }, + { + "author_name": "Nasamon Wanlapakorn", + "author_inst": "Center of Excellence in Clinical Virology, Faculty of Medicine, Chulalongkorn University, Bangkok, 10330, Thailand" + }, + { + "author_name": "Yong Poovorawan", + "author_inst": "Center of Excellence in Clinical Virology, Faculty of Medicine, Chulalongkorn University, Bangkok, 10330, Thailand" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "allergy and immunology" }, { "rel_doi": "10.1101/2021.09.16.21263701", @@ -571925,63 +571568,31 @@ "category": "evolutionary biology" }, { - "rel_doi": "10.1101/2021.09.21.21263880", - "rel_title": "Prior Covid-19 and high RBD-IgG levels correlate with protection against VOC-delta SARS-CoV-2 infection in vaccinated Nursing Home Residents", + "rel_doi": "10.1101/2021.09.17.21263670", + "rel_title": "Effectiveness of vaccination in preventing severe SARS CoV-2 infection in South India-a hospital based cross sectional study", "rel_date": "2021-09-21", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.21.21263880", - "rel_abs": "BackgroundNursing Home (NH) residents are at high risk of serious illness and death from coronavirus disease 2019 (Covid-19), especially with the SARS-CoV-2 variants of concerns (VOC). It is unknown as to whether a history of Covid-19 prior to the vaccine and post-vaccine RBD-IgG levels are predictors of BNT162b2 vaccine effectiveness against VOC-{delta} in nursing home residents.\n\nMethodsWe analyzed the data from two NHs that faced a VOC-{delta} outbreak in July-August 2021. These NHs had suffered prior Covid-19 outbreaks in 2020 and 2021. In many of the residents, RBD-IgG levels were measured 6 weeks after the second vaccine dose, i.e. 3 to 5 months before the VOC-{delta} outbreak onset, and again during the outbreak (SARS-CoV-2 IgG II Quant assay, Abbott Diagnostics). We compared residents with vs without prior Covid-19 for (i) VOC-{delta} incidence, (ii) the correlation between post-vaccine RBD-IgG levels and VOC-{delta} incidence, and (iii) the time-related change in RBD-IgG levels.\n\nResultsAmong the 140 analyzed residents (58 to 101 years; 94 females, 46 men, mean age: 84.6 yr {+/-} 9.5 yr), one resident among the 44 with prior Covid-19 before vaccination developed a VOC-{delta} infection during the outbreak (1.3%) vs 55 of the 96 without Covid-19 prior to vaccination (57.3 %)(p<0.0001). The median value for RBD-IgG 6 weeks after the vaccine and during the outbreak was higher in residents with prior Covid-19 (31,553 AU/mL and 22,880 AU/mL) than in those without (1,050 AU/mL and 260 AU/mL)(p<0.0001). In residents without Covid-19 prior to vaccination, post-vaccination RDB-IgG levels did not predict protection against VOC-{delta} infection.\n\nConclusionsIn contrary to residents with prior SARS-CoV-2 infection, those without a history of Covid-19 before two BNT162b2 doses are not protected against VOC-{delta} infection and their RBD-Ig-G levels are low 3 to 5 months after vaccination. This suggests that a booster vaccine dose should be considered in this group of residents for a better protection against VOC-{delta} infection.", - "rel_num_authors": 11, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.17.21263670", + "rel_abs": "Background & objectivesEstablishing concrete evidence on the effect of vaccination on the severity of SARS CoV-2 infections in real-world situations is the need of the hour. This study aims to estimate the effectiveness of Covid 19 vaccines in preventing the new and severe SARS CoV-2 infections.\n\nDesignCross-sectional study\n\nSetting& ParticipantsWe did this cross-sectional study among the 4565 patients consecutive adult inpatients admitted in the Covid 19 wards of a tertiary care hospital from May 7, 2021, to October 7, 2021, during the second wave of the Covid 19 pandemic. Information on basic demographic variables, RT PCR status, vaccination status, outcome and clinical severity of illness were obtained from the electronic hospital patient records.\n\nResultsOnly 4% of the study participants had prior vaccination. The type of vaccine and number of doses didnt have any protective effect against the new SARS CoV-2 infection and breakthrough infection. Fully vaccinated RTPCR positive patients had an 82% reduction in the need for ICU admission (OR 0.09; AOR 0.18, CI (0.04 to 0.8), P <0.05) and a non-significant 79% in mortality (OR 0.19; AOR 0.21, CI (0.04 to 1.1) P>0.05).\n\nConclusionVaccination doesnt protect against new SARS Cov-2 infection and breakthrough infection however significant protection was documented against severe SARS Cov-2 infection. The protective effect shown by the vaccines in preventing the severe form of SARS Cov-2 infection among fully vaccinated patients was 82%. Vaccination coverage should be increased urgently to halt the impending wave of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Hubert Blain", - "author_inst": "University hospital of Montpellier" + "author_name": "A.charles pon ruban", + "author_inst": "TIRUNELVELI MEDICAL COLLEGE" }, { - "author_name": "Edouard TUAILLON", - "author_inst": "Montpellier University" + "author_name": "Aazmi Mohamed", + "author_inst": "TIRUNELVELI MEDICAL COLLEGE" }, { - "author_name": "Amandine Pisoni", - "author_inst": "Montpellier university" - }, - { - "author_name": "Laure Soriteau", - "author_inst": "Montpellier university" - }, - { - "author_name": "Elodie Million", - "author_inst": "Montpellier University" - }, - { - "author_name": "Marie-Suzanne Leglise", - "author_inst": "Montpellier University" - }, - { - "author_name": "Isabelle Bussereau", - "author_inst": "Montpellier university hospital" - }, - { - "author_name": "Stephanie Miot", - "author_inst": "Montpellier University" - }, - { - "author_name": "Yves Rolland", - "author_inst": "Toulouse university" - }, - { - "author_name": "Marie-Christine Picot", - "author_inst": "Montpellier University" - }, - { - "author_name": "Jean J Bousquet", - "author_inst": "CHU" + "author_name": "Shantaraman Kalyanaraman", + "author_inst": "TIRUNELVELI MEDICAL COLLEGE" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "public and global health" }, { "rel_doi": "10.1101/2021.09.13.21263406", @@ -574351,71 +573962,123 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.09.15.21263613", - "rel_title": "COVID-19 vaccine effectiveness against hospitalizations and ICU admissions in the Netherlands, April- August 2021", + "rel_doi": "10.1101/2021.09.14.21263567", + "rel_title": "Comparison of children and young people admitted with SARS-CoV-2 across the UK in the first and second pandemic waves: prospective multicentre observational cohort study", "rel_date": "2021-09-17", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.15.21263613", - "rel_abs": "The objective of this study was to estimate vaccine effectiveness (VE) against COVID-19 hospitalization and ICU admission, per period according to dominating SARS-CoV-2 variant (Alpha and Delta), per vaccine and per time since vaccination. To this end, data from the national COVID-19 vaccination register was added to the national register of COVID-19 hospitalizations. For the study period 4 April - 29 August 2021, 15,571 hospitalized people with COVID-19 were included in the analysis, of whom 887 (5.7%) were fully vaccinated. Incidence rates of hospitalizations and ICU admissions per age group and vaccination status were calculated, and VE was estimated as 1-incidence rate ratio, adjusted for calendar date and age group in a negative binomial regression model. VE against hospitalization for full vaccination was 94% (95%CI 93-95%) in the Alpha period and 95% (95%CI 94-95%) in the Delta period. The VE for full vaccination against ICU admission was 93% (95%CI 87-96%) in the Alpha period and 97% (95%CI 97-98%) in the Delta period. VE was high in all age groups and did not show waning with time since vaccination up to 20 weeks after full vaccination.", - "rel_num_authors": 13, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.14.21263567", + "rel_abs": "BackgroundChildren and young people (CYP) were less affected than adults in the first wave of SARS-CoV-2 in the UK. We test the hypothesis that clinical characteristics of hospitalized CYP with SARS-CoV-2 in the UK second wave would differ from the first due to the combined impact of the alpha variant, school reopening and relaxation of shielding.\n\nMethodsPatients <19 years hospitalised in the UK with clinician-reported SARS-CoV-2 were enrolled in a prospective multicentre observational cohort study between 17th January 2020 and 31st January 2021. Minimum follow up time was two weeks. Clinical characteristics were compared between the first (W1) and second wave (W2) of infections.\n\nFindings2044 CYP aged <19 years were reported from 187 hospitals. 427/2044 (20.6%) had asymptomatic/incidental SARS-CoV-2 infection and were excluded from main analysis. 16.0% (248/1548) of symptomatic CYP were admitted to critical care and 0.8% (12/1504) died. 5.6% (91/1617) of symptomatic CYP had Multisystem Inflammatory Syndrome in Children (MIS-C).\n\nPatients in W2 were significantly older (median age 6.5 years, IQR 0.3-14.9) than W1 (4.0 (0.4-13.6, p 0.015). Fever was more common in W1, otherwise presenting symptoms and comorbidities were similar across waves. After excluding CYP with MIS-C, patients in W2 had lower PEWS at presentation, lower antibiotic use and less respiratory and cardiovascular support compared to W1. There was no change in the proportion of CYP admitted to critical care between W1 and W2.\n\n58.0% (938/1617) of symptomatic CYP had no reported comorbidity. Patients without co-morbidities were younger (42.4%, 398/938, <1 year old), had lower Paediatric Early Warning Scores (PEWS) at presentation, shorter length of hospital stay and received less respiratory support. MIS-C was responsible for a large proportion of critical care admissions, invasive and non-invasive ventilatory support, inotrope and intravenous corticosteroid use in CYP without comorbidities.\n\nInterpretationSevere disease in CYP admitted with symptomatic SARS-CoV-2 in the UK remains rare. One in five CYP in this cohort had asymptomatic/incidental SARS-CoV-2 infection. We found no evidence of increased disease severity in W2 compared with W1.\n\nFundingShort form: National Institute for Health Research, UK Medical Research Council, Wellcome Trust, Department for International Development and the Bill and Melinda Gates Foundation.\n\nLong form: This work is supported by grants from the National Institute for Health Research (award CO-CIN-01) and the Medical Research Council (grant MC_PC_19059) and by the National Institute for Health Research Health Protection Research Unit (NIHR HPRU) in Emerging and Zoonotic Infections at University of Liverpool in partnership with Public Health England (PHE), in collaboration with Liverpool School of Tropical Medicine and the University of Oxford (NIHR award 200907), Wellcome Trust and Department for International Development (215091/Z/18/Z), and the Bill and Melinda Gates Foundation (OPP1209135). Liverpool Experimental Cancer Medicine Centre provided infrastructure support for this research (grant reference: C18616/A25153). JSN-V-T is seconded to the Department of Health and Social Care, England (DHSC). The views expressed are those of the authors and not necessarily those of the DHSC, DID, NIHR, MRC, Wellcome Trust, or PHE.", + "rel_num_authors": 26, "rel_authors": [ { - "author_name": "Brechje de Gier", - "author_inst": "Center for Infectious Disease Control, National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands" + "author_name": "Swann V Swann PhD", + "author_inst": "Department of Child Life and Health, University of Edinburgh, UK" }, { - "author_name": "Marjolein Kooijman", - "author_inst": "Center for Infectious Disease Control, National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands" + "author_name": "Louisa Pollock PhD", + "author_inst": "Royal Hospital for Children, Glasgow, UK" }, { - "author_name": "Jeanet Kemmeren", - "author_inst": "Center for Infectious Disease Control, National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands" + "author_name": "Karl A Holden MBChB", + "author_inst": "NIHR Health Protection Research Unit in Emerging and Zoonotic Infections and Institute of Infection, Veterinary and Ecological Sciences, Faculty of Health and " }, { - "author_name": "Nicolette de Keizer", - "author_inst": "Amsterdam UMC, University of Amsterdam, Department of Medical Informatics, Amsterdam Public Health research institute, Amsterdam, The Netherlands; National Inte" + "author_name": "Alasdair PS Munro BM", + "author_inst": "NIHR Southampton Clinical Research Facility and NIHR Biomedical Research Centre, University Hospital Southampton NHS Foundation Trust, Southampton, UK" }, { - "author_name": "Dave Dongelmans", - "author_inst": "National Intensive Care Evaluation (NICE) foundation, Amsterdam, the Netherlands; Amsterdam UMC, location AMC, University of Amsterdam, Department of Intensive " + "author_name": "Aisleen Bennett PhD", + "author_inst": "Institute of Infection and Immunity, St George's, University of London, London, UK" }, { - "author_name": "Senna C.J.L. van Iersel", - "author_inst": "Center for Infectious Disease Control, National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands" + "author_name": "Thomas C Williams PhD", + "author_inst": "Department of Child Life and Health, University of Edinburgh, UK" }, { - "author_name": "Jan van de Kassteele", - "author_inst": "Center for Infectious Disease Control, National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands" + "author_name": "Lance Turtle PhD", + "author_inst": "NIHR Health Protection Research Unit in emerging and zoonotic infections, Institute of Infection, Veterinary and Ecological Sciences, University of Liverpool, L" }, { - "author_name": "Stijn P. Andeweg", - "author_inst": "Center for Infectious Disease Control, National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands" + "author_name": "Cameron J Fairfield MSc", + "author_inst": "Centre for Medical Informatics, Usher Institute, University of Edinburgh, UK" }, { - "author_name": "- the RIVM COVID-19 epidemiology and surveillance team", - "author_inst": "" + "author_name": "Thomas M Drake MBChB", + "author_inst": "Centre for Medical Informatics, Usher Institute, University of Edinburgh, UK" }, { - "author_name": "Hester E. de Melker", - "author_inst": "Center for Infectious Disease Control, National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands" + "author_name": "Saul N Faust PhD", + "author_inst": "NIHR Southampton Clinical Research Facility and NIHR Biomedical Research Centre, University Hospital Southampton NHS Foundation Trust, Southampton, UK" }, { - "author_name": "Susan J.M. Hahn\u00e9", - "author_inst": "Center for Infectious Disease Control, National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands" + "author_name": "Ian P Sinha PhD", + "author_inst": "Respiratory Medicine, Alder Hey Childrens Hospital, Liverpool L12 2AP, UK" }, { - "author_name": "Mirjam J. Knol", - "author_inst": "Center for Infectious Disease Control, National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands" + "author_name": "Damian Roland PhD", + "author_inst": "SAPPHIRE Group, Health Sciences, Leicester University, Leicester, UK" }, { - "author_name": "Susan van den Hof", - "author_inst": "Center for Infectious Disease Control, National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands" + "author_name": "Elizabeth Whittaker PhD", + "author_inst": "Paediatric Infectious Diseases, Imperial College Healthcare NHS Trust, Praed St, London, W2 1NY" + }, + { + "author_name": "Shamez Ladhani PhD", + "author_inst": "Immunisation and Countermeasures Division, Public Health England Colindale" + }, + { + "author_name": "Jonathan S Nguyen-Van-Tam DM", + "author_inst": "Division of Epidemiology and Public Health, University of Nottingham School of Medicine, Nottingham, UK" + }, + { + "author_name": "Michelle Girvan BSc", + "author_inst": "Liverpool Clinical Trials Centre, University of Liverpool, Liverpool, UK" + }, + { + "author_name": "Chloe Donohue BSc", + "author_inst": "Liverpool Clinical Trials Centre, University of Liverpool, Liverpool, UK" + }, + { + "author_name": "Cara Donegan LLM", + "author_inst": "NIHR Health Protection Research Unit in Emerging and Zoonotic Infections and Institute of Infection, Veterinary and Ecological Sciences, Faculty of Health and " + }, + { + "author_name": "Rebecca G Spencer LLM", + "author_inst": "NIHR Health Protection Research Unit in Emerging and Zoonotic Infections and Institute of Infection, Veterinary and Ecological Sciences, Faculty of Health and " + }, + { + "author_name": "Hayley E Hardwick", + "author_inst": "NIHR Health Protection Research Unit in Emerging and Zoonotic Infections and Institute of Infection, Veterinary and Ecological Sciences, Faculty of Health and " + }, + { + "author_name": "Peter JM Openshaw PhD", + "author_inst": "National Heart and Lung Institute, Imperial College London, London, UK" + }, + { + "author_name": "J Kenneth Baillie PhD", + "author_inst": "Roslin Institute, University of Edinburgh, Edinburgh, UK" + }, + { + "author_name": "Ewen M Harrison PhD", + "author_inst": "Centre for Medical Informatics, Usher Institute, University of Edinburgh, Edinburgh, UK" + }, + { + "author_name": "Annemarie B Docherty PhD", + "author_inst": "Centre for Medical Informatics, Usher Institute, University of Edinburgh, Edinburgh, UK" + }, + { + "author_name": "Malcolm Gracie Semple PhD", + "author_inst": "NIHR Health Protection Research Unit in Emerging and Zoonotic Infections and Institute of Infection, Veterinary and Ecological Sciences, Faculty of Health and " + }, + { + "author_name": "- ISARIC4C Investigators", + "author_inst": "" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "pediatrics" }, { "rel_doi": "10.1101/2021.09.09.21262609", @@ -576345,121 +576008,93 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.09.03.21263105", - "rel_title": "Emergence of SARS-CoV-2 Resistance with Monoclonal Antibody Therapy", + "rel_doi": "10.1101/2021.09.04.21262414", + "rel_title": "Evaluation of commercially available high-throughput SARS-CoV-2 serological assays for serosurveillance and related applications", "rel_date": "2021-09-15", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.03.21263105", - "rel_abs": "Resistance mutations to monoclonal antibody (mAb) therapy has been reported, but in the non-immunosuppressed population, it is unclear if in vivo emergence of SARS-CoV-2 resistance mutations alters either viral replication dynamics or therapeutic efficacy. In ACTIV-2/A5401, non-hospitalized participants with symptomatic SARS-CoV-2 infection were randomized to bamlanivimab (700mg or 7000mg) or placebo. Treatment-emergent resistance mutations were significantly more likely detected after bamlanivimab 700mg treatment than placebo (7% of 111 vs 0% of 112 participants, P=0.003). There were no treatment-emergent resistance mutations among the 48 participants who received bamlanivimab 7000mg. Participants with emerging mAb resistant virus had significantly higher pre-treatment nasopharyngeal and anterior nasal viral load. Intensive respiratory tract viral sampling revealed the dynamic nature of SARS-CoV-2 evolution, with evidence of rapid and sustained viral rebound after emergence of resistance mutations, and worsened symptom severity. Participants with emerging bamlanivimab resistance often accumulated additional polymorphisms found in current variants of concern/interest and associated with immune escape. These results highlight the potential for rapid emergence of resistance during mAb monotherapy treatment, resulting in prolonged high level respiratory tract viral loads and clinical worsening. Careful virologic assessment should be prioritized during the development and clinical implementation of antiviral treatments for COVID-19.", - "rel_num_authors": 27, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.04.21262414", + "rel_abs": "SARS-CoV-2 serosurveys can estimate cumulative incidence for monitoring epidemics but require characterization of employed serological assays performance to inform testing algorithm development and interpretation of results. We conducted a multi-laboratory evaluation of 21 commercial high-throughput SARS-CoV-2 serological assays using blinded panels of 1,000 highly-characterized blood-donor specimens. Assays demonstrated a range of sensitivities (96%-63%), specificities (99%-96%) and precision (IIC 0.55-0.99). Durability of antibody detection in longitudinal samples was dependent on assay format and immunoglobulin target, with anti-spike, direct, or total Ig assays demonstrating more stable, or increasing reactivity over time than anti-nucleocapsid, indirect, or IgG assays. Assays with high sensitivity, specificity and durable antibody detection are ideal for serosurveillance. Less sensitive assays demonstrating waning reactivity are appropriate for other applications, including characterizing antibody responses after infection and vaccination, and detection of anamnestic boosting by reinfections and vaccine breakthrough infections. Assay performance must be evaluated in the context of the intended use.", + "rel_num_authors": 20, "rel_authors": [ { - "author_name": "Manish Chandra Choudhary", - "author_inst": "Brigham and Women's Hospital, Harvard Medical School, Boston, MA" - }, - { - "author_name": "Kara W Chew", - "author_inst": "University of California, Los Angeles, Los Angeles, CA" - }, - { - "author_name": "Rinki Deo", - "author_inst": "Brigham and Women's Hospital, Harvard Medical School, Boston, MA" - }, - { - "author_name": "James P Flynn", - "author_inst": "Brigham and Women's Hospital, Harvard Medical School, Boston, MA" - }, - { - "author_name": "James Regan", - "author_inst": "Brigham and Women's Hospital, Harvard Medical School, Boston, MA" - }, - { - "author_name": "Charles R Crain", - "author_inst": "Brigham and Women's Hospital, Harvard Medical School, Boston, MA" - }, - { - "author_name": "Carlee Moser", - "author_inst": "Harvard T.H. Chan School of Public Health, Boston, MA" - }, - { - "author_name": "Michael Hughes", - "author_inst": "Harvard T.H. Chan School of Public Health, Boston, MA" + "author_name": "Mars Stone", + "author_inst": "Vitalant Research Institiute" }, { - "author_name": "Justin Ritz", - "author_inst": "Harvard T.H. Chan School of Public Health, Boston, MA" + "author_name": "Eduard Grebe", + "author_inst": "Vitalant Research Institute" }, { - "author_name": "Ruy M Ribeiro", - "author_inst": "Los Alamos National Laboratory, Los Alamos, NM" + "author_name": "Hasan Sulaeman", + "author_inst": "Vitalant Research Institute" }, { - "author_name": "Ruian Ke", - "author_inst": "Los Alamos National Laboratory, Los Alamos, NM" + "author_name": "Clara Di Germanio", + "author_inst": "Vitalant Research Institute" }, { - "author_name": "Joan A Dragavon", - "author_inst": "University of Washington, Seattle, WA" + "author_name": "Honey Dave", + "author_inst": "Vitalant Research Institute" }, { - "author_name": "Arzhang C Javan", - "author_inst": "National Institutes of Health, Bethesda, MD" + "author_name": "Kathleen Kelly", + "author_inst": "Vitalant Research Institute" }, { - "author_name": "Ajay Nirula", - "author_inst": "Lilly Research Laboratories, San Diego, CA" + "author_name": "Brad Biggerstaff", + "author_inst": "Centers for Disease Control and Prevention" }, { - "author_name": "Paul Klekotka", - "author_inst": "Lilly Research Laboratories, San Diego, CA" + "author_name": "Brigit O Crews", + "author_inst": "University of California Irvine Medical Center" }, { - "author_name": "Alexander L Greninger", - "author_inst": "University of Washington, Seattle, WA" + "author_name": "Nam Tran", + "author_inst": "Department of Pathology and Laboratory Medicine University of California, Davis" }, { - "author_name": "Courtney V Fletcher", - "author_inst": "University of Nebraska Medical Center, Omaha, NE" + "author_name": "Keith Jerome", + "author_inst": "University of Washington" }, { - "author_name": "Eric S Daar", - "author_inst": "University of California, Los Angeles, Los Angeles, CA" + "author_name": "Thomas N Denny", + "author_inst": "Duke University" }, { - "author_name": "David A Wohl", - "author_inst": "University of North Carolina, Chapel Hill, NC" + "author_name": "Boris Hogema", + "author_inst": "Department of Blood-Borne Infections, Sanquin Research" }, { - "author_name": "Joseph J Eron", - "author_inst": "University of North Carolina, Chapel Hill, NC" + "author_name": "Mark Destree", + "author_inst": "BloodWorks NorthWest" }, { - "author_name": "Judith S Currier", - "author_inst": "University of California, Los Angeles, Los Angeles, CA" + "author_name": "Jefferson M Jones", + "author_inst": "Centers for Disease Control and Prevention" }, { - "author_name": "Urvi M Parikh", - "author_inst": "University of Pittsburgh, Pittsburgh, PA" + "author_name": "Natalie Thornburg", + "author_inst": "Centers for Disease Control and Prevention" }, { - "author_name": "Scott F Sieg", - "author_inst": "Case Western Reserve University, Cleveland, OH" + "author_name": "Graham Simmons", + "author_inst": "Vitalant Research Institute" }, { - "author_name": "Alan S Perelson", - "author_inst": "Los Alamos National Laboratory, Los Alamos, NM" + "author_name": "Mel Krajden", + "author_inst": "British Columbia Centre for Disease Control" }, { - "author_name": "Robert W Coombs", - "author_inst": "University of Washington, Seattle, WA" + "author_name": "Steven Kleinman", + "author_inst": "Department of Pathology and Laboratory Medicine, University of British Columbia" }, { - "author_name": "Davey M Smith", - "author_inst": "University of California, San Diego, San Diego, CA" + "author_name": "Larry J Dumont", + "author_inst": "Vitalant Research Institute" }, { - "author_name": "Jonathan Z Li", - "author_inst": "Brigham and Women's Hospital, Harvard Medical School, Boston, MA" + "author_name": "Michael Paul Busch", + "author_inst": "VITALANT RESEARCH INSTITUTE" } ], "version": "1", @@ -578111,123 +577746,27 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.09.11.21263428", - "rel_title": "Interrogating COVID-19 Vaccine Hesitancy in the Philippines with a Nationwide Open-Access Online Survey", + "rel_doi": "10.1101/2021.09.15.460506", + "rel_title": "Phylodynamic Pattern of Genetic Clusters, Paradigm Shift on Spatio-temporal Distribution of Clades, and Impact of Spike Glycoprotein Mutations of SARS-CoV-2 Isolates from India", "rel_date": "2021-09-15", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.11.21263428", - "rel_abs": "To mitigate the unprecedented health, social, and economic damage of COVID-19, the Philippines is undertaking a nationwide vaccination program to mitigate the effects of the global pandemic. In this study, we interrogated COVID-19 vaccine hesitancy in the country by deploying a nationwide open-access online survey, two months before the rollout of the national vaccination program. The Health Belief Model (HBM) posits that people are likely to adopt disease prevention behaviors and to accept medical interventions like vaccines if there is sufficient motivation and cues to action. A majority of our 7,193 respondents (62.5%) indicated that they were willing to be vaccinated against COVID-19. Moreover, multivariable analysis revealed that HBM constructs were associated with vaccination intention in the Philippines. Perceptions of high susceptibility, high severity, and significant benefits were all good predictors for vaccination intent. We also found that external cues to action were important. Large majorities of our respondents would only receive the COVID-19 vaccines after many others had received it (72.8%) or after politicians had received it (68.2%). Finally, our study revealed that most (21%) were willing to pay an amount of PHP1,000 [USD20] for the COVID-19 vaccines with an average willing-to-pay amount of PHP1,892 [USD38].", - "rel_num_authors": 26, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2021.09.15.460506", + "rel_abs": "Background: The COVID-19 pandemic is associated with high morbidity and mortality, with the emergence of numerous variants. The dynamics of SARS-CoV-2 with respect to clade distribution is uneven, unpredictable and fast changing. Aims: Retrieving the complete genomes of SARS-CoV-2 from India and subjecting them to analysis on phylogenetic clade diversity, Spike (S) protein mutations and their functional consequences such as immune escape features and impact on infectivity. Methods: Whole genome of SARS-CoV-2 isolates (n=4,326) deposited from India during the period from January 2020 to December 2020 is retrieved from GISAID and various analyses performed using in silico tools. Results: Notable clade dynamicity is observed indicating the emergence of diverse SARS-CoV-2 variants across the country. GR clade is predominant over the other clades and the distribution pattern of clades is uneven. D614G is the commonest and predominant mutation found among the S-protein followed by L54F. Mutation score prediction analyses reveal that there are several mutations in S-protein including the RBD and NTD regions that can influence the virulence of virus. Besides, mutations having immune escape features as well as impacting the immunogenicity and virulence through changes in the glycosylation patterns are identified. Conclusions: The study has revealed emergence of variants with shifting of clade dynamics within a year in India. It is shown uneven distribution of clades across the nation requiring timely deposition of SARS-CoV-2 sequences. Functional evaluation of mutations in S-protein reveals their significance in virulence, immune escape features and disease severity besides impacting therapeutics and prophylaxis.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Alexandria Caple", - "author_inst": "Providence College" - }, - { - "author_name": "Arnie Dimaano", - "author_inst": "University of Santo Tomas" - }, - { - "author_name": "Marc Martin Sagolili", - "author_inst": "University of Santo Tomas" - }, - { - "author_name": "April Anne Uy", - "author_inst": "University of Santo Tomas" - }, - { - "author_name": "Panjee Mariel Aguirre", - "author_inst": "University of Santo Tomas" - }, - { - "author_name": "Dean Lotus Alano", - "author_inst": "University of Santo Tomas" - }, - { - "author_name": "Giselle Sophia Camaya", - "author_inst": "University of Santo Tomas" - }, - { - "author_name": "Brent John Ciriaco", - "author_inst": "University of Santo Tomas" - }, - { - "author_name": "Princess Jerah Clavo", - "author_inst": "University of Santo Tomas" - }, - { - "author_name": "Dominic Cuyugan", - "author_inst": "University of Santo Tomas" - }, - { - "author_name": "Cleinne Florence Geesler Fermo", - "author_inst": "University of Santo Tomas" - }, - { - "author_name": "Paul Jeremy Lanete", - "author_inst": "University of Santo Tomas" - }, - { - "author_name": "Ardwayne Jurel La Torre", - "author_inst": "University of Santo Tomas" - }, - { - "author_name": "Thomas Albert Loteyro", - "author_inst": "University of Santo Tomas" - }, - { - "author_name": "Raisa Mikaela Lua", - "author_inst": "University of Santo Tomas" - }, - { - "author_name": "Nicole Gayle Manansala", - "author_inst": "University of Santo Tomas" - }, - { - "author_name": "Raphael Willard Mosquito", - "author_inst": "University of Santo Tomas" + "author_name": "Siva Subramanian", + "author_inst": "Kings Institute for Preventive Medicine and Research" }, { - "author_name": "Alexa Marie Octaviano", - "author_inst": "University of Santo Tomas" - }, - { - "author_name": "Alexandra Erika Orfanel", - "author_inst": "University of Santo Tomas" - }, - { - "author_name": "Gheyanna Merly Pascual", - "author_inst": "University of Santo Tomas" - }, - { - "author_name": "Aubrey Joy Sale", - "author_inst": "University of Santo Tomas" - }, - { - "author_name": "Sophia Lorraine Tendenilla", - "author_inst": "University of Santo Tomas" - }, - { - "author_name": "Maria Sophia Trinidad", - "author_inst": "University of Santo Tomas" - }, - { - "author_name": "Nicole Jan Trinidad", - "author_inst": "University of Santo Tomas" - }, - { - "author_name": "Daphne Louise Verano", - "author_inst": "University of Santo Tomas" - }, - { - "author_name": "Nicanor Austriaco", - "author_inst": "Providence College" + "author_name": "Satish Kitambi", + "author_inst": "IHETS" } ], "version": "1", - "license": "cc_by_nc_nd", - "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "license": "cc_no", + "type": "new results", + "category": "evolutionary biology" }, { "rel_doi": "10.1101/2021.09.15.459697", @@ -580353,27 +579892,47 @@ "category": "pharmacology and toxicology" }, { - "rel_doi": "10.1101/2021.09.13.21262971", - "rel_title": "Low dose hydroxychloroquine prophylaxis for COVID-19 - a prospective study", + "rel_doi": "10.1101/2021.09.09.21263359", + "rel_title": "A strategy to assess spillover risk of bat SARS-related coronaviruses in Southeast Asia", "rel_date": "2021-09-14", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.13.21262971", - "rel_abs": "BackgroundSince the outbreak of COVID-19 pandemic, the world began a frantic search for possible prophylactic options. While trials on hydroxychloroquine (HCQ) prophylaxis are ongoing, concrete evidence is lacking. The study aimed to determine the relative efficacy of various doses of oral HCQ in prophylaxis and mitigating the severity of COVID-19 in healthcare workers.\n\nMethodsThis was a prospective cohort with four arms (high, medium, low dose, and control) of HCQ prophylaxis, used by healthcare workers at a tertiary care center in India. Participants were grouped as per their opting for any one arm on a voluntary basis as per institute policy under the Government guidance. The outcomes studied were COVID-19 positivity by RT-PCR and its severity assessed by WHO COVID-19 severity scale.\n\nResultsTotal 486 participants were enrolled, of which 29 (6%) opted for low dose, 2 (<1%) medium dose, and none for high dose HCQ while 455 (93.6%) were in the control arm. Of the 164 participants who underwent RT-PCR, 96 (58.2%) tested positive. Out of these 96 positive cases, the majority of them (79 of 96 [82.3%]) were ambulatory and were managed conservatively at home. Only 17.7% (17 of 96) participants, all of them from the control group, required hospitalization with the mild-moderate disease. None of the participants had severe disease, COVID-related complications, ICU stay, or death. The difference in the outcome assessed amongst the various arms was statistically insignificant (p value >0.05).\n\nConclusionThis single-center study demonstrated that HCQ prophylaxis in healthcare workers does not cause a significant reduction in COVID-19 as well as mitigating its severity in those infected. At present, most of the trials have not shown any benefit. The debate continues to rage, should HCQ prophylaxis be given to healthcare workers for chemoprophylaxis?", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.09.21263359", + "rel_abs": "Emerging diseases caused by coronaviruses of likely bat origin (e.g. SARS, MERS, SADS and COVID-19) have disrupted global health and economies for two decades.\n\nEvidence suggests that some bat SARS-related coronaviruses (SARSr-CoVs) could infect people directly, and that their spillover is more frequent than previously recognized. Each zoonotic spillover of a novel virus represents an opportunity for evolutionary adaptation and further spread; therefore, quantifying the extent of this \"hidden\" spillover may help target prevention programs. We derive biologically realistic range distributions for known bat SARSr-CoV hosts and quantify their overlap with human populations. We then use probabilistic risk assessment and data on human-bat contact, human SARSr-CoV seroprevalence, and antibody duration to estimate that [~]400,000 people (median: [~]50,000) are infected with SARSr-CoVs annually in South and Southeast Asia. These data on the geography and scale of spillover can be used to target surveillance and prevention programs for potential future bat-CoV emergence.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "- RE-HCP2 study group", - "author_inst": "" + "author_name": "Cecilia A. S\u00e1nchez", + "author_inst": "EcoHealth Alliance" }, { - "author_name": "Prasan Kumar Panda", - "author_inst": "AIIMS Rishikesh" + "author_name": "Hongying Li", + "author_inst": "EcoHealth Alliance" + }, + { + "author_name": "Kendra L. Phelps", + "author_inst": "EcoHealth Alliance" + }, + { + "author_name": "Carlos Zambrana-Torrelio", + "author_inst": "EcoHealth Alliance" + }, + { + "author_name": "Lin-Fa Wang", + "author_inst": "Duke-NUS Graduate Medical School" + }, + { + "author_name": "Kevin J. Olival", + "author_inst": "EcoHealth Alliance" + }, + { + "author_name": "Peter Daszak", + "author_inst": "EcoHealth Alliance" } ], "version": "1", "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2021.09.10.21262695", @@ -582111,45 +581670,49 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.09.07.21261811", - "rel_title": "A randomized controlled trial of inhaled ciclesonide for outpatient treatment of symptomatic COVID-19 infections", + "rel_doi": "10.1101/2021.09.08.21263279", + "rel_title": "Enhanced Detection of Recently Emerged SARS-CoV-2 Variants of Concern in Wastewater", "rel_date": "2021-09-12", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.07.21261811", - "rel_abs": "ImportanceSystemic corticosteroids are commonly used in the treatment of severe COVID-19. However, their role in the treatment of patients with mild to moderate disease is less clear. The inhaled corticosteroid ciclesonide has shown early promise as a potential treatment for COVID-19.\n\nObjectiveTo determine whether the inhaled steroid ciclesonide is efficacious in patients with high risk for disease progression and can reduce the incidence of long-term COVID-19 symptoms or post-acute sequelae of SARS-CoV-2.\n\nDesignThis was a phase III, multicenter, double-blind, randomized controlled trial to assess the safety and efficacy of ciclesonide metered-dose inhaler (MDI) for the treatment of non-hospitalized participants with symptomatic COVID-19 infection. Patients were screened from June 11, 2020 to November 3, 2020.\n\nSettingThe study was conducted at 10 centers throughout the U.S. public and private, academic and non-academic sites were represented among the centers.\n\nParticipantsParticipants were randomly assigned to ciclesonide MDI 160 {micro}g per actuation, two actuations twice a day (total daily dose 640 {micro}g) or placebo for 30 days.\n\nMain Outcomes and MeasuresThe primary endpoint was time to alleviation of all COVID-19 related symptoms (cough, dyspnea, chills, feeling feverish, repeated shaking with chills, muscle pain, headache, sore throat, and new loss of taste or smell) by Day 30. Secondary endpoints included subsequent emergency department visits or hospital admissions for reasons attributable to COVID-19.\n\nResults413 participants were screened and 400 (96.9%) were enrolled and randomized (197 in the ciclesonide arm and 203 in the placebo arm). The median time to alleviation of all COVID-19-related symptoms was 19.0 days (95% CI: 14.0, 21.0) in the ciclesonide arm and 19.0 days (95% CI: 16.0, 23.0) in the placebo arm. There was no difference in resolution of all symptoms by Day 30 (odds ratio [OR] 1.28, 95% CI: 0.84, 1.97). Participants treated with ciclesonide had fewer subsequent emergency department visits or hospital admissions for reasons attributable to COVID-19 (OR 0.18, 95% CI: 0.04 - 0.85). No subjects died during the study.\n\nConclusions and RelevanceCiclesonide did not achieve the primary efficacy endpoint of time to alleviation of all COVID-19-related symptoms. Future studies of inhaled steroids are needed to explore their efficacy in patients with high risk for disease progression and in reducing the incidence of long-term COVID-19 symptoms or post-acute sequelae of SARS-CoV-2.\n\nTrial RegistrationClinicalTrials.gov\n\nNCT04377711\n\nhttps://clinicaltrials.gov/ct2/show/NCT04377711\n\nKey PointsO_ST_ABSQuestionC_ST_ABSCan the inhaled steroid ciclesonide be efficacious in patients with high risk for disease progression and reduce the incidence of long-term COVID-19 symptoms or post-acute sequelae of SARS-CoV-2?\n\nFindingsIn this randomized clinical trial of 413 patients, ciclesonide did not reduce the time to alleviation of all COVID-19-related symptoms. However, patients treated with ciclesonide had fewer subsequent emergency department visits or hospital admissions for reasons attributable to COVID-19.\n\nMeaningFuture studies of inhaled steroids are needed to explore their efficacy in patients with high risk for disease progression and in reducing the incidence of long-term COVID-19 symptoms or post-acute sequelae of SARS-CoV-2.", - "rel_num_authors": 7, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.08.21263279", + "rel_abs": "As clinical testing declines, wastewater monitoring can provide crucial surveillance on the emergence of SARS-CoV-2 variants of concern (VoC) in communities. Multiple recent studies support that wastewater-based SARS-CoV-2 detection of circulating VoC can precede clinical cases by up to two weeks. Furthermore, wastewater based epidemiology enables wide population-based screening and study of viral evolutionary dynamics. However, highly sensitive detection of emerging variants remains a complex task due to the pooled nature of environmental samples and genetic material degradation. In this paper we propose quasi-unique mutations for VoC identification, implemented in a novel bioinformatics tool (QuaID) for VoC detection based on quasi-unique mutations. The benefits of QuaID are three-fold: (i) provides up to 3 week earlier VoC detection compared to existing approaches, (ii) enables more sensitive VoC detection, which is shown to be tolerant of >50% mutation drop-out, and (iii) leverages all mutational signatures, including insertions & deletions.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Brian M Clemency", - "author_inst": "University at Buffalo" + "author_name": "Nicolae Sapoval", + "author_inst": "Rice University" }, { - "author_name": "Renoj Varughese", - "author_inst": "University at Buffalo" + "author_name": "Yunxi Liu", + "author_inst": "Rice University" }, { - "author_name": "Yaneicy Gonzalez-Rojas", - "author_inst": "Verus Clinical Research Corporation" + "author_name": "Esther Lou", + "author_inst": "Rice University" }, { - "author_name": "Caryn G. Morse", - "author_inst": "Wake Forest School of Medicine" + "author_name": "Loren Hopkins", + "author_inst": "Houston Health and Human Services Department" }, { - "author_name": "Wanda Phipatanakul", - "author_inst": "Boston Children's Hospital, Harvard Medical School" + "author_name": "Katherine B Ensor", + "author_inst": "Rice University" }, { - "author_name": "David J. Koster", - "author_inst": "Instat Clinical Research" + "author_name": "Rebecca Schneider", + "author_inst": "Houston Health and Human Services Department" + }, + { + "author_name": "Lauren Stadler", + "author_inst": "Rice University" }, { - "author_name": "Michael S. Blaiss", - "author_inst": "Medical College of Georgia at Augusta University" + "author_name": "Todd Treangen", + "author_inst": "Rice University" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -583697,147 +583260,87 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.09.10.21263376", - "rel_title": "An open label, adaptive, phase 1 trial of high-dose oral nitazoxanide in healthy volunteers: an antiviral candidate for SARS-CoV-2", - "rel_date": "2021-09-11", + "rel_doi": "10.1101/2021.09.02.21262480", + "rel_title": "The contribution of hospital-acquired infections to the COVID-19 epidemic in England in the first half of 2020", + "rel_date": "2021-09-10", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.10.21263376", - "rel_abs": "Repurposing approved drugs may rapidly establish effective interventions during a public health crisis. This has yielded immunomodulatory treatments for severe COVID-19, but repurposed antivirals have not been successful to date because of redundancy of the target in vivo or suboptimal exposures at studied doses. Nitazoxanide is an FDA approved antiparasitic medicine, that physiologically-based pharmacokinetic (PBPK) modelling has indicated may provide antiviral concentrations across the dosing interval, when repurposed at higher than approved doses. Within the AGILE trial platform (NCT04746183) an open label, adaptive, phase 1 trial in healthy adult participants was undertaken with high dose nitazoxanide. Participants received 1500mg nitazoxanide orally twice-daily with food for 7 days. Primary outcomes were safety, tolerability, optimum dose and schedule. Intensive pharmacokinetic sampling was undertaken day 1 and 5 with Cmin sampling on day 3 and 7. Fourteen healthy participants were enrolled between 18th February and 11th May 2021. All 14 doses were completed by 10/14 participants. Nitazoxanide was safe and well tolerated with no significant adverse events. Moderate gastrointestinal disturbance (loose stools) occurred in 8 participants (57.1%), with urine and sclera discolouration in 12 (85.7%) and 9 (64.3%) participants, respectively, without clinically significant bilirubin elevation. This was self-limiting and resolved upon drug discontinuation. PBPK predictions were confirmed on day 1 but with underprediction at day 5. Median Cmin was above the in vitro target concentration on first dose and maintained throughout. Nitazoxanide administered at 1500mg BID with food was safe and well tolerated and a phase 1b/2a study is now being initiated in COVID-19 patients.", - "rel_num_authors": 32, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.02.21262480", + "rel_abs": "BackgroundSARS-CoV-2 spreads in hospitals, but the contribution of these settings to the overall COVID-19 burden at a national level is unknown.\n\nMethodsWe used comprehensive national English datasets and simulation modelling to determine the total burden (identified and unidentified) of symptomatic hospital-acquired infections. Those unidentified would either be 1) discharged before symptom onset (\"missed\"), or 2) have symptom onset 7 days or fewer from admission (\"misclassified\"). We estimated the contribution of \"misclassified\" cases and transmission from \"missed\" symptomatic infections to the English epidemic before 31st July 2020.\n\nFindingsIn our dataset of hospitalised COVID-19 patients in acute English Trusts with a recorded symptom onset date (n = 65,028), 7% were classified as hospital-acquired (with symptom onset 8 or more days after admission and before discharge). We estimated that only 30% (range across weeks and 200 simulations: 20-41%) of symptomatic hospital-acquired infections would be identified. Misclassified cases and onward transmission from missed infections could account for 15% (mean, 95% range over 200 simulations: 14{middle dot}1%-15{middle dot}8%) of cases currently classified as community-acquired COVID-19.\n\nFrom this, we estimated that 26,600 (25,900 to 27,700) individuals acquired a symptomatic SARS-CoV-2 infection in an acute Trust in England before 31st July 2020, resulting in 15,900 (15,200-16,400) or 20.1% (19.2%-20.7%) of all identified hospitalised COVID-19 cases.\n\nConclusionsTransmission of SARS-CoV-2 to hospitalised patients likely caused approximately a fifth of identified cases of hospitalised COVID-19 in the \"first wave\", but fewer than 1% of all SARS-CoV-2 infections in England. Using symptom onset as a detection method for hospital-acquired SARS-CoV-2 likely misses a substantial proportion (>60%) of hospital-acquired infections.\n\nFundingNational Institute for Health Research, UK Medical Research Council, Society for Laboratory Automation and Screening, UKRI, Wellcome Trust, Singapore National Medical Research Council.\n\nResearch in contextO_ST_ABSEvidence before this studyC_ST_ABSWe searched PubMed with the terms \"((national OR country) AND (contribution OR burden OR estimates) AND (\"hospital-acquired\" OR \"hospital-associated\" OR \"nosocomial\")) AND Covid-19\" for articles published in English up to July 1st 2021. This identified 42 studies, with no studies that had aimed to produce comprehensive national estimates of the contribution of hospital settings to the COVID-19 pandemic. Most studies focused on estimating seroprevalence or levels of infection in healthcare workers only, which were not our focus. Removing the initial national/country terms identified 120 studies, with no country level estimates. Several single hospital setting estimates exist for England and other countries, but the percentage of hospital-associated infections reported relies on identified cases in the absence of universal testing.\n\nAdded value of this studyThis study provides the first national-level estimates of all symptomatic hospital-acquired infections with SARS-CoV-2 in England up to the 31st July 2020. Using comprehensive data, we calculate how many infections would be unidentified and hence can generate a total burden, impossible from just notification data. Moreover, our burden estimates for onward transmission suggest the contribution of hospitals to the overall infection burden.\n\nImplications of all the available evidenceLarge numbers of patients may become infected with SARS-CoV-2 in hospitals though only a small proportion of such infections are identified. Further work is needed to better understand how interventions can reduce such transmission and to better understand the contributions of hospital transmission to mortality.", + "rel_num_authors": 17, "rel_authors": [ { - "author_name": "Lauren E Walker", - "author_inst": "University of Liverpool, 2 Liverpool University Hospitals NHS Foundation Trust" - }, - { - "author_name": "Richard FitzGerald", - "author_inst": "Liverpool University Hospitals NHS Foundation Trust" - }, - { - "author_name": "Geoffrey Saunders", - "author_inst": "Southampton Clinical Trials Unit, University of Southampton, Southampton UK" - }, - { - "author_name": "Rebecca Lyon", - "author_inst": "Liverpool University Hospitals NHS Foundation Trust" - }, - { - "author_name": "Michael Fisher", - "author_inst": "University of Liverpool, 2 Liverpool University Hospitals NHS Foundation Trust" - }, - { - "author_name": "Karen Martin", - "author_inst": "Southampton Clinical Trials Unit, University of Southampton, Southampton UK" - }, - { - "author_name": "Izabela Eberhart", - "author_inst": "Southampton Clinical Trials Unit, University of Southampton, Southampton UK" - }, - { - "author_name": "Christie Woods", - "author_inst": "Liverpool University Hospitals NHS Foundation Trust" - }, - { - "author_name": "Sean Ewings", - "author_inst": "Southampton Clinical Trials Unit, University of Southampton, Southampton UK" - }, - { - "author_name": "Colin Hale", - "author_inst": "Liverpool University Hospitals NHS Foundation Trust" - }, - { - "author_name": "Rajith KR Rajoli", - "author_inst": "University of Liverpool" - }, - { - "author_name": "Laura Else", - "author_inst": "University of Liverpool" + "author_name": "Gwenan M Knight", + "author_inst": "London School of Hygiene and Tropical Medicine" }, { - "author_name": "Sujan Dilly-Penchala", - "author_inst": "University of Liverpool" + "author_name": "Thi Mui Pham", + "author_inst": "University of Oxford" }, { - "author_name": "Alieu Amara", - "author_inst": "University of Liverpool" + "author_name": "James Stimson", + "author_inst": "Public Health England" }, { - "author_name": "David G Lalloo", - "author_inst": "Liverpool School of Tropical Medicine" + "author_name": "Sebastian Funk", + "author_inst": "London School of Hygiene & Tropical Medicine" }, { - "author_name": "Michael Jacobs", - "author_inst": "Liverpool School of Tropical Medicine" + "author_name": "Yalda Jafari", + "author_inst": "London School of Hygiene and Tropical Medicine" }, { - "author_name": "Henry Pertinez", - "author_inst": "University of Liverpool" + "author_name": "Diane Pople", + "author_inst": "Public Health England" }, { - "author_name": "Parys Hatchard", - "author_inst": "Southampton Clinical Trials Unit, University of Southampton, Southampton UK" + "author_name": "Stephanie Evans", + "author_inst": "Public Health England" }, { - "author_name": "Robert Waugh", - "author_inst": "Southampton Clinical Trials Unit, University of Southampton, Southampton UK" + "author_name": "Mo Yin", + "author_inst": "University of Oxford" }, { - "author_name": "Megan Lawrence", - "author_inst": "Southampton Clinical Trials Unit, University of Southampton, Southampton UK" + "author_name": "Colin Brown", + "author_inst": "Public Health England" }, { - "author_name": "Lucy Johnson", - "author_inst": "Southampton Clinical Trials Unit, University of Southampton, Southampton UK" + "author_name": "Alex Bhattacharya", + "author_inst": "Public Health England" }, { - "author_name": "Keira Fines", - "author_inst": "Southampton Clinical Trials Unit, University of Southampton, Southampton UK" + "author_name": "Russell Hope", + "author_inst": "Public Health England" }, { - "author_name": "Helen Reynolds", + "author_name": "Malcolm Gracie Semple", "author_inst": "University of Liverpool" }, { - "author_name": "Timothy Rowland", - "author_inst": "Liverpool University Hospitals NHS Foundation Trust" - }, - { - "author_name": "Rebecca Crook", - "author_inst": "Liverpool University Hospitals NHS Foundation Trust" - }, - { - "author_name": "Kelly Byrne", - "author_inst": "Liverpool School of Tropical Medicine" - }, - { - "author_name": "Pavel Mozgunov", - "author_inst": "MRC Biostatistics Unit, University of Cambridge" - }, - { - "author_name": "Thomas Jaki", - "author_inst": "MRC Biostatistics Unit, University of Cambridge" + "author_name": "- ISARIC4C Investigators", + "author_inst": "" }, { - "author_name": "Saye Khoo", - "author_inst": "University of Liverpool" + "author_name": "- CMMID COVID-19 working group", + "author_inst": "" }, { - "author_name": "Andrew Owen", - "author_inst": "University of Liverpool" + "author_name": "Jonathan M Read", + "author_inst": "Lancaster University" }, { - "author_name": "Gareth Griffiths", - "author_inst": "Southampton Clinical Trials Unit, University of Southampton, Southampton UK" + "author_name": "Ben S Cooper", + "author_inst": "University of Oxford" }, { - "author_name": "Thomas E Fletcher", - "author_inst": "Liverpool University Hospitals NHS Foundation Trust. Liverpool School of Tropical Medicine" + "author_name": "Julie V Robotham", + "author_inst": "Public Health England" } ], "version": "1", - "license": "cc_no", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "pharmacology and therapeutics" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2021.09.03.21262888", @@ -586035,43 +585538,99 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.09.04.21263123", - "rel_title": "Assessment of COVID-19 intervention strategies in the Nordic countries using genomic epidemiology", + "rel_doi": "10.1101/2021.09.08.459398", + "rel_title": "No substantial pre-existing B cell immunity against SARS-CoV-2 in healthy adults", "rel_date": "2021-09-08", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.04.21263123", - "rel_abs": "The Nordic countries, defined here as Norway, Sweden, Denmark, Finland and Iceland, are known for their comparable demographics and political systems. Since these countries implemented different COVID-19 intervention strategies, they provide a natural laboratory for examining how COVID-19 policies and mitigation strategies affected the propagation, evolution and spread of the SARS-CoV-2 virus. We explored how the duration, the size and number of transmission clusters, defined as country-specific monophyletic groups in a SARS-CoV-2 phylogenetic tree, differed between the Nordic countries. We found that Sweden had the largest number of COVID-19 transmission clusters followed by Denmark, Norway, Finland and Iceland. Moreover, Sweden and Denmark had the largest, and most enduring, transmission clusters followed by Norway, Finland and Iceland. In addition, there was a significant positive association between transmission cluster size and duration, suggesting that the size of transmission clusters could be reduced by rapid and effective contact tracing. Thus, these data indicate that to reduce the general burden of COVID-19 there should be a focus on limiting dense gatherings and their subsequent contacts to keep the number, size and duration of transmission clusters to a minimum. Our results further suggest that although geographical connectivity, population density and openness influence the spread and the size of SARS-CoV-2 transmission clusters, country-specific intervention strategies had the largest single impact.", - "rel_num_authors": 6, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2021.09.08.459398", + "rel_abs": "Pre-existing immunity against SARS-CoV-2 may have critical implications for our understanding of COVID-19 susceptibility and severity. Various studies recently provided evidence of pre-existing T cell immunity against SARS-CoV-2 in unexposed individuals. In contrast, the presence and clinical relevance of a pre-existing B cell immunity remains to be fully elucidated. Here, we provide a detailed analysis of the B cell response to SARS-CoV-2 in unexposed individuals. To this end, we extensively investigated the memory B cell response to SARS-CoV-2 in 150 adults sampled pre-pandemically. Comprehensive screening of donor plasma and purified IgG samples for binding and neutralization in various functional assays revealed no substantial activity against SARS-CoV-2 but broad reactivity to endemic betacoronaviruses. Moreover, we analyzed antibody sequences of 8,174 putatively SARS-CoV-2-reactive B cells on a single cell level and generated and tested 158 monoclonal antibodies. None of the isolated antibodies displayed relevant binding or neutralizing activity against SARS-CoV-2. Taken together, our results show no evidence of relevant pre-existing antibody and B cell immunity against SARS-CoV-2 in unexposed adults.", + "rel_num_authors": 20, "rel_authors": [ { - "author_name": "Sebastian Duchene", - "author_inst": "University of Melbourne" + "author_name": "Meryem Seda Ercanoglu", + "author_inst": "Laboratory of Experimental Immunology, Institute of Virology, Faculty of Medicine and University Hospital Cologne, University of Cologne, 50931 Cologne, Germany" }, { - "author_name": "Leo Featherstone", - "author_inst": "University of Melbourne" + "author_name": "Lutz Gieselmann", + "author_inst": "Laboratory of Experimental Immunology, Institute of Virology, Faculty of Medicine and University Hos" }, { - "author_name": "Birgitte Freiesleben de Blasio", - "author_inst": "Norwegian Institute of Public Health" + "author_name": "Sabrina Daehling", + "author_inst": "Laboratory of Experimental Immunology, Institute of Virology, Faculty of Medicine and University Hospital Cologne, University of Cologne, 50931 Cologne, Germany" }, { - "author_name": "Edward C Holmes", - "author_inst": "University of Sydney" + "author_name": "Nareshkumar Poopalasingam", + "author_inst": "Laboratory of Experimental Immunology, Institute of Virology, Faculty of Medicine and University Hospital Cologne, University of Cologne, 50931 Cologne, Germany" }, { - "author_name": "Jon Bohlin", - "author_inst": "Norwegian Institute of Public Health" + "author_name": "Susanne Detmer", + "author_inst": "Laboratory of Experimental Immunology, Institute of Virology, Faculty of Medicine and University Hospital Cologne, University of Cologne, 50931 Cologne, Germany" }, { - "author_name": "John H.-O. Pettersson", - "author_inst": "Uppsala university" + "author_name": "Manuel Koch", + "author_inst": "Institute for Dental Research and Oral Musculoskeletal Biology and Center for Biochemistry, University of Cologne, 50931 Cologne, Germany" + }, + { + "author_name": "Michael Korenkov", + "author_inst": "Laboratory of Experimental Immunology, Institute of Virology, Faculty of Medicine and University Hospital Cologne, University of Cologne, 50931 Cologne, Germany" + }, + { + "author_name": "Sandro Halwe", + "author_inst": "Institute of Virology, Philipps University Marburg, Hans-Meerwein-Strasse 2, 35042 Marburg, Germany" + }, + { + "author_name": "Michael Kluever", + "author_inst": "Institute of Virology, Philipps University Marburg, Hans-Meerwein-Strasse 2, 35042 Marburg, Germany" + }, + { + "author_name": "Veronica Di Cristanziano", + "author_inst": "Laboratory of Experimental Immunology, Institute of Virology, Faculty of Medicine and University Hospital Cologne, University of Cologne, 50931 Cologne, Germany" + }, + { + "author_name": "Ursula Hanna Janicki", + "author_inst": "Laboratory of Experimental Immunology, Institute of Virology, Faculty of Medicine and University Hospital Cologne, University of Cologne, 50931 Cologne, Germany" + }, + { + "author_name": "Maike Schlotz", + "author_inst": "Laboratory of Experimental Immunology, Institute of Virology, Faculty of Medicine and University Hospital Cologne, University of Cologne, 50931 Cologne, Germany" + }, + { + "author_name": "Johanna Worczinski", + "author_inst": "Laboratory of Experimental Immunology, Institute of Virology, Faculty of Medicine and University Hospital Cologne, University of Cologne, 50931 Cologne, Germany" + }, + { + "author_name": "Birgit Gathof", + "author_inst": "Institute of Transfusion Medicine, Faculty of Medicine and University Hospital Cologne, 50937 Cologne, Germany" + }, + { + "author_name": "Henning Gruell", + "author_inst": "Laboratory of Experimental Immunology, Institute of Virology, Faculty of Medicine and University Hospital Cologne, University of Cologne, 50931 Cologne, Germany" + }, + { + "author_name": "Matthias Zehner", + "author_inst": "Laboratory of Experimental Immunology, Institute of Virology, Faculty of Medicine and University Hospital Cologne, University of Cologne, 50931 Cologne, Germany" + }, + { + "author_name": "Stephan Becker", + "author_inst": "Institute of Virology, Philipps University Marburg, Hans-Meerwein-Strasse 2, 35042 Marburg, Germany" + }, + { + "author_name": "Kanika Vanshylla", + "author_inst": "Laboratory of Experimental Immunology, Institute of Virology, Faculty of Medicine and University Hospital Cologne, University of Cologne, 50931 Cologne, Germany" + }, + { + "author_name": "Christoph Kreer", + "author_inst": "Laboratory of Experimental Immunology, Institute of Virology, Faculty of Medicine and University Hospital Cologne, University of Cologne, 50931 Cologne, Germany" + }, + { + "author_name": "Florian Klein", + "author_inst": "Laboratory of Experimental Immunology, Institute of Virology, Faculty of Medicine and University Hospital Cologne, University of Cologne, 50931 Cologne, Germany" } ], "version": "1", - "license": "cc_by_nd", - "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "license": "cc_no", + "type": "new results", + "category": "immunology" }, { "rel_doi": "10.1101/2021.09.08.459408", @@ -587981,85 +587540,49 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2021.09.06.459055", - "rel_title": "Increased neutralization of SARS-CoV-2 Delta variant by nanobody (Nb22) and the structural basis", + "rel_doi": "10.1101/2021.09.06.459005", + "rel_title": "Ineffective neutralization of the SARS-CoV-2 Mu variant by convalescent and vaccine sera", "rel_date": "2021-09-07", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.09.06.459055", - "rel_abs": "Current COVID-19 vaccines need to take at least one month to complete inoculation and then become effective. Around 51% global population are still not fully vaccinated. Instantaneous protection is an unmet need among those who are not fully vaccinated. In addition, breakthrough infections caused by SARS-CoV-2 are widely reported. All these highlight the unmet needing for short-term instantaneous prophylaxis (STIP) in the communities where SARS-CoV-2 is circulating. Previously, we reported nanobodies isolated from an alpaca immunized with the spike protein, exhibiting ultrahigh potency against SARS-CoV-2 and its variants. Herein, we found that Nb22, among our previously reported nanobodies, exhibited ultrapotent neutralization against Delta variant with an IC50 value of 0.41 ng/ml (5.13 pM). Furthermore, the crystal structural analysis revealed that the binding of Nb22 to WH01 and Delta RBDs both effectively blocked the binding of RBD to hACE2. Additionally, intranasal Nb22 exhibited protection against SARS-CoV-2 Delta variant in the post-exposure prophylaxis (PEP) and pre-exposure prophylaxis (PrEP). Of note, intranasal Nb22 also demonstrated high efficacy against SARS-CoV-2 Delta variant in STIP for seven days administered by single dose and exhibited long-lasting retention in the respiratory system for at least one month administered by four doses, providing a means of instantaneous short-term prophylaxis against SARS-CoV-2. Thus, ultrahigh potency, long-lasting retention in the respiratory system as well as stability at room-temperature make the intranasal or inhaled Nb22 to be a potential therapeutic or STIP agent against SARS-CoV-2.\n\nBrief summaryNb22 exhibits ultrahigh potency against Delta variant in vitro and is exploited by crystal structural analysis; furthermore, animal study demonstrates high effectiveness in the treatment and short-term instantaneous prophylaxis in hACE2 mice via intranasal administration.\n\nHighlightsO_LINb22 exhibits ultrapotent neutralization against Delta variant with an IC50 value of 0.41 ng/ml (5.13 pM).\nC_LIO_LIStructural analysis elucidates the ultrapotent neutralization of Nb22 against Delta variant.\nC_LIO_LINb22 demonstrates complete protection in the treatment of Delta variant infection in hACE2 transgenic mice.\nC_LIO_LIWe complete the proof of concept of STIP against SARS-CoV-2 using intranasal Nb22 with ultrahigh potency and long-lasting retention in respiratory system.\nC_LI\n\nGraphic Abstract\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=199 SRC=\"FIGDIR/small/459055v2_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (44K):\norg.highwire.dtl.DTLVardef@144516corg.highwire.dtl.DTLVardef@3dc17forg.highwire.dtl.DTLVardef@6a8962org.highwire.dtl.DTLVardef@619cd7_HPS_FORMAT_FIGEXP M_FIG C_FIG", - "rel_num_authors": 18, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.09.06.459005", + "rel_abs": "On August 30, 2021, the WHO classified the SARS-CoV-2 Mu variant (B.1.621 lineage) as a new variant of interest. The WHO defines \"comparative assessment of virus characteristics and public health risks\" as primary action in response to the emergence of new SARS-CoV-2 variants. Here, we demonstrate that the Mu variant is highly resistant to sera from COVID-19 convalescents and BNT162b2-vaccinated individuals. Direct comparison of different SARS-CoV-2 spike proteins revealed that Mu spike is more resistant to serum-mediated neutralization than all other currently recognized variants of interest (VOI) and concern (VOC). This includes the Beta variant (B.1.351) that has been suggested to represent the most resistant variant to convalescent and vaccinated sera to date (e.g., Collier et al, Nature, 2021; Wang et al, Nature, 2021). Since breakthrough infection by newly emerging variants is a major concern during the current COVID-19 pandemic (Bergwerk et al., NEJM, 2021), we believe that our findings are of significant public health interest. Our results will help to better assess the risk posed by the Mu variant for vaccinated, previously infected and naive populations.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Xilin Wu", - "author_inst": "Medical School, Nanjing University" - }, - { - "author_name": "Yaxing Wang", - "author_inst": "Tianjin Key Laboratory of Function and Application of Biological Macromolecular Structures, School of Life Sciences, Tianjin University" - }, - { - "author_name": "Lin Cheng", - "author_inst": "Shenzhen Third People Hospital" - }, - { - "author_name": "Fengfeng Ni", - "author_inst": "Wuhan Institute of Virology, Wuhan" - }, - { - "author_name": "Linjing Zhu", - "author_inst": "Abrev Biotechnology Co., Ltd." - }, - { - "author_name": "Sen Ma", - "author_inst": "Tianjin Key Laboratory of Function and Application of Biological Macromolecular Structures, School of Life Sciences, Tianjin University" - }, - { - "author_name": "Bilian Huang", - "author_inst": "Center for Public Health Research, Medical School, Nanjing University, Nanjing, P.R. China." - }, - { - "author_name": "Mengmeng Ji", - "author_inst": "School of Life Sciences, Ningxia University, Yinchuan, P.R. China." - }, - { - "author_name": "Huimin Hu", - "author_inst": "State Key Laboratory of Virology, Wuhan Institute of Virology, Center for Biosafety Mega-Science, Chinese Academy of Sciences, Wuhan, P.R.China" - }, - { - "author_name": "Yuncheng Li", - "author_inst": "State Key Laboratory of Virology, Wuhan Institute of Virology, Center for Biosafety Mega-Science, Chinese Academy of Sciences, Wuhan,China" + "author_name": "Keiya Uriu", + "author_inst": "University of Tokyo" }, { - "author_name": "Shijie Xu", - "author_inst": "Department of Antibody, Y-clone Medical Science Co. Ltd. Suzhou, P.R. China." + "author_name": "Izumi Kimura", + "author_inst": "University of Tokyo" }, { - "author_name": "Haixia Shi", - "author_inst": "Department of Antibody, Y-clone Medical Science Co. Ltd. Suzhou, P.R. China" + "author_name": "Kotaro Shirakawa", + "author_inst": "Kyoto University, Graduate School of Medicine" }, { - "author_name": "Linshuo Liu", - "author_inst": "Department of Antibody, Y-clone Medical Science Co. Ltd. Suzhou, P.R. China." + "author_name": "Akifumi Takaori-Kondo", + "author_inst": "Graduate School of Medicine, Kyoto University" }, { - "author_name": "Waqas Nawaz", - "author_inst": "Center for Public Health Research, Medical School, Nanjing University" + "author_name": "Taka-aki Nakada", + "author_inst": "Chiba University" }, { - "author_name": "Qinxue Hu", - "author_inst": "State Key Laboratory of Virology, Wuhan Institute of Virology, Center for Biosafety Mega-Science, Chinese Academy of Sciences, Wuhan, China" + "author_name": "Atsushi Kaneda", + "author_inst": "Chiba University" }, { - "author_name": "Sheng Ye", - "author_inst": "Tianjin Key Laboratory of Function and Application of Biological Macromolecular Structures, School of Life Sciences, Tianjin University" + "author_name": "- The Genotype to Phenotype Japan (G2P-Japan) Consortium", + "author_inst": "-" }, { - "author_name": "Yalan Liu", - "author_inst": "tate Key Laboratory of Virology, Wuhan Institute of Virology, Center for Biosafety Mega-Science, Chinese Academy of Sciences, Wuhan, China" + "author_name": "So Nakagawa", + "author_inst": "Tokai University School of Medicine" }, { - "author_name": "Zhiwei Wu", - "author_inst": "School of Life Sciences, Ningxia University, Yinchuan, P.R. China." + "author_name": "Kei Sato", + "author_inst": "University of Tokyo" } ], "version": "1", @@ -589391,69 +588914,69 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.08.26.21262426", - "rel_title": "The comparability of Anti-Spike SARS-CoV-2 antibody tests is time-dependent: a prospective observational study", + "rel_doi": "10.1101/2021.09.02.21263014", + "rel_title": "No difference in risk of hospitalisation between reported cases of the SARS-CoV-2 Delta variant and Alpha variant in Norway", "rel_date": "2021-09-05", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.26.21262426", - "rel_abs": "ObjectivesVarious commercial anti-Spike SARS-CoV-2 antibody tests are used for studies and in clinical settings after vaccination. An international standard for SARS-CoV-2 antibodies has been established to achieve comparability of such tests, allowing conversions to BAU/ml. This study aimed to investigate the comparability of antibody tests regarding the timing of blood collection after vaccination.\n\nMethodsFor this prospective observational study, antibody levels of 50 participants with homologous AZD1222 vaccination were evaluated at 3 and 11 weeks after the first dose and 3 weeks after the second dose using two commercial anti-Spike binding antibody assays (Roche and Abbott) and a surrogate neutralization assay.\n\nResultsThe correlation between Roche and Abbott changed significantly depending on the time point studied. Although 3 weeks after the first dose, Abbott provided values three times higher than Roche, 11 weeks after the first dose, the values for Roche were twice as high as for Abbott, and 3 weeks after the second dose even 5-6 times higher.\n\nConclusionsThe comparability of quantitative anti-Spike SARS-CoV-2 antibody tests is highly dependent on the timing of blood collection after vaccination. Therefore, standardization of the timing of blood collection might be necessary for the comparability of different quantitative SARS-COV-2 antibody assays.\n\n\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=175 SRC=\"FIGDIR/small/21262426v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (27K):\norg.highwire.dtl.DTLVardef@1e789daorg.highwire.dtl.DTLVardef@b83aforg.highwire.dtl.DTLVardef@1f270daorg.highwire.dtl.DTLVardef@1cf296c_HPS_FORMAT_FIGEXP M_FIG C_FIG", + "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.02.21263014", + "rel_abs": "ObjectivesTo estimate the risk of hospitalisation among reported cases of the Delta-variant of SARS-CoV-2 compared to the Alpha variant in Norway. We also estimated the risk of hospitalisation by vaccination status.\n\nMethodsWe conducted a cohort study on laboratory-confirmed cases of SARS-CoV-2 in Norway, diagnosed between 3 May and 15 August 2021. We calculated adjusted risk ratios (aRR) with 95% confidence intervals (CIs) using multivariable binomial regression, accounting for variant, vaccination status, demographic characteristics, week of sampling and underlying comorbidities.\n\nResultsWe included 7,977 cases of Delta and 12,078 cases of Alpha. Overall, 347 (1.7%) cases were hospitalised. The aRR of hospitalisation for Delta compared to Alpha was 0.97 (95%CI 0.76-1.23). Partially vaccinated cases had a 72% reduced risk of hospitalisation (95%CI 59%-82%), and fully vaccinated cases had a 76% reduced risk (95%CI 61%-85%), compared to unvaccinated cases.\n\nConclusionsWe found no difference in the risk of hospitalisation for Delta cases compared to Alpha cases in Norway. Further research from a wide variety of settings is needed to better understand the association between the Delta variant and severe disease. Our results support the notion that partially and fully vaccinated persons are highly protected against hospitalisation with COVID-19.\n\nHighlightsO_LIThe SARS-CoV-2 Delta variant has dominated in Norway since July 2021\nC_LIO_LIThere was no difference in the risk of hospitalisation for Delta cases compared to Alpha\nC_LIO_LIPartially and fully vaccinated cases had >70% decreased risk of hospitalisation\nC_LI", "rel_num_authors": 13, "rel_authors": [ { - "author_name": "Thomas Perkmann", - "author_inst": "Medical University of Vienna" + "author_name": "Lamprini Veneti", + "author_inst": "Norwegian insitute of public health" }, { - "author_name": "Patrick Mucher", - "author_inst": "Medical University of Vienna" + "author_name": "Beatriz Valcarcel Salamanca", + "author_inst": "Norwegian institute of public health" }, { - "author_name": "Nicole Perkmann-Nagele", - "author_inst": "Medical University of Vienna" + "author_name": "Elina Seppala", + "author_inst": "Norwegian institute of public health" }, { - "author_name": "Astrid Radakovics", - "author_inst": "Medical University of Vienna" + "author_name": "Jostein Starrfelt", + "author_inst": "Norwegian institute of public health" }, { - "author_name": "Manuela Repl", - "author_inst": "Medical University of Vienna" + "author_name": "Margrethe Larsdatter Storm", + "author_inst": "Norwegian institute of public health" }, { - "author_name": "Thomas Koller", - "author_inst": "Medical University of Vienna" + "author_name": "Karoline Bragstad", + "author_inst": "Norwegian institute of public health" }, { - "author_name": "Klaus G Schmetterer", - "author_inst": "Medical University of Vienna" + "author_name": "Olav Hungnes", + "author_inst": "Norwegian institute of public health" }, { - "author_name": "Johannes W Bigenzahn", - "author_inst": "Medical University of Vienna" + "author_name": "Hakon Boas", + "author_inst": "Norwegian institute of public health" }, { - "author_name": "Florentina Leitner", - "author_inst": "Medical University of Vienna" + "author_name": "Reidar Kvale", + "author_inst": "Haukeland University Hospital, Bergen, Norway" }, { - "author_name": "Galateja Jordakieva", - "author_inst": "Medical University of Vienna" + "author_name": "Line Vold", + "author_inst": "Norwegian institute of public health" }, { - "author_name": "Oswald F Wagner", - "author_inst": "Medical University of Vienna" + "author_name": "Karin Nygard", + "author_inst": "Norwegian institute of public health" }, { - "author_name": "Christoph J Binder", - "author_inst": "Medical University of Vienna" + "author_name": "Eirik Alnes Buanes", + "author_inst": "Haukeland University Hospital, Bergen, Norway" }, { - "author_name": "Helmuth Haslacher", - "author_inst": "Medical University of Vienna" + "author_name": "Robert Whittaker", + "author_inst": "Norwegian institute of public health" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -591165,25 +590688,57 @@ "category": "allergy and immunology" }, { - "rel_doi": "10.1101/2021.08.31.21262897", - "rel_title": "How control and relaxation interventions and virus mutations influence the resurgence of COVID-19", + "rel_doi": "10.1101/2021.08.31.21262917", + "rel_title": "Psychological antecedents towards COVID-19 vaccination using the Arabic 5C validated tool: An online study in 13 Arab countries", "rel_date": "2021-09-02", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.31.21262897", - "rel_abs": "After a year of the unprecedented COVID-19 pandemic in 2020, the world has been overwhelmed by COVID-19 resurgences and virus mutations up to today. Here we develop a dynamic intervention, vaccination and mutation-driven epidemiological model with sequential interventions influencing epidemiological compartments and their state transition. We quantify epidemiological differences between waves under fatal viral mutations, the impacts of control or relaxation interventions and fatal virus mutations on resurgence under vaccinated or unvaccinated conditions, and estimate potential trends under varying interventions and mutations. Comprehensive analyses - between waves, with or without vaccinations, across representative countries with distinct ethnic and cultural backgrounds, what-if scenario simulations on second waves, and future 30-day trend - in two COVID-19 waves in Germany, France, Italy, Israel and Japan over 2020 and 2021 obtain quantitative empirical indication of the influence of strong vs. weak interventions, various combinations of control vs. relaxation strategies, and different transmissibility levels of coronavirus mutants on the behaviors and patterns of different waves and resurgences and future infection trends. The analyses quantify that (1) virus mutations, intervention fatigue, early relaxations, and lagging interventions, etc. may be common reasons for the resurgences observed in many countries; (2) timely strong interventions such as full lockdown will contain resurgence; (3) some resurgences relating to fatal mutants could have been better contained by either carrying forward the effective interventions from their early waves or implementing better controls and timing; (4) insufficient evidence is found on distinguishing the infection between unvaccinated and vaccinated countries while substantial vaccinations ensure much low mortality rate and high recovery rate; (5) resurgences with substantial vaccination have a much lower mortality rate and a higher recovery rate than those without vaccination; and (6) in the absence of sufficient vaccination, herd immunity and effective antiviral pharmaceutical treatments and with more infectious mutations, the widespread early or fast relaxation of interventions including public activity restrictions likely result in a COVID-19 resurgence. We also find the severity, number and timing of control and relaxation interventions determines a protection-deconfinement tradeoff, which can be used to evaluate the containment effect and the opportunity of resurgence and reopening under vaccination and fatal mutations.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.31.21262917", + "rel_abs": "Background and aimFollowing emergency approval of vaccines, the amount of scientific literature investigating population hesitancy towards vaccination against the novel coronavirus disease (COVID-19) has increased exponentially. Nevertheless, the associated psychological behaviors with this phenomenon are still not clearly understood. This study aims to assess the psychological antecedents of the Arab population toward COVID-19 vaccines.\n\nMethodsA cross-sectional, online study using a validated Arabic version of the 5C questionnaire was conducted through different media platforms in different Arabic-speaking countries. The questionnaire included three sections: socio-demographics, COVID-19 related questions, and the 5C scale of vaccine psychological antecedents, namely confidence, complacency, constraints, calculation, and collective responsibility.\n\nResultsA total of 4,474 participants, 40.8% males from 13 Arab countries were included in the study. About 26.7% of participants had confidence in COVID-19 vaccination, 10.7% had complacency, 96.5% had no constraints, 48.8% had calculation and 40.4% had collective responsibility. The 5C antecedents showed variation among countries with confidence and collective responsibility being higher in the United Arab Emirates (UAE) (59% and 58%, respectively), complacency and constraints were higher in Morocco (21% and 7%, respectively) and calculation was higher in Sudan (60%). Regression analysis revealed that sex, age, educational degrees, being a health care professional, getting a COVID-19 infection, having a relative infected or died from COVID-19 can affect the 5C psychological antecedents by different degrees.\n\nConclusion and recommendationsWide variations of psychological antecedents between Arab countries exist. Different determinants can affect vaccine psychological antecedents.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Longbing Cao", - "author_inst": "University of Technology Sydney" + "author_name": "Marwa Shawky Abdou", + "author_inst": "Alexandria University, High Institute of Public Health" }, { - "author_name": "Qing Liu", - "author_inst": "University of Technology Sydney" + "author_name": "Khalid A Kheirallah", + "author_inst": "Medical School of Jordan University of Science and Technology" + }, + { + "author_name": "Maged Ossama Aly", + "author_inst": "Alexandria University, High Institute of Public Health" + }, + { + "author_name": "Ahmed Mohamed Ramadan", + "author_inst": "National Research Centre" + }, + { + "author_name": "Yasir Ahmed Mohammed Elhadi", + "author_inst": "High Institute of Public Health" + }, + { + "author_name": "Iffat Elbarazi", + "author_inst": "College of Medicine and Health Sciences, United Arab Emirates University" + }, + { + "author_name": "Ehsan Deghidy", + "author_inst": "Medical Research Institute, Alexandria University" + }, + { + "author_name": "Haider M El Saeh", + "author_inst": "Faculty of Medicine, University of Tripoli" + }, + { + "author_name": "Karem Mohamed Salem", + "author_inst": "Faculty of Medicine, Fayoum University" + }, + { + "author_name": "Ramy Mohamed Ghazy", + "author_inst": "High Institute of Public Health" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -593359,41 +592914,25 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.08.30.458225", - "rel_title": "Epistasis at the SARS-CoV-2 RBD Interface and the Propitiously Boring Implications for Vaccine Escape", + "rel_doi": "10.1101/2021.08.27.457969", + "rel_title": "May a Strain Chlamydia Isolated From SARS Patient's Autopsy Issues Inhibit the Proliferation of SARS-CoV? An Early Observation in Vitro.", "rel_date": "2021-08-31", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.08.30.458225", - "rel_abs": "At the time of this writing, December 2021, potential emergence of vaccine escape variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a grave global concern. The interface between the receptor-binding domain (RBD) of SARS-CoV-2 spike (S) protein and the host receptor (ACE2) overlap with the binding site of principal neutralizing antibodies (NAb), limiting the repertoire of viable mutations. Nonetheless, variants with multiple mutations in the RBD have rose to dominance. Non-additive, epistatic relationships among RBD mutations are apparent, and assessing the impact of such epistasis on the mutational landscape is crucial. Epistasis can substantially increase the risk of vaccine escape and cannot be completely characterized through the study of the wild type (WT) alone. We employed protein structure modeling using Rosetta to compare the effects of all single mutants at the RBD-NAb and RBD-ACE2 interfaces for the WT, Delta, Gamma, and Omicron variants. Overall, epistasis at the RBD interface appears to be limited and the effects of most multiple mutations are additive. Epistasis at the Delta variant interface weakly stabilizes NAb interaction relative to ACE2 interaction, whereas in the Gamma variant, epistasis more substantially destabilizes NAb interaction. Although a small, systematic trend towards NAb destabilization not observed for Delta or Gamma was detected for Omicron, and despite bearing significantly more RBD mutations, the epistatic landscape of the Omicron variant closely resembles that of Gamma. These results suggest that, although Omicron poses new risks not observed with Delta, structural constraints on the RBD hamper continued evolution towards more complete vaccine escape. The modest ensemble of mutations relative to the WT that are currently known to reduce vaccine efficacy is likely to comprise the majority of all possible escape mutations for future variants, predicting continued efficacy of the existing vaccines.\n\nSignificanceEmergence of vaccine escape variants of SARS-CoV-2 is arguably the most pressing problem during the COVID-19 pandemic as vaccines are distributed worldwide. We employed a computational approach to assess the risk of antibody escape resulting from mutations in the receptor-binding domain of the spike protein of the wild type SARS-CoV-2 virus as well as the Delta, Gamma, and Omicron variants. At the time of writing, December, 2021, Omicron is poised to replace Delta as the dominant variant worldwide. The efficacy of the existing vaccines against Omicron could be substantially reduced relative to the WT and the potential for vaccine escape is of grave concern. Our results suggest that although Omicron poses new evolutionary risks not observed for the Delta variant, structural constraints on the RBD make continued evolution towards more complete vaccine escape unlikely. The modest set of escape-enhancing mutations already identified for the wild type likely include the majority of all possible mutations with this effect.", - "rel_num_authors": 6, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.08.27.457969", + "rel_abs": "We found that a strain chlamydia isolated from SARS patients autopsy issues could decrease the proliferation of SARS-CoV in vitro; The inhibitory factors distribute both in the extracellular and intracellular cultures.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Nash Delta Rochman", - "author_inst": "NIH" - }, - { - "author_name": "Guilhem Faure", - "author_inst": "Broad Institute of MIT and Harvard" - }, - { - "author_name": "Yuri I. Wolf", - "author_inst": "NCBI/NLM/NIH" + "author_name": "Xing Quan", + "author_inst": "Zhongshan School of Medicine, Sun Yat-sen University, GuangZhou, 510275, China" }, { - "author_name": "Peter Freddolino", - "author_inst": "University of Michigan" - }, - { - "author_name": "Feng Zhang", - "author_inst": "Broad Institute of MIT and Harvard; McGovern Institute for Brain Research at MIT" - }, - { - "author_name": "Eugene V. Koonin", - "author_inst": "NIH" + "author_name": "Weifei Liu", + "author_inst": "Zhongshan School of Medicine, Sun Yat-sen University, GuangZhou, 510275, China" } ], "version": "1", - "license": "cc0", + "license": "cc_by", "type": "new results", "category": "microbiology" }, @@ -595317,123 +594856,51 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.08.27.21262754", - "rel_title": "Trajectory of viral load in a prospective population-based cohort with incident SARS-CoV-2 G614 infection", + "rel_doi": "10.1101/2021.08.28.21262778", + "rel_title": "COVID-19 OUTCOMES IN PREGNANCY: A REVIEW OF 275 SCREENED STUDIES", "rel_date": "2021-08-31", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.27.21262754", - "rel_abs": "ImportanceSARS-CoV-2 viral trajectory has not been well-characterized in documented incident infections. These data will inform SARS-CoV-2 natural history, transmission dynamics, prevention practices, and therapeutic development.\n\nObjectiveTo prospectively characterize early SARS-CoV-2 viral shedding in persons with incident infection.\n\nDesignProspective cohort study.\n\nSettingSecondary data analysis from a multicenter study in the U.S.\n\nParticipantsThe samples derived from a randomized controlled trial of 829 community-based asymptomatic participants recently exposed (<96 hours) to persons with SARS-CoV-2. Participants collected daily mid-turbinate swabs for SARS-CoV-2 detection by polymerase-chain-reaction and symptom diaries for 14-days. Persons with negative swab for SARS-CoV-2 at baseline who developed infection during the study were included in the analysis.\n\nExposureLaboratory-confirmed SARS-CoV-2 infection.\n\nMain outcomes and measuresThe observed SARS-CoV-2 viral shedding characteristics were summarized and shedding trajectories were examined using a piece-wise linear mixed-effects modeling. Whole viral genome sequencing was performed on samples with cycle threshold (Ct)<34.\n\nResultsNinety-seven persons (57% women, median age 37-years) developed incident infections during 14-days of follow-up. Two-hundred fifteen sequenced samples were assigned to 15 lineages that belonged to the G614 variant. Forty-two (43%), 18(19%), and 31(32%) participants had viral shedding for 1 day, 2-6 days, and [≥]7 days, with median peak viral load Ct of 38.5, 36.7, and 18.3, respectively. Six (6%) participants had 1-6 days of observed viral shedding with censored duration. The peak average viral load was observed on day 3 of viral shedding. The average Ct value was lower, indicating higher viral load, in persons reporting COVID-19 symptoms than asymptomatic. Using the statistical model, the median time from shedding onset to peak viral load was 1.4 days followed by a median of 9.7 days before clearance.\n\nConclusions and RelevanceIncident SARS-CoV-2 G614 infection resulted in a rapid viral load peak followed by slower decay and positive correlation between peak viral load and shedding duration; duration of shedding was heterogeneous. This longitudinal evaluation of the SARS-CoV-2 G614 variant with frequent molecular testing may serve as a reference for comparing emergent viral lineages to inform clinical trial designs and public health strategies to contain the spread of the virus.\n\nKEY POINTSO_ST_ABSQuestionC_ST_ABSWhat are the early SARS-CoV-2 G614 viral shedding characteristics in persons with incident infection?\n\nFindingsIn this prospective cohort of 97 community-based participants who collected daily mid-turbinate swabs for SARS-CoV-2 detection after recent exposure to SARS-CoV-2, viral trajectory was characterized by a rapid peak followed by slower decay. Peak viral load correlated positively with symptoms. The duration of shedding was heterogeneous.\n\nMeaningA detailed description of the SARS-CoV-2 G614 viral shedding trajectory serves as baseline for comparison to new viral variants of concern and inform models for the planning of clinical trials and transmission dynamics to end this pandemic.", - "rel_num_authors": 26, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.28.21262778", + "rel_abs": "In December 2019, a novel strain of severe acute respiratory syndrome (SARS-CoV-2), was declared as a cause of respiratory illness, called coronavirus 2019 (COVID-19), characterized by fever and cough. In diagnostic imaging, the afflicted population showed pathognomonic findings of pneumonia. What started out as an epidemic in China, rapidly spread across geographical locations with a significant daily increase in the number of affected cases. According to the World Health Organization (WHO) reports, the range of worldwide mortality is 3 to 4%. Maternal adaptations and immunological changes predispose pregnant women to a prolonged and severe form of pneumonia, which results in higher rates of maternal, fetal, and neonatal morbidity and mortality. There is limited data about the consequences of COVID-19 in pregnancy, thereby limiting the prevention, counseling, and management of these patients. The objective of this literature review is to explore pregnancy and perinatal outcomes of COVID-19, complications, morbidity, and mortality in this sub-population. We conducted a literature review pertaining to COVID-19 and pregnancy in databases such as: PubMed, Google Scholar, and Science Direct. The studies we chose to focus on were systematic reviews, meta-analysis, case series, and case reports. Twenty four articles were reviewed regarding COVID-19 and pregnancy, complications and their outcomes. Due to immunological changes during pregnancy as evidenced by the flaring of auto-immune diseases; pregnant women may be at an increased risk for infection. Women (19.7%) who had underlying comorbidities such as gestational DM, HTN, hypothyroidism, and autoimmune disease, COPD, or HBV infection were considered high risk. The most common maternal outcomes were premature rupture of membranes (PROM) and pre-eclampsia. Asthma was the most common comorbidity associated with maternal mortality. The most common neonatal complications were fetal distress leading to NICU admissions and preterm birth <37 weeks. The most common laboratory changes were elevated CRP and lymphocytopenia. Most patients underwent C-section due to their underlying comorbidities. Pregnant and lactating women did not shed viral particles through their vaginal mucus and milk, as evidenced by negative nucleic-acid tests of these secretions. Neonatal infections as demonstrated by positive RT-PCR were rare, but direct evidence supporting intrauterine transmission was not confirmed. Direct evidence indicating vertical transmission of COVID-19 is not available, but risk for transmission cannot be ruled out. Pregnant women should be closely monitored due to increased risk of adverse outcomes.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Helen C Stankiewicz Karita", - "author_inst": "University of Washington" - }, - { - "author_name": "Tracy Q Dong", - "author_inst": "Fred Hutchinson Cancer Research Center" - }, - { - "author_name": "Christine Johnston", - "author_inst": "University of Washington" - }, - { - "author_name": "Kathleen M Neuzil", - "author_inst": "University of Maryland" - }, - { - "author_name": "Michael K Paasche-Orlow", - "author_inst": "Boston University School of Medicine" - }, - { - "author_name": "Patricia J Kissinger", - "author_inst": "Tulane University" - }, - { - "author_name": "Anna Bershteyn", - "author_inst": "New York University Grossman School of Medicine" - }, - { - "author_name": "Lorna Thorpe", - "author_inst": "New York University Grossman School of Medicine" - }, - { - "author_name": "Meagan Deming", - "author_inst": "University of Maryland" - }, - { - "author_name": "Angelica Kottkamp", - "author_inst": "New York University Grossman School of Medicine" - }, - { - "author_name": "Miriam Laufer", - "author_inst": "University of Maryland" - }, - { - "author_name": "Raphael Landovitz", - "author_inst": "University of California Los Angeles" - }, - { - "author_name": "Alfred Luk", - "author_inst": "Tulane University" - }, - { - "author_name": "Risa Hoffman", - "author_inst": "University of California Los Angeles" - }, - { - "author_name": "Pavitra Roychoudhury", - "author_inst": "University of Washington" - }, - { - "author_name": "Craig Magaret", - "author_inst": "University of Washington" - }, - { - "author_name": "Alex Greninger", - "author_inst": "University of Washington" - }, - { - "author_name": "Meeili Huang", - "author_inst": "University of Washington" - }, - { - "author_name": "Keith Jerome", - "author_inst": "University of Washington" + "author_name": "Rupalakshmi Vijayan", + "author_inst": "Larkin Community hospital" }, { - "author_name": "Mark Wener", - "author_inst": "University of Washington" + "author_name": "Hanna Moon", + "author_inst": "Larkin Community Hospital" }, { - "author_name": "Connie L Celum", - "author_inst": "University of Washington" + "author_name": "Jasmine Joseph", + "author_inst": "Larkin community hospital" }, { - "author_name": "Helen Y Chu", - "author_inst": "University of Washington" + "author_name": "Madiha Zaidi", + "author_inst": "Larkin community hospital" }, { - "author_name": "Jared Baeten", - "author_inst": "University of Washington" + "author_name": "Chhaya Kamwal", + "author_inst": "Larkin Community hospital" }, { - "author_name": "Anna Wald", - "author_inst": "University of Washington" + "author_name": "Andrelle Senatus", + "author_inst": "Larkin community hospital" }, { - "author_name": "Ruanne V Barnabas", - "author_inst": "University of Washington" + "author_name": "Shavy Nagpal", + "author_inst": "The Research Institute of St. Joe's Hamilton" }, { - "author_name": "Elizabeth R Brown", - "author_inst": "Fred Hutchinson Cancer Research Center" + "author_name": "Miguel Diaz", + "author_inst": "Larkin community hospital" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "obstetrics and gynecology" }, { "rel_doi": "10.1101/2021.08.30.458287", @@ -597115,53 +596582,37 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.08.27.21262731", - "rel_title": "mRNA vaccines effectiveness against COVID-19 hospitalizations and deaths in older adults: a cohort study based on data-linkage of national health registries in Portugal", + "rel_doi": "10.1101/2021.08.27.21262744", + "rel_title": "Previous Infection Combined with Vaccination Produces Neutralizing Antibodies With Potency Against SARS-CoV-2 Variants", "rel_date": "2021-08-29", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.27.21262731", - "rel_abs": "BackgroundWe used electronic health registries to estimate the mRNA vaccine effectiveness (VE) against COVID-19 hospitalizations and deaths in older adults.\n\nMethodsWe established a cohort of individuals aged 65 and more years, resident in Portugal mainland through data linkage of eight national health registries. For each outcome, VE was computed as one minus the confounder-adjusted hazard ratio, estimated by time-dependent Cox regression.\n\nResultsVE against COVID-19 hospitalization [≥]14 days after the second dose was 94% (95%CI 88 to 97) for age-group 65-79 years old (yo) and 82% (95%CI 72 to 89) for [≥]80 yo. VE against COVID-19 related deaths [≥] 14 days after second dose was 96% (95%CI 92 to 98) for age-group 65-79 yo and 81% (95%CI 74 to 87), for [≥]80 yo individuals. No evidence of VE waning was observed after 98 days of second dose uptake.\n\nConclusionsmRNA vaccine effectiveness was high for the prevention of hospitalizations and deaths in age-group 65-79 yo and [≥]80 yo with a complete vaccination scheme, even after 98 days of second dose uptake.", - "rel_num_authors": 10, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.27.21262744", + "rel_abs": "SARS-CoV-2 continues to evolve in humans. Spike protein mutations increase transmission and potentially evade antibodies raised against the original sequence used in current vaccines. Our evaluation of serum neutralizing activity in both persons soon after SARS-CoV-2 infection (in April 2020 or earlier) or vaccination without prior infection confirmed that common spike mutations can reduce antibody antiviral activity. However, when the persons with prior infection were subsequently vaccinated, their antibodies attained an apparent biologic ceiling of neutralizing potency against all tested variants, equivalent to the original spike sequence. These findings indicate that additional antigenic exposure further improves antibody efficacy against variants.\n\nLAY SUMMARYAs SARS-CoV-2 evolves to become better suited for circulating in humans, mutations have occurred in the spike protein it uses for attaching to cells it infects. Protective antibodies from prior infection or vaccination target the spike protein to interfere with its function. These mutations can reduce the efficacy of antibodies generated against the original spike sequence, raising concerns for re-infections and vaccine failures, because current vaccines contain the original sequence. In this study we tested antibodies from people infected early in the pandemic (before spike variants started circulating) or people who were vaccinated without prior infection. We confirmed that some mutations reduce the ability of antibodies to neutralize the spike protein, whether the antibodies were from past infection or vaccination. Upon retesting the previously infected persons after vaccination, their antibodies gained the same ability to neutralize mutated spike as the original spike, suggesting that the combination of infection and vaccination drove the production of enhanced antibodies to reach a maximal level of potency. Whether this can be accomplished by vaccination alone remains to be determined, but the results suggest that booster vaccinations may help improve efficacy against spike variants.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Baltazar Nunes", - "author_inst": "Department of Epidemiology, Instituto Nacional de Saude Dr. Ricardo Jorge, Lisbon, Portugal" - }, - { - "author_name": "Ana Rodrigues", - "author_inst": "Department of Epidemiology, Instituto Nacional de Saude Dr. Ricardo Jorge, Lisbon, Portugal" - }, - { - "author_name": "Irina Kislaya", - "author_inst": "Department of Epidemiology, Instituto Nacional de Saude Dr. Ricardo Jorge, Lisbon, Portugal" - }, - { - "author_name": "Camila Cruz", - "author_inst": "Servicos Partilhados do Ministerio da Saude, Lisbon, Portugal" - }, - { - "author_name": "Andre Peralta-Santos", - "author_inst": "Direcao de Servicos de Informacao e Analise, Direcao-Geral da Saude, Lisbon, Portugal" + "author_name": "F Javier Ibarrondo", + "author_inst": "UCLA" }, { - "author_name": "Joao Lima", - "author_inst": "Servicos Partilhados do Ministerio da Saude, Lisbon, Portugal" + "author_name": "Christian Hofmann", + "author_inst": "UCLA" }, { - "author_name": "Pedro Pinto Leite", - "author_inst": "Direcao de Servicos de Informacao e Analise, Direcao-Geral da Saude, Lisbon, Portugal" + "author_name": "Ayub Ali", + "author_inst": "UCLA" }, { - "author_name": "Duarte Sequeira", - "author_inst": "Servicos Partilhados do Ministerio da Saude, Lisbon, Portugal" + "author_name": "Paul Ayoub", + "author_inst": "UCLA" }, { - "author_name": "Carlos Matias Dias", - "author_inst": "Department of Epidemiology, Instituto Nacional de Saude Dr. Ricardo Jorge, Lisbon, Portugal" + "author_name": "Donald B Kohn", + "author_inst": "UCLA" }, { - "author_name": "Ausenda Machado", - "author_inst": "Department of Epidemiology, Instituto Nacional de Saude Dr. Ricardo Jorge, Lisbon, Portugal" + "author_name": "Otto O Yang", + "author_inst": "University of California Los Angeles" } ], "version": "1", @@ -599253,37 +598704,113 @@ "category": "health informatics" }, { - "rel_doi": "10.1101/2021.08.24.21262524", - "rel_title": "COVID-19 in Scottish care homes: A metapopulation model of spread among residents and staff", + "rel_doi": "10.1101/2021.08.25.21262584", + "rel_title": "Waning of BNT162b2 vaccine protection against SARS-CoV-2 infection in Qatar", "rel_date": "2021-08-27", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.24.21262524", - "rel_abs": "Care homes in the UK were disproportionately affected by the first wave of the COVID-19 pandemic, accounting for almost half of COVID-19 deaths over the course of the period from 6th March - 15th June 2020. Understanding how infectious diseases establish themselves throughout vulnerable communities is crucial for minimising deaths and lowering the total stress on the National Health Service (NHS Scotland). We model the spread of COVID-19 in the health-board of NHS Lothian, Scotland over the course of the first wave of the pandemic with a compartmental Susceptible - Exposed - Infected reported - Infected unreported - Recovered - Dead (SEIARD), metapopulation model. Care home residents, care home workers and the rest of the population are modelled as subpopulations, interacting on a network describing their mixing habits. We explicitly model the outbreaks reproduction rate and care home visitation level over time for each subpopulation, and execute a data fit and sensitivity analysis, focusing on parameters responsible for intra-subpopulation mixing: staff sharing, staff shift patterns and visitation. The results suggest that hospital discharges were not predominantly responsible for the early outbreak in care homes, and that only a few such cases led to infection seeding in care homes by the 6th of March Sensitivity analysis show the main mode of entry into care homes are infections by staff interacting with the general population. Visitation (before cancellation) and staff sharing were less significant in affecting outbreak size. Our model suggests that focusing on the protection and monitoring of staff, followed by reductions in staff sharing and quick cancellations of visitation can significantly reduce future infection attack rates of COVID-19 in care homes.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.25.21262584", + "rel_abs": "BACKGROUNDWaning of vaccine protection against SARS-CoV-2 infection or COVID-19 disease is a concern. This study investigated persistence of BNT162b2 (Pfizer-BioNTech) vaccine effectiveness against infection and disease in Qatar, where the Beta and Delta variants have dominated incidence and PCR testing is done at a mass scale.\n\nMETHODSA matched test-negative, case-control study design was used to estimate vaccine effectiveness against SARS-CoV-2 infection and against any severe, critical, or fatal COVID-19 disease, between January 1, 2021 to August 15, 2021.\n\nRESULTSEstimated BNT162b2 effectiveness against any infection, asymptomatic or symptomatic, was negligible for the first two weeks after the first dose, increased to 36.5% (95% CI: 33.1-39.8) in the third week after the first dose, and reached its peak at 72.1% (95% CI: 70.9-73.2) in the first five weeks after the second dose. Effectiveness declined gradually thereafter, with the decline accelerating [≥]15 weeks after the second dose, reaching diminished levels of protection by the 20th week. Effectiveness against symptomatic infection was higher than against asymptomatic infection, but still waned in the same fashion. Effectiveness against any severe, critical, or fatal disease increased rapidly to 67.7% (95% CI: 59.1-74.7) by the third week after the first dose, and reached 95.4% (95% CI: 93.4-96.9) in the first five weeks after the second dose, where it persisted at about this level for six months.\n\nCONCLUSIONSBNT162b2-induced protection against infection appears to wane rapidly after its peak right after the second dose, but it persists at a robust level against hospitalization and death for at least six months following the second dose.", + "rel_num_authors": 24, "rel_authors": [ { - "author_name": "Matthew John Baister", - "author_inst": "University of Strathclyde" + "author_name": "Hiam Chemaitelly", + "author_inst": "Weill Cornell Medicine-Qatar" }, { - "author_name": "Ewan McTaggart", - "author_inst": "University of Strathclyde" + "author_name": "Patrick Tang", + "author_inst": "Sidra Medicine" }, { - "author_name": "Paul McMenemy", - "author_inst": "University of Stirling" + "author_name": "Mohammad Rubayet Hasan", + "author_inst": "Sidra Medicine" }, { - "author_name": "Itamar Megiddo", - "author_inst": "University of Strathclyde" + "author_name": "Sawsan AlMukdad", + "author_inst": "Weill Cornell Medicine-Qatar" }, { - "author_name": "Adam Kleczkowski", - "author_inst": "University of Strathclyde" + "author_name": "HADI M. YASSINE", + "author_inst": "Qatar University" + }, + { + "author_name": "Fatiha Benslimane", + "author_inst": "Qatar University" + }, + { + "author_name": "Hebah A. Al Khatib", + "author_inst": "Qatar University" + }, + { + "author_name": "Peter Coyle", + "author_inst": "Hamad Medical Corporation" + }, + { + "author_name": "Houssein H. Ayoub", + "author_inst": "Qatar University" + }, + { + "author_name": "Zaina Al Kanaani", + "author_inst": "Hamad Medical Corporation" + }, + { + "author_name": "Einas Al Kuwari", + "author_inst": "Hamad Medical Corporation" + }, + { + "author_name": "Andrew Jeremijenko", + "author_inst": "Hamad Medical Corporation" + }, + { + "author_name": "Anvar Hassan Kaleeckal", + "author_inst": "Hamad Medical Corporation" + }, + { + "author_name": "Ali Nizar Latif", + "author_inst": "Hamad Medical Corporation" + }, + { + "author_name": "Riyazuddin Mohammad Shaik", + "author_inst": "Hamad Medical Corporation" + }, + { + "author_name": "Hanan F. Abdul Rahim", + "author_inst": "Qatar University" + }, + { + "author_name": "Gheyath Nasrallah", + "author_inst": "Qatar University" + }, + { + "author_name": "Mohamed Ghaith Al Kuwari", + "author_inst": "Primary Health Care Corporation" + }, + { + "author_name": "Hamad Eid Al Romaihi", + "author_inst": "Ministry of Public Health" + }, + { + "author_name": "Adeel A Butt", + "author_inst": "Hamad Medical Corporation" + }, + { + "author_name": "Mohamed H. Al-Thani", + "author_inst": "Ministry of Public Health" + }, + { + "author_name": "Abdullatif Al Khal", + "author_inst": "Hamad Medical Corporation" + }, + { + "author_name": "Roberto Bertollini", + "author_inst": "Ministry of Public Health" + }, + { + "author_name": "Laith J Abu-Raddad", + "author_inst": "Weill Cornell Medicine-Qatar" } ], "version": "1", - "license": "cc_by", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -601191,151 +600718,55 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.08.24.21262385", - "rel_title": "The relationship between autoantibodies targeting GPCRs and the renin-angiotensin system associates with COVID-19 severity", + "rel_doi": "10.1101/2021.08.24.21258577", + "rel_title": "Sensitivity of wastewater-based epidemiology for detection of SARS-CoV-2 RNA in a low prevalence setting", "rel_date": "2021-08-26", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.24.21262385", - "rel_abs": "The coronavirus disease 2019 (COVID-19) can evolve to clinical manifestations resembling systemic autoimmune diseases, with the presence of autoantibodies that are still poorly characterized. To address this issue, we performed a cross-sectional study of 246 individuals to determine whether autoantibodies targeting G protein-coupled receptors (GPCRs) and renin-angiotensin system (RAS)-related molecules were associated with COVID-19-related clinical outcomes. Moderate and severe patients exhibited the highest autoantibody levels, relative to both healthy controls and patients with mild COVID-19 symptoms. Random Forest, a machine learning model, ranked anti-GPCR autoantibodies targeting downstream molecules in the RAS signaling pathway such as the angiotensin II type 1 and Mas receptor, and the chemokine receptor CXCR3 as the three strongest predictors of severe disease. Moreover, while the autoantibody network signatures were relatively conserved in patients with mild COVID-19 compared to healthy controls, they were disrupted in moderate and most perturbed in severe patients. Our data indicate that the relationship between autoantibodies targeting GPCRs and RAS-related molecules associates with the clinical severity of COVID-19, suggesting novel molecular pathways for therapeutic interventions.", - "rel_num_authors": 33, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.24.21258577", + "rel_abs": "To assist public health responses to COVID-19, wastewater-based epidemiology (WBE) is being utilised internationally to monitor SARS-CoV-2 infections at the community level. However, questions remain regarding the sensitivity of WBE and its use in low prevalence settings. In this study, we estimated the total number of COVID-19 cases required for detection of SARS-CoV-2 RNA in wastewater. To do this, we leveraged a unique situation where, over a 4-month period, all symptomatic and asymptomatic cases, in a population of approximately 120,000, were precisely known and mainly located in a single managed isolation and quarantine facility (MIQF) building. From 9 July to 6 November 2020, 24-hr composite wastewater samples (n = 113) were collected daily from the sewer outside the MIQF, and from the municipal wastewater treatment plant (WWTP) located 5 km downstream. New daily COVID-19 cases at the MIQF ranged from 0 to 17, and for most of the study period there were no cases outside the MIQF identified. SARS-CoV-2 RNA was detected in 54.0% (61/113) at the WWTP, compared to 95.6% (108/113) at the MIQF. We used logistic regression to estimate the shedding of SARS-CoV-2 RNA into wastewater based on four infectious shedding models. With a total of 5 and 10 COVID-19 infectious cases per 100,000 population (0.005 % and 0.01% prevalence) the predicated probability of SARS-CoV-2 RNA detection at the WWTP was estimated to be 28 and 41%, respectively. When a more realistic proportional shedding model was used, this increased to 58% and 87% for 5 and 10 cases, respectively. In other words, when 10 individuals were actively shedding SARS-CoV-2 RNA in a catchment of 100,000 individuals, there was a high likelihood of detecting viral RNA in wastewater. SARS-CoV-2 RNA detections at the WWTP were associated with increasing COVID-19 cases. Our results show that WBE provides a reliable and sensitive platform for detecting infections at the community scale, even when case prevalence is low, and can be of use as an early warning system for community outbreaks.\n\nHighlightsO_LIOver 4 months, all 0-17 new daily cases in one quarantine building, catchment 120,000 population\nC_LIO_LIWastewater tested daily at quarantine building and downstream wastewater treatment plant, WWTP\nC_LIO_LISARS-CoV-2 RNA detected in 95.6% (108/113) at the MIQF and 54.0% (61/113) at the WWTP\nC_LIO_LISARS-CoV-2 RNA detections at the WWTP associated with increasing COVID-19 cases\nC_LIO_LIProbability of SARS-CoV-2 RNA detection of 87% with 0.01% total case prevalence\nC_LI\n\nGraphical Abstract\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=146 SRC=\"FIGDIR/small/21258577v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (46K):\norg.highwire.dtl.DTLVardef@693a9corg.highwire.dtl.DTLVardef@86fce7org.highwire.dtl.DTLVardef@45dd75org.highwire.dtl.DTLVardef@ce526b_HPS_FORMAT_FIGEXP M_FIG C_FIG", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Otavio Cabral Marques", - "author_inst": "Department of Immunology, Institute of Biomedical Sciences, University of Sao Paulo, Sao Paulo, SP, Brazil" - }, - { - "author_name": "Gilad Halpert", - "author_inst": "Zabludowicz Center for Autoimmune Diseases, Sheba Medical Center, Tel-Aviv University, Tel-Hashomer, Israel" - }, - { - "author_name": "Lena F Schimke", - "author_inst": "Department of Immunology, Institute of Biomedical Sciences, University of Sao Paulo, Sao Paulo, SP, Brazil" - }, - { - "author_name": "Yuri Ostrinski", - "author_inst": "Zabludowicz Center for Autoimmune Diseases, Sheba Medical Center, Tel-Aviv University, Tel-Hashomer, Israel" - }, - { - "author_name": "Israel Zyskind", - "author_inst": "Department of Pediatrics, NYU Langone Medical Center, New York, NY, USA" - }, - { - "author_name": "Miriam T Lattin", - "author_inst": "Department of Biology, Yeshiva University, Manhatten, NY, USA" - }, - { - "author_name": "Florian Tran", - "author_inst": "Department of Internal Medicine I, University Medical Center Schleswig-Holstein Campus Kiel, Kiel, Germany" - }, - { - "author_name": "Stefan Schreiber", - "author_inst": "Department of Internal Medicine I, University Medical Center Schleswig-Holstein Campus Kiel, Kiel, Germany" - }, - { - "author_name": "Alexandre H.C. Marques", - "author_inst": "Department of Immunology, Institute of Biomedical Sciences, University of Sao Paulo, Sao Paulo, SP, Brazil." - }, - { - "author_name": "Igor Salerno Filgueiras", - "author_inst": "Department of Immunology, Institute of Biomedical Sciences, University of Sao Paulo, Sao Paulo, SP, Brazil." - }, - { - "author_name": "Desiree Rodrigues Placa", - "author_inst": "Department of Clinical and Toxicological Analyses, School of Pharmaceutical Sciences, University of Sao Paulo, Sao Paulo, SP, Brazil." - }, - { - "author_name": "Gabriela Crispim Baiocchi", - "author_inst": "Department of Immunology, Institute of Biomedical Sciences, University of Sao Paulo, Sao Paulo, SP, Brazil" - }, - { - "author_name": "Paula P Freire", - "author_inst": "Department of Immunology, Institute of Biomedical Sciences, University of Sao Paulo, Sao Paulo, SP, Brazil." - }, - { - "author_name": "Dennyson Leandro M. Fonseca", - "author_inst": "Department of Clinical and Toxicological Analyses, School of Pharmaceutical Sciences, University of Sao Paulo, Sao Paulo, SP, Brazil" - }, - { - "author_name": "Jens Y. Humrich", - "author_inst": "Department of Rheumatology, University Medical Center Schleswig-Holstein Campus Lubeck, Lubeck, Germany" - }, - { - "author_name": "Tanja Lange", - "author_inst": "Department of Rheumatology, University Medical Center Schleswig-Holstein Campus Lubeck, Lubeck, Germany" - }, - { - "author_name": "Antje Muller", - "author_inst": "Department of Rheumatology, University Medical Center Schleswig-Holstein Campus Lubeck, Lubeck, Germany" - }, - { - "author_name": "Lasse M. Giil", - "author_inst": "Department of Internal Medicine, Haraldsplass Deaconess Hospital, Bergen, Norway" - }, - { - "author_name": "Hanna Grasshoff", - "author_inst": "Department of Rheumatology, University Medical Center Schleswig-Holstein Campus Lubeck, Lubeck, Germany" - }, - { - "author_name": "Anja Schumann", - "author_inst": "Department of Rheumatology, University Medical Center Schleswig-Holstein Campus Lubeck, Lubeck, Germany" - }, - { - "author_name": "Alexander Maximilian Hackel", - "author_inst": "Department of Rheumatology, University Medical Center Schleswig-Holstein Campus Lubeck, Lubeck, Germany" - }, - { - "author_name": "Juliane Junker", - "author_inst": "CellTrend Gesellschaft mit beschrankter Haftung (GmbH), Luckenwalde, Germany" - }, - { - "author_name": "Carlotta Meyer", - "author_inst": "CellTrend Gesellschaft mit beschrankter Haftung (GmbH), Luckenwalde, Germany" - }, - { - "author_name": "Hans D. Ochs", - "author_inst": "Department of Pediatrics, University of Washington School of Medicine, and Seattle Children's Research Institute, Seattle, WA, USA" - }, - { - "author_name": "Yael Bublil Lavi", - "author_inst": "Department of Chemistry Ben Gurion University Beer-Sheva, 84105, Israel" + "author_name": "Joanne Hewitt", + "author_inst": "Institute of Environmental Science and Research Ltd" }, { - "author_name": "Kai Schulze-Forster", - "author_inst": "CellTrend Gesellschaft mit beschrankter Haftung (GmbH), Luckenwalde, Germany" + "author_name": "Sam Trowsdale", + "author_inst": "University of Auckland" }, { - "author_name": "Jonathan I. Silvergerg", - "author_inst": "Department of Dermatology, George Washington University, Washington, DC, USA" + "author_name": "Bridget Armstrong", + "author_inst": "Institute of Environmental Science and Research Ltd" }, { - "author_name": "Howard Amital", - "author_inst": "Zabludowicz Center for Autoimmune Diseases, Sheba Medical Center, Affiliated with the Sackler Faculty of Medicine, Tel-Aviv University, Tel-Hashomer, Israel" + "author_name": "Joanne R Chapman", + "author_inst": "Institute of Environmental Science and Research Ltd" }, { - "author_name": "Jason Zimmerman", - "author_inst": "Maimonides Medical Center, Brooklyn, NY, USA" + "author_name": "Kristen Carter", + "author_inst": "Institute of Environmental Science and Research Ltd" }, { - "author_name": "Harry Heidecke", - "author_inst": "CellTrend Gesellschaft mit beschrankter Haftung (GmbH), Luckenwalde, Germany" + "author_name": "Dawn Croucher", + "author_inst": "Institute of Environmental Science and Research Ltd" }, { - "author_name": "Avi Z Rosenberg", - "author_inst": "Department of Pathology, Johns Hopkins University, Baltimore, Maryland, USA" + "author_name": "Cassandra Billiau", + "author_inst": "Watercare Services Limited" }, { - "author_name": "Gabriela Riemekasten", - "author_inst": "Department of Rheumatology, University Medical Center Schleswig-Holstein Campus Lubeck, Lubeck, Germany" + "author_name": "Rosemary Sim", + "author_inst": "Watercare Services Limited" }, { - "author_name": "Yehuda Shoenfeld", - "author_inst": "Zabludowicz Center for Autoimmune Diseases, Sheba Medical Center, Tel-Aviv University, Tel-Hashomer, Israel" + "author_name": "Brent Gilpin", + "author_inst": "Institute of Environmental Science & Research" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "public and global health" }, { "rel_doi": "10.1101/2021.08.22.21262432", @@ -603240,49 +602671,41 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.08.23.21261779", - "rel_title": "Association of cerebral venous thrombosis with recent COVID-19 vaccination: case-crossover study using ascertainment through neuroimaging in Scotland.", + "rel_doi": "10.1101/2021.08.18.21262187", + "rel_title": "Men are the main COVID-19 transmitters: lessons from couples", "rel_date": "2021-08-24", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.23.21261779", - "rel_abs": "ObjectivesTo investigate the association of primary acute cerebral venous thrombosis (CVT) with COVID-19 vaccination through complete ascertainment of all diagnosed CVT in the population of Scotland.\n\nDesignCase-crossover study comparing recent (1-14 days after vaccination) with less recent exposure to vaccination among cases of CVT.\n\nSettingNational data for Scotland from 1 December 2020, with diagnosed CVT case ascertainment through neuroimaging studies up to 17 May 2021 and diagnostic coding of hospital discharges up to 28 April 2021 and with linkage to vaccination records.\n\nMain outcome measurePrimary acute cerebral venous thrombosis\n\nResultsOf 50 primary acute CVT cases, 29 were ascertained only from neuroimaging studies, 2 were ascertained only from hospital discharges, and 19 were ascertained from both sources. Of these 50 cases, 14 had received the Astra-Zeneca ChAdOx1 vaccine and 3 the Pfizer BNT162b2 vaccine. The incidence of CVT per million doses in the first 14 days after vaccination was 2.2 (95% credible interval 0.9 to 4.1) for ChAdOx1 and 1 (95% credible interval 0.1 to 2.9) for BNT162b2. The rate ratio for CVT associated with exposure to ChAdOx1 in the first 14 days compared with exposure 15-84 days after vaccination was 3.2 (95% credible interval 1.1 to 9.5). The 95% credible interval for the rate ratio associated with recent versus less recent exposure to BNT162b2 (0.6 to 95.8) was too wide for useful inference.\n\nConclusionsThese findings support a causal association between CVT and the AstraZeneca vaccine. The absolute risk of post-vaccination CVT in this population-wide study in Scotland was lower than has been reported for populations in Scandinavia and Germany; the explanation for this is not clear.\n\nWhat is already known on this topicThe risk of cerebral venous thrombosis (CVT) within 28 days of receiving the AstraZeneca ChAdOx1 vaccine has been estimated as 18 to 25 per million doses in Germany and Scandinavia, but only 5 per million doses in the UK based on the Yellow Card reporting scheme. Risk estimates based on adverse event reporting systems are subject to under-ascertainment and other biases.\n\nWhat this study addsAll diagnosed cases of CVT in Scotland were ascertained by searching neuroimaging studies from December 2020 to May 2021 and linked to national vaccination records. The risk of CVT within 28 days of vaccination with ChAdOx1 was estimated as 3.5 per million doses with an upper bound of 6 per million doses, against a background incidence of about 12 per million adults per year. This indicates that the Yellow Card system has not seriously underestimated the risk in the UK; the explanation for higher risk in other European countries is not clear.", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.18.21262187", + "rel_abs": "BackgroundCOVID-19 has affected millions of people worldwide. Clinical manifestations range from severe cases with a lethal outcome to mild or asymptomatic cases. Although there is the same proportion of infected genders, men are more susceptible to severe COVID-19, with a higher risk of death than women. This sex-bias may be explained by biological pathways.\n\nMethodsWe performed an epidemiological survey from July 2020 to July 2021 including 1744 unvaccinated adult Brazilian couples with at least one infected spouse despite living together during the COVID-19 infection without protective measures. The presence or absence of infection was confirmed by RT-PCR and/or serology results. The couples were divided between groups where both partners were infected (concordant couples) or only one spouse remained asymptomatic despite the close contact with the infected one (discordant couples). Statistical analysis of the collected data was performed aiming to verify a differential transmitter potential between genders in household contact.\n\nResultsThe combination of our data collected from concordant and discordant couples showed that the man is the first (or the only) affected in the major occurrences when compared to women. Our findings support other published surveys and are in concordance with previous studies of our group.\n\nConclusionsThese observations support the hypothesis according to which male individuals are more efficient virus transmitters than females, independently of the use of protective masks. In short, the present study confirmed the existence of gender differences not only for susceptibility to infection and resistance to COVID-19 but also in the transmission rate.\n\nHIGHLIGHTSO_LIThere are sex differences in COVID-19 susceptibility and transmission between couples with direct contact without protective measures;\nC_LIO_LIMen are more efficient virus transmitters than women;\nC_LIO_LISex-bias in COVID-19 transmission can be explained by differences in viral load in saliva, immune response and also behavioural protective differences between genders.\nC_LI", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Paul M McKeigue", - "author_inst": "University of Edinburgh" - }, - { - "author_name": "Raj Burgul", - "author_inst": "Forth Valley Royal Hospital" + "author_name": "Monize V. R. Silva", + "author_inst": "Human Genome and Stem Cell Research Center (HUG-CELL), Biosciences Institute, University of Sao Paulo, Sao Paulo, SP, Brazil" }, { - "author_name": "Jennifer Bishop", - "author_inst": "Public Health Scotland" + "author_name": "Mateus V. de Castro", + "author_inst": "Human Genome and Stem Cell Research Center (HUG-CELL), Biosciences Institute, University of Sao Paulo, Sao Paulo, SP, Brazil" }, { - "author_name": "Chris Robertson", - "author_inst": "Department of Mathematics and Statistics, University of Strathclyde" - }, - { - "author_name": "Jim McMenamin", - "author_inst": "Public Health Scotland" + "author_name": "Maria Rita Passos-Bueno", + "author_inst": "Human Genome and Stem Cell Research Center (HUG-CELL), Biosciences Institute, University of Sao Paulo, Sao Paulo, SP, Brazil" }, { - "author_name": "Maureen O'Leary", - "author_inst": "Public Health Scotland" + "author_name": "Paulo A. Otto", + "author_inst": "Department of Genetics and Evolutionary Biology, Biosciences Institute, University of Sao Paulo, Sao Paulo, SP, Brazil" }, { - "author_name": "David A. McAllister", - "author_inst": "University of Glasgow" + "author_name": "Michel S. Naslavsky", + "author_inst": "Department of Genetics and Evolutionary Biology, Biosciences Institute, University of Sao Paulo, Sao Paulo, SP, Brazil" }, { - "author_name": "Helen M Colhoun", - "author_inst": "University of Edinburgh" + "author_name": "Mayana Zatz", + "author_inst": "Human Genome and Stem Cell Research Center (HUG-CELL), Biosciences Institute, University of Sao Paulo, Sao Paulo, SP, Brazil" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -605066,55 +604489,47 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.08.18.21262065", - "rel_title": "Vaccine Effectiveness against Referral to Hospital and Severe Lung Injury Associated with COVID-19: A Population-based Case-control Study in St. Petersburg, Russia", + "rel_doi": "10.1101/2021.08.23.21262209", + "rel_title": "Population birth outcomes in 2020 and experiences of expectant mothers during the COVID-19 pandemic: a Born in Wales mixed methods study using routine data", "rel_date": "2021-08-23", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.18.21262065", - "rel_abs": "BackgroundResults of a randomised trial showed the safety and efficacy of Gam-COVID-Vac against COVID-19. However, compared to other vaccines used across the globe, the real-world data on the effectiveness of Gam-COVID-Vac, especially against the disease caused by Delta variant of concern, was not available. We aimed to assess the effectiveness of vaccination mainly conducted with Gam-COVID-Vac in St. Petersburg, Russia.\n\nMethodsWe designed a case-control study to assess the vaccine effectiveness (VE) against lung injury and referral to hospital. Self-reported vaccination status was collected for individuals with confirmed SARS-CoV-2 infection who were referred for initial low-dose computed tomography triage in two outpatient centres in July 3 - August 9, 2021 in St. Petersburg, Russia. We used logistic regression models to estimate the adjusted (for age, sex, and triage centre) VE for complete (>14 days after the second dose) vaccination. We estimated the VE against referral for hospital admission, COVID-19-related lung injury assessed with LDCT, and decline in oxygen saturation.\n\nResultsIn the final analysis, 13,893 patients were included, 1,291 (9.3%) of patients met our criteria for complete vaccination status, and 495 (3.6%) were referred to hospital. In the primary analysis, the adjusted VE against referral to hospital was 81% (95% CI: 68-88) for complete vaccination. The VE against referral to hospital was more pronounced in women (84%, 95% CI: 66-92) compared to men (76%, 95% CI: 51-88). Vaccine protective effect increased with increasing lung injury categories, from 54% (95% CI: 48-60) against any sign of lung injury to 76% (95% CI: 59-86) against more than 50% lung involvement. A sharp increase was observed in the probability of hospital admission with age for non-vaccinated patients in relation to an almost flat relationship for the completely vaccinated group.\n\nConclusionsCOVID-19 vaccination was effective against referral to hospital in patients with symptomatic SARS-CoV-2 infection in St. Petersburg, Russia. This protection is probably mediated through VE against lung injury associated with COVID-19.", - "rel_num_authors": 9, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.23.21262209", + "rel_abs": "BackgroundPregnancy can be a stressful time and the COVID-19 pandemic has affected all aspects of life. This study aims to investigate the impact of the pandemic on population birth outcomes in Wales, rates of primary immunisations and examine expectant mothers experiences of pregnancy including self-reported levels of stress and anxiety.\n\nMethodsPopulation-level birth outcomes in Wales: Stillbirths, prematurity, birth weight and Caesarean section births before (2016-2019) and during (2020) the pandemic were compared using national-level routine anonymised data held in the Secure Anonymised Information Linkage (SAIL) Databank. The first three scheduled primary immunisations were compared between 2019 and 2020. Self-reported pregnancy experience: 215 expectant mothers (aged 16+) in Wales completed an online survey about their experiences of pregnancy during the pandemic. The qualitative survey data was analysed using codebook thematic analysis.\n\nFindingsThere was no significant difference between annual outcomes including gestation and birth weight, stillbirths, and Caesarean sections for infants born in 2020 compared to 2016-2019. There was an increase in late term births ([≥]42 weeks gestation) during the first lockdown (OR: 1.28, p=0.019) and a decrease in moderate to late preterm births (32-36 weeks gestation) during the second lockdown (OR: 0.74, p=0.001). Fewer babies were born in 2020 (N=29,031) compared to 2016-2019 (average N=32,582). All babies received their immunisations in 2020, but there were minor delays in the timings of vaccines. Those due at 8-weeks were 8% less likely to be on time (within 28-days) and at 16-weeks, they were 19% less likely to be on time. The pandemic had a negative impact on the mental health of 71% of survey respondents, who reported anxiety, stress and loneliness; this was associated with attending scans without their partner, giving birth alone, and minimal contact with midwives.\n\nInterpretationThe pandemic had a negative impact on mothers experiences of pregnancy; however, population-level data suggests that this did not translate to adverse birth outcomes for babies born during the pandemic.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Anton Barchuk", - "author_inst": "European University at St. Petersburg" - }, - { - "author_name": "Mikhail Cherkashin", - "author_inst": "Medical Institute named after Berezin Sergey" - }, - { - "author_name": "Anna Bulina", - "author_inst": "Institute for Interdisciplinary Health Research, European University at St. Petersburg" + "author_name": "Hope Jones", + "author_inst": "Swansea University" }, { - "author_name": "Natalia Berezina", - "author_inst": "Medical Institute named after Berezin Sergey" + "author_name": "Mike Seaborne", + "author_inst": "Swansea University" }, { - "author_name": "Tatyana Rakova", - "author_inst": "Medical Institute named after Berezin Sergey" + "author_name": "Laura Cowley", + "author_inst": "Public Health Wales" }, { - "author_name": "Darya Kuplevatskaya", - "author_inst": "Medical Institute named after Berezin Sergey" + "author_name": "David E Odd", + "author_inst": "Cardiff University" }, { - "author_name": "Oksana Stanevich", - "author_inst": "European University at St. Petersburg" + "author_name": "Shantini Paranjothy", + "author_inst": "University of Aberdeen" }, { - "author_name": "Dmitriy Skougarevskiy", - "author_inst": "European University at St. Petersburg" + "author_name": "Ashley Akbari", + "author_inst": "Swansea University" }, { - "author_name": "Artemy Okhotin", - "author_inst": "Tarusa Hospital" + "author_name": "Sinead Brophy", + "author_inst": "Swansea University" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "public and global health" }, { "rel_doi": "10.1101/2021.08.22.457114", @@ -607112,29 +606527,61 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.08.19.21262267", - "rel_title": "The burden of isolation to the individual: a comparison between isolation for COVID-19 and for other influenza-like illnesses in Japan", + "rel_doi": "10.1101/2021.08.15.21261243", + "rel_title": "Self-testing and vaccination against COVID-19 to minimize school closure", "rel_date": "2021-08-21", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.19.21262267", - "rel_abs": "At present, there is scarce evidence about how much burden the isolation of COVID-19 patients is. We aimed to assess the differences between COVID-19 and other influenza like illnesses in disease burden brought by isolation. We conducted an online questionnaire survey of 302 people who had COVID-19 or other influenza-like illnesses (ILIs) and compared the burden of isolation due to sickness with one-to-one propensity score matching. The primary outcomes are the duration and productivity losses of isolation, the secondary outcome is quality of life (QOL) valuation on the day of the survey. Acute symptoms of outpatient COVID-19 and other ILIs lasted 17 (interquartile range [IQR] 9-32) and 7 (IQR 4-10) days, respectively. The length of isolation due to COVID-19 was 18 (IQR 10-33) days and that due to other ILIs was 7 (IQR 4-11) days, respectively. The monetary productivity loss of isolation due to COVID-19 was 1424.3 (IQR 825.6-2545.5) USD and that due to other ILIs was 606.1 (IQR 297.0-1090.9) USD, respectively. QOL at the time of the survey was lower in the COVID-19 group than in the \"other ILIs\" group (0.89 and 0.96, p = 0.001). COVID-19 infection imposes a substantial disease burden, even in patients with non-severe disease. This burden is larger for COVID-19 than other ILIs, mainly because the required isolation period is longer.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.15.21261243", + "rel_abs": "Schools were closed extensively in 2020-2021 to counter COVID-19 spread, impacting students education and well-being. With highly contagious variants expanding in Europe, safe options to maintain schools open are urgently needed. We developed an agent-based model of SARS-CoV-2 transmission in school. We used empirical contact data in a primary and a secondary school, and data from pilot screenings in 683 schools during the 2021 spring Alpha wave in France. We fitted the model to observed school prevalence to estimate the school-specific reproductive number and performed a cost-benefit analysis examining different intervention protocols. We estimated RAlpha=1.40 (95%CI 1.35-1.45) in the primary and RAlpha=1.46 (1.41-1.51) in the secondary school during the wave, higher than Rt estimated from community surveillance. Considering the Delta variant and vaccination coverage in Europe, we estimated RDelta=1.66 (1.60-1.71) and RDelta=1.10 (1.06-1.14) in the two settings, respectively. Under these conditions, weekly screening with 75% adherence would reduce cases by 34% (95%CI 32-36%) in the primary and 36% (35-39%) in the secondary school compared to symptom-based testing. Insufficient adherence was recorded in pilot screening (median [≤]53%). Regular screening would also reduce student-days lost up to 80% compared to reactive closure. Moderate vaccination coverage in students would still benefit from regular screening for additional control (23% case reduction with 50% vaccinated children). COVID-19 pandemic will likely continue to pose a risk for school opening. Extending vaccination coverage in students, complemented by regular testing largely incentivizing adherence, are essential steps to keep schools open, especially under the threat of more contagious variants.", + "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Shinya Tsuzuki", - "author_inst": "University of Antwerp" + "author_name": "Elisabetta Colosi", + "author_inst": "INSERM, Sorbonne Universit\u00e9, Pierre Louis Institute of Epidemiology and Public Health, Paris, France" }, { - "author_name": "Norio Ohmagari", - "author_inst": "National Center for Global Health and Medicine" + "author_name": "Giulia Bassignana", + "author_inst": "INSERM, Sorbonne Universit\u00e9, Pierre Louis Institute of Epidemiology and Public Health, Paris, France" }, { - "author_name": "Philippe Beutels", - "author_inst": "University of Antwerp" + "author_name": "Diego A Contreras", + "author_inst": "Aix Marseille Univ, Universit\u00e9 de Toulon, CNRS, CPT, Turing Center for Living Systems, Marseille, France" + }, + { + "author_name": "Canelle Poirier", + "author_inst": "INSERM, Sorbonne Universit\u00e9, Pierre Louis Institute of Epidemiology and Public Health, Paris, France" + }, + { + "author_name": "Pierre-Yves Bo\u00eblle", + "author_inst": "INSERM, Sorbonne Universit\u00e9, Pierre Louis Institute of Epidemiology and Public Health" + }, + { + "author_name": "Simon Cauchemez", + "author_inst": "Mathematical Modelling of Infectious Diseases Unit, Institut Pasteur, UMR2000, CNRS, Paris, France" + }, + { + "author_name": "Yazdan Yazdanpanah", + "author_inst": "Infection, Antimicrobials, Modelling, Evolution, INSERM, Universit\u00e9 de Paris, Paris, France" + }, + { + "author_name": "Bruno Lina", + "author_inst": "National Reference Center for Respiratory Viruses, Department of Virology, Infective Agents Institute, Croix-Rousse Hospital, Hospices Civils de Lyon, Lyon, Fra" + }, + { + "author_name": "Arnaud Fontanet", + "author_inst": "Emerging Diseases Epidemiology Unit, Institut Pasteur, Paris, France" + }, + { + "author_name": "Alain Barrat", + "author_inst": "Aix Marseille Univ, Universit\u00e9 de Toulon, CNRS, CPT, Turing Center for Living Systems, Marseille, France" + }, + { + "author_name": "Vittoria Colizza", + "author_inst": "INSERM, Sorbonne Universit\u00e9, Pierre Louis Institute of Epidemiology and Public Health, Paris, France" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -608814,89 +608261,41 @@ "category": "pharmacology and therapeutics" }, { - "rel_doi": "10.1101/2021.08.13.21262037", - "rel_title": "Early Reduction of SARS-CoV-2 Replication in Bronchial Epithelium by Kinin B2 Receptor Antagonism", + "rel_doi": "10.1101/2021.08.11.21261670", + "rel_title": "A third COVID-19 vaccine shot markedly boosts neutralizing antibody potency and breadth", "rel_date": "2021-08-18", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.13.21262037", - "rel_abs": "BackgroundSARS-CoV2 has evolved to enter the host via the ACE2 receptor which is part of the Kinin-kallirein pathway. This complex pathway is only poorly understood in context of immune regulation but critical to control infection. This study examines SARS-CoV2 infection and epithelial mechanisms of the kinin-kallikrein system at the kinin B2 receptor level in SARS-CoV-2 infection that is of direct translational relevance.\n\nMethodsFrom acute SARS-CoV-2-positive patients and -negative controls, transcriptomes of nasal brushings were analyzed. Primary airway epithelial cells (NHBEs) were infected with SARS-CoV-2 and treated with the approved B2R antagonist icatibant. SARS-CoV-2 RNA RT-qPCR, cytotoxicity assays, plaque assays and transcriptome analyses were performed. The treatment effect was further studied in a murine airway inflammation model in vivo.\n\nResultsHere, we report a broad and strong upregulation of kallikreins and the kinin B2 receptor (B2R) in the nasal mucosa of acutely symptomatic SARS-CoV-2-positive patients. A B2R antagonist impeded SARS-CoV-2 replication and spread in NHBEs, as determined in plaque assays on Vero E6 cells. B2R antagonism reduced the expression of SARS-CoV-2 entry receptor ACE2 in vitro and in a murine airway inflammation model in vivo. In addition, it suppressed gene expression broadly, particularly genes involved in G-protein-coupled-receptor signaling and ion transport.\n\nConclusionsIn summary, this study provides evidence that treatment with B2R antagonists protects airway epithelial cells from SARS-CoV-2 by inhibiting its replication and spread, through the reduction of ACE2 levels and the interference with several cellular signaling processes. Future clinical studies need to shed light on the airway protection potential of approved B2R antagonists, like icatibant, in the treatment of early-stage COVID-19.", - "rel_num_authors": 19, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.11.21261670", + "rel_abs": "COVID-19 (coronavirus disease 2019) vaccines have been rapidly developed and deployed globally as a measure to combat the disease. These vaccines have been demonstrated to confer significant protection, but there have been reports of temporal decay in antibody titer. Furthermore, several variants have been identified with variable degrees of antibody resistance. These two factors suggest that a booster vaccination may be worthy of consideration. While such a booster dose has been studied as a series of three homologous vaccines in healthy individuals, to our knowledge, information on a heterologous regimen remains unreported, despite the practical benefits of such a scheme. Here, in this observational study, we investigated the serological profile of four healthy individuals who received two doses of the BNT162b2 vaccine, followed by a third booster dose with the Ad26.COV2.S vaccine. We found that while all individuals had spike-binding antibodies at each of the timepoints tested, there was an appreciable drop in titer by four months following the second vaccination. The third vaccine dose robustly increased titers beyond that of two vaccinations, and these elicited antibodies had neutralizing capability against all SARS-CoV-2 strains tested in both a recombinant vesicular stomatitis virus-based pseudovirus assay and an authentic SARS-CoV-2 assay, except for one individual against B.1.351 in the latter assay. Thus, a third COVID-19 vaccine dose in healthy individuals promoted not just neutralizing antibody potency, but also induced breadth against dominant SARS-CoV-2 variants.\n\nSignificanceCOVID-19 vaccines confer protection from symptomatic disease, but the elicited antibody titer has been found to decrease with time. Furthermore, SARS-CoV-2 variants with relative resistance against antibody neutralization have been identified. To overcome such issues, a third vaccine dose applied as a booster vaccine may be necessary. We studied four healthy individuals who received a heterologous booster dose as a third vaccine. All of these individuals had heightened neutralizing antibody titer following the booster vaccination, and could neutralize nearly all variants tested. Thus, a heterologous third COVID-19 vaccine dose may be a mechanism to both heighten and broaden antibody titers, and could be an additional strategy for controlling the SARS-CoV-2 pandemic.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Constanze A. Jakwerth", - "author_inst": "Center of Allergy & Environment (ZAUM), Technical University of Munich and Helmholtz Center Munich, German Research Center for Environmental Health, Member of t" - }, - { - "author_name": "Martin Feuerherd", - "author_inst": "Institute of Virology, Technical University of Munich/Helmholtz Center Munich, Munich, Germany; German Center of Infectiology Research (DZIF)" - }, - { - "author_name": "Ferdinand M. Guerth", - "author_inst": "Center of Allergy & Environment (ZAUM), Technical University of Munich and Helmholtz Center Munich, German Research Center for Environmental Health, Member of t" - }, - { - "author_name": "Madlen Oelsner", - "author_inst": "Center of Allergy & Environment (ZAUM), Technical University of Munich and Helmholtz Center Munich, German Research Center for Environmental Health, Member of t" - }, - { - "author_name": "Linda Schellhammer", - "author_inst": ") Institute of Laboratory Animal Science, University of Zurich, Zurich, Switzerland" - }, - { - "author_name": "Johanna Giglberger", - "author_inst": "Center of Allergy & Environment (ZAUM), Technical University of Munich and Helmholtz Center Munich, German Research Center for Environmental Health, Member of t" - }, - { - "author_name": "Lisa Pechtold", - "author_inst": "Department of Otorhinolaryngology and Head and Neck Surgery, Medical School, Technical University of Munich" - }, - { - "author_name": "Claudia Jerin", - "author_inst": "Center of Allergy & Environment (ZAUM), Technical University of Munich and Helmholtz Center Munich, German Research Center for Environmental Health, Member of t" - }, - { - "author_name": "Luisa Kugler", - "author_inst": "Department of Otorhinolaryngology and Head and Neck Surgery, Medical School, Technical University of Munich" - }, - { - "author_name": "Carolin Mogler", - "author_inst": "Institute of Pathology, Technical University Munich, Munich, Germany" - }, - { - "author_name": "Bernhard Haller", - "author_inst": "Institute of Medical Informatics, Statistics and Epidemiology, Medical School, Technical University of Munich" - }, - { - "author_name": "Anna Erb", - "author_inst": "Center of Allergy & Environment (ZAUM), Technical University of Munich and Helmholtz Center Munich, German Research Center for Environmental Health, Member of t" - }, - { - "author_name": "Barbara Wollenberg", - "author_inst": "Department of Otorhinolaryngology and Head and Neck Surgery, Medical School, Technical University of Munich" + "author_name": "Sho Iketani", + "author_inst": "Aaron Diamond AIDS Research Center" }, { - "author_name": "Christoph D. Spinner", - "author_inst": "Department of Internal Medicine II, University Hospital rechts der Isar, Medical School, Technical University of Munich" + "author_name": "Lihong Liu", + "author_inst": "Aaron Diamond AIDS Research Center" }, { - "author_name": "Thorsten Buch", - "author_inst": "Institute of Laboratory Animal Science, University of Zurich, Zurich, Switzerland" + "author_name": "Manoj S Nair", + "author_inst": "Aaron Diamond AIDS Research Center" }, { - "author_name": "Ulrike Protzer", - "author_inst": "Institute of Virology, Technical University of Munich/Helmholtz Center Munich, Munich, Germany; German Center of Infectiology Research (DZIF), Munich partner si" + "author_name": "Hiroshi Mohri", + "author_inst": "Aaron Diamond AIDS Research Center" }, { - "author_name": "Carsten B. Schmidt-Weber", - "author_inst": "Center of Allergy & Environment (ZAUM), Technical University of Munich and Helmholtz Center Munich, German Research Center for Environmental Health, Member of t" + "author_name": "Maple Wang", + "author_inst": "Aaron Diamond AIDS Research Center" }, { - "author_name": "Ulrich M. Zissler", - "author_inst": "Center of Allergy & Environment (ZAUM), Technical University of Munich and Helmholtz Center Munich, German Research Center for Environmental Health, Member of t" + "author_name": "Yaoxing Huang", + "author_inst": "Aaron Diamond AIDS Research Center" }, { - "author_name": "Adam M. Chaker", - "author_inst": "Department of Otorhinolaryngology and Head and Neck Surgery, Medical School, Technical University of Munich" + "author_name": "David D Ho", + "author_inst": "Aaron Diamond AIDS Research Center" } ], "version": "1", @@ -610656,35 +610055,67 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2021.08.18.456769", - "rel_title": "Interaction between spike protein of SARS-CoV-2 and human virus receptor ACE2 using two-color fluorescence cross-correlation spectroscopy", + "rel_doi": "10.1101/2021.08.18.456855", + "rel_title": "Cap-independent translation and a precisely localized RNA sequence enable SARS-CoV-2 to control host translation and escape anti-viral response", "rel_date": "2021-08-18", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.08.18.456769", - "rel_abs": "Infection with severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), the cause of coronavirus disease 2019 (COVID-19), is initiated by the interaction between a receptor protein, angiotensin-converting enzyme type 2 (ACE2) on the cell surface, and the viral spike (S) protein. This interaction is similar to the mechanism in SARS-CoV, a close relative of SARS-CoV-2, which was identified in 2003. Drugs and antibodies that inhibit the interaction between ACE2 and S proteins could be key therapeutic methods for preventing viral infection and replication in COVID-19. Here, we demonstrate the interaction between human ACE2 and a fragment of the S protein (S1 subunit) derived from SARS-CoV-2 and SARS-CoV using two-color fluorescence cross-correlation spectroscopy (FCCS), which can detect the interaction of fluorescently labeled proteins. The S1 subunit of SARS-CoV-2 interacted in solution with soluble ACE2, which lacks a transmembrane region, more strongly than that of SARS-CoV. Furthermore, one-to-one stoichiometry of the two proteins during the interaction was indicated. Thus, we propose that this FCCS-based interaction detection system can be used to analyze the interaction strengths of various mutants of the S1 subunit that have evolved during the worldwide pandemic, and also offers the opportunity to screen and evaluate the performance of drugs and antibodies that inhibit the interaction.", - "rel_num_authors": 4, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.08.18.456855", + "rel_abs": "Translation of SARS-CoV-2-encoded mRNAs by the host ribosomes is essential for its propagation. Following infection, the early expressed viral protein NSP1 binds the ribosome, represseses translation and induces mRNA degradation, while the host elicits anti-viral response. The mechanisms enabling viral mRNAs to escape this multifaceted repression remain obscure. Here we show that expression of NSP1 leads to destabilization of multi-exon cellular mRNAs, while intron-less transcripts, such as viral mRNAs and anti-viral interferon genes, remain relatively stable. We identified a conserved and precisely located cap-proximal RNA element devoid of guanosines that confers resistance to NSP1-meidated translation inhibition. Importantly, the primary sequence rather than the secondary structure is critical for protection. We further show that the genomic 5UTR of SARS-CoV-2 exhibits an IRES-like activity and promotes expression of NSP1 in an eIF4E-independent and Torin-1 resistant manner. Upon expression, NSP1 enhances cap-independent translation. However, the sub-genomic 5UTRs are highly sensitive to eIF4E availability, rendering viral propagation partially sensitive to Torin-1. The combined NSP1-mediated degradation of spliced mRNAs and translation inhibition of single-exon genes, along with the unique features present in the viral 5UTRs, ensure robust expression of viral mRNAs. These features can be exploited as potential therapeutic targets.", + "rel_num_authors": 12, "rel_authors": [ { - "author_name": "Ai Fujimoto", - "author_inst": "Hokkaido University" + "author_name": "Boris Slobodin", + "author_inst": "Weizmann Institute of Science" }, { - "author_name": "Yidan Lyu", - "author_inst": "Hokkaido Univeristy" + "author_name": "Urmila Sehrawat", + "author_inst": "Weizmann Institute of Science" }, { - "author_name": "Masataka Kinjo", - "author_inst": "Hokkaido University" + "author_name": "Anastasia Lev", + "author_inst": "Weizmann Institute of Science" }, { - "author_name": "Akira Kitamura", - "author_inst": "Hokkaido University" + "author_name": "Ariel Ogran", + "author_inst": "Weizmann Institute of Science" + }, + { + "author_name": "Davide Fraticelli", + "author_inst": "Weizmann Institute of Science" + }, + { + "author_name": "Daniel Hayat", + "author_inst": "Weizmann Institute of Science" + }, + { + "author_name": "Binyamin Zuckerman", + "author_inst": "Gladstone Institutes" + }, + { + "author_name": "Igor Ulitsky", + "author_inst": "Weizmann Institute of Science" + }, + { + "author_name": "Amir Ben-Shmuel", + "author_inst": "Israel Institute for Biological Research" + }, + { + "author_name": "Haim Levy", + "author_inst": "Israel Institute for Biological Research" + }, + { + "author_name": "Elad Bar-David", + "author_inst": "Israel Institute for Biological Research" + }, + { + "author_name": "Rivka Dikstein", + "author_inst": "The Weizmann Institute of Science" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "new results", - "category": "biophysics" + "category": "molecular biology" }, { "rel_doi": "10.1101/2021.08.16.21262118", @@ -612294,69 +611725,105 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.08.12.21261952", - "rel_title": "DECREASED BREADTH OF THE ANTIBODY RESPONSE TO THE SPIKE PROTEIN OF SARS-CoV-2 AFTER VACCINATION", + "rel_doi": "10.1101/2021.08.11.21261914", + "rel_title": "A Third Dose of SARS-CoV-2 Vaccine Increases Neutralizing Antibodies Against Variants of Concern in Solid Organ Transplant Recipients", "rel_date": "2021-08-14", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.12.21261952", - "rel_abs": "The rapid development of vaccines to prevent infection by SARS-CoV-2 virus causing COVID-19 makes necessary to compare the capacity of the different vaccines in terms of development of a protective humoral response. Here, we have used a highly sensitive and reliable flow cytometry method to measure the titers of antibodies of the IgG1 isotype in blood of healthy volunteers after receiving one or two doses of the vaccines being administered in Spain. We took advantage of the multiplexed capacity of the method to measure simultaneously the reactivity of antibodies with the S protein of the original strain Wuhan and the variants B.1.1.7 (Alpha), B.1.617.2 (Delta) and B.1.617.1 (Kappa). We found significant differences in the titer of anti-S antibodies produced after a first dose of the vaccines ChAdOx1 nCov-19/AstraZeneca, mRNA-1273/Moderna, BNT162b2/Pfizer-BioNTech and Ad26.COV.S/Janssen. Most important, we found a relative reduction in the reactivity of the sera with the Alpha, Delta and Kappa variants, versus the Wuhan one, after the second boosting immunization. These data allow to make a comparison of different vaccines in terms of anti-S antibody generation and cast doubts about the convenience of repeatedly immunizing with the same S protein sequence.", - "rel_num_authors": 14, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.11.21261914", + "rel_abs": "Vaccine-induced SARS-CoV-2 antibody responses are attenuated in solid organ transplant recipients (SOTRs) and breakthrough infections are more common. Additional SARS-CoV-2 vaccine doses increase anti-spike IgG in some SOTRs, but it is uncertain whether neutralization of variants of concern (VOCs) is enhanced. We tested 47 SOTRs for clinical and research anti-spike IgG, pseudoneutralization (ACE2 blocking), and live-virus neutralization (nAb) against VOCs before and after a third SARS-CoV-2 vaccine dose (70% mRNA, 30% Ad26.COV2.S) with comparison to 15 healthy controls after two mRNA vaccine doses. We used correlation analysis to compare anti-spike IgG assays and focused on thresholds associated with neutralizing activity. A third SARS-CoV-2 vaccine dose increased median anti-spike (1.6-fold) and receptor-binding domain (1.5-fold) IgG, as well as pseudoneutralization against VOCs (2.5-fold versus Delta). However, IgG and neutralization activity were significantly lower than healthy controls (p<0.001); 32% of SOTRs had zero detectable nAb against Delta after third vaccination. Correlation with nAb was seen at anti-spike IgG >4 AU on the clinical assay and >10^4 AU on the research assay. These findings highlight benefits of a third vaccine dose for some SOTRs and the need for alternative strategies to improve protection in a significant subset of this population.", + "rel_num_authors": 23, "rel_authors": [ { - "author_name": "Lydia Horndler", - "author_inst": "Centro de Biologia Molecular Severo Ochoa" + "author_name": "Andrew H Karaba", + "author_inst": "Johns Hopkins" }, { - "author_name": "Pilar Delgado", - "author_inst": "Centro de Biologia Molecular Severo Ochoa" + "author_name": "Xianming Zhu", + "author_inst": "Johns Hopkins" }, { - "author_name": "Salvador Romero-Pinedo", - "author_inst": "VITRO SA" + "author_name": "Tao Liang", + "author_inst": "Johns Hopkins" }, { - "author_name": "Marina Quesada", - "author_inst": "VITRO SA" + "author_name": "Kristy H Wang", + "author_inst": "Johns Hopkins" }, { - "author_name": "Ivaylo Balabanov", - "author_inst": "Centro de Biologia Molecular Severo Ochoa" + "author_name": "Alex G Rittenhouse", + "author_inst": "Johns Hopkins" }, { - "author_name": "Rocio Laguna-Goya", - "author_inst": "Hospital 12 de Octubre" + "author_name": "Olivia Akinde", + "author_inst": "Johns Hopkins" }, { - "author_name": "Patricia Almendro-Vazquez", - "author_inst": "Hospital 12 de Octubre" + "author_name": "Yolanda Eby", + "author_inst": "Johns Hopkins" }, { - "author_name": "Miguel A Llamas", - "author_inst": "EMPIREO SL" + "author_name": "Jessica Ruff", + "author_inst": "Johns Hopkins University" }, { - "author_name": "Manuel Fresno", - "author_inst": "Centro de Biologia Molecular Severo Ochoa" + "author_name": "Joel N Blankson", + "author_inst": "Johns Hopkins" }, { - "author_name": "Estela Paz-Artal", - "author_inst": "Hospital 12 de Octubre" + "author_name": "Aura Teles", + "author_inst": "Johns Hopkins" }, { - "author_name": "Hisse M van Santen", - "author_inst": "Centro de Biologia Molecular Severo Ochoa" + "author_name": "Jennifer L Alejo", + "author_inst": "Johns Hopkins" }, { - "author_name": "Stela Alvarez", - "author_inst": "VITRO SA" + "author_name": "Andrea L Cox", + "author_inst": "Johns Hopkins" }, { - "author_name": "Asuncion Olmo", - "author_inst": "VITRO SA" + "author_name": "Justin R Bailey", + "author_inst": "Johns Hopkins" }, { - "author_name": "Balbino Alarcon", - "author_inst": "Centro de Biologia Molecular Severo Ochoa" + "author_name": "Elizabeth Thompson", + "author_inst": "Johns Hopkins University" + }, + { + "author_name": "Sabra L Klein", + "author_inst": "Johns Hopkins" + }, + { + "author_name": "Dan Warren", + "author_inst": "Johns Hopkins University" + }, + { + "author_name": "Jacqueline M Garonzik-Wang", + "author_inst": "Johns Hopkins" + }, + { + "author_name": "Brian J Boyarsky", + "author_inst": "Johns Hopkins" + }, + { + "author_name": "Ioannis Sitaras", + "author_inst": "Johns Hopkins University School of Public Health" + }, + { + "author_name": "Andrew Pekosz", + "author_inst": "Johns Hopkins" + }, + { + "author_name": "Dorry L Segev", + "author_inst": "Johns Hopkins" + }, + { + "author_name": "Aaron AR Tobian", + "author_inst": "Johns Hopkins" + }, + { + "author_name": "William A Werbel", + "author_inst": "Johns Hopkins" } ], "version": "1", @@ -614096,83 +613563,107 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2021.08.12.21261976", - "rel_title": "The production of anti-PF4 antibodies in anti-phospholipid antibody-positive patients is not affected by COVID-19 vaccination", + "rel_doi": "10.1101/2021.08.12.21261987", + "rel_title": "Characterising the persistence of RT-PCR positivity and incidence in a community survey of SARS-CoV-2", "rel_date": "2021-08-13", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.12.21261976", - "rel_abs": "Antibodies against cationic platelet chemokine, platelet factor 4 (PF4/CXCL4) have been described in heparin-induced thrombocytopenia (HIT) but also in patients positive for anti-phospholipid antibodies (aPL) even in the absence of heparin treatment and HIT-related clinical manifestations. Anti-PF4 antibodies have been recently described also in subjects who developed thrombosis with thrombocytopenia syndrome (TTS) in association with adenoviral vector-based, but not with mRNA-based COVID-19 vaccines.\n\nWe investigated whether COVID-19 vaccination affects the production of anti-PF4 immunoglobulins detectable by solid phase assay in aPL-positive patients and their ability to induce in vitro platelet activation. Anti-PF4 were found in 9/126 aPL-positive patients, 4/50 COVID-19, 9/49 other infections and 1/50 aPL-negative systemic lupus erythematosus patients. Clinical manifestations of TTS were not observed in any aPL patient positive for anti-PF4, whose sera failed to cause platelet aggregations. The administration of COVID-19 vaccines did not affect the production of anti-PF4 immunoglobulins or their ability to cause platelet aggregation in 44 aPL-positive patients tested before and after vaccination. In conclusion, heparin treatment-independent anti-PF4 antibodies can be found in aPL-positive patients and asymptomatic carriers, but their presence, titer as well as in vitro effect on platelet activation are not affected by COVID-19 vaccination.", - "rel_num_authors": 16, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.12.21261987", + "rel_abs": "BackgroundCommunity surveys of SARS-CoV-2 RT-PCR swab-positivity provide prevalence estimates largely unaffected by biases from who presents for routine case testing. The REal-time Assessment of Community Transmission-1 (REACT-1) has estimated swab-positivity approximately monthly since May 2020 in England from RT-PCR testing of self-administered throat and nose swabs in random non-overlapping cross-sectional community samples. Estimating infection incidence from swab-positivity requires an understanding of the persistence of RT-PCR swab positivity in the community.\n\nMethodsDuring round 8 of REACT-1 from 6 January to 22 January 2021, of the 2,282 participants who tested RT-PCR positive, we recruited 896 (39%) from whom we collected up to two additional swabs for RT-PCR approximately 6 and 9 days after the initial swab. We estimated sensitivity and duration of positivity using an exponential model of positivity decay, for all participants and for subsets by initial N-gene cycle threshold (Ct) value, symptom status, lineage and age. Estimates of infection incidence were obtained for the entire duration of the REACT-1 study using P-splines.\n\nResultsWe estimated the overall sensitivity of REACT-1 to detect virus on a single swab as 0.79 (0.77, 0.81) and median duration of positivity following a positive test as 9.7 (8.9, 10.6) days. We found greater median duration of positivity where there was a low N-gene Ct value, in those exhibiting symptoms, or for infection with the Alpha variant. The estimated proportion of positive individuals detected on first swab, P0, was found to be higher for those with an initially low N-gene Ct value and those who were pre-symptomatic. When compared to swab-positivity, estimates of infection incidence over the duration of REACT-1 included sharper features with evident transient increases around the time of key changes in social distancing measures.\n\nDiscussionHome self-swabbing for RT-PCR based on a single swab, as implemented in REACT-1, has high overall sensitivity. However, participants time-since-infection, symptom status and viral lineage affect the probability of detection and the duration of positivity. These results validate previous efforts to estimate incidence of SARS-CoV-2 from swab-positivity data, and provide a reliable means to obtain community infection estimates to inform policy response.", + "rel_num_authors": 22, "rel_authors": [ { - "author_name": "Paola Lonati", - "author_inst": "Istituto Auxologico Italiano" + "author_name": "Oliver Eales", + "author_inst": "School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc" }, { - "author_name": "Caterina Bodio", - "author_inst": "Istituto Auxologico Italiano" + "author_name": "Caroline E. Walters", + "author_inst": "School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc" }, { - "author_name": "Mariangela Scavone", - "author_inst": "Health Sciences Department, University of Milan, Milan, ITALY" + "author_name": "Haowei Wang", + "author_inst": "School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc" }, { - "author_name": "Giuliana Martini", - "author_inst": "Centro Emostasi, Laboratorio Analisi Chimico-Cliniche, ASST-Spedali Civili, Brescia, Italy" + "author_name": "David Haw", + "author_inst": "School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc" }, { - "author_name": "Elisa Pesce", - "author_inst": "National Institute of Molecular Genetics" + "author_name": "Kylie E. C. Ainslie", + "author_inst": "School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc" }, { - "author_name": "Alessandra Bandera", - "author_inst": "Department of Pathophysiology and Transplantation, University of Milan; Infectious Diseases Unit, Foundation IRCCS Ca' Granda Ospedale Maggiore Policlinico, Mil" + "author_name": "Christina Atchinson", + "author_inst": "School of Public Health, Imperial College London, UK" }, { - "author_name": "Andrea Lombardi", - "author_inst": "Department of Pathophysiology and Transplantation, University of Milan; Infectious Diseases Unit, Foundation IRCCS Ca' Granda Ospedale Maggiore Policlinico, Mil" + "author_name": "Andrew Page", + "author_inst": "Quadram Institute, Norwich, UK" }, { - "author_name": "Maria Gerosa", - "author_inst": "Department of Clinical Sciences and Community Health, University of Milan, Milan, Italy" + "author_name": "Sophie Prosolek", + "author_inst": "Quadram Institute, Norwich, UK" }, { - "author_name": "Franco Franceschini", - "author_inst": "Department of Clinical and Experimental Sciences, University of Brescia; Unit of Rheumatology and Clinical Immunology, ASST Spedali Civili, Brescia, Italy" + "author_name": "Alexander J. Trotter", + "author_inst": "Quadram Institute, Norwich, UK" }, { - "author_name": "Angela Tincani", - "author_inst": "Department of Clinical and Experimental Sciences, University of Brescia; Unit of Rheumatology and Clinical Immunology, ASST Spedali Civili, Brescia, Italy" + "author_name": "Thanh Le Viet", + "author_inst": "Quadram Institute, Norwich, UK" }, { - "author_name": "Gianmarco Podda", - "author_inst": "Health Sciences Department, University of Milan, Milan, Italy" + "author_name": "Nabil-Fareed Alikhan", + "author_inst": "Quadram Institute, Norwich, UK" }, { - "author_name": "Sergio Abrignani", - "author_inst": "National Institute Molecular Genetics; UniversityMilan, Milan, Italy" + "author_name": "Leigh M Jackson", + "author_inst": "Medical School, University of Exeter, UK" }, { - "author_name": "Renata Grifantini", - "author_inst": "National Institute Molecular Genetics, Milan, Italy" + "author_name": "Catherine Ludden", + "author_inst": "Department of Medicine, University of Cambridge, UK" }, { - "author_name": "Marco Cattaneo", - "author_inst": "Health Sciences Department, University of Milan, Milan, Italy" + "author_name": "- The COVID-19 Genomics UK (COG-UK) Consortium", + "author_inst": "" }, { - "author_name": "Maria Orietta Borghi", - "author_inst": "Department of Clinical Sciences and Community Health, University of Milan; Istituto Auxologico Italiano, Milan, Italy" + "author_name": "Deborah Ashby", + "author_inst": "School of Public Health, Imperial College London, UK" }, { - "author_name": "Pier Luigi Meroni", - "author_inst": "IRCCS Istituto Auxologico Italiano" + "author_name": "Christl A Donnelly", + "author_inst": "School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc" + }, + { + "author_name": "Graham Cooke", + "author_inst": "Department of Infectious Disease, Imperial College London, UK Imperial College Healthcare NHS Trust, UK National Institute for Health Research Imperial Biomedic" + }, + { + "author_name": "Wendy Barclay", + "author_inst": "Department of Infectious Disease, Imperial College London, UK" + }, + { + "author_name": "Helen Ward", + "author_inst": "School of Public Health, Imperial College London, UK Imperial College Healthcare NHS Trust, UK National Institute for Health Research Imperial Biomedical Resear" + }, + { + "author_name": "Ara Darzi", + "author_inst": "Imperial College Healthcare NHS Trust, UK National Institute for Health Research Imperial Biomedical Research Centre, UK Institute of Global Health Innovation a" + }, + { + "author_name": "Paul Elliott", + "author_inst": "School of Public Health, Imperial College London, UK Imperial College Healthcare NHS Trust, UK National Institute for Health Research Imperial Biomedical Resear" + }, + { + "author_name": "Steven Riley", + "author_inst": "School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "rheumatology" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2021.08.13.21261968", @@ -616246,55 +615737,127 @@ "category": "respiratory medicine" }, { - "rel_doi": "10.1101/2021.08.10.21261726", - "rel_title": "COVID-19 Projections for K12 Schools in Fall 2021: Significant Transmission without Interventions", + "rel_doi": "10.1101/2021.08.10.21261842", + "rel_title": "Second round statewide survey for estimation of the burden of active infection and anti-SARS-CoV-2 IgG antibodies in the general population of Karnataka, India", "rel_date": "2021-08-11", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.10.21261726", - "rel_abs": "BackgroundMillions of primary school students across the United States are about to return to in-person learning. Amidst circulation of the highly infectious Delta variant, there is danger that without the appropriate safety precautions, substantial amount of school-based spread of COVID-19 may occur.\n\nMethodsWe used an extended Susceptible-Infected-Recovered computational model to estimate the number of new infections during 1 semester among a student population under different assumptions about mask usage, routine testing, and levels of incoming protection. Our analysis considers three levels of incoming protection (30%, 40%, or 50%; denoted as \"low\", \"mid\", or \"high\"). Universal mask usage decreases infectivity by 50%, and weekly testing may occur among 50% of the student population; positive tests prompt quarantine until recovery, with compliance contingent on symptom status.\n\nResultsWithout masking and testing, more than 75% of susceptible students become get infected within three months in all settings. With masking, this values decreases to 50% for \"low\" incoming protection settings (\"mid\"=35%, \"high\"=24%). Testing half the masked population (\"testing\") further drops infections to 22% (16%, 13%).\n\nConclusionWithout interventions in place, the vast majority of susceptible students will become infected through the semester. Universal masking can reduce student infections by 26-78%, and biweekly testing along with masking reduces infections by another 50%. To prevent new infections in the community, limit school absences, and maintain in-person learning, interventions such as masking and testing must be implemented widely, especially among elementary school settings in which children are not yet eligible for the vaccine.", - "rel_num_authors": 9, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.10.21261842", + "rel_abs": "ObjectiveThe second round of the serial cross-sectional sentinel-based population survey to assess active infection, seroprevalence, and their evolution in the general population across Karnataka was conducted. Additionally, a longitudinal study among participants identified as COVID-19 positive in the first survey round was conducted to assess the clinical sensitivity of the testing kit used.\n\nMethodsThe cross-sectional study of 41,228 participants across 290 healthcare facilities in all 30 districts of Karnataka was done among three groups of participants (low, moderate, and high-risk). Consenting participants were subjected to real-time reverse transcription-polymerase chain reaction (RT-PCR) testing, and antibody (IgG) testing.\n\nResultsOverall weighted adjusted seroprevalence of IgG was 15.6% (95% CI: 14.9-16.3), crude IgG prevalence was 15.0% and crude active prevalence was 0.5%. Statewide infection fatality rate (IFR) was estimated as 0.11%, and COVID-19 burden estimated between 26.1 to 37.7% (at 90% confidence). Clinical sensitivity of the IgG ELISA test kit was estimated as [≥]38.9%.\n\nConclusionThe sentinel-based population survey helped identify districts that needed better testing, reporting, and clinical management. The state was far from attaining natural immunity during the survey and hence must step up vaccination coverage and enforce public health measures to prevent the spread of COVD-19.", + "rel_num_authors": 27, "rel_authors": [ { - "author_name": "Yiwei Zhang", - "author_inst": "North Carolina State University" + "author_name": "M Rajagopal Padma", + "author_inst": "Department of Health and Family Welfare Services Karnataka" }, { - "author_name": "Karl Johnson", - "author_inst": "University of North Carolina Gillings School of Global Public Health" + "author_name": "Prameela Dinesh", + "author_inst": "Department of Health and Family Welfare Services Karnataka" }, { - "author_name": "Zhuoting Yu", - "author_inst": "Georgia Institute of Technology, Atlanta, GA, United States of America" + "author_name": "Rajesh Sundaresan", + "author_inst": "Indian Institute of Science, Bengaluru" }, { - "author_name": "Akane Fujimoto", - "author_inst": "Georgia Institute of Technology, Atlanta, GA, United States of America" + "author_name": "Siva Athreya", + "author_inst": "Indian Statistical Institute Bengaluru Centre" }, { - "author_name": "Kristen Hassmiller Lich", - "author_inst": "University of North Carolina" + "author_name": "Shilpa Shiju", + "author_inst": "Department of Health and Family Welfare Services Karnataka" }, { - "author_name": "Julie Ivy", - "author_inst": "North Carolina State University" + "author_name": "Parimala S Maroor", + "author_inst": "Department of Health and Family Welfare Services Karnataka" }, { - "author_name": "Pinar Keskinocak", - "author_inst": "Georgia Institute of Technology" + "author_name": "R Lalitha Hande", + "author_inst": "UNICEF, Bengaluru" }, { - "author_name": "Maria Mayorga", - "author_inst": "North Carolina State University" + "author_name": "Jawaid Akhtar", + "author_inst": "Department of Health and Family Welfare Services Karnataka" }, { - "author_name": "Julie L Swann", - "author_inst": "North Carolina State University" + "author_name": "Trilok Chandra", + "author_inst": "Department of Health and Family Welfare Services Karnataka" + }, + { + "author_name": "Deepa Ravi", + "author_inst": "Indian Institute of Public Health Bengaluru, Public Health Foundation of India" + }, + { + "author_name": "Eunice Lobo", + "author_inst": "Indian Institute of Public Health Bengaluru, Public Health Foundation of India" + }, + { + "author_name": "Yamuna Ana", + "author_inst": "Indian Institute of Public Health Bengaluru, Public Health Foundation of India" + }, + { + "author_name": "Prafulla Shriyan", + "author_inst": "Indian Institute of Public Health Bengaluru, Public Health Foundation of India" + }, + { + "author_name": "Anita Desai", + "author_inst": "National Institute of Mental Health and Neurosciences" + }, + { + "author_name": "Ambica Rangaiah", + "author_inst": "Bangalore Medical College and Research Institute" + }, + { + "author_name": "Ashok Munivenkatappa", + "author_inst": "ICMR National Institute of Virology, Bengaluru Unit" + }, + { + "author_name": "Krishna S", + "author_inst": "Vijayanagar Institute of Medical Sciences" + }, + { + "author_name": "Shantala Gowdara Basawarajappa", + "author_inst": "Bangalore Medical College and Research Institute" + }, + { + "author_name": "H.G. Sreedhara", + "author_inst": "Hassan Institute of Medical Sciences" + }, + { + "author_name": "Siddhesh KC", + "author_inst": "Shimoga Institute of Medical Sciences" + }, + { + "author_name": "Amrutha Kumari B", + "author_inst": "Mysore Medical College and Research Institute" + }, + { + "author_name": "Nawaz Umar", + "author_inst": "Gulbarga Institute of Medical Sciences" + }, + { + "author_name": "Mythri BA", + "author_inst": "Karnataka Institute of Medical Sciences" + }, + { + "author_name": "Mythri KM", + "author_inst": "Institute of Nephro Urology" + }, + { + "author_name": "Mysore Kalappa Sudarshan", + "author_inst": "Department of Health and Family Welfare Services Karnataka" + }, + { + "author_name": "Ravi Vasanthapuram", + "author_inst": "National Institute of Mental Health and Neurosciences" + }, + { + "author_name": "Giridhara R Babu", + "author_inst": "Indian Institute of Public Health Bengaluru, Public Health Foundation of India" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2021.08.10.21261872", @@ -618055,55 +617618,79 @@ "category": "health policy" }, { - "rel_doi": "10.1101/2021.08.09.21261704", - "rel_title": "Antibody mediated neutralization of authentic SARS-CoV-2 B.1.617 variants harboring L452R and T478K/E484Q", + "rel_doi": "10.1101/2021.08.06.21261491", + "rel_title": "Infected surfaces as a source of transmissible material in healthcare settings dealing with COVID 19 patients", "rel_date": "2021-08-10", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.09.21261704", - "rel_abs": "The capacity of convalescent and vaccine-elicited sera and monoclonal antibodies (mAb) to neutralize SARS-CoV-2 variants is currently of high relevance to assess the protection against infections.\n\nWe performed a cell culture-based neutralization assay focusing on authentic SARS-CoV-2 variants B.1.617.1 (Kappa), B.1.617.2 (Delta), B.1.427/B.1.429 (Epsilon), all harboring the spike substitution L452R.\n\nWe found that authentic SARS-CoV-2 variants harboring L452R had reduced susceptibility to convalescent and vaccine-elicited sera and mAbs. Compared to B.1, Kappa and Delta showed a reduced neutralization by convalescent sera by a factor of 8.00 and 5.33, respectively, which constitutes a 2-fold greater reduction when compared to Epsilon. BNT2b2 and mRNA1273 vaccine-elicited sera were less effective against Kappa, Delta, and Epsilon compared to B.1. No difference was observed between Kappa and Delta towards vaccine-elicited sera, whereas convalescent sera were 1.5-fold less effective against Delta, respectively. Both B.1.617 variants Kappa (+E484Q) and Delta (+T478K) were less susceptible to either casirivimab or imdevimab.\n\nIn conclusion, in contrast to the parallel circulating Kappa variant, the neutralization efficiency of convalescent and vaccine-elicited sera against Delta was moderately reduced. Delta was resistant to imdevimab, which however, might be circumvented by a combination therapy with casirivimab together.", - "rel_num_authors": 9, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.06.21261491", + "rel_abs": "The disease COVID-19 has turned out to be a tremendous slayer and has had some of the most devastating impacts on human beings ever seen in history. To overcome this major public health crisis, an understanding of the transmission of the virus underlying this disease is of paramount importance. Evidence suggests that the most common route of transmission for the SARS-CoV-2 virus is likely via direct contact in person-to-person encounter with aerosol droplets. However, the possibility of transmission via contact with fomites from surfaces is a possible route of infection as well. Environmental contamination in rooms with COVID-19 patient has been widely observed due to viral shedding from both asymptomatic and symptomatic patients. Also, in hospitals, SARS-CoV-2 is known to survive on various surfaces for extended periods of time. Because repetitive contact cycles can spread the virus from one surface to the other in healthcare settings, here we evaluated contamination on different types of surfaces commonly found in healthcare settings. Also, based on various datasets, we analyzed the importance of various surfaces in transmission modalities. Based on the findings of this study, decontamination of surfaces that frequently are in touch contact throughout all segments of the healthcare system should constitute an important part of the infection control and prevention of COVID-19. We also recommend the selection of a non-reactive disinfectant for hospital monitors, devices, ventilators and computers so that active surface disinfection can be effected without damage to the devices.", + "rel_num_authors": 15, "rel_authors": [ { - "author_name": "Alexander Wilhelm", - "author_inst": "University Hospital Frankfurt, Goethe University Frankfurt" + "author_name": "Gulab Dattarao Khedkar", + "author_inst": "COVID 19 Testing Laboratory, Paul Hebert Centre for DNA Barcoding and Biodiversity Studies, Dr. Babasaheb Ambedkar Marathwada University, Aurangabad, Maharashtr" }, { - "author_name": "Tuna Toptan", - "author_inst": "University Hospital Frankfurt, Goethe University Frankfurt" + "author_name": "Pramod Bajaj", + "author_inst": "COVID 19 Testing Laboratory, Paul Hebert Centre for DNA barcoding and biodiversity Studies, Dr. Babasaheb Ambedkar Marathwada University, Aurangabad." }, { - "author_name": "Christiane Pallas", - "author_inst": "University Hospital Frankfurt, Goethe University Frankfurt" + "author_name": "Amol Kalyankar", + "author_inst": "COVID 19 testing laboratory, Paul Hebert Centre for DNA barcoding and biodiversity Studies, Dr. Babasaheb Ambedkar Marathwada University, Aurangabad" }, { - "author_name": "Timo Wolf", - "author_inst": "University Hospital Frankfurt, Goethe University Frankfurt" + "author_name": "Rajeshree Deolalikar", + "author_inst": "COVID 19 testing laboratory, Paul Hebert Centre for DNA barcoding and biodiversity Studies, Dr. Babasaheb Ambedkar Marathwada University, Aurangabad" }, { - "author_name": "Udo Goetsch", - "author_inst": "Public Health Department of the City of Frankfurt am Main" + "author_name": "Vikram Khilare", + "author_inst": "Post Graduate Department of Botany, Vasantrao Naik College, CIDCO, Aurangabad" }, { - "author_name": "Rene Gottschalk", - "author_inst": "Public Health Department of the City of Frankfurt am Main" + "author_name": "Aniket Khedkar", + "author_inst": "Department of Computer Science & Information Technology, MIT ADT University, Loni Kalbhor, Pune" }, { - "author_name": "Maria JGT Vehreschild", - "author_inst": "University Hospital Frankfurt, Goethe University Frankfurt" + "author_name": "Rahul Bajaj", + "author_inst": "Sperm Processor Pvt. Ltd. Aurangabad" }, { - "author_name": "Sandra Ciesek", - "author_inst": "University Hospital Frankfurt, Goethe University Frankfurt" + "author_name": "Chandraprakash Khedkar", + "author_inst": "Department of Dairy Microbiology, College of Dairy Technology, Maharashtra Animal Science, Veterinary and Fisheries University, Nagpur." }, { - "author_name": "Marek Widera", - "author_inst": "University Hospital Frankfurt, Goethe University Frankfurt" + "author_name": "Bharathi Prakash", + "author_inst": "Department of Microbiology, University College, Mangalore" + }, + { + "author_name": "Chaitali Khedkar", + "author_inst": "SMBT Medical College, Ghoti, Nasik" + }, + { + "author_name": "Sunil Chavan", + "author_inst": "District Collectorate, Aurangabad" + }, + { + "author_name": "P. Jyosthna", + "author_inst": "Department of Biotechnology, Sri padmvati Womens University, Tirupati" + }, + { + "author_name": "Vidya Niranjan", + "author_inst": "Department of Biotechnology, RV College of Engineering, Bangalore" + }, + { + "author_name": "Manju Jilla", + "author_inst": "Jilla Hospital and Research Institute, Aurangabad" + }, + { + "author_name": "Unmesh Takalkar", + "author_inst": "United SIIGMA hospital and Research Institute, Aurangabad" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "health systems and quality improvement" }, { "rel_doi": "10.1101/2021.08.09.21261290", @@ -619937,107 +619524,27 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.08.08.21261769", - "rel_title": "Anti-CD38 therapy impairs SARS-CoV-2 vaccine response in multiple myeloma patients", + "rel_doi": "10.1101/2021.08.08.21261745", + "rel_title": "Speeding and Traffic-Related Injuries and Fatalities during the 2020 COVID-19 Pandemic: The Cases of Seattle and New York City", "rel_date": "2021-08-09", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.08.21261769", - "rel_abs": "Multiple myeloma (MM) patients are at risk of fatal outcome after SARS-CoV-2 infection. Preliminary data suggest that MM patients have an impaired response to vaccination. This prospective study analyzed the humoral and cellular immune responses to two doses of BNT162b2 in 72 MM patients, including 48 receiving anti-CD38 immunotherapy. Results evidenced that MM patients display lower levels of SARS-CoV-2 specific IgG and IgA antibodies and decreased neutralization of alpha and delta variants when compared to healthy controls. They also showed decreased numbers of circulating IFN{gamma}-producing Spike SARS-CoV-2 specific T lymphocytes. This defective immune response was particularly marked in patients receiving anti-CD38 immunotherapy. Furthermore, a retrospective investigation of MM patients among COVID-19-related death in the Paris area suggested a limited efficacy of BNT162b2 in patients treated with anti-CD38. Overall, these results show a decreased immunogenicity of BNT162b2 in MM patients and stress the need for novel strategies to improve SARS-CoV-2 prophylaxis in immunocompromised individuals.", - "rel_num_authors": 22, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.08.21261745", + "rel_abs": "Despite fewer cars on roads during the COVID-19 pandemic, deaths associated with motor vehicle collisions in New York City and Seattle remained largely unchanged in 2020. Using police data on weekly counts of collisions, we compared trends in 2020 with those of 2019, while controlling for the reduction of traffic volumes and seasonal weather conditions. Results of difference-in-differences estimation suggest that during the early months of the pandemic, or March-May, the incidence rates of severe or fatal injury crashes related to speeding increased by nearly 8 times in Seattle and more than 4 times in New York City. In the rest of 2020, they were still significantly higher than what would be expected in the absence of the pandemic. This research suggests that in similar situations that depress travel demand (e.g., another pandemic), policymakers should formulate plans to reduce speeding which may prevent an upswing in severe injuries and fatalities.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Soledad Henriquez", - "author_inst": "Hopital Cochin" - }, - { - "author_name": "Jeremie Zerbit", - "author_inst": "Hopital Cochin" - }, - { - "author_name": "Timothee Bruel", - "author_inst": "Institut Pasteur" - }, - { - "author_name": "Amani Ouedrani", - "author_inst": "Institut Necker" - }, - { - "author_name": "Delphine Planas", - "author_inst": "Institut Pasteur" - }, - { - "author_name": "Paul Deschamps", - "author_inst": "Hopital Cochin" - }, - { - "author_name": "Isabelle Staropoli", - "author_inst": "Institut Pasteur" - }, - { - "author_name": "Jerome Hadjadj", - "author_inst": "Hopital Cochin" - }, - { - "author_name": "Bruno Varet", - "author_inst": "Hopital Necker-Enfants Malades" - }, - { - "author_name": "Felipe Suarez", - "author_inst": "Hopital Necker-Enfants Malades" - }, - { - "author_name": "Natalia Ermak", - "author_inst": "Hopital Cochin" - }, - { - "author_name": "Didier Bouscary", - "author_inst": "Hopital Cochin" - }, - { - "author_name": "Lise Willems", - "author_inst": "Hopital Cochin" - }, - { - "author_name": "Guillemette Fouquet", - "author_inst": "Hopital Cochin" - }, - { - "author_name": "Justine Decroocq", - "author_inst": "Hopital Cochin" - }, - { - "author_name": "Patricia Franchi", - "author_inst": "Hopital Cochin" - }, - { - "author_name": "Benedicte Deau-Fischer", - "author_inst": "Hopital Cochin" - }, - { - "author_name": "Benjamin Terrier", - "author_inst": "Hopital Cochin" - }, - { - "author_name": "Jerome Tamburini", - "author_inst": "Hopital Cochin" - }, - { - "author_name": "Lucienne Chatenoud", - "author_inst": "Institut Necker" - }, - { - "author_name": "Olivier Schwartz", - "author_inst": "Institut Pasteur" + "author_name": "Haifeng Liao", + "author_inst": "University of Idaho" }, { - "author_name": "Marguerite Vignon", - "author_inst": "Hopital Cochin" + "author_name": "Michael Lowry", + "author_inst": "University of Idaho" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "emergency medicine" }, { "rel_doi": "10.1101/2021.08.07.21261433", @@ -621999,73 +621506,97 @@ "category": "health policy" }, { - "rel_doi": "10.1101/2021.08.03.21261544", - "rel_title": "A booster dose is immunogenic and will be needed for older adults who have completed two doses vaccination with CoronaVac: a randomised, double-blind, placebo-controlled, phase 1/2 clinical trial", + "rel_doi": "10.1101/2021.08.05.21261532", + "rel_title": "Safety and Immunogenicity of CpG 1018 and Aluminium Hydroxide-Adjuvanted SARS-CoV-2 S-2P Protein Vaccine MVC-COV1901: A Large-Scale Double-Blinded, Randomised, Placebo-Controlled Phase 2 Trial", "rel_date": "2021-08-08", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.03.21261544", - "rel_abs": "ImportanceWhether herd immunity through mass vaccination is sufficient to curb SARS-CoV-2 transmission requires an understanding of the duration of vaccine-induced immunity, and the necessity and timing of booster doses. Objective: To evaluate immune persistence of two priming doses of CoronaVac, and immunogenicity and safety of a third dose in healthy adults [≥]60 years. Design, setting, and participants: We conducted a vaccine booster study built on a single-center, randomized, double-blind phase 1/2 trial of the two-dose schedule of CoronaVac among healthy adults[≥]60 years in Hebei, China. We examined neutralizing antibody titres six months or more after the second dose in all participants. We provided a third dose to 303 participants recruited in phase 2 trial to assess their immune responses.\n\nInterventionsTwo formulations (3 g, and 6 g) were used in phase 1 trial, and an additional formulation of 1.5 g was used in phase 2 trial. All participants were given two doses 28 days apart and followed up 6 months after the second dose. Participants in phase 2 received a third dose 8 months after the second dose.\n\nMain outcomes and measuresGeometric mean titres (GMT) of neutralizing antibodies to live SARS-CoV-2 and adverse events were assessed at multiple time points following vaccination.\n\nResultsNeutralizing antibody titres dropped below the seropositive cutoff of 8 at 6 months after the primary vaccination in all vaccine groups in the phase 1/2 trial. A third dose given 8 months or more after the second dose significantly increased neutralizing antibody levels. In the 3 g group (the licensed formulation), GMT increased to 305 [95%CI 215.3-432.0] on day 7 following the third dose, an approximately 7-fold increase compared with the GMT 28 days after the second dose. All solicited adverse reactions reported within 28 days after a booster dose were of grade 1 or 2 severity.\n\nConclusion and relevanceNeutralizing antibody titres declined substantially six months after two doses of CoronaVac among older adults. A booster dose rapidly induces robust immune responses. This evidence could help policymakers determine the necessity and the timing of a booster dose for older adults.\n\nTrial registrationClinicalTrials.gov (NCT04383574).", - "rel_num_authors": 14, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.05.21261532", + "rel_abs": "BackgroundWe have assessed the safety and immunogenicity of the COVID-19 vaccine MVC-COV1901, a recombinant protein vaccine containing prefusion-stabilized spike protein S-2P adjuvanted with CpG 1018 and aluminium hydroxide.\n\nMethodsThis is a phase 2, prospective, randomised, double-blind, placebo-controlled, and multi-centre study to evaluate the safety, tolerability, and immunogenicity of the SARS-CoV-2 vaccine candidate MVC-COV1901. The study comprised 3,844 participants of [≥] 20 years who were generally healthy or with stable pre-existing medical conditions. The study participants were randomly assigned in a 6:1 ratio to receive either MVC-COV1901 containing 15 g of S-2P protein or placebo containing saline. Participants received two doses of MVC-COV1901 or placebo, administered 28 days apart via intramuscular injection. The primary outcomes were to evaluate the safety, tolerability, and immunogenicity of MVC-COV1901 from Day 1 (the day of first vaccination) to Day 57 (28 days after the second dose). Immunogenicity of MVC-COV1901 was assessed through geometric mean titres (GMT) and seroconversion rates (SCR) of neutralising antibody and antigen-specific immunoglobulin. This clinical trial is registered at ClinicalTrials.gov: NCT04695652.\n\nFindingsFrom the start of this phase 2 trial to the time of interim analysis, no vaccine-related Serious Adverse Events (SAEs) were recorded. The most common solicited adverse events across all study participants were pain at the injection site (64%), and malaise/fatigue (35%). Fever was rarely reported (<1%). For all participants in the MVC-COV1901 group, at 28 days after the second dose against wild type SARS-CoV-2 virus, the GMT was 662{middle dot}3 (408 IU/mL), the GMT ratio was 163{middle dot}2, and the seroconversion rate was 99{middle dot}8%.\n\nInterpretationMVC-COV1901 shows good safety profiles and promising immunogenicity responses. The current data supports MVC-COV1901 to enter phase 3 efficacy trials and could enable regulatory considerations for Emergency Use Authorisation (EUA).\n\nFundingMedigen Vaccine Biologics Corporation and Taiwan Centres for Disease Control.", + "rel_num_authors": 20, "rel_authors": [ { - "author_name": "Minjie Li", - "author_inst": "Hebei Center for Disease Control and Prevention, Shijiazhuang, China" + "author_name": "Szu-Min Hsieh", + "author_inst": "Division of Infectious Diseases, Department of Internal Medicine, National Taiwan University Hospital and College of Medicine, National Taiwan University, Taiwa" }, { - "author_name": "Juan Yang", - "author_inst": "School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China" + "author_name": "Ming-Che Liu", + "author_inst": "Clinical Research Centre, Taipei Medical University Hospital, Taipei, Taiwan" }, { - "author_name": "Lin Wang", - "author_inst": "R&D Department, Sinovac Life Sciences Co., Ltd., Beijing, China" + "author_name": "Yen-Hsu Chen", + "author_inst": "Division of Infectious Diseases, Department of Internal Medicine, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan" }, { - "author_name": "Qianhui Wu", - "author_inst": "School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China" + "author_name": "Wen-Sen Lee", + "author_inst": "Division of Infectious Disease, Department of Internal Medicine, Taipei Municipal Wan Fang Hospital, Taipei Medical University" }, { - "author_name": "Zhiwei Wu", - "author_inst": "Hebei Center for Disease Control and Prevention, Shijiazhuang, China" + "author_name": "Shinn-Jang Hwang", + "author_inst": "Department of Family Medicine, Taipei Veterans General Hospital and National Yang Ming Chiao Tung University School of Medicine, Taipei Taiwan" }, { - "author_name": "Wen Zheng", - "author_inst": "School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China" + "author_name": "Shu-Hsing Cheng", + "author_inst": "Department of Infectious Diseases, Taoyuan General Hospital, Ministry of Health and Welfare, Taoyuan, Taiwan" }, { - "author_name": "Lei Wang", - "author_inst": "Department of Clinical Research, Sinovac Biotech Co., Ltd., Beijing, China" + "author_name": "Wen-Chien Ko", + "author_inst": "Department of Internal Medicine, National Cheng Kung University Hospital and Department of Medicine, College of Medicine, National Cheng Kung University, Tainan" }, { - "author_name": "Wanying Lu", - "author_inst": "School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China" + "author_name": "Kao-Pin Hwang", + "author_inst": "School of Medicine, China Medical University Hospital and Children Hospital, China Medical University, Taichung, Taiwan" }, { - "author_name": "Xiaowei Deng", - "author_inst": "School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China" + "author_name": "Ning-Chi Wang", + "author_inst": "Tri-Service General Hospital, Taipei, Taiwan" }, { - "author_name": "Cheng Peng", - "author_inst": "School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China" + "author_name": "Yu-Lin Lee", + "author_inst": "Department of Internal Medicine, Changhua Christian Hospital, Changhua County, Taiwan" }, { - "author_name": "Bihua Han", - "author_inst": "Hebei Center for Disease Control and Prevention, Shijiazhuang, China" + "author_name": "Yi-Ling Lin", + "author_inst": "Institute of Biomedical Sciences, Academia Sinica, Taipei, Taiwan" }, { - "author_name": "Yuliang Zhao", - "author_inst": "Hebei Center for Disease Control and Prevention, Shijiazhuang, China" + "author_name": "Shin-Ru Shih", + "author_inst": "Research Centre for Emerging Viral Infections, College of Medicine, Chang Gung University, Taoyuan City, Taiwan" }, { - "author_name": "Hongjie Yu", - "author_inst": "School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China" + "author_name": "Chung-Guei Huang", + "author_inst": "Research Centre for Emerging Viral Infections, College of Medicine, Chang Gung University, Taoyuan City, Taiwan" }, { - "author_name": "Weidong Yin", - "author_inst": "Sinovac Biotech Co., Ltd., Beijing, China" + "author_name": "Chun-Che Liao", + "author_inst": "Institute of Biomedical Sciences, Academia Sinica, Taipei, Taiwan" + }, + { + "author_name": "Jian-Jong Liang", + "author_inst": "Institute of Biomedical Sciences, Academia Sinica, Taipei, Taiwan" + }, + { + "author_name": "Chih-Shin Chang", + "author_inst": "Biomedical Translation Research Centre, Academia Sinica, Taipei, Taiwan" + }, + { + "author_name": "Charles Chen", + "author_inst": "Medigen Vaccine Biologics Corp., Taiwan" + }, + { + "author_name": "Chia En Lien", + "author_inst": "Medigen Vaccine Biologics Corp., Taiwan" + }, + { + "author_name": "I-Chen Tai", + "author_inst": "Medigen Vaccine Biologics Corp., Taiwan" + }, + { + "author_name": "Tzou-Yien Lin", + "author_inst": "Department of Paediatrics, Chang Gung Memorial Hospital, Taoyuan City, Taiwan" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -623929,37 +623460,57 @@ "category": "pediatrics" }, { - "rel_doi": "10.1101/2021.08.05.21261675", - "rel_title": "Determinants of the COVID-19 Vaccine Hesitancy Spectrum", + "rel_doi": "10.1101/2021.08.05.21261671", + "rel_title": "Prevalence and correlates of SARS-CoV-2 seropositivity among people who inject drugs in the San Diego-Tijuana border region", "rel_date": "2021-08-07", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.05.21261675", - "rel_abs": "Polls report nearly one-third of the United States population is skeptical or opposed to getting the COVID-19 vaccine. Most of these polls, as well as the scientific research that has been conducted on vaccine hesitancy, was done prior to vaccine eligibility opening to all adults. Now that COVID-19 vaccines are widely available, further research is needed to understand the factors contributing to vaccine intentions across the vaccine hesitancy spectrum. This study conducted an online survey using the Social Science Research Solution (SSRS) Opinion Panel web panelists, representative of U.S. adults age 18 and older who use the internet, with an oversample of rural-dwelling and minority populations between April 8 and April 22, 2021- as vaccine eligibility opened to the country. We examined the relationship between COVID-19 exposure and socio-demographics with vaccine intentions [eager-to-take, wait-and-see, undecided, refuse] among the unvaccinated using multinomial logistic regressions [ref: fully/partially vaccinated]. Results showed vaccine intentions varied by demographic characteristics and risk exposures during the period that eligibility for the vaccine was extended to all adults.\n\nFunding statementFunding for this research was provided by a grant from the National Science Foundation (Grant #2049886). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.05.21261671", + "rel_abs": "BackgroundPeople who inject drugs may be at elevated SARS-CoV-2 risk due to their living conditions and/or exposures when seeking or using drugs. No study to date has reported upon risk factors for SARS-CoV-2 infection among people who inject drugs or sex workers.\n\nMethods and FindingsBetween October, 2020 and June, 2021, participants aged [≥]18 years from San Diego, California, USA and Tijuana, Baja California, Mexico who injected drugs within the last month underwent interviews and testing for SARS-CoV-2 RNA and antibodies. Binomial regressions identified correlates of SARS-CoV-2 seropositivity. Of 386 participants, SARS-CoV-2 seroprevalence was 36.3% (95% CI: 31.5%-41.1%); 92.1% had detectable IgM antibodies. Only 37.5% had previously been tested. Seroprevalence did not differ by country of residence. None tested RNA-positive. Most (89.5%) reported engaging in [≥]1 protective behavior [e.g., facemasks (73.5%), social distancing (46.5%), or increasing handwashing/sanitizers (22.8%)]. In a multivariate model controlling for sex, older age, and Hispanic/Latinx/Mexican ethnicity were independently associated with SARS-CoV-2 seropositivity, as was engaging in sex work (AdjRR: 1.63; 95% CI: 1.18-2.27) and having been incarcerated in the past six months (AdjRR: 1.49; 95% CI: 0.97-2.27). Presence of comorbidities and substance using behaviors were not associated with SARS-CoV-2 seropositivity.\n\nConclusionsThis is the first study to show that sex work and incarceration were independently associated with SARS-CoV-2 infection. Despite engaging in protective measures, over one-third had evidence of infection, reinforcing the need for a coordinated binational response. Risk mitigation and vaccination is especially needed among older and Hispanic people who inject drugs and those with less agency to protect themselves, such as those who are sex workers or incarcerated.", + "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Rachael Piltch-Loeb", - "author_inst": "NYU Global Public Health" + "author_name": "Steffanie Ann Strathdee", + "author_inst": "University of California San Diego" }, { - "author_name": "Diana Silver", - "author_inst": "NYU Global Public Health" + "author_name": "Daniela Abramovitz", + "author_inst": "University of California San Diego" }, { - "author_name": "Yeerae Kim", - "author_inst": "NYU Global Public Health" + "author_name": "Alicia Harvey-Vera", + "author_inst": "University of California San Diego" }, { - "author_name": "Hope Norris", - "author_inst": "NYU Global Public Health" + "author_name": "Carlos Vera", + "author_inst": "University of California San Diego" }, { - "author_name": "Elizabeth McNeill", - "author_inst": "NYU Global Public Health" + "author_name": "Gudelia Rangel", + "author_inst": "El Colegio de la Frontera Norte" }, { - "author_name": "David Abramson", - "author_inst": "NYU Global Public Health" + "author_name": "Irina Artamonova", + "author_inst": "University of California San Diego" + }, + { + "author_name": "Antoine Chaillon", + "author_inst": "University of California San Diego" + }, + { + "author_name": "Caroline Ignacio", + "author_inst": "University of California San Diego" + }, + { + "author_name": "Alheli Calderon", + "author_inst": "University of California San Diego, San Diego State University" + }, + { + "author_name": "Natasha K. Martin", + "author_inst": "University of California San Diego" + }, + { + "author_name": "Thomas L. Patterson", + "author_inst": "University of California San Diego" } ], "version": "1", @@ -625655,67 +625206,79 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2021.08.04.21261618", - "rel_title": "Clinical characteristics and outcomes of COVID-19 breakthrough infections among vaccinated patients with systemic autoimmune rheumatic diseases", + "rel_doi": "10.1101/2021.08.04.21261613", + "rel_title": "Strategies to Estimate Prevalence of SARS-CoV-2 Antibodies in a Texas Vulnerable Population: Results from Phase I of the Texas Coronavirus Antibody REsponse Survey (TX CARES)", "rel_date": "2021-08-05", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.04.21261618", - "rel_abs": "ObjectiveTo describe the characteristics of COVID-19 vaccine breakthrough infections among systemic autoimmune rheumatic disease (SARD) patients.\n\nMethodsWe identified SARDs patients in a large healthcare system with COVID-19 vaccination [≥]14 days prior to a positive SARS-CoV-2 molecular test. Details of the patients SARD, vaccination status, and COVID-19 infection were extracted.\n\nResultsOf 340 confirmed COVID-19 infections among SARDs patients between December 11th, 2020 (date of first COVID-19 vaccine approval in the US) and July 30th, 2021, we identified 16 breakthrough infections. Seven (44%) received the Pfizer-BioNtech vaccine, five (31%) received the Moderna vaccine, and four (25%) received the Janssen/Johnson & Johnson vaccine. The most common SARDs included rheumatoid arthritis (6, 38%), inflammatory myopathy (3, 19%), and systemic lupus erythematosus (3, 19%). Rituximab (5, 31%), glucocorticoids (4, 25%), and mycophenolate mofetil (4, 25%) were the most frequent treatments. Among the breakthrough infections, 15 (93%) were symptomatic, six (38%) were hospitalized, one (6%) required mechanical ventilation, and two (13%) died.\n\nConclusionsSymptomatic, including severe, breakthrough infections were observed in SARDs patients; many were on treatments associated with attenuated antibody responses to vaccination. Further studies are needed to determine the rate of breakthrough infection associated with SARD treatments and other features.\n\nKey messagesO_ST_ABSWhat is already known about this subject?C_ST_ABSBreakthrough infections following COVID-19 vaccination are expected but some patients with systemic autoimmune rheumatic diseases (SARDs) may be at higher risk because of blunted antibody responses to vaccination associated with rheumatic disease treatments and other factors that remain poorly understood.\n\nWhat does this study add?We identify and describe 16 COVID-19 vaccine breakthrough infections within the Mass General Brigham system between December 11th, 2020 and June 26th, 2021. The vast majority of cases were symptomatic and two were fatal.\n\nHow might this impact on clinical practice or future developments?This study complements observations regarding the attenuated antibody response to COVID-19 vaccination in patients with SARDs by identifying serious clinical outcomes from breakthrough infections in patients receiving DMARDs that have been reported to have blunted vaccine responses. Our study identifies characteristics of COVID-19 breakthrough infections that may guide the prioritization of booster vaccines and other risk-mitigating strategies in patients with SARDs.", - "rel_num_authors": 12, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.04.21261613", + "rel_abs": "IntroductionSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and immunity remains uncertain in populations. The state of Texas ranks 2nd in infection with over 2.71 million cases and has seen a disproportionate rate of death across the state. The TX CARES project was funded by the state of Texas to estimate the prevalence of SARS-CoV-2 antibody status in children and adults.\n\nMaterials and MethodsThe TX CARES (Texas Coronavirus Antibody Response Survey) is an ongoing prospective population-based convenience sample from the Texas general population that commenced in October 2020. Volunteer participants are recruited across the state to participate in a 3-time point data collection TX CARES to assess antibody response over time. We use the Roche Elecsys(R) Anti-SARS-CoV-2 Immunoassay to determine SARS-CoV-2 antibody status.\n\nResultsThe crude antibody positivity prevalence in Phase I was 26.1% (80/307). The fully adjusted seroprevalence of the sample was 31.5%. Specifically, 41.1% of males and 21.9% of females were seropositive. For age categories, 33.5% of those 18-34; 24.4% of those 35-44; 33.2% of those 45-54; and 32.8% of those 55+ were seropositive. In this sample,42.2% (89/211) of those negative for the antibody test reported having had a COVID-19 test.\n\nConclusionsIn this survey we enrolled and analyzed data for 319 participants, demonstrating a high survey and antibody test completion rate, and ability to implement a questionnaire and SARS-CoV-2 antibody testing within FQHC clinical settings. We were also able to determine our capability to estimate the cross-sectional seroprevalence within Texass FQHC clinical settings. The crude positivity prevalence for SARS-CoV-2 antibodies in this sample was 26.1% indicating potentially high exposure to COVID-19 for FQHC clinic employees and patients. These methods are being used to guide the completion of a large longitudinal survey in the state of Texas with implications for practice and population health.", + "rel_num_authors": 15, "rel_authors": [ { - "author_name": "Claire Cook", - "author_inst": "Massachusetts General Hospital" + "author_name": "Melissa A Valerio-Shewmaker PhD, MPH", + "author_inst": "University of Texas Health Science Center Houston, School of Public Health, Brownsville Campus, Brownsville, TX, USA" }, { - "author_name": "Naomi Patel", - "author_inst": "Massachusetts General Hospital" + "author_name": "Stacia M Desantis PhD", + "author_inst": "University of Texas Health Science Center Houston, School of Public Health, Houston Campus, Houston, TX, USA" }, { - "author_name": "Kristin D'Silva", - "author_inst": "Massachusetts General Hospital" + "author_name": "Michael D Swartz PhD", + "author_inst": "University of Texas Health Science Center Houston, School of Public Health, Houston Campus, Houston, TX, USA" }, { - "author_name": "Tiffany T-Y Hsu", - "author_inst": "Brigham and Women's Hospital" + "author_name": "Ashraf Yaseen PhD", + "author_inst": "University of Texas Health Science Center Houston, School of Public Health, Houston Campus, Houston, TX, USA" }, { - "author_name": "Michael DiIorio", - "author_inst": "Brigham and Women's Hospital" + "author_name": "Michael O Gonzalez MS", + "author_inst": "University of Texas Health Science Center Houston, School of Public Health, Houston Campus, Houston, TX, USA" }, { - "author_name": "Lauren Prisco", - "author_inst": "Brigham and Women's Hospital" + "author_name": "Harold W Kohl PhD", + "author_inst": "University of Texas Health Science Center Houston, School of Public Health, Austin Campus, Austin, TX, USA" }, { - "author_name": "Lily Martin", - "author_inst": "Brigham and Women's Hospital" + "author_name": "Steven H Kelder PhD", + "author_inst": "University of Texas Health Science Center Houston, School of Public Health, Austin Campus, Austin, TX, USA" }, { - "author_name": "Kathleen M.M. Vanni", - "author_inst": "Brigham and Women's Hospital" + "author_name": "Sarah M Messiah PhD", + "author_inst": "University of Texas Health Science Center Houston, School of Public Health, Dallas Campus, Dallas, TX, USA" }, { - "author_name": "Alessandra Zaccardelli", - "author_inst": "Brigham and Women's Hospital" + "author_name": "Kimberly A Aguillard DrPH", + "author_inst": "University of Texas Health Science Center Houston, School of Public Health, Houston Campus, Houston, TX, USA" }, { - "author_name": "Derrick J. Todd", - "author_inst": "Brigham and Women's Hospital" + "author_name": "Camille J Breaux BA", + "author_inst": "University of Texas Health Science Center Houston, School of Public Health, Houston Campus, Houston, TX, USA" }, { - "author_name": "Jeffrey A Sparks", - "author_inst": "Brigham and Women's Hospital" + "author_name": "Lequing Wu MS", + "author_inst": "University of Texas Health Science Center Houston, School of Public Health, Houston Campus, Houston, TX, USA" }, { - "author_name": "Zachary S Wallace", - "author_inst": "Massachusetts General Hospital" + "author_name": "David Lakey MD", + "author_inst": "University of Texas System, Austin, TX, USA" + }, + { + "author_name": "Jennifer Shuford MD, MPH", + "author_inst": "Texas Department of State Health Services, Austin, TX USA" + }, + { + "author_name": "Stephen Pont MD, MPH", + "author_inst": "Texas Department of State Health Services, Austin, TX USA" + }, + { + "author_name": "Eric Boerwinkle PhD", + "author_inst": "University of Texas Health Science Center Houston, School of Public Health, Houston Campus, Houston, TX, USA" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "rheumatology" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2021.07.30.21261339", @@ -627877,105 +627440,37 @@ "category": "occupational and environmental health" }, { - "rel_doi": "10.1101/2021.08.03.21261441", - "rel_title": "A single intramuscular injection of monoclonal antibody MAD0004J08 induces in healthy adults SARS-CoV-2 neutralising antibody titres exceeding those induced by infection and vaccination", + "rel_doi": "10.1101/2021.08.03.21261414", + "rel_title": "Azithromycin in patients with Covid-19; a systematic review and metanalysis", "rel_date": "2021-08-04", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.03.21261441", - "rel_abs": "BackgroundThe emerging threat represented by SARS-CoV-2 variants, demands the development of therapies for better clinical management of COVID-19. MAD0004J08 is an extremely potent Fc-engineered monoclonal antibody (mAb) able to neutralise in vitro all current SARS-CoV-2 variants of concern (VoCs). This ongoing study, evaluates safety, pharmacokinetics and SARS-CoV-2 sera neutralization effect of MAD0004J08 when administered as single dose intramuscularly in healthy adults.\n\nMethodWe conducted a dose escalation study with sequential enrolment of three cohorts, each with an increasing dose level of MAD0004J08 (48mg, 100mg and 400mg). Within each cohort, 10 young healthy adults were randomized with 4:1 ratio to a single intramuscular (i.m.) injection of MAD0004J08 or placebo. The primary endpoint is the proportion of subjects with severe and/or serious treatment emergent adverse events (TEAEs) within 7 days post-treatment. Secondary endpoints reported in this paper are the proportion of subjects with solicited TEAEs up 7 days post dosing, MAD0004J08 serum concentrations and neutralising activity versus the original SARS-COV-2 Wuhan virus at different timepoints post-dosing. As post-hoc analyses, we compared the sera neutralising titres of subjects who received MAD0004J08 with those of people that had received the COVID-19 BNT162b2 mRNA vaccine in the previous sixty days (n=10) and COVID-19 convalescent patients (n=20), and assessed serum neutralisation activity against the B.1.1.7 (alpha), B.1.351 (beta) and B.1.1.248 (gamma) SARS-CoV-2 variants of concern.\n\nFindingsA total of 30 subjects, 10 per cohort, were enrolled and randomized. Data up to 30 days were available and analysed in this report. No severe TEAEs were reported in any of the cohorts in the 7 days post-treatment. MAD0004J08 was detected in the sera of treated subjects within few hours post-administration and reached almost maximal levels on day 8. The geometric mean neutralising titres (GMT) assessed against the original Wuhan virus peaked on day 8 and ranged 226 - 905, 905 - 2,560, and 1,280 - 5,120 for cohort 1, 2 and 3 respectively. The sera neutralising GMT in MAD0004J08 treated subjects in all the three cohorts were found to be 1{middle dot}5-54{middle dot}5-fold higher compared to sera from convalescent patients and 1{middle dot}83- 76{middle dot}4-fold higher compared to sera from COVID-19 vaccinees. Finally, GMT in MAD0004J08 treated subjects showed high neutralising titres versus the B.1.1.7 (alpha), B.1.351 (beta) and B.1.1.248 (gamma) SARS-CoV-2 VoCs.\n\nInterpretationA single dose administration of MAD0004J08 via i.m. route is safe and well tolerated and results in a rapid systemic distribution of the MAD0004J08 and sera neutralising titres higher than COVID-19 convalescent and vaccinated subjects. A single dose administration of MAD0004J08 is also sufficient to effectively neutralise major SARS-CoV-2 variants of concern. Based on these results, a Phase 2-3 trial is ongoing to further assess the safety, dosage, and efficacy of MAD0004J08 in asymptomatic or mild-moderate symptomatic COVID-19 patients.\n\nFundingEU Malaria Fund, Ministero dello Sviluppo Economico, Ministero della Salute, Regione Toscana, Toscana Life Sciences Sviluppo and European Research Council.\n\nResearch in contextO_ST_ABSEvidence before this studyC_ST_ABSWe searched PUBMED, MEDLINE and MedRxiv for clinical trials, meta-analyses and randomized controlled trials evaluating the antibody neutralization titres vs. different SARS-CoV-2 variants of concern obtained from subjects who received monoclonal antibodies for the treatment of COVID-19 using the following search terms: (\"COVID-19\" OR \"SARS-CoV-2\") AND (\"monoclonal antibody\" OR \"neutralising antibody\") AND (\"variants\" OR \"variants of concern\"). No relevant studies were identified.\n\nAdded value of this studyThis is the first human study assessing safety, PK and neutralising potential of MAD0004J08, a monoclonal antibody against SARS-CoV-2 wild type Wuhan virus and variants of concern, administered intramuscularly at low dosages (48, 100 and 400 mg). MAD0004J08 showed to be safe and well tolerated in the tested dose range. Anti-spike antibodies were detected in the sera of tested SARS-CoV-2 negative healthy adults few hours post-injection. In addition, the sera obtained from MAD0004J08treated subjects, showed to have high neutralisation titres against the Wuhan virus, the B.1.1.7 (alpha), B.1.351 (beta) and B.1.1.248 (gamma) variants of concern.\n\nImplications of all the available evidenceA potent monoclonal antibody such as MAD0004J08, capable of neutralising multiple variants of concern of SARS-CoV-2 rapidly and long lastingly when given as a single intramuscular injection. The antibody, presently tested in a phase 2-3 efficacy trial, can be a major advancement in the prophylaxis and clinical management of COVID-19, because of its broad spectrum, ease of use in non-hospital settings and economic sustainability.", - "rel_num_authors": 22, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.03.21261414", + "rel_abs": "BackgroundAzithromycin (AZM) has been widely used in the management of Covid-19. However, the evidence on its actual effects remains disperse and difficult to apply in clinical settings. This systematic review and metanalysis summarizes the available evidence to date on the beneficial and adverse effect of AZM in patients with Covid-19.\n\nMethodsThe PRISMA 2020 statement criteria were followed. Randomized controlled trials (RCTs) and observational studies comparing clinical outcomes of patients treated, and not treated, with AZM, indexed until the 5th of July 2021, were searched in PubMed, Embase, The Web of Science, Scopus, The Cochrane Central Register of Controlled Trials, and MedRXivs. We used Random-effects models to estimate pooled effect size from aggregate data.\n\nResultsThe initial search produced 4950 results. Finally, 16 studies, five RCTs and 11 with an observational design, with a total of 22984 patients, were included. The metanalysis showed no difference in mortality for those treated, or not, with AZM, OR: 0.95 (0.79-1.13). There was also no significant difference for those treated, and not, with AZM in need for hospital admission or time to admission from ambulatory settings, clinical severity, need for intensive care, or adverse effects.\n\nConclusionsThese results presented in this review do not support the use of AZM in the management of Covid-19. They also show that any harm caused to the patient who received it is unlikely. Future research on treatment for patients with Covid-19 may need to focus on other drugs.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Simone Lanini", - "author_inst": "Istituto Nazionale per le Malattie Infettive Lazzaro Spallanzani, IRCCS, Rome, Italy" - }, - { - "author_name": "Stefano Milleri", - "author_inst": "Centro Ricerche Cliniche di Verona, University and Hospital Trust of Verona, Verona, Italy" - }, - { - "author_name": "Emanuele Andreano", - "author_inst": "Monoclonal Antibody Discovery (MAD) Lab, Fondazione Toscana Life Sciences, Siena, Italy" - }, - { - "author_name": "Sarah Nosari", - "author_inst": "AchilleS Vaccine, Siena, Italy" - }, - { - "author_name": "Ida Paciello", - "author_inst": "Monoclonal Antibody Discovery (MAD) Lab, Fondazione Toscana Life Sciences, Siena, Italy" - }, - { - "author_name": "Giulia Piccini", - "author_inst": "VisMederi S.r.l, Siena, Italy" - }, - { - "author_name": "Alessandra Gentili", - "author_inst": "CROss Research, Mendrisio, Switzerland" - }, - { - "author_name": "Adhuna Phogat", - "author_inst": "Fondazione Toscana Life Sciences, Siena, Italy" - }, - { - "author_name": "Inesa Hyseni", - "author_inst": "VisMederi S.r.l, Siena, Italy; VisMederi Research S.r.l, Siena, Italy" - }, - { - "author_name": "Margherita Leonardi", - "author_inst": "VisMederi S.r.l, Siena, Italy; VisMederi Research S.r.l, Siena, Italy" - }, - { - "author_name": "Alessandro Torelli", - "author_inst": "VisMederi S.r.l, Siena, Italy" - }, - { - "author_name": "Emanuele Montomoli", - "author_inst": "VisMederi S.r.l, Siena, Italy; VisMederi Research S.r.l, Siena, Italy; Department of Molecular and Developmental Medicine, University of Siena, Siena, Italy" - }, - { - "author_name": "Andrea Paolini", - "author_inst": "Fondazione Toscana Life Sciences, Siena, Italy; Toscana Life Sciences Sviluppo, Siena, Italy" - }, - { - "author_name": "Andrea Frosini", - "author_inst": "Fondazione Toscana Life Sciences, Siena, Italy" - }, - { - "author_name": "Andrea Antinori", - "author_inst": "Istituto Nazionale per le Malattie Infettive Lazzaro Spallanzani, IRCCS, Rome, Italy" - }, - { - "author_name": "Emanuele Nicastri", - "author_inst": "Istituto Nazionale per le Malattie Infettive Lazzaro Spallanzani, IRCCS, Rome, Italy" - }, - { - "author_name": "Enrico Girardi", - "author_inst": "Istituto Nazionale per le Malattie Infettive Lazzaro Spallanzani, IRCCS, Rome, Italy" - }, - { - "author_name": "Maria Maddalena Plazzi", - "author_inst": "Istituto Nazionale per le Malattie Infettive Lazzaro Spallanzani, IRCCS, Rome, Italy" + "author_name": "Luis Ayerbe", + "author_inst": "Centre of Primary Care. Queen Mary University of London UK" }, { - "author_name": "Giuseppe Ippolito", - "author_inst": "Istituto Nazionale per le Malattie Infettive Lazzaro Spallanzani, IRCCS, Rome, Italy" + "author_name": "Ivo Forgnone", + "author_inst": "Canal de Panama Primary Care Centre, Madrid, Spain" }, { - "author_name": "Francesco Vaia", - "author_inst": "Istituto Nazionale per le Malattie Infettive Lazzaro Spallanzani, IRCCS, Rome, Italy" + "author_name": "Carlos Risco-Risco", + "author_inst": "Department of Internal Medicine. HM Sanchinarro, University Hospital. Madrid Spain" }, { - "author_name": "Giovanni Della Cioppa", - "author_inst": "Clinical R&D Consultants, Rome, Italy" + "author_name": "Maria Perez-Pinar", + "author_inst": "Carnarvon Medical Centre. Southend on Sea. UK" }, { - "author_name": "Rino Rappuoli", - "author_inst": "Monoclonal Antibody Discovery (MAD) Lab, Fondazione Toscana Life Sciences, Siena, Italy; Department of Biotechnology, Chemistry and Pharmacy, University of Sien" + "author_name": "Salma Ayis", + "author_inst": "School of Population Health and Environmental Sciences, King's College London, London, UK" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -630103,51 +629598,35 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.07.30.21261392", - "rel_title": "Existing human mobility data sources poorly predicted the spatial spread of SARS-CoV-2 in Madagascar", + "rel_doi": "10.1101/2021.08.01.454605", + "rel_title": "The spike protein of SARS-CoV-2 induces endothelial inflammation through integrin \u03b15\u03b21 and NF-\u03baB", "rel_date": "2021-08-02", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.30.21261392", - "rel_abs": "For emerging epidemics such as the COVID-19 pandemic, quantifying travel is a key component of developing accurate predictive models of disease spread to inform public health planning. However, in many LMICs, traditional data sets on travel such as commuting surveys as well as non-traditional sources such as mobile phone data are lacking, or, where available, have only rarely been leveraged by the public health community. Evaluating the accuracy of available data to measure transmission-relevant travel may be further hampered by limited reporting of suspected and laboratory confirmed infections. Here, we leverage case data collected as part of a COVID-19 dashboard collated via daily reports from the Malagasy authorities on reported cases of SARS-CoV-2 across the 22 regions of Madagascar. We compare the order of the timing of when cases were reported with predictions from a SARS-CoV-2 metapopulation model of Madagascar informed using various measures of connectivity including a gravity model based on different measures of distance, Internal Migration Flow data, and mobile phone data. Overall, the models based on mobile phone connectivity and the gravity-based on Euclidean distance best predicted the observed spread. The ranks of the regions most remote from the capital were more difficult to predict but interestingly, regions where the mobile phone connectivity model was more accurate differed from those where the gravity model was most accurate. This suggests that there may be additional features of mobility or connectivity that were consistently underestimated using all approaches, but are epidemiologically relevant. This work highlights the importance of data availability and strengthening collaboration among different institutions with access to critical data - models are only as good as the data that they use, so building towards effective data-sharing pipelines is essential.", - "rel_num_authors": 8, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2021.08.01.454605", + "rel_abs": "Vascular endothelial cells (EC) form a critical interface between blood and tissues that maintains whole-body homeostasis. In COVID-19, disruption of the EC barrier results in edema, vascular inflammation, and coagulation, the hallmarks of the severe disease. However, the mechanisms by which EC are dysregulated in COVID-19 are unclear. Here, we show that the spike protein of SARS-CoV-2 alone activates the EC inflammatory phenotype in a manner dependent on integrin 5{beta}1 signaling. Incubation of human umbilical vein EC with whole spike, its receptor-binding domain, or the integrin-binding tripeptide RGD induced the nuclear translocation of NF-{kappa}B and enhanced the expression of leukocyte adhesion molecules VCAM1 and ICAM1, the adhesion of peripheral blood leukocytes, and the permeability of the monolayer. Inhibitors of integrin 5{beta}1 activation prevented these effects. We suggest that the spike protein, through its RGD motif in the receptor-binding domain, binds to integrin 5{beta}1 in EC to activate Rho GTPases, eNOS pathways, and the NF-{kappa}B gene expression program responsible for vascular leakage and leukocyte infiltration, respectively. These findings uncover a new direct action of SARS-CoV-2 on EC dysfunction and introduce integrin 5{beta}1 as a promising target for treating vascular inflammation in COVID-19.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Tanjona Ramiadantsoa", - "author_inst": "Department of Life Science, University of Fianarantsoa, Madagascar & Department of Mathematics, University of Fianarantsoa, Madagascar & 3. Department of Integ" - }, - { - "author_name": "C. Jessica E. Metcalf", - "author_inst": "Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ, USA & Princeton School of Public and International Affairs, Princeton Unive" - }, - { - "author_name": "Antso Hasina Raherinandrasana", - "author_inst": "Surveillance Unit, Ministry of Health of Madagascar & Faculty of Medicine, University of Antananarivo" + "author_name": "Juan Pablo Robles", + "author_inst": "Instituto de Neurobiolog\u00eda, Universidad Nacional Aut\u00f3noma de M\u00e9xico (UNAM), Quer\u00e9taro, M\u00e9xico." }, { - "author_name": "Santatra Randrianarisoa", - "author_inst": "Mahaliana Labs SARL, Antananarivo, Madagascar" - }, - { - "author_name": "Benjamin L. Rice", - "author_inst": "Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ, USA & Madagascar Health and Environmental Research (MAHERY), Maroantsetra," + "author_name": "Magdalena Zamora", + "author_inst": "Instituto de Neurobiolog\u00eda, Universidad Nacional Aut\u00f3noma de M\u00e9xico (UNAM), Quer\u00e9taro, M\u00e9xico." }, { - "author_name": "Amy Wesolowski", - "author_inst": "Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA" + "author_name": "Gonzalo Martinez de la Escalera", + "author_inst": "Instituto de Neurobiolog\u00eda, Universidad Nacional Aut\u00f3noma de M\u00e9xico (UNAM), Quer\u00e9taro, M\u00e9xico." }, { - "author_name": "Fidiniaina Mamy Randriatsarafara", - "author_inst": "Faculty of Medicine, University of Antananarivo & Direction of preventive Medicine, Ministry of Health" - }, - { - "author_name": "Fidisoa Rasambainarivo", - "author_inst": "Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ, USA & Mahaliana Labs SARL, Antananarivo, Madagascar" + "author_name": "Carmen Clapp", + "author_inst": "Instituto de Neurobiolog\u00eda, Universidad Nacional Aut\u00f3noma de M\u00e9xico (UNAM), Quer\u00e9taro, M\u00e9xico." } ], "version": "1", - "license": "cc_by_nd", - "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "license": "cc_by_nc_nd", + "type": "new results", + "category": "cell biology" }, { "rel_doi": "10.1101/2021.08.02.454771", @@ -632009,55 +631488,91 @@ "category": "obstetrics and gynecology" }, { - "rel_doi": "10.1101/2021.07.23.21260984", - "rel_title": "Staffing and Capacity Planning for SARS-CoV-2 Monoclonal Antibody Infusion Facilities: A Performance Estimation Calculator based on Discrete-Event Simulations", + "rel_doi": "10.1101/2021.07.31.21261387", + "rel_title": "Vaccinated and unvaccinated individuals have similar viral loads in communities with a high prevalence of the SARS-CoV-2 delta variant", "rel_date": "2021-07-31", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.23.21260984", - "rel_abs": "ObjectiveThe COVID-19 pandemic has significantly stressed healthcare systems. The addition of monoclonal antibody (mAb) infusions, which prevent severe disease and reduce hospitalizations, to the repertoire of COVID-19 countermeasures offers the opportunity to reduce system stress but requires strategic planning and use of novel approaches. Our objective was to develop a web-based decision-support tool to help existing and future mAb infusion facilities make better and more informed staffing and capacity decisions.\n\nMaterials and MethodsUsing real-world observations from three medical centers operating with federal field team support, we developed a discrete-event simulation model and performed simulation experiments to assess performance of mAb infusion sites under different conditions.\n\nResults162,000 scenarios were evaluated by simulations. Our analyses revealed that it was more effective to add check-in staff than to add additional nurses for middle-to-large size sites with [≥] 2 infusion nurses; that scheduled appointments performed better than walk-ins when patient load was not high; and that reducing infusion time was particularly impactful when load on resources was only slightly above manageable levels.\n\nDiscussionPhysical capacity, check-in staff, and infusion time were as important as nurses for mAb sites. Health systems can effectively operate an infusion center under different conditions to provide mAb therapeutics even with relatively low investments in physical resources and staff.\n\nConclusionSimulations of mAb infusion sites were used to create a capacity planning tool to optimize resource utility and allocation in constrained pandemic conditions, and more efficiently treat COVID-19 patients at existing and future mAb infusion sites.", - "rel_num_authors": 9, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.31.21261387", + "rel_abs": "The SARS-CoV-2 Delta Variant of Concern is highly transmissible and contains mutations that confer partial immune escape. The emergence of Delta in North America caused the first surge in COVID-19 cases after SARS-CoV-2 vaccines became widely available. To determine whether individuals infected despite vaccination might be capable of transmitting SARS-CoV-2, we compared RT-PCR cycle threshold (Ct) data from 20,431 test-positive anterior nasal swab specimens from fully vaccinated (n = 9,347) or unvaccinated (n=11,084) individuals tested at a single commercial laboratory during the interval 28 June - 1 December 2021 when Delta variants were predominant. We observed no significant effect of vaccine status alone on Ct value, nor when controlling for vaccine product or sex. Testing a subset of low-Ct (<25) samples, we detected infectious virus at similar rates, and at similar titers, in specimens from vaccinated and unvaccinated individuals. These data indicate that vaccinated individuals infected with Delta variants are capable of shedding infectious SARS-CoV-2 and could play a role in spreading COVID-19.", + "rel_num_authors": 18, "rel_authors": [ { - "author_name": "Caglar Caglayan", - "author_inst": "Johns Hopkins Applied Physics Laboratory" + "author_name": "Kasen K Riemersma", + "author_inst": "University of Wisconsin-Madison" }, { - "author_name": "Jonathan Thornhill", - "author_inst": "Johns Hopkins University Applied Physics Laboratory" + "author_name": "Luis A Haddock", + "author_inst": "Department of Pathobiological Sciences, University of Wisconsin School of Veterinary Medicine, Madison, WI, USA" }, { - "author_name": "Miles A. Stewart", - "author_inst": "Johns Hopkins University Applied Physics Laboratory" + "author_name": "Nancy A Wilson", + "author_inst": "Department of Pathology and Laboratory Medicine, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA" }, { - "author_name": "Anastasia S. Lambrou", - "author_inst": "Johns Hopkins University Applied Physics Laboratory" + "author_name": "Nicholas R Minor", + "author_inst": "Department of Pathology and Laboratory Medicine, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA" }, { - "author_name": "Donald Richardson", - "author_inst": "Johns Hopkins University Applied Physics Laboratory" + "author_name": "Jens C Eickhoff", + "author_inst": "Biostatistics and Medical Informatics, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA" }, { - "author_name": "Kaitlin Rainwater-Lovett", - "author_inst": "Johns Hopkins Applied Physics Laboratory" + "author_name": "Brittany E Grogan", + "author_inst": "Public Health Madison & Dane County" }, { - "author_name": "Jeffrey D. Freeman", - "author_inst": "Johns Hopkins University Applied Physics Laboratory" + "author_name": "Amanda Kita-Yarbro", + "author_inst": "Public Health Madison & Dane County" }, { - "author_name": "Tiffany Pfundt", - "author_inst": "Assistant Secretary for Preparedness and Response, U.S. Department of Health and Human Services" + "author_name": "Peter Halfmann", + "author_inst": "University of Wisconsin-Madison" + }, + { + "author_name": "Hannah E Segaloff", + "author_inst": "Epidemic Intelligence Service, CDC, Atlanta, GA, USA" + }, + { + "author_name": "Anna Kocharian", + "author_inst": "Wisconsin Department of Health Services" + }, + { + "author_name": "Kelsey R Florek", + "author_inst": "Wisconsin State Laboratory of Hygiene" + }, + { + "author_name": "Ryan Westergaard", + "author_inst": "Wisconsin Department of Health Services" + }, + { + "author_name": "Allen Bateman", + "author_inst": "Wisconsin State Laboratory of Hygiene" + }, + { + "author_name": "Gunnar E Jeppson", + "author_inst": "Exact Sciences" + }, + { + "author_name": "Yoshihiro Kawaoka", + "author_inst": "University of Wisconsin-Madison" }, { - "author_name": "John T. Redd", - "author_inst": "Assistant Secretary for Preparedness and Response, U.S. Department of Health and Human Services" + "author_name": "David H O'Connor", + "author_inst": "University of Wisconsin-Madison" + }, + { + "author_name": "Thomas C Friedrich", + "author_inst": "University of Wisconsin-Madison" + }, + { + "author_name": "Katarina M Grande", + "author_inst": "Public Health Madison & Dane County" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", - "category": "health systems and quality improvement" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2021.07.28.21261285", @@ -633907,33 +633422,65 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.07.24.21261059", - "rel_title": "Data Analysis and Forecasting of COVID-19 Pandemic in Kuwait", + "rel_doi": "10.1101/2021.07.22.21260973", + "rel_title": "A regression discontinuity analysis of the social distancing recommendations for older adults in Sweden during COVID-19", "rel_date": "2021-07-30", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.24.21261059", - "rel_abs": "The first COVID 19 case of Kuwait was announced on 24th February, 2020 and the daily new cases increases exponentially since then until May, 2020 when the first wave started to decline. The same exponential dynamics has been observed between January and March, 2021. The forecast of new cases and death recorded daily is crucial so that health experts and citizens can be guided in order to avoid escalation of the pandemic. We propose a deterministic method to predict the basic reproduction number Ro of first and second wave of COVID-19 cases in Kuwait and also to forecast the daily new cases and death of the pandemic in the country. Forecasting has been done using ARIMA model, Exponential smoothing model, Holts method, Prophet forecasting model and machine learning models like log-linear, polynomial and support vector regressions. The results presented aligned with other methods used to predict Ro in first and second waves and the forecasting clearly shows the trend of the pandemic in Kuwait. The deterministic prediction of Ro is a good forecasting tool available during the exponential phase of the contagion, which shows an increasing trend during the beginning of the first and second waves of the pandemic in Kuwait.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.22.21260973", + "rel_abs": "ObjectivesTo study the impact of non-mandatory, age-specific social distancing recommendations for older adults (70+ years) in Sweden on isolation behaviors and disease outcomes during the first wave of the COVID-19 pandemic.\n\nMethodsOur study relies on self-reported isolation data from COVID Symptom Study Sweden (n = 96,053) and national register data on COVID-19 hospitalizations, deaths, and confirmed cases. We use a regression discontinuity design to account for confounding factors, exploiting the fact that exposure to the recommendation was a discontinuous function of age.\n\nResultsBy comparing individuals just above to those just below the age limit for the policy, our analyses revealed a sharp drop in the weekly number of visits to crowded places at the 70-year-threshold (-13%). Severe COVID-19 cases (hospitalizations or deaths) also dropped abruptly by 16% at the 70-year-threshold. Our data suggest that the age-specific recommendations prevented approximately 1,800 to 2,700 severe COVID-19 cases, depending on model specification.\n\nConclusionThe non-mandatory, age-specific recommendations helped control the COVID-19 pandemic in Sweden.", + "rel_num_authors": 12, "rel_authors": [ { - "author_name": "Kayode Oshinubi", - "author_inst": "University Grenoble Alpes" + "author_name": "Carl Bonander", + "author_inst": "University of Gothenburg" }, { - "author_name": "Fahimah Al-Awadhi", - "author_inst": "Kuwait University" + "author_name": "Debora Stranges", + "author_inst": "Lund University" }, { - "author_name": "Mustapha Rachdi", - "author_inst": "University Grenoble Alpes" + "author_name": "Johanna Gustavsson", + "author_inst": "Karlstad University" }, { - "author_name": "Jacques Demongeot", - "author_inst": "University Grenoble Alpes" + "author_name": "Matilda Almgren", + "author_inst": "Skane University Hospital" + }, + { + "author_name": "Malin Inghammar", + "author_inst": "Lund University" + }, + { + "author_name": "Mahnaz Moghaddassi", + "author_inst": "Lund University" + }, + { + "author_name": "Anton Nilsson", + "author_inst": "Lund University" + }, + { + "author_name": "Paul W Franks", + "author_inst": "Lund University" + }, + { + "author_name": "Maria F Gomez", + "author_inst": "Lund University" + }, + { + "author_name": "Tove Fall", + "author_inst": "Uppsala University" + }, + { + "author_name": "Jonas Bjork", + "author_inst": "Lund University" + }, + { + "author_name": "- COVID Symptom Study Sweden", + "author_inst": "" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -635685,39 +635232,35 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.07.23.21260716", - "rel_title": "Covid-19 Associated Hepatitis in children (CACH) during the second wave of SARS-CoV-2 infections in Central India: Is it a complication or transient phenomenon.", + "rel_doi": "10.1101/2021.07.28.21259040", + "rel_title": "Outbreak of P.3 (Theta) SARS-CoV-2 emerging variant of concern among food service workers in Louisiana", "rel_date": "2021-07-29", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.23.21260716", - "rel_abs": "ObjectiveWhile pediatric population has largely remained free of severe COVID-19, in some cases SARS-CoV-2 infection has been associated with complications like Multiple Inflammatory Syndrome in children (MIS-C). We mention another unique presentation subsequent to asymptomatic infection of SARS-CoV-2, a unique form of hepatitis designated by us as COVID-19 Associated Hepatitis in Children (CAH-C). The contrasting clinical presentations, temporal association and viral parameters of CAH-C cases, to the MIS-C cases are presented here.\n\nMethodsAs a retrospective and follow-up observational study we reviewed all children testing positive for SARS-CoV-2 during study period. Children presenting with \"sudden onset of hepatitis, elevated transaminases, non-obstructive jaundice, lacking marked inflammatory responses and without evidence of (a) other known causes of acute hepatitis or previous underlying liver disease (b) multi-system involvement\" were classified as CAH-C, are described here.\n\nResultsAmong 475 children tested positive, 47 patients presented with hepatitis, 37 patients had features of CAH-C, having symptoms of hepatitis only, with un-elevated inflammatory markers and uneventful recovery following supportive treatment. Whereas remaining 10 MIS-C hepatitis had protracted illness, multiple system involvement, required admission to critical care, and had mortality of 30%.\n\nConclusionWith the emergence of newer variants of concern (VOC) including the Delta variant which predominated the second wave of infections in India and has now spread to more than 142 countries with changing presentations, CAH-C might be one of them. Cases of such new entities need to be identified early and differentiated from other emerging syndromes in children during the ongoing pandemic for preventing adversities by timely intervention.\n\nConflicts of interestThe authors declare that they have no conflicts of interest related to the study or its findings. All authors have contributed to the conceptualization and manuscript writing of the study, the final version is approved by all the authors. We declare there are no competing interests involved among the authors.\n\nFunding and ethics approvalCurrent research received no specific grant from any funding agency in the public, commercial or not-for-profit sectors. The follow-up and analysis work was performed after obtaining due approval of human ethics committee of the institution (Ref no. IEC/BMC/80/21).", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.28.21259040", + "rel_abs": "In May, 2021, during routine oil and gas industrial quarantine/premobilization procedures, four individuals who recently arrived to Louisiana from the Philippines tested positive for SARS-CoV-2. Subsequent genomic analysis showed that all were infected with a Variant of Interest (P.3-Theta). This increases the number of known P.3 infections in the United States to eleven and highlights the importance of genomic surveillance within industries that are prone to rapidly spread the infection.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Sumit K Rawat", - "author_inst": "Bundelkhand Medical College, India" - }, - { - "author_name": "Ajit anand Asati", - "author_inst": "Bundelkhand Medical College, India" + "author_name": "Rebecca Rose", + "author_inst": "Bioinfoexperts, LLC" }, { - "author_name": "Ashish Jain", - "author_inst": "Bundelkhand Medical College, India" + "author_name": "David J Nolan", + "author_inst": "BioInfoExperts LLC" }, { - "author_name": "Radha Kant Ratho", - "author_inst": "PGIMER, Chandigarh India" + "author_name": "Tessa M LaFleur", + "author_inst": "BioInfoExperts LLC" }, { - "author_name": "Nitu Mishra", - "author_inst": "Bundelkhand Medical College,India" + "author_name": "Susanna L Lamers", + "author_inst": "BioInfoExperts LLC" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "pediatrics" + "category": "epidemiology" }, { "rel_doi": "10.1101/2021.07.24.21261016", @@ -637939,31 +637482,43 @@ "category": "pharmacology and therapeutics" }, { - "rel_doi": "10.1101/2021.07.23.21260998", - "rel_title": "Risk of Myocarditis from COVID-19 Infection in People Under Age 20: A Population-Based Analysis", + "rel_doi": "10.1101/2021.07.26.21261119", + "rel_title": "Safety and efficacy of COVID-19 hyperimmune globulin (HIG) solution in the treatment of active COVID-19 infection- Findings from a Prospective, Randomized, Controlled, Multi-Centric Trial", "rel_date": "2021-07-27", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.23.21260998", - "rel_abs": "BackgroundThere have been recent reports of myocarditis (including myocarditis, pericarditis or myopericarditis) as a side-effect of mRNA-based COVID-19 vaccines, particularly in young males. Less information is available regarding the risk of myocarditis from COVID-19 infection itself. Such data would be helpful in developing a complete risk-benefit analysis for this population.\n\nMethodsA de-identified, limited data set was created from the TriNetX Research Network, aggregating electronic health records from 48 mostly large U.S. Healthcare Organizations (HCOs). Inclusion criteria were a first COVID-19 diagnosis during the April 1, 2020 - March 31, 2021 time period, with an outpatient visit 1 month to 2 years before, and another 6 months to 2 years before that. Analysis was stratified by sex and age (12-17, 12-15, 16-19). Patients were excluded for any prior cardiovascular condition. Primary outcome was an encounter diagnosis of myocarditis within 90 days following the index date. Rates of COVID-19 cases and myocarditis not identified in the system were estimated and the results adjusted accordingly. Wilson score intervals were used for 95% confidence intervals due to the very low probability outcome.\n\nResultsFor the 12-17-year-old male cohort, 6/6,846 (0.09%) patients developed myocarditis overall, with an adjusted rate per million of 450 cases (Wilson score interval 206 - 982). For the 12-15 and 16-19 male age groups, the adjusted rates per million were 601 (257 - 1,406) and 561 (240 - 1,313).\n\nFor 12-17-year-old females, there were 3 (0.04%) cases of myocarditis of 7,361 patients. The adjusted rate was 213 (73 - 627) per million cases. For the 12-15- and 16-19-year-old female cohorts the adjusted rates per million cases were 235 (64 - 857) and 708 (359 - 1,397).\n\nThe outcomes occurred either within 5 days (40.0%) or from 19-82 days (60.0%).\n\nConclusionsMyocarditis (or pericarditis or myopericarditis) from primary COVID19 infection occurred at a rate as high as 450 per million in young males. Young males infected with the virus are up 6 times more likely to develop myocarditis as those who have received the vaccine.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.26.21261119", + "rel_abs": "BackgroundCOVID-19 hyper-immune globulin (HIG) solution is a human plasma-derived, highly-purified, concentrated, virus-inactivated preparation of neutralizing antibodies (NAbs) against COVID-19.\n\nMethodsThis was a randomized, two-arm, controlled, multi-center trial to evaluate the efficacy and safety of COVID-19 HIG in patients who were hospitalized with moderate-severe COVID-19 infection.\n\nResultsA total of 60 patients were randomized (30 in each arm). Overall, COVID-19 HIG was well-tolerated without any serious treatment-emergent adverse event or tolerability issue. The mean change in ordinal scale by day 8 was 1.7{+/-}1.61 in the test arm vs. 2.0{+/-}1.68 in the control arm (mITT; p=0.367). Early and high NAbs were observed in the test arm compared to the control arm.\n\nMore patients had negative RT-PCR by day 3 for the test arm vs. the control arm (mITT: 46.67% in test vs. 37.93% in control). The median time to be RT-PCR negative was 5.5 days for the test arm vs. 8.0 days for the control arm for PP population. Patients receiving COVID-19 HIG showed early improvement (reduction) in the biomarkers (CRP, IL-6, and D-dimer).\n\nConclusionCOVID-19 HIG was found to be safe and well-tolerated. Early and high NAbs were achieved in COVID-19 HIG recipients qualifying the product as a suitable treatment option, particularly in an immunocompromised state. It should be given early in infection to mitigate progression to severe disease. It should be evaluated for post-exposure prophylaxis as well as for prevention (where a vaccine is not suitable or effective). It should be evaluated in the pediatric population as well.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Mendel E Singer", - "author_inst": "Case Western Reserve University School of Medicine, Cleveland, Ohio, USA" + "author_name": "Devang Parikh", + "author_inst": "Intas Pharmaceuticals Ltd." + }, + { + "author_name": "Alok Chaturvedi", + "author_inst": "Intas Pharmaceuticals Ltd." + }, + { + "author_name": "Naman Shah", + "author_inst": "Lambda Therapeutics Research Ltd." + }, + { + "author_name": "Piyush Patel", + "author_inst": "Intas Pharmaceuticals Ltd." }, { - "author_name": "Ira B. Taub", - "author_inst": "Akron Children's Hospital Heart Center, Akron, Ohio, USA" + "author_name": "Ronak Patel", + "author_inst": "Lambda Therapeutics Research Ltd." }, { - "author_name": "David C. Kaelber", - "author_inst": "Case Western Reserve University at The MetroHealth System, Cleveland, Ohio, USA" + "author_name": "Suma Ray", + "author_inst": "Intas Pharmaceuticals Ltd." } ], "version": "1", - "license": "cc_no", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2021.07.27.21260398", @@ -639929,71 +639484,35 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2021.07.23.21260676", - "rel_title": "Can we clinically identify pre-symptomatic and asymptomatic COVID-19?", + "rel_doi": "10.1101/2021.07.26.453805", + "rel_title": "CIGB-300 synthetic peptide, an antagonist of CK2 kinase activity, as a treatment for Covid-19. A computational biology approach", "rel_date": "2021-07-26", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.23.21260676", - "rel_abs": "ObjectivesCOVID-19 has had a severe impact on morbidity and mortality among nursing home (NH) residents. Earlier detection of SARS-CoV-2 may position us to better mitigate risk of spread. Both asymptomatic or pre-symptomatic transmission are common in outbreaks, and threshold temperatures, such as 38C, for screening for infection could miss timely detection in the majority.\n\nDesignRetrospective cohort study using electronic health records\n\nMethodsWe hypothesized that in long-term care residents, temperature trends with SARS-CoV-2 infection could identify infection in pre-symptomatic and asymptomatic individuals earlier. We collected information about age and other demographics, baseline temperature, and specific comorbidities. We created standardized definitions, and an alternative hypothetical model to test measures of temperature variation and compare outcomes to the VA reality.\n\nSettings and participantsOur subjects were 6,176 residents of the VA NHs who underwent SARS-CoV-2 trigger testing.\n\nResultsWe showed that a change from baseline of >0.4C identifies 47% of the SARS-CoV-2 positive NH residents early, and achieves earlier detection by 42.2 hours. Range improves early detection to 55% when paired with a 37.2C cutoff, and achieves earlier detection by 44.4 hours. Temperature elevation >0.4C from baseline, when combined with a 0.7C range, would detect 52% early, leading to earlier detection by more than 3 days in 22% of the residents. This earlier detection comes at the expense of triggering 57,793 tests, as compared to the number of trigger tests ordered in the VA system of 40,691.\n\nConclusion and implicationsOur model suggests that current clinical screening for SARS-CoV-2 in NHs can be substantially improved upon by triggering testing using a patient-derived baseline temperature with a 0.4C degree relative elevation or temperature variability of 0.7C trigger threshold for SARS-CoV2 testing. Such triggers could be automated in facilities that track temperatures in their electronic records.", - "rel_num_authors": 13, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2021.07.26.453805", + "rel_abs": "Drug repositioning became the first choice for treating Covid-19 patients due to the urgent need to deal with the pandemic. Similarities in the hijacking mechanisms used by SARS-CoV-2 and several type of cancer, suggest the repurposing of cancer drugs to treat Covid-19. CK2 kinase antagonists have been proposed for the treatment of cancer. A recent study in cells infected with SARS-CoV-2 virus found a significant CK2 kinase activity, and the use of a CK2 inhibitor showed antiviral responses. CIGB-300, originally designed as an anticancer peptide, is an antagonist of CK2 kinase activity that binds to CK2 phospho-acceptor sites. Recent preliminary results show an antiviral activity of CIGB-300 versus a surrogate model of coronavirus. Here we present a computational biology study that provides evidences at the molecular level of how CIGB-300 might interfere with SARS-CoV-2 life cycle inside infected human cells. First, from SARS-CoV studies, we infer the potential incidence of CIGB-300 in SARS-CoV-2 interference on immune response. Next, from the analysis of multiple Omics data, we propose the action of CIGB-300 since early stage of viral infections perturbing the virus hijacking of RNA splicing machinery. It was also predicted the interference of CIGB-300 in virus-host interactions responsible for the high infectivity and the particular immune response to SARS-CoV-2 infection. Further, we provide evidences of CIGB-300 attenuation of phenotypes related to muscle, bleeding, coagulation and respiratory disorders.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Salaheldin Elhamamsy", - "author_inst": "Alpert Medical School of Brown University" - }, - { - "author_name": "Frank Devone", - "author_inst": "Providence Veterans Administration Medical Center, Center on Innovation-Long Term Services and Supports" + "author_name": "Jamilet Miranda", + "author_inst": "Center for Genetic Engineering and Biotechnology: Centro de Ingenieria Genetica y Biotecnologia" }, { - "author_name": "Tom Bayer", - "author_inst": "Alpert Medical School of Brown University" + "author_name": "Ricardo Bringas", + "author_inst": "Center for Genetic Engineering and Biotechnology: Centro de Ingenieria Genetica y Biotecnologia" }, { - "author_name": "Christopher Halladay", - "author_inst": "Providence Veterans Administration Medical Center, Center on Innovation-Long Term Services and Supports" + "author_name": "Jorge Fern\u00e1ndez de-Cossio", + "author_inst": "Center for Genetic Engineering and Biotechnology: Centro de Ingenieria Genetica y Biotecnologia" }, { - "author_name": "Marilyne Cadieux", - "author_inst": "Alpert Medical School of Brown University" - }, - { - "author_name": "Kevin McConeghy", - "author_inst": "Providence Veterans Administration Medical Center, Center on Innovation-Long Term Services and Supports" - }, - { - "author_name": "Ashna Rajan", - "author_inst": "Alpert Medical School of Brown University" - }, - { - "author_name": "Moniyka Sachar", - "author_inst": "Alpert Medical School of Brown University" - }, - { - "author_name": "Nadia Mujahid", - "author_inst": "Brown University" - }, - { - "author_name": "Aman Nanda", - "author_inst": "Alpert Medical School of Brown University" - }, - { - "author_name": "Lynn McNicoll", - "author_inst": "Alpert Medical School of Brown University" - }, - { - "author_name": "James Rudolph", - "author_inst": "Providence Veterans Administration Medical Center, Center on Innovation-Long Term Services and Supports" - }, - { - "author_name": "Stefan Gravenstein", - "author_inst": "Alpert Medical School of Brown University, Providence Veterans Administration Medical Center, Center on Innovation-Long Term Services and Supports, Brown School" + "author_name": "Yasser Perera", + "author_inst": "Center for Genetic Engineering and Biotechnology: Centro de Ingenieria Genetica y Biotecnologia" } ], "version": "1", - "license": "cc_by_nc_nd", - "type": "PUBLISHAHEADOFPRINT", - "category": "geriatric medicine" + "license": "cc_by", + "type": "new results", + "category": "bioinformatics" }, { "rel_doi": "10.1101/2021.07.19.21260773", @@ -641863,59 +641382,107 @@ "category": "intensive care and critical care medicine" }, { - "rel_doi": "10.1101/2021.07.22.21260952", - "rel_title": "Variant-driven multi-wave pattern of COVID-19 via Machine Learning clustering of spike protein mutations", + "rel_doi": "10.1101/2021.07.22.21260852", + "rel_title": "Comparison of infected and vaccinated transplant recipients highlights the role of Tfh and neutralizing IgG in COVID-19 protection", "rel_date": "2021-07-24", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.22.21260952", - "rel_abs": "Never before such a vast amount of data, including genome sequencing, has been collected for any viral pandemic than for the current case of COVID-19. This offers the possibility to trace the virus evolution and to assess the role mutations play in its spread within the population, in real time. To this end, we focused on the Spike protein for its central role in mediating viral outbreak and replication in host cells. Employing the Levenshtein distance on the Spike protein sequences, we designed a machine learning algorithm yielding a temporal clustering of the available dataset. From this, we were able to identify and define emerging persistent variants that are in agreement with known evidences. Our novel algorithm allowed us to define persistent variants as chains that remain stable over time and to highlight emerging variants of epidemiological interest as branching events that occur over time. Hence, we determined the relationship and temporal connection between variants of interest and the ensuing passage to dominance of the current variants of concern. Remarkably, the analysis and the relevant tools introduced in our work serve as an early warning for the emergence of new persistent variants once the associated cluster reaches 1% of the time-binned sequence data. We validated our approach and its effectiveness on the onset of the Alpha variant of concern. We further predict that the recently identified lineage AY.4.2 ( Delta plus) is causing a new emerging variant. Comparing our findings with the epidemiological data we demonstrated that each new wave is dominated by a new emerging variant, thus confirming the hypothesis of the existence of a strong correlation between the birth of variants and the pandemic multi-wave temporal pattern. The above allows us to introduce the epidemiology of variants that we described via the Mutation epidemiological Renormalisation Group (MeRG) framework.\n\nHighlightsO_LIObjectives To study the relation among Spike protein mutations, the emergence of relevant variants and the multi-wave pattern of the COVID-19 pandemic.\nC_LIO_LISetting Genomic sequencing of the SARS-CoV-2 Spike proteins in the UK nations (England, Scotland, Wales). Epi-demiological data for the number of infections in the UK nations, South Africa, California and India.\nC_LIO_LIMethodology We design a machine learning algorithm, based on the Levenshtein distance on the Spike protein sequences, that leads to a temporal clustering of the available dataset, from which we define emerging persistent variants. The above allows us to introduce the epidemiology of variants that we described via the Mutation epidemiological Renormalisation Group (MeRG) framework.\nC_LIO_LIResults We show that:\nO_LIOur approach, based only on the Spike protein sequence, allows to efficiently identify the variants of concern (VoCs) and of interest (VoIs), as well as other emerging variants occurring during the diffusion of the virus.\nC_LIO_LIWithin our time-ordered chain analysis, a branching relation emerges, thus permitting to reconstruct the evolutionary diversification of Spike variants and the establishment of the epidemiologically relevant ones.\nC_LIO_LIOur analysis provides an early warning for the emergence of new persistent variants once its associated dominant Spike sequence reaches 1% of the time-binned sequence data. Validation on the onset of the Alpha VoC shows that our early warning is triggered 6 weeks before the WHO classification decision.\nC_LIO_LIComparison with the epidemiological data demonstrates that each new wave is dominated by a new emerging variant, thus confirming the hypothesis that there is a strong correlation between the emergence of variants and the multi-wave temporal pattern depicting the viral spread.\nC_LIO_LIA theory of variant epidemiology is established, which describes the temporal evolution of the number of infected by different emerging variants via the MeRG approach. This is corroborated by empirical data.\nC_LI\nC_LI\n\nO_LIConclusions Applying a ML approach to the temporal variability of the Spike protein sequence enables us to identify, classify and track emerging virus variants. Our analysis is unbiased, in the sense that it does not require any prior knowledge of the variant characteristics, and our results are validated by other informed methods that define variants based on the complete genome. Furthermore, correlating persistent variants of our approach to epidemiological data, we discover that each new wave of the COVID-19 pandemic is driven and dominated by a new emerging variant. Our results are therefore indispensable for further studies on the evolution of SARS-CoV-2 and the prediction of evolutionary patterns that determine current and future mutations of the Spike proteins, as well as their diversification and persistence during the viral spread. Moreover, our ML algorithm works as an efficient early warning system for the emergence of new persistent variants that may pose a threat of triggering a new wave of COVID-19. Capable of a timely identification of potential new epidemiological threats when the variant only represents 1% of the new sequences, our ML strategy is a crucial tool for decision makers to define short and long term strategies to curb future outbreaks. The same methodology can be applied to other viral diseases, influenza included, if sufficient sequencing data is available.\nC_LI", - "rel_num_authors": 10, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.22.21260852", + "rel_abs": "Transplant recipients, which receive therapeutic immunosuppression to prevent graft rejection, are characterized by high COVID-19-related mortality and defective response to vaccines. Having observed that previous infection by SARS-CoV-2 but not the standard \"2 doses\" scheme of vaccination, provided complete protection against COVID-19 to transplant recipients, we undertook this translational study to compare the cellular and humoral immune responses of these 2 groups of patients. Neutralizing anti-Receptor Binding Domain (RBD) IgG were identified as the critical immune effectors associated with protection. Generation of anti-RBD IgG was dependent upon spike-specific T follicular helper (Tfh) CD4+ T cells, which acted as limiting checkpoint. Tfh generation was impeded by high dose mycophenolate mofetil in non-responders to vaccine but not in infected patients, suggesting that increasing immunogenicity of vaccine could improve response rate to mRNA vaccine. This theory was validated in two independent prospective cohorts, in which administration of a 3rd dose of vaccine resulted in the generation of anti-RBD IgG in half of non-responders to 2 doses.\n\nOne sentence summaryThe generation of neutralizing IgG, which protects kidney transplant recipients from COVID-19, requires T follicular helper cells.", + "rel_num_authors": 22, "rel_authors": [ { - "author_name": "Adele de Hoffer", - "author_inst": "Politecnico di Torino" + "author_name": "Xavier Charmetant", + "author_inst": "CIRI, INSERM U1111, Universite Claude Bernard Lyon I, CNRS UMR5308, Ecole Normale Superieure de Lyon, Univ. Lyon, 21 avenue Tony Garnier, 69007 Lyon, France." }, { - "author_name": "Shahram Vatani", - "author_inst": "IP2I de Lyon, CNRS, Lyon University" + "author_name": "Maxime ESPI", + "author_inst": "INSERM CIRI U1111, Lyon" }, { - "author_name": "Corentin Cot", - "author_inst": "IP2I de Lyon, CNRS, Lyon University" + "author_name": "Ilies Benotmane", + "author_inst": "Department of Nephrology and Transplantation, Strasbourg University Hospital, Strasbourg, France" }, { - "author_name": "Giacomo Cacciapaglia", - "author_inst": "IP2I de Lyon, CNRS, Lyon University" + "author_name": "Francoise Heibel", + "author_inst": "Department of Nephrology and Transplantation, Strasbourg University Hospital, Strasbourg, France" }, { - "author_name": "Maria Luisa Chiusano", - "author_inst": "University Federico II of Naples" + "author_name": "Fanny Buron", + "author_inst": "Hospices Civils de Lyon, Edouard Herriot Hospital, Department of Transplantation, Nephrology and Clinical Immunology, Lyon, France" }, { - "author_name": "Andrea Cimarelli", - "author_inst": "ENS Lyon and University of Lyon 1" + "author_name": "Gabriela Gautier-Vargas", + "author_inst": "Department of Nephrology and Transplantation, Strasbourg University Hospital, Strasbourg, France" + }, + { + "author_name": "Marion Delafosse", + "author_inst": "Hospices Civils de Lyon, Edouard Herriot Hospital, Department of Transplantation, Nephrology and Clinical Immunology, Lyon, France" + }, + { + "author_name": "Peggy Perrin", + "author_inst": "Department of Nephrology and Transplantation, Strasbourg University Hospital, Strasbourg, France" + }, + { + "author_name": "Alice Koenig", + "author_inst": "CIRI, INSERM U1111, Universite Claude Bernard Lyon I, CNRS UMR5308, Ecole Normale Superieure de Lyon, Univ. Lyon, 21 avenue Tony Garnier, 69007 Lyon, France" + }, + { + "author_name": "Noelle Cognard", + "author_inst": "Department of Nephrology and Transplantation, Strasbourg University Hospital, Strasbourg, France" + }, + { + "author_name": "Charlene Levi", + "author_inst": "Hospices Civils de Lyon, Edouard Herriot Hospital, Department of Transplantation, Nephrology and Clinical Immunology, Lyon, France" + }, + { + "author_name": "Floriane Gallais", + "author_inst": "Department of Virology, Strasbourg University Hospital, Strasbourg, France" + }, + { + "author_name": "Louis Maniere", + "author_inst": "Hospices Civils de Lyon, Edouard Herriot Hospital, Department of Transplantation, Nephrology and Clinical Immunology, Lyon, France" + }, + { + "author_name": "Paola Rossolillo", + "author_inst": "Institut de Genetique et de Biologie Moleculaire et Cellulaire (IGBMC), Centre National de la Recherche Scientifique (CNRS), UMR 7104, Institut National de la S" + }, + { + "author_name": "Eric Soulier", + "author_inst": "Inserm UMR S1109, LabEx Transplantex, Federation de Medecine Translationnelle de Strasbourg (FMTS), Universite de Strasbourg, Strasbourg, France" + }, + { + "author_name": "Florian Pierre", + "author_inst": "Inserm UMR S1109, LabEx Transplantex, Federation de Medecine Translationnelle de Strasbourg (FMTS), Universite de Strasbourg, Strasbourg, France" + }, + { + "author_name": "Anne Ovize", + "author_inst": "Eurofins Biomnis Laboratory, 69007 Lyon, France" + }, + { + "author_name": "Emmanuel Morelon", + "author_inst": "Hospices Civils de Lyon, Edouard Herriot Hospital, Department of Transplantation, Nephrology and Clinical Immunology, Lyon, France. Claude Bernard University (L" }, { - "author_name": "Francesco Conventi", - "author_inst": "INFN sezione di Napoli, Universita di Napoli Parthenope" + "author_name": "Thierry Defrance", + "author_inst": "CIRI, INSERM U1111, Universite Claude Bernard Lyon I, CNRS UMR5308, Ecole Normale Superieure de Lyon, Univ. Lyon, 21 avenue Tony Garnier, 69007 Lyon, France" }, { - "author_name": "Antonio Giannini", - "author_inst": "INFN sezione di Napoli, Universita di Napoli Federico II" + "author_name": "Samira Fafi-Kremer", + "author_inst": "Department of Virology, Strasbourg University Hospital, Strasbourg, France. Inserm UMR S1109, LabEx Transplantex, Federation de Medecine Translationnelle de Str" }, { - "author_name": "Stefan Hohenegger", - "author_inst": "IP2I de Lyon, CNRS, Lyon University" + "author_name": "Sophie Caillard", + "author_inst": "Department of Nephrology and Transplantation, Strasbourg University Hospital, Strasbourg, France. Inserm UMR S1109, LabEx Transplantex, Federation de Medecine T" }, { - "author_name": "Francesco Sannino", - "author_inst": "Universita di Napoli Federico II, Scuola Superiore Meridionale, INFN sezione di Napoli, CP3-Origins and the Danish Institute for Advanced Study (University of S" + "author_name": "Olivier Thaunat", + "author_inst": "CIRI, INSERM U1111, Universite Claude Bernard Lyon I, CNRS UMR5308, Ecole Normale Superieure de Lyon, Lyon, France. 5Hospices Civils de Lyon, Edouard Herriot Ho" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "transplantation" }, { "rel_doi": "10.1101/2021.07.20.21260813", @@ -644805,79 +644372,31 @@ "category": "biochemistry" }, { - "rel_doi": "10.1101/2021.07.23.453352", - "rel_title": "Understanding the role of memory re-activation and cross-reactivity in the defense against SARS-CoV-2", + "rel_doi": "10.1101/2021.07.23.453571", + "rel_title": "Effective presence of antibodies against common human coronavirus in IgG immunoglobulin medicinal products.", "rel_date": "2021-07-23", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.07.23.453352", - "rel_abs": "Recent efforts in understanding the course and severity of SARS-CoV-2 infections have highlighted both potential beneficial as well as detrimental effects of cross-reactive antibodies derived from memory immunity. Specifically, due to a significant degree of sequence similarity between SARS-CoV-2 and other members of the coronavirus family, memory B-cells that emerged from previous infections with endemic human coronaviruses (HCoVs) could be re-activated upon encountering the newly emerged SARS-CoV-2, thus prompting the production of cross-reactive antibodies. Understanding the affinity and concentration of these potentially cross-reactive antibodies to the new SARS-CoV-2 antigens is therefore particularly important when assessing both existing immunity against common HCoVs and adverse effects like antibody-dependent enhancement (ADE) in COVID-19. However, these two fundamental parameters cannot easily be deconvoluted by surface-based assays like enzyme-linked immunosorbent assays (ELISAs) which are routinely used to assess cross-reactivity.\n\nHere, we have used microfluidic antibody-affinity profiling (MAAP) to quantitatively evaluate the humoral immune response in COVID-19 convalescent patients by determining both antibody affinity and concentration against spike antigens of SARS-CoV-2 directly in nine convalescent COVID-19 patient and three pre-pandemic sera that were seropositive for common HCoVs. All 12 sera contained low concentrations of high affinity antibodies against spike antigens of HCoV-NL63 and HCoV-HKU1, indicative of past exposure to these pathogens, while the affinity against the SARS-CoV-2 spike protein was lower. These results suggest that cross-reactivity as a consequence of memory re-activation upon an acute SARS-CoV-2 infection may not be a significant factor in generating immunity against SARS-CoV-2.", - "rel_num_authors": 15, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.07.23.453571", + "rel_abs": "IntroductionIn this series of studies, immunoglobulin products (IgG) formulated for different routes of administration (IV, IM, SC) and prepared from geographically diverse plasma pools were tested for activity against common human coronaviruses (HCoV). IgG products from plasma obtained from Germany, Czech Republic, Slovak Republic, USA and Spain were tested for antibodies to four common HCoV: 229E, OC43, NL63 and HKU1. Since these products are manufactured from pooled plasma from thousands of donors, the antibodies therein are a representation of the HCoV exposure of the population at large.\n\nMethodsIgG products of different concentrations manufactured from geographically diverse plasma pools were tested for antibodies to four common HCoV by ELISA. In addition, neutralization assays were conducted using HCoV-229E expressed in MRC5 cells. Complete concentration-neutralization curves were obtained to calculate potencies.\n\nResultsThe ELISA assays showed that when expressed as specific activity (anti-HCoV activity/mg IgG) similar activity against the four common HCoV was seen across the IgG products regardless of concentration or geographic origin. Highest anti-HCoV activity was seen against HCoV-229E, followed by HCoV-OC43 and then HCoV-NL63 and HCoV-HKU1. The neutralization assays showed similar potency for two preparations of IgG prepared by different processes.\n\nConclusionsThese studies are the first demonstration of antibodies to common HCoV in IgG products. The level of activity was similar regardless of the geographic origin of the plasma pool. These antibodies demonstrated neutralization activity against HCoV-229E in MRC5 cells. These results may explain the cross-reactivity seen with pre-pandemic IgG products and SARS-CoV-2 and contribute to the variability in disease course in different patients.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Viola Denninger", - "author_inst": "Fluidic Analytics, Unit A, The Paddocks Business Centre, Cherry Hinton Road, Cambridge CB1 8DH, United Kingdom" - }, - { - "author_name": "Catherine K. Xu", - "author_inst": "Centre for Misfolding Diseases, Yusuf Hamied Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB2 1EW, United Kingdom" - }, - { - "author_name": "Georg Meisl", - "author_inst": "Centre for Misfolding Diseases, Yusuf Hamied Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB2 1EW, United Kingdom" - }, - { - "author_name": "Alexey S. Morgunov", - "author_inst": "Fluidic Analytics, Unit A, The Paddocks Business Centre, Cherry Hinton Road, Cambridge CB1 8DH, United Kingdom" - }, - { - "author_name": "Sebastian Fiedler", - "author_inst": "Fluidic Analytics, Unit A, The Paddocks Business Centre, Cherry Hinton Road, Cambridge CB1 8DH, United Kingdom" - }, - { - "author_name": "Alison Ilsley", - "author_inst": "Fluidic Analytics, Unit A, The Paddocks Business Centre, Cherry Hinton Road, Cambridge CB1 8DH, United Kingdom" - }, - { - "author_name": "Marc Emmenegger", - "author_inst": "Institute of Neuropathology, University of Zurich, 8091 Zurich, Switzerland" - }, - { - "author_name": "Anisa Y. Malik", - "author_inst": "Fluidic Analytics, Unit A, The Paddocks Business Centre, Cherry Hinton Road, Cambridge CB1 8DH, United Kingdom" - }, - { - "author_name": "Monika A. Piziorska", - "author_inst": "Fluidic Analytics, Unit A, The Paddocks Business Centre, Cherry Hinton Road, Cambridge CB1 8DH, United Kingdom" - }, - { - "author_name": "Matthias M. Schneider", - "author_inst": "Centre for Misfolding Diseases, Yusuf Hamied Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB2 1EW, United Kingdom" - }, - { - "author_name": "Sean R. A. Devenish", - "author_inst": "Fluidic Analytics, Unit A, The Paddocks Business Centre, Cherry Hinton Road, Cambridge CB1 8DH, United Kingdom" - }, - { - "author_name": "Vasilis Kosmoliaptsis", - "author_inst": "Department of Surgery, University of Cambridge, Addenbrookes Hospital, Cambridge, CB2 0QQ, United Kingdom" - }, - { - "author_name": "Adriano Aguzzi", - "author_inst": "Institute of Neuropathology, University of Zurich, 8091 Zurich, Switzerland" + "author_name": "Jos\u00e9-Mar\u00eda D\u00edez", + "author_inst": "Grifols" }, { - "author_name": "Heike Fiegler", - "author_inst": "Fluidic Analytics, Unit A, The Paddocks Business Centre, Cherry Hinton Road, Cambridge CB1 8DH, United Kingdom" + "author_name": "Carolina Romero", + "author_inst": "Grifols" }, { - "author_name": "Tuomas P. J. Knowles", - "author_inst": "Centre for Misfolding Diseases, Yusuf Hamied Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB2 1EW, United Kingdom" + "author_name": "Rodrigo Gajardo", + "author_inst": "Grifols" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by_nc_nd", "type": "new results", - "category": "biophysics" + "category": "immunology" }, { "rel_doi": "10.1101/2021.07.23.453472", @@ -646879,21 +646398,65 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.07.19.21260714", - "rel_title": "Anaphylactic events in mRNA vaccines: a reporting case-control study", + "rel_doi": "10.1101/2021.07.19.21260744", + "rel_title": "Association between reactogenicity and SARS-CoV-2 antibodies after the second dose of the BNT162b2 COVID-19 vaccine", "rel_date": "2021-07-22", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.19.21260714", - "rel_abs": "BackgroundmRNA vaccines are a novel method of eliciting immunity, and play a significant role in the global fight against COVID-19. Anaphylactic reactions are a widespread concern driving vaccine hesitancy due to the serious and potentially fatal nature of anaphylaxis. A quantitative estimation of the risk of anaphylactic and ana-phylactoid reactions deriving from mRNA vaccines is of a significant public health importance.\n\nObjectiveTo estimate the relative Reporting Odds Ratio of anaphylactic and ana-phylactoid reactions following mRNA vaccination vis-a-vis other vaccinations.\n\nDesignReporting case-control study.\n\nSettingPersons reporting adverse events following vaccination to VAERS whose reports were received between 01 January 2000 and 02 July 2021, inclusive.\n\nPatientsEach case of anaphylaxis or anaphylactoid reaction was matched with 2.7 unique controls on average, by gender and age rounded to the nearest integer.\n\nMeasurementsOverall and stratified Reporting Odds Ratios (ROR) were calculated. Stratified contingency tables were tested for homogeneity using the Breslow-Day procedure, and Cochran-Mantel-Haenszel statistics were calculated to test the hypothesis of a ROR of unity.\n\nResults2,665 cases of anaphylaxis or anaphylactoid reactions and 7,125 controls of non-anaphylactic/anaphylactoid reports were compared. The ROR of an anaphylactic or anaphylactoid reaction was 1.325 (95% CI: 1.212 - 1.448, p < 0.001). The matched set of cases and controls revealed an expected inhomogeneity by sex (with women slightly more likely to report anaphylactic presentations) and age band strata (with a bimodal distribution that reflects the common incidence of anaphylactic and allergic pathologies). No significant increase in the risk of anaphylactic adverse events was witnessed among persons who self-reported previous allergic reactions to vaccines. A slightly elevated ROR was observed with patients who reported a history of allergic reactions to NSAIDs and/or fluoroquinolone antibiotics. The precise meaning and relevance of this finding remains to be elucidated.\n\nLimitationsAs a reporting study using data from VAERS, our analysis is subject tunder- and overreporting, the extent of each of which is not known with any degree of precision. Since the Emergency Use Authorizations for both mRNA vaccines mandate reporting of all serious adverse events, reporting bias is likely in favour of non-mRNA vaccines, where such reporting is not mandatory in adults. Consequently, this analysis may exaggerate the ROR of anaphylactic and anaphylactoid events associated with mRNA vaccines, which may in reality be significantly lower.\n\nConclusionsmRNA vaccination is not associated with a statistically significant higher risk of reporting an anaphylactic adverse event to VAERS. Anaphylaxis is a serious but very rare complication of all immunisations. No significant increase in reporting odds was found in any age group or gender, nor in most cases of previously known allergic adverse events in relation to vaccines. This study contributes to the growing body of evidence proving the safety and tolerability of mRNA vaccines.", - "rel_num_authors": 1, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.19.21260744", + "rel_abs": "High vaccine reactogenicities may reflect stronger immune responses, but the epidemiological evidence for coronavirus disease 2019 (COVID-19) vaccines is sparse and inconsistent. We observed that a fever of [≥]38{square} after two doses of the BNT162b2 vaccine was associated with higher severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike IgG titers.", + "rel_num_authors": 12, "rel_authors": [ { - "author_name": "Chris von Csefalvay", - "author_inst": "Starschema" + "author_name": "Shohei Yamamoto", + "author_inst": "National Center for Global Health and Medicine" + }, + { + "author_name": "Ami Fukunaga", + "author_inst": "National Center for Global Medicine" + }, + { + "author_name": "Akihito Tanaka", + "author_inst": "Center Hospital of the National Center for the Global Health and Medicine" + }, + { + "author_name": "Junko S Takeuchi", + "author_inst": "National Center for Global Medicine" + }, + { + "author_name": "Yosuke Inoue", + "author_inst": "National Center for Global Medicine" + }, + { + "author_name": "Moto Kimura", + "author_inst": "National Center for Global Medicine" + }, + { + "author_name": "Gohzoh Ueda", + "author_inst": "National Center for Global Medicine" + }, + { + "author_name": "kenji Maeda", + "author_inst": "National Center for Global Medicine" + }, + { + "author_name": "Tetsuya Mizoue", + "author_inst": "National Center for Global Medicine" + }, + { + "author_name": "Mugen Ujiie", + "author_inst": "National Center for Global Medicine" + }, + { + "author_name": "Wataru Sugiura", + "author_inst": "National Center for Global Medicine" + }, + { + "author_name": "Norio Ohmagari", + "author_inst": "National Center for Global Medicine" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -648929,99 +648492,35 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2021.07.21.21260906", - "rel_title": "Disentangling post-vaccination symptoms from early COVID-19", + "rel_doi": "10.1101/2021.07.21.21260756", + "rel_title": "Workplace risk management for SARS-CoV-2: a three-step early in-tervention strategy for effective containment of infection chains with special regards to virus variants with increased infectivity", "rel_date": "2021-07-22", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.21.21260906", - "rel_abs": "BackgroundIdentifying and testing individuals likely to have SARS-CoV-2 is critical for infection control, including post-vaccination. Vaccination is a major public health strategy to reduce SARS-CoV-2 infection globally. Some individuals experience systemic symptoms post-vaccination, which overlap with COVID-19 symptoms. This study compared early post-vaccination symptoms in individuals who subsequently tested positive or negative for SARS-CoV-2, using data from the COVID Symptom Study (CSS) app.\n\nDesignWe conducted a prospective observational study in UK CSS participants who were asymptomatic when vaccinated with Pfizer-BioNTech mRNA vaccine (BNT162b2) or Oxford-AstraZeneca adenovirus-vectored vaccine (ChAdOx1 nCoV-19) between 8 December 2020 and 17 May 2021, who subsequently reported symptoms within seven days (other than local symptoms at injection site) and were tested for SARS-CoV-2, aiming to differentiate vaccination side-effects per se from superimposed SARS-CoV-2 infection. The post-vaccination symptoms and SARS-CoV-2 test results were contemporaneously logged by participants. Demographic and clinical information (including comorbidities) were also recorded. Symptom profiles in individuals testing positive were compared with a 1:1 matched population testing negative, including using machine learning and multiple models including UK testing criteria.\n\nFindingsDifferentiating post-vaccination side-effects alone from early COVID-19 was challenging, with a sensitivity in identification of individuals testing positive of 0.6 at best. A majority of these individuals did not have fever, persistent cough, or anosmia/dysosmia, requisite symptoms for accessing UK testing; and many only had systemic symptoms commonly seen post-vaccination in individuals negative for SARS-CoV-2 (headache, myalgia, and fatigue).\n\nInterpretationPost-vaccination side-effects per se cannot be differentiated from COVID-19 with clinical robustness, either using symptom profiles or machine-derived models. Individuals presenting with systemic symptoms post-vaccination should be tested for SARS-CoV-2, to prevent community spread.\n\nFundingZoe Limited, UK Government Department of Health and Social Care, Wellcome Trust, UK Engineering and Physical Sciences Research Council, UK National Institute for Health Research, UK Medical Research Council and British Heart Foundation, Alzheimers Society, Chronic Disease Research Foundation, Massachusetts Consortium on Pathogen Readiness (MassCPR).\n\nResearch in contextO_ST_ABSEvidence before this studyC_ST_ABSThere are now multiple surveillance platforms internationally interrogating COVID-19 and/or post-vaccination side-effects. We designed a study to examine for differences between vaccination side-effects and early symptoms of COVID-19. We searched PubMed for peer-reviewed articles published between 1 January 2020 and 21 June 2021, using keywords: \"COVID-19\" AND \"Vaccination\" AND (\"mobile application\" OR \"web tool\" OR \"digital survey\" OR \"early detection\" OR \"Self-reported symptoms\" OR \"side-effects\"). Of 185 results, 25 studies attempted to differentiate symptoms of COVID-19 vs. post-vaccination side-effects; however, none used artificial intelligence (AI) technologies (\"machine learning\") coupled with real-time data collection that also included comprehensive and systematic symptom assessment. Additionally, none of these studies attempt to discriminate the early signs of infection from side-effects of vaccination (specifically here: Pfizer-BioNTech mRNA vaccine (BNT162b2) and Oxford-AstraZeneca adenovirus-vectored vaccine (ChAdOx1 nCoV-19)). Further, none of these studies sought to provide comparisons with current testing criteria used by healthcare services.\n\nAdded value of this studyThis study, in a uniquely large community-based cohort, uses prospective data capture in a novel effort to identify individuals with COVID-19 in the immediate post-vaccination period. Our results show that early symptoms of SARS-CoV-2 cannot be differentiated from vaccination side-effects robustly. Thus, post-vaccination systemic symptoms should not be ignored, and testing should be considered to prevent COVID-19 dissemination by vaccinated individuals.\n\nImplications of all the available evidenceOur study demonstrates the critical importance of testing symptomatic individuals - even if vaccinated - to ensure early detection of SARS-CoV-2 infection, helping to prevent future pandemic waves in the UK and elsewhere.", - "rel_num_authors": 20, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.21.21260756", + "rel_abs": "BackgroundPriority during the SARS-CoV2 pandemic is that employees need to be protected from infection risks and business activities need to be ensured. New virus variants with increased infection risks require an evolved risk strategy.\n\nMaterial and methodsSeveral standard measures such as testing, isolation and quarantine are combined to a novel risk strategy. Epidemiological model calculations and scientific knowledge about the course of SARS-CoV2 infectivity are used to optimize this strategy. The procedure is implemented in an easy-to-use calculator based on Excel.\n\nLayout in practice and resultsAlternative combinations of measures and practical aspects are discussed. Example calculations are used to demonstrate the effect of the discussed measures.\n\nConclusionThat quarantine calculator derived from these principles enables even non-specialists to perform a differentiated risk analysis and to introduce optimized measures. Targeted testing routines and alternative measures ensure staff availability.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Liane S Canas", - "author_inst": "School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK" - }, - { - "author_name": "Marc F. Osterdahl", - "author_inst": "Department of Twin Research and Genetic Epidemiology, Kings College London, London, UK" - }, - { - "author_name": "Jie Deng", - "author_inst": "School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK" - }, - { - "author_name": "Christina Hu", - "author_inst": "ZOE Limited, London, UK" - }, - { - "author_name": "Somesh Selvachandran", - "author_inst": "ZOE Limited, London, UK" - }, - { - "author_name": "Lorenzo Polidori", - "author_inst": "ZOE Limited, London, UK" - }, - { - "author_name": "Anna May", - "author_inst": "ZOE Limited, London, UK" - }, - { - "author_name": "Erika Molteni", - "author_inst": "School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK" - }, - { - "author_name": "Benjamin Murray", - "author_inst": "School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK" - }, - { - "author_name": "Liyuan Chen", - "author_inst": "School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK" - }, - { - "author_name": "Eric Kerfoot", - "author_inst": "School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK" + "author_name": "Andreas Paassen", + "author_inst": "Medical Services, Marl Chemical Park, Evonik Industries AG" }, { - "author_name": "Kerstin Klaser", - "author_inst": "School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK" + "author_name": "Laura Anderle", + "author_inst": "Westphalian University of Applied Sciences, Gelsenkirchen, Germany" }, { - "author_name": "Michela Antonelli", - "author_inst": "School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK" + "author_name": "Karsten John", + "author_inst": "Medical Services, Marl Chemical Park, Evonik Industries AG" }, { - "author_name": "Alexander Hammers", - "author_inst": "School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK; King's College London & Guy's and St Thomas' PET Centre, London, UK" - }, - { - "author_name": "Tim Spector", - "author_inst": "Department of Twin Research and Genetic Epidemiology, Kings College London, London, UK." - }, - { - "author_name": "Sebastien Ourselin", - "author_inst": "School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK" - }, - { - "author_name": "Claire J. Steves", - "author_inst": "Department of Twin Research and Genetic Epidemiology, Kings College London, London, UK." - }, - { - "author_name": "Carole H. Sudre", - "author_inst": "School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK; Medical Research Council Unit for Lifelong Health and Ageing, Departme" - }, - { - "author_name": "Marc Modat", - "author_inst": "School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK" - }, - { - "author_name": "Emma L. Duncan", - "author_inst": "Department of Twin Research and Genetic Epidemiology, Kings College London, London, UK." + "author_name": "Sebastian Wilbrand", + "author_inst": "Medical Services, Marl Chemical Park, Evonik Industries AG" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "respiratory medicine" + "category": "occupational and environmental health" }, { "rel_doi": "10.1101/2021.07.20.21260853", @@ -650591,115 +650090,59 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.07.19.21260803", - "rel_title": "B cell numbers predict humoral and cellular response upon SARS-CoV-2 vaccination among patients treated with rituximab", + "rel_doi": "10.1101/2021.07.22.453029", + "rel_title": "CD8+ T cell signature in acute SARS-CoV-2 infection identifies memory precursors", "rel_date": "2021-07-22", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.19.21260803", - "rel_abs": "ObjectivesPatients with autoimmune inflammatory rheumatic diseases receiving rituximab (RTX) therapy show substantially impaired anti-SARS-CoV-2 vaccine humoral but partly inducible cellular immune responses. However, the complex relationship between antigen-specific B and T cells and the level of B cell repopulation necessary to achieve anti-vaccine responses remain largely unknown.\n\nMethodsAntibody responses to SARS-CoV-2 vaccines and induction of antigen-specific B and CD4/CD8 T cell subsets were studied in 19 rheumatoid arthritis (RA) and ANCA-associated vasculitis (AAV) patients receiving RTX, 12 RA patients on other therapies and 30 healthy controls after SARS-CoV-2 vaccination with either mRNA or vector based vaccines.\n\nResultsA minimum of 10 B cells/{micro}L in the peripheral circulation was necessary in RTX patients to mount seroconversion to anti-S1 IgG upon SARS-CoV-2 vaccination. RTX patients lacking IgG seroconversion showed reduced antigen-specific B cells, lower frequency of TfH-like cells as well as less activated CD4 and CD8 T cells compared to IgG seroconverted RTX patients. Functionally relevant B cell depletion resulted in impaired IFN{gamma} secretion by spike-specific CD4 T cells. In contrast, antigen-specific CD8 T cells were reduced in patients independently of IgG formation.\n\nConclusionsPatients receiving rituximab with B cell numbers above 10 B cells/{micro}l were able to mount humoral and more robust cellular responses after SARS-CoV-2 vaccination that may permit optimization of vaccination in these patients. Mechanistically, the data emphasize the crucial role of co-stimulatory B cell functions for the proper induction of CD4 responses propagating vaccine-specific B and plasma cell differentiation.", - "rel_num_authors": 24, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2021.07.22.453029", + "rel_abs": "Immunological memory is a hallmark of adaptive immunity and facilitates an accelerated and enhanced immune response upon re-infection with the same pathogen1,2. Since the outbreak of the ongoing coronavirus disease 19 (COVID-19) pandemic, a key question has focused on whether severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-specific T cells stimulated during acute infection give rise to long-lived memory T cells3. Using spectral flow cytometry combined with cellular indexing of transcriptomes and T cell receptor (TCR) sequencing we longitudinally characterize individual SARS-CoV-2-specific CD8+ T cells of COVID-19 patients from acute infection to one year into recovery and find a distinct signature identifying long-lived memory CD8+ T cells. SARS-CoV-2-specific memory CD8+ T cells persisting one year after acute infection re-express CD45RA and interleukin-7 receptor (CD127), upregulate T cell factor-1 (TCF1), and maintain low CCR7, thus resembling CD45RA+ effector-memory T (TEMRA) cells. Tracking individual clones of SARS-CoV-2-specific CD8+ T cells, we reveal that an interferon signature marks clones giving rise to long-lived cells, whereas prolonged proliferation and mammalian target of rapamycin (mTOR) signaling are associated with clone contraction and disappearance. Collectively, we identify a transcriptional signature differentiating short-from long-lived memory CD8+ T cells following an acute virus infection in humans.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Ana-Luisa Stefanski", - "author_inst": "Department of Rheumatology and Clinical Immunology, Charite Universitatsmedizin Berlin, Berlin, Germany" - }, - { - "author_name": "Hector Rincon-Arevalo", - "author_inst": "Department of Rheumatology and Clinical Immunology, Charite Universitatsmedizin Berlin, Berlin, Germany" - }, - { - "author_name": "Eva Schrezenmeier", - "author_inst": "Department of Nephrology and Medical Intensive Care, Charite Universitatsmedizin Berlin, Berlin, Germany" - }, - { - "author_name": "Kirsten Karberg", - "author_inst": "Rheumatology outpatient office Berlin, Germany" - }, - { - "author_name": "Franziska Szelinski", - "author_inst": "Department of Rheumatology and Clinical Immunology, Charite Universitatsmedizin Berlin, Berlin, Germany" - }, - { - "author_name": "Jacob Ritter", - "author_inst": "Department of Rheumatology and Clinical Immunology, Charite Universitatsmedizin Berlin, Berlin, Germany" - }, - { - "author_name": "Bernd Jahrsdoerfer", - "author_inst": "Institute of Transfusion Medicine, Ulm University, Ulm, Germany and Institute for Clinical Transfusion Medicine and Immunogenetics, German Red Cross Blood Trans" - }, - { - "author_name": "Hubert Schrezenmeier", - "author_inst": "Institute of Transfusion Medicine, Ulm University, Ulm, Germany and Institute for Clinical Transfusion Medicine and Immunogenetics, German Red Cross Blood Trans" - }, - { - "author_name": "Carolin Ludwig", - "author_inst": "Institute of Transfusion Medicine, Ulm University, Ulm, Germany and Institute for Clinical Transfusion Medicine and Immunogenetics, German Red Cross Blood Trans" - }, - { - "author_name": "Arne Sattler", - "author_inst": "Department for General, Visceral and Vascular Surgery, Charite Universitatsmedizin Berlin, Berlin, Germany" - }, - { - "author_name": "Katja Kotsch", - "author_inst": "Department for General, Visceral and Vascular Surgery, Charite Universitatsmedizin Berlin, Berlin, Germany" - }, - { - "author_name": "Yidan Chen", - "author_inst": "Department of Rheumatology and Clinical Immunology, Charite Universitatsmedizin Berlin, Berlin, Germany" - }, - { - "author_name": "Anne Claussnitzer", - "author_inst": "AGZ Rheumatology Charite Berlin, Germany" - }, - { - "author_name": "Hildrun Haibel", - "author_inst": "Department of Gastroenterology, Infectiology and Rheumatology (including Nutrition Medicine), Charite Universitatsmedizin Berlin, Berlin, Germany" - }, - { - "author_name": "Fabian Proft", - "author_inst": "Department of Gastroenterology, Infectiology and Rheumatology (including Nutrition Medicine), Charite Universitatsmedizin Berlin, Berlin, Germany" + "author_name": "Sarah Adamo", + "author_inst": "University Hospital Zurich" }, { - "author_name": "Gabriella Maria Guerra", - "author_inst": "Deutsches Rheumaforschungszentrum (DRFZ), Berlin, Germany" + "author_name": "Jan Michler", + "author_inst": "ETH Zurich" }, { - "author_name": "Pawel Durek", - "author_inst": "Deutsches Rheumaforschungszentrum (DRFZ), Berlin, Germany" + "author_name": "Yves Zurbuchen", + "author_inst": "University Hospital Zurich" }, { - "author_name": "Frederik Heinrich", - "author_inst": "Deutsches Rheumaforschungszentrum (DRFZ), Berlin, Germany" + "author_name": "Carlo Cervia", + "author_inst": "University Hospital Zurich" }, { - "author_name": "Marta Ferreira Gomes", - "author_inst": "Deutsches Rheumaforschungszentrum (DRFZ), Berlin, Germany" + "author_name": "Patrick Taeschler", + "author_inst": "University Hospital Zurich" }, { - "author_name": "Gerd R. Burmester", - "author_inst": "Department of Rheumatology and Clinical Immunology, Charite Universitatsmedizin Berlin, Berlin, Germany" + "author_name": "Miro E. Raeber", + "author_inst": "University Hospital Zurich" }, { - "author_name": "Andreas Radbruch", - "author_inst": "Deutsches Rheumaforschungszentrum (DRFZ), Berlin, Germany" + "author_name": "Simona Baghai Sain", + "author_inst": "ETH Zurich" }, { - "author_name": "Mir-Farzin Mashreghi", - "author_inst": "Deutsches Rheumaforschungszentrum (DRFZ), Berlin, Germany" + "author_name": "Jakob Nilsson", + "author_inst": "University Hospital Zurich" }, { - "author_name": "Andreia C. Lino", - "author_inst": "Deutsches Rheumaforschungszentrum (DRFZ), Berlin, Germany" + "author_name": "Andreas Moor", + "author_inst": "ETH Zurich" }, { - "author_name": "Thomas Doerner", - "author_inst": "Department of Rheumatology and Clinical Immunology, Charite Universitatsmedizin Berlin, Berlin, Germany" + "author_name": "Onur Boyman", + "author_inst": "University Hospital Zurich" } ], "version": "1", - "license": "cc_no", - "type": "PUBLISHAHEADOFPRINT", - "category": "rheumatology" + "license": "cc_by_nc_nd", + "type": "new results", + "category": "immunology" }, { "rel_doi": "10.1101/2021.07.21.21260904", @@ -652545,53 +651988,109 @@ "category": "respiratory medicine" }, { - "rel_doi": "10.1101/2021.07.17.452778", - "rel_title": "HLA-dependent variation in SARS-CoV-2 CD8+ T cell cross-reactivity with human coronaviruses", + "rel_doi": "10.1101/2021.07.20.453011", + "rel_title": "Previously unrecognized non-reproducible antibody-antigen interactions and their implications for diagnosis of viral infections including COVID-19", "rel_date": "2021-07-20", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.07.17.452778", - "rel_abs": "Pre-existing T cell immunity to SARS-CoV-2 in individuals without prior exposure to SARS-CoV-2 has been reported in several studies. While emerging evidence hints toward prior exposure to common-cold human coronaviruses (HCoV), the extent of- and conditions for-cross-protective immunity between SARS-CoV-2 and HCoVs remain open. Here, by leveraging a comprehensive pool of publicly available functionally evaluated SARS-CoV-2 peptides, we report 126 immunogenic SARS-CoV-2 peptides with high sequence similarity to 285 MHC-presented target peptides from at least one of four HCoV, thus providing a map describing the landscape of SARS-CoV-2 shared and private immunogenic peptides with functionally validated T cell responses. Using this map, we show that while SARS-CoV-2 immunogenic peptides in general exhibit higher level of dissimilarity to both self-proteome and -microbiomes, there exist several SARS-CoV-2 immunogenic peptides with high similarity to various human protein coding genes, some of which have been reported to have elevated expression in severe COVID-19 patients. We then combine our map with a SARS-CoV-2-specific TCR repertoire data from COVID-19 patients and healthy controls and show that whereas the public repertoire for the majority of convalescent patients are dominated by TCRs cognate to private SARS-CoV-2 peptides, for a subset of patients, more than 50% of their public repertoires that show reactivity to SARS-CoV-2, consist of TCRs cognate to shared SARS-CoV-2-HCoV peptides. Further analyses suggest that the skewed distribution of TCRs cognate to shared and private peptides in COVID-19 patients is likely to be HLA-dependent. Finally, by utilising the global prevalence of HLA alleles, we provide 10 peptides with known cognate TCRs that are conserved across SARS-CoV-2 and multiple human coronaviruses and are predicted to be recognised by a high proportion of the global population. Overall, our work indicates the potential for HCoV-SARS-CoV-2 reactive CD8+ T cells, which is likely dependent on differences in HLA-coding genes among individuals. These findings may have important implications for COVID-19 heterogeneity and vaccine-induced immune responses as well as robustness of immunity to SARS-CoV-2 and its variants.", - "rel_num_authors": 9, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.07.20.453011", + "rel_abs": "Antibody-antigen (Ab-Ag) interactions are canonically described by a model which exclusively accommodates non-interaction (0) or reproducible-interaction (RI) states, yet this model is inadequate to explain often-encountered non-reproducible signals. Here, by monitoring diverse experimental systems and confirmed COVID-19 clinical sera using a peptide microarray, we observed that non-specific interactions (NSI) comprise a substantial proportion of non-reproducible antibody-based results. This enabled our discovery and capacity to reliably identify non-reproducible Ab-Ag interactions (NRI), as well as our development of a powerful explanatory model (\"0-RI-NRI-Hook four-state model\") that is [mAb]-dependent, regardless of specificity, which ultimately shows that both NSI and NRI are not predictable yet certain-to-happen. In experiments using seven FDA-approved mAb drugs, we demonstrated the use of NSI counts in predicting epitope type. Beyond challenging the centrality of Ab-Ag interaction specificity data in serology and immunology, our discoveries also facilitated the rapid development of a serological test with uniquely informative COVID-19 diagnosis performance.", + "rel_num_authors": 23, "rel_authors": [ { - "author_name": "Paul Buckley", - "author_inst": "Oxford University" + "author_name": "Jiaojiao Pan", + "author_inst": "Division of Nanobiomedicine, Suzhou Institute of Nano-Tech and Nano-Bionics, Chinese Academy of Sciences, Suzhou, 215123, China." }, { - "author_name": "Chloe Hyun-jung Lee", - "author_inst": "Oxford University" + "author_name": "Lan Yang", + "author_inst": "Division of Nanobiomedicine, Suzhou Institute of Nano-Tech and Nano-Bionics, Chinese Academy of Sciences, Suzhou, 215123, China." }, { - "author_name": "Mariana Pereira Pinho", - "author_inst": "Oxford University" + "author_name": "Yi Deng", + "author_inst": "Division of Nanobiomedicine, Suzhou Institute of Nano-Tech and Nano-Bionics, Chinese Academy of Sciences, Suzhou, 215123, China." }, { - "author_name": "Rosana Ottakandathil Babu", - "author_inst": "Oxford University" + "author_name": "Baoqing Sun", + "author_inst": "Department of Allergy and Clinical Immunology, Guangzhou Institute of Respiratory Health, State Key Laboratory of Respiratory Disease, The First Affiliated Hosp" }, { - "author_name": "Jeongmin Woo", - "author_inst": "Oxford University" + "author_name": "Li Zhang", + "author_inst": "Department of Vaccine Clinical Evaluation, Jiangsu Provincial Center for Disease Prevention and Control, Nanjing, 210009, China." }, { - "author_name": "Agne Antanaviciute", - "author_inst": "Oxford University" + "author_name": "Wenya Wu", + "author_inst": "Division of Nanobiomedicine, Suzhou Institute of Nano-Tech and Nano-Bionics, Chinese Academy of Sciences, Suzhou, 215123, China." }, { - "author_name": "Alison Simmons", - "author_inst": "The University of Oxford" + "author_name": "Jingzhi Li", + "author_inst": "Division of Nanobiomedicine, Suzhou Institute of Nano-Tech and Nano-Bionics, Chinese Academy of Sciences, Suzhou, 215123, China." }, { - "author_name": "Graham Ogg", - "author_inst": "The University of Oxford" + "author_name": "Hu Cheng", + "author_inst": "Division of Nanobiomedicine, Suzhou Institute of Nano-Tech and Nano-Bionics, Chinese Academy of Sciences, Suzhou, 215123, China." }, { - "author_name": "Hashem Koohy", - "author_inst": "The University of Oxford" + "author_name": "Yiting Li", + "author_inst": "Division of Nanobiomedicine, Suzhou Institute of Nano-Tech and Nano-Bionics, Chinese Academy of Sciences, Suzhou, 215123, China." + }, + { + "author_name": "Wenwen Xu", + "author_inst": "Division of Nanobiomedicine, Suzhou Institute of Nano-Tech and Nano-Bionics, Chinese Academy of Sciences, Suzhou, 215123, China." + }, + { + "author_name": "Jiao Yang", + "author_inst": "Division of Nanobiomedicine, Suzhou Institute of Nano-Tech and Nano-Bionics, Chinese Academy of Sciences, Suzhou, 215123, China." + }, + { + "author_name": "Yiyue Sun", + "author_inst": "Division of Nanobiomedicine, Suzhou Institute of Nano-Tech and Nano-Bionics, Chinese Academy of Sciences, Suzhou, 215123, China." + }, + { + "author_name": "Hao Fei", + "author_inst": "Division of Nanobiomedicine, Suzhou Institute of Nano-Tech and Nano-Bionics, Chinese Academy of Sciences, Suzhou, 215123, China." + }, + { + "author_name": "Qinghong Xue", + "author_inst": "China Institute of Veterinary Drug Control, Beijing 100081, China." + }, + { + "author_name": "Youxin Zhou", + "author_inst": "Department of Neurosurgery & Brain and Nerve Research Laboratory, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu 215006, China." + }, + { + "author_name": "Hui Wang", + "author_inst": "Department of Medical Laboratory, The Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and" + }, + { + "author_name": "Peiyan Zheng", + "author_inst": "Department of Allergy and Clinical Immunology, Guangzhou Institute of Respiratory Health, State Key Laboratory of Respiratory Disease, The First Affiliated Hosp" + }, + { + "author_name": "Hao Chen", + "author_inst": "Department of Allergy and Clinical Immunology, Guangzhou Institute of Respiratory Health, State Key Laboratory of Respiratory Disease, The First Affiliated Hosp" + }, + { + "author_name": "Feng Cai Zhu", + "author_inst": "NHC Key laboratory of Enteric Pathogenic Microbiology (Jiangsu Provincial Center for Disease Control" + }, + { + "author_name": "Daxin Peng", + "author_inst": "Colledge of Veterinary Medicine, Yangzhou University, Yangzhou, Jiangsu 225009, China." + }, + { + "author_name": "Jun Han", + "author_inst": "MHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and Prevention, China CDC, Beijing, China" + }, + { + "author_name": "Jiwan Qiu", + "author_inst": "Qyuns Therapeutics, Taizhou, Jiangsu 225316, China." + }, + { + "author_name": "Hongwei Ma", + "author_inst": "Division of Nanobiomedicine, Suzhou Institute of Nano-Tech and Nano-Bionics, Chinese Academy of Sciences, Suzhou, 215123, China." } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "new results", "category": "immunology" }, @@ -654387,55 +653886,59 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.07.16.21260630", - "rel_title": "ABO and Rh blood groups, demographics, and comorbidities in COVID-19 related deaths: a retrospective study in Split-Dalmatia County, Croatia", + "rel_doi": "10.1101/2021.07.16.21260642", + "rel_title": "Vaccination is Australia's most important COVID-19 public health action, even though herd immunity is unlikely", "rel_date": "2021-07-19", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.16.21260630", - "rel_abs": "AimTo examine ABO and Rh blood group distribution in COVID-19 related deaths considering demographics and pathological conditions.\n\nMaterials and MethodsWe conducted a retrospective study at the University Hospital Centre Split, Croatia, that included 245 COVID-positive individuals that died from April 8, 2020, to January 25, 2021. From the hospital database, we extracted data on their blood groups, demographics, and pre-existing comorbidities. To compare findings with the general population, we used information from collected blood group donations (n = 101357) and statistical reports of non-COVID deaths from 2019 (n = 4968).\n\nResultsThe proportion of males was significantly higher in analyzed subjects than in non- COVID deaths from 2019 (63.7% vs. 48.9%, P < 0.001), while the proportion of older individuals did not differ (P = 0.8). The most common pre-existing diseases were hypertension (59.6%), diabetes (37.1%), heart failure (28.8%), digestive disorder (26.5%), and solid tumor (21.6%). The ABO distribution in the deceased and donors group showed statistically significant differences, with the higher prevalence of A/AB group and lower prevalence of 0, but with individual differences significant only for AB and non-AB groups. There was a significantly reduced proportion of females within the deceased with group 0 (P = 0.014) and a higher proportion of AB individuals with coronary heart disease (P = 0.024), while other differences were not significant.\n\nConclusionThe study confirmed a higher risk of death in male individuals. The lower proportion of type 0 in deceased individuals was more pronounced in females, implying that group 0 is not necessarily an independent protective factor. Among analyzed comorbidities, coronary heart disease was identified as a potential risk factor for AB individuals.", - "rel_num_authors": 9, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.16.21260642", + "rel_abs": "The Australian National Cabinet four-step plan to transition to post-pandemic re-opening begins with vaccination to achieve herd protection and protection of the health system against a surge in COVID-19 cases. Assuming a pre-vaccination reproduction number for the Delta variant of 5, we show that for the current Mixed program of vaccinating over 60s with AstraZeneca and 16-60s with Pfizer we would not achieve herd immunity. We would need to cover 85% of the population (including many 5-16 year-olds to achieve herd immunity).\n\nAt lower reproduction number of 3 and our current Mixed strategy, we can achieve herd immunity without vaccinating 5-15 year olds. This will be achieved at a 60% coverage pursuing a strategy targetting high transmitters or 70% coverage using a strategy targetting the vulnerable first. A reproduction number of 7 precludes achieving herd immunity, however vaccination is able to prevent 75% of deaths compared with no vaccination.\n\nWe also examine the impact of vaccination on death in the event that herd immunity is not achieved. Direct effects of vaccination on reducing death are very good for both Pfizer and AstraZeneca vaccines. However we estimate that the Mixed or Pfizer program performs better than the AstraZeneca program.\n\nFurthermore, vaccination levels below the herd immunity threshold can lead to substantial (albeit incomplete) indirect protection for both vaccinated and unvaccinated populations. Given the potential for not reaching herd immunity, we need to consider what level of severe disease and death is acceptable, balanced against the consequences of ongoing aggressive control strategies.\n\nO_TEXTBOXThe known: SARS CoV-2 variants are known to be more transmissible than the original Wuhan strain, making herd immunity challenging.\n\nThe new: We find that vaccinating the older-vulnerable age groups first leads to fewer deaths and is the optimal strategy vaccine coverage is under 70%. Herd immunity achieved solely through vaccinating adults is unlikely, but can still be expected to prevent substantial numbers of deaths.\n\nThe implications: Australia is unlikely to achieve herd immunity unless vaccination is combined with substantial public health measures. Even without herd immunity, vaccination remains a highly effective means to mitigate the impact of COVID-19.\n\nC_TEXTBOX", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Ivan Brdar", - "author_inst": "Department of Internal Emergency Medicine, Split University Hospital Centre, Split, Croatia" + "author_name": "Emma S McBryde", + "author_inst": "James Cook University" }, { - "author_name": "Ivan Jerkovi\u0107", - "author_inst": "University Department of Forensic Sciences, University of Split, Split, Croatia" + "author_name": "Michael T Meehan", + "author_inst": "James Cook University" }, { - "author_name": "\u017deljana Ba\u0161i\u0107", - "author_inst": "University Department of Forensic Sciences, University of Split, Split, Croatia" + "author_name": "Jamie Sziklay", + "author_inst": "University of Hawaii" }, { - "author_name": "Nenad Kunac", - "author_inst": "Department of Pathology, Forensic Medicine and Cytology, Split University Hospital Centre, Split, Croatia" + "author_name": "Adeshina Adekunle", + "author_inst": "Department of Defence" }, { - "author_name": "Deny An\u0111elinovi\u0107", - "author_inst": "Department of Dermatovenerology, University Hospital Center Split, Split, Croatia" + "author_name": "Abdul Kuddus", + "author_inst": "James Cook University" }, { - "author_name": "Jo\u0161ko Bezi\u0107", - "author_inst": "Department of Pathology, Forensic Medicine and Cytology, Split University Hospital Centre, Split, Croatia" + "author_name": "Samson Ogunlade", + "author_inst": "James Cook University" }, { - "author_name": "Ivana Kru\u017ei\u0107", - "author_inst": "University Department of Forensic Sciences, University of Split, Split, Croatia" + "author_name": "Pavithra Jayasundara", + "author_inst": "University of Monash" }, { - "author_name": "Arijana Vuko", - "author_inst": "Department of Pathology, Forensic Medicine and Cytology, Split University Hospital Centre, Split, Croatia" + "author_name": "Romain Ragonnet", + "author_inst": "Monash University" }, { - "author_name": "\u0160imun An\u0111elinovi\u0107", - "author_inst": "Department of Pathology, Forensic Medicine and Cytology, Split University Hospital Centre, Split, Croatia; School of Medicine, University of Split, Split, Croat" + "author_name": "James M Trauer", + "author_inst": "Monash University" + }, + { + "author_name": "Robert C Cope", + "author_inst": "Australian National University" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2021.07.19.21260644", @@ -656285,53 +655788,53 @@ "category": "hiv aids" }, { - "rel_doi": "10.1101/2021.07.12.21260377", - "rel_title": "Impact of BNT162b2 vaccination and isolation on SARS-CoV-2 transmission in Israeli households: an observational study", + "rel_doi": "10.1101/2021.07.12.21260385", + "rel_title": "Estimating the effectiveness of first dose of COVID-19 vaccine against mortality in England: a quasi-experimental study", "rel_date": "2021-07-16", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.12.21260377", - "rel_abs": "BackgroundMassive vaccination rollouts against SARS-CoV-2 infections have facilitated the easing of control measures in countries like Israel. While several studies have characterized the effectiveness of vaccines against severe forms of COVID-19 or SARS-CoV-2 infection, estimates of their impact on transmissibility remain limited. Here, we evaluated the role of vaccination and isolation on SARS-CoV-2 transmission within Israeli households.\n\nMethodsFrom December 2020 to April 2021, confirmed cases were identified among healthcare workers of the Sheba Medical Centre and their family members. Households were recruited and followed up with repeated PCR for a minimum of ten days after case confirmation. Symptoms and vaccination information were collected at the end of follow-up. We developed a data augmentation Bayesian framework to ascertain how age, isolation and BNT162b2 vaccination with more than 7 days after the 2nd dose impacted household transmission of SARS-CoV-2.\n\nFindings210 households with 215 index cases were enrolled. 269 out of 687 (39%) household contacts developed a SARS-CoV-2 infection. Of those, 170 (63%) developed symptoms. Children below 12 years old were less susceptible than adults/teenagers (Relative Risk RR=0{middle dot}50, 95% Credible Interval CI 0{middle dot}32-0{middle dot}79). Vaccination reduced the risk of infection among adults/teenagers (RR=0{middle dot}19, 95% CI 0{middle dot}07-0{middle dot}40). Isolation reduced the risk of infection of unvaccinated adult/teenager (RR=0{middle dot}11, 95% CI 0{middle dot}05-0{middle dot}19) and child contacts (RR=0{middle dot}16, 95% CI 0{middle dot}07-0{middle dot}31) compared to unvaccinated adults/teenagers that did not isolate. Infectivity was significantly reduced in vaccinated cases (RR=0{middle dot}22, 95% CI 0{middle dot}06-0{middle dot}70).\n\nInterpretationWithin households, vaccination reduces both the risk of infection and of transmission if infected. When contacts were not vaccinated, isolation also led to important reductions in the risk of transmission. Vaccinated contacts might reduce their risk of infection if they isolate, although this requires confirmation with additional data.\n\nFundingSheba Medical Center.\n\nResearch in contextO_ST_ABSEvidence before this studyC_ST_ABSThe efficacy of vaccination against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmissions in households remains understudied. On June 28, 2021, we searched PubMed and medRxiv for articles published between December 1, 2020, and June 28, 2021, using the following combination of search terms: (\"COVID-19\" OR \"SARS-CoV-2\") AND (\"household*\" OR \"famil*\") AND \"transmission\" AND \"vaccination\". Our search yielded two articles that investigated the effect of vaccination on SARS-CoV-2 transmission in households. They showed a lower risk of infection in households with vaccinees. Vaccine efficacy on the risk of infection was estimated to 80% after the 2nd dose, and vaccine efficacy on the risk of transmission if infected was estimated to 49% 21 days after the 1st dose. However, these estimates are derived from surveillance data with no active follow-up of the households. In addition, the impact of isolation precautions has not been assessed.\n\nAdded value of this studyBased on the active follow-up of households of health care workers from the Sheba Medical Center in Israel, we estimated the effect of vaccination on household transmission. To our knowledge, our study is the first to conjointly investigate the effect of vaccination, age, and isolation precautions on the risk of infection and the risk of transmission in households while accounting for tertiary infections in the household, infections within the community, the reduced infectivity of asymptomatic cases, misidentification of index cases, and household size. Our study confirmed the high efficacy of BNT-162b2 vaccination to reduce infection risk and transmission risk. It also suggests that isolation might remain beneficial to vaccinated contacts.\n\nImplications of all the available evidenceVaccination reduces susceptibility to infection and case infectivity in households. Isolation precautions also mitigate the risk of infection and should be implemented whenever a household member is infected. They might remain beneficial to vaccinated contacts.", + "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.12.21260385", + "rel_abs": "BackgroundEstimating real-world vaccine effectiveness is vital to assess the impact of the vaccination programme on the pandemic and inform the ongoing policy response. However, estimating vaccine effectiveness using observational data is inherently challenging because of the non-randomised design and the potential for unmeasured confounding.\n\nMethodsWe used a Regression Discontinuity Design (RDD) to estimate vaccine effectiveness against COVID-19 mortality in England, exploiting the discontinuity in vaccination rates resulting from the UKs age-based vaccination priority groups. We used the fact that people aged 80 or over were prioritised for the vaccine roll-out in the UK to compare the risk of COVID-19 and non-COVID-19 death in people aged 75-79 and 80-84.\n\nFindingsThe prioritisation of vaccination of people aged 80 or above led to a large discrepancy in vaccination rates in people 80-84 compared to those 75-79 at the beginning of the vaccination campaign. We found a corresponding difference in COVID-19 mortality, but not in non-COVID-19 mortality, suggesting that our approach appropriately addresses the issue of unmeasured confounding factors. Our results suggest that the first vaccine dose reduced the risk of COVID-19 death by 52.6% (95% Cl 26.6-84.2) in those aged 80.\n\nInterpretationsOur results support existing evidence that a first dose of a COVID-19 vaccine has a strong protective effect against COVID-19 mortality in older adults. The RDD estimate of vaccine effectiveness is comparable to previously published studies using different methods, suggesting that unmeasured confounding factors are unlikely to substantially bias these studies.\n\nFundingOffice for National Statistics.\n\nResearch in ContextO_ST_ABSEvidence before this studyC_ST_ABSWe searched PubMed for studies reporting on the real-world effectiveness of the COVID-19 vaccination on risk of death using terms such as \"COVID-19\", \"vaccine effectiveness\", \"mortality\" and \"death\". The relevant published studies on this topic report vaccine effectiveness estimates against risk of death ranging from 64.2% to 98.7%, for varying times post-vaccination. All of these are observational studies and therefore potentially subject to bias from unmeasured confounding. We found no studies that used a quasi-experimental method such as regression discontinuity design, which is not subject to bias from unmeasured confounding, to calculate the effectiveness of the COVID-19 vaccination on risk of COVID-19 death, or on other outcomes such as hospitalisation or infection.\n\nAdded value of this studyThe estimates of vaccine effectiveness based on observational data may be biased by unmeasured confounding. This study uses a regression discontinuity design to estimate vaccine effectiveness, exploiting the fact that the vaccination campaign in the UK was rolled out following age-based priority groups. This enables the calculation of an unbiased estimate of the effectiveness of the COVID-19 vaccine against risk of death.\n\nThe vaccine effectiveness estimate of 52.6% (95% Cl 26.6-84.2) is slightly lower but similar to previously published estimates, therefore suggesting that these estimates are not substantially affected by unmeasured confounding factors and confirming the effectiveness of the COVID-19 vaccine against risk of COVID-19 death.\n\nImplications of all the available evidenceObtaining an unbiased estimate of COVID-19 vaccine effectiveness is of vital importance in informing policy for lifting COVID-19 related measures. The regression discontinuity design provides confidence that the existing estimates from observational studies are unlikely to be substantially biased by unmeasured confounding.", "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Maylis Layan", - "author_inst": "Institut Pasteur" + "author_name": "Charlotte Bermingham", + "author_inst": "Office for National Statistics, Newport, UK" }, { - "author_name": "Mayan Gilboa", - "author_inst": "Sheba Medical Center" + "author_name": "Jasper Morgan", + "author_inst": "Office for National Statistics, Newport, UK" }, { - "author_name": "Tal Gonen", - "author_inst": "Sheba Medical Center" + "author_name": "Daniel Ayoubkhani", + "author_inst": "Office for National Statistics, Newport, UK" }, { - "author_name": "Miki Goldenfeld", - "author_inst": "Sheba Medical Center" + "author_name": "Myer Glickman", + "author_inst": "Office for National Statistics, Newport, UK" }, { - "author_name": "Lilac Meltzer", - "author_inst": "Sheba Medical Center" + "author_name": "Nazrul Islam", + "author_inst": "Nuffield Department of Population Health, Big Data Institute, University of Oxford, Oxford, UK" }, { - "author_name": "Alessio Andronico", - "author_inst": "Institut Pasteur" + "author_name": "Aziz Sheikh", + "author_inst": "Usher Institute, University of Edinburgh, Edinburgh, UK; Health Data Research UK BREATHE Hub" }, { - "author_name": "Nathanael Hoze", - "author_inst": "Institut Pasteur" + "author_name": "Jonathan Sterne", + "author_inst": "Bristol Medical School, University of Bristol, UK" }, { - "author_name": "Simon Cauchemez", - "author_inst": "Institut Pasteur" + "author_name": "A. Sarah Walker", + "author_inst": "Nuffield department of Medicine, University of Oxford, Oxford, UK" }, { - "author_name": "Gili Regev-Yochay", - "author_inst": "Sheba Medical Center, Israel" + "author_name": "Vah\u00e9 Nafilyan", + "author_inst": "Office for National Statistics, Newport, UK" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -658079,55 +657582,87 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2021.07.16.452680", - "rel_title": "Intestinal organoids expose heterogeneity in SARS-CoV-2 susceptibility", + "rel_doi": "10.1101/2021.07.14.21260488", + "rel_title": "SARS-CoV-2 Antibody Lateral Flow Assay for antibody prevalence studies following vaccine roll out: a Diagnostic Accuracy Study", "rel_date": "2021-07-16", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.07.16.452680", - "rel_abs": "Gastrointestinal effects associated with COVID-19 are highly variable for reasons that are not understood. In this study, we used intestinal organoid-derived cultures differentiated from primary human specimens as a model to examine inter-individual variability. Infection of intestinal organoids derived from different donors with SARS-CoV-2 resulted in orders of magnitude differences in virus replication in small intestinal and colonic organoid-derived monolayers. Susceptibility to infection correlated with ACE2 expression level and was independent of donor demographic or clinical features. ACE2 transcript levels in cell culture matched the amount of ACE2 in primary tissue indicating this feature of the intestinal epithelium is retained in the organoids. Longitudinal transcriptomics of organoid-derived monolayers identified a delayed yet robust interferon signature, the magnitude of which corresponded to the degree of SARS-CoV-2 infection. Interestingly, virus with the Omicron variant spike protein infected the organoids with the highest infectivity, suggesting increased tropism of the virus for intestinal tissue. These results suggest that heterogeneity in SARS-CoV-2 replication in intestinal tissues results from differences in ACE2 levels, which may underlie variable patient outcomes.", - "rel_num_authors": 9, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.14.21260488", + "rel_abs": "BackgroundLateral flow immunoassays (LFIAs) have the potential to deliver affordable, large scale antibody testing and provide rapid results without the support of central laboratories. As part of the development of the REACT programme extensive evaluation of LFIA performance was undertaken with individuals following natural infection. Here we assess the performance of the selected LFIA to detect antibody responses in individuals who have received at least one dose of SARS-CoV-2 vaccine.\n\nMethodsThis is a prospective diagnostic accuracy study.\n\nSettingSampling was carried out at renal outpatient clinic and healthcare worker testing sites at Imperial College London NHS Trust. Laboratory analyses were performed across Imperial College London sites and university facilities.\n\nParticipantsTwo cohorts of patients were recruited; the first was a cohort of 108 renal transplant patients attending clinic following SARS-CoV-2 vaccine booster, the second cohort comprised 40 healthcare workers attending for first SARS-CoV-2 vaccination, and 21 day follow up. A total of 186 paired samples were collected.\n\nInterventionsDuring the participants visit, capillary blood samples were analysed on LFIA device, while paired venous sampling was sent for serological assessment of antibodies to the spike protein (anti-S) antibodies. Anti-S IgG were detected using the Abbott Architect SARS-CoV-2 IgG Quant II CMIA.\n\nMain outcome measuresThe accuracy of Fortress LFIA in detecting IgG antibodies to SARS-CoV-2 compared to anti-spike protein detection on Abbott Assay.\n\nResultsUsing the threshold value for positivity on serological testing of [≥]7.10 BAU/ml, the overall performance of the test produces an estimate of sensitivity of 91.94% (95% CI 85.67% to 96.06%) and specificity of 93.55% (95% CI 84.30% to 98.21%) using the Abbott assay as reference standard.\n\nConclusionsFortress LFIA performs well in the detection of antibody responses for intended purpose of population level surveys, but does not meet criteria for individual testing.", + "rel_num_authors": 17, "rel_authors": [ { - "author_name": "Kyung Ku Jang", - "author_inst": "New York University Grossman School of Medicine" + "author_name": "Alexandra H C Cann", + "author_inst": "Imperial College London" }, { - "author_name": "Maria E Kaczmarek", - "author_inst": "New York University Grossman School of Medicine" + "author_name": "Candice L Clarke", + "author_inst": "Imperial College London" }, { - "author_name": "Simone Dallari", - "author_inst": "New York University Grossman School of Medicine" + "author_name": "Jonathan C Brown", + "author_inst": "Imperial College London" }, { - "author_name": "Ying-Han Chen", - "author_inst": "New York University Grossman School of Medicine" + "author_name": "Tina Thomson", + "author_inst": "Imperial College London" }, { - "author_name": "Takuya Tada", - "author_inst": "New York University Grossman School of Medicine" + "author_name": "Maria Prendecki", + "author_inst": "Imperial College London" }, { - "author_name": "Jordan Axelrad", - "author_inst": "New York University Grossman School of Medicine" + "author_name": "Maya Moshe", + "author_inst": "Imperial College London" }, { - "author_name": "Nathaniel R Landau", - "author_inst": "New York University Grossman School of Medicine" + "author_name": "Anjna Badhan", + "author_inst": "Imperial College London" }, { - "author_name": "Kenneth A Stapleford", - "author_inst": "New York University Grossman School of Medicine" + "author_name": "Paul Elliott", + "author_inst": "Imperial College London School of Public Health" }, { - "author_name": "Ken Cadwell", - "author_inst": "New York University Grossman School of Medicine" + "author_name": "Ara Darzi", + "author_inst": "Imperial College London" + }, + { + "author_name": "Steven Riley", + "author_inst": "Dept Inf Dis Epi, Imperial College" + }, + { + "author_name": "Deborah Ashby", + "author_inst": "Imperial College London" + }, + { + "author_name": "Michelle Willicombe", + "author_inst": "Imperial College London" + }, + { + "author_name": "Peter Kelleher", + "author_inst": "Imperial College London" + }, + { + "author_name": "Paul Randell", + "author_inst": "Imperial College Healthcare NHS Trust, UK" + }, + { + "author_name": "Helen Ward", + "author_inst": "Imperial College London" + }, + { + "author_name": "Wendy Barclay", + "author_inst": "Department of Infectious Disease, Imperial College London, UK" + }, + { + "author_name": "Graham Cooke", + "author_inst": "Imperial College London" } ], "version": "1", - "license": "cc_no", - "type": "new results", - "category": "cell biology" + "license": "cc_by_nc_nd", + "type": "PUBLISHAHEADOFPRINT", + "category": "infectious diseases" }, { "rel_doi": "10.1101/2021.07.14.21260496", @@ -659816,209 +659351,57 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.07.13.21260273", - "rel_title": "Clinical characterization and Genomic analysis of COVID-19 breakthrough infections during second wave in different states of India", + "rel_doi": "10.1101/2021.07.13.21258757", + "rel_title": "Prospective, Randomized, Parallel-Group, Open-Label Study to Evaluate the Efficacy and Safety of IMU-838, in Combination with Oseltamivir, in Adults with Coronavirus Disease 19 The IONIC Trial", "rel_date": "2021-07-15", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.13.21260273", - "rel_abs": "During March to June 2021 India has experienced a deadly second wave of COVID-19 with an increased number of post-vaccination breakthrough infections reported across the country. To understand the possible reason of these breakthroughs we collected 677 clinical samples (throat swab/ nasal swabs) of individuals who had received two doses (n=592) and one dose (n=85) of vaccines (Covishield and Covaxin,) and tested positive for COVID-19, from 17 states/Union Territories of country. These cases were telephonically interviewed and clinical data was analyzed. A total of 511 SARS-CoV-2 genomes were recovered with genome coverage of higher than 98% from both the cases. Analysis of both the cases determined that 86.69% (n=443) of them belonged to the Delta variant along with Alpha, Kappa, Delta AY.1 and Delta AY.2. The Delta variant clustered into 4 distinct sub-lineages. Sub-lineage-I had mutations: ORF1ab-A1306S, P2046L, P2287S, V2930L, T3255I, T3446A, G5063S, P5401L, A6319V and N-G215C; Sub-lineage -II : ORF1ab- P309L, A3209V, V3718A, G5063S, P5401L and ORF7a-L116F; Sub-lineage -III : ORF1ab- A3209V, V3718A, T3750I, G5063S, P5401L and Spike-A222V; Sub-lineage -IV ORF1ab- P309L, D2980N, F3138S and spike - K77T. This study indicated that majority of the clinical cases in the breakthrough were infected with the Delta variant and only 9.8% cases required hospitalization while fatality was observed in only 0.4% cases. This clearly suggests that the vaccination does provide reduction in hospital admission and mortality.", - "rel_num_authors": 49, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.13.21258757", + "rel_abs": "BackgroundGlobally there is a scarcity of effective treatments for SARS-CoV-2 infections (causing COVID 19). Repurposing existing medications may offer the best hope for treating COVID 19 patients to curb the pandemic. IMU-838 is a dihydroorotate dehydrogenase (DHODH) inhibitor, which is an effective mechanism for antiviral effects against respiratory viruses. When used synergistically with Oseltamivir, therapeutic effects have been observed against influenza and SARS-CoV-2 in rodents.(13) The IONIC trial is a randomized control trial that will investigate whether time to clinical improvement in COVID 19 patients is improved following a 14 day course of IMU-838 + Oseltamivir versus Oseltamivir alone.\n\nMethodsIONIC trial is an open label study in which participants will be randomised 1:1 in two parallel arms; the intervention arm (IMU-838 + Oseltamivir) and control arm (Oseltamivir only). The primary outcome is time-to-clinical improvement; defined as the time from randomisation to: a 2-point improvement on WHO ordinal scale; discharge from hospital, or death (whichever occurs first). The study is sponsored by UHCW NHS Trust and funded by LifeArc.\n\nDiscussionThe IONIC Protocol describes an overarching trial design to provide reliable evidence on the efficacy of IMU-838 (vidofludimus calcium) when delivered in combination with an antiviral therapy (Oseltamivir) [IONIC Intervention] for confirmed or suspected COVID-19 infection in adult patients receiving usual standard of care.\n\nTrial RegistrationThe trial was registered with EudraCT (2020-001805-21) on 09.04.2020 and ISRCTN on 23.09.2020 (ISRCTN53038326) and Clinicaltrials.gov on 17.08.2020 (NCT04516915)\n\nStrengths and LimitationsThis study is the first to recruit participants in the trial exploring the effectiveness of IMU-838 in COVID-19. In addition, we believe it is the only trial exploring the effectiveness of IMU-838 in combination with Oseltamivir (Tamiflu) in patients with moderate to severe COVID-19. However, to make the trial design flexible due to the on-going pandemic the trial is un-blinded.", + "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Nivedita Gupta", - "author_inst": "Indian Council of Medical Research, V. Ramalingaswami Bhawan, Ansari Nagar, New Delhi, India Pin-110029" - }, - { - "author_name": "Harmanmeet Kaur", - "author_inst": "Indian Council of Medical Research, V. Ramalingaswami Bhawan, Ansari Nagar, New Delhi, India Pin-110029" - }, - { - "author_name": "Pragya Yadav", - "author_inst": "Indian Council of Medical Research-National Institute of Virology, Pune, India Pin-411021" - }, - { - "author_name": "Labanya Mukhopadhyay", - "author_inst": "Indian Council of Medical Research, V. Ramalingaswami Bhawan, Ansari Nagar, New Delhi, India Pin-110029" - }, - { - "author_name": "Rima R Sahay", - "author_inst": "Indian Council of Medical Research-National Institute of Virology, Pune, India Pin-411021" - }, - { - "author_name": "Abhinendra Kumar", - "author_inst": "Indian Council of Medical Research-National Institute of Virology, Pune, India Pin-411021" - }, - { - "author_name": "Dimpal A Nyayanit", - "author_inst": "Indian Council of Medical Research-National Institute of Virology, Pune, India Pin-411021" + "author_name": "Kavi Sharma", + "author_inst": "University Hospital Coventry and Warwickshire NHS Trust" }, { - "author_name": "Anita M Shete", - "author_inst": "Indian Council of Medical Research-National Institute of Virology, Pune, India Pin-411021" + "author_name": "Dr Lisa Berry", + "author_inst": "University Hospital Coventry and Warwickshire NHS Trust" }, { - "author_name": "Savita Patil", - "author_inst": "Indian Council of Medical Research-National Institute of Virology, Pune, India Pin-411021" + "author_name": "Dr Evangelos Vryonis", + "author_inst": "University Hospitals Coventry & Warwickshire, Coventry, CV22DX" }, { - "author_name": "Triparna Dutta Majumdar", - "author_inst": "Indian Council of Medical Research-National Institute of Virology, Pune, India Pin-411021" + "author_name": "Dr Asad Ali", + "author_inst": "University Hospitals Coventry & Warwickshire, Coventry, CV22DX" }, { - "author_name": "Salaj Rana", - "author_inst": "Indian Council of Medical Research, V. Ramalingaswami Bhawan, Ansari Nagar, New Delhi, India Pin-110029" - }, - { - "author_name": "Swati Gupta", - "author_inst": "Indian Council of Medical Research, V. Ramalingaswami Bhawan, Ansari Nagar, New Delhi, India Pin-110029" + "author_name": "Dr Beatriz Lara", + "author_inst": "University Hospitals Coventry & Warwickshire, Coventry, CV22DX" }, { - "author_name": "Jitendra Narayan", - "author_inst": "Indian Council of Medical Research, V. Ramalingaswami Bhawan, Ansari Nagar, New Delhi, India Pin-110029" + "author_name": "Dr Angela Noufaily", + "author_inst": "Warwick Medical School, Coventry, CV4 7AL" }, { - "author_name": "Neetu Vijay", - "author_inst": "Indian Council of Medical Research, V. Ramalingaswami Bhawan, Ansari Nagar, New Delhi, India Pin-110029" - }, - { - "author_name": "Pradip Barde", - "author_inst": "VRDL National Institute of Research in Tribal Health (NIRTH) Jabalpur - 482003" - }, - { - "author_name": "Gita Natrajan", - "author_inst": "VRDL, Department of Microbiology, KEM Medical College, Mumbai - 400012" - }, - { - "author_name": "Amurtha Kumari B", - "author_inst": "VRDL, Department of Microbiology, Mysore Medical College, Mysore - 570015" - }, - { - "author_name": "Manasa P Kumari", - "author_inst": "VRDL, Department of Microbiology, Mysore Medical College, Mysore - 570015" - }, - { - "author_name": "Debasis Biswas", - "author_inst": "VRDL, Department of Microbiology, All India Institute of Medical Sciences, Bhopal -462020" - }, - { - "author_name": "Jyoti Iravane", - "author_inst": "VRDL, Government Medical College, Aurangabad - 431001" - }, - { - "author_name": "Sharmila Raut", - "author_inst": "VRDL, Indira Gandhi Government Medical College Nagpur - 440012" - }, - { - "author_name": "Shanta Dutta", - "author_inst": "VRDL, National Institute of Cholera and Enteric Diseases, Kolkata - 700010" + "author_name": "Dr Nick Parsons", + "author_inst": "Warwick Medical School, Coventry, CV4 7AL" }, { - "author_name": "Sulochana Devi", - "author_inst": "VRDL, Regional Institute of Medical Sciences, Imphal - 795004" + "author_name": "Christopher James Bradley", + "author_inst": "University Hospitals Coventry & Warwickshire, Coventry, CV22DX" }, { - "author_name": "Purnima Barua", - "author_inst": "VRDL, Jorhat Medical College, Jorhat - 785001" + "author_name": "Becky Haley", + "author_inst": "University Hospitals Coventry & Warwickshire, Coventry, CV22DX" }, { - "author_name": "Piyali Gupta", - "author_inst": "VRDL, Mahatma Gandhi Memorial Medical College, Jamshedpur - 831020" + "author_name": "Maria Tabuso", + "author_inst": "University Hospitals Coventry & Warwickshire, Coventry, CV22DX" }, { - "author_name": "Biswa Borkakoty", - "author_inst": "VRDL, ICMR-Regional Medical Research Centre, Dibrugarh - 786001" - }, - { - "author_name": "Deepjyoti Kalita", - "author_inst": "VRDL, All India Institutes of Medical Sciences, Rishikesh - 249203" - }, - { - "author_name": "Kanwardeep Dhingra", - "author_inst": "VRDL, Government Medical College, Amritsar - 143001" - }, - { - "author_name": "Bashir Fomda", - "author_inst": "VRDL, Sher-i-Kashmir Institute of Medical Sciences, Srinagar - 190011" - }, - { - "author_name": "Yash Joshi", - "author_inst": "Indian Council of Medical Research-National Institute of Virology, Pune, India Pin-411021" - }, - { - "author_name": "Kapil Goyal", - "author_inst": "Department of Virology, Postgraduate Institute of Medical Education and Research, Chandigarh - 160012" - }, - { - "author_name": "Reena John", - "author_inst": "VRDL, Government Medical College, Thrissur - 680596" - }, - { - "author_name": "Ashok Munivenkatappa", - "author_inst": "ICMR-National Institute of Virology Field Unit, Bangalore - 560011" - }, - { - "author_name": "Rahul Dhodapkar", - "author_inst": "VRDL, Jawaharlal Institute of Postgraduate Medical Education & Research, Puducherry - 605006" - }, - { - "author_name": "Priyanka Pandit", - "author_inst": "Indian Council of Medical Research-National Institute of Virology, Pune, India Pin-411021" - }, - { - "author_name": "Sarada Devi", - "author_inst": "VRDL, Government Medical College, Thiruvanthapuram -695011" - }, - { - "author_name": "Manisha Dudhmal", - "author_inst": "Indian Council of Medical Research-National Institute of Virology, Pune, India Pin-411021" - }, - { - "author_name": "Deepa Kinariwala", - "author_inst": "VRDL, B. J. Medical College, Ahmedabad - 380016" - }, - { - "author_name": "Neeta Khandelwal", - "author_inst": "VRDL, Government Medical College, Surat - 395001" - }, - { - "author_name": "Yogendra Kumar Tiwari", - "author_inst": "VRDL, Jhalawar Medical College, Jhalawar - 326001" - }, - { - "author_name": "P K Khatri", - "author_inst": "VRDL, Dr. Sampurnanand Medical College, Jodhpur - 342003" - }, - { - "author_name": "Anjali Gupta", - "author_inst": "VRDL, Sarder Patel Medical College, Bikaner - 334001" - }, - { - "author_name": "Himanshu Khatri", - "author_inst": "VRDL, Department of Microbiology, GMERS Medical College, Himmatnagar - 383001" - }, - { - "author_name": "Bharati Malhotra", - "author_inst": "VRDL, Sawai Man Singh Medical College, Jaipur - 302004" - }, - { - "author_name": "Mythily Nagasundaram", - "author_inst": "VRDL, Coimbatore Medical College, Coimbatore - 641018" - }, - { - "author_name": "Lali Dar", - "author_inst": "VRDL, All India Institute of Medical Sciences, Delhi - 110029" - }, - { - "author_name": "Nazira Sheikh", - "author_inst": "VRDL, Dr. V.M Government Medical College, Solapur - 413003" - }, - { - "author_name": "Neeraj Aggarwal", - "author_inst": "Indian Council of Medical Research, V. Ramalingaswami Bhawan, Ansari Nagar, New Delhi, India Pin-110029" - }, - { - "author_name": "Priya Abraham", - "author_inst": "Indian Council of Medical Research-National Institute of Virology, Pune, India Pin-411021" + "author_name": "Professor Ramesh Arasaradnam", + "author_inst": "University Hospitals Coventry & Warwickshire, Coventry, CV22DX" } ], "version": "1", @@ -661834,23 +661217,59 @@ "category": "health economics" }, { - "rel_doi": "10.1101/2021.07.10.21260297", - "rel_title": "Does trust in government improve Covid-19's crisis management?", + "rel_doi": "10.1101/2021.07.12.21260298", + "rel_title": "Machine Learning Model for Predicting Number of COVID19 Cases in Countries with Low Number of Tests", "rel_date": "2021-07-14", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.10.21260297", - "rel_abs": "Countries have adopted several measures to control the spread of Covid-19. However, substantial differences remain in terms of performance in controlling the virus, potentially due to heterogeneity in citizen engagement with government measures. Drawing on this observation, this paper seeks to analyze the effect of pre-crisis ties, particularly trust in government, on crisis management, proxied by the number of Covid-19 cases and deaths per million population. We examine this question based on a sample of 41 countries for which data are available. Results reveal that a high level of trust in government predicts better crisis management in terms of relatively low levels of cases and deaths. These results, which successfully pass a series of robustness tests, may vary according to level of contamination and increase with time.\n\nJEL ClassificationE71, H12, I12, I18, I38, Z18", - "rel_num_authors": 1, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.12.21260298", + "rel_abs": "The COVID-19 pandemic has presented a series of new challenges to governments and health care systems. Testing is one important method for monitoring and therefore controlling the spread of COVID-19. Yet with a serious discrepancy in the resources available between rich and poor countries not every country is able to employ widespread testing. Here we developed machine learning models for predicting the number of COVID-19 cases in a country based on multilinear regression and neural networks models. The models are trained on data from US states and tested against the reported infections in the European countries. The model is based on four features: Number of tests Population Percentage Urban Population and Gini index. The population and number of tests have the strongest correlation with the number of infections. The model was then tested on data from European countries for which the correlation coefficient between the actual and predicted cases R2 was found to be 0.88 in the multi linear regression and 0.91 for the neural network model. The model predicts that the actual number of infections in countries where the number of tests is less than 10% of their populations is at least 26 times greater than the reported numbers.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Ablam Estel Apeti", - "author_inst": "UCA" + "author_name": "Samy Hashim", + "author_inst": "University of Groninngen" + }, + { + "author_name": "Sally Farooq", + "author_inst": "University of Groningen" + }, + { + "author_name": "Eleni Syriopoulos", + "author_inst": "University of Groningen" + }, + { + "author_name": "Kai de la Lande Cremer", + "author_inst": "University of Groningen" + }, + { + "author_name": "Alexander Vogt", + "author_inst": "University of Groningen" + }, + { + "author_name": "Nol de Jong", + "author_inst": "University of Groningen" + }, + { + "author_name": "Victor L Aguado", + "author_inst": "University of Groningen" + }, + { + "author_name": "Mihai Popescu", + "author_inst": "University of Groningen" + }, + { + "author_name": "Ashraf K Mohamed", + "author_inst": "University of Groningen" + }, + { + "author_name": "Muhamed Amin", + "author_inst": "University of Groningen" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "health economics" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2021.07.10.21260306", @@ -663492,195 +662911,59 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2021.07.07.21260122", - "rel_title": "Viral infection and Transmission in a large well-traced outbreak caused by the Delta SARS-CoV-2 variant", + "rel_doi": "10.1101/2021.07.11.451951", + "rel_title": "Niclosamide reverses SARS-CoV-2 control of lipophagy", "rel_date": "2021-07-12", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.07.21260122", - "rel_abs": "We report the first local transmission of the SARS-CoV-2 Delta variant in mainland China. All 167 infections could be traced back to the first index case. Daily sequential PCR testing of the quarantined subjects indicated that the viral loads of Delta infections, when they first become PCR+, were on average [~]1000 times greater compared to A/B lineage infections during initial epidemic wave in China in early 2020, suggesting potentially faster viral replication and greater infectiousness of Delta during early infection. We performed high-quality sequencing on samples from 126 individuals. Reliable epidemiological data meant that, for 111 transmission events, the donor and recipient cases were known. The estimated transmission bottleneck size was 1-3 virions with most minor intra-host single nucleotide variants (iSNVs) failing to transmit to the recipients. However, transmission heterogeneity of SARS-CoV-2 was also observed. The transmission of minor iSNVs resulted in at least 4 of the 30 substitutions identified in the outbreak, highlighting the contribution of intra-host variants to population level viral diversity during rapid spread. Disease control activities, such as the frequency of population testing, quarantine during pre-symptomatic infection, and level of virus genomic surveillance should be adjusted in order to account for the increasing prevalence of the Delta variant worldwide.", - "rel_num_authors": 44, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2021.07.11.451951", + "rel_abs": "The global effort to combat COVID-19 rapidly produced a shortlist of approved drugs with anti-viral activities for clinical repurposing. However, the jump to clinical testing was lethal in some cases as a full understanding of the mechanism of antiviral activity as opposed to pleiotropic activity/toxicity for these drugs was lacking. Through parallel lipidomic and transcriptomic analyses we observed massive reorganization of lipid profiles of infected Vero E6 cells, especially plasmalogens that correlated with increased levels of virus replication. Niclosamide (NIC), a poorly soluble anti-helminth drug identified for repurposed treatment of COVID-19, reduced the total lipid profile that would otherwise amplify during virus infection. NIC treatment reduced the abundance of plasmalogens, diacylglycerides, and ceramides, which are required for virus production. Future screens of approved drugs may identify more druggable compounds than NIC that can safely but effectively counter SARS-CoV-2 subversion of lipid metabolism thereby reducing virus replication. However, these data support the consideration of niclosamide as a potential COVID-19 therapeutic given its modulation of lipophagy leading to the reduction of virus egress and the subsequent regulation of key lipid mediators of pathological inflammation.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Baisheng Li", - "author_inst": "Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China;Guangdong Workstation for Emerging Infectious Disease Control and Pr" - }, - { - "author_name": "Aiping Deng", - "author_inst": "Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China;Guangdong Workstation for Emerging Infectious Disease Control and Pr" - }, - { - "author_name": "Kuibiao Li", - "author_inst": "Guangzhou Center for Disease Control and Prevention, Guangzhou, Guangdong, China" - }, - { - "author_name": "Yao Hu", - "author_inst": "Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China;Guangdong Workstation for Emerging Infectious Disease Control and Pr" - }, - { - "author_name": "Zhencui Li", - "author_inst": "Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China;Guangdong Workstation for Emerging Infectious Disease Control and Pr" - }, - { - "author_name": "Qianling Xiong", - "author_inst": "Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China;Guangdong Workstation for Emerging Infectious Disease Control and Pr" - }, - { - "author_name": "Zhe Liu", - "author_inst": "Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China;Guangdong Workstation for Emerging Infectious Disease Control and Pr" - }, - { - "author_name": "Qianfang Guo", - "author_inst": "Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China;Guangdong Workstation for Emerging Infectious Disease Control and Pr" - }, - { - "author_name": "Lirong Zou", - "author_inst": "Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China;Guangdong Workstation for Emerging Infectious Disease Control and Pr" - }, - { - "author_name": "Huan Zhang", - "author_inst": "Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China;Guangdong Workstation for Emerging Infectious Disease Control and Pr" - }, - { - "author_name": "Meng Zhang", - "author_inst": "Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China;Guangdong Workstation for Emerging Infectious Disease Control and Pr" - }, - { - "author_name": "Fangzhu Ouyang", - "author_inst": "Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China;Guangdong Workstation for Emerging Infectious Disease Control and Pr" - }, - { - "author_name": "Juan Su", - "author_inst": "Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China;Guangdong Workstation for Emerging Infectious Disease Control and Pr" - }, - { - "author_name": "Wenzhe Su", - "author_inst": "Guangzhou Center for Disease Control and Prevention, Guangzhou, Guangdong, China" - }, - { - "author_name": "Jing Xu", - "author_inst": "Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China;Guangdong Workstation for Emerging Infectious Disease Control and Pr" - }, - { - "author_name": "Huifang Lin", - "author_inst": "Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China;Guangdong Workstation for Emerging Infectious Disease Control and Pr" - }, - { - "author_name": "Jing Sun", - "author_inst": "Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China;Guangdong Workstation for Emerging Infectious Disease Control and Pr" - }, - { - "author_name": "Jinju Peng", - "author_inst": "Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China;Guangdong Workstation for Emerging Infectious Disease Control and Pr" - }, - { - "author_name": "Huimin Jiang", - "author_inst": "Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China;Guangdong Workstation for Emerging Infectious Disease Control and Pr" - }, - { - "author_name": "Pingping Zhou", - "author_inst": "Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China;Guangdong Workstation for Emerging Infectious Disease Control and Pr" - }, - { - "author_name": "Ting Hu", - "author_inst": "Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China;Guangdong Workstation for Emerging Infectious Disease Control and Pr" - }, - { - "author_name": "Min Luo", - "author_inst": "Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China;Guangdong Workstation for Emerging Infectious Disease Control and Pr" - }, - { - "author_name": "Yingtao Zhang", - "author_inst": "Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China;Guangdong Workstation for Emerging Infectious Disease Control and Pr" - }, - { - "author_name": "Huanying Zheng", - "author_inst": "Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China;Guangdong Workstation for Emerging Infectious Disease Control and Pr" - }, - { - "author_name": "Jianpeng Xiao", - "author_inst": "Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China;Guangdong Workstation for Emerging Infectious Disease Control and Pr" - }, - { - "author_name": "Tao Liu", - "author_inst": "Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China;Guangdong Workstation for Emerging Infectious Disease Control and Pr" - }, - { - "author_name": "Rongfei Che", - "author_inst": "Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China;Guangdong Workstation for Emerging Infectious Disease Control and Pr" - }, - { - "author_name": "Hanri Zeng", - "author_inst": "Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China;Guangdong Workstation for Emerging Infectious Disease Control and Pr" - }, - { - "author_name": "Zhonghua Zheng", - "author_inst": "Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China;Guangdong Workstation for Emerging Infectious Disease Control and Pr" - }, - { - "author_name": "Yushi Huang", - "author_inst": "Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China;Guangdong Workstation for Emerging Infectious Disease Control and Pr" - }, - { - "author_name": "Jianxiang Yu", - "author_inst": "Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China;Guangdong Workstation for Emerging Infectious Disease Control and Pr" - }, - { - "author_name": "Lina Yi", - "author_inst": "Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China;Guangdong Workstation for Emerging Infectious Disease Control and Pr" - }, - { - "author_name": "Jie Wu", - "author_inst": "Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China;Guangdong Workstation for Emerging Infectious Disease Control and Pr" - }, - { - "author_name": "Jingdiao Chen", - "author_inst": "Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China;Guangdong Workstation for Emerging Infectious Disease Control and Pr" - }, - { - "author_name": "Haojie Zhong", - "author_inst": "Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China;Guangdong Workstation for Emerging Infectious Disease Control and Pr" + "author_name": "Timothy Garrett", + "author_inst": "University of Florida" }, { - "author_name": "Xiaoling Deng", - "author_inst": "Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China;Guangdong Workstation for Emerging Infectious Disease Control and Pr" + "author_name": "Heather Coatsworth", + "author_inst": "University of Florida" }, { - "author_name": "min Kang", - "author_inst": "Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China;Guangdong Workstation for Emerging Infectious Disease Control and Pr" + "author_name": "Iqbal Mahmud", + "author_inst": "Univ. of Florida" }, { - "author_name": "Oliver G. Pybus", - "author_inst": "Department of Zoology, University of Oxford, Oxford OX1 3SZ, UK" + "author_name": "Timothy Hamerly", + "author_inst": "University of Florida" }, { - "author_name": "Matthew Hall", - "author_inst": "Big Data Institute, Nuffield Department of Medicine, University of Oxford, Old Road Campus, Oxford OX3 7LF, UK" + "author_name": "Caroline J. Stephenson", + "author_inst": "University of Florida" }, { - "author_name": "Katrina A. Lythgoe", - "author_inst": "Big Data Institute, Nuffield Department of Medicine, University of Oxford, Old Road Campus, Oxford OX3 7LF, UK" + "author_name": "Hoda Yazd", + "author_inst": "University of Florida" }, { - "author_name": "Yan Li", - "author_inst": "Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China;Guangdong Workstation for Emerging Infectious Disease Control and Pr" + "author_name": "Jasmine B Ayers", + "author_inst": "University of Florida" }, { - "author_name": "Jun Yuan", - "author_inst": "Guangzhou Center for Disease Control and Prevention, Guangzhou, Guangdong, China" + "author_name": "Megan Miller", + "author_inst": "University of Florida" }, { - "author_name": "Jianfeng He", - "author_inst": "Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China;Guangdong Workstation for Emerging Infectious Disease Control and Pr" + "author_name": "John A Lednicky", + "author_inst": "University of Florida" }, { - "author_name": "Jing Lu", - "author_inst": "Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China;Guangdong Workstation for Emerging Infectious Disease Control and Pr" + "author_name": "Rhoel R. Dinglasan", + "author_inst": "University of Florida" } ], "version": "1", - "license": "cc_by_nc_nd", - "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "license": "cc_no", + "type": "new results", + "category": "microbiology" }, { "rel_doi": "10.1101/2021.07.10.451922", @@ -665422,43 +664705,39 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2021.07.09.451770", - "rel_title": "A photoactivable natural product with broad antiviral activity against enveloped viruses including highly pathogenic coronaviruses", + "rel_doi": "10.1101/2021.07.08.21260212", + "rel_title": "RISK OF ON JOB NON COMPLIANCE TOWARDS VARIOUS COVID-19 STANDARD & TRANSMISSION BASED INFECTION PREVENTION & CONTROL MEASURES/PRECAUTIONS AMONG THE HEALTHCARE WORKS WORKING IN OPD SETTINGs OF PUBLIC SECTOR TERTIORY CARE HOSPITALS OF QUETTA BALOCHISTAN. (Prospective cohort study).", "rel_date": "2021-07-09", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.07.09.451770", - "rel_abs": "The SARS-CoV-2 outbreak has highlighted the need for broad-spectrum antivirals against coronaviruses (CoVs). Here, pheophorbide a (Pba) was identified as a highly active antiviral molecule against HCoV-229E after bioguided fractionation of plant extracts. The antiviral activity of Pba was subsequently shown for SARS-CoV-2 and MERS-CoV, and its mechanism of action was further assessed, showing that Pba is an inhibitor of coronavirus entry by directly targeting the viral particle. Interestingly, the antiviral activity of Pba depends on light exposure, and Pba was shown to inhibit virus-cell fusion by stiffening the viral membrane as demonstrated by cryo-electron microscopy. Moreover, Pba was shown to be broadly active against several other enveloped viruses, and reduced SARS-CoV-2 and MERS-CoV replication in primary human bronchial epithelial cells. Pba is the first described natural antiviral against SARS-CoV-2 with direct photosensitive virucidal activity that holds potential for COVID-19 therapy or disinfection of SARS-CoV-2 contaminated surfaces.", - "rel_num_authors": 6, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.08.21260212", + "rel_abs": "BackgroundCOVID-19 Pandemic is still circulating within the human population and proving to be a deadlier disease with mortality rate ranging from 0.5 to 7%8. Since COVID-19 is a highly transmissible disease; there is always a probability for its out ward spread towards general public and community from the hospitals and healthcare facilities where they come to seek treatment.\n\nMethodologyA prospective cohort study design was used, considering the limited available resources and time __ A total of 200 healthcare workers (Including Doctors, Nurses, Para-Medical staff, Janitorial staff, Reception staff & Pharmacists) working in the OPDs of the two major Public sector hospitals of Quetta were made part of this study. The study participants were selected using simple random sampling technique. The study participants from \"Hospital-A\" were first of all educated and trained on various COVID-19 IPC measures later on various COVID-19-IEC materials; written in simple Urdu language, were displayed clearly everywhere in the OPD. Similarly hand washing station along with Hand sanitizers/Soaps and surgical face masks were also made available free of cost for all the study participants of Hospital-A. More over the importance and effectiveness of COVID-19 IPC measures were continuously announced in the OPD gallery of Hospital-A, these announcements used Simple wording in local languages (i.e. Urdu, Pashto, Balochi & Brahvi). On the other hand in the OPD of \"Hospital-B\" no such interventions were made. The study participants of both the hospitals were followed for one month and observations like-which group showed more on-job non compliance towards various COVID-19 IPC measures were recorded. The data was recorded on daily bases (From 1st May-to-31st May 2021) after observing the study participants and checklist was used for recording various findings. Lastly all the data was analyzed using Microsoft Excel 2007 version.\n\nResultsThe major findings of this study are almost in line with the set objectives, the study results are clearly showing the Risk ratio (R.R) as 0.27, indicating that the intervention group participants were only 27% as likely to develop On-job non-compliance for various COVID-19 IPC measures compare to the non-intervention group.\n\nConclusionThe best suggestion and intervention for the developing countries that could at least address the spread of COVID-19 in a cost effective manner at health facility levels remains to be adoption of various Standard and Transmission based non-pharmacological measures of Infection prevention and Control (IPC)5.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Simon Bordage", - "author_inst": "Univ Lille" - }, - { - "author_name": "Moussa Bamba", - "author_inst": "Univ Lille" + "author_name": "Muhammad Arif", + "author_inst": "FELTP" }, { - "author_name": "Marion Decossas", - "author_inst": "CNRS" + "author_name": "Muhammad Abdullah", + "author_inst": "WHO Balochistan." }, { - "author_name": "Fezan H. Tra Bi", - "author_inst": "Univ Nangui Abrogoua" + "author_name": "Ambreen Chaudhry", + "author_inst": "National Institute of Health" }, { - "author_name": "Olivier Lambert", - "author_inst": "CNRS" + "author_name": "Zakir Hussain", + "author_inst": "Field Epidemiology and laboratory training program Pakistan" }, { - "author_name": "Sevser Sahpaz", - "author_inst": "Unive Lille" + "author_name": "Ehsan Larik", + "author_inst": "Field Epidemiology and laboratory training program Pakistan" } ], "version": "1", - "license": "cc_no", - "type": "new results", - "category": "microbiology" + "license": "cc_by_nc", + "type": "PUBLISHAHEADOFPRINT", + "category": "epidemiology" }, { "rel_doi": "10.1101/2021.07.09.21257475", @@ -667392,27 +666671,79 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.07.07.21259916", - "rel_title": "Modeling the emergence of vaccine-resistant variants with Gaussian convolution.COVID-19: Could the wrong strategy ruin vaccine efficiency?", + "rel_doi": "10.1101/2021.07.07.21259779", + "rel_title": "Deaths in Children and Young People in England following SARS-CoV-2 infection during the first pandemic year: a national study using linked mandatory child death reporting data", "rel_date": "2021-07-08", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.07.21259916", - "rel_abs": "AO_SCPLOWBSTRACTC_SCPLOWThe SARS-CoV-2 virus, which is responsible for the COVID-19 pandemic, has been shown to mutate. In the absence of a vaccine, natural selection will favor variants with higher transmissibility rates. However, when a substantial portion of the population is vaccinated, natural selection will shift towards favoring variants that can resist the vaccine. These variants can therefore become dominant and even cancel out the benefit of the vaccine. This paper develops a compartmental model which simulates this phenomenon and shows how various vaccination strategies can lead to the emergence of vaccine-resistant variants.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.07.21259779", + "rel_abs": "BackgroundDeaths in children and young people (CYP) following SARS-CoV-2 infection are rare. Quantifying the risk of mortality is challenging because of high relative prevalence of asymptomatic and non-specific disease manifestations. Therefore, it is important to differentiate between CYP who have died of SARS-CoV-2 and those who have died of an alternative disease process but coincidentally tested positive.\n\nMethodsDuring the pandemic, the mandatory National Child Mortality Database (NCMD) was linked to Public Health England (PHE) testing data to identify CYP (<18 years) who died with a positive SARS-CoV-2 test. A clinical review of all deaths from March 2020 to February 2021 was undertaken to differentiate between those who died of SARS-CoV-2 infection and those who died of an alternative cause but coincidentally tested positive. Then, using linkage to national hospital admission data, demographic and comorbidity details of CYP who died of SARS-CoV-2 were compared to all other deaths. Absolute risk of death was estimated where denominator data were available.\n\nFindings3105 CYP died from all causes during the first pandemic year in England. 61 of these deaths occurred in CYP who tested positive for SARS-CoV-2. 25 CYP died of SARS-CoV-2 infection; 22 from acute infection and three from PIMS-TS. 99{middle dot}995% of CYP with a positive SARS-CoV-2 test survived. The 25 CYP who died of SARS-CoV-2 equates to a mortality rate of 2/million for the 12,023,568 CYP living in England. CYP >10 years, of Asian and Black ethnic backgrounds, and with comorbidities were over-represented compared to other children.\n\nInterpretationSARS-CoV-2 is very rarely fatal in CYP, even among those with underlying comorbidities. These findings are important to guide families, clinicians and policy makers about future shielding and vaccination.\n\nFundingRH is in receipt of a fellowship from Kidney Research UK. JW is in receipt of a Medical Research Council Fellowship. LF is in receipt of funding from Martin House Childrens Hospice.", + "rel_num_authors": 15, "rel_authors": [ { - "author_name": "Christian Bongiorno", - "author_inst": "University Paris-Saclay, CentraleSupelec" + "author_name": "Clare Smith", + "author_inst": "NHS England and NHS Improvement, London" + }, + { + "author_name": "David Odd", + "author_inst": "Division of Population Medicine, University of Cardiff" + }, + { + "author_name": "Rachel Harwood", + "author_inst": "Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool" + }, + { + "author_name": "Joseph Ward", + "author_inst": "UCL Great Ormond St. Institute of Child Health, London" + }, + { + "author_name": "Michael Linney", + "author_inst": "University Hospitals Sussex NHS Foundation Trust" + }, + { + "author_name": "Matthew Clark", + "author_inst": "NHS England and NHS Improvement, London" + }, + { + "author_name": "Dougal Hargreaves", + "author_inst": "Imperial College London, Department of Primary Care and Public Health" + }, + { + "author_name": "Shamez N Ladhani", + "author_inst": "Immunisation and Countermeasures, Public Health England" + }, + { + "author_name": "Elizabeth S Draper", + "author_inst": "PICANet, Department of Health Sciences, University of Leicester, Leicester" + }, + { + "author_name": "Peter J Davis", + "author_inst": "Paediatric Intensive Care Unit, Bristol Royal Hospital for Children, Bristol" }, { - "author_name": "John Cagnol", - "author_inst": "University Paris-Saclay, CentraleSupelec" + "author_name": "Simon E Kenny", + "author_inst": "NHS England and NHS Improvement, London" + }, + { + "author_name": "Elizabeth Whittaker", + "author_inst": "Imperial College London, London" + }, + { + "author_name": "Karen Luyt", + "author_inst": "Bristol Medical School, University of Bristol, Bristol" + }, + { + "author_name": "Russell M Viner", + "author_inst": "UCL Great Ormond St. Institute of Child Health, London" + }, + { + "author_name": "Lorna K Fraser", + "author_inst": "Martin House Research Centre, Dept of Health Sciences, University of York" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "pediatrics" }, { "rel_doi": "10.1101/2021.07.08.21259871", @@ -669242,27 +668573,43 @@ "category": "intensive care and critical care medicine" }, { - "rel_doi": "10.1101/2021.07.03.21259943", - "rel_title": "Masks in a Post COVID-19 World: A Better Alternative to Curtailing Influenza?", + "rel_doi": "10.1101/2021.07.03.21259961", + "rel_title": "Predictors of black fungus fear during the COVID-19 pandemic among the Bangladeshi health workers: a cross-sectional study", "rel_date": "2021-07-07", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.03.21259943", - "rel_abs": "Over the course of the coronavirus pandemic, it has become apparent that non-pharmaceutical interventions such as masks and social distancing are of great help in mitigating the transmission of airborne infectious diseases. Additionally, data from respiratory specimen analysis from the past year show that current mask mandates established for COVID-19 have inadvertently reduced the rates of other respiratory diseases, including influenza. Thus, the question arises as to whether comparatively mild measures should be kept in place after the pandemic to reduce the impact of influenza. In this study, we employed a series of differential equations to simulate past influenza seasons, assuming people wore face masks. This was achieved by introducing a variable to account for the efficacy and prevalence of masks and then analyzing its impact on influenza transmission rate in an SEIR model fit to the actual past seasons. We then compared influenza rates in this hypothetical scenario with the actual rates over the seasons. Our results show that several combinations of mask efficacy and prevalence can significantly reduce the burden of seasonal influenza. Particularly, our simulations suggest that a minority of individuals wearing masks greatly reduce the number of influenza infections. Considering the efficacy rates of masks and the relatively insignificant monetary cost, we highlight that it may be a viable alternative or complement to influenza vaccinations. We conclude with a brief discussion of our results and other practical aspects", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.03.21259961", + "rel_abs": "BackgroundThe emergence of mucormycosis cases amid the COVID-19 pandemic; fear associated with mucormycosis may turn out to be a terrifying public health issue. This study aimed to assess the association between fear and insomnia status and other predictors of mucormycosis among Bangladeshi healthcare workers.\n\nMethodsFrom 25 May 2021 to 05 June 2021, a cross-sectional study was carried out among healthcare workers. A total of 422 healthcare workers participated in this study. A semi-structured online questionnaire was used for data collection during the COVID-19 pandemic, followed by convenient and snowball sampling methods. A multivariable linear regression model was fitted to assess the association between fear and insomnia status and other predictors of mucormycosis.\n\nResultsThe results indicated that the respondents with insomnia status had a higher score of mucormycosis fear than not having insomnia ({beta} = 3.91, 95% CI: 2.49, 5.33, p <0.001), significantly. Alongside the increased knowledge score of mucormycosis, the average score of fear increased significantly({beta} = 0.35, 95% CI: 0.20, 0.50, p <0.001). The gender, profession, and death of friends and family members due to COVID-19 significantly affected mucormycosis fear score increment.\n\nConclusionsThis is the first study that focused on assessing the association between mucormycosis fear and insomnia status among the health care workers so far. These study findings recommend emphasizing the mental health aspects and ensuring support to the healthcare workers to better tackle the ongoing public health crisis.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Henri Froese", - "author_inst": "Goethe-University Frankfurt am Main" + "author_name": "Md. Kamrul Hasan", + "author_inst": "Department of Public Health, North South University, Dhaka- 1229, Bangladesh" + }, + { + "author_name": "Humayun Kabir", + "author_inst": "Department of Public Health, North South University, Dhaka- 1229, Bangladesh" + }, + { + "author_name": "Mamunur Rahman", + "author_inst": "Department of Pharmacy, East West University, Dhaka-1212, Bangladesh" + }, + { + "author_name": "Anjan Kumar Roy", + "author_inst": "Department of Nursing and Health Science, Jashore University of Science and Technology, Jashore-7408, Bangladesh" + }, + { + "author_name": "Shimpi Akter", + "author_inst": "Bangladesh University of Professionals, Mirpur Cantonment, Dhaka-1216" }, { - "author_name": "Angel G. A. Prempeh", - "author_inst": "Saginaw Valley State University" + "author_name": "Dipak Kumar Mitra", + "author_inst": "Department of Public Health, North South University, Dhaka- 1229, Bangladesh" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "public and global health" }, { "rel_doi": "10.1101/2021.07.05.21260053", @@ -671040,39 +670387,87 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.07.05.21260012", - "rel_title": "A decision-tree approach to treat platelet hyperactivity and anomalous blood clotting in acute COVID-19 patients", + "rel_doi": "10.1101/2021.07.05.21259933", + "rel_title": "Sex-specific epidemiological and clinical characteristics of Covid-19 patients in the southeast region of Bangladesh", "rel_date": "2021-07-07", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.05.21260012", - "rel_abs": "An important component of severe COVID-19 disease is virus-induced endothelilitis. This leads to disruption of normal endothelial function, initiating a state of failing normal clotting physiology. Massively increased levels of von Willebrand Factor (VWF) lead to overwhelming platelet activation, as well as activation of the enzymatic (intrinsic) clotting pathway. In addition, there is an impaired fibrinolysis, caused by, amongst others, increased levels of alpha-(2) antiplasmin. The end result is hypercoagulation [proven by thromboelastography(R) (TEG(R))] and reduced fibrinolysis, inevitably leading to a difficult-to-overcome hypercoagulated physiological state. Platelets in circulation also plays a significant role in clot formation, but themselves may also drive hypercoagulation when they are overactivated due to the interactions of their receptors with the endothelium, immune cells or circulating inflammatory molecules. From the literature it is clear that the role of platelets in severely ill COVID-19 patients has been markedly underestimated or even ignored. We here highlight the value of early management of severe COVID-19 coagulopathy as guided by TEG(R), microclot and platelet mapping. We also argue that the failure of clinical trials, where the efficacy of prophylactic versus therapeutic clexane (low molecular weight heparin (LMWH)) were not always successful, might be because the significant role of platelet activation was not taken into account during the planning of the trial. We conclude that, because of the overwhelming alteration of clotting, the outcome of any trial evaluating an any single anticoagulant, including thrombolytic, would be negative. Here we suggest the use of the degree of platelet dysfunction and presence of microclots in circulation, together with TEG(R), should be used as a guideline for disease severity. A multi-pronged approach, guided by TEG(R) and platelet mapping, would be required to maintain normal clotting physiology in severe COVID-19 disease.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.05.21259933", + "rel_abs": "BackgroundCOVID-19 has become a global pandemic with a high growth rate of confirmed cases. In Bangladesh, both mortality and affected rates are increasing at an alarming rate.\n\nTherefore, more comprehensive studies of the epidemiological and clinical characteristics of COVID-19 are required to control this pandemic.\n\nPurposeThe present study aimed to compare and analyze the sex-specific epidemiological, clinical characteristics, comorbidities, and other information of confirmed COVID-19 patients from the southeast region in Bangladesh for the first time.\n\nMethods385 lab-confirmed cases were studied out of 2,471 tested samples between 5 June and 10 September 2020. RT-PCR was used for COVID-19 identification and SPSS (version 25) for statistical data analysis.\n\nResultsWe found that male patients were roughly affected compared to females patients (male 74.30% vs. female 25.7%) with an average age of 34.86 {+/-} 15.442 years, and B (+ve) blood group has been identified as a high-risk factor for COVID-19 infection. Workplace, local market, and bank were signified as sex-specific risk zone (p < 0.001). Pre-existing medical conditions such as diabetes, hypertension, cardiovascular and respiratory diseases were identified among the patients. Less than half of the confirmed COVID-19 cases in the southeast region were asymptomatic (37.73%) and more prevalent among females than males (male vs. female: 36.84% vs. 40.51%, p = 0.001).\n\nConclusionsThe findings may help health authorities and the government take necessary steps for identification and isolation, treatment, prevention, and control of this global pandemic.", + "rel_num_authors": 17, "rel_authors": [ { - "author_name": "Gert J Laubscher", - "author_inst": "Mediclinic Stellenbosch" + "author_name": "MD. Aminul Islam", + "author_inst": "Noakhali Science and Technology University, Noakhali-3814, Bangladesh" }, { - "author_name": "Petrus J Lourens", - "author_inst": "Mediclinic Stellenbosch" + "author_name": "Abdullah Al Marzan", + "author_inst": "Shahjalal University of Science and Technology" }, { - "author_name": "Chantelle Venter", - "author_inst": "Stellenbosch University" + "author_name": "Md. Sydul Islam", + "author_inst": "Noakhali Science and Technology University, Noakhali-3814, Bangladesh" }, { - "author_name": "Douglas B Kell", - "author_inst": "University of Liverpool" + "author_name": "Samina Sultana", + "author_inst": "President Abdul Hamid Medical College" }, { - "author_name": "Etheresia Pretorius", - "author_inst": "Stellenbosch University" + "author_name": "Md. Iftakhar Parvej", + "author_inst": "Noakhali Science and Technology University, Noakhali-3814, Bangladesh" + }, + { + "author_name": "Mohammad Salim Hossain", + "author_inst": "Noakhali Science and Technology University, Noakhali-3814, Bangladesh" + }, + { + "author_name": "Mohammad Tohid Amin", + "author_inst": "Noakhali Science and Technology University, Noakhali-3814, Bangladesh" + }, + { + "author_name": "Farzana Ehetasum Hossain", + "author_inst": "Noakhali Science and Technology University, Noakhali-3814" + }, + { + "author_name": "Md Abdul Barek", + "author_inst": "Noakhali Science and Technology University" + }, + { + "author_name": "Md. Shafiul Hossen", + "author_inst": "Noakhali Science and Technology University, Noakhali-3814, Bangladesh" + }, + { + "author_name": "Md. Shariful Islam", + "author_inst": "Noakhali Science and Technology University, Noakhali-3814, Bangladesh" + }, + { + "author_name": "Foysal Hossen", + "author_inst": "Noakhali Science and Technology University, Noakhali-3814, Bangladesh" + }, + { + "author_name": "Newaz Mohammed Bahadur", + "author_inst": "Noakhali Science and Technology University, Noakhali-3814, Bangladesh" + }, + { + "author_name": "Md. Shahadat Hossain", + "author_inst": "Noakhali Science and Technology University, Noakhali-3814, Bangladesh" + }, + { + "author_name": "Nazratun Nayeem Choudhury", + "author_inst": "Centre for Health, Population and Development, Independent University Bangladesh, Dhaka 1212, Bangladesh" + }, + { + "author_name": "Md. Didar-ul Alam", + "author_inst": "Noakhali Science and Technology University, Noakhali-3814, Bangladesh" + }, + { + "author_name": "Firoz Ahmed", + "author_inst": "Noakhali Science and Technology University" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "cardiovascular medicine" + "category": "epidemiology" }, { "rel_doi": "10.1101/2021.07.05.21259989", @@ -673138,33 +672533,37 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.07.04.21259954", - "rel_title": "Predictors of hospitalisation and death due to SARS-CoV-2 infection in Finland: a population-based register study with implications to vaccinations", + "rel_doi": "10.1101/2021.07.04.21259991", + "rel_title": "Transmission dynamics of COVID-19 in Ghana and the impact of public health interventions", "rel_date": "2021-07-06", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.04.21259954", - "rel_abs": "IntroductionThe aim of this study was to investigate how age and underlying medical conditions affect the risk of severe outcomes following SARS-CoV-2 infection and how they should be weighed while prioritising vaccinations against COVID-19.\n\nMethodsThis population-based register study includes all SARS-CoV-2 PCR-test-positive cases until 24 Feb 2021, based on the Finnish National Infectious Diseases Register. The cases were linked to other registers to identify presence of comorbidities and severe outcomes (hospitalisation, intensive care treatment, death). The odds of severe outcomes were compared in those with and without the pre-specified comorbidities using logistic regression. Furthermore, population-based rates were compared between those with a given comorbidity and those without any of the specified comorbidities using negative binomial regression.\n\nResultsAge and various comorbidities were found to be predictors of severe COVID-19. Compared to 60-69-year-olds, the odds ratio (OR) of death was 7.1 for 70-79-year-olds, 26.7 for 80-89-year-olds, and 55.8 for [≥]90-year-olds. Among the 20-69-year-olds, chronic renal disease (OR 9.4), malignant neoplasms (5.8), hematologic malignancy (5.6), chronic pulmonary disease (5.4), and cerebral palsy or other paralytic syndromes (4.6) were strongly associated with COVID-19 mortality; severe disorders of the immune system (8.0), organ or stem cell transplant (7.2), chronic renal disease (6.7), and diseases of myoneural junction and muscle (5.5) were strongly associated with COVID-19 hospitalisation. Type 2 diabetes and asthma, two very common comorbidities, were associated with all three outcomes, with ORs from 2.1 to 4.3. The population-based rate of SARS-CoV-2 infection decreased with age. Taking the 60-69-year-olds as reference, the rate ratio was highest (3.0) for 20-29-year-olds but <1 for 70-79-year-olds and 80-89-year-olds.\n\nConclusionComorbidities predispose for severe COVID-19 among younger ages. In vaccine prioritisation both the risk of infection and the risk of severe outcomes, if infected, should be combined.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.04.21259991", + "rel_abs": "The study characterized COVID-19 transmission in Ghana in 2020-21 by estimating the time-varying reproduction number (Rt) and exploring its association with various public health interventions at the national and regional levels. Ghana experienced four pandemic waves with epidemic peaks in July 2020, and January, August and December, 2021. The epidemic peak was the highest nationwide in December 2021 with Rt [≥]2. Throughout 2020-21, per-capita cumulative case count by region increased with population size. Mobility data suggested negative correlation between Rt and staying home in the first 90 days of the pandemic. The relaxation of movement restrictions and religious gatherings were not associated with increased Rt in the regions with lower case burdens. Rt decreased from above 1 when schools reopened in January 2021 to below 1 after vaccination rollout in March 2021. Findings indicated most public health interventions were associated with Rt reduction at the national and regional levels.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Heini Salo", - "author_inst": "Finnish Institute for Health and Welfare (THL)" + "author_name": "Sylvia K. Ofori", + "author_inst": "Georgia Southern University Jiann-Ping Hsu College of Public Health" }, { - "author_name": "Toni Lehtonen", - "author_inst": "Finnish Institute for Health and Welfare" + "author_name": "Jessica S. Schwind", + "author_inst": "Georgia Southern University Jiann-Ping Hsu College of Public Health" }, { - "author_name": "Kari Auranen", - "author_inst": "University of Turku and Finnish Institute for Health and Welfare" + "author_name": "Kelly L. Sullivan", + "author_inst": "Georgia Southern University Jiann-Ping Hsu College of Public Health" }, { - "author_name": "Ulrike Baum", - "author_inst": "Finnish Institute for Health and Welfare" + "author_name": "Benjamin J Cowling", + "author_inst": "The University of Hong Kong" }, { - "author_name": "Tuija Leino", - "author_inst": "Finnish Institute for Health and Welfare" + "author_name": "Gerardo Chowell", + "author_inst": "Georgia State University School of Public Health" + }, + { + "author_name": "Isaac Chun-Hai Fung", + "author_inst": "Georgia Southern University Jiann-Ping Hsu College of Public Health" } ], "version": "1", @@ -674688,95 +674087,91 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.07.01.21259879", - "rel_title": "Multi-site clinical validation of Isothermal Amplification based SARS-COV-2 detection assays using different sampling strategies", + "rel_doi": "10.1101/2021.07.02.21259857", + "rel_title": "The toll of COVID-19 on African children: A descriptive analysis on the COVID-19-related morbidity and mortality among the pediatric population in Sub-Saharan Africa", "rel_date": "2021-07-06", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.01.21259879", - "rel_abs": "BackgroundIsothermal amplification-based tests were developed as rapid, low-cost, and simple alternatives to real-time reverse transcriptase-polymerase chain reaction (RT-PCR) tests for SARS-COV-2 detection.\n\nMethodsClinical performance of two isothermal amplification-based tests (Atila Biosystems iAMP COVID-19 detection test and OptiGene COVID-19 Direct Plus RT-LAMP test) was compared to clinical RT-PCR assays using different sampling strategies. A total of 1378 participants were tested across four study sites.\n\nResultsCompared to standard of care RT-PCR testing, the overall sensitivity and specificity of the Atila iAMP test for detection of SARS-CoV-2 were 76.2% and 94.9%, respectively, and increased to 88.8% and 89.5%, respectively, after exclusion of an outlier study site. Sensitivity varied based on the anatomic collected site. Sensitivity for nasopharyngeal was 65.4% (range across study sites:52.8%-79.8%), mid-turbinate 88.2%, saliva 55.1% (range across study sites:42.9%-77.8%) and anterior nares 66.7% (range across study sites:63.6%-76.5%). The specificity for these anatomic collection sites ranged from 96.7% to 100%. Sensitivity improved in symptomatic patients (overall 82.7%) and those with a higher viral load (overall 92.4% for ct[≤]25). Sensitivity and specificity of the OptiGene Direct Plus RT-LAMP test, conducted at a single study-site, were 25.5% and 100%, respectively.\n\nConclusionsThe Atila iAMP COVID test with mid-turbinate sampling is a rapid, low-cost assay for detecting SARS-COV-2, especially in symptomatic patients and those with a high viral load, and could be used to reduce the risk of SARS-COV-2 transmission in clinical settings. Variation of performance between study sites highlights the need for site-specific clinical validation of these assays before clinical adoption.", - "rel_num_authors": 19, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.02.21259857", + "rel_abs": "IntroductionSince the beginning of the COVID-19 pandemic, very little data on the epidemiological characteristics among the pediatric population in Africa has been published. This paper examines the age and sex distribution of the morbidity and mortality rate in children with COVID-19 and compares it to the adult population within 15 Sub-Saharan African countries.\n\nMethodsA merge line listing dataset using a reverse engineering model shared by countries within the Regional Office for Africa was analyzed. Patients diagnosed within 1 March 2020 and 1 September 2020 with confirmed positive RT-PCR test for SARS-CoV-2 were analyzed. Childrens data were stratified into three age groups: 0-4 years, 5-11 years, and 12-17 years, while adults were combined. The cumulative incidence of cases including its medians and 95% confidence intervals were calculated.\n\nResults9% of the total confirmed cases and 2.4% of the reported deaths were pediatric cases. The 12-17 age group in all 15 countries showed the highest cumulative incidence proportion in children. COVID-19 cases in males and females under the age of 18 were evenly distributed. Among adults, a higher case incidence per 100,000 people was observed compared to children.\n\nConclusionThe cases and deaths within the childrens population was smaller than the adult population. These differences can reflect biases in COVID-19 testing protocols and reporting implemented by countries, highlighting the need for more extensive investigation and focus on the effects of COVID-19 in children.", + "rel_num_authors": 18, "rel_authors": [ { - "author_name": "Kanan T Desai", - "author_inst": "Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Rockville, USA" - }, - { - "author_name": "Karla Alfaro", - "author_inst": "Basic Health International, Pittsburgh, USA" + "author_name": "Sabina Rodriguez Velasquez", + "author_inst": "Institute of Global Health, Faculty of Medicine, University of Geneva" }, { - "author_name": "Laura Mendoza", - "author_inst": "Instituto de Investigaciones en Ciencias de la Salud, Universidad Nacional de Asuncion, San Lorenzo, Paraguay" + "author_name": "Lea Jacques", + "author_inst": "Institute of Global Health, Faculty of Medicine, University of Geneva" }, { - "author_name": "Matthew Faron", - "author_inst": "Medical College of Wisconsin, Milwaukee, USA" + "author_name": "Jyoti Dalal", + "author_inst": "ASP/ GRAPH Network" }, { - "author_name": "Brian Mesich", - "author_inst": "Medical College of Wisconsin, Milwaukee, USA" + "author_name": "Paolo Sestito", + "author_inst": "Institute of Global Health, Faculty of Medicine, University of Geneva" }, { - "author_name": "Mauricio Maza", - "author_inst": "Basic Health International, Pittsburgh, USA" + "author_name": "Zahra Habibi", + "author_inst": "Institute of Global Health, Faculty of Medicine, University of Geneva" }, { - "author_name": "Rhina Dominguez", - "author_inst": "Research Unit, El Salvador National Institute of Health (INS), El Salvador" + "author_name": "Akarsh Venkatasubramanian", + "author_inst": "International Labour Organization, United Nations" }, { - "author_name": "Adriana Valenzuela", - "author_inst": "Instituto de Investigaciones en Ciencias de la Salud, Universidad Nacional de Asuncion, San Lorenzo, Paraguay" + "author_name": "Benedict Nguimbis", + "author_inst": "ASP/ GRAPH Network" }, { - "author_name": "Chyntia Diaz", - "author_inst": "Instituto de Investigaciones en Ciencias de la Salud, Universidad Nacional de Asuncion, San Lorenzo, Paraguay" + "author_name": "Sara Botero Mesa", + "author_inst": "Institute of Global Health, Faculty of Medicine, University of Geneva" }, { - "author_name": "Magaly Martinez", - "author_inst": "Instituto de Investigaciones en Ciencias de la Salud, Universidad Nacional de Asuncion, San Lorenzo, Paraguay" + "author_name": "Cleophas Chimbetete", + "author_inst": "Newlands Clinic" }, { - "author_name": "Juan C Felix", - "author_inst": "Medical College of Wisconsin, Milwaukee, USA" + "author_name": "Olivia Keiser", + "author_inst": "Institute of Global Health, Faculty of Medicine, University of Geneva" }, { - "author_name": "Rachel Masch", - "author_inst": "Basic Health International, Pittsburgh, USA; The Mount Sinai Hospital, New York, USA" + "author_name": "Benido Impouma", + "author_inst": "WHO Regional Office for Africa, Epidemic Preparedness and Response Programme" }, { - "author_name": "Sofia Gabrilovich", - "author_inst": "Rutgers New Jersey Medical School, Newark, USA" + "author_name": "Franck Mboussou", + "author_inst": "WHO Regional Office for Africa, Epidemic Preparedness and Response Programme" }, { - "author_name": "Michael Plump", - "author_inst": "Rutgers New Jersey Medical School, Newark, USA" + "author_name": "George Sie William", + "author_inst": "WHO Regional Office for Africa, Epidemic Preparedness and Response Programme" }, { - "author_name": "Akiva P Novetsky", - "author_inst": "Rutgers New Jersey Medical School, Newark, USA; Rutgers Cancer Institute of New Jersey, New Brunswick, NJ, USA" + "author_name": "Ngoy Nsenga", + "author_inst": "WHO Regional Office for Africa, Epidemic Preparedness and Response Programme" }, { - "author_name": "Mark H Einstein", - "author_inst": "Rutgers New Jersey Medical School, Newark, USA; Rutgers Cancer Institute of New Jersey, New Brunswick, NJ, USA" + "author_name": "Ambrose Talisuna", + "author_inst": "WHO Regional Office for Africa, Epidemic Preparedness and Response Programme" }, { - "author_name": "Nataki C Douglas", - "author_inst": "Rutgers New Jersey Medical School, Newark, USA" + "author_name": "Abdou Salam Gueye", + "author_inst": "WHO Regional Office for Africa, Epidemic Preparedness and Response Programme" }, { - "author_name": "Miriam Cremer", - "author_inst": "Basic Health International, Pittsburgh, USA; Cleveland Clinic Lerner College of Medicine, Clevland, USA" + "author_name": "Cristina Barroso Hofer", + "author_inst": "Department of Infectious Diseases, Universidade Federal do Rio de Janeiro" }, { - "author_name": "Nicolas Wentzensen", - "author_inst": "Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Rockville, USA" + "author_name": "Joseph Waogodo Cabore", + "author_inst": "WHO Regional Office for Africa, Epidemic Preparedness and Response Programme" } ], "version": "1", - "license": "cc0", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2021.06.30.21259819", @@ -676422,33 +675817,45 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2021.06.28.21259629", - "rel_title": "Implications of COVID-19 vaccination and public health countermeasures on SARS-CoV-2 variants of concern in Canada: evidence from a spatial hierarchical cluster analysis", + "rel_doi": "10.1101/2021.06.30.21259752", + "rel_title": "Importance of epidemic severity and vaccine mode of action and availability for delaying the second vaccine dose", "rel_date": "2021-07-05", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.28.21259629", - "rel_abs": "BackgroundThe influence of coronavirus disease-2019 (COVID-19) containment measures on variants of concern (VOC) has been understudied in Canada. Our objective was to identify provinces with disproportionate prevalence of VOC relative to COVID-19 mitigation efforts in provinces and territories in Canada.\n\nMethodsWe analyzed publicly available provincial- and territorial-level data on the prevalence of VOCs in relation to mitigating factors (summarized in three measures: 1. strength of public health countermeasures: stringency index, 2. how much people moved about outside their homes: mobility index, and 3. vaccine intervention: proportion of Canadian population fully vaccinated). Using spatial agglomerative hierarchical cluster analysis (unsupervised machine learning), the provinces and territories were grouped into clusters by stringency index, mobility index and full vaccine coverage. Kruskal-Wallis test was used to determine the differences in the prevalence of VOC (Alpha, or B.1.1.7, Beta, or B.1.351, Gamma, or P.1, and Delta, or B.1.617.2 variants) between the clusters.\n\nResultsThree clusters of vaccine uptake and countermeasures were identified. Cluster 1 consisted of the three Canadian territories, and characterized by higher degree of vaccine deployment and lesser degree of countermeasures. Cluster 2 (located in Central Canada and Atlantic region) was typified by lesser implementation of vaccine deployment and moderate countermeasures. The third cluster was formed by provinces in the Pacific region, Central Canada, and Prairie region, with moderate vaccine deployment but stronger countermeasures. The overall and variant-specific prevalence were significantly different across the clusters.\n\nInterpretationThis study found that implementation of COVID-19 public health measures varied across the provinces and territories. Considering the high prevalence of VOCs in Canada, completing the second dose of COVID-19 vaccine in a timely manner is crucial.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.30.21259752", + "rel_abs": "Following initial optimism regarding the potential for rapid vaccination, delays and shortages in vaccine supplies have occurred in many countries. Various strategies to counter this gloomy reality and speed up vaccination have been set forth, of which the most popular approach has been to delay the second vaccine dose for a longer period than originally recommended by the manufacturers. Controversy has surrounded this strategy, and overly simplistic models have been developed to shed light on this issue. Here we use three different epidemic models, all accounting for the actual COVID-19 epidemic in the Czech Republic, including the rise and eventual prevalence of the B.1.1.7 variant of SARS-CoV-2 virus and real vaccination rollout strategy, to explore when delaying the second vaccine dose from 21 days to 42 days is advantageous. Using the numbers of COVID-19-related deaths as a quantity for comparing various model scenarios, we find that vaccine mode of action at the beginning of the infection course (preventing contagion and symptom appearance), mild epidemic and sufficient vaccine supply rate call for the original inter-delay scenario of 21 days regardless of vaccine efficacy. On the contrary, for vaccine mode of action at the end of infection course (preventing severe symptoms and death), severe epidemic and low vaccine supply rate, the 42-day inter-dose period is preferable, at any plausible vaccine efficacy.\n\nOne sentence summaryWe address when delaying the second vaccine dose is advantageous, considering various epidemic severities and various vaccine actions and availabilities.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Daniel A Adeyinka", - "author_inst": "Department of Community Health and Epidemiology, College of Medicine, University of Saskatchewan, Saskatoon, Canada" + "author_name": "Ludek Berec", + "author_inst": "Faculty of Science, University of South Bohemia" }, { - "author_name": "Cheryl Camillo", - "author_inst": "Johnson-Shoyama Graduate School of Public Policy, University of Regina, Regina, Saskatchewan and Coronavirus Variants Rapid Response Network" + "author_name": "Rene Levinsky", + "author_inst": "CERGE-EI, Prague" }, { - "author_name": "Wendie Marks", - "author_inst": "Department of Community Health and Epidemiology, College of Medicine, University of Saskatchewan, Saskatoon, Canada and Coronavirus Variants Rapid Response Netw" + "author_name": "Jakub Weiner", + "author_inst": "Siesta Labs, Prague, Czechia" }, { - "author_name": "Nazeem Muhajarine", - "author_inst": "U of Saskatchewan and Saskatchewan Population Health and Evaluation Research Unit (SPHERU) and Coronavirus Variants Rapid Response Network" + "author_name": "Martin Smid", + "author_inst": "Czech Academy of Sciences, Institute of Information Theory and Automation" + }, + { + "author_name": "Roman Neruda", + "author_inst": "The Czech Academy of Sciences, Institute of Computer Science" + }, + { + "author_name": "Petra Vidnerova", + "author_inst": "The Czech Academy of Sciences, Institute of Computer Science" + }, + { + "author_name": "Gabriela Suchoparova", + "author_inst": "The Czech Academy of Sciences, Institute of Computer Science" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -678120,47 +677527,43 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.06.29.21259707", - "rel_title": "A new model of unreported COVID-19 cases outperforms three known epidemic-growth models in describing data from Cuba and Spain", + "rel_doi": "10.1101/2021.06.28.21259409", + "rel_title": "Predictors of Depression and Anxiety Symptoms in Brazil during COVID-19", "rel_date": "2021-07-03", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.29.21259707", - "rel_abs": "Estimating the unreported cases of Covid-19 in a region/country is a complicated problem. We propose a new mathematical model that, combined with a deterministic model of the total growth of cases, describes the time evolution of the unreported cases for each reported Covid-19 case. The new model considers the growth of unreported cases in plateau periods and the decrease towards the end of an epidemic wave. We combined the new model with a Gompertz-growth model, a generalized logistic model, and a susceptible-infectious-removed (SIR) model; and fitted them via Bayesian methods to data from Cuba and Spain. The combined-model fits yielded better Bayesian-Information-Criterion values than the Gompertz, logistic, and SIR models alone. This suggests the new model can achieve improved descriptions of the evolution of a Covid-19 epidemic wave. The new model is also able to provide reliable predictions of the epidemic evolution in a short period of time. We include in the paper the steps that researchers should take to use the new model for predictions with other data.", - "rel_num_authors": 7, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.28.21259409", + "rel_abs": "The COVID-19 pandemic in Brazil is extremely severe, and Brazil has the third-highest number of cases in the world. The goal of the study is to identify the prevalence rates and several predictors of depression and anxiety in Brazil during the initial outbreak of COVID-19. We surveyed 482 adults in 23 Brazilian states online on 9-22 May 2020, and found 70.3% of the adults (N=339) had depressive symptoms and 67.2% (N=320) had anxiety symptoms. The results of multi-class logistic regression models revealed that females, younger adults and those with fewer children had a higher likelihood of depression and anxiety symptoms; adults who worked as employees were more likely to have anxiety symptoms than those who were self-employed or unemployed; adults who spent more time browsing COVID-19 information online were more likely to have depression and anxiety symptoms. Our results provide preliminary evidence and early warning for psychiatrists and healthcare organizations to better identify and focus on the more vulnerable sub-populations in Brazil during the ongoing COVID-19 pandemic.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Erick E. Ramirez-Torres", - "author_inst": "Universidad de Oriente" - }, - { - "author_name": "Antonio R. Selva Castaneda", - "author_inst": "Universidad de Oriente" + "author_name": "Stephen X. Zhang", + "author_inst": "University of Adelaide" }, { - "author_name": "Luis Randez", - "author_inst": "Universidad de Zaragoza" + "author_name": "Hao Huang", + "author_inst": "Southwestern University of Finance and Economics" }, { - "author_name": "Luis E. V. Garcia", - "author_inst": "Centro Provincial de Higiene, Epidemiologia y Microbiologia" + "author_name": "Jizhen Li", + "author_inst": "Research Center for Competitive Dynamics and Innovation Strategy, School of Economics and Management, Tsinghua University" }, { - "author_name": "Luis E. B. Cabrales", - "author_inst": "Universidad de Oriente" + "author_name": "Antonelli-Ponti Mayra", + "author_inst": "University Center Barao de Mau" }, { - "author_name": "Scott A. Sisson", - "author_inst": "University of New South Wales" + "author_name": "de Paiva Farias Scheila", + "author_inst": "Federal University of Sergipe" }, { - "author_name": "Juan I. Montijano", - "author_inst": "Universidad de Zaragoza" + "author_name": "da Silva Aparecido Jose", + "author_inst": "Unit of Psychobiology, University of Sao Paulo in Ribeirao Preto" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "psychiatry and clinical psychology" }, { "rel_doi": "10.1101/2021.06.29.21259723", @@ -680006,89 +679409,53 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.06.25.21259525", - "rel_title": "COVID-19 in Children with Down Syndrome: Data from the Trisomy 21 Research Society Survey", + "rel_doi": "10.1101/2021.06.23.21259395", + "rel_title": "COVID-19 Flow-Maps: An open geographic information system on COVID-19 and human mobility for Spain", "rel_date": "2021-07-02", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.25.21259525", - "rel_abs": "ImportanceAdults with Down syndrome (DS) are at higher risk for severe outcomes of coronavirus disease 2019 (COVID-19), but further evidence is required to determine the exact risks for children with DS. The clinical features and epidemiological characteristics of COVID-19 in children with DS, and risk factors for severe outcomes, must be established to inform COVID-19 shielding advice and vaccination priority.\n\nObjectiveTo determine risk factors for a severe course of COVID-19 in pediatric DS patients and to compare the prevalence of severe COVID-19 between pediatric patients with and without DS.\n\nDesignThis retrospective cohort study included pediatric cases (aged <18 years) with DS from the Trisomy 21 Research Society international survey and pediatric cases from the general population published by the US Centers for Disease Control and Prevention (COVID-NET) collected during the first wave of the COVID-19 pandemic (controls).\n\nSettingCohorts included 328 children with DS (127 hospitalized, 39%) and 224 children without DS (all hospitalized) with COVID-19. Of the pediatric DS patients, 64.1% were from low-to-middle-income countries (LMICs), and 35.9% from high-income countries (HICs).\n\nParticipantsClinicians, family members, or caregivers completed the survey on behalf of children with DS affected by COVID-19.\n\nResultsAmong the 328 COVID-19 patients with DS; older age, obesity, and epilepsy were significant risk factors for hospitalization; and age and thyroid disorder were significant risk factors for acute respiratory distress syndrome. The 127 hospitalized COVID-19 patients with DS had a higher incidence of cough, fever, nasal signs and shortness of breath than controls. Compared with controls, hospitalized children with DS (especially those from LMICs) had a higher prevalence of COVID-19-related medical complications (pneumonia, ARDS, acute renal failure).\n\nConclusions and relevanceChildren with DS are at higher risk for severe COVID-19 than the general pediatric population. Efforts should be made to monitor the health of children and young people with DS during the ongoing pandemic and to report any COVID-19 signs and symptoms in a timely manner, especially for those who have comorbidities which are risk factors for severe COVID-19. When vaccination rollout for pediatric populations begins, children with DS should be prioritised.\n\nKey PointsO_ST_ABSQuestionC_ST_ABSWhat are the epidemiological and clinical characteristics of coronavirus disease 2019 (COVID-19) in paediatric patients with Down syndrome (DS)?\n\nFindingsHospitalised COVID-19 patients <18 years of age with DS from a range of countries had a higher incidence of respiratory symptoms, fever, and several medical complications from COVID-19 than patients without DS <18 years from the United States (US). Older age, obesity, and epilepsy were significant risk factors for hospitalisation among paediatric COVID-19 patients with DS; and age and thyroid disorder were significant risk factors for acute respiratory distress syndrome. Mortality rates were low in all paediatric COVID-19 patients (with and without DS), in contrast to previous findings in adults with DS (who exhibit higher mortality than those without DS).\n\nSignificanceChildren with DS are at increased risk for more severe presentations of COVID-19. Efforts should be made to ensure comprehensive and early detection of COVID-19 in this population, and to identify children with DS who present comorbidities that pose a risk for a severe course of COVID-19. Children with DS should be prioritised for COVID-19 vaccination as part of childrens vaccination programmes.", - "rel_num_authors": 19, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.23.21259395", + "rel_abs": "COVID-19 is an infectious disease caused by the SARS-CoV-2 virus, which has spread all over the world leading to a global pandemic. The fast progression of COVID-19 has been mainly related to the high contagion rate of the virus and the worldwide mobility of humans. In the absence of pharmacological therapies, governments from different countries have introduced several non-pharmaceutical interventions to reduce human mobility and social contact. Several studies based on Anonymised Mobile Phone Data have been published analysing the relationship between human mobility and the spread of coronavirus. However, to our knowledge, none of these data-sets integrates cross-referenced geo-localised data on human mobility and COVID-19 cases into one all-inclusive open resource. Herein we present COVID-19 Flow-Maps, a cross-referenced Geographic Information System that integrates regularly updated time-series accounting for population mobility and daily reports of COVID-19 cases in Spain at different scales of time spatial resolution. This integrated and up-to-date data-set can be used to analyse the human dynamics to guide and support the design of more effective non-pharmaceutical interventions.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "David Tresco Emes", - "author_inst": "London School of Hygiene and Tropical Medicine" - }, - { - "author_name": "Anke H\u00fcls", - "author_inst": "Department of Epidemiology and Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA" - }, - { - "author_name": "Nicole Baumer", - "author_inst": "Boston Childrens Hospital and Harvard Medical School, Boston, MA, USA" - }, - { - "author_name": "Mara Dierssen", - "author_inst": "Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Doctor Aiguader 88,Barcelona, Spain. Universitat Pompeu Fabra (UPF), Bar" - }, - { - "author_name": "Shiela Puri", - "author_inst": "Down Syndrome Medical Interest Group UK. Leeds Community Healthcare NHS Trust." - }, - { - "author_name": "Lauren Russel", - "author_inst": "Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, Georgia, USA" - }, - { - "author_name": "Stephanie L Sherman", - "author_inst": "Department of Human Genetics, School of Medicine, Emory University, Atlanta, Georgia, USA" - }, - { - "author_name": "Andre Strydom", - "author_inst": "Institute of Psychiatry, Psychology, and Neuroscience, Department of Forensic and Neurodevelopmental Sciences, Kings College London, London, United Kingdom; The" - }, - { - "author_name": "Stefania Bargagna", - "author_inst": "Fondazione Stella Maris IRCCS, Pisa, Italy" - }, - { - "author_name": "Ana Cl\u00e1udia Brand\u00e3o", - "author_inst": "Hospital Israelita Albert Einstein, Sao Paulo, SP, Brazil" + "author_name": "Miguel Ponce de Leon", + "author_inst": "Barcelona Supercomputing Center" }, { - "author_name": "Alberto C.S. Costa", - "author_inst": "Departments of Pediatrics and of Psychiatry, School of Medicine, Case Western Reserve University, Cleveland, Ohio, USA" + "author_name": "Javier del Valle", + "author_inst": "Barcelona Supercomputing Center" }, { - "author_name": "Brian Allen Chicoine", - "author_inst": "Advocate Medical Group Adult Down Syndrome Center, Park Ridge, IL, USA" + "author_name": "Jose Maria Fernandez", + "author_inst": "Barcelona Supercomputing Center" }, { - "author_name": "Sujay Ghosh", - "author_inst": "Cytogenetics and Genomics Research Unit. Department of Zoology, University of Calcutta.Kolkata. West Bengal, India" + "author_name": "Marc Bernardo", + "author_inst": "Barcelona Supercomputing Center" }, { - "author_name": "Anne-Sophie Rebillat", - "author_inst": "Institut J\u00e9r\u00f4me Lejeune, Paris, France" + "author_name": "Davide Cirillo", + "author_inst": "Barcelona Supercomputing Center" }, { - "author_name": "Giuseppina Sgandurra", - "author_inst": "Department of Developmental Neuroscience, IRCCS Fondazione Stella Maris, Pisa, Italy; Department of Clinical and Experimental Medicine, University of Pisa, Pi" + "author_name": "Jon Sanchez-Valle", + "author_inst": "Barcelona Supercomputing Center" }, { - "author_name": "Diletta Valentini", - "author_inst": "Pediatric Unit, Bambino Ges\u00f9 Children's Hospital, IRCCS, Rome, Italy" + "author_name": "Matthew Smith", + "author_inst": "Barcelona Supercomputing Center" }, { - "author_name": "Tilman R Rohrer", - "author_inst": "Division of Pediatric Endocrinology, Saarland University Medical Center, Homburg/Saar, Germany" + "author_name": "Salvador Capella-Gutierrez", + "author_inst": "Barcelona Supercomputing Center" }, { - "author_name": "Johannes Levin", - "author_inst": "Department of Neurology, Ludwig-Maximilians-Universit\u00e4t M\u00fcnchen, Munich, Germany. German Center for Neurodegenerative Diseases, site Munich. Munich Cluster for " + "author_name": "Tania Gullon", + "author_inst": "Ministerio de Transportes, Movilidad y Agenda Urbana" }, { - "author_name": "Monica Lakhanpaul", - "author_inst": "UCL- Great Ormond Street Institute of Child Health, London, United Kingdom; Whittington NHS Trust, London, United Kingdom; Down Syndrome Medical Interest Group," + "author_name": "Alfonso Valencia", + "author_inst": "Barcelona Supercomputing Center" } ], "version": "1", @@ -682212,85 +681579,73 @@ "category": "otolaryngology" }, { - "rel_doi": "10.1101/2021.06.28.21259671", - "rel_title": "Dimeric IgA is a specific biomarker of recent SARS-CoV-2 infection", + "rel_doi": "10.1101/2021.06.29.21259693", + "rel_title": "Recovery of serum testosterone levels is an accurate predictor of survival from COVID-19 in male patients", "rel_date": "2021-07-01", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.28.21259671", - "rel_abs": "Current tests for SARS-CoV-2 antibodies (IgG, IgM, IgA) cannot differentiate recent and past infections. We describe a point of care, lateral flow assay for SARS-CoV-2 dIgA based on the highly selective binding of dIgA to a chimeric form of secretory component (CSC), that distinguishes dIgA from monomeric IgA. Detection of specific dIgA uses a complex of biotinylated SARS-CoV-2 receptor binding domain and streptavidin-colloidal gold. SARS-CoV-2-specific dIgA was measured both in 112 cross-sectional samples and a longitudinal panel of 362 plasma samples from 45 patients with PCR-confirmed SARS-CoV-2 infection, and 193 discrete pre-COVID-19 or PCR-negative patient samples. The assay demonstrated 100% sensitivity from 11 days post-symptom onset, and a specificity of 98.2%. With an estimated half-life of 6.3 days, dIgA provides a unique biomarker for the detection of recent SARS-CoV-2 infections with potential to enhance diagnosis and management of COVID-19 at point-of-care.", - "rel_num_authors": 18, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.29.21259693", + "rel_abs": "Infection with SARS-CoV-2 portends a broad range of outcomes, from a majority of asymptomatic cases or mild clinical courses to a lethal disease. Robust correlates of severe COVID-19 include old age, male sex, poverty and co-morbidities such as obesity, diabetes or cardiovascular disease. A precise knowledge is still lacking of the molecular and biological mechanisms that may explain the association of severe disease with male sex. Here, we show that testosterone trajectories are highly accurate individual predictors (AUC of ROC = 0.928, p < 0.0001) of survival in male COVID-19 patients. Longitudinal determinations of blood levels of luteinizing hormone (LH) and androstenedione suggest an early modest inhibition of the central LH-androgen biosynthesis axis in a majority of patients, followed by either full recovery in survivors or a peripheral failure in lethal cases. Moreover, failure to reinstate physiological testosterone levels was associated with evidence of impaired T helper differentiation and decrease of non-classical monocytes. The strong association of recovery or failure to reinstate testosterone levels with survival or death from COVID-19 in male patients is suggestive of a significant role of testosterone status in the immune responses to COVID-19.", + "rel_num_authors": 15, "rel_authors": [ { - "author_name": "Heidi E Drummer", - "author_inst": "Burnet Institute" - }, - { - "author_name": "Huy Van", - "author_inst": "Burnet Institute" - }, - { - "author_name": "Ethan Klock", - "author_inst": "JHU" - }, - { - "author_name": "Shuning Zheng", - "author_inst": "Burnet Institute" + "author_name": "Emily Toscano-Guerra", + "author_inst": "Vall d'Hebron Hospital and Research Institute, Barcelona, Spain" }, { - "author_name": "Zihui Wei", - "author_inst": "Burnet Institute" + "author_name": "Monica Martinez-Gallo", + "author_inst": "Vall d'Hebron Hospital, Barcelona, Spain" }, { - "author_name": "Irene Boo", - "author_inst": "Burnet Institute" + "author_name": "Iria Arrese-Munoz", + "author_inst": "Vall d'Hebron Hospital, Barcelona, Spain" }, { - "author_name": "Rob J Center", - "author_inst": "Burnet Institute" + "author_name": "Anna Gine", + "author_inst": "Vall d'Hebron Hospital and Research Institute, Barcelona, Spain" }, { - "author_name": "Fan Li", - "author_inst": "Burnet Institute" + "author_name": "Noelia Diaz-Troyano", + "author_inst": "Vall d'Hebron Hospital, Barcelona, Spain" }, { - "author_name": "Purnima Bhat", - "author_inst": "Australian National University" + "author_name": "Pablo Gabriel-Medina", + "author_inst": "Vall d'Hebron Hospital, Barcelona, Spain" }, { - "author_name": "Rosemary Ffrench", - "author_inst": "National Serology Reference Laboratory" + "author_name": "Mar Riveiro-Barciela", + "author_inst": "Vall d'Hebron Hospital, Barcelona, Spain" }, { - "author_name": "Jillian S.Y. Lau", - "author_inst": "Monash University" + "author_name": "Moises Labrador-Horrillo", + "author_inst": "Hospital Universitari Vall d'Hebron" }, { - "author_name": "James McMahon", - "author_inst": "Monash University" + "author_name": "Fernando Martinez-Valle", + "author_inst": "Vall d'Hebron Hospital, Barcelona, Spain" }, { - "author_name": "Oliver Laeyendecker", - "author_inst": "NIAID & JHMI" + "author_name": "Manuel Hernandez-Gonzalez", + "author_inst": "Vall d'Hebron Hospital, Barcelona, Spain" }, { - "author_name": "Reinaldo E Fernandez", - "author_inst": "JHU" + "author_name": "Francisco Rodriguez-Frias", + "author_inst": "Vall d'Hebron Hospital, Barcelona, Spain" }, { - "author_name": "Yukari C Manabe", - "author_inst": "Johns Hopkins University School of Medicine" + "author_name": "Ricardo Pujol Borrell", + "author_inst": "Vall d'Hebron Hospital, Barcelona, Spain" }, { - "author_name": "Sabra L Klein", - "author_inst": "Johns Hopkins Bloomberg School of Public Health" + "author_name": "Roser Ferrer", + "author_inst": "Vall d'Hebron Hospital, Barcelona, Spain" }, { - "author_name": "Thomas C Quinn", - "author_inst": "Johns Hopkins University School of Medicine" + "author_name": "Timothy M Thomson", + "author_inst": "Institute for Molecular Biology, IBMB-CSIC, Barcelona, Spain" }, { - "author_name": "David A Anderson", - "author_inst": "Burnet Institute" + "author_name": "Rosanna Paciucci", + "author_inst": "Vall d'Hebron Hospital and Research Institute, Barcelona, Spain" } ], "version": "1", @@ -684218,35 +683573,31 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2021.06.30.450531", - "rel_title": "Early detection of SARS-CoV-2 in circulating immune cells in a mouse model", + "rel_doi": "10.1101/2021.06.29.450372", + "rel_title": "Epitope order Matters in multi-epitope-based peptide (MEBP) vaccine design: An in silico study", "rel_date": "2021-06-30", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.06.30.450531", - "rel_abs": "SARS-CoV-2 infects the respiratory tract, lung and then other organs. However, its pathogenesis remains largely unknown. We used RareScope Fluorescence Light Sheet Microscopy (FLSM) and fluorescent in situ hybridization of RNA (RNA-FISH) to detect SARS-CoV-2 RNA and dissemination kinetics in mouse blood circulation. By RNA-FISH, we found that SARS-CoV-2 RNA-positive leukocytes, including CD11c cells, appeared as early as one day after infection and continued through day 10 post infection. Our data suggest that SARS-CoV-2-permissive leukocytes contribute to systemic viral dissemination, and RNA-FISH combined with FLSM can be utilized as a sensitive tool for SARS-CoV-2 detection in blood specimens.", - "rel_num_authors": 4, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.06.29.450372", + "rel_abs": "With different countries facing multiple waves, with some SARS-CoV-2 variants more deadly and virulent, the COVID-19 pandemic is becoming more dangerous by the day and the world is facing an even more dreadful extended pandemic with exponential positive cases and increasing death rates. There is an urgent need for more efficient and faster methods of vaccine development against SARS-CoV-2. Compared to experimental protocols, the opportunities to innovate are very high in immunoinformatics/in silico approaches especially with the recent adoption of structural bioinformatics in peptide vaccine design. In recent times, multi-epitope-based peptide vaccine candidates (MEBPVCs) have shown extraordinarily high humoral and cellular responses to immunization. Most of the publications claim that respective reported MEBPVC(s) assembled using a set of in silico predicted epitopes, to be the computationally validated potent vaccine candidate(s) ready for experimental validation. However, in this article, for a given set of predicted epitopes, it is shown that the published MEBPVC is one among the many possible variants and there is high likelihood of finding more potent MEBPVCs than the published candidate. To test the same, a methodology is developed where novel MEBP variants are derived by changing the epitope order of the published MEBPVC. Further, to overcome the limitations of current qualitative methods of assessment of MEBPVC, to enable quantitative comparison, ranking, and the discovery of more potent MEBPVCs, novel predictors, Percent Epitope Accessibility (PEA), Receptor specific MEBP vaccine potency(RMVP), MEBP vaccine potency(MVP) are introduced. The MEBP variants indeed showed varied MVP scores indicating varied immunogenicity. When the MEBP variants were ranked in descending order of their MVP scores, the published MEBPVC had the least MVP score. Further, the MEBP variants with IDs, SPVC_387 and SPVC_206, had the highest MVP scores indicating these variants to be more potent MEBPVCs than the published MEBPVC and hence should be prioritized for experimental testing and validation. Through this method, more vaccine candidates will be available for experimental validation and testing. This study also opens the opportunity to develop new software tools for designing more potent MEBPVCs in less time. The computationally validated top-ranked MEBPVCs must be experimentally tested, validated, and verified. The differences and deviations between experimental results and computational predictions provide an opportunity for improving and developing more efficient algorithms and reliable scoring schemes and software.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Tingting Geng", - "author_inst": "School of Medicine, UConn Health" - }, - { - "author_name": "Spencer Keilich", - "author_inst": "QCDx LLC" + "author_name": "Muthu Raj Salaikumaran", + "author_inst": "KLEF University" }, { - "author_name": "Fyl Tafas", - "author_inst": "QCDx LLC" + "author_name": "Prasanna Sudharson Kasamuthu", + "author_inst": "KLEF University" }, { - "author_name": "PENGHUA WANG", - "author_inst": "University of Connecticut Health Center" + "author_name": "V L S Prasad Burra", + "author_inst": "K L E F University" } ], "version": "1", "license": "cc_by_nc_nd", "type": "new results", - "category": "microbiology" + "category": "biochemistry" }, { "rel_doi": "10.1101/2021.06.29.450335", @@ -686384,37 +685735,97 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2021.06.22.21257103", - "rel_title": "Is Second dose of vaccination useful in previously SARS-CoV-2 infected Health Care Workers?", + "rel_doi": "10.1101/2021.06.21.21258543", + "rel_title": "Long Term Health Consequences of COVID-19 in Hospitalized Patients from North India: A follow up study of upto 12 months", "rel_date": "2021-06-28", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.22.21257103", - "rel_abs": "SummaryVaccines are the most important public health measure to protect people from COVID-19 worldwide. In addition, healthcare workers account for a large number of infected people. Then, protecting this population from COVID-19 seems crucial in the preservation of healthcare systems. In a context of few doses available, serological assays could be useful to decide whether one or two doses are needed. Our results show that a first dose of BNT162b2 mRNA vaccine seems to act as a boost after SARS-CoV-2 infection in healthcare workers with a previous SARS-CoV-2 infection and a second dose might not be required.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.21.21258543", + "rel_abs": "BackgroundLong-COVID syndrome is now a real and pressing public health concern. We cannot reliably predict who will recover quickly or suffer with mild debilitating long COVID-19 symptoms or battle life-threatening complications. In order to address some of these questions, we studied the presence of symptoms and various correlates in COVID-19 patients who were discharged from hospital, 3 months and up to 12 months after acute COVID-19 illness.\n\nMethodsThis is an observational follow-up study of RT-PCR confirmed COVID-19 patients admitted at 3 hospitals in north India between April - August 2020. Patients were interviewed telephonically using a questionnaire regarding the post-COVID symptoms. The first tele-calling was done in the month of September 2020, which corresponded to 4-16 weeks after disease onset. All those who reported presence of long COVID symptoms, were followed-up with a second call, in the month of March 2021, corresponding to around 9-12 months after the onset of disease.\n\nResultsOf 990 patients who responded to the first call, 615 (62.2%) had mild illness, 227 (22.9%) had moderate and 148 (15.0%) had severe COVID-19 illness at the time of admission. Nearly 40% (399) of these 990 patients reported at least one symptom at that time. Of these 399 long-COVID patients, 311 (almost 78%) responded to the second follow-up. Nearly 8% reported ongoing symptomatic COVID, lasting 1-3 months and 32% patients having post-COVID phase with symptoms lasting 3-12 months. Nearly 11% patients continued to have at least one symptom even at the time of the second interview (9-12 months after the disease onset). Overall, we observed Long-COVID in almost 40% of our study group. Incidence of the symptoms in both the follow-ups remained almost same across age-groups, gender, severity of illness at admission and presence of comorbidity, with no significant association with any of them. Most common symptoms experienced in long COVID phase in our cohort were fatigue, myalgia, neuro-psychiatric symptoms like depression, anxiety, \"brain fog\" and sleep disorder, and breathlessness. Fatigue was found to be significantly more often reported in the elderly population and in those patients who had a severe COVID-19 illness at the time of admission. Persistence of breathlessness was also reported significantly more often in those who had severe disease at the onset. The overall median duration of long COVID symptoms was 16.9 weeks with inter-quartile range of 12.4 to 35.6 weeks. The duration of symptom resolution was not associated with age, gender or comorbidity but was significantly associated with severity of illness at the time of admission (P=0.006).\n\nConclusionsLong-COVID is now being recognized as a new disease entity, which includes a constellation of symptoms. Long-COVID was in almost 40% of our study group with no correlation to age, gender, comorbidities or to the disease severity. The duration of symptom resolution was significantly associated with severity of illness at the time of admission (P = 0.006). In our study, all patients reported minor symptoms such as fatigue, myalgia, neuro-psychiatric symptoms like depression, anxiety, \"brain fog\" and sleep disorder and persistence of breathlessness. Severe organ damage was not reported by our subjects. This might be the longest post-COVID follow-up study on a sample of nearly 1000 cases from India.", + "rel_num_authors": 21, "rel_authors": [ { - "author_name": "Gauthier Pean de Ponfilly", - "author_inst": "Groupe Hospitalier Paris Saint-Joseph" + "author_name": "Sandeep Budhiraja", + "author_inst": "Max Super Specialty Hospital (A unit of Devki Devi Foundation), Saket, New Delhi - 110017" }, { - "author_name": "Benoit Pilmis", - "author_inst": "Groupe Hospitalier Paris Saint-Joseph" + "author_name": "mona Aggarwal", + "author_inst": "Max Super Speciality Hospital, Saket, New Delhi, India" }, { - "author_name": "Iheb El Kaibi", - "author_inst": "Groupe Hospitalier Paris Saint Joseph" + "author_name": "Rebecca Wig", + "author_inst": "Max Super Speciality Hospital, Saket, New Delhi, India" }, { - "author_name": "Nathalie Castreau", - "author_inst": "Groupe Hospitalier Paris Saint Joseph" + "author_name": "Akansha Tyagi", + "author_inst": "Max Super Speciality Hospital, Saket, New Delhi, India" }, { - "author_name": "Sophie Laplanche", - "author_inst": "Groupe Hospitalier Paris Saint Joseph" + "author_name": "R S Mishra", + "author_inst": "Max Super Speciality Hospital, Saket, New Delhi, India" }, { - "author_name": "Alban Le Monnier", - "author_inst": "Groupe Hospitalier Paris Saint-Joseph" + "author_name": "Monica Mahajan", + "author_inst": "Max Super Speciality Hospital, Saket, New Delhi, India" + }, + { + "author_name": "Jay Kirtani", + "author_inst": "Max Super Speciality Hospital, Saket, New Delhi, India" + }, + { + "author_name": "Rommel Roshan Tickoo", + "author_inst": "Max Super Speciality Hospital, Saket, New Delhi, India" + }, + { + "author_name": "Arun Dewan", + "author_inst": "Max Smart Super Speciality Hospital, Saket, New Delhi, India" + }, + { + "author_name": "Ritesh Aggarwal", + "author_inst": "Max Smart Super Speciality Hospital, Saket, New Delhi, India" + }, + { + "author_name": "Prashant Saxena", + "author_inst": "Max Smart Super Speciality Hospital, Saket, New Delhi, India" + }, + { + "author_name": "Namrita Singh", + "author_inst": "Max Smart Super Speciality Hospital, Saket, New Delhi, India" + }, + { + "author_name": "Ashok Kumar", + "author_inst": "Max Smart Super Speciality Hospital, Saket, New Delhi, India" + }, + { + "author_name": "I M Chugh", + "author_inst": "Max Super Speciality Hospital, Shalimar Bagh, New Delhi, India" + }, + { + "author_name": "Pankaj Aneja", + "author_inst": "Max Super Speciality Hospital, Shalimar Bagh, New Delhi, India" + }, + { + "author_name": "Sanjay Dhall", + "author_inst": "Max Super Speciality Hospital, Shalimar Bagh, New Delhi, India" + }, + { + "author_name": "Vandana Boobna", + "author_inst": "Max Super Speciality Hospital, Shalimar Bagh, New Delhi, India" + }, + { + "author_name": "Vineet Arora", + "author_inst": "Max Super Speciality Hospital, Shalimar Bagh, New Delhi, India" + }, + { + "author_name": "Sujeet Jha", + "author_inst": "Max Super Speciality Hospital, Saket, New Delhi, India" + }, + { + "author_name": "Abhaya Indrayan", + "author_inst": "Max Healthcare, New-Delhi, India" + }, + { + "author_name": "supriya bali", + "author_inst": "Max Super Specialty Hospital, Saket, New Delhi - 110017" } ], "version": "1", @@ -688910,27 +688321,51 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.06.20.21259178", - "rel_title": "Taiwan on track to end third COVID-19 community outbreak", + "rel_doi": "10.1101/2021.06.20.21259188", + "rel_title": "Association between preference and e-learning readiness among the Bangladeshi female nursing students in the Covid-19 pandemic: a cross-sectional study", "rel_date": "2021-06-27", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.20.21259178", - "rel_abs": "Since the start of the COVID-19 pandemic on December 31st, 2019, with the World Health Organization being notified of pneumonia of unknown cause in Wuhan (China), Taiwan has successfully ended two COVID-19 community outbreaks. For 19 days, the third community outbreak has now been successfully suppressed, putting Taiwan on path to end it too around Aug. 16th based on our forecast using an exponential model. Since May 28th the 7-day average of reported confirmed infected, which peaked at 593, has been falling to 204 on June 16th and the 7-day average of reported suspected and excluded cases increased to above 25 000. Resulting in a decrease in the ratio of the 7-day average of local & unknown confirmed to suspected cases-the identified control variable-to less than one third of its peak value. The later is a hallmark of working contact tracing, which together with testing and isolation of infected are the keys to ending the community outbreak.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.20.21259188", + "rel_abs": "BackgroundThe COVID-19 pandemic jeopardized the traditional academic learning calendars due to the closing of all educational institutions across the globe. To keep up with the flow of learning, most of the educational institutions shifted toward e-learning. However, the students e-learning preference for various subdomains of e-learning readiness did not identify, particularly among the female nursing students for a developing country like Bangladesh, where those domains pose serious challenges.\n\nResultsA cross-sectional study was conducted among the female nursing students perceived e-learning readiness in subdomains of readiness; availability, technology use, self-confidence, and acceptance. The findings of the study revealed that the prevalence of preference for e-learning was 43.46%. The students did not prefer e-learning compared to prefer group has significantly less availability of technology ({beta} = -3.01, 95% CI: -4.46, -1.56), less use of technology ({beta} = - 3.08, 95% CI: -5.11, -1.06), less self-confidence ({beta} = -4.50, 95% CI: -7.02, -1.98), less acceptance ({beta} = -5.96, 95% CI: -7.76, -4.16) and less training need ({beta} = -1.86, 95% CI: -2.67, - 1.06). The age, degree, residence, parents highest education, having a single room, having any eye problems were significantly associated with the variation of availability of technology, use of technology, self-confidence, acceptance, and training need of e-learning.\n\nConclusionsThe outcomes of the study could be helpful while developing an effective and productive e-learning infrastructure regarding the preparedness of nursing colleges for the continuation of academia in any adverse circumstances like the COVID-19 pandemic.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Torbj\u00f6rn E. M. Nordling", - "author_inst": "National Cheng Kung University" + "author_name": "Humayun Kabir", + "author_inst": "Department of Public Health, North South University, Dhaka-1229." }, { - "author_name": "Yu-Heng Rain", - "author_inst": "National Cheng Kung University" + "author_name": "Tajrin Tahrin Tonmon", + "author_inst": "Department of Public Health, North South University, Dhaka-1229." + }, + { + "author_name": "Md. Kamrul Hasan", + "author_inst": "Department of Public Health, North South University, Dhaka-1229." + }, + { + "author_name": "Lila Biswas", + "author_inst": "CRP Nursing College, Savar, Dhaka - 1343, Bangladesh" + }, + { + "author_name": "Md. Abul Hasnat Chowdhury", + "author_inst": "Department of Public Health, North South University, Dhaka - 1229, Bangladesh" + }, + { + "author_name": "Muhammad Didarul Islam", + "author_inst": "Department of Gerontology and Geriatric Welfare, University of Dhaka - 1000, Bangladesh" + }, + { + "author_name": "Mamunur Rahman", + "author_inst": "Department of Pharmacy, East West University, Dhaka-1212" + }, + { + "author_name": "Dipak Kumar Mitra", + "author_inst": "Department of Public Health, North South University, Dhaka-1229." } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "public and global health" }, { "rel_doi": "10.1101/2021.06.20.21258152", @@ -690904,49 +690339,25 @@ "category": "nutrition" }, { - "rel_doi": "10.1101/2021.06.20.21259219", - "rel_title": "Clinical Manifestations and Pregnancy Outcomes of Covid-19 in Indonesian Referral Hospital in Central Pandemic Area", + "rel_doi": "10.1101/2021.06.21.21259230", + "rel_title": "Switched forced SEIRDV compartmental models to monitor COVID-19 spread and immunization in Italy", "rel_date": "2021-06-25", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.20.21259219", - "rel_abs": "ObjectivesThe data on clinical manifestations and pregnancy outcomes of pregnant women with COVID-19 are limited, particularly in developing countries. The aim of this study is to analyze the clinical manifestations and pregnancy outcomes in COVID-19 maternal cases in a large referral hospital in Indonesia\n\nMethodsThe study used a prospective cohort design of all pregnant women with suspected COVID-19. Subjects were divided into COVID-19 and non COVID-19 group based on real-time polymerase chain reaction (RT-PCR) of SARS-CoV-2. The clinical characteristics, laboratory results, and pregnancy outcomes were then compared between both groups.\n\nResultsFrom 141 suspected maternal cases, 62 COVID-19 cases were confirmed (43.9%), while 79 suspected cases were found to be negative (56.1%). The clinical manifestations and laboratory findings between the two groups were not significantly different (p>0.05). However, the maternal mortality directly caused by COVID-19 was significantly higher compared to the non-COVID-19 group (8.3 vs 1.3%; p=0.044; OR 6.91, 95% CI: 0.79-60.81).\n\nConclusionsThe clinical manifestation and laboratory of suspected pregnant women with positive and negative RT-PCR COVID-19 result are similiar. However, within the Indonesian setting, COVID-19 strongly increases the risk of maternal death through both direct and indirect factors.", - "rel_num_authors": 9, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.21.21259230", + "rel_abs": "This paper presents a new hybrid compartmental model for studying the COVID-19 epidemic evolution in Italy since the beginning of the vaccination campaign started on 2020/12/27 and shows forecasts of the epidemic evolution in Italy. The proposed compartmental model subdivides the population into six compartments and extends the SEIRD model proposed in [E.L.Piccolomini and F.Zama, PLOS ONE, 15(8):1-17, 08 2020] by adding the Vaccinated population and framing the global model as a hybrid-switched dynamical system. Aiming to represent the quantities that characterize the epidemic behaviour from an accurate fit to the observed data, we partition the observation time interval into sub-intervals. The model parameters change according to a switching rule depending on the data behaviour and the infection rate continuity condition. In particular, we study the representation of the infection rate both as linear and exponential piecewise continuous functions. We choose the length of sub-intervals balancing the data fit with the model complexity through the Bayesian Information Criterion. The calibration of the model shows an excellent representation of the epidemic behaviour and thirty days forecasts have proven to reproduce the infection spread reliably. Finally, we discuss different possible forecast scenarios obtained by simulating an increased vaccination rate.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Muhammad Ilham Aldika Akbar", - "author_inst": "Faculty of Medicine Universitas Airlangga" - }, - { - "author_name": "Khanizyah Erza Gumilar", - "author_inst": "Universitas Airlangga Academic Hospital" - }, - { - "author_name": "Rino Andriya", - "author_inst": "Universitas Airlangga Academic Hospital" - }, - { - "author_name": "Manggala Pasca Wardhana", - "author_inst": "Faculty of Medicine Universitas Airlangga" - }, - { - "author_name": "Pungky Mulawardhana", - "author_inst": "Faculty of Medicine Universitas Airlangga" - }, - { - "author_name": "Jimmy Yanuar Annas", - "author_inst": "Faculty of Medicine Universitas Airlangga" - }, - { - "author_name": "Ernawati Ernawati", - "author_inst": "Faculty of Medicine Universitas Airlangga" + "author_name": "Erminia Antonelli", + "author_inst": "University of Bologna" }, { - "author_name": "Muhammad Ardian Cahya Laksana", - "author_inst": "Faculty of Medicine Universitas Airlangga" + "author_name": "Elena Loli Piccolomini", + "author_inst": "University of Bologna" }, { - "author_name": "Gus Dekker", - "author_inst": "Lyell McEwin Hospital, The University of Adelaide, Adelaide, South Australia" + "author_name": "Fabiana Zama", + "author_inst": "University of Bologna" } ], "version": "1", @@ -692642,63 +692053,35 @@ "category": "obstetrics and gynecology" }, { - "rel_doi": "10.1101/2021.06.22.21259308", - "rel_title": "Expert Opinion on COVID-19 Vaccination and the Use of Cladribine Tablets in Clinical Practice", - "rel_date": "2021-06-25", + "rel_doi": "10.1101/2021.06.20.21259194", + "rel_title": "Optimal Selection of COVID-19 Vaccination Sites at the Municipal Level", + "rel_date": "2021-06-24", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.22.21259308", - "rel_abs": "BackgroundGaps in current evidence and guidance leave clinicians with unanswered questions on the use of cladribine tablets for the treatment of multiple sclerosis (MS) in the era of the COVID-19 pandemic, in particular relating to COVID-19 vaccination.\n\nObjectiveWe describe a consensus-based program led by international MS experts with the aim of supplementing current guidelines and treatment labels by providing timely recommendations relating to COVID-19 vaccination and the use of cladribine tablets in clinical practice.\n\nMethodsA steering committee (SC) of 10 international MS experts identified seven clinical questions to answer concerning the use of cladribine tablets and COVID-19 vaccination, which addressed issues relating to patient selection, timing and efficacy, and safety. Clinical recommendations to address each question were drafted using available evidence combined with expert opinion from the SC. An extended faculty of 28 MS experts, representing 19 countries, in addition to the 10 SC members, voted on the recommendations. Consensus on recommendations was achieved when [≥]75% of respondents expressed an agreement score of 7-9, on a 9-point scale.\n\nResultsConsensus was achieved on all 13 recommendations. Clinical recommendations are provided on whether all patients with MS receiving cladribine tablets should be vaccinated against COVID-19, and whether they should be prioritized; the timing of vaccination around dosing of cladribine tablets (i.e., before and after a treatment course); and the safety of COVID-19 vaccination for these patients.\n\nConclusionsThese expert recommendations provide timely guidance on COVID-19 vaccination in patients receiving cladribine tablets, which is relevant to everyday clinical practice.", - "rel_num_authors": 11, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.20.21259194", + "rel_abs": "In this work, we present an approach to determine the optimal location of coronavirus disease (COVID-19) vaccination sites at the municipal level. We assume that each municipality or town is subdivided into smaller administrative units, which we refer to as villages or barangays. The proposed method solves a minimization problem arising from a facility location problem, which is formulated based on the proximity of the vaccination sites to the villages, number of COVID-19 cases, and population densities of the villages. We present a numerical scheme to solve the optimization problem and give a detailed description of the algorithm, which is coded in Python. To make the results reproducible, the codes used in this study are uploaded to a public repository, which also contains complete instructions on how to use them. As an illustration, we apply our method in determining the optimal location of vaccination sites in San Juan, a town in the province of Batangas, in the Philippines. We hope that this study may guide the local government units in coming up with strategic plans for the COVID-19 vaccine rollout.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Peter Rieckmann", - "author_inst": "Center for Clinical Neuroplasticity, Medical Park Loipl, Bischofswiesen, Department of Neurology, University of Erlangen, Germany" - }, - { - "author_name": "Diego Centonze", - "author_inst": "Unit of Neurology and Neurorehabilitation, IRCCS Neuromed, Pozzilli (IS), Italy" - }, - { - "author_name": "Gavin Giovannoni", - "author_inst": "Queen Mary University of London, Blizard Institute, Barts and The London School of Medicine and Dentistry, London, UK" - }, - { - "author_name": "Le H Hua", - "author_inst": "Cleveland Clinic Lou Ruvo Center for Brain Health, Las Vegas, NV, USA" - }, - { - "author_name": "Celia Oreja-Guevara", - "author_inst": "Neurology, Hospital Clinico San Carlos, Idissc, Madrid, Spain and Departamento de Medicina, Facultad de Medicina, Universidad Complutense de Madrid, Spain" - }, - { - "author_name": "Daniel Selchen", - "author_inst": "University of Toronto, Division of Neurology, St. Michael's Hospital, Toronto, ON, Canada" - }, - { - "author_name": "Per Soelberg Sorensen", - "author_inst": "Danish Multiple Sclerosis Center, Department of Neurology, University of Copenhagen and Rigshospitalet, Copenhagen, Denmark" - }, - { - "author_name": "Patrick Vermersch", - "author_inst": "Univ. Lille, INSERM-U1172, CHU Lille, FHU Precise, Lille, France" + "author_name": "Kurt Izak M. Cabanilla", + "author_inst": "Institute of Mathematics, University of the Philippines Diliman" }, { - "author_name": "Heinz Wiendl", - "author_inst": "Department of Neurology, Institute of Translational Neurology, University of Munster, Munster, Germany" + "author_name": "Erika Antonette T. Enriquez", + "author_inst": "Institute of Mathematics, University of the Philippines Diliman" }, { - "author_name": "Hashem Salloukh", - "author_inst": "Merck KGaA, Darmstadt, Germany" + "author_name": "Renier Mendoza", + "author_inst": "Institute of Mathematics, University of the Philippines Diliman" }, { - "author_name": "Bassem I Yammout", - "author_inst": "Nehme and Therese Tohme Multiple Sclerosis Center, American University of Beirut, Beirut, Lebanon and Neurology Institute, Harley Street Medical Center, Abu Dha" + "author_name": "Victoria May P. Mendoza", + "author_inst": "Institute of Mathematics, University of the Philippines Diliman" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "neurology" + "category": "public and global health" }, { "rel_doi": "10.1101/2021.06.16.21258808", @@ -694420,55 +693803,75 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2021.06.22.449540", - "rel_title": "Escherichia coli recombinant expression of SARS-CoV-2 protein fragments.", + "rel_doi": "10.1101/2021.06.23.449568", + "rel_title": "Increased lung cell entry of B.1.617.2 and evasion of antibodies induced by infection and BNT162b2 vaccination", "rel_date": "2021-06-23", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.06.22.449540", - "rel_abs": "We have developed a method for the inexpensive, high-level expression of antigenic protein fragments of SARS-CoV-2 proteins in Escherichia coli. Our approach used the thermophilic family 9 carbohydrate-binding module (CBM9) as an N-terminal carrier protein and affinity tag. The CBM9 module was joined to SARS-CoV-2 protein fragments via a flexible proline-threonine linker, which proved to be resistant to E. coli proteases. Two CBM9-spike protein fragment fusion proteins and one CBM9-nucleocapsid fragment fusion protein largely resisted protease degradation, while most of the CBM9 fusion proteins were degraded at some site in the SARS-CoV-2 protein fragment. All fusion proteins were expressed in E. coli at about 0.1 g/L, and could be purified with a single affinity binding step using inexpensive cellulose powder. Three purified CBM9-SARS-CoV-2 fusion proteins were tested and found to bind antibody directed to the appropriate SARS-CoV-2 antigenic region. The largest intact CBM9 fusion protein incorporates spike protein amino acids 540-588, which is a conserved region immediately C-terminal to the receptor binding domain that is widely recognized by human convalescent sera and contains a putative protective epitope.", - "rel_num_authors": 9, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.06.23.449568", + "rel_abs": "The delta variant of SARS-CoV-2, B.1.617.2, emerged in India and has subsequently spread to over 80 countries. B.1.617.2 rapidly replaced B.1.1.7 as the dominant virus in the United Kingdom, resulting in a steep increase in new infections, and a similar development is expected for other countries. Effective countermeasures require information on susceptibility of B.1.617.2 to control by antibodies elicited by vaccines and used for COVID-19 therapy. We show, using pseudotyping, that B.1.617.2 evades control by antibodies induced upon infection and BNT162b2 vaccination, although with lower efficiency as compared to B.1.351. Further, we found that B.1.617.2 is resistant against Bamlanivimab, a monoclonal antibody with emergency use authorization for COVID-19 therapy. Finally, we show increased Calu-3-lung cell entry and enhanced cell-to-cell fusion of B.1.617.2, which may contribute to augmented transmissibility and pathogenicity of this variant. These results identify B.1.617.2 as an immune evasion variant with increased capacity to enter and fuse lung cells.", + "rel_num_authors": 14, "rel_authors": [ { - "author_name": "Bailey E McGuire", - "author_inst": "University of Victoria" + "author_name": "Prerna Arora", + "author_inst": "Infection Biology Unit, German Primate Center, Kellnerweg 4, 37077 Goettingen, Germany; Faculty of Biology and Psychology, Georg-August-University Goettingen, W" }, { - "author_name": "Julia E Mela", - "author_inst": "University of Victoria" + "author_name": "Nadine Krueger", + "author_inst": "Infection Biology Unit, German Primate Center, Kellnerweg 4, 37077 Goettingen, Germany" }, { - "author_name": "Vanessa C Thompson", - "author_inst": "University of Victoria" + "author_name": "Amy Kempf", + "author_inst": "Infection Biology Unit, German Primate Center, Kellnerweg 4, 37077 Goettingen, Germany; Faculty of Biology and Psychology, Georg-August-University Goettingen, W" }, { - "author_name": "Logan R Cucsksey", - "author_inst": "University of Victoria" + "author_name": "Inga Nehlmeier", + "author_inst": "Infection Biology Unit, German Primate Center, Kellnerweg 4, 37077 Goettingen, Germany" }, { - "author_name": "Claire E Stevens", - "author_inst": "University of Victoria" + "author_name": "Anzhalika Sidarovich", + "author_inst": "Infection Biology Unit, German Primate Center, Kellnerweg 4, 37077 Goettingen, Germany; Faculty of Biology and Psychology, Georg-August-University Goettingen, W" }, { - "author_name": "Ralph L McWhinnie", - "author_inst": "University of Victoria" + "author_name": "Luise Graichen", + "author_inst": "Infection Biology Unit, German Primate Center, Kellnerweg 4, 37077 Goettingen, Germany; Faculty of Biology and Psychology, Georg-August-University Goettingen, W" }, { - "author_name": "Dirk FH Winkler", - "author_inst": "Kinexus Bioinformatics Corporation" + "author_name": "Anna-Sophie Moldenhauer", + "author_inst": "Infection Biology Unit, German Primate Center, Kellnerweg 4, 37077 Goettingen, Germany" }, { - "author_name": "Steven Pelech", - "author_inst": "University of British Columbia" + "author_name": "Martin S. Winkler", + "author_inst": "Department of Anesthesiology, University of Goettingen Medical Center, Goettingen, Georg-August University Goettingen, Robert-Koch-Strasse 40, 37075 Goettingen," }, { - "author_name": "Francis E Nano", - "author_inst": "University of Victoria" + "author_name": "Sebastian Schulz", + "author_inst": "Division of Molecular Immunology, Department of Internal Medicine 3, Friedrich-Alexander University of Erlangen-Nuernberg, Glueckstrasse 6, 91054 Erlangen, Germ" + }, + { + "author_name": "Hans-Martin Jaeck", + "author_inst": "Division of Molecular Immunology, Department of Internal Medicine 3, Friedrich-Alexander University of Erlangen-Nuernberg, Glueckstrasse 6, 91054 Erlangen, Germ" + }, + { + "author_name": "Metodi V. Stankov", + "author_inst": "Department for Rheumatology and Immunology, Hannover Medical School, Carl-Neuberg-Strasse 1, 30625 Hannover, Germany" + }, + { + "author_name": "Georg M.N. Behrens", + "author_inst": "Department for Rheumatology and Immunology, Hannover Medical School, Carl-Neuberg-Strasse 1, 30625 Hannover, Germany" + }, + { + "author_name": "Stefan Poehlmann", + "author_inst": "Infection Biology Unit, German Primate Center, Kellnerweg 4, 37077 Goettingen, Germany; Faculty of Biology and Psychology, Georg-August-University Goettingen, W" + }, + { + "author_name": "Markus Hoffmann", + "author_inst": "Infection Biology Unit, German Primate Center, Kellnerweg 4, 37077 Goettingen, Germany; Faculty of Biology and Psychology, Georg-August-University Goettingen, W" } ], "version": "1", "license": "cc_by_nc_nd", "type": "new results", - "category": "microbiology" + "category": "molecular biology" }, { "rel_doi": "10.1101/2021.06.23.449558", @@ -695818,37 +695221,25 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.06.18.21258796", - "rel_title": "COVID in Post Vaccinated individuals- Beacon of Light", + "rel_doi": "10.1101/2021.06.15.21258991", + "rel_title": "Data-Driven Patterns in Protective Effects of Ibuprofen and Ketorolac on Hospitalized Covid-19 Patients", "rel_date": "2021-06-22", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.18.21258796", - "rel_abs": "IntroductionCOVISHIELD and COVAXIN have been introduced post rapid approval as COVID vaccines in India, which has the second most COVID cases across countries. These vaccines are being administered in a two-dose schedule from 16 Jan 2021. This study deals with the clinical profile of individuals who developed COVID infection post-COVID vaccination.\n\nThis is the first study of similar nature in India.\n\nMethodologyThe study population comprised of individuals who were detected to be COVID positive 04 weeks post-vaccination and were compared with individuals detected positive within the first 04 weeks of vaccination. Data was collected in a digital questionnaire format and analyzed with SPSS v-23 software. Clinical features were profiled in detail. Chi-square analysis was done to find out the association of various demographic features with the severity of the disease.\n\nResultsIn the study population, fever was the commonest symptom (75.1%) followed by anosmia (72.1%), and shortness of breath (16.3%). There was a lower incidence of fever, cough, dyspnea, and requirement of hospitalization in the study population as compared to the control group and previous epidemiological data. The time required for complete recovery and disease severity was favorable in our study population. There was a significant correlation in the rate of hospitalization among the study group and the comparative group (p=0.0001) and between the number of dosage of COVID vaccine with the lowest SpO2 recorded (p=0.001).\n\nConclusionThis study will boost the ongoing initiative of having a maximal vaccinated population countrywide and emphasize the need for two doses of vaccination.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.15.21258991", + "rel_abs": "The impact of nonsteroidal anti-inflammatory drugs (NSAIDs) on patients with Covid-19 has been unclear. A major reason for this uncertainty is the confounding between treatments, patient comorbidities, and illness severity. Here, we perform an observational analysis of over 3000 patients hospitalized for Covid-19 in a New York hospital system to identify the relationship between in-patient treatment with Ibuprofen or Ketorolac and mortality. Our analysis finds evidence consitent with a protective effect for Ibuprofen and Ketorolac, with evidence stronger for a protective effect of Ketorolac than for a protective effect of Ibuprofen.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "V K Sashindran", - "author_inst": "Dept of Internal Medicine, 7 Air Force Hospital, Kanpur" - }, - { - "author_name": "K Rajesh", - "author_inst": "Dept of Internal Medicine, 7 Air Force Hospital, Kanpur" - }, - { - "author_name": "Ankur Nigam", - "author_inst": "Public Health Specialist, Gangtok" - }, - { - "author_name": "Sourya Sourabh Mohakuda", - "author_inst": "Dept of Internal Medicine, 7 Air Force Hospital,Kanpur" + "author_name": "Benjamin J Lengerich", + "author_inst": "MIT" }, { - "author_name": "Navin Bhati", - "author_inst": "Dept of Internal Medicine, 7 Air Force Hospital, Kanpur" + "author_name": "Rich Caruana", + "author_inst": "Microsoft Research" }, { - "author_name": "Mohapatra D", - "author_inst": "Dept of Internal Medicine, 7 Air Force Hospital, Kanpur" + "author_name": "Yin J Aphinyanaphongs", + "author_inst": "NYU Langone Health" } ], "version": "1", @@ -697204,33 +696595,57 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2021.06.17.21258956", - "rel_title": "School teachers' self-reported fear and risk perception during the COVID-19 pandemic - a nationwide survey in Germany", + "rel_doi": "10.1101/2021.06.17.21259121", + "rel_title": "Development of an index to assess Covid-19 hospital care installed capacity in the 450 Brazilian Health Regions", "rel_date": "2021-06-21", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.17.21258956", - "rel_abs": "BackgroundWith COVID-19 cases peaking, COVID-19 vaccination programs starting and health systems reaching their limits in winter 2020/21, schools remained closed in many countries despite ever-recurring debates. To better understand teachers fear of infection and risk perception we conducted a survey in Germany.\n\nMethodsParticipants were recruited through various associations and invited to take part in a cross-sectional COVID-19 specific online survey. Anonymous demographic and self-reported data were collected from those who gave their informed consent. Descriptive statistical analysis was performed. To evaluate with fear associated factors of contracting SARS-CoV-2, an adjusted multivariable regression analysis was performed.\n\nResults6.753 teachers gave their informed consent to answer the online survey. The median age of the teachers was 43 years with 77% being female. Most teachers worked in high schools (29%) and elementary schools (26%). Most participants (73%) feared to contract SARS-CoV-2 at school while 77% intended to be vaccinated against COVID-19. 98% considered students to pose the greatest risk. Multivariable regression analysis revealed that female and younger teachers were significantly more anxious to get infected with SARS-CoV-2 and that the odds teachers were more anxious was 9 times higher for those who favored re-opening of schools the least (p < 0.001).\n\nConclusionsTo the authors knowledge, this is the first study to describe teachers fear and risk perception of COVID-19 and their attitude towards vaccinations in a nationwide survey. The anxiety correlates to the COVID-19 protection measures demanded. Teachers fear is the driving factor and not a rational logic.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.17.21259121", + "rel_abs": "ObjectiveWe assessed the Brazilian health systems ability to respond to the challenges imposed by the Covid-19 pandemic considering hospital capacity in the 450 Health Regions of the country in 2020. Hospital capacity referred to the availability of hospital beds, equipment, and human resources.\n\nMethodsData came from National Register of Health Facilities on the availability of Covid-19 resources in inpatient facilities from January to December,2020. Assessed resources were health professionals, hospital beds, and medical equipment. A synthetic indicator, Installed Capacity Index (ICI) was calculated using Principal Component Analysis.\n\nResultsThere was an increase in all selected indicators between January and December 2020. We observed differences between the Northeast, North regions, and the other regions of the country. Most Health Regions presented low ICI. The ICI increased especially in regions with considerably high baseline capacity in January 2020. The Northeast and North had a higher concentration oflow ICI regions.\n\nConclusionThe information here provided may be used by health authorities, providers, and managers in planning and adjusting for future Covid-19 care and in dimensioning the adequate supply of hospital beds, health care professionals, and devices in Health Regions to reduce associated morbidity and mortality.", + "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Stefanie Weinert", - "author_inst": "Charite - Universitaetsmedizin Berlin" + "author_name": "Claudia C. A. Pereira", + "author_inst": "ENSP/Fiocruz" }, { - "author_name": "Anja Thronicke", - "author_inst": "Charite - Universitaetsmedizin Berlin" + "author_name": "Fernando Soares", + "author_inst": "ENSP/Fiocruz" }, { - "author_name": "Maximilian Hinse", - "author_inst": "Charite - Universitaetsmedizin Berlin" + "author_name": "Gustavo Frio", + "author_inst": "Universidade de Brasilia" + }, + { + "author_name": "Carla Machado", + "author_inst": "Universidade Federal de Minas Gerais" }, { - "author_name": "Friedemann Schad", - "author_inst": "Research Institute Havelhoehe" + "author_name": "Layana Alves", + "author_inst": "Ministerio da Saude, Brazil" }, { - "author_name": "Harald Matthes", - "author_inst": "Charite - Universitaetsmedizin Berlin" + "author_name": "Fernando Herkrath", + "author_inst": "Fiocruz Amazonas" + }, + { + "author_name": "Rodrigo Lima", + "author_inst": "Fiocruz Amazonas" + }, + { + "author_name": "Ivana Barreto", + "author_inst": "Fiocruz Ceara" + }, + { + "author_name": "Everton Silva", + "author_inst": "Universidade de Brasilia" + }, + { + "author_name": "Anny Andrade", + "author_inst": "Fiocruz Amazonas" + }, + { + "author_name": "Leonor Santos", + "author_inst": "Universidade de Brasilia" } ], "version": "1", @@ -699529,59 +698944,63 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.06.16.21259029", - "rel_title": "A Short Plus Long-Amplicon Based Sequencing Approach Improves Genomic Coverage and Variant Detection In the SARS-CoV-2 Genome", + "rel_doi": "10.1101/2021.06.17.21259066", + "rel_title": "Seroprevalence of COVID-19 in HIV Population", "rel_date": "2021-06-20", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.16.21259029", - "rel_abs": "High viral transmission in the COVID-19 pandemic has enabled SARS-CoV-2 to acquire new mutations that impact genome sequencing methods. The ARTIC.v3 primer pool that amplifies short amplicons in a multiplex-PCR reaction is one of the most widely used methods for sequencing the SARS-CoV-2 genome. We observed that some genomic intervals are poorly captured with ARTIC primers. To improve the genomic coverage and variant detection across these intervals, we designed long amplicon primers and evaluated the performance of a short (ARTIC) plus long amplicon (MRL) sequencing approach. Sequencing assays were optimized on VR-1986D-ATCC RNA followed by sequencing of nasopharyngeal swab specimens from five COVID-19 positive patients. ARTIC data covered >90% of the virus genome fraction in the positive control and four of the five patient samples. Variant analysis in the ARTIC data detected 67 mutations, including 66 single nucleotide variants (SNVs) and one deletion in ORF10. Of 66 SNVs, five were present in the spike gene, including nt22093 (M177I), nt23042 (S494P), nt23403 (D614G), nt23604 (P681H), and nt23709 (T716I). The D614G mutation is a common variant that has been shown to alter the fitness of SARS-CoV-2. Two spike protein mutations, P681H and T716I, which are represented in the B.1.1.7 lineage of SARS-CoV-2, were also detected in one patient. Long-amplicon data detected 58 variants, of which 70% were concordant with ARTIC data. Combined analysis of ARTIC +MRL data revealed 22 mutations that were either ambiguous (17) or not called at all (5) in ARTIC data due to poor sequencing coverage. For example, a common mutation in the ORF3a gene at nt25907 (G172V) was missed by the ARTIC assay. Hybrid data analysis improved sequencing coverage overall and identified 59 high confidence mutations for phylogenetic analysis. Thus, we show that while the short amplicon (ARTIC) assay provides good genomic coverage with high throughput, complementation of poorly captured intervals with long amplicon data can significantly improve SARS-CoV-2 genomic coverage and variant detection.", - "rel_num_authors": 10, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.17.21259066", + "rel_abs": "BackgroundSeroprevalence helps us to estimate the exact prevalence of a disease in a population. Although the world has been battling this pandemic for more than a year now, we still do not know about the burden of this disease in people living with HIV/AIDS (PLHA). Seroprevalence data in this population subset is scarce in most parts of the world, including India. The current study aimed to estimate the seroprevalence of anti-SARS-CoV-2 IgG antibody among PLHA.\n\nAimTo determine the seroprevalence of SARS-CoV-2 antibodies in PLHA.\n\nMethodThis was a cross-sectional study conducted at a tertiary care hospital in North India. We recruited HIV positive patients following at the ART centre of the institute. Anti-SARS-CoV-2 IgG antibody levels targeting recombinant spike receptor-binding domain (RBD) protein of SARS CoV-2 were estimated in serum sample by the chemiluminescent immunoassay method.\n\nResultsA total of 164 patients were recruited in the study with a mean age ({+/-}SD) of 41.2 ({+/-}15.4) years, of which 55% were male. Positive serology against SARS CoV-2 was detected in 14% patients (95% CI: 9.1-20.3%).\n\nConclusionThe seroprevalence of COVID-19 infection in PLHA was lower than the general population in the same region, which ranged from 23.48% to 28.3% around the study period.", + "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Carlos Arana", - "author_inst": "UT Southwestern Medical Center" + "author_name": "Shivdas Rajaram Naik", + "author_inst": "AIIMS New Delhi" }, { - "author_name": "Chaoying Liang", - "author_inst": "UT Southwestern Medical Center" + "author_name": "Swasthi S Kumar", + "author_inst": "AIIMS, New Delhi" }, { - "author_name": "Matthew Brock", - "author_inst": "UT Southwestern Medical Center" + "author_name": "Ankit Mittal", + "author_inst": "AIIMS, New Delhi" }, { - "author_name": "Bo Zhang", - "author_inst": "University of Texas Southwestern Medical Center" + "author_name": "Satish Swain", + "author_inst": "AIIMS, New Delhi" }, { - "author_name": "Jinchun Zhou", - "author_inst": "University of Texas Southwestern Medical Center" + "author_name": "Sanjay Ranjan", + "author_inst": "AIIMS, New Delhi" }, { - "author_name": "Li Chen", - "author_inst": "University of Texas Southwestern Medical Center" + "author_name": "Manish Soneja", + "author_inst": "AIIMS, New Delhi" }, { - "author_name": "Brandi Cantarel", - "author_inst": "University of Texas Southwestern Medical Center" + "author_name": "Sanjeev Sinha", + "author_inst": "AIIMS, New Delhi" }, { - "author_name": "Jeffrey SoRelle", - "author_inst": "University of Texas Southwestern Medical Center, Dallas" + "author_name": "Neeraj Nischal", + "author_inst": "AIIMS, New Delhi" }, { - "author_name": "Lora V. Hooper", - "author_inst": "University of Texas Southwestern Medical Center" + "author_name": "Pankaj Jorwal", + "author_inst": "AIIMS, New Delhi" }, { - "author_name": "Prithvi Raj", - "author_inst": "University of Texas Southwestern Medical Center" + "author_name": "Pradeep K Chaturvedi", + "author_inst": "AIIMS, New Delhi" + }, + { + "author_name": "Naveet Wig", + "author_inst": "AIIMS, New Delhi" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "genetic and genomic medicine" + "category": "hiv aids" }, { "rel_doi": "10.1101/2021.06.17.21259050", @@ -701419,39 +700838,27 @@ "category": "occupational and environmental health" }, { - "rel_doi": "10.1101/2021.06.15.21258978", - "rel_title": "Inequities among vulnerable communities during the COVID-19 vaccine rollout", + "rel_doi": "10.1101/2021.06.15.21259004", + "rel_title": "Long COVID symptoms from Reddit: Characterizing post-COVID syndrome from patient reports", "rel_date": "2021-06-18", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.15.21258978", - "rel_abs": "ImportanceFederal and state governments sought to prioritize vulnerable communities in the vaccine rollout through various methods of prioritization, and it is necessary to understand whether inequities exist.\n\nObjectiveTo assess whether vulnerable counties have achieved similar rates of coverage to non-vulnerable areas, and how vaccine acceptance varies by vulnerability.\n\nDesign, Setting, and ParticipantsWe use population-weighted univariate linear regressions to associate the COVID-19 Community Vulnerability Index (CCVI) and its 7 constituent themes with a county-level time series of vaccine coverage and vaccine acceptance. We fit a multilevel model to understand how vulnerability within and across states associates with coverage as of May 8, 2021.\n\nMain Outcome(s) and Measure(s)The COVID-19 Community Vulnerability Index was used as a metric for county-level vulnerability. County-level daily COVID-19 vaccination data on both first doses administered and people fully vaccinated from April 3, 2021 through May 8, 2021 were extracted from the Covid Act Now API. County-level daily COVID-19 vaccine acceptance survey data from January 6, 2021 through May 4, 2021 were obtained via the Carnegie Mellon University Delphi Groups COVIDcast API.\n\nResultsVulnerable counties have consistently lagged less vulnerable counties. As of May 8, the top third of vulnerable counties in the US had fully vaccinated 11.3% fewer people than the bottom third (30.7% vs 34.6% of adult population; linear regression, p= 2.2e-16), and 12.1% fewer initiated vaccinations (40.1% vs 45.6%; linear regression, p= 2.2e-16)). Six out of seven dimensions of vulnerability, including Healthcare System Factors and Socioeconomic Status, predicted lower coverage whereas the Population Density theme associated with higher coverage. Vulnerable counties have also consistently had a slightly lower level of vaccine acceptance, though as of May 4, 2021 this difference was observed to be only 0.7% between low- and high-vulnerability counties (high: 86.1%, low: 85.5%, p=0.027).\n\nConclusions and RelevanceThe vaccination gap between vulnerable and non-vulnerable counties is substantial and not readily explained by a difference in acceptance. Vulnerable populations continue to need additional support, and targeted interventions are necessary to achieve similar coverage in vulnerable counties compared to those less vulnerable to COVID-19.\n\nKey PointsO_ST_ABSQuestionC_ST_ABSAre the US counties most vulnerable to COVID-19 also facing the lowest vaccination coverage?\n\nFindingsUS populations with increased health, social, and economic vulnerabilities have experienced consistently lower vaccination coverage. As of May 8, on average, the top third of vulnerable counties across the US had fully vaccinated 11.3% fewer people than the least vulnerable third. There is only a 0.7% difference in vaccine acceptance between the 2 cohorts..\n\nMeaningThe gap in vaccination coverage among vulnerable US communities cannot be explained by lower acceptance. Structural barriers need to be addressed to decrease these inequities.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.15.21259004", + "rel_abs": "ObjectiveTo mine Reddit to discover long-COVID symptoms self-reported by users, compare symptom distributions across studies, and create a symptom lexicon.\n\nMaterials and MethodsWe retrieved posts from the /r/covidlonghaulers subreddit and extracted symptoms via approximate matching using an expanded meta-lexicon. We mapped the extracted symptoms to standard concept IDs, compared their distributions with those reported in recent literature and analyzed their distributions over time.\n\nResultsFrom 42,995 posts by 4249 users, we identified 1744 users who expressed at least 1 symptom. The most frequently reported long-COVID symptoms were mental health-related symptoms (55.2%), fatigue (51.2%), general ache/pain (48.4%), brain fog/confusion (32.8%) and dyspnea (28.9%) amongst users reporting at least 1 symptom. Comparison with recent literature revealed a large variance in reported symptoms across studies. Temporal analysis showed several persistent symptoms up to 15 months after infection.\n\nConclusionThe spectrum of symptoms identified from Reddit may provide early insights about long-COVID.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Nicholas Stewart", - "author_inst": "Surgo Ventures" - }, - { - "author_name": "Peter Smittenaar", - "author_inst": "Surgo Ventures" - }, - { - "author_name": "Staci Sutermaster", - "author_inst": "Surgo Ventures" - }, - { - "author_name": "Lindsay Coome", - "author_inst": "Surgo Ventures" + "author_name": "Abeed Sarker", + "author_inst": "Emory University" }, { - "author_name": "Sema K. Sgaier", - "author_inst": "Surgo Ventures" + "author_name": "Yao Ge", + "author_inst": "Emory University" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "health policy" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2021.06.16.21258972", @@ -703477,143 +702884,155 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.06.12.448080", - "rel_title": "High efficacy of therapeutic equine hyperimmune antibodies against SARS CoV-2 variants of concern", + "rel_doi": "10.1101/2021.06.15.21258542", + "rel_title": "Casirivimab and imdevimab in patients admitted to hospital with COVID-19 (RECOVERY): a randomised, controlled, open-label, platform trial", "rel_date": "2021-06-16", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.06.12.448080", - "rel_abs": "SARS-CoV-2 variants of concern (VoC) show reduced neutralization by vaccine-induced and therapeutic monoclonal antibodies. We tested therapeutic equine polyclonal antibodies (pAbs) against four VoC (alpha, beta, epsilon and gamma). We show that equine pAbs efficiently neutralize VoC, suggesting they are an effective, broad coverage, low-cost and a scalable COVID-19 treatment.", - "rel_num_authors": 31, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.15.21258542", + "rel_abs": "BackgroundREGEN-COV is a combination of 2 monoclonal antibodies (casirivimab and imdevimab) that bind to two different sites on the receptor binding domain of the SARS-CoV-2 spike protein. We aimed to evaluate the efficacy and safety of REGEN-COV in patients admitted to hospital with COVID-19.\n\nMethodsIn this randomised, controlled, open-label platform trial, several possible treatments were compared with usual care in patients hospitalised with COVID-19. Eligible and consenting patients were randomly allocated (1:1) to either usual standard of care alone (usual care group) or usual care plus a single dose of REGEN-COV 8g (casirivimab 4g and imdevimab 4g) by intravenous infusion (REGEN-COV group). The primary outcome was 28-day mortality assessed first among patients without detectable antibodies to SARS-CoV-2 at randomisation (seronegative) and then in the overall population. The trial is registered with ISRCTN (50189673) and clinicaltrials.gov (NCT04381936).\n\nFindingsBetween 18 September 2020 and 22 May 2021, 9785 patients were randomly allocated to receive usual care plus REGEN-COV or usual care alone, including 3153 (32%) seronegative patients, 5272 (54%) seropositive patients and 1360 (14%) patients with unknown baseline antibody status. In the primary efficacy population of seronegative patients, 396 (24%) of 1633 patients allocated to REGEN-COV and 451 (30%) of 1520 patients allocated to usual care died within 28 days (rate ratio 0{middle dot}80; 95% CI 0{middle dot}70-0{middle dot}91; p=0{middle dot}0010). In an analysis involving all randomised patients (regardless of baseline antibody status), 944 (20%) of 4839 patients allocated to REGEN-COV and 1026 (21%) of 4946 patients allocated to usual care died within 28 days (rate ratio 0{middle dot}94; 95% CI 0{middle dot}86-1{middle dot}03; p=0{middle dot}17). The proportional effect of REGEN-COV on mortality differed significantly between seropositive and seronegative patients (p value for heterogeneity = 0{middle dot}001).\n\nInterpretationIn patients hospitalised with COVID-19, the monoclonal antibody combination of casirivimab and imdevimab (REGEN-COV) reduced 28-day mortality among patients who were seronegative at baseline.\n\nFundingUK Research and Innovation (Medical Research Council) and National Institute of Health Research (Grant ref: MC_PC_19056).", + "rel_num_authors": 34, "rel_authors": [ { - "author_name": "Andres Moreira-Soto", - "author_inst": "Charit\u00e9-Universit\u00e4tsmedizin Berlin" + "author_name": "Peter W Horby", + "author_inst": "Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom" }, { - "author_name": "Mauricio Arguedas", - "author_inst": "Instituto Clodomiro Picado, Facultad de Microbiolog\u00eda, Universidad de Costa Rica" + "author_name": "Marion Mafham", + "author_inst": "Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom" }, { - "author_name": "Hebleen Brenes", - "author_inst": "INCIENSA, Ministry of Health, Costa Rica" + "author_name": "Leon Peto", + "author_inst": "Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom" }, { - "author_name": "Willem Buj\u00e1n", - "author_inst": "School of Medicine, Universidad de Costa Rica" + "author_name": "Mark Campbell", + "author_inst": "Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom" }, { - "author_name": "Eugenia Corrales-Aguilar", - "author_inst": "CIET, Facultad de Microbiolog\u00eda, Universidad de Costa Rica" + "author_name": "Guilherme Pessoa-Amorim", + "author_inst": "Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom" }, { - "author_name": "Cecilia D\u00edaz", - "author_inst": "Instituto Clodomiro Picado, Facultad de Microbiolog\u00eda, Universidad de Costa Rica" + "author_name": "Enti Spata", + "author_inst": "MRC Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom" }, { - "author_name": "Ann Echeverri", - "author_inst": "Caja Costarricense del Seguro Social, Costa Rica" + "author_name": "Natalie Staplin", + "author_inst": "MRC Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom" }, { - "author_name": "Marietta Flores-D\u00edaz", - "author_inst": "Instituto Clodomiro Picado, Facultad de Microbiolog\u00eda, Universidad de Costa Rica" + "author_name": "Jonathan R Emberson", + "author_inst": "MRC Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom" }, { - "author_name": "Aar\u00f3n G\u00f3mez", - "author_inst": "Instituto Clodomiro Picado, Facultad de Microbiolog\u00eda, Universidad de Costa Rica" + "author_name": "Benjamin Prudon", + "author_inst": "North Tees and Hartlepool NHS Foundation Trust, Hartlepool, United Kingdom" }, { - "author_name": "Andr\u00e9s Hern\u00e1ndez", - "author_inst": "Instituto Clodomiro Picado, Facultad de Microbiolog\u00eda, Universidad de Costa Rica" + "author_name": "Paul Hine", + "author_inst": "Liverpool University Hospitals NHS Foundation Trust" }, { - "author_name": "Mar\u00eda Herrera", - "author_inst": "Instituto Clodomiro Picado, Facultad de Microbiolog\u00eda, Universidad de Costa Rica" + "author_name": "Thomas Brown", + "author_inst": "Portsmouth Hospitals University NHS Foundation Trust, Portsmouth, United Kingdom" }, { - "author_name": "Guillermo Le\u00f3n", - "author_inst": "Instituto Clodomiro Picado, Facultad de Microbiolog\u00eda, Universidad de Costa Rica" + "author_name": "Christopher A Green", + "author_inst": "University Hospitals Birmingham NHS Foundation Trust" }, { - "author_name": "Rom\u00e1n Macaya", - "author_inst": "Caja Costarricense del Seguro Social, Costa Rica" + "author_name": "Rahuldeb Sarkar", + "author_inst": "Medway NHS Foundation Trust" }, { - "author_name": "Arne Kh\u00fcne", - "author_inst": "Charit\u00e9-Universit\u00e4tsmedizin Berlin" + "author_name": "Purav Desai", + "author_inst": "Calderdale and Huddersfield NHS Foundation Trust" }, { - "author_name": "Jose Arturo Molina-Mora", - "author_inst": "Research Center in Tropical Diseases, University of Costa Rica" + "author_name": "Bryan Yates", + "author_inst": "Northumbria Healthcare NHS Foundation Trust" }, { - "author_name": "Javier Mora", - "author_inst": "Instituto Clodomiro Picado, Facultad de Microbiolog\u00eda, Universidad de Costa Rica" + "author_name": "Tom Bewick", + "author_inst": "University Hospitals Of Derby and Burton NHS Foundation Trust" }, { - "author_name": "Alfredo Sanabria", - "author_inst": "Caja Costarricense del Seguro Social, Costa Rica" + "author_name": "Simon Tiberi", + "author_inst": "Barts Health NHS Trust" }, { - "author_name": "Andr\u00e9s S\u00e1nchez", - "author_inst": "Instituto Clodomiro Picado, Facultad de Microbiolog\u00eda, Universidad de Costa Rica" + "author_name": "Tim Felton", + "author_inst": "Manchester University NHS Foundation Trust" }, { - "author_name": "Laura S\u00e1nchez", - "author_inst": "Instituto Clodomiro Picado, Facultad de Microbiolog\u00eda, Universidad de Costa Rica" + "author_name": "J Kenneth Baillie", + "author_inst": "Roslin Institute, University of Edinburgh, Edinburgh, United Kingdom" }, { - "author_name": "\u00c1lvaro Segura", - "author_inst": "Instituto Clodomiro Picado, Facultad de Microbiolog\u00eda, Universidad de Costa Rica" + "author_name": "Maya H Buch", + "author_inst": "Centre for Musculoskeletal Research, University of Manchester, Manchester, United Kingdom" }, { - "author_name": "Eduardo Segura", - "author_inst": "Instituto Clodomiro Picado, Facultad de Microbiolog\u00eda, Universidad de Costa Rica" + "author_name": "Lucy C Chappell", + "author_inst": "School of Life Sciences, Kings College London, London, United Kingdom" }, { - "author_name": "Daniela Solano", - "author_inst": "Instituto Clodomiro Picado, Facultad de Microbiolog\u00eda, Universidad de Costa Rica" + "author_name": "Jeremy N Day", + "author_inst": "Oxford University Clinical Research Unit, Ho Chi Minh City, Viet Nam, and Nuffield Department of Medicine, University of Oxford, United Kingdom" }, { - "author_name": "Claudio Soto", - "author_inst": "INCIENSA, Ministry of Health, Costa Rica" + "author_name": "Saul N Faust", + "author_inst": "NIHR Southampton Clinical Research Facility and Biomedical Research Centre, University Hospital Southampton NHS Foundation Trust and University of Southampton, " }, { - "author_name": "Jennifer L. Stynoski", - "author_inst": "Instituto Clodomiro Picado, Facultad de Microbiolog\u00eda, Universidad de Costa Rica" + "author_name": "Thomas Jaki", + "author_inst": "Department of Mathematics and Statistics, Lancaster University, Lancaster, United Kingdom" }, { - "author_name": "Mariangela Vargas", - "author_inst": "Instituto Clodomiro Picado, Facultad de Microbiolog\u00eda, Universidad de Costa Rica" + "author_name": "Katie Jeffery", + "author_inst": "Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom" }, { - "author_name": "Mauren Villalta", - "author_inst": "Instituto Clodomiro Picado, Facultad de Microbiolog\u00eda, Universidad de Costa Rica" + "author_name": "Edmund Juszczak", + "author_inst": "School of Medicine, University of Nottingham, Nottingham, United Kingdom" }, { - "author_name": "Chantal Reusken", - "author_inst": "Centre for Infectious Disease Control, National Institute for Public Health and the Environment, Bilthoven, the Netherlands" + "author_name": "Wei Shen Lim", + "author_inst": "Respiratory Medicine Department, Nottingham University Hospitals NHS Foundation Trust, Nottingham, United Kingdom" }, { - "author_name": "Chistian Drosten", - "author_inst": "Charit\u00e9-Universit\u00e4tsmedizin Berlin" + "author_name": "Alan Montgomery", + "author_inst": "School of Medicine, University of Nottingham, Nottingham, United Kingdom" }, { - "author_name": "Jos\u00e9 Mar\u00eda Guti\u00e9rrez", - "author_inst": "Instituto Clodomiro Picado, Facultad de Microbiolog\u00eda, Universidad de Costa Rica" + "author_name": "Andrew Mumford", + "author_inst": "School of Cellular and Molecular Medicine, University of Bristol, Bristol, United Kingdom" }, { - "author_name": "Alberto Alape-Gir\u00f3n", - "author_inst": "Instituto Clodomiro Picado, Facultad de Microbiolog\u00eda, Universidad de Costa Rica" + "author_name": "Kathryn Rowan", + "author_inst": "Intensive Care National Audit and Research Centre, London, United Kingdom" }, { - "author_name": "Jan Felix Drexler", - "author_inst": "Charit\u00e9-Universit\u00e4tsmedizin Berlin" + "author_name": "Guy Thwaites", + "author_inst": "Oxford University Clinical Research Unit, Ho Chi Minh City, Viet Nam, and Nuffield Department of Medicine, University of Oxford, United Kingdom" + }, + { + "author_name": "David M Weinreich", + "author_inst": "Regeneron Pharmaceuticals Inc, Tarrytown, NY, USA" + }, + { + "author_name": "Richard Haynes", + "author_inst": "MRC Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom" + }, + { + "author_name": "Martin J Landray", + "author_inst": "Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom" } ], "version": "1", - "license": "cc_no", - "type": "new results", - "category": "microbiology" + "license": "cc_by", + "type": "PUBLISHAHEADOFPRINT", + "category": "infectious diseases" }, { "rel_doi": "10.1101/2021.06.10.21258720", @@ -705626,53 +705045,97 @@ "category": "nephrology" }, { - "rel_doi": "10.1101/2021.06.11.21258765", - "rel_title": "Factors associated with COVID-19 susceptibility and severity in patients with multiple sclerosis: A systematic review", + "rel_doi": "10.1101/2021.06.11.21258690", + "rel_title": "Brain imaging before and after COVID-19 in UK Biobank", "rel_date": "2021-06-15", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.11.21258765", - "rel_abs": "BackgroundWe conducted this systematic review to identify factors associated with coronavirus disease (COVID-19) susceptibility and outcomes among people with multiple sclerosis (MS).\n\nMethodsAvailable studies from PubMed, Scopus, EMBASE, Web of Science, and gray literature including reference list and conference abstracts were searched from December 1, 2019, through April 12, 2021. We included cross-sectional, case-control, and cohort studies that reported risk factors of contracting COVID-19 or its outcome in patients with MS on univariate or multivariate regression analyses.\n\nResultsOut of the initial 2719 records and 1553 conference abstracts, a total of 20 studies were included. Factors associated with COVID-19 susceptibility were reported in 11 studies and risk factors for infection outcomes were discussed in 10. History of contact with an infected is strongly suggested as a risk factor for COVID-19 susceptibility. Other factors that could be associated with contracting infection are younger age, relapsing course, and anti-CD20 agents. The evidence suggests that increasing age, greater MS severity, treatment with anti-CD20 agents, previous use of corticosteroids, and specific comorbidities (obesity and coronary artery disease) could be independently associated with worse infection outcomes. Male sex is likely to be a risk factor for more severe disease. The black or African American race was reported as a possible risk factor.\n\nConclusionDue to a paucity of research and methodological issues, no risk factors for COVID-19 susceptibility and outcomes neither be confirmed nor excluded. Further large studies are needed to address factors associated with COVID-19 susceptibility and severity.", - "rel_num_authors": 9, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.11.21258690", + "rel_abs": "There is strong evidence for brain-related abnormalities in COVID-191-13. It remains unknown however whether the impact of SARS-CoV-2 infection can be detected in milder cases, and whether this can reveal possible mechanisms contributing to brain pathology. Here, we investigated brain changes in 785 UK Biobank participants (aged 51-81) imaged twice, including 401 cases who tested positive for infection with SARS-CoV-2 between their two scans, with 141 days on average separating their diagnosis and second scan, and 384 controls. The availability of pre-infection imaging data reduces the likelihood of pre-existing risk factors being misinterpreted as disease effects. We identified significant longitudinal effects when comparing the two groups, including: (i) greater reduction in grey matter thickness and tissue-contrast in the orbitofrontal cortex and parahippocampal gyrus, (ii) greater changes in markers of tissue damage in regions functionally-connected to the primary olfactory cortex, and (iii) greater reduction in global brain size. The infected participants also showed on average larger cognitive decline between the two timepoints. Importantly, these imaging and cognitive longitudinal effects were still seen after excluding the 15 cases who had been hospitalised. These mainly limbic brain imaging results may be the in vivo hallmarks of a degenerative spread of the disease via olfactory pathways, of neuroinflammatory events, or of the loss of sensory input due to anosmia. Whether this deleterious impact can be partially reversed, or whether these effects will persist in the long term, remains to be investigated with additional follow up.", + "rel_num_authors": 20, "rel_authors": [ { - "author_name": "Mahdi Barzegar", - "author_inst": "Isfahan Neuroscience Resaerch Center" + "author_name": "Gwena\u00eblle Douaud", + "author_inst": "FMRIB Centre, Wellcome Centre for Integrative Neuroimaging (WIN), Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK" }, { - "author_name": "Sara Bagherieh", - "author_inst": "Isfahan Neurosciences Research Center" + "author_name": "Soojin Lee", + "author_inst": "FMRIB Centre, Wellcome Centre for Integrative Neuroimaging (WIN), Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK" }, { - "author_name": "Shakiba Houshi", - "author_inst": "Isfahan Neurosciences Research Center" + "author_name": "Fidel Alfaro-Almagro", + "author_inst": "FMRIB Centre, Wellcome Centre for Integrative Neuroimaging (WIN), Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK" }, { - "author_name": "Mozhgan Sadat Hashemi", - "author_inst": "Students' Scientific Research Center" + "author_name": "Christoph Arthofer", + "author_inst": "FMRIB Centre, Wellcome Centre for Integrative Neuroimaging (WIN), Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK" + }, + { + "author_name": "Chaoyue Wang", + "author_inst": "FMRIB Centre, Wellcome Centre for Integrative Neuroimaging (WIN), Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK" + }, + { + "author_name": "Paul McCarthy", + "author_inst": "FMRIB Centre, Wellcome Centre for Integrative Neuroimaging (WIN), Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK" + }, + { + "author_name": "Frederik Lange", + "author_inst": "FMRIB Centre, Wellcome Centre for Integrative Neuroimaging (WIN), Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK" + }, + { + "author_name": "Jesper L.R. Andersson", + "author_inst": "FMRIB Centre, Wellcome Centre for Integrative Neuroimaging (WIN), Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK" + }, + { + "author_name": "Ludovica Griffanti", + "author_inst": "FMRIB Centre, Wellcome Centre for Integrative Neuroimaging (WIN), Nuffield Department of Clinical Neurosciences, University of Oxford; OHBA, Wellcome Centre for" + }, + { + "author_name": "Eugene Duff", + "author_inst": "FMRIB Centre, Wellcome Centre for Integrative Neuroimaging (WIN), Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK; Department of" }, { - "author_name": "Ghasem Pishgahi", - "author_inst": "Students' Scientific Research Center" + "author_name": "Saad Jbabdi", + "author_inst": "FMRIB Centre, Wellcome Centre for Integrative Neuroimaging (WIN), Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK" }, { - "author_name": "Alireza Afshari-Safavi", - "author_inst": "Department of Biostatistics and Epidemiology, Faculty of Health, North Khorasan University of Medical Sciences, Bojnurd, Iran" + "author_name": "Bernd Taschler", + "author_inst": "FMRIB Centre, Wellcome Centre for Integrative Neuroimaging (WIN), Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK" + }, + { + "author_name": "Peter Keating", + "author_inst": "Ear Institute, University College London, London, UK" + }, + { + "author_name": "Anderson M. Winkler", + "author_inst": "National Institutes of Mental Health, National Institutes of Health, Bethesda, MD, USA" + }, + { + "author_name": "Rory Collins", + "author_inst": "Nuffield Department of Population Health, University of Oxford, Oxford, UK" }, { - "author_name": "Omid Mirmosayyeb", - "author_inst": "Isfahan Neuroscience Research Center" + "author_name": "Paul M. Matthews", + "author_inst": "UK Dementia Research Institute and Department of Brain Sciences, Imperial College, London, UK" }, { - "author_name": "Vahid Shaygannejad", - "author_inst": "Isfahan Neurosciences Research Center" + "author_name": "Naomi Allen", + "author_inst": "Nuffield Department of Population Health, University of Oxford, Oxford, UK" + }, + { + "author_name": "Karla L. Miller", + "author_inst": "FMRIB Centre, Wellcome Centre for Integrative Neuroimaging (WIN), Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK" + }, + { + "author_name": "Thomas E. Nichols", + "author_inst": "Big Data Institute, University of Oxford, Oxford, UK" }, { - "author_name": "Aram Zabeti", - "author_inst": "Department of Neurology and Rehabilitation Medicine , University of Cincinnati , Cincinnati , OH , USA" + "author_name": "Stephen M. Smith", + "author_inst": "FMRIB Centre, Wellcome Centre for Integrative Neuroimaging (WIN), Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "neurology" }, @@ -706669,91 +706132,27 @@ "category": "gastroenterology" }, { - "rel_doi": "10.1101/2021.06.10.21258714", - "rel_title": "Phase 1 Trial of Cyclosporine for Hospitalized Patients with COVID-19", + "rel_doi": "10.1101/2021.06.09.21258644", + "rel_title": "Targeted vaccination and the speed of SARS-CoV-2 adaptation", "rel_date": "2021-06-15", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.10.21258714", - "rel_abs": "Coronavirus Disease 2019 (COVID-19) remains a global health emergency with limited treatment options, lagging vaccine rates and inadequate healthcare resources in the face of an ongoing calamity. The disease is characterized by immune dysregulation and cytokine storm. Cyclosporine A (CSA) is a calcineurin inhibitor that modulates cytokine production and may have direct antiviral properties against coronaviruses. To test whether a short course of treatment was safe in COVID-19 patients, we treated 10 hospitalized, oxygen requiring, non-critically ill patients with CSA at a starting dose of 9mg/kg/day. Five patients experienced adverse events, none were serious, and transaminitis was most common. No subject enrolled in this trial required intensive care unit (ICU)-level care and all patients were discharged alive from the hospital. Further, CSA treatment was associated with significant reductions in serum cytokines and chemokines important in COVID-19 hyper-inflammation, including CXCL10. In conclusion, short courses of CSA appear safe and feasible in COVID-19 patients requiring oxygen and therefore, may be a useful adjunct in resource-poor or resource-limited health care settings.", - "rel_num_authors": 18, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.09.21258644", + "rel_abs": "The limited supply of vaccines against SARS-CoV-2 raises the question of targeted vaccination. Older and more sensitive hosts should be vaccinated first to minimize the disease burden. But what are the evolutionary consequences of targeted vaccination? We clarify the consequences of different vaccination strategies through the analysis of the speed of viral adaptation measured as the rate of change of the frequency of vaccine-escape mutations. We show that a vaccine-escape mutant is expected to spread faster if vaccination targets individuals which are likely to be involved in a higher number of contacts. We also discuss the pros and cons of dose-sparing strategies. Because delaying the second dose increases the proportion of the population vaccinated with a single dose, this strategy can both speed-up the spread of the vaccine-escape mutant and reduce the cumulated number of deaths. Hence, slowing down viral adaptation may not always be the optimal vaccination strategy. We contend that a careful assessment of the consequences of alternative vaccination strategies on both (i) the speed of adaptation and (ii) the mortality is required to determine which individuals should be vaccinated first.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Emily A Blumberg", - "author_inst": "University of Pennsylvania" - }, - { - "author_name": "Pablo Tebas", - "author_inst": "Perelman School of Medicine at the University of Pennsylvania" - }, - { - "author_name": "Ian Frank", - "author_inst": "Perelman School of Medicine at the University of Pennsylvania" - }, - { - "author_name": "Amy Marshall", - "author_inst": "Center for Cellular Immunotherapies, Perelman School of Medicine, University of Pennsylvania" - }, - { - "author_name": "Anne Chew", - "author_inst": "Center for Cellular Immunotherapies, Perelman School of Medicine, University of Pennsylvania" - }, - { - "author_name": "Elizabeth A Veloso", - "author_inst": "Center for Cellular Immunotherapies, Perelman School of Medicine, University of Pennsylvania" - }, - { - "author_name": "Alison Carulli", - "author_inst": "Hospital of the University of Pennsylvania" - }, - { - "author_name": "Walter Rogal", - "author_inst": "Center for Cellular Immunotherapies, Perelman School of Medicine, University of Pennsylvania" - }, - { - "author_name": "Avery L Gaymon", - "author_inst": "Center for Cellular Immunotherapies, Perelman School of Medicine, University of Pennsylvania" - }, - { - "author_name": "Aliza H Schmidt", - "author_inst": "Center for Cellular Immunotherapies, Perelman School of Medicine, University of Pennsylvania" - }, - { - "author_name": "Tiffany Barnette", - "author_inst": "Center for Cellular Immunotherapies, Perelman School of Medicine, University of Pennsylvania" - }, - { - "author_name": "Renee Jurek", - "author_inst": "Center for Cellular Immunotherapies, Perelman School of Medicine, University of Pennsylvania" - }, - { - "author_name": "Hooman Noorchashm", - "author_inst": "unaffiliated" - }, - { - "author_name": "Wei-Ting Hwang", - "author_inst": "Perelman School of Medicine at the University of Pennsylvania" - }, - { - "author_name": "Julia Han Noll", - "author_inst": "Center for Cellular Immunotherapies, Department of Microbiology, Parker Institute for Cancer Immunotherapy, Perelman School of Medicine, University of Pennsylv" - }, - { - "author_name": "Joseph A Fraietta", - "author_inst": "Center for Cellular Immunotherapies, Perelman School of Medicine, University of Pennsylvania" - }, - { - "author_name": "Carl H June", - "author_inst": "Department of Medicine, Division of Hematology, Parker Institute for Cancer Immunotherapy, Perelman School of Medicine at the University of Pennsylvania" + "author_name": "Sylvain Gandon", + "author_inst": "CEFE, CNRS, Univ Montpellier, EPHE, IRD, Univ Paul Val\u00e9ry Montpellier 3.1919, route de Mende, Montpellier, France" }, { - "author_name": "Elizabeth O Hexner", - "author_inst": "Department of Medicine, Division of Hematology, Perelman School of Medicine at the University of Pennsylvania" + "author_name": "S\u00e9bastien Lion", + "author_inst": "CEFE, CNRS, Univ Montpellier, EPHE, IRD, Univ Paul Val\u00e9ry Montpellier 3.1919, route de Mende, Montpellier, France" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2021.06.15.448495", @@ -708579,79 +707978,27 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.06.10.21258682", - "rel_title": "Cross-neutralizing activity against SARS-CoV-2 variants in COVID-19 patients: Comparison of four waves of the pandemic in Japan", + "rel_doi": "10.1101/2021.06.11.21258760", + "rel_title": "Convalescent Plasma in Critically ill Patients with COVID-19", "rel_date": "2021-06-13", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.10.21258682", - "rel_abs": "In March 2021, Japan is facing a 4th wave of SARS-CoV-2 infection. To prevent further spread of infection, sera cross-neutralizing activity of patients previously infected with conventional SARS-CoV-2 against novel variants is important but is not firmly established. We investigated the neutralizing potency of 81 COVID-19 patients sera from 4 waves of pandemic against SARS-CoV-2 variants using their authentic viruses. Most sera had neutralizing activity against all variants, showing similar activity against B.1.1.7 and D614G, but lower activity especially against B.1.351. In the 4th wave, sera-neutralizing activity against B.1.1.7 was significantly higher than that against any other variants, including D614G. The cross-neutralizing activity of convalescent sera was effective against all variants but was potentially weaker for B.1.351.", - "rel_num_authors": 15, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.11.21258760", + "rel_abs": "BACKGROUNDThe evidence for benefit of convalescent plasma for critically ill patients with Covid-19 is inconsistent. We hypothesized that convalescent plasma would improve outcomes for critically ill adult patients with Covid-19.\n\nMETHODSIn an ongoing adaptive platform trial, critically ill patients with confirmed Covid-19, defined as receiving intensive care-level organ support, were randomized to open-label convalescent plasma or not (i.e., control group). The primary end point was organ support-free days (i.e., days alive and free of ICU-based organ support) up to day 21. The primary analysis was a Bayesian cumulative logistic model with predefined criteria for superiority or futility. An odds ratio greater than 1 represented improved survival, more organ support-free days, or both.\n\nRESULTSThe convalescent plasma intervention was stopped after pre-specified criteria for futility were met. At that time, 1084 participants had been randomized to convalescent plasma and 916 to no convalescent plasma (control). The median organ support-free days were 0 (interquartile range, -1 to 16) for the convalescent plasma group and 3 (interquartile range, -1 to 16) days for the control group. The median adjusted odds ratio (OR) was 0.97 (95% credible interval 0.83 to 1.15) and posterior probability of futility (OR < 1.2) was 99.4% for convalescent plasma compared to control. In-hospital mortality was 37.3% (401/1075) in convalescent plasma group, and 38.4% (347/904) in controls. The observed treatment effects were consistent across primary and secondary outcomes.\n\nCONCLUSIONSIn critically ill adults with confirmed Covid-19, treatment with convalescent plasma, did not improve clinical outcomes.\n\nClinicaltrials.gov: NCT02735707", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Koichi Furukawa", - "author_inst": "Kobe University" - }, - { - "author_name": "Lidya Handayani Tjan", - "author_inst": "Kobe University" - }, - { - "author_name": "Silvia Sutandhio", - "author_inst": "Kobe University" - }, - { - "author_name": "Yukiya Kurahashi", - "author_inst": "Kobe University" - }, - { - "author_name": "Sachiyo Iwata", - "author_inst": "Hyogo Prefectural Kakogawa Medical Center" - }, - { - "author_name": "Yoshiki Tohma", - "author_inst": "Hyogo Prefectural Kakogawa Medical Center" - }, - { - "author_name": "Shigeru Sano", - "author_inst": "Hyogo Prefectural Kakogawa Medical Center" - }, - { - "author_name": "Sachiko Nakamura", - "author_inst": "Hyogo Prefectural Kakogawa Medical Center" - }, - { - "author_name": "Mitsuhiro Nishimura", - "author_inst": "Kobe University" - }, - { - "author_name": "Jun Arii", - "author_inst": "Kobe University" - }, - { - "author_name": "Tatsunori Kiriu", - "author_inst": "Kobe University" - }, - { - "author_name": "Masatsugu Yamamoto", - "author_inst": "Kobe University" - }, - { - "author_name": "Tatsuya Nagano", - "author_inst": "Kobe University" - }, - { - "author_name": "Yoshihiro Nishimura", - "author_inst": "Kobe University" + "author_name": "- The REMAP-CAP Investigators", + "author_inst": "" }, { - "author_name": "Yasuko Mori", - "author_inst": "Kobe University Graduate School of Medicine" + "author_name": "Lise J Estcourt", + "author_inst": "NHS Blood and Transplant" } ], "version": "1", "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "intensive care and critical care medicine" }, { "rel_doi": "10.1101/2021.06.10.21258550", @@ -710285,47 +709632,47 @@ "category": "allergy and immunology" }, { - "rel_doi": "10.1101/2021.06.07.21258497", - "rel_title": "Data-driven methodology for discovery and response to pulmonary symptomology in hypertension through AI and machine learning: Application to COVID-19 related pharmacovigilance", - "rel_date": "2021-06-12", + "rel_doi": "10.1101/2021.06.09.21258617", + "rel_title": "Vaccination reduces need for emergency care in breakthrough COVID-19 infections: A multicenter cohort study", + "rel_date": "2021-06-11", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.07.21258497", - "rel_abs": "BackgroundPotential therapy and confounding factors including typical co-administered medications, patients disease states, disease prevalence, patient demographics, medical histories, and reasons for prescribing a drug often are incomplete, conflicting, missing, or uncharacterized in spontaneous adverse drug event (ADE) reporting systems. These missing or incomplete features can affect and limit the application of quantitative methods in pharmacovigilance for meta-analyses of data during randomized clinical trials.\n\nMethodsIn this study, we implemented adaptive signal detection approaches to correct spurious association, hidden factors, and confounder misclassification when the covariates are unknown or unmeasured on medications affecting the renin-angiotensin system (RAS), potentially creating an increased risk of life-threatening outcomes in high-risk patients.\n\nResultsFollowing multiple filtering stages to exclude insignificant and noise-driven reports, we found that drugs from antihypertensives agents, urologicals, and antithrombotic agents (macitentan, bosentan, epoprostenol, selexipag, sildenafil, tadalafil, and beraprost) form a similar class with a significantly higher incidence of pADEs. Macitentan and bosentan were associates with 64% and 56% of pADEs, respectively. Because these two medications are prescribed in diseases affecting pulmonary function and may be likely to emerge among the highest reported pADEs, in fact, they serve to validate the methods utilized here. Conversely, doxazosin and rilmenidine were found to have the least pADEs in selected drugs from hypertension patients. Nifedipine and candesartan were also found by our signal detection methods to form a drug cluster, shown by several studies an effective combination of these drugs on lowering blood pressure and appeared an improved side effect profile in comparison with single-agent monotherapy.\n\nConclusionsWe consider pulmonary ADE (pADE) profiles in a long-standing group of therapeutics, RAS-acting agents, in patients with hypertension associated with high-risk for COVID-19. Using these techniques, we confirmed our hypothesis that drugs from the same drug class could have very different pADE profiles affecting outcomes in acute respiratory illness. We found that several indidvual drugs have significant differences between their drug classes and compared to other drug classes.\n\nFundingGJW and MJD accepted funding from BioNexus KC for funding on this project but BioNexus KC had no direct role in this article.\n\nClinical trial numberN/A\n\nAuthor SummaryUnderlying comorbidities continue to negatively affect COVID-19 patients. A recent focus has been on medications affecting RAS. Therefore, with the advent of COVID-19 acute respiratory distress syndrome (ARDS) in high-risk patients with hypertension, identifying specific RAS medications with the lowest incidence of pADEs would be beneficial. For this purpose, we curated the FDA ADE database to search for information related to human pADEs. As part of post-marketing drug safety surveillance, state/federal regulatory agencies and other institutions provide massive collections of ADE reports, these large data-sets present an opportunity to investigate ADEs to provide patient management based on comparative population data analysis. The abundance and prevalence of ADEs are not always detectable during randomized clinical trials and before a drug receives FDA approval for use in the clinic, which may appear with more widespread use. This is especially true for specific agents or diseases since there are simply too few events to be assessed, even in a large clinical trial for side effect profiles of specific disease states. For this purpose, we employed a novel method identifying extraneous causes of differential reporting including sampling variance and selection biases by reducing the effect of covariates.", + "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.09.21258617", + "rel_abs": "ImportanceWhile recent literature has shown the efficacy of the COVID-19 vaccine in preventing infection, its impact on need for emergency care/hospitalization in breakthrough infections remain unclear, particularly in regions with a high rate of variant viral strains.\n\nObjectiveWe aimed to determine if vaccination reduces hospital visits and severe disease in breakthrough COVID-19 infections.\n\nDesignMulticenter observational cohort analysis\n\nSettingEight-hospital acute care regional health system in Michigan, USA\n\nParticipantsConsecutive adult patients with COVID-19 requiring emergency care (EC)/hospitalization were eligible participants. Between December 15, 2020 and April 30, 2021, 11,834 EC encounters with COVID-19 infection were included.\n\nExposuresCOVID-19 vaccination\n\nMain Outcomes and MeasuresPrimary endpoint was rate of COVID-19 emergency care/hospitalization encounters comparing unvaccinated (UV), partially vaccinated (PV), and fully vaccinated (FV) cases. Secondary outcome was severe disease represented as a composite outcome (ICU admission, mechanical ventilation, or in-hospital death).\n\nDemographic and clinical variables were obtained from the electronic record. Vaccination data was obtained from the Michigan Care Improvement Registry and the Centers for Disease Control vaccine tracker.\n\nResults10,880 (91.9%) UV, 825 (7%) PV, and 129 (1.1%) FV were included. Average age was 53.0 {+/-} 18.2 and 52.8% were female. Accounting for the COVID-19 vaccination population groups in Michigan, the ED encounters/hospitalizations rate relevant to COVID-19 infection was 96% lower in FV versus UV (e{beta}:0.04,95% CI 0.03 to 0.06, p <0.001) in negative binomial regression. COVID-19 EC visits rate peaked at 22.61, 12.88, and 1.29 visits per 100000 for the UV, PV, and FV groups, respectively. In the propensity-score matching weights analysis, FV had a lower risk of composite disease compared to UV but statistically insignificant (HR 0.84 95% CI 0.52 to 1.38).\n\nConclusionsThe need for emergency care and/or hospitalization due to breakthrough COVID-19 is an exceedingly rare event in fully vaccinated patients. As vaccination has increased within our region, emergency visits amongst fully vaccinated individuals have remained low and occur much less frequently when compared to unvaccinated individuals. In cases of breakthrough COVID-19, if hospital-based treatment is required, elderly patients with significant comorbidities remain at high risk for severe outcomes regardless of vaccination status.", "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Xuan Xu", - "author_inst": "1DATA Consortium, Kansas State University Olathe, Department of Mathematics, Kansas State University" + "author_name": "Amit Bahl", + "author_inst": "Beaumont Hospital" }, { - "author_name": "Jessica Kawakami", - "author_inst": "1DATA Consortium, School of Pharmacy, Division of Pharmacology and Pharmaceutical Sciences, University of Missouri-Kansas City, Molecular Biology and Biochemis" + "author_name": "Steven Johnson", + "author_inst": "Beaumont Hospital" }, { - "author_name": "Nuwan Indika Millagaha Gedara", - "author_inst": "1DATA Consortium, Department of Business Economics, University of Colombo" + "author_name": "Gabriel Maine", + "author_inst": "Beaumont Hospital" }, { - "author_name": "Jim Riviere", - "author_inst": "1DATA Consortium, Kansas State University and North Carolina State University" + "author_name": "Martha Hernandez Garcia", + "author_inst": "Beaumont Health" }, { - "author_name": "Emma Meyer", - "author_inst": "1DATA Consortium, University of Missouri-Kansas City School of Pharmacy" + "author_name": "Srinivasa Nimmagadda", + "author_inst": "Beaumont Health" }, { - "author_name": "Gerald J Wyckoff", - "author_inst": "1DATA Consortium, Molecular Biology and Biochemistry, SBC University of Missouri-Kansas City School of Pharmacy, Division of Pharmacology and Pharmaceutical Sci" + "author_name": "Lihua Qu", + "author_inst": "Beaumont Health" }, { - "author_name": "Majid Jaberi-Douraki", - "author_inst": "1DATA Consortium, Kansas State University Olathe, Department of Mathematics, Kansas State University" + "author_name": "Nai-Wei Chen", + "author_inst": "Beaumont Health" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "cardiovascular medicine" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2021.06.08.21258481", @@ -712159,137 +711506,73 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.06.08.21258069", - "rel_title": "Bovine Colostrum Derived Antibodies Against SARS-CoV-2 Show Great Potential to Serve as a Prophylactic Agent", + "rel_doi": "10.1101/2021.06.07.21258332", + "rel_title": "Single-dose mRNA vaccine effectiveness against SARS-CoV-2, including P.1 and B.1.1.7 variants: a test-negative design in adults 70 years and older in British Columbia, Canada", "rel_date": "2021-06-09", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.08.21258069", - "rel_abs": "Severe acute respiratory syndrome Coronavirus 2 (SARS-CoV-2) until now imposes a serious burden to health systems globally. Despite worldwide vaccination, social distancing and wearing masks, the spread of the virus is still ongoing. One of the mechanisms how neutralizing antibodies (NAbs) block virus entry into cells encompasses interaction inhibition between the cell surface receptor angiotensin-converting enzyme 2 (ACE2) and the spike (S) protein of SARS-CoV-2. SARS-CoV-2 specific NAb development can be induced in the blood of cattle. Pregnant cows produce NAbs upon immunization, and antibodies move into the colostrum just before calving. Here we immunized cows with SARS-CoV-2 S1 receptor binding domain (RBD) protein in proper adjuvant solutions, followed by one boost with SARS-CoV-2 trimeric S protein, and purified immunoglobulins from colostrum. We demonstrate that this preparation indeed blocks interaction between the trimeric S protein and ACE2 in different in vitro assays. Moreover, we describe the formulation of purified immunoglobulin preparation into a nasal spray. When administered to human subjects, the formulation persists on the nasal mucosa for at least 4 hours as determined by a clinical study. Therefore, we are presenting a solution that shows great potential to serve as a prophylactic agent against SARS-CoV-2 infection as an additional measure to vaccination and wearing masks. Moreover, our technology allows for a rapid and versatile adaption for preparing prophylactic treatments against other diseases by using the defined characteristics of antibody movement into the colostrum.\n\nSignificanceSARS-CoV-2 infections continue to be a high-risk factor for mankind. Antibodies with the potential to neutralize the virus and thus its entry into the host cell have been shown to impose a potent measure against the infection. Human derived neutralizing antibodies are therapeutics and thus fall under the legislation of drugs. However, an alternative could be the purification of efficient neutralizing antibodies from other species. Here, we present immunization of pregnant cows with spike protein of SARS-CoV-2 which results in high quantities of colostrum immunoglobulins that can be easily harvested and safely purified within a remarkably short time. The colostrum immunoglobulin preparation has a great potential to serve in formulations that can be used as prophylactic agent against SARS-CoV-2 infection.", - "rel_num_authors": 31, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.07.21258332", + "rel_abs": "IntroductionRandomized-controlled trials of mRNA vaccine protection against SARS-CoV-2 included relatively few elderly participants. We assess singe-dose mRNA vaccine effectiveness (VE) in adults [≥]70-years-old in British Columbia (BC), Canada where the second dose was deferred by up to 16 weeks and where a spring 2021 wave uniquely included co-dominant circulation of B.1.1.7 and P.1 variants of concern (VOC).\n\nMethodsAnalyses included community-dwelling adults [≥]70-years-old with specimen collection between April 4 (epidemiological week 14) and May 1 (week 17). Adjusted VE was estimated by test-negative design through provincial laboratory and immunization data linkage. Cases were RT-PCR test-positive for SARS-CoV-2 and controls were test-negative. Vaccine status was defined by receipt of a single-dose [≥]21 days before specimen collection, but a range of intervals was assessed. In variant-specific analyses, test-positive cases were restricted to those genetically-characterized as B.1.1.7, P.1 or non-VOC.\n\nResultsVE analyses included 16,993 specimens: 1,226 (7.2%) test-positive cases and 15,767 test-negative controls. Of 1,131 (92%) viruses genetically categorized, 509 (45%), 314 (28%) and 276 (24%) were B.1.1.7, P.1 and non-VOC lineages, respectively. VE was negligible at 14% (95% CI 0-26) during the period 0-13 days post-vaccination but increased from 43% (95% CI 30-53) at 14-20 days to 75% (95% CI 63-83) at 35-41 days post-vaccination. VE at [≥]21 days was 65% (95% CI 58-71) overall: 72% (95% CI 58-81), 67% (95% CI 57-75) and 61% (95% CI 45-72) for non-VOC, B.1.1.7 and P.1, respectively.\n\nConclusionsA single dose of mRNA vaccine reduced the risk of SARS-CoV-2 in adults [≥]70-years-old by about two-thirds, with protection only minimally reduced against B.1.1.7 and P.1 variants. Substantial single-dose protection in older adults reinforces the option to defer the second dose when vaccine supply is scarce and broader first-dose coverage is needed.", + "rel_num_authors": 15, "rel_authors": [ { - "author_name": "Kadri Kangro", - "author_inst": "Icosagen Cell Factory" - }, - { - "author_name": "Mihhail Kurashin", - "author_inst": "Icosagen Cell Factory" - }, - { - "author_name": "Kiira Gildemann", - "author_inst": "Icosagen Cell Factory" - }, - { - "author_name": "Eve Sankovski", - "author_inst": "Icosagen Cell Factory" - }, - { - "author_name": "Eva Zusinaite", - "author_inst": "University of Tartu" - }, - { - "author_name": "Laura Sandra Lello", - "author_inst": "University of Tartu" - }, - { - "author_name": "Raini Pert", - "author_inst": "Icosagen Cell Factory" - }, - { - "author_name": "Ants Kavak", - "author_inst": "Estonian University of Life Sciences" - }, - { - "author_name": "Vaino Poikalainen", - "author_inst": "Teadus ja Tegu" - }, - { - "author_name": "Lembit Lepasalu", - "author_inst": "Teadus ja Tegu" - }, - { - "author_name": "Marilin Kuusk", - "author_inst": "Icosagen Cell Factory" - }, - { - "author_name": "Robin Pau", - "author_inst": "Icosagen Cell Factory" - }, - { - "author_name": "Sander Piiskop", - "author_inst": "Chemi-Pharm" - }, - { - "author_name": "Siimu Rom", - "author_inst": "Chemi-Pharm" - }, - { - "author_name": "Ruth Oltjer", - "author_inst": "Chemi-Pharm" - }, - { - "author_name": "Kairi Tiirik", - "author_inst": "University of Tartu" - }, - { - "author_name": "Karin Kogermann", - "author_inst": "University of Tartu" + "author_name": "Danuta M Skowronski", + "author_inst": "BC Centre for Disease Control" }, { - "author_name": "Mario Plaas", - "author_inst": "University of Tartu" + "author_name": "Solmaz Setayeshgar", + "author_inst": "BC Centre for Disease Control" }, { - "author_name": "Toomas Tiirats", - "author_inst": "Estonian University of Life Sciences" + "author_name": "Macy Zou", + "author_inst": "BC Centre for Disease Control" }, { - "author_name": "Birgit Aasmae", - "author_inst": "Estonian University of Life Sciences" + "author_name": "Natalie Prystajecky", + "author_inst": "BC Centre for Disease Control Public Health Laboratory" }, { - "author_name": "Mihkel Plaas", - "author_inst": "Tartu University Hospital" + "author_name": "John R Tyson", + "author_inst": "BC Centre for Disease Control Public Health Laboratory" }, { - "author_name": "Dagni Krinka", - "author_inst": "Icosagen AS" + "author_name": "Eleni Galanis", + "author_inst": "BC Centre for Disease Control" }, { - "author_name": "Ene Talpsep", - "author_inst": "Icosagen AS" + "author_name": "Monika Naus", + "author_inst": "BC Centre for Disease Control" }, { - "author_name": "Meelis Kadaja", - "author_inst": "Icosagen Cell Factory" + "author_name": "David M Patrick", + "author_inst": "BC Centre for Disease Control" }, { - "author_name": "Joachim Matthias Gerhold", - "author_inst": "Icosagen Cell Factory" + "author_name": "Hind Sbihi", + "author_inst": "BC Centre for Disease Control Data Analytics Services" }, { - "author_name": "Anu Planken", - "author_inst": "Icosagen Cell Factory, North-Estonian Medical Centre" + "author_name": "Shiraz El Adam", + "author_inst": "BC Centre for Disease Control" }, { - "author_name": "Andres Tover", - "author_inst": "Icosagen Cell Factory" + "author_name": "Bonnie Henry", + "author_inst": "Office of the Provincial Health Officer" }, { - "author_name": "Andres Merits", - "author_inst": "University of Tartu" + "author_name": "Linda M N Hoang", + "author_inst": "BC Centre for Disease Control Public Health Laboratory" }, { - "author_name": "Andres Mannik", - "author_inst": "Icosagen Cell Factory" + "author_name": "Manish Sadarangani", + "author_inst": "BC Children's Hospital Research Institute" }, { - "author_name": "Mart Ustav Jr.", - "author_inst": "Icosagen Cell Factory" + "author_name": "Agatha N Jassem", + "author_inst": "BC Centre for Disease Control Public Health Laboratory" }, { - "author_name": "Mart Ustav", - "author_inst": "Icosagen Cell Factory" + "author_name": "Mel Krajden", + "author_inst": "BC Centre for Disease Control Public Health Laboratory" } ], "version": "1", @@ -714277,77 +713560,45 @@ "category": "cell biology" }, { - "rel_doi": "10.1101/2021.06.08.447613", - "rel_title": "Cellular Activities of SARS-CoV-2 Main Protease Inhibitors Reveal Their Unique Characteristics", + "rel_doi": "10.1101/2021.06.07.447341", + "rel_title": "The fatty acid site is coupled to functional motifs in the SARS-CoV-2 spike protein and modulates spike allosteric behaviour", "rel_date": "2021-06-09", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.06.08.447613", - "rel_abs": "As an essential enzyme of SARS-CoV-2, the pathogen of COVID-19, main protease (MPro) triggers acute toxicity to its human cell host, an effect that can be alleviated by an MPro inhibitor with cellular potency. By coupling this toxicity alleviation with the expression of an MPro-eGFP fusion protein in a human cell host for straightforward characterization with fluorescent flow cytometry, we developed an effective method that allows bulk analysis of cellular potency of MPro inhibitors. In comparison to an antiviral assay in which MPro inhibitors may target host proteases or other processes in the SARS-CoV-2 life cycle to convene strong antiviral effects, this novel assay is more advantageous in providing precise cellular MPro inhibition information for assessment and optimization of MPro inhibitors. We used this assay to analyze 30 literature reported MPro inhibitors including MPI1-9 that were newly developed aldehyde-based reversible covalent inhibitors of MPro, GC376 and 11a that are two investigational drugs undergoing clinical trials for the treatment of COVID-19 patients in United States, boceprevir, calpain inhibitor II, calpain inhibitor XII, ebselen, bepridil that is an antianginal drug with potent anti-SARS-CoV-2 activity, and chloroquine and hydroxychloroquine that were previously shown to inhibit MPro. Our results showed that most inhibitors displayed cellular potency much weaker than their potency in direct inhibition of the enzyme. Many inhibitors exhibited weak or undetectable cellular potency up to 10 M. On contrary to their strong antiviral effects, 11a, calpain inhibitor II, calpain XII, ebselen, and bepridil showed relatively weak to undetectable cellular MPro inhibition potency implicating their roles in interfering with key steps other than just the MPro catalysis in the SARS-CoV-2 life cycle to convene potent antiviral effects. characterization of these molecules on their antiviral mechanisms will likely reveal novel drug targets for COVID-19. Chloroquine and hydroxychloroquine showed close to undetectable cellular potency to inhibit MPro. Kinetic recharacterization of these two compounds rules out their possibility as MPro inhibitors. Our results also revealed that MPI5, 6, 7, and 8 have high cellular and antiviral potency with both IC50 and EC50 values respectively below 1 M. As the one with the highest cellular and antiviral potency among all tested compounds, MPI8 has a remarkable cellular MPro inhibition IC50 value of 31 nM that matches closely to its strong antiviral effect with an EC50 value of 30 nM. Given its strong cellular and antiviral potency, we cautiously suggest that MPI8 is ready for preclinical and clinical investigations for the treatment of COVID-19.", - "rel_num_authors": 15, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.06.07.447341", + "rel_abs": "The SARS-CoV-2 spike protein is the first contact point between the SARS-CoV-2 virus and host cells and mediates membrane fusion. Recently, a fatty acid binding site was identified in the spike (Toelzer et al. Science 2020). The presence of linoleic acid at this site modulates binding of the spike to the human ACE2 receptor, stabilizing a locked conformation of the protein. Here, dynamical-nonequilibrium molecular dynamics simulations reveal that this fatty acid site is coupled to functionally relevant regions of the spike, some of them far from the fatty acid binding pocket. Removal of a ligand from the fatty acid binding site significantly affects the dynamics of distant, functionally important regions of the spike, including the receptor-binding motif, furin cleavage site and fusion-peptide-adjacent regions. The results also show significant differences in behaviour between clinical variants of the spike: e.g. the D614G mutation shows a significantly different conformational response for some structural motifs relevant for binding and fusion. The simulations identify structural networks through which changes at the fatty acid binding site are transmitted within the protein. These communication networks significantly involve positions that are prone to mutation, indicating that observed genetic variation in the spike may alter its response to linoleate binding and associated allosteric communication.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Wenyue Cao", - "author_inst": "Texas A&M Drug Discovery Laboratory, Department of Chemistry, Texas A&M University" - }, - { - "author_name": "Chia-Chuan D Cho", - "author_inst": "Texas A&M Drug Discovery Laboratory, Department of Chemistry, Texas A&M University" - }, - { - "author_name": "Zhi Z Geng", - "author_inst": "Texas A&M Drug Discovery Laboratory, Department of Chemistry, Texas A&M University" - }, - { - "author_name": "Xinyu R Ma", - "author_inst": "Texas A&M Drug Discovery Laboratory, Department of Chemistry, Texas A&M University" - }, - { - "author_name": "Robert Allen", - "author_inst": "Sorrento Therapeutics, Inc" - }, - { - "author_name": "Namir Shaabani", - "author_inst": "Sorrento Therapeutics, Inc." - }, - { - "author_name": "Erol C Vatansever", - "author_inst": "Texas A&M Drug Discovery Laboratory, Department of Chemistry, Texas A&M University" - }, - { - "author_name": "Yugendar R Alugubelli", - "author_inst": "Texas A&M Drug Discovery Laboratory, Department of Chemistry, Texas A&M University" - }, - { - "author_name": "Yuying Ma", - "author_inst": "Texas A&M Drug Discovery Laboratory, Department of Chemistry, Texas A&M University" + "author_name": "Ana Sofia Oliveira", + "author_inst": "University of Bristol" }, { - "author_name": "William H Ellenburg", - "author_inst": "Texas A&M Drug Discovery Laboratory, Department of Chemistry, Texas A&M University" + "author_name": "Deborah Shoemark", + "author_inst": "University of Bristol" }, { - "author_name": "Kai S Yang", - "author_inst": "Texas A&M Drug Discovery Laboratory, Department of Chemistry, Texas A&M University" + "author_name": "Amaurys Avila Ibarra", + "author_inst": "University of Bristol" }, { - "author_name": "Yuchen Qiao", - "author_inst": "Texas A&M Drug Discovery Laboratory, Department of Chemistry, Texas A&M University" + "author_name": "Andrew D. Davidson", + "author_inst": "University of Bristol" }, { - "author_name": "Henry Ji", - "author_inst": "Sorrento Therapeutics, Inc." + "author_name": "Imre Berger", + "author_inst": "University of Bristol" }, { - "author_name": "Shiqing Xu", - "author_inst": "Texas A&M Drug Discovery Laboratory, Department of Chemistry, Texas A&M University" + "author_name": "Christiane Schaffitzel", + "author_inst": "University of Bristol" }, { - "author_name": "Wenshe Ray Liu", - "author_inst": "Texas A&M Drug Discovery Laboratory, Department of Chemistry, Texas A&M University" + "author_name": "Adrian J Mulholland", + "author_inst": "University of Bristol" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_by_nc_nd", "type": "new results", "category": "biochemistry" }, @@ -716287,41 +715538,21 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.06.03.21258299", - "rel_title": "SARS-CoV-2 Seroprevalence Among Firefighters in Los Angeles, California", + "rel_doi": "10.1101/2021.06.05.21258394", + "rel_title": "The Effect of Pandemic Prevalence on the Reported Efficacy of SARS-CoV-2 Vaccine Candidates: A Systematic Review and Meta-analysis", "rel_date": "2021-06-07", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.03.21258299", - "rel_abs": "ObjectiveWe estimate the seroprevalence of SARS-CoV-2 antibodies among firefighters in the Los Angeles, California fire department in October 2020 and compare demographic and contextual factors for seropositivity.\n\nMethodsWe conducted a serologic survey of firefighters in Los Angeles, California, USA, in October 2020. Individuals were classified as seropositive for SARS-CoV-2 if they tested positive for immunoglobulin G, immunoglobulin M, or both. We compared demographic and contextual factors for seropositivity.\n\nResultsOf 713 participants, 8.9% tested positive for SARS-CoV-2 antibodies. Seropositivity was not associated with gender, age, or race/ethnicity. Furthermore, firefighters who worked in zip codes with lower income or higher share of minority population did not have higher rates of SARS-CoV-2 infection. Seropositivity was highest among firefighters who reported working in the vicinity of Los Angeles International Airport, which had a known outbreak in July 2020.\n\nConclusionsSeroprevalence among firefighters was no higher than seroprevalence in the general population, suggesting that workplace safety protocols, such as access to PPE and testing, can mitigate increased risk of infection at work. Workplace safety protocols for firefighters also eliminated differences in disease burden by geography and race/ethnicity observed in the general population.", - "rel_num_authors": 7, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.05.21258394", + "rel_abs": "ImportanceThe efficacy of SARS-CoV-2 vaccine candidates reported in Phase 3 trials varies from [~]45% to [~]95%. It is important to explain the reasons for this heterogeneity.\n\nObjectiveTo test the hypothesis that the efficacy of SARS-CoV-2 vaccine candidates falls with increasing prevalence of the COVID-19 pandemic.\n\nData SourcesClinicalTrials.gov, WHO, McGill and LSHTM trackers of COVID-19 candidate vaccines, peer reviewed publications, and press releases were searched until March 31st, 2021.\n\nStudy SelectionAll RCTs reporting efficacy outcomes from Phase 3 trials till March 31st, 2021 were included. Of the 11 vaccine candidates that had started their Phase 3 trials by November 1, 2020. Phase 3 efficacy outcomes were available for 8 vaccine candidates. (PROSPERO CRD42021243121).\n\nData Extraction and SynthesisBoth authors independently extracted the data required from identified sources, using PRISMA guidelines. The analysis included all RCTs reported in peer reviewed publications and publicly available sources. A random effects model with restricted maximum likelihood estimator was used to summarize the treatment effects. Cochrane Risk of Bias Assessment Tool was used to assess risk of bias. Certainty of evidence was assessed using the GRADE tool.\n\nMain Outcomes and MeasuresSARS-CoV-2 infections per protocol in vaccine and placebo groups, risk ratio, prevalence of the COVID-19 infection rate in the populations where the Phase 3 trials were conducted.\n\nResults8 vaccine candidates had reported efficacy data from a total of 20 independent Phase 3 trials, representing a total of 221,968 subjects, 453 infections across the vaccinated groups and 1,554 infections across the placebo groups. The overall estimate of the risk-ratio is 0.24 (95% CI, 0.17-0.34, p < 0.01), with an I2 statistic of 88.73%. The meta-regression analysis with pandemic prevalence as the moderator explains almost half the variance in risk ratios across trials (R2=49.06%, p<0.01).\n\nConclusion and RelevancePandemic prevalence explains almost half of the between-trial variance in reported efficacies. Efficacy of SARS-CoV-2 vaccine candidates declines as the pandemic prevalence increases.\n\nKey PointsO_ST_ABSQuestionC_ST_ABSDoes the prevalence of the COVID-19 pandemic explain the heterogeneity in efficacies reported across Phase 3 trials of SARS-CoV-2 vaccine candidates?\n\nFindingsAlmost 50% of the variance in efficacies reported across Phase 3 trials can be explained by differences in COVID-19 infection rate prevailing across trials. Efficacy of evaluated SARS-CoV-2 vaccine candidates falls significantly with increasing prevalence of the COVID-19 pandemic across trial sites.\n\nMeaningEfficacy of SARS-CoV-2 vaccine candidates needs to be interpreted in conjunction with the prevalence of the COVID-19 pandemic. Adjustment for location-level prevalence analysis would provide better insights into the efficacy results of Phase 3 trials.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Karen Mulligan", - "author_inst": "University of Southern California" - }, - { - "author_name": "Anders H Berg", - "author_inst": "Department of Pathology, Cedars-Sinai Medical Center" - }, - { - "author_name": "Marc Eckstein", - "author_inst": "Los Angeles Fire Department" - }, - { - "author_name": "Acacia Hori", - "author_inst": "University of Southern California" - }, - { - "author_name": "Anna Rodriguez", - "author_inst": "Sol Price School of Public Policy and Leonard D. Schaffer Center for Health Policy & Economics, University of Southern California" - }, - { - "author_name": "Omar Toubat", - "author_inst": "University of Southern California" + "author_name": "Rajeev Sharma", + "author_inst": "University of Waikato" }, { - "author_name": "Neeraj Sood", - "author_inst": "Sol Price School of Public Policy and Leonard D. Schaffer Center for Health Policy & Economics, University of Southern California" + "author_name": "Abhijith Anand", + "author_inst": "University of Arkansas" } ], "version": "1", @@ -718085,43 +717316,67 @@ "category": "genetics" }, { - "rel_doi": "10.1101/2021.06.03.21258238", - "rel_title": "Inferring SARS-CoV-2 RNA shedding into wastewater relative to time of infection", + "rel_doi": "10.1101/2021.06.03.21258290", + "rel_title": "ASSESSMENT OF PERFORMANCE AND IMPLEMENTATION CHARACTERISTICS OF RAPID POINT OF CARE SARS-CoV-2 ANTIGEN TESTING IN KENYA", "rel_date": "2021-06-06", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.03.21258238", - "rel_abs": "Since the start of the COVID-19 pandemic, there has been interest in using wastewater monitoring as an approach for disease surveillance. A significant uncertainty that would improve interpretation of wastewater monitoring data is the intensity and timing with which individuals shed RNA from severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) into wastewater. By combining wastewater and case surveillance data sets from a university campus during a period of heightened surveillance, we inferred that individual shedding of RNA into wastewater peaks on average six days (50% uncertainty interval (UI): 6 - 7; 95% UI: 4 - 8) following infection, and that wastewater measurements are highly overdispersed (negative binomial dispersion parameter, k = 0.39 (95% credible interval: 0.32 - 0.48)). This limits the utility of wastewater surveillance as a leading indicator of secular trends in SARS-CoV-2 transmission during an epidemic, and implies that it could be most useful as an early warning of rising transmission in areas where transmission is low or clinical testing is delayed or of limited capacity.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.03.21258290", + "rel_abs": "BackgroundThe COVID-19 pandemic has resulted in a need for rapid identification of infectious cases. Testing barriers have prohibited adequate screening for SARS COV2, resulting in significant delays in treatment provision and commencement of outbreak control measures. This study aimed to generate evidence on the performance and implementation characteristics of the BD Veritor rapid antigen test as compared to the gold standard test for diagnosis of SARS COV2 in Kenya.\n\nMethodsThis was a field test performance evaluation in symptomatic and asymptomatic adults undergoing testing for SARS COV2. Recruited participants were classified as SARS-CoV2-positive based on the locally implemented gold standard reverse transcription polymerase chain reaction (RT-PCR) test performed on nasopharyngeal swabs. 272 antigen tests were performed with simultaneous gold standard testing, allowing us to estimate sensitivity, specificity, positive and negative predictive values for the BD Veritor rapid antigen test platform. Implementation characteristics were assessed using the Consolidated Framework for Implementation Research for feasibility, acceptability, turn-around time, and ease-of-use metrics.\n\nResults and DiscussionWe enrolled 97 PCR negative symptomatic and 128 PCR negative asymptomatic, and 28 PCR positive symptomatic and 19 PCR positive asymptomatic participants. Compared to the gold standard, the sensitivity of the BD Veritor antigen test was 94% (95% confidence interval [CI] 86.6 to 100.0) while the specificity was 98% (95% confidence interval [CI] 96 to 100). The sensitivity of BD Veritor antigen test was higher among symptomatic (100%) compared to asymptomatic (84%) participants, although this difference was not statistically significant. There was also a lack of association between cycle threshold value and sensitivity of BD Veritor test. The BD Veritor test had quick turnaround time and minimal resource requirements, and laboratory personnel conducting testing felt that it was easier to use than the gold standard RT-PCR.\n\nConclusionThe BD Veritor rapid antigen test exhibited excellent sensitivity and specificity when used to detect SARS-CoV-2 infection among both symptomatic and asymptomatic individuals in varied population settings in Kenya. It was feasible to implement and easy to use, with rapid turnaround time.", + "rel_num_authors": 12, "rel_authors": [ { - "author_name": "Sean M. Cavany", - "author_inst": "University of Notre Dame" + "author_name": "Eva Muthamia", + "author_inst": "Mount Kenya University" }, { - "author_name": "Aaron Bivins", - "author_inst": "University of Notre Dame" + "author_name": "Samuel Mbugua", + "author_inst": "Mount Kenya University" }, { - "author_name": "Zhenyu Wu", - "author_inst": "University of NotreDame" + "author_name": "Mary Mungai", + "author_inst": "Center for Virus Research, Kenya Medical Research Institute" }, { - "author_name": "Devin North", - "author_inst": "University of Notre Dame" + "author_name": "Gama Bandawe", + "author_inst": "Malawi University of Science and Technology" }, { - "author_name": "Kyle Bibby", - "author_inst": "University of Notre Dame" + "author_name": "Firdausi Qadri", + "author_inst": "International Center for Diarrheal Disease Research, Bangladesh (icddr,b)" }, { - "author_name": "Alex Perkins", - "author_inst": "University of Notre Dame" + "author_name": "Zannat Kawser", + "author_inst": "Institute for developing Science and Health initiatives (ideSHi)" + }, + { + "author_name": "Shahin Lockman", + "author_inst": "Harvard T.H. Chan School of Public Health" + }, + { + "author_name": "Louise Ivers", + "author_inst": "Massachusetts General Hospital" + }, + { + "author_name": "David R. Walt", + "author_inst": "Brigham and Women's Hospital/Harvard Medical School" + }, + { + "author_name": "Sara Suliman", + "author_inst": "Brigham and Women's Hospital, Harvard Medical School" + }, + { + "author_name": "Matilu Mwau", + "author_inst": "Kenya Medical Research Institute" + }, + { + "author_name": "Jesse Gitaka", + "author_inst": "Mount Kenya University" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2021.06.03.21257901", @@ -719659,97 +718914,77 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.05.31.21257591", - "rel_title": "Chronic SARS-CoV-2 infection and viral evolution in a hypogammaglobulinaemic individual.", + "rel_doi": "10.1101/2021.06.03.21258106", + "rel_title": "Human genetic factors associated with pneumonia susceptibility, a cue for COVID-19 mortality", "rel_date": "2021-06-04", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.31.21257591", - "rel_abs": "There is widespread interest in the capacity for SARS-CoV-2 evolution in the face of selective pressures from host immunity, either naturally acquired post-exposure or from vaccine acquired immunity. Allied to this is the potential for long perm persistent infections within immune compromised individuals to allow a broader range of viral evolution in the face of sub-optimal immune driven selective pressure. Here we report on an immunocompromised individual who is hypogammaglobulinaemic and was persistently infected with SARS-CoV-2 for over 290 days, the longest persistent infection recorded in the literature to date. During this time, nine samples of viral nucleic acid were obtained and analysed by next-generation sequencing. Initially only a single mutation (L179I) was detected in the spike protein relative to the prototypic SARS-CoV-2 Wuhan-Hu-1 isolate, with no further changes identified at day 58. However, by day 155 the spike protein had acquired a further four amino acid changes, namely S255F, S477N, H655Y and D1620A and a two amino acid deletion ({Delta}H69/{Delta}V70). Infectious virus was cultured from a nasopharyngeal sample taken on day 155 and next-generation sequencing confirmed that the mutations in the virus mirrored those identified by sequencing of the corresponding swab sample. The isolated virus was susceptible to remdesivir in vitro, however a 17-day course of remdesivir started on day 213 had no effect on the viral RT-PCR cycle threshold (Ct) value. On day 265 the patient was treated with the combination of casirivimab and imdevimab. The patient experienced progressive resolution of all symptoms over the next 8 weeks and by day 311 the virus was no longer detectable by RT-PCR. The {Delta}H69/{Delta}V70 deletion in the N-terminus of the spike protein which arose in our patient is also present in the B.1.1.7 variant of concern and has been associated with viral escape mutagenesis after treatment of another immunocompromised patient with convalescent plasma. Our data confirms the significance of this deletion in immunocompromised patients but illustrates it can arise independently of passive antibody transfer, suggesting the deletion may be an enabling mutation that compensates for distant changes in the spike protein that arise under selective pressure.", - "rel_num_authors": 20, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.03.21258106", + "rel_abs": "The risk for community acquired pneumonia (CAP) is partially driven by genetics. To identify the CAP-associated genetic risk loci, we performed a meta-analysis of clinically diagnosed CAP (3,310 individuals) with 2,655 healthy controls. The findings revealed CYP1A1 variants (rs2606345, rs4646903, rs1048943) associated with pneumonia. We observed rs2606345 [G vs T; OR=1.49(1.29-1.69); p=0.0001; I2= 15.5%], and rs1048943 [T vs G; OR= 1.31(0.90-1.71); p=0.002; I2=19.3%] as risk markers and rs4646903 [T vs C; OR= 0.79(0.62-0.96); p=0.03; I2=0%] as a protective marker for susceptibility to CAP, when compared with healthy controls. Our meta-analysis showed the presence of CYP1A1 SNP alleles contributing significant risk toward pneumonia susceptibility. Interestingly, we observed a striking difference of allele frequency for rs2606345 (CYP1A1) among Europeans, Africans and Asians which may provide a possible link for observed variations in death due to coronavirus disease 2019 (COVID-19), a viral pneumonia. We report, for the first time, a significant positive correlation for the risk allele (T or A) of rs2606345, with a higher COVID-19 mortality rate worldwide and within a genetically heterogeneous nation like India. Mechanistically, the risk allele A (rs2606345) is associated with lower expression of CYP1A1 and presumably leads to reduced capacity for xenobiotic detoxification. We note that ambient air pollution, a powerful inducer of CYP1A1 gene expression, is globally associated with lower, not higher mortality, as would normally be predicted. In conclusion, we find that CYP1A1 alleles are associated with CAP mortality, presumably via altered xenobiotic metabolism. We speculate that gene-environment interactions governing CYP1A1 expression may influence COVID-19 mortality.", + "rel_num_authors": 15, "rel_authors": [ { - "author_name": "Maia Kavanagh Williamson", - "author_inst": "School of Cellular and Molecular Medicine, University of Bristol" - }, - { - "author_name": "Fergus Hamilton", - "author_inst": "Infection Sciences, North Bristol NHS Trust, BS10 5NB and MRC Integrative Epidemiology Unit, University of Bristol" + "author_name": "Debleena Guin Ms", + "author_inst": "CSIR-Institute of genomics and integrative biology, Delhi Technological University" }, { - "author_name": "Stephanie Hutchings", - "author_inst": "Public Health England South West Virology Laboratory, Southmead Hospital, BS10 5NB" - }, - { - "author_name": "Hannah M Pymont", - "author_inst": "Public Health England South West Virology Laboratory, Southmead Hospital, BS10 5NB and 2.\tInfection Sciences, North Bristol NHS Trust, BS10 5NB" + "author_name": "Saroj Yadav Ms", + "author_inst": "CSIR-Institute of genomics and integrative biology" }, { - "author_name": "Mark Hackett", - "author_inst": "Infection Sciences, North Bristol NHS Trust, BS10 5NB" + "author_name": "Priyanka Singh Ms", + "author_inst": "CSIR-Institute of genomics and integrative biology" }, { - "author_name": "David Arnold", - "author_inst": "Academic Respiratory Unit, North Bristol NHS Trust, BS10 5NB" + "author_name": "Pooja Singh Ms", + "author_inst": "CSIR-Institute of genomics and integrative biology" }, { - "author_name": "Nick Maskell", - "author_inst": "Academic Respiratory Unit, North Bristol NHS Trust, BS10 5NB / University of Bristol" + "author_name": "Sarita Thakran Ms", + "author_inst": "CSIR-Institute of genomics and integrative biology" }, { - "author_name": "Alasdair P MacGowan", - "author_inst": "North Bristol NHS Trust" + "author_name": "Samiksha Kukal Ms", + "author_inst": "CSIR-Institute of genomics and integrative biology" }, { - "author_name": "mahableshwar Albur", - "author_inst": "Infection Sciences, North Bristol NHS Trust, BS10 5NB" + "author_name": "Neha Kanojia Ms", + "author_inst": "CSIR-Institute of genomics and integrative biology" }, { - "author_name": "Megan Jenkins", - "author_inst": "Infection Sciences, North Bristol NHS Trust, BS10 5NB" + "author_name": "Priyanka Rani Paul Ms", + "author_inst": "CSIR-Institute of genomics and integrative biology" }, { - "author_name": "Izak Heys", - "author_inst": "Infection Sciences, North Bristol NHS Trust, BS10 5NB" + "author_name": "Bijay Pattnaik Dr.", + "author_inst": "CSIR-Institute of genomics and integrative biology, All India Institute of Medical Sciences" }, { - "author_name": "Francesca Knapper", - "author_inst": "Infection Sciences, North Bristol NHS Trust, BS10 5NB" + "author_name": "Viren Sardana Dr.", + "author_inst": "CSIR- Central Scientific Instruments Organisation" }, { - "author_name": "Mustafa Elsayed", - "author_inst": "Infection Sciences, North Bristol NHS Trust, BS10 5NB" + "author_name": "Sandeep Grover Dr.", + "author_inst": "Institute for Clinical Epidemiology and Applied Biometry, University of Tubingen" }, { - "author_name": "Rachel Milligan", - "author_inst": "School of Cellular and Molecular Medicine, University of Bristol" + "author_name": "Yasha Hasija Dr.", + "author_inst": "Delhi technological university" }, { - "author_name": "- The COVID-19 Genomics UK (COG-UK) Consortium", + "author_name": "- Indian Genome Variation Consortium", "author_inst": "" }, { - "author_name": "Peter Muir", - "author_inst": "Public Health England South West Virology Laboratory, Southmead Hospital, BS10 5NB" + "author_name": "Anurag Agrawal Dr.", + "author_inst": "CSIR-Institute of genomics and integrative biology" }, { - "author_name": "Barry Vipond", - "author_inst": "Public Health England South West Virology Laboratory, Southmead Hospital, BS10 5NB" - }, - { - "author_name": "David A Matthews", - "author_inst": "School of Cellular and Molecular Medicine, University of Bristol" - }, - { - "author_name": "Ed Moran", - "author_inst": "Infection Sciences, North Bristol NHS Trust, BS10 5NB" - }, - { - "author_name": "Andrew D. D. Davidson", - "author_inst": "School of Cellular and Molecular Medicine, University of Bristol" + "author_name": "Ritushree Kukreti Dr.", + "author_inst": "CSIR-Institute of genomics and integrative biology" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -721349,21 +720584,65 @@ "category": "hematology" }, { - "rel_doi": "10.1101/2021.06.03.21258293", - "rel_title": "Interim estimates of increased transmissibility, growth rate, and reproduction number of the Covid-19 B.1.617.2 variant of concern in the United Kingdom", + "rel_doi": "10.1101/2021.06.01.21257759", + "rel_title": "Immunological dysfunction persists for 8 months following initial mild-moderate SARS-CoV-2 infection", "rel_date": "2021-06-03", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.03.21258293", - "rel_abs": "This paper relates to data from the Wellcome Sanger Institute, UK, regarding Covid-19 genomic surveillance. We use a simple model to give point estimates of the effective reproduction numbers of the B.1.617.2 and B.1.1.7 lineages in England, from sequenced data as at 15 May 2021. Comparison with the estimated reproduction number of B.1.1.7 enables an estimate of the increased transmissibility of B.1.617.2. We conclude that it is almost certain that there is increased transmissibility that will rapidly lead to B.1.617.2 becoming the prevailing variant in the UK. The derived estimates of increased transmissibility have uncertainty relating to the actual distribution of the generation interval, but they do point, under present conditions of vaccination coverage and NPIs, to exponential growth of positive cases.", - "rel_num_authors": 1, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.01.21257759", + "rel_abs": "A proportion of patients surviving acute COVID-19 infection develop post-COVID syndrome (long COVID) encompassing physical and neuropsychiatric symptoms lasting longer than 12 weeks. Here we studied a prospective cohort of individuals with long COVID compared to age/gender matched subjects without long COVID (from the ADAPT study), healthy donors and individuals infected with other non-SARS CoV2 human coronaviruses (the ADAPT-C study). We found highly activated innate immune cells and an absence of subsets of un-activated naive T and B cells in peripheral blood of long COVID subjects, that did not reconstitute over time. These activated myeloid cells may contribute to the elevated levels of type I (IFN-{beta}) and III interferon (IFN-{lambda}1) that remained persistently high in long COVID subjects at 8 months post-infection. We found positive inter-analyte correlations that consisted of 18 inflammatory cytokines in symptomatic long COVID subjects that was not observed in asymptomatic COVID-19 survivors. A linear classification model was used to exhaustively search through all 20475 combinations of the 29 analytes measured, that had the strongest association with long COVID and found that the best 4 analytes were: IL-6, IFN-{gamma}, MCP-1 (CCL2) and VCAM-1. These four inflammatory biomarkers gave an accuracy of 75.9%, and an F1 score of 0.759, and have also previously been associated with acute severe disease. In contrast, plasma ACE2 levels, while elevated in the serum of people previously infected with SARS-CoV-2 were not further elevated in subjects with long COVID symptoms. This work defines immunological parameters associated with long COVID and suggests future opportunities to prevention and treatment.", + "rel_num_authors": 12, "rel_authors": [ { - "author_name": "John S Dagpunar", - "author_inst": "University of Southampton" + "author_name": "Chansavath Phetsouphanh", + "author_inst": "The Kirby institute, University of New South Wales, NSW 2033, Australia" + }, + { + "author_name": "David Darley", + "author_inst": "St Vincents Hospital, Darlinghurst, NSW 2010, Australia" + }, + { + "author_name": "Daniel B Wilson", + "author_inst": "University of Boston" + }, + { + "author_name": "Annett Howe", + "author_inst": "The Kirby institute, University of New South Wales, NSW 2033, Australia" + }, + { + "author_name": "C. Mee Ling Munier", + "author_inst": "The Kirby institute, University of New South Wales, NSW 2033, Australia" + }, + { + "author_name": "Sheila K Patel", + "author_inst": "Department of Medicine, Austin Health, University of Melbourne, Victoria 3084, Australia" + }, + { + "author_name": "Jennifer A Juno", + "author_inst": "Department of Microbiology and Immunology, Peter Doherty Institute, University of Melbourne, Victoria 3000, Australia" + }, + { + "author_name": "Louise M Burrell", + "author_inst": "University of Melbourne" + }, + { + "author_name": "Stephen J Kent", + "author_inst": "Department of Microbiology and Immunology, Peter Doherty Institute, University of Melbourne, Victoria 3000, Australia" + }, + { + "author_name": "Gregory J Dore", + "author_inst": "The Kirby institute, University of New South Wales, NSW 2033, Australia" + }, + { + "author_name": "Anthony D Kelleher", + "author_inst": "The Kirby institute, University of New South Wales, NSW 2033, Australia" + }, + { + "author_name": "Gail V Matthews", + "author_inst": "The Kirby institute, University of New South Wales, NSW 2033, Australia" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -723459,47 +722738,87 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.06.02.446343", - "rel_title": "Common cardiac medications potently inhibit ACE2 binding to the SARS-CoV-2 Spike, and block virus penetration into human lung cells", + "rel_doi": "10.1101/2021.06.02.446813", + "rel_title": "Efficient discovery of potently neutralizing SARS-CoV-2 antibodies using LIBRA-seq with ligand blocking", "rel_date": "2021-06-02", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.06.02.446343", - "rel_abs": "To initiate SARS-CoV-2 infection, the Receptor Binding Domain (RBD) on the viral spike protein must first bind to the host receptor ACE2 protein on pulmonary and other ACE2-expressing cells. We hypothesized that cardiac glycoside drugs might block the binding reaction between ACE2 and the Spike (S) protein, and thus block viral penetration into target cells. To test this hypothesis we developed a biochemical assay for ACE2:Spike binding, and tested cardiac glycosides as inhibitors of binding. Here we report that ouabain, digitoxin, and digoxin are high-affinity competitive inhibitors of ACE2 binding to the Wuhan S1 and the European [E614G] S1 proteins. These drugs also inhibit ACE2 binding to the Wuhan RBD, as well as to RBD proteins containing the S. Africa [E484K], Mink [Y453F] and UK [N501Y] mutations. As hypothesized, we also found that ouabain and digitoxin blocked penetration by SARS-CoV-2 Spike-pseudotyped virus into human lung cells. These data indicate that cardiac glycosides may block viral penetration into the target cell by first inhibiting ACE2:Spike binding. Clinical concentrations of ouabain and digitoxin are relatively safe for short term use for subjects with normal hearts. It has therefore not escaped our attention that these common cardiac medications could be deployed worldwide as inexpensive repurposed drugs for anti-COVID-19 therapy.", - "rel_num_authors": 7, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.06.02.446813", + "rel_abs": "SARS-CoV-2 therapeutic antibody discovery efforts have met with notable success but have been associated with a generally inefficient process, requiring the production and characterization of exceptionally large numbers of candidates for the identification of a small set of leads. Here, we show that incorporating antibody-ligand blocking as part of LIBRA-seq, the high-throughput sequencing platform for antibody discovery, results in efficient identification of ultra-potent neutralizing antibodies against SARS-CoV-2. LIBRA-seq with ligand blocking is a general platform for functional antibody discovery targeting the disruption of antigen-ligand interactions.", + "rel_num_authors": 17, "rel_authors": [ { - "author_name": "Hung Caohuy", - "author_inst": "Uniformed Services University of the Health Sciences" + "author_name": "Andrea R Shiakolas", + "author_inst": "Vanderbilt University" }, { - "author_name": "Ofer Eidelman", - "author_inst": "Uniformed Services University of the Health Sciences" + "author_name": "Nicole Johnson", + "author_inst": "The University of Texas at Austin" }, { - "author_name": "Tinghua Chen", - "author_inst": "Uniformed Services University of the Health Sciences" + "author_name": "Kevin J Kramer", + "author_inst": "Vanderbilt University" }, { - "author_name": "Qingfeng Yang", - "author_inst": "Uniformed Services University of the Health Sciences" + "author_name": "Naveenchandra Suryadevara", + "author_inst": "Vanderbilt Vaccine Center" }, { - "author_name": "Alakesh Bera", - "author_inst": "Uniformed Services University of the Health Sciences" + "author_name": "Daniel Wrapp", + "author_inst": "The University of Texas at Austin" }, { - "author_name": "Nathan Walton", - "author_inst": "Uniformed Services University of the Health Sciences" + "author_name": "Sivakumar Periasamy", + "author_inst": "University of Texas Medical Branch at Galveston" }, { - "author_name": "Harvey B Pollard", - "author_inst": "Uniformed Services University of the Health Sciences" + "author_name": "Kelsey A Pilewski", + "author_inst": "Vanderbilt University" + }, + { + "author_name": "Nagarajan Raju", + "author_inst": "Vanderbilt Vaccine Center" + }, + { + "author_name": "Rachel Nargi", + "author_inst": "Vanderbilt Vaccine Center" + }, + { + "author_name": "Rachel E Sutton", + "author_inst": "Vanderbilt Vaccine Center" + }, + { + "author_name": "Lauren Walker", + "author_inst": "Vanderbilt University" + }, + { + "author_name": "Ian Setliff", + "author_inst": "Vanderbilt University" + }, + { + "author_name": "James E Crowe Jr.", + "author_inst": "Vanderbilt Vaccine Center" + }, + { + "author_name": "Alexander Bukreyev", + "author_inst": "University of Texas Medical Branch at Galveston" + }, + { + "author_name": "Robert H Carnahan", + "author_inst": "Vanderbilt Vaccine Center" + }, + { + "author_name": "Jason S McLellan", + "author_inst": "The University of Texas at Austin" + }, + { + "author_name": "Ivelin S Georgiev", + "author_inst": "Vanderbilt Vaccine Center" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_no", "type": "new results", - "category": "pharmacology and toxicology" + "category": "immunology" }, { "rel_doi": "10.1101/2021.06.02.446698", @@ -725125,129 +724444,85 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.05.26.21257441", - "rel_title": "Emerging SARS-CoV-2 variants of concern evade humoral immune responses from infection and vaccination", + "rel_doi": "10.1101/2021.05.26.21257700", + "rel_title": "Safety and immunogenicity of a recombinant DNA COVID-19 vaccine containing the coding regions of the spike and nucleocapsid proteins: Preliminary results from an open-label, phase 1 trial in healthy adults aged 19-55 years", "rel_date": "2021-06-01", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.26.21257441", - "rel_abs": "Emerging SARS-CoV-2 variants pose a threat to human immunity induced by natural infection and vaccination. We assessed the recognition of three variants of concern (B.1.1.7, B.1.351 and P.1) in cohorts of COVID-19 patients ranging in disease severity (n = 69) and recipients of the Pfizer/BioNTech vaccine (n = 50). Spike binding and neutralization against all three VOC was substantially reduced in the majority of samples, with the largest 4-7-fold reduction in neutralization being observed against B.1.351. While hospitalized COVID-19 patients and vaccinees maintained sufficient neutralizing titers against all three VOC, 39% of non-hospitalized patients did not neutralize B.1.351. Moreover, monoclonal neutralizing antibodies (NAbs) show sharp reductions in their binding kinetics and neutralizing potential to B.1.351 and P.1, but not to B.1.1.7. These data have implications for the degree to which pre-existing immunity can protect against subsequent infection with VOC and informs policy makers of susceptibility to globally circulating SARS-CoV-2 VOC.", - "rel_num_authors": 29, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.26.21257700", + "rel_abs": "BackgroundWe investigated the safety and immunogenicity of two recombinant COVID-19 DNA vaccine candidates in first-in-human trials. GX-19 contains plasmid DNA encoding SARS-CoV-2 spike protein, and GX-19N contains plasmid DNA encoding SARS-CoV-2 receptor binding domain (RBD) foldon and nucleocapsid protein (NP) as well as plasmid DNA encoding SARS-CoV-2 spike protein.\n\nMethodsTwo open-label phase 1 trials of GX-19 and GX-19N safety and immunogenicity were performed in healthy adults aged 19-55 years. GX-19 trial participants received two vaccine injections (1{middle dot}5 mg or 3{middle dot}0 mg, 1:1 ratio) four weeks apart. GX-19N trial participants received two 3{middle dot}0 mg vaccine injections four weeks apart.\n\nFindingsBetween June 17 and July 30 and December 28 and 31, 2020, 40 and 21 participants were enrolled in the GX-19 and GX-19N trials, respectively. Thirty-two participants (52{middle dot}5%) reported 80 treatment-emergent adverse events (AE) after vaccination. All solicited AEs were mild except one case of moderate fatigue reported in the 1{middle dot}5 mg GX-19 group. Binding antibody responses increased after vaccination in all groups. The geometric mean titers (GMTs) of spike-binding antibodies on day 57 were 85{middle dot}74, 144{middle dot}20, and 201{middle dot}59 in the 1{middle dot}5 mg, 3{middle dot}0 mg GX-19 groups and the 3{middle dot}0 mg GX-19N group, respectively. In GX-19N group, neutralizing antibody response (50% neutralizing titer using FRNT) significantly increased after vaccination, but GMT of neutralizing antibody on day 57 (37.26) was lower than those from human convalescent serum (288.78). GX-19N induced stronger T cell responses than GX-19. The magnitude of GX-19N-induced T cell responses was comparable to those observed in the convalescent PBMCs. GX-19N induced both SARS-CoV-2 spike- and NP-specific T cell responses, and the amino acid sequences of 15-mer peptides containing NP-specific T cell epitopes identified in GX-19N-vaccinated participants were identical with those of diverse SARS-CoV-2 variants\n\nInterpretationGX-19N is safe, tolerated and induces humoral and broad SARS-CoV-2-specific T cell response which may enable cross-reactivity to emerging SARS-CoV-2 variants.\n\nFundingThis research was supported by Korea Drug Development Fund funded by Ministry of Science and ICT, Ministry of Trade, Industry, and Energy, and Ministry of Health and Welfare (HQ20C0016, Republic of Korea).\n\nResearch in contextO_ST_ABSEvidence before this studyC_ST_ABSTo overcome the COVID-19 outbreak, the development of safe and effective vaccines is crucial. Despite the successful clinical efficacy of the approved vaccines, concerns exist regarding emerging new SARS-CoV-2 variants that have mutated receptor binding domains in the spike protein. We searched PubMed for research articles published up to May 1, 2021, using various combinations of the terms \"COVID-19\" or \"SARS-CoV-2\", \"vaccine\", and \"clinical trial\". No language or data restrictions were applied. We also searched the ClinicalTrials.gov registry and World Health Organization (WHO) draft landscape of COVID-19 candidate vaccines for ongoing trials of COVID-19 vaccines up to May 1, 2021. Ten DNA-based vaccines, including the vaccine candidate reported here, are in ongoing clinical trials. Among these, safety and immunogenicity results were reported from only one phase 1 trial of a DNA vaccine against SARS-CoV-2 (INO-4800). INO-4800 demonstrated favorable safety and tolerability and was immunogenic, eliciting humoral and/or cellular immune responses in all vaccinated subjects. There is only one ongoing clinical trial of a vaccine against SARS-CoV-2 variants (mRNA-1273.351).\n\nAdded value of this studyThis is the first-in-human phase 1 trial in healthy adults of a recombinant DNA vaccine for COVID-19 (GX-19N) containing the coding regions of both the spike and nucleocapsid proteins. This trial showed that GX-19N is safe, tolerated, and able to induce both humoral and cellular responses. A two-dose vaccination of 3{middle dot}0 mg GX-19N (on days 1 and 29) induced significant humoral and cellular responses. The neutralizing geometric mean titers in individuals vaccinated with GX-19N were lower than those of human convalescent sera. However, the GX-19N group showed increased T cell responses, which was similar to those analyzed using convalescent PBMCs. Furthermore, GX-19N induced not only SARS-CoV-2 spike-specific T cell responses but also broad nucleocapsid-specific T cell responses, which were also specific to SARS-CoV-2 variants.\n\nImplications of all the available evidenceIt is important to note that GX-19N contains a plasmid encoding both the spike and nucleocapsid proteins, and that it showed broad SARS-CoV-2-specific T cell responses, which may allow cross-reactivity with emerging SARS-CoV-2 variants. Based on these safety and immunogenicity findings, GX-19N was selected for phase 2 immunogenicity trials.", + "rel_num_authors": 18, "rel_authors": [ { - "author_name": "Tom G. Caniels", - "author_inst": "1 Department of Medical Microbiology, Amsterdam UMC, University of Amsterdam, Amsterdam Institute for Infection and Immunity, Amsterdam, the Netherlands." - }, - { - "author_name": "Ilja Bontjer", - "author_inst": "1 Department of Medical Microbiology, Amsterdam UMC, University of Amsterdam, Amsterdam Institute for Infection and Immunity, Amsterdam, the Netherlands." - }, - { - "author_name": "Karlijn van der Straten", - "author_inst": "1 Department of Medical Microbiology, Amsterdam UMC, University of Amsterdam, Amsterdam Institute for Infection and Immunity, Amsterdam, the Netherlands." - }, - { - "author_name": "Meliawati Poniman", - "author_inst": "1 Department of Medical Microbiology, Amsterdam UMC, University of Amsterdam, Amsterdam Institute for Infection and Immunity, Amsterdam, the Netherlands." + "author_name": "Jin Young Ahn", + "author_inst": "Department of Internal Medicine, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul 03722, South Korea" }, { - "author_name": "Judith A. Burger", - "author_inst": "1 Department of Medical Microbiology, Amsterdam UMC, University of Amsterdam, Amsterdam Institute for Infection and Immunity, Amsterdam, the Netherlands." - }, - { - "author_name": "Brent Appelman", - "author_inst": "2 Center for Experimental and Molecular Medicine, Amsterdam UMC, University of Amsterdam, Amsterdam Institute for Infection and Immunity, Amsterdam, the Netherl" + "author_name": "Jeongsoo Lee", + "author_inst": "Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology, 291 Daehak-ro, Yuseong-gu, Daejeon 34141, South Korea" }, { - "author_name": "Ayesha H.A. Lavell", - "author_inst": "3 Department of Internal Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Institute for Infection and Immunity, Amsterdam, the Netherlands." - }, - { - "author_name": "Melissa Oomen", - "author_inst": "1 Department of Medical Microbiology, Amsterdam UMC, University of Amsterdam, Amsterdam Institute for Infection and Immunity, Amsterdam, the Netherlands." - }, - { - "author_name": "Gert-Jan Godeke", - "author_inst": "4 Centre for Infectious Disease Control, National Institute for Public Health and the Environment, Bilthoven, the Netherlands." - }, - { - "author_name": "Coralie Valle", - "author_inst": "4 Centre for Infectious Disease Control, National Institute for Public Health and the Environment, Bilthoven, the Netherlands." - }, - { - "author_name": "Ramona Moegling", - "author_inst": "4 Centre for Infectious Disease Control, National Institute for Public Health and the Environment, Bilthoven, the Netherlands." - }, - { - "author_name": "Hugo D.G. van Willigen", - "author_inst": "1 Department of Medical Microbiology, Amsterdam UMC, University of Amsterdam, Amsterdam Institute for Infection and Immunity, Amsterdam, the Netherlands." + "author_name": "You Suk Suh", + "author_inst": "Genexine Inc., 700 Daewangpangyo-ro, Korea Bio Park Bldg. B, Bundang-gu, Seongnam-si, Gyeonggi-do 13488, South Korea" }, { - "author_name": "Elke Wynberg", - "author_inst": "5 Department of Infectious Diseases, Public Health Service of Amsterdam, GGD, Amsterdam, the Netherlands." + "author_name": "Young Goo Song", + "author_inst": "Department of Internal Medicine, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul 03722, South Korea" }, { - "author_name": "Michiel Schinkel", - "author_inst": "2 Center for Experimental and Molecular Medicine, Amsterdam UMC, University of Amsterdam, Amsterdam Institute for Infection and Immunity, Amsterdam, the Netherl" + "author_name": "Yoon-Jeong Choi", + "author_inst": "Genexine Inc., 700 Daewangpangyo-ro, Korea Bio Park Bldg. B, Bundang-gu, Seongnam-si, Gyeonggi-do 13488, South Korea" }, { - "author_name": "Lonneke A. van Vught", - "author_inst": "2 Center for Experimental and Molecular Medicine, Amsterdam UMC, University of Amsterdam, Amsterdam Institute for Infection and Immunity, Amsterdam, the Netherl" + "author_name": "Kyoung Hwa Lee", + "author_inst": "Department of Internal Medicine, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul 03722, South Korea" }, { - "author_name": "Denise Guerra", - "author_inst": "1 Department of Medical Microbiology, Amsterdam UMC, University of Amsterdam, Amsterdam Institute for Infection and Immunity, Amsterdam, the Netherlands." + "author_name": "Sang Hwan Seo", + "author_inst": "International Vaccine Institute, SNU Research Park, 1 Gwanak-ro, Gwanak-gu, Seoul 08826, South Korea" }, { - "author_name": "Jonne L. Snitselaar", - "author_inst": "1 Department of Medical Microbiology, Amsterdam UMC, University of Amsterdam, Amsterdam Institute for Infection and Immunity, Amsterdam, the Netherlands." + "author_name": "Manki Song", + "author_inst": "International Vaccine Institute, SNU Research Park, 1 Gwanak-ro, Gwanak-gu, Seoul 08826, South Korea" }, { - "author_name": "Devidas N. Chaturbhuj", - "author_inst": "6 Department of Microbiology and Immunology, Weill Medical College of Cornell University, New York, USA." + "author_name": "Jong-Won Oh", + "author_inst": "Department of Biotechnology, Yonsei University, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, South Korea" }, { - "author_name": "Isabel Cuella Martin", - "author_inst": "1 Department of Medical Microbiology, Amsterdam UMC, University of Amsterdam, Amsterdam Institute for Infection and Immunity, Amsterdam, the Netherlands." + "author_name": "Minwoo Kim", + "author_inst": "Department of Biotechnology, Yonsei University, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, South Korea" }, { - "author_name": "- Amsterdam UMC COVID-19 S3/HCW study group", - "author_inst": "" + "author_name": "Han-Yeong Seo", + "author_inst": "Department of Biotechnology, Yonsei University, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, South Korea" }, { - "author_name": "John P. Moore", - "author_inst": "6 Department of Microbiology and Immunology, Weill Medical College of Cornell University, New York, USA." + "author_name": "Jeong-Eun Kwak", + "author_inst": "Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology, 291 Daehak-ro, Yuseong-gu, Daejeon 34141, South Korea" }, { - "author_name": "Menno D. de Jong", - "author_inst": "1 Department of Medical Microbiology, Amsterdam UMC, University of Amsterdam, Amsterdam Institute for Infection and Immunity, Amsterdam, the Netherlands." + "author_name": "Jin Won Youn", + "author_inst": "Genexine Inc., 700 Daewangpangyo-ro, Korea Bio Park Bldg. B, Bundang-gu, Seongnam-si, Gyeonggi-do 13488, South Korea" }, { - "author_name": "Chantal Reusken", - "author_inst": "4 Centre for Infectious Disease Control, National Institute for Public Health and the Environment, Bilthoven, the Netherlands." + "author_name": "Jung Won Woo", + "author_inst": "Genexine Inc., 700 Daewangpangyo-ro, Korea Bio Park Bldg. B, Bundang-gu, Seongnam-si, Gyeonggi-do 13488, South Korea" }, { - "author_name": "Jonne J. Sikkens", - "author_inst": "3 Department of Internal Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Institute for Infection and Immunity, Amsterdam, the Netherlands." + "author_name": "Eui Chul Shin", + "author_inst": "Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology, 291 Daehak-ro, Yuseong-gu, Daejeon 34141, South Korea" }, { - "author_name": "Marije K. Bomers", - "author_inst": "3 Department of Internal Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Institute for Infection and Immunity, Amsterdam, the Netherlands." - }, - { - "author_name": "Godelieve J. de Bree", - "author_inst": "7 Department of Internal Medicine, Amsterdam UMC, University of Amsterdam, Amsterdam Institute for Infection and Immunity, Amsterdam, the Netherlands." - }, - { - "author_name": "Marit J. van Gils", - "author_inst": "1 Department of Medical Microbiology, Amsterdam UMC, University of Amsterdam, Amsterdam Institute for Infection and Immunity, Amsterdam, the Netherlands." + "author_name": "Su-Hyung Park", + "author_inst": "Graduate School of Medical Science & Engineering, Korea Advanced Institute of Science and Technology, 291 Daehak-ro, Yuseong-gu, Daejeon 34141, South Korea" }, { - "author_name": "Dirk Eggink", - "author_inst": "4 Centre for Infectious Disease Control, National Institute for Public Health and the Environment, Bilthoven, the Netherlands." + "author_name": "Young Chul Sung", + "author_inst": "Genexine Inc., 700 Daewangpangyo-ro, Korea Bio Park Bldg. B, Bundang-gu, Seongnam-si, Gyeonggi-do 13488, South Korea" }, { - "author_name": "Rogier W. Sanders", - "author_inst": "1 Department of Medical Microbiology, Amsterdam UMC, University of Amsterdam, Amsterdam Institute for Infection and Immunity, Amsterdam, the Netherlands." + "author_name": "Jun Yong Choi", + "author_inst": "Department of Internal Medicine, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul 03722, South Korea" } ], "version": "1", @@ -726875,51 +726150,51 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2021.06.01.446579", - "rel_title": "SARS-CoV-2 Spreads through Cell-to-Cell Transmission", + "rel_doi": "10.1101/2021.05.28.446136", + "rel_title": "First evidence of SARS-CoV-2 genome detection in zebra mussel (Dreissena polymorpha).", "rel_date": "2021-06-01", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.06.01.446579", - "rel_abs": "Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a highly transmissible coronavirus responsible for the global COVID-19 pandemic. Herein we provide evidence that SARS-CoV-2 spreads through cell-cell contact in cultures, mediated by the spike glycoprotein. SARS-CoV-2 spike is more efficient in facilitating cell-to-cell transmission than SARS-CoV spike, which reflects, in part, their differential cell-cell fusion activity. Interestingly, treatment of cocultured cells with endosomal entry inhibitors impairs cell-to-cell transmission, implicating endosomal membrane fusion as an underlying mechanism. Compared with cell-free infection, cell-to-cell transmission of SARS-CoV-2 is refractory to inhibition by neutralizing antibody or convalescent sera of COVID-19 patients. While ACE2 enhances cell-to-cell transmission, we find that it is not absolutely required. Notably, despite differences in cell-free infectivity, the variants of concern (VOC) B.1.1.7 and B.1.351 have similar cell-to-cell transmission capability. Moreover, B.1.351 is more resistant to neutralization by vaccinee sera in cell-free infection, whereas B.1.1.7 is more resistant to inhibition by vaccine sera in cell-to-cell transmission. Overall, our study reveals critical features of SARS-CoV-2 spike-mediated cell-to-cell transmission, with important implications for a better understanding of SARS-CoV-2 spread and pathogenesis.", + "rel_link": "https://biorxiv.org/cgi/content/short/2021.05.28.446136", + "rel_abs": "The uses of bivalve molluscs in environmental biomonitoring have recently gained momentum due to their ability to indicate and concentrate human pathogenic microorganisms. In the context of the health crisis caused by the COVID-19 epidemic, the objective of this study was to determine if the SARS-CoV-2 ribonucleic acid genome can be detected in zebra mussels (Dreissena polymorpha) exposed to raw and treated urban wastewaters from two separate plants to support its interest as bioindicator of the SARS-CoV-2 genome contamination in water. The zebra mussels were exposed to treated wastewater through caging at the outlet of two plants located in France, as well as to raw wastewater at laboratory scale in controlled conditions. Within their digestive tissues, our results showed that SARS-CoV-2 genome was detected in zebra mussels, whether in raw and treated wastewaters. Moreover, the detection of the SARS-CoV-2 genome in such bivalve molluscans appeared even with low concentrations in raw wastewaters. This is the first detection of the SARS-CoV-2 genome in the tissues of a sentinel species exposed to raw and treated urban wastewaters. Despite the need for development for quantitative approaches, these results support the importance of such invertebrate organisms, especially zebra mussel, for the active surveillance of pathogenic microorganisms and their indicators in environmental waters.\n\nGraphical abstract\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=71 SRC=\"FIGDIR/small/446136v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (19K):\norg.highwire.dtl.DTLVardef@781087org.highwire.dtl.DTLVardef@853128org.highwire.dtl.DTLVardef@5e667forg.highwire.dtl.DTLVardef@19b243e_HPS_FORMAT_FIGEXP M_FIG C_FIG", "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Cong Zeng", - "author_inst": "The Ohio State University" + "author_name": "Antoine Le Guernic", + "author_inst": "Universit\u00e9 de Reims Champagne-Ardenne, UMR-I02 SEBIO, Moulin de la Housse BP1039, 51687 Reims, France" }, { - "author_name": "John P. Evans", - "author_inst": "The Ohio State University" + "author_name": "M\u00e9lissa Palos Ladeiro", + "author_inst": "Universit\u00e9 de Reims Champagne-Ardenne, UMR-I02 SEBIO, Moulin de la Housse BP1039, 51687 Reims, France" }, { - "author_name": "Tiffany King", - "author_inst": "Nationwdie Childrens Hospital" + "author_name": "Nicolas Boudaud", + "author_inst": "Food Safety Department, Actalia, Saint-L\u00f4, F-50000, France" }, { - "author_name": "Yi-Min Zheng", - "author_inst": "The Ohio State University" + "author_name": "Julie Do Nascimento", + "author_inst": "Universit\u00e9 de Reims Champagne-Ardenne, UMR-I02 SEBIO, Moulin de la Housse BP1039, 51687 Reims, France." }, { - "author_name": "Eugene M. Oltz", - "author_inst": "The Ohio State University" + "author_name": "Christophe Gantzer", + "author_inst": "Universit\u00e9 de Lorraine, LCPME, UMR 7564, Institut Jean Barriol, Facult\u00e9 des Sciences et Technologies, Vand\u0153uvre-l\u00e8s-Nancy 54506, France" }, { - "author_name": "Sean P. J. Whelan", - "author_inst": "Washington University in Saint Louis" + "author_name": "Jean-Marie Mouchel", + "author_inst": "Sorbonne Universit\u00e9, CNRS, EPHE, UMR 7619 Metis, E-LTER Zone Atelier Seine, Paris, F-75005, France" }, { - "author_name": "Linda Saif", - "author_inst": "The Ohio State University" + "author_name": "Prunelle Waldman", + "author_inst": "Sorbonne Universit\u00e9, CNRS, EPHE, UMR 7619 Metis, E-LTER Zone Atelier Seine, Paris, F-75005, France" }, { - "author_name": "Shan-Lu Liu", - "author_inst": "The Ohio State University" + "author_name": "Alain Geffard", + "author_inst": "Universit\u00e9 de Reims Champagne-Ardenne, UMR-I02 SEBIO, Moulin de la Housse BP1039, 51687 Reims, France" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_no", "type": "new results", - "category": "microbiology" + "category": "ecology" }, { "rel_doi": "10.1101/2021.05.27.21257900", @@ -728340,35 +727615,99 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.05.28.21257967", - "rel_title": "Effectiveness of the Covid-19 vaccine in preventing infection in dental practitioners: results of a cross-sectional questionnaire based survey", + "rel_doi": "10.1101/2021.05.27.21257918", + "rel_title": "Monitoring emergence of SARS-CoV-2 B.1.1.7 Variant through the Spanish National SARS-CoV-2 Wastewater Surveillance System (VATar COVID-19) from December 2020 to March 2021", "rel_date": "2021-05-30", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.28.21257967", - "rel_abs": "India started its vaccination program at the beginning of 2021, the main beneficiaries being health workers and frontline workers including police, paramilitary forces, sanitation workers, and disaster management volunteers in the first phase. By the time, the second wave of Covid-19 impacted India, approximately 14 million healthcare and frontline workers, including dentists had been vaccinated.\n\nAimTo study the effectiveness of vaccination on a subset of high-risk healthcare workers i.e. dentists in preventing Covid-19 during the second wave of the pandemic.\n\nStudy designA questionnaire based pan-India online survey was carried out to record the Covid-related experiences of dentists prior to and after vaccination.\n\nResultThe sample size for this survey was 4493 respondents from across India. During the second wave, 9.18% (n=364) respondents became positive in spite of the vaccine, while 14.69%(n=78) became positive in the unvaccinated group. A chi-square test of independence was performed to examine the relation between vaccination and the Covid positivity rate in all age groups. The relation between these variables was highly significant, [X2 (1, N = 4493) = 15.9809, p=.000064].\n\nConclusionOur pan-India online survey inferred that vaccination has a definitive role to play in reducing the positivity rate amongst dentists during the second wave of the pandemic across all age groups.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.27.21257918", + "rel_abs": "BackgroundSince its first identification in the United Kingdom in late 2020, the highly transmissible B.1.1.7 variant of SARS-CoV-2, become dominant in several European countries raising great concern.\n\nAimThe aim of this study was to develop a duplex real-time RT-qPCR assay to detect, discriminate and quantitate SARS-CoV-2 variants containing one of its mutation signatures, the {Delta}HV69/70 deletion, to trace the community circulation of the B.1.1.7 variant in Spain through the Spanish National SARS-CoV-2 Wastewater Surveillance System (VATar COVID-19).\n\nResultsB.1.1.7 variant was first detected in sewage from the Southern city of Malaga (Andalucia) in week 20_52, and multiple introductions during Christmas holidays were inferred in different parts of the country, earlier than clinical epidemiological reporting by the local authorities. Wastewater-based B.1.1.7 tracking showed a good correlation with clinical data and provided information at the local level. Data from WWTPs which reached B.1.1.7 prevalences higher than 90% for [≥] 2 consecutive weeks showed that 8.1{+/-}1.8 weeks were required for B.1.1.7 to become dominant.\n\nConclusionThe study highlights the applicability of RT-qPCR-based strategies to track specific mutations of variants of concern (VOCs) as soon as they are identified by clinical sequencing, and its integration into existing wastewater surveillance programs, as a cost-effective approach to complement clinical testing during the COVID-19 pandemic.", + "rel_num_authors": 20, "rel_authors": [ { - "author_name": "Sanjeev Kumar", - "author_inst": "Faculty of Dental Sciences, SGT University, Gurugram" + "author_name": "Albert Carcereny", + "author_inst": "University of Barcelona" }, { - "author_name": "Susmita Saxena", - "author_inst": "ESIC Dental College & Hospital, Rohini, New Delhi" + "author_name": "Adan Martinez-Velazquez", + "author_inst": "University of Barcelona" }, { - "author_name": "Mansi Atri", - "author_inst": "ESIC Dental College & Hospital, Rohini, New Delhi" + "author_name": "Albert Bosch", + "author_inst": "University of Barcelona" }, { - "author_name": "Sunil Kumar Chamola", - "author_inst": "Faculty of Medicine & Health Sciences, SGT University, Gurugram" + "author_name": "Ana Allende", + "author_inst": "CEBAS-CSIC" + }, + { + "author_name": "Pilar Truchado", + "author_inst": "CEBAS-CSIC" + }, + { + "author_name": "Jenifer Cascales", + "author_inst": "CEBAS-CSIC" + }, + { + "author_name": "Jesus L Romalde", + "author_inst": "Universidade de Santiago de Compostela" + }, + { + "author_name": "Marta Lois", + "author_inst": "Universidade de Santiago de Compostela" + }, + { + "author_name": "David Polo", + "author_inst": "Universidade de Santiago de Compostela" + }, + { + "author_name": "Gloria Sanchez", + "author_inst": "IATA-CSIC" + }, + { + "author_name": "Alba Perez-Cataluna", + "author_inst": "IATA-CSIC" + }, + { + "author_name": "Azahara Diaz-Reolid", + "author_inst": "IATA-CSIC" + }, + { + "author_name": "Andres Anton", + "author_inst": "Vall d'Hebron Institut de Recerca (VHIR)" + }, + { + "author_name": "Josep Gregori", + "author_inst": "Vall d'Hebron Institut de Recerca (VHIR)" + }, + { + "author_name": "Damir Garcia-Cehic", + "author_inst": "Vall d'Hebron Institut de Recerca (VHIR)" + }, + { + "author_name": "JOSEP QUER", + "author_inst": "Vall d'Hebron Institut de Recerca (VHIR)" + }, + { + "author_name": "Margarita Palau", + "author_inst": "Ministry of Health, Spain" + }, + { + "author_name": "Cristina Gonzalez Ruano", + "author_inst": "MITECO" + }, + { + "author_name": "Rosa Pinto", + "author_inst": "University of Barcelona" + }, + { + "author_name": "Susana Guix", + "author_inst": "University of Barcelona" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "dentistry and oral medicine" + "category": "epidemiology" }, { "rel_doi": "10.1101/2021.05.27.21257934", @@ -729946,151 +729285,55 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2021.05.28.446200", - "rel_title": "A suitable murine model for studying respiratory coronavirus infection and therapeutic countermeasures in BSL-2 laboratories", - "rel_date": "2021-05-29", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.05.28.446200", - "rel_abs": "Several animal models are being used to explore important features of COVID-19, nevertheless none of them recapitulates all aspects of the disease in humans. The continuous refinement and development of other options of in vivo models are opportune, especially ones that are carried out at BSL-2 (Biosafety Level 2) laboratories. In this study, we investigated the suitability of the intranasal infection with the murine betacoronavirus MHV-3 to recapitulate multiple aspects of the pathogenesis of COVID-19 in C57BL/6J mice. We demonstrate that MHV-3 replicated in lungs 1 day after inoculation and triggered respiratory inflammation and dysfunction. This MHV-model of infection was further applied to highlight the critical role of TNF in cytokine-mediated coronavirus pathogenesis. Blocking TNF signaling by pharmacological and genetic strategies greatly increased the survival time and reduces lung injury of MHV-3-infected mice. In vitro studies showed that TNF blockage decreased SARS-CoV-2 replication in human epithelial lung cells and resulted in the lower release of IL-6 and IL-8 cytokines beyond TNF itself. Taken together, our results demonstrate that this model of MHV infection in mice is a useful BSL-2 screening platform for evaluating pathogenesis for human coronaviruses infections, such as COVID-19.", - "rel_num_authors": 33, + "rel_doi": "10.1101/2021.05.21.21257574", + "rel_title": "Mortality audit of cancer patients with SARS-CoV-2 positivity or COVID-19", + "rel_date": "2021-05-28", + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.21.21257574", + "rel_abs": "Coronavirus disease-2019 (COVID-19) has disrupted cancer care services globally. The present review of cause of deaths was conducted in a tertiary care cancer center in the North East India. In our institute, all cancer patients requiring admission for surgery, chemotherapy, and other daycare procedures require testing for severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). From 09 July 2020 to 16 May 2021, 119 cancer patients with SARS-CoV-2 positive report or COVID-19 have been admitted at our institute Covid ward. A total of 19 cancer patients with COVID-19 succumbed. Of 19 deaths, 13 (68.4%) patients were men and 6 (31.6%) patients were women. The age range from 27 years to 74 years (median =55 years). Vomiting alone or with diarrhea was the most common symptom requiring admission after testing (4/19, 21.0%), followed by bleeding from primary tumour site (3/19, 15.7%). The antecedent and underlying cause of deaths in 19 (100%) patients was cancer. SARS-CoV-2 infection should not be a hindrance for cancer treatment and management.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Ana Claudia dos Santos Pereira Andrade", - "author_inst": "Department of Morphology, Institute of Biological Sciences, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil" + "author_name": "Kaberi Kakati", + "author_inst": "Dr B Borooah Cancer Institute" }, { - "author_name": "Gabriel Henrique Campolina-Silva", - "author_inst": "Department of Biochemistry and Immunology, Institute of Biological Sciences, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil" + "author_name": "Tashnin Rahman", + "author_inst": "Dr. B Borooah Cancer Institute" }, { - "author_name": "Celso Martins Queiroz-Junior", - "author_inst": "Department of Biochemistry and Immunology, Institute of Biological Sciences, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil" - }, - { - "author_name": "Leonardo Camilo de Oliveira", - "author_inst": "Department of Morphology, Institute of Biological Sciences, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil" + "author_name": "Debabrata Barman", + "author_inst": "Dr. B Borooah Cancer Institute" }, { - "author_name": "Larisse de Souza Barbosa Lacerda", - "author_inst": "Department of Morphology, Institute of Biological Sciences, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil" + "author_name": "Mouchumee Bhattacharyya", + "author_inst": "Dr. B Borooah Cancer Institute" }, { - "author_name": "Jordane Clarisse Pimenta", - "author_inst": "Department of Morphology, Institute of Biological Sciences, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil" + "author_name": "Bibhuti Bhusan Borthakur", + "author_inst": "Dr. B Borooah Cancer Institute" }, { - "author_name": "Filipe Resende Oliveira de Souza", - "author_inst": "Department of Morphology, Institute of Biological Sciences, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil" + "author_name": "Rashmisnata Barman", + "author_inst": "Dr. B Borooah Cancer Institute" }, { - "author_name": "Ian de Meira Chaves", - "author_inst": "Department of Morphology, Institute of Biological Sciences, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil" + "author_name": "Apurba Kalita", + "author_inst": "Dr. B Borooah Cancer Institute" }, { - "author_name": "Ingredy Beatriz Passos", - "author_inst": "Department of Microbiology, Institute of Biological Sciences, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil" + "author_name": "Amal Chandra Kataki", + "author_inst": "Dr. B Borooah Cancer Institute" }, { - "author_name": "Danielle Cunha Teixeira", - "author_inst": "Department of Morphology, Institute of Biological Sciences, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil" - }, - { - "author_name": "Paloma Graziele Bittencourt-Silva", - "author_inst": "Department of Physiology and Biophysics, Institute of Biological Sciences, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil." - }, - { - "author_name": "Priscila Aparecida Costa Valadao", - "author_inst": "Department of Morphology, Institute of Biological Sciences, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil" - }, - { - "author_name": "Leonardo Rossi-Oliveira", - "author_inst": "Department of Morphology, Institute of Biological Sciences, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil" - }, - { - "author_name": "Maisa Mota Antunes", - "author_inst": "Department of Morphology, Institute of Biological Sciences, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil" - }, - { - "author_name": "Andre Felipe Almeida Figueiredo", - "author_inst": "Department of Morphology, Institute of Biological Sciences, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil" - }, - { - "author_name": "Natalia Teixeira Wnuk", - "author_inst": "Department of Morphology, Institute of Biological Sciences, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil" - }, - { - "author_name": "Jairo R Temerozo", - "author_inst": "Laboratory on Thymus Research, Oswaldo Cruz Institute, Fiocruz, Rio de Janeiro, RJ, Brazil, National Institute for Science and Technology on Neuroimmunomodulati" - }, - { - "author_name": "Andre Costa Ferreira", - "author_inst": "Laboratorio de Pesquisas Pre clinicas, Universidade Iguacu, Rio de Janeiro, RJ, Brazil; Oswaldo Cruz Foundation Fiocruz, Rio de Janeiro, Rio de Janeiro, Brazil" - }, - { - "author_name": "Allysson Cramer", - "author_inst": "Department of Biochemistry and Immunology, Institute of Biological Sciences, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil" - }, - { - "author_name": "Cleida Aparecida Oliveira", - "author_inst": "Department of Morphology, Institute of Biological Sciences, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil" - }, - { - "author_name": "Ricardo Duraes-Carvalho", - "author_inst": "Laboratory of Virology, Universidade Estadual de Campinas UNICAMP, Campinas, Sao Paulo, Brazil" - }, - { - "author_name": "Clarice Weis Arns", - "author_inst": "Laboratory of Virology, Universidade Estadual de Campinas UNICAMP, Campinas, Sao Paulo, Brazil" - }, - { - "author_name": "Pedro Pires Goulart Guimaraes", - "author_inst": "Department of Physiology and Biophysics, Institute of Biological Sciences, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil" - }, - { - "author_name": "Guilherme Mattos Jardim Costa", - "author_inst": "Department of Morphology, Institute of Biological Sciences, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil" - }, - { - "author_name": "Gustavo Batista de Menezes", - "author_inst": "Department of Morphology, Institute of Biological Sciences, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil" - }, - { - "author_name": "Cristina Guatimosim", - "author_inst": "Department of Morphology, Institute of Biological Sciences, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil" - }, - { - "author_name": "Glauber Santos Ferreira da Silva", - "author_inst": "Department of Physiology and Biophysics, Institute of Biological Sciences, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil." - }, - { - "author_name": "Thiago Moreno L. Souza", - "author_inst": "National Institute for Science and Technology on Innovation on Diseases of Neglected Populations (INCT/IDNP), Center for Technological Development in Health (CD" - }, - { - "author_name": "Breno Rocha Barrioni", - "author_inst": "Department of Metallurgical Engineering and Materials, Federal University of Minas Gerais, School of Engineering, Belo Horizonte, Brazil" - }, - { - "author_name": "Marivalda de Magalhaes Pereira", - "author_inst": "Department of Metallurgical Engineering and Materials, Federal University of Minas Gerais, School of Engineering, Belo Horizonte, Brazil" - }, - { - "author_name": "Lirlandia Pires de Sousa", - "author_inst": "Department of Clinical and Toxicological Analysis, Faculty of Pharmacy, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil." - }, - { - "author_name": "Mauro Martins Teixeira", - "author_inst": "2)\tDepartment of Biochemistry and Immunology, Institute of Biological Sciences, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil" - }, - { - "author_name": "Vivian Vasconcelos Costa", - "author_inst": "Department of Morphology, Institute of Biological Sciences, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil" + "author_name": "Manigreeva Krishnatreya", + "author_inst": "Dr B Borooah Cancer Institute" } ], "version": "1", - "license": "cc_by_nc_nd", - "type": "new results", - "category": "microbiology" + "license": "cc_no", + "type": "PUBLISHAHEADOFPRINT", + "category": "oncology" }, { "rel_doi": "10.1101/2021.05.23.21256350", @@ -731555,47 +730798,135 @@ "category": "bioinformatics" }, { - "rel_doi": "10.1101/2021.05.27.445985", - "rel_title": "SARS-CoV-2 inactivation by human defensin HNP1 and retrocyclin RC-101", + "rel_doi": "10.1101/2021.05.26.445838", + "rel_title": "Reduced sensitivity of infectious SARS-CoV-2 variant B.1.617.2 to monoclonal antibodies and sera from convalescent and vaccinated individuals", "rel_date": "2021-05-27", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.05.27.445985", - "rel_abs": "Severe acute respiratory syndrome coronavirus (SARS-CoV)-2 is an enveloped virus responsible for the COVID-19 respiratory disease pandemic. While induction of adaptive antiviral immunity via vaccination holds promise for combatting the pandemic, the emergence of new potentially more transmissible and vaccine-resistant variants of SARS-CoV-2 is an ever-present threat. Thus, it remains essential to better understand innate immune mechanisms that are active against the virus. One component of the innate immune system with broad anti-pathogen, including antiviral, activity is a group of cationic immune peptides termed defensins. The defensins ability to neutralize enveloped and non-enveloped viruses and to inactivate numerous bacterial toxins correlate with their ability to promote the unfolding of thermodynamically pliable proteins. Accordingly, we found that human neutrophil a-defensin HNP1 and retrocyclin RC-101 destabilize SARS-CoV-2 Spike protein and interfere with Spike-mediated membrane fusion and SARS-CoV-2 infection in cell culture. We show that HNP1 binds to Spike with submicromolar affinity. Although binding of HNP1 to serum albumin is more than 20-fold weaker, serum reduces the anti-SARS-CoV-2 activity of HNP1. At high concentrations of HNP1, its ability to inactivate the virus was preserved even in the presence of serum. These results suggest that specific a- and 8-defensins may be valuable tools in developing SARS-CoV-2 infection prevention strategies.", - "rel_num_authors": 7, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.05.26.445838", + "rel_abs": "The SARS-CoV-2 B.1.617 lineage emerged in October 2020 in India1-6. It has since then become dominant in some indian regions and further spread to many countries. The lineage includes three main subtypes (B1.617.1, B.1617.2 and B.1.617.3), which harbour diverse Spike mutations in the N-terminal domain (NTD) and the receptor binding domain (RBD) which may increase their immune evasion potential. B.1.617.2 is believed to spread faster than the other versions. Here, we isolated infectious B.1.617.2 from a traveller returning from India. We examined its sensitivity to monoclonal antibodies (mAbs) and to antibodies present in sera from COVID-19 convalescent individuals or vaccine recipients, in comparison to other viral lineages. B.1.617.2 was resistant to neutralization by some anti-NTD and anti-RBD mAbs, including Bamlanivimab, which were impaired in binding to the B.1.617.2 Spike. Sera from convalescent patients collected up to 12 months post symptoms and from Pfizer Comirnaty vaccine recipients were 3 to 6 fold less potent against B.1.617.2, relative to B.1.1.7. Sera from individuals having received one dose of AstraZeneca Vaxzevria barely inhibited B.1.617.2. Thus, B.1.617.2 spread is associated with an escape to antibodies targeting non-RBD and RBD Spike epitopes.", + "rel_num_authors": 29, "rel_authors": [ { - "author_name": "Elena Kudryashova", - "author_inst": "The Ohio State University" + "author_name": "Delphine Planas", + "author_inst": "Institut Pasteur" }, { - "author_name": "Ashley Zani", - "author_inst": "The Ohio State University" + "author_name": "David Veyer", + "author_inst": "APHP" }, { - "author_name": "Geraldine Vilmen", - "author_inst": "National Cancer Institute, NIH" + "author_name": "Artem Baidaliuk", + "author_inst": "Institut Pasteur" }, { - "author_name": "Amit Sharma", - "author_inst": "The Ohio State University" + "author_name": "Isabelle Staropoli", + "author_inst": "Institut Pasteur" }, { - "author_name": "Wuyuan Lu", - "author_inst": "Fudan University, Shanghai, China" + "author_name": "Florence Guivel-Benhassine", + "author_inst": "Institut Pasteur" }, { - "author_name": "Jacob S. Yount", - "author_inst": "The Ohio State University" + "author_name": "Maaran Rajah", + "author_inst": "Institut Pasteur" }, { - "author_name": "Dmitri S. Kudryashov", - "author_inst": "The Ohio State University" + "author_name": "Cyril Planchais", + "author_inst": "Institut Pasteur" + }, + { + "author_name": "Francoise Porrot", + "author_inst": "Institut Pasteur" + }, + { + "author_name": "Nicolas Robillard", + "author_inst": "APHP" + }, + { + "author_name": "Julien Puech", + "author_inst": "APHP" + }, + { + "author_name": "Matthieu Prot", + "author_inst": "Institut Pasteur" + }, + { + "author_name": "Floriane Gallais", + "author_inst": "HUS" + }, + { + "author_name": "Pierre Gantner", + "author_inst": "HUS" + }, + { + "author_name": "Aurelie Velay", + "author_inst": "HUS" + }, + { + "author_name": "Julien Le Guen", + "author_inst": "APHP" + }, + { + "author_name": "Najibi Kassis-Chikhani", + "author_inst": "APHP" + }, + { + "author_name": "Dhiaeddine Edriss", + "author_inst": "APHP" + }, + { + "author_name": "Laurent Belec", + "author_inst": "APHP" + }, + { + "author_name": "Aymeric Seve", + "author_inst": "CHR Orleans" + }, + { + "author_name": "Helene Pere", + "author_inst": "APHP" + }, + { + "author_name": "Laura Courtellemenont", + "author_inst": "CHR Orleans" + }, + { + "author_name": "Laurent Hocqueloux", + "author_inst": "CHR Orleans" + }, + { + "author_name": "Samira Fafi-Kremer", + "author_inst": "HUS" + }, + { + "author_name": "Thierry Prazuck", + "author_inst": "CHR Orleans" + }, + { + "author_name": "Hugo Mouquet", + "author_inst": "Institut Pasteur" + }, + { + "author_name": "Timothee Bruel", + "author_inst": "Institut Pasteur" + }, + { + "author_name": "Etienne Simon-Loriere", + "author_inst": "Institut Pasteur" + }, + { + "author_name": "Felix Rey", + "author_inst": "Institut Pasteur" + }, + { + "author_name": "Olivier Schwartz", + "author_inst": "Institut Pasteur" } ], "version": "1", "license": "cc_by_nc_nd", "type": "new results", - "category": "immunology" + "category": "microbiology" }, { "rel_doi": "10.1101/2021.05.27.445918", @@ -733753,55 +733084,51 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2021.05.26.445843", - "rel_title": "Variable Induction of Pro-inflammatory Cytokines by Commercial SARS CoV-2 Spike Protein Reagents: Potential Impacts of LPS on In Vitro Modeling and Pathogenic Mechanisms In Vivo", + "rel_doi": "10.1101/2021.05.26.445422", + "rel_title": "A modular molecular framework for quickly estimating the binding affinity of the spike protein of SARS-CoV-2 variants for ACE2, in presence of mutations at the spike receptor binding domain.", "rel_date": "2021-05-26", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.05.26.445843", - "rel_abs": "Proinflammatory cytokine production following infection with severe acute respiratory syndrome coronavirus 2 (SARS CoV-2) is associated with poor clinical outcomes. Like SARS CoV-1, SARS CoV-2 enters host cells via its spike protein, which attaches to angiotensin-converting enzyme 2 (ACE2). As SARS CoV-1 spike protein is reported to induce cytokine production, we hypothesized that this pathway could be a shared mechanism underlying pathogenic immune responses. We herein compared the capabilities of Middle East Respiratory Syndrome (MERS), SARS CoV-1 and SARS CoV-2 spike proteins to induce cytokine expression in human peripheral blood mononuclear cells (PBMC). We observed that only specific commercial lots of SARS CoV-2 induce cytokine production. Surprisingly, recombinant SARS CoV-2 spike proteins from different vendors and batches exhibited different patterns of cytokine induction, and these activities were not inhibited by blockade of spike protein-ACE2 binding using either soluble ACE2 or neutralizing anti-S1 antibody. Moreover, commercial spike protein reagents contained varying levels of endotoxin, which correlated directly with their abilities to induce cytokine production. The lipopolysaccharide (LPS) inhibitor, polymyxin B, blocked this cytokine induction activity. In addition, SARS CoV-2 spike protein avidly bound soluble LPS in vitro, rendering it a cytokine inducer. These results not only suggest caution in monitoring the purity of SARS CoV-2 spike protein reagents, but they indicate the possibility that interactions of SARS CoV-2 spike protein with LPS from commensal bacteria in virally infected mucosal tissues could promote pathogenic inflammatory cytokine production.", - "rel_num_authors": 9, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.05.26.445422", + "rel_abs": "The rapid spread of new SARS-CoV-2 variants needs the development of rapid tools for predicting the affinity of the mutated proteins responsible for the infection, i.e., the SARS-CoV-2 spike protein, for the human ACE2 receptor, aiming to understand if a variant can be more efficient in invading host cells. Here we show how our computational pipeline, previously used for studying SARS-CoV-2 spike receptor binding domain (RBD)/ACE2 interactions and pre-/post-fusion conformational changes, can be used for predicting binding affinities of the human ACE2 receptor for the spike protein RBD of the characterized infectious variants of concern/interest B.1.1.7-UK (carrying the mutations N501Y, S494P, E484K at the RBD), P.1-Japan/Brazil (RBD mutations: K417N/T, E484K, N501Y), B.1.351-South Africa (RBD mutations: K417N, E484K, N501Y), B.1.427/B.1.429-California (RBD mutations: L452R), the B.1.141 variant (RBD mutations: N439K), and the recent B.1.617.1-India (RBD mutations: L452R; E484Q) and the B.1.620 (RBD mutations: S477N; E484K). Furthermore, we searched for ACE2 structurally related proteins that might be involved in interactions with the SARS-CoV-2 spike protein, in those tissues showing low ACE2 expression, revealing two new proteins, THOP1 and NLN, deserving to be investigated for their possible inclusion in the group of host-cell entry factors responsible for host-cell SARS-CoV-2 invasion and immunity response.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Weiming Ouyang", - "author_inst": "FDA" - }, - { - "author_name": "Tao Xie", - "author_inst": "FDA" + "author_name": "Vincenzo Tragni", + "author_inst": "Department of Biosciences, Biotechnologies and Biopharmaceutics; University of Bari, Italy" }, { - "author_name": "Hui Fang", - "author_inst": "FDA" + "author_name": "Francesca Preziusi", + "author_inst": "Department of Biosciences, Biotechnologies and Biopharmaceutics; University of Bari, Italy" }, { - "author_name": "Chunling Gao", - "author_inst": "FDA" + "author_name": "Luna Laera", + "author_inst": "Department of Biosciences, Biotechnologies and Biopharmaceutics; University of Bari, Italy" }, { - "author_name": "Tzanko Stantchev", - "author_inst": "FDA" + "author_name": "Angelo Onofrio", + "author_inst": "Department of Biosciences, Biotechnologies and Biopharmaceutics; University of Bari, Italy" }, { - "author_name": "Kathleen A. Clouse", - "author_inst": "FDA" + "author_name": "Simona Todisco", + "author_inst": "Department of Sciences; University of Basilicata, Italy" }, { - "author_name": "Kun Yuan", - "author_inst": "FDA" + "author_name": "Mariateresa Volpicella", + "author_inst": "Department of Biosciences, Biotechnologies and Biopharmaceutics; University of Bari, Italy" }, { - "author_name": "Tongzhong Ju", - "author_inst": "FDA" + "author_name": "Anna De Grassi", + "author_inst": "Department of Biosciences, Biotechnologies and Biopharmaceutics; University of Bari, Italy" }, { - "author_name": "David M. Frucht", - "author_inst": "FDA" + "author_name": "Ciro Leonardo Pierri", + "author_inst": "University of Bari" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "new results", - "category": "microbiology" + "category": "biochemistry" }, { "rel_doi": "10.1101/2021.05.26.445786", @@ -735155,43 +734482,83 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2021.05.24.21257710", - "rel_title": "Nursing students' attitudes, knowledge, and willingness to receive the COVID-19 vaccine: A cross-sectional study", + "rel_doi": "10.1101/2021.05.23.21257686", + "rel_title": "Addressing anti-syncytin antibody levels, and fertility and breastfeeding concerns, following BNT162B2 COVID-19 mRNA vaccination", "rel_date": "2021-05-25", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.24.21257710", - "rel_abs": "AimTo investigate nursing students konwledge, attitudes and willingness to receive the COVID-19 vaccine, and the influencing factors.\n\nBackgroundVaccination is one of the effective measures to prevent COVID-19, but the vaccination acceptance varies across countries and populations. As reserve nurses, nursing students have both the professionalism of medical personnel and the special characteristics of school students, their attitudes, knowledge, and willingness to receive the COVID-19 vaccine may greatly affect the vaccine acceptance of the population now and in the future. But little research has been done on vaccine acceptance among nursing students.\n\nDesignA cross-sectional survey of nursing students was conducted via online questionnaires in March 2021.\n\nMethodsDescriptive statistics, independent sample t tests/one-way ANOVA (normal distribution), Mann-Whitney U tests/Kruskal-Wallis H tests (skewness distribution) and multivariate linear regression were performed.\n\nResultsThe score rate of attitude, knowledge and vaccination willingness were 70.07%, 80.70% and 84.38% respectively. Attitude was significantly influenced by family economic conditions and whether a family member had been vaccinated. The main factors influencing knowledge were gender, grade and academic background. In terms of willingness, gender, academic background, visits to risk areas, whether family members were vaccinated, and whether they had side effects were significant influencing factors.\n\nConclusionsThe vaccine acceptance of nursing students was fair. Greater focus needed to be placed on the males, those of younger age, with a science background, and having low grades, as well as on students whose family members had not received the COVID-19 vaccine or had side effects from the vaccine. Targeted intervention strategies were recommended to improve vaccination rates.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.23.21257686", + "rel_abs": "ObjectiveTo determine whether antibodies against the SARS-CoV-2 spike protein following BNT162B2 (Pfizer-BioNTech) COVID-19 mRNA vaccination cross-react with human syncytin-1 protein, and if BNT162B2 mRNA enters breast milk.\n\nMethodsIn this observational cohort study of female front-line workers with no history of COVID-19 infection, we amplified BNT162B2 mRNA in plasma and breast milk and assayed anti-SARS-CoV-2 neutralising antibodies and anti-human syncytin-1 binding antibodies in plasma, at early (1-4 days) and late (4-7 weeks) time points following first-dose vaccination.\n\nResultsFifteen consented participants (mean age 40.4 years, various ethnicities) who received at least one dose of BNT162B2, including five breast-feeding women and two women who were inadvertently vaccinated in early pregnancy, were recruited. BNT162B2 mRNA, detected by amplifying part of the spike-encoding region, was detected in plasma 1-4 days following the first dose (n=13), but not 4-5 weeks later (n=2), nor was the mRNA isolated from aqueous or lipid breast milk fractions collected 0-7 days post-vaccination (n=5). Vaccine recipients demonstrated strong SARS-CoV-2 neutralising activity by at least four weeks after the first dose (n=15), including the two pregnant women. None had placental anti-syncytin-1 binding antibodies at either time-point following vaccination.\n\nConclusionsBNT162B2-vaccinated women did not transmit vaccine mRNA to breast milk, and did not produce a concurrent humoral response to syncytin-1, suggesting that cross-reactivity to syncytin-1 on the developing trophoblast, or other adverse effects in the breast-fed infant from vaccine mRNA ingestion, are unlikely.\n\nWhat are the novel findings of this work?COVID-19 vaccination with BNT162B2 did not elicit a cross-reacting humoral response to human syncytin-1 despite robust neutralising activity to the SARS-CoV2 spike protein, and while vaccine mRNA was isolated from plasma, it was not found in breast milk.\n\nWhat are the clinical implications of this work?Our work directly addresses the fertility and breastfeeding concerns fuelling vaccine hesitancy among reproductive-age women, by suggesting that BNT162B2 vaccination is unlikely to cause adverse effects on the developing trophoblast, via cross-reacting anti-syncytin-1 antibodies, or to the breastfed neonate, via mRNA breast milk transmission.", + "rel_num_authors": 16, "rel_authors": [ { - "author_name": "Ning Jiang", - "author_inst": "Shandong First Medical University" + "author_name": "Citra Nurfarah Mattar", + "author_inst": "Department of Obstetrics and Gynaecology, Yong Loo Lin School of Medicine, National University of Singapore; Department of Obstetrics and Gynaecology, National " }, { - "author_name": "Baojian Wei", - "author_inst": "School of Nursing, Shandong First Medical University & Shandong Academy of Medical Sciences, Taian 271000, Shandong, China." + "author_name": "Winston Koh", + "author_inst": "Molecular Engineering Laboratory, Institute of Molecular and Cell Biology, Agency for Science Technology and Research, Singapore" }, { - "author_name": "Hua Lin", - "author_inst": "School of Nursing, Shandong First Medical University & Shandong Academy of Medical Sciences, Taian 271000, Shandong, China." + "author_name": "Yiqi Seow", + "author_inst": "Molecular Engineering Laboratory, Institute of Molecular and Cell Biology, Agency for Science Technology and Research, Singapore" }, { - "author_name": "Youjuan Wang", - "author_inst": "Shandong First Medical University & Shandong Academy of Medical Sciences, Taian 271000, Shandong, China." + "author_name": "Shawn Hoon", + "author_inst": "Molecular Engineering Laboratory, Institute of Molecular and Cell Biology, Agency for Science Technology and Research, Singapore" }, { - "author_name": "Shouxia Chai", - "author_inst": "School of Nursing, Hubei University of Medicine, Shiyan 442000, Hubei, China." + "author_name": "Aparna VENKATESH", + "author_inst": "Molecular Engineering Laboratory, Institute of Molecular and Cell Biology, Agency for Science Technology and Research, Singapore" }, { - "author_name": "Wei Liu", - "author_inst": "School of Nursing, Shandong First Medical University & Shandong Academy of Medical Sciences, Taian 271000, Shandong, China." + "author_name": "Pradip Dashraath", + "author_inst": "Department of Obstetrics and Gynaecology, National University Hospital, Singapore" + }, + { + "author_name": "Li Min LIM", + "author_inst": "Department of Obstetrics and Gynaecology, National University Hospital, Singapore" + }, + { + "author_name": "Judith ONG", + "author_inst": "Department of Obstetrics and Gynaecology, National University Hospital, Singapore" + }, + { + "author_name": "Rachel Jiayu Lee", + "author_inst": "Department of Obstetrics and Gynaecology, National University Hospital, Singapore" + }, + { + "author_name": "Nuryanti Johana", + "author_inst": "Department of Reproductive Medicine, KK Women's and Children's Hospital, Singapore" + }, + { + "author_name": "Julie SL Yeo", + "author_inst": "Department of Reproductive Medicine, KK Women's and Children's Hospital, Singapore" + }, + { + "author_name": "David Shao Hong Chong", + "author_inst": "Department of Obstetrics and Gynaecology, Yong Loo Lin School of Medicine, National University of Singapore" + }, + { + "author_name": "Lay Kok Tan", + "author_inst": "Department of Maternal Fetal Medicine, KK Women's and Children's Hospital, Singapore" + }, + { + "author_name": "Jerry Kok Yen Chan", + "author_inst": "Department of Maternal Fetal Medicine, KK Women's and Children's Hospital, Singapore; Cancer and Stem Cells Program / OBGYN Academic Clinical Program, Duke-NUS " + }, + { + "author_name": "Mahesh Choolani", + "author_inst": "Department of Obstetrics and Gynaecology, Yong Loo Lin School of Medicine, National University of Singapore; Department of Obstetrics and Gynaecology, National " + }, + { + "author_name": "Paul Anantharajah Tambyah", + "author_inst": "Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore; Division of Infectious Diseases, Department of Medicine, National Uni" } ], "version": "1", "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "nursing" + "category": "obstetrics and gynecology" }, { "rel_doi": "10.1101/2021.05.25.21257797", @@ -737229,55 +736596,47 @@ "category": "bioinformatics" }, { - "rel_doi": "10.1101/2021.05.20.21257545", - "rel_title": "Are we allowed to visit now? Concerns and issues surrounding vaccination and infection risks in UK care homes during COVID-19", + "rel_doi": "10.1101/2021.05.20.21257536", + "rel_title": "RT-qPCR detection of SARS-CoV-2 mutations S 69-70 del, S N501Y and N D3L associated with variants of concern in Canadian wastewater samples", "rel_date": "2021-05-24", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.20.21257545", - "rel_abs": "BackgroundVaccination uptake in the UK and increased care home testing are likely affecting care home visitation. With scant scientific evidence to date, the aim of this longitudinal qualitative study was to explore the impact of both (vaccination and testing) on the conduct and experiences of care home visits.\n\nMethodsFamily carers of care home residents with dementia and care home staff from across the UK took part in baseline (October/November 2020) and follow-up interviews (March 2021). Public advisers were involved in all elements of the research. Data were analysed using thematic analysis.\n\nResultsAcross 62 baseline and follow-up interviews with family carers (n=26; 11) and care home staff (n=16; 9), five core themes were developed: Delayed and inconsistent offers of face-to-face visits; Procedures and facilitation of visits; Frustration and anger among family carers; Variable uptake of the COVID-19 vaccine; Misinformation, education, and free choice. The variable uptake in staff, compared to family carers, was a key factor seemingly influencing visitation, with a lack of clear guidance leading care homes to implement infection control measures and visitation rights differently.\n\nConclusionsWe make five recommendations in this paper to enable improved care home visitation in the ongoing, and in future, pandemics. Visits need to be enabled and any changes to visiting rights must be used as a last resort, reviewed regularly in consultation with residents and carers and restored as soon as possible as a top priority, whilst more education needs to be provided surrounding vaccination for care home staff.", - "rel_num_authors": 9, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.20.21257536", + "rel_abs": "SARS-CoV-2 variants of concern (VoC) have been increasingly detected in clinical surveillance in Canada and internationally. These VoC are associated with higher transmissibility rates and in some cases, increased mortality. In this work we present a national wastewater survey of the distribution of three SARS-CoV-2 mutations found in the B.1.1.7, B.1.351, and P.1 VoC, namely the S-gene 69-70 deletion, N501Y mutation, and N-gene D3L. RT-qPCR allelic discrimination assays were sufficiently sensitive and specific for detection and relative quantitation of SARS-CoV-2 variants in wastewater to allow for rapid population-level screening and surveillance. We tested 261 samples collected from 5 Canadian cities (Vancouver, Edmonton, Toronto, Montreal, and Halifax) and 6 communities in the Northwest Territories from February 16th to March 28th, 2021. VoC were not detected in the Territorial communities, suggesting the absence of VoC SARS-CoV-2 cases in those communities. Percentage of variant remained low throughout the study period in the majority of the sites tested, however the Toronto sites showed a marked increase from ~25% to ~75% over the study period.\n\nThe results of this study highlight the utility of population level molecular surveillance of SARS-CoV-2 VoC using wastewater. Wastewater monitoring for VoC can be a powerful tool in informing public health responses, including monitoring trends independent of clinical surveillance and providing early warning to communities.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Clarissa Marie Giebel", - "author_inst": "University of Liverpool" - }, - { - "author_name": "Kerry Hanna", - "author_inst": "University of Liverpool" - }, - { - "author_name": "Jacqueline Cannon", - "author_inst": "Lewy Body Society" + "author_name": "Shelley W Peterson", + "author_inst": "Public Health Agency of Canada" }, { - "author_name": "Paul Marlow", - "author_inst": "NIHR ARC NWC" + "author_name": "Ravinder Lidder", + "author_inst": "Public Health Agency of Canada" }, { - "author_name": "Hilary Tetlow", - "author_inst": "NIHR ARC NWC" + "author_name": "Jade Daigle", + "author_inst": "Public Health Agency of Canada" }, { - "author_name": "Stephen Mason", - "author_inst": "University of Liverpool" + "author_name": "Quinn Wonitowy", + "author_inst": "Public Health Agency of Canada" }, { - "author_name": "Justine Shenton", - "author_inst": "Sefton Advocacy" + "author_name": "Audra Nagasawa", + "author_inst": "Statistics Canada" }, { - "author_name": "Manoj Rajagopal", - "author_inst": "Lancashire & South Cumbria NHS Trust" + "author_name": "Michael R Mulvey", + "author_inst": "Public Health Agency of Canada" }, { - "author_name": "Mark Gabbay", - "author_inst": "University of Liverpool" + "author_name": "Chand S Mangat", + "author_inst": "Public Health Agency of Canada" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "geriatric medicine" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2021.05.22.21257660", @@ -739219,35 +738578,83 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.05.21.21257589", - "rel_title": "The risk of SARS-CoV-2 outbreaks in low prevalence settings following the removal of travel restrictions", + "rel_doi": "10.1101/2021.05.20.21257517", + "rel_title": "Public Health and Health Systems Impacts of SARS-CoV-2 Variants of Concern: A Rapid Scoping Review", "rel_date": "2021-05-22", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.21.21257589", - "rel_abs": "Countries around the world have introduced travel restrictions to reduce SARS-CoV-2 transmission. As vaccines are gradually rolled out, attention has turned to when travel restrictions and other non-pharmaceutical interventions (NPIs) can be relaxed. Here, using SARS-CoV-2 as a case study, we develop a mathematical branching process model to assess the risk that, following the removal of NPIs, cases introduced into new locations initiate a local outbreak. Our model accounts for changes in background population immunity due to vaccination. We consider two locations in which the vaccine rollout has progressed quickly - specifically, the Isle of Man (a British crown dependency in the Irish Sea) and the country of Israel. Rather than aiming to make exact quantitative predictions about the outbreak risk in different locations, we instead use data from these locations to demonstrate the general principle that the outbreak risk is unlikely to be eliminated completely when travel restrictions and other NPIs are removed in low prevalence settings. This conclusion holds even once vaccine programmes are completed. Key factors underlying these results are the potential for transmission even following vaccination, incomplete vaccine uptake, and the recent emergence of SARS-CoV-2 variants with increased transmissibility. Combined, these factors suggest that when travel restrictions are relaxed, it will still be necessary to implement surveillance of incoming passengers to identify infected individuals quickly. This measure, as well as tracing and testing (and/or isolating) contacts of detected infected passengers, should remain in place to suppress potential outbreaks until case numbers globally are reduced.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.20.21257517", + "rel_abs": "BackgroundAs of April 2021, three SARS-CoV-2 variants of concern (VOC: B.1.1.7, B.1.351 and P.1) have been detected in over 132 countries. Increased transmissibility of VOC has implications for public health measures and health system arrangements. This rapid scoping review aims to provide a synthesis of current evidence related to public health measures and health system arrangements associated with VOC.\n\nMethodsRapid scoping review. Seven databases were searched up to April 7, 2021 for terms related to VOC, transmission, public health and health systems. A grey literature search was conducted up to April 14, 2021. Title, abstracts and full text were screened independently by two reviewers. Data were double extracted using a standardized form. Studies were included if they reported on at least one of the VOC and public health or health system outcomes.\n\nResultsOf the 2487 articles and 59 grey literature sources retrieved, 37 studies and 21 guidance documents were included. Included studies used a wide range of designs and methods. Most of the studies and guidance documents reported on B.1.1.7, and 18 studies and 4 reports provided data for consideration in relation to public health measures. Public health measures, including lockdowns, physical distancing, testing and contact tracing, were identified as critical adjuncts to a comprehensive vaccination campaign. No studies reported on handwashing or masking procedures related to VOC. For health system arrangements, 17 studies were identified. Some studies found an increase in hospitalization due to B.1.1.7 but no difference in length of stay or ICU admission. Six studies found an increased risk of death ranging from 15-67% with B.1.1.7 compared non-B.1.1.7, but three studies reported no change. One study reported on the effectiveness of personal protective equipment in reducing VOC transmission in the hospital. No studies reported on screening staff and visitors, adjusting service provisions, or adjusting patient accommodations and shared spaces, which is a significant gap in the literature. Guidance documents did not tend to cite any evidence and were thus assumed to be based on expert opinion.\n\nConclusionWhile the findings should be interpreted with caution as most of the sources identified were preprints, findings suggest a combination of non-pharmaceutical interventions (e.g., masking, physical distancing, lockdowns, testing) should be employed alongside a vaccine strategy to improve population and health system outcomes. While the findings are mixed on the impact of VOC on health system arrangements, the evidence is trending towards increased hospitalization and death.", + "rel_num_authors": 16, "rel_authors": [ { - "author_name": "Rahil Sachak-Patwa", - "author_inst": "University of Oxford" + "author_name": "Janet A Curran", + "author_inst": "Dalhousie University" }, { - "author_name": "Helen M Byrne", - "author_inst": "University of Oxford" + "author_name": "Justine Dol", + "author_inst": "Dalhousie University" }, { - "author_name": "Louise Dyson", - "author_inst": "University of Warwick" + "author_name": "Leah Boulos", + "author_inst": "Maritime SPOR Support Unit" }, { - "author_name": "Robin N Thompson", - "author_inst": "University of Oxford" + "author_name": "Mari Somerville", + "author_inst": "Dalhousie University" + }, + { + "author_name": "Bearach Reynolds", + "author_inst": "ESI Fellow" + }, + { + "author_name": "Allyson Gallant", + "author_inst": "Dalhousie University" + }, + { + "author_name": "Lynora Saxinger", + "author_inst": "University of Alberta" + }, + { + "author_name": "Alexander Doroshenko", + "author_inst": "University of Alberta" + }, + { + "author_name": "Danielle Shin", + "author_inst": "Dalhousie University" + }, + { + "author_name": "Helen Wong", + "author_inst": "Dalhousie University" + }, + { + "author_name": "Daniel Crowther", + "author_inst": "Dalhousie University" + }, + { + "author_name": "Marilyn MacDonald", + "author_inst": "Dalhousie University" + }, + { + "author_name": "Ruth Martin-Misener", + "author_inst": "Dalhousie University" + }, + { + "author_name": "Jill Hayden", + "author_inst": "Dalhousie University" + }, + { + "author_name": "Jeannette Comeau", + "author_inst": "IWK Health Centre" + }, + { + "author_name": "Holly McCulloch", + "author_inst": "IWK Health Centre" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "public and global health" }, { "rel_doi": "10.1101/2021.05.19.21257311", @@ -741165,33 +740572,41 @@ "category": "endocrinology" }, { - "rel_doi": "10.1101/2021.05.20.21257556", - "rel_title": "A 2SIR-VD Model for Optimizing Geographical COVID-19 Vaccine Distribution in the Philippines", + "rel_doi": "10.1101/2021.05.19.21257474", + "rel_title": "Short Telomeres and a T-Cell Shortfall in COVID-19: The Aging Effect", "rel_date": "2021-05-21", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.20.21257556", - "rel_abs": "COVID-19 is a novel respiratory disease first identified in Wuhan, China, that is caused by the novel coronavirus, SARS-CoV-2. It has triggered a global pandemic of historic proportions. The government of the Philippines began its national vaccine drive on March 1, 2021, with the goal of vaccinating seventy million of its citizens by the end of the calendar year. To determine the optimum geographical distribution strategy in the Philippines for the limited supply of vaccines that is currently available, we developed and adapted a basic SIR model that allows us to understand the evolution of a pandemic when public health authorities are vaccinating two susceptible populations within a country with different vaccine rates. Our analysis with our 2SIR-VD model revealed that prioritizing vaccine deployment to the National Capital Region (NCR) of the Philippines minimized the number of COVID-19 cases in the country. We therefore recommend deploying 90% of the available vaccine supply to the NCR to mitigate viral transmission there. The remaining 10% would allow the rest of the archipelago to vaccinate all of their senior citizens, thus shielding this vulnerable population against severe disease and death from COVID-19.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.19.21257474", + "rel_abs": "The slow pace of global vaccination and the rapid emergence of SARS-CoV-2 variants suggest recurrent waves of COVID-19 in coming years. Therefore, understanding why deaths from COVID-19 are highly concentrated among older adults is essential for global health. Severe COVID-19 T-cell lymphopenia is more common among older adults, and it entails poor prognosis. Much about the primary etiology of this form of lymphopenia remains unknown, but regardless of its causes, offsetting the decline in T-cell count during SARS-CoV-2 infection demands fast and massive T-cell clonal expansion, which is telomere length (TL)-dependent. We have built a model that captures the effect of age-dependent TL shortening in hematopoietic cells and its effect on T-cell clonal expansion capacity. The model shows that an individual with average hematopoietic cell TL (HCTL) at age twenty years maintains maximal T-cell clonal expansion capacity until the 6th decade of life when this capacity plummets by more than 90% over the next ten years. The collapse coincides with the steep increase in COVID-19 mortality with age. HCTL metrics may thus explain the vulnerability of older adults to COVID-19. That said, the wide inter-individual variation in HCTL across the general population means that some younger adults with inherently short HCTL might be at risk of severe COVID-19 lymphopenia and mortality from the disease.\n\nSignificance StatementDeclining immunity with advancing age is a general explanation for the increased mortality from COVID-19 among older adults. This mortality far exceeds that from viral illnesses such as the seasonal influenza, and it thus requires specific explanations. One of these might be diminished ability with age to offset the development of severe T-cell lymphopenia (a low T-cell count in the blood) that often complicates COVID-19. We constructed a model showing that age-dependent shortening of telomeres might constrain the ability of T-cells of some older COVID-19 patients to undertake the massive proliferation required to clear the virus that causes the infection. The model predicts that individuals with short telomeres, principally seniors, might be at a higher risk of death from COVID-19.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Allan Paolo Almajose", - "author_inst": "University of the Philippines - Diliman" + "author_name": "James J Anderson", + "author_inst": "University of Washington" }, { - "author_name": "Angus White", - "author_inst": "Providence College" + "author_name": "Ezra Susser", + "author_inst": "Columbia University" }, { - "author_name": "Chelsea Diego", - "author_inst": "University of Santo Tomas" + "author_name": "Konstantin G Arbeev", + "author_inst": "Duke University" }, { - "author_name": "Red Lazaro", - "author_inst": "University of Santo Tomas" + "author_name": "Anatoliy I Yashin", + "author_inst": "Duke University" }, { - "author_name": "Nicanor Austriaco", - "author_inst": "University of Santo Tomas" + "author_name": "Daniel Levy", + "author_inst": "NIH/National Heart, Lung, and Blood Institute" + }, + { + "author_name": "Simon Verhulst", + "author_inst": "University of Groningen" + }, + { + "author_name": "Abraham Aviv", + "author_inst": "Rutgers, The State University of New Jersey" } ], "version": "1", @@ -743003,103 +742418,47 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2021.05.20.444848", - "rel_title": "Alum:CpG adjuvant enables SARS-CoV-2 RBD-induced protection in aged mice and synergistic activation of human elder type 1 immunity", + "rel_doi": "10.1101/2021.05.19.444889", + "rel_title": "An AAV-ie based Vaccine effectively protects against SARS-CoV-2 and Circulating Variants", "rel_date": "2021-05-20", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.05.20.444848", - "rel_abs": "Global deployment of vaccines that can provide protection across several age groups is still urgently needed to end the COVID-19 pandemic especially for low- and middle-income countries. While vaccines against SARS-CoV-2 based on mRNA and adenoviral-vector technologies have been rapidly developed, additional practical and scalable SARS-CoV-2 vaccines are needed to meet global demand. In this context, protein subunit vaccines formulated with appropriate adjuvants represent a promising approach to address this urgent need. Receptor-binding domain (RBD) is a key target of neutralizing antibodies (Abs) but is poorly immunogenic. We therefore compared pattern recognition receptor (PRR) agonists, including those activating STING, TLR3, TLR4 and TLR9, alone or formulated with aluminum hydroxide (AH), and benchmarked them to AS01B and AS03-like emulsion-based adjuvants for their potential to enhance RBD immunogenicity in young and aged mice. We found that the AH and CpG adjuvant formulation (AH:CpG) demonstrated the highest enhancement of anti-RBD neutralizing Ab titers in both age groups ([~]80-fold over AH), and protected aged mice from the SARS-CoV-2 challenge. Notably, AH:CpG-adjuvanted RBD vaccine elicited neutralizing Abs against both wild-type SARS-CoV-2 and B.1.351 variant at serum concentrations comparable to those induced by the authorized mRNA BNT162b2 vaccine. AH:CpG induced similar cytokine and chemokine gene enrichment patterns in the draining lymph nodes of both young adult and aged mice and synergistically enhanced cytokine and chemokine production in human young adult and elderly mononuclear cells. These data support further development of AH:CpG-adjuvanted RBD as an affordable vaccine that may be effective across multiple age groups.\n\nOne Sentence SummaryAlum and CpG enhance SARS-CoV-2 RBD protective immunity, variant neutralization in aged mice and Th1-polarizing cytokine production by human elder leukocytes.", - "rel_num_authors": 21, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.05.19.444889", + "rel_abs": "Prophylactic vaccines against SARS-CoV-2 have been extensively developed globally to overcome the COVID-19 pandemic. However, recently emerging SARS-CoV-2 variants B.1.1.7 and B.1.351 limit the vaccine protection effects and successfully escape antibody cocktail treatment. Herein, based on our previously engineered adeno-associated viral (AAV) vector, AAV-ie, and systematic immunogen screening, we developed an AAV-ie-S1 vaccine with thermostability, high efficiency, safety, and single-dose vaccination advantage. Importantly, the AAV-ie-S1 immune sera efficiently neutralize B.1.1.7 and B.1.351, indicating a potential to circumvent the spreading of SARS-CoV-2.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Marisa E. McGrath", - "author_inst": "Department of Microbiology and Immunology, University of Maryland School of Medicine" - }, - { - "author_name": "Robert E. Haupt", - "author_inst": "Department of Microbiology and Immunology, University of Maryland School of Medicine" - }, - { - "author_name": "Hyuk-Soo Seo", - "author_inst": "Department of Cancer Biology, Dana-Farber Cancer Institute" - }, - { - "author_name": "Kijun Song", - "author_inst": "Department of Cancer Biology, Dana-Farber Cancer Institute" - }, - { - "author_name": "Andrew Z. Xu", - "author_inst": "Department of Cancer Biology, Dana-Farber Cancer Institute" - }, - { - "author_name": "Timothy M. Caradonna", - "author_inst": "Ragon Institute of MGH, MIT, and Harvard" - }, - { - "author_name": "Jared Feldman", - "author_inst": "Ragon Institute of MGH, MIT, and Harvard" - }, - { - "author_name": "Blake M. Hauser", - "author_inst": "Ragon Institute of MGH, MIT, and Harvard" - }, - { - "author_name": "Aaron G. Schmidt", - "author_inst": "Ragon Institute of MGH, MIT, and Harvard" - }, - { - "author_name": "Robert K. Ernst", - "author_inst": "Department of Microbial Pathogenesis, University of Maryland School of Dentistry" - }, - { - "author_name": "Carly Dillen", - "author_inst": "Department of Microbiology and Immunology, University of Maryland School of Medicine" - }, - { - "author_name": "Stuart M. Weston", - "author_inst": "Department of Microbiology and Immunology, University of Maryland School of Medicine" - }, - { - "author_name": "Robert M. Johnson", - "author_inst": "Department of Microbiology and Immunology, University of Maryland School of Medicine" - }, - { - "author_name": "Holly L. Hammond", - "author_inst": "Department of Microbiology and Immunology, University of Maryland School of Medicine" + "author_name": "Simeng Zhao", + "author_inst": "iHuman Institute, ShanghaiTech University" }, { - "author_name": "Romana Mayer", - "author_inst": "Department of Pathology, University of Maryland Medical Center" + "author_name": "Fangzhi Tan", + "author_inst": "iHuman Institute, ShanghaiTech University" }, { - "author_name": "Allen Burke", - "author_inst": "Department of Pathology, University of Maryland Medical Center" + "author_name": "Junzi Ke", + "author_inst": "iHuman Institute, ShanghaiTech University" }, { - "author_name": "Aiquan Chang", - "author_inst": "Center for Virology and Vaccine Research, Beth Israel Deaconess Medical Center" + "author_name": "Jie Yang", + "author_inst": "iHuman Institute, ShanghaiTech University" }, { - "author_name": "Jingyou Yu", - "author_inst": "Center for Virology and Vaccine Research, Beth Israel Deaconess Medical Center" + "author_name": "Chao-bo Lin", + "author_inst": "School of Life Science and Technology, ShanghaiTech University" }, { - "author_name": "Dan H. Barouch", - "author_inst": "Center for Virology and Vaccine Research, Beth Israel Deaconess Medical Center" + "author_name": "Haopeng Wang", + "author_inst": "School of Life Science and Technology, ShanghaiTech University" }, { - "author_name": "Sirano Dhe-Paganon", - "author_inst": "Department of Cancer Biology, Dana-Farber Cancer Institute" - }, - { - "author_name": "Matthew Frieman", - "author_inst": "Department of Microbiology and Immunology, University of Maryland School of Medicine" + "author_name": "guisheng zhong", + "author_inst": "iHuman institute" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "new results", - "category": "immunology" + "category": "microbiology" }, { "rel_doi": "10.1101/2021.05.20.445008", @@ -744845,31 +744204,35 @@ "category": "pharmacology and toxicology" }, { - "rel_doi": "10.1101/2021.05.17.20249000", - "rel_title": "Virtually in Synch: A Pilot Study on Affective Dimensions of Dancing with Parkinson's during COVID- 19", - "rel_date": "2021-05-19", + "rel_doi": "10.1101/2021.05.14.21257209", + "rel_title": "Prediction of the effective reproduction number of COVID-19 in Greece. A machine learning approach using Google mobility data.", + "rel_date": "2021-05-18", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.17.20249000", - "rel_abs": "Loss of social supports and community programs due to lockdowns and other measures associated with COVID-19 has been linked with concerns over mental health and feelings of isolation. These challenges can be particularly acute for the elderly and people living with chronic or pervasive health conditions. Dance for PD, a program specifically developed for people living with Parkinsons Disease, formerly offered in hundreds of locations around the globe, either halted or shifted to a virtual format. Our study investigates the transition of these dance-based programs to an online environment, with the aim of determining the extent to which a virtual format provides affective support or other benefits. Given the increased incidence of mental health problems and social isolation associated with COVID-19, this investigation aims to contribute to the development of better supports for vulnerable populations while helping us understand the specific contributions of dance-based programs in a virtual environment.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.14.21257209", + "rel_abs": "This paper demonstrates how a short-term prediction of the effective reproduction number (Rt) of COVID-19 in regions of Greece is achieved based on online mobility data. Various machine learning methods are applied to predict Rt and attribute importance analysis is performed to reveal the most important variables that affect the accurate prediction of Rt. Our results are based on an ensemble of diverse Rt methodologies to provide non-precautious and non-indulgent predictions. The model demonstrates robust results and the methodology overall represents a promising approach towards COVID-19 outbreak prediction. This paper can help health related authorities when deciding non-nosocomial interventions to prevent the spread of COVID-19.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Katayoun Ghanai", - "author_inst": "York University" + "author_name": "Athanasios Arvanitis", + "author_inst": "Environmental Informatics Research Group, School of Mechanical Engineering, Aristotle University of Thessaloniki, 54124 Thessaloniki, Box 483, Greece" }, { - "author_name": "Rebecca E Barnstaple", - "author_inst": "York University" + "author_name": "Irini Furxhi", + "author_inst": "Dept. of Accounting and Finance, Kemmy Business School, University of Limerick, Ireland. V94PH93" }, { - "author_name": "Joseph FX DeSouza", - "author_inst": "York University" + "author_name": "Thomas Tasioulis", + "author_inst": "Environmental Informatics Research Group, School of Mechanical Engineering, Aristotle University of Thessaloniki, 54124 Thessaloniki, Box 483, Greece" + }, + { + "author_name": "Konstantinos Karatzas", + "author_inst": "Environmental Informatics Research Group, School of Mechanical Engineering, Aristotle University of Thessaloniki, 54124 Thessaloniki, Box 483, Greece" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "rehabilitation medicine and physical therapy" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2021.05.14.21257234", @@ -748143,77 +747506,29 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.05.12.21257120", - "rel_title": "Performance evaluation of the BD SARS-CoV-2 reagents for the BD MAX\u2122 system", + "rel_doi": "10.1101/2021.05.08.21256896", + "rel_title": "Epidemiological characteristics and incubation period of SARS-CoV-2 during the 2020-2021 winter pandemic wave in north China: an observational study", "rel_date": "2021-05-18", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.12.21257120", - "rel_abs": "BackgroundThe RT-qPCR assay for detecting SARS-CoV-2 virus is the favorable approach to test suspected COVID-19 cases. However, discordant results can occur when two or more assays are compared. Variability in analytical sensitivities between assays, among other factors, may account for these differences in reporting.\n\nMethodsThe limits of detection (LOD) for the BD SARS-CoV-2 Reagents for BD MAX System (\"MAX SARS-CoV-2 assay\"), the Biomerieux BioFire(R) Respiratory Panel 2.1 (\"BioFire SARS-CoV-2 assay\"), the Roche cobas SARS-CoV-2 assay (\"cobas SARS-CoV-2 assay\"), and the Hologic Aptima(R) SARS-CoV-2 assay Panther(R) (\"Aptima SARS-CoV-2 assay\") RT-qPCR systems were determined using a total of 84 contrived nasopharyngeal specimens with seven target levels for each comparator. The positive and negative percent agreement (PPA and NPA, respectively) for the MAX SARS-CoV-2 assay were compared to the Aptima SARS-CoV-2 assay in a post-market clinical study utilizing 708 paired nasopharyngeal specimens collected from suspected COVID-19 cases. Discordant results were further tested by the cobas and BioFire SARS-CoV-2 assays.\n\nResultsThe measured LOD for the MAX SARS-CoV-2 assay (251 copies/mL) was comparable to the cobas SARS-CoV-2 assay (298 copies/mL) and the BioFire SARS-CoV-2 assay (302 copies/mL); the Aptima SARS-CoV-2 assay had a LOD of 612 copies/mL. The MAX SARS-CoV-2 assay had a PPA of 100% (95%CI: [97.3%-100.0%]) and a NPA of 96.7% (95%CI: [94.9%-97.9%]) when compared to the Aptima SARS-CoV-2 assay.\n\nConclusionsThe MAX SARS-CoV-2 assay exhibited a high analytical sensitivity and specificity for SARS-CoV-2 detection. The clinical performance of the MAX SARS-CoV-2 assay agreed with another sensitive EUA cleared assay.", - "rel_num_authors": 15, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.08.21256896", + "rel_abs": "As the emergence of new variants of SARS-CoV-2 persists across the world, it is of importance to understand the distributional behavior of incubation period of the variants for both medical research and public health policy-making. We collected the published individual level data of 941 patients of the 2020-2021 winter pandemic wave in Hebei province, north China. We computed some epidemiological characteristics of the wave and estimated the distribution of the incubation period. We further assessed the covariate effects of sex, age and living with a case with respect to incubation period by a model. The infection-fatality rate was only 0.1%. The estimated median incubation period was at least 22 days, significantly extended from the estimates (ranging from 4 to 8.5 days) of the previous wave in mainland China and those ever reported elsewhere around the world. The proportion of asymptomatic patients was 90.6%. No significant covariate effect was found. The distribution of incubation period of the new variants showed a clear extension from their early generations.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Karen Yanson", - "author_inst": "Becton, Dickinson and Company" - }, - { - "author_name": "William LaViers", - "author_inst": "Becton, Dickinson and Company" - }, - { - "author_name": "Lori Neely", - "author_inst": "Becton, Dickinson and Company" - }, - { - "author_name": "Elizabeth Lockamy", - "author_inst": "Becton, Dickinson and Company" - }, - { - "author_name": "Luis Carlos Castillo-Hernandez", - "author_inst": "CTMD Research" - }, - { - "author_name": "Christopher Oldfied", - "author_inst": "Fellows Research Alliance, Inc" - }, - { - "author_name": "Ron Ackerman", - "author_inst": "Comprehensive Clinical Trials" - }, - { - "author_name": "Jamie Ackerman", - "author_inst": "Comprehensive Clinical Research, LLC" - }, - { - "author_name": "Daniel Ortiz", - "author_inst": "Beaumont Health" - }, - { - "author_name": "Sixto Pacheco", - "author_inst": "BioCollections Worldwide Inc" - }, - { - "author_name": "Patricia Simner", - "author_inst": "Johns Hopkins University School of Medicine" - }, - { - "author_name": "Stephen Young", - "author_inst": "TriCore Reference Laboratories" - }, - { - "author_name": "Erin McElvania", - "author_inst": "NorthShore University HealthSystem" + "author_name": "Tiantian Liu", + "author_inst": "East China Normal University" }, { - "author_name": "Yu-Chih Lin", - "author_inst": "Becton, Dickinson and Company" + "author_name": "Zijian Chen", + "author_inst": "East China Normal University" }, { - "author_name": "Charles Cooper", - "author_inst": "Becton, Dickinson and Company" + "author_name": "Jin Xu", + "author_inst": "East China Normal University" } ], "version": "1", - "license": "cc_by", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -750081,77 +749396,89 @@ "category": "health informatics" }, { - "rel_doi": "10.1101/2021.05.11.21257004", - "rel_title": "SARS-CoV-2 R.1 lineage variants prevailed in Tokyo in March 2021", + "rel_doi": "10.1101/2021.05.11.21256972", + "rel_title": "SARS-CoV-2 mRNA vaccines induce a greater array of spike-specific antibody isotypes with more potent complement binding capacity than natural infection", "rel_date": "2021-05-17", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.11.21257004", - "rel_abs": "BackgroundThe spread of SARS-CoV-2 variants, such as B.1.1.7 and B.1.351, has become a crucial issue worldwide. Therefore, we began testing all patients with COVID-19 for the N501Y and E484K mutations associated with SARS-CoV-2.\n\nStudy designNasopharyngeal swab samples from 108 patients who visited our hospital between February and April 2021 were analyzed. The samples were analyzed using reverse transcription-polymerase chain reaction with melting curve analysis to detect the N501Y and E484K mutations. A part of the samples were also subjected to whole genome sequencing. Clinical parameters such as mortality and admission to the intensive care unit were analyzed to examine the association between increased disease severity and the E484K mutation.\n\nResultsThe ratio of cases showing the 501N+484K mutation rapidly increased from 8% in February to 46% in March. Whole genome sequencing revealed that the viruses with 501N+484K mutation are R.1 lineage variants. Evidence of increased disease severity related to the R.1 variants were not found.\n\nConclusionsWe found that the R.1 lineage variants rapidly prevailed in Tokyo in March 2021.", - "rel_num_authors": 15, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.11.21256972", + "rel_abs": "Antibodies (Abs) are essential for the host immune response against SARS-CoV-2, and all the vaccines developed so far have been designed to induce Abs targeting the SARS-CoV-2 spike. Many studies have examined Ab responses in the blood from vaccinated and infected individuals. However, since SARS-CoV-2 is a respiratory virus, it is also critical to understand the mucosal Ab responses at the sites of initial virus exposure. Here, we examined plasma versus saliva Ab responses in vaccinated and convalescent patients. Although saliva levels were significantly lower, a strong correlation was observed between plasma and saliva total Ig levels against all SARS-CoV-2 antigens tested. Virus-specific IgG1 responses predominated in both saliva and plasma, while a lower prevalence of IgM and IgA1 Abs was observed in saliva. Antiviral activities of plasma Abs were also studied. Neutralization titers against the initial WA1 (D614G), B.1.1.7 (alpha) and B.1.617.2 (delta) strains were similar but lower against the B.1.351 (beta) strain. Spike-specific antibody-dependent cellular phagocytosis (ADCP) activities were also detected and the levels correlated with spike-binding Ig titers. Interestingly, while neutralization and ADCP potencies of vaccinated and convalescent groups were comparable, enhanced complement deposition to spike-specific Abs was noted in vaccinated versus convalescent groups and corresponded with higher levels of IgG1 plus IgG3 among the vaccinated individuals. Altogether, this study demonstrates the detection of Ab responses after vaccination or infection in plasma and saliva that correlate significantly, although Ig isotypic differences were noted. The induced plasma Abs displayed Fab-mediated and Fc-dependent functions with comparable neutralization and ADCP potencies, but a greater capacity to activate complement was elicited upon vaccination.", + "rel_num_authors": 18, "rel_authors": [ { - "author_name": "Katsutoshi Nagano", - "author_inst": "Tokyo Medical and Dental University" + "author_name": "J\u00e9romine Klingler", + "author_inst": "Division of Infectious Diseases, Department of Medicine, Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Chihiro Tani-Sassa", - "author_inst": "Tokyo Medical and Dental University" + "author_name": "Gregory S Lambert", + "author_inst": "Division of Infectious Diseases, Department of Medicine, Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Yumi Iwasaki", - "author_inst": "Tokyo Medical and Dental University" + "author_name": "Vincenza Itri", + "author_inst": "Division of Infectious Diseases, Department of Medicine, Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Yuna Takatsuki", - "author_inst": "Tokyo Medical and Dental University" + "author_name": "Sean Liu", + "author_inst": "Division of Infectious Diseases, Department of Medicine, Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Sonoka Yuasa", - "author_inst": "Tokyo Medical and Dental University" + "author_name": "Juan C Bandres", + "author_inst": "James J. Peters VA Medical Center" }, { - "author_name": "Yuta Takahashi", - "author_inst": "Tokyo Medical and Dental University" + "author_name": "Gospel Enyindah-Asonye", + "author_inst": "Division of Infectious Diseases, Department of Medicine, Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Jun Nakajima", - "author_inst": "Tokyo Medical and Dental University" + "author_name": "Xiaomei Liu", + "author_inst": "Division of Infectious Diseases, Department of Medicine, Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Kazunari Sonobe", - "author_inst": "Tokyo Medical and Dental University" + "author_name": "Viviana Simon", + "author_inst": "Icahn School of Medicine" }, { - "author_name": "Naoya Ichimura", - "author_inst": "Tokyo Medical and Dental University" + "author_name": "Charles R Gleason", + "author_inst": "Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Yoko Nukui", - "author_inst": "Tokyo Medical and Dental University" + "author_name": "Giulio Kleiner", + "author_inst": "Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Hiroaki Takeuchi", - "author_inst": "Tokyo Medical and Dental University" + "author_name": "Hsin-Ping Chiu", + "author_inst": "Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Kousuke Tanimoto", - "author_inst": "Tokyo Medical and Dental University" + "author_name": "Chuan-Tien Hung", + "author_inst": "Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Yukie Tanaka", - "author_inst": "Tokyo Medical and Dental University" + "author_name": "Shreyas Kowdle", + "author_inst": "Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Akinori Kimura", - "author_inst": "Tokyo Medical and Dental University" + "author_name": "Fatima Amanat", + "author_inst": "Department of Microbiology, Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Shuji Tohda", - "author_inst": "Tokyo Medical and Dental University" + "author_name": "Benhur Lee", + "author_inst": "Department of Microbiology, Icahn School of Medicine at Mount Sinai" + }, + { + "author_name": "Susan Zolla-Pazner", + "author_inst": "Icahn School of Medicine at Mount Sinai" + }, + { + "author_name": "Chitra Upadhyay", + "author_inst": "Division of Infectious Diseases, Department of Medicine, Icahn School of Medicine at Mount Sinai" + }, + { + "author_name": "Catarina E Hioe", + "author_inst": "Icahn School of Medicine at Mount Sinai" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -752111,39 +751438,47 @@ "category": "scientific communication and education" }, { - "rel_doi": "10.1101/2021.05.16.444344", - "rel_title": "Key informant perceptions on wildlife hunting in India during the COVID-19 lockdown", - "rel_date": "2021-05-17", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.05.16.444344", - "rel_abs": "Lockdowns intended to control the COVID-19 pandemic resulted in major socioeconomic upheavals across the world. While there were numerous reports of these lockdowns benefiting wildlife by reducing human movement and habitat disturbance, increased hunting during these lockdowns emerged as a conservation concern, particular in tropical Asia and Africa. We used online interviews with key informants including wildlife researchers, enforcement staff and NGO employees (N=99), and media reports (N=98), to examine the impacts of Indias COVID-19 lockdown (March-May 2020) on wildlife hunting across the country. We asked whether and how hunting patterns changed during the lockdown, and explored socioeconomic and institutional factors underlying these changes. Over half the interviewees spread over 43 administrative districts perceived hunting (mammals, in particular) to have increased during the lockdown relative to a pre-lockdown reference period. Interviewees identified household consumption (53% of respondents) and sport and recreation (34%) as main motivations for hunting during the lockdown, and logistical challenges for enforcement (36%), disruption of food supply (32%), and need for recreational opportunities (32%) as key factors associated with hunting during this period. These insights were corroborated by statements by experts extracted from media articles. Collectively, our findings suggest that the COVID-19 lockdown potentially increased hunting across much of India, and emphasize the role of livelihood and food security in mitigating threats to wildlife during such periods of acute socioeconomic perturbation.", - "rel_num_authors": 5, + "rel_doi": "10.1101/2021.05.13.21256857", + "rel_title": "A Predictive Modelling Framework for COVID-19 Transmission to Inform the Management of Mass Events", + "rel_date": "2021-05-16", + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.13.21256857", + "rel_abs": "Modelling COVID-19 transmission at live events and public gatherings is essential to evaluate and control the probability of subsequent outbreaks. Model estimates can be used to inform event organizers about the possibility of super-spreading and the predicted efficacy of safety protocols, as well as to communicate to participants their personalised risk so that they may choose whether to attend. Yet, despite the fast-growing body of literature on COVID transmission dynamics, current risk models either neglect contextual information on vaccination rates or disease prevalence or do not attempt to quantitatively model transmission, thus limiting their potential to provide insightful estimates. This paper attempts to bridge this gap by providing informative risk metrics for live public events, along with a measure of their associated uncertainty. Starting with a thorough review of the literature and building upon existing models, our approach ties together three main components: (a) reliable modelling of the number of infectious cases at the time of the event, (b) evaluation of the efficiency of pre-event screening and risk mitigation protocols, and (c) modelling the transmission dynamics during the event. We demonstrate how uncertainty in the input parameters can be included in the model using Monte Carlo simulations. We discuss the underlying assumptions and limitations of our approach and implications for policy around live events management.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Uttara Mendiratta", - "author_inst": "WCS-India" + "author_name": "Claire Donnat", + "author_inst": "University of Chicago" }, { - "author_name": "Munib Khanyari", - "author_inst": "Nature Conservation Foundation" + "author_name": "Freddy Bunbury", + "author_inst": "Carnegie Institution for Science" }, { - "author_name": "Nandini Velho", - "author_inst": "Srishti Manipal Institute of Art, Design, Law and Technology" + "author_name": "Jack Kreindler", + "author_inst": "Imperial College London" }, { - "author_name": "Kulbhushansingh Suryawanshi", - "author_inst": "Nature Conservation Foundation" + "author_name": "Filippos T. Filippidis", + "author_inst": "Imperial College London" }, { - "author_name": "Nirmal U. Kulkarni", - "author_inst": "WCS-India" + "author_name": "Austen El-Osta", + "author_inst": "Imperial College London" + }, + { + "author_name": "Tonu Esko", + "author_inst": "University of Tartu" + }, + { + "author_name": "Matthew Harris", + "author_inst": "Imperial College London" } ], "version": "1", - "license": "cc_by", - "type": "new results", - "category": "ecology" + "license": "cc_by_nc_nd", + "type": "PUBLISHAHEADOFPRINT", + "category": "health policy" }, { "rel_doi": "10.1101/2021.05.13.21257088", @@ -754180,137 +753515,121 @@ "category": "psychiatry and clinical psychology" }, { - "rel_doi": "10.1101/2021.05.11.443572", - "rel_title": "Siglec-1 on dendritic cells mediates SARS-CoV-2 trans-infection of target cells while on macrophages triggers proinflammatory responses", + "rel_doi": "10.1101/2021.05.14.444205", + "rel_title": "Common Mechanism of SARS-CoV and SARS-CoV-2 Pathogenesis across Species", "rel_date": "2021-05-14", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.05.11.443572", - "rel_abs": "COVID-19 pandemic is not yet under control by vaccination, and effective antivirals are critical for preparedness. Here we report that macrophages and dendritic cells, key antigen presenting myeloid cells (APCs), are largely resistant to SARS-CoV-2 infection. APCs effectively captured viruses within cellular compartments that lead to antigen degradation. Macrophages sense SARS-CoV-2 and released higher levels of cytokines, including those related to cytokine storm in severe COVID-19. The sialic acid-binding Ig-like lectin 1 (Siglec-1/CD169) present on APCs, which interacts with sialylated gangliosides on membranes of retroviruses or filoviruses, also binds SARS-CoV-2 via GM1. Blockage of Siglec-1 receptors by monoclonal antibodies reduces SARS-CoV-2 uptake and transfer to susceptible target cells. APCs expressing Siglec-1 and carrying SARS-CoV-2 are found in pulmonary tissues of non-human primates. Single cell analysis reveals the in vivo induction of cytokines in those macrophages. Targeting Siglec-1 could offer cross-protection against SARS-CoV-2 and other enveloped viruses that exploit APCs for viral dissemination, including those yet to come in future outbreaks.", - "rel_num_authors": 30, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.05.14.444205", + "rel_abs": "Sarbecovirus (CoV) infections, including Severe Acute Respiratory CoV (SARS-CoV) and SARS-CoV-2, are considerable human threats. Human GWAS studies have recently identified loci associated with variation in SARS-CoV-2 susceptibility. However, genetically tractable models that reproduce human CoV disease outcomes are needed to mechanistically evaluate genetic determinants of CoV susceptibility. We used the Collaborative Cross (CC) and human GWAS datasets to elucidate host susceptibility loci that regulate CoV infections and to identify host quantitative trait loci that modulate severe CoV and pan-CoV disease outcomes including a major disease regulating loci including CCR9. CCR9 ablation resulted in enhanced titer, weight loss, respiratory dysfunction, mortality, and inflammation, providing mechanistic support in mitigating protection from severe SARS-CoV-2 pathogenesis across species. This study represents a comprehensive analysis of susceptibility loci for an entire genus of human pathogens conducted, identifies a large collection of susceptibility loci and candidate genes that regulate multiple aspects type-specific and cross-CoV pathogenesis, and also validates the paradigm of using the CC platform to identify common cross-species susceptibility loci and genes for newly emerging and pre-epidemic viruses.", + "rel_num_authors": 26, "rel_authors": [ { - "author_name": "Daniel Perez-Zsolt", - "author_inst": "Irsicaixa" - }, - { - "author_name": "Jordana Munoz Basagoiti", - "author_inst": "IrsiCaixa" - }, - { - "author_name": "Jordi Rodo", - "author_inst": "IRTA-CRESA" - }, - { - "author_name": "Marc Elousa", - "author_inst": "CNAG CRG, Centre for Genomic Regulation (CRG)" - }, - { - "author_name": "Dalia Raich Regue", - "author_inst": "IrsiCaixa" + "author_name": "Alexandra Schafer", + "author_inst": "University of North Carolina at Chapel Hill, Chapel Hill, NC" }, { - "author_name": "Critina Risco", - "author_inst": "Centro Nacional de Biotecnologia, CSIC" + "author_name": "Lisa E. Gralinski", + "author_inst": "University of North Carolina at Chapel Hill, Chapel Hill, NC" }, { - "author_name": "Martin Sachse", - "author_inst": "Centro Nacional de Biotecnologia, CSIC" + "author_name": "Sarah R. Leist", + "author_inst": "University of North Carolina at Chapel Hill, Chapel Hill, NC" }, { - "author_name": "Maria Pino", - "author_inst": "Division of Microbiology and Immunology, Yerkes National Primate Research Center, Emory University" + "author_name": "Emma S. Winkler", + "author_inst": "Washington University School of Medicine, St. Louis, MO" }, { - "author_name": "Sanjeev Gumber", - "author_inst": "Division of Microbiology and Immunology, Yerkes National Primate Research Center, Emory University" + "author_name": "Brea K. Hampton", + "author_inst": "University of North Carolina at Chapel Hill" }, { - "author_name": "Mirko Paiardini", - "author_inst": "Emory University" + "author_name": "Michael A. Mooney", + "author_inst": "Oregon Health & Science University, Portland, OR" }, { - "author_name": "Jakub Chojnacki", - "author_inst": "IrsiCaixa AIDS Research Institute" + "author_name": "Kara L. Jensen", + "author_inst": "University of North Carolina at Chapel Hill, Chapel Hill, NC" }, { - "author_name": "Itziar Erkizia", - "author_inst": "AIDS research Institute, Irsicaixa" + "author_name": "Rachel L. Graham", + "author_inst": "University of North Carolina at Chapel Hill, Chapel Hill, NC" }, { - "author_name": "Xabier Muniz", - "author_inst": "IrsiCaixa AIDS Research Institute" + "author_name": "Sudhakar Agnihothram", + "author_inst": "University of North Carolina at Chapel Hill, Chapel Hill, NC" }, { - "author_name": "Ester Ballana", - "author_inst": "IrsiCaixa AIDS Research Institute" + "author_name": "Sophia Jeng", + "author_inst": "Oregon Health & Science University, Portland, OR" }, { - "author_name": "Eva Riveira Munoz", - "author_inst": "IrsiCaixa AIDS Research Institute" + "author_name": "Steven Chamberlin", + "author_inst": "Oregon Health & Science University, Portland, OR" }, { - "author_name": "Marc Noguera-Julian", - "author_inst": "irsiCaixa Institute for AIDS research" + "author_name": "Timothy A. Bell", + "author_inst": "University of North Carolina at Chapel Hill, Chapel Hill, NC" }, { - "author_name": "Roger Paredes", - "author_inst": "IrsiCaixa AIDS Research Institute" + "author_name": "D. Trevor Scobey", + "author_inst": "University of North Carolina at Chapel Hill, Chapel Hill, NC" }, { - "author_name": "Benjamin Trinite", - "author_inst": "IrsiCaixa AIDS Research Institute" + "author_name": "Laura A. VanBlargan", + "author_inst": "Washington University School of Medicine, St. Louis, MO" }, { - "author_name": "Ferran Tarres Freixas", - "author_inst": "IrsiCaixa AIDS Research Institute" + "author_name": "Larissa B. Thackray", + "author_inst": "Washington University School of Medicine, St. Louis, MO" }, { - "author_name": "Ignacio Blanco", - "author_inst": "Hospital Germans Trias i Pujol" + "author_name": "Pablo Hock", + "author_inst": "University of North Carolina at Chapel Hill, ChapelHill, NC" }, { - "author_name": "Victor Guallar", - "author_inst": "Barcelona Supercomputing Center" + "author_name": "Darla R. Miller", + "author_inst": "University of North Carolina at Chapel Hill, Chapel Hill, NC" }, { - "author_name": "Jorge Carrillo", - "author_inst": "Institut de Recerca de la SIDA irsiCaixa" + "author_name": "Ginger D. Shaw", + "author_inst": "University of North Carolina at Chapel Hill, Chapel Hill, NC" }, { - "author_name": "Julia Blanco", - "author_inst": "Institut de Recerca de la SIDA irsiCaixa" + "author_name": "Fernando Pardo Manuel de Villena", + "author_inst": "University of North Carolina at Chapel Hill, Chapel Hill, NC" }, { - "author_name": "Amalio Telenti", - "author_inst": "The Scripps Research Institute" + "author_name": "Shannon K. McWeeney", + "author_inst": "Oregon Health & Science University, Portland, OR" }, { - "author_name": "Holger Heyn", - "author_inst": "CNAG-CRG" + "author_name": "Stephanie A. Montgomery", + "author_inst": "University of North Carolina at Chapel Hill, Chapel Hill, NC" }, { - "author_name": "Joaquim Segales", - "author_inst": "IRTA-CReSA" + "author_name": "Michael S. Diamond", + "author_inst": "Washington University School of Medicine, St. Louis, MO" }, { - "author_name": "Bonaventura Clotet", - "author_inst": "AIDS Research Institute IrsiCaixa" + "author_name": "Mark T. Heise", + "author_inst": "University of North Carolina at Chapel Hill, Chapel Hill, NC" }, { - "author_name": "Javier Martinez-Picado", - "author_inst": "IrsiCaixa AIDS Research Institute" + "author_name": "Vineet D. Menachery", + "author_inst": "University of Texas Medical Branch, Galveston, TX" }, { - "author_name": "Julia Vergara-Alert", - "author_inst": "IRTA-CRESA" + "author_name": "Martin T. Ferris", + "author_inst": "University of North Carolina at Chapel Hill, Chapel Hill, NC" }, { - "author_name": "Nuria Izquierdo-Useros", - "author_inst": "AIDS Research Institute IrsiCaixa" + "author_name": "Ralph S. Baric", + "author_inst": "University of North Carolina at Chapel Hill, Chapel Hill, NC" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "new results", "category": "microbiology" }, @@ -756038,107 +755357,71 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.05.08.21256867", - "rel_title": "SARS-CoV-2 lineage dynamics in England from January to March 2021 inferred from representative community samples", - "rel_date": "2021-05-14", + "rel_doi": "10.1101/2021.05.11.21257040", + "rel_title": "Trajectories of child emotional and behavioural difficulties before and during the COVID-19 pandemic in a longitudinal UK cohort", + "rel_date": "2021-05-13", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.08.21256867", - "rel_abs": "Genomic surveillance for SARS-CoV-2 lineages informs our understanding of possible future changes in transmissibility and vaccine efficacy. However, small changes in the frequency of one lineage over another are often difficult to interpret because surveillance samples are obtained from a variety of sources. Here, we describe lineage dynamics and phylogenetic relationships using sequences obtained from a random community sample who provided a throat and nose swab for rt-PCR during the first three months of 2021 as part of the REal-time Assessment of Community Transmission-1 (REACT-1) study. Overall, diversity decreased during the first quarter of 2021, with the B.1.1.7 lineage (first identified in Kent) predominant, driven by a 0.3 unit higher reproduction number over the prior wild type. During January, positive samples were more likely B.1.1.7 in younger and middle-aged adults (aged 18 to 54) than in other age groups. Although individuals infected with the B.1.1.7 lineage were no more likely to report one or more classic COVID-19 symptoms compared to those infected with wild type, they were more likely to be antibody positive 6 weeks after infection. Viral load was higher in B.1.1.7 infection as measured by cycle threshold (Ct) values, but did not account for the increased rate of testing positive for antibodies. The presence of infections with non-imported B.1.351 lineage (first identified in South Africa) during January, but not during February or March, suggests initial establishment in the community followed by fade-out. However, this occurred during a period of stringent social distancing and targeted public health interventions and does not immediately imply similar lineages could not become established in the future. Sequence data from representative community surveys such as REACT-1 can augment routine genomic surveillance.", - "rel_num_authors": 22, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.11.21257040", + "rel_abs": "ImportanceCOVID-19 public health mitigation measures are likely to have detrimental effects on emotional and behavioural problems in children. However, longitudinal studies with pre-pandemic data are scarce.\n\nObjectiveTo explore trajectories of childrens emotional and behavioural difficulties during the COVID-19 pandemic.\n\nDesign and settingData were from children from the third generation of a birth cohort study; the Avon Longitudinal Study of Parents and Children - Generation 2 (ALSPAC-G2) in the southwest of England.\n\nParticipantsThe study population comprised of 708 children (median age at COVID-19 data collection was 4.4 years, SD=2.9, IQR= [2.2 to 6.9]), whose parents provided previous pre-pandemic surveys and a survey between 26 May and 5 July 2020 that focused on information about the COVID-19 pandemic as restrictions from the first lockdown in the UK were eased.\n\nExposuresWe employed multi-level mixed effects modelling with random intercepts and slopes to examine whether childrens trajectories of emotional and behavioural difficulties (a combined total difficulties score) during the pandemic differ from expected pre-pandemic trajectories.\n\nMain outcomesChildren had up to seven measurements of emotional and behavioural difficulties from infancy to late childhood, using developmentally appropriate scales such as the Emotionality Activity Sociability Temperament Survey in infancy and Strengths and Difficulties Questionnaire in childhood.\n\nResultsThe observed normative pattern of childrens emotional and behavioural difficulties pre-pandemic, was characterised by an increase in scores during infancy peaking around the age of 2, and then declining throughout the rest of childhood. Pre-pandemic, the decline in difficulties scores after age 2 was 0.6 points per month; but was approximately one third of that in post-pandemic trajectories (there was a difference in mean rate of decline after age 2 of 0.2 points per month in pre vs during pandemic trajectories [95 % CI: 0.10 to 0.30, p <0.001]). This lower decline in scores over the years translated to older children having pandemic difficulty scores higher than would be expected from pre-pandemic trajectories (for example, an estimated 10.0 point (equivalent of 0.8 standard deviations) higher score (95% CI: 5.0 to 15.0) by age 8.5 years). Results remained similar although somewhat attenuated after adjusting for maternal anxiety and age.\n\nConclusion and relevanceThe COVID-19 pandemic may be associated with greater persistence of emotional and behavioural difficulties after the age 2. Emotional difficulties in childhood predict later mental health problems. Further evidence and monitoring of emotional and behavioural difficulties are required to fully understand the potential role of the pandemic on young children.\n\nKey FindingsO_ST_ABSQuestionC_ST_ABSHow has the COVID-19 pandemic influenced emotional difficulties in young children?\n\nFindingsUsing repeated longitudinal data from before and during the pandemic we provide evidence that emotional difficulty scores of primary school aged children are higher by an estimated 10.0 points (0.8 standard deviations) (95% CI: 5.0 to 15.0) by age 8.5 years than would be expected based on pre pandemic data.\n\nMeaningThe level of difference in emotional difficulties found in the current study has been linked to increased likelihood of mental health problems in adolescence and adulthood. Therefore, this increase in difficulties needs careful monitoring and support.", + "rel_num_authors": 13, "rel_authors": [ { - "author_name": "Oliver Eales", - "author_inst": "School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc" - }, - { - "author_name": "Andrew Page", - "author_inst": "Quadram Institute, Norwich, UK" - }, - { - "author_name": "Sonja N. Tang", - "author_inst": "School of Public Health, Imperial College London, UK" - }, - { - "author_name": "Caroline E. Walters", - "author_inst": "School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc" - }, - { - "author_name": "Haowei Wang", - "author_inst": "School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc" - }, - { - "author_name": "David Haw", - "author_inst": "School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc" - }, - { - "author_name": "Alexander J. Trotter", - "author_inst": "Quadram Institute, Norwich, UK" - }, - { - "author_name": "Thanh Le Viet", - "author_inst": "Quadram Institute, Norwich, UK" - }, - { - "author_name": "Ebenezer Foster-Nyarko", - "author_inst": "Quadram Institute, Norwich, UK" - }, - { - "author_name": "Sophie Prosolek", - "author_inst": "Quadram Institute, Norwich, UK" + "author_name": "Elise Paul", + "author_inst": "University College London" }, { - "author_name": "Christina Atchinson", - "author_inst": "School of Public Health, Imperial College London, UK" + "author_name": "Daphne Kounali", + "author_inst": "University of Bristol" }, { - "author_name": "Deborah Ashby", - "author_inst": "School of Public Health, Imperial College London, UK" + "author_name": "Alex Siu Fung Kwong", + "author_inst": "University of Bristol" }, { - "author_name": "Graham Cooke", - "author_inst": "Department of Infectious Disease, Imperial College London, UK Imperial College Healthcare NHS Trust, UK National Institute for Health Research Imperial Biomedic" + "author_name": "Daniel Smith", + "author_inst": "University of Bristol" }, { - "author_name": "Wendy Barclay", - "author_inst": "Department of Infectious Disease, Imperial College London, UK" + "author_name": "Ilaria Costantini", + "author_inst": "University of Bristol" }, { - "author_name": "Christl A Donnelly", - "author_inst": "School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc" + "author_name": "Deborah A Lawlor", + "author_inst": "University of Bristol" }, { - "author_name": "Justin O'Grady", - "author_inst": "Quadram Institute, Norwich, UK" + "author_name": "Kapil Sayal", + "author_inst": "University of Nottingham" }, { - "author_name": "Erik Volz", - "author_inst": "School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc" + "author_name": "Helen Bould", + "author_inst": "University of Bristol" }, { - "author_name": "- The COVID-19 Genomics UK (COG-UK) Consortium", - "author_inst": "" + "author_name": "Nicholas J Timpson", + "author_inst": "University of Bristol" }, { - "author_name": "Ara Darzi", - "author_inst": "Imperial College Healthcare NHS Trust, UK National Institute for Health Research Imperial Biomedical Research Centre, UK Institute of Global Health Innovation a" + "author_name": "Kate Northstone", + "author_inst": "University of Bristol" }, { - "author_name": "Helen Ward", - "author_inst": "School of Public Health, Imperial College London, UK Imperial College Healthcare NHS Trust, UK National Institute for Health Research Imperial Biomedical Resear" + "author_name": "Melanie Lewcock", + "author_inst": "University of Bristol" }, { - "author_name": "Paul Elliott", - "author_inst": "School of Public Health, Imperial College London, UK Imperial College Healthcare NHS Trust, UK National Institute for Health Research Imperial Biomedical Resear" + "author_name": "Kate J Tilling", + "author_inst": "University of Bristol" }, { - "author_name": "Steven Riley", - "author_inst": "School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc" + "author_name": "Rebecca Pearson", + "author_inst": "University of Bristol" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "psychiatry and clinical psychology" }, { "rel_doi": "10.1101/2021.05.12.21257080", @@ -758476,27 +757759,59 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.05.07.21256856", - "rel_title": "A model to analyze rideshare data to surveil novel strains of SARS-CoV-2", + "rel_doi": "10.1101/2021.05.10.21256933", + "rel_title": "Fixed dosing of tocilizumab in ICU admitted COVID-19 patients is a superior choice compared to bodyweight based dosing; an observational population pharmacokinetic and pharmacodynamic study", "rel_date": "2021-05-12", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.07.21256856", - "rel_abs": "BackgroundThe emergence of novel, potentially vaccine-resistant strains of SARS-CoV-2 poses a serious risk to public health. The interactions between passengers and drivers facilitated by rideshare platforms such as Uber are, essentially, a series of partially standardized, random experiments of SARS-CoV-2 transmission. Rideshare companies share data with government health agencies, but no statistical method is available to aggregate these data for the systematic study of the transmission dynamics of COVID-19.\n\nMethodsWe develop a proof-of-concept model for the analysis of data from rideshare interactions merged with COVID-19 diagnosis records. Using simulated data with rideshare volumes, disease prevalence, and diagnosis rates based on a large US city, we use the model to test hypotheses about the emergence of viral strains and their transmission characteristics in the presence of non-pharmaceutical interventions and superspreaders.\n\nFindingsData from 10 simulated trials of SARS-CoV-2 propagation within the Los Angeles rideshare network resulted in an average of 190,387.1 potentially infectious rideshare interactions. Assuming access to data on 25% of the total estimated infections (Partial Reporting), these interactions resulted in an average of 409.0 diagnosed rideshare infections given our transmission model assumptions. For each of the 10 simulated trials, analysis given Partial Reporting could consistently differentiate between a baseline strain and an emergent, more infectious viral strain, enabling hypothesis testing about transmission characteristics.\n\nInterpretationSimulated evaluation of a novel statistical model suggests that rideshare data combined with COVID-19 diagnosis data have the potential to automate continued surveillance of emergent novel strains of SARS-CoV-2 and their transmission characteristics.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.10.21256933", + "rel_abs": "BackgroundTocilizumab improves outcome, including survival, in intensive care unit (ICU) admitted COVID-19 patients. The currently applied dosage of 8 mg/kg is based on use of this drug for other indications, however is has not formally been investigated for COVID-19. In this study pharmacokinetics and dynamics of tocilizumab were investigated in ICU admitted COVID-19 patients.\n\nMethodsThis was an open-label, single-center observational pharmacokinetic and -dynamic evaluation study. Enrolled patients, with polymerase chain reaction confirmed Covid-19 were admitted to the ICU for mechanical ventilation or high flow nasal canula oxygen support. All patients were 18 years of age or older and received tocilizumab within 24 hours after admission to the ICU and received 6 mg dexamethasone daily as concomitant therapy.\n\nResults29 patients were enrolled between 15 December 2020 and 15 March 2021. A total of 139 tocilizumab plasma samples were obtained covering the pharmacokinetic curve of day 0 up to day 20 after tocilizumab initiation. A population pharmacokinetic model with parallel linear and non-linear clearance was developed and validated. Average AUC0-inf 1stDOSE was 938 [{+/-}190] ug/mL*days. Tocilizumab half-life was estimated to be 4{middle dot}15 [{+/-}0{middle dot}24] days. All patients had tocilizumab exposure above 1 ug/ml for at least 15 days.\n\nConclusionThis study provides evidence to support a fixed dose of 600 mg tocilizumab in COVID-19 patients. Furthermore our findings suggest that alternative cost saving regimens with even lower doses are likely to be as effective as the current 8 mg/kg recommendation.\n\nFundingNo external funding was received for this work\n\nBackgroundIn the randomized controlled trial REMAP-CAP, the IL-6 receptor antagonist tocilizumab was shown to improve outcome, including survival in ICU admitted COVID-19 patients. Because obesity is a risk factor for development of severe COVID-19, concerns have been raised about overtreatment as well as undertreatment through weight-based dosing of tocilizumab. Furthermore pharmacokinetic and pharmacodynamic parameters of medications are often found to be different in severely ill patients when compared to mild or moderately ill patients. However, the effects of different dosing schedules were only investigated to a very limited extent in non-randomized observational studies. Hence, evaluation of the PK/PD parameters of tocilizumab in severely ill patients - is warranted.\n\nAdded value of this studyThis study provides valuable information about the population pharmacokinetics and dynamics of tocilizumab in dexamethasone cotreated ICU admitted COVID-19 patients. This research shows that there is no rationale for the 8 mg/kg dosing recommendation in ICU patients. Fixed dosing of 600 mg tocilizumab is a cost saving, logistically attractive and safe alternative without losing efficacy.\n\nImplications of all the evidenceDue to the ongoing pandemic, shortages of tocilizumab and other IL-6 receptor antagonists may be anticipated. A fixed tocilizumab dose regimen has many practical and safety advantages, e.g. it will reduce dosing errors and avoid unnecessary wastage of medication. More importantly, according to the data presented in this study, relative underdosing of patients with low, or low-normal bodyweight compared to patients with high bodyweight will be avoided. Last but not least, in view of the large number of patients currently being treated with these agents, a significant cost saving can also be expected.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Conrad W Safranek", - "author_inst": "Stanford University" + "author_name": "Dirk Jan A.R. Moes", + "author_inst": "Department of Clinical Pharmacy & Toxicology, Leiden University Medical Center, The Netherlands" }, { - "author_name": "David Scheinker", - "author_inst": "Stanford University" + "author_name": "David J. van Westerloo", + "author_inst": "Department of Intensive Care, Leiden University Medical Center, The Netherlands" + }, + { + "author_name": "Sandra M. Arend", + "author_inst": "Department of Infectious Diseases, Leiden University Medical Center, The Netherlands" + }, + { + "author_name": "Jesse J. Swen", + "author_inst": "Department of Clinical Pharmacy & Toxicology, Leiden University Medical Center, The Netherlands" + }, + { + "author_name": "Annick de Vries", + "author_inst": "Biologics Lab, Sanquin Diagnostic Services, The Netherlands" + }, + { + "author_name": "Henk-Jan Guchelaar", + "author_inst": "Department of Clinical Pharmacy & Toxicology, Leiden University Medical Center, The Netherlands" + }, + { + "author_name": "Simone A. Joosten", + "author_inst": "Department of Infectious Diseases, Leiden University Medical Center, The Netherlands" + }, + { + "author_name": "Mark G.J. de Boer", + "author_inst": "Department of Infectious Diseases, Leiden University Medical Center, The Netherlands" + }, + { + "author_name": "Teun van Gelder", + "author_inst": "Department of Clinical Pharmacy & Toxicology, Leiden University Medical Center, The Netherlands" + }, + { + "author_name": "Judith van Paassen", + "author_inst": "Department of Intensive Care, Leiden University Medical Center, The Netherlands" } ], "version": "1", "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "pharmacology and therapeutics" }, { "rel_doi": "10.1101/2021.05.08.21256879", @@ -760770,47 +760085,43 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.05.10.21256529", - "rel_title": "Severity assessment of single dose Oxford-AstraZeneca vaccinated individuals infected with SARS CoV-2 in the Southeast Bangladesh", + "rel_doi": "10.1101/2021.05.06.21256773", + "rel_title": "Risk of COVID-19 infection and work place exposure of front-line mass media professionals", "rel_date": "2021-05-11", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.10.21256529", - "rel_abs": "The present global endeavor to uncover the most effective vaccines against severe acute respiratory syndrome coronavirus (SARS-CoV-2) that can tremendously prevent transmission, infection and significantly reduce public health risk. COVID-19 vaccination program is underway in different parts of the world including Bangladesh but till to date there is no available health data revealed among the vaccinated peoples. We conducted a cross-sectional study from February 15 to April 15, 2021 to assess the health status of 1st dose Oxford-AstraZeneca vaccinated individuals infected with SARS CoV-2. Standard virological method, real-time reverse transcriptase-polymerase chain reaction (RT-qPCR) was performed to detect SARS-CoV-2 and the different health parameters from vaccinated individuals were collected through direct mobile phone contact using pre-structured questionnaires. A total of 6146 suspected samples were tested and 1752 were found positive for SARS-CoV-2, of them 200 individuals were identified who received 1st dose of COVID-19 vaccine. Within the test period, majority of male (65.6%) and female (34.4%) carried moderate numbers of viruses which comprise between 30.01-35 cyclic threshold (ct) values. Among the vaccinated individuals, 165 (82.5%; 95% CI: 76.51 - 87.5) persons were not hospitalized and 177 (88.5%; 95% CI: 83.24 - 92.57) did not show any respiratory difficulties. Only a few (16) (8%; 95% CI: 4.64 - 12.67) of COVID-19 positive patients needed extra oxygen support and 199 (99.5%; 95% CI: 97.25 - 99.99) individuals didnt require any intensive care unit (ICU) interference. Overall, oxygen saturation was recorded around 96.8% and respiratory difficulties did not extend more than 5 days, irrespective of age and sex during the infection period. Within the vaccinated COVID-19 positive individuals 113 (56.5%; 95% CI: 49.33 - 63.48) and 111(55.5%; 95% CI: 48.32 - 62.51) persons have normal physiological taste and smell. However, we have found a larger proportion of vaccinated persons (129) (64.5%; 95% CI: 57.44 - 71.12) carrying different comorbidity, among them high blood pressure 36 (27.9%; 95% CI, 20.37 - 36.48) and diabetes 32 (24.8%; 95% CI: 17.63 - 33.18) were found more prevalent. Moreover, the significant finding of the present study was 199 (99.5%; 95% CI: 97.25 - 99.99) vaccinated individuals survived with good health conditions and became negative in RT-qPCR. The authors suggest that health risk assessment among the COVID-19 vaccinated persons when infected with SARS-CoV-2 is crucial and time demanding task for the whole world. However, the present study illustrates that the administration of the 1st dose Oxford-AstraZeneca vaccine significantly reduces health risk during the COVID-19 infection period.", - "rel_num_authors": 7, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.06.21256773", + "rel_abs": "IntroductionMass media plays a crucial role in creating awareness and knowledge sharing in this Corona virus disease 2019 (COVID-19) pandemic. However, the risk of exposure and extent of COVID-19 infection among media professional are less elucidated yet. Therefore, this study was intended to investigate the workplace-related risk of COVID-19 exposure and the association between exposure to COVID-19 and participants characteristics, including various forms of respiratory protection for mass-media professionals.\n\nMethodsThis closed web-based cross-sectional survey was conducted among 199 mass-media professionals in Bangladesh by snowball sampling approach. A multivariate logistic regression model was used for the analytical exploration. Adjusted and Unadjusted Odds Ratio (OR) with 95% confidence intervals (95% CI) were calculated for the specified exposures. Chi-square test was used to observe the association. Ethical issues were maintained according to the guidance of the declaration of the Helsinki.\n\nResultsOf all, 39.2% of mass-media professionals were tested positive for COVID-19, whereas 6% of symptomatic or suspected participants did not do the test. Mass media professionals who worked in electronic media reported more COVID-19 infection (adjusted odds ratio, AOR= 6.25; 95% Confidence interval: Lower limit 1.43, upper limit 27.43; P =0.02). However, no significant relationship was found between the type of job role and COVID-19 infection. Furthermore, infected colleagues (OR/P=1.92/0.04) were identified as significant contact of acquiring infection. However, the study result showed that reused/new medical mask, homemade/cloth-made mask (vs. use of respirator mask) was not significantly (p=0.82) associated with mass media professionals infection.\n\nConclusionsProfessionals working in electronic media were at higher risk of being infected by COVID-19 and mostly acquired from infected colleagues. Using a respirator mask was not associated with a lower risk of test positive infection in mass media professionals. This study will aid the policy maker and public health authorities during the COVID-19 pandemic to make proper implementation strategies.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Eaftekhar Ahmed Rana", - "author_inst": "Chattogram Veterinary and Animal Sciences University" - }, - { - "author_name": "Pronesh Dutta", - "author_inst": "Chattogram Veterinary and Animal Sciences University" + "author_name": "Sarabon Tahura", + "author_inst": "1.\tDepartment of Pediatric Respiratory Medicine, Bangladesh Institute of Child Health, Dhaka Shishu (Children) Hospital, Dhaka, Bangladesh" }, { - "author_name": "Md. Sirazul Islam", - "author_inst": "Chattogram Veterinary and Animal Sciences University" + "author_name": "Bilkis Banu", + "author_inst": "2.\tHeidelberg Institute of Global Health, Heidelberg University, Germany; Department of Public Health, Northern University Bangladesh, Dhaka, Bangladesh" }, { - "author_name": "Tanvir Ahmad Nizami", - "author_inst": "Chattogram Veterinary and Animal Sciences University" + "author_name": "Nasrin Akter", + "author_inst": "3.\tDepartment of Public Health, Northern University Bangladesh, Dhaka, Bangladesh" }, { - "author_name": "Tridip Das", - "author_inst": "Chattogram Veterinary and Animal Sciences University" + "author_name": "Sarder Mahmud Hossain", + "author_inst": "3.\tDepartment of Public Health, Northern University Bangladesh, Dhaka, Bangladesh" }, { - "author_name": "Sharmin Chowdhury", - "author_inst": "Chattogram Veterinary and Animal Sciences University" + "author_name": "Rashidul Alam Mahumud", + "author_inst": "4.\tFaculty of Medicine and Health, The University of Sydney, Australia" }, { - "author_name": "Goutam Buddha Das", - "author_inst": "Chattogram Veterinary and Animal Sciences University" + "author_name": "Md Rishad Ahmed", + "author_inst": "5.\tCHU Sainte-Justine Research Center, Montreal, Canada" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2021.05.11.21257030", @@ -763260,55 +762571,79 @@ "category": "nephrology" }, { - "rel_doi": "10.1101/2021.05.07.21256839", - "rel_title": "Cross-sectional study of the association between perceived organizational support and COVID-19 vaccine intention", + "rel_doi": "10.1101/2021.05.05.21256384", + "rel_title": "Genomic and epidemiological analysis of SARS-CoV-2 viruses in Sri Lanka", "rel_date": "2021-05-10", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.07.21256839", - "rel_abs": "ObjectivesThis study examined the association between perceived organizational support (POS) and COVID-19 vaccine intention and the influence of the implementation of workplace infection prevention measures.\n\nMethodsWe analyzed 23,846 workers using data from an Internet survey of workers aged 20-65 years conducted in December 2020, during a period of widespread COVID-19 infection in Japan.\n\nResultsA higher POS was associated with a higher intention to vaccinate. The relationship between POS and vaccine intention was attenuated when adjusted for infection prevention measures in the workplace.\n\nConclusionsIn workplaces where POS is present, a sense of responsibility to the group and altruistic behavior may arise. This means employees act to acquire herd immunity to protect others, which may result in increased vaccine intention. The association between POS and vaccination intention was attenuated by adjusting for workplace infection prevention measures, which suggested that infection prevention measures may be a confounding factor or that POS created a health climate that promoted infection prevention measures. The results suggest that working to improve employee well-being and implementing appropriate workplace infection prevention measures during infectious disease outbreaks may promote vaccination behavior and contribute to the acquisition of herd immunity in the community.", - "rel_num_authors": 9, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.05.21256384", + "rel_abs": "BackgroundIn order to understand the molecular epidemiology of SARS-CoV-2 in Sri Lanka, since March 2020, we carried out genomic sequencing overlaid on available epidemiological data until April 2021.\n\nMethodsWhole genome sequencing was carried out on diagnostic sputum or nasopharyngeal swabs from 373 patients with COVID-19. Molecular clock phylogenetic analysis was undertaken to further explore dominant lineages.\n\nResultsThe B.1.411 lineage was most prevalent, which was established in Sri Lanka and caused outbreaks throughout the country until March 2021. The estimated time of the most recent common ancestor of this lineage was 29th June 2020 (95% lower and upper bounds 23rd May to 30th July), suggesting cryptic transmission may have occurred, prior to a large epidemic starting in October 2020. Returning travellers were identified with infections caused by lineage B.1.258, as well as the more transmissible B.1.1.7 lineage, which has replaced B.1.411 to fuel the ongoing large outbreak in the country.\n\nConclusionsThe large outbreak that started in early October, is due to spread of a single virus lineage, B.1.411 until the end of March 2021, when B.1.1.7 emerged and became the dominant lineage.", + "rel_num_authors": 15, "rel_authors": [ { - "author_name": "Yuichi Kobayashi", - "author_inst": "University of Occupational and Environmental Health, Japan" + "author_name": "Chandima Jeewandara", + "author_inst": "University of Sri Jayewardenepura" }, { - "author_name": "Tomohisa Nagata", - "author_inst": "University of Occupational and Environmental Health, Japan" + "author_name": "Deshni Jayathilaka", + "author_inst": "University of Sri Jayewardenepura" }, { - "author_name": "Yoshihisa Fujino", - "author_inst": "University of Occupational and Environmental Health, Japan" + "author_name": "Diyanath Ranasinghe", + "author_inst": "Universityof Sri Jayewardenepura" }, { - "author_name": "Ayako Hino", - "author_inst": "University of Occupational and Environmental Health, Japan" + "author_name": "Nienyun Sharon Hsu", + "author_inst": "University of Sheffield" }, { - "author_name": "Seiichiro Tateishi", - "author_inst": "University of Occupational and Environmental Health, Japan" + "author_name": "Dinuka Ariyaratne", + "author_inst": "University of Sri Jayawardenepura" }, { - "author_name": "Akira Ogami", - "author_inst": "University of Occupational and Environmental Health, Japan" + "author_name": "Tibutius Thanesh Jayadas", + "author_inst": "University of Sri Jayawardenepura" }, { - "author_name": "Mayumi Tsuji", - "author_inst": "University of Occupational and Environmental Health, Japan" + "author_name": "Deshan Madusanka", + "author_inst": "University of Sri Jayawardenepura" }, { - "author_name": "Shinya Matsuda", - "author_inst": "University of Occupational and Environmental Health, Japan" + "author_name": "Benjamin B. Lindsey", + "author_inst": "University of Sheffield" }, { - "author_name": "Koji Mori", - "author_inst": "University of Occupational and Environmental Health, Japan" + "author_name": "Laksiri Gomes", + "author_inst": "Universityof Sri Jayewardenepura" + }, + { + "author_name": "Matthew D Parker", + "author_inst": "University of Sheffield" + }, + { + "author_name": "Ananda Wijewickrama", + "author_inst": "National Institute of Infectious Diseases" + }, + { + "author_name": "Malika Karunaratne", + "author_inst": "National Institute of Infectious Diseases" + }, + { + "author_name": "Graham Ogg", + "author_inst": "University of Oxford" + }, + { + "author_name": "Thushan de Silva", + "author_inst": "University of Sheffield" + }, + { + "author_name": "Gathsaurie Neelika Malavige", + "author_inst": "University of Sri Jayewardenepura" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "occupational and environmental health" + "category": "genetic and genomic medicine" }, { "rel_doi": "10.1101/2021.05.07.21256834", @@ -765402,55 +764737,51 @@ "category": "biochemistry" }, { - "rel_doi": "10.1101/2021.05.07.443114", - "rel_title": "Following the Trail of One Million Genomes: Footprints of SARS-CoV-2 Adaptation to Humans", + "rel_doi": "10.1101/2021.05.09.443238", + "rel_title": "Design of the SARS-CoV-2 RBD vaccine antigen improves neutralizing antibody response", "rel_date": "2021-05-10", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.05.07.443114", - "rel_abs": "Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has accumulated genomic mutations at an approximately linear rate since it first infected human populations in late 2019. Controversies remain regarding the identity, proportion, and effects of adaptive mutations as SARS-CoV-2 evolves from a bat-to a human-adapted virus. The potential for vaccine-escape mutations poses additional challenges in pandemic control. Despite being of great interest to therapeutic and vaccine development, human-adaptive mutations in SARS-CoV-2 are masked by a genome-wide linkage disequilibrium under which neutral and even deleterious mutations can reach fixation by chance or through hitchhiking. Furthermore, genome-wide linkage equilibrium imposes clonal interference by which multiple adaptive mutations compete against one another. Informed by insights from microbial experimental evolution, we analyzed close to one million SARS-CoV-2 genomes sequenced during the first year of the COVID-19 pandemic and identified putative human-adaptive mutations according to the rates of synonymous and missense mutations, temporal linkage, and mutation recurrence. Furthermore, we developed a forward-evolution simulator with the realistic SARS-CoV-2 genome structure and base substitution probabilities able to predict viral genome diversity under neutral, background selection, and adaptive evolutionary models. We conclude that adaptive mutations have emerged early, rapidly, and constantly to dominate SARS-CoV-2 populations despite clonal interference and purifying selection. Our analysis underscores a need for genomic surveillance of mutation trajectories at the local level for early detection of adaptive and immune-escape variants. Putative human-adaptive mutations are over-represented in viral proteins interfering host immunity and binding host-cell receptors and thus may serve as priority targets for designing therapeutics and vaccines against human-adapted forms of SARS-CoV-2.", - "rel_num_authors": 9, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.05.09.443238", + "rel_abs": "The receptor binding domain (RBD) of the SARS-CoV-2 spike protein is the primary target of neutralizing antibodies and is a component of almost all vaccine candidates. Here, RBD immunogens were created with stabilizing amino acid changes that improve the neutralizing antibody response, as well as characteristics for production, storage, and distribution. A computational design and in vitro screening platform identified three improved immunogens, each with approximately nine amino acid changes relative to the native RBD sequence and four key changes conserved between immunogens. The changes are adaptable to all vaccine platforms, are compatible with established changes in SARS-CoV-2 vaccines, and are compatible with mutations in emerging variants of concern. The immunogens elicit higher levels of neutralizing antibodies than native RBD, focus the immune response to structured neutralizing epitopes, and have increased production yields and thermostability. Incorporating these variant-independent amino acid changes in next-generation vaccines may enhance the neutralizing antibody response and lead to pan-SARS-CoV-2 protection.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Saymon Akther", - "author_inst": "Graduate Center, City University of New York" - }, - { - "author_name": "Edgaras Bezrucenkovas", - "author_inst": "Hunter College City University of New York" + "author_name": "Thayne H Dickey", + "author_inst": "National Institute of Allergy and Infectious Diseases" }, { - "author_name": "Li Li", - "author_inst": "Graduate Center, City University of New York" + "author_name": "Wai Kwan Tang", + "author_inst": "National Institute of Allergy and Infectious Diseases" }, { - "author_name": "Brian Sulkow", - "author_inst": "Hunter College City University of New York" + "author_name": "Brandi Butler", + "author_inst": "National Institute of Allergy and Infectious Diseases" }, { - "author_name": "Lia Di", - "author_inst": "Hunter College City University of New York" + "author_name": "Tarik Ouahes", + "author_inst": "National Institute of Allergy and Infectious Diseases" }, { - "author_name": "Desiree Pante", - "author_inst": "Hunter College City University of New York" + "author_name": "Sachy Orr-Gonzalez", + "author_inst": "National Institute of Allergy and Infectious Diseases" }, { - "author_name": "Che L. Martin", - "author_inst": "New York Presbyterian Hospital" + "author_name": "Nichole D Salinas", + "author_inst": "National Institute of Allergy and Infectious Diseases" }, { - "author_name": "Benjamin J. Luft", - "author_inst": "Stony Brook University" + "author_name": "Lynn E Lambert", + "author_inst": "National Institute of Allergy and Infectious Diseases" }, { - "author_name": "Weigang Qiu", - "author_inst": "Hunter College of The City University of New York" + "author_name": "Niraj H Tolia", + "author_inst": "National Institute of Allergy and Infectious Disease" } ], "version": "1", "license": "", "type": "new results", - "category": "evolutionary biology" + "category": "molecular biology" }, { "rel_doi": "10.1101/2021.05.10.443480", @@ -767920,23 +767251,47 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.05.06.21256523", - "rel_title": "The COVID-19 pandemic storm in India", + "rel_doi": "10.1101/2021.05.06.21256651", + "rel_title": "Higher case fatality rate among obstetric patients with COVID-19 in the second year of pandemic in Brazil: do new genetic variants play a role?", "rel_date": "2021-05-08", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.06.21256523", - "rel_abs": "The sharp increase in the number of new COVID-19 patients in India in the second half of April 2021 has caused alarm around the world. A detailed analysis of this pandemic storm is still ahead. We present the results of anterior analysis using a generalized SIR-model (susceptible-infected-removed). The final size of this pandemic wave and its duration are predicted. Obtained results show that the COVID-19 pandemic will be a problem for mankind for a very long time.", - "rel_num_authors": 1, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.06.21256651", + "rel_abs": "BackgroundIn Brazil, a 20% increase in maternal mortality rate due to COVID-19 is projected for 2020. On January 4, 2021, the P.1 SARS-CoV-2 genetic variant was firstly identified in the country and recent data has indicated an association with higher hospitalization rates and mortality. The impact of P.1 variant in the obstetric population remains unclear.\n\nMethodsWe carried out a preliminary analysis of sociodemographic and clinical characteristics of COVID-19 confirmed maternal deaths (between 10-50 years old) comparing cases reported to the Brazilian official severe acute respiratory syndrome (SARS) surveillance system (SS) in 2020 with those from 2021 (until April 12, 2021). This preliminary analysis employed methods described in previous reports from our group.\n\nResults803 maternal deaths out of 8,248 COVID-19 maternal SARS cases with a recorded outcome were reported to the SARS-SS since March 2020. Case fatality rate was significantly higher in 2021 (15.6% vs 7.4%). The first three months of 2021 already account for 46.2% of all deaths occurred in the 13-months analysed period. COVID-19 fatal cases from 2021 had a lower proportion of at least one risk factor or comorbidity as compared to 2020 but had a higher frequency of obesity. There were no significant differences in terms of age, type of residence area (urban, rural, or peri-urban), type of funding of the notification unit (public vs. private), COVID-19 diagnostic criteria, pregnancy status (pregnancy or postpartum), cardiovascular disease or diabetes. The proportion of hospitalization, ICU admission, and respiratory support before death was also not significantly different.\n\nConclusionCase fatality rate was increased in the three first months of 2021 when compared to 2020. Once variables related to health care access and demographics are not significantly different and women seem to be healthier in the 2021 sample, such difference may be related to the circulation of more aggressive genetic variants in the country.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Igor Nesteruk", - "author_inst": "Institute of Hydromechanics National Academy of sciences of Ukraine" + "author_name": "Maira Libertad Soligo Takemoto", + "author_inst": "Sao Paulo State University (UNESP), Medical School of Botucatu." + }, + { + "author_name": "Marcos Nakamura-Pereira", + "author_inst": "Instituto Nacional de Saude da Mulher, da Crianca e do Adolescente Fernandes Figueira - Fundacao Oswaldo Cruz" + }, + { + "author_name": "Mariane de Oliveira Menezes", + "author_inst": "Sao Paulo State University (Unesp), Medical School, Botucatu" + }, + { + "author_name": "Leila Katz", + "author_inst": "Instituto de Medicina Integral Professor Fernando Figueira (IMIP)" + }, + { + "author_name": "Roxana Knobel", + "author_inst": "Universidade Federal de Santa Catarina (UFSC), Department of Gynecology and Obstetrics." + }, + { + "author_name": "Melania Maria Ramos Amorim", + "author_inst": "Instituto de Medicina Integral Professor Fernando Figueira (IMIP)" + }, + { + "author_name": "Carla Betina Andreucci", + "author_inst": "Universidade Federal de Sao Carlos (UFSCAR), Department of Medicine" } ], "version": "1", "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "obstetrics and gynecology" }, { "rel_doi": "10.1101/2021.05.04.21256626", @@ -769818,27 +769173,163 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.05.06.21256476", - "rel_title": "Japan's Covid mitigation strategy and its epidemic prediction", + "rel_doi": "10.1101/2021.05.07.21256652", + "rel_title": "Safety and immunogenicity of INO-4800 DNA vaccine against SARS-CoV-2: a preliminary report of a randomized, blinded, placebo-controlled, Phase 2 clinical trial in adults at high risk of viral exposure", "rel_date": "2021-05-07", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.06.21256476", - "rel_abs": "The COVID-19 epidemic curve in Japan was constructed based on daily reported data from January 14, 2020 until April 20, 2021. A SEIR compartmental model was used for the curve fitting by updating the estimation per wave. In the current vaccination pace of 1/1000, restrictions (state of emergency in Japan) would be repeated 4 times until the end of next March. In the case of 1/500, another round of restriction would be required in the summer 2021, after which the infection would be mitigated. In the case of 1/250, there would be no need for restriction after the current spring restriction. The scenario of completing the vaccination of 110 million people by the end of March 2020 corresponds to the case of 1/250 in this curve. When considering the likely spread of variant with greater infectiousness (here we assume 1.3 times greater than the original virus), 1/500 pace of vaccination would not be enough to contain it and need several series of restrictions. There are currently several variants of concern that are already spreading in urban areas in this country. In the new stage of the replacement of variants, if the vaccination pace could not be quadrupled from the current pace, Japan could not become a zero covid (zero corona) country at least one year.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.07.21256652", + "rel_abs": "BackgroundVaccines against SARS-CoV-2 are still urgently needed as only 5% of the global population has been vaccinated. Here we report the safety and immunogenicity of a DNA vaccine (INO-4800) targeting the full-length Spike antigen of SARS-CoV-2 when given to adults at high-risk of exposure.\n\nMethodsINO-4800 was evaluated in 401 participants randomized at a 3:3:1:1 ratio to receive either INO-4800 (1 mg or 2 mg dose) or placebo (1 or 2 injections) intradermally (ID) followed by electroporation (EP) using CELLECTRA(R) 2000 at Days 0 and 28. ClinicalTrials.gov Identifier: NCT04642638\n\nFindingsThe majority of adverse events (AEs) were of Grade 1 and 2 in severity and did not appear to increase in frequency with the second dose. The number of participants experiencing each of the most common AEs did not differ appreciably between the two dosing groups. The geometric mean fold rise (GMFR) of binding and neutralizing antibody levels were statistically significantly greater in the 2.0 mg dose group versus the 1.0 mg dose group. The T cell immune responses measured by the ELISpot assay were also higher in the 2.0 mg dose group compared to the 1.0 mg dose group.\n\nInterpretationINO-4800 at both the 1.0 mg and 2.0 mg doses when administered in a 2-dose regimen appeared to be safe and well-tolerated in all adult ages. However, the comparative immunogenicity analysis favored selection of INO-4800 2.0 mg dose for advancement into a Phase 3 efficacy evaluation.\n\nFundingThe trial was funded by the Department of Defense Joint Program Executive Office for Chemical, Biological, Radiological and Nuclear Defense, (JPEO-CBRND) in coordination with the Office of the Assistant Secretary of Defense for Health Affairs (OASD(HA)) and the Defense Health Agency.\n\nResearch in contextINO-4800 is among several vaccines being tested against SARS-CoV-2, the virus that causes COVID-19 with the goal of inducing a protective immune response. The DNA vaccine, INO-4800, administered by ID injection followed by electroporation (EP) using the CELLECTRA(R) 2000 device, induces a balanced immune response that includes engagement of both T cells and B 1-5.\n\nAdded value of this studyThis is the first report of a randomized, blinded, placebo-controlled clinical trial of INO-4800, a DNA vaccine targeting the SARS-CoV-2 Spike antigen delivered ID followed by EP, in adults at high risk of SARS-CoV-2 exposure.", + "rel_num_authors": 36, "rel_authors": [ { - "author_name": "Yasuharu Tokuda", - "author_inst": "Muribushi Okinawa Center for Teaching Hospitals" + "author_name": "Mammen P Mammen Jr.", + "author_inst": "Inovio Pharmaceuticals" }, { - "author_name": "Toshikazu Kuniya", - "author_inst": "Kobe University" + "author_name": "Pablo Tebas", + "author_inst": "University of Pennsylvania, School of Medicine" + }, + { + "author_name": "Joseph Agnes", + "author_inst": "Inovio Pharmaceuticals" + }, + { + "author_name": "Mary Giffear", + "author_inst": "Inovio Pharmaceuticals" + }, + { + "author_name": "Kimberly A Kraynyak", + "author_inst": "Inovio Pharmaceuticals" + }, + { + "author_name": "Elliott Blackwood", + "author_inst": "Inovio Pharmaceuticals" + }, + { + "author_name": "Dinah Amante", + "author_inst": "Inovio Pharmaceuticals" + }, + { + "author_name": "Emma L Reuschel", + "author_inst": "Wistar Institute" + }, + { + "author_name": "Mansi Purwar", + "author_inst": "Wistar Institute" + }, + { + "author_name": "Aaron Christensen-Quick", + "author_inst": "Inovio Pharmaceuticals" + }, + { + "author_name": "Nieman Liu", + "author_inst": "Inovio Pharmaceuticals" + }, + { + "author_name": "Viviane M Andrade", + "author_inst": "Inovio Pharmaceuticals" + }, + { + "author_name": "Julie Carter", + "author_inst": "Inovio Pharmaceuticals" + }, + { + "author_name": "Gabriella Garuffi", + "author_inst": "Inovio Pharmaceutical" + }, + { + "author_name": "Malissa C Diehl", + "author_inst": "Inovio Pharmceuticals" + }, + { + "author_name": "Albert Sylvester", + "author_inst": "Inovio Pharmaceuticals" + }, + { + "author_name": "Matthew P Morrow", + "author_inst": "Inovio Pharmaceuticals" + }, + { + "author_name": "Patrick Pezzoli", + "author_inst": "Inovio Pharmaceuticals" + }, + { + "author_name": "Abhijeet J Kulkarni", + "author_inst": "Wistar Institute" + }, + { + "author_name": "Faraz I Zaidi", + "author_inst": "Wistar Institute" + }, + { + "author_name": "Drew Frase", + "author_inst": "Wistar Institute" + }, + { + "author_name": "Kevin Liaw", + "author_inst": "Wistar Institute" + }, + { + "author_name": "Hedieh Badie", + "author_inst": "Inovio Pharmaceuticals" + }, + { + "author_name": "Keiko O Simon", + "author_inst": "Inovio Pharmaceuticals" + }, + { + "author_name": "Trevor R. F. Smith", + "author_inst": "Inovio Pharmaceuticals" + }, + { + "author_name": "Stephanie Ramos", + "author_inst": "Inovio Pharmaceuticals" + }, + { + "author_name": "Robert Spitz", + "author_inst": "ICON GPHS" + }, + { + "author_name": "Jessica Lee", + "author_inst": "Inovio Pharmaceuticals" + }, + { + "author_name": "Micheal Dallas", + "author_inst": "Inovio Pharmaceuticals" + }, + { + "author_name": "Ami Shah Brown", + "author_inst": "Inovio Pharmaceuticals" + }, + { + "author_name": "Jacqueline E Shea", + "author_inst": "Inovio Pharmaceuticals" + }, + { + "author_name": "J. Joseph Kim", + "author_inst": "Inovio Pharmaceuticals" + }, + { + "author_name": "David B Weiner", + "author_inst": "Wistar Institute" + }, + { + "author_name": "Kate E Broderick", + "author_inst": "Inovio Pharmaceuticals" + }, + { + "author_name": "Jean D Boyer", + "author_inst": "Inovio Pharmaceuticals" + }, + { + "author_name": "Laurent M Humeau", + "author_inst": "Inovio Pharmaceuticals" } ], "version": "1", "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2021.05.07.443089", @@ -771892,23 +771383,75 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.05.02.21256474", - "rel_title": "Infants are more susceptible to COVID-19 than children", + "rel_doi": "10.1101/2021.05.05.442536", + "rel_title": "Uncovering cryptic pockets in the SARS-CoV-2 spike glycoprotein", "rel_date": "2021-05-05", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.02.21256474", - "rel_abs": "Angiotensin-converting enzyme 2 (ACE2) has been found to mediate the host cell entry of SARS-CoV-2 that causes COVID-19. However, the link between ACE2 and the observed susceptibility of SARS-CoV-2 infection remains elusive. In contrast, observational studies can help identify the susceptibility biomarker of SARS-CoV-2 infection, those associated with age for example. Data of all PCR tests performed in the state of Sao Paulo of Brazil were gathered from the government database and were analyzed using multivariate logistic regression. Adjusted odds ratios for positive test results were calculated with the adjustment of age, gender, and comorbidities. Over 1.7 million test results were included in the study of which 38% were positive. Elderly was most vulnerable to SARS-CoV-2 infection. While underages were less susceptible than adults aged below 60 years, susceptibility was not equal among different pediatric groups. It is found that age and susceptibility to SARS-CoV-2 infection are not inversely related, but U-shaped, with infants more susceptible than children. Biomarkers that are linearly associated with age cannot explain the reduced susceptibility in children. These include lymphocyte count and cross-reactive antibodies against other coronaviruses that offers cross-protection. The expression level of ACE2 may still be able to explain but further investigations are needed.", - "rel_num_authors": 1, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2021.05.05.442536", + "rel_abs": "The recent global COVID-19 pandemic has prompted a rapid response in terms of vaccine and drug development targeting the viral pathogen, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In this work, we modelled a complete membrane-embedded SARS-CoV-2 spike (S) protein, the primary target of vaccine and therapeutics development, based on available structural data and known glycan content. We then used molecular dynamics (MD) simulations to study the system in the presence of benzene probes designed to enhance discovery of cryptic, potentially druggable pockets on the S protein surface. We uncovered a novel cryptic pocket with promising druggable properties located underneath the 617-628 loop, which was shown to be involved in the formation of S protein multimers on the viral surface. A marked multi-conformational behaviour of this loop in simulations was validated using hydrogen-deuterium exchange mass spectrometry (HDX-MS) experiments, supportive of opening and closing dynamics. Interestingly, the pocket is also the site of the D614G mutation, known to be important for SARS-CoV-2 fitness, and within close proximity to mutations in the novel SARS-CoV-2 strains B.1.1.7 and B.1.1.28, both of which are associated with increased transmissibility and severity of infection. The pocket was present in systems emulating both immature and mature glycosylation states, suggesting its druggability may not be dependent upon the stage of virus maturation. Overall, the predominantly hydrophobic nature of the cryptic pocket, its well conserved surface, and proximity to regions of functional relevance in viral assembly and fitness are all promising indicators of its potential for therapeutic targeting. Our method also successfully recapitulated hydrophobic pockets in the receptor binding domain and N-terminal domain associated with detergent or lipid binding in prior cryo-electron microscopy (cryo-EM) studies. Collectively, this work highlights the utility of the benzene mapping approach in uncovering potential druggable sites on the surface of SARS-CoV-2 targets.", + "rel_num_authors": 14, "rel_authors": [ { - "author_name": "Char Leung", - "author_inst": "Deakin University" + "author_name": "Lorena Zuzic", + "author_inst": "Bioinformatics Institute, Agency for Science, Technology and Research (A*STAR)" + }, + { + "author_name": "Firdaus Samsudin", + "author_inst": "Bioinformatics Institute, Agency for Science, Technology and Research (A*STAR)" + }, + { + "author_name": "Aishwary Tukaram Shivgan", + "author_inst": "Bioinformatics Institute, Agency for Science, Technology and Research (A*STAR)" + }, + { + "author_name": "Palur V Raghuvamsi", + "author_inst": "Bioinformatics Institute, Agency for Science, Technology and Research (A*STAR)" + }, + { + "author_name": "Jan K Marzinek", + "author_inst": "Bioinformatics Institute, Agency for Science, Technology and Research (A*STAR)" + }, + { + "author_name": "Alister Boags", + "author_inst": "Bioinformatics Institute, Agency for Science, Technology and Research (A*STAR)" + }, + { + "author_name": "Conrado Pedebos", + "author_inst": "University of Southampton" + }, + { + "author_name": "Nikhil Kumar Tulsian", + "author_inst": "National University of Singapore" + }, + { + "author_name": "Jim Warwicker", + "author_inst": "The University of Manchester" + }, + { + "author_name": "Paul MacAry", + "author_inst": "Life Sciences Institute, Centre for Life Sciences, National University of Singapore" + }, + { + "author_name": "Max Crispin", + "author_inst": "University of Southampton" + }, + { + "author_name": "Syma Khalid", + "author_inst": "University of Southampton" + }, + { + "author_name": "Ganesh S Anand", + "author_inst": "Department of Chemistry, The Pennsylvania State University" + }, + { + "author_name": "Peter J Bond", + "author_inst": "Bioinformatics Institute, Agency for Science, Technology and Research (A*STAR)" } ], "version": "1", "license": "cc_by_nc_nd", - "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "type": "new results", + "category": "biophysics" }, { "rel_doi": "10.1101/2021.05.04.442699", @@ -773833,79 +773376,43 @@ "category": "oncology" }, { - "rel_doi": "10.1101/2021.05.03.21256506", - "rel_title": "Comprehensive mapping of neutralizing antibodies against SARS-CoV-2 variants induced by natural infection or vaccination", + "rel_doi": "10.1101/2021.05.02.21256495", + "rel_title": "Male-Female Disparities in Years of Potential Life Lost Attributable to COVID-19 in the United States: A State-by-State Analysis", "rel_date": "2021-05-05", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.03.21256506", - "rel_abs": "BackgroundImmunity after SARS-CoV-2 infection or vaccination has been threatened by recently emerged SARS-CoV-2 variants. A systematic summary of the landscape of neutralizing antibodies against emerging variants is needed.\n\nMethodsWe systematically searched PubMed, Embase, Web of Science, and 3 pre-print servers for studies that evaluated neutralizing antibodies titers induced by previous infection or vaccination against SARS-CoV-2 variants and comprehensively collected individual data. We calculated lineage-specific GMTs across different study participants and types of neutralization assays.\n\nFindingsWe identified 56 studies, including 2,483 individuals and 8,590 neutralization tests, meeting the eligibility criteria. Compared with lineage B, we estimate a 1.5-fold (95% CI: 1.0-2.2) reduction in neutralization against the B.1.1.7, 8.7-fold (95% CI: 6.5-11.7) reduction against B.1.351 and 5.0-fold (95% CI: 4.0-6.2) reduction against P.1. The estimated neutralization reductions for B.1.351 compared to lineage B were 240.2-fold (95% CI: 124.0-465.6) reduction for non-replicating vector platform, 4.6-fold (95% CI: 4.0-5.2) reduction for RNA platform, and 1.6-fold (95% CI: 1.2-2.1) reduction for protein subunit platform. The neutralizing antibodies induced by administration of inactivated vaccines and mRNA vaccines against lineage P.1 were also remarkably reduced by an average of 5.9-fold (95% CI: 3.7-9.3) and 1.5-fold (95% CI: 1.2-1.9).\n\nInterpretationOur findings indicate that the antibody response established by natural infection or vaccination might be able to effectively neutralize B.1.1.7, but neutralizing titers against B.1.351 and P.1 suffered large reductions. Standardized protocols for neutralization assays, as well as updating immune-based prevention and treatment, are needed.\n\nFundingChinese National Science Fund for Distinguished Young Scholars\n\nResearch in contextO_ST_ABSEvidence before this studyC_ST_ABSSeveral newly emerged SARS-CoV-2 variants have raised significant concerns globally, and there is concern that SARS-CoV-2 variants can evade immune responses that are based on the prototype strain. It is not known to what extent do emerging SARS-CoV-2 variants escape the immune response induced by previous infection or vaccination. However, existing studies of neutralizing potency against SARS-CoV-2 variants are based on limited numbers of samples and lack comparability between different laboratory methods. Furthermore, there are no studies providing whole picture of neutralizing antibodies induced by prior infections or vaccination against emerging variants. Therefore, we systematically reviewed and quantitively synthesized evidence on the degree to which antibodies from previous SARS-CoV-2 infection or vaccination effectively neutralize variants.\n\nAdded value of this studyIn this study, 56 studies, including 2,483 individuals and 8,590 neutralization tests, were identified. Antibodies from natural infection or vaccination are likely to effectively neutralize B.1.1.7, but neutralizing titers against B.1.351 and P.1 suffered large reductions. Lineage B.1.351 escaped natural-infection-mediated neutralization the most, with GMT of 79.2 (95% CI: 68.5-91.6), while neutralizing antibody titers against the B.1.1.7 variant were largely preserved (254.6, 95% CI: 214.1-302.8). Compared with lineage B, we estimate a 1.5-fold (95% CI: 1.0-2.2) reduction in neutralization against the B.1.1.7, 8.7-fold (95% CI: 6.5-11.7) reduction against B.1.351 and 5.0-fold (95% CI: 4.0-6.2) reduction against P.1. The neutralizing antibody response after vaccinating with non-replicating vector vaccines against lineage B.1.351 was worse than responses elicited by vaccines on other platforms, with levels lower than that of individuals who were previously infected. The neutralizing antibodies induced by administration of inactivated vaccines and mRNA vaccines against lineage P.1 were also remarkably reduced by an average of 5.9-fold (95% CI: 3.7-9.3) and 1.5-fold (95% CI: 1.2-1.9).\n\nImplications of all the available evidenceOur findings indicate that antibodies from natural infection of the parent lineage of SARS-CoV-2 or vaccination may be less able to neutralize some emerging variants, and antibody-based therapies may need to be updated. Furthermore, standardized protocols for neutralizing antibody testing against SARS-CoV-2 are needed to reduce lab-to-lab variations, thus facilitating comparability and interpretability across studies.", - "rel_num_authors": 15, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.02.21256495", + "rel_abs": "Males are at higher risk relative to females of severe outcomes following COVID-19 infection. Focusing on COVID-19-attributable mortality in the United States (U.S.), we quantify and contrast years of potential life lost (YPLL) attributable to COVID-19 by sex based on data from the U.S. National Center for Health Statistics as of 31 March 2021, specifically by contrasting male and female percentages of total YPLL with their respective percent population shares and calculating age-adjusted male-to-female YPLL rate ratios both nationally and for each of the 50 states and the District of Columbia. Using YPLL before age 75 to anchor comparisons between males and females and a novel Monte Carlo simulation procedure to perform estimation and uncertainty quantification, our results reveal a near-universal pattern across states of higher COVID-19-attributable YPLL among males compared to females. Furthermore, the disproportionately high COVID-19 mortality burden among males is generally more pronounced when measuring mortality in terms of YPLL compared to age-irrespective death counts, reflecting dual phenomena of males dying from COVID-19 at higher rates and at systematically younger ages relative to females. The U.S. COVID-19 epidemic also offers lessons underscoring the importance of a public health environment that recognizes sex-specific needs as well as different patterns in risk factors, health behaviors, and responses to interventions between men and women. Public health strategies incorporating focused efforts to increase COVID-19 vaccinations among men are particularly urged.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Xinhua Chen", - "author_inst": "School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China" - }, - { - "author_name": "Zhiyuan Chen", - "author_inst": "School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China" - }, - { - "author_name": "Andrew S Azman", - "author_inst": "Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA" - }, - { - "author_name": "Ruijia Sun", - "author_inst": "School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China" - }, - { - "author_name": "Wanying Lu", - "author_inst": "School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China" - }, - { - "author_name": "Nan Zheng", - "author_inst": "School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China" - }, - { - "author_name": "Jiaxin Zhou", - "author_inst": "School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China" - }, - { - "author_name": "Qianhui Wu", - "author_inst": "School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China" - }, - { - "author_name": "Xiaowei Deng", - "author_inst": "School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China" - }, - { - "author_name": "Zeyao Zhao", - "author_inst": "School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China" + "author_name": "Jay J Xu", + "author_inst": "University of California, Los Angeles" }, { - "author_name": "Xinghui Chen", - "author_inst": "School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China" + "author_name": "Jarvis T Chen", + "author_inst": "Harvard University" }, { - "author_name": "Shijia Ge", - "author_inst": "Department of Infectious Diseases, Huashan Hospital, Fudan University, Shanghai, China" + "author_name": "Thomas R Belin", + "author_inst": "University of California, Los Angeles" }, { - "author_name": "Juan Yang", - "author_inst": "School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China" + "author_name": "Ronald S Brookmeyer", + "author_inst": "University of California, Los Angeles" }, { - "author_name": "Daniel T Leung", - "author_inst": "Division of Infectious Diseases, University of Utah School of Medicine, Salt Lake City, UT, USA" + "author_name": "Marc A Suchard", + "author_inst": "University of California, Los Angeles" }, { - "author_name": "Hongjie Yu", - "author_inst": "School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China" + "author_name": "Christina M Ramirez", + "author_inst": "University of California, Los Angeles" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "public and global health" }, { "rel_doi": "10.1101/2021.05.03.21256509", @@ -775379,133 +774886,85 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2021.05.03.442371", - "rel_title": "Impaired T-cell and antibody immunity after COVID-19 infection in chronically immunosuppressed transplant recipients", + "rel_doi": "10.1101/2021.05.03.442538", + "rel_title": "CCR2-dependent monocyte-derived cells restrict SARS-CoV-2 infection", "rel_date": "2021-05-04", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.05.03.442371", - "rel_abs": "Assessment of T-cell immunity to the COVID-19 coronavirus requires reliable assays and is of great interest, given the uncertain longevity of the antibody response. Some recent reports have used immunodominant spike (S) antigenic peptides and anti-CD28 co-stimulation in varying combinations to assess T-cell immunity to SARS-CoV-2. These assays may cause T-cell hyperstimulation and could overestimate antiviral immunity in chronically immunosuppressed transplant recipients, who are predisposed to infections and vaccination failures. Here, we evaluate CD154-expressing T-cells induced by unselected S antigenic peptides in 204 subjects-103 COVID-19 patients and 101 healthy unexposed subjects. Subjects included 72 transplanted and 130 non-transplanted subjects. S-reactive CD154+T-cells co-express and can thus substitute for IFN{gamma} (n=3). Assay reproducibility in a variety of conditions was acceptable with coefficient of variation of 2-10.6%. S-reactive CD154+T-cell frequencies were a) higher in 42 healthy unexposed transplant recipients who were sampled pre-pandemic, compared with 59 healthy non-transplanted subjects (p=0.02), b) lower in Tr COVID-19 patients compared with healthy transplant patients (p<0.0001), c) lower in Tr patients with severe COVID-19 (p<0.0001), or COVID-19 requiring hospitalization (p<0.05), compared with healthy Tr recipients. S-reactive T-cells were not significantly different between the various COVID-19 disease categories in NT recipients. Among transplant recipients with COVID-19, cytomegalovirus co-infection occurred in 34%; further, CMV-specific T-cells (p<0.001) and incidence of anti-receptor-binding-domain IgG (p=0.011) were lower compared with non-transplanted COVID-19 patients. Healthy unexposed transplant recipients exhibit pre-existing T-cell immunity to SARS-CoV-2. COVID-19 infection leads to impaired T-cell and antibody responses to SARS-CoV-2 and increased risk of CMV co-infection in transplant recipients.", - "rel_num_authors": 30, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.05.03.442538", + "rel_abs": "SARS-CoV-2 has caused a historic pandemic of respiratory disease (COVID-19) and current evidence suggests severe disease is associated with dysregulated immunity within the respiratory tract. However, the innate immune mechanisms that mediate protection during COVID-19 are not well defined. Here we characterize a mouse model of SARS-CoV-2 infection and find that early CCR2-dependent infiltration of monocytes restricts viral burden in the lung. We find that a recently developed mouse-adapted MA-SARS-CoV-2 strain, as well as the emerging B. 1.351 variant, trigger an inflammatory response in the lung characterized by expression of pro-inflammatory cytokines and interferon-stimulated genes. scRNA-seq analysis of lung homogenates identified a hyper-inflammatory monocyte profile. Using intravital antibody labeling, we demonstrate that MA-SARS-CoV-2 infection leads to increases in circulating monocytes and an influx of CD45+ cells into the lung parenchyma that is dominated by monocyte-derived cells. We utilize this model to demonstrate that mechanistically, CCR2 signaling promotes infiltration of classical monocytes into the lung and expansion of monocyte-derived cells. Parenchymal monocyte-derived cells appear to play a protective role against MA-SARS-CoV-2, as mice lacking CCR2 showed higher viral loads in the lungs, increased lung viral dissemination, and elevated inflammatory cytokine responses. These studies have identified a CCR2-monocyte axis that is critical for promoting viral control and restricting inflammation within the respiratory tract during SARS-CoV-2 infection.", + "rel_num_authors": 18, "rel_authors": [ { - "author_name": "Chethan Ashokkumar", - "author_inst": "Plexision Inc., Pittsburgh, PA" - }, - { - "author_name": "Vinayak Rohan", - "author_inst": "Medical University of South Carolina, Charleston, SC" - }, - { - "author_name": "Alexander H Kroemer", - "author_inst": "Medstar Georgetown Transplant Institute, Washington, DC" - }, - { - "author_name": "Sohail Rao", - "author_inst": "DHR Health and DHR Health Institute for Research and Development, Edinburg, Tx, University of Houston, Houston, TX" - }, - { - "author_name": "George Mazariegos", - "author_inst": "Hillman Center for Pediatric Transplantation, University of Pittsburgh, PA" - }, - { - "author_name": "Brandon W Higgs", - "author_inst": "Hillman Center for Pediatric Transplantation, University of Pittsburgh, PA" - }, - { - "author_name": "Satish Nadig", - "author_inst": "Medical University of South Carolina, Charleston, SC" - }, - { - "author_name": "Jose Almeda", - "author_inst": "DHR Health and DHR Health Institute for Research and Development, Edinburg, Tx, University of Houston, Houston, TX" - }, - { - "author_name": "Harmeet Dhani", - "author_inst": "Medstar Georgetown Transplant Institute, Washington, DC" - }, - { - "author_name": "Khalid Khan", - "author_inst": "Medstar Georgetown Transplant Institute, Washington, DC" - }, - { - "author_name": "Nada Yazigi", - "author_inst": "Medstar Georgetown Transplant Institute, Washington, DC" - }, - { - "author_name": "Udeme Ekong", - "author_inst": "Medstar Georgetown Transplant Institute, Washington, DC" - }, - { - "author_name": "Stuart Kaufman", - "author_inst": "Medstar Georgetown Transplant Institute, Washington, DC" + "author_name": "Abigail Vanderheiden", + "author_inst": "Emory University" }, { - "author_name": "Monica M Betancourt-Garcia", - "author_inst": "DHR Health and DHR Health Institute for Research and Development, Edinburg, Tx, University of Houston, Houston, TX" + "author_name": "Jeronay Thomas", + "author_inst": "Emory University" }, { - "author_name": "Kavitha Mukund", - "author_inst": "University of California, San Diego, CA" + "author_name": "Allison L Soung", + "author_inst": "Washington University School of Medicine" }, { - "author_name": "Pradeep Sethi", - "author_inst": "Plexision Inc., Pittsburgh, PA" + "author_name": "Meredith E Davis-Gardner", + "author_inst": "Emory University" }, { - "author_name": "Shikhar Mehrotra", - "author_inst": "Medical University of South Carolina, Charleston, SC" + "author_name": "Katharine Floyd", + "author_inst": "Emory University" }, { - "author_name": "Kyle Soltys", - "author_inst": "Hillman Center for Pediatric Transplantation, University of Pittsburgh, PA" + "author_name": "Fengzhi Jin", + "author_inst": "Emory University" }, { - "author_name": "Manasi S Singh", - "author_inst": "Medical University of South Carolina, Charleston, SC" + "author_name": "David A Cowan", + "author_inst": "Emory University" }, { - "author_name": "Geoffrey Bond", - "author_inst": "Hillman Center for Pediatric Transplantation, University of Pittsburgh, PA" + "author_name": "Kathryn Pellegrini", + "author_inst": "Emory University" }, { - "author_name": "Ajai Khanna", - "author_inst": "Hillman Center for Pediatric Transplantation, University of Pittsburgh, PA" + "author_name": "Adrian Creanga", + "author_inst": "Vaccine Research Center" }, { - "author_name": "Mylarappa Ningappa", - "author_inst": "Hillman Center for Pediatric Transplantation, University of Pittsburgh, PA" + "author_name": "Amarendra Pegu", + "author_inst": "Vaccine Research Center" }, { - "author_name": "Brianna Spishock", - "author_inst": "Plexision Inc., Pittsburgh, PA" + "author_name": "Alexandrine Derrien-Colemyn", + "author_inst": "Vaccine Research Center" }, { - "author_name": "Elizabeth Sindhi", - "author_inst": "Plexision Inc., Pittsburgh, PA" + "author_name": "Pei-Yong Shi", + "author_inst": "University of Texas Medical Branch" }, { - "author_name": "Neha Atale", - "author_inst": "Plexision Inc., Pittsburgh, PA" + "author_name": "Arash Grakoui", + "author_inst": "Emory University" }, { - "author_name": "Maggie Saunders", - "author_inst": "Plexision Inc., Pittsburgh, PA" + "author_name": "Robyn S Klein", + "author_inst": "Washington University School of Medicine" }, { - "author_name": "Prabhakar Baliga", - "author_inst": "Medical University of South Carolina, Charleston, SC" + "author_name": "Steven E Bosinger", + "author_inst": "Emory University" }, { - "author_name": "Thomas Fishbein", - "author_inst": "Medstar Georgetown Transplant Institute, Washington, DC" + "author_name": "Jacob E Kohlmeier", + "author_inst": "Emory University" }, { - "author_name": "Shankar Subramaniam", - "author_inst": "University of California, San Diego, CA" + "author_name": "Vineet D Menachery", + "author_inst": "University of Texas Medical Branch" }, { - "author_name": "Rakesh Sindhi", - "author_inst": "Hillman Center for Pediatric Transplantation, University of Pittsburgh, PA and Plexision Inc., Pittsburgh, PA" + "author_name": "Mehul S Suthar", + "author_inst": "Emory University" } ], "version": "1", @@ -776803,47 +776262,35 @@ "category": "intensive care and critical care medicine" }, { - "rel_doi": "10.1101/2021.04.30.21256219", - "rel_title": "Data driven phenotyping and COVID-19 case definitions: a pattern recognition approach.", + "rel_doi": "10.1101/2021.04.29.21256178", + "rel_title": "American older adults in COVID-19 Times: Vulnerability types, aging attitudes and emotional responses", "rel_date": "2021-05-03", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.30.21256219", - "rel_abs": "IntroductionCOVID-19 has pathological pulmonary as well as several extrapulmonary manifestations and thus many different symptoms may arise in patients. The aim of our study was to determine COVID-19 syndromic phenotypes in a data driven manner using survey results extracted from Carnegie Mellon Universitys Delphi Group.\n\nMethodsMonthly survey results (>1 million responders per month; 320.326 responders with positive COVID-19 test and disease duration <30 days were included in this study) were used sequentially in identifying and validating COVID-19 syndromic phenotypes. Logistic Regression Weighted Multiple Correspondence Analysis (LRW-MCA) was used as a preprocessing procedure, in order to weight and transform symptoms recorded by the survey to eigenspace coordinates (i.e. object scores per case / dimension), with a goal of capturing a total variance of > 75%. These scores along with symptom duration were subsequently used by the Two Step Clustering algorithm to produce symptom clusters. Post-hoc logistic regression models adjusting for age, gender and comorbidities and confirmatory linear principal components analyses were used to further explore the data. The model created from 66.165 included responders in August, was subsequently validated in data from March - December 2020.\n\nResultsFive validated COVID-19 syndromes were identified in August: 1. Afebrile (0%), Non-Coughing (0%), Oligosymptomatic (ANCOS) 2. Febrile (100%) Multisymptomatic (FMS) 3. Afebrile (0%) Coughing (100%) Oligosymptomatic (ACOS), 4. Oligosymptomatic with additional self-described symptoms (100%; OSDS) and 5. Olfaction / Gustatory Impairment Predominant (100%; OGIP).\n\nDiscussionWe present 5 distinct symptom phenotypes within the COVID-19 spectrum that remain stable within 9 - 12 days of first symptom onset. The typical febrile respiratory phenotype is presented as a minority among identified syndromes, a finding that may impact both epidemiological surveillance norms and transmission dynamics.", - "rel_num_authors": 7, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.29.21256178", + "rel_abs": "BackgroundThe coronavirus disease aroused challenges to the emotional well-being of vulnerable older adults in hard-hit areas. This study investigates different vulnerability types among American older adults and how modes of vulnerability are associated with aging attitudes and emotional responses.\n\nMethodsUsing Latent Class Analysis, we investigated 2003 respondents aged over 50 from HRS. Hierarchical linear regressions with the affective profile as cluster identity were used to examine the relationship between vulnerability type and positive aging attitudes with positive and negative emotional responses.\n\nResultsWe detected three vulnerability types among American older adults: the slight vulnerability (72%), the healthcare use vulnerability (19%), and the dual vulnerabilities (9%). No significant difference in positive emotions was found between vulnerability types. However, more negative emotions were found among older adults with healthcare use vulnerability (B=0.746, SE=0.759) and dual vulnerabilities (B=1.186, SE=0.274) than those with slight vulnerability. Positive aging attitudes associate with more positive emotions (B=0.266, SE=0.017) but less negative emotions (B=-0.183, SE=0.016) and had significant moderation effects on the relationship between vulnerability types and negative emotional responses (B=-0.118, SE=0.045).\n\nConclusionOlder adults emotional well-being should not be neglected as they deserve the support of prevention and intervention strategies, in particular when they have vulnerabilities in healthcare use and financial sustainment. Female, non-white races, and those aged below 65, been uncoupled, less educated, and with ADL difficulties should prioritize.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Georgios D. Vavougios", - "author_inst": "University of Thessaly" - }, - { - "author_name": "Christoforos Konstantatos", - "author_inst": "Department of Business Administration, University of Patras, University of Patras, Greece" - }, - { - "author_name": "Pavlos Christoforos Sinigalias", - "author_inst": "Department of Mechanical Engineering and Aeronautics, University of Patras, Greece" - }, - { - "author_name": "Sotirios G Zarogiannis", - "author_inst": "Department of Physiology, Faculty of Medicine, School of Health Sciences, University of Thessaly, BIOPOLIS, Larissa 41500, Greece." + "author_name": "Mingqi Fu", + "author_inst": "Wuhan University" }, { - "author_name": "Kostas Kolomvatos", - "author_inst": "Department of Computer Science and Telecommunications, University of Thessaly, Papasiopoulou 2 - 4, Galaneika, Lamia 35131, Greece." + "author_name": "Jing Guo", + "author_inst": "Peking University" }, { - "author_name": "George Stamoulis", - "author_inst": "Department of Electrical and Computer Engineering, University of Thessaly, 37 Glavani to 28th October Str, Deligiorgi Building, 4th floor, Volos 38221, Greece" + "author_name": "Xi Chen", + "author_inst": "Yale University" }, { - "author_name": "Konstantinos I. Gourgoulianis", - "author_inst": "Department of Respiratory Medicine, Faculty of Medicine, School of Health Sciences, University of Thessaly, Biopolis, Larissa 41500, Greece" + "author_name": "Qilin Zhang", + "author_inst": "Wuhan University" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "psychiatry and clinical psychology" }, { "rel_doi": "10.1101/2021.04.30.21256240", @@ -778749,75 +778196,91 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.04.30.442029", - "rel_title": "Evolutionary insights into a non-coding deletion of SARS-CoV-2 B.1.1.7", + "rel_doi": "10.1101/2021.04.29.21256294", + "rel_title": "Elevated blood glucose levels as a primary risk factor for the severity of COVID-19", "rel_date": "2021-05-01", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.04.30.442029", - "rel_abs": "Three prevalent SARS-CoV-2 Variants of Concern (VOCs) were emerged and caused epidemic waves. It is essential to uncover the key genetic changes that cause the high transmissibility of VOCs. However, different viral mutations are generally tightly linked so traditional population genetic methods may not reliably detect beneficial mutation. In this study, we proposed a new pandemic-scale phylogenomic approach to detect mutations crucial to transmissibility. We analyzed 3,646,973 high-quality SARS-CoV-2 genomic sequences and the epidemiology metadata. Based on the sequential occurrence order of mutations and the instantaneously accelerated furcation rate, the analysis revealed that two non-coding mutations at the position of 28271 (g.a28271-/t) might be crucial for the high transmissibility of Alpha, Delta and Omicron VOCs. Both two mutations cause an A-to-T change at the core Kozak site of the N gene. The analysis also revealed that the non-coding mutations (g.a28271-/t) alone are unlikely to cause high viral transmissibility, indicating epistasis or multilocus interaction in viral transmissibility. A convergent evolutionary analysis revealed that g.a28271-/t, S:P681H/R and N:R203K/M occur independently in the three-VOC lineages, suggesting a potential interaction among these mutations. Therefore, this study unveils that non-synonymous and non-coding mutations could affect the transmissibility synergistically.", - "rel_num_authors": 14, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.29.21256294", + "rel_abs": "SARS-CoV-2 started spreading towards the end of 2019 causing COVID-19, a disease that reached pandemic proportions among the human population within months. The reasons for the spectrum of differences in the severity of the disease across the population, and in particular why the disease affects more severely the aging population and those with specific preconditions are unclear. We developed machine learning models to mine 240,000 scientific papers openly accessible in the CORD-19 database, and constructed knowledge graphs to synthesize the extracted information and navigate the collective knowledge in an attempt to search for a potential common underlying reason for disease severity. The literature repeatedly pointed to elevated blood glucose as a key facilitator in the progression of COVID-19. Indeed, when we retraced the steps of the SARS-CoV-2 infection we found evidence linking elevated glucose to each step of the life-cycle of the virus, progression of the disease, and presentation of symptoms. Specifically, elevations of glucose provide ideal conditions for the virus to evade and weaken the first level of the immune defense system in the lungs, gain access to deep alveolar cells, bind to the ACE2 receptor and enter the pulmonary cells, accelerate replication of the virus within cells increasing cell death and inducing an pulmonary inflammatory response, which overwhelms an already weakened innate immune system to trigger an avalanche of systemic infections, inflammation and cell damage, a cytokine storm and thrombotic events. We tested the feasibility of the hypothesis by analyzing data across papers, reconstructing atomistically the virus at the surface of the pulmonary airways, and performing quantitative computational modeling of the effects of glucose levels on the infection process. We conclude that elevation in glucose levels can facilitate the progression of the disease through multiple mechanisms and can explain much of the variance in disease severity seen across the population. The study proposes diagnostic recommendations, new areas of research and potential treatments, and cautions on treatment strategies and critical care conditions that induce elevations in blood glucose levels.\n\nHighlightsO_LIPatients with severe COVID-19 commonly present with elevated blood glucose levels.\nC_LIO_LIElevated blood glucose impacts numerous biochemical pathways that can facilitate many steps of the SARS-CoV-2 infection.\nC_LIO_LIElevated blood glucose increases glucose in the pulmonary airway surface liquid (ASL), which breaks down the primary innate antiviral defenses of the lungs and facilitates viral infection and replication.\nC_LIO_LIElevated blood glucose causes dysregulations of the immune response that facilitates the cytokine storm and acute respiratory distress syndrome (ARDS).\nC_LIO_LIElevated glucose levels act synergistically with SARS-CoV-2-dependent inactivation of angiotensin-converting enzyme 2 (ACE2) to escalate the disease to multi-organ failure and thrombotic events.\nC_LI\n\n\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=122 SRC=\"FIGDIR/small/21256294v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (52K):\norg.highwire.dtl.DTLVardef@14ccae0org.highwire.dtl.DTLVardef@9b3ce5org.highwire.dtl.DTLVardef@1bae6e7org.highwire.dtl.DTLVardef@18d6861_HPS_FORMAT_FIGEXP M_FIG C_FIG", + "rel_num_authors": 18, "rel_authors": [ { - "author_name": "Jianing Yang", - "author_inst": "Shanghai Institute of Nutrition and Health" + "author_name": "Emmanuelle Logette", + "author_inst": "Ecole Polytechnique Federale de Lausanne" }, { - "author_name": "Guoqing Zhang", - "author_inst": "Shanghai Institute of Nutrition and Health" + "author_name": "Charlotte Lorin", + "author_inst": "Ecole Polytechnique Federale de Lausanne" }, { - "author_name": "Dalang Yu", - "author_inst": "Shanghai Institute of Nutrition and Health" + "author_name": "Cyrille Pierre Henry Favreau", + "author_inst": "Ecole Polytechnique Federale de Lausanne" }, { - "author_name": "Ruifang Cao", - "author_inst": "Shanghai Institute of Nutrition and Health" + "author_name": "Eugenia Oshurko", + "author_inst": "Ecole Polytechnique Federale de Lausanne" }, { - "author_name": "Xiaoxian Wu", - "author_inst": "Institute of Plant Physiology and Ecology" + "author_name": "Jay S Coggan", + "author_inst": "Ecole Polytechnique Federale de Lausanne" }, { - "author_name": "Yunchao Ling", - "author_inst": "Shanghai Institute of Nutrition and Health" + "author_name": "Francesco Casalegno", + "author_inst": "Ecole Polytechnique Federale de Lausanne" }, { - "author_name": "Yi-Hsuan Pan", - "author_inst": "East China Normal University" + "author_name": "Mohameth Francois Sy", + "author_inst": "Ecole Polytechnique Federale de Lausanne" }, { - "author_name": "Chunyan Yi", - "author_inst": "Shanghai Institute of Biochemistry and Cell Biology" + "author_name": "Caitlin Monney", + "author_inst": "Ecole Polytechnique Federale de Lausanne" }, { - "author_name": "Xiaoyu Sun", - "author_inst": "Shanghai Institute of Biochemistry and Cell Biology" + "author_name": "Marine Laure Bertschy", + "author_inst": "Ecole Polytechnique Federale de Lausanne" }, { - "author_name": "Bing Sun", - "author_inst": "Shanghai Institute of Biochemistry and Cell Biology" + "author_name": "Emilie Delattre", + "author_inst": "Ecole Polytechnique Federale de Lausanne" }, { - "author_name": "Yu Zhang", - "author_inst": "Institute of Plant Physiology and Ecology" + "author_name": "Pierre-Alexandre Fonta", + "author_inst": "Ecole Polytechnique Federale de Lausanne" }, { - "author_name": "Guo-Ping Zhao", - "author_inst": "Institute of Plant Physiology and Ecology" + "author_name": "Jan Krepl", + "author_inst": "Ecole Polytechnique Federale de Lausanne" }, { - "author_name": "Yixue Li", - "author_inst": "Shanghai Institute of Nutrition and Health" + "author_name": "Stanislav Schmidt", + "author_inst": "Ecole Polytechnique Federale de Lausanne" }, { - "author_name": "Haipeng Li", - "author_inst": "Shanghai Institute of Nutrition and Health" + "author_name": "Daniel Keller", + "author_inst": "Ecole Polytechnique Federale de Lausanne" + }, + { + "author_name": "Samuel Kerrien", + "author_inst": "Ecole Polytechnique Federale de Lausanne" + }, + { + "author_name": "Enrico Scantamburlo", + "author_inst": "Ecole Polytechnique Federale de Lausanne" + }, + { + "author_name": "Anna-Kristin Kaufmann", + "author_inst": "Ecole Polytechnique Federale de Lausanne" + }, + { + "author_name": "Henry Markram", + "author_inst": "Ecole Polytechnique Federale de Lausanne" } ], "version": "1", - "license": "cc_by_nd", - "type": "new results", - "category": "evolutionary biology" + "license": "cc_no", + "type": "PUBLISHAHEADOFPRINT", + "category": "infectious diseases" }, { "rel_doi": "10.1101/2021.04.28.21256243", @@ -780141,39 +779604,47 @@ "category": "biophysics" }, { - "rel_doi": "10.1101/2021.04.29.442038", - "rel_title": "ACE2 glycans preferentially interact with the RBD of SARS-CoV-2 over SARS-CoV", + "rel_doi": "10.1101/2021.04.30.442139", + "rel_title": "Cell-free glycoengineering of the recombinant SARS-CoV-2 spike glycoprotein", "rel_date": "2021-04-30", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.04.29.442038", - "rel_abs": "We report a distinct difference in the interactions of the glycans of the host-cell receptor, ACE2, with SARS-CoV-2 and SARS-CoV S-protein receptor-binding domains (RBDs). Our analysis demonstrates that the ACE2 glycan at N90 may offer protection against infections of both coronaviruses, while the ACE2 glycan at N322 enhances interactions with the SARS-CoV-2 RBD. The interactions of the ACE2 glycan at N322 with SARS-CoV RBD are blocked by the presence of the RBD glycan at N357 of the SARS-CoV RBD. The absence of this glycosylation site on SARS-CoV-2 RBD may enhance its binding with ACE2.", - "rel_num_authors": 5, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.04.30.442139", + "rel_abs": "The baculovirus-insect cell expression system is readily utilized to produce viral glycoproteins for research as well as for subunit vaccines and vaccine candidates, for instance against SARS-CoV-2 infections. However, the glycoforms of recombinant proteins derived from this expression system are inherently different from mammalian cell-derived glycoforms with mainly complex-type N-glycans attached, and the impact of these differences in protein glycosylation on the immunogenicity is severely underinvestigated. This applies also to the SARS-CoV-2 spike glycoprotein, which is the antigen target of all licensed vaccines and vaccine candidates including virus like particles and subunit vaccines that are variants of the spike protein. Here, we expressed the transmembrane-deleted human {beta}-1,2 N-acetlyglucosamintransferases I and II (MGAT1{triangleup}TM and MGAT2{triangleup}TM) and the {beta}-1,4-galactosyltransferase (GalT{triangleup}TM) in E. coli to in-vitro remodel the N-glycans of a recombinant SARS-CoV-2 spike glycoprotein derived from insect cells. In a cell-free sequential one-pot reaction, fucosylated and afucosylated paucimannose-type N-glycans were converted to complex-type galactosylated N-glycans. In the future, this in-vitro glycoengineering approach can be used to efficiently generate a wide range of N-glycans on antigens considered as vaccine candidates for animal trials and preclinical testing to better characterize the impact of N-glycosylation on immunity and to improve the efficacy of protein subunit vaccines.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Atanu Acharya", - "author_inst": "Georgia Institute of Technology" + "author_name": "Johannes Ruhnau", + "author_inst": "Max Planck Institute for Dynamics of Complex Technical Systems, Bioprocess Engineering" }, { - "author_name": "Diane Lynch", - "author_inst": "Georgia Institute of Technology" + "author_name": "Valerian Grote", + "author_inst": "Max Planck Institute for Dynamics of Complex Technical Systems, Bioprocess Engineering" }, { - "author_name": "Anna Pavlova", - "author_inst": "Georgia Institute of Technology" + "author_name": "Mariana Juarez-Osorio", + "author_inst": "Max Planck Institute for Dynamics of Complex Technical Systems, Bioprocess Engineering" }, { - "author_name": "Yui Tik Pang", - "author_inst": "Georgia Institute of Technology" + "author_name": "Dunja Bruder", + "author_inst": "Infection Immunology Group, Institute of Medical Microbiology, Infection Prevention and Control, Health Campus Immunology, Infectiology and Inflammation, OvGU M" }, { - "author_name": "James Gumbart", - "author_inst": "Georgia Institute of Technology" + "author_name": "Erdmann Rapp", + "author_inst": "Max Planck Institute for Dynamics of Complex Technical Systems, Bioprocess Engineering & glyXera GmbH" + }, + { + "author_name": "Thomas F. T. Rexer", + "author_inst": "Max Planck Institute for Dynamics of Complex Technical Systems, Bioprocess Engineering" + }, + { + "author_name": "Udo Reichl", + "author_inst": "Max Planck Institute for Dynamics of Complex Technical Systems, Bioprocess Engineering" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "new results", - "category": "biophysics" + "category": "synthetic biology" }, { "rel_doi": "10.1101/2021.04.30.442182", @@ -782143,37 +781614,101 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.04.26.21256093", - "rel_title": "Impairment of T cells' antiviral and anti-inflammation immunities dominates the death from COVID-19", + "rel_doi": "10.1101/2021.04.27.21254849", + "rel_title": "Local emergence and decline of a SARS-CoV-2 variant with mutations L452R and N501Y in the spike protein", "rel_date": "2021-04-29", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.26.21256093", - "rel_abs": "Clarifying dominant factors determining the immune heterogeneity from non-survivors to survivors is crucial for developing therapeutics and vaccines against COVID-19. The main difficulty is quantitatively analyzing the multi-level clinical data, including viral dynamics, immune response, and tissue damages. Here, we adopt a top-down modelling approach to quantify key functional aspects and their dynamical interplay in the battle between the virus and the immune system, yielding an accurate description of real-time clinical data involving hundreds of patients for the first time. The quantification of antiviral responses demonstrates that, compared to antibodies, T cells play a more dominant role in virus clearance, especially for mild patients (96.5%). Moreover, the anti-inflammatory responses, namely the cytokine inhibition and tissue repair rates, also positively correlate with T cell number and are significantly suppressed in non-survivors. Simulations show that the lack of T cells leads to more significant inflammation, proposing an explanation for the monotonous increase of COVID-19 mortality with age and higher mortality for males. We conclude that T cells play a crucial role in the immunity against COVID-19, which reveals a new direction----improvement of T cell number for advancing current prevention and treatment.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.27.21254849", + "rel_abs": "Variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are replacing the initial wild-type strain, jeopardizing current efforts to contain the pandemic. Amino acid exchanges in the spike protein are of particular concern as they can render the virus more transmissible or reduce vaccine efficacy. Here, we conducted whole genome sequencing of SARS-CoV-2 positive samples from the Rhine-Neckar district in Germany during January-March 2021. We detected a total of 166 samples positive for a variant with a distinct mutational pattern in the spike gene comprising L18F, L452R, N501Y, A653V, H655Y, D796Y and G1219V with a later gain of A222V. This variant was designated A.27.RN according to its phylogenetic clade classification. It emerged in parallel with the B.1.1.7 variant, increased to >50% of all SARS-CoV-2 variants by week five. Subsequently it decreased to <10% of all variants by calendar week eight when B.1.1.7 had become the dominant strain. Antibodies induced by BNT162b2 vaccination neutralized A.27.RN but with a two-to-threefold reduced efficacy as compared to the wild-type and B.1.1.7 strains. These observations strongly argue for continuous and comprehensive monitoring of SARS-CoV-2 evolution on a population level.", + "rel_num_authors": 21, "rel_authors": [ { - "author_name": "Zhen-su She", - "author_inst": "Peking University" + "author_name": "Jan-Philipp Mallm", + "author_inst": "German Cancer Research Center (DKFZ)" }, { - "author_name": "Gregory Scholes", - "author_inst": "Princeton University" + "author_name": "Christian Bundschuh", + "author_inst": "Heidelberg University" }, { - "author_name": "Luhao Zhang", - "author_inst": "Princeton University" + "author_name": "Heeyoung Kim", + "author_inst": "Heidelberg University" }, { - "author_name": "Rong Li", - "author_inst": "Peking University" + "author_name": "Niklas Weidner", + "author_inst": "Heidelberg University" + }, + { + "author_name": "Simon Steiger", + "author_inst": "German Cancer Research Center (DKFZ)" + }, + { + "author_name": "Isabelle Lander", + "author_inst": "German Cancer Research Center (DKFZ)" + }, + { + "author_name": "Kathleen B\u00f6rner", + "author_inst": "Heidelberg University" + }, + { + "author_name": "Katharina Bauer", + "author_inst": "German Cancer Research Center (DKFZ)" + }, + { + "author_name": "Daniel H\u00fcbschmann", + "author_inst": "German Cancer Research Center (DKFZ)" + }, + { + "author_name": "Vladimir Benes", + "author_inst": "European Molecular Biology Laboratory (EMBL)" + }, + { + "author_name": "Tobias Rausch", + "author_inst": "European Molecular Biology Laboratory (EMBL)" + }, + { + "author_name": "Nayara Trevisan Doimo de Azevedo", + "author_inst": "European Molecular Biology Laboratory (EMBL)" + }, + { + "author_name": "Anja Telzerow", + "author_inst": "European Molecular Biology Laboratory (EMBL)" + }, + { + "author_name": "Katharina Laurence Jost", + "author_inst": "Heidelberg University" }, { - "author_name": "Gang Song", - "author_inst": "Beijing Hospital" + "author_name": "Sylvia Parth\u00e9", + "author_inst": "Heidelberg University" + }, + { + "author_name": "Paul Schnitzler", + "author_inst": "Heidelberg University" + }, + { + "author_name": "Michael Boutros", + "author_inst": "German Cancer Research Center (DKFZ)" + }, + { + "author_name": "Barbara M\u00fcller", + "author_inst": "Heidelberg University" + }, + { + "author_name": "Ralf Bartenschlager", + "author_inst": "Heidelberg University" + }, + { + "author_name": "Hans-Georg Kr\u00e4usslich", + "author_inst": "Heidelberg University" + }, + { + "author_name": "Karsten Rippe", + "author_inst": "German Cancer Research Center (DKFZ)" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -784017,47 +783552,35 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2021.04.27.21256221", - "rel_title": "The herbal combination of Sugarcane, Black Myrobalan, and mastic as a supplementary treatment for COVID-19: a randomized clinical trial", - "rel_date": "2021-04-28", + "rel_doi": "10.1101/2021.04.24.21255968", + "rel_title": "MORTALITY OF CARE HOME RESIDENTS AND COMMUNITY-DWELLING CONTROLS DURING THE COVID-19 PANDEMIC IN 2020: MATCHED COHORT STUDY", + "rel_date": "2021-04-27", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.27.21256221", - "rel_abs": "BackgroundGiven the COVID-19 pandemics, researchers are beseeched for effective treatments. Herbal medicine is also queried for potential supplementary treatments for COVID-19. We aimed to evaluate the effects of Sugarcane, Black Myrobalan, and Mastic herbal medications for COVID-19 patients.\n\nMethodsThis was a double-blinded randomized clinical trial study conducted over three months from May to July 2020 in patients admitted with a diagnosis of COVID-19 in Peymaniyeh Hospital in Jahrom, Iran. The intervention group received the treatment protocol approved by the Ministry of Health of Iran during the period of hospitalization and the herbal supplement obtained from the combination of black myrobalan and mastic and sugarcane, twice a day (3g of herbal supplements). All patients were compared in terms of demographic variables, vital signs, clinical and laboratory variables.\n\nResults72 patients with COVID-19, divided into intervention (n=37) and control (n=35) groups. intervention and control groups had not any significant difference in terms of baseline characteristics. The time-to-event analysis revealed a significant difference in 4 symptoms of cough, fever, dyspnea, and myalgia (P<0.05). The Control group had a significantly lower decrease in C-reactive protein during 7 days (P<0.05). Patients in the herbal supplement group were hospitalized for 4.12 days and in the control group were hospitalized for 8.37 days (P=0.001). ICU admission and death only happened in 3 (8.6%) patients of the control group.\n\nConclusionWhile advanced studies with more sample size are needed; the proposed combination seems to be effective in the symptom treatment and reducing the length of hospitalization.", - "rel_num_authors": 7, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.24.21255968", + "rel_abs": "ObjectiveTo estimate mortality of care home (CH) residents, and matched community-dwelling controls, during the Covid-19 pandemic from primary care electronic health records.\n\nDesignMatched cohort study\n\nSettingGeneral practices contributing to the Clinical Practice Research Datalink Aurum Database in England.\n\nParticipantsThere were 83,627 CH residents contributing data in 2020, with 26,923 deaths; 80,730 (97%) were matched on age, gender and general practice with 300,445 community-dwelling adults.\n\nMain outcome measuresAll-cause mortality. Adjusted rate ratios (RR) by negative binomial regression were adjusted for age, gender, number of long-term conditions (LTCs), frailty category, region, calendar month or week, and clustering by general practice.\n\nResultsDuring April 2020, the mortality rate of CH residents was 27.2 deaths per 1,000 patients per week, compared with 2.31 per 1,000 for controls, RR 11.1 (95% confidence interval 10.1 to 12.2). Compared with CH residents, LTCs and frailty were differentially associated with greater mortality in community-dwelling controls. During April 2020, mortality rates per 1,000 patients per week for persons with 9+ LTCs were: CH, 37.9; controls 17.7; RR 2.14 (1.18 to 3.89). In severe frailty, mortality rates were: CH, 29.6; controls 5.1; RR 6.17 (5.74 to 6.62).\n\nConclusionsIndividual-patient data from primary care electronic health records may be used to estimate mortality in care home residents. Mortality is substantially higher than for community-dwelling comparators and showed a disproportionate increase in the first wave of the Covid-19 pandemic. Multiple morbidity and frailty were associated with greater absolute risks but lower relative risks because community-dwelling frail or multi-morbid patients also experienced high mortality.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Alireza Hashemi Shiri", - "author_inst": "Complementary Medicine Researcher, Jahrom University of Medical Sciences, Jahrom, Iran." - }, - { - "author_name": "Esmayil Rayatdoost", - "author_inst": "Department of Emergency Medicine, Jahrom University of Medical Sciences, Jahrom, Iran." - }, - { - "author_name": "Hamid Afkhami", - "author_inst": "Bachelor of Science in Medical Laboratory Science, Jahrom University of Medical Sciences, Jahrom, Iran." - }, - { - "author_name": "Ruhollah Ravanshad", - "author_inst": "Bachelor of Science in Nursing, Jahrom University of Medical Sciences, Jahrom, Iran." + "author_name": "Martin C Gulliford", + "author_inst": "King's College London" }, { - "author_name": "Seyed Ehsan Hosseini", - "author_inst": "Bachelor of Science in Nursing, Jahrom University of Medical Sciences, Jahrom, Iran." + "author_name": "A Toby Prevost", + "author_inst": "King's College London" }, { - "author_name": "Navid Kalani", - "author_inst": "Research center for social Determinants of Health, Jahrom University of Medical Sciences, Jahrom, Iran." + "author_name": "Andrew Clegg", + "author_inst": "University of Leeds" }, { - "author_name": "Rahim Raoufi", - "author_inst": "Department of Infectious Diseases, Faculty of Medicine, University of Medical Sciences, Jahrom, Iran." + "author_name": "Emma C Rezel-Potts", + "author_inst": "King's College London" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "respiratory medicine" + "category": "epidemiology" }, { "rel_doi": "10.1101/2021.04.24.21255655", @@ -785738,57 +785261,89 @@ "category": "biochemistry" }, { - "rel_doi": "10.1101/2021.04.27.441589", - "rel_title": "Long-lasting humoral immunity in Covid-19 infected patients at a University Hospital Clinic in Ostergotland County Council during 2020-2021.", + "rel_doi": "10.1101/2021.04.26.441518", + "rel_title": "Nucleocapsid vaccine elicits spike-independent SARS-CoV-2 protective immunity", "rel_date": "2021-04-27", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.04.27.441589", - "rel_abs": "Longitudinal serum samples and nasopharyngeal/nasal swab samples were collected from forty-eight individuals (median age 66yrs) with Covid-19 PCR-positive test results at Linkoping University Hospital. Samples were collected from initial visit and for 6 months follow up. Presence of serum IgG and IgA against SARS-CoV-2 antigens (S1-spike, nucleocapsid and NSP3) were analyzed. Nasal swabs were tested for presence of IgA against the outer envelope S1 spike protein. Ninety-two percent of participants were seropositive against SARS-CoV-2 recombinant proteins at day 28 from study entry and all (100%) were seropositive from samples collected at 2 months or later. The most common antibody responses (both serum IgG, mainly IgG1 and IgA) were detected against the S1-spike protein and the nucleoprotein. In samples collected from nasal tissues considerably lower frequencies of IgA-positive reactivities were detected. Sixteen to 18 percent of study participants showed detectable IgA levels in nasal samples, except at day 60 when 36% of tested individuals showed presence of IgA against the S1-spike protein. The study suggests that the absolute majority of studied naturally infected Covid-19 patient in the Linkoping, Ostergotland health region develop over 6 months lasting detectable levels of serum IgG and IgA responses towards the SARS-CoV-2 S1-spike protein as well as against the nucleoprotein, but not against the non-structural protein 3.", - "rel_num_authors": 11, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.04.26.441518", + "rel_abs": "Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is responsible for the COVID-19 pandemic. Neutralizing antibodies target the receptor binding domain of the spike (S) protein, a focus of successful vaccine efforts. Concerns have arisen that S-specific vaccine immunity may fail to neutralize emerging variants. We show that vaccination with HAd5 expressing the nucleocapsid (N) protein can establish protective immunity, defined by reduced weight loss and viral load, in both Syrian hamsters and k18-hACE2 mice. Challenge of vaccinated mice was associated with rapid N-specific T cell recall responses in the respiratory mucosa. This study supports the rationale for including additional viral antigens, even if they are not a target of neutralizing antibodies, to broaden epitope coverage and immune effector mechanisms.", + "rel_num_authors": 19, "rel_authors": [ { - "author_name": "Jorma Hinkula", - "author_inst": "Linkoping University" + "author_name": "William E Matchett", + "author_inst": "University of Minnesota" }, { - "author_name": "Mohammad Azharuddin", - "author_inst": "Linkoping University" + "author_name": "Vineet Joag", + "author_inst": "University of Minnesota" }, { - "author_name": "Daniel Aili", - "author_inst": "Linkopings Universitet" + "author_name": "James Michael Stolley", + "author_inst": "University of Minnesota" }, { - "author_name": "Sajjad Naeimipour", - "author_inst": "Linkoping University" + "author_name": "Frances K Shephard", + "author_inst": "University of Minnesota" }, { - "author_name": "Robert Selegard", - "author_inst": "Linkopings Universitet" + "author_name": "Clare F Quarnstrom", + "author_inst": "University of Minnesota" }, { - "author_name": "Maria Sunnerhagen", - "author_inst": "Linkopings Universitet" + "author_name": "Clayton K Mickelson", + "author_inst": "University of Minnesota" }, { - "author_name": "Hirak K Patra", - "author_inst": "Univercity College London" + "author_name": "Sathi Wijeyesinghe", + "author_inst": "University of Minnesota" }, { - "author_name": "Sofia K Sjoberg", - "author_inst": "Linkoping University hospital" + "author_name": "Andrew G Soerens", + "author_inst": "University of Minnesota" }, { - "author_name": "Katarina Niward", - "author_inst": "Linkoping University" + "author_name": "Samuel Becker", + "author_inst": "University of Minnesota" }, { - "author_name": "Hakan Hanberger", - "author_inst": "Linkoping University" + "author_name": "Joshua M Thiede", + "author_inst": "University of Minnesota" + }, + { + "author_name": "Eyob Weyu", + "author_inst": "University of Minnesota" + }, + { + "author_name": "Jennifer Walter", + "author_inst": "University of Minnesota" + }, + { + "author_name": "Michelle N Vu", + "author_inst": "University of Texas Medical Branch at Galveston" + }, + { + "author_name": "Vineet D Menachery", + "author_inst": "University of Texas Medical Branch" + }, + { + "author_name": "Tyler D. Bold", + "author_inst": "University of Minnesota" + }, + { + "author_name": "Vaiva Vezys", + "author_inst": "University of Minnesota" }, { - "author_name": "Asa Ostholm-Balked", - "author_inst": "Linkoping University hospital" + "author_name": "Marc K Jenkins", + "author_inst": "University of Minnesota" + }, + { + "author_name": "Ryan A. Langlois", + "author_inst": "University of Minnesota" + }, + { + "author_name": "David Masopust", + "author_inst": "University of Minnesota" } ], "version": "1", @@ -787504,63 +787059,59 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2021.04.23.441187", - "rel_title": "Predicted structural mimicry of spike receptor-binding motifs from highly pathogenic human coronaviruses", + "rel_doi": "10.1101/2021.04.22.21255922", + "rel_title": "Role of non-aerosols activities in the transmission of SARS-Cov-2 infection among health care workers.", "rel_date": "2021-04-26", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.04.23.441187", - "rel_abs": "Viruses often encode proteins that mimic host proteins in order to facilitate infection. Little work has been done to understand the potential mimicry of the SARS-CoV-2, SARS-CoV, and MERS-CoV spike proteins, particularly the receptor-binding motifs, which could be important in determining tropism of the virus. Here, we use structural bioinformatics software to characterize potential mimicry of the three coronavirus spike protein receptor-binding motifs. We utilize sequence-independent alignment tools to compare structurally known or predicted three-dimensional protein models with the receptor-binding motifs and verify potential mimicry with protein docking simulations. Both human and non-human proteins were found to be similar to all three receptor-binding motifs. Similarity to human proteins may reveal which pathways the spike protein is co-opting, while analogous non-human proteins may indicate shared host interaction partners and overlapping antibody cross-reactivity. These findings can help guide experimental efforts to further understand potential interactions between human and coronavirus proteins.\n\nHighlightsO_LIPotential coronavirus spike protein mimicry revealed by structural comparison\nC_LIO_LIHuman and non-human protein potential interactions with virus identified\nC_LIO_LIPredicted structural mimicry corroborated by protein-protein docking\nC_LIO_LIEpitope-based alignments may help guide vaccine efforts\nC_LI\n\nGraphical abstract\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=111 SRC=\"FIGDIR/small/441187v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (22K):\norg.highwire.dtl.DTLVardef@1f09454org.highwire.dtl.DTLVardef@19a5557org.highwire.dtl.DTLVardef@158d3fdorg.highwire.dtl.DTLVardef@c59511_HPS_FORMAT_FIGEXP M_FIG C_FIG", - "rel_num_authors": 11, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.22.21255922", + "rel_abs": "BackgroundSince the emergence of SARS-CoV-2, health care workers (HCWs) have been on the front line in caring for COVID-19 patients. Better knowledge of risk factors for SARS-CoV-2 infection is crucial for the prevention of disease among this population.\n\nMethodsWe conducted a seroprevalence survey among HCWs in a French university hospital after the first wave (May-June 2020), based on a validated lateral flow immuno-assay test (LFIAT) for SARS-CoV-2. Demographic characteristics as well as data on the working characteristics of COVID-19 and non-COVID-19 wards and 23 care activities were systematically recorded. The effectiveness of protective equipment was also estimated, based on self-declaration of mask use. SARS-CoV-2 IgG status was modelled by multiple imputations approach, accounting for the performance of the test and data on serum validation ELISA immunoassay.\n\nFindingsAmong the 3,234 enrolled HCWs, the prevalence of SARS-CoV-2 IgG was 3.8%. Contact with relatives or HCWs who developed COVID-19 were risk factors for SARS-CoV-2 infection, but not contact with COVID-19 patients. In multivariate analyses, suboptimal use of protective equipment during naso-pharyngeal sampling, patient mobilisation, clinical and eye examination was associated with SARS-CoV-2 infection. In addition, patients washing and dressing and aerosol-generating procedures were risk factors for SARS-CoV-2 infection with or without self-declared appropriate use of protective equipment.\n\nInterpretationMain routes of transmission of SARS-CoV-2 IgG among HCWs were i) contact with relatives or HCWs with COVID-19, ii) close or prolonged contact with patients, iii) aerosol-generating procedures.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Christopher A Beaudoin", - "author_inst": "University of Cambridge" + "author_name": "Christophe Paris Pr", + "author_inst": "University Hospital Rennes" }, { - "author_name": "Arian Rokkum Jamasb", - "author_inst": "University of Cambridge" + "author_name": "Emilie Tadie MD", + "author_inst": "University Hospital Rennes" }, { - "author_name": "Ali Alsulami", - "author_inst": "University of Cambridge" + "author_name": "Christopher Heslan MD", + "author_inst": "University Hospital Rennes" }, { - "author_name": "Liviu Copoiu", - "author_inst": "University of Cambridge" + "author_name": "Pierre Gary-Bobo MD", + "author_inst": "University Hospital Rennes" }, { - "author_name": "Andries J van Tonder", - "author_inst": "University of Cambridge" + "author_name": "Sitty Oumary MD", + "author_inst": "University Hospital Rennes" }, { - "author_name": "Sharif Hala", - "author_inst": "King Saud bin Abdulaziz University for Health Sciences" + "author_name": "Anais Sitruck Miss", + "author_inst": "Inserm IRSET" }, { - "author_name": "Bridget P Bannerman", - "author_inst": "University of Cambridge" + "author_name": "Pascal Wild PhD", + "author_inst": "INRS" }, { - "author_name": "Sherine E Thomas", - "author_inst": "University of Cambridge" + "author_name": "Pierre Tattevin Pr", + "author_inst": "University Hospital Rennes" }, { - "author_name": "Sundeep Chaitanya Vedithi", - "author_inst": "University of Cambridge" + "author_name": "Vincent Thibault Pr", + "author_inst": "University Hospital Rennes" }, { - "author_name": "Pedro H M Torres", - "author_inst": "Universidade Federal do Rio de Janeiro" - }, - { - "author_name": "Tom L Blundell", - "author_inst": "University of Cambridge" + "author_name": "Ronan Garlantezec Pr", + "author_inst": "University Hospital Rennes" } ], "version": "1", - "license": "cc_no", - "type": "new results", - "category": "bioinformatics" + "license": "cc_by_nc_nd", + "type": "PUBLISHAHEADOFPRINT", + "category": "occupational and environmental health" }, { "rel_doi": "10.1101/2021.04.23.21255815", @@ -789202,51 +788753,43 @@ "category": "intensive care and critical care medicine" }, { - "rel_doi": "10.1101/2021.04.17.21255642", - "rel_title": "Monitoring global trends in Covid-19 vaccination intention and confidence: a social media-based deep learning study", + "rel_doi": "10.1101/2021.04.23.21255564", + "rel_title": "County-Level Estimates of Excess Mortality associated with COVID-19 in the United States", "rel_date": "2021-04-25", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.17.21255642", - "rel_abs": "BackgroundThis study developed deep learning models to monitor global intention and confidence of Covid-19 vaccination in real time.\n\nMethodsWe collected 6.73 million English tweets regarding Covid-19 vaccination globally from January 2020 to February 2021. Fine-tuned Transformer-based deep learning models were used to classify tweets in real time as they relate to Covid-19 vaccination intention and confidence. Temporal and spatial trends were performed to map the global prevalence of Covid-19 vaccination intention and confidence, and public engagement on social media was analyzed.\n\nFindingsGlobally, the proportion of tweets indicating intent to accept Covid-19 vaccination declined from 64.49% on March to 39.54% on September 2020, and then began to recover, reaching 52.56% in early 2021. This recovery in vaccine acceptance was largely driven by the US and European region, whereas other regions experienced the declining trends in 2020. Intent to accept and confidence of Covid-19 vaccination were relatively high in South-East Asia, Eastern Mediterranean, and Western Pacific regions, but low in American, European, and African regions. 12.71% tweets expressed misinformation or rumors in South Korea, 14.04% expressed distrust in government in the US, and 16.16% expressed Covid-19 vaccine being unsafe in Greece, ranking first globally. Negative tweets, especially misinformation or rumors, were more engaged by twitters with fewer followers than positive tweets.\n\nInterpretationThis global real-time surveillance study highlights the importance of deep learning based social media monitoring to detect emerging trends of Covid-19 vaccination intention and confidence to inform timely interventions.\n\nFundingNational Natural Science Foundation of China.\n\nResearch in contextO_ST_ABSEvidence before this studyC_ST_ABSWith COVID-19 vaccine rollout, each country should investigate its vaccination intention in local contexts to ensure massive vaccination. We searched PubMed for all articles/preprints until April 9, 2021 with the keywords \"(\"Covid-19 vaccines\"[Mesh] OR Covid-19 vaccin*[TI]) AND (confidence[TI] OR hesitancy[TI] OR acceptance[TI] OR intention[TI])\". We identified more than 100 studies, most of which are country-level cross-sectional surveys, and the largest global survey of Covid-19 vaccine acceptance only covered 32 countries to date. However, how Covid-19 vaccination intention changes over time remain unknown, and many countries are not covered in previous surveys yet. A few studies assessed public sentiments towards Covid-19 vaccination using social media data, but only targeting limited geographical areas. There is a lack of real-time surveillance, and no study to date has globally monitored Covid-19 vaccination intention in real time.\n\nAdded value of this studyTo our knowledge, this is the largest global monitoring study of Covid-19 vaccination intention and confidence with social media data in over 100 countries from the beginning of the pandemic to February 2021. This study developed deep learning models by fine-tuning a Bidirectional Encoder Representation from Transformer (BERT)-based model with 8000 manually-classified tweets, which can be used to monitor Covid-19 vaccination beliefs using social media data in real time. It achieves temporal and spatial analyses of the evolving beliefs to Covid-19 vaccines across the world, and also an insight for many countries not yet covered in previous surveys. This study highlights that the intention to accept Covid-19 vaccination have experienced a declining trend since the beginning of the pandemic in all world regions, with some regions recovering recently, though not to their original levels. This recovery was largely driven by the US and European region (EUR), whereas other regions experienced the declining trends in 2020. Intention to accept and confidence of Covid-19 vaccination were relatively high in South-East Asia region (SEAR), Eastern Mediterranean region (EMR), and Western Pacific region (WPR), but low in American region (AMR), EUR, and African region (AFR). Many AFR countries worried more about vaccine effectiveness, while EUR, AMR, and WPR concerned more about vaccine safety (the most concerns with 16.16% in Greece). Online misinformation or rumors were widespread in AMR, EUR, and South Korea (12.71%, ranks first globally), and distrust in government was more prevalent in AMR (14.04% in the US, ranks first globally). Our findings can be used as a reference point for survey data on a single country in the future, and inform timely and specific interventions for each country to address Covid-19 vaccine hesitancy.\n\nImplications of all the available evidenceThis global real-time surveillance study highlights the importance of deep learning based social media monitoring as a quick and effective method for detecting emerging trends of Covid-19 vaccination intention and confidence to inform timely interventions, especially in settings with limited sources and urgent timelines. Future research should build multilingual deep learning models and monitor Covid-19 vaccination intention and confidence in real time with data from multiple social media platforms.", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.23.21255564", + "rel_abs": "BackgroundThe COVID-19 pandemic in the U.S. has been largely monitored on the basis of death certificates containing reference to COVID-19. However, prior analyses reveal that a significant percentage of excess deaths associated with the pandemic were not directly assigned to COVID-19.\n\nMethodsIn the present study, we estimate a generalized linear model of expected mortality in 2020 based on historical trends in deaths by county of residence between 2011 and 2019. We use the results of the model to generate estimates of excess mortality and excess deaths not assigned to COVID-19 for 1,470 county-sets in the U.S. representing 3,138 counties.\n\nResultsDuring 2020, more than one-fourth of U.S. residents (91.2 million) lived in counties where less than 75% of excess deaths were assigned to COVID-19. Across the country, we estimated that 439,698 excess deaths occurred in 2020, among which 86.7% were assigned to COVID-19. Some regions (Mideast, Great Lakes, New England, and Far West) reported the most excess deaths in large central metros, whereas other regions (Southwest, Southeast, Plains, and Rocky Mountains) reported the highest excess mortality in nonmetro areas. The proportion assigned to COVID-19 was lowest in large central metro areas (79.3%) compared to medium or small metros (87.4%), nonmetro areas (89.4%) and large fringe metros (95.2%). Regionally, the proportion of excess deaths assigned to COVID-19 was lowest in the Southeast (81.1%), Far West (81.2%), Southwest (82.6%), and Rocky Mountains (85.2%). Across the regions, the number of excess deaths exceeded the number of directly assigned COVID-19 deaths in the majority of counties. The exception to this was in New England, which reported more directly assigned COVID-19 deaths than excess deaths in large central metro areas, large fringe metros, and medium or small metros.\n\nConclusionsAcross the U.S., many counties had substantial numbers of excess deaths that were not accounted for in direct COVID-19 death counts. Estimates of excess mortality at the local level can inform the allocation of resources to areas most impacted by the pandemic and contribute to positive protective behavior feedback loops (i.e. increases in mask-wearing and vaccine uptake).", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Xinyu Zhou", - "author_inst": "Fudan University" + "author_name": "Calvin A. Ackley", + "author_inst": "U.S. Bureau of Economic Analysis" }, { - "author_name": "Alex de Figueiredo", - "author_inst": "London School of Hygiene and Tropical Medicine" - }, - { - "author_name": "Qin Xu", - "author_inst": "Fudan University" - }, - { - "author_name": "Leesa Lin", - "author_inst": "London School of Hygiene and Tropical Medicine" + "author_name": "Dielle J. Lundberg", + "author_inst": "Boston University School of Public Health" }, { - "author_name": "Per E Kummervold", - "author_inst": "FISABIO-Public Health" + "author_name": "Lei Ma", + "author_inst": "Boston University" }, { - "author_name": "Heidi Larson", - "author_inst": "London School of Hygiene and Tropical Medicine" + "author_name": "Irma T. Elo", + "author_inst": "University of Pennsylvania" }, { - "author_name": "Mark Jit", - "author_inst": "London School of Hygiene & Tropical Medicine" + "author_name": "Samuel H. Preston", + "author_inst": "University of Pennsylvania" }, { - "author_name": "Zhiyuan Hou", - "author_inst": "Fudan University" + "author_name": "Andrew C Stokes", + "author_inst": "Boston University School of Public Health" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "epidemiology" }, { "rel_doi": "10.1101/2021.04.23.21255984", @@ -790684,97 +790227,49 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.04.22.21255913", - "rel_title": "Impact of vaccination on SARS-CoV-2 cases in the community: a population-based study using the UK COVID-19 Infection Survey", + "rel_doi": "10.1101/2021.04.21.21255873", + "rel_title": "Real World Effectiveness of COVID-19 mRNA Vaccines against Hospitalizations and Deaths in the United States", "rel_date": "2021-04-23", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.22.21255913", - "rel_abs": "ObjectivesTo assess the effectiveness of COVID-19 vaccination in preventing SARS-CoV-2 infection in the community.\n\nDesignProspective cohort study.\n\nSettingThe UK population-representative longitudinal COVID-19 Infection Survey.\n\nParticipants373,402 participants aged [≥]16 years contributing 1,610,562 RT-PCR results from nose and throat swabs between 1 December 2020 and 3 April 2021.\n\nMain outcome measuresNew RT-PCR-positive episodes for SARS-CoV-2 overall, by self-reported symptoms, by cycle threshold (Ct) value (<30 versus [≥]30), and by gene positivity (compatible with the B.1.1.7 variant versus not).\n\nResultsOdds of new SARS-CoV-2 infection were reduced 65% (95% CI 60 to 70%; P<0.001) in those [≥]21 days since first vaccination with no second dose versus unvaccinated individuals without evidence of prior infection (RT-PCR or antibody). In those vaccinated, the largest reduction in odds was seen post second dose (70%, 95% CI 62 to 77%; P<0.001).There was no evidence that these benefits varied between Oxford-AstraZeneca and Pfizer-BioNTech vaccines (P>0.9).There was no evidence of a difference in odds of new SARS-CoV-2 infection for individuals having received two vaccine doses and with evidence of prior infection but not vaccinated (P=0.89). Vaccination had a greater impact on reducing SARS-CoV-2 infections with evidence of high viral shedding Ct<30 (88% reduction after two doses; 95% CI 80 to 93%; P<0.001) and with self-reported symptoms (90% reduction after two doses; 95% CI 82 to 94%; P<0.001); effects were similar for different gene positivity patterns.\n\nConclusionVaccination with a single dose of Oxford-AstraZeneca or Pfizer-BioNTech vaccines, or two doses of Pfizer-BioNTech, significantly reduced new SARS-CoV-2 infections in this large community surveillance study. Greater reductions in symptomatic infections and/or infections with a higher viral burden are reflected in reduced rates of hospitalisations/deaths, but highlight the potential for limited ongoing transmission from asymptomatic infections in vaccinated individuals.\n\nRegistrationThe study is registered with the ISRCTN Registry, ISRCTN21086382.", - "rel_num_authors": 20, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.21.21255873", + "rel_abs": "The authors have withdrawn this manuscript because they are continuing to review the analytical methods utilized in this iteration of the work and, as of yet, do not have adequate confidence in their reproducibility. Therefore, the authors do not wish this work to be cited as reference for the project. If you have any questions, please contact the corresponding author.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Emma Pritchard", - "author_inst": "University of Oxford" - }, - { - "author_name": "Philippa Matthews", - "author_inst": "University of Oxford" - }, - { - "author_name": "Nicole Stoesser", - "author_inst": "University of Oxford" - }, - { - "author_name": "David Eyre", - "author_inst": "University of Oxford" - }, - { - "author_name": "Owen Gethings", - "author_inst": "Office for National Statistics" - }, - { - "author_name": "Karina-Doris Vitha", - "author_inst": "University of Oxford" - }, - { - "author_name": "Joel Jones", - "author_inst": "Office for National Statistics" - }, - { - "author_name": "Thomas House", - "author_inst": "University of Manchester" - }, - { - "author_name": "Harper VanSteenhouse", - "author_inst": "Glasgow Lighthouse Laboratory" - }, - { - "author_name": "Iain Bell", - "author_inst": "Office for National Statistics" - }, - { - "author_name": "John Bell", - "author_inst": "University of Oxford" - }, - { - "author_name": "John Newton", - "author_inst": "Public Health England" - }, - { - "author_name": "Jeremy Farrar", - "author_inst": "Wellcome Trust" + "author_name": "Farhaan S Vahidy", + "author_inst": "Houston Methodist" }, { - "author_name": "Ian Diamond", - "author_inst": "Office for National Statistics," + "author_name": "Lauren Pischel", + "author_inst": "Yale University School of Medicine" }, { - "author_name": "Emma Rourke", - "author_inst": "Office for National Statistics" + "author_name": "Mauricio E Tano", + "author_inst": "Houston Methodist" }, { - "author_name": "Ruth Studley", - "author_inst": "Office for National Statistics" + "author_name": "Alan P Pan", + "author_inst": "Houston Methodist" }, { - "author_name": "Derrick W Crook", - "author_inst": "NIHR Oxford Biomedical Research Centre" + "author_name": "Marc L Boom", + "author_inst": "Houston Methodist" }, { - "author_name": "tim E peto", - "author_inst": "oxford university" + "author_name": "Henry Dirk Sostman", + "author_inst": "Houston Methodist" }, { - "author_name": "Ann Sarah Walker", - "author_inst": "University of Oxford" + "author_name": "Khurram Nasir", + "author_inst": "Houston Methodist" }, { - "author_name": "Koen B Pouwels", - "author_inst": "University of Oxford" + "author_name": "Saad B Omer", + "author_inst": "Yale Institute for Global Health" } ], "version": "1", - "license": "cc_by", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -792730,33 +792225,45 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.04.20.21255796", - "rel_title": "Analysis of the Number of Tests, the Positivity Rate, and Their Dependency Structure during COVID-19 Pandemic", + "rel_doi": "10.1101/2021.04.20.21255829", + "rel_title": "Manufacturer Signal-to-Cutoff Threshold Underestimates Cumulative Incidence of SARS-CoV-2 Infection: Evidence from the Los Angeles Firefighters Study", "rel_date": "2021-04-23", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.20.21255796", - "rel_abs": "BackgroundApplying recent advances in medical instruments, information technology, and unprecedented data sharing into COVID-19 research revolutionized medical sciences, and causes some unprecedented analyses, discussions, and models.\n\nMethodsModeling of this dependency is done using four classes of copulas: Clayton, Frank, Gumbel, and FGM. The estimation of the parameters of the copulas is obtained using the maximum likelihood method. To evaluate the goodness of fit of the copulas, we calculate AIC. All computations are conducted on Matlab R2015b, R 4.0.3, Maple 2018a, and EasyFit 5.6, and the plots are created on software Matlab R2015b and R 4.0.3.\n\nResultsAs time passes, the number of tests increases, and the positivity rate becomes lower. The epidemic peaks are occasions that violate the stated general rule -due to the early growth of the number of tests. If we divide data of each country into peaks and otherwise, about both of them, the rising number of tests is accompanied by decreasing the positivity rate.\n\nConclusionThe positivity rate can be considered a representative of the level of the spreading. Approaching zero positivity rate is a good criterion to scale the success of a health care system in fighting against an epidemic. We expect that if the number of tests is great enough, the positivity rate does not depend on the number of tests. Accordingly, the number and accuracy of tests can play a vital role in the quality level of epidemic data.\n\nKey messages- In a country, increasing the positivity rate is more representative than increasing the number of tests to warn about an epidemic peak.\n- Approaching zero positivity rate is a good criterion to scale the success of a health care system in fighting against an epidemic.\n- Except for the first half of the epidemic peaks, in a country, the higher number of tests is associated with a lower positivity rate.\n- In countries with high test per million, there is no significant dependency between the number of tests and positivity rate.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.20.21255829", + "rel_abs": "While SARS-CoV-2 serologic testing is used to measure cumulative incidence of COVID-19, appropriate signal-to-cut off (S/Co) thresholds remain unclear. We demonstrate S/Co thresholds based on known negative samples significantly increases seropositivity and more accurately estimates cumulative incidence of disease compared to manufacturer-based thresholds.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Babak Jamshidi", - "author_inst": "Kermanshah University of Medical Sciences" + "author_name": "Omar Toubat", + "author_inst": "Keck School of Medicine of USC" }, { - "author_name": "Hakim Bekrizadeh", - "author_inst": "Payame Noor University" + "author_name": "Anders H. Berg", + "author_inst": "Cedars-Sinai Medical Center" }, { - "author_name": "Shahriar Jamshidi Zargaran", - "author_inst": "Isfahan University of Medical Sciences" + "author_name": "Kimia Sobhani", + "author_inst": "Cedars-Sinai Medical Center" }, { - "author_name": "Mansour Rezaei", - "author_inst": "Kermanshah University of Medical Sciences" + "author_name": "Karen Mulligan", + "author_inst": "University of Southern California" + }, + { + "author_name": "Acacia M. Hori", + "author_inst": "Keck School of Medicine of USC" + }, + { + "author_name": "Jay Bhattacharya", + "author_inst": "Stanford University" + }, + { + "author_name": "Neeraj Sood", + "author_inst": "University of Southern California" } ], "version": "1", - "license": "cc_by", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -794460,18 +793967,51 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.04.21.440861", - "rel_title": "InterARTIC: an interactive web application for whole-genome nanopore sequencing analysis of SARS-CoV-2 and other viruses", + "rel_doi": "10.1101/2021.04.22.21255574", + "rel_title": "Mutation-specific SARS-CoV-2 PCR Screen: Rapid and Accurate Detection of Variants of Concern and the Identification of a Newly Emerging Variant with Spike L452R Mutation", "rel_date": "2021-04-22", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.04.21.440861", - "rel_abs": "MotivationInterARTIC is an interactive web application for the analysis of viral whole-genome sequencing (WGS) data generated on Oxford Nanopore Technologies (ONT) devices. A graphical interface enables users with no bioinformatics expertise to analyse WGS experiments and reconstruct consensus genome sequences from individual isolates of viruses, such as SARS-CoV-2. InterARTIC is intended to facilitate widespread adoption and standardisation of ONT sequencing for viral surveillance and molecular epidemiology.\n\nWorked exampleWe demonstrate the use of InterARTIC for the analysis of ONT viral WGS data from SARS-CoV-2 and Ebola virus, using a laptop computer or the internal computer on an ONT GridION sequencing device. We showcase the intuitive graphical interface, workflow customisation capabilities and job-scheduling system that facilitate execution of small- and large-scale WGS projects on any common virus.\n\nImplementationInterARTIC is a free, open-source web application implemented in Python. The application can be downloaded as a set of pre-compiled binaries that are compatible with all common Ubuntu distributions, or built from source. For further details please visit: https://github.com/Psy-Fer/interARTIC/.", - "rel_num_authors": 0, - "rel_authors": null, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.22.21255574", + "rel_abs": "The emergence of more transmissible and/or more virulent SARS-CoV-2 variants of concern (VOCs) has triggered intensive genomic surveillance, which is costly and difficult to sustain operationally over the long-term. To address this problem, we developed a set of four multiplex mutation-specific PCR-based assays with same-day reporting that can detect five VOCs and three variants of interest (VOIs), as defined in the March 2021 guidelines from the United States (US) Centers for Disease Control and Prevention. The screening results were compared to the whole genome sequencing (WGS) and showed 100% concordance for strain typing for B.1.1.7 (25) and P.1 (5) variants using Spike (S) mutations N501Y, E484K and H69_V70del assays. The S L450R assay, designed to detect the B.1.427/429 VOCs, also identified multiple isolates of a newly emerging multiply-mutated B.1.526.1 variant that is now rapidly increasing in the Eastern US. PCR approaches can be easily adopted in clinical laboratories, provide rapid screening methods to allow early detection of newly emergent variants and to efficiently triage cases for full genomic sequencing.", + "rel_num_authors": 8, + "rel_authors": [ + { + "author_name": "Huanyu Wang", + "author_inst": "Nationwide Children's Hospital" + }, + { + "author_name": "Sophonie Jean", + "author_inst": "Nationwide Children's Hospital" + }, + { + "author_name": "Richard Eltringham", + "author_inst": "Nationwide Children's Hospital" + }, + { + "author_name": "John Madison", + "author_inst": "Nationwide Children's Hospital" + }, + { + "author_name": "Pamela Snyder", + "author_inst": "The Ohio State University" + }, + { + "author_name": "Huolin Tu", + "author_inst": "The Ohio State University" + }, + { + "author_name": "Daniel Jones", + "author_inst": "The Ohio State University" + }, + { + "author_name": "Amy L. Leber", + "author_inst": "Nationwide Children's Hospital" + } + ], "version": "1", - "license": "cc_by", - "type": "new results", - "category": "bioinformatics" + "license": "cc_by_nd", + "type": "PUBLISHAHEADOFPRINT", + "category": "epidemiology" }, { "rel_doi": "10.1101/2021.04.22.441007", @@ -796337,105 +795877,105 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.04.13.21255445", - "rel_title": "Point-of-Care Ultrasound (POCUS) Predicts Clinical Outcomes in Patients with COVID-19.", + "rel_doi": "10.1101/2021.04.13.21255438", + "rel_title": "Cyclooxygenase inhibitor use is associated with increased COVID-19 severity", "rel_date": "2021-04-20", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.13.21255445", - "rel_abs": "IntroductionPoint-of-care ultrasound (POCUS) may detect the cardiopulmonary manifestations of COVID-19 and expediently predict patient outcomes.\n\nMethodsWe conducted a prospective cohort study at four medical centers from 3/2020-1/2021 to evaluate POCUS findings and clinical outcomes with COVID-19. Our inclusion criteria included adult patients hospitalized for COVID-19 who received cardiac or lung POCUS with a 12-zone protocol. Images were interpreted by two reviewers blinded to clinical outcomes. Our primary outcome was ICU admission incidence. Secondary outcomes included intubation and supplemental oxygen usage.\n\nResultsN=160 patients (N=201 scans) were included. Scans were collected a median 23 hours (IQR:7-80) from emergency department triage. Triage POCUS findings associated with ICU admission included B-lines (OR 4.41 [95% CI:1.71-14.30]; p<0.01) or consolidation (OR 2.49 [95% CI:1.35-4.86]; p<0.01). B-lines were associated with intubation (OR 3.10 [95% CI:1.15-10.27]; p=0.02) and supplemental oxygen usage (OR 3.74 [95% CI:1.63-8.63; p<0.01).\n\nConsolidations present on triage were associated with the need for oxygen at discharge (OR 2.16 [95% CI: 1.01-4.70]; p=0.047). A normal lung triage scan was protective for ICU admission (OR 0.28 [95% CI:0.09-0.75; p<0.01) or need for supplemental oxygen during the hospitalization (OR 0.26 [95% CI:0.11-0.61]; p<0.01). Triage cardiac POCUS scans were not associated with any outcomes.\n\nDiscussionLung POCUS findings detected early in the hospitalization may provide expedient risk stratification for important COVID-19 clinical outcomes, including ICU admission, intubation, or need for oxygen on discharge. A normal admission scan appears protective against adverse outcomes, which may aid in triage decisions of patients.", + "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.13.21255438", + "rel_abs": "BackgroundNon-steroidal anti-inflammatory drugs (NSAIDs) are commonly used to reduce pain, fever, and inflammation but have been associated with complications in community-acquired pneumonia. Observations shortly after the start of the COVID-19 pandemic in 2020 suggested that ibuprofen was associated with an increased risk of adverse events in COVID-19 patients, but subsequent observational studies failed to demonstrate increased risk and in one case showed reduced risk associated with NSAID use.\n\nMethodsA 38-center retrospective cohort study was performed that leveraged the harmonized, high-granularity electronic health record data of the National COVID Cohort Collaborative. A propensity-matched cohort of COVID-19 inpatients was constructed by matching cases (treated with NSAIDs) and controls (not treated) from 857,061 patients with COVID-19. The primary outcome of interest was COVID-19 severity in hospitalized patients, which was classified as: moderate, severe, or mortality/hospice. Secondary outcomes were acute kidney injury (AKI), extracorporeal membrane oxygenation (ECMO), invasive ventilation, and all-cause mortality at any time following COVID-19 diagnosis.\n\nResultsLogistic regression showed that NSAID use was not associated with increased COVID-19 severity (OR: 0.57 95% CI: 0.53-0.61). Analysis of secondary outcomes using logistic regression showed that NSAID use was not associated with increased risk of all-cause mortality (OR 0.51 95% CI: 0.47-0.56), invasive ventilation (OR: 0.59 95% CI: 0.55-0.64), AKI (OR: 0.67 95% CI: 0.63-0.72), or ECMO (OR: 0.51 95% CI: 0.36-0.7). In contrast, the odds ratios indicate reduced risk of these outcomes, but our quantitative bias analysis showed E-values of between 1.9 and 3.3 for these associations, indicating that comparatively weak or moderate confounder associations could explain away the observed associations.\n\nConclusionsStudy interpretation is limited by the observational design. Recording of NSAID use may have been incomplete. Our study demonstrates that NSAID use is not associated with increased COVID-19 severity, all-cause mortality, invasive ventilation, AKI, or ECMO in COVID-19 inpatients. A conservative interpretation in light of the quantitative bias analysis is that there is no evidence that NSAID use is associated with risk of increased severity or the other measured outcomes. Our findings are the largest EHR-based analysis of the effect of NSAIDs on outcome in COVID-19 patients to date. Our results confirm and extend analogous findings in previous observational studies using a large cohort of patients drawn from 38 centers in a nationally representative multicenter database.", "rel_num_authors": 23, "rel_authors": [ { - "author_name": "Andre Kumar", - "author_inst": "Stanford Unviersity" + "author_name": "Justin Reese", + "author_inst": "Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA" }, { - "author_name": "Yingjie Weng", - "author_inst": "Stanford University" + "author_name": "Ben Coleman", + "author_inst": "The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA" }, { - "author_name": "Sally Graglia", - "author_inst": "UCSF" + "author_name": "Lauren Chan", + "author_inst": "Translational and Integrative Sciences Center, Oregon State University, Corvallis, OR, USA" }, { - "author_name": "Thomas Lew", - "author_inst": "Stanford University" + "author_name": "Hannah Blau", + "author_inst": "The Jackson Laboratory for Genomic Medicine: Farmington, CT, US" }, { - "author_name": "Kavita Gandhi", - "author_inst": "UCSF" + "author_name": "Tiffany J Callahan", + "author_inst": "Computational Bioscience, University of Colorado Anschutz Medical Campus, Boulder, CO, USA, Center for Health AI, University of Colorado Anschutz Medical Campus" }, { - "author_name": "Farhan Lalani", - "author_inst": "UCSF" + "author_name": "Luca Cappelletti", + "author_inst": "Universit\u00e0 degli Studi di Milano, Milan, IT" }, { - "author_name": "David Chia", - "author_inst": "UCSF" + "author_name": "Tommaso Fontana", + "author_inst": "Universita degli Studi di Milano, Milan, IT" }, { - "author_name": "Youyou Duanmu", - "author_inst": "Stanford" + "author_name": "Katie Rebecca Bradwell", + "author_inst": "Palantir Technologies, Denver, CO, USA" }, { - "author_name": "Trevor Jensen", - "author_inst": "UCSF" + "author_name": "Nomi L Harris", + "author_inst": "Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA" }, { - "author_name": "Viveta Lobo", - "author_inst": "Stanford" + "author_name": "Elena Casiraghi", + "author_inst": "Universit\u00e0 degli Studi di Milano, Milan, IT" }, { - "author_name": "Jeffrey Nahn", - "author_inst": "UCSF" + "author_name": "Giorgio Valentini", + "author_inst": "Universit\u00e0 degli Studi di Milano, Milan, IT" }, { - "author_name": "Nicholas Iverson", - "author_inst": "UCSF" + "author_name": "Guy Karlebach", + "author_inst": "The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA" }, { - "author_name": "Molly Rosenthal", - "author_inst": "UCSF" + "author_name": "Rachel Deer", + "author_inst": "University of Texas Medical Branch, Galveston, TX, USA" }, { - "author_name": "Andrea Gordon", - "author_inst": "Stanford" + "author_name": "Julie A McMurry", + "author_inst": "Center for Health AI, University of Colorado Anschutz Medical Campus, Aurora, CO, USA" }, { - "author_name": "John Kugler", - "author_inst": "Stanford" + "author_name": "Melissa A Haendel", + "author_inst": "Center for Health AI, University of Colorado Anschutz Medical Campus, Aurora, CO, USA" }, { - "author_name": "Minh Chi Tran", - "author_inst": "Stanford" + "author_name": "Christopher G Chute", + "author_inst": "Schools of Medicine, Public Health, and Nursing, Johns Hopkins University, Baltimore, MD, USA" }, { - "author_name": "Xiaolin Jia", - "author_inst": "Stanford" + "author_name": "Emily Pfaff", + "author_inst": "North Carolina Translational and Clinical Sciences Institute (NC TraCS), University of North Carolina at Chapel Hill, Chapel Hill, NC, USA" }, { - "author_name": "Charles Liao", - "author_inst": "Stanford" + "author_name": "Richard Moffitt", + "author_inst": "Department of Biomedical Informatics, Stony Brook University, Stony Brook, NY, USA" }, { - "author_name": "Alice Cha", - "author_inst": "Stanford" + "author_name": "Heidi Spratt", + "author_inst": "University of Texas Medical Branch, Galveston, TX, USA" }, { - "author_name": "Evan Baum", - "author_inst": "Stanford" + "author_name": "Jasvinder Singh", + "author_inst": "University of Alabama at Birmingham, Birmingham, AL, USA, Medicine Service, VA Medical Center, Birmingham, AL, USA" }, { - "author_name": "Douglas Halket", - "author_inst": "Stanford" + "author_name": "Christopher J Mungall", + "author_inst": "Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA" }, { - "author_name": "Jai Madhok", - "author_inst": "Stanford" + "author_name": "Andrew E Williams", + "author_inst": "Tufts Medical Center Clinical and Translational Science Institute, Tufts Medical Center, Boston, MA, USA, Tufts University School of Medicine, Institute for Cli" }, { - "author_name": "Muhammad Fazal", - "author_inst": "Stanford" + "author_name": "Peter N Robinson", + "author_inst": "The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA, Institute for Systems Genomics, University of Connecticut, Farmington, CT, USA." } ], "version": "1", @@ -798007,25 +797547,29 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.04.17.21255656", - "rel_title": "Rapid detection of SARS CoV-2 N501Y mutation in clinical samples", + "rel_doi": "10.1101/2021.04.19.21255759", + "rel_title": "Analyzing the effect of relaxing restriction on the COVID-19 outbreak for some US states", "rel_date": "2021-04-20", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.17.21255656", - "rel_abs": "Severe acute respiratory syndrome coronavirus-2 (SARS CoV-2) variants poses major threats in increasing infectivity, transmission, mortality of Coronavirus Disease 2019 (Covid-19). Additionally, SARS CoV-2 variants resist antibody neutralizations or may abolish vaccine efficacies. Researches to develop economical and fast methods will support the developing or poor countries to challenge the Covid-19 pandemic via tracking common mutations that may help to deploy the vaccination programs and control the virus. Current study has developed a novel low-cost rapid technique, exploiting real time PCR probes and conventional PCR specific primers, to identify N501Y mutation, which was independently emerged in the UK, South African and Brazilian variants. Currently, these variants tend to spread to all over the world and seem to be more infectious, transmissible and fatal. This study helps tracking the N501Y mutation for understanding its clinical and epidemiological characteristics, in those countries where sequencing facilities are lacking or expensive. Further study should focus on other common mutations in the variants of concerns of SARS CoV-2.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.19.21255759", + "rel_abs": "The ongoing pandemic disease COVID-19 has caused worldwide social and financial disruption. As many countries are engaged in designing vaccines, the harmful second and third waves of COVID-19 have already appeared in many countries. To investigate changes in transmission rates and the effect of social distancing in the USA, we formulate a system of ordinary differential equations using data of confirmed cases and deaths in these states: California, Texas, Florida, Georgia, Illinois, Louisiana, Michigan, and Missouri in the USA to be able to investigate changes in transmission rates of the outbreak and effect of social distancing. Our models and the corresponding parameter estimations show social distancing reduces the transmission by 60% to 90%, and thus obeying the movement restriction rules plays a crucial rule to reduce the magnitudes of the outbreak waves. Our analysis shows the current management restrictions do not sufficiently slow the disease propagation.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Sirwan M.A. Al-Jaf", - "author_inst": "University of Garmian" + "author_name": "Mahir Demir", + "author_inst": "Michigan State University" }, { - "author_name": "Sherko Subhan Niranji", - "author_inst": "University of Garmian" + "author_name": "ibrahim Halil Aslan", + "author_inst": "Batman University" + }, + { + "author_name": "Suzanne Lenhart", + "author_inst": "University of Tennessee, Knoxville" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -800157,45 +799701,133 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2021.04.13.21255281", - "rel_title": "The increase in the risk of severity and fatality rate of covid-19 in southern Brazil after the emergence of the Variant of Concern (VOC) SARS-CoV-2 P.1 was greater among young adults without pre-existing risk conditions", + "rel_doi": "10.1101/2021.04.12.21255368", + "rel_title": "A point-of-care lateral flow assay for neutralising antibodies against SARS-CoV-2", "rel_date": "2021-04-19", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.13.21255281", - "rel_abs": "BackgroundThe SARS-CoV-2 P.1 variant has been considered as \"variant of concern (VOC)\" since the end of 2020 when it was firstly identified in the Brazilian state of Amazonas and from there spread to other regions of Brazil. This variant was associated with an increase in transmissibility and worsening of the epidemiological situation in the places where it was detected. The aim of this study was to analyze the severity profile of covid-19 cases in the Rio Grande do Sul state, southern region of Brazil, before and after the emergence of the P.1 variant, considering also the context of the hospitals overload and the collapse of health services.\n\nMethodsWe analyzed data from the Influenza Epidemiological Surveillance Information System, SIVEP-Gripe (Sistema de Informacao de Vigilancia Epidemiologica da Gripe) and compare two epidemiological periods: the \"first wave\" comprised by cases occurred during November and December 2020 (EW 45 to 53) and the \"second wave\" with cases occurred in February 2021 (EW 5 to 8), considering that in this month there was a predominance of the new variant P.1. We calculated the proportion of severe forms among the total cases of covid-19, the case fatality rates (CFR) and hospital case fatality rate (hCFR) over both waves time set using the date of onset of symptoms as a reference. We analyzed separately the patients without pre-existing conditions of risk, by age and sex. For comparison between periods, we calculated the Risk Ratio (RR) with their respective 95% confidence intervals and the p-values.\n\nFindingsWe observed that in the second wave there were an increase in the proportion of severe cases and covid-19 deaths among younger age groups and patients without pre-existing conditions of risk. The proportion of people under the age of 60 among the cases that evolved to death raised from 18% (670 deaths) in November and December (1st wave) to 28% (1370 deaths) in February (2nd wave). A higher proportion of patients without pre-existing risk conditions was also observed among those who evolved to death due to covid-19 in the second wave (22%, 1,077 deaths) than in the first one (13%, 489 deaths). The CFR for covid-19 increased overall and in different age groups, in both sexes. The increase occurred in a greatest intensity in the population between 20 and 59 years old and among patients without pre-existing risk conditions. Female 20 to 39 years old, with no pre-existing risk conditions, were at risk of death 5.65 times higher in February (95%CI = 2.9 - 11.03; p <0.0001) and in the age group of 40 and 59 years old, this risk was 7.7 times higher (95%CI = 5.01-11.83; p <0.0001) comparing with November-December.\n\nInterpretationOur findings showed an increase in the proportion of young people and people without previous illnesses among severe cases and deaths in the state of RS after the identification of the local transmission of variant P.1 in the state. There was also an increase in the proportion of severe cases and in the CFR, in almost all subgroups analyzed, this increase was heterogeneous in different age groups and sex. As far as we know, these are the first evidences that the P.1 variant can disproportionately increase the risk of severity and deaths among population without pre-existing diseases, suggesting related changes in pathogenicity and virulence profiles. New studies still need to be done to confirm and deepen these findings.", - "rel_num_authors": 7, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.12.21255368", + "rel_abs": "As vaccines against SARS-CoV-2 are now being rolled out, a better understanding of immunity to the virus; whether through infection, or passive or active immunisation, and the durability of this protection is required. This will benefit from the ability to measure SARS-CoV-2 immunity, ideally with rapid turnaround and without the need for laboratory-based testing. Current rapid point-of-care (POC) tests measure antibodies (Ab) against the SARS-CoV-2 virus, however, these tests provide no information on whether the antibodies can neutralise virus infectivity and are potentially protective, especially against newly emerging variants of the virus. Neutralising Antibodies (NAb) are emerging as a strong correlate of protection, but most current NAb assays require many hours or days, samples of venous blood, and access to laboratory facilities, which is especially problematic in resource-limited settings. We have developed a lateral flow POC test that can measure levels of RBD-ACE2 neutralising antibodies from whole blood, with a result that can be determined by eye (semi-quantitative) or on a small instrument (quantitative), and results show high correlation with microneutralisation assays. This assay also provides a measure of total anti-RBD antibody, thereby providing evidence of exposure to SARS-CoV-2, regardless of whether NAb are present in the sample. By testing samples from immunised macaques, we demonstrate that this test is equally applicable for use with animal samples, and we show that this assay is readily adaptable to test for immunity to newly emerging SARS-CoV-2 variants. Accordingly, the COVID-19 NAb-test test described here can provide a rapid readout of immunity to SARS-CoV-2 at the point of care.", + "rel_num_authors": 29, "rel_authors": [ { - "author_name": "Andre R R Freitas", - "author_inst": "Faculdade de Medicina Sao Leopoldo Mandic de Campinas" + "author_name": "Thomas S. Fulford", + "author_inst": "Peter Doherty Institute" }, { - "author_name": "Daniele R Q Lemos", - "author_inst": "Faculdade de Medicina do Centro Universitario Christus" + "author_name": "Huy Van", + "author_inst": "Burnet Institute" }, { - "author_name": "Otto A Beckedorff", - "author_inst": "Faculdade de Medicina Sao Leopoldo Mandic de Campinas" + "author_name": "Nicholas A. Gherardin", + "author_inst": "Peter Doherty Institute" + }, + { + "author_name": "Shuning Zheng", + "author_inst": "Burnet Institute" + }, + { + "author_name": "Marcin Ciula", + "author_inst": "Peter Doherty Institute" + }, + { + "author_name": "Heidi E. Drummer", + "author_inst": "Burnet Institute" + }, + { + "author_name": "Samuel Redmond", + "author_inst": "Peter Doherty Institute" }, { - "author_name": "Luciano P G Cavalcante", - "author_inst": "Programa de Pos-graduacao em Saude Coletiva da Universidade Federal do Ceara, Fortaleza-CE -" + "author_name": "Hyon-Xhi Tan", + "author_inst": "Peter Doherty Institute" + }, + { + "author_name": "Rob J. Center", + "author_inst": "Burnet Institute" }, { - "author_name": "Andre M Siqueira", - "author_inst": "Instituto Nacional de Infectologia Evandro Chagas - FIOCRUZ" + "author_name": "Fan Li", + "author_inst": "Burnet Institute" }, { - "author_name": "Regiane C S Mello", - "author_inst": "Programa de Pos-graduacao em Saude Coletiva - Faculdade de Medicina Sao Leopoldo Mandic de Campinas" + "author_name": "Samantha L. Grimley", + "author_inst": "Peter Doherty Institute" }, { - "author_name": "Eliana N C Barros", - "author_inst": "Centro de Farmacovigilancia, Seguranca Clinica e Gestao de Risco do Instituto Butantan." + "author_name": "Bruce D. Wines", + "author_inst": "Burnet Institute" + }, + { + "author_name": "Thi H.O. Nguyen", + "author_inst": "Peter Doherty Institute" + }, + { + "author_name": "Francesca L. Mordant", + "author_inst": "Peter Doherty Institute" + }, + { + "author_name": "Louise C. Rowntree", + "author_inst": "Peter Doherty Institute" + }, + { + "author_name": "Allen C. Cheng", + "author_inst": "Monash University" + }, + { + "author_name": "Denise L. Doola", + "author_inst": "James Cook University" + }, + { + "author_name": "Katherine Bond", + "author_inst": "Peter Doherty Institute" + }, + { + "author_name": "P. Mark Hogarth", + "author_inst": "Burnet Institute" + }, + { + "author_name": "Zoe McQuilten", + "author_inst": "Monash University" + }, + { + "author_name": "Kanta Subbarao", + "author_inst": "Peter Doherty Institute" + }, + { + "author_name": "Katherine Kedzierska", + "author_inst": "Peter Doherty Institute" + }, + { + "author_name": "Jennifer A. Juno", + "author_inst": "Peter Doherty Institute" + }, + { + "author_name": "Adam K. Wheatley", + "author_inst": "Peter Doherty Institute" + }, + { + "author_name": "Stephen J. Kent", + "author_inst": "Peter Doherty Institute" + }, + { + "author_name": "Deborah A. Williamson", + "author_inst": "Peter Doherty Institute" + }, + { + "author_name": "Damian F.J. Purcell", + "author_inst": "Peter Doherty Institute" + }, + { + "author_name": "David A. Anderson", + "author_inst": "Burnet Institute" + }, + { + "author_name": "Dale I. Godfrey", + "author_inst": "Peter Doherty Institute" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -802055,35 +801687,79 @@ "category": "palliative medicine" }, { - "rel_doi": "10.1101/2021.04.19.440452", - "rel_title": "Rapid decay of host basal mRNAs during SARS-CoV-2 infection perturbs host antiviral mRNA biogenesis and export", + "rel_doi": "10.1101/2021.04.16.21255459", + "rel_title": "Increased Transmissibility of SARS-CoV-2 Lineage B.1.1.7 by Age and Viral Load: Evidence from Danish Households", "rel_date": "2021-04-19", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.04.19.440452", - "rel_abs": "A key feature of the mammalian innate immune response to viral infection is the transcriptional induction of interferon (IFN) genes, which encode for secreted proteins that prime the antiviral response and limit viral replication and dissemination. A hallmark of severe COVID-19 disease caused by SARS-CoV-2 is the low presence of IFN proteins in patient serum despite elevated levels of IFN-encoding mRNAs, indicative of post-transcriptional inhibition of IFN protein production. Herein, we show SARS-CoV-2 infection limits type I and type III IFN biogenesis by preventing the release of mRNA from their sites of transcription and/or triggering their nuclear degradation. In addition, SARS-CoV-2 infection inhibits nuclear-cytoplasmic transport of IFN mRNAs as a consequence of widespread cytosolic mRNA degradation mediated by both activation of the host antiviral endoribonuclease, RNase L, and by the SARS-CoV-2 protein, Nsp1. These findings argue that inhibition of host and/or viral Nsp1-mediated mRNA decay, as well as IFN treatments, may reduce viral-associated pathogenesis by promoting the innate immune response.", - "rel_num_authors": 4, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.16.21255459", + "rel_abs": "1AimThe aim of this study was to estimate the household transmissibility of SARS-CoV-2 for lineage B.1.1.7 compared with other lineages, by age and viral load. Further-more, we wanted to estimate whether there is a multiplicative or additive effect of the increased transmissibility of B.1.1.7 compared with other lineages.\n\nBackgroundNew lineages of SARS-CoV-2 are of potential concern due to higher transmissibility, risk of severe outcomes, and/or escape from neutralizing antibodies. Lineage B.1.1.7 has been estimated to be more transmissible than other previously known lineages, but the association between transmissibility and risk factors, such as age of primary case and viral load is still unknown.\n\nMethodsWe used comprehensive administrative data from Denmark, comprising the full population, all SARS-CoV-2 RT-PCR tests, and all WGS lineage data (January 11 to February 7, 2021), to estimate household transmissibility stratified by lineage B.1.1.7 and other lineages.\n\nResultsWe included 5,241 households with primary cases; 808 were infected with SARS-CoV-2 lineage B.1.1.7 and 4,433 were infected with other lineages. The attack rate was 38% in households with a primary case infected with B.1.1.7 and 27% in households with a primary case infected with other lineages. Primary cases infected with B.1.1.7 had an increased transmissibility of 1.5-1.7 times that of primary cases infected with other lineages. The increased transmissibility of B.1.1.7 was multiplicative across age and viral load.\n\nConclusionsThe results found in this study add new knowledge that can be used to mitigate the further spread of SARS-CoV-2 lineage B.1.1.7, which is becoming increasingly widespread in numerous countries. Our results clarify that the transmissibility of B.1.1.7 should be included as a multiplicative effect in mathematical models used as a tool for decision makers. The results may have important public health implications, as household transmission may serve as a bridge between otherwise separate transmission domains, such as schools and physical workplaces, despite implemented non-pharmaceutical interventions.", + "rel_num_authors": 15, "rel_authors": [ { - "author_name": "James M Burke", - "author_inst": "University of Colorado Boulder" + "author_name": "Frederik Plesner Lyngse", + "author_inst": "University of Copenhagen" }, { - "author_name": "Laura A St Clair", - "author_inst": "Colorado State University" + "author_name": "K\u00e5re M\u00f8lbak", + "author_inst": "Statens Serum Institut" }, { - "author_name": "Rushika Perera", - "author_inst": "Colorado State University" + "author_name": "Robert Leo Skov", + "author_inst": "Statens Serum Institut" }, { - "author_name": "Roy Parker", - "author_inst": "University of Colorado Boulder; Howard Hughes Medical Institute" + "author_name": "Lasse Engbo Christiansen", + "author_inst": "Technical University of Denmark" + }, + { + "author_name": "Laust Hvas Mortensen", + "author_inst": "Statistics Denmark" + }, + { + "author_name": "Mads Plesner Albertsen", + "author_inst": "Aalborg University" + }, + { + "author_name": "Camilla Holten M\u00f8ller", + "author_inst": "Statens Serum Institut" + }, + { + "author_name": "Tyra Grove Krause", + "author_inst": "Statens Serum Institut" + }, + { + "author_name": "Morten Rasmussen", + "author_inst": "Statens Serum Institut" + }, + { + "author_name": "Thomas Yssing Michaelsen", + "author_inst": "Aalborg University" + }, + { + "author_name": "Marianne Voldstedlund", + "author_inst": "Statens Serum Institut" + }, + { + "author_name": "Jannik Fonager", + "author_inst": "Statens Serum Institut" + }, + { + "author_name": "Nina Ruth Steenhard", + "author_inst": "Statens Serum Institut" + }, + { + "author_name": "- The Danish Covid-19 Genome Consortium", + "author_inst": "-" + }, + { + "author_name": "Carsten Thure Kirkeby", + "author_inst": "University of Copenhagen" } ], "version": "1", - "license": "cc_by_nc_nd", - "type": "new results", - "category": "immunology" + "license": "cc_by", + "type": "PUBLISHAHEADOFPRINT", + "category": "epidemiology" }, { "rel_doi": "10.1101/2021.04.12.21255337", @@ -803845,23 +803521,43 @@ "category": "allergy and immunology" }, { - "rel_doi": "10.1101/2021.04.11.21255289", - "rel_title": "An explicit formula for minimizing the infected peak in an SIR epidemic model when using a fixed number of complete lockdowns", + "rel_doi": "10.1101/2021.04.10.21255251", + "rel_title": "Controlling long-term SARS-CoV-2 infections is important for slowing viral evolution", "rel_date": "2021-04-17", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.11.21255289", - "rel_abs": "Careful timing of NPIs (non-pharmaceutical interventions) such as social distancing may avoid high \"second waves\" of infections of COVID-19. This paper asks what should be the timing of a set of k complete-lockdowns of prespecified lengths (such as two weeks) so as to minimize the peak of the infective compartment. Perhaps surprisingly, it is possible to give an explicit and easily computable rule for when each lockdown should commence. Simulations are used to show that the rule remains fairly accurate even if lockdowns are not perfect.", - "rel_num_authors": 1, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.10.21255251", + "rel_abs": "The rapid emergence and expansion of novel SARS-CoV-2 variants is an unpleasant surprise that threatens our ability to achieve herd immunity for COVID-19. These fitter SARS-CoV-2 variants often harbor multiple point mutations, conferring one or more traits that provide an evolutionary advantage, such as increased transmissibility, immune evasion and longer infection duration. In a number of cases, variant emergence has been linked to long-term infections in individuals who were either immunocompromised or treated with convalescent plasma. In this paper, we explore the mechanism by which fitter variants of SARS-CoV-2 arise during long-term infections using a mathematical model of viral evolution and identify means by which this evolution can be slowed. While viral load and infection duration play a strong role in favoring the emergence of such variants, the overall probability of emergence and subsequent transmission from any given infection is low, suggesting that viral variant emergence and establishment is a product of random chance. To the extent that luck plays a role in favoring the emergence of novel viral variants with an evolutionary advantage, targeting these low-probability random events might allow us to tip the balance of fortune away from these advantageous variants and prevent them from being established in the population.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Eduardo Sontag", - "author_inst": "Northeastern University" + "author_name": "Debra Van Egeren", + "author_inst": "Dana-Farber Cancer Institute" + }, + { + "author_name": "Alexander Novokhodko", + "author_inst": "University of Washington" + }, + { + "author_name": "Madison Stoddard", + "author_inst": "Fractal Therapeutics" + }, + { + "author_name": "Uyen Tran", + "author_inst": "Fractal Therapeutics" + }, + { + "author_name": "Diane Joseph-McCarthy", + "author_inst": "Boston University" + }, + { + "author_name": "Arijit Chakravarty", + "author_inst": "Fractal Therapeutics" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "public and global health" }, { "rel_doi": "10.1101/2021.04.11.21255283", @@ -805667,75 +805363,43 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2021.04.16.440104", - "rel_title": "Homo-harringtonine (HHT) - A highly effective drug against coronaviruses and the potential for large-scale clinical applications", - "rel_date": "2021-04-16", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.04.16.440104", - "rel_abs": "In the search for treatment schemes of COVID-19, we start by examining the general weakness of coronaviruses and then identify approved drugs attacking that weakness. The approach, if successful, should identify drugs with a specific mechanism that is at least as effective as the best drugs proposed and are ready for clinical trials. All coronaviruses translate their non-structural proteins ([~]16) in concatenation, resulting in a very large super-protein. Homo-harringtonine (HHT), which has been approved for the treatment of leukemia, blocks protein elongation very effectively. Hence, HHT can repress the replication of many coronaviruses at the nano-molar concentration. In two mouse models, HHT clears SARS-CoV-2 in 3 days, especially by nasal dripping of 40 ug per day. We also use dogs to confirm the safety of HHT delivered by nebulization. The nebulization scheme could be ready for large-scale applications at the onset of the next epidemics. For the current COVID-19, a clinical trial has been approved by the Ditan hospital of Beijing but could not be implemented for want of patients. The protocol is available to qualified medical facilities.", - "rel_num_authors": 14, + "rel_doi": "10.1101/2021.04.12.21255201", + "rel_title": "Predicting severe COVID-19 outcomes for triage and resource allocation", + "rel_date": "2021-04-15", + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.12.21255201", + "rel_abs": "BackgroundWhile numerous studies have identified factors associated with severe COVID-19 outcomes, they have yet to quantify these characteristics. Therefore, our studys purpose is to stratify these risk factors and use them to predict outcomes.\n\nStudy DesignThis is a retrospective review of the CDC COVID-19 Surveillance Data. Logistic regression models calculated risk estimates for independent variables, and random forest models predicted the chance of severe outcomes.\n\nResultsOur sample of 3,798,261 patients with COVID-19 consisted mainly of females (51.9%), 10-to 69-year-olds, and White/Non-Hispanics (34.9%). Most were not healthcare workers (90.6%) and did not have preexisting medical conditions (47.1%). Age had an increased risk of severe outcomes that grew every decade of life. White patients had a decreased occurrence of severe outcomes than Non-Whites, except for Pacific Islanders with comparable mortality. The variable selection algorithm detected that three outcomes were more accurate without healthcare worker classification: mechanical ventilation/intubation, pneumonia, and ARDS Acute respiratory distress. However, providers had a decreased risk of severe outcomes overall. Also, patients with preexisting conditions demonstrated an increased risk in all outcomes. Compared to the logistic regressions, the predictive models had a higher performance (AUC>0.8). The death model had the best metrics, followed by hospitalization and ventilation. We amassed these predictive models into the Severe COVID-19 Calculator web application that estimates the probability of severe outcomes.\n\nConclusionsSeveral patient social and medical demographics recorded by the CDC significantly affect severe COVID-19 outcomes suggesting a multifactorial influence. To account for these variables, a generated Severe Covid-19 Calculator can accurately predict the chance of severe outcomes in citizens that may contract or have COVID-19.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Hai-Jun Wen", - "author_inst": "State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-sen University, Guangzhou 510275, China" - }, - { - "author_name": "Pei Lin", - "author_inst": "State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-sen University, Guangzhou 510275, China" - }, - { - "author_name": "Zhi-Chao Xu", - "author_inst": "State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-sen University, Guangzhou 510275, China" - }, - { - "author_name": "Wen-Bin He", - "author_inst": "State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Science, Kunming 650223, China" - }, - { - "author_name": "Jing Feng", - "author_inst": "State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Science, Kunming 650223, China" - }, - { - "author_name": "Si-Jin Wu", - "author_inst": "Laboratory of Molecular Modeling and Design, State Key Laboratory of Molecular Reaction Dynamics, Dalian Institute of Chemical Physics, Chinese Academy of Scien" - }, - { - "author_name": "Guo-Dong Wang", - "author_inst": "State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology / Center for Excellence in Animal Evolution and Genetics, Chinese Academy " - }, - { - "author_name": "Xue-Mei Lyu", - "author_inst": "State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology / Center for Excellence in Animal Evolution and Genetics, Chinese Academy " + "author_name": "Anthony Onde Morada", + "author_inst": "Geisinger Commonwealth School of Medicine" }, { - "author_name": "Feng-Liang Liu", - "author_inst": "Key Laboratory of Animal Models and Human Disease Mechanisms of Chinese Academy of Sciences / Key Laboratory of Bioactive Peptides of Yunnan Province, Kunming I" + "author_name": "Caleb Scheidel", + "author_inst": "Methods Consultants" }, { - "author_name": "Yong-Tang Zheng", - "author_inst": "Key Laboratory of Animal Models and Human Disease Mechanisms of Chinese Academy of Sciences / Key Laboratory of Bioactive Peptides of Yunnan Province, Kunming I" + "author_name": "Jennifer Lynn Brown", + "author_inst": "Guthrie Robert Packer Hospital" }, { - "author_name": "Hui Zeng", - "author_inst": "Beijing Ditan Hospital, Capital Medical University, Beijing 100102, China" + "author_name": "Jeremy Albright", + "author_inst": "Methods Consultants" }, { - "author_name": "Xiong-Lei He", - "author_inst": "State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-sen University, Guangzhou 510275, China" + "author_name": "Victor Kolade", + "author_inst": "Guthrie Robert Packer Hospital" }, { - "author_name": "Fu-Jie Zhang", - "author_inst": "Beijing Ditan Hospital, Capital Medical University, Beijing 100102, China" - }, - { - "author_name": "Chung-I Wu", - "author_inst": "State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-sen University, Guangzhou 510275, China / Southern Marine Science and Engineering Guangdong" + "author_name": "Burt Cagir", + "author_inst": "Guthrie Robert Packer Hospital" } ], "version": "1", - "license": "cc_no", - "type": "new results", - "category": "microbiology" + "license": "cc_by_nc_nd", + "type": "PUBLISHAHEADOFPRINT", + "category": "health policy" }, { "rel_doi": "10.1101/2021.04.12.21253817", @@ -807349,35 +807013,91 @@ "category": "bioengineering" }, { - "rel_doi": "10.1101/2021.04.15.439956", - "rel_title": "Time-series trend of pandemic SARS-CoV-2 variants visualized using batch-learning self-organizing map for oligonucleotide compositions", + "rel_doi": "10.1101/2021.04.15.440004", + "rel_title": "Computationally prioritized drugs inhibit SARS-CoV-2 infection and syncytia formation", "rel_date": "2021-04-15", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.04.15.439956", - "rel_abs": "To confront the global threat of coronavirus disease 2019, a massive number of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genome sequences have been decoded, with the results promptly released through the GISAID database. Based on variant types, eight clades have already been defined in GISAID, but the diversity can be far greater. Owing to the explosive increase in available sequences, it is important to develop new technologies that can easily grasp the whole picture of the big-sequence data and support efficient knowledge discovery. An ability to efficiently clarify the detailed time-series changes in genome-wide mutation patterns will enable us to promptly identify and characterize dangerous variants that rapidly increase their population frequency. Here, we collectively analyzed over 150,000 SARS-CoV-2 genomes to understand their overall features and time-dependent changes using a batch-learning self-organizing map (BLSOM) for oligonucleotide composition, which is an unsupervised machine learning method. BLSOM can separate clades defined by GISAID with high precision, and each clade is subdivided into clusters, which shows a differential increase/decrease pattern based on geographic region and time. This allowed us to identify prevalent strains in each region and to show the commonality and diversity of the prevalent strains. Comprehensive characterization of the oligonucleotide composition of SARS-CoV-2 and elucidation of time-series trends of the population frequency of variants can clarify the viral adaptation processes after invasion into the human population and the time-dependent trend of prevalent epidemic strains across various regions, such as continents.", - "rel_num_authors": 4, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.04.15.440004", + "rel_abs": "New affordable therapeutic protocols for COVID-19 are urgently needed despite the increasing number of effective vaccines and monoclonal antibodies. To this end, there is increasing attention towards computational methods for drug repositioning and de novo drug design.\n\nHere, we systematically integrated multiple data-driven computational approaches to perform virtual screening and prioritize candidate drugs for the treatment of COVID-19. From the set of prioritized drugs, we selected a subset of representative candidates to test in human cells. Two compounds, 7-hydroxystaurosporine and bafetinib, showed synergistic antiviral effects in our in vitro experiments, and strongly inhibited viral-induced syncytia formation. Moreover, since existing drug repositioning methods provide limited usable information for de novo drug design, we extracted and prioritized the chemical substructures of the identified drugs, providing a chemical vocabulary that may help to design new effective drugs.", + "rel_num_authors": 18, "rel_authors": [ { - "author_name": "Takashi Abe", - "author_inst": "Smart Information Systems, Faculty of Engineering, Niigata University" + "author_name": "Angela Serra", + "author_inst": "Tampere University" }, { - "author_name": "Ryuki Furukawa", - "author_inst": "Smart Information Systems, Faculty of Engineering, Niigata University" + "author_name": "Michele Fratello", + "author_inst": "Tampere University" }, { - "author_name": "Yuki Iwasaki", - "author_inst": "Nagahama Institute of Bio-Science and Technology" + "author_name": "Antonio Federico", + "author_inst": "Tampere University" }, { - "author_name": "Toshimichi Ikemura", - "author_inst": "Nagahama Institute of Bio-Science and Technology" + "author_name": "Ravi Ojha", + "author_inst": "University of Helsinki" + }, + { + "author_name": "Riccardo Provenzani", + "author_inst": "University of Helsinki" + }, + { + "author_name": "Ervin Tasnadi", + "author_inst": "University of Helsinki" + }, + { + "author_name": "Luca Cattelani", + "author_inst": "Tampere University" + }, + { + "author_name": "Giusy del Giudice", + "author_inst": "Tampere University" + }, + { + "author_name": "Pia Anneli Sofia Kinaret", + "author_inst": "University of Helsinki" + }, + { + "author_name": "Laura Aliisa Saarimaki", + "author_inst": "Tampere University" + }, + { + "author_name": "Alisa Pavel", + "author_inst": "Tampere University" + }, + { + "author_name": "Vincenzo Cerullo", + "author_inst": "University of Helsinki" + }, + { + "author_name": "Olli Vapalahti", + "author_inst": "University of Helsinki" + }, + { + "author_name": "Peter Horvath", + "author_inst": "University of Helsinki" + }, + { + "author_name": "Antonio Di Lieto", + "author_inst": "Aarhus University" + }, + { + "author_name": "Jari Yli-Kauhaluoma", + "author_inst": "University of Helsinki" + }, + { + "author_name": "Giuseppe Balistreri", + "author_inst": "University of Helsinki" + }, + { + "author_name": "Dario Greco", + "author_inst": "Tampere University" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_by_nc_nd", "type": "new results", - "category": "bioinformatics" + "category": "pharmacology and toxicology" }, { "rel_doi": "10.1101/2021.04.14.21255474", @@ -809147,99 +808867,31 @@ "category": "health policy" }, { - "rel_doi": "10.1101/2021.04.08.21255167", - "rel_title": "Refining long-COVID by a prospective multimodal evaluation of patients with long-term symptoms related to SARS-CoV-2 infection", + "rel_doi": "10.1101/2021.04.08.21255169", + "rel_title": "The allometric propagation of COVID-19 is explained by human travel", "rel_date": "2021-04-13", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.08.21255167", - "rel_abs": "BackgroundCOVID-19 long-haulers or \"long-COVID\" represent 10% of COVID-19 patients and remain understudied.\n\nMethodsIn this prospective study, we recruited 30 consecutive patients seeking medical help for persistent symptoms (> 30 days) attributed to COVID-19. All reported a viral illness compatible with COVID-19. The patients underwent a multi-modal evaluation including clinical, psychological, virological, specific immunological assays and were followed longitudinally.\n\nResultsThe median age was 40 [interquartile range: 35-54] and 18 (60%) were female. After a median time of 152 [102-164] days after symptom onset, fever, cough and dyspnea were less frequently reported as compared with the initial presentation, but paresthesia and burning pain emerged in 18 (60%) and 13 (43%) patients, respectively. The clinical examination was unremarkable in all patients although the median fatigue and pain visual analogic scales were 7 [5-8] and 5 [2-6], respectively.\n\nExtensive biological studies were unremarkable, as were multiplex cytokine and ultra-sensitive interferon-a2 measurements. At this time, nasopharyngeal swab and stool RT-PCR were negative for all tested patients. Using SARS-CoV-2 serology and IFN-{gamma} ELISPOT, we found evidence of a previous SARS-CoV-2 infection in 50% (15/30) of patients, with objective evidence of lack or waning of immune response in two. Finally, psychiatric evaluation showed that 11 (36.7%), 13 (43.3%) and 9 (30%) patients had a positive screening for anxiety, depression and post-traumatic stress disorder, respectively.\n\nConclusionsHalf of patients seeking medical help for long-COVID lack SARS-CoV-2 immunity. The presence of SARS-CoV-2 immunity did not cluster clinically or biologically long haulers, who reported severe fatigue, altered quality of life, and exhibited psychological distress.\n\nKey pointsO_LIAmong 30 consecutive patients reporting persistent symptoms (median 6 months) self-attributed to COVID-19, pain, fatigue and disability were reported in virtually all patients.\nC_LIO_LIMore than one third of patients suffer from psychological disorders such as anxiety, depression and/or post-traumatic stress disorder, regardless of SARS-CoV-2 immunity.\nC_LIO_LIAt the time of evaluation, only 50% of patients had cellular and/or humoral sign of a past SARS-CoV-2, and serology positivity varied depending of the kit used.\nC_LIO_LIExhaustive clinical, biological and immunological evaluations failed to find an alternative diagnosis, or to identify specific cytokine signature including type I interferon.\nC_LI", - "rel_num_authors": 20, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.08.21255169", + "rel_abs": "We analyzed the number of cumulative positive cases of COVID-19 as a function of time in countries around the World. We tracked the increase in cases from the onset of the pandemic in each region for up to 150 days. We found that in 81 out of 146 regions the trajectory was described with a power-law function for up to 30 days. We also detected scale-free properties in the majority of sub-regions in Australia, Canada, China, and the United States (US). We developed an allometric model that was capable of fitting the initial phase of the pandemic and was the best predictor for the propagation of the illness for up to 100 days. We then determined that the power-law COVID-19 exponent correlated with measurements of human mobility. The COVID-19 exponent correlated with the magnitude of air passengers per country. This correlation persisted when we analyzed the number of air passengers per US states, and even per US metropolitan areas. Furthermore, the COVID-19 exponent correlated with the number of vehicle miles travelled in the US. Together, air and vehicular travel explained 70 % of the variability of the COVID-19 exponent. Taken together, our results suggest that the scale-free propagation of the virus is present at multiple geographical scales and is correlated with human mobility. We conclude that models of disease transmission should integrate scale-free dynamics as part of the modeling strategy and not only as an emergent phenomenological property.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Marc SCHERLINGER", - "author_inst": "CHU de Strasbourg" - }, - { - "author_name": "Renaud Felten", - "author_inst": "Rheumatology department, Strasbourg University Hospital" - }, - { - "author_name": "Floriane Gallais", - "author_inst": "Virology department, Strasbourg University Hospital" - }, - { - "author_name": "Charlotte Nazon", - "author_inst": "Virology department, Strasbourg University Hospital" - }, - { - "author_name": "Emmanuel Chatelus", - "author_inst": "Rheumatology department, Strasbourg University Hospital" - }, - { - "author_name": "Luc Pijnenburg", - "author_inst": "Rheumatology department, Strasbourg University Hospital" - }, - { - "author_name": "Amaury Mengin", - "author_inst": "Psychiatry department, Strasbourg University Hospital" - }, - { - "author_name": "Adrien Gras", - "author_inst": "Psychiatry department, Strasbourg University Hospital" - }, - { - "author_name": "Pierre Vidailhet", - "author_inst": "Psychiatry department, Strasbourg University Hospital" - }, - { - "author_name": "Rachel Arnould-Michel", - "author_inst": "Rheumatology department, Strasbourg University Hospital" - }, - { - "author_name": "Sabrina Bibi-triki", - "author_inst": "Laboratoire d immunoRhumatologie Moleculaire, Institut national de la sante et de la recherche medicale (INSERM) UMR_S 1109" - }, - { - "author_name": "Raphael Carapito", - "author_inst": "Laboratoire d immunoRhumatologie Moleculaire, Institut national de la sante et de la recherche medicale (INSERM) UMR_S 1109" - }, - { - "author_name": "Seiamak Bahram", - "author_inst": "Laboratoire d immunoRhumatologie Moleculaire, Institut national de la sante et de la recherche medicale (INSERM) UMR_S 1109" - }, - { - "author_name": "sophie trouillet-assant", - "author_inst": "Hospices Civils de Lyon" - }, - { - "author_name": "Magali Perret", - "author_inst": "Hospices civils de Lyon" - }, - { - "author_name": "Alexandre Belot", - "author_inst": "Hospices Civils de Lyon" - }, - { - "author_name": "Laurent Arnaud", - "author_inst": "Rheumatology department, Strasbourg University Hospital" - }, - { - "author_name": "Jacques-Eric Gottenberg", - "author_inst": "Rheumatology department, Strasbourg University Hospital" + "author_name": "Rohisha Tuladhar", + "author_inst": "University of Texas at San Antonio" }, { - "author_name": "Samira Fafi-Kremer", - "author_inst": "Virology department, Strasbourg University Hospital" + "author_name": "Paolo Grigolini", + "author_inst": "University of North Texas" }, { - "author_name": "Jean Sibilia", - "author_inst": "Rheumatology department, Strasbourg University Hospital" + "author_name": "Fidel Santamaria", + "author_inst": "University of Texas at San Antonio" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2021.04.08.21255156", @@ -811021,63 +810673,35 @@ "category": "cell biology" }, { - "rel_doi": "10.1101/2021.04.13.439668", - "rel_title": "From partial to whole genome imputation of SARS-CoV-2 for epidemiological surveillance", + "rel_doi": "10.1101/2021.04.07.21255010", + "rel_title": "The effects of quality of evidence communication on perception of public health information about COVID-19: two randomised controlled trials", "rel_date": "2021-04-13", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.04.13.439668", - "rel_abs": "Backgroundthe current SARS-CoV-2 pandemic has emphasized the utility of viral whole genome sequencing in the surveillance and control of the pathogen. An unprecedented ongoing global initiative is increasingly producing hundreds of thousands of sequences worldwide. However, the complex circumstances in which viruses are sequenced, along with the demand of urgent results, causes a high rate of incomplete and therefore useless, sequences. However, viral sequences evolve in the context of a complex phylogeny and therefore different positions along the genome are in linkage disequilibrium. Therefore, an imputation method would be able to predict missing positions from the available sequencing data.\n\nResultsWe developed impuSARS, an application that includes Minimac, the most widely used strategy for genomic data imputation and, taking advantage of the enormous amount of SARS-CoV-2 whole genome sequences available, a reference panel containing 239,301 sequences was built. The impuSARS application was tested in a wide range of conditions (continuous fragments, amplicons or sparse individual positions missing) showing great fidelity when reconstructing the original sequences. The impuSARS application is also able to impute whole genomes from commercial kits covering less than 20% of the genome or only from the Spike protein with a precision of 0.96. It also recovers the lineage with a 100% precision for almost all the lineages, even in very poorly covered genomes (< 20%)\n\nConclusionsimputation can improve the pace of SARS-CoV-2 sequencing production by recovering many incomplete or low-quality sequences that would be otherwise discarded. impuSARS can be incorporated in any primary data processing pipeline for SARS-CoV-2 whole genome sequencing.", - "rel_num_authors": 11, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.07.21255010", + "rel_abs": "BackgroundThe quality of evidence about the effectiveness of non-pharmaceutical health interventions is often low, but little is known about the effects of communicating indications of evidence quality to the public.\n\nMethodsIn two blinded, randomised, controlled, online experiments, US participants (total n=2140) were shown one of several versions of an infographic illustrating the effectiveness of eye protection in reducing COVID-19 transmission. Their trust in the information, understanding, feelings of effectiveness of eye protection, and the likelihood of them adopting it were measured.\n\nFindingsCompared to those given no quality cues, participants who were told the quality of the evidence on eye protection was low, rated the evidence less trustworthy (p=.001), and rated it as subjectively less effective (p=.020). The same effects emerged compared to those who were told the quality of the evidence was high, and in one of the two studies, those shown low quality of evidence said they were less likely to use eye protection (p=.005). Participants who were told the quality of the evidence was high showed no significant differences on these measures compared to those given no information about evidence quality.\n\nInterpretationWithout quality of evidence cues, participants responded to the evidence about the public health intervention as if it was high quality and this affected their subjective perceptions of its efficacy and trust in the provided information. This raises the ethical dilemma of weighing the importance of transparently stating when the evidence base is actually low quality against evidence that providing such information can decrease trust, perception of intervention efficacy, and likelihood of adopting it.\n\nFundingThe Winton Centre for Risk & Evidence Communication, thanks to the David & Claudia Harding Foundation\n\nO_TEXTBOXResearch in ContextO_ST_ABSEvidence before this studyC_ST_ABSThis is the first quantitative, empirical study, to our knowledge, on the effects of communicating the quality of evidence underlying an effectiveness estimate of a public health intervention on a public audience.\n\nAdded value of this studyThis study provides novel insights into the effects of quality of evidence communication in a public health context. It is thus of high theoretical as well as translational value.\n\nImplications of all the available evidenceMembers of the public may assume that information around the effectiveness of a measure such as wearing eye protection to protect against COVID-19 are based on high quality evidence if they are given no cues to suggest otherwise. Yet, when given a statement of the quality of the evidence, this can (appropriately) affect their feelings of the trustworthiness of the information and their subjective judgement of the effectiveness of the measure. This raises the issue of whether there is an ethical imperative to communicate the quality of underlying evidence, particularly when it is low, albeit with the recognition that this may reduce uptake of a public health measure.\n\nC_TEXTBOX", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Francisco M Ortuno", - "author_inst": "Clinical Bioinformatics Area. Fundacion Progreso y Salud, Sevilla, Spain" - }, - { - "author_name": "Carlos Loucera", - "author_inst": "Clinical Bioinformatics Area. Fundacion Progreso y Salud, Sevilla, Spain" - }, - { - "author_name": "Carlos S Casimiro-Soriguer", - "author_inst": "Clinical Bioinformatics Area. Fundacion Progreso y Salud, Sevilla, Spain" - }, - { - "author_name": "Jose A Lepe", - "author_inst": "Hospital Universitario Virgen del Rocio. Sevilla, Spain" - }, - { - "author_name": "Pedro Camacho Martinez", - "author_inst": "Hospital Universitario Virgen del Rocio. Sevilla, Spain" - }, - { - "author_name": "Laura Merino Diaz", - "author_inst": "Hospital Universitario Virgen del Rocio. Sevilla,Spain" - }, - { - "author_name": "Natalia Chueca", - "author_inst": "Hospital Universitario San Cecilio, Granada, Spain" - }, - { - "author_name": "Adolfo de Salazar", - "author_inst": "Hospital Universitario San Cecilio, Granada, Spain" + "author_name": "Claudia R. Schneider", + "author_inst": "University of Cambridge" }, { - "author_name": "Federico Garcia", - "author_inst": "Hospital Universitario San Cecilio, Granada, Spain" + "author_name": "Alexandra L.J. Freeman", + "author_inst": "University of Cambridge" }, { - "author_name": "Javier Perez-Florido", - "author_inst": "Clinical Bioinformatics Area. Fundacion Progreso y Salud, Sevilla, Spain" + "author_name": "David Spiegelhalter", + "author_inst": "University of Cambridge" }, { - "author_name": "Joaquin Dopazo", - "author_inst": "Clinical Bioinformatics Area, Fundacion Progreso y Salud, Sevilla, Spain" + "author_name": "Sander van der Linden", + "author_inst": "University of Cambridge" } ], "version": "1", - "license": "cc_by_nc", - "type": "new results", - "category": "genomics" + "license": "cc_by_nc_nd", + "type": "PUBLISHAHEADOFPRINT", + "category": "public and global health" }, { "rel_doi": "10.1101/2021.04.13.439586", @@ -812683,105 +812307,41 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.04.08.21255144", - "rel_title": "Accuracy of antigen and nucleic acid amplification testing on saliva and naopharyngeal samples for detection of SARS-CoV-2 in ambulatory care", + "rel_doi": "10.1101/2021.04.08.21255109", + "rel_title": "Incidence of Long-term Post-acute Sequelae of SARS-CoV-2 Infection Related to Pain and Other Symptoms: A Living Systematic Review and Meta-analysis", "rel_date": "2021-04-11", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.08.21255144", - "rel_abs": "BackgroundNasopharyngeal sampling for nucleic acid amplification testing (NAAT) is the current standard diagnostic test for of coronavirus disease 2019 (COVID-19). However, the NAAT technique is lengthy and nasopharyngeal sampling requires trained personnel. Saliva NAAT represents an interesting alternative but diagnostic performances vary widely between studies.\n\nObjectiveTo assess the diagnostic accuracy of a nasopharyngeal point-of-care antigen (Ag) test and of saliva NAAT for detection of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), as compared to nasopharyngeal NAAT.\n\nDesignProspective participant enrollment from 19 October through 18 December 2020.\n\nSettingTwo community COVID-19 screening centers in Paris, France.\n\nParticipants1452 ambulatory children and adults referred for SARS-CoV-2 testing.\n\nInterventionsNAAT on a saliva sample (performed with three different protocols for pre-processing, amplification and detection of SARS-CoV-2) and Ag testing on a nasopharyngeal sample.\n\nMeasurementsPerformance of saliva NAAT and nasopharyngeal Ag testing.\n\nResultsOverall, 129/1443 (9%) participants tested positive on nasopharyngeal NAAT (102/564 [18%] in symptomatic and 27/879 [3%] in asymptomatic participants). Sensitivity was of 94% (95% CI, 86% to 98%), 23% (CI, 14% to 35%), 94% (CI, 88% to 97%) and 96% (CI, 91% to 99%) for the nasopharyngeal Ag test and the three different protocols of saliva NAAT, respectively. Estimates of specificity were above 95% for all methods. Diagnostic accuracy was similar in symptomatic and asymptomatic individuals.\n\nLimitationsFew children (n=122, 8%) were included.\n\nConclusionIn the ambulatory setting, diagnostic accuracy of nasopharyngeal Ag testing and of saliva NAAT seems similar to that of nasopharyngeal NAAT, subject to strict compliance with specific pre-processing and amplification protocols.\n\nRegistration numberNCT04578509\n\nFunding SourcesFrench Ministry of Health and the Assistance Publique-Hopitaux de Paris Foundation.", - "rel_num_authors": 22, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.08.21255109", + "rel_abs": "ImportancePersistent symptoms are reported in patients who survive the initial stage of COVID-19, often referred to as \"long COVID\" or \"post-acute sequelae of SARS-CoV-2 infection\" (PASC); however, evidence on incidence is still lacking, and symptoms relevant to pain are yet to be assessed.\n\nObjectiveTo determine long-term symptoms in COVID-19 survivors after infection.\n\nData SourcesA literature search was performed using the electronic databases PubMed, EMBASE, Scopus, and CHINAL and preprint servers MedR{chi}iv and BioR{chi}iv through January 15, 2021.\n\nStudy SelectionEligible studies were those reporting patients with a confirmed diagnosis of SARS-CoV-2 and who showed any symptoms persisting beyond the acute phase.\n\nData Extraction and SynthesisIncidence rate of symptoms were pooled using inverse variance methods with a DerSimonian-Laird random-effects model.\n\nMain Outcomes and MeasuresThe primary outcome was pain-related symptoms such as headache or myalgia. Secondary outcomes were symptoms relevant to pain (depression or muscle weakness) and symptoms frequently reported (anosmia and dyspnea). Heterogeneity among studies and publication bias for each symptom were estimated. The source of heterogeneity was explored using meta-regression, with follow-up period, age and sex as covariates.\n\nResultsIn total, 35 studies including 18,711 patients were eligible. Eight pain-related symptoms and 26 other symptoms were identified. The highest pooled incidence among pain-related symptoms was chest pain (17%, 95% CI, 12%-25%), followed by headache (16%, 95% CI, 9%-27%), arthralgia (13%, 95% CI, 7%-24%), neuralgia (12%, 95% CI, 3%-38%) and abdominal pain (11%, 95% CI, 7%-16%). The highest pooled incidence among other symptoms was fatigue (45%, 95% CI, 32%-59%), followed by insomnia (26%, 95% CI, 9%-57%), dyspnea (25%, 95% CI, 15%-38%), weakness (25%, 95% CI, 8%-56%) and anosmia (19%, 95% CI, 13%-27%). Substantial heterogeneity was identified (I2, 50-100%). Meta-regression analyses partially accounted for the source of heterogeneity, and yet, 53% of the symptoms remained unexplained.\n\nConclusions and RelevanceThe current meta-analysis may provide a complete picture of incidence in PASC. It remains unclear, however, whether post-COVID symptoms progress or regress over time or to what extent PASC are associated with age or sex.\n\nKey PointsO_ST_ABSQuestionC_ST_ABSWhat is the incidence rate of long-term post-acute sequelae of SARS-Cov-2 infection related to pain and other symptoms?\n\nFindingsIn the current meta-analysis of 35 studies with 18,711 patients, the highest estimated incidence among pain-related symptoms was chest pain (17%), followed by headache (16%), arthralgia (13%), neuralgia (12%) and abdominal pain (11%). That among other symptoms was fatigue (45%), followed by insomnia (26%), dyspnea (25%), weakness (25%) and anosmia (19%).\n\nMeaningThese findings suggest that long-term post-acute sequelae of SARS-Cov-2 infection must not be overlooked or underestimated especially when vaccination has become the focus.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Solen Kerneis", - "author_inst": "Universite de Paris, Assistance Publique-Hopitaux de Paris, hopital Bichat" - }, - { - "author_name": "Caroline Elie", - "author_inst": "APHP" - }, - { - "author_name": "Jacques Fourgeaud", - "author_inst": "APHP" - }, - { - "author_name": "Laure Choupeaux", - "author_inst": "APHP" - }, - { - "author_name": "Severine Mercier Delarue", - "author_inst": "APHP" - }, - { - "author_name": "Marie Laure Alby", - "author_inst": "COVISAN" - }, - { - "author_name": "Pierre Quentin", - "author_inst": "COVISAN" - }, - { - "author_name": "Juliette Pavie", - "author_inst": "APHP" + "author_name": "Hiroshi Hoshijima", + "author_inst": "Tohoku University Graduate School of Dentistry" }, { - "author_name": "Patricia Brazille", - "author_inst": "APHP" - }, - { - "author_name": "Marie Laure Nere", - "author_inst": "APHP" - }, - { - "author_name": "Marine Minier", - "author_inst": "APHP" - }, - { - "author_name": "Audrey Gabassi", - "author_inst": "APHP" - }, - { - "author_name": "Aurelien Gibaud", - "author_inst": "APHP" - }, - { - "author_name": "Sebastien Gauthier", - "author_inst": "APHP" - }, - { - "author_name": "Chrystel Leroy", - "author_inst": "APHP" - }, - { - "author_name": "Etienne Voirin Mathieu", - "author_inst": "APHP" - }, - { - "author_name": "Claire Poyart", - "author_inst": "APHP" - }, - { - "author_name": "Michel Vidaud", - "author_inst": "APHP" + "author_name": "Takahiro Mihara", + "author_inst": "Yokohama City University Graduate School of Medicine" }, { - "author_name": "Beatrice Parfait", - "author_inst": "APHP" + "author_name": "Hiroyuki Seki", + "author_inst": "Kyorin University School of Medicine" }, { - "author_name": "Constance Delaugerre", - "author_inst": "APHP" + "author_name": "Shunsuke Hyuga", + "author_inst": "Kitasato University School of Medicine" }, { - "author_name": "Jean Marc Treluyer", - "author_inst": "APHP" + "author_name": "Norifumi Kuratani", + "author_inst": "Saitama Children's Medical Center" }, { - "author_name": "Jerome Le Goff", - "author_inst": "APHP" + "author_name": "Toshiya Shiga", + "author_inst": "International University of Health and Welfare" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -814693,73 +814253,53 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.04.08.21254705", - "rel_title": "Real-world Effect of Monoclonal Antibody Treatment in COVID-19 Patients in a Diverse Population in the United States", + "rel_doi": "10.1101/2021.04.08.21255135", + "rel_title": "Early evidence of COVID-19 vaccine effectiveness within the general population of California", "rel_date": "2021-04-10", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.08.21254705", - "rel_abs": "BackgroundMonoclonal antibodies (mAbs) against SARS-CoV-2 are a promising treatment for limiting the progression of COVID-19 and decreasing strain on hospitals. Their use, however, remains limited, particularly in disadvantaged populations.\n\nMethodsElectronic health records were reviewed from SARS-CoV-2 patients at a single medical center in the United States that initiated mAb infusions in January 2021 with the support of the U.S. Department of Health and Human Services National Disaster Medical System. Patients who received mAbs were compared to untreated patients from the time period before mAb availability who met eligibility criteria for mAb treatment. We used logistic regression to measure the effect of mAb treatment on the risk of hospitalization or emergency department (E.D.) visit within 30 days of laboratory-confirmed COVID-19.\n\nResultsOf 598 COVID-19 patients, 270 (45%) received bamlanivimab and 328 (55%) were untreated. Two hundred and thirty-one patients (39%) were Hispanic. Among treated patients, 5/270 (1.9%) presented to the E.D. or required hospitalization within 30 days of a positive SARS-CoV-2 test, compared to 39/328 (12%) untreated patients (p<0.001). After adjusting for age, gender, and comorbidities, the risk of E.D. visit or hospitalization was 82% lower in mAb-treated patients compared to untreated patients (95% confidence interval [CI]: 66%-94%).\n\nConclusionsIn this diverse, real-world COVID-19 patient population, mAb treatment significantly decreased the risk of subsequent E.D. visit or hospitalization. Broader treatment with mAbs, including in disadvantaged patient populations, can decrease the burden on hospitals and should be facilitated in all populations in the United States to ensure health equity.\n\nSummaryIn a diverse, real-world COVID-19 patient population, treatment with monoclonal antibodies significantly decreased the risk of subsequent emergency department visit or hospitalization within 30 days of a positive SARS-CoV-2 viral test.", - "rel_num_authors": 14, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.08.21255135", + "rel_abs": "BackgroundEstimates of COVID-19 vaccine effectiveness under real-world conditions, and understanding of barriers to uptake, are necessary to inform vaccine rollout.\n\nMethodsWe enrolled cases (testing positive) and controls (testing negative) from among the population whose SARS-CoV-2 molecular diagnostic test results from 24 February-29 April 2021 were reported to the California Department of Public Health. Participants were matched on age, sex, and geographic region. We assessed participants self-reported history of COVID-19 vaccine receipt (BNT162b2 and mRNA-1273). Participants were considered fully vaccinated two weeks after second dose receipt. Among unvaccinated participants, we assessed willingness to receive vaccination, when eligible. We measured vaccine effectiveness (VE) via the matched odds ratio of prior vaccination, comparing cases with controls.\n\nResultsWe enrolled 1023 eligible participants aged [≥]18 years. Among 525 cases, 71 (13.5%) received BNT162b2 or mRNA-1273; 20 (3.8%) were fully vaccinated with either product. Among 498 controls, 185 (37.1%) received BNT162b2 or mRNA-1273; 86 (16.3%) were fully vaccinated with either product. Two weeks after second dose receipt, VE was 86.8% (95% confidence interval: 68.6-94.7%) and 85.6% (69.1-93.9%) for BNT162b2 and mRNA-1273, respectively. Fully vaccinated participants receiving either product experienced 91.3% (79.7-96.3%) and 68.3% (28.5-86.0%) VE against symptomatic and asymptomatic infection, respectively. Among unvaccinated participants, 42.4% (159/375) residing in rural regions and 23.8% (67/281) residing in urban regions reported hesitancy to receive COVID-19 vaccination.\n\nConclusionsAuthorized mRNA vaccines are effective at reducing documented SARS-CoV-2 infections within the general population of California. Vaccine hesitancy presents a barrier to reaching coverage levels needed for herd immunity.\n\nBrief pointsO_LIVaccination is preventing documented SARS-CoV-2 infection in California, with 68% and 91% effectiveness against asymptomatic and symptomatic infection, respectively.\nC_LIO_LIVaccine effectiveness was equivalent for BNT126b2 and mRNA-1273.\nC_LIO_LIOnly 66% of unvaccinated participants were willing to receive the vaccine when eligible.\nC_LI", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Kaitlin Rainwater-Lovett", - "author_inst": "Johns Hopkins Applied Physics Laboratory" - }, - { - "author_name": "John T. Redd", - "author_inst": "Office of the Assistant Secretary of Preparedness and Response, U.S. Department of Health and Human Services, Washington, DC" - }, - { - "author_name": "Miles A. Stewart", - "author_inst": "Johns Hopkins Applied Physics Laboratory" - }, - { - "author_name": "Natalia Elias Calles", - "author_inst": "TMC HealthCare" - }, - { - "author_name": "Tyler Cluff", - "author_inst": "TMC HealthCare" - }, - { - "author_name": "Mike Fang", - "author_inst": "Johns Hopkins Applied Physics Laboratory" + "author_name": "Kristin Andrejko", + "author_inst": "University of California at Berkeley" }, { - "author_name": "Mark J. Panaggio", - "author_inst": "Johns Hopkins Applied Physics Laboratory" + "author_name": "Jake M Pry", + "author_inst": "California Department of Public Health" }, { - "author_name": "Anastasia S. Lambrou", - "author_inst": "Johns Hopkins Applied Physics Laboratory" + "author_name": "Jennifer F Myers", + "author_inst": "California Department of Public Health" }, { - "author_name": "Jonathan K. Thornhill", - "author_inst": "Johns Hopkins Applied Physics Laboratory" + "author_name": "Nicholas P Jewell", + "author_inst": "London School of Hygiene and Tropical Medicine" }, { - "author_name": "Christopher Bradburne", - "author_inst": "Johns Hopkins Applied Physics Laboratory" + "author_name": "John Openshaw", + "author_inst": "Stanford University" }, { - "author_name": "Samuel Imbriale", - "author_inst": "Johns Hopkins Applied Physics Laboratory" + "author_name": "James Watt", + "author_inst": "California Department of Public Health" }, { - "author_name": "Jeffrey D. Freeman", - "author_inst": "Johns Hopkins Applied Physics Laboratory" + "author_name": "Seema Jain", + "author_inst": "California Department of Health" }, { - "author_name": "Michael Anderson", - "author_inst": "Office of the Assistant Secretary of Preparedness and Response, US Department of Health and Human Services" + "author_name": "Joseph A Lewnard", + "author_inst": "University of California Berkeley" }, { - "author_name": "Robert P. Kadlec", - "author_inst": "Office of the Assistant Secretary of Preparedness and Response, US Department of Health and Human Services" + "author_name": "- California COVID-19 Case-Control Study Team", + "author_inst": "" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -816243,39 +815783,55 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2021.04.05.21254919", - "rel_title": "Identifiability and Predictability of Integer- and Fractional-Order Epidemiological Models Using Physics-Informed Neural Networks", + "rel_doi": "10.1101/2021.04.08.21254762", + "rel_title": "Companionship for women using English maternity services during COVID-19: National and organisational perspectives", "rel_date": "2021-04-09", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.05.21254919", - "rel_abs": "We analyze a plurality of epidemiological models through the lens of physics-informed neural networks (PINNs) that enable us to identify multiple time-dependent parameters and to discover new data-driven fractional differential operators. In particular, we consider several variations of the classical susceptible-infectious-removed (SIR) model by introducing more compartments and delay in the dynamics described by integer-order, fractional-order, and time-delay models. We report the results for the spread of COVID-19 in New York City, Rhode Island and Michigan states, and Italy, by simultaneously inferring the unknown parameters and the unobserved dynamics. For integer-order and time-delay models, we fit the available data by identifying time-dependent parameters, which are represented by neural networks (NNs). In contrast, for fractional differential models, we fit the data by determining different time-dependent derivative orders for each compartment, which we represent by NNs. We investigate the identifiability of these unknown functions for different datasets, and quantify the uncertainty associated with NNs and with control measures in forecasting the pandemic.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.08.21254762", + "rel_abs": "ObjectivesTo explore the impact of COVID-19 on companionship for women using maternity services in England, as part of the Achieving Safe and Personalised maternity care In Response to Epidemics (ASPIRE COVID-19 UK) study.\n\nSettingMaternity care provision in England.\n\nParticipantsInterviews were held with 26 national governmental, professional, and service-user organisation leads including representatives from the Royal College of Midwives, NHS England, Birthrights and AIMS (July-Dec). Other data included public-facing outputs logged from 25 maternity Trusts (Sept/Oct) and data extracted from 78 documents from 8 key governmental, professional and service-user organisations that informed national maternity care guidance and policy (Feb-Dec).\n\nResultsSix themes emerged: Postcode lottery of care highlights variations in companionship practices, Confusion and stress around rules relates to a lack of and variable information concerning companionship, Unintended consequences concerns the negative impacts of restricted companionship on service-users and staff, Need for flexibility highlights concerns about applying companionship policies irrespective of need, Acceptable time for support highlights variations in when and if companionship was allowed antenatally and intrapartum; and Loss of human rights for gain in infection control emphasizes how a predominant focus on infection control was at a cost to psychological safety and womens human rights.\n\nConclusionsPolicies concerning companionship have been inconsistently applied within English maternity services during the COVID-19 pandemic. In some cases, policies were not justified by the level of risk, and were applied indiscriminately regardless of need. This was associated with psychological harms for some women and staff. There is an urgent need to determine how to balance risks and benefits sensitively and flexibly and to optimise outcomes during the current and future crisis situations.\n\nStrengths and limitations of this studyO_LIThis is the first paper to consider links between policy and practice in companionship in maternity care during the COVID-19 pandemic;\nC_LIO_LIData triangulation across stakeholders, policy and practice provides nuanced and context related perspectives on why and how companionship was impacted;\nC_LIO_LIStakeholders included representatives from all key agencies involved in maternity care;\nC_LIO_LIPractice related issues were collected from the maternity Trust website and social media-based public facing information, which may or may not reflect actual care practices;\nC_LIO_LIThe study does not include information directly reported by parents and healthcare professionals.\nC_LI", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Ehsan Kharazmi", - "author_inst": "Brown University" + "author_name": "Gill Thomson", + "author_inst": "University of Central Lancashire" }, { - "author_name": "Min Cai", - "author_inst": "Brown University and Shanghai University" + "author_name": "Marie Clare Balaam", + "author_inst": "University of Central Lancashire" }, { - "author_name": "Xiaoning Zheng", - "author_inst": "Brown University and Jinan University" + "author_name": "Rebecca Nowland", + "author_inst": "University of Central Lancashire" }, { - "author_name": "Guang Lin", - "author_inst": "Purdue University" + "author_name": "Nicola Crossland", + "author_inst": "University of Central Lancashire" }, { - "author_name": "George Em Karniadakis", - "author_inst": "Brown University" + "author_name": "Gill Moncrieff", + "author_inst": "University of Central Lancashire" + }, + { + "author_name": "Stephanie Heys", + "author_inst": "North West Ambulance Service" + }, + { + "author_name": "Arni Sarian", + "author_inst": "University of Central Lancashire" + }, + { + "author_name": "Joanne Cull", + "author_inst": "University of Central Lancashire" + }, + { + "author_name": "Soo Downe", + "author_inst": "University of Central Lancashire" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "health systems and quality improvement" }, { "rel_doi": "10.1101/2021.04.09.439149", @@ -818837,107 +818393,55 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.04.01.21254765", - "rel_title": "Mental health inequalities in healthcare, economic, and housing disruption during COVID -19: an investigation in 12 longitudinal studies", + "rel_doi": "10.1101/2021.04.01.21254770", + "rel_title": "Relative expression of pro-inflammatory molecules in COVID-19 patients manifested disease severities.", "rel_date": "2021-04-07", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.01.21254765", - "rel_abs": "BackgroundThe COVID-19 pandemic and associated virus suppression measures have disrupted lives and livelihoods and people already experiencing mental ill-health may have been especially vulnerable.\n\nAimTo quantify mental health inequalities in disruptions to healthcare, economic activity and housing.\n\nMethod59,482 participants in 12 UK longitudinal adult population studies with data collected prior to and during the COVID-19 pandemic. Within each study we estimated the association between psychological distress assessed pre-pandemic and disruptions since the start of the pandemic to three domains: healthcare (medication access, procedures, or appointments); economic activity (employment, income, or working hours); and housing (change of address or household composition). Meta-analyses were used to pool estimates across studies.\n\nResultsAcross the analysed datasets, one to two-thirds of participants experienced at least one disruption, with 2.3-33.2% experiencing disruptions in two or more domains. One standard deviation higher pre-pandemic psychological distress was associated with: (i) increased odds of any healthcare disruptions (OR=1.30; [95% CI:1.20-1.40]) with fully adjusted ORs ranging from 1.24 [1.09-1.41] for disruption to procedures and 1.33 [1.20- 1.49] for disruptions to prescriptions or medication access; (ii) loss of employment (OR=1.13 [1.06-1.21]) and income (OR=1.12 [1.06 -1.19]) and reductions in working hours/furlough (OR=1.05 [1.00-1.09]); (iii) no associations with housing disruptions (OR=1.00 [0.97-1.03]); and (iv) increased likelihood of experiencing a disruption in at least two domains (OR=1.25 [1.18-1.32]) or in one domain (OR=1.11 [1.07-1.16]) relative to no disruption.\n\nConclusionPeople experiencing psychological distress pre-pandemic have been more likely to experience healthcare and economic disruptions, and clusters of disruptions across multiple domains during the pandemic. Failing to address these disruptions risks further widening the existing inequalities in mental health.", - "rel_num_authors": 22, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.01.21254770", + "rel_abs": "Aggressive immune response, due to over-expressed pro-inflammatory molecules, had been characterized in COVID-19 patients. Some of those mediators have a dual and opposite role on immune-systems to play behind differential disease severities. We investigated the expression of some cytokines and chemokines in COVID-19 patients in Bangladesh. We diagnosed the patients by detecting SARS-CoV-2 RNA in nasal swab samples by the real-time RT-PCR method. Thirty adult patients were preselected based on their disease severities and grouped into mild, moderate, and severe cases. Nine healthy volunteers participated in this study as control. Relative expression of nine cytokines/chemokine in total leukocytes was semi-quantified in SYBRgreen-based qRT-PCR. We performed statistical tests on transformed log data using SPSS 24.0. At the onset of symptoms (day-1), ACE2 (P < 0.05) and IL-6 (P > 0.05) were up-regulated in all COVID-19 groups, although expression levels did not significantly correlate with disease severities. However, expression of IL-6, MCP-1, MIP-1, TNF-, RANTES, and ACE2, on day-14, were positively correlated with disease severities. Relative viral load at day-1 showed no significant correlation with cytokine expression but had a significant positive correlation with RANTES and ACE2 expression on day-14 (P < 0.05). Male patients had a higher level of IL-6 than female patients on day-1 (P < 0.05). All COVID-19 patients showed up-regulated cytokines and chemokines on the day-14 compared to day-1 except TNF-. Female patients had higher expression of ACE2 and IL-12 on day-14. Up-regulated cytokines/chemokines at the convalescent stage, especially IL-6, may target anti-cytokine therapy in post-COVID-19 patients management.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Giorgio Di Gessa", - "author_inst": "Institute of Epidemiology and Health Care, University College London" - }, - { - "author_name": "Jane Maddock", - "author_inst": "MRC Unit for Lifelong Health and Ageing, University College London" - }, - { - "author_name": "Michael J Green", - "author_inst": "MRC/CSO Social & Public Health Sciences Unit, University of Glasgow" - }, - { - "author_name": "Ellen J Thompson", - "author_inst": "Department of Twin Research and Genetic Epidemiology, School of Life Course Sciences, Kings College London" - }, - { - "author_name": "Eoin McElroy", - "author_inst": "Department of Neuroscience, Psychology and Behaviour, University of Leicester" - }, - { - "author_name": "Helena L Davies", - "author_inst": "Social, Genetic & Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, Kings College London" - }, - { - "author_name": "Jessica Mundy", - "author_inst": "Social, Genetic & Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, Kings College London" - }, - { - "author_name": "Anna J Stevenson", - "author_inst": "Centre for Genomic and Experimental Medicine, University of Edinburgh" - }, - { - "author_name": "Alex S.F Kwong", - "author_inst": "Division of Psychiatry, University of Edinburgh and MRC Integrative Epidemiology Unit, University of Bristol" - }, - { - "author_name": "Gareth J Griffith", - "author_inst": "MRC Integrative Epidemiology Unit, University of Bristol" - }, - { - "author_name": "Srinivasa Vittal Katikireddi", - "author_inst": "MRC/CSO Social & Public Health Sciences Unit, University of Glasgow" - }, - { - "author_name": "Claire L Niedzwiedz", - "author_inst": "Institute of Health & Wellbeing, University of Glasgow" - }, - { - "author_name": "George B Ploubidis", - "author_inst": "Centre for Longitudinal Studies, UCL Social Research Institute, University College London" - }, - { - "author_name": "Emla Fitzsimons", - "author_inst": "Centre for Longitudinal Studies, UCL Social Research Institute, University College London" + "author_name": "Shireen Nigar", + "author_inst": "Jashore University of Science and Technology" }, { - "author_name": "Morag Henderson", - "author_inst": "Centre for Longitudinal Studies, UCL Social Research Institute, University College London" + "author_name": "SM Tanjil Shah", + "author_inst": "University of Dhaka" }, { - "author_name": "Richard J. Silverwood", - "author_inst": "Centre for Longitudinal Studies, UCL Social Research Institute, University College London" + "author_name": "Ali Ahasan Setu", + "author_inst": "Jashore University of Science and Technology" }, { - "author_name": "Nishi Chaturvedi", - "author_inst": "MRC Unit for Lifelong Health and Ageing, University College London" + "author_name": "Sourav Dutta Dip", + "author_inst": "Jashore University of Science and Technology" }, { - "author_name": "Gerome Breen", - "author_inst": "Social, Genetic & Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, Kings College London and Maudsley Biomedical Research Cen" + "author_name": "Habiba Ibnat", + "author_inst": "Jashore University of Science and Technology" }, { - "author_name": "Claire J Steves", - "author_inst": "Department of Twin Research and Genetic Epidemiology, School of Life Course Sciences, Kings College London" + "author_name": "M. Touhid Islam", + "author_inst": "250 Bedded Jashore General Hospital" }, { - "author_name": "Andrew Steptoe", - "author_inst": "Institute of Epidemiology and Health Care, University College London" + "author_name": "Selina Akter", + "author_inst": "Jashore University of Science and Technology" }, { - "author_name": "David J Porteous", - "author_inst": "Centre for Genomic and Experimental Medicine, University of Edinburgh" + "author_name": "Iqbal Kabir Jahid", + "author_inst": "Jashore University of Science and Technology" }, { - "author_name": "Praveetha Patalay", - "author_inst": "Centre for Longitudinal Studies and MRC Unit for Lifelong Health and Ageing, University College London" + "author_name": "Md. Anwar Hossain", + "author_inst": "University of Dhaka" } ], "version": "1", - "license": "cc_by", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "psychiatry and clinical psychology" + "category": "pathology" }, { "rel_doi": "10.1101/2021.04.02.21254839", @@ -820607,69 +820111,25 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.04.05.21253827", - "rel_title": "Sex and gender differences in COVID testing, hospital admission, presentation, and drivers of severe outcomes in the DC/Maryland region", + "rel_doi": "10.1101/2021.04.04.21254884", + "rel_title": "Comparing between survived and deceased patients with Diabetes Mellitus and COVID-19 in Bangladesh: A cross- sectional study from COVID-19 dedicated hospital", "rel_date": "2021-04-07", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.05.21253827", - "rel_abs": "Structured AbstractO_ST_ABSBackgroundC_ST_ABSRates of severe illness and mortality from SARS-CoV-2 are greater for males, but the mechanisms for this difference are unclear. Understanding the differences in outcomes between males and females across the age spectrum will guide both public health and biomedical interventions.\n\nMethodsRetrospective cohort analysis of SARS-CoV-2 testing and admission data in a health system. Patient-level data were assessed with descriptive statistics and logistic regression modeling was used to identify features associated with increased male risk of severe outcomes.\n\nResultsIn 213,175 SARS-CoV-2 tests, despite similar positivity rates (8.2%F vs 8.9%M), males were more frequently hospitalized (28%F vs 33%M). Of 2,626 hospitalized individuals, females had less severe presenting respiratory parameters and males had more fever. Comorbidity burden was similar, but with differences in specific conditions. Medications relevant for SARS-CoV-2 were used at similar frequency except tocilizumab (M>F). Males had higher inflammatory lab values. In a logistic regression model, male sex was associated with a higher risk of severe outcomes at 24 hours (odds ratio (OR) 3.01, 95%CI 1.75, 5.18) and at peak status (OR 2.58, 95%CI 1.78,3.74) among 18-49 year-olds. Block-wise addition of potential explanatory variables demonstrated that only the inflammatory labs substantially modified the OR associated with male sex across all ages.\n\nConclusionHigher levels of clinical inflammatory labs are the only features that are associated with the heightened risk of severe outcomes and death for males in COVID-19.\n\nTrial registrationNA\n\nFundingHopkins inHealth; COVID-19 Administrative Supplement (HHS Region 3 Treatment Center), Office of the ASPR; NIH/NCI U54CA260492 (SK), NIH/NIA U54AG062333 (SK).", - "rel_num_authors": 14, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.04.21254884", + "rel_abs": "The current coronavirus disease 2019 (COVID-19) outbreak was reported to cause significantly higher mortality and morbidity among patients with diabetes mellitus (DM). Although Bangladesh is amongst the top 10 countries with diabetic people, data on these patients with COVID-19 is scarce from this region. This study aimed to illustrate the clinical features and outcomes of hospitalized patients with COVID-19 and DM in Bangladesh while comparing survivors and deceased.\n\nThis retrospective cross-sectional study was conducted among RT-PCR confirmed COVID-19 patients with pre-existing Diabetes Mellitus in a specialized COVID-19 hospital in Bangladesh. Data from hospital records were analyzed.\n\nAmong 921 RT-PCR confirmed COVID-19 admitted during the study period, 231 ([~]25%) patients with pre-existing DM (median age 60 years) were included in the analysis. The death rate among all hospitalized patients (with and without DM) was 2.8% compared to 11.3% among diabetic patients. The median hospital stay was 13 days (IQR 10.5, 17.0) for survivors and five days (IQR 2.0-8.3) for the deceased. The clinical features were not significantly different between survivors and the deceased. However, deceased patients had significantly lower blood oxygen level (85% vs 93%, p <0.001), and higher neutrophil-lymphocyte ratio (7.9 vs 4.5, p 0.003) and serum ferritin (946.0 vs 425.0 ng/ml, p 0.03). Glycemic status was poor in both groups.\n\nThis study would help identify a subgroup of diabetic patients with COVID-19 who are at higher risk of in-hospital death and improve clinical decision making.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Eileen P. Scully", - "author_inst": "Johns Hopkins University School of Medicine" - }, - { - "author_name": "Grant Schumock", - "author_inst": "The Johns Hopkins Bloomberg School of Public Health" - }, - { - "author_name": "Martina Fu", - "author_inst": "The Johns Hopkins Bloomberg School of Public Health" - }, - { - "author_name": "Guido Massaccesi", - "author_inst": "Johns Hopkins University School of Medicine" - }, - { - "author_name": "John Muschelli", - "author_inst": "The Johns Hopkins Bloomberg School of Public Health" - }, - { - "author_name": "Joshua Betz", - "author_inst": "The Johns Hopkins Bloomberg School of Public Health" - }, - { - "author_name": "Eili Y. Klein", - "author_inst": "Johns Hopkins University School of Medicine" - }, - { - "author_name": "Natalie E. West", - "author_inst": "Johns Hopkins University School of Medicine" - }, - { - "author_name": "Matthew L. Robinson", - "author_inst": "Johns Hopkins University School of Medicine" - }, - { - "author_name": "Brian T Garibaldi", - "author_inst": "Johns Hopkins University School of Medicine" - }, - { - "author_name": "Karen Bandeen- Roche", - "author_inst": "The Johns Hopkins Bloomberg School of Public Health" - }, - { - "author_name": "Scott Zeger", - "author_inst": "The Johns Hopkins Bloomberg School of Public Health" + "author_name": "Md. Shahed Morshed", + "author_inst": "Emergency medical officer, Kurmitola general hospital, Dhaka, Bangladesh" }, { - "author_name": "Sabra L. Klein", - "author_inst": "The Johns Hopkins Bloomberg School of Public Health" + "author_name": "Abdullah Al Mosabbir", + "author_inst": "Biomedical Research Foundation, Dhaka" }, { - "author_name": "Amita Gupta", - "author_inst": "Johns Hopkins School of Medicine" + "author_name": "Mohammad Sorowar Hossain", + "author_inst": "Biomedical Research Foundation" } ], "version": "1", @@ -822381,63 +821841,63 @@ "category": "emergency medicine" }, { - "rel_doi": "10.1101/2021.04.05.21254937", - "rel_title": "Increased vulnerability to SARS-CoV-2 infection among indigenous people living in the urban area of Manaus", - "rel_date": "2021-04-07", + "rel_doi": "10.1101/2021.03.22.21254110", + "rel_title": "Drug repositioning candidates identified using in-silico quasi-quantum molecular simulation demonstrate reduced COVID-19 mortality in 1.5M patient records", + "rel_date": "2021-04-06", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.05.21254937", - "rel_abs": "BackgroundThe COVID-19 pandemic threatens indigenous peoples living in suburban areas of large Brazilian cities and has thus far intensified their pre-existing socio-economic inequalities. This study evaluated the epidemiological situation of SARS-CoV-2 infection among residents of the biggest urban multiethnic indigenous community of the Amazonas state, Brazil.\n\nMethodsBlood samples of 280 indigenous people who live in the urban community known as Parque das Tribos, which is located in the surrounding area of Manaus, were tested for the presence of anti- SARS-CoV-2 IgA or IgG antibodies using an enzyme-linked immunosorbent assay. An epidemiological standardized interviewer-administered questionnaire was applied to assess the risk factors and sociodemographic information of the study population.\n\nResultsWe found a total positivity rate of 64.64% (95% CI 59.01-70.28) for SARS-CoV-2 infection. IgA and IgG were detected in 55.71% (95% CI 49.89-61.54) and 60.71% (95% CI 54.98-66.45) of the individuals tested, respectively. From the total number (n=280), 80.11% of positive individuals (95%; CI 74.24-85.98) were positive for both IgA and IgG Abs. All individuals with COVID-19-related symptoms on the day of blood collection (n=11) were positive for IgG, while IgA was detected in 84.61% (n=55) of individuals who had presented symptoms several weeks before the blood collection. Individuals aged 30-39 were more susceptible to SARS-CoV-2 infection (prevalence ratio [PR] 0.77; 95% CI 0.58-1.03; p=0.033). People whose main source of information on COVID-19 was religious leaders or friends showed higher susceptibility to infection (PR 1.22; 95% CI 1.00-1.49; p=0.040). In addition, individuals who left home more frequently were at higher risk of infection (PR 1.22; 95% CI 1.00-1.49; p=0.048). Five or more individuals per household increased almost 5-fold the risk of virus transmission (Odds ratio [OR] 2.56; 95% CI; 1.09-6.01; p=0.019). Over 95% of the study population had no access to clean water and/or sanitation.\n\nConclusionsThe disproportionate dissemination of SARS-CoV-2 infection observed in the Parque das Tribos urban indigenous community might be driven by typical cultural behavior and socioeconomic inequalities. Despite the pandemic threat, this population is not being targeted by public policies and appears to be chronically invisible to the Brazilian authorities.", + "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.22.21254110", + "rel_abs": "BackgroundDrug repositioning is a key component of COVID-19 pandemic response, through identification of existing drugs that can effectively disrupt COVID-19 disease processes, contributing valuable insights into disease pathways. Traditional non in silico drug repositioning approaches take substantial time and cost to discover effect and, crucially, to validate repositioned effects.\n\nMethodsUsing a novel in-silico quasi-quantum molecular simulation platform that analyzes energies and electron densities of both target proteins and candidate interruption compounds on High Performance Computing (HPC), we identified a list of FDA-approved compounds with potential to interrupt specific SARS-CoV-2 proteins. Subsequently we used 1.5M patient records from the National COVID Cohort Collaborative to create matched cohorts to refine our in-silico hits to those candidates that show statistically significant clinical effect.\n\nResultsWe identified four drugs, Metformin, Triamcinolone, Amoxicillin and Hydrochlorothiazide, that were associated with reduced mortality by 27%, 26%, 26%, and 23%, respectively, in COVID-19 patients.\n\nConclusionsTogether, these findings provide support to our hypothesis that in-silico simulation of active compounds against SARS-CoV-2 proteins followed by statistical analysis of electronic health data results in effective therapeutics identification.", "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Gemilson Soares Pontes GSP", - "author_inst": "Instituto Nacional de Pesquisa da Amazonia (INPA); Universidade Federal do Amazonas (UFAM), Programa de Pos-graduacao em Imunologia Basica e Aplicada; Universid" + "author_name": "Joy Alamgir", + "author_inst": "ARIScience" }, { - "author_name": "Jean de Melo Silva JMS", - "author_inst": "Instituto Nacional de Pesquisa da Amazonia (INPA)" + "author_name": "Masanao Yajima", + "author_inst": "Boston University" }, { - "author_name": "Renato Pinheiro-Silva RPS", - "author_inst": "Universidade do Estado do Amazonas, Programa de Pos-graduacao em Ciencias Aplicadas a Hematologia" + "author_name": "Rosa Ergas", + "author_inst": "ARIScience" }, { - "author_name": "Anderson Nogueira Barbosa ANB", - "author_inst": "Instituto Nacional de Pesquisa da Amazonia (INPA)" + "author_name": "Xinci Chen", + "author_inst": "ARIScience" }, { - "author_name": "Luciano Cardenes Santos LCS", - "author_inst": "Universidade Federal do Mato Grosso, Campus do Araguaia" + "author_name": "Nicholas Hill", + "author_inst": "Great Plains Tribal Leader Health Board" }, { - "author_name": "Antonio de Padua Quirino Ramalho APQR", - "author_inst": "Faculdade de Medicina, Departamento de Saude Coletiva, Universidade Federal do Amazonas (UFAM)" + "author_name": "Naved Munir", + "author_inst": "Caromont Regional Medical Center" }, { - "author_name": "Carlos Eduardo de Castro Alves CECA", - "author_inst": "Universidade Federal do Amazonas (UFAM), Programa de Pos-graduacao em Imunologia Basica e Aplicada" + "author_name": "Mohsan Saeed", + "author_inst": "Boston University" }, { - "author_name": "Danielle Furtado da Silva DFS", - "author_inst": "Programa de Pos-graduacao em Biodiversidade e Biotecnologia da Amazonia Legal, PPG-BIONORTE" + "author_name": "Kenneth Gersing", + "author_inst": "National Institutes of Health" }, { - "author_name": "Leonardo Calheiros de Oliveira LCO", - "author_inst": "Universidade do Estado do Amazonas, Programa de Pos-graduacao em Ciencias Aplicadas a Hematologia" + "author_name": "Melissa Haendel", + "author_inst": "Oregon Health & Science University" }, { - "author_name": "Allyson Guimaraes da Costa AGC", - "author_inst": "Universidade Federal do Amazonas (UFAM), Programa de Pos-graduacao em Imunologia Basica e Aplicada; Universidade do Estado do Amazonas, Programa de Pos-graduaca" + "author_name": "Christopher Chute", + "author_inst": "Johns Hopkins University" }, { - "author_name": "Ana Carla Bruno ACB", - "author_inst": "Instituto Nacional de Pesquisa da Amazonia (INPA)" + "author_name": "Ruhul Abid", + "author_inst": "Brown University" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2021.04.01.21254709", @@ -824275,63 +823735,63 @@ "category": "medical ethics" }, { - "rel_doi": "10.1101/2021.03.31.21254731", - "rel_title": "Risk quantification for SARS-CoV-2 infection through airborne transmission in university settings", + "rel_doi": "10.1101/2021.03.31.21254699", + "rel_title": "Tryptophan and arginine metabolism is significantly altered at the time of admission in hospital for severe COVID-19 patients: findings from longitudinal targeted metabolomics analysis", "rel_date": "2021-04-06", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.31.21254731", - "rel_abs": "The COVID-19 pandemic has significantly impacted learning as many institutions switched to remote or hybrid instruction. An in-depth assessment of the risk of infection that takes into account environmental setting and mitigation strategies is needed to make safe and informed decisions regarding reopening university spaces. A quantitative model of infection probability that accounts for space-specific parameters is presented to enable assessment of the risk in reopening university spaces at given densities. The model uses local positivity rate, room capacity, mask filtration efficiency, air exchange rate, room volume, and time spent in the space as parameters to calculate infection probabilities in teaching spaces, dining halls, dorms, and shared bathrooms. The model readily calculates infection probabilities in various university spaces, with mask filtration efficiency and air exchange rate being among the dominant variables. When applied to university spaces, this model demonstrated that, under specific conditions that are feasible to implement, in-person classes could be held in large lecture halls with an infection risk over the semester < 1%. Meal pick-ups from dining halls and the use of shared bathrooms in residential dormitories among small groups of students could also be accomplished with low risk. The results of applying this model to spaces at Harvard University (Cambridge and Allston campuses) and Stanford University are reported. Finally, a user-friendly web application was developed using this model to calculate infection probability following input of space-specific variables. The successful development of a quantitative model and its implementation through a web application may facilitate accurate assessments of infection risk in university spaces. In light of the impact of the COVID-19 pandemic on universities, this tool could provide crucial insight to students, faculty, and university officials in making informed decisions.", + "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.31.21254699", + "rel_abs": "The heterogeneity in severity and outcome of COVID-19 cases points out the urgent need for early molecular characterization of patients followed by risk-stratified care. The main objective of this study was to evaluate the fluctuations of serum metabolomic profiles of COVID-19 patients with severe illness during the different disease stages in a longitudinal manner. We demonstrate a distinct metabolomic signature in serum samples of 32 hospitalized patients at the acute phase compared to the recovery period, suggesting the tryptophan (tryptophan, kynurenine, and 3-hydroxy-DL-kynurenine) and arginine (citrulline and ornithine) metabolism as contributing pathways in the immune response to SARS-CoV-2 with a potential link to the clinical severity of the disease. In addition, we provide evidence for glutamine metabolism in M2 macrophages as a complementary process and contribution of phenylalanine and tyrosine in the molecular mechanisms underlying the severe course of the infection. In conclusion, our results provide several functional metabolic markers for disease progression and severe outcome with potential clinical application.\n\nImportanceAlthough the host defense mechanisms against SARS-CoV-2 infection are still poorly described, they are of central importance in shaping the course of the disease and the possible outcome. Metabolomic profiling may complement the lacking knowledge of the molecular mechanisms underlying clinical manifestations and pathogenesis of COVID-19. Moreover, early identification of metabolomics{square}based biomarker signatures is proved to serve as an effective approach for the prediction of disease outcome. Here we provide the list of metabolites describing the severe, acute phase of the infection and bring the evidence of crucial metabolic pathways linked to aggressive immune responses. Finally, we suggest metabolomic phenotyping as a promising method for developing personalized care strategies in COVID-19 patients.", "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Mythri Ambatipudi", - "author_inst": "Harvard University" + "author_name": "Laura Ansone", + "author_inst": "Latvian Biomedical Research and Study Centre" }, { - "author_name": "Paola Carrillo Gonzalez", - "author_inst": "Harvard University" + "author_name": "Monta Ustinova", + "author_inst": "Latvian Biomedical Research and Study Centre" }, { - "author_name": "Kazi Tasnim", - "author_inst": "Harvard University" + "author_name": "Anna Terentjeva", + "author_inst": "Riga Stradins University" }, { - "author_name": "Jordan Daigle", - "author_inst": "Harvard University" + "author_name": "Ingus Perkons", + "author_inst": "Institute of Food Safety, Animal Health and Environment (BIOR)" }, { - "author_name": "Taisa Kulyk", - "author_inst": "Harvard University" + "author_name": "Liga Birzniece", + "author_inst": "Latvian Biomedical Research and Study Centre" }, { - "author_name": "Nicholas Jeffreys", - "author_inst": "Harvard University" + "author_name": "Vita Rovite", + "author_inst": "Latvian Biomedical Research and Study Centre" }, { - "author_name": "Nishant Sule", - "author_inst": "Harvard University" + "author_name": "Baiba Rozentale", + "author_inst": "Riga Stradins University" }, { - "author_name": "Rafael Trevino", - "author_inst": "Harvard University" + "author_name": "Ludmila Viksna", + "author_inst": "Riga Stradins University" }, { - "author_name": "Emily M He", - "author_inst": "Harvard University" + "author_name": "Oksana Kolesova", + "author_inst": "Riga Stradins University" }, { - "author_name": "David Mooney", - "author_inst": "Harvard University" + "author_name": "Kristaps Klavins", + "author_inst": "Riga Technical University" }, { - "author_name": "Esther E Koh", - "author_inst": "Harvard University" + "author_name": "Janis Klovins", + "author_inst": "Latvian Biomedical Research and Study Centre" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", - "category": "occupational and environmental health" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2021.04.01.21254743", @@ -826225,45 +825685,25 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.04.01.21254484", - "rel_title": "A Rapid SARS-CoV-2 Variant Detection by Molecular-Clamping Based RT-qPCR", + "rel_doi": "10.1101/2021.04.01.21254182", + "rel_title": "Rapid, Affordable and Scalable SARS-CoV-2 Detection from Saliva", "rel_date": "2021-04-05", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.01.21254484", - "rel_abs": "We applied XNA-based Molecular Clamping Technology to develop a multiplex qPCR assay for rapid and accurate detection of SARS-CoV-2 mutations. A total of 278 previously tested SARS-COV-2 positive samples originating primarily from San Francisco Bay Area were tested, including 139 Samples collected in middle January and 139 samples collected at the end of February 2021, respectively. The SARS-CoV-2 Spike-gene D614G mutation was detected from 58 samples (41.7%) collected in January 2021 and, 78 samples (56.1%) collected in February. Notably, while there were no N501Y mutation detected in samples from January, seven of the February samples were tested positive for the N501Y and D614G mutations. The results suggest a relatively recent and speedy spreading of the UK variant (B.1.1.7) in Northern California. This new Molecular Clamping technology-based multiplex RT-qPCR assay is highly sensitive and specific and can help speed up large scale testing for SARS-CoV-2 variants.", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.01.21254182", + "rel_abs": "Here we present an inexpensive, rapid, and robust RT-LAMP based SARS-CoV-2 detection method that is easily scalable, enabling point of care facilities and clinical labs to determine results from patients saliva directly in 30 minutes for less than $2 a sample. The method utilizes a novel combination of widely available reagents that can be prepared in bulk, plated and frozen and remain stable until samples are received. This innovation dramatically reduces preparation time, enabling high-throughput automation and testing with time to results (including setup) in less than one hour for 96 patient samples simultaneously when using a 384 well format. By utilizing a dual-reporter (phenol red pH indicator for end-point detection and SYTO-9 fluorescent dye for real-time), the assay also provides internal validation of results and redundancy in the event of an instrument malfunction.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Shuo Shen", - "author_inst": "Diacarta Inc" - }, - { - "author_name": "Andrew Y Fu", - "author_inst": "Diacarta Inc" - }, - { - "author_name": "Maidar Jamba", - "author_inst": "Diacarta Inc" - }, - { - "author_name": "Jonathan Li", - "author_inst": "Diacarta Inc" - }, - { - "author_name": "Mike J Powell", - "author_inst": "Diacarta Inc" - }, - { - "author_name": "Aiguo Zhang", - "author_inst": "Diacarta Inc" + "author_name": "Andrew Hayden", + "author_inst": "University at Albany" }, { - "author_name": "Chuanyi M Lu", - "author_inst": "University of California and VA Healthcare System, San Francisco, CA 94121" + "author_name": "Marcy Kuentzel", + "author_inst": "University at Albany" }, { - "author_name": "Michael Y Sha", - "author_inst": "Diacarta Inc" + "author_name": "Sridar V Chittur", + "author_inst": "University at Albany" } ], "version": "1", @@ -828143,53 +827583,113 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.03.30.21254653", - "rel_title": "Differences in risk for SARS-CoV-2 infection among healthcare workers", + "rel_doi": "10.1101/2021.03.30.21254591", + "rel_title": "Genomic monitoring unveil the early detection of the SARS-CoV-2 B.1.351 lineage (20H/501Y.V2) in Brazil", "rel_date": "2021-04-04", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.30.21254653", - "rel_abs": "Healthcare workers (HCWs) are a risk group for SARS-CoV-2 infection, but which healthcare work that conveys risk and to what extent such risk can be prevented is not clear. Starting on April 24th, 2020, all employees at work (n=15,300) at the Karolinska University Hospital, Stockholm, Sweden were invited and 92% consented to participate in a SARS-CoV-2 cohort study. Complete SARS-CoV-2 serology was available for n=12,928 employees and seroprevalences were analyzed by age, sex, profession, patient contact, and hospital department. Relative risks were estimated to examine the association between type of hospital department as a proxy for different working environment exposure and risk for seropositivity, adjusting for age, sex, sampling week, and profession. Wards that were primarily responsible for COVID-19 patients were at increased risk (adjusted OR 1.95 (95% CI 1.65-2.32) with the notable exception of the infectious diseases and intensive care units (adjusted OR 0.86 (95% CI 0.66-1.13)), that were not at increased risk despite being highly exposed. Several units with similar types of work varied greatly in seroprevalences. Among the professions examined, nurse assistants had the highest risk (adjusted OR 1.62 (95% CI 1.38-1.90)). Although healthcare workers, in particular nurse assistants, who attend to COVID-19 patients are a risk group for SARS-CoV-2 infection, several units caring for COVID-19 patients had no excess risk. Large variations in seroprevalences among similar units suggest that healthcare work-related risk of SARS-CoV-2 infection may be preventable.", - "rel_num_authors": 10, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.30.21254591", + "rel_abs": "Sao Paulo State, the most populous area in Brazil, currently experiences a second wave of the COVID-19 pandemic which overwhelmed the healthcare system. Recently, due to the paucity of SARS-CoV-2 complete genome sequences, we established a Network for Pandemic Alert of Emerging SARS-CoV-2 Variants to rapidly understand the spread of SARS-CoV-2 and monitor in nearly real-time the circulating SARS-CoV-2 variants into the state. Through full genome analysis of 217 SARS-CoV-2 complete genome sequences obtained from the largest regional health departments we were able to identify the co-circulation of multiple SARS-CoV-2 lineages such as i) B.1.1 (0.92%), ii) B.1.1.1 (0.46%), iii) B.1.1.28 (25.34%), iv) B.1.1.7 (5.99%), v) B.1.566 (1.84%), vi) P.1 (64.05%), and P.2 (0.92%). Further our analysis allowed the detection, for the first time in Brazil of the South African variant of concern (VOC), the B.1.351 (501Y.V2) (0.46%). The identified lineage was characterized by the presence of the following mutations: ORF1ab: T265I, R724K, S1612L, K1655N, K3353R, SGF 3675_F3677del, P4715L, E5585D; Spike: D80A, D215G, L242_L244del, A262D, K417N, E484K, N501Y, D614G, A701V, C1247F; ORF3a: Q57H, S171L, E: P71L; ORF7b: Y10F, N: T205I; ORF14: L52F. Origin of the most recent common ancestor of this genomic variant was inferred to be between middle October to late December 2020. Analysis of generated sequences demonstrated the predominance of the P.1 lineage and allowed the early detection of the South African strain for the first time in Brazil. Our findings highlight the importance to increase active monitoring to ensure the rapid detection of new SARS-CoV-2 variants with a potential impact in pandemic control and vaccination strategies.", + "rel_num_authors": 25, "rel_authors": [ { - "author_name": "K. Miriam Elfstrom", - "author_inst": "Karolinska University Laboratory" + "author_name": "Svetoslav N Slavov PhD", + "author_inst": "Blood Center of Ribeirao Preto" }, { - "author_name": "Jonas Blomqvist", - "author_inst": "Karolinska University Hospital" + "author_name": "Jose Patane PhD", + "author_inst": "Butantan Institute" }, { - "author_name": "Peter Nilsson", - "author_inst": "SciLifeLab" + "author_name": "Rafael S Bezerra BSc", + "author_inst": "Blood Center of Ribeirao Preto" }, { - "author_name": "Sofia Hober", - "author_inst": "KTH Royal Institute of Technology" + "author_name": "Marta Giovanetti PhD", + "author_inst": "Instituto Oswaldo Cruz" }, { - "author_name": "Elisa Pin", - "author_inst": "SciLifeLab" + "author_name": "Vagner Fonseca MSc", + "author_inst": "Universidade Federal de Minas Gerais" }, { - "author_name": "Anna Manberg", - "author_inst": "SciLifeLab" + "author_name": "Antonio J Martins PhD", + "author_inst": "Butantan Institute" }, { - "author_name": "Ville Pimenoff", - "author_inst": "Karolinska Institutet" + "author_name": "Vincent L Viala PhD", + "author_inst": "Butantan Institute" }, { - "author_name": "Laila Sara Arroyo Muhr", - "author_inst": "Karolinska Institutet" + "author_name": "Evandra S Rodrigues PhD", + "author_inst": "Blood Center of Ribeirao Preto" }, { - "author_name": "Kalle Conneryd-Lundgren", - "author_inst": "Karolinska University Hospital" + "author_name": "Elaine V Santos PhD", + "author_inst": "Blood Center of Ribeirao Preto" }, { - "author_name": "Joakim Dillner", - "author_inst": "Karolinska University Hospital" + "author_name": "Claudia R.S Barros PhD", + "author_inst": "Butantan Institute" + }, + { + "author_name": "Elaine C Marqueze PhD", + "author_inst": "Butantan Institute" + }, + { + "author_name": "Bibiana Santos MSc", + "author_inst": "Mendelics" + }, + { + "author_name": "Flavia Aburjaile PhD", + "author_inst": "Universidade Federal de Minas Gerais" + }, + { + "author_name": "Raul M Neto PhD", + "author_inst": "Butantan Institute" + }, + { + "author_name": "Debora B Moretti PhD", + "author_inst": "Butantan Institute" + }, + { + "author_name": "Ricardo Haddad MSc", + "author_inst": "Butantan Institute" + }, + { + "author_name": "Rodrigo T Calado PhD", + "author_inst": "Blood Center of Ribeirao Preto" + }, + { + "author_name": "Joao Paulo Kitajima PhD", + "author_inst": "Mendelics" + }, + { + "author_name": "Erika Freitas PhD", + "author_inst": "Mendelics" + }, + { + "author_name": "David Schlesinger PhD", + "author_inst": "Mendelics" + }, + { + "author_name": "Luiz C.J Alcantara PhD", + "author_inst": "Instituto Oswaldo Cruz" + }, + { + "author_name": "M. Carolina Elias PhD", + "author_inst": "Butantan Institute" + }, + { + "author_name": "Sandra C.S Vessoni PhD", + "author_inst": "Butantan Institute" + }, + { + "author_name": "Simone Kashima PhD", + "author_inst": "Blood Center of Ribeirao Preto" + }, + { + "author_name": "Dimas T Covas Md-PhD", + "author_inst": "Butantan Institute" } ], "version": "1", @@ -830189,81 +829689,61 @@ "category": "biophysics" }, { - "rel_doi": "10.1101/2021.03.28.21254507", - "rel_title": "Efficacy and safety of convalescent plasma and intravenous immunoglobulin in critically ill COVID-19 patients. A controlled clinical trial.", + "rel_doi": "10.1101/2021.03.29.21254534", + "rel_title": "Characterization of antibody response in asymptomatic and symptomatic SARS-CoV-2 infection", "rel_date": "2021-03-31", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.28.21254507", - "rel_abs": "BackgroundThe proportion of critically ill COVID-19 patients has collapsed hospital care worldwide. The need for alternative therapies for this group of patients is imperative. This study aims to compare the safety and efficacy of convalescent plasma (CP) compared with human immunoglobulin (IVIg) in patients requiring the administration of high oxygen levels or mechanical ventilation.\n\nMethodsThis is a controlled, randomized, open clinical trial of patients with pneumonia secondary to SARS-CoV-2 infection, that fulfilled criteria for severe or critical disease. They were randomized in a 1:2 ratio; group 1 was administered IVIg at a dose of 0.3 grams per kilogram of ideal weight, in an 8-hour infusion every 24 hours, for 5 days. Group 2 was administered 200 ml of CP infused in 2 hours, for 2 days. The primary outcomes were duration of hospitalization and mortality at 28 days.\n\nResultsOne hundred and ninety (190) patients were randomized; 130 to the CP group, and 60 to the IVIg group. Their average age was 58 years (IQR 47 - 72), and most were male (n= 119, 62.6 %). On inclusion, 85.2 % of patients (n=162) were on invasive mechanical ventilation therapy. Overall mortality in all included patients was 53 % (n= 102), with a median follow-up of 14 days (IQI 8 - 26). Mortality at 28 days was 45.2 % (n=86). In the intention-to-treat analysis, there was no difference between groups neither in mortality on follow-up (53.8 vs. 53.3, p =1.0) nor at 28 days (46.2 vs 43 %, p=0.75, Log Rank p = 0.83). Per-protocol analysis between treatment groups revealed no difference in mortality throughout hospitalization (51.5 vs 51.4 %, p=1.0) nor after 28 days (42.1 vs 42.87 %, p=0.92 Log Rank p = 0.54). Only 23 patients in the CP group received plasma with detectable anti-SARS-CoV-2 antibodies.\n\nConclusionsIn critically ill patients or on invasive mechanical ventilation for treatment of Covid-19, the use of CP is not superior to IVIg in terms of hospitalization duration or mortality. The use of CP is based on complex logistics and requires an assured level of antibodies if used therapeutically. IVIg does not appear to be useful in this group of patients.\n\nclinicaltrials.gov identifier: NCT04381858.", - "rel_num_authors": 17, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.29.21254534", + "rel_abs": "SARS-CoV-2 pandemic is causing high morbidity and mortality burden worldwide with unprecedented strain on health care systems.\n\nTo elucidate the mechanism of infection, protection, or rapid evolution until fatal outcome of the disease we performed a study in hospitalized COVID-19 patients to investigate the time course of the antibody response in relation to the outcome. In comparison we investigated the time course of the antibody response in SARS-CoV-2 asymptomatic subjects.\n\nStudy results show that patients produce a strong antibody response to SARS-CoV-2 with high correlation between different viral antigens (spike protein and nucleoprotein) and among antibody classes (IgA, IgG, and IgM and neutralizing antibodies). The peak is reached by 3 weeks from hospital admission followed by a sharp decrease. No difference was observed in any parameter of the antibody classes, including neutralizing antibodies, between subjects who recovered or with fatal outcome. Only few asymptomatic subjects developed antibodies at detectable levels.", + "rel_num_authors": 12, "rel_authors": [ { - "author_name": "Jose Lenin Beltran Gonzalez", - "author_inst": "Centenario Hospital Miguel Hidalgo" - }, - { - "author_name": "Mario Gonzalez Gamez", - "author_inst": "Centenario Hospital Miguel Hidalgo" - }, - { - "author_name": "Emmanuel Antonio Mendoza Enciso", - "author_inst": "Centenario Hospital Miguel Hidalgo" - }, - { - "author_name": "Ramiro Josue Esparza Maldonado", - "author_inst": "Centenario Hospital Miguel Hidalgo" - }, - { - "author_name": "Daniel Hernandez Palacios", - "author_inst": "Centenario Hospital Miguel Hidalgo" - }, - { - "author_name": "Samuel Duenas Campos", - "author_inst": "Centenario Hospital Miguel Hidalgo" + "author_name": "Serena Marchi", + "author_inst": "University of Siena" }, { - "author_name": "Itzel Ovalle Robles", - "author_inst": "Centenario Hospital Miguel Hidalgo" + "author_name": "Viviani Simonetta", + "author_inst": "University of Siena" }, { - "author_name": "Mariana Jocelyn Macias Guzman", - "author_inst": "Centenario Hospital Miguel Hidalgo" + "author_name": "Edmond Remarque", + "author_inst": "Biomedical Primate Research Centre" }, { - "author_name": "Andrea Lucia Garcia Diaz", - "author_inst": "Centenario Hospital Miguel Hidalgo" + "author_name": "Antonella Ruello", + "author_inst": "Humanitas Gavazzeni" }, { - "author_name": "Cesar Mauricio Gutierrez Pena", - "author_inst": "Centenario Hospital Miguel Hidalgo" + "author_name": "Emilio Bombardieri", + "author_inst": "Humanitas Gavazzeni" }, { - "author_name": "Ana Lilia Reza Escalera", - "author_inst": "Centenario Hospital Miguel Hidalgo" + "author_name": "Valentina Bollati", + "author_inst": "University of Milan" }, { - "author_name": "Maria Teresa Tiscareno Gutierrez", - "author_inst": "Centenario Hospital Miguel Hidalgo" + "author_name": "Gregorio Milani", + "author_inst": "University of Milan" }, { - "author_name": "Elba Galvan Guerra", - "author_inst": "Laboratorio Clinico del Campestre" + "author_name": "Alessandro Manenti", + "author_inst": "VisMederi srl" }, { - "author_name": "Maria del Rocio Dorantes Morales", - "author_inst": "Aguascalientes State Transfusion Center" + "author_name": "Giulia Lapini", + "author_inst": "VisMederi srl" }, { - "author_name": "Lucila Martinez Medina", - "author_inst": "Centenario Hospital Miguel Hidalgo" + "author_name": "Annunziata Rebuffat", + "author_inst": "Presidio Ospedaliero di Campostaggia" }, { - "author_name": "Victor Antonio Monroy Colin", - "author_inst": "Centenario Hospital Miguel Hidalgo" + "author_name": "Emanuele Montomoli", + "author_inst": "University of Siena" }, { - "author_name": "Jose Manuel Arreola Guerra", - "author_inst": "Centenario Hospital Miguel Hidalgo" + "author_name": "Claudia Trombetta", + "author_inst": "University of Siena" } ], "version": "1", @@ -831767,71 +831247,39 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.03.29.21254560", - "rel_title": "Innate immune deficiencies in patients with COVID-19", + "rel_doi": "10.1101/2021.03.28.21254520", + "rel_title": "Returning to the workplace during the COVID-19 pandemic: The concerns of Australian workers", "rel_date": "2021-03-31", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.29.21254560", - "rel_abs": "COVID-19 can cause acute respiratory distress syndrome (ARDS), leading to death in a significant number of individuals. Evidence of a strong role of the innate immune system is accumulating, but the precise cells and mechanism involved remain unclear. In this study, we investigated the links between circulating innate phagocyte phenotype and functions and severity in COVID-19 patients. Eighty-four consecutive patients were included, 44 of which were in intensive care units (ICU). We performed an in-depth phenotyping of neutrophil and monocyte subpopulations and measured soluble activation markers in plasma. Additionally, myeloid cell functions (phagocytosis, oxidative burst, and NETosis) were evaluated on fresh cells from patients. Resulting parameters were linked to disease severity and prognosis. Both ICU and non-ICU patients had circulating neutrophils and monocytes with an activated phenotype, as well as elevated concentrations of soluble activation markers (calprotectin, myeloperoxidase, neutrophil extracellular traps, MMP9, sCD14) in their plasma. ICU patients were characterized by increased CD10low CD13low immature neutrophils, LOX-1+ and CCR5+ immunosuppressive neutrophils, and HLA-DRlow CD14low downregulated monocytes. Markers of immature and immunosuppressive neutrophils were strongly associated with severity and poor outcome. Moreover, neutrophils and monocytes of ICU patients had impaired antimicrobial functions, which correlated with organ dysfunction, severe infections, and mortality. Our study reveals a marked dysregulation of innate immunity in COVID-19 patients, which was correlated with severity and prognosis. Together, our results strongly argue in favor of a pivotal role of innate immunity in COVID-19 severe infections and pleads for targeted therapeutic options.\n\nOne Sentence SummaryOur study reveals a marked dysregulation of innate immunity in COVID-19 patients, which correlates with severity and prognosis.", - "rel_num_authors": 13, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.28.21254520", + "rel_abs": "PurposeTo determine the nature and prevalence of workers concerns regarding workplaces reopening during the pandemic. To identify characteristics of workers and industries where particular concerns are more common.\n\nMethodsProspective cohort study of 1063 employed Australian adults, enrolled at the start of the pandemic. Data on attitudes to workplaces reopening were collected 1 July - 30 September 2020. The frequency of concerns describes infection risk and changes to work and impact on home life. Regression models examined associations between demographic and industry factors with reopening concerns.\n\nResultsMore than four in five (82.4%) of workers reported concerns about workplace infection risk. Just over half (53.4%) reported concerns about impacts to work and home life. Concerns were more prevalent for workers reporting psychological distress, financial stress, and among those exclusively working from home. Concerns regarding infection risk were common for workers in health care (IRR=1.16, 95% CI=[1.01, 1.33]), retail (IRR=1.31, 95% CI=[1.06, 1.61]), and accommodation/food service industries (IRR=1.25, 95% CI=[1.01, 1.55]). Concerns regarding changes to work and home life were more common for female workers (IRR=1.24, 95% CI=[1.07, 1.43]), and partners/spouses with dependent children (IRR=1.44, 95% CI=[1.16, 1.79]).\n\nConclusionConcerns of COVID-19 infection in the workplace are common. Many workers are also concerned about changes to their work and home life. The prevalence of concerns is related to the nature of work and responsibilities at home. Actions that reduce risk of workplace transmission, coupled with effective communication of infection controls, may alleviate worker concerns whilst recognising workers family and social circumstances.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Marine Peyneau", - "author_inst": "AP-HP, Bichat Hospital, Autoimmunity and Hypersensitivity Laboratory; Paris, France" - }, - { - "author_name": "Vanessa Granger", - "author_inst": "AP-HP, Bichat Hospital, Autoimmunity and Hypersensitivity Laboratory; Paris, France" - }, - { - "author_name": "Paul-Henri Wicky", - "author_inst": "AP-HP, Bichat hospital Medial and infectious diseases ICU (MI2); Paris France" - }, - { - "author_name": "Dounia Khelifi-Touhami", - "author_inst": "AP-HP, Bichat Hospital, Autoimmunity and Hypersensitivity Laboratory; Paris, France" - }, - { - "author_name": "Jean-Francois Timsit", - "author_inst": "AP-HP, Bichat hospital Medial and infectious diseases ICU (MI2); Paris France" - }, - { - "author_name": "Francois-Xavier Lescure", - "author_inst": "AP-HP, Hopital Bichat, Infectious Diseases Department ; Paris, France" - }, - { - "author_name": "Yazdan Yazdanpanah", - "author_inst": "AP-HP, Hopital Bichat, Infectious Diseases Department ; Paris, France" - }, - { - "author_name": "Alexy Tran-Dihn", - "author_inst": "AP-HP, Bichat Hospital, Departement Anesthesie-Reanimation, DMU PARABOL, Universite de Paris; Paris France" - }, - { - "author_name": "Philippe Montravers", - "author_inst": "AP-HP, Bichat Hospital, Departement Anesthesie-Reanimation, DMU PARABOL, Universite de Paris; Paris France" + "author_name": "Daniel Griffiths", + "author_inst": "Monash University" }, { - "author_name": "Renato Monteiro", - "author_inst": "APHP, Bichat Hospital, Immunological Dysfunction Laboratory, Paris, France" + "author_name": "Luke Sheehan", + "author_inst": "Monash University" }, { - "author_name": "Sylvie Chollet-Martin", - "author_inst": "AP-HP, Bichat Hospital, Autoimmunity and Hypersensitivity Laboratory; Paris, France" + "author_name": "Caryn van Vreden", + "author_inst": "Monash University" }, { - "author_name": "Margarita Hurtado-Nedelec", - "author_inst": "APHP, Bichat Hospital, Immunological Dysfunction Laboratory, Paris, France" + "author_name": "Peter Whiteford", + "author_inst": "Australian National University" }, { - "author_name": "Luc de Chaisemartin", - "author_inst": "AP-HP, Bichat Hospital, Autoimmunity and Hypersensitivity Laboratory; Paris, France" + "author_name": "Alex Collie", + "author_inst": "Monash University" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "allergy and immunology" + "category": "occupational and environmental health" }, { "rel_doi": "10.1101/2021.03.29.21254211", @@ -833593,99 +833041,63 @@ "category": "biochemistry" }, { - "rel_doi": "10.1101/2021.03.30.437173", - "rel_title": "Severity of SARS-CoV-2 infection as a function of the interferon landscape across the respiratory tract of COVID-19 patients.", - "rel_date": "2021-03-30", + "rel_doi": "10.1101/2021.03.29.437480", + "rel_title": "COVID-19 and the abrupt shift to remote learning: Impact on grades and perceived learning for undergraduate biology students", + "rel_date": "2021-03-29", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.03.30.437173", - "rel_abs": "The COVID-19 outbreak driven by SARS-CoV-2 has caused more than 2.5 million deaths globally, with the most severe cases characterized by over-exuberant production of immune-mediators, the nature of which is not fully understood. Interferons of the type I (IFN-I) or type III (IFN-III) families are potent antivirals, but their role in COVID-19 remains debated. Our analysis of gene and protein expression along the respiratory tract shows that IFNs, especially IFN-III, are over-represented in the lower airways of patients with severe COVID-19, while high levels of IFN-III, and to a lesser extent IFN-I, characterize the upper airways of patients with high viral burden but reduced disease risk or severity; also, IFN expression varies with abundance of the cell types that produce them. Our data point to a dynamic process of inter- and intra-family production of IFNs in COVID-19, and suggest that IFNs play opposing roles at distinct anatomical sites.", - "rel_num_authors": 20, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.03.29.437480", + "rel_abs": "Institutions across the world transitioned abruptly to remote learning in 2020 due to the COVID-19 pandemic. This rapid transition to remote learning has generally been predicted to negatively affect students, particularly those marginalized due to their race, socioeconomic class, or gender identity. In this study, we examined the impact of this transition in the Spring 2020 semester on the grades of students enrolled in the in-person biology program at a large university in Southwestern United States as compared to the grades earned by students in the fully online biology program at the same institution. We also surveyed in-person instructors to understand changes in assessment practices as a result of the transition to remote learning during the pandemic. Finally, we surveyed students in the in-person program to learn about their perceptions of the impacts of this transition. We found that both online and in-person students received a similar small increase in grades in Spring 2020 compared to Spring 2018 and 2019. We also found no evidence of disproportionately negative impacts on grades received by students marginalized due to their race, socioeconomic class, or gender in either modality. Focusing on in-person courses, we documented that instructors made changes to their courses when they transitioned to remote learning, which may have offset some of the potential negative impacts on course grades. However, despite receiving higher grades, in-person students reported negative impacts on their learning, interactions with peers and instructors, feeling part of the campus community, and career preparation. Women reported a more negative impact on their learning and career preparation compared to men. This work provides insights into students perceptions of how they were disadvantaged as a result of the transition to remote instruction and illuminates potential actions that instructors can take to create more inclusive education moving forward.", + "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Achille Broggi", - "author_inst": "Harvard Medical School" - }, - { - "author_name": "Laura Pandolfi", - "author_inst": "Fondazione IRCCS Policlinico San Matteo" - }, - { - "author_name": "Stefania Crotta", - "author_inst": "Francis Crick Institute" - }, - { - "author_name": "Roberto Ferrarese", - "author_inst": "San Raffaele Hospital" - }, - { - "author_name": "Sofia Sisti", - "author_inst": "San Raffaele Hospital" - }, - { - "author_name": "Nicola Clementi", - "author_inst": "Vita-Salute San Raffaele University" - }, - { - "author_name": "Alessandro Ambrosi", - "author_inst": "San Raffaele Hospital" - }, - { - "author_name": "Vanessa Frangipane", - "author_inst": "Fondazione IRCCS Policlinico San Matteo" - }, - { - "author_name": "Laura Saracino", - "author_inst": "Fondazione IRCCS Policlinico San Matteo" - }, - { - "author_name": "Laura Marongiu", - "author_inst": "university of Milano-Bicocca" + "author_name": "K Supriya", + "author_inst": "Arizona State University" }, { - "author_name": "Fabio Facchini", - "author_inst": "University of Milano-Bicocca" + "author_name": "Chris Mead", + "author_inst": "Arizona State University" }, { - "author_name": "Andrea Bottazzi", - "author_inst": "Fondazione IRCCS Policlinico San Matteo" + "author_name": "Ariel D. Anbar", + "author_inst": "Arizona State University" }, { - "author_name": "Tomaso Fossali", - "author_inst": "Sacco Hospital" + "author_name": "Joshua L. Caulkins", + "author_inst": "Arizona State University" }, { - "author_name": "Riccardo Colombo", - "author_inst": "Sacco Hospital" + "author_name": "James P. Collins", + "author_inst": "Arizona State University" }, { - "author_name": "Massimo Clementi", - "author_inst": "Vita-Salute San Raffaele University" + "author_name": "Katelyn M. Cooper", + "author_inst": "Arizona State University" }, { - "author_name": "Elena Tagliabue", - "author_inst": "Multimedica" + "author_name": "Paul C. LePore", + "author_inst": "Arizona State University" }, { - "author_name": "Antonio Pontiroli", - "author_inst": "University of Milano" + "author_name": "Tiffany Lewis", + "author_inst": "Arizona State University" }, { - "author_name": "Federica Meloni", - "author_inst": "Fondazione IRCCS Policlinico San Matteo" + "author_name": "Amy Pate", + "author_inst": "Arizona State University" }, { - "author_name": "Andreas Wack", - "author_inst": "Francis Crick Institute" + "author_name": "Rachel A. Scott", + "author_inst": "Arizona State University" }, { - "author_name": "Nicasio Mancini", - "author_inst": "University Vita-Salute San Raffaele" + "author_name": "Sara E. Brownell", + "author_inst": "Arizona State University" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "new results", - "category": "immunology" + "category": "scientific communication and education" }, { "rel_doi": "10.1101/2021.03.24.21254279", @@ -835451,43 +834863,35 @@ "category": "bioinformatics" }, { - "rel_doi": "10.1101/2021.03.26.21254369", - "rel_title": "Using Google Health Trends to investigate COVID19 incidence in Africa", + "rel_doi": "10.1101/2021.03.29.437540", + "rel_title": "SARS-CoV-2, a threat to marine mammals? A study from Italian seawaters", "rel_date": "2021-03-29", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.26.21254369", - "rel_abs": "The COVID-19 pandemic has caused over 350 million cases and over five million deaths globally. From these numbers, over 10 million cases and over 200 thousand deaths have occurred on the African continent as of 22 January 2022. Prevention and surveillance remain the cornerstone of interventions to halt the further spread of COVID-19. Google Health Trends (GHT), a free Internet tool, may be valuable to help anticipate outbreaks, identify disease hotspots, or understand the patterns of disease surveillance.\n\nWe collected COVID-19 case and death incidence for 54 African countries and obtained averages for four, five-month study periods in 2020-2021. Average case and death incidences were calculated during these four time periods to measure disease severity. We used GHT to characterize COVID-19 incidence across Africa, collecting numbers of searches from GHT related to COVID-19 using four terms: coronavirus, coronavirus symptoms, COVID19, and pandemic. The terms were related to weekly COVID-19 case incidences for the entire study period via multiple linear regression analysis and weighted linear regression analysis. We also assembled 72 predictors assessing Internet accessibility, demographics, economics, health, and others, for each country, to summarize potential mechanisms linking GHT searches and COVID-19 incidence.\n\nCOVID-19 burden in Africa increased steadily during the study period as in the rest of the world. Important increases for COVID-19 death incidence were observed for Seychelles and Tunisia over the study period. Our study demonstrated a weak correlation between GHT and COVID-19 incidence for most African countries. Several predictors were useful in explaining the pattern of GHT statistics and their relationship to COVID-19 including: log of average weekly cases, log of cumulative total deaths, and log of fixed total number of broadband subscriptions in a country. Apparently, GHT may best be used for surveillance of diseases that are diagnosed more consistently.\n\nGHT-based surveillance for an ongoing epidemic might be useful in specific situations, such as when countries have significant levels of infection with low variability. Overall, GHT-based surveillance showed little applicability in the studied countries. Future studies might assess the algorithm in different epidemic contexts.", - "rel_num_authors": 6, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2021.03.29.437540", + "rel_abs": "Zoonotically transmitted coronaviruses were responsible for three disease outbreaks since 2002, with the \"Severe Acute Respiratory Syndrome Coronavirus-2\" (SARS-CoV-2) causing the dramatic \"Coronavirus Disease-2019\" (CoViD-19) pandemic, which affected public health, economy, and society on a global scale. The impacts of the SARS-CoV-2 pandemic permeate into our environment and wildlife as well; in particular, concern has been raised about the viral occurrence and persistence in aquatic and marine ecosystems. The discharge of untreated wastewaters carrying infectious SARS-CoV-2 into natural water systems that are home of sea mammals may have dramatic consequences on vulnerable species.\n\nThe efficient transmission of coronaviruses raise questions regarding the contributions of virus-receptors interactions. The main receptor of SARS-CoV-2 is Angiotensin Converting Enzyme-2 (ACE-2), serving as a functional receptor for the viral spike (S) protein. This study was aimed, through the comparative analysis of the ACE-2 receptor with the human one, at assessing the susceptibility to SARS-CoV-2 of the different species of marine mammals living in Italian waters. We also determined, by means of immunohistochemistry, ACE-2 receptor localization in the lung tissue from different cetacean species, in order to provide a preliminary characterization of ACE-.2 expression in the marine mammals respiratory tract.\n\nFurthermore, in order to evaluate if and how wastewater management in Italy may lead to susceptible marine mammal populations being exposed to the virus, geo-mapping data of wastewater plants, associated to the identification of specific stretches of coast more exposed to extreme weather events, overlapped to marine mammal population data, were carried out. Results showed the SARS-CoV-2 exposure for marine mammals inhabiting Italian coastal waters. Thus, we highlight the potential hazard of reverse zoonotic transmission of SARS-CoV-2 infection, along with its impact on marine mammals regularly inhabiting the Mediterranean Sea, whilst also stressing the need of appropriate action to prevent further damage to specific vulnerable populations.\n\nSignificance StatementGrowing concern exists that SARS-CoV-2, as already ascertained for its SARS-CoV and MERS-CoV \"predecessors\", originated from an animal \"reservoir\", performing thereafter its spillover into mankind, that was possibly anticipated by viral \"passage\" into a secondary animal host. Within the dramatic SARS-CoV-2 pandemic context, hitherto characterized by over 110 million cases and almost 2,500,000 deaths on a global scale, several domestic and wild animal species have been reported as susceptible to natural and/or experimental SARS-CoV-2 infection. In this respect, while some marine mammal species are deemed as potentially susceptible to SARS-CoV-2 infection on the basis of the sequence homology of their ACE-2 viral receptor with the human one, this study addresses such a critical issue also in stranded sea mammal specimens.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Alex Fulk", - "author_inst": "University of Kansas" - }, - { - "author_name": "Daniel Romero-Alvarez", - "author_inst": "University of Kansas" - }, - { - "author_name": "Qays Abu Saymeh", - "author_inst": "University of Kansas" + "author_name": "Cinzia Centelleghe", + "author_inst": "Department of Comparative Biomedicine and Food Science, University of Padua, Padua, Italy" }, { - "author_name": "Jarron Saint Onge", - "author_inst": "University of Kansas" + "author_name": "Sandro Mazzariol", + "author_inst": "Department of Comparative Biomedicine and Food Science, University of Padua, Padua, Italy" }, { - "author_name": "A. Townsend Peterson", - "author_inst": "University of Kansas" + "author_name": "Giovanni Di Guardo", + "author_inst": "Faculty of Veterinary Medicine, University of Teramo, Italy" }, { - "author_name": "Folashade B Agusto", - "author_inst": "University of Kansas" + "author_name": "Giancarlo Lauriano", + "author_inst": "Italian National Institute for Environmental Protection and Research (ISPRA)" } ], "version": "1", "license": "cc_no", - "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "type": "new results", + "category": "pathology" }, { "rel_doi": "10.1101/2021.03.26.21254331", @@ -837189,61 +836593,77 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2021.03.20.21254022", - "rel_title": "Supporting COVID-19 policy response with large-scale mobility-based modeling", + "rel_doi": "10.1101/2021.03.18.21253604", + "rel_title": "A rapid assessment of wastewater for genomic surveillance of SARS-CoV-2 variants at sewershed scale in Louisville, KY", "rel_date": "2021-03-26", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.20.21254022", - "rel_abs": "Social distancing measures, such as restricting occupancy at venues, have been a primary intervention for controlling the spread of COVID-19. However, these mobility restrictions place a significant economic burden on individuals and businesses. To balance these competing demands, policymakers need analytical tools to assess the costs and benefits of different mobility reduction measures.In this paper, we present our work motivated by our interactions with the Virginia Department of Health on a decision-support tool that utilizes large-scale data and epidemiological modeling to quantify the impact of changes in mobility on infection rates. Our model captures the spread of COVID-19 by using a fine-grained, dynamic mobility network that encodes the hourly movements of people from neighborhoods to individual places, with over 3 billion hourly edges. By perturbing the mobility network, we can simulate a wide variety of reopening plans and forecast their impact in terms of new infections and the loss in visits per sector. To deploy this model in practice, we built a robust computational infrastructure to support running millions of model realizations, and we worked with policymakers to develop an intuitive dashboard interface that communicates our models predictions for thousands of potential policies, tailored to their jurisdiction. The resulting decision-support environment provides policymakers with much-needed analytical machinery to assess the tradeoffs between future infections and mobility restrictions.", - "rel_num_authors": 12, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.18.21253604", + "rel_abs": "In this communication, we report on the genomic surveillance of SARS-CoV-2 using wastewater samples in Jefferson County, KY. In February 2021, we analyzed seven wastewater samples for SARS-CoV-2 genomic surveillance. Variants observed in smaller catchment areas, such as neighborhood manhole locations, were not necessarily consistent when compared to associated variant results in downstream treatment plants, suggesting catchment size or population could impact the ability to detect diversity.", + "rel_num_authors": 16, "rel_authors": [ { - "author_name": "Serina Y Chang", - "author_inst": "Stanford University" + "author_name": "Joshua Fuqua", + "author_inst": "University of Louisville" }, { - "author_name": "Mandy L Wilson", - "author_inst": "Biocomplexity Institute & Initiative, University of Virginia" + "author_name": "Eric Rouchka", + "author_inst": "University of Louisville" }, { - "author_name": "Bryan Lewis", - "author_inst": "Biocomplexity Institute & Initiative, University of Virginia" + "author_name": "Sabine Waigel", + "author_inst": "University of Louisville" }, { - "author_name": "Zakaria Mehrab", - "author_inst": "Biocomplexity Institute & Initiative, University of Virginia" + "author_name": "Kevin Sokoloski", + "author_inst": "University of Louisville" }, { - "author_name": "Komal K Dudakiya", - "author_inst": "Persistent Systems" + "author_name": "Donghoon Chung", + "author_inst": "University of Louisville" }, { - "author_name": "Emma Pierson", - "author_inst": "Microsoft Research" + "author_name": "Wolfgang Zacharias", + "author_inst": "University of Louisville" }, { - "author_name": "Pang Wei Koh", - "author_inst": "Stanford University" + "author_name": "Mei Zhang", + "author_inst": "University of Louisville" }, { - "author_name": "Jaline Gerardin", - "author_inst": "Northwestern University" + "author_name": "Julia Chariker", + "author_inst": "University of Louisville" }, { - "author_name": "Beth Redbird", - "author_inst": "Northwestern University" + "author_name": "Daymond Talley", + "author_inst": "Louisville/Jefferson County Metropolitan Sewer District, Morris Forman Water Quality Treatment Center" }, { - "author_name": "David Grusky", - "author_inst": "Stanford University" + "author_name": "Ian Santisteban", + "author_inst": "University of Louisville" }, { - "author_name": "Madhav Marathe", - "author_inst": "Biocomplexity Institute & Initiative, University of Virginia" + "author_name": "Arvind Vasrsani", + "author_inst": "Arizona State University" }, { - "author_name": "Jure Leskovec", - "author_inst": "Stanford University" + "author_name": "Sarah Moyer", + "author_inst": "Department of Public Health and Wellness, Louisville Metro Government" + }, + { + "author_name": "Rochelle H Holm", + "author_inst": "University of Louisville" + }, + { + "author_name": "Ray Yeager", + "author_inst": "University of Louisville" + }, + { + "author_name": "Ted R Smith", + "author_inst": "University of Louisville" + }, + { + "author_name": "Aruni Bhatnagar", + "author_inst": "University of Louisville" } ], "version": "1", @@ -839267,59 +838687,39 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2021.03.22.21254121", - "rel_title": "Continuity of routine immunization programs in Canada during the COVID-19 pandemic", + "rel_doi": "10.1101/2021.03.23.21253748", + "rel_title": "Endogenous interferon-beta but not interferon-alpha or interferon-lambda levels in upper respiratory tract predict clinical outcome in critical COVID-19 patients independent of viral load", "rel_date": "2021-03-26", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.22.21254121", - "rel_abs": "IntroductionIn Canada, the COVID-19 pandemic has interrupted many routine health services, placed additional strain on the health care system, and resulted in many Canadians being either unable or unwilling to attend routine immunization appointments. We sought to capture and synthesize information about changes to routine immunization programs in response to the pandemic and plans to catch-up any missed immunizations.\n\nMethodsProvincial/territorial (P/T) public health leaders were interviewed via teleconference between August-October 2020 to collect information on the following topics: how routine immunization delivery was affected during and after initial lockdown periods, plans to catch-up missed doses, and major challenges and achievements in continuing routine immunization programs. Data were coded and categorized according to common responses and descriptive analysis was performed.\n\nResultsInterviews occurred with participants from 11 of 13 P/Ts. School immunization programs were reported to be most negatively affected by the pandemic (n=9). In the early pandemic period, infant, preschool, and maternal/prenatal programs were prioritized, with most P/Ts continuing these services with adaptations for COVID-19. After the initial lockdown period, all routine programs were continuing with adaptations in most P/Ts. Infant, preschool, and school programs were most often targeted for catch-up through measures such as appointment rebooking and making additional clinics and/or providers available. Major challenges included resource limitations (e.g., staff shortages, PPE shortages, limited infrastructure) (n=11), public health restrictions (n=8), and public hesitancy to attend appointments (n=5).\n\nConclusionsCanadian routine immunization programs faced some disruptions due to the COVID-19 pandemic, particularly the school, adult, and older adult programs. Further research is needed to determine the measurable impact of the pandemic on routine vaccine coverage levels.", - "rel_num_authors": 10, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.23.21253748", + "rel_abs": "Although the subject of intensive preclinical and clinical research, controversy on the protective vs. deleterious effect of interferon (IFN) in COVID-19 remains. Some apparently conflicting results are likely due to the intricacy of IFN subtypes (type I: IFN-alpha/beta, type III: IFN-lambda), timing and mode of administration (nebulized/subcutaneous) and clinical groups targeted (asymptomatic/mild, moderate, severe/critical COVID-19). Within the COntAGIouS (COvid-19 Advanced Genetic and Immunologic Sampling) clinical trial, we investigated endogenous type I and type III IFNs in nasal mucosa as possible predictors of clinical outcome in critical patients, as well as their correlation to SARS-CoV-2 viral load, using nCounter technology. We found that endogenous IFN-beta expression in the nasal mucosa predicts clinical outcome, independent of viral replication or Apache II score, and should be considered as a prognostic tool in a precision medicine approach of IFN therapy in COVID-19 clinical management.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Hannah Sell", - "author_inst": "University of Alberta" + "author_name": "Soraya Maria MENEZES", + "author_inst": "KU Leuven, Universtity of Leuven" }, { - "author_name": "Ali Assi", - "author_inst": "University of Alberta" - }, - { - "author_name": "Michelle Driedger", - "author_inst": "University of Manitoba" - }, - { - "author_name": "Eve Dub\u00e9", - "author_inst": "Universit\u00e9 Laval" - }, - { - "author_name": "Arnaud Gagneur", - "author_inst": "Universit\u00e9 de Sherbrooke" - }, - { - "author_name": "Samantha B Meyer", - "author_inst": "University of Waterloo" - }, - { - "author_name": "Joan Robinson", - "author_inst": "University of Alberta" + "author_name": "Marcos Braz", + "author_inst": "KU Leuven" }, { - "author_name": "Manish Sadarangani", - "author_inst": "University of British Columbia" + "author_name": "Veronica Llorens-Rico", + "author_inst": "KU Leuven" }, { - "author_name": "Matthew Tunis", - "author_inst": "Public Health Agency of Canada" + "author_name": "Joost Wauters", + "author_inst": "KU Leuven" }, { - "author_name": "Shannon E MacDonald", - "author_inst": "University of Alberta" + "author_name": "Johan Van Weyenbergh", + "author_inst": "KU Leuven" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "respiratory medicine" }, { "rel_doi": "10.1101/2021.03.23.21254196", @@ -840929,27 +840329,39 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.03.25.21254326", - "rel_title": "Acute and longer-term psychological distress associated with testing positive for COVID-19: longitudinal evidence from a population-based study of US adults", + "rel_doi": "10.1101/2021.03.24.21254094", + "rel_title": "Public Opinion about the UK Government during COVID-19 and Implications for Public Health: A Topic Modelling Analysis of Open-Ended Survey Response Data", "rel_date": "2021-03-26", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.25.21254326", - "rel_abs": "BackgroundThe novel coronavirus (SARS-CoV-2) has produced a considerable public health burden but the impact that contracting the disease has on mental health is unclear. In this observational population-based cohort study, we examined longitudinal changes in psychological distress associated with testing positive for COVID-19.\n\nMethodsParticipants (N = 8,002; Observations = 139,035) were drawn from 23 waves of the Understanding America Study, a nationally representative survey of American adults followed-up every two weeks from April 1 2020 to February 15 2021. Psychological distress was assessed using the standardized total score on the Patient Health Questionnaire-4 (PHQ-4).\n\nResultsOver the course of the study 576 participants reported testing positive for COVID-19. Using regression analysis including individual and time fixed effects we found that psychological distress increased by 0.29 standard deviations (p <.001) during the two-week period when participants first tested positive for COVID-19. Distress levels remained significantly elevated (d = 0.16, p <.01) for a further two weeks, before returning to baseline levels. Coronavirus symptom severity explained changes in distress attributable to COVID-19, whereby distress was more pronounced among those whose symptoms were more severe and were slower to subside.\n\nConclusionsThis study indicates that testing positive for COVID-19 is associated with an initial increase in psychological distress that diminishes quickly as symptoms subside. While COVID-19 may not produce lasting psychological distress among the majority of the general population it remains possible that a minority may suffer longer-term mental health consequences.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.24.21254094", + "rel_abs": "Confidence in the central UK Government has declined since the beginning of the COVID-19 pandemic, and while this may be linked to specific government actions to curb the spread of the virus, understanding is still incomplete. Examining public opinion is important, as research suggests that low confidence in government increases the extent of non-compliance with infection-dampening rules (for instance, social distancing); however, the detailed reasons for this association are still unclear. To understand public opinion on the central UK government during COVID-19, we used structural topic modelling, a text mining technique, to extract themes from over 4000 free-text survey responses, collected between 14 October and 26 November 2020. We identified eleven topics, among which were topics related to perceived government corruption and cronyism, complaints about inconsistency in rules and messaging, lack of clear planning, and lack of openness and transparency. Participants reported that elements of the governments approach had made it difficult to comply with guidelines (e.g., changing rules) or were having impacts on mental wellbeing (e.g., inability to plan for the future). Results suggested that consistent, transparent communication and messaging from the government is critical to improving compliance with measures to contain the virus, as well as protecting mental health during health emergencies.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Michael Daly", - "author_inst": "Maynooth University" + "author_name": "Liam Wright", + "author_inst": "University College London" }, { - "author_name": "Eric Robinson", - "author_inst": "University of Liverpool" + "author_name": "Alexandra Burton", + "author_inst": "University College London" + }, + { + "author_name": "Alison McKinlay", + "author_inst": "University College London" + }, + { + "author_name": "Andrew Steptoe", + "author_inst": "University College London" + }, + { + "author_name": "Daisy Fancourt", + "author_inst": "University College London" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "psychiatry and clinical psychology" + "category": "public and global health" }, { "rel_doi": "10.1101/2021.03.26.21254380", @@ -842519,47 +841931,47 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2021.03.26.21254259", - "rel_title": "Hemodialysis Patients Show a Highly Diminished Antibody Response after COVID-19 mRNA Vaccination Compared to Healthy Controls", + "rel_doi": "10.1101/2021.03.25.21253694", + "rel_title": "From classic to rap: Airborne transmission of different singing styles, with respect to risk assessment of a SARS-CoV-2 infection", "rel_date": "2021-03-26", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.26.21254259", - "rel_abs": "1.1.1 Background and ObjectivesHemodialysis patients are prone to infection with SARS-COV2 and show a high probability of a severe course of disease and high mortality when infected. In many countries hemodialysis patients are prioritised in vaccination programs to protect this vulnerable community. However, no hemodialysis patients were included in efficacy trials of SARS CoV-2 vaccines and therefore efficacy and safety data for this patient group are lacking. These data would be critical, since hemodialysis patients showed decreased responses against various other vaccines and this could mean decreased response to SARS CoV-2 vaccines.\n\n1.2 Design, setting, participants, and measurementsWe conducted a prospective cohort study consisting of a group of 81 hemodialysis patients and 80 healthy controls who were vaccinated with mRNA vaccine BNT162b2 (BionTech/Pfizer, 2 doses with an interval of 21 days). Anti-SARS-COV-2 S antibody response in all participants was measured 21 days after the second dose. The groups were compared with univariate quantile regressions and a multiple analysis. Adverse events (AEs) of the vaccination were assessed with a standardized questionnaire. We also performed a correlation of HBs-Antibody response with the SARS-COV-2 antibody response in the hemodialysis patients.\n\n1.3 ResultsDialysis patients had significantly lower Anti-SARS-COV-2 S antibody titres than healthy control patients 21 days after vaccination with BNT162b2 (median dialysis Patients 171 U/ml versus median controls 2500 U/ml). Age also had a significant but less pronounced influence on antibody titres. Dialysis patients showed less AEs than the control group. No significant correlation was found for Hepatitis B vaccine antibody response and SARS CoV-2 vaccine antibody response.\n\n1.4 ConclusionsHemodialysis patients exhibit highly diminished SARS-COV-2 S antibody titres compared to a cohort of controls. Therefore these patients could be much less protected by SARS CoV-2 mRNA vaccination than expected. Alternative vaccination schemes must be considered and preventive measures must be maintained after vaccination.", + "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.25.21253694", + "rel_abs": "1.Since the Covid-19 virus spreads through airborne transmission, questions concerning the risk of spreading infectious droplets during singing and music making has arisen.\n\nTo contribute to this question and to help clarify the possible risks, we analyzed 15 singing scenarios (1) qualitatively - by making airflows visible, while singing - and (2) quantitatively - by measuring air velocities at three distances (1m, 1.5m and 2m). Air movements were considered positive when lying above 0.1 m/s, which is the usual room air velocity in venue, such as the concert hall of the Bamberg Symphony, where our measurements with three professional singers (female classical style, male classic style, female popular music style) took place.\n\nOur findings highlight that high measurements for respiratory air velocity while singing are comparable to measurements of speaking and - by far - less than coughing. All measurements for singing stayed within a reach of 1.5m, while only direct voiceless blowing achieved measurements at the 2m sensor. Singing styles that use plosive sounds, i.e. using consonants more often as in rap, produced the highest air velocities of 0.17 m/s at the 1m sensor. Also, singing while wearing a facemask produces no air movements over 0.1 m/s.\n\nOn the basis of our recent studies on measurements of airflows and air velocities of professional singers and wind instrument players, as well as further studies on CO{square} measurements in room settings of music activities, we publish our results - in consideration of further up-to-date research - in our frequently updated risk assessment (first published in April 2020). On this behalf, we suggest 2m radial distances for singers, especially in choirs.", "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Benedikt Simon", - "author_inst": "LKH Mistelbach" + "author_name": "Bernhard Richter", + "author_inst": "Freiburg Institute for Musicians Medicine" }, { - "author_name": "Harald Rubey", - "author_inst": "LK Mistelbach" + "author_name": "Anna Maria Hipp", + "author_inst": "Freiburg Institute for Musicians Medicine" }, { - "author_name": "Andreas Treipl", - "author_inst": "LK Mistelbach" + "author_name": "Bernd Schubert", + "author_inst": "Tintschl BioEngerie und Stroemungstechnik AG" }, { - "author_name": "Martin Gromann", - "author_inst": "LK Mistelbach" + "author_name": "Marcus Rudolf Axt", + "author_inst": "Bamberg Symphony" }, { - "author_name": "Boris Hemedi", - "author_inst": "LK Hainburg" + "author_name": "Markus Stratmann", + "author_inst": "Bamberg Symphony" }, { - "author_name": "Sonja Zehetmayer", - "author_inst": "Medical University of Vienna" + "author_name": "Christian Schmoelder", + "author_inst": "Bamberg Symphony" }, { - "author_name": "Bernhard Kirsch", - "author_inst": "LK Mistelbach" + "author_name": "Claudia Spahn", + "author_inst": "Freiburg Institute for Musicians Medicine" } ], "version": "1", "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "nephrology" + "category": "occupational and environmental health" }, { "rel_doi": "10.1101/2021.03.25.21254253", @@ -844357,103 +843769,31 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.03.24.436864", - "rel_title": "A public vaccine-induced human antibody protects against SARS-CoV-2 and emerging variants", + "rel_doi": "10.1101/2021.03.24.436812", + "rel_title": "Building alternative consensus trees and supertrees using k-means and Robinson and Foulds distance", "rel_date": "2021-03-25", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.03.24.436864", - "rel_abs": "The emergence of antigenically distinct severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants with increased transmissibility is a public health threat. Some of these variants show substantial resistance to neutralization by SARS-CoV-2 infection- or vaccination-induced antibodies, which principally target the receptor binding domain (RBD) on the virus spike glycoprotein. Here, we describe 2C08, a SARS-CoV-2 mRNA vaccine-induced germinal center B cell-derived human monoclonal antibody that binds to the receptor binding motif within the RBD. 2C08 broadly neutralizes SARS-CoV-2 variants with remarkable potency and reduces lung inflammation, viral load, and morbidity in hamsters challenged with either an ancestral SARS-CoV-2 strain or a recent variant of concern. Clonal analysis identified 2C08-like public clonotypes among B cell clones responding to SARS-CoV-2 infection or vaccination in at least 20 out of 78 individuals. Thus, 2C08-like antibodies can be readily induced by SARS-CoV-2 vaccines and mitigate resistance by circulating variants of concern.\n\nOne Sentence SummaryProtection against SARS-CoV-2 variants by a potently neutralizing vaccine-induced human monoclonal antibody.", - "rel_num_authors": 21, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.03.24.436812", + "rel_abs": "Each gene has its own evolutionary history which can substantially differ from the evolutionary histories of other genes. For example, some individual genes or operons can be affected by specific horizontal gene transfer and recombination events. Thus, the evolutionary history of each gene should be represented by its own phylogenetic tree which may display different evolutionary patterns from the species tree that accounts for the main patterns of vertical descent. The output of traditional consensus tree or supertree inference methods is a unique consensus tree or supertree. Here, we describe a new efficient method for inferring multiple alternative consensus trees and supertrees to best represent the most important evolutionary patterns of a given set of phylogenetic trees (i.e. additive trees or X-trees). We show how a specific version of the popular k-means clustering algorithm, based on some interesting properties of the Robinson and Foulds topological distance, can be used to partition a given set of trees into one (when the data are homogeneous) or multiple (when the data are heterogeneous) cluster(s) of trees. We adapt the popular Cali[n]ski-Harabasz, Silhouette, Ball and Hall, and Gap cluster validity indices to tree clustering with k-means. A special attention is paid to the relevant but very challenging problem of inferring alternative supertrees, built from phylogenies constructed for different, but mutually overlapping, sets of taxa. The use of the Euclidean approximation in the objective function of the method makes it faster than the existing tree clustering techniques, and thus perfectly suitable for the analysis of large genomic datasets. In this study, we apply it to discover alternative supertrees characterizing the main patterns of evolution of SARS-CoV-2 and the related betacoronaviruses.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Aaron J. Schmitz", - "author_inst": "Washington University School of Medicine in St. Louis" - }, - { - "author_name": "Jackson S. Turner", - "author_inst": "Washington University School of Medicine in St. Louis" - }, - { - "author_name": "Zhuoming Liu", - "author_inst": "Washington University School of Medicine in St. Louis" - }, - { - "author_name": "Ishmael D. Aziati", - "author_inst": "Washington University School of Medicine in St. Louis" - }, - { - "author_name": "Rita E. Chen", - "author_inst": "Washington University School of Medicine in St. Louis" + "author_name": "Nadia Tahiri", + "author_inst": "University of Quebec in Montreal" }, { - "author_name": "Astha Joshi", - "author_inst": "Washington University School of Medicine in St. Louis" - }, - { - "author_name": "Traci L. Bricker", - "author_inst": "Washington University School of Medicine in St. Louis" - }, - { - "author_name": "Tamarand L. Darling", - "author_inst": "Washington University School of Medicine in St. Louis" - }, - { - "author_name": "Daniel C. Adelsberg", - "author_inst": "Icahn School of Medicine at Mount Sinai" - }, - { - "author_name": "Wafaa B. Al Soussi", - "author_inst": "Washington University School of Medicine in St. Louis" - }, - { - "author_name": "James Brett Case", - "author_inst": "Washington University School of Medicine in St. Louis" - }, - { - "author_name": "Tingting Lei", - "author_inst": "Washington University School of Medicine in St. Louis" - }, - { - "author_name": "Mahima Thapa", - "author_inst": "Washington University School of Medicine in St. Louis" - }, - { - "author_name": "Fatima Amanat", - "author_inst": "Icahn School of Medicine at Mount Sinai" - }, - { - "author_name": "Pei-Yong Shi", - "author_inst": "University of Texas Medical Branch at Galveston" - }, - { - "author_name": "Rachel M. Presti", - "author_inst": "Washington University School of Medicine in St. Louis" - }, - { - "author_name": "Florian Krammer", - "author_inst": "Icahn School of Medicine at Mount Sinai" - }, - { - "author_name": "Goran Bajic", - "author_inst": "Icahn School of Medicine at Mount Sinai" - }, - { - "author_name": "Sean P.J. Whelan", - "author_inst": "Washington University School of Medicine in St. Louis" - }, - { - "author_name": "Michael S. Diamond", - "author_inst": "Washington University School of Medicine in St. Louis" + "author_name": "Bernard Fichet", + "author_inst": "Aix-Marseille University" }, { - "author_name": "Adrianus C.M. Boon", - "author_inst": "Washington University School of Medicine in St. Louis" + "author_name": "Vladimir Makarenkov", + "author_inst": "University of Quebec in Montreal" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nd", "type": "new results", - "category": "immunology" + "category": "evolutionary biology" }, { "rel_doi": "10.1101/2021.03.20.21253956", @@ -846202,65 +845542,37 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.03.16.21253669", - "rel_title": "The Case for Altruism in Institutional Diagnostic Testing", + "rel_doi": "10.1101/2021.03.14.21253554", + "rel_title": "Improved Prediction of COVID-19 Transmission and Mortality Using Google Search Trends for Symptoms in the United States", "rel_date": "2021-03-24", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.16.21253669", - "rel_abs": "Amid COVID-19, many institutions deployed vast resources to test their members regularly for safe reopening. This self-focused approach, however, not only overlooks surrounding communities but also remains blind to community transmission that could breach the institution. To test the relative merits of a more altruistic strategy, we built an epidemiological model that assesses the differential impact on case counts when institutions instead allocate a proportion of their tests to members close contacts in the larger community. We found that testing outside the institution benefits the institution in all plausible circumstances, with the optimal proportion of tests to use externally landing at 45% under baseline model parameters. Our results were robust to local prevalence, secondary attack rate, testing capacity, and contact reporting level, yielding a range of optimal community testing proportions from 18% to 58%. The model performed best under the assumption that community contacts are known to the institution; however, it still demonstrated a significant benefit even without complete knowledge of the contact network.", - "rel_num_authors": 13, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.14.21253554", + "rel_abs": "Accurate forecasting of emerging infectious diseases can guide public health officials in making appropriate decisions related to the allocation of public health resources. Due to the exponential spread of the COVID-19 infection worldwide, several computational models for forecasting the transmission and mortality rates of COVID-19 have been proposed in the literature. To accelerate scientific and public health insights into the spread and impact of COVID-19, Google released the Google COVID-19 search trends symptoms open-access dataset. Our objective is to develop 7 and 14 -day-ahead forecasting models of COVID-19 transmission and mortality in the US using the Google search trends for COVID-19 related symptoms. Specifically, we propose a stacked long short-term memory (SLSTM) architecture for predicting COVID-19 confirmed and death cases using historical time series data combined with auxiliary time series data from the Google COVID-19 search trends symptoms dataset. Considering the SLSTM networks trained using historical data only as the base models, our base models for 7 and 14 -day-ahead forecasting of COVID cases had the mean absolute percentage error (MAPE) values of 6.6% and 8.8%, respectively. On the other side, our proposed models had improved MAPE values of 3.2% and 5.6%, respectively. For 7 and 14 -day-ahead forecasting of COVID-19 deaths, the MAPE values of the base models were 4.8% and 11.4%, while the improved MAPE values of our proposed models were 4.7% and 7.8%, respectively. We found that the Google search trends for \"pneumonia,\" \"shortness of breath,\" and \"fever\" are the most informative search trends for predicting COVID-19 transmission. We also found that the search trends for \"hypoxia\" and \"fever\" were the most informative trends for forecasting COVID-19 mortality.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Ivan Specht", - "author_inst": "The Broad Institute of MIT and Harvard; Harvard University" - }, - { - "author_name": "Kian Sani", - "author_inst": "The Broad Institute of MIT and Harvard; Harvard University" - }, - { - "author_name": "Yolanda Botti-Lodovico", - "author_inst": "The Broad Institute of MIT and Harvard; Howard Hughes Medical Institute" - }, - { - "author_name": "Michael Hughes", - "author_inst": "Colorado Mesa University" - }, - { - "author_name": "Kristin Heumann", - "author_inst": "Colorado Mesa University" - }, - { - "author_name": "Amy Bronson", - "author_inst": "Colorado Mesa University" - }, - { - "author_name": "John Marshall", - "author_inst": "Colorado Mesa University" + "author_name": "Meshrif Alruily", + "author_inst": "College of Computer and Information Sciences, Jouf University, Saudi Arabia" }, { - "author_name": "Emily Baron", - "author_inst": "COVIDCheck Colorado" - }, - { - "author_name": "Eric Parrie", - "author_inst": "COVIDCheck Colorado" + "author_name": "Mohamed Ezz", + "author_inst": "College of Computer and Information Sciences, Jouf University, Saudi Arabia" }, { - "author_name": "Olivia Glennon", - "author_inst": "Fathom Information Design" + "author_name": "Ayman Mohamed Mostafa", + "author_inst": "College of Computer and Information Sciences, Jouf University, Saudi Arabia" }, { - "author_name": "Ben Fry", - "author_inst": "Fathom Information Design" + "author_name": "Nacim Yanes", + "author_inst": "College of Computer and Information Sciences, Jouf University, Saudi Arabia" }, { - "author_name": "Andres Colubri", - "author_inst": "The Broad Institute of MIT and Harvard; Program in Bioinformatics and Integrative Biology, University of Massachusetts Medical School" + "author_name": "Mostafa Abbas", + "author_inst": "Geisinger Clinic" }, { - "author_name": "Pardis C Sabeti", - "author_inst": "The Broad Institute or MIT and Harvard; Harvard University; Massachusetts Consortium on Pathogen Readiness; Howard Hughes Medical Institute" + "author_name": "Yasser El-Manzalawy", + "author_inst": "Geisinger Clinic" } ], "version": "1", @@ -847830,67 +847142,43 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.03.23.21254203", - "rel_title": "Evaluation of the ROX index in SARS-CoV-2 Acute Respiratory failure treated with both High-Flow Nasal Oxygen (HFNO) and Continuous Positive Airway Pressure (CPAP)", + "rel_doi": "10.1101/2021.03.23.21254165", + "rel_title": "Introducing the 4Ps Model of Transitioning to Distance Learning: a convergent mixed methods study conducted during the COVID-19 pandemic.", "rel_date": "2021-03-24", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.23.21254203", - "rel_abs": "BackgroundNon-invasive respiratory support including high-flow nasal oxygen (HFNO), and continuous positive airway pressure (CPAP) have been used to provide therapy in selected SARS-CoV-2 patients with acute respiratory failure (ARF). The value of the ROX index, a validated benchmark for outcomes in HFNO is unknown in CPAP.\n\nObjectiveCan the ROX, a validated benchmark in HFNO be used for measuring treatment outcomes of CPAP in SARS-COV-2 ARF?\n\nStudy Design and MethodsA non-randomised prospective protocol driven observational non-intensive care unit study in 130 SARS-COV-2 patients with ARF treated with non-invasive therapy from March 2020 to January 2021. The primary end point was failure of therapy (death or escalation). Secondary outcomes included time to failure including invasive mechanical ventilation (IMV) or death, the effect of escalation to CPAP from HFNO and the utility of ROX in ARF.\n\nResultsHFNO was better than CPAP in treating SARS-COV-2 ARF: 17/35 (48.5%) with successful HFNO therapy versus 24/95 (25.2%) with CPAP. The ROX index was more sensitive to outcomes with CPAP compared to HFNO and distinguished treatment failure early at 1, 4, 6, 12, and 24 hours with the highest sensitivity at 24 hours (ROX-24h). The AUC for the ROX-24h was 0.77 for HFNO (P<0.0001), and 0.84 for CPAP (P<0.0001). The ROX-24h cut-points predicted failure with HFNO when < 3.9 (PPV 71%, NPV 75%) and CPAP < 4.3 (PPV 75%, NPV 91%). For success, ROX-24h cut-points of 7.6 for HFNO (PPV 85%, NPV 48%) and 6.1 for CPAP (PPV 88%, NPV 62%) were observed. Escalation from HFNO to CPAP was mostly not successful.\n\nConclusionARF in SARS-COV-2 can be successfully managed by non-invasive support. The ROX index, validated for HFNO, provides a timely, low resource measure for both HFNO and CPAP avoiding delayed intubation.\n\nTrial registrationStudy approved by NHS HRAREC (20/HRA/2344;ethics 283888)\n\nKEY MESSAGEO_ST_ABSWhat is the key question?C_ST_ABSCan the ROX, a validated benchmark in high-flow nasal oxygen (HFNO) be used for measuring treatment outcomes of continuous positive airway pressure (CPAP) in SARS-COV-2 ARF?\n\nWhat is the bottom line?The ROX index, validated for HFNO, provides a timely, low resource measure for both HFNO and CPAP support avoiding delayed intubation.\n\nWhy read on?The present study compares the efficacy of HFNO and CPAP, two common globally used modalities of treatment for SARS-CoV-2 and notes the superior utility of the ROX-24h in CPAP to predict outcome, enabling timely escalation decisions.", - "rel_num_authors": 12, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.23.21254165", + "rel_abs": "Significant concern has been raised regarding the effect of COVID-19 on medical education. The aim of this study was to shed light on the distance learning experiences of medical students and their instructors. A convergent mixed methods approach was utilized. Qualitative and quantitative data was collected using a survey.\n\nThe percentage of the total average of satisfaction among stakeholders was 76.4%. The qualitative analysis revealed several themes. This study introduced the 4Ps Model of Transitioning to Distance Learning. It would be useful to leverage the lessons-learned to tailor blended medical programs, with a reasonable melange of experiences. The study also contributes to the mixed methods research through showcasing a means of adapting it to evaluate critical situations reliably and rapidly.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Hakim Ghani", - "author_inst": "West Herts NHS Trust" - }, - { - "author_name": "Michael Shaw", - "author_inst": "West Herts NHS Trust" - }, - { - "author_name": "Phyoe Pyae", - "author_inst": "West Herts NHS Trust" - }, - { - "author_name": "Rigers Cama", - "author_inst": "West Herts NHS Trust" - }, - { - "author_name": "Meghna Prabhakar", - "author_inst": "West Herts NHS Trust" - }, - { - "author_name": "Alessio Navarra", - "author_inst": "West Herts NHS Trust" - }, - { - "author_name": "Janice Yu Ji Lee", - "author_inst": "Addenbrookes Hospital, Cambridge" + "author_name": "Farah Otaki", + "author_inst": "Mohammed Bin Rashid University of Medicine and Health Sciences (MBRU)" }, { - "author_name": "Felix Chua", - "author_inst": "Royal Brompton & Harefield NHS Foundation Trust" + "author_name": "Shroque Zaher", + "author_inst": "Mohammed Bin Rashid University of Medicine and Health Sciences (MBRU)" }, { - "author_name": "Rahul Mogal", - "author_inst": "West Herts NHS Trust" + "author_name": "Stefan Du Plessis", + "author_inst": "Mohammed Bin Rashid University of Medicine and Health Sciences (MBRU)" }, { - "author_name": "Andrew Barlow", - "author_inst": "West Herts NHS Trust" + "author_name": "Ritu Lakhtakia", + "author_inst": "Mohammed Bin Rashid University of Medicine and Health Sciences (MBRU)" }, { - "author_name": "Nazril Nordin", - "author_inst": "West Herts NHS Trust" + "author_name": "Nabil M. Zary", + "author_inst": "Mohammed Bin Rashid University of Medicine and Health Sciences (MBRU)" }, { - "author_name": "Rama Vancheeswaran", - "author_inst": "West Herts NHS Trust" + "author_name": "Ibrahim M. Inuwa", + "author_inst": "Mohammed Bin Rashid University of Medicine and Health Sciences (MBRU)" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "respiratory medicine" + "category": "medical education" }, { "rel_doi": "10.1101/2021.03.19.21253940", @@ -849780,57 +849068,69 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.03.16.21253377", - "rel_title": "First and second SARS-CoV-2 waves in inner London: A comparison of admission characteristics and the effects of the B.1.1.7 variant", + "rel_doi": "10.1101/2021.03.14.21253557", + "rel_title": "Mortality and Severity in COVID-19 Patients on ACEIs & ARBs - A Meta-Regression Analysis", "rel_date": "2021-03-24", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.16.21253377", - "rel_abs": "IntroductionA second wave of SARS-CoV-2 infection spread across the UK in 2020 linked with emergence of the more transmissible B.1.1.7 variant. The emergence of new variants, particularly during relaxation of social distancing policies and implementation of mass vaccination, highlights the need for real-time integration of detailed patient clinical data alongside pathogen genomic data. We linked clinical data with viral genome sequence data to compare cases admitted during the first and second waves of SARS-CoV-2 infection.\n\nMethodsClinical, laboratory and demographic data from five electronic health record (EHR) systems was collected for all cases with a positive SARS-CoV-2 RNA test between March 13th 2020 and February 17th 2021. SARS-CoV-2 viral sequencing was performed using Oxford Nanopore Technology. Descriptive data are presented comparing cases between waves, and between cases of B.1.1.7 and non-B.1.1.7 variants.\n\nResultsThere were 5810 SARS-CoV-2 RNA positive cases comprising inpatients (n=2341), healthcare workers (n=1549), outpatients (n=874), emergency department (ED) attenders not subsequently admitted (n=532), inter-hospital transfers (n=281) and nosocomial cases (n=233). There were two dominant waves of hospital admissions, with wave one starting from March 13th (n=838) and wave two from October 20th (n=1503), both with a temporally aligned rise in nosocomial cases (n=96 in wave one, n=137 in wave two). 1470 SARS-CoV-2 isolates were successfully sequenced, including 216/838 (26%) admitted cases from wave one, 472/1503 (31%) admitted cases in wave two and 121/233 (52%) nosocomial cases. The first B.1.1.7 variant was identified on 15th November 2020 and increased rapidly such that it comprised 400/472 (85%) of sequenced isolates from admitted cases in wave two. Females made up a larger proportion of admitted cases in wave two (47.3% vs 41.8%, p=0.011), and in those infected with the B.1.1.7 variant compared to non-B.1.1.7 variants (48.0% vs 41.8%, p=0.042). A diagnosis of frailty was less common in wave two (11.5% v 22.8%, p<0.001) and in the group infected with B.1.1.7 (14.5% v 22.4%, p=0.001). There was no difference in severity on admission between waves, as measured by hypoxia at admission (wave one: 64.3% vs wave two: 65.5%, p=0.67). However, a higher proportion of cases infected with the B.1.1.7 variant were hypoxic on admission compared to other variants (70.0% vs 62.5%, p=0.029).\n\nConclusionsAutomated EHR data extraction linked with SARS-CoV-2 genome sequence data provides valuable insight into the evolving characteristics of cases admitted to hospital with COVID-19. The proportion of cases with hypoxia on admission was greater in those infected with the B.1.1.7 variant, which supports evidence the B.1.1.7 variant is associated with more severe disease. The number of nosocomial cases was similar in both waves despite introduction of many infection control interventions before wave two, an observation requiring further investigation.", - "rel_num_authors": 11, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.14.21253557", + "rel_abs": "PurposeThe primary objective of this review is to examine studies reporting association of mortality in COVID-19 patients with whether they were on Angiotensin-converting-enzyme inhibitors (ACEIs) and Angiotensin II receptor blockers (ARBs). A secondary objective is to similarly access associations with higher severity of the disease in COVID-19 patients.\n\nMaterials and MethodsWe searched multiple COVID-19 databases (WHO, CDC, LIT-COVID) for randomized trials and longitudinal studies from all over the world reporting mortality and severity published before January 18th, 2021. Meta-analyses were performed using 53 studies for mortality outcome and 43 for the severity outcome. Mantel-Haenszel odds ratios were generated to describe overall effect size using random effect models. To account for between study results variations, multivariate meta-Regression was performed with preselected covariates using maximum likelihood method for both the mortality and severity models.\n\nResultOur findings showed that the use of ACEIs/ARBs did not significantly influence either mortality (OR=1.16 95% CI 0.94 to 1.44, p= 0.15, I2 = 93.2%) or severity (OR=1.18, 95% CI 0.94 to 1.48 p= 0.15, I2 = 91.1%) in comparison to not being on ACEIs/ARBs in COVID-19 positive patients. Multivariate meta-regression for the mortality model demonstrated that 36% of between study variations could be explained by differences in age, gender, and proportion of heart diseases in the study samples. Multivariate meta-regression for the severity model demonstrated that 8% of between study variations could be explained by differences in age, proportion of diabetes, heart disease and study country in the study samples.\n\nConclusionWe found no association of mortality or severity in COVID-19 patients taking ACEIs/ARBs.", + "rel_num_authors": 14, "rel_authors": [ { - "author_name": "Luke B Snell", - "author_inst": "King's College London" + "author_name": "Romil Singh", + "author_inst": "Mayo Clinic, Rochester, Minnesota, USA" }, { - "author_name": "Wenjuan Wang", - "author_inst": "School of Population Health and Environmental Sciences, King's College London, London, UK" + "author_name": "Sawai Singh Rathore", + "author_inst": "Dr. Sampurnanand Medical College and Hospital, Jodhpur, Rajasthan, India" }, { - "author_name": "Adela Alcolea-Medina", - "author_inst": "Viapath, London, UK" + "author_name": "Hira Khan", + "author_inst": "Islamic International Medical College, Rawalpindi, Pakistan" }, { - "author_name": "Themoula Charalampous", - "author_inst": "Centre for Clinical Infection and Diagnostics Research, School of Immunology and Microbial Sciences, King's College London, London, UK" + "author_name": "Abhishek Bhurwal", + "author_inst": "Rutgers Robert Wood Johnson School of Medicine, New Brunswick, NJ, USA" }, { - "author_name": "Gaia Nebbia", - "author_inst": "Centre for Clinical Infection and Diagnostics Research, School of Immunology and Microbial Sciences, King's College London, London, UK" + "author_name": "Mack Sheraton", + "author_inst": "Trinity West Medical Center, Steubenville, Ohio, USA" }, { - "author_name": "Rahul Batra", - "author_inst": "Centre for Clinical Infection and Diagnostics Research, School of Immunology and Microbial Sciences, King's College London, London, UK" + "author_name": "Prithwish Ghosh", + "author_inst": "Mayo Clinic, Rochester, Minnesota, USA" }, { - "author_name": "Leonardo de Jongh", - "author_inst": "NIHR Biomedical Research Centre, Guy's and St Thomas' NHS Foundation Trust" + "author_name": "Sohini Anand", + "author_inst": "Patliputra Medical College and Hospital, Dhanbad, Jharkhand, India" }, { - "author_name": "Finola Higgins", - "author_inst": "NIHR Biomedical Research Centre, Guy's and St Thomas' NHS Foundation Trust" + "author_name": "Janaki Makadia", + "author_inst": "GMERS Medical College and Hospital, Gotri, Vadodara, Gujrat, India" }, { - "author_name": "Yanzhong Wang", - "author_inst": "School of Population Health and Environmental Sciences, King's College London, London, UK" + "author_name": "FNU Ayesha", + "author_inst": "Services Institute of Medical Sciences, Lahore, Pakistan" }, { - "author_name": "Jonathan D Edgeworth", - "author_inst": "Centre for Clinical Infection and Diagnostics Research, School of Immunology and Microbial Sciences, King's College London, London, UK" + "author_name": "Kiran Mahapure", + "author_inst": "KAHER J. N. Medical College, Belgaum, Karnataka, India" }, { - "author_name": "Vasa Curcin", - "author_inst": "School of Population Health and Environmental Sciences, King's College London, London, UK" + "author_name": "Ishita Mehra", + "author_inst": "North Alabama Medical Center, Florence, AL, USA" + }, + { + "author_name": "Aysun Tekin", + "author_inst": "Mayo Clinic, Rochester, Minnesota, USA" + }, + { + "author_name": "Rahul Kashyap", + "author_inst": "Mayo Clinic, Rochester, Minnesota, USA" + }, + { + "author_name": "Vikas Bansal", + "author_inst": "Mayo Clinic, Rochester, Minnesota, USA" } ], "version": "1", @@ -851970,85 +851270,65 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.03.19.21251426", - "rel_title": "T-cell receptor sequencing identifies prior SARS-CoV-2 infection and correlates with neutralizing antibody titers and disease severity", + "rel_doi": "10.1101/2021.03.20.21253976", + "rel_title": "Weekly SARS-CoV-2 screening of asymptomatic students and staff to guide and evaluate strategies for safer in-person learning", "rel_date": "2021-03-22", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.19.21251426", - "rel_abs": "Measuring the adaptive immune response to SARS-CoV-2 can enable the assessment of past infection as well as protective immunity and the risk of reinfection. While neutralizing antibody (nAb) titers are one measure of protection, such assays are challenging to perform at a large scale and the longevity of the SARS-CoV-2 nAb response is not fully understood. Here, we apply a T-cell receptor (TCR) sequencing assay that can be performed on a small volume standard blood sample to assess the adaptive T-cell response to SARS-CoV-2 infection. Samples were collected from a cohort of 302 individuals recovered from COVID-19 up to 6 months after infection. Previously published findings in this cohort showed that two commercially available SARS-CoV-2 serologic assays correlate well with nAb testing. We demonstrate that the magnitude of the SARS-CoV-2-specific T-cell response strongly correlates with nAb titer, as well as clinical indicators of disease severity including hospitalization, fever, or difficulty breathing. While the depth and breadth of the T-cell response declines during convalescence, the T-cell signal remains well above background with high sensitivity up to at least 6 months following initial infection. Compared to serology tests detecting binding antibodies to SARS-CoV-2 spike and nucleoprotein, the overall sensitivity of the TCR-based assay across the entire cohort and all timepoints was approximately 5% greater for identifying prior SARS-CoV-2 infection. Notably, the improved performance of T-cell testing compared to serology was most apparent in recovered individuals who were not hospitalized and were sampled beyond 150 days of their initial illness, suggesting that antibody testing may have reduced sensitivity in individuals who experienced less severe COVID-19 illness and at later timepoints. Finally, T-cell testing was able to identify SARS-CoV-2 infection in 68% (55/81) of convalescent samples having nAb titers below the lower limit of detection, as well as 37% (13/35) of samples testing negative by all three antibody assays. These results demonstrate the utility of a TCR-based assay as a scalable, reliable measure of past SARS-CoV-2 infection across a spectrum of disease severity. Additionally, the TCR repertoire may be useful as a surrogate for protective immunity with additive clinical value beyond serologic or nAb testing methods.", - "rel_num_authors": 18, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.20.21253976", + "rel_abs": "BackgroundData suggest that COVID-19 transmission in K-12 schools is uncommon, but few studies have confirmed this using widespread screening of asymptomatic individuals.\n\nObjectiveTo evaluate the incidence of asymptomatic COVID-19, document the frequency of in-school transmission, and confirm feasibility of widespread asymptomatic screening in schools.\n\nDesignProspective observational study\n\nSettingSingle mid-sized suburban school district including 10 schools and a central office.\n\nParticipantsDistrict staff and students\n\nInterventionsAsymptomatic screening PCR for SARS-CoV-2\n\nMeasurementsConcurrent with a hybrid model and layered mitigation, weekly pooled testing of staff and secondary students was offered using saliva samples collected at home. Identification of >1 case in a school prompted investigation for possible in-school transmission. Staff and families were surveyed about satisfaction with the screening program.\n\nResultsFrom weeks 1-18, rates of incident COVID-19 in the surrounding community rose steadily. Weekly staff and student screening identified 0-7 asymptomatic cases/week. In week 7, 5 cases were identified among staff who shared an office setting. Enhancements to mitigation strategies were undertaken. The proportion of survey respondents self-reporting comfort with in-person learning before versus after implementation of screening increased.\n\nLimitationsBecause screening testing was not mandatory, the results from the participating population might not represent the entire school community.\n\nConclusionsIn this school district with layered mitigation measures, in-school transmission was rare. The program identified a cluster with in-school staff-to-staff transmission and spurred enhancement of safety strategies. A weekly COVID-19 screening program can provide critical data to inform mitigation efforts, and provides school-specific, current data to inform decisions about in-person learning models. Screening provided reassurance and identified asymptomatic cases.\n\nFundingThe Wellesley Education Foundation provided funding for the testing.", + "rel_num_authors": 13, "rel_authors": [ { - "author_name": "Rebecca Elyanow", - "author_inst": "Adaptive Biotechnologies, Seattle, Washington, USA" + "author_name": "Shira Doron", + "author_inst": "Tufts University Medical Center" }, { - "author_name": "Thomas M. Snyder", - "author_inst": "Adaptive Biotechnologies, Seattle, Washington, USA" - }, - { - "author_name": "Sudeb C. Dalai", - "author_inst": "Adaptive Biotechnologies, Seattle, Washington, USA; and Stanford University School of Medicine, Stanford, California, USA" - }, - { - "author_name": "Rachel M. Gittelman", - "author_inst": "Adaptive Biotechnologies, Seattle, Washington, USA" - }, - { - "author_name": "Jim Boonyaratanakornkit", - "author_inst": "Department of Medicine, University of Washington, Seattle, Washington, USA, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA" - }, - { - "author_name": "Anna Wald", - "author_inst": "Department of Medicine, University of Washington, Seattle, Washington, USA; Fred Hutchinson Cancer Research Center, Seattle, Washington, USA; Department of Epid" - }, - { - "author_name": "Stacy Selke", - "author_inst": "Department of Laboratory Medicine and Pathology, University of Washington, Seattle, Washington, USA" + "author_name": "Robin Ingalls", + "author_inst": "Boston University School of Medicine" }, { - "author_name": "Mark H. Wener", - "author_inst": "Department of Laboratory Medicine and Pathology, University of Washington, Seattle, Washington, USA" + "author_name": "Anne Beauchamp", + "author_inst": "Wellesley Public Schools" }, { - "author_name": "Chihiro Morishima", - "author_inst": "Department of Laboratory Medicine and Pathology, University of Washington, Seattle, Washington, USA" + "author_name": "Jesse Boehm", + "author_inst": "Broad Institute" }, { - "author_name": "Alex L. Greninger", - "author_inst": "Department of Laboratory Medicine and Pathology, University of Washington, Seattle, Washington, USA" + "author_name": "Helen Boucher", + "author_inst": "Tufts University Medical Center" }, { - "author_name": "Michael R. Holbrook", - "author_inst": "National Institute of Allergy and Infectious Diseases Integrated Research Facility, Frederick, Maryland, USA" + "author_name": "Linda Chow", + "author_inst": "Wellesley School Committee" }, { - "author_name": "Ian M. Kaplan", - "author_inst": "Adaptive Biotechnologies, Seattle, Washington, USA" + "author_name": "Linda Corridan", + "author_inst": "Wellesley Public Schools" }, { - "author_name": "H. Jabran Zahid", - "author_inst": "Microsoft Research, Redmond, Washington, USA" + "author_name": "Cathryn Goehringer", + "author_inst": "COVID-19 Response Advisors" }, { - "author_name": "Jonathan M. Carlson", - "author_inst": "Microsoft Research, Redmond, Washington, USA" + "author_name": "Douglas Golenbock", + "author_inst": "University of Massachusetts Medical School" }, { - "author_name": "Lance Baldo", - "author_inst": "Adaptive Biotechnologies, Seattle, Washington, USA" + "author_name": "Liz Larsen", + "author_inst": "Wellesley Education Foundation" }, { - "author_name": "Thomas Manley", - "author_inst": "Adaptive Biotechnologies, Seattle, Washington, USA" + "author_name": "David Lussier", + "author_inst": "Wellesley Public Schools" }, { - "author_name": "Harlan S. Robins", - "author_inst": "Adaptive Biotechnologies, Seattle, Washington, USA" + "author_name": "Marcia Testa", + "author_inst": "Wellesley Board of Health" }, { - "author_name": "David M. Koelle", - "author_inst": "Department of Medicine, University of Washington, Seattle, Washington, USA; Fred Hutchinson Cancer Research Center, Seattle, Washington, USA; Department of Labo" + "author_name": "Andrea L Ciaranello", + "author_inst": "Massachusetts General Hospital" } ], "version": "1", @@ -853740,79 +853020,91 @@ "category": "intensive care and critical care medicine" }, { - "rel_doi": "10.1101/2021.03.11.21253275", - "rel_title": "Effect of vaccination on transmission of COVID-19: an observational study in healthcare workers and their households", + "rel_doi": "10.1101/2021.03.20.436243", + "rel_title": "A bispecific monomeric nanobody induces SARS-COV-2 spike trimer dimers", "rel_date": "2021-03-21", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.11.21253275", - "rel_abs": "BackgroundThe effect of vaccination for COVID-19 on onward transmission is unknown.\n\nMethodsA national record linkage study determined documented COVID-19 cases and hospitalisations in unvaccinated household members of vaccinated and unvaccinated healthcare workers from 8th December 2020 to 3rd March 2021. The primary endpoint was COVID-19 14 days following the first dose.\n\nResultsThe cohort comprised of 194,362 household members (mean age 31{middle dot}1 {+/-} 20{middle dot}9 years) and 144,525 healthcare workers (mean age 44{middle dot}4 {+/-} 11{middle dot}4 years). 113,253 (78{middle dot}3%) of healthcare workers received at least one dose of the BNT162b2 mRNA or ChAdOx1 nCoV-19 vaccine and 36,227 (25{middle dot}1%) received a second dose. There were 3,123 and 4,343 documented COVID-19 cases and 175 and 177 COVID-19 hospitalisations in household members of healthcare workers and healthcare workers respectively. Household members of vaccinated healthcare workers had a lower risk of COVID-19 case compared to household members of unvaccinated healthcare worker (rate per 100 person-years 9{middle dot}40 versus 5{middle dot}93; HR 0{middle dot}70, 95% confidence interval [CI] 0{middle dot}63 to 0{middle dot}78). The effect size for COVID-19 hospitalisation was similar, with the confidence interval crossing the null (HR 0{middle dot}77 [95% CI 0{middle dot}53 to 1{middle dot}10]). The rate per 100 person years was lower in vaccinated compared to unvaccinated healthcare workers for documented (20{middle dot}13 versus 8{middle dot}51; HR 0{middle dot}45 [95% CI 0{middle dot}42 to 0{middle dot}49]) and hospitalized COVID-19 (0{middle dot}97 versus 0{middle dot}14; HR 0{middle dot}16 [95% CI 0{middle dot}09 to 0{middle dot}27]). Compared to the period before the first dose, the risk of documented COVID-19 case was lower at [≥] 14 days after the second dose for household members (HR 0{middle dot}46 [95% CI 0{middle dot}30to 0{middle dot}70]) and healthcare workers (HR 0{middle dot}08 [95% CI 0{middle dot}04 to 0{middle dot}17]).\n\nInterpretationVaccination of health care workers was associated with a substantial reduction in COVID-19 cases in household contacts consistent with an effect of vaccination on transmission.", - "rel_num_authors": 15, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2021.03.20.436243", + "rel_abs": "Antibodies binding to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike have therapeutic promise, but emerging variants show the potential for virus escape. This emphasizes the need for therapeutic molecules with distinct and novel neutralization mechanisms. Here we isolated a nanobody that interacts simultaneously with two RBDs from different spike trimers of SARS-CoV-2, rapidly inducing the formation of spike trimer-dimers leading to the loss of their ability to attach to the host cell receptor, ACE2. We show that this nanobody potently neutralizes SARS-CoV-2, including the B.1.351 variant, and cross-neutralizes SARS-CoV. Furthermore, we demonstrate the therapeutic potential of the nanobody against SARS-CoV-2 and the B.1.351 variant in a human ACE2 transgenic mouse model. This naturally elicited bispecific monomeric nanobody establishes a novel strategy for potent inactivation of viral antigens and represents a promising antiviral against emerging SARS-CoV-2 variants.", + "rel_num_authors": 18, "rel_authors": [ { - "author_name": "Anoop Shah", - "author_inst": "London School of Hygiene and Tropical Medicine" + "author_name": "Leo Hanke", + "author_inst": "Karolinska Institutet" }, { - "author_name": "Ciara Gribben", - "author_inst": "Public Health Scotland" + "author_name": "Hrishikesh Das", + "author_inst": "Karolinska Institutet" }, { - "author_name": "Jennifer Bishop", - "author_inst": "Public Health Scotland" + "author_name": "Daniel Sheward", + "author_inst": "Karolinska Institutet" }, { - "author_name": "Peter Hanlon", - "author_inst": "University of Glasgow" + "author_name": "Laura Perez Vidakovics", + "author_inst": "Karolinska Institutet" }, { - "author_name": "David Caldwell", - "author_inst": "Public Health Scotland" + "author_name": "Egon Urgard", + "author_inst": "Karolinska Institutet" }, { - "author_name": "Rachael Wood", - "author_inst": "PublicHealth Scotland" + "author_name": "Ainhoa Moliner Morro", + "author_inst": "Karolinska Institutet" }, { - "author_name": "Martin Reid", - "author_inst": "Public Health Scotland" + "author_name": "Kim Changil", + "author_inst": "Karolinska Institutet" }, { - "author_name": "Jim McMenamin", - "author_inst": "Public Health Scotland" + "author_name": "Vivien Karl", + "author_inst": "Karolinska Institutet" }, { - "author_name": "David Goldberg", - "author_inst": "Public Health Scotland" + "author_name": "Alec Pankow", + "author_inst": "Karolinska Institutet" }, { - "author_name": "Diane Stockton", - "author_inst": "Public Health Scotland" + "author_name": "Natalie Smith", + "author_inst": "Karolinska Institutet" }, { - "author_name": "Sharon Hutchinson", - "author_inst": "Public Health Scotland" + "author_name": "Bartlomiej Porebski", + "author_inst": "Science for Life Laboratory, Division of Genome Biology, Department of Medical Biochemistry and Biophysics, Karolinska Institute, Stockholm, Sweden" }, { - "author_name": "Chris Robertson", - "author_inst": "Public Health Scotland" + "author_name": "Oscar Fernandez-Capetillo", + "author_inst": "Science for Life Laboratory, Division of Genome Biology, Department of Medical Biochemistry and Biophysics, Karolinska Institute, Stockholm, Sweden" }, { - "author_name": "Paul M McKeigue", - "author_inst": "Public Health Scotland" + "author_name": "Erdinc Sezgin", + "author_inst": "Karolinska Institutet" }, { - "author_name": "Helen M Colhoun", - "author_inst": "Public Health Scotland" + "author_name": "Gabriel Pedersen", + "author_inst": "Statens Serum Institut" }, { - "author_name": "David McAllister", - "author_inst": "University of Glasgow" + "author_name": "Jonathan M Coquet", + "author_inst": "Karolinska Institutet" + }, + { + "author_name": "B Martin Hallberg", + "author_inst": "Karolinska Institutet" + }, + { + "author_name": "Benjamin Murrell", + "author_inst": "Karolinska Institutet" + }, + { + "author_name": "Gerald M McInerney", + "author_inst": "Karolinska Institutet" } ], "version": "1", - "license": "cc_by", - "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "license": "cc_no", + "type": "new results", + "category": "immunology" }, { "rel_doi": "10.1101/2021.03.20.436257", @@ -855830,65 +855122,237 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.03.19.21253982", - "rel_title": "Low levels of protective humoral immunity following mild or asymptomatic infection with SARS-CoV-2 in a community-based serological study", + "rel_doi": "10.1101/2021.03.19.21254004", + "rel_title": "Heterogeneous immunological recovery trajectories revealed in post-acute COVID-19", "rel_date": "2021-03-20", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.19.21253982", - "rel_abs": "The degree of protective humoral immunity after mild or asymptomatic SARS-CoV-2 infection is not known. We measured antibody-mediated neutralization of spike protein-ACE2 receptor binding--a surrogate measure of protection against SARS-CoV-2 infection--in a large and diverse community-based seroprevalence study. Comparisons were made across three groups of seropositive participants that differed in the severity of infection and engagement with clinical care (N=790). The clinical group was seropositive for prior infection, symptomatic, and diagnosed with COVID-19 by a healthcare provider. The symptomatic group was seropositive and reported one or more symptoms of infection but received no clinical care. The asymptomatic group was seropositive but reported no symptoms. 86.2% of all infections were mild or asymptomatic; 13.8% received clinical care. Of the clinical cases, 96.3% were outpatient; only 3.7% required hospitalization. Moderate or high levels of neutralizing activity were detected following 27.5% of clinical infections, in comparison with 5.4% of symptomatic and 1.5% of asymptomatic infections. The majority of infections in the general population are mild or asymptomatic and likely result in low levels of antibody-mediated protective immunity.", - "rel_num_authors": 12, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.19.21254004", + "rel_abs": "The immunological picture of how different patients recover from COVID-19, and how those recovery trajectories are influenced by infection severity, remain unclear. We investigated 140 COVID-19 patients from diagnosis to convalescence using clinical data, viral load assessments, and multi-omic analyses of blood plasma and circulating immune cells. Immune-phenotype dynamics resolved four recovery trajectories. One trajectory signals a return to pre-infection healthy baseline, while the other three are characterized by differing fractions of persistent cytotoxic and proliferative T cells, distinct B cell maturation processes, and memory-like innate immunity. We resolve a small panel of plasma proteins that, when measured at diagnosis, can predict patient survival and recovery-trajectory commitment. Our study offers novel insights into post-acute immunological outcomes of COVID-19 that likely influence long-term adverse sequelae.", + "rel_num_authors": 55, "rel_authors": [ { - "author_name": "Thomas W. McDade", - "author_inst": "Northwestern University" + "author_name": "Yapeng Su", + "author_inst": "Institute for Systems Biology" }, { - "author_name": "Amelia Sancilio", - "author_inst": "Northwestern University" + "author_name": "Dan Yuan", + "author_inst": "Institute for Systems Biology" }, { - "author_name": "Richard T. D'Aquila", - "author_inst": "Northwestern University" + "author_name": "Daniel G Chen", + "author_inst": "Institute for Systems Biology" }, { - "author_name": "Brian Mustanski", - "author_inst": "Northwestern University" + "author_name": "Kai Wang", + "author_inst": "Institute for Systems Biology" }, { - "author_name": "Lauren A. Vaught", - "author_inst": "Northwestern University" + "author_name": "Jongchan Choi", + "author_inst": "Institute for Systems Biology" }, { - "author_name": "Nina L. Reiser", - "author_inst": "Northwestern University" + "author_name": "Chengzhen L Dai", + "author_inst": "Institute for Systems Biology" }, { - "author_name": "Matt P. Velez", - "author_inst": "Northwestern University" + "author_name": "Sunga Hong", + "author_inst": "Institute for Systems Biology" }, { - "author_name": "Ryan R. Hsieh", - "author_inst": "Northwestern University" + "author_name": "Rongyu Zhang", + "author_inst": "Institute for Systems Biology" }, { - "author_name": "Daniel T. Ryan", - "author_inst": "Northwestern University" + "author_name": "Jingyi Xie", + "author_inst": "Institute for Systems Biology" }, { - "author_name": "Rana Saber", - "author_inst": "Northwestern University" + "author_name": "Sarah Li", + "author_inst": "Institute for Systems Biology" }, { - "author_name": "Elizabeth M. McNally", - "author_inst": "Northwestern University" + "author_name": "Kelsey Scherler", + "author_inst": "Institute for Systems Biology" }, { - "author_name": "Alexis R. Demonbreun", - "author_inst": "Northwestern University" + "author_name": "Ana-Jimena Pavlovitch-Bedzyk", + "author_inst": "Stanford University" + }, + { + "author_name": "Shen Dong", + "author_inst": "Institute for Systems Biology" + }, + { + "author_name": "Christopher Lausted", + "author_inst": "Institute for Systems Biology" + }, + { + "author_name": "Rachel H Ng", + "author_inst": "Institute for Systems Biology" + }, + { + "author_name": "Inyoul Lee", + "author_inst": "Institute for Systems Biology" + }, + { + "author_name": "Shannon Fallen", + "author_inst": "Institute for Systems Biology" + }, + { + "author_name": "Sergey A Kornilov", + "author_inst": "Institute for Systems Biology" + }, + { + "author_name": "Priyanka Baloni", + "author_inst": "Institute for Systems Biology" + }, + { + "author_name": "Venkata R Duvvuri", + "author_inst": "Institute for Systems Biology" + }, + { + "author_name": "Kristin G Anderson", + "author_inst": "Fred Hutch Cancer Research Center" + }, + { + "author_name": "Jing Li", + "author_inst": "Stanford University" + }, + { + "author_name": "Fan Yang", + "author_inst": "Stanford University" + }, + { + "author_name": "Clifford Rostomily", + "author_inst": "Institute for Systems Biology" + }, + { + "author_name": "Pamela Troisch", + "author_inst": "Institute for Systems Biology" + }, + { + "author_name": "Brett Smith", + "author_inst": "Institute for Systems Biology" + }, + { + "author_name": "Jing Zhou", + "author_inst": "Isoplexis Corporation" + }, + { + "author_name": "Sean Mackay", + "author_inst": "Isoplexis Corporation" + }, + { + "author_name": "Kim Murry", + "author_inst": "Institute for Systems Biology" + }, + { + "author_name": "Rick Edmark", + "author_inst": "Institute for Systems Biology" + }, + { + "author_name": "Lesley Jones", + "author_inst": "Institute for Systems Biology" + }, + { + "author_name": "Yong Zhou", + "author_inst": "Institute for Systems Biology" + }, + { + "author_name": "Lee Rowen", + "author_inst": "Institute for Systems Biology" + }, + { + "author_name": "Rachel Liu", + "author_inst": "Institute for Systems Biology" + }, + { + "author_name": "William Chour", + "author_inst": "Institute for Systems Biology" + }, + { + "author_name": "William R Berrington", + "author_inst": "Swedish Medical Center" + }, + { + "author_name": "Julie A Wallick", + "author_inst": "Swedish Medical Center" + }, + { + "author_name": "Heather A Algren", + "author_inst": "Swedish Medical Center" + }, + { + "author_name": "Terri Wrin", + "author_inst": "Monogram Biosciences" + }, + { + "author_name": "Christos Petropoulos", + "author_inst": "Monogram Biosciences" + }, + { + "author_name": "Wei Wei", + "author_inst": "Institute for Systems Biology" + }, + { + "author_name": "Nathan D Price", + "author_inst": "Institute for Systems Biology" + }, + { + "author_name": "Naeha Subramanian", + "author_inst": "Institute for Systems Biology" + }, + { + "author_name": "Jennifer Hadlock", + "author_inst": "Institute for Systems Biology" + }, + { + "author_name": "Andrew T Magis", + "author_inst": "Institute for Systems Biology" + }, + { + "author_name": "Antoni Ribas", + "author_inst": "UCLA" + }, + { + "author_name": "Lewis L Lanier", + "author_inst": "UCSF" + }, + { + "author_name": "Scott D Boyd", + "author_inst": "Stanford University" + }, + { + "author_name": "Jeffery A Bluestone", + "author_inst": "UCSF" + }, + { + "author_name": "Leroy Hood", + "author_inst": "Institute for Systems Biology" + }, + { + "author_name": "Raphael Gottardo", + "author_inst": "Fred Hutch Cancer Research Center" + }, + { + "author_name": "Philip D Greenberg", + "author_inst": "Fred Hutch Cancer Research Center" + }, + { + "author_name": "Mark M Davis", + "author_inst": "Stanford University" + }, + { + "author_name": "Jason D Goldman", + "author_inst": "Swedish Medical Center" + }, + { + "author_name": "James R Heath", + "author_inst": "Institute for Systems Biology" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -857720,59 +857184,23 @@ "category": "psychiatry and clinical psychology" }, { - "rel_doi": "10.1101/2021.03.18.21253443", - "rel_title": "Intensity of COVID-19 in care homes following Hospital Discharge in the early stages of the UK epidemic", + "rel_doi": "10.1101/2021.03.17.21253728", + "rel_title": "Learning from the Experiences of COVID-19 Survivors: A Descriptive Study", "rel_date": "2021-03-20", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.18.21253443", - "rel_abs": "BackgroundA defining feature of the COVID-19 pandemic in many countries was the tragic extent to which care home residents were affected, and the difficulty preventing introduction and subsequent spread of infection. Management of risk in care homes requires good evidence on the most important transmission pathways. One hypothesised route at the start of the pandemic, prior to widespread testing, was transfer of patients from hospitals, which were experiencing high levels of nosocomial events.\n\nMethodsWe tested the hypothesis that hospital discharge events increased the intensity of care home cases using a national individually linked health record cohort in Wales, UK. We monitored 186,772 hospital discharge events over the period March to July 2020, tracking individuals to 923 care homes and recording the daily case rate in the homes populated by 15,772 residents. We estimated the risk of an increase in cases rates following exposure to a hospital discharge using multi-level hierarchical logistic regression, and a novel stochastic Hawkes process outbreak model.\n\nFindingsIn regression analysis, after adjusting for care home size, we found no significant association between hospital discharge and subsequent increases in care home case numbers (odds ratio: 0.99, 95% CI 0.82, 1.90). Risk factors for increased cases included care home size, care home resident density, and provision of nursing care. Using our outbreak model, we found a significant effect of hospital discharge on the subsequent intensity of cases. However, the effect was small, and considerably less than the effect of care home size, suggesting the highest risk of introduction came from interaction with the community. We estimated approximately 1.8% of hospital discharged patients may have been infected.\n\nInterpretationThere is growing evidence in the UK that the risk of transfer of COVID-19 from the high-risk hospital setting to the high-risk care home setting during the early stages of the pandemic was relatively small. Although access to testing was limited to initial symptomatic cases in each care home at this time, our results suggest that reduced numbers of discharges, selection of patients, and action taken within care homes following transfer all may have contributed to mitigation. The precise key transmission routes from the community remain to be quantified.", - "rel_num_authors": 10, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.17.21253728", + "rel_abs": "BackgroundThere are still many unanswered questions about the novel coronavirus, however, a largely underutilized source of knowledge are the millions of people who have recovered after contracting the virus. This includes majority of undocumented cases of the COVID-19 which are classified as mild or moderate and received little to no clinical care during the course of illness.\n\nObjectiveTo document and glean insights from the experiences of persons with first-hand experience with coronavirus, especially the so-called mild to moderate cases that self-resolved in isolation.\n\nMethodsThis online-based survey study called C19 Insider Scoop recruited adult participants that are 18-years or older who reside in the United States and tested positive for COVID-19 or antibodies. Participants were recruited through various methods including online support groups for COVID-19 survivors, advertisement in local news outlets, and advertisement through professional and other networks. The main outcomes measured include knowledge on contraction/transmission of the virus, symptoms, and personal experiences on road to recovery.\n\nResultsA total of 72 participants (53 females/19 males, ages 18 - 73 yrs. old, mean = 41-yrs.) from 22 U.S. states participated in this study. We found that the top known source of how people contracted the COVID-19 virus was through a family or household member (n=26 or 35%). This was followed by essential workers contracting the virus through the workplace (n=13 or 18%).\n\nParticipants reported up to 27 less-documented symptoms that they experienced during their illness such as brain/memory fog, palpitations, ear pain/discomfort and neurological problems. In addition, 47 out of 72 participants (65%) reported that their symptoms lasted longer than the commonly cited 2-weeks even for mild cases of COVID-19. In our study, the mean recovery time was 4.5-weeks, and exactly one-half of survivors (50%) still experienced lingering symptoms of COVID-19 after an average of 65-days following illness onset. Additionally, 37 participants (51%) reported that they experienced stigma associated with having COVID-19.\n\nConclusionThis study presents preliminary findings which suggests that emphasis on family/household spread of COVID-19 may be lacking and there is a general underestimation of the recovery time even for mild cases of the virus. Although a larger study is needed to validate these results, it is important to note that as more people experience COVID-19, insights from prior survivors can enable a more informed public, pave the way for others who may be affected, and guide further research.", + "rel_num_authors": 1, "rel_authors": [ { - "author_name": "Joe Hollinghurst", - "author_inst": "Swansea University" - }, - { - "author_name": "Laura North", - "author_inst": "Swansea University" - }, - { - "author_name": "Chris Emmerson", - "author_inst": "Public Health Wales" - }, - { - "author_name": "Ashley Akbari", - "author_inst": "Swansea University" - }, - { - "author_name": "Fatemeh Torabi", - "author_inst": "Swansea University" - }, - { - "author_name": "Ronan A Lyons", - "author_inst": "Swansea University" - }, - { - "author_name": "Alan G Hawkes", - "author_inst": "Swansea University" - }, - { - "author_name": "Ed Bennett", - "author_inst": "Swansea University" - }, - { - "author_name": "Mike B Gravenor", - "author_inst": "Swansea University" - }, - { - "author_name": "Richard Fry", - "author_inst": "Swansea University" + "author_name": "Temiloluwa Prioleau", + "author_inst": "Dartmouth" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "health informatics" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2021.03.17.20200246", @@ -859618,75 +859046,91 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.03.15.21253615", - "rel_title": "Safety of administering biologics to IBD patients at an outpatient infusion center In New York City during the COVID-19 pandemic: Sars-CoV-2 seroprevalence and clinical and social characteristics", + "rel_doi": "10.1101/2021.03.15.21253625", + "rel_title": "A proteome-wide genetic investigation identifies several SARS-CoV-2-exploited host targets of clinical relevance", "rel_date": "2021-03-17", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.15.21253615", - "rel_abs": "Patients with immune-mediated inflammatory diseases (IMIDs) and acquired and genetic immunodeficiencies receiving therapeutic infusions are considered high risk for SARS-CoV-2 infection. However, the seroprevalance in this group and the safety of routine administrations at outpatient infusion centers are unknown. To determine the infection rate and clinical-social factors related to SARS-CoV-2 in asymptomatic patients with IMIDs and immunodeficiencies receiving routine non-cancer therapeutic infusions, we conducted a seroprevalence study at our outpatient infusion center. We report the first prospective SARS-CoV-2 sero-surveillance of 444 IBD/IMID, immunodeficiency, and immune competent patients at an outpatient infusion center in the U.S. showing lower seroprevalence in patients compared with the general population and provide clinical and social characteristics associated with seroprevalence in this group. These data suggest that patients can safely continue infusions at outpatient centers.", - "rel_num_authors": 14, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.15.21253625", + "rel_abs": "The virus SARS-CoV-2 can exploit biological vulnerabilities in susceptible hosts that predispose to development of severe COVID-19. Previous reports have identified several host proteins related to the interferon response (e.g. OAS1), interleukin-6 signalling (IL-6R), and the coagulation cascade (linked via ABO) that were associated with risk of COVID-19. In the present study, we performed proteome-wide genetic colocalisation tests leveraging publicly available protein and COVID-19 datasets, to identify additional proteins that may contribute to COVID-19 risk. Our analytic approach identified several known targets (e.g. ABO, OAS1), but also nominated new proteins such as soluble FAS (colocalisation probability > 0.9, p = 1 x 10-4), implicating FAS-mediated apoptosis as a potential target for COVID-19 risk. We also undertook polygenic (pan) and cis-Mendelian randomisation analyses that showed consistent associations of genetically predicted ABO protein with several COVID-19 phenotypes. The ABO signal was associated with plasma concentrations of several proteins, with the strongest association observed with CD209 in several proteomic datasets. We demonstrated experimentally that CD209 directly interacts with the spike protein of SARS-CoV-2, suggesting a mechanism that could explain the ABO association with COVID-19. Our work provides a prioritised list of host targets potentially exploited by SARS-CoV-2 and is a precursor for further research on CD209 and FAS as therapeutically tractable targets for COVID-19.", + "rel_num_authors": 18, "rel_authors": [ { - "author_name": "Serre-Yu Wong", - "author_inst": "Icahn School of Medicine at Mount Sinai" + "author_name": "Mohd Anisul Karim", + "author_inst": "Wellcome Trust Sanger Institute" }, { - "author_name": "Stephanie Gold", - "author_inst": "Icahn School of Medicine at Mount Sinai" + "author_name": "Jarrod Shilts", + "author_inst": "Wellcome Trust Sanger Institute" }, { - "author_name": "Emma K. Accorsi", - "author_inst": "Harvard T.H. Chan School of Public Health" + "author_name": "Jeremy Schwartzentruber", + "author_inst": "Wellcome Trust Sanger Institute" }, { - "author_name": "Tori L. Cowger", - "author_inst": "Harvard T.H. Chan School of Public Health" + "author_name": "James Hayhurst", + "author_inst": "European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI)" }, { - "author_name": "Dean Wiseman", - "author_inst": "Icahn School of Medicine at Mount Sinai" + "author_name": "Annalisa Buniello", + "author_inst": "European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI)" }, { - "author_name": "Reema Navalurkar", - "author_inst": "Icahn School of Medicine at Mount Sinai" + "author_name": "Elmutaz Shaikho Elhaj Mohammed", + "author_inst": "Bristol-Myers Squibb" }, { - "author_name": "Rebekah Dixon", - "author_inst": "Icahn School of Medicine at Mount Sinai" + "author_name": "Jie Zheng", + "author_inst": "University of Bristol" }, { - "author_name": "Drew S. Helmus", - "author_inst": "Icahn School of Medicine at Mount Sinai" + "author_name": "Michael V. Holmes", + "author_inst": "University of Oxford" }, { - "author_name": "- CiTI Study Group", - "author_inst": "" + "author_name": "David Ochoa", + "author_inst": "European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI)" }, { - "author_name": "Adolfo Firpo-Betancourt", - "author_inst": "Icahn School of Medicine at Mount Sinai" + "author_name": "Miguel Carmona", + "author_inst": "European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI)" }, { - "author_name": "Damodara Rao Mendu", - "author_inst": "Icahn School of Medicine at Mount Sinai" + "author_name": "Joseph Maranville", + "author_inst": "Bristol-Myers Squibb" }, { - "author_name": "Susan Zolla-Pazner", - "author_inst": "Icahn School of Medicine at Mount Sinai" + "author_name": "Tom R. Gaunt", + "author_inst": "University of Bristol" }, { - "author_name": "Ken Cadwell", - "author_inst": "New York University School of Medicine" + "author_name": "Valur Emilsson", + "author_inst": "Icelandic Heart Association" }, { - "author_name": "Jean-Frederic Colombel", - "author_inst": "Icahn School of Medicine at Mount Sinai" + "author_name": "Vilmundur Gudnason", + "author_inst": "Icelandic Heart Association" + }, + { + "author_name": "Ellen M. McDonagh", + "author_inst": "European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI)" + }, + { + "author_name": "Gavin J. Wright", + "author_inst": "Wellcome Trust Sanger Institute" + }, + { + "author_name": "Maya Ghoussaini", + "author_inst": "Wellcome Trust Sanger Institute" + }, + { + "author_name": "Ian Dunham", + "author_inst": "European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI)" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", - "category": "gastroenterology" + "category": "pharmacology and therapeutics" }, { "rel_doi": "10.1101/2021.03.15.21253509", @@ -861304,35 +860748,55 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.03.17.21253775", - "rel_title": "Estimating the increased transmissibility of the B.1.1.7 strain over previously circulating strains in England using fractions of GISAID sequences and the distribution of serial intervals", + "rel_doi": "10.1101/2021.03.11.21253409", + "rel_title": "Metagenomic sequencing of municipal wastewater provides a near-complete SARS-CoV-2 genome sequence identified as the B.1.1.7 variant of concern from a Canadian municipality concurrent with an outbreak", "rel_date": "2021-03-17", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.17.21253775", - "rel_abs": "The B.1.1.7 strain, also referred to as Alpha variant, is a variant strain of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The Alpha variant is considered to possess higher transmissibility compared to the strains previously circulating in England. This paper proposes a new method to estimate the selective advantage of a mutant strain over another strain using the time course of strain frequencies and the distribution of the serial interval of infections. This method allows the instantaneous reproduction numbers of infections to vary over calendar time. The proposed method also assumes that the selective advantage of a mutant strain over previously circulating strains is constant. Applying the method to SARS-CoV-2 sequence data from England, the instantaneous reproduction number of the B.1.1.7 strain was estimated to be 26.6-45.9% higher than previously circulating strains in England. This result indicates that control measures should be strengthened by 26.6-45.9% when the B.1.1.7 strain is newly introduced to a country where viruses with similar transmissibility to the preexisting strain in England are predominant.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.11.21253409", + "rel_abs": "Laboratory-based wastewater surveillance for SARS-CoV-2, the causative agent of the ongoing COVID-19 pandemic, can be conducted using RT-qPCR-based screening of municipal wastewater samples. Although it provides rapid viral detection and can inform SARS-CoV-2 abundance in wastewater, this approach lacks the resolution required for viral genotyping and does not support tracking of viral genome evolution. The recent emergence of several variants of concern, a result of mutations across the genome including the accrual of important mutations within the viral spike glycoprotein, has highlighted the need for a method capable of detecting the cohort of mutations associated with these and newly emerging genotypes. Here we provide an innovative methodology for the recovery of a near-complete SARS-CoV-2 sequence from a wastewater sample collected from across Canadian municipalities including one that experienced a significant outbreak attributable to the SARS-CoV-2 B.1.1.7 variant of concern. Our results demonstrate that a combined interrogation of genome consensus-level sequences and alternative alleles enables the identification of a SARS-CoV-2 variant of concern and the detection of a new allele within a viral accessory gene that may be representative of a recently evolved B.1.1.7 sublineage.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Chayada Piantham", - "author_inst": "Hokkaido University" + "author_name": "Chrystal Landgraff", + "author_inst": "Public Health Agency of Canada" }, { - "author_name": "Natalie M Linton", - "author_inst": "Graduate School of Medicine, Hokkaido University" + "author_name": "Lu Ya Ruth Wang", + "author_inst": "Division of Enteric Diseases, National Microbiology Laboratory, Public Health Agency of Canada" }, { - "author_name": "Hiroshi Nishiura", - "author_inst": "Graduate School of Medicine, Kyoto University" + "author_name": "Cody Buchanan", + "author_inst": "Division of Enteric Diseases, National Microbiology Laboratory, Public Health Agency of Canada" }, { - "author_name": "Kimihito Ito", - "author_inst": "Hokkaido University" + "author_name": "Matthew Wells", + "author_inst": "Division of Enteric Diseases, National Microbiology Laboratory, Public Health Agency of Canada" + }, + { + "author_name": "Justin Schonfeld", + "author_inst": "Division of Enteric Diseases, National Microbiology Laboratory, Public Health Agency of Canada" + }, + { + "author_name": "Kyrylo Bessonov", + "author_inst": "Division of Enteric Diseases, National Microbiology Laboratory, Public Health Agency of Canada" + }, + { + "author_name": "Jennifer Ali", + "author_inst": "Division of Enteric Diseases, National Microbiology Laboratory, Public Health Agency of Canada" + }, + { + "author_name": "Erin Robert", + "author_inst": "Division of Enteric Diseases, National Microbiology Laboratory, Public Health Agency of Canada" + }, + { + "author_name": "Celine Nadon", + "author_inst": "Division of Enteric Diseases, National Microbiology Laboratory, Public Health Agency of Canada and Department of Medical Microbiology and Infectious Diseases, M" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "public and global health" }, { "rel_doi": "10.1101/2021.03.05.21251413", @@ -863550,59 +863014,31 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2021.03.15.435440", - "rel_title": "Rationally designed immunogens enable immune focusing to the SARS-CoV-2 receptor binding motif", - "rel_date": "2021-03-16", + "rel_doi": "10.1101/2021.03.14.435337", + "rel_title": "Shed the light on virus: virucidal effects of 405 nm visible light on SARS-CoV-2 and influenza A virus.", + "rel_date": "2021-03-15", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.03.15.435440", - "rel_abs": "Eliciting antibodies to surface-exposed viral glycoproteins can lead to protective responses that ultimately control and prevent future infections. Targeting functionally conserved epitopes may help reduce the likelihood of viral escape and aid in preventing the spread of related viruses with pandemic potential. One such functionally conserved viral epitope is the site to which a receptor must bind to facilitate viral entry. Here, we leveraged rational immunogen design strategies to focus humoral responses to the receptor binding motif (RBM) on the SARS-CoV-2 spike. Using glycan engineering and epitope scaffolding, we find an improved targeting of the serum response to the RBM in context of SARS-CoV-2 spike imprinting. Furthermore, we observed a robust SARS-CoV-2-neutralizing serum response with increased potency against related sarbecoviruses, SARS-CoV, WIV1-CoV, RaTG13-CoV, and SHC014-CoV. Thus, RBM focusing is a promising strategy to elicit breadth across emerging sarbecoviruses and represents an adaptable design approach for targeting conserved epitopes on other viral glycoproteins.\n\nOne Sentence SummarySARS-CoV-2 immune focusing with engineered immunogens", - "rel_num_authors": 10, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.03.14.435337", + "rel_abs": "Germicidal potential of specific wavelengths within the electromagnetic spectrum is an area of growing interest. While ultra-violet (UV) based technologies have shown satisfactory virucidal potential, the photo-toxicity in humans coupled with UV associated polymer degradation limit its use in occupied spaces. Alternatively, longer wavelengths with less irradiation energy such as visible light (405 nm) have largely been explored in the context of bactericidal and fungicidal applications. Such studies indicated that 405 nm mediated inactivation is caused by the absorbance of porphyrins within the organism creating reactive oxygen species which result in free radical damage to its DNA and disruption of cellular functions. The virucidal potential of visible-light based technologies has been largely unexplored and speculated to be ineffective given the lack of porphyrins in viruses. The current study demonstrated increased susceptibility of lipid-enveloped respiratory pathogens of importance such as SARS-CoV-2 (causative agent of COVID-19) as well as the influenza A virus to 405nm, visible light in the absence of exogenous photosensitizers indicating a potential porphyrin-independent alternative mechanism of visible light mediated viral inactivation. These results were obtained using less than expected irradiance levels which are generally safe for humans and commercially achievable. Our results support further exploration of the use of visible light technology for the application of continuous decontamination in occupied areas within hospitals and/or infectious disease laboratories, specifically for the inactivation of respiratory pathogens such as SARS-CoV-2 and Influenza A.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Blake M. Hauser", - "author_inst": "Ragon Institute of MGH, MIT and Harvard" - }, - { - "author_name": "Maya Sangesland", - "author_inst": "Ragon Institute of MGH, MIT and Harvard" + "author_name": "Clifford J Yahnke", + "author_inst": "Kenall Manufacturing" }, { - "author_name": "Kerri J. St. Denis", - "author_inst": "Ragon Institute of MGH, MIT and Harvard" - }, - { - "author_name": "Ian W. Windsor", - "author_inst": "Ragon Institute of MGH, MIT and Harvard" - }, - { - "author_name": "Jared Feldman", - "author_inst": "Ragon Institute of MGH, MIT and Harvard" - }, - { - "author_name": "Evan C. Lam", - "author_inst": "Ragon Institute of MGH, MIT and Harvard" - }, - { - "author_name": "Ty Kannegieter", - "author_inst": "Ragon Institute of MGH, MIT and Harvard" - }, - { - "author_name": "Alejandro B. Balazs", - "author_inst": "Ragon Institute of MGH, MIT and Harvard" - }, - { - "author_name": "Daniel Lingwood", - "author_inst": "Ragon Institute of MGH, MIT and Harvard" + "author_name": "Raveen J Rathnasinghe", + "author_inst": "Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Aaron G. Schmidt", - "author_inst": "Ragon Institute of MGH, MIT and Harvard; Department of Microbiology, Harvard Medical School" + "author_name": "Adolfo Garcia-Sastre", + "author_inst": "Icahn School of Medicine at Mount Sinai" } ], "version": "1", "license": "cc_no", "type": "new results", - "category": "immunology" + "category": "microbiology" }, { "rel_doi": "10.1101/2021.03.13.21253485", @@ -866000,61 +865436,37 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.03.12.21253410", - "rel_title": "Rapid review of social contact patterns during the COVID-19 pandemic", + "rel_doi": "10.1101/2021.03.12.21253470", + "rel_title": "The efficacy and safety of remdesivir in the treatment of patients with COVID-19: a systematic review and meta-analysis", "rel_date": "2021-03-13", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.12.21253410", - "rel_abs": "BackgroundPhysical distancing measures aim to reduce person-to-person contact, a key driver of transmission of respiratory infections such as SARS-CoV-2. In response to unprecedented restrictions on human contact during the COVID-19 pandemic, a number of studies measured social contact patterns under the implementation of physical distancing measures. This rapid review aims to synthesize empirical data on the changing social contact patterns during the COVID-19 pandemic.\n\nMethodWe conducted a systematic review using PubMed, Medline, Embase and Google Scholar following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. We descriptively compared the distribution of contacts observed during the pandemic to pre-COVID data across countries to explore changes in contact patterns during physical distancing measures.\n\nResultsWe identified 12 studies that reported social contact patterns during the COVID-19 pandemic. The majority of studies (11/12) collected data during the initial mitigation period in the spring of 2020 marked by government-declared lockdowns and the most stringent physical distancing measures. Some studies collected additional data after relaxation of initial mitigation. Most study settings reported a mean of between 2-5 contacts per person per day, a substantial reduction compared to pre-COVID rates which ranged from 7-26 contacts per day in similar settings. This reduction was particularly pronounced for contacts outside of the home. Consequently, levels of assortative mixing by age substantially declined. After relaxation of initial mitigation, mean contact rates subsequently increased but did not return to pre-COVID levels. Increases in contacts post-relaxation were driven by working-age adults.\n\nConclusionInformation on changes in contact patterns during physical distancing measures can guide more realistic representations of contact patterns in mathematical models for SARS-CoV-2 transmission.", - "rel_num_authors": 11, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.12.21253470", + "rel_abs": "BackgroundThe global total of COVID-19 cases will reach 20 million this week, with 750,000 deaths. It has spread to more than 200 countries and regions around the world. At present, the global pandemic continues to rise and continues to spread worldwide. It is necessary to explore the effective and safe treatment of COVID-19 as soon as possible. Remdesiviras was an antiviral agent with therapeutic potential, but it was still controversial.\n\nObjectiveThrough systematic review and meta-analysis, to evaluate the effect and safety of remdesivir in the treatment of patients with COVID-19, and will provide a reliable reference for the treatment of COVID-19.\n\nMethodsWe used the following search string: \"COVID-19\" [Mesh], \"remdesivir\" [Mesh], \"randomized controlled trial\" [Mesh]. We used the Medical Subject Heading (MeSH) terms and corresponding keywords to make the search strategy. We searched six databases, PubMed, EMBASE, Cochrane Library, Web of Science, clinical trials.gov and chictr.org.cn. Data analyses were conducted by using the software Review Manager 5.3 and STATA version 14.0.\n\nResultsOur systematic search identified 5 meta-analyses of RCTs, including 1782 patients with COVID-19.The clinical improvement of remdesivir in the treatment of COVID-19 was superior to the placebo-controlled group (relative risk (RR) =1.17, 95% confidence interval (CI)=1.07-1.29, p=0.0009). The following are the Single-Arm Study, Meta-analysis results. The pooled prevalence of clinical improvement significant findings was 62% (95% CI = 59-65%, p=0.00), during treatment of COVID-19 with remdesivir. The incidence rates of Acute kidney injury, Hepatic enzyme increased, Any serious adverse event were 5% (95%CI=3-7%, p=0.00), 11%(95%CI=5-16%, p=0.00), 22%(95%CI=18-27%, p=0.00), respectively, and the mortality was 13%(95%CI=8-19%, p=0.00), during treatment of COVID-19 with remdesivir.\n\nConclusionThis analysis confirms that remdesivir is effective in the clinical improvement of COVID-19 patients, and the rate of clinical improvement was 62%. In addition, adverse events and mortality should also be paid attention to. Future research should aim that more large-scale studies were needed to confirm the results, to further elucidate the underlying mechanisms.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Carol Y. Liu", - "author_inst": "Department of Epidemiology, Emory University Rollins School of Public Health, Atlanta, GA 30322, USA" - }, - { - "author_name": "Juliette Berlin", - "author_inst": "Department of Epidemiology, Emory University Rollins School of Public Health, Atlanta, GA 30322, USA" - }, - { - "author_name": "Moses C. Kiti", - "author_inst": "Department of Epidemiology, Emory University Rollins School of Public Health, Atlanta, GA 30322, USA" - }, - { - "author_name": "Emanuele Del Fava", - "author_inst": "Max Planck Institute for Demographic Research, Rostock, Germany" - }, - { - "author_name": "Andr\u00e9 Grow", - "author_inst": "Max Planck Institute for Demographic Research, Rostock, Germany" - }, - { - "author_name": "Emilio Zagheni", - "author_inst": "Max Planck Institute for Demographic Research, Rostock, Germany" - }, - { - "author_name": "Alessia Melegaro", - "author_inst": "Centre for Research on Social Dynamics and Public Policy & Covid Crisis Lab, Bocconi University, 20136 Milan, Italy" + "author_name": "Lixiang Lou Sr.", + "author_inst": "The Graduate School of Qinghai University, Xining, China" }, { - "author_name": "Samuel M. Jenness", - "author_inst": "Department of Epidemiology, Emory University Rollins School of Public Health, Atlanta, GA 30322, USA" + "author_name": "Hui Zhang Sr.", + "author_inst": "The Graduate School of Qinghai University, Xining, China" }, { - "author_name": "Saad Omer", - "author_inst": "Yale Institute of Global Health, Yale University, Connecticut, USA" + "author_name": "Zeqing Li Sr.", + "author_inst": "Affiliated Hospital of Qinghai University, Xining, China" }, { - "author_name": "Benjamin Lopman", - "author_inst": "Department of Epidemiology, Emory University Rollins School of Public Health, Atlanta, GA 30322, USA" + "author_name": "Baoming Tang Sr.", + "author_inst": "Affiliated Hospital of Qinghai University, Xining, China" }, { - "author_name": "Kristin Nelson", - "author_inst": "Department of Epidemiology, Emory University Rollins School of Public Health, Atlanta, GA 30322, USA" + "author_name": "Zhaowei Li Sr.", + "author_inst": "Affiliated Hospital of Qinghai University" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -867982,55 +867394,127 @@ "category": "transplantation" }, { - "rel_doi": "10.1101/2021.03.09.434696", - "rel_title": "Contribution of SARS-CoV-2 accessory proteins to viral pathogenicity in K18 hACE2 transgenic mice", + "rel_doi": "10.1101/2021.03.09.21251364", + "rel_title": "Optimization of magnetic bead-based nucleic acid extraction for SARS-CoV-2 testing using readily available reagents", "rel_date": "2021-03-12", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.03.09.434696", - "rel_abs": "Severe Acute Respiratory Syndrome coronavirus 2 (SARS-CoV-2) is the viral pathogen responsible for the current coronavirus disease 2019 (COVID-19) pandemic. To date, it is estimated that over 113 million individuals have been infected with SARS-CoV-2 and over 2.5 million human deaths have been recorded worldwide. Currently, three vaccines have been approved by the Food and Drug Administration for emergency use only. However much of the pathogenesis observed during SARS-CoV-2 infection remains elusive. To gain insight into the contribution of individual accessory open reading frame (ORF) proteins in SARS-CoV-2 pathogenesis, we used our recently described reverse genetics system approach to successfully engineer recombinant (r)SARS-CoV-2, where we individually removed viral 3a, 6, 7a, 7b, and 8 ORF proteins, and characterized these recombinant viruses in vitro and in vivo. Our results indicate differences in plaque morphology, with ORF deficient ({Delta}ORF) viruses producing smaller plaques than those of the wild-type (rSARS-CoV-2/WT). However, growth kinetics of {Delta}ORF viruses were like those of rSARS-CoV-2/WT. Interestingly, infection of K18 human angiotensin converting enzyme 2 (hACE2) transgenic mice with the {Delta}ORF rSARS-CoV-2 identified ORF3a and ORF6 as the major contributors of viral pathogenesis, while {Delta}ORF7a, {Delta}ORF7b and {Delta}ORF8 rSARS-CoV-2 induced comparable pathology to rSARS-CoV-2/WT. This study demonstrates the robustness of our reverse genetics system to generate rSARS-CoV-2 and the major role for ORF3a and ORF6 in viral pathogenesis, providing important information for the generation of attenuated forms of SARS-CoV-2 for their implementation as live-attenuated vaccines for the treatment of SARS-CoV-2 infection and associated COVID-19.\n\nIMPORTANCEDespite great efforts put forward worldwide to combat the current coronavirus disease 2019 (COVID-19) pandemic, Severe Acute Respiratory Syndrome coronavirus 2 (SARS-CoV-2) continues to be a human health and socioeconomic threat. Insights into the pathogenesis of SARS-CoV-2 and contribution of viral proteins to disease outcome remains elusive. Our study aims to determine the contribution of SARS-CoV-2 accessory open reading frame (ORF) proteins in viral pathogenesis and disease outcome, and develop a synergistic platform combining our robust reverse genetics system to generate recombinant (r)SARS-CoV-2 with a validated rodent model of infection and disease. We demonstrated that SARS-CoV-2 ORF3a and ORF6 contribute to lung pathology and ultimately disease outcome in K18 hACE2 transgenic mice, while ORF7a, ORF7b, and ORF8 have little impact on disease outcome. Moreover, our combinatory platform serves as the foundation to generate attenuated forms of the virus to develop live-attenuated vaccines for the treatment of SARS-CoV-2.", - "rel_num_authors": 9, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.09.21251364", + "rel_abs": "The COVID-19 pandemic has highlighted the need for generic reagents and flexible systems in diagnostic testing. Magnetic bead-based nucleic acid extraction protocols using 96-well plates on open liquid handlers are readily amenable to meet this need. Here, one such approach is rigorously optimized to minimize cross-well contamination while maintaining sensitivity.\n\nArticle SummaryA scalable, non-proprietary, magnetic bead-based automated nucleic acid extraction protocol optimised for minimum cross-well contamination", + "rel_num_authors": 27, "rel_authors": [ { - "author_name": "Jesus Silvas", - "author_inst": "Texas Biomedical Research Institute" + "author_name": "Simon Haile", + "author_inst": "Canada's Michael Smith Genome Sciences Centre" }, { - "author_name": "Desarey Morales Vasquez", - "author_inst": "Texas Biomedical Research Institute" + "author_name": "Aidan M Nikiforuk", + "author_inst": "School of Population and Public Health, University of British Columbia, Vancouver, British Columbia, Canada" }, { - "author_name": "Jun-Gyu Park", - "author_inst": "Texas Biomedical Research Institute" + "author_name": "Pawan K Pandoh", + "author_inst": "Canada's Michael Smith Genome Sciences Centre" }, { - "author_name": "Kevin Chiem", - "author_inst": "Texas Biomedical Research Institute" + "author_name": "David D.W. Twa", + "author_inst": "BC Cancer Research Centre, BC Cancer, Vancouver, British Columbia, Canada" }, { - "author_name": "Jordi Torrelles", - "author_inst": "Texas Biomedical Research Institute" + "author_name": "Duane E Smailus", + "author_inst": "Canada's Michael Smith Genome Sciences Centre" }, { - "author_name": "Roy Neal Platt", - "author_inst": "Texas Biomedical Research Instititue" + "author_name": "Jason Nguyen", + "author_inst": "British Columbia Centre for Disease Control Public Health Laboratory, Vancouver, Canada" }, { - "author_name": "Tim Anderson", - "author_inst": "Texas Biomedical Research Institute" + "author_name": "Stephen Pleasance", + "author_inst": "Canada's Michael Smith Genome Sciences Centre" }, { - "author_name": "Chengjin Ye", - "author_inst": "Texas Biomedical Research Institute" + "author_name": "Angus Wong", + "author_inst": "Canada's Michael Smith Genome Sciences Centre" }, { - "author_name": "Luis Mart\u00ednez-Sobrido", - "author_inst": "Texas Biomedical Research Institute" + "author_name": "Yongjun Zhao", + "author_inst": "Canada's Michael Smith Genome Sciences Centre" + }, + { + "author_name": "Diane Eisler", + "author_inst": "British Columbia Centre for Disease Control Public Health Laboratory, Vancouver, Canada" + }, + { + "author_name": "Michelle Moksa", + "author_inst": "Department of Microbiology and Immunology, Michael Smith Laboratories, University of British Columbia, Vancouver, British Columbia, Canada" + }, + { + "author_name": "Qi Cao", + "author_inst": "Department of Microbiology and Immunology, Michael Smith Laboratories, University of British Columbia, Vancouver, British Columbia, Canada" + }, + { + "author_name": "Marcus Wong", + "author_inst": "Department of Microbiology and Immunology, Michael Smith Laboratories, University of British Columbia, Vancouver, British Columbia, Canada" + }, + { + "author_name": "Edmund Su", + "author_inst": "Department of Microbiology and Immunology, Michael Smith Laboratories, University of British Columbia, Vancouver, British Columbia, Canada" + }, + { + "author_name": "Martin Krzywinski", + "author_inst": "Canada's Michael Smith Genome Sciences Centre" + }, + { + "author_name": "Jessica M T Nelson", + "author_inst": "Canada's Michael Smith Genome Sciences Centre" + }, + { + "author_name": "Andrew J Mungall", + "author_inst": "Canada's Michael Smith Genome Sciences Centre" + }, + { + "author_name": "Frankie Tsang", + "author_inst": "British Columbia Centre for Disease Control Public Health Laboratory, Vancouver, Canada" + }, + { + "author_name": "Leah M Prentice", + "author_inst": "Provincial Laboratory Medicine Services, Provincial Health Services Authority, Vancouver, British Columbia, Canada" + }, + { + "author_name": "Agatha Jassem", + "author_inst": "British Columbia Centre for Disease Control Public Health Laboratory, Vancouver, Canada" + }, + { + "author_name": "Amee R Manges", + "author_inst": "School of Population and Public Health, University of British Columbia, Vancouver, British Columbia, Canada" + }, + { + "author_name": "Steven J.M Jones", + "author_inst": "Canada's Michael Smith Genome Sciences Centre" + }, + { + "author_name": "Robin J Coope", + "author_inst": "Canada's Michael Smith Genome Sciences Centre" + }, + { + "author_name": "Natalie Prystajecky", + "author_inst": "British Columbia Centre for Disease Control Public Health Laboratory, Vancouver, Canada" + }, + { + "author_name": "Marco A Marra", + "author_inst": "Canada's Michael Smith Genome Sciences Centre" + }, + { + "author_name": "Mel Krajden", + "author_inst": "British Columbia Centre for Disease Control Public Health Laboratory, Vancouver, Canada" + }, + { + "author_name": "Martin Hirst", + "author_inst": "Canada's Michael Smith Genome Sciences Centre" } ], "version": "1", - "license": "", - "type": "new results", - "category": "microbiology" + "license": "cc_by", + "type": "PUBLISHAHEADOFPRINT", + "category": "genetic and genomic medicine" }, { "rel_doi": "10.1101/2021.03.08.21253150", @@ -869804,71 +869288,39 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.03.10.21253331", - "rel_title": "Disulfiram associated with lower risk of Covid-19: a retrospective cohort study", + "rel_doi": "10.1101/2021.03.10.21253292", + "rel_title": "Repeated Testing Necessary: Assessing Negative Predictive Value of SARS-CoV-2 qPCR in a Population of Young Adults", "rel_date": "2021-03-12", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.10.21253331", - "rel_abs": "In the global COVID-19 pandemic, there is a substantial need for effective, low-cost therapeutics. We investigated the potential effects of disulfiram on the incidence and outcomes of COVID-19 in an observational study in a large database of US Veterans Administration clinical records, the VA Corporate Data Warehouse (CDW). The study is motivated by the unique properties of disulfiram, which has been used as an anti-alcoholism drug since 1948, is non-toxic, easy to manufacture and inexpensive. Disulfiram reduces hyperinflammation in mammalian cells by inhibition of the gasdermin D pore. In a mouse model of sepsis, disulfiram reduced inflammatory cytokines and mortality. Disulfiram also is a low micromolar inhibitor of the Mpro and PLpro viral proteases of SARS-CoV-2.\n\nTo investigate the potential effects of disulfiram on the incidence and severity of COVID-19, we carried out an epidemiological study in the CDW. The VA dataset used has 944,127 patients tested for SARS-Cov-2, 167,327 with a positive test, and 2,233 on disulfiram, of which 188 had a positive SARS-Cov-2 test. A multivariable Cox regression adjusted for age, gender, race/ethnicity, region, a diagnosis of alcohol use disorders, and Charlson comorbidity score revealed a reduced incidence of COVID-19 with disulfiram use with a hazard ratio of 0.66 and 95% confidence interval of 0.57 to 0.76 (P < 0.001). There were no deaths among the 188 SARS-Cov-2 positive patients treated with disulfiram. The expected number of deaths would have been 5-6 according to the 3% death rate among the untreated (P-value 0.03).\n\nOur finding of a lower hazard ratio and less severe outcomes for COVID-19 in patients treated with disulfiram compared to those not treated is a statistical association and does not prove any causative effect of disulfiram. However, the results of this study suggest that there is a pharmacological contribution to the reduced incidence and severity of COVID-19 with the use of disulfiram. Given the known anti-inflammatory and viral anti-protease effects of disulfiram, it is reasonable and urgent to initiate accelerated clinical trials to assess whether disulfiram reduces SARS-CoV-2 infection, disease severity and death.\n\nSTRUCTURED OUTLINEO_ST_ABSImportanceC_ST_ABSIdentifying already approved medications with well characterized antiviral or anti-inflammatory properties supported by real world evidence as candidates for clinical trials for repurposing is an important strategy to manage the pandemic given the ongoing challenges with producing and administering vaccines, the emergence of more infectious viral mutants and the paucity of approved therapies.\n\nObjectiveTo investigate the potential effects of disulfiram on the incidence and severity of COVID-19.\n\nDesignRetrospective cohort study from February 20, 2020 to February 1, 2021.\n\nSettingVeterans Health Administration. Veterans who had visited a VA primary care provider in the 18 months before their first SARS-CoV-2 test.\n\nParticipants2,233 Veterans with at least one SARS-CoV-2 laboratory (positive or negative) test result on or after February 20, 2020 and at least one pharmacy record for disulfiram on or after February 20, 2019 and 941,894 Veterans without a pharmacy record for disulfiram.\n\nExposureTreatment with disulfiram\n\nMain OutcomePositive test result for SARS-CoV-2\n\nResultsA multivariable Cox regression analysis adjusted for age, gender, race/ethnicity, region, diagnosis of an alcohol use disorder, and Charlson comorbidity score resulted in a reduced hazard of COVID-19 infection with disulfiram use, with a hazard ratio of 0.66 and 95% confidence interval of 0.57 to 0.76 (P < 0.001).\n\nConclusions and RelevanceThe results of this study suggest that disulfiram use contributes to a reduced incidence of COVID-19. Given the known anti-inflammatory and anti-protease effects of disulfiram, its low cost, low side effects, and general availability, it is reasonable and urgent to initiate accelerated clinical trials to assess the effect of disulfiram on infection and the development of advanced disease.", - "rel_num_authors": 13, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.10.21253292", + "rel_abs": "Determining when individuals should be released from quarantine is critical for successfully managing a COVID-19 outbreak and local protocols frequently call for testing during the quarantine period, generally after a reasonable incubation period, which raises a question about the interpretation of test results during the quarantine period. We report the negative predictive value of SARS-CoV-2 qPCR tests based on a retrospective longitudinal analysis of 5349 qPCR tests collected from 1227 US service members infected with COVID-19 aboard the USS Theodore Roosevelt (CVN-71) aircraft carrier. In our retrospective evaluation of recovering qPCR-positive quarantined crew members undergoing repeated testing, the negative predictive value is 80% for tests occurring as late as seven weeks following an initial positive qPCR test result. Repeated qPCR testing is necessary to ensure that a once-infected person is no longer shedding viral RNA. When deciding the stringency of exit criteria, we recommend considering local operational and community risk factors.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Nathanael Fillmore", - "author_inst": "Boston VA Cooperative Studies Program (CSP) Center, VA Boston Healthcare System" - }, - { - "author_name": "Steven Bell", - "author_inst": "Department of Clinical Neurosciences, University of Cambridge, UK" - }, - { - "author_name": "Ciyue Shen", - "author_inst": "Department of Cell Biology, Harvard Medical School and Department of Data Sciences, Dana-Farber Cancer Institute, Boston" - }, - { - "author_name": "Vinh Nguyen", - "author_inst": "Boston VA Cooperative Studies Program (CSP) Center, VA Boston Healthcare System" - }, - { - "author_name": "Jennifer La", - "author_inst": "Boston VA Cooperative Studies Program (CSP) Center, VA Boston Healthcare System" - }, - { - "author_name": "Maureen Dubreuil", - "author_inst": "Section of Rheumatology, Boston University School of Medicine and Rheumatology, VA Boston Healthcare System" - }, - { - "author_name": "Judith Strymish", - "author_inst": "Department of Medicine, Harvard Medical School, Boston and Infection Disease, VA Boston Healthcare System" + "author_name": "Elaine E Thompson", + "author_inst": "The Henry M. Jackson Foundation for the Advancement of Military Medicine" }, { - "author_name": "Mary Brophy", - "author_inst": "Boston VA Cooperative Studies Program (CSP) Center, VA Boston Healthcare System and Section of Hematology and Medical Oncology, Boston University School of Medi" + "author_name": "Joseph H Rosenthal", + "author_inst": "The Henry M. Jackson Foundation for the Advancement of Military Medicine" }, { - "author_name": "Gautam Mehta", - "author_inst": "Institute for Liver and Digestive Health, University College London and Institute of Hepatology, Foundation for Liver Research, London" + "author_name": "James Wren", + "author_inst": "The Henry M. Jackson Foundation for the Advancement of Military Medicine" }, { - "author_name": "Hao Wu", - "author_inst": "Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School and Program in Cellular and Molecular Medicine, Boston Children's Hospital" - }, - { - "author_name": "Judy Lieberman", - "author_inst": "Program in Cellular and Molecular Medicine, Boston Children's Hospital and Department of Pediatrics, Harvard Medical School, Boston" + "author_name": "Erik Seetao", + "author_inst": "The Henry M. Jackson Foundation for the Advancement of Military Medicine" }, { - "author_name": "Nhan Do", - "author_inst": "Boston VA Cooperative Studies Program (CSP) Center, VA Boston Healthcare System and Section of General Internal Medicine, Boston University School of Medicine" - }, - { - "author_name": "Chris Sander", - "author_inst": "MSKCC" + "author_name": "Niels H Olson", + "author_inst": "Uniformed Services University, U.S. Naval Hospital Guam" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc0", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "pathology" }, { "rel_doi": "10.1101/2021.03.10.21252851", @@ -871406,41 +870858,33 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2021.03.11.21253395", - "rel_title": "Airborne Transmission of COVID-19 and Mitigation Using Box Fan Air Cleaners in a Poorly Ventilated Classroom", + "rel_doi": "10.1101/2021.03.11.21253374", + "rel_title": "Acceptability of COVID-19 vaccination among health care workers in Ghana", "rel_date": "2021-03-12", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.11.21253395", - "rel_abs": "Many indoor places, including aged classrooms and offices, prisons, homeless shelters, etc., are poorly ventilated but resource-limited to afford expensive ventilation upgrade or commercial air purification systems, raising concerns on the safety of opening activities in these places in the era of COVID-19 pandemic. To address this challenge, using computational fluid dynamics, we conducted a systematic investigation of airborne transmission in a classroom equipped with a single horizontal unit ventilator (HUV) and evaluate the performance of low-cost box fan air cleaner for risk mitigation. Our study shows that placing box fan air cleaners in the classroom results in a substantial reduction of airborne transmission risk across the entire space. The air cleaner can achieve optimal performance when placed near the asymptomatic patient. However, without knowing the location of the patient, the performance of the cleaner is optimal near the HUV with the air flowing downwards. In addition, we find that it is more efficient in reducing aerosol concentration and spread in the classroom by adding air cleaners in comparison with raising the flow rate of HUV alone. The number and placement of air cleaners need to be adjusted to maintain its efficacy for larger classrooms and to account for the thermal gradient associated with human thermal plume and hot ventilation air during cold seasons. Overall, our study shows that box fan air cleaners can serve as an effective low-cost alternative for mitigating airborne transmission risks in poorly ventilated spaces.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.11.21253374", + "rel_abs": "The acceptance or otherwise of the COVID-19 vaccine by health care workers can influence the uptake of COVID-19 vaccines among the general population as they are a reliable source of health information. In this study, we sought to determine the acceptability of COVID-19 vaccines among health care workers in Ghana. Using a cross-sectional design, we collected data from 234 health care workers through a self-administered online survey from 16 January to 15 February 2021. Descriptive, bivariate and multivariate analyses using binary logistic regression were performed using STATA version 15. The results showed that 39.3% of health care workers had the intention of receiving the COVID-19 vaccine. Factors such as sex, category of health care workers, relative being diagnosed with COVID-19, and trust in the accuracy of the measures taken by the government in the fight against COVID-19 proved to be significant predictors of the acceptability of the COVID-19 vaccine. Concerns about the safety of vaccines and the adverse side effects of the vaccine were identified as the main reasons why health care workers would decline uptake of the COVID-19 vaccine in Ghana. The self-reported low intention of health care workers to accept the COVID-19 vaccine in Ghana requires the urgent call of the Government of Ghana and other stakeholders to critically address health care workers concerns about the safety and adverse side effects of COVID-19 vaccines, as this would increase vaccine uptake. Interventions must also take into consideration sex and the category of health care workers to achieve the desired results.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Ruichen He", - "author_inst": "University of Minnesota" - }, - { - "author_name": "Wanjiao Liu", - "author_inst": "Research and Advanced Engineering, Ford Motor Company" + "author_name": "Martin Wiredu Agyekum", + "author_inst": "Regional Institute for Population Studies, University of Ghana" }, { - "author_name": "John Elson", - "author_inst": "Research and Advanced Engineering, Ford Motor Company" + "author_name": "Grace Frempong Afrifa-Anane", + "author_inst": "Department of Environment and Public Health, University of Environment and Sustainable Development" }, { - "author_name": "Rainer Vogt", - "author_inst": "Ford-Werke GmbH, Research & Innovation Center" + "author_name": "Frank Kyei-Arthur", + "author_inst": "Department of Environment and Public Health, University of Environment and Sustainable Development" }, { - "author_name": "Clay Maranville", - "author_inst": "Research and Advanced Engineering, Ford Motor Company" - }, - { - "author_name": "Jiarong Hong", - "author_inst": "University of Minnesota" + "author_name": "Bright Addo", + "author_inst": "Kwame Nkrumah University of Science and Technology" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "public and global health" }, @@ -872992,29 +872436,73 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.03.12.21253447", - "rel_title": "Impact of Vaccine Prioritization Strategies on Mitigating COVID-19: An Agent-Based Simulation Study using an Urban Region in the United States", + "rel_doi": "10.1101/2021.03.11.21253421", + "rel_title": "Exposure to SARS-CoV-2 within the household is associated with greater symptom severity and stronger antibody responses in a community-based sample of seropositive adults", "rel_date": "2021-03-12", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.12.21253447", - "rel_abs": "BackgroundApproval of novel vaccines for COVID-19 had brought hope and expectations, but not without additional challenges. One central challenge was understanding how to appropriately prioritize the use of limited supply of vaccines. This study examined the efficacy of the various vaccine prioritization strategies using the vaccination campaign underway in the U.S.\n\nMethodsThe study developed a granular agent-based simulation model for mimicking community spread of COVID-19 under various social interventions including full and partial closures, isolation and quarantine, use of face mask and contact tracing, and vaccination. The model was populated with parameters of disease natural history, as well as demographic and societal data for an urban community in the U.S. with 2.8 million residents. The model tracks daily numbers of infected, hospitalized, and deaths for all census age-groups. The model was calibrated using parameters for viral transmission and level of community circulation of individuals. Published data from the Florida COVID-19 dashboard was used to validate the model. Vaccination strategies were compared using a hypothesis test for pairwise comparisons.\n\nResultsThree prioritization strategies were examined: a minor variant of CDCs recommendation, an age-stratified strategy, and a random strategy. The impact of vaccination was also contrasted with a no vaccination scenario. The study showed that the campaign against COVID-19 in the U.S. using vaccines developed by Pfizer/BioNTech and Moderna 1) reduced the cumulative number of infections by 10% and 2) helped the pandemic to subside below a small threshold of 100 daily new reported cases sooner by approximately a month when compared to no vaccination. A comparison of the prioritization strategies showed no significant difference in their impacts on pandemic mitigation.\n\nConclusionsEven though vaccines for COVID-19 were developed and approved much quicker than ever before, their impact on pandemic mitigation was small as the explosive spread of the virus had already infected a significant portion of the population, thus reducing the susceptible pool. A notable observation from the study is that instead of adhering strictly to a sequential prioritizing strategy, focus should perhaps be on distributing the vaccines among all eligible as quickly as possible, after providing for the most vulnerable. As much of the population worldwide is yet to be vaccinated, results from this study should aid public health decision makers in effectively allocating their limited vaccine supplies.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.11.21253421", + "rel_abs": "Magnitude of SARS-CoV-2 virus exposure may contribute to symptom severity. In a sample of seropositive adults (n=1101), we found that individuals who lived with a known COVID-19 case exhibited greater symptom severity and IgG concentrations compared to individuals who were seropositive but did not live with a known case (P<0.0001).", + "rel_num_authors": 14, "rel_authors": [ { - "author_name": "Hanisha Anand Tatapudi", - "author_inst": "University of South Florida" + "author_name": "Joshua M. Schrock", + "author_inst": "Northwestern University" }, { - "author_name": "Rachita Das", - "author_inst": "Miller School of Medicine" + "author_name": "Daniel T. Ryan", + "author_inst": "Northwestern University" }, { - "author_name": "Tapas K Das", - "author_inst": "University of South Florida" + "author_name": "Rana Saber", + "author_inst": "Northwestern University" + }, + { + "author_name": "Nanette Benbow", + "author_inst": "Northwestern University" + }, + { + "author_name": "Lauren A. Vaught", + "author_inst": "Northwestern University" + }, + { + "author_name": "Nina Reiser", + "author_inst": "Northwestern University" + }, + { + "author_name": "Matthew P. Velez", + "author_inst": "Northwestern University" + }, + { + "author_name": "Ryan Hsieh", + "author_inst": "Northwestern University" + }, + { + "author_name": "Michael E. Newcomb", + "author_inst": "Northwestern University" + }, + { + "author_name": "Alexis R. Demonbreun", + "author_inst": "Northwestern University" + }, + { + "author_name": "Brian Mustanski", + "author_inst": "Northwestern University" + }, + { + "author_name": "Elizabeth M. McNally", + "author_inst": "Northwestern University" + }, + { + "author_name": "Richard D'Aquila", + "author_inst": "Northwestern University" + }, + { + "author_name": "Thomas W McDade", + "author_inst": "Northwestern University" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -874740,117 +874228,53 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.03.08.21252958", - "rel_title": "Immune response to SARS-CoV-2 variants of concern in vaccinated individuals", + "rel_doi": "10.1101/2021.03.09.21252401", + "rel_title": "Agreement between commercially available ELISA and in-house Luminex SARS-CoV-2 antibody immunoassays", "rel_date": "2021-03-10", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.08.21252958", - "rel_abs": "The SARS-CoV-2 pandemic virus is consistently evolving with mutations within the receptor binding domain (RBD)1 being of particular concern2-4. To date, there is little research into protection offered following vaccination or infection against RBD mutants in emerging variants of concern (UK3, South African5, Mink6 and Southern California7). To investigate this, serum and saliva samples were obtained from groups of vaccinated (Pfizer BNT-162b28), infected and uninfected individuals. Antibody responses among groups, including salivary antibody response and antibody binding to RBD mutant strains were examined. The neutralization capacity of the antibody response against a patient-isolated South African variant was tested by viral neutralization tests and further verified by an ACE2 competition assay. We found that humoral responses in vaccinated individuals showed a robust response after the second dose. Interestingly, IgG antibodies were detected in large titers in the saliva of vaccinated subjects. Antibody responses showed considerable differences in binding to RBD mutants in emerging variants of concern. A substantial reduction in RBD binding and neutralization was detected for the South African variant. Taken together our data reinforces the importance of administering the second dose of Pfizer BNT-162b2 to acquire high levels of neutralizing antibodies. High antibody titers in saliva suggest that vaccinated individuals may have reduced transmission potential. Substantially reduced neutralization for the South African variant highlights importance of surveillance strategies to detect new variants and targeting these in future vaccines.", - "rel_num_authors": 26, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.09.21252401", + "rel_abs": "AO_SCPLOWBSTRACTC_SCPLOWSerological diagnostic of the severe respiratory distress syndrome coronavirus 2 (SARS-CoV-2) is a valuable tool for the determination of immunity and surveillance of exposure to the virus. In the context of an ongoing pandemic, it is essential to externally validate widely used tests to assure correct diagnostics and epidemiological estimations. We evaluated the performance of the COVID-19 ELISA IgG and IgM/A (Vircell, S.L.) against a highly specific and sensitive in-house Luminex immunoassay in a set of samples from pregnant women and cord blood. The agreement between both assays was moderate to high for IgG but low for IgM/A. Considering seropositivity by either IgG and/or IgM/A, the technical performance of the ELISA was highly imbalanced, with 96% sensitivity at the expense of 22% specificity. As for the clinical performance, the negative predictive value reached 87% while the positive predictive value was 51%. Our results stress the need for highly specific and sensitive assays and external validation of diagnostic tests with different sets of samples to avoid the clinical, epidemiological and personal disturbances derived from serological misdiagnosis.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Matthias Becker", - "author_inst": "NMI Natural and Medical Sciences Institute at the University of Tuebingen, Reutlingen, Germany" - }, - { - "author_name": "Alex Dulovic", - "author_inst": "NMI Natural and Medical Sciences Institute at the University of Tuebingen, Reutlingen, Germany" - }, - { - "author_name": "Daniel Junker", - "author_inst": "NMI Natural and Medical Sciences Institute at the University of Tuebingen, Reutlingen, Germany" - }, - { - "author_name": "Natalia Ruetalo", - "author_inst": "Institute for Medical Virology and Epidemiology, University Hospital Tuebingen, Tuebingen, Germany" - }, - { - "author_name": "Philipp Kaiser", - "author_inst": "NMI Natural and Medical Sciences Institute at the University of Tuebingen, Reutlingen, Germany" - }, - { - "author_name": "Yudi Pinilla", - "author_inst": "Institute of Tropical Medicine, University of Tuebingen, Germany" - }, - { - "author_name": "Constanze Heinzel", - "author_inst": "Institute of Tropical Medicine, University of Tuebingen, Germany" - }, - { - "author_name": "Julia Haering", - "author_inst": "NMI Natural and Medical Sciences Institute at the University of Tuebingen, Reutlingen, Germany" - }, - { - "author_name": "Bjoern Traenkle", - "author_inst": "NMI Natural and Medical Sciences Institute at the University of Tuebingen, Reutlingen, Germany" - }, - { - "author_name": "Teresa Wagner", - "author_inst": "NMI Natural and Medical Sciences Institute at the University of Tuebingen, Reutlingen, Germany" - }, - { - "author_name": "Mirjam Layer", - "author_inst": "Institute for Medical Virology and Epidemiology, University Hospital Tuebingen, Tuebingen, Germany" - }, - { - "author_name": "Martin Mehrlaender", - "author_inst": "Department of Anaesthesiology and Intensive Care Medicine, University Hospital Tuebingen, Tuebingen, Germany" - }, - { - "author_name": "Valbona Mirakaj", - "author_inst": "Department of Anaesthesiology and Intensive Care Medicine, University Hospital Tuebingen, Tuebingen, Germany" - }, - { - "author_name": "Jana Held", - "author_inst": "Institute of Tropical Medicine, University of Tuebingen, Germany" - }, - { - "author_name": "Hannes Planatscher", - "author_inst": "Signatope GmbH, Reutlingen, Germany" - }, - { - "author_name": "Katja Schenke-Layland", - "author_inst": "NMI Natural and Medical Sciences Institute at the University of Tuebingen, Reutlingen, Germany" - }, - { - "author_name": "Gerard Krause", - "author_inst": "Helmholtz Centre for Infection Research, Braunschweig, Germany" + "author_name": "Rebeca Santano", + "author_inst": "ISGlobal, Hospital Clinic - Universitat de Barcelona, Barcelona, Catalonia, Spain" }, { - "author_name": "Monika Strengert", - "author_inst": "Helmholtz Centre for Infection Research, Braunschweig, Germany" + "author_name": "Diana Barrios", + "author_inst": "ISGlobal, Hospital Clinic - Universitat de Barcelona, Barcelona, Catalonia, Spain" }, { - "author_name": "Tamam Bakchoul", - "author_inst": "Institute for Clinical and Experimental Transfusion Medicine, University Hospital Tuebingen, Tuebingen, Germany" + "author_name": "Fatima Crispi", + "author_inst": "BCNatal, Barcelona Center for Maternal-Fetal and Neonatal Medicine, Hospital Sant Joan de Deu and Hospital Clinic, IDIBAPS, Universitat de Barcelona, CIBER-ER, " }, { - "author_name": "Karina Althaus", - "author_inst": "Institute for Clinical and Experimental Transfusion Medicine, University Hospital Tuebingen, Tuebingen, Germany" + "author_name": "Francesca Crovetto", + "author_inst": "BCNatal, Barcelona Center for Maternal-Fetal and Neonatal Medicine, Hospital Sant Joan de Deu and Hospital Clinic, IDIBAPS, Universitat de Barcelona, CIBER-ER, " }, { - "author_name": "Rolf Fendel", - "author_inst": "Institute of Tropical Medicine, University of Tuebingen, Germany" + "author_name": "Marta Vidal", + "author_inst": "ISGlobal, Hospital Clinic - Universitat de Barcelona, Barcelona, Catalonia, Spain" }, { - "author_name": "Andrea Kreidenweiss", - "author_inst": "Institute of Tropical Medicine, University of Tuebingen, Germany" + "author_name": "Jordi Chi", + "author_inst": "ISGlobal, Hospital Clinic - Universitat de Barcelona, Barcelona, Catalonia, Spain" }, { - "author_name": "Michael Koeppen", - "author_inst": "Department of Anaesthesiology and Intensive Care Medicine, University Hospital Tuebingen, Tuebingen, Germany" + "author_name": "Luis Izquierdo", + "author_inst": "ISGlobal, Hospital Clinic - Universitat de Barcelona, Barcelona, Catalonia, Spain" }, { - "author_name": "Ulrich Rothbauer", - "author_inst": "NMI Natural and Medical Sciences Institute at the University of Tuebingen, Reutlingen, Germany" + "author_name": "Eduard Gratacos", + "author_inst": "BCNatal, Barcelona Center for Maternal-Fetal and Neonatal Medicine, Hospital Sant Joan de Deu and Hospital Clinic, IDIBAPS, Universitat de Barcelona, CIBER-ER, " }, { - "author_name": "Michael Schindler", - "author_inst": "Institute for Medical Virology and Epidemiology, University Hospital Tuebingen, Tuebingen, Germany" + "author_name": "Gemma Moncunill", + "author_inst": "ISGlobal, Hospital Clinic - Universitat de Barcelona, Barcelona, Catalonia, Spain" }, { - "author_name": "Nicole Schneiderhan-Marra", - "author_inst": "NMI Natural and Medical Sciences Institute at the University of Tuebingen, Reutlingen, Germany" + "author_name": "Carlota Dobano", + "author_inst": "ISGlobal, Hospital Clinic - Universitat de Barcelona, Barcelona, Catalonia, Spain" } ], "version": "1", @@ -877430,33 +876854,33 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.03.08.21252586", - "rel_title": "Categorizing the Status of COVID-19 Outbreaks Around the World", + "rel_doi": "10.1101/2021.03.05.21252990", + "rel_title": "A quantitative risk estimation platform for indoor aerosol transmission of COVID-19", "rel_date": "2021-03-09", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.08.21252586", - "rel_abs": "Although the SARS-CoV-19 virus spread rapidly around in world in early 2020, disease epidemics in different places evolved differently as the year progressed - and the state of the COVID-19 pandemic now varies significantly across different countries and territories. We have created a taxonomy of possible categories of disease dynamics, and used the evolution of reported COVID-19 cases relative to changes in disease control measures, together with total reported cases and deaths, to allocate most countries and territories among the possible categories. As of 31 January 2021, we find that the disease was (1) kept out or suppressed quickly through quarantines and testing & tracing in 39 countries with 29 million people, (2) suppressed on one or more occasions through control measures in 74 countries with 2.49 billion people, (3) spread slowly but not suppressed, with cases still increasing or just past a peak, in 31 countries with 1.45 billion people, (4) spread through the population, but slowed a result of control measures, leading to a \"flattened curve\" and fewer infections than if the epidemic were unmitigated, in 32 countries with 2.24 billion people, and (5) spread through the population with some but limited mitigation in 5 countries with 168 million people. In addition, several countries have experienced increases in cases after disease appeared to have finished spreading due to declining numbers of susceptible people. For some of these countries - for example Kenya, Pakistan and Afghanistan - the resurgences can be explained by the relaxation of control measures (and may have been enhanced by disease spread in population segments that experienced lower infection levels during the first waves). For other countries, the resurgences point to the effects of new virus variants with higher transmissibility or immunity resistance - including most countries in Southern Africa (where the B.1.351 variant has been identified) and several countries in West Africa (potentially due to the B.1.1.7 or other variants). These findings are consistent with mounting evidence of high infection rates in several low- and middle-income countries, both from seroprevalence studies and estimates of actual deaths from COVID-19 combined with estimates of expected mortality rates. We estimate that 1.3-3.0 billion people, or 17-39% of the global population, have been infected by SARS-CoV-2 to date, and that at least 4.5 million people have died from COVID-19 - much higher than reported cases and deaths. Disease control policies and vaccination strategies should be designed based on the state of the COVID-19 epidemic in the population - and consequently may need to be different in different countries.\n\nKey Points The state of the COVID-19 pandemic varies significantly in different countries and territories around the world - and policies for disease control and vaccination will need to be tailored accordingly.\nIn any epidemic, there are several possibilities for how the disease will spread over time - and our analysis finds that, in fact, as of 31 January 2021, there were many countries and territories in each of the main categories of COVID-19 epidemic dynamics that might have been expected:\nO_LIKept out or suppressed quickly through quarantines and testing & tracing - in 39 countries with 29 million people (0.4% of the global population), mostly small island states and a few countries in Southeast Asia. [Category H in the following map and table]\nC_LIO_LISuppressed through control measures (social distancing, hygiene and testing & tracing) -in 74 countries with 2.49 billion people (31.9% of global population), mostly in Europe, East Asia and the Pacific. [Categories F and G]\nC_LIO_LISpread slowly but not suppressed, with cases still increasing or just past a peak - in 31 countries with 1.45 billion people (18.6% of global population), including many countries in Latin America, Eastern Europe and the Middle East, as well as the United States and Russia. [Categories D and E]\nC_LIO_LISpread through the population, but slowed as a result of control measures, leading to a \"flattened curve\" and fewer infections than if the epidemic were unmitigated - in 32 countries with 2.24 billion people (28.8% of global population), mostly in South and Southeast Asia (including India) and Africa. [Category B]\nC_LIO_LISpread through the population with some but limited mitigation or \"flattening the curve\" -in 5 countries with 168 million people (2.2% of global population). [Category A]\nC_LIO_LIExperienced increases in cases after disease appeared to have finished spreading, which in some countries might have been solely due to relaxation of control measures (especially in wealthier population segments which experienced low infection levels during the first wave) - for example in Kenya and in Pakistan and some Central Asian countries - but which in some countries is likely to be due to new virus variants with higher transmissibility or immunity resistance - for example in most countries in Southern Africa and several in West Africa, and possibly also in parts of South and Central America. [Category J and many countries in Category K]\nC_LI\nThese findings are backed up by mounting evidence of high infection rates in several low- and middle-income countries. Seroprevalence studies in Kenya, Nigeria, Pakistan and South Africa have reported finding antibodies for SARS-CoV-2 in large percentages of the studied populations - and suggest that current infection levels are likely above 50% in each country. Studies of actual deaths due to COVID-19, combined with estimates of expected mortality rates, similarly suggest that SARS-CoV-2 has, by now, infected more than half of the populations in Bolivia, Ecuador, Peru, Mexico, South Africa, Sudan, Syria, Yemen and Zambia.\nCountries of all income levels, and from all regions, appear in each of the main disease dynamics categories; however, there are clear income and geographical patterns in states of COVID-19 epidemics around the world. Most high-income countries have controlled the spread of SARS-CoV-2 through measures. Middle-income countries are spread across all categories, and account for 45 of the 63 countries which have slowed the disease significantly but not fully suppressed it. Some low-income have experienced largely unmitigated susceptibility-driven dynamics, while others have \"flattened the curve\" to varying degrees.\nWe estimate that between one and two out of every five people globally has been infected by SARS-CoV-2 to date, and that at least 4.5 million people have died from COVID-19. Our estimate of total infections - 1.3-3.0 billion people, or 17-39% of the global population - is between 13 and 30 times the number of confirmed cases, and twice to four times as much as previous estimates of total infection numbers. We estimate that 4.6-10.0 million people have died from COVID-19, between 2.1 and 4.5 times the number of deaths attributed to COVID-19.\nAn estimated 8.9-12.5 million lives remained at risk from COVID-19 as of the end of January 2021, prior to vaccination efforts - mainly in high-income countries (2.4-2.9 million), China (2.1 million) and India (1.7-2.9 million). Vaccinations, of course, have already started to reduce these numbers substantially.\nOur analytical approach is simple but useful - providing insight into the epidemic status even in many low-income countries with limited disease monitoring, and with potential to provide early warnings of significant new variants. We compare the evolution of reported cases with changes in stringency of disease control measures, and check that infection levels are plausible given total reported cases and deaths and the income level of the country. Anomalies in which changes in the evolution of reported cases cannot be explained by changes in the stringency index provide indications of possible significant variants of the virus. Up to the end of January, the data provide indications of the presence of significant new variants in:\nO_LIMost countries in Southern Africa (where the B.1.351 variant, with higher transmissibility and some resistance to immunity, was first identified in South Africa)\nC_LIO_LISeveral countries in West Africa (likely with higher transmissibility and resistance to immunity, possibly the B.1.1.7 variant, which was first identified in the UK and has been found in Ghana and Nigeria, or possibly a different variant).\nC_LI\nThey also suggest, with less certainty, that the disease dynamics may be affected by new variants in several countries in South and Central America (perhaps the P.1 variant descended from the B.1.1.28 variant which was first identified as coming from the Brazilian Amazon).\nDifferent countries should adopt different disease control policies, according to the state of the COVID-19 epidemic in the population.\nO_LIFor countries that have kept the disease out or suppressed outbreaks through control measures, their measures need to be kept in place - and potentially strengthened especially in the face of higher-transmissibility variants - until vaccines have been widely administered.\nC_LIO_LIFor countries in which the disease is spreading slowly, full control measures should be maintained at least until new case numbers fully decline from the peak; later, it may be possible to relax some measures, but if measures are relaxed too soon or too much after cases peak, then significant further outbreaks can be expected (as has already happened in several such countries).\nC_LIO_LIFor countries in which cases have declined following a flattened curve, there may be room to relax control measures that have the greatest negative health, economic and social consequences - but the most effective control measures will need to be maintained (even when cases remain low for extended periods), and measures may need to be strengthened to tackle variants which higher transmissibility or ability to evade immune responses.\nC_LIO_LIFor countries in which the disease spread was largely unmitigated, many control measures could be relaxed for most people - although there may be risks if sizeable population segments have much lower infection levels than the general population or from variants with a high degree of immunity resistance.\nC_LI\nThese findings may have implications for the optimal distribution of early batches of vaccines within countries.\nO_LIFor countries that have kept the disease out or suppressed outbreaks through control measures, vaccinations should be given first to frontline healthcare and essential workers and to elderly and vulnerable groups (starting with the oldest and most vulnerable).\nC_LIO_LIFor countries in which the disease is spreading slowly, detailed modelling should be done to determine whether the optimal strategy is to vaccinate at-risk groups first or to vaccinate key transmitters to halt the outbreak and \"crush the curve\" while waiting for further vaccine supplies to arrive. For any country choosing the key transmitter strategy - as Indonesia has done and has been suggested for the United States - it will be essential to maintain control measures, and to keep higher transmissibility variants out, or otherwise the benefits of a key transmitter vaccination strategy could be lost.\nC_LIO_LIFor countries in which the cases declined following a flattened curve, vaccinations should probably be given first to elderly and vulnerable groups, but the optimal strategy may switch to vaccinating key transmitters if there are resurgences in cases due to higher-transmissibility or immunity-resistant variants.\nC_LIO_LIFor countries in which the disease spread was largely unmitigated, vaccination should concentrate on elderly and vulnerable people, because population-level immunity already exists, and the greatest danger lies in vulnerable people becoming infected due to endemic SARS-CoV-2 from variants that will likely circulate over many years.\nC_LI\nThese findings may also have implications for the optimal distribution of the first vaccines across countries. For most countries, the optimal allocation of vaccines doses is likely still to be according to population size - as current recommendations suggest. However, the global optimal allocation strategy might include providing somewhat greater supplies, during the next few months, to countries where using the vaccine to halt spread of the disease might be possible (provided that disease control measures are maintained in those countries).\nVaccination strategies will need to account for current and potential future virus variants as well as the likelihood that immunity from vaccination will wane over time. Higher-transmissibility variants of the SARS-CoV-2 virus increase the urgency of distributing vaccines in countries which have controlled the disease to date, and may alter the optimal strategy for countries deciding between vaccination first of elderly and vulnerable people or of key transmitters. Immunity-resistant variants of the virus may reduce the effectiveness of current vaccines, but are not likely to negate fully the protection they offer. Immunity acquired through vaccination is likely to wane over time - like immunity acquired through infection. In many, perhaps most, countries, the time to vaccinate the whole population will exceed the timeframe in which immunity from vaccination wanes or new immunity-resistant variants emerge. Looking to the longer term, therefore, new virus variants and waning immunity are likely to necessitate re-vaccination (with vaccines tailored to the latest variants) on a regular basis - and the optimal long-term strategies for ongoing vaccination will vary widely across countries and will depend on many factors.\n\n\nO_FIG O_LINKSMALLFIG WIDTH=154 HEIGHT=200 SRC=\"FIGDIR/small/21252586v3_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (46K):\norg.highwire.dtl.DTLVardef@c39b02org.highwire.dtl.DTLVardef@1f5ccceorg.highwire.dtl.DTLVardef@590b3dorg.highwire.dtl.DTLVardef@1f0f1c5_HPS_FORMAT_FIGEXP M_FIG C_FIG O_FIG O_LINKSMALLFIG WIDTH=151 HEIGHT=200 SRC=\"FIGDIR/small/21252586v3_ufig2.gif\" ALT=\"Figure 2\">\nView larger version (60K):\norg.highwire.dtl.DTLVardef@190e169org.highwire.dtl.DTLVardef@bec2a2org.highwire.dtl.DTLVardef@1dc3cf0org.highwire.dtl.DTLVardef@24d56b_HPS_FORMAT_FIGEXP M_FIG C_FIG SummaryThe state of the COVID-19 pandemic varies significantly in different countries and territories around the world - and policies for disease control and vaccination will need to be tailored accordingly. Although the SARS-CoV-19 virus spread rapidly around in world in early 2020, the state of disease epidemics in different countries diverged rapidly as the year progressed. Many high-income countries have had second or third waves; other countries have seen cases continue to increase gradually; still others have experienced declines in cases to low levels after peaks in mid-2020. Facing different situations, different countries might need to adopt different policies in the coming months, including different disease control measures and vaccination strategies.\n\nEach country needs to know its COVID-19 status. There are several possible courses that a disease epidemic can take in a population. The disease can spread rapidly until its runs out of people remaining to infect; the disease can be slowed with control measures but still spread until large numbers of people are infected and immune; the disease can be suppressed or \"crushed\" by control measures; or the disease can be kept out completely. More complex disease dynamics will occur when a virus mutates, if new variants evade immune responses in people already infected or spread faster than before, or if the disease spreads differently in different segments of a population. Our research suggests that different countries have experienced outbreaks in each of the main possible categories:\n\nO_LISusceptibility-Driven Dynamics with Limited Mitigation [Category A] - in which the disease spread until it infect most people and declined due to low susceptibility levels (i.e., low share of the population still able to be infected).\nC_LIO_LISusceptibility-Driven Dynamics Mitigated by Measures [Categories B and C] - in which the disease curve was \"flattened\" by control measures, but the disease still spread and declined after infecting large numbers of people (but fewer than if there were no mitigation).\nC_LIO_LISusceptibility-plus-Measures-Driven Dynamics [Categories D and E] - in which the disease was slowed significantly but not suppressed, i.e., the curve was \"flattened\" but not \"crushed\", and the disease is still spreading in the population.\nC_LIO_LIMeasures-Driven Dynamics [Categories F and G] - in which the disease has been constrained to date mainly through control measures (social distancing, hygiene and testing & tracing), but, of course, could spread again if measures are relaxed because only a minority of the population has been infected.\nC_LIO_LIIndex-Case-Control Dynamics [Category H] - in which the disease has been kept out or suppressed to date through strict control measures (especially quarantines and testing & tracing).\nC_LIO_LIComplex Disease Dynamics due to Differences Across Population Segments and/or New Variants [Categories I and J, and many countries in Category K] - in which the disease experienced an apparently susceptibility-driven curve but with low overall infection levels (i.e., share of population infected) because some segments of the population have not had many infections, or in which the disease later shows an unexpected resurgence, due to spreading within the previously less-affected population segments or due to the emergence of immunity-evading strains of the virus.\nC_LI\n\nFrom reported data on COVID-19 cases and disease control measures, we can categorize, for most countries and territories, the dynamics of the disease to date. First, we compare the timing of increases and/or decreases in reported new cases with the timing of changes in the \"Stringency Index\" of control measures compiled by the Oxford COVID-19 Government Response Tracker - and select the appropriate disease dynamics category. Second, we check if the infection levels expected for the category or categories indicated in the first step, are consistent with predicted ranges from the total numbers of reported cases and deaths using plausible ranges for the case detection rate, death detection rate and infection fatality ratio (IFR) given the countrys income level. This approach yields definitive categories for most countries and territories. COVID-19 disease dynamics are complicated in many countries, due to changes in control measures, seasonal patterns, geographical differences within countries, variability in case testing over time and emergence of new variants; such effects can be seen in the reported cases and deaths for many countries, but they do not obscure the basic drivers of disease dynamics - in other words, which of the categories applies - for most countries.\n\nThe results suggest that there is a wide variation in the state of the COVID-19 epidemic around the world - as of 31 January 2021 - as illustrated in the map and the table below. COVID-19 has been suppressed through control measures - Categories F, G and H - in 113 countries and territories with 2.52 billion people or about 32.3% of the global population. However, the rest of the world are in different situations. A total of 31 countries, with populations of 1.45 billion people (18.6% of global population), fall into Categories D and E, meaning that the disease spread has been slowed but not suppressed and cases are currently still increasing or just past their peak. In the 23 countries of Category B, home to 2.05 billion people (26.3%), the disease was slowed but not suppressed, and cases have declined fully from the peak. In a further 9 countries with 0.19 billion people (2.5%), the disease spread through the population after initial waves were suppressed. COVID-19 outbreaks in 5 countries with 0.17 billion people (2.2%) were only somewhat mitigated by control measures and the virus has likely infected most of the population, falling into Category A.\n\nFor several countries, which have apparent anomalies and fall outside the \"basic\" categories, the methodology provides important insights into epidemic status - pointing to situations where significant differences may exist across population segments or providing early warnings of new variants with higher transmissibility or resistance to immunity. For 5 Arabian Peninsula countries (3 of which are in Category I) and Singapore, it is likely that the virus has spread widely among migrant worker communities but has been controlled in the rest of the population. Categories J and K include 28 countries in which reported cases have surged after first waves which were likely or possibly susceptibility-driven, with curves flattened to various extents as a result of control measures which mitigated the epidemics. For some countries - including (1) Kenya, (2) Pakistan, Afghanistan, Kyrgyzstan and Kazakhstan, and (3) Egypt and Sudan - the second peaks are likely due to relaxation of measures but larger than might be expected due to disproportionate effects of the second waves on population segments (likely more affluent groups) which had lower infection levels during the first waves. For other countries - including (1) most countries in Southern Africa and (2) many countries in West Africa - the data suggest the presence of new virus variants with higher transmissibility and possible resistance to immunity, because resurgences or accelerations in cases happened in several neighbouring countries around the same time, and often without changes in control measures, and the second surges in cases usually involved faster increases than the first waves. The B.1.351 variant, with higher transmissibility and some resistance to immunity, was first identified in South Africa and is known to have caused most cases in the countrys second wave; the B.1.1.7 variant, which has higher transmissibility, has been found in Ghana and Nigeria. Several countries in South and Central America have experienced second waves or surges in cases: Surinames might be due to a higher-transmissibility variant (perhaps the P.1 variant that was first identified as coming from the Brazilian Amazon); Bolivias was large but could be explained by a significant decline in control measures; increases in Brazil and several other countries across South and Central America might simply be due to relaxation of social distancing behaviours over the Christmas and New Year holiday season although a role for virus variants cannot be discounted.\n\nCountries of all income levels appear in each of the main disease dynamics categories; however there are clear correlations between income groups and COVID-19 status categories. Most high-income countries have controlled the spread of SARS-CoV-2 through measures (and thus fall in Categories F, G and H). Middle-income countries are spread across all categories, and account for 45 of the 63 countries which have slowed the disease significantly but not fully suppressed it (Categories B, C, D and E). Some low-income countries have experienced largely unmitigated susceptibility-driven dynamics (Category A), while others have \"flattened the curve\" to varying degrees (Categories B, C, D and E). A mix of low- and middle-income countries are among the 34 countries in Categories J and K.\n\nClear geographical patterns have emerged in the states of COVID-19 epidemics. There was more diversity in the state of the epidemic within regions earlier in the pandemic, but regional patterns had become clear by the end of January 2021.\n\nO_LIIn the Americas, the disease has spread slowly but has not been suppressed (Categories D and E) in most countries, including those with the largest populations, while many (but not all) of the Caribbean islands have kept SARS-CoV-2 out or under control (Category H).\nC_LIO_LIWestern and Northern European countries have, for the most part, controlled the disease through social distancing and hygiene measures, through two or three waves, and fall in Categories F and G.\nC_LIO_LIAcross Eastern Europe, the Levant, the Caucuses and Iran, all countries have constrained growth of the disease significantly, but infection levels in most have grown to moderate levels: different countries in these regions are included in Categories C, D/E and F/G, although their infection levels may all be in the moderate range.\nC_LIO_LIIn South and Central Asia, the virus has spread widely in most countries and cases have declined. In India, Bangladesh, Nepal and Uzbekistan, the case curve was flattened considerably, and current infection levels are likely moderate (Category B). In Pakistan, Afghanistan, Kyrgyzstan, and Kazakhstan (all in Category J), there have been two peaks in cases. Bhutan has contained the outbreaks of the virus to date (Category F).\nC_LIO_LIMany countries in East and South-East Asia have largely kept the disease under control or kept it out (Categories F, G and H). However, Malaysia, Mongolia and Myanmar experienced widespread outbreaks in the second half of 2020, the Philippines appears to be past the peak of its epidemic (Category B), and Indonesia has had a continuous but very slow rise in cases since the start of the pandemic (Category E).\nC_LIO_LIIn Australia, New Zealand and most Pacific Island States, SARS-CoV-2 has been excluded through quarantines, together with testing and tracing and lockdowns when the virus has spread beyond quarantined individuals (Categories F and H).\nC_LIO_LIAfrican countries appear to have differed greatly in how the disease has spread. Many countries appear to have experienced widespread epidemics followed by declines in case numbers, with varying degrees of \"curve flattening\" due to control measures (Categories A and B). In some countries - Tunisia, Libya, Togo, Botswana and Mozambique - cases spread very slowly (Categories D and E). A few countries appear to have kept the disease out, and a few others appear to have experienced full outbreaks after having previously kept the virus largely out. As described earlier, most countries in Southern Africa and many in West Africa experienced rapid growth in case numbers in December and January (putting many in Categories J and K) - suggestive of the presence of one or more new variants with higher transmissibility and possible resistance to immunity.\nC_LI\n\nWe estimate that 1.3-3.0 billion people have been infected by SARS-CoV-2 to date, or about 17-39% of the global population. This estimate is between 13 and 30 times the number of confirmed cases, and perhaps twice to four times as much as previous estimates of total infection numbers. We estimate that 4.6-10.0 million people have died from COVID-19, between 2.1 and 4.5 times the number of deaths attributed to COVID-19.\n\nAn estimated 8.9-12.5 million lives remain at risk from COVID-19, which can be saved through appropriate disease control measures and effective deployment of vaccines. Of these estimated extra deaths, if 90% of the population were to contract SARS-CoV-2, high-income countries account for about 2.4-2.9 million, China for about 2.1 million, and India for about 1.7- 2.9 million. Vaccinations, of course, have already started to reduce these numbers substantially.\n\nThe findings of this report are backed up by mounting evidence of high infection rates in several low- and middle-income countries. Immunity testing provides direct evidence of the current state of the COVID-19 epidemic. Serological studies in several cities and regions in Brazil, India, Kenya, Pakistan, Qatar and South Africa have already reported finding antibodies for SARS-CoV-2 in large percentages of the studied populations. Note, however, that serological testing will underestimate the number of people who have been infected, due to waning of SARS-CoV-2 antibodies which affects significant numbers of people at about 4-6 months after infection. Consequently, serological testing might understate the actual degree of immunity in a population, because some people may have antibodies at levels below the detection threshold of the serology tests or may have memory B cell or T cell responses, either or both of which will likely reduce the severity of their illness if reinfected, and may reduce their vulnerability to reinfection and their likelihood to pass on the virus to other people if reinfected. In some places, reliable estimates of actual deaths due to COVID-19 may be a substitute for immunity testing to determine the share of population infected to date, at least approximately. Estimates, using a variety of methodologies, in Bolivia, Ecuador, Mexico, Peru, South Africa, Sudan, Syria, Yemen and Zambia all indicate that moderate to high shares of their populations have already been infected.\n\nDifferent countries should adopt different disease control policies, according to the state of the COVID-19 epidemic in the population. The following recommendations for countries in different categories take into account their current infection levels and the potential for additional infections if measures are relaxed or if new variants become common in a country.\n\n[tpltrtarr]Category A: Control measures should be relaxed for most people; such relaxation is not likely to lead to many more cases and deaths. In some low- and middle-income countries, wealthier population segments may have implemented greater degrees of social distancing during the epidemic to date, and have much lower infection levels than in the overall population; these segments should maintain social distancing, until vaccines arrive, because otherwise they could experience substantial outbreaks (which may have generated \"second waves\" in some countries). If and when new virus strains with higher transmissibility and/or resistance to immunity arrive, control measures should be strengthened again to avoid new outbreaks, if the new variants cause high mortality levels and if it seems likely that control measures will be more effective at controlling the new outbreaks than they were during the initial outbreaks.\n[tpltrtarr]Categories B and C: Control measures currently in place that have the greatest negative health, economic and social consequences could be relaxed. However, many control measures, especially the most effective in limiting virus spread, will need to be maintained, even though current case numbers are low; otherwise, significant resurgences can take place (as has happened, for instance, in Kenya and Bolivia). Population segments that may have maintained lower infection levels during the outbreak to date will need to maintain social distancing. If and when new virus strains with higher transmissibility and/or resistance to immunity arrive, control measures will likely have to be strengthened again to avoid new outbreaks.\n[tpltrtarr]Categories D and E: Control measures should be maintained at least until new case numbers fully decline from the peak; if measures are relaxed too soon after cases peak, then significant further outbreaks can be expected (as has happened, for instance, in Brazil, Colombia and Paraguay). Once cases fully decline from the peak - through further infections or as a result of vaccination programmes - then, and only then, some of the disease control measures with the greatest negative health, economic and social consequences could be relaxed. For some countries in Categories D and E, it may be possible to push R0_e below 1 and hence \"crush the curve\" by introducing some additional control measures or improving compliance with existing measures. New virus strains, especially with higher transmissibility, can generate resurgences or accelerations in growth of cases (as seen, for example, in Mozambique and Togo).\n[tpltrtarr]Categories F and G: COVID-19 control measures, put in place by governments and implemented by citizens, have saved perhaps 13.1-14.2 million lives. To continue to protect these lives, control measures need to be maintained until vaccines become widely available - and strengthened, if necessary, to compensate for new virus variants with higher transmissibility.\n[tpltrtarr]Category H: Measures to keep the disease out - mainly strict quarantines for new arrivals and testing & tracing of suspected cases - should be maintained until vaccines become widely available.\n\n\nThe findings of this report may have implications for the optimal distribution of early batches of vaccines within countries. Current policies in several countries call for deployment of vaccines first to healthcare workers and then by age cohort, starting with the oldest. These plans are aligned with the results of modelling (by Imperial College London and others) which suggest that, when the supply of vaccines is limited, the optimal strategy is to target the elderly and other high-risk groups. However, the models indicate that, if the supply is sufficient to stop transmission of the virus, the optimal strategy switches to targeting key transmitters (e.g., working age people and potentially children) to indirectly protect the elderly and vulnerable. Consequently, the optimal strategy may vary according to the disease status category for each country:\n\n[tpltrtarr]Category A: Vaccination should concentrate on elderly and vulnerable people, starting with the oldest and most vulnerable. There is no alternative strategy to consider because population-level immunity already exists, and the greatest danger lies in vulnerable people becoming infected due to endemic SARS-CoV-2.\n[tpltrtarr]Categories B and C: Vaccinations should probably be given first to elderly and vulnerable groups, and to frontline healthcare and other essential workers. However, if there are resurgences in cases across the population due to higher-transmissibility or immunity-resistant variants, then the optimal strategy may switch to targeting key transmitters, similar to some countries in Categories D and E.\n[tpltrtarr]Categories D and E: In some of these countries, the optimal strategy may to be vaccinate key transmitters - while maintaining current disease control measures - because it may be possible to halt the outbreak and \"crush the curve\", while waiting for further vaccine supplies to arrive (after which disease control measures could be released). This strategy is being pursued by Indonesia and was suggested for the United States of America in a recent paper. However, careful modelling and planning would be necessary, for any country considering such an approach, to determine if a key transmitter strategy would in fact be optimal and if it would be feasible to implement. Further, for such a strategy to work, it will be necessary to keep control measures in place and to keep high-transmissibility variants of the virus out, until enough people have been vaccinated.\n[tpltrtarr]Categories F, G and H: Vaccinations should be given first to frontline healthcare and other essential workers and to elderly and vulnerable groups (starting with the oldest and most vulnerable).\n\n\nThese findings may also have implications for the optimal distribution of the first vaccines across countries. Modelling by the Imperial College London COVID-19 Response Team suggests that the optimal allocation of vaccine doses among countries \"is sensitive to many assumptions and will vary depending both on the vaccine characteristics and the stage of the epidemic in each country at vaccine introduction,\" and concluded that, \"[g]iven this uncertainty, allocating vaccine doses according to population size appears to be the next most efficient approach.\" Our findings reinforce the uncertainty strongly: it is very likely that that stage of the epidemic varies greatly across countries. For most countries, the optimal allocation of vaccines doses is likely still to be according to population size - and then for those countries to give doses first to elderly and vulnerable people. However, the global optimal allocation strategy might include providing somewhat greater supplies, during the next few months, to Category D and E countries where using the vaccine to halt spread of the disease might be possible (provided that disease control measures are maintained in those countries). It is clear, in any case, that further modelling of vaccine allocation strategies is essential, taking into account the actual vaccine efficacies and projected available doses by month, as well as allowing for disease stage categories in different countries.\n\nVaccination strategies will need to account for current and potential future virus variants as well as the likelihood that immunity from vaccination will wane over time. Higher-transmissibility variants of the SARS-CoV-2 virus increase the urgency of distributing vaccines, especially in Category F and G countries which may struggle to keep the disease suppressed, and might cause vaccination of key transmitters to be a less effective strategy for Category D and E countries if higher-transmissibility variants mean that they cant suppress the disease fully with limited vaccinations. Immunity-resistant variants of the virus may reduce the effectiveness of current vaccines, but are not likely to negate fully the protection offered by existing vaccines. Immunity acquired through vaccination is likely to wane over time - like immunity acquired through infection. Looking to the longer term, new virus variants and waning immunity are likely to necessitate re-vaccination (with vaccines effective against the latest variants) on a regular basis. In many, perhaps most, countries, the time to vaccinate the whole population will exceed the timeframe in which immunity from vaccination wanes or new immunity-resistant variants emerge. In making long-term plans, therefore, countries may face a wide range of options for who to vaccinate (elderly and vulnerable populations, key transmitters or entire populations) and for frequency of vaccination (every 6 months, annual, or once if residual benefits are sufficient). Optimal strategies for each country will be complicated to determine, as the choice will depend on many factors, including vaccine effectiveness in reducing mortality and in reducing transmission, how effectiveness wanes over time, mortality rates and transmissibility of new variants (in general and in previously infected or vaccinated people), and, once the risks to life and health from \"endemic COVID\" decrease to the point where COVID-19 is not an overriding issue, comparison with other health and budgetary priorities.", + "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.05.21252990", + "rel_abs": "Aerosol transmission has played a significant role in the transmission of COVID-19 disease worldwide. We developed a COVID-19 aerosol transmission risk estimation platform to better understand how key parameters associated with indoor spaces and infector emissions affect inhaled deposited dose of aerosol particles that convey the SARS-CoV-2 virus. The model calculates the concentration of size-resolved, virus-laden aerosol particles in well-mixed indoor air challenged by emissions from an index case(s). The model uses a mechanistic approach, accounting for particle emission dynamics, particle deposition to indoor surfaces, ventilation rate, and single-zone filtration. The novelty of this model relates to the concept of \"inhaled & deposited dose\" in the respiratory system of receptors linked to a dose-response curve for human coronavirus HCoV-229E. We estimated the volume of inhaled & deposited dose of particles in the 0.5 to 4 m range expressed in picoliters (pL) in a well-documented COVID-19 outbreak in restaurant X in Guangzhou China. We anchored the attack rate with the dose-response curve of HCoV-229E which provides a preliminary estimate of the average SARS-CoV-2 dose per person, expressed in plaque forming units (PFUs). For a reasonable emission scenario, we estimate approximately three PFU per pL deposited, yielding roughly 10 PFUs deposited in the respiratory system of those infected in Restaurant X. To explore the platforms utility, we tested the model with four COVID-19 outbreaks. The risk estimates from the model fit reasonably well with the reported number of confirmed cases given available metadata from the outbreaks and uncertainties associated with model assumptions.\n\nPractical ImplicationsThe model described in this paper is more mechanistic in nature than standard probabilistic models that fail to account for particle deposition to indoor materials, filtration, and deposition of particles in the respiratory system of receptors. As such, it provides added insights into how building-related factors affect relative infection risk associated with inhaled deposited dose. An online version of this mechanistic aerosol risk estimation platform is available at Safeairspaces.com. Importantly, the modular nature of this approach allows for easy updates when new information is available regarding dose-response relationships for SARS-CoV-2 or its variants.", "rel_num_authors": 4, "rel_authors": [ { - "author_name": "John Paul Callan", - "author_inst": "Personal Capacity" + "author_name": "Hooman Parhizkar", + "author_inst": "university of oregon" }, { - "author_name": "Carlijn J. A. Nouwen", - "author_inst": "Personal Capacity" + "author_name": "Kevin Van Den Wymelenberg", + "author_inst": "University of Oregon" }, { - "author_name": "Axel S. Lexmond", - "author_inst": "Personal Capacity" + "author_name": "Charles Haas", + "author_inst": "Drexel university" }, { - "author_name": "Othmane Fourtassi", - "author_inst": "Personal Capacity" + "author_name": "Richard Corsi", + "author_inst": "Portland State University" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "public and global health" }, @@ -879860,117 +879284,45 @@ "category": "molecular biology" }, { - "rel_doi": "10.1101/2021.03.08.434300", - "rel_title": "Pediatric nasal epithelial cells are less permissive to SARS-CoV-2 replication compared to adult cells", + "rel_doi": "10.1101/2021.03.06.434226", + "rel_title": "Experimental susceptibility of North American raccoons (Procyon lotor) and striped skunks (Mephitis mephitis) to SARS-CoV-2", "rel_date": "2021-03-08", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.03.08.434300", - "rel_abs": "Children typically experience more mild symptoms of COVID-19 when compared to adults. There is a strong body of evidence that children are also less susceptible to SARS-CoV-2 infection with the ancestral viral isolate. However, the emergence of SARS-CoV-2 variants of concern (VOCs) has been associated with an increased number of pediatric infections. Whether this is the result of widespread adult vaccination or fundamental changes in the biology of SARS-CoV-2 remains to be determined. Here, we use primary nasal epithelial cells from children and adults, differentiated at an air-liquid interface to show that the ancestral SARS-CoV-2 replicates to significantly lower titers in the nasal epithelial cells of children compared to those of adults. This was associated with a heightened antiviral response to SARS-CoV-2 in the nasal epithelial cells of children. Importantly, the Delta variant also replicated to significantly lower titres in the nasal epithelial cells of children. This trend was markedly less pronounced in the case of Omicron. It is also striking to note that, at least in terms of viral RNA, Omicron replicated better in pediatric NECs compared to both Delta and the ancestral virus. Taken together, these data show that the nasal epithelium of children supports lower infection and replication of ancestral SARS-CoV-2, although this may be changing as the virus evolves.", - "rel_num_authors": 25, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.03.06.434226", + "rel_abs": "Skunks and raccoons were intranasally inoculated or indirectly exposed to SARS-CoV-2. Both species are susceptible to infection; however, the lack of, and low quantity of infectious virus shed by raccoons and skunks, respectively, and lack of cage mate transmission in both species, suggest that neither species are competent SARS-CoV-2 reservoirs.\n\nArticle Summary LineExperimental SARS-CoV-2 inoculation of North American raccoons and striped skunks showed susceptibility to infection, but transient, low-level shedding suggests that neither species is likely to be a competent natural reservoir.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Yanshan Zhu", - "author_inst": "School of Chemistry and Molecular Biosciences, The University of Queensland, Brisbane, Australia" - }, - { - "author_name": "Keng Yih Chew", - "author_inst": "School of Chemistry and Molecular Biosciences, The University of Queensland, Brisbane, Australia" - }, - { - "author_name": "Melanie Wu", - "author_inst": "School of Chemistry and Molecular Biosciences, The University of Queensland, Brisbane, Queensland, Australia" - }, - { - "author_name": "Anjana C. Karawita", - "author_inst": "School of Chemistry and Molecular Biosciences, The University of Queensland, Brisbane, Australia" - }, - { - "author_name": "Georgina McCallum", - "author_inst": "School of Chemistry and Molecular Biosciences, The University of Queensland, Brisbane, Queensland, Australia" - }, - { - "author_name": "Lauren E Steele", - "author_inst": "School of Chemistry and Molecular Biosciences, The University of Queensland, Brisbane, Queensland, Australia" - }, - { - "author_name": "Ayaho Yamamoto", - "author_inst": "Child Health Research Centre, The University of Queensland, South Brisbane, QLD 4101, Australia" - }, - { - "author_name": "Larisa L. Labzin", - "author_inst": "Institute for Molecular Bioscience (IMB), The University of Queensland, Brisbane, Australia" - }, - { - "author_name": "Tejasri Yarlagadda", - "author_inst": "Centre for Immunology and Infection Control, Faculty of Health, School of Biomedical Sciences, Queensland University of Technology, Brisbane Queensland 4000, Au" - }, - { - "author_name": "Alexander A. Khromykh", - "author_inst": "School of Chemistry and Molecular Biosciences, The University of Queensland, Brisbane, Australia; Australian Infectious Diseases Research Centre, Global Virus N" - }, - { - "author_name": "Xiaohui Wang", - "author_inst": "Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, Australia" - }, - { - "author_name": "Julian Sng", - "author_inst": "School of Chemistry and Molecular Biosciences, The University of Queensland, Brisbane, Queensland, Australia" - }, - { - "author_name": "Claudia J. Stocks", - "author_inst": "Institute for Molecular Bioscience (IMB), The University of Queensland, Brisbane, Australia" - }, - { - "author_name": "Yao Xia", - "author_inst": "School of Science, Edith Cowan University; School of Biomedical Science, University of Western Australia, Perth, Australia" - }, - { - "author_name": "Tobias R. Kollmann", - "author_inst": "Wal-yan Respiratory Research Centre, Telethon Kids Institute, The University of Western Australia, Perth, Australia" - }, - { - "author_name": "David Martino", - "author_inst": "Wal-yan Respiratory Research Centre, Telethon Kids Institute, The University of Western Australia, Perth, Australia" - }, - { - "author_name": "Merja Joensuu", - "author_inst": "Clem Jones Centre for Ageing Dementia Research, Queensland Brain Institute, The University of Queensland, Brisbane, QLD, Australia; Queensland Brain Institute, " - }, - { - "author_name": "Frederic A Meunier", - "author_inst": "Clem Jones Centre for Ageing Dementia Research, Queensland Brain Institute, The University of Queensland, Brisbane, QLD, Australia; Queensland Brain Institute, " - }, - { - "author_name": "Giuseppe Balistreri", - "author_inst": "Queensland Brain Institute, The University of Queensland, Brisbane, QLD, Australia; Department of Virology, Faculty of Medicine, University of Helsinki, Finland" + "author_name": "Raquel Francisco", + "author_inst": "University of Georgia" }, { - "author_name": "Helle Bielefeldt-Ohmann", - "author_inst": "School of Chemistry and Molecular Biosciences, The University of Queensland, Brisbane, Australia" + "author_name": "Sonia M Hernandez", + "author_inst": "University of Georgia" }, { - "author_name": "Asha C. Bowen", - "author_inst": "Wal-yan Respiratory Research Centre, Telethon Kids Institute, The University of Western Australia, Perth, Australia" + "author_name": "Daniel G Mead", + "author_inst": "University of Georgia" }, { - "author_name": "Anthony Kicic", - "author_inst": "Wal-yan Respiratory Research Centre, Telethon Kids Institute, The University of Western Australia, Perth, Australia" + "author_name": "Kayla G Adcock", + "author_inst": "University of Georgia" }, { - "author_name": "Peter D. Sly", - "author_inst": "Child Health Research Centre, The University of Queensland, South Brisbane, QLD 4101, Australia; Australian Infectious Diseases Research Centre, Global Virus Ne" + "author_name": "Sydney C Burke", + "author_inst": "University of Georgia" }, { - "author_name": "Kirsten M. Spann", - "author_inst": "Centre for Immunology and Infection Control, Faculty of Health, School of Biomedical Sciences, Queensland University of Technology, Brisbane Queensland 4000, Au" + "author_name": "Nicole M Nemeth", + "author_inst": "University of Georgia" }, { - "author_name": "Kirsty R. Short", - "author_inst": "School of Chemistry and Molecular Biosciences, The University of Queensland, Brisbane, Australia; Australian Infectious Diseases Research Centre, Global Virus N" + "author_name": "Michael J Yabsley", + "author_inst": "University of Georgia" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "new results", "category": "microbiology" }, @@ -881394,61 +880746,169 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.03.04.21252084", - "rel_title": "Factors associated with increased mortality in critically ill COVID-19 patients in a Mexican public hospital: the other faces of health system oversaturation.", + "rel_doi": "10.1101/2021.03.04.21252532", + "rel_title": "Serological reconstruction of COVID-19 epidemics through analysis of antibody kinetics to SARS-CoV-2 proteins", "rel_date": "2021-03-08", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.04.21252084", - "rel_abs": "BACKGROUNDThe lethality rate of COVID-19 in Mexico is one of the highest worldwide, but in-hospital factors associated with this increased rate have yet to be explored. This study aims to evaluate those factors that could be associated with mortality at 28-days in critically ill COVID-19 patients in Mexico.\n\nMETHODSThis is a retrospective analysis of the patients included in the clinical trial (NCT04381858) which recruited patients with severe COVID-19 with high oxygen requirement or mechanical ventilation from May to October 2020. The primary outcome, death at 28, was analyzed.\n\nRESULTSBetween May and October 2020, 196 predominantly male patients (n=122, 62.2%) with an average of 58.1 years ({+/-} 15.5), were included in the cohort. Mortality at 28 days was 44.3 % (n= 84). Patients included in the second trimester had a greater mortality rate when compared with those recruited in the first trimester (54.1 vs 32.1, p< 0.01). On multivariate analysis, the detected protective factors were the use of fentanyl HR 0.51 (95%CI 0.31 - 0.85, p=0.01), the use of antibiotics HR 0.22 (95% CI 0.13 - 0.36, p<0.01), and a previously healthy state (no comorbidities other than obesity) HR 0.58 (95%CI 0.35 - 0.94, p =0.03); risk factors were severe kidney injury (AKIN3) HR 1.74 (95%CI 1.04 - 2.9, p=0.035), elevated D-Dimer levels HR 1.02 (95%CI 1.007 - 1.04, p=0.005), shock OR 5.8 (2.4 - 13.8, p<0.01), and recruitment in the second trimester OR 2.3 ((1.1 - 4.8, p=0.02).\n\nCONCLUSIONSIn-hospital mortality in critically ill COVID-19 patients has increased in our center. The appropriate use of antibiotics, the type of sedation, and AKIN3 are modifiable factors directly related to this increased mortality. The increase in mortality observed in the second trimester is explained by hospital overcrowding that began in August 2020.", - "rel_num_authors": 11, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.04.21252532", + "rel_abs": "Infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) induces a complex antibody response that varies by orders of magnitude between individuals and over time. Waning antibody levels lead to reduced sensitivity of serological diagnostic tests over time. This undermines the utility of serological surveillance as the SARS-CoV-2 pandemic progresses into its second year. Here we develop a multiplex serological test for measuring antibodies of three isotypes (IgG, IgM, IgA) to five SARS-CoV-2 antigens (Spike (S), receptor binding domain (RBD), Nucleocapsid (N), Spike subunit 2, Membrane-Envelope fusion) and the Spike proteins of four seasonal coronaviruses. We measure antibody responses in several cohorts of French and Irish hospitalized patients and healthcare workers followed for up to eleven months after symptom onset. The data are analysed with a mathematical model of antibody kinetics to quantify the duration of antibody responses accounting for inter-individual variation. One year after symptoms, we estimate that 36% (95% range: 11%, 94%) of anti-S IgG remains, 31% (9%, 89%) anti-RBD IgG remains, and 7% (1%, 31%) anti-N IgG remains. Antibodies of the IgM isotype waned more rapidly, with 9% (2%, 32%) anti-RBD IgM remaining after one year. Antibodies of the IgA isotype also waned rapidly, with 10% (3%, 38%) anti-RBD IgA remaining after one year. Quantitative measurements of antibody responses were used to train machine learning algorithms for classification of previous infection and estimation of time since infection. The resulting diagnostic test classified previous infections with 99% specificity and 98% (95% confidence interval: 94%, 99%) sensitivity, with no evidence for declining sensitivity over the time scale considered. The diagnostic test also provided accurate classification of time since infection into intervals of 0 - 3 months, 3 - 6 months, and 6 - 12 months. Finally, we present a computational method for serological reconstruction of past SARS-CoV-2 transmission using the data from this test when applied to samples from a single cross-sectional sero-prevalence survey.", + "rel_num_authors": 38, "rel_authors": [ { - "author_name": "Mariana Jocelyn Macias Guzman", - "author_inst": "Centenario Hospital Miguel Hidalgo" + "author_name": "Stephane Pelleau", + "author_inst": "Malaria: Parasites and Hosts Unit, Department of Parasites and Insect Vectors, Institut Pasteur, Paris, France" }, { - "author_name": "Alejandro Castillo Gonzalez", - "author_inst": "Centenario Hospital Miguel Hidalgo" + "author_name": "Tom Woudenberg", + "author_inst": "Malaria: Parasites and Hosts Unit, Department of Parasites and Insect Vectors, Institut Pasteur, Paris, France" }, { - "author_name": "Jose Lenin Beltran Gonzalez", - "author_inst": "Centenario Hospital Miguel Hidalgo" + "author_name": "Jason Rosado", + "author_inst": "Malaria: Parasites and Hosts Unit, Department of Parasites and Insect Vectors, Institut Pasteur, Paris, France" }, { - "author_name": "Mario Gonzalez Gamez", - "author_inst": "Centenario Hospital Miguel Hidalgo" + "author_name": "Francoise Donnadieu", + "author_inst": "Malaria: Parasites and Hosts Unit, Department of Parasites and Insect Vectors, Institut Pasteur, Paris, France" }, { - "author_name": "Emmanuel Antonio Mendoza Enciso", - "author_inst": "Centenario Hospital Miguel Hidalgo" + "author_name": "Laura Garcia", + "author_inst": "Malaria: Parasites and Hosts Unit, Department of Parasites and Insect Vectors, Institut Pasteur, Paris, France" }, { - "author_name": "Itzel Ovalle Robles", - "author_inst": "Centenario Hospital Miguel Hidalgo" + "author_name": "Thomas Obadia", + "author_inst": "Malaria: Parasites and Hosts Unit, Department of Parasites and Insect Vectors, Institut Pasteur, Paris, France" }, { - "author_name": "Andrea Lucia Garcia Diaz", - "author_inst": "Centenario Hospital Miguel Hidalgo" + "author_name": "Soazic Gardais", + "author_inst": "Malaria: Parasites and Hosts Unit, Department of Parasites and Insect Vectors, Institut Pasteur, Paris, France" }, { - "author_name": "Cesar Mauricio Gutierrez Pena", - "author_inst": "Centenario Hospital Miguel Hidalgo" + "author_name": "Yasmine Elgharbawy", + "author_inst": "Malaria: Parasites and Hosts Unit, Department of Parasites and Insect Vectors, Institut Pasteur, Paris, France" }, { - "author_name": "Lucila Martinez Medina", - "author_inst": "Centenario Hospital Miguel Hidalgo" + "author_name": "Aurelie Velay", + "author_inst": "CHU de Strasbourg, Laboratoire de Virologie, F-67091 Strasbourg, France" }, { - "author_name": "Victor Antonio Monroy Colin", - "author_inst": "Centenario Hospital Miguel Hidalgo" + "author_name": "Maria Gonzalez", + "author_inst": "CHU de Strasbourg, Service de Pathologies Professionnelles, F-67091 Strasbourg, France" }, { - "author_name": "Jose Manuel Arreola Guerra", - "author_inst": "Centenario Hospital Miguel Hidalgo" + "author_name": "Jacques-Yves Nizou", + "author_inst": "Institut Mutualiste Montsouris, Paris, France" + }, + { + "author_name": "Nizar Khelil", + "author_inst": "Institut Mutualiste Montsouris, Paris, France" + }, + { + "author_name": "Konstantinos Zannis", + "author_inst": "Institut Mutualiste Montsouris, Paris, France" + }, + { + "author_name": "Charlotte Cockram", + "author_inst": "Spatial Regulation of Genomes Unit, Department of Genomes and Genetics, Institut Pasteur, Paris, France" + }, + { + "author_name": "Sarah Merkling", + "author_inst": "Insect-Virus Interactions Unit, Department of Virology and CNRS UMR 2000, Institut Pasteur, Paris, France" + }, + { + "author_name": "Annalisa Meola", + "author_inst": "Structural Virology Unit, Department of Virology and CNRS UMR 3569, Institut Pasteur, Paris, France" + }, + { + "author_name": "Solen Kerneis", + "author_inst": "Equipe Mobile d Infectiologie, APHP Centre-Universite de Paris, Paris, France" + }, + { + "author_name": "Benjamin Terrier", + "author_inst": "Department of Internal Medicine, National Referral Center for Rare Systemic Autoimmune Diseases, Assistance Publique Hopitaux de Paris-Centre (APHP-CUP), Univer" + }, + { + "author_name": "Jerome de Seze", + "author_inst": "Centre d Investigation Clinique - INSERM CIC-1434, Strasbourg, France" + }, + { + "author_name": "Delphine Planas", + "author_inst": "Virus and Immunity Unit, Department of Virology, Institut Pasteur, Paris, France" + }, + { + "author_name": "Olivier Schwartz", + "author_inst": "Virus and Immunity Unit, Department of Virology, Institut Pasteur, Paris, France" + }, + { + "author_name": "Francois Dejardin", + "author_inst": "Production and Purification of Recombinant Proteins Technological Platform, Center for Technological Resources and Research, Institut Pasteur, Paris, France" + }, + { + "author_name": "Stephane Petres", + "author_inst": "Production and Purification of Recombinant Proteins Technological Platform, Center for Technological Resources and Research, Institut Pasteur, Paris, France" + }, + { + "author_name": "Cassandre von Platen", + "author_inst": "Center for Translational Science, Institut Pasteur, Paris, France" + }, + { + "author_name": "Laurence Arowas", + "author_inst": "Investigation Clinique et Acces aux Ressources Biologiques (ICAReB), Center for Translational Research, Institut Pasteur, Paris, France." + }, + { + "author_name": "Louise Perrin de Facci", + "author_inst": "Investigation Clinique et Acces aux Ressources Biologiques (ICAReB), Center for Translational Research, Institut Pasteur, Paris, France." + }, + { + "author_name": "Darragh Duffy", + "author_inst": "Translational Immunology Lab, Institut Pasteur, Paris, France" + }, + { + "author_name": "Cliona Ni Cheallaigh", + "author_inst": "Department of Infectious Diseases, St James Hospital, Dublin, Ireland" + }, + { + "author_name": "Niall Conlon", + "author_inst": "Department of Immunology, St James Hospital, Dublin, Ireland" + }, + { + "author_name": "Liam Townsend", + "author_inst": "Department of Infectious Diseases, St James Hospital, Dublin, Ireland" + }, + { + "author_name": "Heidi Auerswald", + "author_inst": "Virology Unit, Institut Pasteur du Cambodge, Institut Pasteur International Network, Phnom Penh, Cambodia" + }, + { + "author_name": "Marija Backovic", + "author_inst": "Structural Virology Unit, Department of Virology and CNRS UMR 3569, Institut Pasteur, Paris, France" + }, + { + "author_name": "Bruno Hoen", + "author_inst": "Direction de la Recherche Medicale, Institut Pasteur, Paris, France" + }, + { + "author_name": "Arnaud Fontanet", + "author_inst": "Epidemiology of Emerging Diseases Unit, Department of Global Health, Institut Pasteur, Paris, France" + }, + { + "author_name": "Ivo Mueller", + "author_inst": "Division of Population Health and Immunity, The Walter and Eliza Hall Institute, Melbourne, Australia" + }, + { + "author_name": "Samira Fafi-Kremer", + "author_inst": "CHU de Strasbourg, Laboratoire de Virologie, F-67091 Strasbourg, France" + }, + { + "author_name": "Timothee Bruel", + "author_inst": "Virus and Immunity Unit, Department of Virology, Institut Pasteur, Paris, France" + }, + { + "author_name": "Michael T White", + "author_inst": "Malaria: Parasites and Hosts Unit, Department of Parasites and Insect Vectors, Institut Pasteur, Paris, France" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -883124,51 +882584,23 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2021.03.05.21252709", - "rel_title": "A Simple RT-PCR Melting temperature Assay to Rapidly Screen for Widely Circulating SARS-CoV-2 Variants.", + "rel_doi": "10.1101/2021.03.06.21253035", + "rel_title": "Value-based pricing of a COVID-19 vaccine", "rel_date": "2021-03-08", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.05.21252709", - "rel_abs": "BackgroundThe increased transmission of SARS-CoV-2 variants of concern (VOC) which originated in the United Kingdom (B.1.1.7), South Africa (B1.351), Brazil (P.1) and in United States (B.1.427/429) requires a vigorous public health response, including real time strain surveillance on a global scale. Although genome sequencing is the gold standard for identifying these VOCs, it is time consuming and expensive. Here, we describe a simple, rapid and high-throughput reverse-transcriptase PCR (RT-PCR) melting temperature (Tm) screening assay that identifies these three major VOCs.\n\nMethodsRT-PCR primers and four sloppy molecular beacon (SMB) probes were designed to amplify and detect the SARS-CoV-2 N501Y (A23063T) and E484K (G23012A) mutations and their corresponding wild type sequences. After RT-PCR, the VOCs were identified by a characteristic Tm of each SMB. Assay optimization and testing was performed with RNA from SARS-CoV-2 USA WA1/2020 (WT), a B.1.17 and a B.1.351 variant strains. The assay was then validated using clinical samples.\n\nResultsThe limit of detection (LOD) for both the WT and variants was 4 and 10 genomic copies/reaction for the 501 and 484 codon assays, respectively. The assay was 100% sensitive and 100% specific for identifying the N501Y and E484K mutations in cultured virus and in clinical samples as confirmed by Sanger sequencing.\n\nConclusionWe have developed an RT-PCR melt screening test for the three major VOCs which can be used to rapidly screen large numbers of patient samples providing an early warning for the emergence of these variants and a simple way to track their spread.", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.06.21253035", + "rel_abs": "AimThe purpose of this study is to determine the value-based price of a COVID-19 vaccine from a societal perspective in Germany.\n\nMethodsA decision model was constructed using, e.g., information on age-specific fatality rates, intensive care unit (ICU) costs and outcomes, and herd protection threshold. Three strategies were analysed: vaccination (with 95% and 50% efficacy), a mitigation strategy, and no intervention. The base-case time horizon was 5 years. The value of a vaccine included savings from avoiding COVID-19 mitigation measures and health benefits from avoiding COVID-19 related mortality. The value of an additional life year was borrowed from new, innovative oncological drugs, as cancer reflects a condition with a similar morbidity and mortality burden in the general population in the short term as COVID-19.\n\nResultsA vaccine with a 95% efficacy dominates the mitigation strategy strictly. The value-based price ({euro}1494) is thus determined by the comparison between vaccination and no intervention. This price is particularly sensitive to the probability of ICU admission and the herd protection threshold. In contrast, the value of a vaccine with 50% efficacy is more ambiguous.\n\nConclusionThis study yields a value-based price for a COVID-19 vaccine with 95% efficacy, which is more than 50 times greater than the purchasing price.", + "rel_num_authors": 1, "rel_authors": [ { - "author_name": "Padmapriya P. Banada", - "author_inst": "Rutgers Biomedical and Health Sciences" - }, - { - "author_name": "Raquel Green", - "author_inst": "New Jersey Medical School-RBHS" - }, - { - "author_name": "Sukalyani Banik", - "author_inst": "Rutgers Biomedical and Health Sciences" - }, - { - "author_name": "Abby Chopoorian", - "author_inst": "Rutgers New Jersey Medical School-RBHS" - }, - { - "author_name": "Deanna Streck", - "author_inst": "Institute of Genomic Medicine, Rutgers New Jersey Medical School-RBHS" - }, - { - "author_name": "Robert Jones", - "author_inst": "Craic computing LLC" - }, - { - "author_name": "Soumitesh Chakravorty", - "author_inst": "Rutgers New Jersey Medical School-RBHS and Cepheid" - }, - { - "author_name": "David Alland", - "author_inst": "New Jersey Medical School - RBHS" + "author_name": "Afschin Gandjour", + "author_inst": "Frankfurt School of Finance & Management" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "health economics" }, { "rel_doi": "10.1101/2021.03.07.21252959", @@ -885374,51 +884806,51 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.02.28.21252608", - "rel_title": "Association between SARS-CoV-2 Transmission Risk, Viral Load, and Age: A Nationwide Study in Danish Households", + "rel_doi": "10.1101/2021.03.03.21252014", + "rel_title": "COVID-19 test positivity: predictive value of various symptoms in a large community-based testing program in California", "rel_date": "2021-03-05", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.28.21252608", - "rel_abs": "AimThe objective of this nationwide study was to investigate the association between SARS-CoV-2 transmissibility, viral load, and age of primary cases in Danish households.\n\nBackgroundSpread in households represents a major mode of transmission of SARS-CoV-2. In order to take proper action against the spread of the disease, it is important to have a better understanding of transmission in the household domain--including the role of viral load of primary cases.\n\nMethodsThe study was designed as an observational cohort study, using detailed administrative register data. We included the full population of Denmark and all SARS-CoV-2 tests (August 25, 2020 to February 10, 2021) to estimate transmissibility in house-holds comprising 2-6 people. RT-PCR Cycle threshold (Ct) values were used as a proxy for viral load.\n\nResultsWe identified 63,657 primary cases and 139,882 household members of which 21% tested positive by RT-PCR within a 1-14 day period after the primary case. There was an approximately linear association between Ct value of the sample and transmissibility, implying that cases with samples having a higher viral load were more transmissible than cases with samples having a lower viral load. However, even for primary cases with relatively high sample Ct values, the transmissibility was not negligible, e.g., for primary cases with a sample Ct value of 38, we found that 13% of the primary cases had at least one secondary household case. Moreover, 34% of all secondary cases were found in households with primary cases having sample Ct values >30. An increasing transmissibility with age of the primary cases for adults ([≥]20 years) and a decreasing transmissibility with age for children (<20 years) were found.\n\nConclusionsAlthough primary cases with sample high viral loads (low Ct values) were associated with higher SARS-CoV-2 transmissibility, we found no obvious cut-off for sample Ct values to eliminate transmissibility and a substantial amount of household transmission occurred in households where the primary cases had high sample Ct values (low viral load), The study further showed that transmissibility increases with age. These results have important public health implications, as they suggest that contact tracing should prioritize cases according to Ct values and age, and underline the importance of quick identification and isolation of cases. Furthermore, the study highlights that households can serve as a transmission bridge by creating connections between otherwise separate domains.", + "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.03.21252014", + "rel_abs": "BackgroundMuch of the early data on COVID-19 symptomatology was captured in the hospital setting. In a community setting the symptoms most predictive of SARS-CoV-2 positivity may be different. Data from the California sites of a COVID-19 community testing program are presented here.\n\nMethodsPrior to being tested, participants in the Baseline COVID-19 Testing Program completed an online screener, in which they self-reported basic demographics and the presence or absence of 10 symptoms. Both positive and negative COVID-19 RT-PCR tests were linked back to the screener data. A multivariable model of positivity was fit using generalized estimating equations, adjusting for month of testing as a fixed effect and accounting for clustering of data within each test site.\n\nResultsAmong 547,018 first-time tests in California in 2020, positivity rates were 3.4%, 9.9%, and 19.8% for participants with no symptoms, 1 symptom, or 2 or more symptoms at the time of screening, respectively. All ten symptoms were individually associated with higher positivity rates, but only six of ten symptoms were associated with higher positivity when adjusting for other symptoms. Major symptoms with highest predictive value were recent loss of taste or smell, fever, and coughing with ORs of 3.27, 1.97, and 1.95, respectively. Shortness of breath and vomiting or diarrhea were negatively associated with positivity adjusting for other symptoms and, absent other symptoms, participants with these symptoms did not have significantly higher positivity rates than asymptomatic participants.\n\nConclusionsRecent loss of taste and smell should be elevated to a major symptom along with fever and coughing in public health messaging and in our community approach to testing and surveillance, while mild to moderate shortness of breath should be de-emphasized as a sensitive early predictor of COVID-19 positivity.", "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Frederik Plesner Lyngse", - "author_inst": "University of Copenhagen" + "author_name": "David P Miller", + "author_inst": "Verily Life Sciences" }, { - "author_name": "K\u00e5re M\u00f8lbak", - "author_inst": "Statens Serum Institut" + "author_name": "Scott Morrow", + "author_inst": "San Mateo County" }, { - "author_name": "Kristina Tr\u00e6holt Franck", - "author_inst": "Statens Serum Institut" + "author_name": "Robert M Califf", + "author_inst": "Verily Life Sciences" }, { - "author_name": "Claus Nielsen", - "author_inst": "Statens Serum Institut" + "author_name": "Cameron Kaiser", + "author_inst": "Riverside County" }, { - "author_name": "Robert Leo Skov", - "author_inst": "Statens Serum Institut" + "author_name": "Ritu Kapur", + "author_inst": "Verily Life Sciences" }, { - "author_name": "Marianne Voldstedlund", - "author_inst": "Statens Serum Institut" + "author_name": "Casimir Starsiak III", + "author_inst": "Verily Life Sciences" }, { - "author_name": "Arieh S. Cohen", - "author_inst": "Statens Serum Institut" + "author_name": "Jessica Mega", + "author_inst": "Verily Life Sciences" }, { - "author_name": "Carsten Thure Kirkeby", - "author_inst": "University of Copenhagen" + "author_name": "William J Marks Jr.", + "author_inst": "Verily Life Sciences" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "public and global health" }, { "rel_doi": "10.1101/2021.03.04.21252540", @@ -887092,31 +886524,39 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2021.03.04.433970", - "rel_title": "Molecular strategies for antibody binding and escape of SARS-CoV-2 and its mutations", + "rel_doi": "10.1101/2021.03.02.21249552", + "rel_title": "Modeling transmission dynamics and effectiveness of worker screening programs for SARS-CoV-2 in pork processing plants", "rel_date": "2021-03-05", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.03.04.433970", - "rel_abs": "The COVID19 pandemic, caused by SARS-CoV-2, has infected more than 100 million people worldwide. Due to the rapid spreading of SARS-CoV-2 and its impact, it is paramount to find effective treatments against it. Human neutralizing antibodies are an effective method to fight viral infection. However, the recent discovery of new strains that substantially change the S-protein sequence has raised concern about vaccines and antibodies effectiveness. Here, we investigated the binding mechanisms between the S-protein and several antibodies. Multiple mutations were included to understand the strategies for antibody escape in new variants. We found that the combination of mutations K417N and E484K produced higher binding energy to ACE2 than the wild type, suggesting higher efficiency to enter host cells. The mutations effect depends on the antibody class. While Class I enhances the binding avidity in the presence of N501Y mutation, class II antibodies showed a sharp decline in the binding affinity. Our simulations suggest that Class I antibodies will remain effective against the new strains. In contrast, Class II antibodies will have less affinity to the S-protein, potentially affecting these antibodies efficiency.", - "rel_num_authors": 3, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.02.21249552", + "rel_abs": "Pork processing plants were apparent hotspots for SARS-CoV2 in the spring of 2020. As a result, the swine industry was confronted with a major occupational health, financial, and animal welfare crisis. The objective of this work was to describe the epidemiological situation within processing plants, develop mathematical models to simulate transmission in these plants, and test the effectiveness of routine PCR screening at minimizing SARS-CoV2 circulation. Cumulative incidence of clinical (PCR-confirmed) disease plateaued at [~]2.5% to 25% across the three plants studied here. For larger outbreaks, antibody prevalence was approximately 30% to 40%. Secondly, we developed a mathematical model that accounts for asymptomatic, pre-symptomatic, and background \"community\" transmission. By calibrating this model to observed epidemiological data, we estimated the initial reproduction number (R) of the virus. Across plants, R generally ranged between 2 and 4 during the initial phase, but subsequently declined to [~]1 after two to three weeks, most likely as a result of implementation/compliance with biosecurity measures in combination with population immunity. Using the calibrated model to simulate a range of possible scenarios, we show that the effectiveness of routine PCR-screening at minimizing disease spread was far more influenced by testing frequency than by delays in results, R, or background community transmission rates. Testing every three days generally averted about 25% to 40% of clinical cases across a range of assumptions, while testing every 14 days typically averted 7 to 13% of clinical cases. However, the absolute number of additional clinical cases expected and averted was influenced by whether there was residual immunity from a previous peak (i.e., routine testing is implemented after the workforce had experienced an initial outbreak). In contrast, when using PCR-screening to prevent outbreaks or in the early stages of an outbreak, even frequent testing may not prevent a large outbreak within the workforce. This research helps to identify protocols that minimize risk to occupational safety and health and support continuity of business for U.S. processing plants. While the model was calibrated to meat processing plants, the structure of the model and insights about testing are generalizable to other settings where large number of people work in close proximity.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Mohamed Hendy", - "author_inst": "The University of British Columbia" + "author_name": "Kimberly VanderWaal", + "author_inst": "University of Minnesota" }, { - "author_name": "Samuel Kaufman", - "author_inst": "The University of British Columbia" + "author_name": "Lora Black", + "author_inst": "Sanford Research" }, { - "author_name": "Mauricio Ponga", - "author_inst": "University of British Columbia" + "author_name": "Judy Hodge", + "author_inst": "Katrime Integrated Health" + }, + { + "author_name": "Addisalem Bedada", + "author_inst": "University of Minnesota" + }, + { + "author_name": "Scott Dee", + "author_inst": "Pipestone Veterinary Services" } ], "version": "1", - "license": "cc_by_nc", - "type": "new results", - "category": "biophysics" + "license": "cc_no", + "type": "PUBLISHAHEADOFPRINT", + "category": "epidemiology" }, { "rel_doi": "10.1101/2021.03.02.21252801", @@ -889066,37 +888506,45 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2021.03.01.21252678", - "rel_title": "COVID-19 Mortality in California Based on Death Certificates: Disproportionate Impacts Across Racial/Ethnic Groups and Nativity", + "rel_doi": "10.1101/2021.03.01.21252457", + "rel_title": "Recent changes in COVID-19 Vaccine Hesitancy among Healthcare Workers", "rel_date": "2021-03-03", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.01.21252678", - "rel_abs": "PurposeTo examine characteristics of coronavirus disease 2019 (COVID-19) decedents in California (CA) and evaluate for disproportionate mortality across race/ethnicity and ethnicity/nativity.\n\nMethodsCOVID-19 deaths were identified from death certificates. Age-adjusted mortality rate ratios (MRR) were compared across race/ethnicity. Proportionate mortality rates (PMR) were compared across race/ethnicity and by ethnicity/nativity.\n\nResultsWe identified 10,200 COVID-19 deaths in CA occurring February 1 through July 31, 2020. Decedents tended to be older, male, Hispanic, foreign-born, and have lower educational attainment. MRR indicated elevated COVID-19 morality rates among Asian/Pacific Islander, Black, and Hispanic groups compared with the White group, with Black and Hispanic groups having the highest MRR at 2.75 (95%CI:2.54-2.97) and 4.18 (95%CI: 3.99-4.37), respectively. Disparities were larger at younger ages. Similar results were observed with PMR, which remained in analyses stratified by education. Elevated PMR were observed in all ethnicity/nativity groups, especially foreign-born Hispanic individuals, relative to U.S.-born non-Hispanic individuals, were generally larger at younger ages, and persisted after stratifying by education.\n\nConclusionsDifferential COVID-19 mortality was observed in California across racial/ethnic groups and by ethnicity/nativity groups with evidence of greater disparities among younger age groups. Identifying COVID-19 disparities is an initial step towards mitigating disease impacts in vulnerable communities.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.01.21252457", + "rel_abs": "IntroductionEarly COVID-19 vaccine acceptance rates suggest that up to one-third of HCWs may be vaccine-hesitant. However, it is unclear whether hesitancy among HCWs has improved with time and if there are temporal changes whether these differ by healthcare worker role.\n\nMethodsIn October 2020, a brief survey was sent to all participants in the Healthcare Worker Exposure Response and Outcomes (HERO) Registry with a yes/no question regarding vaccination under emergency use authorization (EUA): \"If an FDA emergency use-approved vaccine to prevent coronavirus/COVID-19 was available right now at no cost, would you agree to be vaccinated?\" The poll was repeated in December 2020, with the same question sent to all registry participants. Willingness was defined as a \"Yes\" response, and hesitancy was defined as a \"No\" response. Participants were stratified into clinical care roles. Baseline demographics of survey respondents at each timepoint were compared using appropriate univariate statistics (chi-squared and t-tests). Analyses were descriptive, with frequencies and percentages reported for each category.\n\nResultsOf 4882 HERO active registry participants during September 1 - October 31, 2020, 2070 (42.4%) completed the October survey, and n=1541 (31.6%) completed the December survey. 70.2% and 67.7% who were in clinical care roles, respectively. In October, 54.2% of HCWs in clinical roles said they would take an EUA-approved vaccine, which increased to 76.2% in December. The largest gain in vaccine willingness was observed among physicians, 64.0% of whom said they would take a vaccine in October, compared with 90.5% in December. Nurses were the least likely to report that they would take a vaccine in both October (46.6%) and December (66.9%). We saw no statistically significant differences in age, race/ethnicity, gender, or medical role between time points. When restricting to the 998 participants who participated at both time points, 69% were vaccine-willing at both time points; 15% were hesitant at both time points, 13% who were hesitant in October were willing in December; and 2.9% who were willing in October were hesitant in December.\n\nConclusionsIn a set of cross-sectional surveys of vaccine acceptance among healthcare workers, willingness improved substantially over 2 calendar months during which the US had a presidential election and two vaccine manufacturers released top-line Phase 3 trial results. While improved willingness was observed in all role categories, nurses reported the most vaccine hesitancy at both time points.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Erika Garcia", - "author_inst": "University of Southern California" + "author_name": "Emily C OBrien", + "author_inst": "Duke University" }, { - "author_name": "Sandrah P Eckel", - "author_inst": "University of Southern California" + "author_name": "Haolin Xu", + "author_inst": "Duke University" }, { - "author_name": "Zhanghua Chen", - "author_inst": "University of Southern California" + "author_name": "Lauren W. Cohen", + "author_inst": "Duke University" }, { - "author_name": "Kenan Li", - "author_inst": "University of Southern California" + "author_name": "Elizabeth A. Shenkman", + "author_inst": "University of Florida" }, { - "author_name": "Frank Gilliland", - "author_inst": "University of Southern California" + "author_name": "Russell L. Rothman", + "author_inst": "Vanderbilt University" + }, + { + "author_name": "Christopher B. Forrest", + "author_inst": "Children's Hospital of Philadelphia" + }, + { + "author_name": "Adrian F. Hernandez", + "author_inst": "Duke University" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", "category": "public and global health" }, @@ -891344,107 +890792,79 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.03.02.21252768", - "rel_title": "Impact of COVID-19 pre-test probability on positive predictive value of high cycle threshold SARS-CoV-2 real-time reverse transcription PCR test results", + "rel_doi": "10.1101/2021.03.02.21252734", + "rel_title": "Relation of severe COVID-19 in Scotland to transmission-related factors and risk conditions eligible for shielding support: REACT-SCOT case-control study", "rel_date": "2021-03-03", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.02.21252768", - "rel_abs": "BackgroundPerformance characteristics of SARS-CoV-2 nucleic acid detection assays are understudied within contexts of low pre-test probability, including screening asymptomatic persons without epidemiological links to confirmed cases, or asymptomatic surveillance testing. SARS-CoV-2 detection without symptoms may represent resolved infection with persistent RNA shedding, presymptomatic or asymptomatic infection, or a false positive test. This study assessed clinical specificity of SARS-CoV-2 real-time reverse transcription polymerase chain reaction (rRT-PCR) assays by retesting positive specimens from five pre-test probability groups ranging from high to low with an alternate assay.\n\nMaterials and MethodsA total of 122 rRT-PCR positive specimens collected from unique patients between March and July 2020 were retested using a laboratory-developed nested RT-PCR assay targeting the RNA-dependent RNA polymerase (RdRp) gene followed by Sanger sequencing.\n\nResultsSignificantly less positive results in the lowest pre-test probability group (facilities with institution-wide screening having [≤] 3 positive asymptomatic cases) were reproduced with the nested RdRp gene RT-PCR assay than in all other groups combined (5/32, 15{middle dot}6% vs 61/90, 68%; p <0{middle dot}0001), and in each subgroup with higher pre-test probability (individual subgroup range 50{middle dot}0% to 85{middle dot}0%).\n\nConclusionsA higher proportion of false-positive test results are likely with lower pre-test probability. Positive SARS-CoV-2 PCR results should be interpreted within the context of patient history, clinical setting, known exposure, and estimated community disease prevalence. Large-scale SARS-CoV-2 screening testing initiatives among low pre-test probability populations should be evaluated thoroughly prior to implementation given the risk of false positives and consequent potential for harm at the individual and population level.", - "rel_num_authors": 22, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.02.21252734", + "rel_abs": "BackgroundClinically vulnerable individuals have been advised to shield themselves during the COVID-19 epidemic. The objectives of this study were to investigate: (1) the risk of severe COVID-19 in those eligible for shielding, and (2) the relation of severe COVID-19 to transmission-related factors in those in shielding and the general population.\n\nMethodsAll 178578 diagnosed cases of COVID-19 in Scotland from 1 March 2020 to 18 February 2021 were matched for age, sex and primary care practice to 1744283 controls from the general population. This dataset (REACT-SCOT) was linked to the list of 212702 individuals identified as eligible for shielding. Severe COVID-19 was defined as cases that entered critical care or were fatal.\n\nResultsWith those without risk conditions as reference category, the univariate rate ratio for severe COVID-19 was 3.21 (95% CI 3.01 to 3.41) in those with moderate risk conditions and 6.3 (95% CI 5.8 to 6.8) in those eligible for shielding. The highest rate was in solid organ transplant recipients: rate ratio 13.4 (95% CI 9.6 to 18.8). Risk of severe COVID-19 increased with the number of adults but decreased with the number of school-age children in the household. Severe COVID-19 was strongly associated with recent exposure to hospital (defined as 5 to 14 days before presentation date): rate ratio 12.3 (95% CI 11.5 to 13.2) overall. To test for causality, a case-crossover analysis was undertaken; with less recent exposure only (15 to 24 days before first testing positive) as reference category, the rate ratio associated with recent exposure only was 5.9 (95% CI 3.6 to 9.7). The population attributable risk fraction for recent exposure to hospital peaked at 50% in May 2020 and again at 65% in December 2020.\n\nConclusionsThe effectiveness of shielding vulnerable individuals was limited by the inability to control transmission in hospital and from other adults in the household. For solid organ transplant recipients, in whom the efficacy of vaccines is uncertain, these results support a policy of offering vaccination to household contacts. Mitigating the impact of the epidemic requires control of nosocomial transmission.", + "rel_num_authors": 15, "rel_authors": [ { - "author_name": "Jonathan B Gubbay", - "author_inst": "Ontario Agency for Health Protection and Promotion" - }, - { - "author_name": "Heather Rilkoff", - "author_inst": "Public Health Ontario" - }, - { - "author_name": "Heather L. Kristjanson", - "author_inst": "Ontario Agency For Health Protection and Promotion" - }, - { - "author_name": "Jessica D. Forbes", - "author_inst": "Ontario Agency for Health Protection and Promotion" - }, - { - "author_name": "Michelle Murti", - "author_inst": "Ontario Agency for Health Protection and Promotion" - }, - { - "author_name": "AliReza Eshaghi", - "author_inst": "Ontario Agency for Health Protection and Promotion" - }, - { - "author_name": "George Broukhanski", - "author_inst": "University of Toronto" - }, - { - "author_name": "Antoine Corbeil", - "author_inst": "Public Health Ontario" + "author_name": "Paul M McKeigue", + "author_inst": "University of Edinburgh" }, { - "author_name": "Nahuel Fittipaldi", - "author_inst": "Public Health Ontario" + "author_name": "David McAllister", + "author_inst": "University of Glasgow" }, { - "author_name": "Jessica Hopkins", - "author_inst": "Public Health Ontario" + "author_name": "David Caldwell", + "author_inst": "Public Health Scotland" }, { - "author_name": "Erik Kristjanson", - "author_inst": "Public Health Ontario" + "author_name": "Ciara Gribben", + "author_inst": "Public Health Scotland" }, { - "author_name": "Julianne V Kus", - "author_inst": "Public Health Ontario" + "author_name": "Jen Bishop", + "author_inst": "Public Health Scotland" }, { - "author_name": "Liane Macdonald", - "author_inst": "Public Health Ontario" + "author_name": "Stuart J McGurnaghan", + "author_inst": "University of Edinburgh" }, { - "author_name": "Anna Majury", - "author_inst": "Public Health Ontario, Ontario, Canada" + "author_name": "Matthew Armstrong", + "author_inst": "Public Health Scotland" }, { - "author_name": "Gustavo V Mallo", - "author_inst": "Public Health Ontario" + "author_name": "Joke Delvaux", + "author_inst": "Public Health Scotland" }, { - "author_name": "Tony Mazzulli", - "author_inst": "Mt Sinai Hospital, and University Health Network" + "author_name": "Sam Colville", + "author_inst": "Public Health Scotland" }, { - "author_name": "Roberto G Melano", - "author_inst": "Public Health Ontario" + "author_name": "Sharon Hutchinson", + "author_inst": "Glasgow Caledonian University; Public Health Scotland" }, { - "author_name": "Romy Olsha", - "author_inst": "Public Health Ontario" + "author_name": "Chris Robertson", + "author_inst": "Strathclyde University; Public Health Scotland" }, { - "author_name": "Stephen J Perusini", - "author_inst": "Public Health Ontario" + "author_name": "Nazir Lone", + "author_inst": "University of Edinburgh" }, { - "author_name": "Vanessa Tran", - "author_inst": "Ontario Public Health Laboratory" + "author_name": "Jim McMenamin", + "author_inst": "Public Health Scotland" }, { - "author_name": "Vanessa Gray Allen", - "author_inst": "Public Health Ontario" + "author_name": "David Goldberg", + "author_inst": "Public Health Scotland" }, { - "author_name": "Samir N Patel", - "author_inst": "Public Health Ontario" + "author_name": "Helen M Colhoun", + "author_inst": "University of Edinburgh" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2021.03.02.21252750", @@ -893170,35 +892590,107 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.02.28.21252181", - "rel_title": "Impact of COVID-19 on healthcare workers at a cancer care centre", + "rel_doi": "10.1101/2021.03.02.433434", + "rel_title": "High-content screening of coronavirus genes for innate immune suppression revealsenhanced potency of SARS-CoV-2 proteins", "rel_date": "2021-03-02", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.28.21252181", - "rel_abs": "BackgroundThe services of front-line health care workers (HCWs) have been paramount in the management of novel coronavirus disease 2019 (COVID-19). Health care professionals have been at high occupational risk of getting disease and even dying of the disease, however; they have been the subject of very limited studies in terms of COVID-19. The objectives of this study are to examine the incidence and the impact of COVID-19 infection among HCWs in terms of recovery, productivity, quality of life (QOL) and post-COVID complications.\n\nMaterials and MethodsThis was a retrospective, questionnaire based study including demographic details, workplace characteristics, symptoms, source/ spread of infection, details of recovery and the consequences of COVID-19 comprising impaired productivity/ QOL, post-COVID-19 complications and others. The data were analyzed by using IBM SPSS software (Version 23, SPSS Inc., Chicago, IL, USA).\n\nResults and ConclusionsOut of a total of 1482 employees, 18.3% (271) were laboratory confirmed to have contracted novel contagion during the study period of 5 months. The median age at diagnosis was 29 (range, 21-62) years. Front-line workers and female workers were the most infected personnel with COVID-19. Flu-like symptoms were the most frequently experienced symptoms. The median time for recovery was 20 (range, 2-150) days. The relationship between pre-existing comorbidities and age was highly significant. The QOL and productivity were associated with pre-existing comorbidities, severity of the disease, time for recovery and post-COVID syndrome. More than a half (51.8%) of all HCWs had suffered from post-COVID complications. There was no fatality reported due to COVID-19. The post-COVID complications were related to pre-existing comorbidities, severity of disease, time for recovery and status of recovery. Further research to explore the consequences of COVID-19 is warranted. The general public needs to be aware of symptoms and management of the post-COVID syndrome.", - "rel_num_authors": 4, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2021.03.02.433434", + "rel_abs": "Suppression of the host intracellular innate immune system is an essential aspect of viral replication. Here, we developed a suite of medium-throughput high-content cell-based assays to reveal the effect of individual coronavirus proteins on antiviral innate immune pathways. Using these assays, we screened the 196 protein products of seven coronaviruses (SARS-CoV-2, SARS-CoV-1, 229E, NL63, OC43, HKU1 and MERS). This includes a previously unidentified gene in SARS-CoV-2 encoded within the Spike gene. We observe immune-suppressing activity in both known host-suppressing genes (e.g., NSP1, Orf6, NSP3, and NSP5) as well as other coronavirus genes, including the newly identified SARS-CoV-2 protein. Moreover, the genes encoded by SARS-CoV-2 are generally more potent immune suppressors than their homologues from the other coronaviruses. This suite of pathway-based and mechanism-agnostic assays could serve as the basis for rapid in vitro prediction of the pathogenicity of novel viruses based on provision of sequence information alone.", + "rel_num_authors": 22, "rel_authors": [ { - "author_name": "Atika Dogra", - "author_inst": "Rajiv Gandhi Cancer Institute and Research Centre" + "author_name": "Erika J Olson", + "author_inst": "Harvard Medical School" }, { - "author_name": "ANUJ PARKASH", - "author_inst": "RAJIV GANDHI CANCER INSTITUTE AND RESEARCH CENTRE" + "author_name": "David M Brown", + "author_inst": "J. Craig Venter Institute" }, { - "author_name": "Anurag Mehta", - "author_inst": "Rajiv Gandhi Cancer Institute and Research Centre" + "author_name": "Timothy Z Chang", + "author_inst": "Harvard Medical School" }, { - "author_name": "Meenu Bhatia", - "author_inst": "Rajiv Gandhi Cancer Institute and Research Centre" + "author_name": "Lin Ding", + "author_inst": "J. Craig Venter Institute" + }, + { + "author_name": "Tai L Ng", + "author_inst": "Harvard Medical School" + }, + { + "author_name": "H. Sloane Weiss", + "author_inst": "Harvard Medical School" + }, + { + "author_name": "Peter Koch", + "author_inst": "Harvard Medical School" + }, + { + "author_name": "Yukiye Koide", + "author_inst": "Harvard Medical School" + }, + { + "author_name": "Nathan Rollins", + "author_inst": "Harvard Medical School" + }, + { + "author_name": "Pia Mach", + "author_inst": "Harvard Medical School" + }, + { + "author_name": "Tobias Meisinger", + "author_inst": "Harvard Medical School" + }, + { + "author_name": "Trenton Bricken", + "author_inst": "Harvard Medical Shool" + }, + { + "author_name": "Joshus Rollins", + "author_inst": "Harvard Medical School" + }, + { + "author_name": "Yun Zhang", + "author_inst": "J. Craig Venter Institute" + }, + { + "author_name": "Colin Molloy", + "author_inst": "Harvard Medical School" + }, + { + "author_name": "Yun Zhang", + "author_inst": "J. Craig Venter Institute" + }, + { + "author_name": "Briodget N Queenan", + "author_inst": "Harvard Medical School" + }, + { + "author_name": "Timothy Mitchison", + "author_inst": "Harvard Medical School" + }, + { + "author_name": "Debora Marks", + "author_inst": "Harvard Medical School" + }, + { + "author_name": "Jeffrey C Way", + "author_inst": "Harvard Medical School" + }, + { + "author_name": "John I Glass", + "author_inst": "J. Craig Venter Institute" + }, + { + "author_name": "Pamela A Silver", + "author_inst": "Harvard Medical School" } ], "version": "1", "license": "cc_by_nc_nd", - "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "type": "new results", + "category": "systems biology" }, { "rel_doi": "10.1101/2021.03.02.433522", @@ -894916,51 +894408,83 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.02.09.21251427", - "rel_title": "A rigorous evaluation of optimal peptide targets for MS-based clinical diagnostics of Coronavirus Disease 2019 (COVID-19).", + "rel_doi": "10.1101/2021.02.27.433054", + "rel_title": "Mice immunized with the vaccine candidate HexaPro spike produce neutralizing antibodies against SARS-CoV-2", "rel_date": "2021-03-01", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.09.21251427", - "rel_abs": "The Coronavirus Disease 2019 (COVID-19) global pandemic has had a profound, lasting impact on the worlds population. A key aspect to providing care for those with COVID-19 and checking its further spread is early and accurate diagnosis of infection, which has been generally done via methods for amplifying and detecting viral RNA molecules. Detection and quantitation of peptides using targeted mass spectrometry-based strategies has been proposed as an alternative diagnostic tool due to direct detection of molecular indicators from non-invasively collected samples as well as the potential for high-throughput analysis in a clinical setting; many studies have revealed the presence of viral peptides within easily accessed patient samples. However, evidence suggests that some viral peptides could serve as better indicators of COVID-19 infection status than others, due to potential misidentification of peptides derived from human host proteins, poor spectral quality, high limits of detection etc. In this study we have compiled a list of 639 peptides identified from Sudden Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) samples, including from in vitro and clinical sources. These datasets were rigorously analyzed using automated, Galaxy-based workflows containing tools such as PepQuery, BLAST-P, and the Multi-omic Visualization Platform as well as the open-source tools MetaTryp and Proteomics Data Viewer (PDV). Using PepQuery for confirming peptide spectrum matches, we were able to narrow down the 639 peptide possibilities to 87 peptides which were most robustly detected and specific to the SARS-CoV-2 virus. The specificity of these sequences to coronavirus taxa was confirmed using Unipept and BLAST-P. Applying stringent statistical scoring thresholds, combined with manual verification of peptide spectrum match quality, 4 peptides derived from the nucleocapsid phosphoprotein and membrane protein were found to be most robustly detected across all cell culture and clinical samples, including those collected non-invasively. We propose that these peptides would be of the most value for clinical proteomics applications seeking to detect COVID-19 from a variety of sample types. We also contend that samples taken from the upper respiratory tract and oral cavity have the highest potential for diagnosis of SARS-CoV-2 infection from easily collected patient samples using mass spectrometry-based proteomics assays.", - "rel_num_authors": 8, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2021.02.27.433054", + "rel_abs": "Updated and revised versions of COVID-19 vaccines are vital due to genetic variations of the SARS-CoV-2 spike antigen. Furthermore, vaccines that are safe, cost-effective, and logistically friendly are critically needed for global equity, especially for middle to low income countries. Recombinant protein-based subunit vaccines against SARS-CoV-2 have been reported with the use of the receptor binding domain (RBD) and the prefusion spike trimers (S-2P). Recently, a new version of prefusion spike trimers, so called \"HexaPro\", has been shown for its physical property to possess two RBD in the \"up\" conformation, as opposed to just one exposed RBD found in S-2P. Importantly, this HexaPro spike antigen is more stable than S-2P, raising its feasibility for global logistics and supply chain. Here, we report that the spike protein HexaPro offers a promising candidate for SARS-CoV-2 vaccine. Mice immunized by the recombinant HexaPro adjuvanted with aluminium hydroxide using a prime-boost regimen produced high-titer neutralizing antibodies for up to 56 days after initial immunization against live SARS-CoV-2 infection. In addition, the level of neutralization activity is comparable to that of convalescence sera. Our results indicate that the HexaPro subunit vaccine confers neutralization activity in sera collected from mice receiving the prime-boost regimen.", + "rel_num_authors": 16, "rel_authors": [ { - "author_name": "Andrew T Rajczewski", - "author_inst": "University of Minnesota" + "author_name": "Chotiwat Seephetdee", + "author_inst": "Department of Biochemistry, Faculty of Science, Mahidol University, Bangkok, Thailand, 10400" }, { - "author_name": "Subina Mehta", - "author_inst": "University of Minnesota" + "author_name": "Nattawut Buasri", + "author_inst": "Department of Biochemistry, Faculty of Science, Mahidol University, Bangkok, Thailand, 10400" }, { - "author_name": "Dinh Duy An Ngyuen", - "author_inst": "University of Minnesota" + "author_name": "Kanit Bhukhai", + "author_inst": "Department of Physiology, Faculty of Science, Mahidol University, Bangkok, Thailand, 10400" }, { - "author_name": "Bj\u00f6rn Andreas Gr\u00fcning", - "author_inst": "Uni-Freiburg" + "author_name": "Kitima Srisanga", + "author_inst": "Department of Biochemistry, Faculty of Science, Mahidol University, Bangkok, Thailand, 10400" }, { - "author_name": "James E Johnson", - "author_inst": "University of Minnesota" + "author_name": "Suwimon Manopwisedjaroen", + "author_inst": "Department of Microbiology, Faculty of Science, Mahidol University, Bangkok, Thailand, 10400" }, { - "author_name": "Thomas F McGowan", - "author_inst": "University of Minnesota" + "author_name": "Sarat Lertjintanakit", + "author_inst": "Department of Biochemistry, Faculty of Science, Mahidol University, Bangkok, Thailand, 10400" }, { - "author_name": "Timothy Griffin", - "author_inst": "University of Minnesota" + "author_name": "Nut Phueakphud", + "author_inst": "Department of Biochemistry, Faculty of Science, Mahidol University, Bangkok, Thailand, 10400" }, { - "author_name": "Pratik Jagtap", - "author_inst": "University of Minnesota" + "author_name": "Chatbenja Pakiranay", + "author_inst": "Department of Biochemistry, Faculty of Science, Mahidol University, Bangkok, Thailand, 10400" + }, + { + "author_name": "Niwat Kangwanrangsan", + "author_inst": "Department of Pathobiology, Faculty of Science, Mahidol University, Bangkok, Thailand, 10400" + }, + { + "author_name": "Sirawat Srichatrapimuk", + "author_inst": "Chakri Naruebodindra Medical Institute, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok, Samut Prakan, Thailand, 10540" + }, + { + "author_name": "Somnuek Sungkanuparph", + "author_inst": "Chakri Naruebodindra Medical Institute, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok, Samut Prakan, Thailand, 10540" + }, + { + "author_name": "Suppachok Kirdlarp", + "author_inst": "Chakri Naruebodindra Medical Institute, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok, Samut Prakan, Thailand, 10540" + }, + { + "author_name": "Somchai Chutipongtanate", + "author_inst": "Department of Pediatrics, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok, Thailand, 10400" + }, + { + "author_name": "Arunee Thitithanyanont", + "author_inst": "Department of Microbiology, Faculty of Science, Mahidol University, Bangkok, Thailand, 10400" + }, + { + "author_name": "Suradej Hongeng", + "author_inst": "Department of Pediatrics, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok, Thailand, 10400" + }, + { + "author_name": "Patompon Wongtrakoongate", + "author_inst": "Department of Biochemistry, Faculty of Science, Mahidol University, Bangkok, Thailand, 10400 and Center for Neuroscience, Faculty of Science, Mahidol University" } ], - "version": "2", + "version": "1", "license": "cc_by_nc_nd", - "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "type": "new results", + "category": "immunology" }, { "rel_doi": "10.1101/2021.03.01.433110", @@ -896630,195 +896154,23 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.02.25.21252433", - "rel_title": "Predicting COVID-19 related death using the OpenSAFELY platform", + "rel_doi": "10.1101/2021.02.25.21252445", + "rel_title": "Emergent effects of contact tracing robustly stabilize outbreaks", "rel_date": "2021-03-01", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.25.21252433", - "rel_abs": "ObjectivesTo compare approaches for obtaining relative and absolute estimates of risk of 28-day COVID-19 mortality for adults in the general population of England in the context of changing levels of circulating infection.\n\nDesignThree designs were compared. (A) case-cohort which does not explicitly account for the time-changing prevalence of COVID-19 infection, (B) 28-day landmarking, a series of sequential overlapping sub-studies incorporating time-updating proxy measures of the prevalence of infection, and (C) daily landmarking. Regression models were fitted to predict 28-day COVID-19 mortality.\n\nSettingWorking on behalf of NHS England, we used clinical data from adult patients from all regions of England held in the TPP SystmOne electronic health record system, linked to Office for National Statistics (ONS) mortality data, using the OpenSAFELY platform.\n\nParticipantsEligible participants were adults aged 18 or over, registered at a general practice using TPP software on 1st March 2020 with recorded sex, postcode and ethnicity. 11,972,947 individuals were included, and 7,999 participants experienced a COVID-19 related death. The study period lasted 100 days, ending 8th June 2020.\n\nPredictorsA range of demographic characteristics and comorbidities were used as potential predictors. Local infection prevalence was estimated with three proxies: modelled based on local prevalence and other key factors; rate of A&E COVID-19 related attendances; and rate of suspected COVID-19 cases in primary care.\n\nMain outcome measuresCOVID-19 related death.\n\nResultsAll models discriminated well between patients who did and did not experience COVID-19 related death, with C-statistics ranging from 0.92-0.94. Accurate estimates of absolute risk required data on local infection prevalence, with modelled estimates providing the best performance.\n\nConclusionsReliable estimates of absolute risk need to incorporate changing local prevalence of infection. Simple models can provide very good discrimination and may simplify implementation of risk prediction tools in practice.", - "rel_num_authors": 44, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.25.21252445", + "rel_abs": "Covid-19 neither dissolved nor got out of control over a year. In many instances, the new daily cases exhibit an equilibrium at a meagre percentage of the population. Seemingly impossible due to the precise cancellation of positive and negative effects. Here, I propose models on real-world networks that capture the mysterious dynamics. I investigate the contact-tracing and related effects as possible causes. I differentiate the impact of contact-tracing into three--one direct and two emergent--effects: isolation of the documented patients direct infectees (descendants), isolation of non-descendant infectees, and temporary isolation of susceptible contacts. Contrary to expectation, isolation of descendants cannot stabilize an equilibrium; based on current data, the effect of the latter two are necessary and greater in effect overall. The reliance on emergent effects shows that even if contact-tracing is 100% efficient, its effect on the epidemic dynamics would be dependent. Moreover, This newly characterized dynamic claims that all outbreaks will eventually show such stable dynamics.", + "rel_num_authors": 1, "rel_authors": [ { - "author_name": "Elizabeth J Williamson", - "author_inst": "London School of Hygiene & Tropical Medicine, Keppel Street, WC1E 7HT" - }, - { - "author_name": "John Tazare", - "author_inst": "London School of Hygiene & Tropical Medicine, Keppel Street, WC1E 7HT" - }, - { - "author_name": "Krishnan Bhaskaran", - "author_inst": "London School of Hygiene & Tropical Medicine, Keppel Street, WC1E 7HT" - }, - { - "author_name": "Helen I McDonald", - "author_inst": "London School of Hygiene & Tropical Medicine, Keppel Street, WC1E 7HT; NIHR Health Protection Research Unit (HPRU) in Immunisation" - }, - { - "author_name": "Alex J Walker", - "author_inst": "The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG" - }, - { - "author_name": "Laurie Tomlinson", - "author_inst": "London School of Hygiene & Tropical Medicine, Keppel Street, WC1E 7HT" - }, - { - "author_name": "Kevin Wing", - "author_inst": "London School of Hygiene & Tropical Medicine, Keppel Street, WC1E 7HT" - }, - { - "author_name": "Sebastian Bacon", - "author_inst": "The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG" - }, - { - "author_name": "Chris Bates", - "author_inst": "TPP, TPP House, 129 Low Lane, Horsforth, Leeds, LS18 5PX" - }, - { - "author_name": "Helen J Curtis", - "author_inst": "The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG" - }, - { - "author_name": "Harriet Forbes", - "author_inst": "London School of Hygiene & Tropical Medicine, Keppel Street, WC1E 7HT" - }, - { - "author_name": "Caroline Minassian", - "author_inst": "London School of Hygiene & Tropical Medicine, Keppel Street, WC1E 7HT" - }, - { - "author_name": "Caroline E Morton", - "author_inst": "The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG" - }, - { - "author_name": "Emily Nightingale", - "author_inst": "London School of Hygiene & Tropical Medicine, Keppel Street, WC1E 7HT" - }, - { - "author_name": "Amir Mehrkar", - "author_inst": "The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG" - }, - { - "author_name": "Dave Evans", - "author_inst": "The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG" - }, - { - "author_name": "Brian D Nicholson", - "author_inst": "The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG" - }, - { - "author_name": "Dave Leon", - "author_inst": "London School of Hygiene & Tropical Medicine, Keppel Street, WC1E 7HT" - }, - { - "author_name": "Peter Inglesby", - "author_inst": "The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG" - }, - { - "author_name": "Brian MacKenna", - "author_inst": "The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG" - }, - { - "author_name": "Nicholas G Davies", - "author_inst": "London School of Hygiene & Tropical Medicine, Keppel Street, WC1E 7HT" - }, - { - "author_name": "Nicholas J DeVito", - "author_inst": "The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG" - }, - { - "author_name": "Henry Drysdale", - "author_inst": "The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG" - }, - { - "author_name": "Jonathan Cockburn", - "author_inst": "TPP, TPP House, 129 Low Lane, Horsforth, Leeds, LS18 5PX" - }, - { - "author_name": "William J Hulme", - "author_inst": "The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG" - }, - { - "author_name": "Jessica Morley", - "author_inst": "The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG" - }, - { - "author_name": "Ian Douglas", - "author_inst": "London School of Hygiene & Tropical Medicine, Keppel Street, WC1E 7HT" - }, - { - "author_name": "Christopher T Rentsch", - "author_inst": "London School of Hygiene & Tropical Medicine, Keppel Street, WC1E 7HT" - }, - { - "author_name": "Rohini Mathur", - "author_inst": "London School of Hygiene & Tropical Medicine, Keppel Street, WC1E 7HT" - }, - { - "author_name": "Angel Wong", - "author_inst": "London School of Hygiene & Tropical Medicine, Keppel Street, WC1E 7HT" - }, - { - "author_name": "Anna Schultze", - "author_inst": "London School of Hygiene & Tropical Medicine, Keppel Street, WC1E 7HT" - }, - { - "author_name": "Richard Croker", - "author_inst": "The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG" - }, - { - "author_name": "John Parry", - "author_inst": "TPP, TPP House, 129 Low Lane, Horsforth, Leeds, LS18 5PX" - }, - { - "author_name": "Frank Hester", - "author_inst": "TPP, TPP House, 129 Low Lane, Horsforth, Leeds, LS18 5PX" - }, - { - "author_name": "Sam Harper", - "author_inst": "TPP, TPP House, 129 Low Lane, Horsforth, Leeds, LS18 5PX" - }, - { - "author_name": "Richard Grieve", - "author_inst": "London School of Hygiene & Tropical Medicine, Keppel Street, WC1E 7HT" - }, - { - "author_name": "David A Harrison", - "author_inst": "Intensive Care National Audit & Research Centre (ICNARC), 24 High Holborn, Holborn, London WC1V 6AZ" - }, - { - "author_name": "Ewout W Steyerberg", - "author_inst": "Leiden University Medical Center, Leiden, the Netherlands" - }, - { - "author_name": "Rosalind M Eggo", - "author_inst": "London School of Hygiene & Tropical Medicine, Keppel Street, WC1E 7HT" - }, - { - "author_name": "Karla Diaz-Ordaz", - "author_inst": "London School of Hygiene & Tropical Medicine, Keppel Street, WC1E 7HT" - }, - { - "author_name": "Ruth Keogh", - "author_inst": "London School of Hygiene & Tropical Medicine, Keppel Street, WC1E 7HT" - }, - { - "author_name": "Stephen JW Evans", - "author_inst": "London School of Hygiene & Tropical Medicine, Keppel Street, WC1E 7HT" - }, - { - "author_name": "Liam Smeeth", - "author_inst": "London School of Hygiene & Tropical Medicine, Keppel Street, WC1E 7HT" - }, - { - "author_name": "Ben Goldacre", - "author_inst": "The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG" + "author_name": "Seyfullah Enes Kotil", + "author_inst": "Bahcesehir University" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2021.02.25.21252447", @@ -898200,37 +897552,97 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.02.21.21252168", - "rel_title": "Early Antibody Responses Associated with Survival in COVID19 Patients", + "rel_doi": "10.1101/2021.02.22.21252228", + "rel_title": "Hydroxychloroquine for SARS-CoV-2 positive patients quarantined at home: The first interim analysis of a remotely conducted randomized clinical trial", "rel_date": "2021-02-26", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.21.21252168", - "rel_abs": "Neutralizing antibodies to the SARS CoV-2 spike proteins have been issued Emergency Use Authorizations and are a likely mechanism of vaccines to prevent COVID-19. However, benefit of treatment with monoclonal antibodies has only been observed in clinical trials in outpatients with mild to moderate COVID-19 but not in patients who are hospitalized and/or have advanced disease. To address this observation, we evaluated the timing of anti SARS-CoV-2 antibody production in hospitalized patients with the use of a highly sensitive multiplexed bead-based immunoassay allowing for early detection of antibodies to SARS-CoV-2. We found that significantly lower levels of antibodies to the SARS-CoV-2 spike protein in the first week after symptom onset were associated with patients who expired as compared to patients who were discharged. We also developed a model, based on antibody level trajectory, to predict COVID 19 outcome that is compatible with greater antibody benefit earlier in COVID 19 disease.\n\nAuthor SummaryWe evaluated antibodies to SARS-CoV-2 over time in patients that were hospitalized with COVID 19. Early detection of Anti-SARS-CoV-2 antibodies was associated with survival in patients hospitalized with COVID 19. Early antibody levels predicted outcome in our study. This result is consistent with the benefit of therapeutic antibodies early in the course of COVID 19 disease. With additional study, early antibody levels may be helpful in deciding on appropriate therapies.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.22.21252228", + "rel_abs": "BackgroundOlder patients are at risk of increased morbidity and mortality from COVID-19 disease due to Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). There are few effective treatments for outpatients with COVID-19.\n\nObjectiveTo evaluate the efficacy of hydroxychloroquine to reduce time in quarantine for symptomatic [≥]40 years-old COVID-19 patients.\n\nDesignA randomized, double-blind, placebo-controlled clinical trial.\n\nSettingOutpatients with polymerase chain reaction confirmed COVID-19 at a University of Pennsylvania affiliated testing center between April 15, 2020 and, July 14, 2020.\n\nParticipantsOut of 5511 SARS-CoV-2 positive patients, 1072 met initial eligibility criteria for telephone-based recruitment, but only 34 subjects were able to be randomized.\n\nInterventionsHydroxychloroquine 400 mg per twice daily (n=17) or matching placebo (n=17), taken orally for up to 14 days.\n\nMeasurementsThe primary outcome was the time to release from quarantine. Secondary outcomes included the participant-reported secondary infection of co-inhabitants, hospitalization, treatment-related adverse events, time to symptom improvement, and incidence of cardiac arrhythmia.\n\nResultsThe median time to release from quarantine for HCQ-treated vs. placebo-treated participants was 8 days (range 4-19 days) vs. 11 days (4-18 days); z-score +0.58, p=n.s. This did not meet the pre-specified criteria for early termination, however, this study was terminated early due to lack of feasibility. There was no mortality in either study arm.\n\nLimitationSince this study was terminated early due to a lack of feasibility, no conclusion can be made about the efficacy of hydroxychloroquine as a treatment for COVID-19 patients 40 years of age or older quarantined at home.\n\nConclusionThe design of this remotely conducted study could guide testing of other more promising agents during the COVID-19 pandemic.\n\nTrial registrationClinicaltrials.gov identifier: NCT04329923", + "rel_num_authors": 20, "rel_authors": [ { - "author_name": "Zhao-hua Zhou", - "author_inst": "US Food and Drug Administration" + "author_name": "Ravi Amaravadi", + "author_inst": "University of Pennsylvania" }, { - "author_name": "Sai Dharmarajan", - "author_inst": "US Food and Drug Administration" + "author_name": "Lydia Giles", + "author_inst": "University of Pennsylvania" }, { - "author_name": "Mari Lehtimaki", - "author_inst": "US Food and Drug Administration" + "author_name": "Mary Carberry", + "author_inst": "University of Pennsylvania" }, { - "author_name": "Susan L Kirshner", - "author_inst": "US Food and Drug Administration" + "author_name": "Matthew Craig Hyman", + "author_inst": "University of Pennsylvania" }, { - "author_name": "Steven Kozlowski", - "author_inst": "US Food and Drug Administration" + "author_name": "Ian Frank", + "author_inst": "University of Pennsylvania" + }, + { + "author_name": "Sunita Nasta", + "author_inst": "University of Pennsylvania" + }, + { + "author_name": "Jennifer Walsh", + "author_inst": "University of Pennsylvania" + }, + { + "author_name": "E. Paul Wileyto", + "author_inst": "University of Pennsylvania" + }, + { + "author_name": "Phyllis Gimotty", + "author_inst": "University of Pennsylvania" + }, + { + "author_name": "Michael Milone", + "author_inst": "University of Pennsylvania" + }, + { + "author_name": "Edith Teng", + "author_inst": "University of Pennsylvania" + }, + { + "author_name": "Niraj Vyas", + "author_inst": "University of Pennsylvania" + }, + { + "author_name": "Steve Balian", + "author_inst": "University of Pennsylvania" + }, + { + "author_name": "Jonathan Kolansky", + "author_inst": "University of Pennsylvania" + }, + { + "author_name": "Nabil Abdulhay", + "author_inst": "University of Pennsylvania" + }, + { + "author_name": "Shaun Mcgovern", + "author_inst": "University of Pennsylvania" + }, + { + "author_name": "Sarah Gamblin", + "author_inst": "University of Pennsylvania" + }, + { + "author_name": "Olivia Doran", + "author_inst": "University of Pennsylvania" + }, + { + "author_name": "Paul Callahan", + "author_inst": "University of Pennsylvania" + }, + { + "author_name": "Benjamin Abella", + "author_inst": "University of Pennsylvania" } ], "version": "1", - "license": "cc0", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -900366,27 +899778,59 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2021.02.19.21252117", - "rel_title": "A Comprehensive County Level Framework to Identify Factors Affecting Hospital Capacity and Predict Future Hospital Demand", + "rel_doi": "10.1101/2021.02.18.21251999", + "rel_title": "Practical strategies for SARS-CoV-2 RT-PCR testing in resource-constrained settings", "rel_date": "2021-02-25", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.19.21252117", - "rel_abs": "BackgroundAs of February 19, 2021, our review yielded a small number of studies that investigated high resolution hospitalization demand data from a public health planning perspective. The earlier studies compiled were conducted early in the pandemic and do not include any analysis of the hospitalization trends in the last 3 months when the US experienced a substantial surge in hospitalization and ICU demand. The earlier studies also focused on COVID 19 transmission influence on COVID 19 hospitalization rates. While this emphasis is understandable, there is evidence to suggest that non COVID hospitalization demand is being displaced due to the hospitalization and ICU surge. Further, with the discovery of multiple mutated variants of COVID 19, it is important to remain vigilant in an effort to control the pandemic. Given these circumstances, the development of a high resolution framework that examines overall hospitalizations and ICU usage rate for COVID and non COVID patients would allow us to build a prediction system that can identify potential vulnerable locations for hospitalization capacity in the nation so that appropriate remedial measures can be planned.\n\nMethodThe current study recognizes that COVID 19 has affected overall hospitalizations - not only COVID 19 hospitalizations. Drawing from the recently released Department of Health and Human services (DHH) weekly hospitalization data (or the time period August 28th, 2020 to January 22nd, 2021.), we study the overall hospitalization and ICU usage as two components: COVID 19 hospitalization and ICU per capita rates; and non COVID hospitalization and ICU per capita rates. A mixed linear mixed model is adopted to study the response variables in our study. The estimated models are subsequently employed to generate predictions for county level hospitalization and ICU usage rates in the future under a host of COVID 19 transmission scenarios considering the new variants of COVID 19 and vaccination impacts.\n\nFindingsWe find a significant association of the virus transmissibility with COVID (positive) and non COVID (negative) hospitalization and ICU usage rates. Several county level factors including demographics, mobility and health indicators are also found to be strongly associated with the overall hospitalization and ICU demand. Among the various scenarios considered, the results indicate a small possibility of a new wave of infections that can substantially overload hospitalization and ICU usage. In the scenario where vaccinations proceed as expected reducing transmission, our results indicate that hospitalizations and ICU usage rates are likely to reduce significantly.\n\nInterpretationThe research exercise presents a framework to predict evolving hospitalization and ICU usage trends in response to COVID 19 transmission rates while controlling for other factors. Our work highlights how future hospitalization demand varies by location and time in response to a range of pessimistic and optimistic scenarios. Further, the exercise allows us to identify vulnerable counties and regions under stress with high hospitalization and ICU rates that can be assisted with remedial measures. The model will also allow hospitals to understand evolving displaced non COVID hospital demand.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.18.21251999", + "rel_abs": "Alternatives to nasopharyngeal sampling are needed to increase capacity for SARS-CoV-2 testing. Among 275 participants, we piloted the collection of nasal mid-turbinate swabs amenable to self-testing, including polyester flocked swabs as well as 3D printed plastic lattice swabs, placed into viral transport media or an RNA stabilization agent. Flocked nasal swabs identified 104/121 individuals who were PCR-positive for SARS-CoV-2 by nasopharyngeal sampling (sensitivity 87%, 95% CI 79-92%), mostly missing those with low viral load (<103 viral copies/uL). 3D-printed nasal swabs showed similar sensitivity. When nasal swabs were placed directly into RNA preservative, the mean 1.4 log decrease in viral copies/uL compared to nasopharyngeal samples was reduced to <1 log, even when samples were left at room temperature for up to 7 days. We also evaluated pooling strategies that involved pooling specimens in the lab versus pooling swabs at the point of collection, finding both successfully detected samples >102 viral copies/uL.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Tanmoy Bhowmik", - "author_inst": "University of Central Florida" + "author_name": "Meredith Smith Muller", + "author_inst": "University of North Carolina at Chapel Hill" }, { - "author_name": "Naveen Eluru", - "author_inst": "University of Central Florida" + "author_name": "Srijana Bhattarai Chhetri", + "author_inst": "University of North Carolina at Chapel Hill" + }, + { + "author_name": "Christopher Basham", + "author_inst": "University of North Carolina at Chapel Hill" + }, + { + "author_name": "Tyler Rapp", + "author_inst": "University of North Carolina at Chapel Hill" + }, + { + "author_name": "Feng-Chang Lin", + "author_inst": "University of North Carolina at Chapel Hill" + }, + { + "author_name": "Kelly Lin", + "author_inst": "University of North Carolina at Chapel Hill" + }, + { + "author_name": "Daniel Westreich", + "author_inst": "Duke University" + }, + { + "author_name": "Carla Cerami", + "author_inst": "Medical Research Council The Gambia Unit" + }, + { + "author_name": "Jonathan J. Juliano", + "author_inst": "University of North Carolina School of Medicine" + }, + { + "author_name": "Jessica T Lin", + "author_inst": "University of North Carolina at Chapel Hill" } ], "version": "1", - "license": "cc_no", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2021.02.23.21251975", @@ -902268,49 +901712,37 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.02.23.21252277", - "rel_title": "Impact of the Tier system on SARS-CoV-2 transmission in the UK between the first and second national lockdowns", + "rel_doi": "10.1101/2021.02.22.21252255", + "rel_title": "An integrated framework for building trustworthy data-driven epidemiological models: Application to the COVID-19 outbreak in New York City", "rel_date": "2021-02-24", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.23.21252277", - "rel_abs": "ObjectiveMeasure the effects of the Tier system on the COVID-19 pandemic in the UK between the first and second national lockdowns, before the emergence of the B.1.1.7 variant of concern.\n\nDesignModelling study combining estimates of the real-time reproduction number Rt (derived from UK case, death and serological survey data) with publicly available data on regional non-pharmaceutical interventions. We fit a Bayesian hierarchical model with latent factors using these quantities, to account for broader national trends in addition to subnational effects from Tiers.\n\nSettingThe UK at Lower Tier Local Authority (LTLA) level.\n\nPrimary and secondary outcome measuresReduction in real-time reproduction number Rt.\n\nResultsNationally, transmission increased between July and late September, regional differences notwithstanding. Immediately prior to the introduction of the tier system, Rt averaged 1.3 (0.9 - 1.6) across LTLAs, but declined to an average of 1.1 (0.86 - 1.42) two weeks later. Decline in transmission was not solely attributable to Tiers. Tier 1 had negligible effects. Tiers 2 and 3 respectively reduced transmission by 6% (5%-7%) and 23% (21%-25%). 93% of LTLAs would have begun to suppress their epidemics if every LTLA had gone into Tier 3 by the second national lockdown, whereas only 29% did so in reality.\n\nConclusionsThe relatively small effect sizes found in this analysis demonstrate that interventions at least as stringent as Tier 3 are required to suppress transmission, especially considering more transmissible variants, at least until effective vaccination is widespread or much greater population immunity has amassed.\n\nStrengths and limitations of this studyO_LIFirst study to measure effects of UK Tier system for SARS-CoV-2 control at national and regional level.\nC_LIO_LIModel makes minimal assumptions and is primarily data driven.\nC_LIO_LIInsufficient statistical power to estimate effects of individual interventions that comprise Tiers, or their interaction.\nC_LIO_LIEstimates show that Tiers 1 and 2 are insufficient to suppress transmission, at least until widespread population immunity has amassed. Emergence of more transmissible variants of concern unfortunately supports this conclusion.\nC_LI", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.22.21252255", + "rel_abs": "Epidemiological models can provide the dynamic evolution of a pandemic but they are based on many assumptions and parameters that have to be adjusted over the time when the pandemic lasts. However, often the available data are not sufficient to identify the model parameters and hence infer the unobserved dynamics. Here, we develop a general framework for building a trustworthy data-driven epidemiological model, consisting of a workflow that integrates data acquisition and event timeline, model development, identifiability analysis, sensitivity analysis, model calibration, model robustness analysis, and forecasting with uncertainties in different scenarios. In particular, we apply this framework to propose a modified susceptible-exposed-infectious-recovered (SEIR) model, including new compartments and model vaccination in order to forecast the transmission dynamics of COVID-19 in New York City (NYC). We find that we can uniquely estimate the model parameters and accurately predict the daily new infection cases, hospitalizations, and deaths, in agreement with the available data from NYCs governments website. In addition, we employ the calibrated data-driven model to study the effects of vaccination and timing of reopening indoor dining in NYC.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Daniel J Laydon", - "author_inst": "Imperial College London" - }, - { - "author_name": "Swapnil Mishra", - "author_inst": "Imperial College London" - }, - { - "author_name": "Wes R Hinsley", - "author_inst": "Imperial College London" - }, - { - "author_name": "Pantelis Samartsidis", - "author_inst": "MRC Biostatistics Unit, Cambridge Institute of Public Health" + "author_name": "Sheng Zhang", + "author_inst": "Purdue University" }, { - "author_name": "Seth Flaxman", - "author_inst": "Imperial College London" + "author_name": "Joan Ponce", + "author_inst": "Purdue University" }, { - "author_name": "Axel Gandy", - "author_inst": "Imperial College London" + "author_name": "Zhen Zhang", + "author_inst": "Brown University" }, { - "author_name": "Neil M Ferguson", - "author_inst": "Imperial College London" + "author_name": "Guang Lin", + "author_inst": "Purdue University" }, { - "author_name": "Samir Bhatt", - "author_inst": "Imperial College London" + "author_name": "George Em Karniadakis", + "author_inst": "Brown University" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -904110,35 +903542,191 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.02.19.21252093", - "rel_title": "The Association of Opioid Use Disorder and COVID-19 in Shahroud, Iran", + "rel_doi": "10.1101/2021.02.18.21251504", + "rel_title": "Efferocytosis of SARS-CoV-2-infected dying cells impairs macrophage anti-inflammatory programming and continual clearance of apoptotic cells", "rel_date": "2021-02-23", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.19.21252093", - "rel_abs": "BackgroundCOVID-19 quickly spread to the world, causing a pandemic. While some studies have found no link between Opioid Use Disorder (OUD) and COVID-19, the role of the opioid on COVID-19 is challenging. The present study aimed to determine the relationship between OUD and COVID-19.\n\nMethodsThis was a prospective cohort study. We used data from the third phase of the Shahroud eye cohort study on 4394 participants which started in September 2019 and ended before the COVID-19 epidemic in Shahroud in February 2020. The participants were followed for 10.5 months till November 2020. COVID-19 was detected by RT-PCR on swap samples from the oropharynx and nasopharynx. The incidence of COVID-19 compared in OUD and Non-OUD participants, and relative risk was calculated in Log Binomial Regression model.\n\nResultsAmong the 4394 participants with a mean age of 61.1 years, 120 people had OUD. The incidence of COVID-19 in participants with OUD and Non-OUD were 3.3% and 4.5%, respectively. The relative risk of OUD for COVID-19 was 0.75 (95% Confidence intervals: 0.28 - 1.98; P= 0.555).\n\nConclusionsOpioid use disorder was not associated with COVID-19. The claim that people with OUD are less likely to develop COVID-19 is not supported by this data.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.18.21251504", + "rel_abs": "COVID-19 is a disease of dysfunctional immune responses, but the mechanisms triggering immunopathogenesis are not established. The functional plasticity of macrophages allows this cell type to promote pathogen elimination and inflammation or suppress inflammation and promote tissue remodeling and injury repair. During an infection, the clearance of dead and dying cells, a process named efferocytosis, can modulate the interplay between these contrasting functions. Here, we show that engulfment of SARS-CoV2-infected apoptotic cells exacerbates inflammatory cytokine production, inhibits the expression of efferocytic receptors, and impairs continual efferocytosis by macrophages. We also provide evidence supporting that lung monocytes and macrophages from severe COVID-19 patients have compromised efferocytic capacity. Our findings reveal that dysfunctional efferocytosis of SARS-CoV-2-infected cell corpses suppress macrophage anti-inflammation and efficient tissue repair programs and provide mechanistic insights for the excessive production of pro-inflammatory cytokines and accumulation of tissue damage associated with COVID-19 immunopathogenesis.", + "rel_num_authors": 43, "rel_authors": [ { - "author_name": "Zhaleh Jamali", - "author_inst": "Student Research Committee, School of Medicine, Shahroud University of Medical Sciences, Shahroud, Iran" + "author_name": "Ana C. G. Salina", + "author_inst": "Departamento de Biologia Celular e Molecular e Bioagentes Patogenicos, Faculdade de Medicina de Ribeirao Preto, Universidade de Sao Paulo, Ribeirao Preto, SP, B" }, { - "author_name": "Mohammad Hassan Emamian", - "author_inst": "Ophthalmic Epidemiology Research Center, Shahroud University of Medical Sciences, Shahroud, Iran" + "author_name": "Douglas dos-Santos", + "author_inst": "Departamento de Biologia Celular e Molecular e Bioagentes Patogenicos, Faculdade de Medicina de Ribeirao Preto, Universidade de Sao Paulo, Ribeirao Preto, SP, B" }, { - "author_name": "Hassan Hashemi", - "author_inst": "Noor Ophthalmology Research Center, Noor Eye Hospital, Tehran, Iran" + "author_name": "Tamara S. Rodrigues", + "author_inst": "Departamento de Biologia Celular e Molecular e Bioagentes Patogenicos, Faculdade de Medicina de Ribeirao Preto, Universidade de Sao Paulo, Ribeirao Preto, SP, B" }, { - "author_name": "Akbar Fotouhi", - "author_inst": "Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran" + "author_name": "Marlon Fortes-Rocha", + "author_inst": "Departamento de Biologia Celular e Molecular e Bioagentes Patogenicos, Faculdade de Medicina de Ribeirao Preto, Universidade de Sao Paulo, Ribeirao Preto, SP, B" + }, + { + "author_name": "Edismauro G. Freitas-Filho", + "author_inst": "Departamento de Biologia Celular e Molecular e Bioagentes Patogenicos, Faculdade de Medicina de Ribeirao Preto, Universidade de Sao Paulo, Ribeirao Preto, SP, B" + }, + { + "author_name": "Daniel L. Alzamora-Terrel", + "author_inst": "Departamento de Biologia Celular e Molecular e Bioagentes Patogenicos, Faculdade de Medicina de Ribeirao Preto, Universidade de Sao Paulo, Ribeirao Preto, SP, B" + }, + { + "author_name": "Icaro Castro", + "author_inst": "Departamento de Analises Clinicas e Toxicologicas, Faculdade de Ciencias Farmaceuticas, Universidade de Sao Paulo, Brazil" + }, + { + "author_name": "Thais F. C. Fraga", + "author_inst": "Faculdade de Medicina de Ribeirao Preto" + }, + { + "author_name": "Mikhael H. F. de Lima", + "author_inst": "Departamento de Farmacologia, Faculdade de Medicina de Ribeirao Preto, Universidade de Sao Paulo, Ribeirao Preto, SP, Brazil" + }, + { + "author_name": "Daniele C. Nascimento", + "author_inst": "Departamento de Farmacologia, Faculdade de Medicina de Ribeirao Preto, Universidade de Sao Paulo, Ribeirao Preto, SP, Brazil" + }, + { + "author_name": "Camila M. Silva", + "author_inst": "Departamento de Farmacologia, Faculdade de Medicina de Ribeirao Preto, Universidade de Sao Paulo, Ribeirao Preto, Sao Paulo, Brazil" + }, + { + "author_name": "Juliana E. Toller-Kawahisa", + "author_inst": "Departamento de Farmacologia, Faculdade de Medicina de Ribeirao Preto, Universidade de Sao Paulo, Ribeirao Preto, Sao Paulo, Brazil." + }, + { + "author_name": "Amanda Becerra", + "author_inst": "Departamento de Biologia Celular e Molecular e Bioagentes Patogenicos, Faculdade de Medicina de Ribeirao Preto, Universidade de Sao Paulo, Ribeirao Preto, SP, B" + }, + { + "author_name": "Samuel Oliveira", + "author_inst": "Departamento de Biologia Celular e Molecular e Bioagentes Patogenicos, Faculdade de Medicina de Ribeirao Preto, Universidade de Sao Paulo, Ribeirao Preto, SP, B" + }, + { + "author_name": "Diego B. Caetite", + "author_inst": "Departamento de Farmacologia, Faculdade de Medicina de Ribeirao Preto, Universidade de Sao Paulo, Ribeirao Preto, Sao Paulo, Brazil" + }, + { + "author_name": "Leticia Almeida", + "author_inst": "Departamento de Biologia Celular e Molecular e Bioagentes Patogenicos, Faculdade de Medicina de Ribeirao Preto, Universidade de Sao Paulo, Ribeirao Preto, SP, B" + }, + { + "author_name": "Adriene Y. Ishimoto", + "author_inst": "Departamento de Biologia Celular e Molecular e Bioagentes Patogenicos, Faculdade de Medicina de Ribeirao Preto, Universidade de Sao Paulo, Ribeirao Preto, SP, B" + }, + { + "author_name": "Thais M. Lima", + "author_inst": "Departamento de Biologia Celular e Molecular e Bioagentes Patogenicos, Faculdade de Medicina de Ribeirao Preto, Universidade de Sao Paulo, Ribeirao Preto, SP, B" + }, + { + "author_name": "Ronaldo B. Martins", + "author_inst": "Departamento de Biologia Celular e Molecular e Bioagentes Patogenicos, Faculdade de Medicina de Ribeirao Preto, Universidade de Sao Paulo, Ribeirao Preto, SP, B" + }, + { + "author_name": "Flavio Veras", + "author_inst": "Departamento de Farmacologia, Faculdade de Medicina de Ribeirao Preto, Universidade de Sao Paulo, Ribeirao Preto, Sao Paulo, Brazil" + }, + { + "author_name": "Natalia B. do Amaral", + "author_inst": "Divisao de Imunologia Clinica, Emergencia, Doencas Infecciosas e Unidade de Terapia Intensiva, Faculdade de Medicina de Ribeirao Preto, Universidade de Sao Paul" + }, + { + "author_name": "Marcela C. Giannini", + "author_inst": "Divisao de Imunologia Clinica, Emergencia, Doencas Infecciosas e Unidade de Terapia Intensiva, Faculdade de Medicina de Ribeirao Preto, Universidade de Sao Paul" + }, + { + "author_name": "Leticia P. Bonjorno", + "author_inst": "Divisao de Imunologia Clinica, Emergencia, Doencas Infecciosas e Unidade de Terapia Intensiva, Faculdade de Medicina de Ribeirao Preto, Universidade de Sao Paul" + }, + { + "author_name": "Maria I. F. Lopes", + "author_inst": "Divisao de Imunologia Clinica, Emergencia, Doencas Infecciosas e Unidade de Terapia Intensiva, Faculdade de Medicina de Ribeirao Preto, Universidade de Sao Paul" + }, + { + "author_name": "Maira N. Benatti", + "author_inst": "Departamento de Patologia e Medicina Legal, Faculdade de Medicina de Ribeirao Preto, Universidade de Sao Paulo, Ribeirao Preto, SP, Brazil" + }, + { + "author_name": "Sabrina S. Batah", + "author_inst": "Departamento de Patologia e Medicina Legal, Faculdade de Medicina de Ribeirao Preto, Universidade de Sao Paulo, Ribeirao Preto, SP, Brazil" + }, + { + "author_name": "Rodrigo C. Santana", + "author_inst": "Divisao de Imunologia Clinica, Emergencia, Doencas Infecciosas e Unidade de Terapia Intensiva, Faculdade de Medicina de Ribeirao Preto, Universidade de Sao Paul" + }, + { + "author_name": "Fernando C. Vilar", + "author_inst": "Divisao de Imunologia Clinica, Emergencia, Doencas Infecciosas e Unidade de Terapia Intensiva, Faculdade de Medicina de Ribeirao Preto, Universidade de Sao Paul" + }, + { + "author_name": "Maria A. Martins", + "author_inst": "Divisao de Imunologia Clinica, Emergencia, Doencas Infecciosas e Unidade de Terapia Intensiva, Faculdade de Medicina de Ribeirao Preto, Universidade de Sao Paul" + }, + { + "author_name": "Rodrigo L. Assad", + "author_inst": "Divisao de Imunologia Clinica, Emergencia, Doencas Infecciosas e Unidade de Terapia Intensiva, Faculdade de Medicina de Ribeirao Preto, Universidade de Sao Paul" + }, + { + "author_name": "Sergio C. L. de Almeida", + "author_inst": "Divisao de Imunologia Clinica, Emergencia, Doencas Infecciosas e Unidade de Terapia Intensiva, Faculdade de Medicina de Ribeirao Preto, Universidade de Sao Paul" + }, + { + "author_name": "Fabiola R. de Oliveira", + "author_inst": "Divisao de Imunologia Clinica, Emergencia, Doencas Infecciosas e Unidade de Terapia Intensiva, Faculdade de Medicina de Ribeirao Preto, Universidade de Sao Paul" + }, + { + "author_name": "Eurico Arruda Neto", + "author_inst": "Departamento de Biologia Celular e Molecular e Bioagentes Patogenicos, Faculdade de Medicina de Ribeirao Preto, Universidade de Sao Paulo, Ribeirao Preto, SP, B" + }, + { + "author_name": "Thiago M. Cunha", + "author_inst": "Departamento de Farmacologia, Faculdade de Medicina de Ribeirao Preto, Universidade de Sao Paulo, Ribeirao Preto, Sao Paulo, Brazil" + }, + { + "author_name": "Jose C Alves-Filho", + "author_inst": "Departamento de Farmacologia, Faculdade de Medicina de Ribeirao Preto, Universidade de Sao Paulo, Ribeirao Preto, Sao Paulo, Brazil" + }, + { + "author_name": "Vania L. D. Bonato", + "author_inst": "Faculdade de Medicina de Ribeirao Preto" + }, + { + "author_name": "Fernando Q. Cunha", + "author_inst": "Departamento de Farmacologia, Faculdade de Medicina de Ribeirao Preto, Universidade de Sao Paulo, Ribeirao Preto, Sao Paulo, Brazil" + }, + { + "author_name": "Alexandre T. Fabro", + "author_inst": "Departamento de Patologia e Medicina Legal, Faculdade de Medicina de Ribeirao Preto, Universidade de Sao Paulo, Ribeirao Preto, SP, Brazil." + }, + { + "author_name": "Helder I Nakaya", + "author_inst": "Departamento de Analises Clinicas e Toxicologicas, Faculdade de Ciencias Farmaceuticas, Universidade de Sao Paulo, Brazil" + }, + { + "author_name": "Dario S. Zamboni", + "author_inst": "Departamento de Biologia Celular e Molecular e Bioagentes Patogenicos, Faculdade de Medicina de Ribeirao Preto, Universidade de Sao Paulo, Ribeirao Preto, SP, B" + }, + { + "author_name": "Paulo Louzada-Junior", + "author_inst": "Divisao de Imunologia Clinica, Emergencia, Doencas Infecciosas e Unidade de Terapia Intensiva, Faculdade de Medicina de Ribeirao Preto, Universidade de Sao Paul" + }, + { + "author_name": "Rene D. R. Oliveira", + "author_inst": "Divisao de Imunologia Clinica, Emergencia, Doencas Infecciosas e Unidade de Terapia Intensiva, Faculdade de Medicina de Ribeirao Preto, Universidade de Sao Paul" + }, + { + "author_name": "Larissa D. Cunha", + "author_inst": "Departamento de Biologia Celular e Molecular e Bioagentes Patogenicos, Faculdade de Medicina de Ribeirao Preto, Universidade de Sao Paulo, Ribeirao Preto, SP, B" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "addiction medicine" + "category": "allergy and immunology" }, { "rel_doi": "10.1101/2021.02.20.21252129", @@ -905932,113 +905520,173 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.02.20.21251520", - "rel_title": "Wastewater Monitoring of SARS-CoV-2 from Acute Care Hospitals Identifies Nosocomial Transmission and Outbreaks", + "rel_doi": "10.1101/2021.02.19.21251340", + "rel_title": "Multicenter cohort study of children hospitalized with SARS-CoV-2 infection", "rel_date": "2021-02-23", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.20.21251520", - "rel_abs": "BackgroundSARS-CoV-2 has been detected in wastewater and its abundance correlated with community COVID-19 cases, hospitalizations and deaths. We sought to use wastewater-based detection of SARS-CoV-2 to assess the epidemiology of SARS-CoV-2 in hospitals.\n\nMethodsBetween August and December 2020, twice-weekly wastewater samples from three tertiary-care hospitals (totaling >2100 dedicated inpatient beds) were collected. Wastewater samples were concentrated and cleaned using the 4S-silica column method and assessed for SARS-CoV-2 gene-targets (N1, N2 and E) and controls using RT-qPCR. Wastewater SARS-CoV-2 as measured by quantification cycle (Cq), genome copies and genomes normalized to the fecal biomarker PMMoV were compared to the total daily number of patients hospitalized with active COVID-19, confirmed cases of hospital-acquired infection, and the occurrence of unit-specific outbreaks.\n\nResultsOf 165 wastewater samples collected, 159 (96%) were assayable. The N1-gene from SARS-CoV-2 was detected in 64.1% of samples, N2 in 49.7% and E in 10%. N1 and N2 in wastewater increased over time both in terms of amount of detectable virus and the proportion of samples that were positive, consistent with increasing hospitalizations (Pearsons r=0.679, P<0.0001, Pearsons r=0.728, P<0.0001, respectively). Despite increasing hospitalizations through the study period, wastewater analysis was able to identify incident nosocomial-acquired cases of COVID-19 (Pearsons r =0.389, P<0.001) and unit-specific outbreaks by increases in detectable SARS-CoV-2 N1-RNA (median 112 copies/ml) versus outbreak-free periods (0 copies/ml; P<0.0001).\n\nConclusionsWastewater-based monitoring of SARS-CoV-2 represents a promising tool for SARS-CoV-2 passive surveillance and case identification, containment, and mitigation in acute-care medical facilities.\n\nSupplemental Material includedO_ST_ABSKey-points summaryC_ST_ABSSAS-CoV-2 RNA is detectable in hospital wastewater. Wastewater SARS-CoV-2 RNA increases in conjunction with COVID-19-related hospitalizations. Spikes in SARS-CoV-2 wastewater signal correspond to incident hospital-acquired cases and outbreaks, suggesting passive surveillance via wastewater has great promise for COVID-19 monitoring.", - "rel_num_authors": 24, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.19.21251340", + "rel_abs": "BackgroundA cohort study was conducted to describe and compare the characteristics of SARS-CoV-2 infection in hospitalized children in three countries.\n\nMethodsThis was a retrospective cohort of consecutive children admitted to 15 hospitals (13 in Canada and one each in Iran and Costa Rica) up to November 16, 2020. Cases were included if they had SARS-CoV-2 infection or multi-system inflammatory syndrome in children (MIS-C) with molecular detection of SARS-CoV-2 or positive SARS-CoV-2 serology.\n\nResultsOf 211 included cases (Canada N=95; Costa Rica N=84; Iran N=32), 103 (49%) had a presumptive diagnosis of COVID-19 or MIS-C at admission while 108 (51%) were admitted with other diagnoses. Twenty-one (10%) of 211 met criteria for MIS-C. Eighty-seven (41%) had comorbidities. Children admitted in Canada were older than those admitted to non-Canadian sites (median 4.1 versus 2.2 years; p<0.001) and less likely to require mechanical ventilation (3/95 [3%] versus 15/116 [13%]; p<0.05). Sixty-four of 211 (30%) required supplemental oxygen or intensive care unit (ICU) admission and 4 (1.9%) died. Age < 30 days, admission outside Canada, presence of at least one comorbidity and chest imaging compatible with COVID-19 predicted severe or critical COVID-19 (defined as death or need for supplemental oxygen or ICU admission).\n\nConclusionsApproximately half of hospitalized children with confirmed SARS-CoV-2 infection or MIS-C were admitted with other suspected diagnoses. Disease severity was higher at non-Canadian sites. Neonates, children with comorbidities and those with chest radiographs compatible with COVID-19 were at increased risk for severe or critical COVID-19.\n\nMain pointsApproximately half of hospitalized children with laboratory confirmed MIS-C or SARS-CoV-2 infection were admitted with another primary diagnoses. The severity of disease was higher in the middle income countries (Costa Rica and Iran) than in Canada.", + "rel_num_authors": 39, "rel_authors": [ { - "author_name": "Nicole Acosta", - "author_inst": "University of Calgary" + "author_name": "JOAN ROBINSON", + "author_inst": "University of Alberta" }, { - "author_name": "Maria Bautista", - "author_inst": "University of Calgary" + "author_name": "Michelle Barton", + "author_inst": "Western University, London, Ontario" }, { - "author_name": "Jordan Hollman", - "author_inst": "University of Calgary" + "author_name": "Jesse Papenburg", + "author_inst": "McGill University, Montreal, Quebec" }, { - "author_name": "Janine McCalder", - "author_inst": "University of Calgary" + "author_name": "Rolando Ulloa-Gutierrez", + "author_inst": "Hospital Nacional de Ninos \"Dr. Carlos Saenz Herrera\", Caja Costarricense de Seguro Social (CCSS); San Jose, Costa Rica" }, { - "author_name": "Alexander Buchner Beaudet", - "author_inst": "University of Calgary" + "author_name": "Helena Brenes-Chacon", + "author_inst": "Hospital Nacional de Ninos \"Dr. Carlos Saenz Herrera\", Caja Costarricense de Seguro Social (CCSS); San Jose, Costa Rica" }, { - "author_name": "Lawrence Man", - "author_inst": "University of Calgary" + "author_name": "Adriana Yock-Corrales", + "author_inst": "Hospital Nacional de Ninos \"Dr. Carlos Saenz Herrera\", Caja Costarricense de Seguro Social (CCSS); San Jose, Costa Rica" }, { - "author_name": "Barbara J Waddell", - "author_inst": "University of Calgary" + "author_name": "Gabriela Ivankovich-Escoto", + "author_inst": "Hospital Nacional de Ninos \"Dr. Carlos Saenz Herrera\", Caja Costarricense de Seguro Social (CCSS); San Jose, Costa Rica" }, { - "author_name": "Jianwei Chen", - "author_inst": "University of Calgary" + "author_name": "Alejandra Soriano-Fallas", + "author_inst": "Hospital Nacional de Ninos \"Dr. Carlos Saenz Herrera\", Caja Costarricense de Seguro Social (CCSS); San Jose, Costa Rica" }, { - "author_name": "Carmen Li", - "author_inst": "University of Calgary" + "author_name": "Marcela Hernandez-de Mezerville", + "author_inst": "Hospital Nacional de Ninos \"Dr. Carlos Saenz Herrera\", Caja Costarricense de Seguro Social (CCSS); San Jose, Costa Rica" }, { - "author_name": "Darina Kuzma", - "author_inst": "University of Calgary" + "author_name": "Ari Bitnun", + "author_inst": "University of Toronto, Toronto, Ontario" }, { - "author_name": "Srijak Bhatnagar", - "author_inst": "University of Calgary" + "author_name": "Shaun K. Morris", + "author_inst": "University of Toronto, Toronto, Ontario" }, { - "author_name": "Jenine Leal", - "author_inst": "Alberta Health Services" + "author_name": "Tala El Tal", + "author_inst": "University of Toronto, Toronto, Ontario" }, { - "author_name": "Jon Meddings", - "author_inst": "University of Calgary" + "author_name": "E. Ann Yeh", + "author_inst": "University of Toronto, Toronto, Ontario" }, { - "author_name": "Jia Hu", - "author_inst": "Alberta Health Services" + "author_name": "Peter Gill", + "author_inst": "University of Toronto, Toronto, Ontario" }, { - "author_name": "Jason Cabaj", - "author_inst": "Alberta Health Services" + "author_name": "Ronald M. Laxer", + "author_inst": "University of Toronto, Toronto, Ontario" }, { - "author_name": "Norma J Ruecker", - "author_inst": "City of Calgary" + "author_name": "Alireza Nateghian", + "author_inst": "Iran University of Medial Sciences, Tehran, Iran" }, { - "author_name": "Christopher Naugler", - "author_inst": "University of Calgary" + "author_name": "Behzad Haghighi Aski", + "author_inst": "Iran University of Medical Sciences, Tehran, Iran" }, { - "author_name": "Dylan R Pillai", - "author_inst": "University of Calgary" + "author_name": "Ali Manafif", + "author_inst": "Iran University of Medical Sciences, Tehran, Iran" }, { - "author_name": "Gopal Achari", - "author_inst": "University of Calgary" + "author_name": "Marie-Astrid Lefebvre", + "author_inst": "McGill University, Montreal, Quebec" }, { - "author_name": "M. Cathryn Ryan", - "author_inst": "University of Calgary" + "author_name": "Chelsea Caya", + "author_inst": "McGill University, Montreal, Quebec" }, { - "author_name": "John M Conly", - "author_inst": "University of Calgary" + "author_name": "Suzette Cooke", + "author_inst": "University of Calgary, Calgary, Alberta" }, { - "author_name": "Kevin Frankowski", - "author_inst": "University of Calgary; Advancing Canadian Wastewater Assets (ACWA)" + "author_name": "Tammie Dewan", + "author_inst": "University of Calgary, Calgary, Alberta" }, { - "author_name": "Casey RJ Hubert", - "author_inst": "University of Calgary" + "author_name": "Lea Restivo", + "author_inst": "University of Calgary, Calgary, Alberta" }, { - "author_name": "Michael D Parkins", - "author_inst": "University of Calgary" + "author_name": "Isabelle Th\u00e9riault", + "author_inst": "Laval University, Quebec City, Quebec" + }, + { + "author_name": "Adriana Trajtman", + "author_inst": "University of Manitoba, Winnipeg, Manitoba" + }, + { + "author_name": "Rachel Dwilow", + "author_inst": "University of Manitoba, Winnipeg, Manitoba" + }, + { + "author_name": "Jared Bullard", + "author_inst": "University of Manitoba, Winnipeg, Manitoba" + }, + { + "author_name": "Manish Sadarangani", + "author_inst": "BC Children's Hospital Research Institute, Vancouver, British Columbia" + }, + { + "author_name": "Ashley Roberts", + "author_inst": "University of British Columbia, Vancouver, British Columbia" + }, + { + "author_name": "Nicole Le Saux", + "author_inst": "University of Ottawa, Ottawa, Ontario" + }, + { + "author_name": "Jennifer Bowes", + "author_inst": "University of Ottawa, Ottawa, Ontario" + }, + { + "author_name": "Jacqueline K. Wong", + "author_inst": "McMaster University, Hamilton, Ontario" + }, + { + "author_name": "Rupeena Purewal", + "author_inst": "University of Saskatchewan, Saskatoon, Saskatchewan" + }, + { + "author_name": "Janell Lautermilch", + "author_inst": "University of Saskatchewan, Saskatoon, Saskatchewan" + }, + { + "author_name": "Kirk Leifso", + "author_inst": "Queen's University, Kingston, Ontario" + }, + { + "author_name": "Cheryl Foo", + "author_inst": "Memorial University, St John's, Newfoundland and Labrador" + }, + { + "author_name": "Leigh Anne Newhook", + "author_inst": "Memorial University, St John's, Newfoundland and Labrador" + }, + { + "author_name": "Ann Bayliss", + "author_inst": "Trillium Health Partners, Mississauga, Ontario" + }, + { + "author_name": "Dara Petel", + "author_inst": "Western University, London, Ontario" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -907710,59 +907358,59 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2021.02.23.432569", - "rel_title": "Inhalable Nanobody (PiN-21) prevents and treats SARS-CoV-2 infections in Syrian hamsters at ultra-low doses", + "rel_doi": "10.1101/2021.02.20.21251927", + "rel_title": "Rapid SARS-CoV-2 variants spread detected in France using specific RT-PCR testing", "rel_date": "2021-02-23", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.02.23.432569", - "rel_abs": "Globally there is an urgency to develop effective, low-cost therapeutic interventions for coronavirus disease 2019 (COVID-19). We previously generated the stable and ultrapotent homotrimeric Pittsburgh inhalable Nanobody 21 (PiN-21). Using Syrian hamsters that model moderate to severe COVID-19 disease, we demonstrate the high efficacy of PiN-21 to prevent and treat SARS-CoV-2 infection. Intranasal delivery of PiN-21 at 0.6 mg/kg protects infected animals from weight loss and substantially reduces viral burdens in both lower and upper airways compared to control. Aerosol delivery of PiN-21 facilitates deposition throughout the respiratory tract and dose minimization to 0.2 mg/kg. Inhalation treatment quickly reverses animals weight loss post-infection and decreases lung viral titers by 6 logs leading to drastically mitigated lung pathology and prevents viral pneumonia. Combined with the marked stability and low production cost, this novel therapy may provide a convenient and cost-effective option to mitigate the ongoing pandemic.", + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.20.21251927", + "rel_abs": "SARS-CoV-2 variants raise major concerns regarding the control of COVID-19 epidemics. We analyse 40,000 specific RT-PCR tests performed on SARS-CoV-2-positive samples collected between Jan 26 and Feb 16, 2021. We find a high transmission advantage of variants and show that their spread in the country is more advanced than anticipated.", "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Sham Nambulli", - "author_inst": "University of Pittsburgh" + "author_name": "Stephanie Haim-Boukobza", + "author_inst": "Laboratoire Cerba, France" }, { - "author_name": "Yufei Xiang", - "author_inst": "University of Pittsburgh" + "author_name": "Sabine Trombert-Paolantoni", + "author_inst": "Laboratoire Cerba, France" }, { - "author_name": "Natasha L Tilston-Lunel", - "author_inst": "University of Pittsburgh" + "author_name": "Benedicte Roquebert", + "author_inst": "Laboratoire Cerba, France" }, { - "author_name": "Linda J Rennick", - "author_inst": "University of Pittsburgh" + "author_name": "Emmanuel Lecorche", + "author_inst": "Laboratoire Cerba, France" }, { - "author_name": "Zhe Sang", - "author_inst": "University of Pittsburgh" + "author_name": "Laura Verdurme", + "author_inst": "Laboratoire Cerba, France" }, { - "author_name": "William B Klimstra", - "author_inst": "University of Pittsburgh" + "author_name": "Vincent Foulongne", + "author_inst": "CHU de Montpellier, Montpellier" }, { - "author_name": "Douglas S Reed", - "author_inst": "University of Pittsburgh" + "author_name": "Christian Selinger", + "author_inst": "MIVEGEC, CNRS, IRD, University of Montpellier" }, { - "author_name": "Nicholas A Crossland", - "author_inst": "Boston University School of Medicine" + "author_name": "Yannis Michalakis", + "author_inst": "MIVEGEC, CNRS, IRD, University of Montpellier" }, { - "author_name": "Yi Shi", - "author_inst": "University of Pittsburgh" + "author_name": "Mircea T Sofonea", + "author_inst": "MIVEGEC, CNRS, IRD, University of Montpellier" }, { - "author_name": "Paul W Duprex", - "author_inst": "University of Pittsburgh" + "author_name": "Samuel Alizon", + "author_inst": "MIVEGEC, CNRS, IRD, University of Montpellier" } ], "version": "1", - "license": "cc_no", - "type": "new results", - "category": "microbiology" + "license": "cc_by_nc", + "type": "PUBLISHAHEADOFPRINT", + "category": "epidemiology" }, { "rel_doi": "10.1101/2021.02.21.21252147", @@ -909452,51 +909100,75 @@ "category": "cell biology" }, { - "rel_doi": "10.1101/2021.02.18.21252032", - "rel_title": "The COVID-19 Incarceration Model: a tool for corrections staff to analyze outbreaks of COVID-19", - "rel_date": "2021-02-21", + "rel_doi": "10.1101/2021.02.15.21251752", + "rel_title": "Predicting mortality, duration of treatment, pulmonary embolism and required ceiling of ventilatory support for COVID-19 inpatients: A Machine-Learning Approach", + "rel_date": "2021-02-20", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.18.21252032", - "rel_abs": "Correctional facilities are at high risk of COVID-19 outbreaks due to the inevitable close contacts in the environment. Such facilities are a high priority in the public health response to the epidemic. We developed a user-friendly Excel spreadsheet model (building on the previously developed Recidiviz model) to analyze COVID-19 outbreaks in correctional facilities and the potential impact of prevention strategies -the COVID-19 Incarceration Model. The model requires limited inputs and can be used by non-modelers. The impact of a COVID-19 outbreak and mitigation strategies is illustrated for an example prison setting.", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.15.21251752", + "rel_abs": "IntroductionWithin the UK, COVID-19 has contributed towards over 103,000 deaths. Multiple risk factors for COVID-19 have been identified including various demographics, co-morbidities, biochemical parameters, and physical assessment findings. However, using this vast data to improve clinical care has proven challenging.\n\nAimsto develop a reliable, multivariable predictive model for COVID-19 in-patient outcomes, to aid risk-stratification and earlier clinical decision-making.\n\nMethodsAnonymized data regarding 44 independent predictor variables of 355 adults diagnosed with COVID-19, at a UK hospital, was manually extracted from electronic patient records for retrospective, case-controlled analysis. Primary outcomes included inpatient mortality, level of ventilatory support and oxygen therapy required, and duration of inpatient treatment. Secondary pulmonary embolism was the only secondary outcome. After balancing data, key variables were feature selected for each outcome using random forests. Predictive models were created using Bayesian Networks, and cross-validated.\n\nResultsOur multivariable models were able to predict, using feature selected risk factors, the probability of inpatient mortality (F1 score 83.7%, PPV 82%, NPV 67.9%); level of ventilatory support required (F1 score varies from 55.8% \"High-flow Oxygen level\" to 71.5% \"ITU-Admission level\"); duration of inpatient treatment (varies from 46.7% for \"[≥] 2 days but < 3 days\" to 69.8% \"[≤] 1 day\"); and risk of pulmonary embolism sequelae (F1 score 85.8%, PPV of 83.7%, and NPV of 80.9%).\n\nConclusionOverall, our findings demonstrate reliable, multivariable predictive models for 4 outcomes, that utilize readily available clinical information for COVID-19 adult inpatients. Further research is required to externally validate our models and demonstrate their utility as clinical decision-making tools.\n\nHighlightsO_LIUsing COVID-19 risk-factor data to assist clinical decision making is a challenge\nC_LIO_LIAnonymous data from 355 COVID-19 inpatients was collected & balanced\nC_LIO_LIKey independent variables were feature selected for 4 different outcomes\nC_LIO_LIAccurate, multi-variable predictive models were computed, using Bayesian Networks\nC_LIO_LIFuture research should externally validate our models & demonstrate clinical utility\nC_LI", + "rel_num_authors": 14, "rel_authors": [ { - "author_name": "Jisoo Amy Kwon", - "author_inst": "The Kirby Institute, University of New South Wales" + "author_name": "Abhinav Vepa", + "author_inst": "Milton Keynes University Hospital" }, { - "author_name": "Neil A Bretana", - "author_inst": "UniSA Online, University of South Australia, Australia" + "author_name": "Amer Saleem", + "author_inst": "Milton Keynes University Hospital" }, { - "author_name": "Luke Grant", - "author_inst": "Corrective Services NSW, Australia" + "author_name": "Kambiz Rakhshanbabanari", + "author_inst": "Coventry University" }, { - "author_name": "Jennifer Galouzis", - "author_inst": "Corrective Services NSW, Australia" + "author_name": "Amr Omar", + "author_inst": "Milton Keynes University Hospital" }, { - "author_name": "Wendy Hoey", - "author_inst": "Justice Health Forensic Mental Health Network NSW, Australia" + "author_name": "Diana Dharmaraj", + "author_inst": "Milton Keynes University Hospital" }, { - "author_name": "James Blogg", - "author_inst": "Justice Health Forensic Mental Health Network NSW, Australia" + "author_name": "Junaid Sami", + "author_inst": "Milton Keynes University Hospital" }, { - "author_name": "Andrew R Lloyd", - "author_inst": "Kirby Institute, UNSW Sydney, Sydney, New South Wales, Australia" + "author_name": "Shital Parekh", + "author_inst": "Milton Keynes University Hospital" }, { - "author_name": "Richard T Gray", - "author_inst": "Kirby Institute, UNSW Sydney, Sydney, New South Wales, Australia" + "author_name": "Mohamed Ibrahim", + "author_inst": "Milton Keynes University Hospital" + }, + { + "author_name": "Mohammed Raza", + "author_inst": "Milton Keynes University Hospital" + }, + { + "author_name": "Poonam Kapila", + "author_inst": "Milton Keynes University Hospital" + }, + { + "author_name": "Prithwiraj Chakrabarti", + "author_inst": "Milton Keynes University Hospital" + }, + { + "author_name": "Tabassom Sedighi", + "author_inst": "Cranfield University" + }, + { + "author_name": "Omid Chatrabgoun", + "author_inst": "Malayer University" + }, + { + "author_name": "Alireza Daneshkhah", + "author_inst": "Coventry University" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "public and global health" }, { "rel_doi": "10.1101/2021.02.15.21251772", @@ -910938,43 +910610,39 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.02.09.21251326", - "rel_title": "Lockdown and non-COVID-19 deaths: Cause-specific mortality during the first wave of the 2020 pandemic in Norway. A population-based register study", + "rel_doi": "10.1101/2021.02.15.21251745", + "rel_title": "The Effect of NFL and NCAA Football Games on the Spread of COVID-19 in the United States: An Empirical Analysis", "rel_date": "2021-02-19", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.09.21251326", - "rel_abs": "ObjectiveTo explore the potential impact of the first wave of COVID-19 pandemic on all cause and cause-specific mortality in Norway.\n\nDesignPopulation based register study.\n\nSettingThe Norwegian cause of Death Registry and the National Population Register of Norway.\n\nParticipantsAll recorded deaths in Norway during March to May from 2010 to 2020.\n\nMain outcome measuresRate (per 100 000) of all-cause mortality and causes of death in the EU Shortlist for Causes of Death March to May 2020. The rates were age-standardised and adjusted to a 100% register coverage and compared with a 95% prediction interval (PI) based on corresponding rates for 2010-2019.\n\nResults113 710 deaths were included, of which 10 226 from 2020. We did not observe any deviation from predicted total mortality. There were fewer than predicted deaths from chronic lower respiratory diseases excluding asthma (11.4, 95% PI 11.8 to 15.2) and from other non-ischemic, non-rheumatic heart diseases (13.9, 95% PI 14.5 to 20.2). The death rates were higher than predicted for Alzheimers disease (7.3, 95% PI 5.5 to 7.3) and diabetes mellitus (4.1, 95% PI 2.1 to 3.4).\n\nConclusionsThere was no significant difference in the frequency of the major causes of death in the first wave of the 2020 COVID-19 pandemic in Norway. An increase in diabetes mellitus deaths and reduced mortality due to some heart and lung conditions may be linked to infection control measures.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.15.21251745", + "rel_abs": "ImportanceIn 2020 and early 2021, the National Football League (NFL) and National Collegiate Athletic Association (NCAA) had opted to host games in stadiums across the country. The in-person attendance of games has varied with time and from county to county. There is currently no evidence on whether limited in-person attendance of games has caused a substantial increase in coronavirus disease 2019 (COVID-19) cases.\n\nObjectiveTo assess whether NFL and NCAA football games with limited in-person attendance have contributed to a substantial increase in COVID-19 cases in the counties they were held.\n\nDesignIn this time-series cross-sectional study, we matched every county hosting game(s) with in-person attendance (treated) in 2020 and 2021 with a county that has an identical game history for up to 14 days (control). We employed a standard matching method to further refine this matched set so that the treated and matched control counties have similar population size, non-pharmaceutical intervention(s) in place, and COVID-19 trends. We assessed the effect of hosting games with in-person attendance using a difference-in-difference estimator.\n\nSettingU.S. counties.\n\nParticipantsU.S. counties hosting NFL and/or NCAA games.\n\nExposureHosting NFL and/or NCAA games.\n\nMain outcomes and measuresEstimating the impact of NFL and NCAA games with in-person attendance on new, reported COVID-19 cases per 100,000 residents at the county-level up to 14 days post-game.\n\nResultsThe matching algorithm returned 361 matching sets of counties. The effect of in-person attendance at NFL and NCAA games on community COVID-19 spread is not significant as it did not surpass 5 new daily cases of COVID-19 per 100,000 residents on average.\n\nConclusions and relevanceThis time-series, cross-sectional matching study with a difference-in-differences design did not find an increase in COVID-19 cases per 100,000 residents in the counties where NFL and NCAA games were held with in-person attendance. Our study suggests that NFL and NCAA football games hosted with limited in-person attendance do not cause a significant increase in local COVID-19 cases.\n\nKey pointsO_ST_ABSQuestionC_ST_ABSDid NFL and NCAA football games with limited in-person attendance cause a substantia increase in coronavirus disease 2019 (COVID-19) cases in the U.S. counties where the games were held?\n\nFindingsThis time-series, cross-sectional study of U.S. counties with NFL and NCAA football games used matching and difference-in-differences design to estimate the effect of games with limited in-person attendance on county-level COVID-19 spread. Our study does not find an increase in county-level COVID-19 cases per 100,000 residents due to NFL and NCAA football games held with limited in-person attendance.\n\nMeaningThis study suggests that NFL and NCAA games held with limited in-person attendance do not cause an increase in COVID-19 cases in the counties they are held.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Guttorm Raknes", - "author_inst": "Norwegian Institute of Public Health" - }, - { - "author_name": "Marianne Sorlie Strom", - "author_inst": "Norwegian Institute of Public Health, Bergen, Norway" + "author_name": "Asmae Toumi", + "author_inst": "Massachusetts General Hospital" }, { - "author_name": "Gerhard Sulo", - "author_inst": "Norwegian Institute of Public Health" + "author_name": "Haoruo Zhao", + "author_inst": "Georgia Institute of Technology" }, { - "author_name": "Simon Nygaard Overland", - "author_inst": "Norwegian Institute of Public Health" + "author_name": "Jagpreet Chhatwal", + "author_inst": "Massachusetts General Hospital" }, { - "author_name": "Mathieu Roelants", - "author_inst": "KU Leuven - University of Leuven, Leuven, Belgium" + "author_name": "Benjamin P. Linas", + "author_inst": "Boston University School of Public Health" }, { - "author_name": "Petur Benedikt Juliusson", - "author_inst": "Norwegian Institute of Public Health" + "author_name": "Turgay Ayer", + "author_inst": "Georgia Institute of Technology" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "health policy" }, { "rel_doi": "10.1101/2021.02.16.21251850", @@ -912388,23 +912056,99 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2021.02.16.21251769", - "rel_title": "Associations of Race/Ethnicity and Other Demographic and Socioeconomic Factors with Vaccination During the COVID-19 Pandemic in the United States", + "rel_doi": "10.1101/2021.02.17.21251929", + "rel_title": "COVID-BioB Cohort Study: the neutralizing antibody response to SARS-CoV-2 in symptomatic COVID-19 is persistent and critical for virus control and survival.", "rel_date": "2021-02-19", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.16.21251769", - "rel_abs": "BackgroundTo date, there has been limited data available to understand the associations between race/ethnicity and socioeconomic and related characteristics with novel coronavirus disease (COVID-19) vaccine initiation and planned vaccination in the United States.\n\nMethodsTo better characterize COVID-19 vaccinations nationally, we leveraged large cross-sectional surveys conducted between January and March 2021 with relatively complete race/ethnicity and socioeconomic data and nationally-representative of U.S. households to estimate trends in levels of COVID-19 vaccine initiation and vaccine intention. We further used survey data from January and March 2021 in adults aged 18-85 years to analyze the associations between race/ethnicity, education, pre-pandemic household income, and financial hardship during the pandemic and the adjusted odds of: 1) receipt of [≥]1 dose of a COVID-19 vaccine; and 2) among those unvaccinated, the definite intention to receive a vaccine, controlling for other demographic and socioeconomic factors.\n\nResultsWe observed persistent disparities in vaccine initiation for non-Hispanic Blacks, Hispanics, and non-Hispanic multiracial persons, and in vaccine intention for Blacks and multiracial persons, compared to non-Hispanic Whites and non-Hispanic Asians. In late March 2021, the prevalence estimates of Hispanics and Blacks receiving a vaccine were 12 percentage points and 8 percentage points lower than for Whites, respectively. Moreover, both education and income levels exhibited positive dose-response relationships with vaccine initiation (P for trend[≤]01 and <.001, respectively). Substantial financial hardship was linked to 35-44% lower odds of vaccination (P<.001). The most common reasons for vaccine hesitancy were concerns about side effects and safety, with evidence of higher levels of concerns about vaccine safety among Blacks vs. Whites.\n\nConclusionsIn this large, nationally-representative study with relatively complete race/ethnicity and socioeconomic data, we find that being Black non-Hispanic and having the least education and income were each independently associated with a markedly lower likelihood of definitely planning to get vaccinated or having been vaccinated. In the ensuing months of the pandemic, addressing the persevering racial/ethnic and socioeconomic inequities in vaccination due to differential access and vaccine hesitancy is essential to mitigate the pandemics higher risks of infection and adverse health outcomes in Hispanic, Black, and socioeconomically-disadvantaged communities.", - "rel_num_authors": 1, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.17.21251929", + "rel_abs": "Understanding how antibody to SARS-CoV-2 evolve during infection may provide important insight into therapeutic approaches to prevent fatal COVID-19 illness and vaccines. Here, we profile the antibody response of 162 well-characterized COVID-19 symptomatic patients followed longitudinally for up to eight months from symptom onset. Using two newly developed assays we detect SARS-CoV-2 neutralization and antibodies binding to Spike antigens and nucleoprotein as well as to Spike S2 antigen of seasonal beta-coronaviruses, and to hemagglutinin of the H1N1 flu virus. Presence of neutralizing antibodies withing the first weeks from symptom onset correlates with time to a negative swab result (p=0.002) while lack of neutralization with an increased risk of a fatal disease outcome (HR 2.918, 95%CI 1.321-6.449; p=0.008). Neutralizing antibody titers progressively drop after 5-8 weeks but are still detectable up to 8 months in the majority of recovered patients regardless of age or co-morbidities. IgG to Spike antigens are the best correlate of neutralization. Antibody responses to seasonal coronaviruses are temporary boosted and parallel those to SARS-CoV-2 without dampening the specific response or worsening disease progression. Thus, a compromised immune response to the Spike rather than an enhanced one is a major trait of patients with critical conditions. Patients should be promptly identified and immediately start therapeutic interventions aimed at restoring their immunity.", + "rel_num_authors": 20, "rel_authors": [ { - "author_name": "Daniel Kim", - "author_inst": "Northeastern University" + "author_name": "Stefania Dispinseri", + "author_inst": "IRCCS Ospedale San Raffaele" + }, + { + "author_name": "Massimiliano Secchi", + "author_inst": "IRCCS Ospedale San Raffaele" + }, + { + "author_name": "Maria Franca Pirillo", + "author_inst": "Istituto Superiore di Sanita" + }, + { + "author_name": "Monica Tolazzi", + "author_inst": "IRCCS Ospedale San Raffaele" + }, + { + "author_name": "Martina Borghi", + "author_inst": "Istituto Superiore di Sanita" + }, + { + "author_name": "Cristina Brigatti", + "author_inst": "IRCCS Ospedale San Raffaele" + }, + { + "author_name": "Maria Laura De Angelis", + "author_inst": "Istituto Superiore di Sanita" + }, + { + "author_name": "Marco Baratella", + "author_inst": "IRCCS Ospedale San Raffaele" + }, + { + "author_name": "Elena Bazzigaluppi", + "author_inst": "IRCCS Ospedale San Raffaele" + }, + { + "author_name": "Giulietta Venturi", + "author_inst": "Istituto Superiore di Sanita" + }, + { + "author_name": "Francesca Sironi", + "author_inst": "IRCCS Ospedale San Raffaele" + }, + { + "author_name": "Andrea Canitano", + "author_inst": "Istituto Superiore di Sanita" + }, + { + "author_name": "Ilaria Marzinotto", + "author_inst": "IRCCS Ospedale San Raffaele" + }, + { + "author_name": "Cristina Tresoldi", + "author_inst": "IRCCS Ospedale San Raffaele" + }, + { + "author_name": "Fabio Ciceri", + "author_inst": "IRCCS Ospedale San Raffaele" + }, + { + "author_name": "Lorenzo Piemonti", + "author_inst": "IRCCS Ospedale San Raffaele" + }, + { + "author_name": "Donatella Negri", + "author_inst": "Istituto Superiore di Sanita" + }, + { + "author_name": "Andrea Cara", + "author_inst": "Istituto Superiore di Sanita" + }, + { + "author_name": "Vito Lampasona", + "author_inst": "IRCCS Ospedale San Raffaele" + }, + { + "author_name": "Gabriella Scarlatti", + "author_inst": "IRCCS Ospedale San Raffaele" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2021.02.17.21251895", @@ -914130,55 +913874,55 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.02.19.431972", - "rel_title": "Antiviral activity of influenza A virus defective interfering particles against SARS-CoV-2 replication in vitro through stimulation of innate immunity", + "rel_doi": "10.1101/2021.02.19.431311", + "rel_title": "SARS-CoV-2 variant evolution in the United States: High accumulation of viral mutations over time likely through serial Founder Events and mutational bursts.", "rel_date": "2021-02-19", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.02.19.431972", - "rel_abs": "SARS-CoV-2 causing COVID-19 emerged in late 2019 and resulted in a devastating pandemic. Although the first approved vaccines were already administered by the end of 2020, worldwide vaccine availability is still limited. Moreover, immune escape variants of the virus are emerging against which the current vaccines may confer only limited protection. Further, existing antivirals and treatment options against COVID-19 only show limited efficacy. Influenza A virus (IAV) defective interfering particles (DIPs) were previously proposed not only for antiviral treatment of the influenza disease but also for pan-specific treatment of interferon (IFN)-sensitive respiratory virus infections. To investigate the applicability of IAV DIPs as an antiviral for the treatment of COVID-19, we conducted in vitro co-infection experiments with cell culture-derived DIPs and the IFN-sensitive SARS-CoV-2 in human lung cells. We show that treatment with IAV DIPs leads to complete abrogation of SARS-CoV-2 replication. Moreover, this inhibitory effect was dependent on janus kinase/signal transducers and activators of transcription (JAK/STAT) signaling. Further, our results suggest boosting of IFN-induced antiviral activity by IAV DIPs as a major contributor in suppressing SARS-CoV-2 replication. Thus, we propose IAV DIPs as an effective antiviral agent for treatment of COVID-19, and potentially also for suppressing the replication of new variants of SARS-CoV-2.", + "rel_link": "https://biorxiv.org/cgi/content/short/2021.02.19.431311", + "rel_abs": "Since the first case of COVID-19 in December 2019 in Wuhan, China, SARS-CoV-2 has spread worldwide and within a year has caused 2.29 million deaths globally. With dramatically increasing infection numbers, and the arrival of new variants with increased infectivity, tracking the evolution of its genome is crucial for effectively controlling the pandemic and informing vaccine platform development. Our study explores evolution of SARS-CoV-2 in a representative cohort of sequences covering the entire genome in the United States, through all of 2020 and early 2021. Strikingly, we detected many accumulating Single Nucleotide Variations (SNVs) encoding amino acid changes in the SARS-CoV-2 genome, with a pattern indicative of RNA editing enzymes as major mutators of SARS-CoV-2 genomes. We report three major variants through October of 2020. These revealed 14 key mutations that were found in various combinations among 14 distinct predominant signatures. These signatures likely represent evolutionary lineages of SARS-CoV-2 in the U.S. and reveal clues to its evolution such as a mutational burst in the summer of 2020 likely leading to a homegrown new variant, and a trend towards higher mutational load among viral isolates, but with occasional mutation loss. The last quartile of 2020 revealed a concerning accumulation of mostly novel low frequency replacement mutations in the Spike protein, and a hypermutable glutamine residue near the putative furin cleavage site. Finally, the end of the year data revealed the presence of known variants of concern including B.1.1.7, which has acquired additional Spike mutations. Overall, our results suggest that predominant viral sequences are dynamically evolving over time, with periods of mutational bursts and unabated mutation accumulation. This high level of existing variation, even at low frequencies and especially in the Spike-encoding region may be become problematic when superspreader events, akin to serial Founder Events in evolution, drive these rare mutations to prominence.\n\nAUTHOR SUMMARYThe pandemic of coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has caused the death of more than 2.29 million people and continues to be a severe threat internationally. Although simple measures such as social distancing, periodic lockdowns and hygiene protocols were immediately put into force, the infection rates were only temporarily minimized. When infection rates exploded again new variants of the virus began to emerge. Our study focuses on a representative set of sequences from the United States throughout 2020 and early 2021. We show that the driving force behind the variants of public health concern, is widespread infection and superspreader events. In particular, we show accumulation of mutations over time with little loss from genetic drift, including in the Spike region, which could be problematic for vaccines and therapies. This lurking accumulated genetic variation may be a superspreader event from becoming more common and lead to variants that can escape the immune protection provided by the existing vaccines.", "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Ulfert Rand", - "author_inst": "Helmholtz Centre for Infection Research" + "author_name": "Rafail Nikolaos Tasakis", + "author_inst": "German Cancer Research Center (DKFZ), Heidelberg, Germany" }, { - "author_name": "Sascha Young Kupke", - "author_inst": "Max Planck Institute for Dynamics of Complex Technical Systems" + "author_name": "Georgios Samaras", + "author_inst": "German Cancer Research Center (DKFZ), Heidelberg, Germany" }, { - "author_name": "Hanna Shkarlet", - "author_inst": "Helmholtz Centre for Infection Research and Otto von Guericke University Magdeburg" + "author_name": "Anna Jamison", + "author_inst": "The Nightingale-Bamford School, New York, NY, USA" }, { - "author_name": "Marc Dominique Hein", - "author_inst": "Otto von Guericke University Magdeburg" + "author_name": "Michelle Lee", + "author_inst": "Cornell University, Ithaca, NY, USA" }, { - "author_name": "Tatjana Hirsch", - "author_inst": "Helmholtz Centre for Infection Research" + "author_name": "Alexandra Paulus", + "author_inst": "The Nightingale-Bamford School, New York, NY, USA" }, { - "author_name": "Pavel Marichal-Gallardo", - "author_inst": "Max Planck Institute for Dynamics of Complex Technical Systems" + "author_name": "Gabrielle Whitehouse", + "author_inst": "The Nightingale-Bamford School, New York, NY, USA" }, { - "author_name": "Luka Cicin-Sain", - "author_inst": "Helmholtz Centre for Infection Research and German Centre for Infection Research" + "author_name": "Laurent Verkoczy", + "author_inst": "San Diego Biomedical Research Institute (SDBRI), San Diego, CA, USA" }, { - "author_name": "Udo Reichl", - "author_inst": "Max Planck Institute for Dynamics of Complex Technical Systems and Otto von Guericke University Magdeburg" + "author_name": "F. Nina Papavasiliou", + "author_inst": "German Cancer Research Center (DKFZ), Heidelberg, Germany" }, { - "author_name": "Dunja Bruder", - "author_inst": "Helmholtz Centre for Infection Research and Otto von Guericke University Magdeburg" + "author_name": "Marilyn Diaz", + "author_inst": "San Diego Biomedical Research Institute (SDBRI), San Diego, CA, USA" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "new results", - "category": "microbiology" + "category": "genetics" }, { "rel_doi": "10.1101/2021.02.18.21250737", @@ -915932,39 +915676,39 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.02.15.21251771", - "rel_title": "Interrogating structural inequalities in COVID-19 Mortality in England and Wales", + "rel_doi": "10.1101/2021.02.15.21251726", + "rel_title": "Are we back to normal yet? The impact of the COVID-19 pandemic on mental health with a specific focus on schizotypal traits in the general population of Germany and the UK, comparing responses from April/May vs. September/October", "rel_date": "2021-02-17", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.15.21251771", - "rel_abs": "BackgroundNumerous observational studies have highlighted structural inequalities in COVID-19 mortality in the UK. Such studies often fail to consider the complex spatial nature of such inequalities in their analysis, leading to the potential for bias and an inability to reach conclusions about the most appropriate structural levels for policy intervention.\n\nMethodsWe use publicly available population data on COVID-19 related- and all-cause mortality between March and July 2020 in England and Wales to investigate the spatial scale of such inequalities. We propose a multiscale approach to simultaneously consider four spatial scales at which processes driving inequality may act and apportion inequality between these.\n\nResultsAdjusting for population age structure, number of care homes and residing in the North we find highest regional inequality in March and June/July. We find finer-grained within-region increased steadily from March until July. The importance of spatial context increases over the study period. No analogous pattern is visible for non-COVID mortality. Higher relative deprivation is associated with increased COVID-19 mortality at all stages of the pandemic but does not explain structural inequalities.\n\nConclusionsResults support initial stochastic viral introduction in the South, with initially high inequality decreasing before the establishment of regional trends by June and July, prior to reported regionality of the \"second-wave\". We outline how this framework can help identify structural factors driving such processes, and offer suggestions for a long-term, locally-targeted model of pandemic relief in tandem with regional support to buffer the social context of the area.\n\nKey MessagesO_LIRegional inequality in COVID-19 mortality declined from an initial peak in April, before increasing again in June/July.\nC_LIO_LIWithin-region inequality increased steadily from March until July.\nC_LIO_LIStrong regional trends are evident in COVID-19 mortality in June/July, prior to wider reporting of regional differences in \"second wave\".\nC_LIO_LIAnalogous spatial inequalities are not present in non-COVID related mortality over the study period.\nC_LIO_LIThese inequalities are not explained by age structure, care homes, or deprivation.\nC_LI", + "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.15.21251726", + "rel_abs": "Studies reported a strong impact on mental health during the first wave of the COVID-19 pandemic in March-June, 2020. In this study, we assessed the impact of the pandemic on mental health in general and on schizoptypal traits in two independent general population samples of the UK (May sample N: 239, October sample N: 126; participation at both timepoints: 21) and in two independent general population samples of Germany (May sample N: 543, October sample N: 401; participation at both timepoints: 100) using online surveys. Whereas general psychological symptoms (global symptom index, GSI) and percentage of responders above clinical cut-off for further psychological investigation were higher in the May sample compared to the October sample, schizotypy scores (Schizotypal Personality Questionnaire) were higher in the October sample. We investigated potential associations, using general linear regression models (GLM). For schizotypy scores, we found that loneliness, use of drugs, and financial burden were more strongly corrected with schizotypy in the October compared to the May sample. We identified similar associations for GSI, as for schizotypy scores, in the May and October samples. We furthermore found that living in the UK was related to higher schizotypal scores or GSI. However, individual estimates of the GLM are highly comparable between the two countries. In conclusion, this study shows that while the general psychological impact is lower in the October than the May sample, potentially showing a normative response to an exceptional situation; schizotypy scores are higher at the second timepoint, which may be due to a stronger impact of estimates of loneliness, drug use, and financial burden. The ongoing, exceptional circumstances within this pandemic might increase the risk for developing psychosis in some individuals. The development of general psychological symptoms and schizotypy scores over time requires further attention and investigation.", "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Gareth J Griffith", - "author_inst": "University of Bristol" + "author_name": "Sarah Daimer", + "author_inst": "Technical University of Munich" }, { - "author_name": "George Davey Smith", - "author_inst": "University of Bristol" + "author_name": "Lorenz Mihatsch", + "author_inst": "Technical University of Munich" }, { - "author_name": "David Manley", - "author_inst": "University of Bristol, School of Geographical Sciences" + "author_name": "Lisa Ronan", + "author_inst": "University of Cambridge" }, { - "author_name": "Laura D Howe", - "author_inst": "University of Bristol" + "author_name": "Graham K Murray", + "author_inst": "University of Cambridge" }, { - "author_name": "Gwilym Owen", - "author_inst": "University of Liverpool" + "author_name": "Franziska Knolle", + "author_inst": "Technical University Munich" } ], "version": "1", "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "psychiatry and clinical psychology" }, { "rel_doi": "10.1101/2021.02.16.21251807", @@ -917813,87 +917557,55 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2021.02.09.21251149", - "rel_title": "A multi-centre service evaluation of the impact of the COVID-19 pandemic on presentation of newly diagnosed cancers and type 1 diabetes in children in the UK", + "rel_doi": "10.1101/2021.02.15.21250916", + "rel_title": "SARS-CoV-2 antibody immunoassays in serial samples reveal earlier seroconversion in acutely ill COVID-19 patients developing ARDS", "rel_date": "2021-02-16", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.09.21251149", - "rel_abs": "BackgroundThe COVID-19 pandemic led to changes in patterns of presentation to Emergency Departments (ED). Child health professionals were concerned that this could contribute to the delayed diagnosis of life-threatening conditions, including childhood cancer (CC) and type 1 diabetes (T1DM). Our multicentre, UK-based service evaluation assessed diagnostic intervals and disease severity for these conditions.\n\nMethodsWe collected presentation route, timing and disease severity for children with newly diagnosed CC in three principal treatment centres, and T1DM in four centres between 1stJanuary - 31st July 2020 and the corresponding period in 2019. We assessed the impact of lockdown on total diagnostic interval (TDI), patient interval (PI), system interval (SI) and disease severity.\n\nFindingsFor CCs and T1DM, the route to diagnosis and severity of illness at presentation were unchanged across all time periods. Diagnostic intervals for CCs during lockdown were comparable to that in 2019 (TDI 4.6, PI 1.1 and SI 2.1 weeks), except for an increased PI in Jan-Mar 2020 (median 2.7 weeks). Diagnostic intervals for T1DM during lockdown were similar to that in 2019 (TDI 16 vs 15 and PI 14 vs 14 days), except for an increased PI in Jan-Mar 2020 (median 21 days).\n\nInterpretationThere is no evidence of diagnostic delay or increased illness severity for CC or T1DM, during the first phase of the pandemic across the participating centres. This provides reassuring data for children and families with these life-changing conditions.\n\nResearch in ContextO_ST_ABSEvidence before this studyC_ST_ABSThis project was initiated after the first national lockdown in March 2020 during COVID-19 pandemic in the UK. At the design stage, Medline was searched (with no language limit), using the keywords ((Cancer) OR (neoplasm) OR (Type 1 diabetes mellitus)) AND ((Covid-19) OR (SARS-CoV-2) OR (Pandemics)) AND ((Emergency department attendances) OR (diabetes ketoacidosis) OR (Delayed diagnosis) OR (interval) OR (wait)) to identify publications reporting the impact of the pandemic and public health measures on both overall and paediatric healthcare services. Significant changes in service utilisation in the UK were reported following the commencement of the first lockdown, including a 49% reduction in emergency department attendances in the week following the lockdown; and two adult studies reported that referral via the urgent two-week wait cancer referral diagnoses decreased by 84% from Mar-May and 60% in June 2020. As for Type 1 diabetes (T1DM), a 30 patient UK-study reported an increase in newly diagnosed T1DM during the first six weeks of lockdown. Increased proportions of severe diabetic ketoacidosis (DKA) at presentation were also reported in an Italian survey involving 53 paediatric diabetes centres. Through the search we identified a need for multi-centre, more thorough assessment on referral pathways, time taken from symptom onset to diagnosis, and its association with severity at presentation for children diagnosed with life-changing conditions during the national lockdown.\n\nAdded value of this studyOur findings suggest that the first national lockdown in the UK were not associated with delayed diagnosis of childhood cancer or type 1 diabetes at participating centres. This provides reassuring information for children and families with these life-changing conditions.\n\nImplicationWe believe that our study can play a key role in allaying parental and professional concern. it is important to establish whether subsequent public health measures have impacted the diagnostic interval in the context of an evolving backlog of patient referrals across the UK.", - "rel_num_authors": 17, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.15.21250916", + "rel_abs": "ObjectivesDuring the COVID-19 pandemic, SARS-CoV-2 antibody testing has been suggested for (1) screening populations for disease prevalence, (2) diagnostics, and (3) guiding therapeutic applications. Here, we conducted a detailed clinical evaluation of four Anti-SARS-CoV-2 immunoassays in samples from acutely ill COVID-19 patients and in two negative cohorts.\n\nMethods443 serum specimens from serial sampling of 29 COVID-19 patients were used to determine clinical sensitivities. Patients were stratified for the presence of acute respiratory distress syndrome (ARDS). Individual serum specimens from a pre-COVID-19 cohort of 238 healthy subjects and from a PCR-negative clinical cohort of 257 patients were used to determine clinical specificities. All samples were measured side-by-side with the Anti-SARS-CoV-2-ELISA (IgG), Anti-SARS-CoV-2-ELISA (IgA) and Anti-SARS-CoV-2-NCP-ELISA (IgG) (Euroimmun AG, Lubeck, Germany) and the Elecsys Anti-SARS-CoV-2 ECLIA (Roche Diagnostics International, Rotkreuz, Switzerland).\n\nResultsMedian seroconversion occurred earlier in ARDS patients (8-9 days) than in non-ARDS patients (11-17 days), except for EUR N-IgG. Rates of positivity and mean signal ratios in the ARDS group were significantly higher than in the non-ARDS group. Sensitivities between the four tested immunoassays were equivalent. In the set of negative samples, the specificity of the Anti-SARS-CoV-2-ELISA (IgA) was lower (93.9 %) compared to all other assays ([≥]98.8 %) and the specificity of Anti-SARS-CoV-2-NCP-ELISA (IgG) was lower (98.8 %) than that of Elecsys Anti-SARS-CoV-2 (100 %).\n\nConclusionsSerial sampling in COVID-19 patients revealed earlier seroconversion and higher signal ratios of SARS-CoV-2 antibodies as a potential risk marker for the development of ARDS, suggesting a utility for antibody testing in acutely diseased patients.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "- COVID-19 Pandemic UK-based Interest Group of Childhood Cancer and Diabetes", - "author_inst": "" - }, - { - "author_name": "Gemma Williams", - "author_inst": "Leeds Children's Hospital" - }, - { - "author_name": "Ross McLean", - "author_inst": "University Hospital Wishaw, Lanarkshire" - }, - { - "author_name": "Jo-Fen Liu", - "author_inst": "Children's Brain Tumour Research Centre, University of Nottingham" - }, - { - "author_name": "Timothy Ritzmann", - "author_inst": "Children's Brain Tumour Research Centre, University of Nottingham & Nottingham University Hospitals NHS Trust" - }, - { - "author_name": "Madhumita Dandapani", - "author_inst": "Children's Brain Tumour Research Centre, University of Nottingham & Nottingham University Hospitals NHS Trust" - }, - { - "author_name": "Dhurgshaarna Shanmugavadivel", - "author_inst": "Children's Brain Tumour Research Centre, University of Nottingham" - }, - { - "author_name": "Pooja Sachdev", - "author_inst": "Nottingham University Hospitals NHS Trust" - }, - { - "author_name": "Mark Brougham", - "author_inst": "Royal Hospital for Sick Children, Edinburgh" + "author_name": "Marie-Luise Buchholtz", + "author_inst": "Institute of Laboratory Medicine, University Hospital, LMU Munich, Munich, Germany" }, { - "author_name": "Rod Mitchell", - "author_inst": "University of Edinburgh & Royal Hospital for Sick Children" + "author_name": "Florian M. Arend", + "author_inst": "Institute of Laboratory Medicine, University Hospital, LMU Munich, Munich, Germany" }, { - "author_name": "Nicholas T Conway", - "author_inst": "Tayside Children's Hospital & University of Dundee" + "author_name": "Peter Eichhorn", + "author_inst": "Institute of Laboratory Medicine, University Hospital, LMU Munich, Munich, Germany" }, { - "author_name": "James Law", - "author_inst": "Nottingham University Hospitals NHS Trust" + "author_name": "Michael Weigand", + "author_inst": "Institute of Laboratory Medicine, University Hospital, LMU Munich, Munich, Germany" }, { - "author_name": "Alice Cunnington", - "author_inst": "Nottingham University Hospitals NHS Trust" + "author_name": "Alisa Kleinhempel", + "author_inst": "Institute of Laboratory Medicine, University Hospital, LMU Munich, Munich, Germany" }, { - "author_name": "Gbemi Ogunnaike", - "author_inst": "Nottingham University Hospitals NHS Trust" + "author_name": "Kurt H\u00e4usler", + "author_inst": "Institute of Laboratory Medicine, University Hospital, LMU Munich, Munich, Germany" }, { - "author_name": "Karen Brougham", - "author_inst": "Royal Hospital for Sick Children, Edinburgh" + "author_name": "Mathias Bruegel", + "author_inst": "Institute of Laboratory Medicine, University Hospital, LMU Munich, Munich, Germany" }, { - "author_name": "Elizabeth Bayman", - "author_inst": "Royal Hospital for Sick Children, Edinburgh" + "author_name": "Lesca M. Holdt", + "author_inst": "Institute of Laboratory Medicine, University Hospital, LMU Munich, Munich, Germany" }, { - "author_name": "David A Walker", - "author_inst": "Children's Brain Tumour Research Centre, University of Nottingham" + "author_name": "Daniel Teupser", + "author_inst": "Institute of Laboratory Medicine, University Hospital, LMU Munich, Munich, Germany" } ], "version": "1", "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "pediatrics" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2021.02.16.21251803", @@ -919466,35 +919178,75 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.02.13.21251683", - "rel_title": "Learning Where to Look for COVID-19 Growth: Multivariate Analysis of COVID-19 Cases Over Time using Explainable Convolution-LSTM", - "rel_date": "2021-02-16", + "rel_doi": "10.1101/2021.02.10.21251350", + "rel_title": "C-reactive protein guided use of procalcitonin in COVID-19", + "rel_date": "2021-02-15", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.13.21251683", - "rel_abs": "Determinant factors which contribute to the prediction should take into account multivariate analysis for capturing coarse-to-fine contextual information. From the preliminary descriptive analysis, it shows that environmental factor such as UV (ultraviolet) is one of the essential factors that should be considered to observe the COVID-19 epidemic drivers, During summer, UV can inactivate viruses that live in the air and on the surface of the objects especially at noon in tropical or subtropical countries. However, it may not be significant in closed spaces like workspace and areas with the intensive human-to-human transmission, especially in densely populated areas. Different COVID-19 pandemic growth patterns in northern subtropical, southern subtropical and tropical countries occur over time. Moreover, there are education, government, morphological, health, economic, and behavioral factors contributing to the growth of COVID-19. Multivariate analysis via visual attribution of explainable Convolution-LSTM is utilized to see high contributing factors responsible for the growth of daily COVID-19 cases. For future works, data to be analyzed should be more detailed in terms of the region and the period where the time-series sample is acquired. The explainable Convolution-LSTM code is available here: https://github.com/cbasemaster/time-series-attribution", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.10.21251350", + "rel_abs": "Low procalcitonin (PCT) concentrations (<0.5ng/mL) can facilitate exclusion of bacterial co-infection in viral infections, including COVID-19. However, costs associated with PCT measurement preclude universal adoption, indicating a need to identify settings where PCT provides clinical information beyond that offered by other inflammatory markers, such as C-reactive protein (CRP) and white cell count (WCC). In an unselected cohort of 299 COVID-19 patients, we tested the hypothesis that PCT<0.5ng/mL was associated with lower levels of CRP and WCC. We demonstrated that CRP values below the geometric mean of the entire patient population had a negative predictive value for PCT<0.5ng/mL of 97.6% and 100% at baseline and 48 hours into admission respectively, and that this relationship was not confounded by intensive care admission or microbiological findings. CRP-guided PCT testing algorithms can reduce costs and support antimicrobial stewardship strategies in COVID-19.", + "rel_num_authors": 14, "rel_authors": [ { - "author_name": "Novanto Yudistira", - "author_inst": "Brawijaya University" + "author_name": "Rebecca Houghton", + "author_inst": "Hampshire Hospitals NHS Foundation Trust" }, { - "author_name": "Sutiman Bambang Sumitro", - "author_inst": "Brawijaya University" + "author_name": "Nathan Moore", + "author_inst": "Hampshire Hospitals NHS Foundation Trust" }, { - "author_name": "Alberth Christian Nahas", - "author_inst": "INDONESIAN AGENCY FOR METEOROLOGY, CLIMATOLOGY, AND GEOPHYSICS (BMKG)" + "author_name": "Rebecca Williams", + "author_inst": "Hampshire Hospitals NHS Foundation Trust" }, { - "author_name": "Nelly Florida Riama", - "author_inst": "INDONESIAN AGENCY FOR METEOROLOGY, CLIMATOLOGY, AND GEOPHYSICS (BMKG)" + "author_name": "Fatima El-Bakri", + "author_inst": "Hampshire Hospitals NHS Foundation Trust" + }, + { + "author_name": "Jonathan Peters", + "author_inst": "Hampshire Hospitals NHS Foundation Trust" + }, + { + "author_name": "Matilde Mori", + "author_inst": "Hampshire Hospitals NHS Foundation Trust" + }, + { + "author_name": "Gabrielle Vernet", + "author_inst": "Hampshire Hospitals NHS Foundation Trust" + }, + { + "author_name": "Jessica Lynch", + "author_inst": "Hampshire Hospitals NHS Foundation Trust" + }, + { + "author_name": "Henry Lewis", + "author_inst": "Hampshire Hospitals NHS Foundation Trust" + }, + { + "author_name": "Maryanna Tavener", + "author_inst": "Hampshire Hospitals NHS Foundation Trust" + }, + { + "author_name": "Tom Durham", + "author_inst": "Hampshire Hospitals NHS Foundation Trust" + }, + { + "author_name": "Jack Bowyer", + "author_inst": "Hampshire Hospitals NHS Foundation Trust" + }, + { + "author_name": "Kordo Saeed", + "author_inst": "University of Southampton, School of Medicine" + }, + { + "author_name": "Gabriele Pollara", + "author_inst": "University College London" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "health economics" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2021.02.10.21250915", @@ -921116,51 +920868,23 @@ "category": "nursing" }, { - "rel_doi": "10.1101/2021.02.09.21251443", - "rel_title": "Evaluation of Facial Protection Against Close-Contact Droplet Transmission", + "rel_doi": "10.1101/2021.02.12.21249710", + "rel_title": "Risk of Corona virus disease 2019 (COVID-19) among spectacles wearing population of Northern India", "rel_date": "2021-02-15", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.09.21251443", - "rel_abs": "BackgroundFace shields are used as an alternative to facemasks, but their effectiveness in mitigating the spread of SARS-CoV-2 is unclear. The goal of this study is to compare the performance of face shields, surgical facemasks, and cloth facemasks for mitigation of droplet transmission during close contact conditions.\n\nMethodsA novel test system was developed to simulate droplet transmission during close contact conditions using two breathing headforms (transmitter and receiver) placed 4 feet apart with one producing droplets containing a DNA marker. Sampling coupons were placed throughout the test setup and subsequently analyzed for presence of DNA marker using quantitative PCR.\n\nResultsAll PPE donned on the transmitter headform provided a significant reduction in transmission of DNA marker to the receiver headform: cloth facemask (78.5%), surgical facemask (89.4%), and face shield (96.1%). All PPE resulted in increased contamination of the eye region of the transmitter headform (9,525.4% average for facemasks and 765.8% for the face shield). Only the face shield increased contamination of the neck region (207.4%), with the cloth facemask and surgical facemask resulting in reductions of 85.9% and 90.2%, respectively.\n\nConclusionsThis study demonstrates face shields can provide similar levels of protection against direct droplet exposure compared to surgical and cloth masks. However, all PPE tested resulted in release of particles that contaminated surfaces. Contamination caused by deflection of the users exhalation prompts concerns for contact transmission via surfaces in exhalation flow path (e.g., face, eyeglasses, etc.).", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.12.21249710", + "rel_abs": "IntroductionSevere Acute Respiratory Syndrome Corona virus-2 (SARS-CoV-2) spread mainly through respiratory droplets and contact routes. Long term use of spectacles may prevent repeated touching and rubbing of the eyes. Aim of the study is to find out the protective effectiveness of the spectacles against COVID-19, if present.\n\nObjectivesTo know the association between infection with SARSCoV-2 and wearing of spectacles.\n\nMaterials and methodsIn this study, 304 patients of Corona virus disease 2019 (COVID-19) were selected. Their spectacles wearing behaviour were assessed through a questionnaire. Spectacles wearing behaviour of general population were obtained from older studies (for comparison). Data was put in the tabulate form and Chi- Square test was used for statistical analysis.\n\nResultsIn this study, among the 304 total patients, 58 patients showed the behavior of using spectacles continuously during day time and always on outdoor activities. While the spectacles wearing behaviour is about 40% among general Indian population. The protective effectiveness of the spectacles was found statistically significant (p-value. 00113).\n\nConclusionThe present study showed that the occurrence of Covid-19 was less in spectacles wearing population than the population not wearing those. The nasolacrimal duct may be a route of virus transmission from conjunctival sac to the nasopharynx.", + "rel_num_authors": 1, "rel_authors": [ { - "author_name": "Thomas B Stephenson", - "author_inst": "Applied Research Associates, Engineering Science Division" - }, - { - "author_name": "Courtney Cumberland", - "author_inst": "Applied Research Associates, Engineering Science Division" - }, - { - "author_name": "Geoff Kibble", - "author_inst": "Applied Research Associates, Engineering Science Division" - }, - { - "author_name": "Christopher Church", - "author_inst": "Applied Research Associates, Engineering Science Division" - }, - { - "author_name": "Sheila Nogueira-Prewitt", - "author_inst": "Applied Research Associates, Engineering Science Division" - }, - { - "author_name": "Sebastian MacNamara", - "author_inst": "Applied Research Associates, Engineering Science Division" - }, - { - "author_name": "Delbert A Harnish", - "author_inst": "Applied Research Associates, Engineering Science Division" - }, - { - "author_name": "Brian K Heimbuch", - "author_inst": "Applied Research Associates, Engineering Science Division" + "author_name": "Amit Kumar Saxena", + "author_inst": "NPCB Center, Department of Health" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "occupational and environmental health" + "category": "ophthalmology" }, { "rel_doi": "10.1101/2021.02.11.20196766", @@ -922974,30 +922698,158 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.02.09.21251288", - "rel_title": "Epidemic transmission with quarantine measures: application to COVID-19", + "rel_doi": "10.1101/2021.02.09.21251404", + "rel_title": "Temporal trends of SARS-CoV-2 seroprevalence in transfusion blood donors during the first wave of the COVID-19 epidemic in Kenya", "rel_date": "2021-02-12", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.09.21251288", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.09.21251404", + "rel_num_authors": 35, "rel_authors": [ { - "author_name": "Sergey A Trigger", - "author_inst": "Joint Institute for High Temperatures Russian Academy of Sciences" + "author_name": "Ifedayo M. O Adetifa", + "author_inst": "KEMRI-Wellcome Trust Research Programme" }, { - "author_name": "Eugeny Borisovich Czerniawski", - "author_inst": "Joint Institute for High Temperatures" + "author_name": "Sophie Uyoga", + "author_inst": "KEMRI Wellcome Trust Research Programme" }, { - "author_name": "Alexander Mikhailovich Ignatov", - "author_inst": "Prokhorov General Physics Institute, Russian Academy of Sciences" + "author_name": "John N. Gitonga", + "author_inst": "KEMRI-Wellcome Trust Research Programme" + }, + { + "author_name": "Daisy Mugo", + "author_inst": "KEMRI-Wellcome Trust Research Programme" + }, + { + "author_name": "Mark Otiende", + "author_inst": "KEMRI-Wellcome Trust Research Programme" + }, + { + "author_name": "James Nyagwange", + "author_inst": "KEMRI-Wellcome Trust Research Programme" + }, + { + "author_name": "Henry K. Karanja", + "author_inst": "KEMRI-Wellcome Trust Research Programme" + }, + { + "author_name": "James Tuju", + "author_inst": "KEMRI-Wellcome Trust Research Programme" + }, + { + "author_name": "Perpetual Wanjiku", + "author_inst": "KEMRI-Wellcome Trust Research Programme" + }, + { + "author_name": "Rashid Aman", + "author_inst": "Ministry of Health, Government of Kenya" + }, + { + "author_name": "Mercy Mwangangi", + "author_inst": "Ministry of Health, Government of Kenya" + }, + { + "author_name": "Patrick Amoth", + "author_inst": "Ministry of Health, Government of Kenya" + }, + { + "author_name": "Kadondi Kasera", + "author_inst": "Ministry of Health, Government of Kenya" + }, + { + "author_name": "Wangari Ng'ang'a", + "author_inst": "Presidential Policy & Strategy Unit, The Presidency, Government of Kenya" + }, + { + "author_name": "Charles Rombo", + "author_inst": "Kenya National Blood Transfusion Services, Ministry of Health" + }, + { + "author_name": "Christine Yegon", + "author_inst": "Kenya National Blood Transfusion Services, Ministry of Health" + }, + { + "author_name": "Khamisi Kithi", + "author_inst": "Kenya National Blood Transfusion Services, Ministry of Health" + }, + { + "author_name": "Elizabeth Odhiambo", + "author_inst": "Kenya National Blood Transfusion Services, Ministry of Health" + }, + { + "author_name": "Thomas Rotich", + "author_inst": "Kenya National Blood Transfusion Services, Ministry of Health" + }, + { + "author_name": "Irene Orgut", + "author_inst": "Kenya National Blood Transfusion Services, Ministry of Health" + }, + { + "author_name": "Sammy Kihara", + "author_inst": "Kenya National Blood Transfusion Services, Ministry of Health" + }, + { + "author_name": "Christian Bottomley", + "author_inst": "Department of Infectious Diseases Epidemiology, London School of Hygiene and Tropical Medicine" + }, + { + "author_name": "E Wangeci Kagucia", + "author_inst": "KEMRI-Wellcome Trust Research Programme" + }, + { + "author_name": "Katherine E. Gallagher", + "author_inst": "KEMRI-Wellcome Trust Research Programme" + }, + { + "author_name": "Athony Etyang", + "author_inst": "KEMRI-Wellcome Trust Research Programme" + }, + { + "author_name": "Shirine Voller", + "author_inst": "KEMRI-Wellcome Trust Research Programme" + }, + { + "author_name": "Teresa Lambe", + "author_inst": "Nuffield Department of Medicine, Oxford University" + }, + { + "author_name": "Daniel Wright", + "author_inst": "Jenner Institute, University of Oxford" + }, + { + "author_name": "Edwine Barasa", + "author_inst": "KEMRI-Wellcome Trust Research Programme" + }, + { + "author_name": "Benjamin Tsofa", + "author_inst": "KEMRI-Wellcome Trust Research Programme" + }, + { + "author_name": "Philip Bejon", + "author_inst": "KEMRI-Wellcome Trust Research Programme" + }, + { + "author_name": "Lynette I Ochola-Oyier", + "author_inst": "KEMRI-Wellcome Trust Research Programme" + }, + { + "author_name": "Ambrose Agweyu", + "author_inst": "KEMRI-Wellcome Trust Research Programme" + }, + { + "author_name": "J. Anthony G Scott", + "author_inst": "KEMRI-Wellcome Trust Research Programme" + }, + { + "author_name": "George M Warimwe", + "author_inst": "KEMRI-Wellcome Trust Research Programme" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2021.02.09.21251416", @@ -924928,27 +924780,55 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.02.08.21251359", - "rel_title": "Country specific mutational profile of SARS-CoV-2 in pre- and post-international travel ban: Effect on vaccine efficacy", + "rel_doi": "10.1101/2021.02.08.21251386", + "rel_title": "How much do superspreaders matter? Epidemic dynamics in inhomogeneous populations", "rel_date": "2021-02-11", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.08.21251359", - "rel_abs": "In order to curb the rapid transmission of SARS-CoV-2, nation-wide lockdowns were implemented as a preliminary measure. Since most countries enforced travel-bans during end of March 2020, the country-specific patterns should be discernible in the subsequent months. We identified frequently mutated non-synonymous mutations in 2,15,000 SARS-CoV-2 sequences during pre and post-travel-ban periods in 35 countries. We further investigated the mutational profile on a bi-monthly basis and traced the progress over the time. Several new mutations have emerged post-travel-ban and on the rise in specific countries, chief among them being A222V and S477N in Spike, and A220V in Nucleocapsid protein. Consequently, we examined the Spike protein epitopes to inspect whether any of these country-specific mutations overlapped with these epitopes. Several mutations were found to be contained within one or more epitopes, including the highly mutated residues of Spike protein, advocating the requirement of active monitoring of vaccine efficacies in respective countries.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.08.21251386", + "rel_abs": "A variant of the SIR model for an inhomogeneous population is introduced in order to account for the effect of variability in susceptibility and infectiousness across a population. An initial formulation of this dynamics leads to infinitely many differential equations. Our model, however, can be reduced to a single first-order one-dimensional differential equation. Using this approach, we provide quantitative solutions for different distributions. In particular, we use GPS data from [~] 107 cellphones to determine an empirical distribution of the number of individual contacts and use this to infer a possible distribution of susceptibility and infectivity. We quantify the effect of superspreaders on the early growth rate [R]0 of the infection and on the final epidemic size, the total number of people who are ever infected. We discuss the features of the distribution that contribute most to the dynamics of the infection.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Sayantan Laha", - "author_inst": "Indian Statistical institute" + "author_name": "Kyle Kawagoe", + "author_inst": "University of Chicago" }, { - "author_name": "Raghunath Chatterjee", - "author_inst": "Indian Statistical institute" + "author_name": "Mark Rychnovsky", + "author_inst": "Columbia University" + }, + { + "author_name": "Serina Y Chang", + "author_inst": "Stanford University" + }, + { + "author_name": "Greg Huber", + "author_inst": "Chan Zuckerberg Biohub" + }, + { + "author_name": "Lucy M Li", + "author_inst": "Chan Zuckerberg Biohub" + }, + { + "author_name": "Jonathan Miller", + "author_inst": "Okinawa Institute of Science and Technology" + }, + { + "author_name": "Reuven Pnini", + "author_inst": "Okinawa Institute of Science and Technology" + }, + { + "author_name": "Boris Veytsman", + "author_inst": "Chan Zuckerberg Initiative" + }, + { + "author_name": "David Yllanes", + "author_inst": "Chan Zuckerberg Biohub" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2021.02.08.21250899", @@ -926930,133 +926810,193 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2021.02.10.430499", - "rel_title": "Bifurcated monocyte states are predictive of mortality in severe COVID-19", - "rel_date": "2021-02-10", + "rel_doi": "10.1101/2021.02.08.430146", + "rel_title": "SARS-CoV-2 RBD-Tetanus toxoid conjugate vaccine induces a strong neutralizing immunity in preclinical studies", + "rel_date": "2021-02-09", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.02.10.430499", - "rel_abs": "Coronavirus disease 2019 (COVID-19) caused by SARS-CoV-2 infection presents with varied clinical manifestations1, ranging from mild symptoms to acute respiratory distress syndrome (ARDS) with high mortality2,3. Despite extensive analyses, there remains an urgent need to delineate immune cell states that contribute to mortality in severe COVID-19. We performed high-dimensional cellular and molecular profiling of blood and respiratory samples from critically ill COVID-19 patients to define immune cell genomic states that are predictive of outcome in severe COVID-19 disease. Critically ill patients admitted to the intensive care unit (ICU) manifested increased frequencies of inflammatory monocytes and plasmablasts that were also associated with ARDS not due to COVID-19. Single-cell RNAseq (scRNAseq)-based deconvolution of genomic states of peripheral immune cells revealed distinct gene modules that were associated with COVID-19 outcome. Notably, monocytes exhibited bifurcated genomic states, with expression of a cytokine gene module exemplified by CCL4 (MIP-1{beta}) associated with survival and an interferon signaling module associated with death. These gene modules were correlated with higher levels of MIP-1{beta} and CXCL10 levels in plasma, respectively. Monocytes expressing genes reflective of these divergent modules were also detectable in endotracheal aspirates. Machine learning algorithms identified the distinctive monocyte modules as part of a multivariate peripheral immune system state that was predictive of COVID-19 mortality. Follow-up analysis of the monocyte modules on ICU day 5 was consistent with bifurcated states that correlated with distinct inflammatory cytokines. Our data suggests a pivotal role for monocytes and their specific inflammatory genomic states in contributing to mortality in life-threatening COVID-19 disease and may facilitate discovery of new diagnostics and therapeutics.", - "rel_num_authors": 29, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.02.08.430146", + "rel_abs": "Controlling the global COVID-19 pandemic depends, among other measures, on developing preventive vaccines at an unprecedented pace. Vaccines approved for use and those in development intend to use neutralizing antibodies to block viral sites binding to the hosts cellular receptors. Virus infection is mediated by the spike glycoprotein trimer on the virion surface via its receptor binding domain (RBD). Antibody response to this domain is an important outcome of the immunization and correlates well with viral neutralization. Here we show that macromolecular constructs with recombinant RBD conjugated to tetanus toxoid induce a potent immune response in laboratory animals. Some advantages of the immunization with the viral antigen coupled to tetanus toxoid have become evident such as predominant IgG immune response due to affinity maturation and long-term specific B-memory cells. This paper demonstrates that subunit conjugate vaccines can be an alternative for COVID-19, paving the way for other viral conjugate vaccines based on the use of small viral proteins involved in the infection process.", + "rel_num_authors": 44, "rel_authors": [ { - "author_name": "Anthony R Cillo", - "author_inst": "University of Pittsburgh" + "author_name": "Yury Valdes-Balbin", + "author_inst": "Finlay Vaccine Institute, 200 and 21 Street, Havana 11600, Cuba" }, { - "author_name": "Ashwin Somasundaram", - "author_inst": "University of Pittsburgh" + "author_name": "Darielys Santana-Mederos", + "author_inst": "Finlay Vaccine Institute, 200 and 21 Street, Havana 11600, Cuba" }, { - "author_name": "Feng Shan", - "author_inst": "University of Pittsburgh" + "author_name": "Lauren Quintero", + "author_inst": "Finlay Vaccine Institute, 200 and 21 Street, Havana 11600, Cuba" }, { - "author_name": "Carly Cardello", - "author_inst": "University of Pittsburgh" + "author_name": "Sonsire Fernandez", + "author_inst": "Finlay Vaccine Institute, 200 and 21 Street, Havana 11600, Cuba" }, { - "author_name": "Creg J Workman", - "author_inst": "University of Pittsburgh" + "author_name": "Laura Rodriguez", + "author_inst": "Finlay Vaccine Institute, 200 and 21 Street, Havana 11600, Cuba" }, { - "author_name": "Georgios D Kitsios", - "author_inst": "University of Pittsburgh" + "author_name": "Belinda Sanchez-Ramirez", + "author_inst": "Center of Molecular Immunology, P.O. Box 16040, 216 St. Havana, Cuba" }, { - "author_name": "Ayana Ruffin", - "author_inst": "University of Pittsburgh" + "author_name": "Rocmira Perez", + "author_inst": "Finlay Vaccine Institute, 200 and 21 Street, Havana 11600, Cuba" }, { - "author_name": "Sheryl Kunning", - "author_inst": "University of Pittsburgh" + "author_name": "Claudia Acosta", + "author_inst": "Finlay Vaccine Institute, 200 and 21 Street, Havana 11600, Cuba" }, { - "author_name": "Caleb Lampenfeld", - "author_inst": "University of Pittsburgh" + "author_name": "Yanira Mendez", + "author_inst": "Laboratory of Synthetic and Biomolecular Chemistry, Faculty of Chemistry, University of Havana, Cuba" }, { - "author_name": "Sayali Onkar", - "author_inst": "University of Pittsburgh" + "author_name": "Manuel G Ricardo", + "author_inst": "Laboratory of Synthetic and Biomolecular Chemistry, Faculty of Chemistry, University of Havana, Cuba" }, { - "author_name": "Stephanie Grebinowski", - "author_inst": "University of Pittsburgh" + "author_name": "Tays Hernandez", + "author_inst": "Center of Molecular Immunology, P.O. Box 16040, 216 St. Havana, Cuba" }, { - "author_name": "Gaurav Deshmukh", - "author_inst": "Meso Scale Discovery" + "author_name": "Gretchen Bergado", + "author_inst": "Center of Molecular Immunology, P.O. Box 16040, 216 St. Havana, Cuba" }, { - "author_name": "Barbara Methe", - "author_inst": "University of Pittsburgh" + "author_name": "Franciscary Pi", + "author_inst": "Center of Molecular Immunology, P.O. Box 16040, 216 St. Havana, Cuba" }, { - "author_name": "Chang Liu", - "author_inst": "University of Pittsburgh" + "author_name": "Annet Valdes", + "author_inst": "Center of Molecular Immunology, P.O. Box 16040, 216 St. Havana, Cuba" }, { - "author_name": "Sham Nambulli", - "author_inst": "University of Pittsburgh" + "author_name": "Tania Carmenate", + "author_inst": "Center of Molecular Immunology, P.O. Box 16040, 216 St. Havana, Cuba" }, { - "author_name": "Lawrence Andrews", - "author_inst": "University of Pittsburgh" + "author_name": "Ubel Ramirez", + "author_inst": "Finlay Vaccine Institute, 200 and 21 Street, Havana 11600, Cuba." }, { - "author_name": "W. Paul Duprex", - "author_inst": "University of Pittsburgh" + "author_name": "Reynaldo Oliva", + "author_inst": "Finlay Vaccine Institute, 200 and 21 Street, Havana 11600, Cuba." }, { - "author_name": "Alok J Joglekar", - "author_inst": "University of Pittsburgh" + "author_name": "Jean-Pierre Soubal", + "author_inst": "Finlay Vaccine Institute, 200 and 21 Street, Havana 11600, Cuba." }, { - "author_name": "Panayiotis V Benos", - "author_inst": "University of Pittsburgh" + "author_name": "Raine Garrido", + "author_inst": "Finlay Vaccine Institute, 200 and 21 Street, Havana 11600, Cuba." }, { - "author_name": "Prabir Ray", - "author_inst": "University of Pittsburgh" + "author_name": "Felix Cardoso", + "author_inst": "Finlay Vaccine Institute, 200 and 21 Street, Havana 11600, Cuba." }, { - "author_name": "Anuradha Ray", - "author_inst": "University of Pittsburgh" + "author_name": "Mario Landys", + "author_inst": "Finlay Vaccine Institute, 200 and 21 Street, Havana 11600, Cuba." }, { - "author_name": "Bryan J McVerry", - "author_inst": "University of Pittsburgh" + "author_name": "Mildrey Farinas", + "author_inst": "Finlay Vaccine Institute, 200 and 21 Street, Havana 11600, Cuba" }, { - "author_name": "Yingze Zhang", - "author_inst": "University of Pittsburgh" + "author_name": "Humberto Gonzalez", + "author_inst": "Finlay Vaccine Institute, 200 and 21 Street, Havana 11600, Cuba" }, { - "author_name": "Janet S Lee", - "author_inst": "University of Pittsburgh" + "author_name": "Juliet Enriquez", + "author_inst": "Civil Defense National Research Laboratory, Cuba" }, { - "author_name": "Jishnu Das", - "author_inst": "University of Pittsburgh" + "author_name": "Enrique Noa", + "author_inst": "Civil Defense National Research Laboratory, Cuba" }, { - "author_name": "Harinder Singh", - "author_inst": "University of Pittsburgh" + "author_name": "Anamary Suarez", + "author_inst": "Civil Defense National Research Laboratory, Cuba" }, { - "author_name": "Alison Morris", - "author_inst": "University of Pittsburgh" + "author_name": "Cheng Fang", + "author_inst": "Shanghai Fenglin Glycodrug Promotion Center, Shanghai 200032, China" }, { - "author_name": "Tullia C Bruno", - "author_inst": "University of Pittsburgh" + "author_name": "Luis A Espinosa", + "author_inst": "Center for Genetic Engineering and Biotechnology, Ave 31 e/ 158 y 190, Playa, Havana, Cuba" }, { - "author_name": "Dario AA Vignali", - "author_inst": "University of Pittsburgh" + "author_name": "Yassel Ramos", + "author_inst": "Center for Genetic Engineering and Biotechnology, Ave 31 e/ 158 y 190, Playa, Havana, Cuba" + }, + { + "author_name": "Luis Javier Gonzalez", + "author_inst": "Center for Genetic Engineering and Biotechnology, Ave 31 e/ 158 y 190, Playa, Havana, Cuba" + }, + { + "author_name": "Yanet Climent", + "author_inst": "Finlay Vaccine Institute, 200 and 21 Street, Havana 11600, Cuba." + }, + { + "author_name": "Gertrudis Rojas", + "author_inst": "Center of Molecular Immunology, P.O. Box 16040, 216 St. Havana, Cuba" + }, + { + "author_name": "Ernesto Relova-Hernandez", + "author_inst": "Center of Molecular Immunology, P.O. Box 16040, 216 St. Havana, Cuba" + }, + { + "author_name": "Yanelys Cabrera-Infante", + "author_inst": "Center of Molecular Immunology, P.O. Box 16040, 216 St. Havana, Cuba" + }, + { + "author_name": "Sum Lai Losada", + "author_inst": "Center of Molecular Immunology, P.O. Box 16040, 216 St. Havana, Cuba" + }, + { + "author_name": "Tammy Boggiano", + "author_inst": "Center of Molecular Immunology, P.O. Box 16040, 216 St. Havana, Cuba" + }, + { + "author_name": "Eduardo Ojito", + "author_inst": "Center of Molecular Immunology, P.O. Box 16040, 216 St. Havana, Cuba" + }, + { + "author_name": "Kalet Leon-Monzon", + "author_inst": "Center of Molecular Immunology, P.O. Box 16040, 216 St. Havana, Cuba" + }, + { + "author_name": "Fabrizio Chiodo", + "author_inst": "Finlay Vaccine Institute, 200 and 21 Street, Havana 11600, Cuba" + }, + { + "author_name": "Francoise Paquet", + "author_inst": "Centre de Biophysique Moleculaire, Centre National de la Recherche Scientifique UPR 4301, rue Charles Sadron, F-45071, Orleans, Cedex 2, France" + }, + { + "author_name": "Guangwu Chen", + "author_inst": "Chengdu Olisynn Biotech. Co. Ltd., and State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, Chengdu 610041, China." + }, + { + "author_name": "Daniel G Rivera", + "author_inst": "Laboratory of Synthetic and Biomolecular Chemistry, Faculty of Chemistry, University of Havana, Cuba" + }, + { + "author_name": "Dagmar Garcia-Rivera", + "author_inst": "Finlay Vaccine Institute, 200 and 21 Street, Havana 11600, Cuba" + }, + { + "author_name": "Vicente Verez-Bencomo", + "author_inst": "FinlayVaccine Institute" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "new results", "category": "immunology" }, @@ -928512,49 +928452,81 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2021.02.04.21251127", - "rel_title": "SARS-CoV-2 Transmission Risk from sports Equipment (STRIKE)", + "rel_doi": "10.1101/2021.02.03.21250823", + "rel_title": "Implementation of an in-house real-time reverse transcription-PCR assay for the rapid detection of the SARS-CoV-2 Marseille-4 variant", "rel_date": "2021-02-08", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.04.21251127", - "rel_abs": "OBJECTIVESTo investigate the potential of shared sporting equipment as transmission vectors of SARS-CoV-2 during the reintroduction of sports such as soccer, rugby, cricket, tennis, golf and gymnastics.\n\nSETTINGLaboratory based live SARS-CoV-2 virus study\n\nINTERVENTIONSTen different types of sporting equipment were inoculated with 40l droplets containing clinically relevant high and low concentrations of live SARS-CoV-2 virus. Materials were then swabbed at time points relevant to sports (1, 5, 15, 30, 90 minutes). The amount of live SARS-CoV-2 recovered at each time point was enumerated using viral plaque assays, and viral decay and half-life was estimated through fitting linear models to log transformed data from each material.\n\nMAIN OUTCOME MEASUREThe primary outcome measure was quantification of retrievable SARS-CoV-2 virus from each piece of equipment at pre-determined time points.\n\nRESULTSAt one minute, SARS-CoV-2 virus was recovered in only seven of the ten types of equipment with the low dose inoculum, one at five minutes and none at 15 minutes. Retrievable virus dropped significantly for all materials tested using the high dose inoculum with mean recovery of virus falling to 0.74% at 1 minute, 0.39% at 15 minutes and 0.003% at 90 minutes. Viral recovery, predicted decay, and half-life varied between materials with porous surfaces limiting virus transmission.\n\nCONCLUSIONSThis study shows that there is an exponential reduction in SARS-CoV-2 recoverable from a range of sports equipment after a short time period, and virus is less transferrable from materials such as a tennis ball, red cricket ball and cricket glove. Given this rapid loss of viral load and the fact that transmission requires a significant inoculum to be transferred from equipment to the mucous membranes of another individual it seems unlikely that sports equipment is a major cause for transmission of SARS-CoV-2. These findings have important policy implications in the context of the pandemic and may promote other infection control measures in sports to reduce the risk of SARS-CoV-2 transmission and urge sports equipment manufacturers to identify surfaces that may or may not be likely to retain transferable virus.\n\nO_TEXTBOXWHAT IS ALREADY KNOWN ON THIS TOPICO_LITransmission of SARS-CoV-2 between individuals playing sport may be via respiratory droplets when in close proximity to an infected person.\nC_LIO_LISARS-CoV-2 remains viable on a variety of surfaces resulting in recommendations to reduce the sharing of sports equipment such as tennis balls when sports were re-opened.\nC_LI\n\nWHAT THIS STUDY ADDSO_LIThe recoverable SARS-CoV-2 viral load reduces exponentially with mean viral load of all materials less than 1% of the original inoculum after 1 minute.\nC_LIO_LIThe type of material has a significant effect on SARS-CoV-2 transfer, with less virus transferred from porous materials such as bovine leather or nylon woven cloth.\nC_LIO_LIPolicies on infection control measures in sport may be better directed towards areas other than reducing the sharing of sports equipment.\nC_LIO_LISports equipment manufacturers may consider using materials that absorb or retain virus as a way of reducing viral transmission from sports equipment.\nC_LI\n\nC_TEXTBOX", - "rel_num_authors": 9, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.03.21250823", + "rel_abs": "IntroductionThe SARS-CoV-2 pandemic has been associated with the occurrence since summer 2020 of several viral variants that overlapped or succeeded each other in time. Those of current concern harbor mutations within the spike receptor binding domain (RBD) that may be associated with viral escape to immune responses. In our geographical area a viral variant we named Marseille-4 harbors a S477N substitution in this RBD.\n\nMaterials and methodsWe aimed to implement an in-house one-step real-time reverse transcription-PCR (qPCR) assay with a hydrolysis probe that specifically detects the SARS-CoV-2 Marseille-4 variant.\n\nResultsAll 6 cDNA samples from Marseille-4 variant strains identified in our institute by genome next-generation sequencing (NGS) tested positive using our Marseille-4 specific qPCR, whereas all 32 cDNA samples from other variants tested negative. In addition, 39/42 (93%) respiratory samples identified by NGS as containing a Marseille-4 variant strain and 0/26 samples identified as containing non-Marseille-4 variant strains were positive. Finally, 1,585/2,889 patients SARS-CoV-2-diagnosed in our institute, 10/277 (3.6%) respiratory samples collected in Algeria, and none of 207 respiratory samples collected in Senegal, Morocco, or Lebanon tested positive using our Marseille-4 specific qPCR.\n\nDiscussionOur in-house qPCR system was found reliable to detect specifically the Marseille-4 variant and allowed estimating it is involved in more than half of our SARS-CoV-2 diagnoses since December 2020. Such approach allows the real-time surveillance of SARS-CoV-2 variants, which is warranted to monitor and assess their epidemiological and clinical characterics based on comprehensive sets of data.", + "rel_num_authors": 17, "rel_authors": [ { - "author_name": "Thomas Edwards", - "author_inst": "Department of Tropical Disease Biology, Liverpool School of Tropical Medicine, Pembroke Place, Liverpool, L3 5QA" + "author_name": "Marielle Bedotto", + "author_inst": "IHU Mediterranee Infection" }, { - "author_name": "Grant A Kay", - "author_inst": "Department of Tropical Disease Biology, Liverpool School of Tropical Medicine, Pembroke Place, Liverpool, L3 5QA" + "author_name": "Pierre-Edouard Fournier", + "author_inst": "IHU Mediterranee Infection" }, { - "author_name": "Ghaith Aljayyoussi", - "author_inst": "Department of Tropical Disease Biology, Liverpool School of Tropical Medicine, Pembroke Place, Liverpool, L3 5QA" + "author_name": "Linda Houhamdi", + "author_inst": "IHU Mediterranee Infection" }, { - "author_name": "Sophie I Owen", - "author_inst": "Department of Tropical Disease Biology, Liverpool School of Tropical Medicine, Pembroke Place, Liverpool, L3 5QA" + "author_name": "Anthony LEVASSEUR", + "author_inst": "Aix-Marseille University" }, { - "author_name": "Andy R Harland", - "author_inst": "Wolfson School of Mechanical, Manufacturing and Electrical Engineering, Loughborough University, Ashby Road, Loughborough, LE11 3TU" + "author_name": "Jeremy Delerce", + "author_inst": "IHU Mediterranee Infection" }, { - "author_name": "Nicholas S Pierce", - "author_inst": "England and Wales Cricket Board and National Centre for Sport and Exercise Medicine, Loughborough University, LE11 3TU" + "author_name": "Lucine Pinault", + "author_inst": "IHU Mediterranee Infection" }, { - "author_name": "James D F Calder", - "author_inst": "Department of Bioengineering, Imperial College London, London, SW7 2AZ" + "author_name": "Abdou Padane", + "author_inst": "Institut de Recherche en Sante, de Surveillance Epidemiologique et de Formations (IRESSEF)" }, { - "author_name": "Tom Fletcher", - "author_inst": "Department of Clinical Sciences, Liverpool School of Tropical Medicine, Pembroke Place, Liverpool, L3 5QA" + "author_name": "Amanda CHAMIEH", + "author_inst": "Saint George Hospital University Medical Center, University of Balamand, Beirut" }, { - "author_name": "Emily R Adams", - "author_inst": "Department of Tropical Disease Biology, Liverpool School of Tropical Medicine, Pembroke Place, Liverpool, L3 5QA" + "author_name": "Herve TISSOT-DUPONT", + "author_inst": "IHU Mediterranee Infection" + }, + { + "author_name": "Philippe BROUQUI", + "author_inst": "IHU Mediterranee Infection" + }, + { + "author_name": "Cheikh Sokhna", + "author_inst": "Vecteurs - Infections Tropicales et Mediterraneennes (VITROME), Campus International IRD-UCAD de l IRD" + }, + { + "author_name": "Eid Azar", + "author_inst": "Saint George Hospital University Medical Center" + }, + { + "author_name": "Rachid Saile", + "author_inst": "Hassan II University of Casablanca" + }, + { + "author_name": "Souleymane Mboup", + "author_inst": "Institut de Recherche en Sante, de Surveillance Epidemiologique et de Formations (IRESSEF)" + }, + { + "author_name": "Idir Bitam", + "author_inst": "Ecole superieure en sciences de l aliment et des industries agro-alimentaires, Alger" + }, + { + "author_name": "Philippe Colson", + "author_inst": "Aix-Marseille university" + }, + { + "author_name": "Didier Raoult", + "author_inst": "Aix Marseille Universite IHU Mediterranee Infection" } ], "version": "1", @@ -930074,29 +930046,77 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.02.05.21250572", - "rel_title": "Modeling the Effect of Population-Wide Vaccination on the Evolution of COVID-19 Epidemic in Canada", + "rel_doi": "10.1101/2021.02.05.21250127", + "rel_title": "Engagement with COVID-19 Public Health Measures in the United States: A Cross-Sectional Social Media Analysis from June to November 2020", "rel_date": "2021-02-08", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.05.21250572", - "rel_abs": "Population-wide vaccination is critical for containing the COVID-19 pandemic when combined with effective testing and prevention measures. Since the beginning of the COVID-19 outbreak, several companies worked tirelessly for the development of an efficient vaccine that would put an end to this pandemic. Today, a number of COVID-19 vaccines have been approved for use by a number of national regulatory organizations. Vaccination campaigns have already started in several countries with different daily-vaccination rates depending on the countrys vaccination capacity. Therefore, we find it timely and extremely important to conduct a study on the effect of population-wide vaccination campaigns on the evolution of the COVID-19 epidemic. To this end, we propose a new deterministic mathematical model to forecast the COVID-19 epidemic evolution under the effect of vaccination and vaccine efficacy. This model, referred to as SIRV, consists of a compartmental SIR (susceptible, infectious and removed) model augmented with an additional state V representing the effectively vaccinated population as well as two inputs representing the daily-vaccination rate and the vaccine efficacy. Using our SIRV model, we predict the evolution of the COVID-19 epidemic in Canada and its most affected provinces (Ontario, Quebec, British Columbia, Alberta, Saskatchewan, and Manitoba), for different daily vaccination rates and vaccine efficacy. Projections suggest that, without vaccination, 219, 000 lives could be lost across Canada by the end of 2021 due to COVID-19. The ongoing vaccination campaign across Canada seems to unfold relatively slowly at an average daily rate close to 1/2 vaccine per 1, 000 population. At this pace, we could be saving more than 77, 496 lives by the end of the year. Doubling the current vaccination efforts (1 vaccine per day per 1, 000 population) could be sufficient to save 125, 839 lives in Canada during the current year 2021. We would like to point out that our study assumes that the vaccine is perfectly safe without any short or long term side-effects. This study has been conducted independently at arms length from vaccine manufacturers, using the available data from Canada health services. This study can be easily adapted to other places in the world.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.05.21250127", + "rel_abs": "BackgroundThe coronavirus disease 2019 (COVID-19) has continued to spread in the US and globally. Closely monitoring public engagement and perception of COVID-19 and preventive measures using social media data could provide important information for understanding the progress of current interventions and planning future programs.\n\nObjectiveTo measure the publics behaviors and perceptions regarding COVID-19 and its daily life effects during the recent 5 months of the pandemic.\n\nMethodsNatural language processing (NLP) algorithms were used to identify COVID-19 related and unrelated topics in over 300 million online data sources from June 15 to November 15, 2020. Posts in the sample were geotagged, and sensitivity and specificity were both calculated to validate the classification of posts. The prevalence of discussion regarding these topics was measured over this time period and compared to daily case rates in the US.\n\nResultsThe final sample size included 9,065,733 posts, 70% of which were sourced from the US. In October and November, discussion including mentions of COVID-19 and related health behaviors did not increase as it had from June to September, despite an increase in COVID-19 daily cases in the US beginning in October. Additionally, counter to reports from March and April, discussion was more focused on daily life topics (69%), compared with COVID-19 in general (37%) and COVID-19 public health measures (20%).\n\nConclusionsThere was a decline in COVID-19-related social media discussion sourced mainly from the US, even as COVID-19 cases in the US have increased to the highest rate since the beginning of the pandemic. Targeted public health messaging may be needed to ensure engagement in public health prevention measures until a vaccine is widely available to the public.", + "rel_num_authors": 15, "rel_authors": [ { - "author_name": "Soulaimane Berkane", - "author_inst": "University of Quebec in Outaouais" + "author_name": "Daisy Massey", + "author_inst": "Yale School of Medicine" }, { - "author_name": "Intissar Harizi", - "author_inst": "Ottawa" + "author_name": "Yuan Lu", + "author_inst": "Yale School of Medicine, New Haven, Connecticut" }, { - "author_name": "Abdelhamid Tayebi", - "author_inst": "Lakehead University" + "author_name": "Chenxi Huang", + "author_inst": "Yale School of Medicine, New Haven, Connecticut" + }, + { + "author_name": "Alina Cohen", + "author_inst": "Signals Analytics" + }, + { + "author_name": "Yahel Oren", + "author_inst": "Signals Analytics" + }, + { + "author_name": "Tali Moed", + "author_inst": "Signals Analytics" + }, + { + "author_name": "Pini Matzner", + "author_inst": "Signals Analytics" + }, + { + "author_name": "Shiwani Mahajan", + "author_inst": "Yale School of Medicine" + }, + { + "author_name": "Cesar Caraballo", + "author_inst": "Yale School of Medicine" + }, + { + "author_name": "Navin Kumar", + "author_inst": "Yale University, Department of Sociology" + }, + { + "author_name": "Yuchen Xue", + "author_inst": "Foundation for a Smoke-Free World" + }, + { + "author_name": "Qinglan Ding", + "author_inst": "College of Health and Human Sciences, Purdue University, West Lafayette, Indiana" + }, + { + "author_name": "Rachel P Dreyer", + "author_inst": "Yale University" + }, + { + "author_name": "Brita Roy", + "author_inst": "Yale School of Medicine" + }, + { + "author_name": "Harlan Krumholz", + "author_inst": "Yale University" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "public and global health" }, @@ -932332,83 +932352,31 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2021.02.05.429959", - "rel_title": "Targeting CTP Synthetase 1 to Restore Interferon Induction and Impede Nucleotide Synthesis in SARS-CoV-2 Infection", + "rel_doi": "10.1101/2021.02.06.430094", + "rel_title": "The local topological free energy of the SARS-CoV-2 Spike protein", "rel_date": "2021-02-07", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.02.05.429959", - "rel_abs": "The newly emerged SARS-CoV-2 caused a global pandemic with astonishing mortality and morbidity. The mechanisms underpinning its highly infectious nature remain poorly understood. We report here that SARS-CoV-2 exploits cellular CTP synthetase 1 (CTPS1) to promote CTP synthesis and suppress interferon (IFN) induction. Screening a SARS-CoV-2 expression library identified ORF7b and ORF8 that suppressed IFN induction via inducing the deamidation of interferon regulatory factor 3 (IRF3). Deamidated IRF3 fails to bind the promoters of classic IRF3-responsible genes, thus muting IFN induction. Conversely, a shRNA-mediated screen focused on cellular glutamine amidotransferases corroborated that CTPS1 deamidates IRF3 to inhibit IFN induction. Functionally, ORF7b and ORF8 activate CTPS1 to promote de novo CTP synthesis while shutting down IFN induction. De novo synthesis of small-molecule inhibitors of CTPS1 enabled CTP depletion and IFN induction in SARS-CoV-2 infection, thus impeding SARS-CoV-2 replication. Our work uncovers a strategy that a viral pathogen couples immune evasion to metabolic activation to fuel viral replication. Inhibition of the cellular CTPS1 offers an attractive means for developing antiviral therapy that would be resistant to SARS-CoV-2 mutation.", - "rel_num_authors": 16, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.02.06.430094", + "rel_abs": "The novel coronavirus SARS-CoV-2 infects human cells using a mechanism that involves binding and structural rearrangement of its spike protein. Understanding protein rearrangement and identifying specific residues where mutations affect protein rearrangement has attracted a lot of attention for drug development. We use a mathematical method introduced in [9] to associate a local topological/geometrical free energy along the SARS-CoV-2 spike protein backbone. Our results show that the total local topological free energy of the SARS-CoV-2 spike protein monotonically decreases from pre-to post-fusion and that its distribution along the protein domains is related to their activity in protein rearrangement. By using density functional theory (DFT) calculations with inclusion of solvent effects, we show that high local topological free energy conformations are unstable compared to those of low topological free energy. By comparing to experimental data, we find that the high local topological free energy conformations in the spike protein are associated with mutations which have the largest experimentally observed effect to protein rearrangement.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Youliang Rao", - "author_inst": "University of Southern California" - }, - { - "author_name": "Ting-Yu Wang", - "author_inst": "University of Southern California" - }, - { - "author_name": "Chao Qin", - "author_inst": "University of Southern California" - }, - { - "author_name": "Bianca Espinosa", - "author_inst": "University of Southern California" - }, - { - "author_name": "Qizhi Liu", - "author_inst": "University of Southern California" - }, - { - "author_name": "Arunika Ekanayake", - "author_inst": "University of Southern California" - }, - { - "author_name": "Jun Zhao", - "author_inst": "University of Southern California" - }, - { - "author_name": "Ali Can Savas", - "author_inst": "University of Southern California" - }, - { - "author_name": "Shu Zhang", - "author_inst": "University of Southern California" - }, - { - "author_name": "Mehrnaz Zarinfar", - "author_inst": "University of Southern California" - }, - { - "author_name": "Yongzhen Liu", - "author_inst": "University of Southern California" - }, - { - "author_name": "Wenjie Zhu", - "author_inst": "Chinese Academy of Medical Sciences & Peking Union Medical College" - }, - { - "author_name": "Nicholas Alexander Graham", - "author_inst": "University of Southern California" + "author_name": "Quenisha Baldwin", + "author_inst": "Tuskegee University" }, { - "author_name": "Taijiao Jiang", - "author_inst": "Suzhou Institute of Systems Medicine" - }, - { - "author_name": "Chao Zhang", - "author_inst": "University of Southern California" + "author_name": "Bobby G Sumpter", + "author_inst": "Oak Ridge National Laboratory" }, { - "author_name": "Pinghui Feng", - "author_inst": "university of Southern California" + "author_name": "Eleni Panagiotou", + "author_inst": "University of Tennessee at Chattanooga" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nd", "type": "new results", - "category": "microbiology" + "category": "bioinformatics" }, { "rel_doi": "10.1101/2021.02.06.430088", @@ -934202,77 +934170,81 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.02.02.21250799", - "rel_title": "Infection and mRNA-1273 vaccine antibodies neutralize SARS-CoV-2 UK variant", + "rel_doi": "10.1101/2021.02.02.21250988", + "rel_title": "SARS-CoV-2 specific T cell responses are lower in children and increase with age and time after infection", "rel_date": "2021-02-05", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.02.21250799", - "rel_abs": "Antibody responses against the SARS-CoV-2 Spike protein correlate with protection against COVID-19. Serum neutralizing antibodies appear early after symptom onset following SARS-CoV-2 infection and can last for several months. Similarly, the messenger RNA vaccine, mRNA-1273, generates serum neutralizing antibodies that are detected through at least day 119. However, the recent emergence of the B.1.1.7 variant has raised significant concerns about the breadth of these neutralizing antibody responses. In this study, we used a live virus neutralization assay to compare the neutralization potency of sera from infected and vaccinated individuals against a panel of SARS-CoV-2 variants, including SARS-CoV-2 B.1.1.7. We found that both infection- and vaccine-induced antibodies were effective at neutralizing the SARS-CoV-2 B.1.1.7 variant. These findings support the notion that in the context of the UK variant, vaccine-induced immunity can provide protection against COVID-19. As additional SARS-CoV-2 viral variants continue to emerge, it is crucial to monitor their impact on neutralizing antibody responses following infection and vaccination.", - "rel_num_authors": 15, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.02.21250988", + "rel_abs": "SARS-CoV-2 infection of children leads to a mild illness and the immunological differences with adults remains unclear. We quantified the SARS-CoV-2 specific T cell responses in adults and children (<13 years of age) with RT-PCR confirmed asymptomatic and symptomatic infection for long-term memory, phenotype and polyfunctional cytokines. Acute and memory CD4+ T cell responses to structural SARS-CoV-2 proteins significantly increased with age, whilst CD8+ T cell responses increased with time post infection. Infected children had significantly lower CD4+ and CD8+ T cell responses to SARS-CoV-2 structural and ORF1ab proteins compared to infected adults. SARS-CoV-2-specific CD8+ T cell responses were comparable in magnitude to uninfected negative adult controls. In infected adults CD4+ T cell specificity was skewed towards structural peptides, whilst children had increased contribution of ORF1ab responses. This may reflect differing T cell compartmentalisation for antigen processing during antigen exposure or lower recruitment of memory populations. T cell polyfunctional cytokine production was comparable between children and adults, but children had a lower proportion of SARS-CoV-2 CD4+ T cell effector memory. Compared to adults, children had significantly lower levels of antibodies to {beta}-coronaviruses, indicating differing baseline immunity. Total T follicular helper responses was increased in children during acute infection indicating rapid co-ordination of the T and B cell responses. However total monocyte responses were reduced in children which may be reflective of differing levels of inflammation between children and adults. Therefore, reduced prior {beta}-coronavirus immunity and reduced activation and recruitment of de novo responses in children may drive milder COVID-19 pathogenesis.", + "rel_num_authors": 16, "rel_authors": [ { - "author_name": "Venkata Viswanadh Edara", - "author_inst": "Emory University School of Medicine" + "author_name": "Carolyn A Cohen", + "author_inst": "HKU-Pasteur Research Pole, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China." }, { - "author_name": "Katharine Floyd", - "author_inst": "Emory University School of Medicine" + "author_name": "Athena PY Li", + "author_inst": "HKU-Pasteur Research Pole, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China." }, { - "author_name": "Lilin Lai", - "author_inst": "Emory University School of Medicine" + "author_name": "Asmaa Hachim", + "author_inst": "HKU-Pasteur Research Pole, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China." }, { - "author_name": "Meredith Gardner", - "author_inst": "Emory University School of Medicine" + "author_name": "David SC Hui", + "author_inst": "Department of Medicine and Therapeutics, Prince of Wales Hospital, Chinese University of Hong Kong, Hong Kong SAR, China." }, { - "author_name": "William Hudson", - "author_inst": "Emory University School of Medicine" + "author_name": "Mike YW Kwan", + "author_inst": "Department of Paediatric and Adolescent Medicine, Hong Kong Hospital Authority Infectious Disease Center, Princess Margaret Hospital, Special Administrative Reg" }, { - "author_name": "Anne Piantadosi", - "author_inst": "Emory University School of Medicine" + "author_name": "Owen TY Tsang", + "author_inst": "Infectious Diseases Centre, Princess Margaret Hospital, Hospital Authority of Hong Kong, Special Administrative Region of Hong Kong, China." }, { - "author_name": "Jesse Waggoner", - "author_inst": "Emory University School of Medicine" + "author_name": "Susan S Chiu", + "author_inst": "Department of Paediatric and Adolescent Medicine, The University of Hong Kong and Queen Mary Hospital, Hospital Authority of Hong Kong, Special Administrative R" }, { - "author_name": "Ahmed Babiker", - "author_inst": "Emory University" + "author_name": "Wai Hung Chan", + "author_inst": "Department of Paediatrics, Queen Elizabeth Hospital, Hospital Authority of Hong Kong, Special Administrative Region of Hong Kong, China." }, { - "author_name": "Rafi Ahmed", - "author_inst": "Emory University School of Medicine" + "author_name": "Yat Sun Yau", + "author_inst": "Department of Paediatrics, Queen Elizabeth Hospital, Hospital Authority of Hong Kong, Special Administrative Region of Hong Kong, China." }, { - "author_name": "Xuping Xie", - "author_inst": "Emory University School of Medcine" + "author_name": "Niloufar Kavian", + "author_inst": "HKU-Pasteur Research Pole, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China." }, { - "author_name": "Kumari Lokugamage", - "author_inst": "University of Texas Medical Branch" + "author_name": "Fionn NL Ma", + "author_inst": "HKU-Pasteur Research Pole, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China." }, { - "author_name": "Vineet Menachery", - "author_inst": "University of Texas Medical Branch" + "author_name": "Eric HY Lau", + "author_inst": "WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong," }, { - "author_name": "Pei-Yong Shi", - "author_inst": "University of Texas Medical Branch" + "author_name": "Samuel MS Cheng", + "author_inst": "Division of Public Health Laboratory Sciences, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China." }, { - "author_name": "- COVID-19 Neutralization Study Group", - "author_inst": "" + "author_name": "Leo LM Poon", + "author_inst": "Division of Public Health Laboratory Sciences, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China." }, { - "author_name": "Mehul S Suthar", - "author_inst": "Emory University" + "author_name": "Malik JS Peiris", + "author_inst": "Division of Public Health Laboratory Sciences, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China." + }, + { + "author_name": "Sophie A Valkenburg", + "author_inst": "HKU-Pasteur Research Pole, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China." } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -937000,39 +936972,55 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2021.02.02.429486", - "rel_title": "The mutation profile of SARS-CoV-2 is primarily shaped by the host antiviral defense", + "rel_doi": "10.1101/2021.02.03.429670", + "rel_title": "The SARS-CoV-2 transcriptome and the dynamics of the S gene furin cleavage site in primary human airway epithelia", "rel_date": "2021-02-04", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.02.02.429486", - "rel_abs": "Understanding SARS-CoV-2 evolution is a fundamental effort in coping with the COVID-19 pandemic. The virus genomes have been broadly evolving due to the high number of infected hosts world-wide. Mutagenesis and selection are the two inter-dependent mechanisms of virus diversification. However, which mechanisms contribute to the mutation profiles of SARS-CoV-2 remain under-explored. Here, we delineate the contribution of mutagenesis and selection to the genome diversity of SARS-CoV-2 isolates. We generated a comprehensive phylogenetic tree with representative genomes. Instead of counting mutations relative to the reference genome, we identified each mutation event at the nodes of the phylogenetic tree. With this approach, we obtained the mutation events that are independent of each other and generated the mutation profile of SARS-CoV-2 genomes. The results suggest that the heterogeneous mutation patterns are mainly reflections of host (i) antiviral mechanisms that are achieved through APOBEC, ADAR, and ZAP proteins and (ii) probable adaptation against reactive oxygen species.\n\nImportanceSARS-CoV-2 genomes are evolving worldwide. Revealing the evolutionary characteristics of SARS-CoV-2 is essential to understand host-virus interactions. Here, we aim to understand whether mutagenesis or selection is the primary driver of SARS-CoV-2 evolution. This study provides an unbiased computational method for profiling and analyzing independently occurring SARS-CoV-2 mutations. The results point out three host antiviral mechanisms shaping the mutational profile of SARS-CoV-2 through APOBEC, ADAR, and ZAP proteins. Besides, reactive oxygen species might have an impact on the SARS-CoV-2 mutagenesis.", - "rel_num_authors": 5, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.02.03.429670", + "rel_abs": "The novel severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) caused the devastating ongoing coronavirus disease-2019 (COVID-19) pandemic which poses a great threat to global public health. The spike (S) polypeptide of SARS-CoV-2 consists of the S1 and S2 subunits and is processed by cellular proteases at the S1/S2 boundary. The inclusion of the 4 amino acids (PRRA) at the S1/S2 boundary forms a furin cleavage site (FCS), 682RRAR{downarrow}S686, distinguishing SARS-CoV-2 from its closest relative, the SARS-CoV. Various deletions surrounding the FCS have been identified in patients. When SARS-CoV-2 propagated in Vero cells, the virus acquired various deletions surrounding the FCS. In the present study, we studied the viral transcriptome in SARS-CoV-2 infected primary human airway epithelia (HAE) cultured at an air-liquid interface (ALI) with an emphasis on the viral genome stability at the S1/S2 boundary using RNA-seq. While we found overall the viral transcriptome is similar to that generated from infected Vero cells, we identified a high percentage of mutated viral genome and transcripts in HAE-ALI. Two highly frequent deletions were found at the S1/S2 boundary of the S gene: one is a deletion of 12 amino acids, 678TNSPRRAR{downarrow}SVAS689, which contains the FCS, another is a deletion of 5 amino acids, 675QTQTN679, which is two amino acids upstream of the FCS. Further studies on the dynamics of the FCS deletions in apically released virions revealed that the selective pressure for the FCS maintains the S gene stability in HAE-ALI but with exceptions, in which the FCS deletions are remained at a high rate. Thus, our study presents evidence for the role of unique properties of human airway epithelia in the dynamics of the FCS region during infection of human airways, which is donor-dependent.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Cem Azgari", - "author_inst": "Sabanci University" + "author_name": "Wei Zou", + "author_inst": "Department of Microbiology and Immunology, University of Michigan Ann Arbor, MI 48109" }, { - "author_name": "Zeynep Kilinc", - "author_inst": "Sabanci University" + "author_name": "Min Xiong", + "author_inst": "University of Kansas Medical Center" }, { - "author_name": "Berk Turhan", - "author_inst": "Sabanci University" + "author_name": "Siyuan Hao", + "author_inst": "University of Kansas Medical Center" }, { - "author_name": "Defne Circi", - "author_inst": "Sabanci University" + "author_name": "Elizabeth Yan Zhang-Chen", + "author_inst": "GeneGoCell Inc. San Diego, CA 92121" }, { - "author_name": "Ogun Adebali", - "author_inst": "Sabanci University" + "author_name": "Nathalie Baumlin", + "author_inst": "Department of Internal Medicine University of Kansas Medical Center" + }, + { + "author_name": "Michael D. Kim", + "author_inst": "Department of Internal Medicine University of Kansas Medical Center" + }, + { + "author_name": "Matthias Salathe", + "author_inst": "Department of Internal Medicine University of Kansas Medical Center" + }, + { + "author_name": "Ziying Yan", + "author_inst": "Department of Anatomy and Cell Biology, University of Iowa" + }, + { + "author_name": "Jianming Qiu", + "author_inst": "University of Kansas Medical Center" } ], "version": "1", - "license": "cc_by_nd", + "license": "", "type": "new results", - "category": "evolutionary biology" + "category": "microbiology" }, { "rel_doi": "10.1101/2021.02.04.429604", @@ -938918,37 +938906,45 @@ "category": "allergy and immunology" }, { - "rel_doi": "10.1101/2021.02.02.21250979", - "rel_title": "Vaccinating Australia: How long will it take?", + "rel_doi": "10.1101/2021.02.01.21250959", + "rel_title": "Increased hazard of death in community-tested cases of SARS-CoV-2 Variant of Concern 202012/01", "rel_date": "2021-02-03", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.02.21250979", - "rel_abs": "The Australian Governments COVID-19 vaccine rollout strategy is scheduled to commence in late February 2021 and aims to vaccinate the Australian adult population by the end of October 2021. The task of vaccinating some 20 million people within this timeframe presents considerable logistical challenges. Key to meeting this target is the rate of vaccine delivery: the number of vaccine doses that can be administered per day. In the opening phase, high priority groups will receive the Pfizer/BioNTech vaccine through hospital hubs at an initial rate of 80,000 doses per week. However, pending regulatory approval, the currently announced plan appears to be to distribute the AstraZeneca vaccine to the bulk of the popluation through a combination of general practices and community pharmacies. Here, we run a series of projections to estimate how long it will take to vaccinate the Australian population under different assumptions about the rate of vaccine administration as well as the schedule for second doses and prevalence of vaccine hesitancy. Our analysis highlights the ambitious rate of vaccine administration that will be neccessary to meet the Australian Government completion target of October 2021. A rate of 200,000 doses per day would comfortably meet that target; 80,000 doses a day would see roll-out extended until mid-2022. Speed is of the essence when it comes to vaccine rollout: protecting the population quickly will minimise the risk of sporadic and costly lockdowns lockdowns and the potential for small, local clusters getting out of control and sparking new epidemic waves. The government should gather all its resources to maximise the daily vaccination rate, ideally aiming to ramp up administration to at least 200,000 doses per day as quickly as possible. Quickly achieving and maintaining this pace will likely require dedicated large-scale vaccination sites that are capable of delivering thousands of doses a week in addition to the enthusiastic participation of GP practices and community pharmacies around the country. Lessons on the neccessary logistical planning, including coordination of delivery, ultra-cold-chain storage and staffing, can potentially be learned from Israel, where between 7,000 and 20,000 vaccinations per million population have been delivered daily throughout January.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.01.21250959", + "rel_abs": "SARS-CoV-2 lineage B.1.1.7, a variant first detected in the United Kingdom in September 20201, has spread to multiple countries worldwide. Several studies have established that B.1.1.7 is more transmissible than preexisting variants, but have not identified whether it leads to any change in disease severity2. We analyse a dataset linking 2,245,263 positive SARS-CoV-2 community tests and 17,452 COVID-19 deaths in England from 1 September 2020 to 14 February 2021. For 1,146,534 (51%) of these tests, the presence or absence of B.1.1.7 can be identified because of mutations in this lineage preventing PCR amplification of the spike gene target (S gene target failure, SGTF1). Based on 4,945 deaths with known SGTF status, we estimate that the hazard of death associated with SGTF is 55% (95% CI 39-72%) higher after adjustment for age, sex, ethnicity, deprivation, care home residence, local authority of residence and test date. This corresponds to the absolute risk of death for a 55-69-year-old male increasing from 0.6% to 0.9% (95% CI 0.8-1.0%) within 28 days after a positive test in the community. Correcting for misclassification of SGTF and missingness in SGTF status, we estimate a 61% (42-82%) higher hazard of death associated with B.1.1.7. Our analysis suggests that B.1.1.7 is not only more transmissible than preexisting SARS-CoV-2 variants, but may also cause more severe illness.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Mark J Hanly", - "author_inst": "Centre for Big Data Research in Health, UNSW Australia" + "author_name": "Nicholas G Davies", + "author_inst": "London School of Hygiene and Tropical Medicine" }, { - "author_name": "Tim Churches", - "author_inst": "South Western Sydney Clinical School, Faculty of Medicine & Health, UNSW Sydney & Ingham Institute for Applied Medical Research" + "author_name": "Christopher I Jarvis", + "author_inst": "London School of Hygiene and Tropical Medicine" }, { - "author_name": "Oisin Fitzgerald", - "author_inst": "Centre for Big Data Research in Health, UNSW Sydney" + "author_name": "- CMMID COVID-19 Working Group", + "author_inst": "" }, { - "author_name": "Chandini Raina MacIntyre", - "author_inst": "University of New South Wales" + "author_name": "W. John Edmunds", + "author_inst": "London School of Hygiene and Tropical Medicine" + }, + { + "author_name": "Nicholas P. Jewell", + "author_inst": "London School of Hygiene and Tropical Medicine" }, { - "author_name": "Louisa Jorm", - "author_inst": "Centre for Big Data Research in Health, UNSW Sydney" + "author_name": "Karla Diaz-Ordaz", + "author_inst": "London School of Hygiene and Tropical Medicine" + }, + { + "author_name": "Ruth H. Keogh", + "author_inst": "London School of Hygiene and Tropical Medicine" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -940588,55 +940584,91 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.02.03.429601", - "rel_title": "Bacterial expression and purification of functional recombinant SARS-CoV-2 spike receptor binding domain", + "rel_doi": "10.1101/2021.02.03.429146", + "rel_title": "CovRadar: Continuously tracking and filtering SARS-CoV-2 mutations for molecular surveillance", "rel_date": "2021-02-03", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.02.03.429601", - "rel_abs": "The COVID-19 pandemic caused by SARS-CoV-2 has applied significant pressure on overtaxed healthcare around the world, underscoring the urgent need for rapid diagnosis and treatment. We have developed a bacterial strategy for the expression and purification of the SARS-CoV-2 spike protein receptor binding domain using the CyDisCo system to create and maintain the correct disulfide bonds for protein integrity and functionality. We show that it is possible to quickly and inexpensively produce functional, active antigen in bacteria capable of recognizing and binding to the ACE2 (angiotensin-converting enzyme) receptor as well as antibodies in COVID-19 patient sera.", - "rel_num_authors": 9, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.02.03.429146", + "rel_abs": "The SARS-CoV-2 pandemic underlined the importance of molecular surveillance to track the evolution of the virus and inform public health interventions. Fast analysis, easy visualization and convenient filtering of the latest virus sequences are essential for this purpose. However, access to computational resources, the lack of bioinformatics expertise, and the sheer volume of sequences in public databases complicate surveillance efforts. CovRadar combines an analytical pipeline and a web application designed for the molecular surveillance of the spike gene of SARS-CoV-2, an important vaccine target. The intuitive web front-end focuses on mutations rather than viral lineages and provides easy access to frequencies and spatio-temporal distributions from global sample collections. The data is regularly updated based on a scalable and reproducible analytical back-end. With this platform, we aim to give users, those with or without bioinformatics skills or sufficient computational resources, the possibility to track and explore mutational changes in the SARS-CoV-2 spike gene and to filter, download, and further analyze data that meet their questions and needs. Advanced computational users have the ability to apply the analytical pipeline and data visualization methods locally on their own data. CovRadar is freely accessible at https://covradar.net, source code is available at https://gitlab.com/dacs-hpi/covradar.\n\nGRAPHICAL ABSTRACT\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=150 SRC=\"FIGDIR/small/429146v3_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (52K):\norg.highwire.dtl.DTLVardef@194a562org.highwire.dtl.DTLVardef@1f5f0d3org.highwire.dtl.DTLVardef@195b5dborg.highwire.dtl.DTLVardef@1d65231_HPS_FORMAT_FIGEXP M_FIG C_FIG", + "rel_num_authors": 18, "rel_authors": [ { - "author_name": "Janani Prahlad", - "author_inst": "University of Nebraska Medical Center" + "author_name": "Alice Wittig", + "author_inst": "Robert Koch Institute, Hasso Plattner Institute" }, { - "author_name": "Lucas Struble", - "author_inst": "University of Nebraska Medical Center" + "author_name": "F\u00e1bio Miranda", + "author_inst": "Hasso Plattner Institute" }, { - "author_name": "William E Lutz", - "author_inst": "University of Nebraska Medical Center" + "author_name": "Martin H\u00f6lzer", + "author_inst": "Robert Koch Institute, Friedrich Schiller University Jena" }, { - "author_name": "Savanna A Wallin", - "author_inst": "University of Nebraska Medical Center" + "author_name": "Tom Altenburg", + "author_inst": "Hasso Plattner Institute" }, { - "author_name": "Surender Khurana", - "author_inst": "University of Nebraska Medical Center" + "author_name": "Jakub M Bartoszewicz", + "author_inst": "Hasso Plattner Institute" }, { - "author_name": "Andy Schnaubelt", - "author_inst": "University of Nebraska Medical Center" + "author_name": "Sebastian Beyvers", + "author_inst": "Justus Liebig University Giessen" }, { - "author_name": "Mara J Broadhurst", - "author_inst": "University of Nebraska Medical Center" + "author_name": "Marius A Dieckmann", + "author_inst": "Justus Liebig University Giessen" }, { - "author_name": "Ken Bayles", - "author_inst": "University of Nebraska Medical Center" + "author_name": "Ulrich Genske", + "author_inst": "Hasso Plattner Institute, Charit\u00e9, Free University of Berlin, Humboldt University of Berlin, Berlin Institute of Health" }, { - "author_name": "Gloria E. O. Borgstahl", - "author_inst": "University of Nebraska Medical Center" + "author_name": "Sven H Giese", + "author_inst": "Hasso Plattner Institute" + }, + { + "author_name": "Melania Nowicka", + "author_inst": "Hasso Plattner Institute" + }, + { + "author_name": "Hugues Richard", + "author_inst": "Robert Koch Institute" + }, + { + "author_name": "Henning Schiebenhoefer", + "author_inst": "Hasso Plattner Institute" + }, + { + "author_name": "Anna-Juliane Schmachtenberg", + "author_inst": "Hasso Plattner Institute" + }, + { + "author_name": "Paul Sieben", + "author_inst": "Hasso Plattner Institute" + }, + { + "author_name": "Ming Tang", + "author_inst": "Hasso Plattner Institute, Hannover Medical School" + }, + { + "author_name": "Julius Tembrockhaus", + "author_inst": "Hasso Plattner Institute" + }, + { + "author_name": "Bernhard Y Renard", + "author_inst": "Hasso Plattner Institute" + }, + { + "author_name": "Stephan Fuchs", + "author_inst": "Robert Koch Institute" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "new results", - "category": "biochemistry" + "category": "bioinformatics" }, { "rel_doi": "10.1101/2021.02.02.429311", @@ -942710,55 +942742,115 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.02.01.429283", - "rel_title": "A Thermostable, Flexible RNA Vaccine Delivery Platform for Pandemic Response", + "rel_doi": "10.1101/2021.02.02.428995", + "rel_title": "Therapeutic antibodies, targeting the SARS-CoV-2 spike N-terminal domain, protect lethally infected K18-hACE2 mice", "rel_date": "2021-02-02", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.02.01.429283", - "rel_abs": "Current RNA vaccines against SARS-CoV-2 are limited by instability of both the RNA and the lipid nanoparticle delivery system, requiring storage at -20{degrees}C or -70{degrees}C and compromising universally accessible vaccine distribution. This study demonstrates the thermostability and adaptability of a nanostructured lipid carrier (NLC) RNA vaccine delivery system for use in pandemic preparedness and pandemic response. Liquid NLC is stable at refrigerated temperatures for [≥] 1 year, enabling stockpiling and rapid deployment by point-of-care mixing with any vaccine RNA. Alternatively, NLC complexed with RNA may be readily lyophilized and stored at room temperature for [≥] 8 months or refrigerated temperature for [≥] 21 months. This thermostable RNA vaccine platform could significantly improve distribution of current and future pandemic response vaccines, particularly in low-resource settings.\n\nOne Sentence SummaryAn RNA vaccine delivery system stable at room temperature for 8+ months and refrigerated for 21+ months.", - "rel_num_authors": 9, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.02.02.428995", + "rel_abs": "Since the onset of the current COVID-19 pandemic, high priority is given to the development of neutralizing antibodies, as a key approach for the design of therapeutic strategies to countermeasure and eradicate the disease. Previously, we reported the development of human therapeutic monoclonal antibodies (mAbs) exhibiting very high protective ability. These mAbs recognize epitopes on the spike receptor binding domain (RBD) of SARS-CoV-2 that is considered to represent the main rout of receptor engagement by the SARS-CoV-2 virus. The recent emergence of viral variants emphasizes the notion that efficient antibody treatments need to rely on mAbs against several distinct key epitopes in order to circumvent the occurrence of therapy escape-mutants. Here we report the isolation and characterization of 12 neutralizing mAbs, identified by screening a phage-display library constructed from lymphatic cells collected from severe COVID-19 patients. The antibodies target three distinct epitopes on the spike N-terminal domain (NTD) of SARS-CoV-2, one of them defining a major site of vulnerability of the virus. Extensive characterization of these mAbs suggests a neutralization mechanism which relies both on amino-acid and N-glycan recognition on the virus, and involvement of receptors other than the hACE2 on the target cell. Two of the selected mAbs, which demonstrated superior neutralization potency in vitro, were further evaluated in vivo, demonstrating their ability to fully protect K18-hACE2 transgenic mice even when administered at low doses and late after infection. The study demonstrates the high potential of the mAbs for therapy of SARS-CoV-2 infection and underlines the possible role of the NTD in mediating infection of host cells via alternative cellular portals other than the canonical ACE2 receptor.", + "rel_num_authors": 24, "rel_authors": [ { - "author_name": "Alana Gerhardt", - "author_inst": "Infectious Disease Research Institute" + "author_name": "Tal Noy-Porat", + "author_inst": "Israel Institute for Biological Research" }, { - "author_name": "Emily Voigt", - "author_inst": "Infectious Disease Research Institute" + "author_name": "Adva Mechaly", + "author_inst": "Israel Institute for Biological Research" }, { - "author_name": "Michelle Archer", - "author_inst": "Infectious Disease Research Institute" + "author_name": "Yinon Levy", + "author_inst": "Israel Institute for Biological Research" }, { - "author_name": "Sierra Reed", - "author_inst": "Infectious Disease Research Institute" + "author_name": "Efi Makdasi", + "author_inst": "Israel Institute for Biological Research" }, { - "author_name": "Elise Larson", - "author_inst": "Infectious Disease Research Institute" + "author_name": "Ron Alcalay", + "author_inst": "Israel Institute for Biological Research" }, { - "author_name": "Neal Van Hoeven", - "author_inst": "Infectious Disease Research Institute" + "author_name": "David Gur", + "author_inst": "Israel Institute for Biological Research" }, { - "author_name": "Ryan Kramer", - "author_inst": "Infectious Disease Research Institute" + "author_name": "Moshe Aftalion", + "author_inst": "Israel Institute for Biological Research" }, { - "author_name": "Christopher Fox", - "author_inst": "Infectious Disease Research Institute" + "author_name": "Reut Falach", + "author_inst": "Israel Institute for Biological Research" }, { - "author_name": "Corey Casper", - "author_inst": "Infectious Disease Research Institute" + "author_name": "Shani Leviatan Ben-Arye", + "author_inst": "Tel Aviv University" + }, + { + "author_name": "Shirley Lazar", + "author_inst": "Israel Institute for Biological Research" + }, + { + "author_name": "Ayelet Zauberman", + "author_inst": "Israel Institute for Biological Research" + }, + { + "author_name": "Eyal Epstein", + "author_inst": "Israel Institute for Biological Research" + }, + { + "author_name": "Theodor Chitlaru", + "author_inst": "Israel Institute for Biological Research" + }, + { + "author_name": "Shay Weiss", + "author_inst": "Israel Institute for Biological Research" + }, + { + "author_name": "Hagit Achdout", + "author_inst": "Israel Institute for Biological Research" + }, + { + "author_name": "Jonathan D. Edgeworth", + "author_inst": "Kings College London" + }, + { + "author_name": "Raghavendra Kikkeri", + "author_inst": "Indian Institute of Science Education and Research" + }, + { + "author_name": "Hai Yu", + "author_inst": "University of California, Davis" + }, + { + "author_name": "Xi Chen", + "author_inst": "University of California-Davis" + }, + { + "author_name": "Shmuel Yitzhaki", + "author_inst": "Israel Institute for Biological Research" + }, + { + "author_name": "Shmuel C. Shapira", + "author_inst": "Israel Institute for Biological Research" + }, + { + "author_name": "Vered Padler-Karavani", + "author_inst": "Tel Aviv University" + }, + { + "author_name": "Ohad Mazor", + "author_inst": "Israel Institute for Biological Research" + }, + { + "author_name": "Ronit Rosenfeld", + "author_inst": "Israel Institute for Biological Research" } ], "version": "1", - "license": "cc_no", + "license": "", "type": "new results", - "category": "bioengineering" + "category": "immunology" }, { "rel_doi": "10.1101/2021.01.28.428568", @@ -944272,97 +944364,25 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.01.28.21250717", - "rel_title": "Comparative performance of multiplex salivary and commercially available serologic assays to detect SARS-CoV-2 IgG and neutralization titers", + "rel_doi": "10.1101/2021.01.28.21250721", + "rel_title": "Significance of SARS-CoV-2 Specific Antibody Testing during COVID-19 Vaccine Allocation", "rel_date": "2021-02-01", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.28.21250717", - "rel_abs": "Oral fluid (hereafter saliva) offers a non-invasive sampling method for the detection of SARS-CoV-2 antibodies. However, data comparing performance of salivary tests against commercially-available serologic and neutralizing antibody (nAb) assays are lacking. This study compared the performance of a multiplex salivary SARS-CoV-2 IgG assay targeting antibodies to nucleocapsid (N), receptor binding domain (RBD) and spike (S) antigens to three commercially-available SARS-CoV-2 serology enzyme immunoassays (EIAs) (Ortho Vitros, Euroimmun, and BioRad) and nAb. Paired saliva and plasma samples were collected from 101 eligible COVID-19 convalescent plasma (CCP) donors >14 days since PCR+ confirmed diagnosis. Concordance was evaluated using positive (PPA) and negative (NPA) percent agreement, overall percent agreement (PA), and Cohens kappa coefficient. The range between salivary and plasma EIAs for SARS-CoV-2-specific N was PPA: 54.4-92.1% and NPA: 69.2-91.7%, for RBD was PPA: 89.9-100% and NPA: 50.0-84.6%, and for S was PPA: 50.6-96.6% and NPA: 50.0-100%. Compared to a plasma nAb assay, the multiplex salivary assay PPA ranged from 62.3% (N) and 98.6% (RBD) and NPA ranged from 18.8% (RBD) to 96.9% (S). Combinations of N, RBD, and S and a summary algorithmic index of all three (N/RBD/S) in saliva produced ranges of PPA: 87.6-98.9% and NPA: 50-91.7% with the three EIAs and ranges of PPA: 88.4-98.6% and NPA: 21.9-34.4% with the nAb assay. A multiplex salivary SARS-CoV-2 IgG assay demonstrated comparable performance to three commercially-available plasma EIAs and a nAb assay, and may be a viable alternative to assist in screening CCP donors and monitoring population-based seroprevalence and vaccine antibody response.", - "rel_num_authors": 21, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.28.21250721", + "rel_abs": "ObjectiveTo assess the value of using SARS-CoV-2 specific antibody testing to prioritize the vaccination of susceptible individuals as part of a COVID-19 vaccine distribution plan when vaccine supply is limited.\n\nMethodsA compartmental model was used to simulate COVID-19 spread when considering diagnosis, isolation, and vaccination of a cohort of 1 million individuals. The scenarios modeled represented 4 pandemic severity scenarios and various times when the vaccine becomes available during the pandemic. Eligible individuals have a probability p of receiving antibody testing prior to vaccination (p = 0, 0.25, 0.5, 0.75, and 1). The value of serology testing was evaluated by comparing the infection attack rate, peak infections, peak day, and deaths.\n\nResultsThe use of antibody testing to prioritize the allocation of limited vaccines reduces infection attack rates and deaths. The size of the reduction depends on when the vaccine becomes available relative to the infection peak day. The largest reduction in cases and deaths occurs when the vaccine is deployed before and close to the infection peak day. The reduction in the number of cases and deaths diminishes as vaccine deployment is delayed and moves closer to the peak day.\n\nConclusionsAntibody testing as part of the vaccination plan is an effective method to maximize the benefit of a COVID-19 vaccine. Decision-makers need to consider relative timing between the infection peak day and when the vaccine becomes available.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Christopher D Heaney", - "author_inst": "Johns Hopkins Bloomberg School of Public Health" - }, - { - "author_name": "Nora Pisanic", - "author_inst": "Department of Environmental Health and Engineering, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA" - }, - { - "author_name": "Pranay R Randad", - "author_inst": "Department of Environmental Health and Engineering, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA" - }, - { - "author_name": "Kate Kruczynski", - "author_inst": "Department of Environmental Health and Engineering, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA" - }, - { - "author_name": "Tyrone Howard", - "author_inst": "Department of Environmental Health and Engineering, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA" - }, - { - "author_name": "Xianming Zhu", - "author_inst": "Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD, USA" - }, - { - "author_name": "Kirsten Littlefield", - "author_inst": "Johns Hopkins Bloomberg School of Public Health," - }, - { - "author_name": "Eshan Patel", - "author_inst": "NIAID" - }, - { - "author_name": "Ruchee Shrestha", - "author_inst": "Johns Hopkins University School of Medicine" - }, - { - "author_name": "Oliver Laeyendecker", - "author_inst": "NIAID & JHMI" - }, - { - "author_name": "Shmuel Shoham", - "author_inst": "The Johns Hopkins Hospital, , MD" - }, - { - "author_name": "David J Sullivan", - "author_inst": "Johns Hopkins Bloomberg School of Public Health" - }, - { - "author_name": "Kelly Gebo", - "author_inst": "Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA" - }, - { - "author_name": "Daniel Hanley", - "author_inst": "Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA" - }, - { - "author_name": "Andrew Redd", - "author_inst": "Johns Hopkins University School of Medicine" - }, - { - "author_name": "Thomas Quinn", - "author_inst": "Johns Hopkins University School of Medicine" - }, - { - "author_name": "Arturo Casadevall", - "author_inst": "Johns Hopkins School of Public Health" - }, - { - "author_name": "Jonathan M Zenilman", - "author_inst": "Johns Hopkins University" - }, - { - "author_name": "Andrew Pekosz", - "author_inst": "Johns Hopkins Bloomberg School of Public Health" + "author_name": "Akane B Fujimoto", + "author_inst": "Georgia Institute of Technology" }, { - "author_name": "Evan M Bloch", - "author_inst": "Johns Hopkins Medicine" + "author_name": "Inci Yildirim", + "author_inst": "Yale School of Medicine and Yale Institute of Global Health" }, { - "author_name": "Aaron AR Tobian", - "author_inst": "Johns Hopkins Hospital" + "author_name": "Pinar Keskinocak", + "author_inst": "Georgia Institute of Technology" } ], "version": "1", @@ -946106,69 +946126,41 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.01.29.21250552", - "rel_title": "Aerosol emission from the respiratory tract: an analysis of relative risks from oxygen delivery systems", + "rel_doi": "10.1101/2021.01.29.21250655", + "rel_title": "Impact of public sentiments on the transmission of COVID-19 across a geographical gradient", "rel_date": "2021-02-01", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.29.21250552", - "rel_abs": "BackgroundRisk of aerosolisation of SARS-CoV-2 directly informs organisation of acute healthcare and PPE guidance. Continuous positive airways pressure (CPAP) and high-flow nasal oxygen (HFNO) are widely used modes of oxygen delivery and respiratory support for patients with severe COVID-19, with both considered as high risk aerosol generating procedures. However, there are limited high quality experimental data characterising aerosolisation during oxygen delivery and respiratory support.\n\nMethodsHealthy volunteers were recruited to breathe, speak, and cough in ultra-clean, laminar flow theatres followed by using oxygen and respiratory support systems. Aerosol emission was measured using two discrete methodologies, simultaneously. Hospitalised patients with COVID-19 were also recruited and had aerosol emissions measured during breathing, speaking, and coughing.\n\nFindingsIn healthy volunteers (n = 25 subjects; 531 measures), CPAP (with exhalation port filter) produced less aerosols than breathing, speaking and coughing (even with large >50L/m facemask leaks). HFNO did emit aerosols, but the majority of these particles were generated from the HFNO machine, not the patient. HFNO-generated particles were small (<1m), passing from the machine through the patient and to the detector without coalescence with respiratory aerosol, thereby unlikely to carry viral particles. Coughing was associated with the highest aerosol emissions with a peak concentration at least 10 times greater the mean concentration generated from speaking or breathing. Hospitalised patients with COVID-19 (n = 8 subjects; 56 measures) had similar size distributions to healthy volunteers.\n\nInterpretationIn healthy volunteers, CPAP is associated with less aerosol emission than breathing, speaking or coughing. Aerosol emission from the respiratory tract does not appear to be increased by HFNO. Although direct comparisons are complex, cough appears to generate significant aerosols in a size range compatible with airborne transmission of SARS-CoV-2. As a consequence, the risk of SARS-CoV-2 aerosolisation is likely to be high in all areas where patients with Covid-19 are coughing. Guidance on personal protective equipment policy should reflect these updated risks.\n\nFundingNIHR-UKRI Rapid COVID call (COV003), Wellcome Trust GW4-CAT Doctoral Training Scheme (FH), MRC CARP Fellowship(JD, MR/T005114/1). Natural Environment Research Council grant (BB, NE/P018459/1)\n\nResearch in contextO_ST_ABSEvidence before this studyC_ST_ABSPubMed was searched from inception until 10/1/21 using the terms aerosol, and variations of non-invasive positive pressure ventilation and high-flow nasal oxygen therapy. Studies were included if they measured aerosol generated from volunteers or patients receiving non-invasive positive pressure ventilation (NIV) or high flow nasal oxygen therapy (HFNO), or provided experimental evidence on a simulated human setting. One study was identified (Gaeckle et al, 2020) which measured aerosol emission with one methodology (APS) but was limited by high background concentration of aerosol and a low number of participants (n = 10).\n\nAdded value of this studyThis study used multiple methodologies to measure aerosol emission from the respiratory tract before and during CPAP and high-flow nasal oxygen, in an ultra-clean, laminar flow theatre with near-zero background aerosol and recruited patients with COVID-19 to ensure similar aerosol distributions. We conclude that there is negligible aerosol generation with CPAP, that aerosol emission from HFNO is from the machine and not the patient, coughing emits aerosols consistent with airborne transmission of SARS CoV2 and that healthy volunteers are a reasonable proxy for COVID-19 patients.\n\nImplications of all the available evidenceCPAP and HFNO should not be considered high risk aerosol generating procedures, based on our study and that of Gaeckle et al. Recorded aerosol emission from HFNO stems from the machine. Cough remains a significant aerosol risk. PPE guidance should be updated to ensure medical staff are protected with appropriate PPE in situations when patients with suspected or proven COVID-19 are likely to cough.", - "rel_num_authors": 14, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.29.21250655", + "rel_abs": "COVID-19 is a respiratory disease caused by a recently discovered, novel coronavirus, SARS-COV2. The disease has led to over 81 million confirmed cases of COVID-19, with close to 2 million deaths. In the current social climate, the risk of COVID-19 infection is driven by individual and public perception of risk and sentiments. A number of factors influences public perception, including an individuals belief system, prior knowledge about a disease and information about a disease. In this paper, we develop a model for COVID-19 using a system of ordinary differential equations following the natural history of the infection. The model uniquely incorporates social behavioral aspects such as quarantine and quarantine violation. The model is further driven by peoples sentiments (positive and negative) which accounts for the influence of disinformation. Peoples sentiments were obtained by parsing through and analyzing COVID-19 related tweets from Twitter, a social media platform across six countries. Our results show that our model incorporating public sentiments is able to capture the trend in the trajectory of the epidemic curve of the reported cases. Furthermore, our results show that positive public sentiments reduce disease burden in the community. Our results also show that quarantine violation and early discharge of the infected population amplifies the disease burden on the community. Hence, it is important to account for public sentiment and individual social behavior in epidemic models developed to study diseases like COVID-19.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Fergus W Hamilton", - "author_inst": "University of Bristol" - }, - { - "author_name": "Florence Gregson", - "author_inst": "University of Bristol" - }, - { - "author_name": "David T Arnold", - "author_inst": "University of Bristol" - }, - { - "author_name": "Sadiyah Sheikh", - "author_inst": "University of Bristol" - }, - { - "author_name": "Kirsty Ward", - "author_inst": "North Bristol NHS Trust" - }, - { - "author_name": "Jules Brown", - "author_inst": "North Bristol NHS Trust" - }, - { - "author_name": "Ed Moran", - "author_inst": "North Bristol NHS Trust" - }, - { - "author_name": "Carrie White", - "author_inst": "North Bristol NHS Trust" + "author_name": "Folashade Agusto", + "author_inst": "University of Kansas, Lawrence, KS" }, { - "author_name": "Anna Morley", - "author_inst": "North Bristol NHS Trust" + "author_name": "Eric Numfor", + "author_inst": "Augusta University, Augusta, GA" }, { - "author_name": "- AERATOR Group", - "author_inst": "" + "author_name": "Karthik Srinivasan", + "author_inst": "University of Kansas, Lawrence, KS" }, { - "author_name": "Bryan R Bzdek", - "author_inst": "University of Bristol" + "author_name": "Enahoro Iboi", + "author_inst": "Spelman College, Atlanta, GA" }, { - "author_name": "Jonathan Reid", - "author_inst": "University of Bristol" + "author_name": "Alexander Fulk", + "author_inst": "University of Kansas, Lawrence, KS" }, { - "author_name": "Nick Maskell", - "author_inst": "University of Bristol" + "author_name": "Jarron M. Saint Onge", + "author_inst": "University of Kansas, Lawrence, KS, and University of Kansas, Lawrence, KS" }, { - "author_name": "James W Dodd", - "author_inst": "University of Bristol" + "author_name": "Townsend Peterson", + "author_inst": "University of Kansas, Lawrence, KS" } ], "version": "1", @@ -947708,89 +947700,141 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.01.28.21250598", - "rel_title": "Nationwide Seroprevalence of SARS-CoV-2 in Saudi Arabia", + "rel_doi": "10.1101/2021.01.27.21250637", + "rel_title": "Evidence for SARS-CoV-2 Spike Protein in the Urine of COVID-19 patients", "rel_date": "2021-01-31", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.28.21250598", - "rel_abs": "BackgroundEstimated seroprevalence of Coronavirus Infectious Disease 2019 (COVID-19), caused by the Severe Acute Respiratory Syndrome-Coronavirus-2 (SARS-CoV-2) is a critical evidence for a better evaluation of the virus spread and monitoring the progress of the COVID-19 pandemic in a population. In the Kingdom of Saudi Arabia (KSA), SARS-CoV-2 seroprevalence has been reported in specific regions, but an extensive nationwide study has not been reported. Here, we report a nationwide study to determine the prevalence of SARS-CoV-2 in the population of KSA during the pandemic, using serum samples from healthy blood donors, non-COVID patients and healthcare workers (HCWs) in six different regions of the kingdom, with addition samples from COVID-19 patients.\n\nMethodsA total of 11703 serum samples were collected from different regions of the KSA including; 5395 samples from residual healthy blood donors (D); 5877 samples from non-COVID patients collected through residual sera at clinical biochemistry labs from non-COVID patients (P); and 400 samples from consented HCWs. To determine the seroprevalence of SARS-CoV-2, all serum samples, in addition to positive control sera from RT-PCR confirmed COVID-19 patients, were subjected to in-house ELISA with a sample pooling strategy, which was further validated by testing individual samples that make up some of the pools, with a statistical estimation method to report seroprevalence estimates\n\nResultsOverall (combining D and P groups) seroprevalence estimate was around 11% in Saudi Arabia; and was 5.1% (Riyadh), 1.5% (Jazan), 18.4% (Qassim), 20.8% (Hail), 14.7% (ER; Alahsa), and 18.8% in Makkah. Makkah samples were only D group and had a rate of 24.4% and 12.8% in the cities of Makkah and Jeddah, respectively. The seroprevalence in Saudi Arabia across the sampled areas would be 12 times the COVID-19 infection rate. Among HCWs, 7.5% (4.95-10.16 CI 95%) had reactive antibodies to SARS-CoV-2 without reporting any previously confirmed infection. This was higher in HCWs with hypertension. The study also presents the demographics and prevalence of co-morbidities in HCWs and subset of non-COVID-19 population.\n\nConclusionOur study estimates the overall national serological prevalence of COVID-19 in Saudi Arabia to be 11%, with an apparent disparity between regions.", - "rel_num_authors": 18, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.27.21250637", + "rel_abs": "SARS-CoV-2 infection has so far affected over 42 million people worldwide, causing over 1.1 million deaths. With the large majority of SARS-CoV-2 infected individuals being asymptomatic, major concerns have been raised about possible long-term consequences of the infection. We developed an antigen capture assay to detect SARS-CoV-2 spike protein in urine samples from COVID-19 patients whose diagnosis was confirmed by PCR from nasopharyngeal swabs (NP-PCR+). The study used a collection of 233 urine samples from 132 participants from Yale New Haven Hospital and the Childrens Hospital of Philadelphia obtained during the pandemic (106 NP-PCR+ and 26 NP-PCR-) as well as a collection of 20 urine samples from 20 individuals collected before the pandemic. Our analysis identified 23 out of 91 (25%) NP-PCR+ adult participants with SARS-CoV-2 spike S1 protein in urine (Ur-S+). Interestingly, although all NP-PCR+ children were Ur-S-, 1 NP-PCR-child was found to be positive for spike protein in urine. Of the 23 Ur-S+ adults, only 1 individual showed detectable viral RNA in urine. Our analysis further showed that 24% and 21% of NP-PCR+ adults have high levels of albumin and cystatin C in urine, respectively. Among individuals with albuminuria (>0.3 mg/mg of creatinine) statistical correlation could be found between albumin and spike protein in urine. Together, our data showe that 1 of 4 of SARS-CoV-2 infected individuals develop renal abnormalities such as albuminuria. Awareness about the long-term impact of these findings is warranted.", + "rel_num_authors": 31, "rel_authors": [ { - "author_name": "Naif Khalaf Alharbi", - "author_inst": "King Abdullah International Medical Research Center, Riyadh, Saudi Arabia. King Saud bin Abdulaziz University for Health Sciences, Riyadh, Saudi Arabia." + "author_name": "Santosh George", + "author_inst": "Department of Internal Medicine, Section of Infectious Diseases, Yale School of Medicine, New Haven, Connecticut, CT 06520 USA." }, { - "author_name": "Suliman Alghnam", - "author_inst": "King Abdullah International Medical Research Center, Riyadh, Saudi Arabia. King Saud bin Abdulaziz University for Health Sciences, Riyadh, Saudi Arabia." + "author_name": "Anasuya Chattopadhyay Pal", + "author_inst": "Department of Internal Medicine, Section of Infectious Diseases, Yale School of Medicine, New Haven, Connecticut, CT 06520 USA." }, { - "author_name": "Abdullah Algaissi", - "author_inst": "Department of Medical Laboratories Technology, College of Applied Medical Sciences, Medical Research Center, Jazan University, Jazan 45142, Saudi Arabia" + "author_name": "Jacqueline Gagnon", + "author_inst": "L2 Diagnostics, LLC, New Haven, Connecticut, USA." + }, + { + "author_name": "Sushma Timalsina", + "author_inst": "L2 Diagnostics, LLC, New Haven, Connecticut, USA." + }, + { + "author_name": "Pallavi Singh", + "author_inst": "Department of Internal Medicine, Section of Infectious Diseases, Yale School of Medicine, New Haven, Connecticut, CT 06520 USA." }, { - "author_name": "Hind Albalawi", - "author_inst": "King Abdullah International Medical Research Center, Riyadh, Kingdom of Saudi Arabia" + "author_name": "Pratap Vydyam", + "author_inst": "Department of Internal Medicine, Section of Infectious Diseases, Yale School of Medicine, New Haven, Connecticut, CT 06520 USA." }, { - "author_name": "Mohammed W Alenazi", - "author_inst": "King Abdullah International Medical Research Center, Riyadh, Kingdom of Saudi Arabia" + "author_name": "Muhammad Munshi", + "author_inst": "Department of Internal Medicine, Section of Infectious Diseases, Yale School of Medicine, New Haven, Connecticut, CT 06520 USA." }, { - "author_name": "Areeb M Albargawi", - "author_inst": "King Abdullah International Medical Research Center, Riyadh, Kingdom of Saudi Arabia" + "author_name": "Joy E Chiu", + "author_inst": "Department of Internal Medicine, Section of Infectious Diseases, Yale School of Medicine, New Haven, Connecticut, CT 06520 USA." }, { - "author_name": "Abdullah G Alharbi", - "author_inst": "King Fahad Specialized Hospital, Qassim, Saudi Arabia." + "author_name": "Isaline Renard", + "author_inst": "Department of Internal Medicine, Section of Infectious Diseases, Yale School of Medicine, New Haven, Connecticut, CT 06520 USA." }, { - "author_name": "Abdulaziz Alhazmi", - "author_inst": "Department of Medical Laboratories Technology, College of Applied Medical Sciences, Medical Research Center, Jazan University, Jazan 45142, Saudi Arabia" + "author_name": "Christina A Harden", + "author_inst": "Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT 06520 USA." }, { - "author_name": "Ali Al Qarni", - "author_inst": "King Abdulaziz Hospital, Ministry of National Guard Health Affairs, Alahsa, Saudi Arabia" + "author_name": "Isabel M Ott", + "author_inst": "Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT 06520 USA." }, { - "author_name": "Ali Alfarhan", - "author_inst": "King Abdulaziz Medical City, Ministry of National Guard Health Affairs, Riyadh, Saudi Arabia" + "author_name": "Anne E Watkins", + "author_inst": "Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT 06520 USA." }, { - "author_name": "Hossam M. Zowawi", - "author_inst": "King Saud bin Abdulaziz University for Health Sciences, Riyadh, Saudi Arabia" + "author_name": "Chantal B F Vogels", + "author_inst": "Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT 06520 USA." }, { - "author_name": "Hind Alhatmi", - "author_inst": "King Abdulaziz Medical City, Ministry of National Guard Health Affairs, Riyadh, Saudi Arabia" + "author_name": "Peiwen Lu", + "author_inst": "Department of Immunology, Yale School of Medicine, New Haven, Connecticut, CT 06520 USA." }, { - "author_name": "Jahad Alghamdi", - "author_inst": "King Abdullah International Medical Research Center, Riyadh, Saudi Arabia. King Saud bin Abdulaziz University for Health Sciences, Riyadh, Saudi Arabia." + "author_name": "Maria Tokuyama", + "author_inst": "Department of Immunology, Yale School of Medicine, New Haven, Connecticut, CT 06520 USA." }, { - "author_name": "Fayhan Alroqi", - "author_inst": "King Abdullah International Medical Research Center, Riyadh, Kingdom of Saudi Arabia. King Saud bin Abdulaziz University for Health Sciences, Riyadh, Saudi Arab" + "author_name": "Arvind Venkataraman", + "author_inst": "Department of Immunology, Yale School of Medicine, New Haven, Connecticut, CT 06520 USA." }, { - "author_name": "Yaseen M. Arabi", - "author_inst": "King Abdullah International Medical Research Center, Riyadh, Kingdom of Saudi Arabia. King Saud bin Abdulaziz University for Health Sciences, Riyadh, Saudi Arab" + "author_name": "Arnau Casanovas-Massana", + "author_inst": "Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT 06520 USA." }, { - "author_name": "Anwar M. Hashem", - "author_inst": "Department of Medical Microbiology and Parasitology, Faculty of Medicine, King Abdulaziz University, Jeddah, Saudi Arabia. Vaccines and Immunotherapy Unit, King" + "author_name": "Anne L Wyllie", + "author_inst": "Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT 06520 USA." + }, + { + "author_name": "Veena Rao", + "author_inst": "Department of Internal Medicine, Section of Cardiovascular Medicine, Yale School of Medicine, New Haven, Connecticut, CT 06520 USA." + }, + { + "author_name": "Melissa Campbell", + "author_inst": "Department of Pediatrics, Section of Infectious Diseases, Yale School of Medicine, New Haven, Connecticut, CT 06520 USA." + }, + { + "author_name": "Shelli F Farhadian", + "author_inst": "Department of Internal Medicine, Section of Infectious Diseases, Yale School of Medicine, New Haven, Connecticut, CT 06520 USA." + }, + { + "author_name": "Nathan D Grubaugh", + "author_inst": "Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT 06520 USA." + }, + { + "author_name": "Charles S Dela Cruz", + "author_inst": "Department of Internal Medicine, Section of Pulmonary, Critical Care, and Sleep Medicine, New Haven, Connecticut, CT 06520 USA." + }, + { + "author_name": "Albert I Ko", + "author_inst": "Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT 06520 USA." + }, + { + "author_name": "Amalia Berna Perez", + "author_inst": "Department of Pediatrics, Division of Infectious Diseases, Perelman School of Medicine, University of Pennsylvania, Children?s Hospital of Philadelphia, Philade" + }, + { + "author_name": "Elikplim H Akaho", + "author_inst": "Department of Pediatrics, Division of Infectious Diseases, Perelman School of Medicine, University of Pennsylvania, Children?s Hospital of Philadelphia, Philade" }, { - "author_name": "Mohammed Bosaeed", - "author_inst": "King Abdullah International Medical Research Center, Riyadh, Kingdom of Saudi Arabia. King Saud bin Abdulaziz University for Health Sciences, Riyadh, Saudi Arab" + "author_name": "Dennis G Moledina", + "author_inst": "Department of Internal Medicine, Section of Nephrology and Clinical and Translational Research Accelerator, Yale School of Medicine, New Haven, Connecticut, CT " }, { - "author_name": "Omar Aldibasi", - "author_inst": "King Abdullah International Medical Research Center, Riyadh, Saudi Arabia. King Saud bin Abdulaziz University for Health Sciences, Riyadh, Saudi Arabia." + "author_name": "Jeffrey Testani", + "author_inst": "Department of Internal Medicine, Section of Cardiovascular Medicine, Yale School of Medicine, New Haven, Connecticut, CT 06520 USA." + }, + { + "author_name": "Audrey R John", + "author_inst": "Department of Pediatrics, Division of Infectious Diseases, Perelman School of Medicine, University of Pennsylvania, Children?s Hospital of Philadelphia, Philade" + }, + { + "author_name": "Michel Ledizet", + "author_inst": "L2 Diagnostics, LLC, New Haven, Connecticut, USA." + }, + { + "author_name": "Choukri Ben Mamoun", + "author_inst": "Department of Internal Medicine, Section of Infectious Diseases, Yale School of Medicine, New Haven, Connecticut, CT 06520 USA." } ], "version": "1", - "license": "cc_by", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -949718,35 +949762,47 @@ "category": "nutrition" }, { - "rel_doi": "10.1101/2021.01.28.21250547", - "rel_title": "Ownership and COVID-19 in care homes for older people: A living systematic review of outbreaks, infections, and mortalities", + "rel_doi": "10.1101/2021.01.27.21250617", + "rel_title": "More than 50 Long-term effects of COVID-19: a systematic review and meta-analysis", "rel_date": "2021-01-29", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.28.21250547", - "rel_abs": "BackgroundThe adult social care sector is increasingly outsourced to for-profit providers, who constitute the largest provider of care homes in many developed countries. During the COVID-19 pandemic, for-profit providers have been accused of failing their residents by prioritising profits over care, prevention, and caution, which has been reported to result in a higher prevalence of COVID-19 infections and deaths in for-profit care homes. Although many of these reports are anecdotal or based on news reports, there is a growing body of academic research investigating ownership variation across COVID-19 outcomes, which has not been systematically appraised and synthesised.\n\nObjectivesTo identify, appraise, and synthesise the available research on ownership variation in COVID-19 outcomes (outbreaks, infections, deaths, shortage of personal protective equipment (PPE) and staff) across for-profit, public, and non-profit care homes for older people, and to update our findings as new research becomes available.\n\nDesignLiving systematic review.\n\nMethodsThis review was prospectively registered with Prospero (CRD42020218673). We searched 17 databases and performed forward and backward citation tracking of all included studies. Search results were screened and reviewed in duplicate. Risk of bias (RoB) was assessed in duplicate according to the COSMOS-E guidance. Data was extracted by ABM and independently validated. The results were synthesised by country, RoB, and model adjustments, and visualised using harvest plots.\n\nResultsTwenty-nine studies across five countries were included, with 75% of included studies conducted in the Unites States. For-profit ownership was not consistently associated with a higher probability of a COVID-19 outbreak. However, there was compelling evidence of worse COVID-19 outcomes following an outbreak, with for-profit care homes having higher rates of accumulative infections and deaths. For-profit providers were also associated with shortages in PPE, which may have contributed to the higher incidence of infections and deaths in the early stages of the pandemic. Chain affiliation was often correlated with an increased risk of outbreak but was usually not reported to be associated with higher rates of deaths and infections.\n\nConclusionFor-profit ownership was a consistent risk factor for higher cumulative COVID-19 infections and deaths in the first wave of the pandemic. Thus, ownership and the characteristics associated with FP care home providers may present key regulatable factors that can be addressed to improve health outcomes in vulnerable populations and reduce health disparities. This review will be updated as new research becomes published, which may change the conclusion of our synthesis.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.27.21250617", + "rel_abs": "COVID-19, caused by SARS-CoV-2, can involve sequelae and other medical complications that last weeks to months after initial recovery, which has come to be called Long-COVID or COVID long-haulers. This systematic review and meta-analysis aims to identify studies assessing long-term effects of COVID-19 and estimates the prevalence of each symptom, sign, or laboratory parameter of patients at a post-COVID-19 stage. LitCOVID (PubMed and Medline) and Embase were searched by two independent researchers. All articles with original data for detecting long-term COVID-19 published before 1st of January 2021 and with a minimum of 100 patients were included. For effects reported in two or more studies, meta-analyses using a random-effects model were performed using the MetaXL software to estimate the pooled prevalence with 95% CI. Heterogeneity was assessed using I2 statistics. This systematic review followed Preferred Reporting Items for Systematic Reviewers and Meta-analysis (PRISMA) guidelines, although the study protocol was not registered. A total of 18,251 publications were identified, of which 15 met the inclusion criteria. The prevalence of 55 long-term effects was estimated, 21 meta-analyses were performed, and 47,910 patients were included. The follow-up time ranged from 14 to 110 days post-viral infection. The age of the study participants ranged between 17 and 87 years. It was estimated that 80% (95% CI 65-92) of the patients that were infected with SARS-CoV-2 developed one or more long-term symptoms. The five most common symptoms were fatigue (58%), headache (44%), attention disorder (27%), hair loss (25%), and dyspnea (24%). All meta-analyses showed medium (n=2) to high heterogeneity (n=13). In order to have a better understanding, future studies need to stratify by sex, age, previous comorbidities, severity of COVID-19 (ranging from asymptomatic to severe), and duration of each symptom. From the clinical perspective, multi-disciplinary teams are crucial to developing preventive measures, rehabilitation techniques, and clinical management strategies with whole-patient perspectives designed to address long COVID-19 care.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Anders M Bach-Mortensen", - "author_inst": "University of Oxford" + "author_name": "Sandra Lopez-Leon", + "author_inst": "Novartis Pharmaceuticals" }, { - "author_name": "Ani Movsisyan", - "author_inst": "LMU, Munich" + "author_name": "Talia Wegman-Ostrosky", + "author_inst": "Instituto Nacional de Cancerologia" }, { - "author_name": "Ben Verboom", - "author_inst": "University of Oxford" + "author_name": "Carol Perelman", + "author_inst": "National Autonomous University of Mexico" }, { - "author_name": "Michelle Degli Esposti", - "author_inst": "University of Oxford" + "author_name": "Rosalinda Sepulveda", + "author_inst": "Harvard T.H. Chan School of Public Health Boston" + }, + { + "author_name": "Paulina A Rebolledo", + "author_inst": "Emory University School of Medicine" + }, + { + "author_name": "Angelica Cuapio", + "author_inst": "Karolinska Institute" + }, + { + "author_name": "Sonia Villapol", + "author_inst": "Houston Methodist Research Institute" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "health policy" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2021.01.27.21250428", @@ -951188,55 +951244,43 @@ "category": "bioinformatics" }, { - "rel_doi": "10.1101/2021.01.29.428847", - "rel_title": "Information retrieval in an infodemic: the case of COVID-19 publications", + "rel_doi": "10.1101/2021.01.29.428808", + "rel_title": "The evolutionary making of SARS-CoV-2", "rel_date": "2021-01-29", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.01.29.428847", - "rel_abs": "The COVID-19 pandemic has led to an exponential surge and an enormous amount of published literature, both accurate and inaccurate, a term usually coined as an infodemic. In the context of searching for COVID-19 related scientific literature, we present an information retrieval methodology for effectively finding relevant publications for different information needs. Our multi-stage information retrieval architecture combines probabilistic weighting models and re-ranking algorithms based on neural masked language models. The methodology was evaluated in the context of the TREC-COVID challenge, achieving competitive results with the top ranking teams participating in the competition. Particularly, the ranking combination of bag-of-words and language models significantly outperformed a BM25-based baseline model (16 percentage points for the NDCG@20 metric), correctly retrieving more than 16 out of the top 20 documents retrieved. The proposed pipeline could thus support the effective search and discovery of relevant information in the case of an infodemic.", - "rel_num_authors": 9, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.01.29.428808", + "rel_abs": "A mechanistic understanding of how SARS-CoV-2 (sarbecovirus, betacoronavirus) infects human cells is emerging, but the evolutionary trajectory that gave rise to this pathogen is poorly understood. Here we scan SARS-CoV-2 protein sequences in-silico for innovations along the evolutionary lineage starting with the last common ancestor of coronaviruses. SARS-CoV-2 substantially differs from viruses outside sarbecovirus both in its set of encoded proteins and in their domain architectures, indicating divergent functional demands. Within sarbecoviruses, sub-domain level profiling using predicted linear epitopes reveals how the primary interface between host cell and virus, the spike, was gradually reshaped. The only epitope that is private to SARS-CoV-2 overlaps with the furin cleavage site, a \"switch\" that modulates spikes conformational landscape in response to host-cell interaction. This cleavage site has fundamental relevance for both immune evasion and cell infection, and the apparently ongoing evolutionary fine-tuning of its use by SARS-CoV-2 should be monitored.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Douglas Teodoro", - "author_inst": "HES-SO - University of Applied Sciences and Arts of Western Switzerland" + "author_name": "Ruben Iruegas L\u00f3pez", + "author_inst": "Applied Bioinformatics Group, Inst of Cell Biology and Neuroscience, Goethe University Frankfurt, Frankfurt, Germany" }, { - "author_name": "Sohrab Ferdowsi", - "author_inst": "HES-SO - University of Applied Sciences and Arts of Western Switzerland" + "author_name": "Julian Dosch", + "author_inst": "Institute of Cell Biology and Neuroscience, Goethe University Frankfurt, Frankfurt, Germany" }, { - "author_name": "Nikolay Borissov", - "author_inst": "Riskclik AG, Bern, Switzerland" - }, - { - "author_name": "Elaham Kashani", - "author_inst": "Institute of Pathology, University of Bern, Bern, Switzerland" - }, - { - "author_name": "David Vicente Alvarez", - "author_inst": "HES-SO - University of Applied Sciences and Arts of Western Switzerland" - }, - { - "author_name": "Jenny Copara", - "author_inst": "HES-SO - University of Applied Sciences and Arts of Western Switzerland" + "author_name": "Mateusz Sikora", + "author_inst": "Max-Planck-Institut fur Biophysik, Frankfurt, Germany; Faculty of Physics, University of Vienna, Vienna, Austria" }, { - "author_name": "Racha Gouareb", - "author_inst": "HES-SO - University of Applied Sciences and Arts of Western Switzerland" + "author_name": "Gerhard Hummer", + "author_inst": "Max-Planck-Institute of Biophysics, Frankfurt, Germany; Institute of Biophysics, Goethe University Frankfurt, Frankfurt, Germany" }, { - "author_name": "Nona Naderi", - "author_inst": "HES-SO University of Applied Sciences and Arts of Western Switzerland" + "author_name": "Roberto Covino", + "author_inst": "Frankfurt Institute for Advanced Studies, Frankfurt, Germany" }, { - "author_name": "Poorya Amini", - "author_inst": "Riskclik AG, Bern, Switzerland" + "author_name": "Ingo Ebersberger", + "author_inst": "Inst of Cell Biology and Neuroscience, Goethe University Frankfurt, Frankfurt, Germany; Senckenberg Biodiversity and Climate Research Centre (S-BIK-F), Frankfur" } ], "version": "1", - "license": "", + "license": "cc_by", "type": "new results", - "category": "bioinformatics" + "category": "evolutionary biology" }, { "rel_doi": "10.1101/2021.01.26.21250511", @@ -953250,75 +953294,63 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2021.01.27.427998", - "rel_title": "Neutralization of spike 69/70 deletion, E484K, and N501Y SARS-CoV-2 by BNT162b2 vaccine-elicited sera", + "rel_doi": "10.1101/2021.01.26.426655", + "rel_title": "An Updated Investigation Prior To COVID-19 Vaccination Program In Indonesia: Full-Length Genome Mutation Analysis Of SARS-CoV-2", "rel_date": "2021-01-27", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.01.27.427998", - "rel_abs": "We engineered three SARS-CoV-2 viruses containing key spike mutations from the newly emerged United Kingdom (UK) and South African (SA) variants: N501Y from UK and SA; 69/70-deletion+N501Y+D614G from UK; and E484K+N501Y+D614G from SA. Neutralization geometric mean titers (GMTs) of twenty BTN162b2 vaccine-elicited human sera against the three mutant viruses were 0.81- to 1.46-fold of the GMTs against parental virus, indicating small effects of these mutations on neutralization by sera elicited by two BNT162b2 doses.", - "rel_num_authors": 14, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.01.26.426655", + "rel_abs": "IntroductionIndonesia kick-started the big project of COVID-19 vaccination program in January 2021 by employed vaccine to the president of Indonesia. The outbreak and rapid transmission of COVID-19 have endangered the global health and economy. This study aimed to investigate the full-length genome mutation analysis of 166 Indonesian SARS-CoV-2 isolates as 12 January 2021.\n\nMethodsAll data of isolates was extracted from the Global Initiative on Sharing All Influenza Data (GISAID) EpiCoV database. CoVsurver was employed to investigate the full-length genome mutation analysis of all isolates. Furthermore, this study also focused on the unlocking of mutation in Indonesian SARS-CoV-2 isolates S protein. WIV04 isolate that was originated from Wuhan, China was used as a virus reference according to CoVsurver default. All data was visualized using GraphPad Prism software, PyMOL, and BioRender.\n\nResultsThis study result showed that a full-length genome mutation analysis of 166 Indonesian SARS-CoV-2 isolates was successfully discovered. Every single mutation in S protein was described and then visualised by employing BioRender. Furthermore, it also found that D614G mutation appeared in 103 Indonesian SARS-CoV-2 isolates.\n\nConclusionTo sum up, this study helps to observe the spread of the COVID-19 transmission. However, it would like to propose that the epidemiological surveillance and genomics studies might be improved on COVID-19 pandemic in Indonesia.", + "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Xuping Xie", - "author_inst": "University of Texas Medical Branch" - }, - { - "author_name": "Yang Liu", - "author_inst": "University of Texas Medical Branch" - }, - { - "author_name": "Jianying Liu", - "author_inst": "University of Texas Medical Branch" - }, - { - "author_name": "Xianwen Zhang", - "author_inst": "University of Texas Medical Branch" + "author_name": "Reviany V. Nidom", + "author_inst": "Coronavirus and Vaccine Formulation Research Group, Professor Nidom Foundation, Surabaya, Indonesia; Riset AIRC Indonesia, Surabaya, Indonesia." }, { - "author_name": "Jing Zou", - "author_inst": "University of Texas Medical Branch" + "author_name": "Setyarina Indrasari", + "author_inst": "Coronavirus and Vaccine Formulation Research Group, Professor Nidom Foundation, Surabaya, Indonesia; Riset AIRC Indonesia, Surabaya, Indonesia." }, { - "author_name": "Camila R. Fontes-Garfias", - "author_inst": "University of Texas Medical Branch" + "author_name": "Irine Normalina", + "author_inst": "Coronavirus and Vaccine Formulation Research Group, Professor Nidom Foundation, Surabaya, Indonesia; Riset AIRC Indonesia, Surabaya, Indonesia." }, { - "author_name": "Hongjie Xia", - "author_inst": "University of Texas Medical Branch" + "author_name": "Astria N. Nidom", + "author_inst": "Coronavirus and Vaccine Formulation Research Group, Professor Nidom Foundation, Surabaya, Indonesia." }, { - "author_name": "Kena A. Swanson", - "author_inst": "Pfizer" + "author_name": "Balqis Afifah", + "author_inst": "Coronavirus and Vaccine Formulation Research Group, Professor Nidom Foundation, Surabaya, Indonesia." }, { - "author_name": "Mark Cutler", - "author_inst": "Pfizer" + "author_name": "Lestari Dewi", + "author_inst": "Faculty of Medicine, Universitas Hang Tuah, Surabaya, Indonesia." }, { - "author_name": "David Cooper", - "author_inst": "Pfizer" + "author_name": "Andra Kusuma Putra", + "author_inst": "Dr. Ramelan Naval Hospital, Surabaya, Indonesia." }, { - "author_name": "Vineet D Menachery", - "author_inst": "University of Texas Medical Branch" + "author_name": "Arif Nur Muhammad Ansori", + "author_inst": "Coronavirus and Vaccine Formulation Research Group, Professor Nidom Foundation, Surabaya, Indonesia; Program Pendidikan Magister menuju Doktor untuk Sarjana Ung" }, { - "author_name": "Scott Weaver", - "author_inst": "University of Texas Medical Branch" + "author_name": "Muhammad Khaliim Jati Kusala", + "author_inst": "Coronavirus and Vaccine Formulation Research Group, Professor Nidom Foundation, Surabaya, Indonesia; Program Pendidikan Magister menuju Doktor untuk Sarjana Ung" }, { - "author_name": "Philip Dormitzer", - "author_inst": "Pfizer" + "author_name": "Mohammad Yusuf Alamudi", + "author_inst": "Coronavirus and Vaccine Formulation Research Group, Professor Nidom Foundation, Surabaya, Indonesia." }, { - "author_name": "Pei-Yong Shi", - "author_inst": "University of Texas Medical Branch" + "author_name": "Chairul Anwar Nidom", + "author_inst": "Coronavirus and Vaccine Formulation Research Group, Professor Nidom Foundation, Surabaya, Indonesia; Riset AIRC Indonesia, Surabaya, Indonesia; Faculty of Veter" } ], "version": "1", "license": "cc_by_nc_nd", "type": "new results", - "category": "microbiology" + "category": "molecular biology" }, { "rel_doi": "10.1101/2021.01.27.428372", @@ -954732,47 +954764,99 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.01.23.21250375", - "rel_title": "Preliminary Evidence on Long COVID in children", + "rel_doi": "10.1101/2021.01.22.21249865", + "rel_title": "Longevity of SARS-CoV-2 immune responses in haemodialysis patients and protection against reinfection", "rel_date": "2021-01-26", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.23.21250375", - "rel_abs": "There is increasing evidence that adult patients diagnosed with acute COVID-19 suffer from Long COVID initially described in Italy.\n\nTo date, data on Long COVID in children are lacking.\n\nWe assessed persistent symptoms in pediatric patients previously diagnosed with COVID-19. More than a half reported at least one persisting symptom even after 120 days since COVID-19, with 42.6% being impaired by these symptoms during daily activities. Symptoms like fatigue, muscle and joint pain, headache, insomnia, respiratory problems and palpitations were particularly frequent, as also described in adults.\n\nThe evidence that COVID-19 can have long-term impact children as well, including those with asymptomatic/paucisymptomatic COVID-19, highlight the need for pediatricians, mental health experts and policy makers of implementing measures to reduce impact of the pandemic on childs health.", - "rel_num_authors": 7, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.22.21249865", + "rel_abs": "BackgroundPatients with end stage kidney disease (ESKD) receiving in-centre haemodialysis (ICHD) have had high rates of SARS-CoV-2 infection. Following infection, ICHD patients frequently develop serological evidence of infection, even with asymptomatic disease. The aim of this study is to investigate the durability and functionality of immune responses to SARS-CoV-2 infection in ICHD patients.\n\nMethodsThree hundred and fifty-six ICHD patients were longitudinally screened for SARS-CoV-2 antibodies and underwent routine PCR-testing for symptomatic and asymptomatic infection. Patients were screened for nucleocapsid protein (anti-NP) and receptor binding domain (anti-RBD) antibodies. Patients who became seronegative at 6 months were investigated for SARS-CoV-2 specific T-cell responses.\n\nResultsOne hundred and twenty-nine (36.2%) patients had detectable antibody to anti-NP at Time 0, of which 127 (98.4%) also had detectable anti-RBD. At 6 months, of 111 patients tested, 71(64.0%) and 97 (87.4%) remained anti-NP and anti-RBD seropositive respectively, p<0.001. For patients who retained antibody, both anti-NP and anti-RBD levels reduced significantly after 6 months. Ten patients who were anti-NP and anti-RBD seropositive at Time 0, had no detectable antibody at 6 months; of which 8 were found to have SARS-CoV-2 antigen specific T cell responses.\n\nIndependent of antibody status at 6 months, patients with baseline positive SARS-CoV-2 serology were significantly less likely to have PCR confirmed infection over the following 6 months.\n\nConclusionsICHD patients mount durable immune responses 6 months post SARS-CoV-2 infection, with <3% of patients showing no evidence of humoral or cellular immunity. These immune responses are associated with a reduced risk of subsequent reinfection.\n\nSIGNIFICANCE STATEMENTFollowing infection with SARS-CoV-2, patients with end stage kidney disease (ESKD) frequently develop serological evidence of infection, even with asymptomatic disease. Patients with ESKD receiving in-centre haemodialysis (ICHD) have had high rates of SARS-CoV-2 infection. What is not known is how durable the serological responses in ESKD patients are or whether evidence of prior immune responses protect patients from reinfection. In this study of 356 ICHD patients, at 6 months following the detection of SARS-CoV-2 antibodies, fewer than 3% of patients lacked evidence of either humoral or cellular immunity. Furthermore, patients with serological evidence of infection had a significantly lower risk of being diagnosed with subsequent infection or reinfection, suggesting functional immune protection.", + "rel_num_authors": 20, "rel_authors": [ { - "author_name": "danilo buonsenso", - "author_inst": "Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy" + "author_name": "Candice L Clarke", + "author_inst": "Imperial College London" }, { - "author_name": "Daniel Munblit", - "author_inst": "Department of Paediatrics and Paediatric Infectious Diseases, Institute of Child's Health, Sechenov First Moscow State Medical University (Sechenov University)," + "author_name": "Maria Prendecki", + "author_inst": "Imperial College London" }, { - "author_name": "Cristina De Rose", - "author_inst": "Department of Woman and Child Health and Public Health, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy" + "author_name": "Amrita Dhutia", + "author_inst": "Imperial College Healthcare NHS Trust" }, { - "author_name": "Dario Sinatti", - "author_inst": "Department of Woman and Child Health and Public Health, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy" + "author_name": "Claire Edwards", + "author_inst": "Imperial College Healthcare NHS Trust" }, { - "author_name": "Antonia Ricchiuto", - "author_inst": "Department of Woman and Child Health and Public Health, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy" + "author_name": "Virginia Prout", + "author_inst": "Imperial College Healthcare NHS Trust" }, { - "author_name": "Angelo Carfi", - "author_inst": "Geriatric Department, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy" + "author_name": "Liz Lightstone", + "author_inst": "Imperial College London" }, { - "author_name": "Piero Valentini", - "author_inst": "Department of Woman and Child Health and Public Health, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy" + "author_name": "Eleanor Parker", + "author_inst": "Imperial College London" + }, + { + "author_name": "Federica Marchesin", + "author_inst": "Imperial College London" + }, + { + "author_name": "Megan Griffith", + "author_inst": "Imperial College Healthcare NHS Trust" + }, + { + "author_name": "Rawya Charif", + "author_inst": "Imperial College Healthcare NHS Trust" + }, + { + "author_name": "Graham Pickard", + "author_inst": "Department of Infection and Immunity North West London Pathology NHS Trust" + }, + { + "author_name": "Alison Cox", + "author_inst": "Department of Infection and Immunity North West London Pathology NHS Trust" + }, + { + "author_name": "Myra McClure", + "author_inst": "Imperial College London" + }, + { + "author_name": "Richard Tedder", + "author_inst": "Imperial College London" + }, + { + "author_name": "Paul Randell", + "author_inst": "Department of Infection and Immunity North West London Pathology NHS Trust" + }, + { + "author_name": "Louise Greathead", + "author_inst": "Department of Infection and Immunity North West London Pathology NHS Trust" + }, + { + "author_name": "Mary Guckian", + "author_inst": "Department of Infection and Immunity North West London Pathology NHS Trust" + }, + { + "author_name": "Stephen P McAdoo", + "author_inst": "Imperial College London" + }, + { + "author_name": "Peter Kelleher", + "author_inst": "Immunology of Infection Group, Department of Infectious Diseases, Imperial College London" + }, + { + "author_name": "Michelle Willicombe", + "author_inst": "Imperial College London" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "pediatrics" + "category": "nephrology" }, { "rel_doi": "10.1101/2021.01.23.21250164", @@ -956850,21 +956934,25 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.01.26.21249544", - "rel_title": "COVID-19 Test Positivity Rate as a marker for hospital overload", + "rel_doi": "10.1101/2021.01.23.21250242", + "rel_title": "Super-Spreaders Out, Super-Spreading In: The Effects of Infectiousness Heterogeneity and Lockdowns on Herd Immunity", "rel_date": "2021-01-26", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.26.21249544", - "rel_abs": "The use of antigen tests for the diagnosis of COVID-19 in Italy has risen sharply in autumn 2020. Although, Italian regions like Alto Adige, Veneto, Toscana, Lazio, Piemonte and Marche did a large use of these tests for screening and surveillance purposes or for implementing diagnosis protocols, in addition to molecular tests, they were not reported in the statistics in the last months of 2020. As a consequence of this situation the test positivity rate (TPR) index, defined as the number of new positive cases divided by the number of tests, has lost in accuracy. Only in the recent days, starting from the 15th of January 2021, antigen tests have become part of the statistics for all the Italian regions. Despite the lack of data, we have noticed that TPR has a strong correlation with the number of patients admitted in hospitals, and that TPR peaks in general precede the peaks of hospitalized people which occur on average about 15 days later.\n\nIn this paper, we have deepened this intuition, analysing the TPR course and its relationship with the number of hospitalized people. To conduct the study we have defined a novel version of the TPR index which takes into account the number of tests done with respect to the population (considering both molecular and antigen tests), the number of infected individuals, and the number of patients healed. Successively, starting from a limited set of data which were made available in November 2020, we have reconstructed the antigen tests time series of four Italian regions, and we computed the TPR index for them.\n\nThe results show that TPR peaks precede peaks of hospitalized people in both the first and the second phases of the pandemic in Italy, provided that antigen tests are considered. Moreover, the TPR index trend, can be used to deduct important information on the course of the epidemic, and on the impact of COVID-19 in the health care system, which can be monitored in advance.", - "rel_num_authors": 1, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.23.21250242", + "rel_abs": "Recently, [8] has proposed that heterogeneity of infectiousness (and susceptibility) across individuals in infectious diseases, plays a major role in affecting the Herd Immunity Thresh-old (HIT). Such heterogeneity has been observed in COVID-19 and is recognized as overdis-persion (or \"super-spreading\"). The model of [8] suggests that super-spreaders contribute significantly to the effective reproduction factor, R, and that they are likely to get infected and immune early in the process. Consequently, under R0 {approx} 3 (attributed to COVID-19), the Herd Immunity Threshold (HIT) is as low as 5%, in contrast to 67% according to the traditional models [1, 2, 4, 10].\n\nThis work follows up on [8] and proposes that heterogeneity of infectiousness (susceptibility) has two \"faces\" whose mix affects dramatically the HIT: (1) Personal-Trait-, and (2) Event-Based-Infectiousness (Susceptibility). The former is a personal trait of specific individuals (super-spreaders) and is nullified once those individuals are immune (as in [8]). The latter is event-based (e.g cultural super-spreading events) and remains effective throughout the process, even after the super-spreaders immune. We extend [8]s model to account for these two factors, analyze it and conclude that the HIT is very sensitive to the mix between (1) and (2), and under R0 {approx} 3 it can vary between 5% and 67%. Preliminary data from COVID-19 suggests that herd immunity is not reached at 5%.\n\nWe address operational aspects and analyze the effects of lockdown strategies on the spread of a disease. We find that herd immunity (and HIT) is very sensitive to the lock-down type. While some lockdowns affect positively the disease blocking and increase herd immunity, others have adverse effects and reduce the herd immunity.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Mauro Gaspari", - "author_inst": "University of Bologna" + "author_name": "Jhonatan Tavori", + "author_inst": "Tel Aviv University" + }, + { + "author_name": "Hanoch Levy", + "author_inst": "Tel Aviv University" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -958516,43 +958604,111 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2021.01.20.21250145", - "rel_title": "Impact of COVID-19 Pandemic on Inpatient Rehabilitation and the Original Infection Control Measures for Rehabilitation Team", + "rel_doi": "10.1101/2021.01.21.21249764", + "rel_title": "Pervasive transmission of E484K and emergence of VUI-NP13L with evidence of SARS-CoV-2 co-infection events by two different lineages in Rio Grande do Sul, Brazil", "rel_date": "2021-01-26", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.20.21250145", - "rel_abs": "ObjectiveThis study aimed to investigate the impact of the coronavirus disease 2019 (COVID-19) pandemic on inpatient rehabilitation, and to determine the effectiveness of the original infection control measures implemented for the rehabilitation team.\n\nMethodsIn this single-center, retrospective, observational study, we calculated multiple rehabilitation indices of patients discharged from our rehabilitation ward between February 28 and May 25, 2020 when Hokkaido was initially affected by COVID-19, and compared them with those calculated during the same period in 2019. Fishers exact test and the Mann-Whitney U test were used for statistical analysis. We also verified the impact of implementing the original infection control measures for the rehabilitation team on preventing nosocomial infections.\n\nResultsA total of 93 patients (47 of 2020 group, 46 of 2019 group) were included. The median age was 87 and 88 years, respectively, with no differences in age, sex, and main disease between the groups. Training time per day in the ward in 2020 was significantly lower than that in 2019 (p = 0.013). No significant differences were found in the qualitative evaluation indices of Functional Independence Measure (FIM) score at admission, FIM gain, length of ward stay, FIM efficiency, and rate of discharge to home. None of the patients or staff members had confirmed COVID-19 during the study period.\n\nConclusionsEarly COVID-19 pandemic in Hokkaido affected the quantitative index for inpatient rehabilitation but not the qualitative indices. No symptomatic nosocomial COVID-19 infections were observed with our infection control measures.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.21.21249764", + "rel_abs": "Emergence of novel SARS-CoV-2 lineages are under the spotlight of the media, scientific community and governments. Recent reports of novel variants in the United Kingdom, South Africa and Brazil (B.1.1.28-E484K) have raised intense interest because of a possible higher transmission rate or resistance to the novel vaccines. Nevertheless, the spread of B.1.1.28 (E484K) and other variants in Brazil is still unknown. In this work, we investigated the population structure and genomic complexity of SARS-CoV-2 in Rio Grande do Sul, the southernmost state in Brazil. Most samples sequenced belonged to the B.1.1.28 (E484K) lineage, demonstrating its widespread dispersion. We were the first to identify two independent events of co-infection caused by the occurrence of B.1.1.28 (E484K) with either B.1.1.248 or B.1.91 lineages. Also, clustering analysis revealed the occurrence of a novel cluster of samples circulating in the state (named VUI-NP13L) characterized by 12 lineage-defining mutations. In light of the evidence for E484K dispersion, co-infection and emergence of VUI-NP13L in Rio Grande do Sul, we reaffirm the importance of establishing strict and effective social distancing measures to counter the spread of potentially more hazardous SARS-CoV-2 strains.\n\nHighlightsO_LIThe novel variant B.1.1.28 (E484K) previously described in Rio de Janeiro is currently spread across the southernmost state of Brazil;\nC_LIO_LIThe novel variant VUI-NP13L was also identified by causing a local outbreak in Rio Grande do Sul;\nC_LIO_LIB.1.1.28 (E484K) is able to establish successful coinfection events co-occurring simultaneously with different lineages of SARS-CoV-2.\nC_LI", + "rel_num_authors": 23, "rel_authors": [ { - "author_name": "Yukimasa Igawa", - "author_inst": "Aizen hospital" + "author_name": "Ronaldo da Silva Francisco Junior", + "author_inst": "Laboratorio Nacional de Computacao Cientifica" + }, + { + "author_name": "L. Felipe Benites", + "author_inst": "Laboratorio de Microbiologia Molecular, Universidade Feevale" + }, + { + "author_name": "Alessandra P Lamarca", + "author_inst": "Laboratorio Nacional de Computacao Cientifica" + }, + { + "author_name": "Luiz Gonzaga P de Almeida", + "author_inst": "Laboratorio Nacional de Computacao Cientifica" + }, + { + "author_name": "Alana Witt Hansen", + "author_inst": "Laboratorio de Microbiologia Molecular, Universidade Feevale" + }, + { + "author_name": "Juliana Schons Gularte", + "author_inst": "Laboratorio de Microbiologia Molecular, Universidade Feevale" + }, + { + "author_name": "Meriane Demoliner", + "author_inst": "Laboratorio de Microbiologia Molecular, Universidade Feevale" + }, + { + "author_name": "Alexandra L Gerber", + "author_inst": "Laboratorio Nacional de Computacao Cientifica" + }, + { + "author_name": "Ana Paula de C Guimaraes", + "author_inst": "Laboratorio Nacional de Computacao Cientifica" + }, + { + "author_name": "Ana Karolina Eisen Antunes", + "author_inst": "Laboratorio de Microbiologia Molecular, Universidade Feevale" + }, + { + "author_name": "Fagner Henrique Heldt", + "author_inst": "Laboratorio de Microbiologia Molecular, Universidade Feevale" + }, + { + "author_name": "Larissa Mallmann", + "author_inst": "Laboratorio de Microbiologia Molecular, Universidade Feevale" + }, + { + "author_name": "Bruna Hermann", + "author_inst": "Laboratorio de Microbiologia Molecular, Universidade Feevale" }, { - "author_name": "Takahiro Sugimoto", - "author_inst": "Aizen hospital" + "author_name": "Ana Luiza Ziulkosk", + "author_inst": "Laboratorio de Microbiologia Molecular, Universidade Feevale" }, { - "author_name": "Hiromasa Horimoto", - "author_inst": "Aizen hospital" + "author_name": "Vyctoria Goes", + "author_inst": "Laboratorio de Microbiologia Molecular, Universidade Feevale" }, { - "author_name": "Yusuke Moriya", - "author_inst": "Aizen hospital" + "author_name": "Karoline Schallenberger", + "author_inst": "Laboratorio de Microbiologia Molecular, Universidade Feevale" + }, + { + "author_name": "Micheli Fillipi", + "author_inst": "Laboratorio de Microbiologia Molecular, Universidade Feevale" + }, + { + "author_name": "Francini Pereira", + "author_inst": "Laboratorio de Microbiologia Molecular, Universidade Feevale" + }, + { + "author_name": "Matheus Nunes Weber", + "author_inst": "Laboratorio de Microbiologia Molecular, Universidade Feevale" + }, + { + "author_name": "Paula Rodrigues de Almeida", + "author_inst": "Laboratorio de Microbiologia Molecular, Universidade Feevale" + }, + { + "author_name": "Juliane Deise Fleck", + "author_inst": "Laboratorio de Microbiologia Molecular, Universidade Feevale" }, { - "author_name": "Masaki Okada", - "author_inst": "Aizen hospital" + "author_name": "Ana Tereza Ribeiro de Vasconcelos", + "author_inst": "Laboratorio Nacional de Computacacao Cientifica" }, { - "author_name": "Yasuyuki Yamada", - "author_inst": "Aizen hospital" + "author_name": "Fernando Rosado Spilki", + "author_inst": "Laboratorio de Microbiologia Molecular, Universidade Feevale" } ], "version": "1", - "license": "cc_by", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "rehabilitation medicine and physical therapy" + "category": "genetic and genomic medicine" }, { "rel_doi": "10.1101/2021.01.25.427948", @@ -960458,31 +960614,131 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.01.21.21250045", - "rel_title": "Mental health and wellbeing amongst people with informal caring responsibilities across different time points during the COVID-19 pandemic: A population-based propensity score matching analysis", + "rel_doi": "10.1101/2021.01.22.21250320", + "rel_title": "High-throughput sequencing of SARS-CoV-2 in wastewater provides insights into circulating variants", "rel_date": "2021-01-25", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.21.21250045", - "rel_abs": "AimsDue to a prolonged period of national and regional lockdown measures during the coronavirus (COVID-19) pandemic, there has been an increase reliance on informal care and a consequent increase in care intensity for informal carers. In light of this, the current study compared the experiences of carers and non-carers on various mental health and wellbeing measures across 5 key time points during the pandemic.\n\nMethodsData analysed were from the UCL COVID -19 Social Study. Our study focused on 5 time points in England: (i) the first national lockdown (March-April 2020; N=12,053); (ii) the beginning of lockdown rules easing (May 2020; N=24,374); (iii) further easing (July 2020; N=21,395); (iv) new COVID-19 restrictions (September 2020; N=4,792); and (v) the three-tier system restrictions (October 2020; N=4,526). We considered 5 mental health and wellbeing measures-depression, anxiety, loneliness, life satisfaction and sense of worthwhile. Propensity score matching were applied for the analyses.\n\nResultsWe found that informal carers experienced higher levels of depressive symptoms and anxiety than non-carers across all time points. During the first national lockdown, carers also experienced a higher sense of life being worthwhile. No association was found between informal caring responsibilities and levels of loneliness and life satisfaction.\n\nConclusionGiven that carers are an essential national health care support, especially during a pandemic, it is crucial to integrate carers needs into healthcare planning and delivery. These results highlight there is a pressing need to provide adequate and targeted mental health support for carers during and following this pandemic.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.22.21250320", + "rel_abs": "Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged from a zoonotic spill-over event and has led to a global pandemic. The public health response has been predominantly informed by surveillance of symptomatic individuals and contact tracing, with quarantine, and other preventive measures have then been applied to mitigate further spread. Non-traditional methods of surveillance such as genomic epidemiology and wastewater-based epidemiology (WBE) have also been leveraged during this pandemic. Genomic epidemiology uses high-throughput sequencing of SARS-CoV-2 genomes to inform local and international transmission events, as well as the diversity of circulating variants. WBE uses wastewater to analyse community spread, as it is known that SARS-CoV-2 is shed through bodily excretions. Since both symptomatic and asymptomatic individuals contribute to wastewater inputs, we hypothesized that the resultant pooled sample of population-wide excreta can provide a more comprehensive picture of SARS-CoV-2 genomic diversity circulating in a community than clinical testing and sequencing alone. In this study, we analysed 91 wastewater samples from 11 states in the USA, where the majority of samples represent Maricopa County, Arizona (USA). With the objective of assessing the viral diversity at a population scale, we undertook a single-nucleotide variant (SNV) analysis on data from 52 samples with >90% SARS-CoV-2 genome coverage of sequence reads, and compared these SNVs with those detected in genomes sequenced from clinical patients. We identified 7973 SNVs, of which 5680 were \"novel\" SNVs that had not yet been identified in the global clinical-derived data as of 17th June 2020 (the day after our last wastewater sampling date). However, between 17th of June 2020 and 20th November 2020, almost half of the SNVs have since been detected in clinical-derived data. Using the combination of SNVs present in each sample, we identified the more probable lineages present in that sample and compared them to lineages observed in North America prior to our sampling dates. The wastewater-derived SARS-CoV-2 sequence data indicates there were more lineages circulating across the sampled communities than represented in the clinical-derived data. Principal coordinate analyses identified patterns in population structure based on genetic variation within the sequenced samples, with clear trends associated with increased diversity likely due to a higher number of infected individuals relative to the sampling dates. We demonstrate that genetic correlation analysis combined with SNVs analysis using wastewater sampling can provide a comprehensive snapshot of the SARS-CoV-2 genetic population structure circulating within a community, which might not be observed if relying solely on clinical cases.", + "rel_num_authors": 28, "rel_authors": [ { - "author_name": "Hei Wan Mak", - "author_inst": "University College London" + "author_name": "Rafaela S. Fontenele", + "author_inst": "Arizona State University" }, { - "author_name": "Feifei Bu", - "author_inst": "University College London" + "author_name": "Simona Kraberger", + "author_inst": "Arizona State University" }, { - "author_name": "Daisy Fancourt", - "author_inst": "University College London" + "author_name": "James Hadfield", + "author_inst": "Fred Hutchinson Cancer Research Center" + }, + { + "author_name": "Erin M. Driver", + "author_inst": "Arizona State University" + }, + { + "author_name": "Devin Bowes", + "author_inst": "Arizona State University" + }, + { + "author_name": "LaRinda A. Holland", + "author_inst": "Arizona State University" + }, + { + "author_name": "Temitope O.C. Faleye", + "author_inst": "Arizona State University" + }, + { + "author_name": "Sangeet Adhikari", + "author_inst": "Arizona State University" + }, + { + "author_name": "Rahul Kumar", + "author_inst": "Arizona State University" + }, + { + "author_name": "Rosa Inchausti", + "author_inst": "City of Tempe" + }, + { + "author_name": "Wydale K. Holmes", + "author_inst": "City of Tempe" + }, + { + "author_name": "Stephanie Deitrick", + "author_inst": "City of Tempe" + }, + { + "author_name": "Philip Brown", + "author_inst": "City of Tempe" + }, + { + "author_name": "Darrell Duty", + "author_inst": "City of Tempe" + }, + { + "author_name": "Ted Smith", + "author_inst": "University of Louisville" + }, + { + "author_name": "Aruni Bhatnagar", + "author_inst": "University of Louisville" + }, + { + "author_name": "Ray A. Yeager II", + "author_inst": "University of Louisville" + }, + { + "author_name": "Rochelle H. Holm", + "author_inst": "University of Louisville" + }, + { + "author_name": "Natalia Hoogesteijn von Reitzenstein", + "author_inst": "Jacobs Engineering Group Inc." + }, + { + "author_name": "Elliott Wheeler", + "author_inst": "Jacobs Engineering Group Inc." + }, + { + "author_name": "Kevin Dixon", + "author_inst": "Jacobs Engineering Group Inc." + }, + { + "author_name": "Tim Constantine", + "author_inst": "Jacobs Engineering Group Inc." + }, + { + "author_name": "Melissa A. Wilson", + "author_inst": "Arizona State University" + }, + { + "author_name": "Efrem S. Lim", + "author_inst": "Arizona State University" + }, + { + "author_name": "Xiaofang Jiang", + "author_inst": "National Institute of Health" + }, + { + "author_name": "Rolf U. Halden", + "author_inst": "Arizona State University" + }, + { + "author_name": "Matthew Scotch", + "author_inst": "Arizona State University" + }, + { + "author_name": "Arvind Varsani", + "author_inst": "Arizona State University" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc0", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2021.01.25.428042", @@ -961976,51 +962232,31 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.01.20.21249905", - "rel_title": "A cross-sectional analysis of demographic and behavioral risk factors of SARS-CoV-2 antibody positivity among a sample of U.S. college students", + "rel_doi": "10.1101/2021.01.21.21250228", + "rel_title": "Simulating the impact of different vaccination policies on the COVID-19 pandemic in New York City", "rel_date": "2021-01-22", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.20.21249905", - "rel_abs": "BackgroundColleges and universities across the United States are developing and implementing data-driven prevention and containment measures against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Identifying risk factors for SARS-CoV-2 seropositivity could help to direct these efforts.\n\nObjectiveTo estimate the associations between demographic factors and social behaviors and SARS-CoV-2 seropositivity and self-reported positive SARS-CoV-2 diagnostic test.\n\nMethodsIn September 2020, we randomly sampled Indiana University Bloomington (IUB) undergraduate students. Participants completed a cross-sectional, online survey about demographics, SARS-CoV-2 testing history, relationship status, and risk behaviors. Additionally, during a subsequent appointment, participants were tested for SARS-CoV-2 antibodies using a fingerstick procedure and SARS-CoV-2 IgM/IgG rapid assay kit. We used unadjusted modified Poisson regression models to evaluate the associations between predictors of both SARS-CoV-2 seropositivity and self-reported positive SARS-CoV-2 infection history.\n\nResultsOverall, 1,076 students were included in the serological testing analysis, and 1,239 students were included in the SARS-CoV-2 infection history analysis. Current seroprevalence of SARS-CoV-2 was 4.6% (95% CI: 3.3%, 5.8%). Prevalence of self-reported SARS-CoV-2 infection history was 10.3% (95% CI: 8.6%, 12.0%). Greek membership, having multiple romantic partners, knowing someone in ones immediate environment with SARS-CoV-2 infection, drinking alcohol more than 1 day per week, and hanging out with more than 4 people when drinking alcohol increased both the likelihood of seropositivity and SARS-CoV-2 infection history.\n\nConclusionOur findings have implications for American colleges and universities and could be used to inform SARS-C0V-2 prevention and control strategies on such campuses.", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.21.21250228", + "rel_abs": "PurposeTo analyze potential COVID-19 epidemic outcomes in New York City under different SARS-CoV-2 virus circulation scenarios and vaccine rollout policies from early Jan 2021 to end of June 2021.\n\nKey findingsIn anticipation of the potential arrival and dominance of the more infectious SARS-CoV-2 variant:\n\nO_LIMass-vaccination would be critical to mitigating epidemic severity (26-52% reduction in infections, hospitalizations, and deaths, compared to no vaccination, provided the new UK variant supplants currently circulating variants).\nC_LIO_LIPrioritizing key risk groups for earlier vaccination would lead to greater reductions in hospitalizations and deaths than infections. Thus, in general this would be a good strategy.\nC_LIO_LICurrent vaccination prioritization policy is suboptimal. To avert more hospitalizations and deaths, mass-vaccination of all individuals 65 years or older should be done as soon as possible. For groups listed in the same phase, 65+ year-olds should be given first priority ahead of others.\nC_LIO_LIAvailable vaccine doses should be given to the next priority groups as soon as possible without awaiting hesitant up-stream groups.\nC_LIO_LIWhile efficacy of vaccination off-protocol is unknown, provided immune response following a first vaccine dose persists, delaying the 2nd vaccine dose by [~]1 month (i.e. administer the two doses 8 weeks apart) can substantially reduce infections, hospitalizations, and deaths compared to the 3-week apart regimen. Across all scenarios tested here, delaying the 2nd vaccine dose leads to the largest reduction in severe epidemic outcomes (e.g. hospitalizations and deaths). Therefore, to protect as many people as possible, this strategy should be considered if rapid increases in infections, hospitalization or deaths and/or shortages in vaccines were to occur.\nC_LI", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Sina Kianersi", - "author_inst": "Indiana University School of Public Health-Bloomington" - }, - { - "author_name": "Christina Ludema", - "author_inst": "Indiana University School of Public Health-Bloomington" - }, - { - "author_name": "Jonathan T. Macy", - "author_inst": "Indiana University School of Public Health-Bloomington" - }, - { - "author_name": "Edlin Garcia", - "author_inst": "Indiana University School of Public Health-Bloomington" - }, - { - "author_name": "Chen Chen", - "author_inst": "Indiana University School of Public Health-Bloomington" - }, - { - "author_name": "Maya Luetke", - "author_inst": "Indiana University School of Public Health-Bloomington" + "author_name": "Wan Yang", + "author_inst": "Columbia University" }, { - "author_name": "Mason H. Lown", - "author_inst": "Indiana University School of Public Health-Bloomington" + "author_name": "Sasikiran Kandula", + "author_inst": "Columbia University" }, { - "author_name": "Molly Rosenberg", - "author_inst": "Indiana University School of Public Health-Bloomington" + "author_name": "Jeffrey Shaman", + "author_inst": "Columbia University" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "public and global health" }, { "rel_doi": "10.1101/2021.01.21.21250266", @@ -963642,91 +963878,59 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2021.01.21.427657", - "rel_title": "High-throughput screening of the ReFRAME, Pandemic Box, and COVID Box drug repurposing libraries against SARS-CoV2 nsp15 endoribonuclease to identify small-molecule inhibitors of viral activity.", + "rel_doi": "10.1101/2021.01.20.427043", + "rel_title": "Design of Specific Primer Sets for the Detection of B.1.1.7, B.1.351 and P.1 SARS-CoV-2 Variants using Deep Learning", "rel_date": "2021-01-21", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.01.21.427657", - "rel_abs": "SARS-CoV-2 has caused a global pandemic, and has taken over 1.7 million lives as of mid-December, 2020. Although great progress has been made in the development of effective countermeasures, with several pharmaceutical companies approved or poised to deliver vaccines to market, there is still an unmet need of essential antiviral drugs with therapeutic impact for the treatment of moderate-to-severe COVID-19. Towards this goal, a high-throughput assay was used to screen SARS-CoV-2 nsp15 uracil-dependent endonuclease (endoU) function against 13 thousand compounds from drug and lead repurposing compound libraries. While over 80% of initial hit compounds were pan-assay inhibitory compounds, three hits were confirmed as nsp15 endoU inhibitors in the 1-20 M range in vitro. Furthermore, Exebryl-1, a {beta}-amyloid anti-aggregation molecule for Alzheimers therapy, was shown to have antiviral activity between 10 to 66 M, in VERO, Caco-2, and Calu-3 cells. Although the inhibitory concentrations determined for Exebryl-1 exceed those recommended for therapeutic intervention, our findings show great promise for further optimization of Exebryl-1 as an nsp15 endoU inhibitor and as a SARS-CoV-2 antiviral.\n\nAuthor summaryDrugs to treat COVID-19 are urgently needed. To address this, we searched libraries of drugs and drug-like molecules for inhibitors of an essential enzyme of the virus that causes COVID-19, SARS-CoV-2 nonstructural protein (nsp)15. We found several molecules that inhibited the nsp15 enzyme function and one was shown to be active in inhibiting the SARS-CoV-2 virus. This demonstrates that searching for SARS-CoV-2 nsp15 inhibitors can lead inhibitors of SARS-CoV-2, and thus therapeutics for COVID-19. We are currently working to see if these inhibitors could be turned into a drug to treat COVID-19.", - "rel_num_authors": 18, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.01.20.427043", + "rel_abs": "As the COVID-19 pandemic continues, new SARS-CoV-2 variants with potentially dangerous features have been identified by the scientific community. Variant B.1.1.7 lineage clade GR from Global Initiative on Sharing All Influenza Data (GISAID) was first detected in the UK, and it appears to possess an increased transmissibility. At the same time, South African authorities reported variant B.1.351, that shares several mutations with B.1.1.7, and might also present high transmissibility. Earlier this year, a variant labelled P.1 with 17 non-synonymous mutations was detected in Brazil. Recently the World Health Organization has raised concern for the variants B.1.617.2 mainly detected in India but now exported worldwide. It is paramount to rapidly develop specific molecular tests to uniquely identify new variants. Using a completely automated pipeline built around deep learning and evolutionary algorithms techniques, we designed primer sets specific to variants B.1.1.7, B.1.351, P.1 and respectively. Starting from sequences openly available in the GISAID repository, our pipeline was able to deliver the primer sets for each variant. In-silico tests show that the sequences in the primer sets present high accuracy and are based on 2 mutations or more. In addition, we present an analysis of key mutations for SARS-CoV-2 variants. Finally, we tested the designed primers for B.1.1.7 using RT-PCR. The presented methodology can be exploited to swiftly obtain primer sets for each new variant, that can later be a part of a multiplexed approach for the initial diagnosis of COVID-19 patients.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Ryan Choi", - "author_inst": "Center for Emerging and Reemerging Infectious Diseases (CERID), University of Washington" - }, - { - "author_name": "Mowei Zhou", - "author_inst": "Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory (PNNL)" - }, - { - "author_name": "Roger Shek", - "author_inst": "Center for Emerging and Reemerging Infectious Diseases (CERID), University of Washington" - }, - { - "author_name": "Jesse W Wilson", - "author_inst": "Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory (PNNL)" - }, - { - "author_name": "Logan Tillery", - "author_inst": "Center for Emerging and Reemerging Infectious Diseases (CERID), University of Washington" - }, - { - "author_name": "Justin K Craig", - "author_inst": "Center for Emerging and Reemerging Infectious Diseases (CERID), University of Washington" - }, - { - "author_name": "Indraneel A Salukhe", - "author_inst": "Department of Microbiology, University of Washington" - }, - { - "author_name": "Sarah E Hickson", - "author_inst": "Department of Microbiology, University of Washington" - }, - { - "author_name": "Neeraj Kumar", - "author_inst": "Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory (PNNL)" + "author_name": "Carmina Perez-Romero", + "author_inst": "Departamento de Investigacion, Universidad Central de Queretaro (UNICEQ), Av. 5 de Febrero 1602, San Pablo, 76130 Santiago de Queretaro, Qro., Mexico" }, { - "author_name": "Rhema M James", - "author_inst": "Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory (PNNL)" + "author_name": "Alberto Tonda", + "author_inst": "UMR 518 MIA-Paris, INRAE, c/o 113 rue Nationale, 75103, Paris, France" }, { - "author_name": "Garry W Buchko", - "author_inst": "Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory (PNNL), School of Molecular Bioscience, Washington State University" + "author_name": "Lucero Mendoza-Maldonado", + "author_inst": "Hospital Civil de Guadalajara \"Dr. Juan I. Menchaca\". Salvador Quevedo y Zubieta 750, Independencia Oriente, C.P. 44340 Guadalajara, Jalisco, Mexico" }, { - "author_name": "Ruilian Wu", - "author_inst": "Bioenergy and Biome Sciences, Los Alamos National Laboratory (LANL)" + "author_name": "Etienne Coz", + "author_inst": "Institut Pasteur" }, { - "author_name": "Sydney Huff", - "author_inst": "Center for Emerging and Reemerging Infectious Diseases (CERID), University of Washington" + "author_name": "Patrick Tabeling", + "author_inst": "Institut Pasteur" }, { - "author_name": "Tu-Trinh Nguyen", - "author_inst": "Calibr, a division of The Scripps Research Institute" + "author_name": "Jessica Vanhomwegen", + "author_inst": "Institut Pasteur" }, { - "author_name": "Brett L Hurst", - "author_inst": "Institute for Antiviral Research, Utah State University" + "author_name": "Eric Claassen", + "author_inst": "Athena Institute, Vrije Universiteit, De Boelelaan 1085, 1081 HV Amsterdam, the Netherlands" }, { - "author_name": "Sara Cherry", - "author_inst": "Department of Pathology and Laboratory Medicine, University of Pennsylvania" + "author_name": "Johan Garssen", + "author_inst": "Department Immunology, Danone Nutricia research, Uppsalalaan 12, 3584 CT Utrecht, the Netherlands. Division of Pharmacology, Utrecht Institute for Pharmaceutica" }, { - "author_name": "Lynn K Barrett", - "author_inst": "Center for Emerging and Reemerging Infectious Diseases (CERID), University of Washington" + "author_name": "Aletta D Kraneveld", + "author_inst": "Division of Pharmacology, Utrecht Institute for Pharmaceutical Sciences, Faculty of Science, Utrecht University, Universiteitsweg 99, 3584 CG Utrecht, the Nethe" }, { - "author_name": "Wesley C Van Voorhis", - "author_inst": "Center for Emerging and Reemerging Infectious Diseases (CERID), University of Washington" + "author_name": "Alejandro Lopez-Rincon", + "author_inst": "Division of Pharmacology, Utrecht Institute for Pharmaceutical Sciences, Faculty of Science, Utrecht University, Universiteitsweg 99, 3584 CG Utrecht, the Nethe" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by_nc", "type": "new results", - "category": "microbiology" + "category": "bioinformatics" }, { "rel_doi": "10.1101/2021.01.21.427676", @@ -964988,105 +965192,125 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.01.18.21250044", - "rel_title": "Blood transcriptional biomarkers of acute viral infection for detection of pre-symptomatic SARS-CoV 2 infection", + "rel_doi": "10.1101/2021.01.15.21249756", + "rel_title": "Factors associated with deaths due to COVID-19 versus other causes: population-based cohort analysis of UK primary care data and linked national death registrations within the OpenSAFELY platform", "rel_date": "2021-01-20", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.18.21250044", - "rel_abs": "We hypothesised that host-response biomarkers of viral infections may contribute to early identification of SARS-CoV-2 infected individuals, critical to breaking chains of transmission. We identified 20 candidate blood transcriptomic signatures of viral infection by systematic review and evaluated their ability to detect SARS-CoV-2 infection, compared to the gold-standard of virus PCR tests, among a prospective cohort of 400 hospital staff subjected to weekly testing when fit to attend work. The transcriptional signatures had limited overlap, but were mostly co-correlated as components of type 1 interferon responses. We reconstructed each signature score in blood RNA sequencing data from 41 individuals over sequential weeks spanning a first positive SARS-CoV-2 PCR, and after 6-month convalescence. A single blood transcript for IFI27 provided the highest accuracy for discriminating individuals at the time of their first positive viral PCR result from uninfected controls, with area under the receiver operating characteristic curve (AUROC) of 0.95 (95% confidence interval 0.91-0.99), sensitivity 0.84 (0.7-0.93) and specificity 0.95 (0.85-0.98) at a predefined test threshold. The test performed equally well in individuals with and without symptoms, correlated with viral load, and identified incident infections one week before the first positive viral PCR with sensitivity 0.4 (0.17-0.69) and specificity 0.95 (0.85-0.98). Our findings strongly support further urgent evaluation and development of blood IFI27 transcripts as a biomarker for early phase SARS-CoV-2 infection, for screening individuals such as contacts of index cases, in order to facilitate early case isolation and early antiviral treatments as they emerge.", - "rel_num_authors": 22, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.15.21249756", + "rel_abs": "BackgroundMortality from COVID-19 shows a strong relationship with age and pre-existing medical conditions, as does mortality from other causes. However it is unclear how specific factors are differentially associated with COVID-19 mortality as compared to mortality from other causes.\n\nMethodsWorking on behalf of NHS England, we carried out a cohort study within the OpenSAFELY platform. Primary care data from England were linked to national death registrations. We included all adults (aged [≥]18 years) in the database on 1st February 2020 and with >1 year of continuous prior registration, the cut-off date for deaths was 9th November 2020. Associations between individual-level characteristics and COVID-19 and non-COVID deaths were estimated by fitting age- and sex-adjusted logistic models for these two outcomes.\n\nResults17,456,515 individuals were included. 17,063 died from COVID-19 and 134,316 from other causes. Most factors associated with COVID-19 death were similarly associated with non-COVID death, but the magnitudes of association differed. Older age was more strongly associated with COVID-19 death than non-COVID death (e.g. ORs 40.7 [95% CI 37.7-43.8] and 29.6 [28.9-30.3] respectively for [≥]80 vs 50-59 years), as was male sex, deprivation, obesity, and some comorbidities. Smoking, history of cancer and chronic liver disease had stronger associations with non-COVID than COVID-19 death. All non-white ethnic groups had higher odds than white of COVID-19 death (OR for Black: 2.20 [1.96-2.47], South Asian: 2.33 [2.16-2.52]), but lower odds than white of non-COVID death (Black: 0.88 [0.83-0.94], South Asian: 0.78 [0.75-0.81]).\n\nInterpretationSimilar associations of most individual-level factors with COVID-19 and non-COVID death suggest that COVID-19 largely multiplies existing risks faced by patients, with some notable exceptions. Identifying the unique factors contributing to the excess COVID-19 mortality risk among non-white groups is a priority to inform efforts to reduce deaths from COVID-19.\n\nFundingWellcome, Royal Society, National Institute for Health Research, National Institute for Health Research Oxford Biomedical Research Centre, UK Medical Research Council, Health Data Research UK.", + "rel_num_authors": 27, "rel_authors": [ { - "author_name": "Rishi K Gupta", - "author_inst": "Institute of Global Health, University College London, London, UK" + "author_name": "Krishnan Bhaskaran", + "author_inst": "London School of Hygiene and Tropical Medicine" }, { - "author_name": "Joshua Rosenheim", - "author_inst": "Division of Infection and Immunity, University College London, London, UK" + "author_name": "Sebastian CJ Bacon", + "author_inst": "University of Oxford" }, { - "author_name": "Lucy C K Bell", - "author_inst": "University College London" + "author_name": "Stephen JW Evans", + "author_inst": "London School of Hygiene Tropical Medicine" }, { - "author_name": "Aneesh Chandran", - "author_inst": "Division of Infection and Immunity, University College London, London, UK" + "author_name": "Chris J Bates", + "author_inst": "The Phoenix Partnership" }, { - "author_name": "Jose Afonso Guerra-Assuncao", - "author_inst": "Division of Infection and Immunity, University College London, London, UK" + "author_name": "Christopher T Rentsch", + "author_inst": "London School of Hygiene and Tropical Medicine" }, { - "author_name": "Gabriele Pollara", - "author_inst": "Division of Infection and Immunity, University College London, London, UK" + "author_name": "MacKenna Brian", + "author_inst": "University of Oxford" }, { - "author_name": "Matthew Whelan", - "author_inst": "Division of Infection and Immunity, University College London, London, UK" + "author_name": "Laurie Tomlinson", + "author_inst": "London School of Hygiene and Tropical Medicine" }, { - "author_name": "Jessica Artico", - "author_inst": "Barts Heart Centre, St Bartholomew's Hospital, Barts Health NHS Trust, London, UK, London, UK" + "author_name": "Alex J Walker", + "author_inst": "University of Oxford" }, { - "author_name": "George Joy", - "author_inst": "Barts Heart Centre, St Bartholomew's Hospital, Barts Health NHS Trust, London, UK, London, UK" + "author_name": "Anna Schultze", + "author_inst": "London School of Hygiene and Tropical Medicine" }, { - "author_name": "Hibba Kurdi", - "author_inst": "Barts Heart Centre, St Bartholomew's Hospital, Barts Health NHS Trust, London, UK, London, UK" + "author_name": "Caroline E Morton", + "author_inst": "University of Oxford" }, { - "author_name": "Daniel M Altmann", - "author_inst": "Department of Immunology and Inflammation, Imperial College London, London, UK" + "author_name": "Daniel Grint", + "author_inst": "London School of Hygiene and Tropical Medicine" }, { - "author_name": "Rosemary Boyton", - "author_inst": "Lung Division, Royal Brompton & Harefield NHS Foundation Trust, London, UK" + "author_name": "Amir Mehrkar", + "author_inst": "University of Oxford" }, { - "author_name": "Mala Maini", - "author_inst": "Division of Infection and Immunity, University College London, London, UK" + "author_name": "Rosalind M Eggo", + "author_inst": "London School of Hygiene and Tropical Medicine" }, { - "author_name": "Aine McKnight", - "author_inst": "Blizard Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK." + "author_name": "Peter Inglesby", + "author_inst": "University of Oxford" }, { - "author_name": "Jonathan Lambourne", - "author_inst": "Department of Infection, Barts Health NHS Trust, London, UK" + "author_name": "Ian J Douglas", + "author_inst": "London School of Hygiene and Tropical Medicine" }, { - "author_name": "Teresa Cutino-moguel", - "author_inst": "Department of Virology, Barts Health NHS Trust, London, UK" + "author_name": "Helen I McDonald", + "author_inst": "London School of Hygiene and Tropical Medicine" }, { - "author_name": "Charlotte Manisty", - "author_inst": "Institute of Cardiovascular Sciences, University College London, London, UK" + "author_name": "Jonathan Cockburn", + "author_inst": "The Phoenix Partnership" }, { - "author_name": "Thomas Alexander Treibel", - "author_inst": "Institute of Cardiovascular Sciences, University College London, London, UK" + "author_name": "Elizabeth J Williamson", + "author_inst": "London School of Hygiene and Tropical Medicine" }, { - "author_name": "James Moon", - "author_inst": "Institute of Cardiovascular Sciences, University College London, London, UK" + "author_name": "David Evans", + "author_inst": "University of Oxford" }, { - "author_name": "Benjamin Chain", - "author_inst": "Division of Infection and Immunity, University College London, London, UK" + "author_name": "Helen J Curtis", + "author_inst": "University of Oxford" }, { - "author_name": "Mahdad Noursadeghi", - "author_inst": "Division of Infection and Immunity, University College London, London, UK" + "author_name": "William J Hulme", + "author_inst": "University of Oxford" }, { - "author_name": "- The COVIDsortium Investigators", - "author_inst": "" + "author_name": "John Parry", + "author_inst": "University of Oxford" + }, + { + "author_name": "Frank Hester", + "author_inst": "The Phoenix Partnership" + }, + { + "author_name": "Sam Harper", + "author_inst": "The Phoenix Partnership" + }, + { + "author_name": "David Spiegelhalter", + "author_inst": "Winton Centre for Risk and Evidence Communication, Centre for Mathematical Sciences, University of Cambridge" + }, + { + "author_name": "Liam Smeeth", + "author_inst": "London School of Hygiene and Tropical Medicine" + }, + { + "author_name": "Ben Goldacre", + "author_inst": "University of Oxford" } ], "version": "1", - "license": "cc_no", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -966854,51 +967078,43 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2021.01.19.427330", - "rel_title": "Temporal dynamics of SARS-CoV-2 mutation accumulation within and across infected hosts", + "rel_doi": "10.1101/2021.01.19.21249790", + "rel_title": "COVID-19: making the best out of a forced transition to online medical teaching. A mixed methods study", "rel_date": "2021-01-20", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.01.19.427330", - "rel_abs": "Analysis of SARS-CoV-2 genetic diversity within infected hosts can provide insight into the generation and spread of new viral variants and may enable high resolution inference of transmission chains. However, little is known about temporal aspects of SARS-CoV-2 intrahost diversity and the extent to which shared diversity reflects convergent evolution as opposed to transmission linkage. Here we use high depth of coverage sequencing to identify within-host genetic variants in 325 specimens from hospitalized COVID-19 patients and infected employees at a single medical center. We validated our variant calling by sequencing defined RNA mixtures and identified a viral load threshold that minimizes false positives. By leveraging clinical metadata, we found that intrahost diversity is low and does not vary by time from symptom onset. This suggests that variants will only rarely rise to appreciable frequency prior to transmission. Although there was generally little shared variation across the sequenced cohort, we identified intrahost variants shared across individuals who were unlikely to be related by transmission. These variants did not precede a rise in frequency in global consensus genomes, suggesting that intrahost variants may have limited utility for predicting future lineages. These results provide important context for sequence-based inference in SARS-CoV-2 evolution and epidemiology.", - "rel_num_authors": 8, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.19.21249790", + "rel_abs": "Introductionthe COVID-19 pandemic resulted in a decreed confinement in our country from March until the end of term in June 2020. This forced a transition exclusively to distance learning. The aim of this study was to broaden the understanding of fully online distance learning from the experiences of undergraduate medical students and faculty members during confinement, and identify its key elements.\n\nMethodsA convergent mixed methods study analyzing: (a) an online teaching follow- up program, (b) two focus groups and a nominal group with students and faculty, respectively, and (c) a survey with students from 1st to 5th year.\n\nResultsThirteen strongly interconnected categories were identified. Four played an organizational role: course planning, coordination, communication and pedagogical coherence. The remaining nine categories were: learning outcomes, teaching methodology, online resources, evaluation, time management, workload, student motivation, participation, and teacher-student relationship. Among the key aspects of learning were those that promoted rapport between faculty and students, such as synchronous sessions, especially those based on clinical cases.\n\nConclusionthe experiences from confinement allowed us to gain insight into some of the key aspects of online medical teaching. Promoting student motivation and participation at all levels was essential to distance learning in Medicine.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Andrew L. Valesano", - "author_inst": "University of Michigan" - }, - { - "author_name": "Kalee E. Rumfelt", - "author_inst": "University of Michigan" - }, - { - "author_name": "Derek E. Dimcheff", - "author_inst": "University of Michigan" + "author_name": "Montserrat Virumbrales", + "author_inst": "Universitat Internacional de Catalunya" }, { - "author_name": "Christopher N. Blair", - "author_inst": "University of Michigan" + "author_name": "Marta Elorduy", + "author_inst": "Universitat Internacional de Catalunya" }, { - "author_name": "William J. Fitzsimmons", - "author_inst": "University of Michigan" + "author_name": "Mariona Graell", + "author_inst": "Universitat Internacional de Catalunya" }, { - "author_name": "Joshua G. Petrie", - "author_inst": "University of Michigan" + "author_name": "Pau Mezquita", + "author_inst": "Universitat Internacional de Catalunya" }, { - "author_name": "Emily Toth Martin", - "author_inst": "University of Michigan" + "author_name": "Pedro Brotons", + "author_inst": "Universitat Internacional de Catalunya" }, { - "author_name": "Adam S. Lauring", - "author_inst": "University of Michigan" + "author_name": "Albert Balaguer", + "author_inst": "Universitat Internacional de Catalunya" } ], "version": "1", - "license": "cc_by_nc", - "type": "new results", - "category": "microbiology" + "license": "cc_by_nc_nd", + "type": "PUBLISHAHEADOFPRINT", + "category": "medical education" }, { "rel_doi": "10.1101/2021.01.19.20248560", @@ -968496,35 +968712,71 @@ "category": "genomics" }, { - "rel_doi": "10.1101/2021.01.15.426908", - "rel_title": "Interferon-regulated genetic programs and JAK/STAT pathway activate the intronic promoter of the short ACE2 isoform in renal proximal tubules", + "rel_doi": "10.1101/2021.01.19.427256", + "rel_title": "An all-solid-state heterojunction oxide transistor for the rapid detection of biomolecules and SARS-CoV-2 spike S1 protein", "rel_date": "2021-01-19", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.01.15.426908", - "rel_abs": "Recently, a short, interferon-inducible isoform of Angiotensin-Converting Enzyme 2 (ACE2), dACE2 was identified. ACE2 is a SARS-Cov-2 receptor and changes in its renal expression have been linked to several human nephropathies. These changes were never analyzed in context of dACE2, as its expression was not investigated in the kidney. We used Human Primary Proximal Tubule (HPPT) cells to show genome-wide gene expression patterns after cytokine stimulation, with emphasis on the ACE2/dACE2 locus. Putative regulatory elements controlling dACE2 expression were identified using ChIP-seq and RNA-seq. qRT-PCR differentiating between ACE2 and dACE2 revealed 300- and 600-fold upregulation of dACE2 by IFN and IFN{beta}, respectively, while full length ACE2 expression was almost unchanged. JAK inhibitor ruxolitinib ablated STAT1 and dACE2 expression after interferon treatment. Finally, with RNA-seq, we identified a set of genes, largely immune-related, induced by cytokine treatment. These gene expression profiles provide new insights into cytokine response of proximal tubule cells.", - "rel_num_authors": 4, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.01.19.427256", + "rel_abs": "Solid-state transistor sensors that can detect biomolecules in real time are highly attractive for emerging bioanalytical applications. However, combining cost-effective manufacturing with high sensitivity, specificity and fast sensing response, remains challenging. Here we develop low-temperature solution-processed In2O3/ZnO heterojunction transistors featuring a geometrically engineered tri-channel architecture for rapid real-time detection of different biomolecules. The sensor combines a high electron mobility channel, attributed to the quasi-two-dimensional electron gas (q2DEG) at the buried In2O3/ZnO heterointerface, in close proximity to a sensing surface featuring tethered analyte receptors. The unusual tri-channel design enables strong coupling between the buried q2DEG and the minute electronic perturbations occurring during receptor-analyte interactions allowing for robust, real-time detection of biomolecules down to attomolar (aM) concentrations. By functionalizing the tri-channel surface with SARS-CoV-2 (Severe Acute Respiratory Syndrome Coronavirus 2) antibody receptors, we demonstrate real-time detection of the SARS-CoV-2 spike S1 protein down to attomolar concentrations in under two minutes.", + "rel_num_authors": 13, "rel_authors": [ { - "author_name": "Jakub Jankowski", - "author_inst": "Laboratory of Genetics and Physiology, National Institute of Diabetes and Digestive and Kidney Diseases, U.S. National Institutes of Health, Bethesda, MD 20892," + "author_name": "Yen-Hung Lin", + "author_inst": "University of Oxford" }, { - "author_name": "Hye Kyung Lee", - "author_inst": "Laboratory of Genetics and Physiology, National Institute of Diabetes and Digestive and Kidney Diseases, U.S. National Institutes of Health, Bethesda, MD 20892," + "author_name": "Yang Han", + "author_inst": "Tianjin University" + }, + { + "author_name": "Abhinav Sharma", + "author_inst": "King Abdullah University of Science and Technology (KAUST)" }, { - "author_name": "Julia Wilflingseder", - "author_inst": "Department of Physiology and Pathophysiology, University of Veterinary Medicine, Veterinarplatz 1, 1210, Vienna, Austria" + "author_name": "Wejdan S. AlGhamdi", + "author_inst": "King Abdullah University of Science and Technology (KAUST)" }, { - "author_name": "Lothar Hennighausen", - "author_inst": "Laboratory of Genetics and Physiology, National Institute of Diabetes and Digestive and Kidney Diseases, U.S. National Institutes of Health, Bethesda, MD 20892," + "author_name": "Chien-Hao Liu", + "author_inst": "National Taiwan University" + }, + { + "author_name": "Tzu-Hsuan Chang", + "author_inst": "National Taiwan University" + }, + { + "author_name": "Xi-Wen Xiao", + "author_inst": "National Taiwan University" + }, + { + "author_name": "Akmaral Seitkhan", + "author_inst": "King Abdullah University of Science and Technology (KAUST)" + }, + { + "author_name": "Alexander D. Mottram", + "author_inst": "Vidyasirimedhi Institute of Science and Technology" + }, + { + "author_name": "Pichaya Pattanasattayavong", + "author_inst": "Vidyasirimedhi Institute of Science and Technology" + }, + { + "author_name": "Hendrik Faber", + "author_inst": "King Abdullah University of Science and Technology (KAUST)" + }, + { + "author_name": "Martin Heeney", + "author_inst": "Imperial College London" + }, + { + "author_name": "Thomas D. Anthopoulos", + "author_inst": "King Abdullah University of Science and Technology (KAUST)" } ], "version": "1", - "license": "", + "license": "cc_by_nc_nd", "type": "new results", - "category": "genomics" + "category": "bioengineering" }, { "rel_doi": "10.1101/2021.01.15.426849", @@ -971234,25 +971486,29 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.01.14.21249797", - "rel_title": "Modelling the Spreading of the SARS-CoV-2 in Presence of the Lockdown and Quarantine Measures by a \"Kinetic-Type Reactions\" Approach", + "rel_doi": "10.1101/2021.01.13.21249773", + "rel_title": "Optimal piecewise constant vaccination and lockdown policies for COVID-19", "rel_date": "2021-01-15", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.14.21249797", - "rel_abs": "We propose a realistic model for the evolution of the COVID-19 pandemic subject to the lockdown and quarantine measures, which takes into account the time-delay for recovery or death processes. The dynamic equations for the entire process are derived by adopting a kinetic-type reactions approach. More specifically, the lockdown and the quarantine measures are modelled by some kind of inhibitor reactions where susceptible and infected individuals can be trapped into inactive states. The dynamics for the recovered people is obtained by accounting people who are only traced back to hospitalised infected people. To get the evolution equation we take inspiration from the Michaelis-Mentens enzyme-substrate reaction model (the so-called MM reaction) where the enzyme is associated to the available hospital beds, the substrate to the infected people, and the product to the recovered people, respectively. In other words, everything happens as if the hospitals beds act as a catalyzer in the hospital recovery process. Of course, in our case the reverse MM reactions has no sense in our case and, consequently, the kinetic constant is equal to zero. Finally, the O.D.E.s for people tested positive to COVID-19 is simply modelled by the following kinetic scheme S + I {Rightarrow} 2I with I {Rightarrow} R or I {Rightarrow} D, with S, I, R, and D denoting the compartments Susceptible, Infected, Recovered, and Deceased people, respectively. The resulting kinetic-type equations provide the O.D.E.s, for elementary reaction steps, describing the number of the infected people, the total number of the recovered people previously hospitalised, subject to the lockdown and the quarantine measure, and the total number of deaths. The model foresees also the second wave of Infection by Coronavirus. The tests carried out on real data for Belgium, France and Germany confirmed the correctness of our model.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.13.21249773", + "rel_abs": "We formulate a controlled system of ordinary differential equations, with vaccination and lockdown interventions as controls, to simulate the mitigation of COVID-19. The performance of the controls is measured through a cost functional involving vaccination and lockdown costs as well as the burden of COVID19 quantified in DALYs. We calibrate parameters with data from Mexico City and Valle de Mexico. By using differential evolution, we minimize the cost functional subject to the controlled system and find optimal policies that are constant in time intervals of a given size. The main advantage of these policies relies on its practical implementation since the health authority has to make only a finite number of different decisions. Our methodology to find optimal policies is relatively general, allowing changes in the dynamics, the cost functional, or the frequency the policymaker changes actions.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Giorgio SONNINO", - "author_inst": "Universite' Libre de Bruxelles (ULB), Department of Physics" + "author_name": "Gabriel Adrian Salcedo-Varea", + "author_inst": "Universidad de Sonora" }, { - "author_name": "Philippe PEETERS", - "author_inst": "Universite' Libre de Bruxelles (ULB), Department de Physique" + "author_name": "Francisco Penunuri", + "author_inst": "Universidad Autonoma de Yucatan" }, { - "author_name": "Pasquale NARDONE", - "author_inst": "Universite' Libre de Bruxelles (ULB), Department of Physics" + "author_name": "David Gonzalez-Sanchez", + "author_inst": "CONACYT-Universidad de Sonora" + }, + { + "author_name": "Saul Diaz-Infante", + "author_inst": "CONACYT-Universidad de Sonora" } ], "version": "1", @@ -973015,47 +973271,63 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.01.15.426787", - "rel_title": "Correlation of Computerized Tomography (CT) Severity Score for COVID-19 pneumonia with Clinical Outcomes", + "rel_doi": "10.1101/2021.01.12.426407", + "rel_title": "Distinct Patterns of Emergence of SARS-CoV-2 Spike Variants including N501Y in Clinical Samples in Columbus Ohio", "rel_date": "2021-01-15", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.01.15.426787", - "rel_abs": "IntroductionVarious CT severity scores have already been described in literature since the start of this pandemic. One pertinent issue with all of the previously described severity scores is their relative challenging calculation and variance in inter-observer agreement. The severity score proposed in our study is relatively simpler, easier to calculate and apart from a trained radiologist, can easily be calculated even by physicians with good inter-observer agreement. Therefore, a rapid CT severity score calculation can give a clue to physician about possible clinical outcome without being dependent on radiologist who may not be readily available especially in third world countries.\n\nObjectiveThe objective of this study is to develop a simple CT severity score (CT-SS) with good inter-observer agreement and access its correlation with clinical outcome.\n\nMethodsThis retrospective study was conducted by the Department of Radiology and Internal Medicine, at the Aga Khan University Hospital Karachi, from April 2020 to August 2020. Non-probability consecutive sampling was used to include all patients who were positive for COVID-19 on PCR, and underwent CT chest examination at AKUH. Severity of disease was calculated in each lobe on the basis of following proposed CT severity scoring system (CT-SS). For each lobe the percentage of involvement by disease was scored - 0% involvement was scored 0, <50% involvement was scored 1 and >50% involvement was scored 2. Maximum score for one lobe was 2 and hence total maximum overall score for all lobes was 10. Continuous data was represented using mean and standard deviation, and compared using independent sample t-tests. Categorical data was represented using frequencies and percentages, and compared using Chi-squared tests. Inter-observer reliability between radiologist and COVID intensivist for the 10 point CT-SS rated on 0-10 was assessed using the Kappa statistic. A p-value < 0.05 was considered significant for all analyses.\n\nResultsA total of 73 patients were included, the majority male (58.9%) with mean age 55.8 {+/-} 13.93 years. The CT-SS rated on 0-10 showed substantial inter-observer reliability between radiologist and intensivist with a Kappa statistic of 0.78. Patients with CT-SS 8-10 had a significantly higher ICU admission & intubation rate (53.8% vs. 23.5%) and mortality rate (35.9% vs. 11.8%; p = 0.017), as compared to those with CT-SS 0-7.\n\nConclusionWe conclude that the described CT severity score (CT-SS) is a quick, effective and easily reproducible tool for prediction of adverse clinical outcome in patients with COVID 19 pneumonia. The tool shows good inter-observer agreement when calculated by radiologist and physician independently.", - "rel_num_authors": 7, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.01.12.426407", + "rel_abs": "Following the worldwide emergence of the p.Asp614Gly shift in the Spike (S) gene of SARS-CoV-2, there have been few recurring pathogenic shifts occurring during 2020, as assessed by genomic sequencing. This situation has evolved in the last several months with the emergence of several distinct variants (first identified in the United Kingdom and South Africa) that manifest multiple changes in the S gene, particularly p.Asn501Tyr (N501Y), that likely have clinical impact. We report here the emergence in Columbus, Ohio in December 2020 of two novel SARS-CoV-2 clade 20G variants. One variant, that has become the predominant virus found in nasopharyngeal swabs in the December 2020-January 2021 period, harbors S p.Gln677His (Q677H), affecting a consensus QTQTN domain near the S1/S2 furin cleavage site, nucleocapsid (N) p.Asp377Tyr (D377Y) and membrane glycoprotein (M) p.Ala85Ser (A85S) mutations, with additional S mutations in subsets. The other variant present in two samples, contains S N501Y, which is a marker of the UK-B.1.1.7 (clade 20I/501Y.V1) strain, but lacks all other mutations from that virus. The Ohio variant is from a different clade and shares multiple mutations with the clade 20G viruses circulating in the area prior to December 2020. These two SARS-CoV-2 viruses, which we show are also present and evolving currently in several other parts of North America, add to the diversity of S gene shifts occurring worldwide. These and other shifts in this period of the pandemic support multiple independent acquisition of functionally significant and potentially complementing mutations affecting the S QTQTN site (Q675H or Q677H) and certain receptor binding domain mutations (e.g., E484K and N501Y).", + "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Kiran Hilal", - "author_inst": "Aga Khan University Hospital" + "author_name": "Huolin Tu", + "author_inst": "James Molecular Laboratory, The Ohio State University Wexner Medical Center" }, { - "author_name": "Jehanzeb Shahid", - "author_inst": "Aga Khan University Hospital" + "author_name": "Matthew R Avenarius", + "author_inst": "Department of Pathology, The Ohio State University Wexner Medical Center" }, { - "author_name": "Abdullah Aameen", - "author_inst": "Aga Khan University Hospital" + "author_name": "Laura Kubatko", + "author_inst": "The Ohio State University" }, { - "author_name": "Russell Seth Martins", - "author_inst": "Aga Khan University Medical College Pakistan" + "author_name": "Matthew Hunt", + "author_inst": "The James Molecular Laboratory, The Ohio State University Wexner Medical Center" }, { - "author_name": "Avinash Nankani", - "author_inst": "Dow University of Health Sciences" + "author_name": "Xiaokang Pan", + "author_inst": "James Molecular Laboratory, The Ohio State University Wexner Medical Center" }, { - "author_name": "Ainan Arshad", - "author_inst": "Aga Khan University Hospital" + "author_name": "Peng Ru", + "author_inst": "The Ohio State University Comprehensive Cancer Center" }, { - "author_name": "Haq Tu", - "author_inst": "Aga Khan University Hospital" + "author_name": "Jason Garee", + "author_inst": "The Ohio State University Wexner Medical Center" + }, + { + "author_name": "Keelie Thomas", + "author_inst": "Department of Pathology, The Ohio State University Wexner Medical Center" + }, + { + "author_name": "Peter Mohler", + "author_inst": "Departments of Physiology and Internal Medicine and Davis Heart and Lung Research Institute, he College of Medicine and Ohio State University Wexner Medical Cen" + }, + { + "author_name": "Preeti Pancholi", + "author_inst": "Department of Pathology, The Ohio State University Wexner Medical Center," + }, + { + "author_name": "Dan Jones", + "author_inst": "Department of Pathology, The Ohio State University Wexner Medical Center," } ], "version": "1", - "license": "cc_by", + "license": "cc_no", "type": "new results", - "category": "pathology" + "category": "genomics" }, { "rel_doi": "10.1101/2021.01.10.21249370", @@ -974961,109 +975233,29 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.01.14.21249690", - "rel_title": "Mapping SARS-CoV-2 Antibody Epitopes in COVID-19 Patients with a Multi-Coronavirus Protein Microarray", + "rel_doi": "10.1101/2021.01.13.21249412", + "rel_title": "Real-time optical analysis of a colorimetric LAMP assay for SARS-CoV-2 in saliva with a handheld instrument improves accuracy compared to endpoint assessment", "rel_date": "2021-01-15", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.14.21249690", - "rel_abs": "The emergence and rapid worldwide spread of SARS-CoV-2 has accelerated research and development for controlling the pandemic. A multi-coronavirus protein microarray was created containing full-length proteins, overlapping protein fragments of varying lengths and peptide libraries from SARS-CoV-2 and four other human coronaviruses. Sera from confirmed COVID-19 patients as well as unexposed individuals were applied to multi-coronavirus arrays to identify specific antibody reactivity. High level IgG, IgM and IgA reactivity to structural proteins S, M and N, as well as accessory proteins, of SARS-CoV-2 were observed that was specific to COVID-19 patients. Overlapping 100, 50 and 30 amino acid fragments of SARS-CoV-2 proteins identified antigenic regions. Numerous proteins of SARS-CoV, MERS-CoV and the endemic human coronaviruses, HCoV-NL63 and HCoV-OC43 were also more reactive with IgG, IgM and IgA in COVID-19 patient sera than in unexposed control sera, providing further evidence of immunologic cross-reactivity between these viruses. The multi-coronavirus protein microarray is a useful tool for mapping antibody reactivity in COVID-19 patients.", - "rel_num_authors": 23, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.13.21249412", + "rel_abs": "Controlling the course of the COVID-19 pandemic will require widespread deployment of consistent and accurate diagnostic testing of the novel coronavirus SARS-CoV-2. Ideally, tests should detect a minimum viral load, be minimally invasive, and provide a rapid and simple readout. Current FDA-approved RT-qPCR-based standard diagnostic approaches require invasive nasopharyngeal swabs and involve laboratory-based analyses that can delay results. Recently, a loop mediated isothermal nucleic acid amplification (LAMP) test that utilizes colorimetric readout received FDA approval. This approach utilizes a pH indicator dye to detect drop in pH from nucleotide hydrolysis during nucleic acid amplification. This method has only been approved for use with RNA extracted from clinical specimens collected via nasopharyngeal swabs. In this study, we developed a quantitative LAMP-based strategy to detect SARS-CoV-2 RNA in saliva. Our detection system distinguished positive from negative sample types using a handheld instrument that monitors optical changes throughout the LAMP reaction. We used this system in a streamlined LAMP testing protocol that could be completed in less than two hours to directly detect inactivated SARS-CoV-2 in minimally processed saliva that bypassed RNA extraction, with a limit of detection (LOD) of 50 genomes/reaction. The quantitative method correctly detected virus in 100% of contrived clinical samples spiked with inactivated SARS- CoV-2 at either 1X (50 genomes/reaction) or 2X (100 genomes/reaction) of the LOD. Importantly the quantitative method was based on dynamic optical changes during the reaction so was able to correctly classify samples that were misclassified by endpoint observation of color.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "David Camerini", - "author_inst": "Antigen Discovery Innc." - }, - { - "author_name": "Arlo Z Randall", - "author_inst": "Antigen Discovery Inc." - }, - { - "author_name": "Krista Trappl-Kimmons", - "author_inst": "Antigen Discovery Incorporated" + "author_name": "Lena Diaz", + "author_inst": "Department of Molecular Biosciences and Bioengineering, University of Hawaii at Manoa" }, { - "author_name": "Amit Oberai", - "author_inst": "Antigen Discovery Inc." - }, - { - "author_name": "Christopher Hung", - "author_inst": "Antigen Discovery Inc" - }, - { - "author_name": "Joshua Edgar", - "author_inst": "Antigen Discovery Inc." - }, - { - "author_name": "Adam Shandling", - "author_inst": "Antigen Discovery Inc." - }, - { - "author_name": "Vu Huynh", - "author_inst": "Antigen Discovery Inc." - }, - { - "author_name": "Andy A Teng", - "author_inst": "Antigen Discovery Inc." - }, - { - "author_name": "Gary Hermanson", - "author_inst": "Antigen Discovery Inc." - }, - { - "author_name": "Jozelyn V Pablo", - "author_inst": "Antigen Discovery Inc." - }, - { - "author_name": "Megan M Stumpf", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Sandra N Lester", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Jennifer Harcourt", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Azaibi Tamin", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Mohammed Rasheed", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Natalie J Thornburg", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Panayampalli S Satheshkumar", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Xiaowu Liang", - "author_inst": "Antigen Discovery Inc." - }, - { - "author_name": "Richard B Kennedy", - "author_inst": "Mayo Clinic" - }, - { - "author_name": "Angela Yee", - "author_inst": "Antigen Discovery Inc." + "author_name": "Brandon E. Johnson", + "author_inst": "Center for Biomedical Research, The Queen's Medical Center" }, { - "author_name": "Michael Townsend", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Joseph J Campo", - "author_inst": "Antigen Discovery Inc." + "author_name": "Daniel M. Jenkins", + "author_inst": "Department of Molecular Biosciences and Bioengineering, University of Hawaii at Manoa" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -976983,77 +977175,41 @@ "category": "health informatics" }, { - "rel_doi": "10.1101/2021.01.12.21249702", - "rel_title": "Diverse Humoral Immune Responses in Younger and Older Adult COVID-19 Patients", + "rel_doi": "10.1101/2021.01.11.21249549", + "rel_title": "The Relationship between Democracy embracement and COVID-19 reported casualties worldwide", "rel_date": "2021-01-13", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.12.21249702", - "rel_abs": "We sought to discover links between antibody responses to SARS-CoV-2 and patient clinical variables, cytokine profiles and antibodies to endemic coronaviruses. Serum from patients of varying ages and clinical severity were collected and used to probe a novel multi-coronavirus protein microarray containing SARS-CoV-2 proteins and overlapping protein fragments of varying length as well as SARS-CoV, MERS-CoV, HCoV-OC43 and HCoV-NL63 proteins. IgG, IgA and IgM antibody responses to specific epitopes within the spike (S), nucleocapsid (N) and membrane proteins (M) were higher in older adult patients. Moreover, the older age group displayed more consistent correlations of antibody reactivity with systemic cytokine and chemokine responses when compared to the younger adult group. A subset of patients, however, had little or no response to SARS-CoV-2 antigens and disproportionately severe clinical outcomes. Further characterization of these serosilent individuals with cytokine analysis revealed significant differences in IL-10, IL-15, IP-10, EGF and sCD40L levels when compared to seroreactive patients in the cohort.", - "rel_num_authors": 15, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.11.21249549", + "rel_abs": "BackgroundThe COVID-19 toll of cases and deaths followed an uneven pattern across the world. The literature has partly explained the observed discrepancy between the different countries by country-specific and systemic patterns worldwide. In this study, we propose an additional explanation that the magnitude of COVID-19 toll reported to the WHO could be influenced by the level of free speech and Democracy in the reporting countries.\n\nMethodsWe constructed a longitudinal dataset including the daily COVID-19 count of cases and deaths worldwide and each countrys respective score on the Freedom in the World index. We applied two Generalized Estimating Equation models to investigate if a countrys reported toll count of COVID-19 cases and deaths is related to that countrys freedom level. We controlled for factors identified in the current literature to affect the pandemics spread.\n\nResultsA countrys score on the Freedom In the World Index was associated with its reported COVID-19 cases count (57028.43, 95% CI 985.3619 - 113071.5, P= 0.0461) and deaths count (3473.273, 95% CI1217.12-5729.42, P=.002). Also, despite having almost equal shares of the worlds population, countries at the bottom category of the Freedom index reported 21% and 11% of the COVID-19 toll cases and death counts reported by countries of highest scores on the index, respectively.\n\nConclusionsThe known magnitude of the COVID-19 pandemics morbidity and mortality appears to be as transparent as the reporting countries uphold free speech and Democracy. This pattern could potentially misguide international aid and global vaccine distribution plans.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Jennifer M Sasson", - "author_inst": "University of Virginia Health System" - }, - { - "author_name": "Joseph J Campo", - "author_inst": "Antigen Discovery Inc." - }, - { - "author_name": "Rebecca M Carpenter", - "author_inst": "University of Virginia Health System" - }, - { - "author_name": "Mary K Young", - "author_inst": "University of Virginia Health System" - }, - { - "author_name": "Arlo Z Randall", - "author_inst": "Antigen Discovery Inc." - }, - { - "author_name": "Krista Trappl-Kimmons", - "author_inst": "Antigen Discovery Inc." - }, - { - "author_name": "Amit Oberai", - "author_inst": "Antigen Discovery Inc." - }, - { - "author_name": "Christopher Hung", - "author_inst": "Antigen Discovery Inc." - }, - { - "author_name": "Joshua Edgar", - "author_inst": "Antigen Discovery Inc." - }, - { - "author_name": "Andy A Teng", - "author_inst": "Antigen Discovery Inc." + "author_name": "Muhammad Ragaa Hussein", + "author_inst": "Uiversity of Texas UTHealth School of Public Health" }, { - "author_name": "Jozelyn V Pablo", - "author_inst": "Antigen Discovery Inc." + "author_name": "Thamer AlSulaiman", + "author_inst": "University of Iowa Department of Computer Science" }, { - "author_name": "Xiaowu Liang", - "author_inst": "Antigen Discovery Inc." + "author_name": "Mohamed Fouad Habib", + "author_inst": "Science Collaboration Development Center" }, { - "author_name": "Angela Yee", - "author_inst": "Antigen Discovery Inc." + "author_name": "Engy A. Awad", + "author_inst": "Science Collaboration Development Center" }, { - "author_name": "William A Petri Jr.", - "author_inst": "University of Virginia Health System" + "author_name": "Islam Morsi", + "author_inst": "German University in Cairo" }, { - "author_name": "David Camerini", - "author_inst": "Antigen Discovery Inc." + "author_name": "John R. Herbold", + "author_inst": "University of Texas UTHealth School of Public Health" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -978713,47 +978869,71 @@ "category": "biophysics" }, { - "rel_doi": "10.1101/2021.01.12.426404", - "rel_title": "Ineffectual AEC1 Differentiation from KRT8hi Transitional Cells without Fibrosis Associated with Fatal Acute Respiratory Failure in COVID-19 ARDS", + "rel_doi": "10.1101/2021.01.13.426553", + "rel_title": "Distinct lung-homing receptor expression and activation profiles on NK cell and T cell subsets in COVID-19 and influenza", "rel_date": "2021-01-13", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.01.12.426404", - "rel_abs": "ARDS due to COVID-19 and other etiologies results from injury to the alveolar epithelial cell (AEC) barrier resulting in noncardiogenic pulmonary edema, which causes acute respiratory failure; clinical recovery requires epithelial regeneration. During physiologic regeneration in mice, AEC2s proliferate, exit the cell cycle, and transiently assume a transitional state before differentiating into AEC1s; persistence of the transitional state is associated with pulmonary fibrosis in humans. It is unknown whether transitional cells emerge and differentiate into AEC1s without fibrosis in human ARDS and why transitional cells differentiate into AEC1s during physiologic regeneration but persist in fibrosis. We hypothesized that incomplete but ongoing AEC1 differentiation from transitional cells without fibrosis may underlie persistent barrier permeability and fatal acute respiratory failure in ARDS. Immunostaining of postmortem ARDS lungs revealed abundant transitional cells in organized monolayers on alveolar septa without fibrosis. They were typically cuboidal or partially spread, sometimes flat, and occasionally expressed AEC1 markers. Immunostaining and/or interrogation of scRNAseq datasets revealed that transitional cells in mouse models of physiologic regeneration, ARDS, and fibrosis express markers of cell cycle exit but only in fibrosis express a specific senescence marker. Thus, in severe, fatal early ARDS, AEC1 differentiation from transitional cells is incomplete, underlying persistent barrier permeability and respiratory failure, but ongoing without fibrosis; senescence of transitional cells may be associated with pulmonary fibrosis.", - "rel_num_authors": 7, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.01.13.426553", + "rel_abs": "Respiratory viral infections with SARS-CoV-2 or influenza viruses commonly induce a strong infiltration of immune cells into the lung, with potential detrimental effects on the integrity of the lung tissue. Despite comprising the largest fractions of circulating lymphocytes in the lung, little is known about how blood natural killer (NK) cells and T cell subsets are equipped for lung-homing in COVID-19 and influenza. Using 28-colour flow cytometry and re-analysis of published RNA-seq datasets, we provide a detailed comparative analysis of NK cells and T cells in peripheral blood from moderately sick COVID-19 and influenza patients, focusing on the expression of chemokine receptors known to be involved in leukocyte recruitment to the lung. The results reveal a predominant role for CXCR3, CXCR6, and CCR5 in COVID-19 and influenza patients, mirrored by scRNA-seq signatures in peripheral blood and bronchoalveolar lavage from publicly available datasets. NK cells and T cells expressing lung-homing receptors displayed stronger phenotypic signs of activation as compared to cells lacking lung-homing receptors, and activation was overall stronger in influenza as compared to COVID-19. Together, our results indicate migration of functionally competent CXCR3+, CXCR6+, and/or CCR5+ NK cells and T cells to the lungs in moderate COVID-19 and influenza patients, identifying potential common targets for future therapeutic interventions in respiratory viral infections.\n\nAuthor summaryThe composition of in particular CXCR3+ and/or CXCR6+ NK cells and T cells is altered in peripheral blood upon infection with SARS-CoV-2 or influenza virus in patients with moderate disease. Lung-homing receptor-expression is biased towards phenotypically activated NK cells and T cells, suggesting a functional role for these cells co-expressing in particular CXCR3 and/or CXCR6 upon homing towards the lung.", + "rel_num_authors": 13, "rel_authors": [ { - "author_name": "Christopher Ting", - "author_inst": "University of Michigan" + "author_name": "Demi Brownlie", + "author_inst": "Karolinska Institutet" }, { - "author_name": "Mohit Aspal", - "author_inst": "University of Michigan" + "author_name": "Inga R\u00f8dahl", + "author_inst": "Karolinska Institutet" }, { - "author_name": "Neil Vaishampayan", - "author_inst": "University of Michigan" + "author_name": "Renata Varnaite", + "author_inst": "Karolinska Institutet" }, { - "author_name": "Steven K. Huang", - "author_inst": "University of Michigan" + "author_name": "Hilmir Asgeirsson", + "author_inst": "Karolinska University Hospital" }, { - "author_name": "Fa Wang", - "author_inst": "University of Michigan" + "author_name": "Hedvig Glans", + "author_inst": "Karolinska University Hospital" }, { - "author_name": "Carol Farver", - "author_inst": "University of Michigan" + "author_name": "Sara Falck-Jones", + "author_inst": "Karolinska Institutet" }, { - "author_name": "Rachel Lynne Zemans", - "author_inst": "University of Michigan" + "author_name": "Sindhu Vangeti", + "author_inst": "Karolinska Institutet" + }, + { + "author_name": "Marcus Buggert", + "author_inst": "Karolinska Institutet" + }, + { + "author_name": "Hans-Gustaf Ljunggren", + "author_inst": "Karolinska Institutet" + }, + { + "author_name": "Jakob Micha\u00eblsson", + "author_inst": "Karolinska Institutet" + }, + { + "author_name": "Sara Gredmark-Russ", + "author_inst": "Karolinska Institutet" + }, + { + "author_name": "Anna Smed-S\u00f6rensen", + "author_inst": "Karolinska Institutet" + }, + { + "author_name": "Nicole Marquardt", + "author_inst": "Karolinska Institutet" } ], "version": "1", - "license": "cc_no", + "license": "cc_by", "type": "new results", - "category": "pathology" + "category": "immunology" }, { "rel_doi": "10.1101/2021.01.11.426287", @@ -980299,81 +980479,61 @@ "category": "biophysics" }, { - "rel_doi": "10.1101/2021.01.10.20248831", - "rel_title": "Factors indicating intention to vaccinate with a COVID-19 vaccine among older U.S. Adults", + "rel_doi": "10.1101/2021.01.06.21249342", + "rel_title": "Indoor dust as a matrix for surveillance of COVID-19 outbreaks", "rel_date": "2021-01-11", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.10.20248831", - "rel_abs": "AO_SCPLOWBSTRACTC_SCPLOWO_ST_ABSBACKGROUNDC_ST_ABSThe success of vaccination efforts to curb the COVID-19 pandemic will require broad public uptake of immunization and highlights the importance of understanding factors associated with willingness to receive a vaccine.\n\nMETHODSAdults enrolled in the Heartline clinical study were invited to complete a COVID-19 vaccine assessment through the Heartline mobile application between November 6-20, 2020. Factors associated with willingness to receive a COVID-19 vaccine were evaluated using an ordered logistic regression as well as a Random Forest classification algorithm.\n\nRESULTSAmong 9,106 study participants, 81.3% (n=7402) responded and had available demographic data. The majority (91.3%) reported a willingness to be vaccinated. Factors most strongly associated with vaccine willingness were beliefs about the safety and efficacy of COVID-19 vaccines and vaccines in general. Women and Black or African American respondents reported lower willingness to vaccinate. Among those less willing to get vaccinated, 66.2% said that they would talk with their health provider before making a decision. During the study, positive results from the first COVID-19 vaccine outcome study were released; vaccine willingness increased after this report.\n\nCONCLUSIONSEven among older adults at high-risk for COVID-19 complications who are participating in a longitudinal clinical study, 1 in 11 reported lack of willingness to receive COVID-19 vaccine in November 2020. Variability in vaccine willingness by gender, race, education, and income suggests the potential for uneven vaccine uptake. Education by health providers directed toward assuaging concerns about vaccine safety and efficacy can help improve vaccine acceptance among those less willing.\n\nClinicaltrials.gov NCT04276441", - "rel_num_authors": 16, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.06.21249342", + "rel_abs": "Ongoing disease surveillance is a critical tool to mitigate viral outbreaks, especially during a pandemic. Environmental monitoring has significant promise even following widespread vaccination among high-risk populations. The goal of this work is to demonstrate molecular SARS-CoV-2 monitoring in bulk floor dust and related samples as a proof-of-concept of a non-invasive environmental surveillance methodology for COVID-19 and potentially other viral diseases. Surface swab, passive sampler, and bulk floor dust samples were collected from rooms of individuals infected with COVID-19, and SARS-CoV-2 was measured with quantitative reverse transcription polymerase chain reaction (RT-qPCR) and two digital PCR (dPCR) methods. Bulk dust samples had geometric mean concentration of 159 copies/mg-dust and ranged from non-detects to 23,049 copies/mg-dust detected using ddPCR. An average of 88% of bulk dust samples were positive for the virus among detection methods compared to 55% of surface swabs and fewer on the passive sampler (19% carpet, 29% polystyrene). In bulk dust, SARS-CoV-2 was detected in 76%, 93%, and 97% of samples measured by qPCR, chip-based dPCR, and droplet dPCR respectively. Detectable viral RNA in the bulk vacuum bags did not measurably decay over 4 weeks, despite the application of a disinfectant before room cleaning. Future monitoring efforts should further evaluate RNA persistence and heterogeneity in dust. This study did not measure virus viability in dust or potential transmission associated with dust. Overall, this work demonstrates that bulk floor dust is a potentially useful matrix for long-term monitoring of viral disease outbreaks in high-risk populations and buildings.\n\nImportanceEnvironmental surveillance to assess pathogen presence within a community is proving to be a critical tool to protect public health, and it is especially relevant during the ongoing COVID-19 pandemic. Importantly, environmental surveillance tools also allow for the detection of asymptomatic disease carriers and for routine monitoring of a large number of people as has been shown for SARS-CoV-2 wastewater monitoring. However, additional monitoring techniques are needed to screen for outbreaks in high-risk settings such as congregate care facilities. Here, we demonstrate that SARS-CoV-2 can be detected in bulk floor dust collected from rooms housing infected individuals. This analysis suggests that dust may be a useful and efficient matrix for routine surveillance of viral disease outbreaks.", + "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Janeta Nikolovski", - "author_inst": "Janssen Pharmaceutical Companies of Johnson & Johnson" - }, - { - "author_name": "Martin Koldijk", - "author_inst": "Janssen Pharmaceutical Companies of Johnson & Johnson" - }, - { - "author_name": "Gerrit Jan Weverling", - "author_inst": "Janssen Pharmaceutical Companies of Johnson & Johnson" - }, - { - "author_name": "John Spertus", - "author_inst": "University of Missouri Kansas City School of Medicine" - }, - { - "author_name": "Mintu Turakhia", - "author_inst": "Stanford University School of Medicine" - }, - { - "author_name": "Leslie Saxon", - "author_inst": "University of Southern California School of Medicine" + "author_name": "Nicole Renninger", + "author_inst": "Ohio State University" }, { - "author_name": "Charles Michael Gibson", - "author_inst": "Harvard Medical School" + "author_name": "Nicholas Nastasi", + "author_inst": "Ohio State University" }, { - "author_name": "John Whang", - "author_inst": "Janssen Pharmaceutical Companies of Johnson & Johnson" + "author_name": "Ashleigh Bope", + "author_inst": "Ohio State University" }, { - "author_name": "Troy Sarich", - "author_inst": "Janssen Pharmaceutical Companies of Johnson & Johnson" + "author_name": "Samuel J. Cochran", + "author_inst": "Ohio State University" }, { - "author_name": "Robert Zambon", - "author_inst": "Janssen Pharmaceutical Companies of Johnson & Johnson" + "author_name": "Sarah R. Haines", + "author_inst": "Ohio State University" }, { - "author_name": "Nnamdi Ezeanochie", - "author_inst": "Johnson & Johnson" + "author_name": "Neeraja Balasubrahmaniam", + "author_inst": "Ohio State University" }, { - "author_name": "Jennifer Turgiss", - "author_inst": "Johnson & Johnson" + "author_name": "Katelyn Stuart", + "author_inst": "Ohio State University" }, { - "author_name": "Robyn Jones", - "author_inst": "Johnson & Johnson" + "author_name": "Aaron Bivins", + "author_inst": "Ohio State University" }, { - "author_name": "Jeff Stoddard", - "author_inst": "Janssen Pharmaceutical Companies of Johnson & Johnson" + "author_name": "Kyle Bibby", + "author_inst": "University of Notre Dame" }, { - "author_name": "Paul Burton", - "author_inst": "Janssen Pharmaceutical Companies of Johnson & Johnson" + "author_name": "Natalie M. Hull", + "author_inst": "The Ohio State University" }, { - "author_name": "Ann Marie Navar", - "author_inst": "UT Southwestern Medical Center" + "author_name": "Karen C. Dannemiller", + "author_inst": "Ohio State University" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -982593,121 +982753,33 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.01.08.21249445", - "rel_title": "COVID-19 seroprevalence among healthcare workers of a large COVID Hospital in Rome reveals strengths and limits of two different serological tests", + "rel_doi": "10.1101/2021.01.08.21249432", + "rel_title": "Levels of SARS-CoV-2 population exposure are considerably higher than suggested by seroprevalence surveys", "rel_date": "2021-01-09", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.08.21249445", - "rel_abs": "In several hospitals worldwide, healthcare workers are currently at the forefront against coronavirus disease 2019 (COVID-19). Since Fondazione Policlinico Universitario A. Gemelli (FPG) IRCCS has been enlisted as a COVID hospital, healthcare workers deployed to COVID wards were separated from those with limited or no exposure, whereas administrative staff was destined to work-from-home.\n\nBetween June 4 and July 3 2020, an investigation was carried out to evaluate seroprevalence of SARS-CoV-2 IgG antibodies among employees of the FPG using point-of-care (POC) and venous blood tests. Sensitivity, specificity and predictive values were determined with reverse-transcription polymerase chain reaction (RT-PCR) on nasal/oropharyngeal swabs as gold standard.\n\nFour thousand, seven hundred seventy-seven participants were enrolled. Seroprevalence was 3.66% using the POC test and 1.19% using venous blood test, with a significant difference between the two (p < 0.05).\n\nPOC sensitivity and specificity were, respectively, 63.64% (95% confidence interval (CI): 62.20% to 65.04%) and 96.64% (95% CI: 96.05% to 97.13%), while those of the venous blood test were, respectively, 78.79% (95% CI: 77.58% to 79.94%) and 99.36% (95% CI: 99.07% to 99.55%). Among low-risk population, point-of-cares predictive values were 58.33% (positive) and 98.23% (negative) whereas venous blood tests were 92.86% (positive) and 98.53% (negative). In conclusion, point-of-care tests have low diagnostic accuracy, while venous blood tests seem to show an overall poor reliability.", - "rel_num_authors": 26, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.08.21249432", + "rel_abs": "Accurate knowledge of accurate levels of prior population exposure has critical ramifications for preparedness plans of subsequent SARS-CoV-2 epidemic waves and vaccine prioritization strategies. Serological studies can be used to estimate levels of past exposure and thus position populations in their epidemic timeline. To circumvent biases introduced by decaying antibody titers over time, population exposure estimation methods should account for seroreversion, to reflect that changes in seroprevalence measures over time are the net effect of increases due to recent transmission and decreases due to antibody waning. Here, we present a new method that combines multiple datasets (serology, mortality, and virus positivity ratios) to estimate seroreversion time and infection fatality ratios and simultaneously infer population exposure levels. The results indicate that the average time to seroreversion is six months, and that true exposure may be more than double the current seroprevalence levels reported for several regions of England.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Giuseppe Vetrugno", - "author_inst": "Risk Management Unit, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy. Department of Health Care Surveillance and Bioethics, section of Legal" - }, - { - "author_name": "Daniele Ignazio La Milia", - "author_inst": "Hospital Health Management, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy." - }, - { - "author_name": "Floriana D'Ambrosio", - "author_inst": "Section of Hygiene, University Department of Health Sciences and Public Health, Universita' Cattolica del Sacro Cuore, Rome, Italy" - }, - { - "author_name": "Marcello Di Pumpo", - "author_inst": "Section of Hygiene, University Department of Health Sciences and Public Health, Universita' Cattolica del Sacro Cuore, Rome, Italy." - }, - { - "author_name": "Roberta Pastorino", - "author_inst": "Department of Woman and Child Health and Public Health - Public Health Area, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy." - }, - { - "author_name": "Stefania Boccia", - "author_inst": "Section of Hygiene, University Department of Health Sciences and Public Health, Universita' Cattolica del Sacro Cuore, Rome, Italy. Department of Woman and Chil" - }, - { - "author_name": "Rosalba Ricci", - "author_inst": "Department of laboratory and infectivological sciences, Fondazione Policlinico A. Gemelli IRCCS, Rome, Italy." - }, - { - "author_name": "Fabio De-Giorgio", - "author_inst": "Department of Health Care Surveillance and Bioethics, section of Legal Medicine, Universita' Cattolica del Sacro Cuore, Rome, Italy. Fondazione Policlinico Univ" - }, - { - "author_name": "Michela Cicconi", - "author_inst": "Risk Management Unit, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy. Section of Hygiene, University Department of Health Sciences and Publi" - }, - { - "author_name": "Federica Foti", - "author_inst": "Risk Management Unit, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy." - }, - { - "author_name": "Domenico Pascucci", - "author_inst": "Section of Hygiene, University Department of Health Sciences and Public Health, Universita' Cattolica del Sacro Cuore, Rome, Italy." - }, - { - "author_name": "Francesco Castrini", - "author_inst": "Section of Hygiene, University Department of Health Sciences and Public Health, Universita' Cattolica del Sacro Cuore, Rome, Italy." - }, - { - "author_name": "Elettra Carini", - "author_inst": "Hospital Health Management, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy. Section of Hygiene, University Department of Health Sciences and" - }, - { - "author_name": "Andrea Cambieri", - "author_inst": "Hospital Health Management, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy." - }, - { - "author_name": "Maria Elena D'Alfonso", - "author_inst": "Hospital Health Management, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy" - }, - { - "author_name": "Gennaro Capalbo", - "author_inst": "Hospital Health Management, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy." - }, - { - "author_name": "Massimo Fantoni", - "author_inst": "Department of laboratory and infectivological sciences, Fondazione Policlinico A. Gemelli IRCCS, Rome, Italy. Department of Health Care Surveillance and Bioethi" - }, - { - "author_name": "Umberto Moscato", - "author_inst": "Section of Hygiene, University Department of Health Sciences and Public Health, Universita' Cattolica del Sacro Cuore, Rome, Italy. Department of Woman and Chil" - }, - { - "author_name": "Domenico Staiti", - "author_inst": "Department of Woman and Child Health and Public Health-Public Health Area, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy. University Depart" - }, - { - "author_name": "Francesco Maria De Simone", - "author_inst": "Department of Woman and Child Health and Public Health-Public Health Area, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy." - }, - { - "author_name": "Filippo Berloco", - "author_inst": "Hospital Health Management, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy." - }, - { - "author_name": "Maurizio Zega", - "author_inst": "Director of Nursing Service Technician and Rehabilitation Administration (S.I.T.R.A.), Fondazione Policlinico Universitario Agostino Gemelli, Rome, Italy." - }, - { - "author_name": "Paola Cattani", - "author_inst": "Department of laboratory and infectivological sciences, Fondazione Policlinico A. Gemelli IRCCS, Rome, Italy." + "author_name": "Siyu Chen", + "author_inst": "Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, United Kingdom." }, { - "author_name": "Brunella Posteraro", - "author_inst": "Department of Basic Biotechnological Sciences, Intensive and Perioperative Clinics, Universita' Cattolica del Sacro Cuore, Rome, Italy. Department of Medical an" + "author_name": "Jennifer A Flegg", + "author_inst": "School of Mathematics and Statistics, University of Melbourne, Melbourne, Australia." }, { - "author_name": "Maurizio Sanguinetti", - "author_inst": "Department of laboratory and infectivological sciences, Fondazione Policlinico A. Gemelli IRCCS, Rome, Italy. Department of Basic Biotechnological Sciences, Int" + "author_name": "Lisa J White", + "author_inst": "Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield 5 Department of Medicine, University of Oxford, United Kingdom." }, { - "author_name": "Patrizia Laurenti", - "author_inst": "Section of Hygiene, University Department of Health Sciences and Public Health, Universita' Cattolica del Sacro Cuore, Rome, Italy. Department of Woman and Chil" + "author_name": "Ricardo Aguas", + "author_inst": "Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom." } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -984383,55 +984455,167 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.01.07.21249116", - "rel_title": "Multi-organ complement deposition in COVID-19 patients", + "rel_doi": "10.1101/2021.01.06.20249026", + "rel_title": "Recurrent dissemination of SARS-CoV-2 through the Uruguayan-Brazilian border", "rel_date": "2021-01-08", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.07.21249116", - "rel_abs": "BackgroundIncreased levels of circulating complement activation products have been reported in COVID-19 patients, but only limited information is available on complement involvement at tissue level. The mechanisms and pathways of local complement activation remain unclear.\n\nMethodsWe performed immunofluorescence analyses of autopsy specimens of lungs, kidney and liver from nine COVID-19 patients who died of acute respiratory failure. Snap-frozen samples embedded in OCT were stained with antibodies against complement components and activation products, IgG and spike protein of SARS-CoV-2.\n\nFindingsLung deposits of C1q, C4, C3 and C5b-9 were localized in the capillaries of the interalveolar septa and on alveolar cells. IgG displayed a similar even distribution, suggesting classical pathway activation. The spike protein is a potential target of IgG, but its uneven distribution suggests that other viral and tissue molecules may be targeted by IgG. Factor B deposits were also seen in COVID-19 lungs and are consistent with activation of the alternative pathway, whereas MBL and MASP-2 were hardly detectable. Analysis of kidney and liver specimens mirrored findings observed in the lung. Complement deposits were seen on tubules and vessels of the kidney with only mild C5b-9 staining in glomeruli, and on hepatic artery and portal vein of the liver.\n\nInterpretationComplement deposits in different organs of deceased COVID-19 patients caused by activation of the classical and alternative pathways support the multi-organ nature of the disease.\n\nFundingGrants from the Italian Ministry of Health (COVID-2020-12371808) to PLM and National Institutes of Health HL150146 to NP are gratefully acknowledged.", - "rel_num_authors": 9, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.06.20249026", + "rel_abs": "BackgroundUruguay is one of the few countries in the Americas that successfully contained the COVID-19 epidemic during the first half of 2020. Nevertheless, the intensive human mobility across the dry border with Brazil is a major challenge for public health authorities. We aimed to investigate the origin of SARS-CoV-2 strains detected in Uruguayan localities bordering Brazil as well as to measure the viral flux across this [~]1,100 km uninterrupted dry frontier.\n\nMethodsUsing complete SARS-CoV-2 genomes from the Uruguayan-Brazilian bordering region and phylogeographic analyses, we inferred the virus dissemination frequency between Brazil and Uruguay and characterized local outbreak dynamics during the first months (May-July) of the pandemic.\n\nFindingsPhylogenetic analyses revealed multiple introductions of SARS-CoV-2 Brazilian lineages B.1.1.28 and B.1.1.33 into Uruguayan localities at the bordering region. The most probable sources of viral strains introduced to Uruguay were the Southeast Brazilian region and the state of Rio Grande do Sul. Some of the viral strains introduced in Uruguayan border localities between early May and mid-July were able to locally spread and originated the first outbreaks detected outside the metropolitan region. The viral lineages responsible for Uruguayan suburban outbreaks were defined by a set of between four and 11 mutations (synonymous and non-synonymous) respect to the ancestral B.1.1.28 and B.1.1.33 viruses that arose in Brazil, supporting the notion of a rapid genetic differentiation between SARS-CoV-2 subpopulations spreading in South America.\n\nInterpretationAlthough Uruguayan borders have remained essentially closed to non-Uruguayan citizens, the inevitable flow of people across the dry border with Brazil allowed the repeated entry of the virus into Uruguay and the subsequent emergence of local outbreaks in Uruguayan border localities. Implementation of coordinated bi-national surveillance systems are crucial to achieve an efficient control of the SARS-CoV-2 spread across this kind of highly permeable borderland regions around the world.\n\nResearch in contextO_ST_ABSEvidence before this studyC_ST_ABSSince the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), causative agent of coronavirus disease 19 (COVID-19), was first detected in South America on February 26, 2020, it has rapidly spread through the region, causing nearly 350,000 deaths by December, 2020. In contrast to most American countries, Uruguay avoided an early exponential growth of SARS-CoV-2 cases and during the first six months of the pandemic it registered the lowest incidence of SARS-CoV-2 cases and deaths among South American countries. The intensive cross-border human mobility through the [~]1,100 km uninterrupted dry frontier between Uruguay and Brazil, might poses a major challenge for long-term control of the epidemic in Uruguay. Previous genomic studies conducted in Uruguay have analyzed sequences mostly sampled at the capital city, Montevideo, and detected prevalent SARS-CoV-2 lineages different from those described in Brazil, thus finding no evidence of frequent viral exchanges between these countries.\n\nAdded value of this studyHere we present the first genomic study of SARS-CoV-2 strains detected in different Uruguayan and Brazilian localities along the bordering region. The samples analyzed include 30% (n = 59) of all laboratory confirmed SARS-CoV-2 cases from Uruguayan departments at the Brazilian border between March and July, 2020, as well as 68 SARS-CoV-2 sequences from individuals diagnosed in the southernmost Brazilian state of Rio Grande do Sul between March and August, 2020. We demonstrate that SARS-CoV-2 viral lineages that widely spread in the Southeastern Brazilian region (B.1.1.28 and B.1.1.33) were also responsible for most viral infections in Rio Grande do Sul and neighboring Uruguayan localities. We further uncover that major outbreaks detected in Uruguayan localities bordering Brazil in May and June, 2020, were originated from two independent introduction events of the Brazilian SARS-CoV-2 lineage B.1.1.33, unlike previous outbreaks in the Uruguayan metropolitan region that were seeded by European SARS-CoV-2 lineages.\n\nImplications of all the available evidenceOur findings confirm that although Uruguayan borders have remained essentially closed to non-Uruguayan citizens, dissemination of SARS-CoV-2 across the Uruguayan-Brazilian frontier was not fully suppressed and had the potential to ignite local transmission chains in Uruguay. These findings also highlight the relevance of implementing bi-national public health cooperation workforces combining epidemiologic and genomic data to monitor the viral spread throughout this kind of highly permeable dry frontiers around the world.", + "rel_num_authors": 37, "rel_authors": [ { - "author_name": "Paolo Macor", - "author_inst": "Department of Life Sciences, University of Trieste, Trieste, Italy" + "author_name": "Daiana Mir", + "author_inst": "Centro Universitario Regional del Litoral Norte. Universidad de la Republica, Salto" }, { - "author_name": "Paolo Durigutto", - "author_inst": "Istituto Auxologico Italiano, IRCCS, Laboratory of Immuno-Rheumatology, Milan, Italy" + "author_name": "Natalia Rego", + "author_inst": "Institut Pasteur de Montevideo" }, { - "author_name": "Alessandro Mangogna", - "author_inst": "Institute for Maternal and Child Health, IRCCS Burlo Garofolo, Trieste, Italy" + "author_name": "Paola Cristina Resende", + "author_inst": "Instituto Oswaldo Cruz - Fiocruz, Rio de Janeiro" }, { - "author_name": "Rossana Bussani", - "author_inst": "Department of Medical, Surgical and Health Sciences, University of Trieste, Trieste, Italy" + "author_name": "Fernando Lopez-Tort", + "author_inst": "CENUR Litoral Norte . UdelaR, Salto, Uruguay" }, { - "author_name": "Stefano D'Errico", - "author_inst": "Department of Medical, Surgical and Health Sciences, University of Trieste, Trieste, Italy" + "author_name": "Tamara Fernandez-Calero", + "author_inst": "Institut Pasteur de Montevideo, Universidad Catolica del Uruguay" }, { - "author_name": "Martina Zanon", - "author_inst": "Department of Medical, Surgical and Health Sciences, University of Trieste, Trieste, Italy" + "author_name": "Veronica Noya", + "author_inst": "Sanatorio Americano" }, { - "author_name": "Nicola Pozzi", - "author_inst": "Edward A. Doisy Department of Biochemistry and Molecular Biology, Saint Louis University School of Medicine, St. Louis, MO, US" + "author_name": "Mariana Brandes", + "author_inst": "Institut Pasteur de Montevideo" }, { - "author_name": "Pier Luigi Meroni", - "author_inst": "Istituto Auxologico Italiano, IRCCS, Laboratory of Immuno-Rheumatology, Milan, Italy" + "author_name": "Tania Possi", + "author_inst": "Sanatorio Americano" }, { - "author_name": "Francesco Tedesco", - "author_inst": "Istituto Auxologico Italiano, IRCCS, Laboratory of Immuno-Rheumatology, Milan, Italy" + "author_name": "Mailen Arleo", + "author_inst": "Sanatorio Americano" + }, + { + "author_name": "Natalia Reyes", + "author_inst": "Sanatorio Americano" + }, + { + "author_name": "Matias Victoria", + "author_inst": "CENUR Litoral Norte . UdelaR, Salto, Uruguay" + }, + { + "author_name": "Andres Lizasoain", + "author_inst": "CENUR Litoral Norte . UdelaR, Salto, Uruguay" + }, + { + "author_name": "Matias Castells", + "author_inst": "CENUR Litoral Norte . UdelaR, Salto, Uruguay" + }, + { + "author_name": "Leticia Maya", + "author_inst": "CENUR Litoral Norte . UdelaR, Salto, Uruguay" + }, + { + "author_name": "Matias Salvo", + "author_inst": "CENUR Litoral Norte . UdelaR, Salto, Uruguay" + }, + { + "author_name": "Tatiana Schaffer Gregianini", + "author_inst": "Secretaria de Saude do Estado do Rio Grande do Sul" + }, + { + "author_name": "Marilda Tereza Mar da Rosa", + "author_inst": "Secretaria de Saude do Estado do Rio Grande do Sul" + }, + { + "author_name": "Leticia Garay Martins", + "author_inst": "Secretaria de Saude do Estado do Rio Grande do Sul" + }, + { + "author_name": "Cecilia Alonso", + "author_inst": "CENUR Este-Sede Rocha-UdelaR" + }, + { + "author_name": "Yasser Vega", + "author_inst": "Laboratorio DILAVE/MGAP-INIA-UdelaR -Tacuarembo" + }, + { + "author_name": "Cecilia Salazar", + "author_inst": "Institut Pasteur de Montevideo" + }, + { + "author_name": "Ignacio Ferres", + "author_inst": "Institut Pasteur de Montevideo" + }, + { + "author_name": "Jose Sotelo", + "author_inst": "Instituto de Investigaciones Biologicas Clemente Estable" + }, + { + "author_name": "Jose Sotelo", + "author_inst": "Instituto de Investigaciones Biologicas Clemente Estable" + }, + { + "author_name": "Pablo Smircich", + "author_inst": "Instituto de Investigaciones Biologicas Clemente Estable" + }, + { + "author_name": "Cecilia Matho", + "author_inst": "Instituto de Investigaciones Biologicas Clemente Estable" + }, + { + "author_name": "Ighor Arantes", + "author_inst": "Instituto Oswaldo Cruz - Fiocruz, Rio de Janeiro, Brazil." + }, + { + "author_name": "Luciana Appolinario", + "author_inst": "Instituto Oswaldo Cruz - Fiocruz, Rio de Janeiro, Brazil." + }, + { + "author_name": "Ana Carolina Mendonca", + "author_inst": "Instituto Oswaldo Cruz - Fiocruz, Rio de Janeiro, Brazil." + }, + { + "author_name": "Maria Jose Benitez-Galeano", + "author_inst": "Centro Universitario Regional del Litoral Norte. Universidad de la Republica, Salto" + }, + { + "author_name": "Martin Grana", + "author_inst": "Institut Pasteur de Montevideo" + }, + { + "author_name": "Camila Simoes", + "author_inst": "Institut Pasteur de Montevideo" + }, + { + "author_name": "Fernando Motta", + "author_inst": "Instituto Oswaldo Cruz - Fiocruz, Rio de Janeiro, Brazil." + }, + { + "author_name": "Marilda Mendonca Siqueira", + "author_inst": "Instituto Oswaldo Cruz - Fiocruz, Rio de Janeiro, Brazil." + }, + { + "author_name": "Gonzalo Bello", + "author_inst": "Instituto Oswaldo Cruz- Fiocruz, Riio de Janeiro, Brazil." + }, + { + "author_name": "Rodney Colina", + "author_inst": "CENUR Litoral Norte - UdelaR, Salto, Uruguay" + }, + { + "author_name": "Lucia Spangenberg", + "author_inst": "Institut Pasteur de Montevideo, Universidad Catolica del Uruguay" } ], "version": "1", "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "allergy and immunology" + "category": "epidemiology" }, { "rel_doi": "10.1101/2021.01.07.21249418", @@ -985920,27 +986104,47 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2021.01.07.21249390", - "rel_title": "Interleukin-6 Receptor Antagonists in Critically Ill Patients with Covid-19 - Preliminary report", + "rel_doi": "10.1101/2021.01.07.425705", + "rel_title": "Sequencing of SARS CoV2 in local transmission cases through oxford nanopore MinION platform from Karachi Pakistan", "rel_date": "2021-01-07", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.07.21249390", - "rel_abs": "BackgroundThe efficacy of interleukin-6 receptor antagonists in critically ill patients with coronavirus disease 2019 (Covid-19) is unclear.\n\nMethodsWe evaluated tocilizumab and sarilumab in an ongoing international, multifactorial, adaptive platform trial. Adult patients with Covid-19, within 24 hours of commencing organ support in an intensive care unit, were randomized to receive either tocilizumab (8mg/kg) or sarilumab (400mg) or standard care (control). The primary outcome was an ordinal scale combining in-hospital mortality (assigned -1) and days free of organ support to day 21. The trial uses a Bayesian statistical model with pre-defined triggers to declare superiority, efficacy, equivalence or futility.\n\nResultsTocilizumab and sarilumab both met the pre-defined triggers for efficacy. At the time of full analysis 353 patients had been assigned to tocilizumab, 48 to sarilumab and 402 to control. Median organ support-free days were 10 (interquartile range [IQR] -1, 16), 11 (IQR 0, 16) and 0 (IQR -1, 15) for tocilizumab, sarilumab and control, respectively. Relative to control, median adjusted odds ratios were 1.64 (95% credible intervals [CrI] 1.25, 2.14) for tocilizumab and 1.76 (95%CrI 1.17, 2.91) for sarilumab, yielding >99.9% and 99.5% posterior probabilities of superiority compared with control. Hospital mortality was 28.0% (98/350) for tocilizumab, 22.2% (10/45) for sarilumab and 35.8% (142/397) for control. All secondary outcomes and analyses supported efficacy of these IL-6 receptor antagonists.\n\nConclusionsIn critically ill patients with Covid-19 receiving organ support in intensive care, treatment with the IL-6 receptor antagonists, tocilizumab and sarilumab, improved outcome, including survival. (ClinicalTrials.gov number: NCT02735707)", - "rel_num_authors": 2, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2021.01.07.425705", + "rel_abs": "The first case of severe acute respiratory syndrome 2 (SARS CoV2) was imported to Pakistan in February 2020 since then 10,258 deaths have been witnessed. The virus has been mutating and local transmission cases from different countries vary due to host dependent viral adaptation. Many distinct clusters of variant SARS CoV2 have been defined globally. In this study, the epidemiology of SARS CoV2 was studied and locally transmitted SARS CoV2 isolates from Karachi were sequenced to compared and identify any possible variants.The real time PCR was performed on nasopharyngeal specimen to confirm SARSCoV2 with Orf 1ab and E gene as targets. The viral sequencing was performed through oxford nanopore technology MinION platform. Isolates from first and second wave of COVID-19 outbreak in Karachi were compared. The overall positivity rate for PCR was 26.24% with highest number of positive cases in June. Approximately, 37.45% PCR positive subjects aged between 19-40 years. All the isolates belonged to GH clade and shared missense mutation D614G in spike protein linked to increased transmission rate worldwide. Another spike protein mutation A222V coexisted with D614G in the virus from second wave of COVID-19. Based on the present findings it is suggested that the locally transmitted virus from Karachi vary from those reported from other parts of Pakistan. Slight variability was also observed between viruses from first and second wave. Variability in any potential vaccine target may result in failed trials therefore information on any local viral variants is always useful for effective vaccine design and/or selection.\n\nAuthors summaryDespite precautionary measures the COVID-19 pandemic is causing deaths all over the world. The continuous mutations in viral genome is making it difficult to design vaccines. Variability in genome is host dependent and data sharing has revealed that variant for different geographical locations may harbor different mutations. Keeping this in mind the current study was focused on the epidemiology of SARS CoV2 in symptomatic and asymptomatic COVID -19 suspected cases with impact of age and gender. The locally transmitted SARS CoV2 isolates from Karachi were sequenced to compared and identify any possible variants. The sequenced viral genome varied from the already submitted sequences from Pakistan thereby confirming that slightly different viruses were causing infections during different time periods in Karachi. All belonged to GH clade with D614G, P323L and Q57H mutations. The virus from second wave had A222V mutation making it more different. This information can be useful in selecting or designing a vaccine.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "- The REMAP-CAP Investigators", - "author_inst": "" + "author_name": "Samina Naz Mukry", + "author_inst": "National Institute of Blood Diseases and Bone Marrow Transplantation" }, { - "author_name": "Anthony C Gordon", - "author_inst": "Imperial College London" + "author_name": "Shariq Ahmed", + "author_inst": "National Institute of Blood Diseases and Bone Marrow Transplantation" + }, + { + "author_name": "Ali Raza Bukhari", + "author_inst": "National Institute of Blood Diseases and Bone Marrow Transplantation" + }, + { + "author_name": "Aneeta Shahni", + "author_inst": "National Institute of Blood Diseases and Bone Marrow Transplantation" + }, + { + "author_name": "Gul Sufaida", + "author_inst": "National Institute of Blood Diseases and Bone Marrow Transplantation" + }, + { + "author_name": "Arshi Naz", + "author_inst": "National Institute of Blood Diseases and Bone Marrow Transplantation" + }, + { + "author_name": "Tahir Sultan Shamsi", + "author_inst": "National Institute of Blood Diseases and Bone Marrow Transplantation" } ], "version": "1", - "license": "cc_by_nc_nd", - "type": "PUBLISHAHEADOFPRINT", - "category": "intensive care and critical care medicine" + "license": "cc_by", + "type": "new results", + "category": "genomics" }, { "rel_doi": "10.1101/2021.01.04.21249233", @@ -987674,39 +987878,43 @@ "category": "developmental biology" }, { - "rel_doi": "10.1101/2021.01.05.425339", - "rel_title": "Distinct mutations and lineages of SARS-CoV-2 virus in the early phase of COVID-19 global pandemic and subsequent global expansion", + "rel_doi": "10.1101/2021.01.06.20240903", + "rel_title": "The spread of breathing air from wind instruments and singers using schlieren techniques", "rel_date": "2021-01-06", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.01.05.425339", - "rel_abs": "A novel coronavirus, SARS-CoV-2, has caused over 190 million cases and over 4 million deaths worldwide since it occurred in December 2019 in Wuhan, China. Here we conceptualized the temporospatial evolutionary and expansion dynamics of SARS-CoV-2 by taking a series of cross-sectional view of viral genomes from early outbreak in January 2020 in Wuhan to early phase of global ignition in early April, and finally to the subsequent global expansion by late December 2020. Based on the phylogenetic analysis of the early patients in Wuhan, Wuhan/WH04/2020 is supposed to be a more appropriate reference genome of SARS-CoV-2, instead of the first sequenced genome Wuhan-Hu-1. By scrutinizing the cases from the very early outbreak, we found a viral genotype from the Seafood Market in Wuhan featured with two concurrent mutations (i.e. M type) had become the overwhelmingly dominant genotype (95.3%) of the pandemic one year later. By analyzing 4,013 SARS-CoV-2 genomes from different continents by early April, we were able to interrogate the viral genomic composition dynamics of initial phase of global ignition over a timespan of 14-week. 11 major viral genotypes with unique geographic distributions were also identified. WE1 type, a descendant of M and predominantly witnessed in western Europe, consisted a half of all the cases (50.2%) at the time. The mutations of major genotypes at the same hierarchical level were mutually exclusive, which implying that various genotypes bearing the specific mutations were propagated during human-to-human transmission, not by accumulating hot-spot mutations during the replication of individual viral genomes. As the pandemic was unfolding, we also used the same approach to analyze 261,323 SARS-CoV-2 genomes from the world since the outbreak in Wuhan (i.e. including all the publicly available viral genomes) in order to recapitulate our findings over one-year timespan. By 25 December 2020, 95.3% of global cases were M type and 93.0% of M-type cases were WE1. In fact, at present all the four variants of concern (VOC) are the descendants of WE1 type. This study demonstrates the viral genotypes can be utilized as molecular barcodes in combination with epidemiologic data to monitor the spreading routes of the pandemic and evaluate the effectiveness of control measures. Moreover, the dynamics of viral mutational spectrum in the study may help the early identification of new strains in patients to reduce further spread of infection, guide the development of molecular diagnosis and vaccines against COVID-19, and help assess their accuracy and efficacy in real world at real time.", - "rel_num_authors": 5, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.06.20240903", + "rel_abs": "In this article, the spread of breathing air when playing wind instruments and singing was investigated and visualized using two methods: (1) schlieren imaging with a schlieren mirror and (2) background-oriented schlieren (BOS). These methods visualize airflow by visualizing density gradients in transparent media. The playing of professional woodwind and brass instrument players, as well as professional classical trained singers, were investigated to estimate the spread distances of the breathing air. For a better comparison and consistent measurement series, a single high and a single low note as well as an extract of a musical piece were investigated. Additionally, anemometry was used to determine the velocity of the spreading breathing air and the extent to which it was still quantifiable. The results presented in this article show there is no airflow escaping from the instruments, which is transported farther than 1.2 m into the room. However, differences in the various instruments have to be considered to assess properly the spread of the breathing air. The findings discussed below help to estimate the risk of cross-infection for wind instrument players and singers and to develop efficacious safety precautions, which is essential during critical health periods such as the current COVID-19 pandemic.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Yan Chen", - "author_inst": "SeekIn Inc" + "author_name": "Lia Becher", + "author_inst": "Bauhaus-University Weimar, Department of Building Physics, Weimar, Germany" }, { - "author_name": "Shiyong Li", - "author_inst": "SeekIn Inc" + "author_name": "Amayu Wakoya Gena", + "author_inst": "Bauhaus-University Weimar, Department of Building Physics, Weimar, Germany" }, { - "author_name": "Wei Wu", - "author_inst": "SeekIn Inc" + "author_name": "Hayder Alsaad", + "author_inst": "Bauhaus-University Weimar, Department of Building Physics, Weimar, Germany" }, { - "author_name": "Shuaipeng Geng", - "author_inst": "Shenyou Bio" + "author_name": "Bernhard Richter", + "author_inst": "Freiburg Institute for Musicians' Medicine, Medical Faculty University Freiburg and Freiburg University of Music, Freiburg, Germany" }, { - "author_name": "Mao Mao", - "author_inst": "Yonsei University" + "author_name": "Claudia Spahn", + "author_inst": "Freiburg Institute for Musicians' Medicine, Medical Faculty University Freiburg and Freiburg University of Music, Freiburg, Germany" + }, + { + "author_name": "Conrad Voelker", + "author_inst": "Bauhaus-University Weimar, Department of Building Physics, Weimar, Germany" } ], "version": "1", - "license": "cc_by_nc_nd", - "type": "new results", - "category": "genomics" + "license": "cc_no", + "type": "PUBLISHAHEADOFPRINT", + "category": "occupational and environmental health" }, { "rel_doi": "10.1101/2021.01.06.20249035", @@ -989000,33 +989208,37 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.01.03.21249159", - "rel_title": "Pharmacokinetic modelling to estimate intracellular favipiravir ribofuranosyl-5'-triphosphate exposure to support posology for SARS-CoV-2", + "rel_doi": "10.1101/2020.12.29.20248991", + "rel_title": "Prior Bariatric Surgery in COVID-19 Positive Patients May Be Protective", "rel_date": "2021-01-05", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.03.21249159", - "rel_abs": "BackgroundThe role of favipiravir as a treatment for COVID-19 is unclear, with discrepant activity against SARS-CoV-2 in vitro, concerns about teratogenicity and pill burden, and an unknown optimal dose. In Vero-E6 cells, high concentrations are needed to inhibit SARS-CoV-2 replication. The purpose of this analysis was to use available data to simulate intracellular pharmacokinetics of favipiravir ribofuranosyl-5-triphosphate (FAVI-RTP) to better understand the putative applicability as a COVID-19 intervention.\n\nMethodsPreviously published in vitro data for the intracellular production and elimination of FAVI- RTP in MDCK cells incubated with parent favipiravir was fitted with a mathematical model to describe the time course of intracellular FAVI-RTP concentrations as a function of incubation concentration of parent favipiravir. Parameter estimates from this model fitting were then combined with a previously published population PK model for the plasma exposure of parent favipiravir in Chinese patients with severe influenza (the modelled free plasma concentration of favipiravir substituting for in vitro incubation concentration) to predict the human intracellular FAVI-RTP pharmacokinetics.\n\nResultsIn vitro FAVI-RTP data was adequately described as a function of in vitro incubation media concentrations of parent favipiravir with an empirical model, noting that the model simplifies and consolidates various processes and is used under various assumptions and within certain limits. Parameter estimates from the fittings to in vitro data predict a flatter dynamic range of peak to trough for intracellular FAVI-RTP when driven by a predicted free plasma concentration profile.\n\nConclusionThis modelling approach has several important limitations that are discussed in the main text of the manuscript. However, the simulations indicate that despite rapid clearance of the parent drug from plasma, sufficient intracellular FAVI-RTP may be maintained across the dosing interval because of its long intracellular half-life. Population average intracellular FAVI-RTP concentrations are estimated to maintain the Km for the SARS-CoV-2 polymerase for 3 days following 800 mg BID dosing and 9 days following 1200 mg BID dosing after a 1600 mg BID loading dose on day 1. Further evaluation of favipiravir as part of antiviral combinations for SARS-CoV-2 is warranted.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.29.20248991", + "rel_abs": "IntroductionPatients infected with novel COVID-19 virus have a spectrum of illnesses ranging from asymptomatic to death. Data has shown that age, gender and obesity are strongly correlated with poor outcomes in COVID-19 positive patients. Bariatric surgery is the only treatment that provides significant, sustained weight loss in the severely obese. We look at whether prior bariatric surgery correlates with increased risk of hospitalization and outcome severity after COVID-19 infection.\n\nMethodsA cross-sectional retrospective analysis of a COVID-19 database from a single, NYC-based, academic institution was conducted. A cohort of COVID-19 positive patients with a history of bariatric surgery (n=124) were matched in a 4:1 ratio to a control cohort of COVID-19 positive patients who were eligible for bariatric surgery (BMI [≥]40 kg/m2 or BMI [≥]35 kg/m2 with a comorbidity) (n=496). A comparison of outcomes, including mechanical ventilation requirements and deceased at discharge, was done between cohorts using Chi-square test or Fishers exact test. Additionally, overall length of stay and duration of time in ICU were compared using Wilcoxon Rank Sum test. Conditional logistic regression analyses were done to determine both unadjusted (UOR) and adjusted odds ratios (AOR).\n\nResultsA total of 620 COVID-19 positive patients were included in this analysis. The categorization of bariatric surgeries included 36% Roux-en-Y Gastric Bypass (RYGB, n=45), 35% laparoscopic adjustable gastric banding (LAGB, n=44), and 28% laparoscopic sleeve gastrectomy (LSG, n=35). The body mass index (BMI) for the bariatric group was 36.1 kg/m2 (SD=8.3), which was significantly lower than the control group, 41.4 kg/m2 (SD=6.5) (p<0.0001). There was also less burden of diabetes in the bariatric group (32%) compared to the control group (48%) (p=0.0019). Patients with a history of bariatric surgery were less likely to be admitted through the emergency room (UOR=0.39, p=0.0001), less likely to have had a ventilator used during the admission (UOR=0.42, p=0.028), had a shorter length of stay in both the ICU (p=0.033) and overall (UOR=0.44, p=0.0002), and were less likely to be deceased at discharge compared to the control group (OR=0.42, p=0.028).\n\nConclusionA history of bariatric surgery significantly decreases the risk of emergency room admission, mechanical ventilation, prolonged ICU stay, and death in patients with COVID-19.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Henry Pertinez", - "author_inst": "University of Liverpool" + "author_name": "Megan Jenkins", + "author_inst": "NYU Langone Health" }, { - "author_name": "Rajith Rajoli", - "author_inst": "University of Liverpool" + "author_name": "Gabrielle Maranga", + "author_inst": "NYU Langone Health" }, { - "author_name": "Saye H Khoo", - "author_inst": "University of Liverpool" + "author_name": "G. Craig Wood", + "author_inst": "Geisinger Obesity Institute" }, { - "author_name": "Andrew Owen", - "author_inst": "University of Liverpool" + "author_name": "Christopher M Petrilli", + "author_inst": "NYU Langone Health" + }, + { + "author_name": "Christine Ren-Fielding", + "author_inst": "NYU Langone Health" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -990518,43 +990730,43 @@ "category": "neurology" }, { - "rel_doi": "10.1101/2020.12.28.20248958", - "rel_title": "Lived experiences of pregnant and new mothers during COVID-19 pandemic: A narrative analysis of YouTube birth stories.", + "rel_doi": "10.1101/2020.12.29.20249005", + "rel_title": "An Intrinsic and Extrinsic Evaluation of Learned COVID-19 Concepts using Open-Source Word Embedding Sources", "rel_date": "2021-01-04", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.28.20248958", - "rel_abs": "IntroductionThe COVID-19 pandemic has brought on unprecedented changes, not only to our daily lives but also to our healthcare system. The pandemic has particularly impacted pregnant women that must give birth with tight restrictions and significant uncertainties. Birth stories have frequently been used as a way for women to describe their experiences with the birthing process. In this uncertain time, birth stories can provide valuable insight into how pregnancy and birth stressors during a pandemic can impact the patients overall experience. This study sought to describe and understand pregnant and new mothers lived experiences during the COVID-19 pandemic.\n\nMethodsResearchers extracted relevant YouTube birth stories using predetermined search terms and inclusion criteria. The mothers birth stories were narrated in their second or third trimester or those who had recently given birth during the study period. Birth stories were analyzed using an inductive and deductive approach to capture different aspects of the birthing experience.\n\nResultsOverall, eighty-three birth stories were analyzed. Within these birth stories, four broad themes and twelve subthemes emerged. Key themes included a sense of loss, hospital experiences, experiences with healthcare providers, and unique experiences during birth and postpartum. The birth stories revealed negative and positive birth experiences. Particularly, mothers were frustrated with constantly changing policies within the healthcare setting that negatively affected their birthing experience. On the other hand, support from healthcare professionals, having their partners in the delivery room, and having a positive mindset was instrumental in having a positive birth experience.\n\nConclusionResults from this study provided a detailed description of womens lived experience with giving birth during the COVID-19 pandemic. Healthcare providers need to provide clear communication and compassionate patient-centered care to relieve womens anxiety about uncertain and unpredictable policy as the pandemic continues to evolve.", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.29.20249005", + "rel_abs": "IntroductionScientists are developing new computational methods and prediction models to better clinically understand COVID-19 prevalence, treatment efficacy, and patient outcomes. These efforts could be improved by leveraging documented, COVID-19-related symptoms, findings, and disorders from clinical text sources in the electronic health record. Word embeddings can identify terms related to these clinical concepts from both the biomedical and non-biomedical domains and are being shared with the open-source community at large. However, its unclear how useful openly-available word embeddings are for developing lexicons for COVID-19-related concepts.\n\nObjectiveGiven an initial lexicon of COVID-19-related terms, characterize the returned terms by similarity across various, open-source word embeddings and determine common semantic and syntactic patterns between the COVID-19 queried terms and returned terms specific to word embedding source.\n\nMaterials and MethodsWe compared 7 openly-available word embedding sources. Using a series of COVID-19-related terms for associated symptoms, findings, and disorders, we conducted an inter-annotator agreement study to determine how accurately the most semantically similar returned terms could be classified according to semantic types by three annotators. We conducted a qualitative study of COVID-19 queried terms and their returned terms to identify useful patterns for constructing lexicons. We demonstrated the utility of applying such terms to discharge summaries by reporting the proportion of patients identified by concept for pneumonia, acute respiratory distress syndrome, and COVID-19 cohorts.\n\nResultsWe observed high, pairwise inter-annotator agreement (Cohens Kappa) for symptoms (0.86 to 0.99), findings (0.93 to 0.99), and disorders (0.93 to 0.99). Word embedding sources generated based on characters tend to return more lexical variants and synonyms; in contrast, embeddings based on tokens more often return a variety of semantic types. Word embedding sources queried using an adjective phrase compared to a single term (e.g., dry cough vs. cough; muscle pain vs. pain) are more likely to return qualifiers of the same semantic type (e.g., \"dry\" returns consistency qualifiers like \"wet\", \"runny\"). Terms for fever, cough, shortness of breath, and hypoxia retrieved a higher proportion of patients than other clinical features. Terms for dry cough returned a higher proportion of COVID-19 patients than pneumonia and ARDS populations.\n\nDiscussionWord embeddings are a valuable technology for learning terms, including synonyms. When leveraging openly-available word embedding sources, choices made for the construction of the word embeddings can significantly influence the phrases returned.", "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Kobi V Ajayi", - "author_inst": "Texas A&M University" + "author_name": "Soham Parikh", + "author_inst": "University of Pennsylvania" }, { - "author_name": "Idethia S Harvey", - "author_inst": "Texas A&M University" + "author_name": "Anahita Davoudi", + "author_inst": "University of Pennsylvania" }, { - "author_name": "Sonya Panjwani", - "author_inst": "Texas A&M University" + "author_name": "Shun Yu", + "author_inst": "University of Pennsylvania" }, { - "author_name": "Inyang Uwak", - "author_inst": "Texas A&M University" + "author_name": "Carolina Giraldo", + "author_inst": "University of Pennsylvania" }, { - "author_name": "Whitney Garney", - "author_inst": "Texas A&M University" + "author_name": "Emily Schriver", + "author_inst": "Penn Medicine" }, { - "author_name": "Robin L Page", - "author_inst": "Texas A&M University" + "author_name": "Danielle Mowery", + "author_inst": "University of Pennsylvania" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "obstetrics and gynecology" + "category": "health informatics" }, { "rel_doi": "10.1101/2020.12.29.20248900", @@ -991968,53 +992180,45 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.12.30.20248888", - "rel_title": "The Joint Impact of COVID-19 Vaccination and Non-Pharmaceutical Interventions on Infections, Hospitalizations, and Mortality: An Agent-Based Simulation", + "rel_doi": "10.1101/2020.12.31.20249081", + "rel_title": "THE INFLUENCE OF HLA GENOTYPE ON SUSCEPTIBILITY TO, AND SEVERITY OF, COVID-19 INFECTION", "rel_date": "2021-01-04", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.30.20248888", - "rel_abs": "BackgroundVaccination against SARS-CoV-2 has the potential to significantly reduce transmission and morbidity and mortality due to COVID-19. This modeling study simulated the comparative and joint impact of COVID-19 vaccine efficacy and coverage with and without non-pharmaceutical interventions (NPIs) on total infections, hospitalizations, and deaths.\n\nMethodsAn agent-based simulation model was employed to estimate incident SARS-CoV-2 infections and COVID-19-associated hospitalizations and deaths over 18 months for the State of North Carolina, a population of roughly 10.5 million. Vaccine efficacy of 50% and 90% and vaccine coverage of 25%, 50%, and 75% (at the end of a 6-month distribution period) were evaluated. Six vaccination scenarios were simulated with NPIs (i.e., reduced mobility, school closings, face mask usage) maintained and removed during the period of vaccine distribution.\n\nResultsIn the worst-case vaccination scenario (50% efficacy and 25% coverage), 2,231,134 new SARS-CoV-2 infections occurred with NPIs removed and 799,949 infections with NPIs maintained. In contrast, in the best-case scenario (90% efficacy and 75% coverage), there were 450,575 new infections with NPIs maintained and 527,409 with NPIs removed. When NPIs were removed, lower efficacy (50%) and higher coverage (75%) reduced infection risk by a greater magnitude than higher efficacy (90%) and lower coverage (25%) compared to the worst-case scenario (absolute risk reduction 13% and 8%, respectively).\n\nConclusionSimulation results suggest that premature lifting of NPIs while vaccines are distributed may result in substantial increases in infections, hospitalizations, and deaths. Furthermore, as NPIs are removed, higher vaccination coverage with less efficacious vaccines can contribute to a larger reduction in risk of SARS-CoV-2 infection compared to more efficacious vaccines at lower coverage. Our findings highlight the need for well-resourced and coordinated efforts to achieve high vaccine coverage and continued adherence to NPIs before many pre-pandemic activities can be resumed.", - "rel_num_authors": 10, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.31.20249081", + "rel_abs": "BackgroundThe impact of COVID-19 varies markedly, not only between individual patients but also between different populations. We hypothesised that differences in human leukocyte antigen (HLA) genes might influence this variation.\n\nMethodsUsing next generation sequencing, we analysed the class I and class II classical HLA genes of 147 white British patients with variable clinical outcomes. 49 of these patients were admitted to hospital with severe COVID infection. They had no significant pre-existing comorbidities. We compared the results to those obtained from a group of 69 asymptomatic hospital workers who evidence of COVID exposure based on blood antibody testing. Allelic frequencies in both the severe and asymptomatic groups were compared to local and national healthy controls with adjustments made for age and sex. With the inclusion of hospital staff who had reported localised symptoms only (limited to loss of smell/taste, n=13) or systemic symptoms not requiring hospital treatment (n=16), we carried out ordinal logistic regression modelling to determine the relative influence of age, BMI, sex and the presence of specific HLA genes on symptomatology.\n\nFindingsWe found a significant difference in the allelic frequency of HLA-DRB1*04:01 in the severe patient compared to the asymptomatic staff group (5.1% versus 16.7%, p=0.003 after adjustment for age and sex). There was a significantly lower frequency of the haplotype DQA1*01:01/DQB1*05:01/DRB1*01:01 in the asymptomatic group compared to the background population (p=0.007). Ordinal logistic regression modelling confirmed the significant influence of DRB1*04:01 on the clinical severity of COVID-19 observed in the cohorts.\n\nInterpretationThis study provides evidence that patient age, sex, BMI and HLA genotype interact to determine the clinical outcome of COVID-19 infection.\n\nResearch in contextO_ST_ABSEvidence before this studyC_ST_ABSHLA genes are implicated in host resistance or susceptibility to a range of pathogens. No studies thus far have compared HLA allele frequencies in patients requiring hospital admission following COVID-19 exposure to a group of asymptomatic individuals.\n\nAdded value of this studyThe results indicate that the presence of HLA-DRB1*04:01 might confer protection from the development of respiratory failure following exposure to COVID. Individuals remaining asymptomatic following exposure to COVID are less likely to carry the haplotype DQA1*01:01/DQB1*05:01/DRB1*01:01 compared to the background population. This may indicate a host defence pathway not primarily dependent on an IgG response for clearance of infection. These findings conflict with larger genome wide association studies which compared HLA allelic frequencies of severely unwell patients with the background population.\n\nImplications of all the available evidenceThe findings could have implications for targeted vaccination regimes as well as helping assess the impact of social restrictions on mortality rates in different populations.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Mehul D Patel", - "author_inst": "University of North Carolina at Chapel Hill" + "author_name": "David J Langton", + "author_inst": "ExplantLab, Newcastle Helix" }, { - "author_name": "Erik Rosenstrom", - "author_inst": "North Carolina State University" - }, - { - "author_name": "Julie S Ivy", - "author_inst": "North Carolina State University" - }, - { - "author_name": "Maria E Mayorga", - "author_inst": "North Carolina State University" + "author_name": "Stephen C Bourke", + "author_inst": "North Tyneside General Hospital, North Shields, Tyne and Wear, NE29 8NH" }, { - "author_name": "Pinar Keskinocak", - "author_inst": "Georgia Institute of Technology" + "author_name": "Benedicte A Lie", + "author_inst": "Department of Medical Genetics, University of Oslo and Oslo University Hospital" }, { - "author_name": "Ross M Boyce", - "author_inst": "University of North Carolina at Chapel Hill" + "author_name": "Gabrielle Reiff", + "author_inst": "University Hospital of North Tees, Stockton, TS19 8PE" }, { - "author_name": "Kristen Hassmiller Lich", - "author_inst": "University of North Carolina at Chapel Hill" + "author_name": "Shonali Natu", + "author_inst": "University Hospital of North Tees, Stockton, TS19 8PE" }, { - "author_name": "Raymond L Smith", - "author_inst": "East Carolina University" + "author_name": "Rebecca Darlay", + "author_inst": "Institute of Human Genetics, Newcastle University, International Centre for Life, NE1 3BZ" }, { - "author_name": "Karl T Johnson", - "author_inst": "University of North Carolina at Chapel Hill" + "author_name": "John Burn", + "author_inst": "Institute of Human Genetics, Newcastle University, International Centre for Life, NE1 3BZ" }, { - "author_name": "Julie L Swann", - "author_inst": "North Carolina State University" + "author_name": "Carlos Echevarria", + "author_inst": "Royal Victoria Infirmary, Newcastle upon Tyne, NE1 4LP" } ], "version": "1", @@ -993506,47 +993710,43 @@ "category": "bioinformatics" }, { - "rel_doi": "10.1101/2021.01.02.425099", - "rel_title": "Spike protein disulfide disruption as a potential treatment for SARS-CoV-2", + "rel_doi": "10.1101/2021.01.03.425115", + "rel_title": "The ancient cardioprotective mechanisms of ACE2 bestow SARS-CoV-2 with a wide host range", "rel_date": "2021-01-04", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.01.02.425099", - "rel_abs": "The coronaviral pandemic is exerting a tremendously detrimental impact on global health, quality of life and the world economy, emphasizing the need for effective medications for current and future coronaviral outbreaks as a complementary approach to vaccines. The Spike protein, responsible for cell receptor binding and viral internalization, possesses multiple disulfide bonds raising the possibility that disulfide-reducing agents might disrupt Spike function, prevent viral entry and serve as effective drugs against SARS-CoV-2. Here we show the first experimental evidence that reagents capable of reducing disulfide bonds can inhibit viral infection in cell-based assays. Molecular dynamics simulations of the Spike receptor-binding domain (RBD) predict increased domain flexibility when the four disulfide bonds of the domain are reduced. This flexibility is particularly prominent for the surface loop, comprised of residues 456-490, which interacts with the Spike cell receptor ACE2. Consistent with this finding, the addition of exogenous disulfide bond reducing agents affects the RBD secondary structure, lowers its melting temperature from 52 to 36-39{degrees}C and decreases its binding affinity to ACE2 by two orders of magnitude at 37{degrees}C. Finally, the reducing agents dithiothreitol (DTT) and tris(2-carboxyethyl)phosphine (TCEP) inhibit viral replication at high {micro}M - low mM levels with a negligible effect on cell viability at these concentrations. The antiviral effect of monothiol-based reductants N-Acetyl-L-cysteine (NAC) and reduced glutathione (GSH) was not observed due to decreases in cell viability. Our research demonstrates the clear potential for medications that disrupt Spike disulfides as broad-spectrum anticoronaviral agents and as a first-line defense against current and future outbreaks.", - "rel_num_authors": 7, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.01.03.425115", + "rel_abs": "SARS-CoV-2 infects a broader range of mammalian species than previously anticipated, suggesting there may be additional unknown hosts wherein the virus can evolve and potentially circumvent effective vaccines. We find that SARS-CoV-2 gains a wide host range by binding ACE2 sites essential for ACE2 carboxypeptidase activity. Six mutations found only in rodent species immune to SARS-CoV-2 are sufficient to abolish viral binding to human and dog ACE2. This is achieved through context-dependent mutational effects (intramolecular epistasis) conserved despite ACE2 sequence divergence between species. Across mammals, this epistasis generates sequence-function diversity, but through structures all bound by SARS-CoV-2. Mutational trajectories to the mouse conformation not bound by SARS-CoV-2 are blocked, by single mutations functionally deleterious in isolation, but compensatory in combination, explaining why human polymorphisms at these sites are virtually non-existent. Closed to humans, this path was opened to rodents via permissive cardiovascular phenotypes and ancient increases to ACE2 activity, serendipitously granting SARS-CoV-2 immunity. This reveals how ancient evolutionary trajectories are linked with unprecedented phenotypes such as COVID-19 and suggests extreme caution should be taken to monitor and prevent emerging animal reservoirs of SARS-CoV-2.\n\nOne sentence summaryA conserved mechanism essential for ACE2 catalytic activity is exploited by SARS-CoV-2 binding, allowing the virus to infect a wide range of species.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Andrey M. Grishin", - "author_inst": "University of Saskatchewan" - }, - { - "author_name": "Nataliya V. Dolgova", - "author_inst": "University of Saskatchewan" + "author_name": "Gianni M Castiglione", + "author_inst": "Johns Hopkins University" }, { - "author_name": "Shelby Harms", - "author_inst": "University of Saskatchewan" + "author_name": "Lingli Zhou", + "author_inst": "Johns Hopkins University" }, { - "author_name": "Ingrid J. Pickering", - "author_inst": "University of Saskatchewan" + "author_name": "Zhenhua Xu", + "author_inst": "Johns Hopkins University" }, { - "author_name": "Graham N. George", - "author_inst": "University of Saskatchewan" + "author_name": "Zachary Neiman", + "author_inst": "Johns Hopkins University" }, { - "author_name": "Darryl Falzarano", - "author_inst": "University of Saskatchewan" + "author_name": "Chien-Fu Hung", + "author_inst": "Johns Hopkins University" }, { - "author_name": "Miroslaw Cygler", - "author_inst": "University of Saskatchewan" + "author_name": "Elia J Duh", + "author_inst": "Johns Hopkins School of Medicine" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "new results", - "category": "microbiology" + "category": "molecular biology" }, { "rel_doi": "10.1101/2021.01.03.425141", @@ -995272,23 +995472,23 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.12.27.20248905", - "rel_title": "Probability that an infection like Covid-19 stops without reaching herd immunity, calculated with a stochastic agent-based model.", + "rel_doi": "10.1101/2020.12.26.20248883", + "rel_title": "Covid-19, Lockdowns and Motor Vehicle Collisions: Empirical Evidence from Greece", "rel_date": "2021-01-02", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.27.20248905", - "rel_abs": "The spread of an infection is simulated with a stochastic agent-based model. In a certain range of R0 values, the infection either rapidly comes to halt or a large proportion of the population is infected until herd immunity is achieved. Which of these two possibilities actually occurs is random. The probability of each case is determined quasi-empirically. This stochastic phenomenon may explain unexpected infection trajectories.", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.26.20248883", + "rel_abs": "Reduced mobility during Covid-19 lockdowns means fewer vehicles at risk of collision, but also an opportunity to speed on empty streets. Other collision risk factors that have changed during the pandemic include alcohol consumption, sleeping patterns, distraction, unemployment and economic uncertainty. Evidence on the impact of the Covid-19 pandemic on motor vehicle collisions is scarce, as such statistics are often released with a delay. The objective of this paper is to examine the impact of the first wave of the pandemic and the first lockdown on motor vehicle collisions and associated injuries and deaths in Greece. Using monthly data at the regional unit level, I provide descriptive evidence and subsequently follow a difference-in-difference econometric approach, comparing trends in 2020 to those of the previous five years while controlling for unemployment and petrol prices. I found a steep decline in collisions, injuries and deaths compared to what would have been otherwise expected. In March and April 2020, there were about 1,226 fewer collisions, 72 fewer deaths, 40 fewer serious injuries and 1,426 fewer minor injuries compared to what would have been expected in the absence of the pandemic.", "rel_num_authors": 1, "rel_authors": [ { - "author_name": "Manfred Karl Robert Eissler", - "author_inst": "Praxis Dres Eissler" + "author_name": "Sotiris Vandoros", + "author_inst": "King's College London and Harvard T.H. Chan School of Public Health" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "public and global health" }, { "rel_doi": "10.1101/2020.12.26.20248865", @@ -996893,73 +997093,41 @@ "category": "genomics" }, { - "rel_doi": "10.1101/2020.12.29.424482", - "rel_title": "Structural basis for broad coronavirus neutralization", + "rel_doi": "10.1101/2020.12.29.424733", + "rel_title": "SARS-CoV-2 highly conserved s2m element dimerizes via a kissing complex and interacts with host miRNA-1307-3p", "rel_date": "2020-12-29", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.12.29.424482", - "rel_abs": "Three highly pathogenic {beta}-coronaviruses crossed the animal-to-human species barrier in the past two decades: SARS-CoV, MERS-CoV and SARS-CoV-2. SARS-CoV-2 has infected more than 64 million people worldwide, claimed over 1.4 million lives and is responsible for the ongoing COVID-19 pandemic. We isolated a monoclonal antibody, termed B6, cross-reacting with eight {beta}-coronavirus spike glycoproteins, including all five human-infecting {beta}-coronaviruses, and broadly inhibiting entry of pseudotyped viruses from two coronavirus lineages. Cryo-electron microscopy and X-ray crystallography characterization reveal that B6 binds to a conserved cryptic epitope located in the fusion machinery and indicate that antibody binding sterically interferes with spike conformational changes leading to membrane fusion. Our data provide a structural framework explaining B6 cross-reactivity with {beta}-coronaviruses from three lineages along with proof-of-concept for antibody-mediated broad coronavirus neutralization elicited through vaccination. This study unveils an unexpected target for next-generation structure-guided design of a pan-coronavirus vaccine.", - "rel_num_authors": 15, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.12.29.424733", + "rel_abs": "The ongoing COVID-19 pandemic highlights the necessity for a more fundamental understanding of the coronavirus life cycle. The causative agent of the disease, SARS-CoV-2, is being studied extensively from a structural standpoint in order to gain insight into key molecular mechanisms required for its survival. Contained within the untranslated regions of the SARS-CoV-2 genome are various conserved stem-loop elements that are believed to function in RNA replication, viral protein translation, and discontinuous transcription. While the majority of these regions are variable in sequence, a 41-nucleotide s2m element within the 3 UTR is highly conserved among coronaviruses and three other viral families. In this study, we demonstrate that the s2m element of SARS-CoV-2 dimerizes by forming an intermediate homodimeric kissing complex structure that is subsequently converted to a thermodynamically stable duplex conformation. This process is aided by the viral nucleocapsid protein, potentially indicating a role in mediating genome dimerization. Furthermore, we demonstrate that the s2m element interacts with multiple copies of host cellular miRNA-1307-3p. Taken together, our results highlight the potential significance of the dimer structures formed by the s2m element in key biological processes and implicate the motif as a possible therapeutic drug target for COVID-19 and other coronavirus-related diseases.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Maximilian Sauer", - "author_inst": "University of Washington" - }, - { - "author_name": "Young-Jun Park", - "author_inst": "University of Washington" - }, - { - "author_name": "M. Alejandra Tortorici", - "author_inst": "University of Washington" - }, - { - "author_name": "Alexandra C Walls", - "author_inst": "University of Washington" - }, - { - "author_name": "Leah Homad", - "author_inst": "Fred Hutchinson Cancer Research Center" - }, - { - "author_name": "Oliver Acton", - "author_inst": "University of Washington" - }, - { - "author_name": "John E Bowen", - "author_inst": "University of Washington" - }, - { - "author_name": "Chunyan Wang", - "author_inst": "Utrecht University" - }, - { - "author_name": "Xiaoli Xiong", - "author_inst": "University of Washington" + "author_name": "Joshua A. Imperatore", + "author_inst": "Duquesne University" }, { - "author_name": "Willem de van der Schueren", - "author_inst": "Fred Hutchinson Cancer Research Center" + "author_name": "Caylee L Cunningham", + "author_inst": "Duquesne University" }, { - "author_name": "Joel Quispe", - "author_inst": "University of Washington" + "author_name": "Kendy A. Pellegrene", + "author_inst": "Duquesne University" }, { - "author_name": "Berend-Jan Bosch", - "author_inst": "Utrecht University" + "author_name": "Robert G. Brinson", + "author_inst": "Institute for Bioscience and Biotechnology Research, National Institute of Standards and Technology and the University of Maryland" }, { - "author_name": "Benjamin G Hoffstrom", - "author_inst": "Fred Hutchinson Cancer Research Center" + "author_name": "John P. Marino", + "author_inst": "Institute for Bioscience and Biotechnology Research, National Institute of Standards and Technology and the University of Maryland" }, { - "author_name": "Andrew T McGuire", - "author_inst": "Fred Hutchinson Cancer Research Center" + "author_name": "Jeffrey D. Evanseck", + "author_inst": "Duquesne University" }, { - "author_name": "David Veesler", - "author_inst": "University of Washington" + "author_name": "Mihaela Rita Mihailescu", + "author_inst": "Duquesne University" } ], "version": "1", @@ -998538,99 +998706,83 @@ "category": "biophysics" }, { - "rel_doi": "10.1101/2020.12.23.20248598", - "rel_title": "Genomic characterization of a novel SARS-CoV-2 lineage from Rio de Janeiro, Brazil", + "rel_doi": "10.1101/2020.12.23.20231589", + "rel_title": "Characteristics of SARS-CoV-2 Testing for Rapid Diagnosis of COVID-19 during the Initial Stages of a Global Pandemic", "rel_date": "2020-12-26", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.23.20248598", - "rel_abs": "In this study, we report the sequencing of 180 new viral genomes obtained from different municipalities of the state of Rio de Janeiro from April to December 2020. We identified a novel lineage of SARS-CoV-2, originated from B.1.1.28, distinguished by five single-nucleotide variants (SNVs): C100U, C28253U, G28628U, G28975U, and C29754U. The SNV G23012A (E484K), in the receptor-binding domain of Spike protein, was widely spread across the samples. This mutation was previously associated with escape from neutralizing antibodies against SARS-CoV-2. This novel lineage emerged in late July being first detected by us in late October and still mainly restricted to the capital of the state. However, as observed for other strains it can be rapidly spread in the state. The significant increase in the frequency of this lineage raises concerns about public health management and continuous need for genomic surveillance during the second wave of infections.\n\nArticle Summary LineWe identified a novel circulating lineage of SARS-CoV-2 in the state of Rio de Janeiro Brazil originated from B.1.1.28 lineage.", - "rel_num_authors": 20, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.23.20231589", + "rel_abs": "Accurate SARS-CoV-2 diagnosis is essential to guide prevention and control of COVID-19. From January 11 - April 22, 2020, Public Health Ontario conducted SARS-CoV-2 testing of 86,942 specimens collected from 80,354 individuals, primarily using real-time reverse-transcription polymerase chain reaction (rRT-PCR) methods. We analyzed test results across specimen types and for individuals with multiple same-day and multi-day collected specimens. Nasopharyngeal compared to throat swabs had a higher positivity (8.8% vs. 4.8%) and an adjusted estimate 2.9 Ct lower (SE=0.5, p<0.001). Same-day specimens showed high concordance (98.8%), and the median Ct of multi-day specimens increased over time. Symptomatic cases had rRT-PCR results with an adjusted estimate 3.0 Ct (SE=0.5, p<0.001) lower than asymptomatic/pre-symptomatic cases. Overall test sensitivity was 84.6%, with a negative predictive value of 95.5%. Molecular testing is the mainstay of SARS-CoV-2 diagnosis and testing protocols will continue to be dynamic and iteratively modified as more is learned about this emerging pathogen.", + "rel_num_authors": 16, "rel_authors": [ { - "author_name": "Carolina M Voloch", - "author_inst": "Universidade Federal do Rio de Janeiro" - }, - { - "author_name": "Ronaldo da Silva Francisco Junior", - "author_inst": "Laboratorio Nacional de Computacao Cientifica" - }, - { - "author_name": "Luiz Gonzaga P de Almeida", - "author_inst": "Laboratorio Nacional de Computacao Cientifica" - }, - { - "author_name": "Cynthia C Cardoso", - "author_inst": "Universidade Federal do Rio de Janeiro" - }, - { - "author_name": "Otavio J Brustolini", - "author_inst": "Laboratorio Nacional de Computacao Cientifica" + "author_name": "Jennifer L Guthrie", + "author_inst": "Public Health Ontario" }, { - "author_name": "Alexandra L Gerber", - "author_inst": "Laboratorio Nacional de Computacao Cientifica" + "author_name": "Allison J Chen", + "author_inst": "Public Health Ontario" }, { - "author_name": "Ana Paula de C Guimaraes", - "author_inst": "Laboratorio Nacional de Computacao Cientifica" + "author_name": "Dalton R Budhram", + "author_inst": "Public Health Ontario" }, { - "author_name": "Diana Mariani", - "author_inst": "Universidade Federal do Rio de Janeiro" + "author_name": "Kirby Cronin", + "author_inst": "Public Health Ontario" }, { - "author_name": "Raissa Mirella da Costa", - "author_inst": "Universidade Federal do Rio de Janeiro; Hospital Naval Marcilio Dias" + "author_name": "Adriana Peci", + "author_inst": "Public Health Ontario" }, { - "author_name": "Orlando Costa Ferreira Junior", - "author_inst": "Universidade Federal do Rio de Janeiro" + "author_name": "Paul Nelson", + "author_inst": "Public Health Ontario" }, { - "author_name": "- Covid19-UFRJ Workgroup", - "author_inst": "" + "author_name": "Gustavo V Mallo", + "author_inst": "Public Health Ontario" }, { - "author_name": "- LNCC-Workgroup", - "author_inst": "" + "author_name": "George Broukhanski", + "author_inst": "Public Health Ontario" }, { - "author_name": "Adriana Cony Cavalcanti", - "author_inst": "Laboratorio Central de Saude Publica Noel Nutels, Rio de Janeiro, Brazil" + "author_name": "Michelle Murti", + "author_inst": "Public Health Ontario" }, { - "author_name": "Thiago Silva Frauches", - "author_inst": "Secretaria Municipal de Saude de Marica, Marica, Brazil" + "author_name": "Anna Majury", + "author_inst": "Public Health Ontario" }, { - "author_name": "Claudia Maria Braga de Mello", - "author_inst": "Secretaria Estadual de Saude do Rio de Janeiro, Rio de Janeiro, Brazil." + "author_name": "Tony Mazzulli", + "author_inst": "Public Health Ontario" }, { - "author_name": "Rafael de Mello Galiez", - "author_inst": "Universidade Federal do Rio de Janeiro" + "author_name": "Vanessa G Allen", + "author_inst": "Public Health Ontario" }, { - "author_name": "Debora Souza Faffe", - "author_inst": "Universidade Federal do Rio de Janeiro" + "author_name": "Samir N Patel", + "author_inst": "Public Health Ontario" }, { - "author_name": "Terezinha M P P Castineira", - "author_inst": "Universidade Federal do Rio de Janeiro" + "author_name": "Julianne V Kus", + "author_inst": "Public Health Ontario" }, { - "author_name": "AMILCAR TANURI", - "author_inst": "Universidade Federal do Rio de Janeiro" + "author_name": "Vanessa Tran", + "author_inst": "Public Health Ontario" }, { - "author_name": "Ana Tereza Ribeiro de Vasconcelos", - "author_inst": "Universidade Federal do Rio de Janeiro" + "author_name": "Jonathan B Gubbay", + "author_inst": "Public Health Ontario" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "genetic and genomic medicine" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2020.12.23.20248425", @@ -1000212,119 +1000364,55 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.12.24.20248822", - "rel_title": "Estimated transmissibility and severity of novel SARS-CoV-2 Variant of Concern 202012/01 in England", - "rel_date": "2020-12-26", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.24.20248822", - "rel_abs": "A novel SARS-CoV-2 variant, VOC 202012/01 (lineage B.1.1.7), emerged in southeast England in November 2020 and is rapidly spreading towards fixation. Using a variety of statistical and dynamic modelling approaches, we estimate that this variant has a 43-90% (range of 95% credible intervals 38-130%) higher reproduction number than preexisting variants. A fitted two-strain dynamic transmission model shows that VOC 202012/01 will lead to large resurgences of COVID-19 cases. Without stringent control measures, including limited closure of educational institutions and a greatly accelerated vaccine roll-out, COVID-19 hospitalisations and deaths across England in 2021 will exceed those in 2020. Concerningly, VOC 202012/01 has spread globally and exhibits a similar transmission increase (59-74%) in Denmark, Switzerland, and the United States.", - "rel_num_authors": 25, + "rel_doi": "10.1101/2020.12.23.423942", + "rel_title": "SARS-CoV-2 infecting the inner ear results in potential hearing damage at the early stage or prognosis of COVID-19 in rodents", + "rel_date": "2020-12-25", + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2020.12.23.423942", + "rel_abs": "ObjectivesIn order to find out the association between the sensorineural hearing loss and COVID-19, we detected the expression ACE2 and TMPRSS2 in the mouse the hamster.\n\nDesignUsing the public data from NCBI and GISAID, we assessed the expression of ACE2 and TMPRSS2 at the transcriptomic, DNA, and protein levels of ACE2 in the brain, inner ear, and muscle from the golden Syrian hamster (Mesocricetus auratus) and mouse (Mus musculus).\n\nResultsWe identified ACE2 and TMPRSS2 expressed at different level in the inner ear and brain at DNA and transcriptomic levels of both mouse and the hamster. The protein expression shows a similar pattern of the brain and inner ear, while the expression of ACE2 from the inner ear was relatively higher than it from the muscle.\n\nConclusionSARS-CoV-2 could infect the hearing system potentially and SSNHL could be a characteristic to detect asymptomatic patients of COVID-19.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Nicholas G Davies", - "author_inst": "London School of Hygiene and Tropical Medicine" - }, - { - "author_name": "Sam Abbott", - "author_inst": "London School of Hygiene and Tropical Medicine" - }, - { - "author_name": "Rosanna C. Barnard", - "author_inst": "London School of Hygiene and Tropical Medicine" - }, - { - "author_name": "Christopher I. Jarvis", - "author_inst": "London School of Hygiene and Tropical Medicine" - }, - { - "author_name": "Adam J. Kucharski", - "author_inst": "London School of Hygiene & Tropical Medicine" - }, - { - "author_name": "James D Munday", - "author_inst": "London School of Hygiene and Tropical Medicine" - }, - { - "author_name": "Carl A. B. Pearson", - "author_inst": "London School of Hygiene and Tropical Medicine" - }, - { - "author_name": "Timothy Russell", - "author_inst": "London School of Hygiene and Tropical Medicine" - }, - { - "author_name": "Damien Tully", - "author_inst": "London School of Hygiene and Tropical Medicine" - }, - { - "author_name": "Alex D. Washburne", - "author_inst": "Selva Analytics LLC" - }, - { - "author_name": "Tom Wenseleers", - "author_inst": "KU Leuven" - }, - { - "author_name": "Amy Gimma", - "author_inst": "London School of Hygiene and Tropical Medicine" - }, - { - "author_name": "William Waites", - "author_inst": "London School of Hygiene and Tropical Medicine" - }, - { - "author_name": "Kerry L. M. Wong", - "author_inst": "London School of Hygiene and Tropical Medicine" - }, - { - "author_name": "Kevin van Zandvoort", - "author_inst": "London School of Hygiene and Tropical Medicine" - }, - { - "author_name": "Justin D. Silverman", - "author_inst": "College of Information Science and Technology, Pennsylvania State University" - }, - { - "author_name": "- CMMID COVID-19 Working Group", - "author_inst": "" + "author_name": "Xia Xue", + "author_inst": "Zhengzhou University" }, { - "author_name": "- The COVID-19 Genomics UK (COG-UK) Consortium", - "author_inst": "" + "author_name": "Yongan Tian", + "author_inst": "Zhengzhou University" }, { - "author_name": "Karla Diaz-Ordaz", - "author_inst": "London School of Hygiene and Tropical Medicine" + "author_name": "Mingsan Miao", + "author_inst": "Henan University of Chinese Medicine" }, { - "author_name": "Ruth H Keogh", - "author_inst": "London School of Hygiene and Tropical Medicine" + "author_name": "Jianyao Wang", + "author_inst": "Zhengzhou University" }, { - "author_name": "Rosalind M Eggo", - "author_inst": "London School of Hygiene and Tropical Medicine" + "author_name": "Wenxue Tang", + "author_inst": "Zhengzhou University" }, { - "author_name": "Sebastian Funk", - "author_inst": "London School of Hygiene and Tropical Medicine" + "author_name": "Yaohe Wang", + "author_inst": "Zhengzhou University" }, { - "author_name": "Mark Jit", - "author_inst": "London School of Hygiene and Tropical Medicine" + "author_name": "Jianbo Liu", + "author_inst": "The Second Affiliated Hospital of Zhengzhou University" }, { - "author_name": "Katherine E. Atkins", - "author_inst": "London School of Hygiene and Tropical Medicine" + "author_name": "Hongen Xu", + "author_inst": "Zhengzhou University" }, { - "author_name": "W. John Edmunds", - "author_inst": "London School of Hygiene and Tropical Medicine" + "author_name": "Jinxin Miao", + "author_inst": "Henan University of Chinese Medicine" } ], "version": "1", - "license": "cc_by", - "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "license": "cc_no", + "type": "new results", + "category": "bioinformatics" }, { "rel_doi": "10.1101/2020.12.23.424229", @@ -1002190,39 +1002278,103 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2020.12.22.20248676", - "rel_title": "Acceptance and Attitudes Toward COVID-19 Vaccines: A Cross-Sectional Study from Jordan", + "rel_doi": "10.1101/2020.12.23.20248758", + "rel_title": "Introduction into the Marseille geographical area of a mild SARS-CoV-2 variant originating from sub-Saharan Africa", "rel_date": "2020-12-24", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.22.20248676", - "rel_abs": "BackgroundVaccines are effective interventions that can reduce the high burden of diseases globally. However, public vaccine hesitancy is a pressing problem for public health authorities. With the availability of COVID-19 vaccines, little information is available on the public acceptability and attitudes towards the COVID-19 vaccines in Jordan. This study aimed to investigate the acceptability of COVID-19 vaccines and its predictors in addition to the attitudes towards these vaccines among public in Jordan.\n\nMethodsAn online, cross-sectional, and self-administered questionnaire was instrumentalized to survey adult participants from Jordan on the acceptability of COVID-19 vaccines. Logistic regression analysis was used to find the predictors of COVID-19 vaccines acceptability.\n\nResultsA total of 3,100 participants completed the survey. The public acceptability of COVID-19 vaccines was fairly low (37.4%) in Jordan. Males (OR=2.488, 95CI%=1.834-3.375, p<.001) and those who took the seasonal influenza vaccine (OR=2.036, 95CI%=1.306-3.174, p=.002) were more likely to accept Covid-19 vaccines. Similarly, participants who believed that vaccines are generally safe (OR=9.258, 95CI%=6.020-14.237, p<.001) and those who were willing to pay for vaccines (OR=19.223, 95CI%=13.665-27.042, p<.001), once available, were more likely to accept the COVID-19 vaccines. However, those above 35 years old (OR=0.376, 95CI%=0.233-0.607, p<.001) and employed participants (OR=0.542, 95CI%=0.405-0.725, p<.001) were less likely to accept the COVID-19 vaccines. Moreover, participants who believed that there was a conspiracy behind COVID-19 (OR=0.502, 95CI%=0.356- 0.709, p<.001) and those who do not trust any source of information on COVID-19 vaccines (OR=0.271, 95CI%=0.183 - 0.400, p<.001), were less likely to have acceptance towards them. The most trusted sources of information on COVID-19 vaccines were healthcare providers.\n\nConclusionSystematic interventions are required by public health authorities to reduce the levels of vaccines hesitancy and improve their acceptance. We believe these results and specifically the low rate of acceptability is alarming to Jordanian health authorities and should stir further studies on the root causes and the need of awareness campaigns. These interventions should take the form of reviving the trust in national health authorities and structured awareness campaigns that offer transparent information about the safety and efficacy of the vaccines and the technology that was utilized in their production.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.23.20248758", + "rel_abs": "BACKGROUNDIn Marseille, France, the COVID-19 incidence evolved unusually with several successive epidemic episodes. The second outbreak started in July, was associated with North Africa, and involved travelers and an outbreak on passenger ships. This suggested the involvement of a new viral variant.\n\nMETHODSWe sequenced the genomes from 916 SARS-CoV-2 strains from COVID-19 patients in our institute. The patients demographic and clinical features were compared according to the infecting viral variant.\n\nRESULTSFrom June 26th to August 14th, we identified a new viral variant (Marseille-1). Based on genome sequences (n=89) or specific qPCR (n=53), 142 patients infected with this variant were detected. It is characterized by a combination of 10 mutations located in the nsp2, nsp3, nsp12, S, ORF3a, ORF8 and N/ORF14 genes. We identified Senegal and Gambia, where the virus had been transferred from China and Europe in February-April as the sources of the Marseille-1 variant, which then most likely reached Marseille through Maghreb when French borders reopened. In France, this variant apparently remained almost limited to Marseille. In addition, it was significantly associated with a milder disease compared to clade 20A ancestor strains.\n\nCONCLUSIONOur results demonstrate that SARS-CoV-2 can genetically diversify rapidly, its variants can diffuse internationally and cause successive outbreaks.", + "rel_num_authors": 21, "rel_authors": [ { - "author_name": "Tamam El-Elimat", - "author_inst": "Department of Medicinal Chemistry and Pharmacognosy, Faculty of Pharmacy, Jordan University of Science and Technology, Irbid 22110, Jordan" + "author_name": "Philippe Colson", + "author_inst": "Aix-Marseille university" }, { - "author_name": "Mahmoud M. AbuAlSamen", - "author_inst": "Department of Family and Community Medicine, Faculty of Medicine, University of Jordan, Amman 11942, Jordan" + "author_name": "Anthony Levasseur", + "author_inst": "Aix-Marseille University" }, { - "author_name": "Basima A. Almomani", - "author_inst": "Department of Clinical Pharmacy, Faculty of Pharmacy, Jordan University of Science and Technology, Irbid 22110, Jordan" + "author_name": "Philippe Gautret", + "author_inst": "IHU Mediterranee Infection" + }, + { + "author_name": "Florence Fenollar", + "author_inst": "University Aix-Marseille (URMITE)" + }, + { + "author_name": "Van-Thuan Hoang", + "author_inst": "Thai Binh Medical University of Medicine and Pharmacy" + }, + { + "author_name": "Jeremy Delerce", + "author_inst": "Aix-Marseille University" + }, + { + "author_name": "Idir Bitam", + "author_inst": "Ecole Nationale Superieure en Sciences de l'Aliment et des Industries Agroalimentaire, Alger, Algeria" + }, + { + "author_name": "Rachid Saile", + "author_inst": "Hassan II University of Casablanca, Morocco" + }, + { + "author_name": "Mossaab Maaloum", + "author_inst": "Hassan II University of Casablanca, Morocco" }, { - "author_name": "Nour A. Al-Sawalha", - "author_inst": "Department of Clinical Pharmacy, Faculty of Pharmacy, Jordan University of Science and Technology, Irbid 22110, Jordan" + "author_name": "Abdou Padane", + "author_inst": "Institut de Recherche en Sante, de Surveillance Epidemiologique et de Formation (IRESSEF), Rufisque, Senegal" }, { - "author_name": "Feras Q. Alali", - "author_inst": "Faculty of Pharmacy, QU Health, Qatar University, Doha 2713, Qatar and Biomedical and Pharmaceutical Research Unit, QU Health, Qatar University, Doha 2713, Qata" + "author_name": "Marielle Bedotto", + "author_inst": "IHU Mediterranee Infection, Marseille, France" + }, + { + "author_name": "Ludivine Brechard", + "author_inst": "IHU Mediterranee-infection, Marseille, France" + }, + { + "author_name": "Vincent Bossi", + "author_inst": "IHU Mediterranee-Infection" + }, + { + "author_name": "Mariem Ben Khedher", + "author_inst": "Aix-Marseille Univ, Microbes Evolution Phylogeny and Infections (MEPHI), Marseille, France" + }, + { + "author_name": "Herve Chaudet", + "author_inst": "IHU Mediterranee Infection, Marseille, France" + }, + { + "author_name": "Matthieu Million", + "author_inst": "Aix-Marseille university, Marseille, France" + }, + { + "author_name": "Herve Tissot-Dupont", + "author_inst": "IHU Mediterranee Infection, Marseille, France" + }, + { + "author_name": "Jean Christophe Lagier", + "author_inst": "IHU Mediterranee Infection" + }, + { + "author_name": "Souleymane Mboup", + "author_inst": "Institut de Recherche en Sante, de Surveillance Epidemiologique et de Formation (IRESSEF), Rufisque, Senegal" + }, + { + "author_name": "Pierre-Edouard Fournier", + "author_inst": "IHU Mediterranee Infection" + }, + { + "author_name": "Didier Raoult", + "author_inst": "URMITE CNRS-IRD-INSERM" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "health policy" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2020.12.22.20245993", @@ -1003763,39 +1003915,83 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2020.12.22.423894", - "rel_title": "Ferritin nanoparticle based SARS-CoV-2 RBD vaccine induces persistent antibody response and long-term memory in mice", + "rel_doi": "10.1101/2020.12.22.423965", + "rel_title": "Development of a novel hybrid alphavirus-SARS-CoV-2 particle for rapid in vitro screening and quantification of neutralization antibodies, antiviral drugs, and viral mutations", "rel_date": "2020-12-23", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.12.22.423894", - "rel_abs": "Since the outbreak of COVID-19, over 200 vaccine candidates have been documented and some of them have advanced to clinical trials with encouraging results. However, the antibody persistence over 3 months post immunization and the long-term memory have been rarely reported. Here, we report that a ferritin nanoparticle based SARS-CoV-2 RBD vaccine induced in mice an efficient antibody response which lasts for at least 7 months post immunization. Significantly higher number of memory B cells were maintained and a significantly higher level of recall response was induced upon antigen challenge. Thus, we believe our current study provide the first information about the long-term antibody persistence and memory response of a COVID-19 vaccine. This information would be also timely useful for the development and evaluation of other vaccines.", - "rel_num_authors": 5, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.12.22.423965", + "rel_abs": "Timely development of vaccines and antiviral drugs is critical to control the COVID-19 pandemic 1-6. Current methods for quantifying vaccine-induced neutralizing antibodies involve the use of pseudoviruses, such as the SARS-CoV-2 spike protein (S) pseudotyped lentivirus7-14. However, these pseudoviruses contain structural proteins foreign to SARS-CoV-2, and require days to infect and express reporter genes15. Here we describe the development of a new hybrid alphavirus-SARS-CoV-2 (Ha-CoV-2) particle for rapid and accurate quantification of neutralization antibodies and viral variants. Ha-CoV-2 is a non-replicating SARS-CoV-2 virus-like particle, composed of SARS-CoV-2 structural proteins (S, M, N, and E) and a RNA genome derived from a fast expressing alphavirus vector 16. We demonstrated that Ha-CoV-2 can rapidly and robustly express reporter genes in target cells within 3-6 hours. We further validated Ha-CoV-2 for rapid quantification of neutralization antibodies, viral variants, and antiviral drugs. In addition, as a proof-of-concept, we assembled and compared the relative infectivity of a panel of 10 Ha-CoV-2 variant isolates (D614G, P.1, B.1.1.207, B.1.351, B.1.1.7, B.1.429, B.1.258, B.1.494, B.1.2, B.1.1298), and demonstrated that these variants in general are 2-10 fold more infectious. Furthermore, we quantified the anti-serum from an infected and vaccinated individual; the one dose vaccination with Moderna mRNA-1273 has greatly increased the anti-serum titer for approximately 6 fold. The post-vaccination serum has also demonstrated various neutralizing activities against all 9 variants tested. These results demonstrated that Ha-CoV-2 can be used as a robust platform for rapid quantification of neutralizing antibodies against SARS-CoV-2 and its variants.", + "rel_num_authors": 16, "rel_authors": [ { - "author_name": "Wenjun Wang", - "author_inst": "Institute of Biophysics, Chinese Academy of Sciences" + "author_name": "Brian Hetrick", + "author_inst": "George Mason University" }, { - "author_name": "Baoying Huang", - "author_inst": "National Institute for Viral Disease Control and Prevention, China CDC" + "author_name": "Sijia He", + "author_inst": "George Mason University" }, { - "author_name": "Yanping Zhu", - "author_inst": "Institute of Biophysics, Chinese Academy of Sciences" + "author_name": "Linda D Chilin", + "author_inst": "George Mason University" }, { - "author_name": "Wenjie Tan", - "author_inst": "National Institute for Viral Disease Control and Prevention, China CDC" + "author_name": "Deemah Dabbagh", + "author_inst": "George Mason University" }, { - "author_name": "Mingzhao Zhu", - "author_inst": "Institute of Biophysics, Chinese Academy of Sciences" + "author_name": "Farhang Alem", + "author_inst": "George Mason university" + }, + { + "author_name": "Aarthi Narayanan", + "author_inst": "George Mason University" + }, + { + "author_name": "Alessandra Luchini", + "author_inst": "George Mason University" + }, + { + "author_name": "Tuanjie Li", + "author_inst": "Georgetown University" + }, + { + "author_name": "Xuefeng Liu", + "author_inst": "Georgetown University" + }, + { + "author_name": "Joshua Copeland", + "author_inst": "TruGenomix Inc" + }, + { + "author_name": "Angela Pak", + "author_inst": "TruGenomix Inc" + }, + { + "author_name": "Tshaka Cunningham", + "author_inst": "TruGenomix Inc." + }, + { + "author_name": "Lance Liotta", + "author_inst": "George Mason University" + }, + { + "author_name": "Emanuel Petricoin", + "author_inst": "George Mason University" + }, + { + "author_name": "Ali Andalibi", + "author_inst": "George Mason University" + }, + { + "author_name": "Yuntao Wu", + "author_inst": "George Mason University" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "new results", - "category": "immunology" + "category": "microbiology" }, { "rel_doi": "10.1101/2020.12.22.424071", @@ -1005613,81 +1005809,25 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.12.21.20248383", - "rel_title": "Transmission risk of SARS-CoV-2 on airplanes and high-speed trains", + "rel_doi": "10.1101/2020.12.19.20248374", + "rel_title": "Airborne Transmission of Virus-Laden Aerosols inside a Music Classroom: Effects of Portable Purifiers and Aerosol Injection Rates", "rel_date": "2020-12-22", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.21.20248383", - "rel_abs": "Modern transportation plays a key role in the long-distance and rapid spread of SARS-CoV-2. However, little is known about the transmission risk of SARS-CoV-2 on confined vehicles, such as airplanes and trains. Based on the itinerary and epidemiological data of COVID-19 cases and close contacts among 9,265 airline passengers on 291 airplanes and 29,335 passengers on 830 high-speed trains in China from December 20, 2019 to March 17, 2020, we estimated that the upper bound of overall attack rate of COVID-19 among passengers was 0.60% (95% confidence interval: 0.43%-0.84%) for airplanes and 0.35% (0.28%-0.44%) for trains departing from Wuhan before its lockdown, respectively. The reproduction number during travel ranged from 0.12 to 0.19 on airplanes and from 0.07 to 0.12 on trains, with the risk varying by seat distance from the index case and joint travel time, but the difference in risk was not significant between the types of aircraft and train. Overall, the risk of SARS-CoV-2 transmission on planes and high-speed trains with high efficiency air filtration devices was relatively low. Our findings improve understanding of COVID-19 spread during travel and may inform response efforts, such as lifting travel restrictions, and resuming transportation in the pandemic.", - "rel_num_authors": 16, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.19.20248374", + "rel_abs": "The ongoing COVID-19 pandemic has shifted attention to the airborne transmission of exhaled droplet nuclei within indoor environments. The spread of aerosols through singing and musical instruments in music performances has necessitated precautionary methods such as masks and portable purifiers. This study investigates the effects of placing portable air purifiers at different locations inside a classroom, as well as the effects of different aerosol injection rates (e.g., with and without masks, different musical instruments and different injection modes). Aerosol deposition, airborne concentration and removal are analyzed in this study. It was found that using purifiers could help in achieving ventilation rates close to the prescribed values by the World Health Organization (WHO), while also achieving aerosol removal times within the Center of Disease Control and Prevention (CDC) recommended guidelines. This could help in deciding break periods between classroom sessions, which was around 25 minutes through this study. Moreover, proper placement of purifiers could offer significant advantages in reducing airborne aerosol numbers (offering orders of magnitude higher aerosol removal when compared to nearly zero removal when having no purifiers), and improper placement of the purifiers could worsen the situation. The study suggests the purifier to be placed close to the injector to yield a benefit, and away from the people to be protected. The injection rate was found to have an almost linear correlation with the average airborne aerosol suspension rate and deposition rate, which could be used to predict the trends for scenarios with other injection rates.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Maogui Hu", - "author_inst": "Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, China" - }, - { - "author_name": "Jinfeng Wang", - "author_inst": "Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, China" - }, - { - "author_name": "Hui Lin", - "author_inst": "China Academy of Electronics and Information Technology, Beijing, China" - }, - { - "author_name": "Corrine W Ruktanonchai", - "author_inst": "WorldPop, School of Geography and Environmental Science, University of Southampton, UK" - }, - { - "author_name": "Chengdong Xu", - "author_inst": "Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, China" - }, - { - "author_name": "Bin Meng", - "author_inst": "Beijing Union University, Beijing, China" - }, - { - "author_name": "Xin Zhang", - "author_inst": "Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China" - }, - { - "author_name": "Alessandra Carioli", - "author_inst": "WorldPop, School of Geography and Environmental Science, University of Southampton, UK" - }, - { - "author_name": "Yuqing Feng", - "author_inst": "Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, China" - }, - { - "author_name": "Qian Yin", - "author_inst": "Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, China" - }, - { - "author_name": "Jessica R Floyd", - "author_inst": "WorldPop, School of Geography and Environmental Science, University of Southampton, UK" - }, - { - "author_name": "Nick W Ruktanonchai", - "author_inst": "WorldPop, School of Geography and Environmental Science, University of Southampton, UK" - }, - { - "author_name": "Zhongjie Li", - "author_inst": "Divisions of Infectious Diseases, Chinese Center for Disease Control and Prevention, Beijing, China" - }, - { - "author_name": "Weizhong Yang", - "author_inst": "School of Population Medicine and Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China" - }, - { - "author_name": "Andrew J Tatem", - "author_inst": "WorldPop, School of Geography and Environmental Science, University of Southampton, UK" + "author_name": "Sai Ranjeet Narayanan", + "author_inst": "University of Minnesota" }, { - "author_name": "Shengjie Lai", - "author_inst": "WorldPop, School of Geography and Environmental Science, University of Southampton, UK" + "author_name": "Suo Yang", + "author_inst": "University of Minnesota" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1006943,55 +1007083,47 @@ "category": "radiology and imaging" }, { - "rel_doi": "10.1101/2020.12.21.20248662", - "rel_title": "Home confinement during COVID-19 pandemic reduced physical activity but not health-related quality of life in previously active older women", + "rel_doi": "10.1101/2020.12.22.20248666", + "rel_title": "When months matter; modelling the impact of the COVID-19 pandemic on the diagnostic pathway of Motor Neurone Disease (MND)", "rel_date": "2020-12-22", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.21.20248662", - "rel_abs": "BackgroundTo investigate the effect of COVID-19 home confinement on levels of physical activity, sedentary behavior and health-related quality of life (HRQL) in older women previously participating in exercise and educational programs.\n\nMethods64 older women (age = 72{+/-}5 ys) who participated in a physical exercise/educational program and adhered to government home confinement recommendations have their levels of physical activity, sedentary behavior and HRQL assessed before and during (11 to 13 weeks after introduction of government recommendations to reduce virus transmission) COVID-19 pandemic.\n\nResultsThere were significant reductions in total physical activity (-259 METs/week, P = 0.02), as a result of a [~]17.0 % reduction in walking (-30.8 min/week, P = 0.004) and [~]41.8 % reduction in vigorous-intensity activity (-29.6 min/week, P < 0.001). Sedentary behavior also increased (2.24 h/week, P < 0.001; 1.07 h/week days, P < 0.001; and 1.54 h/weekend days, P < 0.001). However, no significant change occurred in moderate-intensity physical activity, and HRQL domains and facets, except for an improvement in environment domain.\n\nConclusionHome confinement due to COVID-19 pandemic decreased levels of physical activity and increased levels of sedentary behavior in previously active older women who participated in an educational program. However, there were no significant changes in HRQL. These results suggest that educational programs promoting healthy behaviors may attenuate the impact of home confinement in older women.", - "rel_num_authors": 9, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.22.20248666", + "rel_abs": "BackgroundA diagnosis of MND takes an average 10-16 months from symptom onset. Early diagnosis is important to access supportive measures to maximise quality of life. The COVID-19 pandemic has caused significant delays in NHS pathways; the majority of GP appointments now occur online with subsequent delays in secondary care assessment. Given the rapid progression of MND, patients may be disproportionately affected resulting in late stage new presentations. We used Monte Carlo simulation to model the pre-COVID-19 diagnostic pathway and then introduced plausible COVID-19 delays.\n\nMethodsThe diagnostic pathway was modelled using gamma distributions of time taken: 1) from symptom onset to GP presentation, 2) for specialist referral, and 3) for diagnosis reached after neurology appointment. We incorporated branches to simulate delays: when patients did not attend their GP and when the GP consultation did not result in referral. An emergency presentation was triggered when diagnostic pathway time was within 30 days of projected median survival. Total time-to-diagnosis was calculated over 100,000 iterations. The pre-COVID-19 model was estimated using published data and the Improving MND Care Survey 2019. We estimated COVID-19 delays using published statistics.\n\nResultsThe pre-COVID model reproduced known features of the MND diagnostic pathway, with a median time to diagnosis of 399 days and predicting 5.2% of MND patients present as undiagnosed emergencies. COVID-19 resulted in diagnostic delays from 558 days when only primary care was 25% delayed, to 915 days when both primary and secondary care were 75%. The model predicted an increase in emergency presentations ranging from 15.4%-44.5%.\n\nInterpretationsThe model suggests the COVID-19 pandemic will result in later-stage diagnoses and more emergency presentations of undiagnosed MND. Late-stage presentations may require rapid escalation to multidisciplinary care. Proactive recognition of acute and late-stage disease with altered service provision will optimise care for people with MND.\n\nFundingThis research was supported and funded by a grant from the Reta Lila Weston Trust. NS was supported by the National Institute for Health Research University College London Hospitals Biomedical Research Centre.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Vanessa Teixeira do Amaral", - "author_inst": "Sao Paulo State University" - }, - { - "author_name": "Isabela Roque Marcal", - "author_inst": "Sao Paulo State University" - }, - { - "author_name": "Thiago da Cruz Silva", - "author_inst": "Sao Paulo State University" + "author_name": "Ella Burchill", + "author_inst": "King's College London" }, { - "author_name": "Fernanda Bianchi Souza", - "author_inst": "Sao Paulo State University" + "author_name": "Vishal Rawji", + "author_inst": "Department of Clinical and Movement Neurosciences, Queen Square Institute of Neurology, University College London" }, { - "author_name": "Yacco Volpato Munhoz", - "author_inst": "Sao Paulo State University" + "author_name": "Katy Styles", + "author_inst": "Founder of We Care Campaign, http://wecarecampaign.tilda.ws" }, { - "author_name": "Pedro Henrique Camprigher Witzler", - "author_inst": "Sao Paulo State University" + "author_name": "Siobhan Rooney", + "author_inst": "Vice-Chair of the North Ireland MND Association branch" }, { - "author_name": "Matheus Monge Soares Correa", - "author_inst": "Sao Paulo State University" + "author_name": "Patrick Stone", + "author_inst": "Marie Curie Palliative Care Research Department, Division of Psychiatry, University College London, London, UK" }, { - "author_name": "Bianca Fernandes", - "author_inst": "Sao Paulo State University" + "author_name": "Ronan Astin", + "author_inst": "National Institute of Health Research, UCLH Biomedical Research centre, UCLH" }, { - "author_name": "Emmanuel Gomes Ciolac", - "author_inst": "Sao Paulo State University" + "author_name": "Nikhil Sharma", + "author_inst": "Department of Clinical and Movement Neurosciences, Queen Square Institute of Neurology, University College London" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "sports medicine" + "category": "neurology" }, { "rel_doi": "10.1101/2020.12.19.20248493", @@ -1009281,45 +1009413,37 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.12.18.20248518", - "rel_title": "Impact of the COVID-19 Pandemic and Vaccine Hesitancy among Farmworkers from Monterey County, California", + "rel_doi": "10.1101/2020.12.16.20245191", + "rel_title": "Impact of housing conditions on changes in youth's mental health following the initial national COVID-19 lockdown: A cohort study", "rel_date": "2020-12-22", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.18.20248518", - "rel_abs": "ObjectivesTo examine the impact of the COVID-19 pandemic on farmworkers from Monterey County, California.\n\nMethodsWe recruited adult farmworkers (n=1115) between July 16, 2020 and November 30, 2020. We collected information on sociodemographic characteristics, health behaviors, economic and social stressors experienced during COVID-19, and willingness to be vaccinated via interviews by phone.\n\nResultsStudy participants, particularly female farmworkers, reported adverse effects of the pandemic on their mental health and home environment (e.g., 24% overall reported depression and/or anxiety symptoms). The pandemic also resulted in greater financial burden for many farmworkers, with 37% food insecure and 51% unable to pay bills. Half of respondents reported that they were extremely likely to be vaccinated. Vaccine hesitancy was most common in participants who were women, younger, born in the United States, and living in more rural areas.\n\nConclusionsWe found that the pandemic has substantially impacted the mental and physical health and economic and food security of farmworkers.\n\nPublic Health ImplicationsThis study highlights the need to provide farmworkers with supplemental income, and increased mental and family health, and food support services.", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.16.20245191", + "rel_abs": "BackgroundYouths mental health has on average declined initially during the pandemic and few studies have investigated whether these declines were dependent on housing conditions.\n\nMethodsWe used data from 7445 youth from the Danish National Birth Cohort (DNBC), collected at participants 18th year of life and subsequently three weeks into the initial national lockdown (April 2020). We examined associations between housing conditions (access to outdoor spaces, urbanicity, household density, and household composition) and changes in mental health parameters (mental well-being, Quality of Life (QoL) and loneliness. We report results from multivariate linear and logistic regression models.\n\nFindingsYouth without access to outdoor spaces had a greater decrease in mental well-being compared to those with a garden, mean difference: -0{middle dot}83 (95 % CI -1{middle dot}19,-0{middle dot}48), and correspondingly greater odds of onset of low mental well-being, OR: 1{middle dot}68 (95 % CI 1{middle dot}15, 2{middle dot}47). Youth in higher density households and those living alone also had greater odds of onset of low mental well-being (OR: 1{middle dot}23 (95 % CI 1{middle dot}05, 1{middle dot}43) and OR: 1{middle dot}47 (95 % CI 1{middle dot}05, 2{middle dot}07), respectively). Onset of low QoL was associated with living in denser households, as well as living alone. Living alone more than doubled odds of onset of loneliness, OR: 2{middle dot}12 (95 % CI 1{middle dot}59, 2{middle dot}82).\n\nInterpretationNot all youth were equally affected by the pandemic and our findings inform policy makers that youth living alone, in denser households, and without direct access to outdoor spaces are especially vulnerable to mental health declines.\n\nResearch in contextO_ST_ABSEvidence before this studyC_ST_ABSMental health is associated with certain housing characteristics, such as access to green space and household composition. Additionally, we know that mental health amongst youth has been especially impacted by the COVID-19 pandemic and/or social restrictions, at a time where a majority of youth spend more time at home. Cross-sectional studies have indicated that housing conditions during the initial lockdowns were associated with mental health among youth.\n\nAdded value to this studyWe are able to provide evidence that housing conditions have been important factors in how youths mental health has changed, due to data collections in our cohort before and during the pandemic. We demonstrate that living alone without access to outdoor spaces and in denser households during lockdown are all associated with deteriorations in mental health in a longitudinal design. The deteriorations in mental well-being are at a level indicative of anxiety and/or depression, indicating that these mental health changes are meaningful from a public health perspective. To our knowledge, this is the first study to examine associations longitudinally in a youth cohort.\n\nImplications of all the available evidenceNot all youth will be equally affected by the pandemic and social restrictions. Public health recommendations could be that youth avoid living alone, in dense households and without access to outdoor spaces during a lockdown, if this is at all possible to choose. Additionally, mental health and public health professionals should be aware of these vulnerabilities as they seek to assist youth at times when social restrictions are in place to control community transmission. Additionally, as we look to the future and work towards equitable and health-promoting housing, we must consider aspects that are important to mental health during pandemics and otherwise.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Ana M Mora", - "author_inst": "University of California, Berkeley" - }, - { - "author_name": "Joseph A Lewnard", - "author_inst": "University of California Berkeley" - }, - { - "author_name": "Katherine Kogut", - "author_inst": "University of California, Berkeley" + "author_name": "Jonathan Groot", + "author_inst": "University of Copenhagen" }, { - "author_name": "Stephen Rauch", - "author_inst": "University of California, Berkeley" + "author_name": "Am\u00e9lie Cl\u00e9o Keller", + "author_inst": "University of Copenhagen" }, { - "author_name": "Norma Morga", - "author_inst": "Clinica de Salud del Valle de Salinas" + "author_name": "Andrea Joensen", + "author_inst": "University of Copenhagen" }, { - "author_name": "Nicholas Jewell", - "author_inst": "University of California, Berkeley" + "author_name": "Tri-Long Nguyen", + "author_inst": "University of Copenhagen" }, { - "author_name": "Maximiliano Cuevas", - "author_inst": "Clinica de Salud del Valle de Salinas" + "author_name": "Anne-Marie Nybo Andersen", + "author_inst": "University of Copenhagen" }, { - "author_name": "Brenda Eskenazi", - "author_inst": "University of California, Berkeley" + "author_name": "Katrine Strandberg-Larsen", + "author_inst": "University of Copenhagen" } ], "version": "1", @@ -1011155,41 +1011279,81 @@ "category": "scientific communication and education" }, { - "rel_doi": "10.1101/2020.12.18.20248478", - "rel_title": "The challenges of the coming mass vaccination and exit strategy in prevention and control of COVID-19, a modelling study", + "rel_doi": "10.1101/2020.12.18.20248336", + "rel_title": "Real-world data suggest antibody positivity to SARS-CoV-2 is associated with a decreased risk of future infection", "rel_date": "2020-12-20", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.18.20248478", - "rel_abs": "With success in the development of COVID-19 vaccines, it is urgent and challenging to analyse how the coming large-scale vaccination in the population and the growing public desire of relaxation of non-pharmaceutical interventions (NPIs) interact to impact the prevention and control of the COVID-19 pandemic. Using mathematical models, we focus on two aspects: 1) how the vaccination program should be designed to balance the dynamic exit of NPIs; 2) how much the vaccination coverage is needed to avoid a second wave of the epidemics when the NPIs exit in stages. We address this issue globally, and take six countries--China, Brazil, Indonesia, Russia, UK, and US--in our case study. We showed that a dynamic vaccination program in three stages can be an effective approach to balance the dynamic exit of the NPIs in terms of mitigating the epidemics. The vaccination rates and the accumulative vaccination coverage in these countries are estimated by fitting the model to the real data. We observed that the required effective vaccination coverages are greatly different to balance the dynamic exit of NPIs in these countries, providing a quantitative criterion for the requirement of an integrative package of NPIs. We predicted the epidemics under different vaccination rates for these countries, and showed that the vaccination can significantly decrease the peak value of a future wave. Furthermore, we found that a lower vaccination coverage can result in a subsequent wave once the NPIs exit. Therefore, there is a critical (minimum) vaccination coverage, depending on effectiveness of NPIs to avoid a subsequent wave. We estimated the critical vaccination coverages for China, Brazil, and Indonesia under different scenarios. In conclusion, we quantitatively showed that the dynamic vaccination program can be the effective approach to supplement or even eventually replace NPIs in mitigating the epidemics and avoiding future waves, and we suggest that country level-based exit strategies of the NPIs should be considered, according to the possible quarantine rate and testing ability, and the accessibility, affordability and efficiency of the vaccines.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.18.20248336", + "rel_abs": "ImportanceThere is limited evidence regarding whether the presence of serum antibodies to SARS-CoV-2 is associated with a decreased risk of future infection. Understanding susceptibility to infection and the role of immune memory is important for identifying at-risk populations and could have implications for vaccine deployment.\n\nObjectiveThe purpose of this study was to evaluate subsequent evidence of SARS-CoV-2 infection based on diagnostic nucleic acid amplification test (NAAT) among individuals who are antibody-positive compared with those who are antibody-negative, using real-world data.\n\nDesignThis was an observational descriptive cohort study.\n\nParticipantsThe study utilized a national sample to create cohorts from a de-identified dataset composed of commercial laboratory test results, open and closed medical and pharmacy claims, electronic health records, hospital billing (chargemaster) data, and payer enrollment files from the United States. Patients were indexed as antibody-positive or antibody-negative according to their first SARS-CoV-2 antibody test recorded in the database. Patients with more than 1 antibody test on the index date where results were discordant were excluded.\n\nMain Outcomes/MeasuresPrimary endpoints were index antibody test results and post-index diagnostic NAAT results, with infection defined as a positive diagnostic test post-index, as measured in 30-day intervals (0-30, 31-60, 61-90, >90 days). Additional measures included demographic, geographic, and clinical characteristics at the time of the index antibody test, such as recorded signs and symptoms or prior evidence of COVID-19 (diagnoses or NAAT+) and recorded comorbidities.\n\nResultsWe included 3,257,478 unique patients with an index antibody test. Of these, 2,876,773 (88.3%) had a negative index antibody result, 378,606 (11.6%) had a positive index antibody result, and 2,099 (0.1%) had an inconclusive index antibody result. Patients with a negative antibody test were somewhat older at index than those with a positive result (mean of 48 versus 44 years). A fraction (18.4%) of individuals who were initially seropositive converted to seronegative over the follow up period. During the follow-up periods, the ratio (CI) of positive NAAT results among individuals who had a positive antibody test at index versus those with a negative antibody test at index was 2.85 (2.73 - 2.97) at 0-30 days, 0.67 (0.6 - 0.74) at 31-60 days, 0.29 (0.24 - 0.35) at 61-90 days), and 0.10 (0.05 - 0.19) at >90 days.\n\nConclusionsPatients who display positive antibody tests are initially more likely to have a positive NAAT, consistent with prolonged RNA shedding, but over time become markedly less likely to have a positive NAAT. This result suggests seropositivity using commercially available assays is associated with protection from infection. The duration of protection is unknown and may wane over time; this parameter will need to be addressed in a study with extended duration of follow up.\n\nKey PointsO_ST_ABSQuestionC_ST_ABSCan real-world data be used to evaluate the comparative risk of SARS-CoV-2 infection for individuals who are antibody-positive versus antibody-negative?\n\nFindingOf patients indexed on a positive antibody test, 10 of 3,226 with a NAAT (0.3%) had evidence of a positive NAAT > 90 days after index, compared with 491 of 16,157 (3.0%) indexed on a negative antibody test.\n\nMeaningIndividuals who are seropositive for SARS-CoV-2 based on commercial assays may be at decreased future risk of SARS-CoV-2 infection.", + "rel_num_authors": 16, "rel_authors": [ { - "author_name": "Biao Tang", - "author_inst": "Xi'an Jiaotong University" + "author_name": "Raymond A. Harvey", + "author_inst": "Aetion, Inc." }, { - "author_name": "Peiyu Liu", - "author_inst": "Shaanxi Normal University" + "author_name": "Jeremy A. Rassen", + "author_inst": "Aetion, Inc." }, { - "author_name": "Jie Yang", - "author_inst": "Shaanxi Normal University" + "author_name": "Carly A. Kabelac", + "author_inst": "Aetion, Inc." }, { - "author_name": "Jianhong Wu", - "author_inst": "York University" + "author_name": "Wendy Turenne", + "author_inst": "Aetion, Inc." }, { - "author_name": "Yanni Xiao", - "author_inst": "Xi'an Jiaotong University" + "author_name": "Sandy Leonard", + "author_inst": "HealthVerity" }, { - "author_name": "Sanyi Tang", - "author_inst": "Shaanxi Normal University" + "author_name": "Reyna Klesh", + "author_inst": "HealthVerity" + }, + { + "author_name": "William A. Meyer III", + "author_inst": "Quest Diagnostics" + }, + { + "author_name": "Harvey W. Kaufman", + "author_inst": "Quest Diagnostics" + }, + { + "author_name": "Steve Anderson", + "author_inst": "LabCorp" + }, + { + "author_name": "Oren Cohen", + "author_inst": "LabCorp" + }, + { + "author_name": "Valentina I. Petkov", + "author_inst": "National Cancer Institute" + }, + { + "author_name": "Kathy A. Cronin", + "author_inst": "National Cancer Institute" + }, + { + "author_name": "Alison L. Van Dyke", + "author_inst": "National Cancer Institute" + }, + { + "author_name": "Douglas R. Lowy", + "author_inst": "National Cancer Institute" + }, + { + "author_name": "Norman E. Sharpless", + "author_inst": "National Cancer Institute" + }, + { + "author_name": "Lynne T. Penberthy", + "author_inst": "National Cancer Institute" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1013200,37 +1013364,25 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.12.17.20248389", - "rel_title": "Enhancing the estimation of compartmental model parameters for COVID-19 data with a high level of uncertainty", + "rel_doi": "10.1101/2020.12.17.20248424", + "rel_title": "Assessing Global Covid-19 Cases Data through Compositional Data Analysis(CoDa)", "rel_date": "2020-12-19", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.17.20248389", - "rel_abs": "Reliable data is essential to obtain adequate simulations for forecasting the dynamics of epidemics. In this context, several political, economic, and social factors may cause inconsistencies in the reported data, which reflect the capacity for realistic simulations and predictions. In the case of COVID-19, for example, such uncertainties are mainly motivated by large-scale underreporting of cases due to reduced testing capacity in some locations. In order to mitigate the effects of noise in the data used to estimate parameters of models, we propose strategies capable of improving the ability to predict the spread of the diseases. Using a compartmental model in a COVID-19 study case, we show that the regularization of data by means of Gaussian Process Regression can reduce the variability of successive forecasts, improving predictive ability. We also present the advantages of adopting parameters of compartmental models that vary over time, in detriment to the usual approach with constant values.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.17.20248424", + "rel_abs": "BackgroundCovid-19 cases data pose an enormous challenge to any analysis. The evaluation of such a global pandemic requires matching reports that follow different procedures and even overcoming some countries censorship that restricts publications.\n\nMethodsThis work proposes a methodology that could assist future studies. Compositional Data Analysis (CoDa) is proposed as the proper approach as Covid-19 cases data is compositional in nature. Under this methodology, for each country three attributes were selected: cumulative number of deaths (D); cumulative number of recovered patients(R); present number of patients (A).\n\nResultsAfter the operation called closure, with c=1, a ternary diagram and Log-Ratio plots, as well as, compositional statistics are presented. Cluster analysis is then applied, splitting the countries into discrete groups.\n\nConclusionsThis methodology can also be applied to other data sets such as countries, cities, provinces or districts in order to help authorities and governmental agencies to improve their actions to fight against a pandemic.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Gustavo B Libotte", - "author_inst": "National Laboratory for Scientific Computing" - }, - { - "author_name": "Lucas Anjos", - "author_inst": "National Laboratory for Scientific Computing" - }, - { - "author_name": "Regina C Almeida", - "author_inst": "National Laboratory for Scientific Computing" - }, - { - "author_name": "Sandra M C Malta", - "author_inst": "National Laboratory for Scientific Computing" + "author_name": "Luis Braga", + "author_inst": "Federal University of Rio de Janeiro" }, { - "author_name": "Renato S Silva", - "author_inst": "National Laboratory for Scientific Computing" + "author_name": "Dina Feingenbaun", + "author_inst": "Federal University of Rio de Janeiro" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1015082,67 +1015234,31 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2020.12.16.423178", - "rel_title": "Genomic and phylogenetic analyses of SARS-CoV-2 strains isolated in the city of Gwangju, South Korea", + "rel_doi": "10.1101/2020.12.15.20248299", + "rel_title": "Fundamental Limitations of Contact Tracing for COVID-19", "rel_date": "2020-12-18", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.12.16.423178", - "rel_abs": "Since the first identification of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in China in late December 2019, the coronavirus disease 2019 (COVID-19) has spread fast around the world. RNA viruses, including SARS-CoV-2, have higher gene mutations than DNA viruses during virus replication. Variations in SARS-CoV-2 genome could contribute to efficiency of viral spread and severity of COVID-19. In this study, we analyzed the locations of genomic mutations to investigate the genetic diversity among isolates of SARS-CoV-2 in Gwangju. We detected non-synonymous and frameshift mutations in various parts of SARS-CoV-2 genome. The phylogenetic analysis for whole genome showed that SARS-CoV-2 genomes in Gwangju isolates are clustered within clade V and G. Our findings not only provide a glimpse into changes of prevalent virus clades in Gwangju, South Korea, but also support genomic surveillance of SARS-CoV-2 to aid in the development of efficient therapeutic antibodies and vaccines against COVID-19.", - "rel_num_authors": 12, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.15.20248299", + "rel_abs": "Contact tracing has played a central role in COVID-19 control in many jurisdictions and is often used in conjunction with other measures such as travel restrictions and social distancing mandates. Contact tracing is made ineffective, however, by delays in testing, calling, and isolating. Even if delays are minimized, contact tracing can only prevent a fraction of onward transmissions from contacts. Without other measures in place, contact tracing alone is insufficient to prevent exponential growth in the number of cases. Even when used effectively with other measures, occasional bursts in call loads can overwhelm contact tracing systems and lead to a loss of control. We propose embracing approaches to COVID-19 control that broadly test individuals without symptoms, in whatever way is economically feasible - either with fast cheap tests that can be deployed widely, with pooled testing, or with screening of judiciously chosen groups of high-risk individuals. Only by ramping up testing of asymptomatic individuals can we avoid the inherent delays that limit the efficacy of contact tracing.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Kim Min Ji", - "author_inst": "Health and Environmental Research Institution of Gwangju Metropolitan city" - }, - { - "author_name": "Lee Ji-eun", - "author_inst": "Health and Environmental Research Institution of Gwangju Metropolitan city" - }, - { - "author_name": "Chung Jae Keun", - "author_inst": "Health and Environmental Research Institution of Gwangju Metropolitan city" - }, - { - "author_name": "Kim Tae sun", - "author_inst": "Health and Environmental Research Institution of Gwangju Metropolitan city" - }, - { - "author_name": "Park Jungwook", - "author_inst": "Health and Environmental Research Institution of Gwangju Metropolitan city" - }, - { - "author_name": "Lim Mi hyeon", - "author_inst": "Health and Environmental Research Institution of Gwangju Metropolitan city" - }, - { - "author_name": "Hwang Da jeong", - "author_inst": "Health and Environmental Research Institution of Gwangju Metropolitan city" - }, - { - "author_name": "Jeong Jin", - "author_inst": "Health and Environmental Research Institution of Gwangju Metropolitan city" - }, - { - "author_name": "Yoon Ji-eun", - "author_inst": "Health and Environmental Research Institution of Gwangju Metropolitan city" - }, - { - "author_name": "Kee Hye young", - "author_inst": "Health and Environmental Research Institution of Gwangju Metropolitan city" + "author_name": "Paul F Tupper", + "author_inst": "Simon Fraser University" }, { - "author_name": "Seo Jin jong", - "author_inst": "Health and Environmental Research Institution of Gwangju Metropolitan city" + "author_name": "Sarah Otto", + "author_inst": "University of British Columbia" }, { - "author_name": "Kim Kwang gon", - "author_inst": "Health and Environmental Research Institution of Gwangju Metropolitan city" + "author_name": "Caroline Colijn", + "author_inst": "Simon Fraser University" } ], "version": "1", - "license": "cc_by_nc_nd", - "type": "confirmatory results", - "category": "microbiology" + "license": "cc_by", + "type": "PUBLISHAHEADOFPRINT", + "category": "infectious diseases" }, { "rel_doi": "10.1101/2020.12.15.20248278", @@ -1016788,43 +1016904,27 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2020.12.14.20221937", - "rel_title": "QFEA - A Method for Assessing the Filtration Efficiency of Face Mask Materials for Early Design Prototypes and Home Mask Makers", + "rel_doi": "10.1101/2020.12.15.20248284", + "rel_title": "Impact of COVID-19 related unemployment on increased cardiovascular disease in a high-income country: Modeling health loss, cost and equity", "rel_date": "2020-12-17", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.14.20221937", - "rel_abs": "The COVID-19 pandemic has led to a surge in the design and production of fabric face coverings. There are few published methods which enable mask designers, makers and purchasers to assess the relative filtration ability of mask making materials. Those methods which do exist are prohibitively expensive and difficult to conduct. As a result, mask makers, non-profits, and small-scale designers face difficult decisions when designing face coverings for personal and commercial use. In this paper, we propose a novel method, the Qualitative Filtration Efficiency Assessment (QFEA), for easily and inexpensively comparing the filtration efficiency of common materials. This method provides a highly affordable and readily available way to assess potential mask materials.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.15.20248284", + "rel_abs": "BackgroundCardiovascular disease (CVD) is a leading cause of health loss and health sector economic burdens in high-income countries. Unemployment is associated with increased risk of CVD, and so there is concern that the economic downturn associated with the COVID-19 pandemic will increase the CVD burden.\n\nAimsThis modeling study aimed to quantify health loss, health cost burden and health inequities among people with CVD due to additional unemployment caused by COVID-19 pandemic-related economic disruption in one high-income country: New Zealand (NZ).\n\nMethodsWe adapted an established and validated multi-state life-table model for CVD in the national NZ population. We modeled indirect effects (ie, higher CVD incidence due to high unemployment rates) for various scenarios of pandemic-related unemployment projections.\n\nResultsWe estimated the CVD-related heath loss in NZ to range from 23,300 to 36,900 HALYs (health-adjusted life years) for the different unemployment scenarios. Health inequities for M[a]ori (Indigenous population) were 3.7 times greater compared to non-M[a]ori (49.9 vs 13.5 HALYs lost per 1000 people).\n\nConclusions and policy implicationsUnemployment due to the COVID-19 pandemic is likely to cause significant health loss and health inequities from CVD in this high-income country. Prevention measures should be considered by governments to reduce this risk, including job creation programs and measures directed towards CVD prevention.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Eugenia O'Kelly", - "author_inst": "Cambridge University" - }, - { - "author_name": "Anmol Arora", - "author_inst": "University of Cambridge" - }, - { - "author_name": "Corinne E O'Kelly", - "author_inst": "Independent Researcher" - }, - { - "author_name": "Charlotte Pearson", - "author_inst": "University of Oregon" - }, - { - "author_name": "James Ward", - "author_inst": "University of Cambridge" + "author_name": "Nhung Nghiem", + "author_inst": "University of Otago" }, { - "author_name": "P John Clarkson", - "author_inst": "University of Cambridge" + "author_name": "Nick Wilson", + "author_inst": "University of Otago, Wellington" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "health economics" }, { "rel_doi": "10.1101/2020.12.15.20248256", @@ -1018182,71 +1018282,91 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.12.15.20248039", - "rel_title": "IMPACT OF A SARS-COV-2 INFECTION IN PATIENTS WITH CELIAC DISEASE", + "rel_doi": "10.1101/2020.12.15.20248237", + "rel_title": "Mental and social health of children and adolescents with pre-existing mental or somatic problems during the COVID-19 pandemic lockdown", "rel_date": "2020-12-16", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.15.20248039", - "rel_abs": "ObjectiveThe SARS-CoV-2 pandemic has spread across the world causing a dramatic number of infections and deaths. No data are available about the effects of an infection in patients affected by celiac disease (CD) in terms of the development of related symptoms and antibodies. We aimed to investigate the impact of the SARS-CoV-2 pandemic in celiac patients.\n\nDesignDuring a lockdown, the celiac patients living in the Milan area were contacted and interviewed about the development of COVID-19 symptoms as well as adherence to an anti-virus lifestyle and a gluten-free diet (GFD). They were also given a stress questionnaire to fill in. The development of anti-SARS-CoV-2 IgG and IgA (anti-RBD and N proteins) and the expression of the duodenal ACE2 receptor were investigated. When available, duodenal histology, anti-tissue transglutaminase IgA (tTGA), presence of immunologic comorbidities and adherence to the GFD were analysed as possible risk factors.\n\nResults362 celiac patients have been interviewed and 42 (11%) presented with COVID-19 symptoms. The presence of symptoms was not influenced by tTGA positivity, presence of duodenal atrophy or adherence to GFD. 37% of the symptomatic patients presented anti-SARS-CoV-2 immunoglobulins (Ig). Globally, 18% of celiac patients showed anti-SARS-CoV-2 Ig vs 25% of the non-celiac control (p=0.18). The values of anti-RBD IgG/IgA and anti-N IgG did not differ from the non-celiac controls. Celiac patients had a significant lower level of anti-N IgA. The ACE2 receptor was detected in the non-atrophic duodenal mucosa of celiac patients; atrophy was associated with a lower expression of the ACE2 receptor.\n\nConclusionCD patients have an anti-SARS-CoV-2 Ig positiveness and profile similar to non-celiac controls, except for anti-N IgA. The main celiac parameters and adherence to the GFD do not influence the development of a different Ig profile.\n\nWhat is already known about this subject?The SARS-CoV-2 pandemic has spread across the world causing infections and deaths. little is known about the possible relationship between autoimmune comorbidities and SARS-CoV-2 infection and COVID-19, and nothing it known about celiac disease.\n\nWhat are the new findings?In a large cohort of celiac patients living in a high SARS-CoV-2 incidence area in Northern Italy, no difference was observed evidenced in terms of the development of anti-SARS-CoV-2 Ig and their IgG and IgA profile compared with the normal population\n\nHow might it impact clinical practice in the foreseeable future?The absence of a relationship between celiac disease and SARS-CoV-2/COVID-19 has a relevant impact on health policy to control the pandemic by supporting an optimal resource location.", - "rel_num_authors": 13, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.15.20248237", + "rel_abs": "BackgroundThe COVID-19 lockdown increases psychological problems in children and adolescents from the general population. Here we investigate the mental and social health during the COVID-19 lockdown in children and adolescents with pre-existing mental or somatic problems.\n\nMethodWe included participants (8-18 years) from a psychiatric (N = 249) and pediatric (N = 90) sample, and compared them to a general population sample (N = 844). Measures were assessed during the first lockdown (April-May 2020) in the Netherlands. Main outcome measures were Patient-Reported Outcomes Measurement Information System (PROMIS(R)) domains: Global Health, Peer Relationships, Anxiety, Depressive Symptoms, Anger, and Sleep-Related Impairment. Additionally, socio-demographic variables, COVID-19-related questions, changes in atmosphere at home from a parent and child perspective, and childrens experiences of lockdown regulations were assessed.\n\nResultsOn all measures except Global Health, the pediatric sample reported least problems. The psychiatric sample reported significantly more problems than the general population sample on all measures except for Anxiety and Peer Relationships. Having a COVID-19 affected friend/relative and a COVID-19 related change in work situation negatively moderated outcome, but not in the samples with pre-existing problems. All parents reported significant decreases in atmosphere at home, as did children from the general population.\n\nConclusionWe observed significant differences in mental and social health between three child and adolescent samples during the COVID-19 pandemic lockdown and identified COVID-19-related factors influencing mental and social health. Our findings contribute to current and future policies during pandemic related lockdowns regarding the mental and social health of children and adolescents.", + "rel_num_authors": 18, "rel_authors": [ { - "author_name": "Luca Elli", - "author_inst": "Fondazione IRCCS Ca' Granda" + "author_name": "Josjan Zijlmans", + "author_inst": "Amsterdam University Medical Center" }, { - "author_name": "Federica Facciotti", - "author_inst": "European Institute of Oncology IRCCS, Department of Experimental Oncology" + "author_name": "Lorynn Teela", + "author_inst": "Amsterdam University Medical Center" }, { - "author_name": "Vincenza Lombardo", - "author_inst": "Fondazione IRCCS Ca' Granda" + "author_name": "Hanneke van Ewijk", + "author_inst": "Curium-Leiden University Medical Center" }, { - "author_name": "Alice Scricciolo", - "author_inst": "Fondazione IRCCS Ca' Granda" + "author_name": "Helen Klip", + "author_inst": "Karakter Child and Adolescent Psychiatry University Centre" }, { - "author_name": "David S Sanders", - "author_inst": "University of Sheffield" + "author_name": "Malindi van der Mheen", + "author_inst": "Amsterdam University Medical Center, Levvel" }, { - "author_name": "Valentina Vaira", - "author_inst": "University of Milan" + "author_name": "Hyun Ruisch", + "author_inst": "University of Groningen" }, { - "author_name": "Donatella Barisani", - "author_inst": "University of Milano-Bicocca" + "author_name": "Michiel Luijten", + "author_inst": "Amsterdam University Medical Center" }, { - "author_name": "Maurizio Vecchi", - "author_inst": "University of Milan" + "author_name": "Maud van Muilekom", + "author_inst": "Amsterdam University Medical Center" + }, + { + "author_name": "Kim Oostrom", + "author_inst": "Amsterdam University Medical Center" }, { - "author_name": "Andrea Costantino", - "author_inst": "Fondazione IRCCS Ca' Granda" + "author_name": "Jan Buitelaar", + "author_inst": "Karakter Child and Adolescent Psychiatry University Centre, Radboudumc" }, { - "author_name": "Lucia Scaramella", - "author_inst": "Fondazione IRCCS Ca' Granda" + "author_name": "Pieter Hoekstra", + "author_inst": "University of Groningen" }, { - "author_name": "Bernardo Dell'Osso", - "author_inst": "University of Milan" + "author_name": "Ramon Lindauer", + "author_inst": "Amsterdam University Medical Center, Levvel" }, { - "author_name": "Luisa Doneda", - "author_inst": "University of Milan" + "author_name": "Arne Popma", + "author_inst": "Amsterdam University Medical Center, Levvel" + }, + { + "author_name": "Wouter Staal", + "author_inst": "Karakter Child and Adolescent Psychiatry University Centre" + }, + { + "author_name": "Robert Vermeiren", + "author_inst": "Curium-Leiden University Medical Center" + }, + { + "author_name": "Hedy van Oers", + "author_inst": "Amsterdam University Medical Center" }, { - "author_name": "Leda Roncoroni", - "author_inst": "Fondazione IRCCS Ca' Granda" + "author_name": "Lotte Haverman", + "author_inst": "Amsterdam University Medical Center" + }, + { + "author_name": "Tinca Polderman", + "author_inst": "Amsterdam University Medical Center, Curium-Leiden University Medical Center, Karakter Child and Adolescent Psychiatry University Centre, University of Groninge" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "gastroenterology" + "category": "psychiatry and clinical psychology" }, { "rel_doi": "10.1101/2020.12.15.20248238", @@ -1020044,109 +1020164,29 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.12.11.20210419", - "rel_title": "Safety and immunogenicity trial of an inactivated SARS-CoV-2 vaccine-BBV152: a phase 1, double-blind, randomised control trial", + "rel_doi": "10.1101/2020.12.11.20246561", + "rel_title": "Evolution of COVID-19 patients treated with a combination of nutraceuticals to reduce symptomatology and improve prognosis: a multi-centred, retrospective cohort study", "rel_date": "2020-12-15", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.11.20210419", - "rel_abs": "BackgroundBBV152 is a whole-virion inactivated SARS-CoV-2 vaccine formulated with a TLR 7/8 agonist molecule adsorbed to alum (Algel-IMDG).\n\nMethodsWe conducted a double-blind randomized controlled phase 1 clinical trial to evaluate the safety and immunogenicity of BBV152. A total of 375 participants were randomized equally to receive three vaccine formulations (n=100 each) prepared with 3 g with Algel-IMDG, 6 g with Algel-IMDG, and 6 g with Algel, and an Algel only control arm (n=75). Vaccines were administered on a two-dose intramuscular accelerated schedule on day 0 (baseline) and day 14. The primary outcomes were reactogenicity and safety. The secondary outcomes were immunogenicity based on the anti-IgG S1 response (detected with an enzyme-linked immunosorbent assay [ELISA] and wild-type virus neutralization [microneutralization and plaque reduction neutralization assays]). Cell-mediated responses were also evaluated.\n\nResultsReactogenicity was absent in the majority of participants, with mild events. The majority of adverse events were mild and were resolved. One serious adverse event was reported, which was found to be unrelated to vaccination. All three vaccine formulations resulted in robust immune responses comparable to a panel of convalescent serum. No significant differences were observed between the 3-g and 6-g Algel-IMDG groups. Neutralizing responses to homologous and heterologous SARS-CoV-2 strains were detected in all vaccinated individuals. Cell-mediated responses were biased to a Th-1 phenotype.\n\nConclusionsBBV152 induced binding and neutralising antibody responses and with the inclusion of the Algel-IMDG adjuvant, this is the first inactivated SARS-CoV-2 vaccine that has been reported to induce a Th1-biased response. Vaccine induced neutralizing antibody titers were reported with two divergent SARS-CoV-2 strains. BBV152 is stored between 2{degrees}C and 8{degrees}C, which is compatible with all national immunization program cold chain requirements. Both Algel-IMDG formulations were selected for the phase 2 immunogenicity trials. Further efficacy trials are underway.\n\nClinicaltrials.gov: NCT04471519", - "rel_num_authors": 23, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.11.20246561", + "rel_abs": "Although a vast knowledge has already been gathered on the pathophysiology of COVID-19, there are still limited, non-optimal treatment options. In this paper, we describe a multicentre, retrospective, observational study to describe the course of SARS-CoV-2 disease in patients treated with ImmunoFormulation (IF), an add-on therapy developed to decrease duration of clinical symptoms. In parallel, a group of patients that did not receive IF was used for comparison (using standard of care treatment). A total of 39 patients were evaluated. Throughout the observational period, 90% of patients recovered in the IF cohort and 47.4% in the Control cohort (p=0.0057). From the symptoms with statistically significant differences, the duration of symptoms (i.e., the time to recover from it) was shorter in the IF cohort than in control cohort (in days, average), especially for fever (2.25 x 21.78), dry cough (4.38 x 24.00), dyspnoea (3.67 x 20.00), headache (2.00 x 26.50), diarrhoea (5.25 x 25.25), and weakness (1.92 x 23.30). This demonstrates a potential promising role of IF as adjuvant therapy on the evolution of symptomatology to COVID-19 patients.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Raches Ella", - "author_inst": "Bharat Biotech International Limited" - }, - { - "author_name": "Krishna Mohan", - "author_inst": "Bharat Biotech" - }, - { - "author_name": "Harsh Jogdand", - "author_inst": "Bharat Biotech" - }, - { - "author_name": "Sai Prasad", - "author_inst": "Bharat Biotech" - }, - { - "author_name": "Siddharth Reddy", - "author_inst": "Bharat Biotech" - }, - { - "author_name": "Vamshi Krishna Sarangi", - "author_inst": "Bharat Biotech" - }, - { - "author_name": "Brunda Ganneru", - "author_inst": "Bharat Biotech" + "author_name": "Mariana Hernandez", + "author_inst": "Clinica Arvila Magna" }, { - "author_name": "Gajanan Sapkal", - "author_inst": "ICMR- National Institute of Virology" + "author_name": "Jully Urrea", + "author_inst": "Clinica Arvila Magna" }, { - "author_name": "Pragya Yadav", - "author_inst": "ICMR-National Institute of Virology" - }, - { - "author_name": "Samiran Panda", - "author_inst": "Indian Council of Medical Research" - }, - { - "author_name": "Nivedita Gupta", - "author_inst": "Indian Council of Medical Research" - }, - { - "author_name": "Prabhakar Reddy", - "author_inst": "Nizam's Institute of Medical Sciences" - }, - { - "author_name": "Savita Verma", - "author_inst": "PGIMS-Rohtak" - }, - { - "author_name": "Sanjay Rai", - "author_inst": "All India Institute of Medical Sciences - New Delhi" - }, - { - "author_name": "Chandramani Singh", - "author_inst": "All India Institute of Medical Sciences - Patna" - }, - { - "author_name": "Sagar Redkar", - "author_inst": "Redkar Hospital" - }, - { - "author_name": "Chandra Sekhar Gillurkar", - "author_inst": "Gillurkar Hospital" - }, - { - "author_name": "Jitendra Singh Kushwaha", - "author_inst": "Prakhar Hospital" - }, - { - "author_name": "Venkat Rao", - "author_inst": "IMS SUM Hospital" - }, - { - "author_name": "Satyajit Mohapatra", - "author_inst": "SRM Hospital" - }, - { - "author_name": "Randeep Guleria", - "author_inst": "All India Institute of Medical Sciences - New Delhi" - }, - { - "author_name": "Krishna Ella", - "author_inst": "Bharat Biotech" - }, - { - "author_name": "Balram Bhargava", - "author_inst": "Indian Council of Medical Research" + "author_name": "Luciano Bascoy", + "author_inst": "Clinic Bascoy" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1021854,35 +1021894,115 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.12.10.20247403", - "rel_title": "Simulation-Based Study on the COVID-19 Airborne Transmission in a Restaurant", + "rel_doi": "10.1101/2020.12.12.20246934", + "rel_title": "CD177, a specific marker of neutrophil activation, is a hallmark of COVID-19 severity and death", "rel_date": "2020-12-14", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.10.20247403", - "rel_abs": "COVID-19 has shown a high potential of transmission via virus-carrying aerosols as supported by growing evidence. However, detailed investigations that draw direct links between aerosol transport and virus infection are still lacking. To fill in the gap, we conducted a systematic computational fluid dynamics (CFD)-based investigation of indoor air flow and the associated aerosol transport in a restaurant setting, where likely cases of airborne infection of COVID-19 caused by asymptomatic individuals were widely reported by the media. We employed an advanced in-house large eddy simulation (LES) solver and other cutting-edge numerical methods to resolve complex indoor processes simultaneously, including turbulence, flow-aerosol interplay, thermal effect, and the filtration effect by air conditioners. Using the aerosol exposure index derived from the simulation, we are able to provide a spatial map of the airborne infection risk under different settings. Our results have shown a remarkable direct linkage between regions of high aerosol exposure index and the reported infection patterns in the restaurant, providing strong support to the airborne transmission occurring in this widely-reported incidence. Using flow structure analysis and reverse-time tracing of aerosol trajectories, we are able to further pinpoint the influence of environmental parameters on the infection risks and highlight the needs for more effective preventive measures, e.g., placement of shielding according to the local flow patterns. Our research, thus, has demonstrated the capability and value of high-fidelity CFD tools for airborne infection risk assessment and the development of effective preventive measures.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.12.20246934", + "rel_abs": "COVID-19 SARS-CoV-2 infection exhibits wide inter-individual clinical variability, from silent infection to severe disease and death. The identification of high-risk patients is a continuing challenge in routine care. We aimed to identify factors that influence clinical worsening. We analyzed 52 cell populations, 71 analytes, and RNA-seq gene expression in the blood of severe patients from the French COVID cohort upon hospitalization (n = 61). COVID-19 patients showed severe abnormalities of 27 cell populations relative to healthy donors (HDs). Forty-two cytokines, neutrophil chemo-attractants, and inflammatory components were elevated in COVID-19 patients. Supervised gene expression analyses showed differential expression of genes for neutrophil activation, interferon signaling, T- and B-cell receptors, EIF2 signaling, and ICOS-ICOSL pathways in COVID-19 patients. Unsupervised analysis confirmed the prominent role of neutrophil activation, with a high abundance of CD177, a specific neutrophil activation marker. CD177 was the most highly differentially-expressed gene contributing to the clustering of severe patients and its abundance correlated with CD177 protein serum levels. CD177 levels were higher in COVID-19 patients from both the French and \"confirmatory\" Swiss cohort (n = 203) than in HDs (P< 0.01) and in ICU than non-ICU patients (P< 0.001), correlating with the time to symptoms onset (P = 0.002). Longitudinal measurements showed sustained levels of serum CD177 to discriminate between patients with the worst prognosis, leading to death, and those who recovered (P = 0.01). These results highlight neutrophil activation as a hallmark of severe disease and CD177 assessment as a reliable prognostic marker for routine care.", + "rel_num_authors": 24, "rel_authors": [ { - "author_name": "Han Liu", - "author_inst": "University of Minnesota" + "author_name": "Yves Levy", + "author_inst": "Vaccine Research Insitute" }, { - "author_name": "Sida He", - "author_inst": "University of Minnesota" + "author_name": "Aurelie Wiedemann", + "author_inst": "Vaccine research Institute" }, { - "author_name": "Lian Shen", - "author_inst": "University of Minnesota" + "author_name": "Boris P Hejblum", + "author_inst": "Univ. Bordeaux, Department of Public Health, Inserm Bordeaux Population Health Research Centre," }, { - "author_name": "Jiarong Hong", - "author_inst": "University of Minnesota" + "author_name": "Melany Durand", + "author_inst": "Univ. Bordeaux, Department of Public Health, Inserm Bordeaux Population Health Research Centre," + }, + { + "author_name": "Cecile Lefebvre", + "author_inst": "Vaccine Research Insitute" + }, + { + "author_name": "Mathieu Surenaud", + "author_inst": "Vaccine Reseach Insitute" + }, + { + "author_name": "Christine Lacabaratz", + "author_inst": "Vaccine Research Institute" + }, + { + "author_name": "Matthieu Perreau", + "author_inst": "Swiss Vaccine Research Institute" + }, + { + "author_name": "Emile Foucat", + "author_inst": "Vaccine Research Insitute" + }, + { + "author_name": "Marie Dechenaud", + "author_inst": "Vaccine Research Insitute" + }, + { + "author_name": "Pascaline Tisserand", + "author_inst": "Vaccine research Insitute" + }, + { + "author_name": "Fabiola Blengio", + "author_inst": "Vaccine research Institute" + }, + { + "author_name": "Benjamin Hivert", + "author_inst": "Univ. Bordeaux, Department of Public Health, Inserm Bordeaux Population Health Research Centre" + }, + { + "author_name": "Marine Gautier", + "author_inst": "Univ. Bordeaux, Department of Public Health, Inserm Bordeaux Population Health Research Centre" + }, + { + "author_name": "Minerva Cervantes", + "author_inst": "AP-HP, Hopital Bichat, Service de Maladies Infectieuses et Tropicales" + }, + { + "author_name": "Delphine Bachelet", + "author_inst": "AP-HP, Hopital Bichat, Departement Epidemiologie Biostatistiques et Recherche Clinique" + }, + { + "author_name": "Cedric Laouenan", + "author_inst": "APHP, Hopital Bichat" + }, + { + "author_name": "lila Bouadma", + "author_inst": "APHP- Hopital Bichat" + }, + { + "author_name": "Jean-Francois Timsit", + "author_inst": "APHP-Hopital Bichat" + }, + { + "author_name": "Yazdan Yazdanpanah", + "author_inst": "AP-HP, Hopital Bichat, Service de Maladies Infectieuses et Tropicales" + }, + { + "author_name": "Giuseppe Pantaleo", + "author_inst": "Lausanne University Hospital" + }, + { + "author_name": "Hakim Hocini", + "author_inst": "Vaccine Research Institute" + }, + { + "author_name": "Rodolphe Thiebaut", + "author_inst": "Univ. Bordeaux, Department of Public Health, Inserm Bordeaux Population Health Research Centre" + }, + { + "author_name": "French COVID Study Group", + "author_inst": "APHP, Hopital Bichat" } ], "version": "1", "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "allergy and immunology" }, { "rel_doi": "10.1101/2020.12.12.20248102", @@ -1023552,47 +1023672,127 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2020.12.12.422516", - "rel_title": "SARS-CoV-2 RNA reverse-transcribed and integrated into the human genome", + "rel_doi": "10.1101/2020.12.13.422550", + "rel_title": "Identification of four linear B-cell epitopes on the SARS-CoV-2 spike protein able to elicit neutralizing antibodies", "rel_date": "2020-12-13", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.12.12.422516", - "rel_abs": "Prolonged SARS-CoV-2 RNA shedding and recurrence of PCR-positive tests have been widely reported in patients after recovery, yet these patients most commonly are non-infectious1-14. Here we investigated the possibility that SARS-CoV-2 RNAs can be reverse-transcribed and integrated into the human genome and that transcription of the integrated sequences might account for PCR-positive tests. In support of this hypothesis, we found chimeric transcripts consisting of viral fused to cellular sequences in published data sets of SARS-CoV-2 infected cultured cells and primary cells of patients, consistent with the transcription of viral sequences integrated into the genome. To experimentally corroborate the possibility of viral retro-integration, we describe evidence that SARS-CoV-2 RNAs can be reverse transcribed in human cells by reverse transcriptase (RT) from LINE-1 elements or by HIV-1 RT, and that these DNA sequences can be integrated into the cell genome and subsequently be transcribed. Human endogenous LINE-1 expression was induced upon SARS-CoV-2 infection or by cytokine exposure in cultured cells, suggesting a molecular mechanism for SARS-CoV-2 retro-integration in patients. This novel feature of SARS-CoV-2 infection may explain why patients can continue to produce viral RNA after recovery and suggests a new aspect of RNA virus replication.", - "rel_num_authors": 7, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.12.13.422550", + "rel_abs": "SARS-CoV-2 unprecedentedly threatens the public health at worldwide level. There is an urgent need to develop an effective vaccine within a highly accelerated time. Here, we present the most comprehensive S-protein-based linear B-cell epitope candidate list by combining epitopes predicted by eight widely-used immune-informatics methods with the epitopes curated from literature published between Feb 6, 2020 and July 10, 2020. We find four top prioritized linear B-cell epitopes in the hotspot regions of S protein can specifically bind with serum antibodies from horse, mouse, and monkey inoculated with different SARS-CoV-2 vaccine candidates or a patient recovering from COVID-19. The four linear B-cell epitopes can induce neutralizing antibodies against both pseudo and live SARS-CoV-2 virus in immunized wild-type BALB/c mice. This study suggests that the four linear B-cell epitopes are potentially important candidates for serological assay or vaccine development.", + "rel_num_authors": 27, "rel_authors": [ { - "author_name": "Liguo Zhang", - "author_inst": "Whitehead Institute for Biomedical Research, Cambridge, MA, USA" + "author_name": "Lin Li", + "author_inst": "Beihang University" }, { - "author_name": "Alexsia Richards", - "author_inst": "Whitehead Institute for Biomedical Research, Cambridge, MA, USA" + "author_name": "Zhongpeng Zhao", + "author_inst": "State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Academy of Military Medical Sciences" }, { - "author_name": "Andrew Khalil", - "author_inst": "Whitehead Institute for Biomedical Research, Cambridge, MA, USA" + "author_name": "Xiaolan Yang", + "author_inst": "Beijing Institute of Microbiology and Epidemiology, Academy of Military Medical Sciences" }, { - "author_name": "Emile Wogram", - "author_inst": "Whitehead Institute for Biomedical Research, Cambridge, MA, USA" + "author_name": "WenDong Li", + "author_inst": "Beihang University" }, { - "author_name": "Haiting Ma", - "author_inst": "Whitehead Institute for Biomedical Research, Cambridge, MA, USA" + "author_name": "Shaolong Chen", + "author_inst": "Beijing Institute of Microbiology and Epidemiology, Academy of Military Medical Sciences" }, { - "author_name": "Richard A. Young", - "author_inst": "Whitehead Institute for Biomedical Research, Cambridge, MA, USA" + "author_name": "Ting Sun", + "author_inst": "Beihang University" }, { - "author_name": "Rudolf Jaenisch", - "author_inst": "Whitehead Institute for Biomedical Research, Cambridge, MA, USA" + "author_name": "Lu Wang", + "author_inst": "Beihang University" + }, + { + "author_name": "YuFei He", + "author_inst": "Beihang University" + }, + { + "author_name": "Guang Liu", + "author_inst": "Beihang University" + }, + { + "author_name": "Xiaohan Han", + "author_inst": "Beihang University" + }, + { + "author_name": "Hao Wen", + "author_inst": "Beihang University" + }, + { + "author_name": "Yong Liu", + "author_inst": "Beihang University" + }, + { + "author_name": "Yifan Chen", + "author_inst": "Beihang University" + }, + { + "author_name": "Haoyu Wang", + "author_inst": "Beihang University" + }, + { + "author_name": "Jing Li", + "author_inst": "Beihang University" + }, + { + "author_name": "Zhongyi Su", + "author_inst": "Beihang University" + }, + { + "author_name": "Du Chen", + "author_inst": "Beihang University" + }, + { + "author_name": "Yiting Wang", + "author_inst": "Beihang University" + }, + { + "author_name": "Xinyang Li", + "author_inst": "Beihang University" + }, + { + "author_name": "Zeqian Yang", + "author_inst": "Beihang University" + }, + { + "author_name": "Jie Wang", + "author_inst": "Beihang University" + }, + { + "author_name": "Min Li", + "author_inst": "Beijing Institute of Microbiology and Epidemiology, Academy of Military Medical Sciences" + }, + { + "author_name": "Tiecheng Wang", + "author_inst": "Institute of Military Veterinary, Academy of Military Medical Sciences" + }, + { + "author_name": "Ying Wang", + "author_inst": "Beihang University" + }, + { + "author_name": "Yubo Fan", + "author_inst": "Beihang University" + }, + { + "author_name": "Hui Wang", + "author_inst": "Beijing Institute of Microbiology and Epidemiology, Academy of Military Medical Sciences" + }, + { + "author_name": "Jing Zhang", + "author_inst": "Beihang University" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "new results", - "category": "genomics" + "category": "microbiology" }, { "rel_doi": "10.1101/2020.12.08.20246009", @@ -1025337,51 +1025537,51 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2020.12.08.20246231", - "rel_title": "Artificial intelligence-enabled analysis of UK and US public attitudes on Facebook and Twitter towards COVID-19 vaccinations", + "rel_doi": "10.1101/2020.12.09.20242396", + "rel_title": "Through The Back Door: Expiratory Accumulation of SARS-Cov-2 in the Olfactory Mucosa as Mechanism for CNS Penetration", "rel_date": "2020-12-11", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.08.20246231", - "rel_abs": "BackgroundGlobal efforts towards the development and deployment of a vaccine for SARS-CoV-2 are rapidly advancing. We developed and applied an artificial-intelligence (AI)-based approach to analyse social-media public sentiment in the UK and the US towards COVID-19 vaccinations, to understand public attitude and identify topics of concern.\n\nMethodsOver 300,000 social-media posts related to COVID-19 vaccinations were extracted, including 23,571 Facebook-posts from the UK and 144,864 from the US, along with 40,268 tweets from the UK and 98,385 from the US respectively, from 1st March - 22nd November 2020. We used natural language processing and deep learning based techniques to predict average sentiments, sentiment trends and topics of discussion. These were analysed longitudinally and geo-spatially, and a manual reading of randomly selected posts around points of interest helped identify underlying themes and validated insights from the analysis.\n\nResultsWe found overall averaged positive, negative and neutral sentiment in the UK to be 58%, 22% and 17%, compared to 56%, 24% and 18% in the US, respectively. Public optimism over vaccine development, effectiveness and trials as well as concerns over safety, economic viability and corporation control were identified. We compared our findings to national surveys in both countries and found them to correlate broadly.\n\nConclusionsAI-enabled social-media analysis should be considered for adoption by institutions and governments, alongside surveys and other conventional methods of assessing public attitude. This could enable real-time assessment, at scale, of public confidence and trust in COVID-19 vaccinations, help address concerns of vaccine-sceptics and develop more effective policies and communication strategies to maximise uptake.", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.09.20242396", + "rel_abs": "IntroductionSARS-CoV-2 is a respiratory virus supposed to enter the organism through aerosol or fomite transmission to the nose, eyes and oropharynx. It is responsible for various clinical symptoms, including hyposmia and other neurological ones. Current literature suggests the olfactory mucosa as a port of entry to the CNS, but how the virus reaches the olfactory groove is still unknown. Because the first neurological symptoms of invasion (hyposmia) do not correspond to first signs of infection, the hypothesis of direct contact through airborne droplets during primary infection and therefore during inspiration is not plausible. The aim of this study is to evaluate if a secondary spread to the olfactory groove in a retrograde manner during expiration could be more probable.\n\nMethodsFour three-dimensional virtual models were obtained from actual CT scans and used to simulate expiratory droplets. The volume mesh consists of 25 million of cells, the simulated condition is a steady expiration, driving a flow rate of 270 ml/s, for a duration of 0.6 seconds. The droplet diameter is of 5 m.\n\nResultsThe analysis of the simulations shows the virus to have a high probability to be deployed in the rhinopharynx, on the tail of medium and upper turbinates. The possibility for droplets to access the olfactory mucosa during the expiratory phase is lower than other nasal areas, but consistent.\n\nDiscussionThe data obtained from these simulations demonstrates the virus can be deployed in the olfactory groove during expiration. Even if the total amount in a single act is scarce, it must be considered it is repeated tens of thousands of times a day, and the source of contamination continuously acts on a timescale of several days. The present results also imply CNS penetration of SARS-CoV-2 through olfactory mucosa might be considered a complication and, consequently, prevention strategies should be considered in diseased patients.", "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Amir Hussain", - "author_inst": "Edinburgh Napier University, UK" + "author_name": "Maurizio Quadrio", + "author_inst": "Politecnico di Milano, Dept. of Aerospace Sciences and Technologies" }, { - "author_name": "Ahsen Tahir", - "author_inst": "Edinburgh Napier University, UK" + "author_name": "Carlotta Pipolo", + "author_inst": "University of MIlan, Unit of Otolaryngology, ASST Santi Paolo e Carlo, Department of Health Sciences" }, { - "author_name": "Zain Hussain", - "author_inst": "Edinburgh Medical School, College of Medicine and Veterinary Medicine, University of Edinburgh, UK" + "author_name": "Antonio Mario Bulfamante", + "author_inst": "University of MIlan, Unit of Otolaryngology, ASST Santi Paolo e Carlo, Department of Health Sciences" }, { - "author_name": "Zakariya Sheikh", - "author_inst": "Edinburgh Medical School, College of Medicine and Veterinary Medicine, University of Edinburgh, UK" + "author_name": "Andrea Schillaci", + "author_inst": "Politecnico di Milano, Dept. of Aerospace Sciences and Technologies" }, { - "author_name": "Mandar Gogate", - "author_inst": "Edinburgh Napier University, UK" + "author_name": "Jacopo Banchetti", + "author_inst": "Politecnico di Milano, Dept. of Aerospace Sciences and Technologies" }, { - "author_name": "Kia Dashtipour", - "author_inst": "Edinburgh Napier University, UK" + "author_name": "Luca Castellani", + "author_inst": "University of MIlan, Unit of Otolaryngology, ASST Santi Paolo e Carlo, Department of Health Sciences" }, { - "author_name": "Azhar Ali", - "author_inst": "NHS Forth Medical Group, UK & Harvard T.H. Chan School of Public Health, USA" + "author_name": "Alberto Maria Saibene", + "author_inst": "University of MIlan, Unit of Otolaryngology, ASST Santi Paolo e Carlo, Department of Health Sciences" }, { - "author_name": "Aziz Sheikh", - "author_inst": "Usher Institute, Edinburgh Medical School, University of Edinburgh, UK" + "author_name": "Giovanni Felisati", + "author_inst": "University of MIlan, Unit of Otolaryngology, ASST Santi Paolo e Carlo, Department of Health Sciences" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "otolaryngology" }, { "rel_doi": "10.1101/2020.12.09.20246462", @@ -1026931,25 +1027131,29 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2020.12.10.20247130", - "rel_title": "Airborne magnetic nanoparticles: environmental risk factors for the transmission of SARS-CoV-2", + "rel_doi": "10.1101/2020.12.11.20247304", + "rel_title": "Predictors of Physical and Mental Health in Healthcare Teams Working with COVID-19 patients: a scoping review protocol.", "rel_date": "2020-12-11", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.10.20247130", - "rel_abs": "ObjectivesTo examine the impact of concentrations of ambient fine particulate matter (PM2.5) air pollution on the incidence of COVID-19.\n\nMethodsPublicly available data of COVID-19 deaths in March/October 2020 were compared with concentrations of PM2.5 measured in previous years at urban and suburban areas in Thessaloniki. Similar publicly available data of PM2.5 concentrations from Tehran were gathered for comparison. Cross-correlation and Granger causality analysis were performed in order to assess linkage.\n\nResultsOn the one hand, the mean PM2.5 concentrations in Thessaloniki were significantly higher in the winter, however the magnetic fraction of particulate matter in the autumn is twice its annual average, suggesting that traffic-related emissions alone may not explain the entire variability of PM2.5. On the other hand, it is implied that changes in coronavirus-related deaths follow changes in airborne magnetite, with the correlation between the two data sets being maximized at the lag time of one-month. Further insight is provided by the monthly pattern of PM2.5 mass concentrations in Tehran. We find that air pollution Granger causes COVID-19 deaths (p<0.05).\n\nConclusionsA significant association has been found between PM2.5 values and the impact of the COVID-19 pandemic on a bunch of regions. Reported links between pollution levels, climate conditions and other factors affecting vulnerability to COVID-19 may instead reflect inhalation exposure to magnetic nanoparticles. A hypothesis has been set that ubiquitous airborne magnetite pollution, together with certain climatic conditions, may promote a longer permanence of the viral particles in the air, thus favoring transmission.\n\nKey messagesO_ST_ABSWhat is already known about this subject?C_ST_ABS{blacktriangleright}{blacktriangleright} Due to their small dimensions, airborne particles are able to penetrate through inhalation into many human organs, from the lungs to the cardiovascular system and the brain, which can threaten our health. Research has shown that air pollution is an important cofactor increasing the risk of mortality from coronaviruses.\n\n\nWhat are the new findings?{blacktriangleright}{blacktriangleright} Evidence exists that the magnetic fraction of PM has modulated the transmission of SARS-CoV-2 in Thessaloniki, and potentially in any other region in the world.\n\n\nHow might this impact on policy or clinical practice in the foreseeable future?{blacktriangleright}{blacktriangleright} Policymakers should take care not to overestimate the effect of social distancing interventions and should consider the impact of air pollution in current or future epidemic waves.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.11.20247304", + "rel_abs": "IntroductionAs a result of the current pandemic (COVID-19), many clinical teams are exposed to stressful situations that may lead to physical and mental issues for clinical staff themselves (we exclude the effects of personal infection with the virus). Recent studies suggest some predictors could depend on context, notably country and the type of the health system.\n\nMethods and AnalysisThis protocol was follows using the PRISMA-ScR guideline (Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews), which was revised and approved by the research team. This study aims to identify factors and evidence of the physical, behavioural and mental consequences of sustained clinical practice in a continuing pandemic. Our research seeks to fill this gap in the literature, and the results may suggest to governments, healthcare authorities and healthcare providers appropriate measures to mitigate risks to healthcare workers during a pandemic response.\n\nDissemination and ethicsThe current research design is based on the use of publicly available information and does not require ethical approval. The findings will be disseminated in conferences. Results will be published and additionally shared with relevant local and national authorities.\n\nStrengths and Limitations of the studyThis will be the first scoping review to identify factors and evidence of the physical, behavioural and mental consequences of sustained clinical practice in a continuing pandemic with health impacts for clinical staff.\n\nThe search strategy includes six electronic databases with peer-reviewed literature, as well as a broad range of grey literature sources.\n\nAlthough this study will not require a quality appraisal, which is consistent with the framework proposed by Arksey and OMalley, the current study will formally assess the studies quality.\n\nThis scoping review study has been registered with Open Science Framework to enhance its transparency.\n\nThe search strategy proposed is broad, but the search strategy is limited to articles published in English, Spanish, Portuguese or Italian.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Carlos Martinez-Boubeta", - "author_inst": "Ecoresources P.C" + "author_name": "Nelson Aguirre-Duarte", + "author_inst": "The University of Auckland" }, { - "author_name": "Konstantinos Simeonidis", - "author_inst": "Department of Chemical Engineering, Aristotle University of Thessaloniki, Greece" + "author_name": "John Ovretveit", + "author_inst": "Stockholm Health Care Services, Karolinska Institutet" + }, + { + "author_name": "Timothy Kenealy", + "author_inst": "The University of Auckland" } ], "version": "1", - "license": "cc_by", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "occupational and environmental health" }, @@ -1029333,67 +1029537,47 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2020.12.09.417121", - "rel_title": "An interactive viral genome evolution network analysis system enabling rapid large-scale molecular tracing of SARS-CoV-2", + "rel_doi": "10.1101/2020.12.10.419440", + "rel_title": "Coiled-coil heterodimers with increased stability for cellular regulation and sensing SARS-CoV-2 spike protein-mediated cell fusion", "rel_date": "2020-12-10", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.12.09.417121", - "rel_abs": "Comprehensive analyses of viral genomes can provide a global picture on SARS-CoV-2 transmission and help to predict the oncoming trends of pandemic. This molecular tracing is mainly conducted through extensive phylogenetic network analyses. However, the rapid accumulation of SARS-CoV-2 genomes presents an unprecedented data size and complexity that has exceeded the capacity of existing methods in constructing evolution network through virus genotyping. Here we report a Viral genome Evolution Network Analysis System (VENAS), which uses Hamming distances adjusted by the minor allele frequency to construct viral genome evolution network. The resulting network was topologically clustered and divided using community detection algorithm, and potential evolution paths were further inferred with a network disassortativity trimming algorithm. We also employed parallel computing technology to achieve rapid processing and interactive visualization of >10,000 viral genomes, enabling accurate detection and subtyping of the viral mutations through different stages of Covid-19 pandemic. In particular, several core viral mutations can be independently identified and linked to early transmission events in Covid-19 pandemic. As a general platform for comprehensive viral genome analysis, VENAS serves as a useful computational tool in the current and future pandemics.", - "rel_num_authors": 12, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.12.10.419440", + "rel_abs": "Coiled-coil (CC) dimer-forming peptides are attractive designable modules for mediating protein association. Highly stable CCs are desired for biological activity regulation and assay. Here, we report the design and versatile applications of orthogonal CC dimer-forming peptides with a dissociation constant in the low nanomolar range. In vitro stability and specificity was confirmed in mammalian cells by enzyme reconstitution, transcriptional activation using a combination of DNA-binding and a transcriptional activation domain, and cellular-enzyme-activity regulation based on externally-added peptides. In addition to cellular regulation, coiled-coil-mediated reporter reconstitution was used for the detection of cell fusion mediated by the interaction between the spike protein of pandemic SARS-CoV2 and the ACE2 receptor. This assay can be used to investigate the mechanism and screen inhibition of viral spike protein-mediated fusion under the biosafety level 1conditions.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Yunchao Ling", - "author_inst": "Bio-Med Big Data Center, CAS Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and H" - }, - { - "author_name": "Ruifang Cao", - "author_inst": "Bio-Med Big Data Center, CAS Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and H" - }, - { - "author_name": "Jiaqiang Qian", - "author_inst": "Bio-Med Big Data Center, CAS Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and H" - }, - { - "author_name": "Jiefu Li", - "author_inst": "Bio-Med Big Data Center, CAS Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and H" - }, - { - "author_name": "Haokui Zhou", - "author_inst": "Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences" - }, - { - "author_name": "Liyun Yuan", - "author_inst": "Bio-Med Big Data Center, CAS Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and H" + "author_name": "Tjasa Plaper", + "author_inst": "National Institute of Chemistry" }, { - "author_name": "Zhen Wang", - "author_inst": "Bio-Med Big Data Center, CAS Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and H" + "author_name": "Jana Aupic", + "author_inst": "National Institute of Chemistry" }, { - "author_name": "Guangyong Zheng", - "author_inst": "Bio-Med Big Data Center, CAS Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and H" + "author_name": "Petra Dekleva", + "author_inst": "National Institute of Chemistry" }, { - "author_name": "Guoping Zhao", - "author_inst": "Bio-Med Big Data Center, CAS Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and H" + "author_name": "Fabio Lapenta", + "author_inst": "National Institute of Chemistry" }, { - "author_name": "Yixue Li", - "author_inst": "Bio-Med Big Data Center, CAS Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and H" + "author_name": "Mateja Mancek", + "author_inst": "National Institute of Chemistry" }, { - "author_name": "Zefeng Wang", - "author_inst": "Bio-Med Big Data Center, CAS Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and H" + "author_name": "Roman Jerala", + "author_inst": "National Institute of Chemistry" }, { - "author_name": "Guoqing Zhang", - "author_inst": "Bio-Med Big Data Center, CAS Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and H" + "author_name": "Mojca Bencina", + "author_inst": "National Institute of Chemistry" } ], "version": "1", "license": "cc_no", "type": "new results", - "category": "evolutionary biology" + "category": "synthetic biology" }, { "rel_doi": "10.1101/2020.12.10.420109", @@ -1031011,39 +1031195,147 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2020.12.07.20245043", - "rel_title": "Particle-Based COVID-19 Simulator with Contact Tracing and Testing", + "rel_doi": "10.1101/2020.12.07.20230235", + "rel_title": "A 6-mRNA host response whole-blood classifier trained using patients with non-COVID-19 viral infections accurately predicts severity of COVID-19", "rel_date": "2020-12-08", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.07.20245043", - "rel_abs": "GoalThe COVID-19 pandemic has emerged as the most severe public health crisis in over a century. As of January 2021, there are more than 100 million cases and 2.1 million deaths. For informed decision making, reliable statistical data and capable simulation tools are needed. Our goal is to develop an epidemic simulator that can model the effects of random population testing and contact tracing.\n\nMethodsOur simulator models individuals as particles with the position, velocity, and epidemic status states on a 2D map and runs an SEIR epidemic model with contact tracing and testing modules. The simulator is available on GitHub under the MIT license.\n\nResultsThe results show that the synergistic use of contact tracing and massive testing is effective in suppressing the epidemic (the number of deaths was reduced by 72%).\n\nConclusionsThe Particle-based COVID-19 simulator enables the modeling of intervention measures, random testing, and contact tracing, for epidemic mitigation and suppression.\n\nImpact StatementOur particle-based epidemic simulator, calibrated with COVID-19 data, models each individual as a unique particle with a location, velocity, and epidemic state, enabling the consideration of contact tracing and testing measures.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.07.20230235", + "rel_abs": "BackgroundDetermining the severity of COVID-19 remains an unmet medical need. Our objective was to develop a blood-based host-gene-expression classifier for the severity of viral infections and validate it in independent data, including COVID-19.\n\nMethodsWe developed the classifier for the severity of viral infections and validated it in multiple viral infection settings including COVID-19. We used training data (N=705) from 21 retrospective transcriptomic clinical studies of influenza and other viral illnesses looking at a preselected panel of host immune response messenger RNAs.\n\nResultsWe selected 6 host RNAs and trained logistic regression classifier with a cross-validation area under curve of 0.90 for predicting 30-day mortality in viral illnesses. Next, in 1,417 samples across 21 independent retrospective cohorts the locked 6-RNA classifier had an area under curve of 0.91 for discriminating patients with severe vs. non-severe infection. Next, in independent cohorts of prospectively (N=97) and retrospectively (N=100) enrolled patients with confirmed COVID-19, the classifier had an area under curve of 0.89 and 0.87, respectively, for identifying patients with severe respiratory failure or 30-day mortality. Finally, we developed a loop-mediated isothermal gene expression assay for the 6-messenger-RNA panel to facilitate implementation as a rapid assay.\n\nConclusionsWith further study, the classifier could assist in the risk assessment of COVID-19 and other acute viral infections patients to determine severity and level of care, thereby improving patient management and reducing healthcare burden.", + "rel_num_authors": 32, "rel_authors": [ { - "author_name": "Askat Kuzdeuov", - "author_inst": "Institute of Smart Systems and Artificial Intelligence, Nazarbayev University" + "author_name": "Ljubomir Buturovic", + "author_inst": "Inflammatix Inc." }, { - "author_name": "Aknur Karabay", - "author_inst": "Institute of Smart Systems and Artificial Intelligence, Nazarbayev University" + "author_name": "Hong Zheng", + "author_inst": "Institute for Immunity, Transplantation and Infection, School of Medicine, Stanford University, Palo Alto, CA 94305, USA" }, { - "author_name": "Daulet Baimukashev", - "author_inst": "Institute of Smart Systems and Artificial Intelligence, Nazarbayev University" + "author_name": "Benjamin Tang", + "author_inst": "Centre for Immunology and Allergy Research, Westmead Institute for Medical Research, Sydney, Australia" }, { - "author_name": "Bauyrzhan Ibragimov", - "author_inst": "Institute of Smart Systems and Artificial Intelligence, Nazarbayev University" + "author_name": "Kevin Lai", + "author_inst": "Department of Emergency Medicine, Westmead Hospital, Sydney, Australia" }, { - "author_name": "Huseyin Atakan Varol", - "author_inst": "Institute of Smart Systems and Artificial Intelligence, Nazarbayev University" + "author_name": "Win Sen Kuan", + "author_inst": "Department of Emergency Medicine, National University Hospital Singapore, Singapore" + }, + { + "author_name": "Mark Gillett", + "author_inst": "Department of Emergency Medicine, Royal North Shore Hospital, Sydney, Australia" + }, + { + "author_name": "Rahul Santram", + "author_inst": "Department of Emergency Medicine, St Vincent Hospital, Sydney, Australia" + }, + { + "author_name": "Maryam Shojaei", + "author_inst": "Centre for Immunology and Allergy Research, Westmead Institute for Medical Research, Sydney, Australia" + }, + { + "author_name": "Raquel Almansa", + "author_inst": "Group for Biomedical Research in Sepsis (BioSepsis), Instituto de Investigacion Biomedica de Salamanca (IBSAL), Salamanca, Spain" + }, + { + "author_name": "Jose Angel Nieto", + "author_inst": "Servicio de Urgencias de Atencion Primaria, Salamanca" + }, + { + "author_name": "Sonsoles Munoz", + "author_inst": "Servicio de Urgencias de Atencion Primaria, Salamanca" + }, + { + "author_name": "Carmen Herrero", + "author_inst": "Servicio de Urgencias de Atencion Primaria, Salamanca" + }, + { + "author_name": "Nikolaos Antonakos", + "author_inst": "4th Department of Internal Medicine, National and Kapodistrian University of Athens, Medical School, 124 62 Athens, Greece" + }, + { + "author_name": "Panayiotis Koufargyris", + "author_inst": "4th Department of Internal Medicine, National and Kapodistrian University of Athens, Medical School, 124 62 Athens, Greece" + }, + { + "author_name": "Marina Kontogiorgi", + "author_inst": "4th Department of Internal Medicine, National and Kapodistrian University of Athens, Medical School, 124 62 Athens, Greece" + }, + { + "author_name": "Georgia Damoraki", + "author_inst": "4th Department of Internal Medicine, National and Kapodistrian University of Athens, Medical School, 124 62 Athens, Greece" + }, + { + "author_name": "Oliver Liesenfeld", + "author_inst": "Inflammatix, Inc., 863 Mitten Rd, Suite 104, Burlingame, CA, 94010, USA" + }, + { + "author_name": "James Wacker", + "author_inst": "Inflammatix, Inc., 863 Mitten Rd, Suite 104, Burlingame, CA, 94010, USA" + }, + { + "author_name": "Uros Midic", + "author_inst": "Inflammatix, Inc., 863 Mitten Rd, Suite 104, Burlingame, CA, 94010, USA" + }, + { + "author_name": "Roland Luethy", + "author_inst": "Inflammatix, Inc., 863 Mitten Rd, Suite 104, Burlingame, CA, 94010, USA" + }, + { + "author_name": "David Rawling", + "author_inst": "Inflammatix, Inc., 863 Mitten Rd, Suite 104, Burlingame, CA, 94010, USA" + }, + { + "author_name": "Melissa Remmel", + "author_inst": "Inflammatix, Inc., 863 Mitten Rd, Suite 104, Burlingame, CA, 94010, USA" + }, + { + "author_name": "Sabrina Coyle", + "author_inst": "Inflammatix, Inc., 863 Mitten Rd, Suite 104, Burlingame, CA, 94010, USA" + }, + { + "author_name": "Yiran Liu", + "author_inst": "Institute for Immunity, Transplantation and Infection, School of Medicine, Stanford University, Palo Alto, CA 94305, USA" + }, + { + "author_name": "Aditya M Rao", + "author_inst": "Institute for Immunity, Transplantation and Infection, School of Medicine, Stanford University, Palo Alto, CA 94305, USA" + }, + { + "author_name": "Denis Dermadi", + "author_inst": "Institute for Immunity, Transplantation and Infection, School of Medicine, Stanford University, Palo Alto, CA 94305, USA" + }, + { + "author_name": "Jiaying Toh", + "author_inst": "Institute for Immunity, Transplantation and Infection, School of Medicine, Stanford University, Palo Alto, CA 94305, USA" + }, + { + "author_name": "Lara Murphy Jones", + "author_inst": "Institute for Immunity, Transplantation and Infection, School of Medicine, Stanford University, Palo Alto, CA 94305, USA" + }, + { + "author_name": "Michele Donato", + "author_inst": "Institute for Immunity, Transplantation and Infection, School of Medicine, Stanford University, Palo Alto, CA 94305, USA" + }, + { + "author_name": "Purvesh Khatri", + "author_inst": "Stanford University" + }, + { + "author_name": "Evangelos J Giamarellos-Bourboulis", + "author_inst": "4th Department of Internal Medicine, National and Kapodistrian University of Athens, Medical School, 124 62 Athens, Greece" + }, + { + "author_name": "Timothy E Sweeney", + "author_inst": "Inflammatix, Inc., 863 Mitten Rd, Suite 104, Burlingame, CA, 94010, USA" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "genetic and genomic medicine" }, { "rel_doi": "10.1101/2020.12.07.20245431", @@ -1032503,79 +1032795,35 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2020.12.04.20242115", - "rel_title": "Lipid storm within the lungs of severe COVID-19 patients: Extensive levels of cyclooxygenase and lipoxygenase-derived inflammatory metabolites.", + "rel_doi": "10.1101/2020.12.04.20244137", + "rel_title": "Predicting Hospital Utilization and Inpatient Mortality of Patients Tested for COVID-19", "rel_date": "2020-12-07", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.04.20242115", - "rel_abs": "BACKGROUNDSevere Acute Respiratory Syndrome coronavirus 2 (SARS-CoV-2) is the infectious agent responsible for Coronavirus disease 2019 (COVID-19). While SARS-CoV-2 infections are often benign, there are also severe COVID-19 cases, characterized by severe bilobar pneumonia that can decompensate to an acute respiratory distress syndrome, notably characterized by increased inflammation and a cytokine storm. While there is no cure against severe COVID-19 cases, some treatments significantly decrease the severity of the disease, notably aspirin and dexamethasone, which both directly or indirectly target the biosynthesis (and effects) of numerous bioactive lipids.\n\nOBJECTIVEOur working hypothesis was that severe COVID-19 cases necessitating mechanical ventilation were characterized by increased bioactive lipid levels modulating lung inflammation. We thus quantitated several lung bioactive lipids using liquid chromatography combined to tandem mass spectrometry.\n\nRESULTSWe performed an exhaustive assessment of the lipid content of bronchoalveolar lavages from 25 healthy controls and 33 COVID-19 patients necessitating mechanical ventilation. Severe COVID-19 patients were characterized by increased fatty acid levels as well as an accompanying inflammatory lipid storm. As such, most quantified bioactive lipids were heavily increased. There was a predominance of cyclooxygenase metabolites, notably TXB2 >> PGE2 [~] 12-HHTrE > PGD2. Leukotrienes were also increased, notably LTB4, 20-COOH-LTB4, LTE4, and eoxin E4. 15-lipoxygenase metabolites derived from linoleic, arachidonic, eicosapentaenoic and docosahexaenoic acids were also increased. Finally, yet importantly, specialized pro-resolving mediators, notably lipoxin A4 and the D-series resolvins, were also found at important levels, underscoring that the lipid storm occurring in severe SARS-CoV-2 infections involves pro- and anti-inflammatory lipids.\n\nCONCLUSIONSOur data unmask the important lipid storm occurring in the lungs of patients afflicted with severe COVID-19. We discuss which clinically available drugs could be helpful at modulating the lipidome we observed in the hope of minimizing the deleterious effects of pro-inflammatory lipids and enhancing the effects of anti-inflammatory and/or pro-resolving lipids.", - "rel_num_authors": 15, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.04.20244137", + "rel_abs": "Using structured elements from Electronic Health Records (EHR), we seek to: i) build predictive models to stratify patients tested for COVID-19 by their likelihood for hospitalization, ICU admission, mechanical ventilation and inpatient mortality, and ii) identify the most important EHR-based features driving the predictions. We leveraged EHR data from the Duke University Health System tested for COVID-19 or hospitalized between March 11, 2020 and August 24, 2020, to build models to predict hospital admissions within 4 weeks. Models were also created for ICU admissions, need for mechanical ventilation and mortality following admission. Models were developed on a cohort of 86,355 patients with 112,392 outpatient COVID-19 tests or any-cause hospital admissions between March 11, 2020 and June 4, 2020. The four models considered resulted in AUROC=0.838 (CI: 0.832-0.844) and AP=0.272 (CI: 0.260-0.287) for hospital admissions, AUROC=0.847 (CI: 0.839-855) and AP=0.585 (CI: 0.565-0.603) for ICU admissions, AUROC=0.858 (CI: 0.846-0.871) and AP=0.434 (CI: 0.403-0.467) for mechanical ventilation, and AUROC=0.0.856 (CI: 0.842-0.872) and AP=0.243 (CI: 0.205-0.282) for inpatient mortality. Patient history abstracted from the EHR has the potential for being used to stratify patients tested for COVID-19 in terms of utilization and mortality. The dominant EHR features for hospital admissions and inpatient outcomes are different. For the former, age, social indicators and previous utilization are the most important predictive features. For the latter, age and physiological summaries (pulse and blood pressure) are the main drivers.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Anne-Sophie Archambault", - "author_inst": "Centre de recherche de l'Institut universitaire de cardiologie et de pneumologie de Quebec - Universite Laval, Faculty of medicine, Quebec City, Canada" + "author_name": "Connor Davis", + "author_inst": "Duke Institute for Health Innovation" }, { - "author_name": "Younes Zaid", - "author_inst": "Biology Department, Faculty of Sciences, Mohammed V University, Rabat, Morocco" + "author_name": "Michael Gao", + "author_inst": "Duke Institute for Health Innovation" }, { - "author_name": "Volatiana Rakotoarivelo", - "author_inst": "Centre de recherche de l'Institut universitaire de cardiologie et de pneumologie de Quebec - Universite Laval, Faculty of medicine, Quebec City, Canada" - }, - { - "author_name": "Etienne Dore", - "author_inst": "Centre de Recherche du Centre Hospitalier Universitaire de Quebec - Universite Laval, Quebec City, Canada" - }, - { - "author_name": "Isabelle Dubuc", - "author_inst": "Centre de Recherche du Centre Hospitalier Universitaire de Quebec - Universite Laval, Quebec City, Canada" - }, - { - "author_name": "Cyril Martin", - "author_inst": "Centre de recherche de l'Institut universitaire de cardiologie et de pneumologie de Quebec - Universite Laval, Faculty of medicine, Quebec City, Canada" - }, - { - "author_name": "Youssef Amar", - "author_inst": "Moroccan Foundation for Advanced Science, Innovation & Research (MAScIR), Rabat, Morocco" - }, - { - "author_name": "Amine Cheikh", - "author_inst": "Cheikh Zaid Hospital, Abulcasis University of Health Sciences, Rabat, Morocco" + "author_name": "Marshall Nichols", + "author_inst": "Duke Institute for Health Innovation" }, { - "author_name": "Hakima Fares", - "author_inst": "Cheikh Zaid Hospital, Abulcasis University of Health Sciences, Rabat, Morocco" - }, - { - "author_name": "Amine El Hassani", - "author_inst": "Cheikh Zaid Hospital, Abulcasis University of Health Sciences, Rabat, Morocco" - }, - { - "author_name": "Youssef Tijani", - "author_inst": "Faculty of Medicine, Mohammed VI University of Health Sciences, Casablanca, Morocco" - }, - { - "author_name": "Michel Laviolette", - "author_inst": "Centre de recherche de l'Institut universitaire de cardiologie et de pneumologie de Quebec - Universite Laval, Faculty of medicine, Quebec City, Canada" - }, - { - "author_name": "Eric Boilard", - "author_inst": "Centre de Recherche du Centre Hospitalier Universitaire de Quebec - Universite Laval, department of microbiology-infectiology-immunology, Quebec City, Canada" - }, - { - "author_name": "Louis Flamand", - "author_inst": "Centre de Recherche du Centre Hospitalier Universitaire de Quebec - Universite Laval, department of microbiology-infectiology-immunology, Quebec City, Canada" - }, - { - "author_name": "Nicolas Flamand", - "author_inst": "Centre de recherche de l'Institut universitaire de cardiologie et de pneumologie de Quebec - Universite Laval, Faculty of medicine, Quebec City, Canada" + "author_name": "Ricardo Henao", + "author_inst": "Duke University" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "health informatics" }, { "rel_doi": "10.1101/2020.12.04.20244244", @@ -1033937,45 +1034185,45 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.12.04.20244129", - "rel_title": "Self-harm and the COVID-19 pandemic: a study of factors contributing to self-harm during lockdown restrictions", + "rel_doi": "10.1101/2020.12.05.20244590", + "rel_title": "Aripiprazole as a candidate treatment of COVID-19 identified through genomic analysis", "rel_date": "2020-12-07", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.04.20244129", - "rel_abs": "IntroductionThe COVID-19 pandemic and resulting public health measures may have major impacts on mental health, including on self-harm. We have investigated what factors related to the pandemic influenced hospital presentations following self-harm during lockdown in England.\n\nMethodMental health clinicians assessing individuals aged 18 years and over presenting to hospitals in Oxford and Derby following self-harm during the period March 23rd to 17th May 2020 recorded whether the self-harm was related to the impact of COVID- 19 and, if so, what specific factors were relevant. These factors were organized into a classification scheme. Information was also collected on patients demographic characteristics, method of self-harm and suicide intent.\n\nResultsOf 228 patients assessed, in 46.9% (N=107) COVID-19 and lockdown restrictions were identified as influencing self-harm. This applied more to females than males (53.5%, N=68/127 v 38.6%, N=39/101, {chi}2 = 5.03, p=0.025), but there were no differences in age, methods of self-harm or suicide intent between the two groups. The most frequent COVID-related factors were mental health issues, including new and worsening disorders, and cessation or reduction of services (including absence of face-to-face support), isolation and loneliness, reduced contact with key individuals, disruption to normal routine, and entrapment. Multiple, often inter- connected COVID-related factors were identified in many patients.\n\nConclusionsCOVID-related factors were identified as influences in nearly half of individuals presenting to hospitals following self-harm in the period following introduction of lockdown restrictions. Females were particularly affected. The fact that mental health problems, including issues with delivery of care, predominated has implications for organisation of services during such periods. The contribution of isolation, loneliness and sense of entrapment highlight the need for relatives, friends and neighbours to be encouraged to reach out to others, especially those living alone. The classification of COVID-related factors can be used as an aide-memoire for clinicians.", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.05.20244590", + "rel_abs": "BackgroundAntipsychotics suppress expression of inflammatory cytokines and inducible inflammatory enzymes. Elopiprazole (a phenylpiperazine antipsychotic drug in phase 1) has been characterized as a therapeutic drug to treat SARS-CoV-2 infection in a repurposing study. We aim to investigate the potential effects of aripiprazole (an FDA approved phenylpiperazine) on COVID19-related immunological parameters.\n\nMethodsDifferential gene expression profiles of non-COVID versus COVID RNA-Seq samples (CRA002390 project in GSA database) and drug-naive patients with psychosis at baseline and after three months of aripiprazole treatment was identified. An integrative analysis between COVID and aripiprazole immunomodulatory antagonist effects was performed.\n\nFindings82 out the 377 genes (21.7%) with expression significantly altered by aripiprazole have also their expression altered in COVID-19 patients and in 93.9% of these genes their expression is reverted by aripiprazole. The number of common genes with expression altered in both analyses is significantly higher than expected (Fishers Exact Test, two tail; P value=3.2e-11). 11 KEGG pathways were significantly enriched with genes with altered expression both in COVID-19 patients and aripiprazole medicated schizophrenia patients (P adj<0.05). The most significant pathways were associated to the immune system such as the \"inflammatory bowel disease (IBD)\" (the most significant pathway with a P adj of 0.00021), \"Th1 and Th2 cell differentiation\" and \"B cell receptor signaling pathway\", all three related to the defense against infections.\n\nInterpretationThis exploratory investigation may provide further support to the notion that protective effect is exerted by phenylpiperazine by modulating the immunological dysregulation associated to COVID-19. Along with many ongoing studies and clinical trials, repurposing available medications could be of use in countering SARS-CoV-2 infection, but require further studies and trials.", "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Keith Hawton", - "author_inst": "University of Oxford" + "author_name": "Benedicto Crespo-Facorro", + "author_inst": "Department of Psychiatry, School of Medicine, University Hospital Virgen del Rocio - IBIS - CIBERSAM. Sevilla, Spain." }, { - "author_name": "Karen Lascelles", - "author_inst": "University of Oxford" + "author_name": "Miguel Ruiz-Veguilla", + "author_inst": "Department of Psychiatry, School of Medicine, University Hospital Virgen del Rocio. IBIS. CIBERSAM Sevilla, Spain" }, { - "author_name": "Fiona Brand", - "author_inst": "University of Oxford" + "author_name": "Javier Vazquez-Bourgon", + "author_inst": "Department of Psychiatry, University Hospital Marques de Valdecilla - Instituto de Investigacion Marques de Valdecilla (IDIVAL), Santander, Spain." }, { - "author_name": "Deborah Casey", - "author_inst": "University of Oxford" + "author_name": "Ana C. Sanchez-Hidalgo", + "author_inst": "Seville Biomedical Research Centre (IBiS), Sevilla, Spain" }, { - "author_name": "Elizabeth Bale", - "author_inst": "Univeristy of Oxford" + "author_name": "Nathalia Garrido-Torres", + "author_inst": "University Hospital Virgen del Rocio. IBiS. Sevilla, Spain" }, { - "author_name": "Jennifer Ness", - "author_inst": "Derbyshire Healthcare NHS Foundation Trust" + "author_name": "Jose M. Cisneros", + "author_inst": "Department of Infectious Diseases, Microbiology and Preventive Medicine, Institute of Biomedicine of Seville, University Hospital Virgen del Rocio, University o" }, { - "author_name": "Samantha Kelly", - "author_inst": "Derbyshire Healthcare NHS Foundation Trust" + "author_name": "Carlos Prieto", + "author_inst": "Bioinformatics Service, Nucleus, University of Salamanca, Salamanca, Spain." }, { - "author_name": "Keith Waters", - "author_inst": "Derbyshire Helathcare NHS Foundation Trust" + "author_name": "Jesus Sainz", + "author_inst": "Spanish National Research Council (CSIC), Institute of Biomedicine and Biotechnology of Cantabria (IBBTEC), Santander, Spain" } ], "version": "1", @@ -1035759,121 +1036007,49 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.12.02.20238907", - "rel_title": "Functional profile, homing and residency of protective T cell immune responses against SARS-CoV-2", + "rel_doi": "10.1101/2020.12.02.20242354", + "rel_title": "COVID-19 as cause of viral sepsis: A Systematic Review and Meta-Analysis", "rel_date": "2020-12-04", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.02.20238907", - "rel_abs": "Considering that SARS-CoV-2 interacts with the host at the respiratory tract mucosal interface, T cells strategically placed within these surfaces, namely resident memory T cells, will be essential to limit viral spread and disease. Importantly, these cells are mostly non-recirculating, which reduces the window of opportunity to examine circulating lymphocytes in blood as they home to the lung parenchyma. Here, we demonstrate that viral specific T cells can migrate and establish in the lung as resident memory T cells remaining detectable up to 10 months after initial infection. Moreover, focusing on the acute phase of the infection, we identified virus-specific T cell responses in blood with functional, migratory and apoptotic patterns modulated by viral proteins and associated with clinical outcome. Our study highlights IL-10 secretion by virus-specific T cells associated to a better outcome and the persistence of resident memory T cells as key players for future protection against SARS-CoV-2 infection.", - "rel_num_authors": 26, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.02.20242354", + "rel_abs": "ImportanceCOVID-19 is a heterogenous disease most frequently causing respiratory tract infection but in its severe forms, respiratory failure and multiple organ dysfunction syndrome may occur, resembling sepsis. The prevalence of viral sepsis among COVID-19 patients is still unclear.\n\nObjectiveWe aimed to describe this in a systematic review.\n\nData sourcesMEDLINE(PubMed), Cochrane and Google Scholar databases were searched for studies reporting on patients hospitalized with confirmed COVID-19, diagnosed with sepsis or infection-related organ dysfunctions or receiving organ replacement therapy.\n\nStudy selectionEligible were full-text English articles of randomized and non-randomized clinical trials and observational studies reporting on patients with confirmed COVID-19, who are diagnosed with sepsis or have infection-related organ dysfunctions. Systematic reviews, editorials, conference abstracts, animal studies, case reports, articles neither in English nor full-text, and studies with fewer than 30 participants were excluded.\n\nData extraction and synthesisAll eligible studies were included in a narrative synthesis of results and after reviewing all included studies a meta-analysis was conducted. Separate sensitivity analyses were conducted per adult vs pediatric populations and per Intensive Care Unit (ICU) vs non-ICU populations.\n\nMain outcomes and measuresPrimary endpoint was the prevalence of sepsis using Sepsis-3 criteria among patients with COVID-19 and among secondary, new onset of infection-related organ dysfunction. Outcomes were expressed as proportions with respective 95% confidence interval (CI).\n\nResultsOf 1,903 articles, 104 were analyzed. The prevalence of sepsis in COVID-19 was 39.9% (95% CI, 35.9-44.1; I2, 99%). In sensitivity analysis, sepsis was present in 25.1% (95% CI, 21.8-28.9; I2 99%) of adult patients hospitalized in non-Intensive-Care-Unit (ICU) wards (40 studies) and in 83.8 (95% CI, 78.1-88.2; I2,91%) of adult patients hospitalized in the ICU (31 studies). Sepsis in children hospitalized with COVID-19 was as high as 7.8% (95% CI, 0.4-64.9; I2, 97%). Acute Respiratory Distress Syndrome was the most common organ dysfunction in adult patients in non-ICU (27.6; 95% CI, 21.6-34.5; I2, 99%) and ICU (88.3%; 95% CI, 79.7-93.5; I2, 97%)\n\nConclusions and relevanceDespite the high heterogeneity in reported results, sepsis frequently complicates COVID-19 among hospitalized patients and is significantly higher among those in the ICU. PROSPERO registration number: CRD42020202018. No funding.\n\nKEY POINTSO_ST_ABSQuestionC_ST_ABSWhat is the prevalence of viral sepsis by Sepsis-3 definition among hospitalized patients with COVID-19?\n\nFindingsIn this systematic review and meta-analysis, we systematically reviewed published literature for evidence of organ failure in COVID-19, to estimate the prevalence of viral sepsis in this setting, by means of SOFA score calculation. The prevalence of sepsis in COVID-19 was 39.9% (95% CI, 35.9-44.1; I2, 99%).\n\nMeaningThis is the first study to address the burden of viral sepsis in hospitalized patients with COVID-19, a highly heterogenous infection ranging from asymptomatic cases to severe disease leading to death, as reflected in the high heterogeneity of this study.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Judith Grau-Exp\u00f3sito", - "author_inst": "Vall d'Hebron Research Institute (VHIR)" - }, - { - "author_name": "Nerea S\u00e1nchez-Gaona", - "author_inst": "Vall Hebron Institut de Recerca (VHIR)" - }, - { - "author_name": "N\u00faria Massana", - "author_inst": "Vall Hebron Institut de Recerca (VHIR)" - }, - { - "author_name": "Marina Suppi", - "author_inst": "Vall Hebron Institut de Recerca (VHIR)" - }, - { - "author_name": "Antonio Astorga-Gamaza", - "author_inst": "Vall Hebron Institut de Recerca (VHIR)" - }, - { - "author_name": "David Perea", - "author_inst": "Vall Hebron Institut de Recerca (VHIR)" - }, - { - "author_name": "Joel Rosado", - "author_inst": "Vall Hebron Hospital Universitari" - }, - { - "author_name": "Anna Falc\u00f3", - "author_inst": "Vall Hebron Hospital Universitari" - }, - { - "author_name": "Cristina Kirkegaard", - "author_inst": "Vall Hebron Hospital Universitari" - }, - { - "author_name": "Ariadna Torrella", - "author_inst": "Vall Hebron Hospital Universitari," - }, - { - "author_name": "Bibiana Planas", - "author_inst": "Vall Hebron Hospital Universitari" - }, - { - "author_name": "Jordi Navarro", - "author_inst": "Vall Hebron Hospital Universitari" - }, - { - "author_name": "Paula Suanzes", - "author_inst": "Vall Hebron Hospital Universitari" - }, - { - "author_name": "Daniel Alvarez-de la Sierra", - "author_inst": "Vall Hebron Hospital Universitari" - }, - { - "author_name": "Alfonso Ayora", - "author_inst": "Vall Hebron Hospital Universitari" - }, - { - "author_name": "Irene Sansano", - "author_inst": "Vall Hebron Hospital Universitari" - }, - { - "author_name": "Juliana Esperalba", - "author_inst": "Vall Hebron Hospital Universitari" - }, - { - "author_name": "Cristina Andr\u00e9s", - "author_inst": "Vall Hebron Hospital Universitari" - }, - { - "author_name": "Andr\u00e9s Ant\u00f3n", - "author_inst": "Vall Hebron Hospital Universitari" + "author_name": "Eleni Karakike", + "author_inst": "4th Department of Iternal Medicine, National and Kapodistrian University of Athens" }, { - "author_name": "Santiago Ram\u00f3n y Cajal", - "author_inst": "Vall Hebron Hospital Universitari" + "author_name": "Evangelos Giamarellos-Bourboulis", + "author_inst": "4th Department of Internal Medicine, National and Kapodistrian University of Athens" }, { - "author_name": "Benito Almirante", - "author_inst": "Vall Hebron Hospital Universitari" + "author_name": "Miltiades Kyprianou", + "author_inst": "4th Department of Internal Medicine, National and Kapodistrian University of Athens" }, { - "author_name": "Ricardo Pujol-Borrell", - "author_inst": "Vall Hebron Hospital Universitari" + "author_name": "Carolin Fleischmann-Struzek", + "author_inst": "Institute for Infectious Diseases and Infection Control, Jena University Hospital, Jena, Germany; Center for Sepsis Control and Care, Jena University Hospital, " }, { - "author_name": "Vicen\u00e7 Falc\u00f3", - "author_inst": "Vall Hebron Hospital Universitari" + "author_name": "Mathias W Pletz", + "author_inst": "Institute for Infectious Diseases and Infection Control, Jena University Hospital, Jena, Germany" }, { - "author_name": "Joaqu\u00edn Burgos", - "author_inst": "Vall Hebron Hospital Universitari" + "author_name": "Mihai G Netea", + "author_inst": "Department of Internal Medicine and Center for Infectious Diseases, Radboud University, Nijmegen, The Netherlands; Immunology and Metabolism, Life & Medical Sci" }, { - "author_name": "Mar\u00eda J. Buz\u00f3n", - "author_inst": "Vall Hebron Institut de Recerca (VHIR)" + "author_name": "Konrad Reinhart", + "author_inst": "Department of Anesthesiology and Operative Intensive Care Medicine (CCM, CVK), Charite Universitaetsmedizin Berlin, corporate member of Freie Universitaet Berli" }, { - "author_name": "Meritxell Genesc\u00e0", - "author_inst": "Vall Hebron Research Institute (VHIR)" + "author_name": "Evdoxia Kyriazopoulou", + "author_inst": "4th Department of Internal Medicine, National and Kapodistrian University of Athens" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1037605,17 +1037781,25 @@ "category": "psychiatry and clinical psychology" }, { - "rel_doi": "10.1101/2020.12.03.20243717", - "rel_title": "Covid-19 Will Reduce US Life Expectancy at Birth by More Than One Year in 2020", + "rel_doi": "10.1101/2020.12.04.20243840", + "rel_title": "How do the public interpret COVID-19 swab test results? Comparing the impact of official information about results and reliability used in the UK, US and New Zealand: a randomised, controlled trial", "rel_date": "2020-12-04", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.03.20243717", - "rel_abs": "On December 3rd, 2020, the cumulative number of U.S. Covid-19 deaths tallied by Johns Hopkins University (JHU) online dashboard reached 275,000, surpassing the number at which life table calculations show Covid-19 mortality will lower the U.S. life expectancy at birth (LEB) for 2020 by one full year. Such an impact on the U.S. LEB is unprecedented since the end of World War II. With additional deaths by the year end, the reduction in 2020 LEB induced by Covid-19 deaths will inexorably exceed one year. Factoring the expected continuation of secular gains against other causes of mortality, the U.S. LEB should still drop by more than a full year between 2019 and 2020. By comparison, the opioid-overdose crisis led to a decline in U.S. LEB averaging .1 year annually, from 78.9 years in 2014 to 78.6 years in 2017. At its peak, the HIV epidemic reduced the U.S. LEB by .3 year in a single year, from 75.8 years in 1992 to 75.5 years in 1993. As of now, the US LEB is expected to fall back to the level it first reached in 2010. In other words, the impact of Covid-19 on U.S. mortality can be expected to cancel a decade of gains against all other causes of mortality combined.", - "rel_num_authors": 1, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.04.20243840", + "rel_abs": "ObjectivesTo assess the effects of different official information on public interpretation of a personal COVID-19 PCR ( swab) test result.\n\nDesignA 5xx2 factorial, randomised, between-subjects experiment, comparing four wordings of information about the test result and a control arm of no additional information; for both positive and negative test results.\n\nSettingOnline experiment using recruitment platform Respondi.\n\nParticipantsUK participants (n=1,744, after a pilot of n=1,657) collected by quota sampling to be proportional to the UK national population on age and sex.\n\nInterventionsParticipants were given a hypothetical COVID-19 swab test result for John who was presented as having a 50% chance of having COVID-19 based on symptoms alone. Participants were randomised to receive either a positive or negative result for John, then randomised again to receive either no more information, or text information on the interpretation of COVID-19 test results copied from the public websites of the UKs National Health Service, the USs Centers for Disease Control, New Zealands Ministry of Health, or a modified version of the UKs wording incorporating uncertainty. Information identifying the source of the wording was removed.\n\nMain outcome measuresParticipants were asked \"What is your best guess as to the percent chance that John actually had COVID-19 at the time of his test, given his result?\"; questions about their feelings of trustworthiness in the result, their perceptions of the quality of the underlying evidence, and what action they felt John should take in the light of his result.\n\nResultsOf those presented with a positive COVID-19 test result for John, the mean estimate of the probability that he had the virus was 73%; for those presented with a negative result, 38%. There was no main effect of information (wording) on these means. However, those participants given the official information on the UK website, which did not mention any uncertainty around the test result, were significantly more likely to give a categorical (100% or 0%) answer (for positive result, p <.001; negative, p =.006). When asked how much they agreed that John should self-isolate, those who were told his test was positive agreed to a greater extent (mean 86 on a 0-100 scale), but many of those who were told he had a negative result still agreed (mean 51). There was also an interaction between wording and test result (p < 0.001), with those seeing the New Zealand wording about the uncertainties of the test result significantly more likely to agree that he should continue to self-isolate after a negative test than those who saw the UK wording (p =.01), the experimental wording (p =.02) or no wording at all (p =.003). Participants rated positive test results more trustworthy and higher quality of evidence than negative results.\n\nConclusionsThe UK public perceive positive test results for COVID-19 as more reliable and trustworthy than negative results without being given any information about the reliability of the tests. When additionally given the UKs current official wording about the interpretation of the test results, people became more likely to interpret the results as definitive. The publics assessment of the face value of both the positive and negative test results was generally conservative. The proportion of participants who felt that a symptomatic individual who tests negative definitely should not self-isolate was highest among those reading the UK wording (17.4%) and lowest among those reading the New Zealand wording (3.8%) and US wording (5.1%).\n\nPre-registration and data repositorypre-registration of pilot at osf.io/8n62f, pre-registration of main experiment at osf.io/7rcj4, data and code in https://osf.io/pvhba/.\n\nWhat is already known on this topicO_LIDifferent countries have had different approaches to conveying the meaning of a COVID-19 swab test result, particularly regarding the uncertainties inherent in the result due to limitations of specificity and sensitivity.\nC_LIO_LIPrevious research has suggested that peoples trust and understanding is not affected by conveying quantified uncertainties numerically, but that perceptions of the quality of the underlying evidence can affect trust.\nC_LIO_LIIt is not known whether the different wordings around COVID-19 test uncertainties are likely to affect peoples trust in, or behavioural response to, the results they receive.\nC_LI\n\nWhat this study addsO_LIThis study provides the first empirical evidence to our knowledge of the responses the public have to COVID-19 swab test results.\nC_LIO_LIIt suggests that the public have a higher degree of trust and confidence in positive swab test results than negative when they are not given any other information accompanying the result. The experimental wording that we created for this study appeared to boost their trust in and assessment of quality of positive test results, but did not change their lower ratings of negative results.\nC_LIO_LIThe wording used by the UKs National Health Service, which does not include any cues of uncertainty in the result, was more likely to lead people to definitive (100% or 0%) answers to questions about the meaning of the result.\nC_LIO_LIThe wording used by New Zealands Ministry of Health, which is more explicit about the reliability of the tests, appears to lead people to be more cautious about recommending that a test participant with a negative test (but still symptomatic) no longer needs to self-isolate.\nC_LI", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Patrick Heuveline", - "author_inst": "UCLA" + "author_name": "Gabriel Recchia", + "author_inst": "University of Cambridge" + }, + { + "author_name": "Claudia R Schneider", + "author_inst": "University of Cambridge" + }, + { + "author_name": "Alexandra LJ Freeman", + "author_inst": "University of Cambridge" } ], "version": "1", @@ -1039055,55 +1039239,27 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2020.12.01.20241612", - "rel_title": "Impact of COVID-19 restrictions on pre-school children's eating, activity and sleep behaviours: a qualitative study", + "rel_doi": "10.1101/2020.12.01.20241836", + "rel_title": "No current evidence for risk of vaccine-driven virulence evolution in SARS-CoV-2", "rel_date": "2020-12-03", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.01.20241612", - "rel_abs": "BackgroundIn spring 2020, the COVID-19 lockdown placed unprecedented restrictions on the behaviour and movements of the UK population. Citizens were ordered to stay at home, only allowed to leave their houses to buy essential supplies, attend medical appointments or exercise once a day. This qualitative study explored how lockdown and its subsequent easing changed young childrens everyday activities, eating and sleep habits to gain insight into the impact for health and wellbeing.\n\nMethodsIn summer 2020 we interviewed 20 parents of children due to start school in September 2020 (aged 3-5 years) by phone or video call to explore their experiences of lockdown and its easing. We recruited participants through nurseries and local Facebook community groups in the South West and West Midlands of England. Half the sample were from Black, Asian or Minority Ethnic backgrounds and half lived in the most deprived quintile. We analysed interviews using thematic analysis.\n\nResultsChildrens activity, screen time, eating, and sleep routines had some level of disruption. Parents reported children ate more snacks during lockdown, but also spent more time preparing meals and eating as a family. Most parents reported a reduction in their childrens physical activity and an increase in screen time, which some linked to difficulties in getting their child to sleep. Parents sometimes expressed guilt about changes in activity, screen time and snacking over lockdown. Most felt these changes would be temporary with no lasting impact, though others worried about re-establishing healthy routines.\n\nConclusionsThe spring COVID-19 lockdown negatively impacted on pre-school childrens eating, activity and sleep routines. While some positive changes were reported, there were wide-spread reports of lack of routines, habits and boundaries which, at least in the short-term, were likely to have been detrimental for child health and development. Guidance and support for families during times of COVID-19 restrictions could be valuable to help them maintain healthy activity, eating, screen-time and sleeping routines to protect child health and ensure unhealthy habits are not adopted.", - "rel_num_authors": 9, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.01.20241836", + "rel_abs": "How might COVID-19 vaccines alter selection for increased SARS-CoV-2 virulence, or lethality? Framing current evidence surrounding SARS-CoV-2 biology and COVID-19 vaccines in the context of evolutionary theory indicates that prospects for virulence evolution remain uncertain. However, differential effects of vaccinal immunity on transmission and disease severity between respiratory compartments could select for increased virulence. To bound expectations for this outcome, we analyze an evo-epidemiological model. Synthesizing model predictions with vaccine efficacy data, we conclude that while vaccine driven virulence evolution remains a theoretical risk, it is unlikely to threaten prospects for herd immunity in immunized populations. Given that this event would nevertheless impact unvaccinated populations, virulence should be monitored to facilitate swift mitigation efforts.\n\nSignificance statementVaccines can provide personal and population level protection against infectious disease, but these benefits can exert strong selective pressures on pathogens. Virulence, or lethality, is one pathogen trait that can evolve in response to vaccination. We investigated whether COVID-19 vaccines could select for increased SARS-CoV-2 virulence by reviewing current evidence about vaccine efficacy and SARS-CoV-2 biology in the context of evolutionary theory, and subsequently analyzing a mathematical model. Our findings indicate that while vaccine-driven virulence evolution in SARS-CoV-2 is a theoretical risk, the consequences of this event would be limited for vaccinated populations. However, virulence evolution should be monitored, as the ramifications of a more virulent strain spreading into an under-vaccinated population would be more severe.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Joanne L Clarke", - "author_inst": "University of Birmingham" - }, - { - "author_name": "Ruth Kipping", - "author_inst": "University of Bristol" - }, - { - "author_name": "Stephanie Chambers", - "author_inst": "University of Glasgow" - }, - { - "author_name": "Kate Willis", - "author_inst": "University of Bristol" - }, - { - "author_name": "Hilary Taylor", - "author_inst": "University of Bristol" - }, - { - "author_name": "Rachel Brophy", - "author_inst": "University of Bristol" - }, - { - "author_name": "Kimberly J Hannam", - "author_inst": "University of Bristol" - }, - { - "author_name": "Sharon Simpson", - "author_inst": "University of Glasgow" + "author_name": "Ian F Miller", + "author_inst": "Princeton University" }, { - "author_name": "Beki Langford", - "author_inst": "University of Bristol" + "author_name": "C. Jessica E Metcalf", + "author_inst": "Princeton University" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2020.12.01.20242131", @@ -1040593,93 +1040749,53 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.11.30.20229732", - "rel_title": "Validation of a combined ELISA to detect IgG, IgA and IgM antibody responses to SARS-CoV-2 in mild or moderate non-hospitalised patients", + "rel_doi": "10.1101/2020.11.29.20240440", + "rel_title": "Model-based evaluation of the impact of noncompliance with public health measures on COVID-19 disease control", "rel_date": "2020-12-02", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.30.20229732", - "rel_abs": "BackgroundFrequently SARS-CoV-2 results in mild or moderate disease with potentially lower concentrations of antibodies compared to those that are hospitalised. Here, we validated an ELISA using SARS-CoV-2 trimeric spike glycoprotein, with targeted detection of IgG, IgA and IgM (IgGAM) using serum and dried blood spots (DBS) from adults with mild or moderate disease.\n\nMethodsTargeting the SARS-CoV-2 trimeric spike, a combined anti-IgG, IgA and IgM serology ELISA assay was developed using 62 PCR-confirmed non-hospitalised, mild or moderate COVID-19 samples, [≥]14 days post symptom onset and 624 COVID-19 negative samples. The assay was validated using 73 PCR-confirmed non-hospitalised COVID-19 and 359 COVID-19 negative serum samples with an additional 81 DBSs, and further validated in 226 PCR-confirmed non-hospitalised COVID-19 and 426 COVID-19 negative clinical samples.\n\nResultsA sensitivity and specificity of 98.6% (95% CI, 92.6-100.0), 98.3% (95% CI, 96.4-99.4), respectively, was observed following validation of the SARS-CoV-2 ELISA. No cross-reactivities with endemic coronaviruses or other human viruses were observed, and no change in results were recorded for interfering substances. The assay was stable at temperature extremes and components were stable for 15 days once opened. A matrix comparison showed DBS to correlate with serum results. Clinical validation of the assay reported a sensitivity of 94.7% (95% CI, 90.9-97.2%) and a specificity of 98.4% (95% CI, 96.6-99.3%).\n\nConclusionsThe human anti-IgGAM SARS-CoV-2 ELISA provides accurate and sensitive detection of SARS-CoV-2 antibodies in non-hospitalised adults with mild or moderate disease. The use of dried blood spots makes the assay accessible to the wider community.\n\nSupplementary MaterialNo", - "rel_num_authors": 19, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.29.20240440", + "rel_abs": "The word pandemic conjures dystopian images of bodies stacked in the streets and societies on the brink of collapse. Despite this frightening picture, denialism and noncompliance with public health measures are common in the historical record, for example during the 1918 Influenza pandemic or the 2015 Ebola epidemic. The unique characteristics of SARS-CoV-2--its high reproductive number (R0), time-limited natural immunity and considerable potential for asymptomatic spread--exacerbate the public health repercussions of noncompliance with biomedical and nonpharmaceutical interventions designed to limit disease transmission. In this work, we used game theory to explore when noncompliance confers a perceived benefit to individuals, demonstrating that noncompliance is a Nash equilibrium under a broad set of conditions. We then used epidemiological modeling to explore the impact of noncompliance on short-term disease control, demonstrating that the presence of a noncompliant subpopulation prevents suppression of disease spread. Our modeling shows that the existence of a noncompliant population can also prevent any return to normalcy over the long run. For interventions that are highly effective at preventing disease spread, however, the consequences of noncompliance are borne disproportionately by noncompliant individuals. In sum, our work demonstrates the limits of free-market approaches to compliance with disease control measures during a pandemic. The act of noncompliance with disease intervention measures creates a negative externality, rendering COVID-19 disease control ineffective in the short term and making complete suppression impossible in the long term. Our work underscores the importance of developing effective strategies for prophylaxis through public health measures aimed at complete suppression and the need to focus on compliance at a population level.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Alex M Cook", - "author_inst": "The Binding Site Group Ltd, 8 Calthorpe Road, Birmingham, B15 1QT, UK." - }, - { - "author_name": "Sian E Faustini", - "author_inst": "Clinical Immunology Service, University of Birmingham College of Medical and Dental Sciences, Birmingham, B15 2TT, UK." - }, - { - "author_name": "Leigh J Williams", - "author_inst": "The Binding Site Group Ltd, 8 Calthorpe Road, Birmingham, B15 1QT, UK." - }, - { - "author_name": "Adam F Cunningham", - "author_inst": "Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, B15 2TT, UK." - }, - { - "author_name": "Mark T Drayson", - "author_inst": "Clinical Immunology Service, University of Birmingham College of Medical and Dental Sciences, Birmingham, B15 2TT, UK." - }, - { - "author_name": "Adrian Shields", - "author_inst": "Clinical Immunology Service, University of Birmingham College of Medical and Dental Sciences, Birmingham, B15 2TT, UK & University Hospitals Birmingham NHS Foun" - }, - { - "author_name": "Dale Kay", - "author_inst": "The Binding Site Group Ltd, 8 Calthorpe Road, Birmingham, B15 1QT, UK." - }, - { - "author_name": "Lorna Taylor", - "author_inst": "The Royal Wolverhampton NHS trust, Wolverhampton Road, Wolverhampton, West Midlands, WV10 0QP, UK." - }, - { - "author_name": "Tim Plant", - "author_inst": "Clinical Immunology Service, University of Birmingham College of Medical and Dental Sciences, Birmingham, B15 2TT, UK." - }, - { - "author_name": "Aarnoud Huissoon", - "author_inst": "Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, B15 2TT, UK & University Hospitals Birmingham NHS Foundation Trust, Birmingham," - }, - { - "author_name": "Gregg Wallis", - "author_inst": "The Binding Site Group Ltd, 8 Calthorpe Road, Birmingham, B15 1QT, UK." + "author_name": "Madison Stoddard", + "author_inst": "Fractal Therapeutics, Cambridge, MA, USA" }, { - "author_name": "Sarah Beck", - "author_inst": "University Hospitals Birmingham NHS Foundation Trust, Birmingham, B15 2GW, UK." + "author_name": "Debra Van Egeren", + "author_inst": "Harvard Medical School, Boston, MA, USA; Dana-Farber Cancer Institute, Boston, MA, USA; Boston Children's Hospital, Boston, MA, USA" }, { - "author_name": "Sian E Jossi", - "author_inst": "Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, B15 2TT, UK." + "author_name": "Kaitlyn Johnson", + "author_inst": "Department of Biomedical Engineering, University of Texas, Austin, TX, USA" }, { - "author_name": "Marisol Perez-Toledo", - "author_inst": "Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, B15 2TT, UK." + "author_name": "Smriti Rao", + "author_inst": "Department of Economics, Assumption College, Worcester, MA, USA" }, { - "author_name": "M L Newby", - "author_inst": "School of Biological Sciences, University of Southampton, Southampton, SO17 1BJ, UK." + "author_name": "Josh Furgeson", + "author_inst": "International Initiative for Impact Evaluation, Cambridge, MA, USA" }, { - "author_name": "Joel D Allen", - "author_inst": "School of Biological Sciences, University of Southampton, Southampton, SO17 1BJ, UK." + "author_name": "Douglas E White", + "author_inst": "Independent Researcher" }, { - "author_name": "Max Crispin", - "author_inst": "School of Biological Sciences, University of Southampton, Southampton, SO17 1BJ, UK." + "author_name": "Ryan P Nolan", + "author_inst": "Halozyme Therapeutics, San Diego, CA, USA" }, { - "author_name": "Stephen Harding", - "author_inst": "The Binding Site Group Ltd, 8 Calthorpe Road, Birmingham, B15 1QT, UK" + "author_name": "Natasha Hochberg", + "author_inst": "Boston Medical Center, Boston, MA, USA; Department of Epidemiology, Boston University School of Public Health, Boston, MA, USA; Department of Medicine, Boston U" }, { - "author_name": "Alex G Richter", - "author_inst": "Clinical Immunology Service, University of Birmingham College of Medical and Dental Sciences, Birmingham, B15 2TT, UK & University Hospitals Birmingham NHS Foun" + "author_name": "Arijit Chakravarty", + "author_inst": "Fractal Therapeutics, Cambridge, MA, USA" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1042063,49 +1042179,69 @@ "category": "pathology" }, { - "rel_doi": "10.1101/2020.12.02.408153", - "rel_title": "LL-37 fights SARS-CoV-2: The Vitamin D-Inducible Peptide LL-37 Inhibits Binding of SARS-CoV-2 Spike Protein to its Cellular Receptor Angiotensin Converting Enzyme 2 In Vitro", + "rel_doi": "10.1101/2020.12.01.407015", + "rel_title": "Shared B cell memory to coronaviruses and other pathogens varies in human age groups and tissues", "rel_date": "2020-12-02", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.12.02.408153", - "rel_abs": "ObjectiveSevere acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is the pathogen accountable for the coronavirus disease 2019 (COVID-19) pandemic. Viral entry via binding of the receptor binding domain (RBD) located within the S1 subunit of the SARS-CoV-2 Spike (S) protein to its target receptor angiotensin converting enzyme (ACE) 2 is a key step in cell infection. The efficient transition of the virus is linked to a unique protein called open reading frame (ORF) 8. As SARS-CoV-2 infections can develop into life-threatening lower respiratory syndromes, effective therapy options are urgently needed. Several publications propose vitamin D treatment, although its mode of action against COVID-19 is not fully elucidated. It is speculated that vitamin Ds beneficial effects are mediated by up-regulating LL-37, a well-known antimicrobial peptide with antiviral effects.\n\nMethodsRecombinantly expressed SARS-CoV-2 S protein, the extended S1 subunit (S1e), the S2 subunit (S2), the receptor binding domain (RBD), and ORF8 were used for surface plasmon resonance (SPR) studies to investigate LL-37s ability to bind to SARS-CoV-2 proteins and to localize its binding site within the S protein. Binding competition studies were conducted to confirm an inhibitory action of LL-37 on the attachment of SARS-CoV-2 S protein to its entry receptor ACE2.\n\nResultsWe could show that LL-37 binds to SARS-CoV-2 S protein (LL-37/SStrep KD = 410 nM, LL-37/SHis KD = 410 nM) with the same affinity, as SARS-CoV-2 binds to hACE2 (hACE2/SStrep KD = 370 nM, hACE2/SHis KD = 370 nM). The binding is not restricted to the RBD of the S protein, but rather distributed along the entire length of the protein. Interaction between LL-37 and ORF8 was detected with a KD of 290 nM. Further, inhibition of the binding of SStrep (IC50 = 740 nM), S1e (IC50 = 170 nM), and RBD (IC50 = 130 nM) to hACE2 by LL-37 was demonstrated.\n\nConclusionsWe have revealed a biochemical link between vitamin D, LL-37, and COVID-19 severity. SPR analysis demonstrated that LL-37 binds to SARS-CoV-2 S protein and inhibits binding to its receptor hACE2, and most likely viral entry into the cell. This study supports the prophylactic use of vitamin D to induce LL-37 that protects from SARS-CoV-2 infection, and the therapeutic administration of vitamin D for the treatment of COVID-19 patients. Further, our results provide evidence that the direct use of LL-37 by inhalation and systemic application may reduce the severity of COVID-19.", - "rel_num_authors": 8, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.12.01.407015", + "rel_abs": "Vaccination and infection promote the formation, tissue distribution, and clonal evolution of B cells encoding humoral immune memory. We evaluated convergent antigen-specific antibody genes of similar sequences shared between individuals in pediatric and adult blood, and deceased organ donor tissues. B cell memory varied for different pathogens. Polysaccharide antigen-specific clones were not exclusive to the spleen. Adults convergent clones often express mutated IgM or IgD in blood and are class-switched in lymphoid tissues; in contrast, children have abundant class-switched convergent clones in blood. Consistent with serological reports, pre-pandemic children had class-switched convergent clones to SARS-CoV-2, enriched in cross-reactive clones for seasonal coronaviruses, while adults showed few such clones in blood or lymphoid tissues. These results extend age-related and anatomical mapping of human humoral pathogen-specific immunity.\n\nOne Sentence SummaryChildren have elevated frequencies of pathogen-specific class-switched memory B cells, including SARS-CoV-2-binding clones.", + "rel_num_authors": 13, "rel_authors": [ { - "author_name": "Annika Roth", - "author_inst": "Institute for Clinical Chemistry, Medical Faculty, University of Cologne" + "author_name": "Fan Yang", + "author_inst": "Stanford University" }, { - "author_name": "Steffen Luetke", - "author_inst": "Institute for Biochemistry II, Clinic for Pediatric and Adolescent Medicine, Medical Faculty, University of Cologne" + "author_name": "Sandra Abel Nielsen", + "author_inst": "Stanford University" }, { - "author_name": "Denise Meinberger", - "author_inst": "Institute for Clinical Chemistry, Medical Faculty, University of Cologne" + "author_name": "Ramona A. Hoh", + "author_inst": "Stanford University" }, { - "author_name": "Gabriele Hermes", - "author_inst": "Institute for Clinical Chemistry, Medical Faculty, University of Cologne" + "author_name": "Ji-Yeun Lee", + "author_inst": "Stanford University" }, { - "author_name": "Gerhard Sengle", - "author_inst": "Institute for Biochemistry II, Clinic for Pediatric and Adolescent Medicine, Medical Faculty, University of Cologne" + "author_name": "Tho D. Pham", + "author_inst": "Stanford University" }, { - "author_name": "Manuel Koch", - "author_inst": "Institute for Biochemistry II, Institute for Dental Research and Oral Musculoskeletal Biology, Center for Molecular Medicine Cologne, University of Cologne" + "author_name": "Katherine J.L. Jackson", + "author_inst": "Garvan Institute of Medical Research" }, { - "author_name": "Thomas Streichert", - "author_inst": "Institute for Clinical Chemistry, Medical Faculty, University of Cologne" + "author_name": "Krishna M. Roskin", + "author_inst": "Cincinnati Children Hospital Medical Center" }, { - "author_name": "Andreas R. Klatt", - "author_inst": "University of Cologne" + "author_name": "Yi Liu", + "author_inst": "Calico Life Sciences" + }, + { + "author_name": "Robert S. Ohgami", + "author_inst": "University of California, San Francisco" + }, + { + "author_name": "Eleanor M. Osborne", + "author_inst": "Sarah Cannon Cancer Center9Sarah Cannon Cancer Center" + }, + { + "author_name": "Claus U. Niemann", + "author_inst": "University of California, San Francisco" + }, + { + "author_name": "Julie Parsonnet", + "author_inst": "Stanford University" + }, + { + "author_name": "Scott D. Boyd", + "author_inst": "Stanford University" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "new results", "category": "immunology" }, @@ -1044305,81 +1044441,33 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.11.25.20235366", - "rel_title": "Clinical characteristics and mortality associated with COVID-19 in Jakarta, Indonesia: a hospital-based retrospective cohort study", + "rel_doi": "10.1101/2020.11.25.20238899", + "rel_title": "Universities and COVID-19 Growth at the Start of the 2020 Academic Year", "rel_date": "2020-11-30", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.25.20235366", - "rel_abs": "BackgroundData on COVID-19-related mortality and associated factors from low-resource settings are scarce. This study examined clinical characteristics and factors associated with in-hospital mortality of COVID-19 patients in Jakarta, Indonesia, from March 2 to July 31, 2020.\n\nMethodsThis retrospective cohort included all hospitalised patients with PCR-confirmed COVID-19 in 55 hospitals. We extracted demographic and clinical data, including hospital outcomes (discharge or death). We used Cox regression to examine factors associated with mortality.\n\nFindingsOf 4265 patients with a definitive outcome by July 31, 3768 (88%) were discharged and 497 (12%) died. The median age was 46 years (IQR 32-57), 5% were children, and 31% had at least one comorbidity. Age-specific mortalities were 11% (7/61) for <5 years; 4% (1/23) for 5-9; 2% (3/133) for 10-19; 2% (8/638) for 20-29; 3% (26/755) for 30-39; 7% (61/819) for 40-49; 17% (155/941) for 50-59; 22% (132/611) for 60-69; and 34% (96/284) for [≥]70. Risk of death was associated with higher age; pre-existing hypertension, cardiac disease, chronic kidney disease or liver disease; clinical diagnosis of pneumonia; multiple (>3) symptoms; and shorter time from symptom onset to admission. Patients <50 years with >1 comorbidity had a nearly six-fold higher risk of death than those without (adjusted hazard ratio 5{middle dot}50, 95% CI 2{middle dot}72-11{middle dot}13; 27% vs 3% mortality).\n\nInterpretationOverall mortality was lower than reported in high-income countries, probably due to younger age distribution and fewer comorbidities. However, deaths occurred across all ages, with >10% mortality among children <5 years and adults >50 years.", - "rel_num_authors": 17, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.25.20238899", + "rel_abs": "The global pandemic of 2020 caused by the novel coronavirus of 2019 (COVID-19) has uprooted the education system of the United States. As American colleges and universities try to resume regular instruction for the 2020-2021 academic year, outbreaks have begun to emerge and university towns across the country are now virus hotspots. The current paper provides two studies. First, the current work investigates how the growth of COVID-19 compares in areas with large universities against those without. Results showed markedly increase case growth in counties with large universities at the start of the fall 2020 semester. Secondly, this work provides a highly accessible and modifiable epidemiological tool known as a susceptible-infected-removed model for educational administrators that will allow users to see the impact of COVID-19 historically and predictively. The results of an exemplar model using a large public research university, Texas Tech University, are discussed.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Henry Surendra", - "author_inst": "Eijkman-Oxford Clinical Research Unit, Jakarta, Indonesia" - }, - { - "author_name": "Iqbal RF Elyazar", - "author_inst": "Eijkman-Oxford Clinical Research Unit, Jakarta, Indonesia" - }, - { - "author_name": "Bimandra A Djaafara", - "author_inst": "Eijkman-Oxford Clinical Research Unit, Jakarta, Indonesia" - }, - { - "author_name": "Lenny L Ekawati", - "author_inst": "Eijkman-Oxford Clinical Research Unit, Jakarta, Indonesia" - }, - { - "author_name": "Kartika Saraswati", - "author_inst": "Eijkman-Oxford Clinical Research Unit, Jakarta, Indonesia" - }, - { - "author_name": "Verry Adrian", - "author_inst": "Jakarta Provincial Health Office, Jakarta, Indonesia" - }, - { - "author_name": "Widyastuti Widyastuti", - "author_inst": "Jakarta Provincial Health Office, Jakarta, Indonesia" - }, - { - "author_name": "Dwi Oktavia", - "author_inst": "Jakarta Provincial Health Office, Jakarta, Indonesia" - }, - { - "author_name": "Ngabila Salama", - "author_inst": "Jakarta Provincial Health Office, Jakarta, Indonesia" - }, - { - "author_name": "Rosa N Lina", - "author_inst": "Eijkman-Oxford Clinical Research Unit, Jakarta, Indonesia" - }, - { - "author_name": "Adhi Andrianto", - "author_inst": "Eijkman-Oxford Clinical Research Unit, Jakarta, Indonesia" - }, - { - "author_name": "Karina D Lestari", - "author_inst": "Eijkman-Oxford Clinical Research Unit, Jakarta, Indonesia" - }, - { - "author_name": "Erlina Burhan", - "author_inst": "Faculty of Medicine, Universitas Indonesia, Jakarta, Indonesia" + "author_name": "Michael S Penuliar", + "author_inst": "Texas Tech University - Health Sciences Center" }, { - "author_name": "Anuraj H Shankar", - "author_inst": "Eijkman-Oxford Clinical Research Unit, Jakarta, Indonesia" + "author_name": "Candice Clark", + "author_inst": "Texas Tech University - Health Sciences Center" }, { - "author_name": "Guy Thwaites", - "author_inst": "Oxford University Clinical Research Unit, Ho Chi Minh City, Vietnam" + "author_name": "Debbie Curti", + "author_inst": "Texas Tech University - Health Sciences Center" }, { - "author_name": "J. Kevin Baird", - "author_inst": "Eijkman-Oxford Clinical Research Unit, Jakarta, Indonesia" + "author_name": "Cathy Hudson", + "author_inst": "Texas Tech University - Health Sciences Center" }, { - "author_name": "Raph L Hamers", - "author_inst": "Eijkman-Oxford Clinical Research Unit, Jakarta, Indonesia" + "author_name": "Billy Philips", + "author_inst": "Texas Tech University - Health Sciences Center" } ], "version": "1", @@ -1045775,113 +1045863,45 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.11.27.20237966", - "rel_title": "Predicting critical illness on initial diagnosis of COVID-19: Development and validation of the PRIORITY model for outpatient applicability.", + "rel_doi": "10.1101/2020.11.27.20237032", + "rel_title": "Proteo-genomic analysis of SARS-CoV-2: A clinical landscape of SNPs, COVID-19 proteome and host responses", "rel_date": "2020-11-30", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.27.20237966", - "rel_abs": "ObjectivesCurrently available COVID-19 prognostic models have focused on laboratory and radiological data obtained following admission. However, these tests are not available on initial assessment or in resource-limited settings. We aim to develop and validate a prediction model, based on clinical history and examination findings on initial diagnosis of COVID-19, to identify patients at risk of critical outcomes.\n\nMethodsWe used data from the SEMI-COVID-19 Registry, a nationwide multicenter cohort of consecutive patients hospitalized for COVID-19 from 132 centers in Spain. Clinical signs and symptoms, demographic variables, and medical history ascertained at hospital admission were screened using Least Absolute Shrinkage and Selection Operator (LASSO) and logistic regression to construct a predictive model. We externally validated the final model in a separate cohort of patients admitted at less-complex hospitals (< 300 beds).We undertook decision curve analysis to assess the clinical usefulness of the predictive model. The primary outcome was a composite of in-hospital death, mechanical ventilation or admission to intensive care unit.\n\nResultsThere were 10,433 patients, 7,850 (primary outcome 25.1%) in the development cohort and 2,583 (primary outcome 27.0%) in the validation cohort. Variables in the final model included: age, cardiovascular disease, chronic kidney disease, dyspnea, tachypnea, confusion, systolic blood pressure, and SpO2[≤]93% or oxygen requirement.The C-statistic in the development cohort was 0.823 (95% CI,0.813-0.834). On external validation, the C-statistic was 0.792 (95% CI,0.772-0.812). The model showed a positive net benefit for threshold probabilities between 3% and 79%.\n\nConclusionsAmong patients presenting with COVID-19, the model based on easily-obtained clinical information had good discrimination and generalizability for identifying patients at risk of critical outcomes without the need of additional testing. The online calculator provided would facilitate triage of patients during the pandemic. This study could provide a useful tool for decision-making in health systems under pandemic pressure and resource-limited settings.", - "rel_num_authors": 24, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.27.20237032", + "rel_abs": "A novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of COVID-19 and continues to be a global health challenge. To understand viral disease biology, we have carried out proteo-genomic analysis using next generation sequencing (NGS) and mass-spectrometry on nasopharyngeal swabs of COVID-19 patients to examine clinical genome and proteome. Our study confirms the hyper mutability of SARS-CoV-2 showing multiple SNPs. NGS analysis detected 27 mutations of which 14 are synonymous, 11 are missense and 2 are extragenic in nature. Phylogenetic analysis of SARS-CoV-2 isolates indicated their close relation to Bangladesh isolate and multiple origins of isolates within a country. Our proteomic analysis, for the first time identified 13 different SARS-CoV-2 proteins from the clinical swabs. Of the total 41 peptides captured by HRMS, 8 matched to nucleocapsid protein, 2 to ORF9b, 1 to spike glycoprotein and ORF3a, with remaining mapping to ORF1ab polyprotein. Additionally, host proteome analysis revealed several key host proteins to be uniquely expressed in COVID-19 patients. Pathway analysis of these proteins points towards modulation in immune response, especially involving neutrophil and IL-12 mediated signaling. Besides revealing the aspects of host-virus pathogenesis, our study opens new avenues to develop better diagnostic markers and therapeutics.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Miguel Martinez-Lacalzada", - "author_inst": "Hospital Universitario Ramon y Cajal" - }, - { - "author_name": "Adri\u00e1n Viteri-Noel", - "author_inst": "Hospital Universitario Ramon y Cajal" - }, - { - "author_name": "Luis Manzano", - "author_inst": "Hospital Universitario Ramon y Cajal" - }, - { - "author_name": "Martin Fabregate-Fuente", - "author_inst": "Hospital Universitario Ramon y Cajal" - }, - { - "author_name": "Manuel Rubio-Rivas", - "author_inst": "Bellvitge University Hospital" - }, - { - "author_name": "Sara Luis Garcia", - "author_inst": "Gregorio Mara\u00f1on University Hospital" + "author_name": "Sheetal Tushir", + "author_inst": "INDIAN INSTITUTE OF SCIENCE" }, { - "author_name": "Francisco Arnalich Fern\u00e1ndez", - "author_inst": "La Paz University Hospital" - }, - { - "author_name": "Jos\u00e9 Luis Beato P\u00e9rez", - "author_inst": "Albacete University Hospital Complex" + "author_name": "Sathisha Kamanna", + "author_inst": "INDIAN INSTITUTE OF SCIENCE" }, { - "author_name": "Elpidio Calvo Manuel", - "author_inst": "San Carlos Clinical Hospital" + "author_name": "Sujith S Nath", + "author_inst": "INDIAN INSTITUTE OF SCIENCE" }, { - "author_name": "Alexia Constanza Espi\u00f1o", - "author_inst": "La Princesa University Hospital" + "author_name": "Aishwarya Bhat", + "author_inst": "INDIAN INSTITUTE OF SCIENCE" }, { - "author_name": "Santiago J Freire Castro", - "author_inst": "A Coru\u00f1a University Hospital" + "author_name": "Steffimol Rose", + "author_inst": "INDIAN INSTITUTE OF SCIENCE" }, { - "author_name": "Jose Loureiro-Amigo", - "author_inst": "Mois\u00e8s Broggi Hospital" + "author_name": "Advait R Aithal", + "author_inst": "INDIAN INSTITUTE OF SCIENCE" }, { - "author_name": "Maria Pesqueira Fontan", - "author_inst": "Santiago Clinical Hospital" - }, - { - "author_name": "Adela Pina", - "author_inst": "Dr. Peset University Hospital" - }, - { - "author_name": "Ana Mar\u00eda \u00c1lvarez Su\u00e1rez", - "author_inst": "Cabue\u00f1es Hospital" - }, - { - "author_name": "Andrea Silva Asiain", - "author_inst": "Nuestra Se\u0148ora del Prado Hospital" - }, - { - "author_name": "Beatriz Garc\u00eda L\u00f3pez", - "author_inst": "Zamora Hospital Complex" - }, - { - "author_name": "Jairo Luque del Pino", - "author_inst": "Costa del Sol Hospital" - }, - { - "author_name": "Jaime Sanz C\u00e1novas", - "author_inst": "Regional University Hospital of M\u00e1laga" - }, - { - "author_name": "Paloma Chazarra P\u00e9rez", - "author_inst": "San Juan de Alicante University Hospital" - }, - { - "author_name": "Gema Mar\u00eda Garc\u00eda Garc\u00eda", - "author_inst": "Badajoz University Hospital Complex" - }, - { - "author_name": "Jes\u00fas Mill\u00e1n N\u00fa\u00f1ez-Cort\u00e9s", - "author_inst": "Gregorio Mara\u00f1on University Hospital" - }, - { - "author_name": "Jos\u00e9 Manuel Casas Rojo", - "author_inst": "Infanta Cristina University Hospital" - }, - { - "author_name": "Ricardo G\u00f3mez Huelgas", - "author_inst": "Regional University Hospital of M\u00e1laga" + "author_name": "Utpal Tatu", + "author_inst": "INDIAN INSTITUE OF SCIENCE" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1047217,55 +1047237,131 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.11.30.403824", - "rel_title": "First computational design of Covid-19 coronavirus vaccine using lambda superstrings", + "rel_doi": "10.1101/2020.11.29.402339", + "rel_title": "Recombinant Fc-fusion vaccine of RBD induced protection against SARS-CoV-2 in non-human primate and mice", "rel_date": "2020-11-30", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.11.30.403824", - "rel_abs": "In this work we have developed, by employing lambda superstrings, a map of candidate vaccines against SARS-CoV-2 with lengths between 9 and 200, based on estimations of the immunogenicity of the epitopes and the binding affinity of epitopes to MHC class I molecules using tools from the IEDB Analysis Resource, as well as the overall predictions obtained using the VaxiJen tool. We have synthesized one of the peptides, specifically the one of length 22, and we have carried out an immunogenicity assay and a cytokine assay, which has given positive results in both cases.", - "rel_num_authors": 9, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.11.29.402339", + "rel_abs": "The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) continues to infect people globally. The increased COVID-19 cases and no licensed vaccines highlight the need to develop safe and effective vaccines against SARS-CoV-2 infection. Multiple vaccines candidates are under pre-clinical or clinical trails with different strengths and weaknesses. Here we developed a pilot scale production of a recombinant subunit vaccine (RBD-Fc Vacc) with the Receptor Binding Domain of SARS-CoV-2 S protein fused with the Fc domain of human IgG1. RBD-Fc Vacc induced SARS-CoV-2 specific neutralizing antibodies in non-human primates and human ACE2 transgenic mice. The antibodies induced in macaca fascicularis neutralized three divergent SARS-CoV2 strains, suggesting a broader neutralizing ability. Three times immunizations protected Macaca fascicularis (20ug or 40ug per dose) and mice (10ug or 20ug per dose) from SARS-CoV-2 infection respectively. These data support clinical development of SARS-CoV-2 vaccines for humans. RBD-Fc Vacc is currently being assessed in randomized controlled phase 1/II human clinical trails.\n\nSummaryThis study confirms protective efficacy of a SARS-CoV-2 RBD-Fc subunit vaccine.", + "rel_num_authors": 28, "rel_authors": [ { - "author_name": "Luis Mart\u00ednez", - "author_inst": "University of the Basque Country (UPV/EHU)" + "author_name": "Yansong Sun", + "author_inst": "Beijing Institute of Microbiology and Epidemiology" }, { - "author_name": "Iker Malaina", - "author_inst": "University of the Basque Country (UPV/EHU)" + "author_name": "Gencheng Han", + "author_inst": "Institute of MilitaryCognition and Brain Sciences" }, { - "author_name": "David Salcines", - "author_inst": "Instituto de Investigaci\u00f3n Marqu\u00e9s de Valdecilla" + "author_name": "Wenjin Wei", + "author_inst": "ZHONGYIANKE Biotech Co., LTD." }, { - "author_name": "H\u00e9ctor Ter\u00e1n", - "author_inst": "Instituto de Investigaci\u00f3n Marqu\u00e9s de Valdecilla" + "author_name": "Zhongyu Hu", + "author_inst": "National Institutes for Food and Drug Control" }, { - "author_name": "Santos Alegre", - "author_inst": "University of the Basque Country (UPV/EHU)" + "author_name": "Shihui Sun", + "author_inst": "State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing" }, { - "author_name": "Ildefonso Mart\u00cdnez de la Fuente", - "author_inst": "CEBAS-CSIC" + "author_name": "Lei He", + "author_inst": "Beijing Institute of Microbiology and Epidemiology" + }, + { + "author_name": "Zhongpeng Zhao", + "author_inst": "State Key Laboratory of Pathogens and Biosecurity" + }, + { + "author_name": "Hongjing Gu", + "author_inst": "State Key Laboratory of Pathogens and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing 100071, China" }, { - "author_name": "Elena Gonz\u00e1lez", - "author_inst": "Hospital Universitario Marqu\u00e9s de Valdecilla" + "author_name": "Tiecheng Wang", + "author_inst": "Institute of Military Veterinary, Academay of Military Medical Sciences" }, { - "author_name": "Gonzalo Ocejo", - "author_inst": "Hospital Universitario Marqu\u00e9s de Valdecilla" + "author_name": "Xiaolan Yang", + "author_inst": "State Key Laboratory of Pathogens and Biosecurity, Beijing Institute of Microbiology and Epidemiology" + }, + { + "author_name": "Shaolong Chen", + "author_inst": "Beijing Institute of Microbiology and Epidemiology" + }, + { + "author_name": "Yongqiang Deng", + "author_inst": "State Key Laboratory of Pathogen and Biosecurity" }, { - "author_name": "Carmen \u00c1lvarez", - "author_inst": "Universidad Internacional de La Rioja" + "author_name": "Jiangfan Li", + "author_inst": "Beijing Institute of Microbiology and Epidemiology" + }, + { + "author_name": "Jian Zhao", + "author_inst": "JOINN Biologics" + }, + { + "author_name": "Liang Li", + "author_inst": "Institute of Military Veterinary, Academay of Military Medical Sciences" + }, + { + "author_name": "Xinwang Li", + "author_inst": "ZHONGYIANKE Biotech Co., LTD." + }, + { + "author_name": "Peng He", + "author_inst": "National Institutes for Food and Drug Control" + }, + { + "author_name": "Ge Li", + "author_inst": "Academy of Military Medical Sciences" + }, + { + "author_name": "Hao Li", + "author_inst": "Institute of Disease Control and Prevention, Academy of Military Medical Sciences" + }, + { + "author_name": "Chunrui Gao", + "author_inst": "ZHONGYIANKE Biotech Co., LTD." + }, + { + "author_name": "Xiaoling Lang", + "author_inst": "JOINN Biologics" + }, + { + "author_name": "Shusheng Geng", + "author_inst": "JOINN Biologics" + }, + { + "author_name": "Xin Wang", + "author_inst": "ZHONGYIANKE Biotech Co., LTD." + }, + { + "author_name": "Guoqiang Fei", + "author_inst": "ZHONGYIANKE Biotech Co., LTD." + }, + { + "author_name": "Yan Li", + "author_inst": "Institute of Military Cognition and Brain Science" + }, + { + "author_name": "Yuwei Gao", + "author_inst": "Academy of Military Medical Sciences" + }, + { + "author_name": "Xin Fang", + "author_inst": "National Institutes for Food and Drug Control" + }, + { + "author_name": "Yuee Zhao", + "author_inst": "Beijing Institute of Microbiology and Epidemiology" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_no", "type": "new results", - "category": "bioinformatics" + "category": "immunology" }, { "rel_doi": "10.1101/2020.11.30.403873", @@ -1048743,17 +1048839,33 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.11.25.20235457", - "rel_title": "EXPLORING THE HEALTHY BEHAVIORS OF NIGERIANS DURING THE COVID-19 PANDEMIC.", + "rel_doi": "10.1101/2020.11.24.20237909", + "rel_title": "Psychological distress among people with probable COVID-19 infection: analysis of the UK Household Longitudinal Study", "rel_date": "2020-11-28", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.25.20235457", - "rel_abs": "Healthy behaviors remain important for staying safe during the coronavirus disease 2019 (COVID-19) pandemic. This study, therefore, explored the healthy behaviors of Nigerians during the COVID-19 pandemic and the impact of COVID-19 related news on healthy behaviors. Thirty-three (17 females and 16 males) participants from the general Nigerian population with age range of 23-64 years were recruited via social media using the snowball technique. Responses were elicited using semi-structured questions and subjected to thematic analysis. The healthy behaviors identified included; \"social distancing\", \"changes in nutrition\", \"hand washing or sanitizing\", \"exercise\", \"increased vigilance from those with comorbidities\", and \"use of facemask\". In another analysis, the impacts of COVID-19 related news on healthy behaviors were; \"behavior modification\", \"anxious impacts\", and \"fake news about COVID-19 caused people to stop listening to COVID-19 related news\". Findings generated practical implications for enhancing healthy behaviors during the COVID-19 pandemic. The role of the media in strengthening healthy behaviors during the pandemic was also highlighted.", - "rel_num_authors": 1, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.24.20237909", + "rel_abs": "Studies exploring the longer-term effects of experiencing COVID-19 infection on mental health are lacking. We explored the relationship between reporting probable COVID-19 symptoms in April 2020 and psychological distress (measured using the General Health Questionnaire) one, two, three, five and seven months later. Data were taken from the UK Household Longitudinal Study, a nationally representative household panel survey of UK adults. Elevated levels of psychological distress were found up to seven months after probable COVID-19, compared to participants with no likely infection. Associations were stronger among younger age groups and men. Further research into the psychological sequalae of COVID-19 is urgently needed.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Ifeanyichukwu Meek Eyisi", - "author_inst": "Covenant University" + "author_name": "Claire L Niedzwiedz", + "author_inst": "University of Glasgow" + }, + { + "author_name": "Michaela Benzeval", + "author_inst": "University of Essex" + }, + { + "author_name": "Kirsten Hainey", + "author_inst": "University of Glasgow" + }, + { + "author_name": "Alastair Leyland", + "author_inst": "University of Glasgow" + }, + { + "author_name": "Srinivasa Vittal Katikireddi", + "author_inst": "University of Glasgow" } ], "version": "1", @@ -1050477,131 +1050589,55 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2020.11.25.399139", - "rel_title": "Highly functional virus-specific cellular immune response in asymptomatic SARS-CoV-2 infection", + "rel_doi": "10.1101/2020.11.27.400788", + "rel_title": "Unheeded SARS-CoV-2 protein? Look deep into negative-sense RNA", "rel_date": "2020-11-27", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.11.25.399139", - "rel_abs": "The efficacy of virus-specific T cells in clearing pathogens involves a fine balance between their antiviral and inflammatory features. SARS-CoV-2-specific T cells in individuals who clear SARS-CoV-2 infection without symptoms or disease could reveal non-pathological yet protective characteristics. We therefore compared the quantity and function of SARS-CoV-2-specific T cells in a cohort of asymptomatic individuals (n=85) with that of symptomatic COVID-19 patients (n=76), at different time points after antibody seroconversion. We quantified T cells reactive to structural proteins (M, NP and Spike) using ELISpot assays, and measured the magnitude of cytokine secretion (IL-2, IFN-{gamma}, IL-4, IL-6, IL-1{beta}, TNF- and IL-10) in whole blood following T cell activation with SARS-CoV-2 peptide pools as a functional readout. Frequencies of T cells specific for the different SARS-CoV-2 proteins in the early phases of recovery were similar between asymptomatic and symptomatic individuals. However, we detected an increased IFN-{gamma} and IL-2 production in asymptomatic compared to symptomatic individuals after activation of SARS-CoV-2-specific T cells in blood. This was associated with a proportional secretion of IL-10 and pro-inflammatory cytokines (IL-6, TNF- and IL-1{beta}) only in asymptomatic infection, while a disproportionate secretion of inflammatory cytokines was triggered by SARS-CoV-2-specific T cell activation in symptomatic individuals. Thus, asymptomatic SARS-CoV-2 infected individuals are not characterized by a weak antiviral immunity; on the contrary, they mount a robust and highly functional virus-specific cellular immune response. Their ability to induce a proportionate production of IL-10 might help to reduce inflammatory events during viral clearance.", - "rel_num_authors": 28, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.11.27.400788", + "rel_abs": "SARS-CoV-2 is a novel positive-sense single-stranded RNA virus from the Coronaviridae family (genus Betacoronavirus), which has been established as causing the COVID-19 pandemic. The genome of SARS-CoV-2 is one of the largest among known RNA viruses, comprising of at least 26 known protein-coding loci. Studies thus far have outlined the coding capacity of the positive-sense strand of the SARS-CoV-2 genome, which can be used directly for protein translation. However, it has been recently shown that transcribed negative-sense viral RNA intermediates that arise during viral genome replication from positive-sense viruses can also code for proteins. No studies have yet explored the potential for negative-sense SARS-CoV-2 RNA intermediates to contain protein coding-loci. Thus, using sequence and structure-based bioinformatics methodologies, we have investigated the presence and validity of putative negative-sense ORFs (nsORFs) in the SARS-CoV-2 genome. Nine nsORFs were discovered to contain strong eukaryotic translation initiation signals and high codon adaptability scores, and several of the nsORFs were predicted to interact with RNA-binding proteins. Evolutionary conservation analyses indicated that some of the nsORFs are deeply conserved among related coronaviruses. Three-dimensional protein modelling revealed the presence of higher order folding among all putative SARS-CoV-2 nsORFs, and subsequent structural mimicry analyses suggest similarity of the nsORFs to DNA/RNA-binding proteins and proteins involved in immune signaling pathways. Altogether, these results suggest the potential existence of still undescribed SARS-CoV-2 proteins, which may play an important role in the viral lifecycle and COVID-19 pathogenesis.\n\nContactpetr.pecinka@osu.cz; tlb20@cam.ac.uk", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Nina Le Bert", - "author_inst": "Duke-NUS Medical School" - }, - { - "author_name": "Hannah E Clapham", - "author_inst": "Saw Swee Hock School of Public Health, National University of Singapore" - }, - { - "author_name": "Anthony T Tan", - "author_inst": "Duke-NUS Medical School" - }, - { - "author_name": "Wan Ni Chia", - "author_inst": "Duke-NUS Medical School" - }, - { - "author_name": "Christine YL Tham", - "author_inst": "Duke-NUS Medical School" - }, - { - "author_name": "Jane M Lim", - "author_inst": "Saw Swee Hock School of Public Health, National University of Singapore" - }, - { - "author_name": "Kamini Kunasegaran", - "author_inst": "Duke-NUS Medical School" - }, - { - "author_name": "Linda Tan", - "author_inst": "Saw Swee Hock School of Public Health, National University of Singapore" - }, - { - "author_name": "Charles-Antoine Dutertre", - "author_inst": "Gustave Roussy" - }, - { - "author_name": "Nivedita Shankar", - "author_inst": "Saw Swee Hock School of Public Health, National University of Singapore" - }, - { - "author_name": "Joey ME Lim", - "author_inst": "Duke-NUS Medical School" - }, - { - "author_name": "Louisa Jin Sun", - "author_inst": "Alexandra Hospital, National University Health System" - }, - { - "author_name": "Marina Zahari", - "author_inst": "Saw Swee Hock School of Public Health, National University of Singapore" - }, - { - "author_name": "Zaw M Tun", - "author_inst": "Saw Swee Hock School of Public Health, National University of Singapore" - }, - { - "author_name": "Vishakha Kumar", - "author_inst": "Saw Swee Hock School of Public Health, National University of Singapore" - }, - { - "author_name": "Beng Lee Lim", - "author_inst": "Duke-NUS Medical School" - }, - { - "author_name": "Siew Hoon Lim", - "author_inst": "Singapore General Hospital" - }, - { - "author_name": "Adeline Chia", - "author_inst": "Duke-NUS Medical School" - }, - { - "author_name": "Yee-Joo Tan", - "author_inst": "Yong Loo Lin School of Medicine, National University of Singapore" - }, - { - "author_name": "Paul Anantharajah Tambyah", - "author_inst": "National University Hospital" + "author_name": "Martin Bartas", + "author_inst": "University of Ostrava" }, { - "author_name": "Shirin Kalimuddin", - "author_inst": "Singapore General Hospital" + "author_name": "Adriana Volna", + "author_inst": "Department of Physics, Faculty of Science, University of Ostrava, Ostrava, 71000, Czech Republic" }, { - "author_name": "David CB Lye", - "author_inst": "National Centre of Infectious Diseases" + "author_name": "Christopher A Beaudoin", + "author_inst": "University of Cambridge" }, { - "author_name": "Jenny GH Low", - "author_inst": "Singapore General Hospital" + "author_name": "Ebbe Toftgaard Poulsen", + "author_inst": "Deparment of Molecular Biology and Genetics, Aarhus University, 8000 Aarhus, Denmark" }, { - "author_name": "Lin-Fa Wang", - "author_inst": "Duke-NUS Medical School" + "author_name": "Jiri Cerven", + "author_inst": "Department of Biology and Ecology, University of Ostrava, Ostrava, 710 00, Czech Republic" }, { - "author_name": "Wei Yee Wan", - "author_inst": "Singapore General Hospital" + "author_name": "Vaclav Brazda", + "author_inst": "Institute of Biophysics, Czech Academy of Sciences, Brno, 612 65, Czech Republic" }, { - "author_name": "Li Yang Hsu", - "author_inst": "Saw Swee Hock School of Public Health, National University of Singapore" + "author_name": "Vladimir Spunda", + "author_inst": "Department of Physics, Faculty of Science, University of Ostrava, 710 00 Ostrava, Czech Republic" }, { - "author_name": "Antonio Bertoletti", - "author_inst": "Duke-NUS Medical School" + "author_name": "Tom L Blundell", + "author_inst": "University of Cambridge" }, { - "author_name": "Clarence C Tam", - "author_inst": "Saw Swee Hock School of Public Health, National University of Singapore" + "author_name": "Petr Pecinka", + "author_inst": "Department of Biology and Ecology, University of Ostrava, Ostrava, 710 00, Czech Republic" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nd", "type": "new results", - "category": "immunology" + "category": "bioinformatics" }, { "rel_doi": "10.1101/2020.11.25.20236646", @@ -1052223,25 +1052259,45 @@ "category": "emergency medicine" }, { - "rel_doi": "10.1101/2020.11.23.20237172", - "rel_title": "Effect of hot zone infection outbreaks on the dynamics of SARS-CoV-2 spread in the community at large", + "rel_doi": "10.1101/2020.11.23.20237024", + "rel_title": "COVID-19: Short term prediction model using daily incidence data", "rel_date": "2020-11-24", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.23.20237172", - "rel_abs": "Transmission of SARS-CoV-2 appears especially effective in \"hot zone\" locations where individuals interact in close proximity. We present mathematical models describing two types of hot zones. First, we consider a metapopulation model of infection spread where transmission hot zones are explicitly described by independent demes in which the same people repeatedly interact (referred to as \"static\" hot zones, e.g. nursing homes, food processing plants, prisons, etc.). These are assumed to exists in addition to a \"community at large\" compartment in which virus transmission is less effective. This model yields a number of predictions that are relevant to interpreting epidemiological patterns in COVID19 data. Even if the rate of community virus spread is assumed to be relatively slow, outbreaks in hot zones can temporarily accelerate initial community virus growth, which can lead to an overestimation of the viral reproduction number in the general population. Further, the model suggests that hot zones are a reservoir enabling the prolonged persistence of the virus at \"infection plateaus\" following implementation of non-pharmaceutical interventions, which has been frequently observed in data. The second model considers \"dynamic\" hot zones, which can repeatedly form by drawing random individuals from the community, and subsequently dissolve (e.g. restaurants, bars, movie theaters). While dynamic hot zones can accelerate the average rate of community virus spread and can provide opportunities for targeted interventions, they do not predict the occurrence of infection plateaus or other atypical epidemiological dynamics. The models therefore identify two types of transmission hot zones with very different effects on the infection dynamics, which warrants further epidemiological investigations.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.23.20237024", + "rel_abs": "BackgroundPrediction of the dynamics of new SARS-CoV-2 infections during the current COVID-19 pandemic is critical for public health planning of efficient health care allocation and monitoring the effects of policy interventions. We describe a new approach that forecasts the number of incident cases in the near future given past occurrences using only a small number of assumptions.\n\nMethodsOur approach to forecasting future COVID-19 cases involves 1) modeling the observed incidence cases using a Poisson distribution for the daily incidence number, and a gamma distribution for the series interval; 2) estimating the effective reproduction number assuming its value stays constant during a short time interval; and 3) drawing future incidence cases from their posterior distributions, assuming that the current transmission rate will stay the same, or change by a certain degree.\n\nResultsWe apply our method to predicting the number of new COVID-19 cases in a single state in the U.S. and for a subset of counties within the state to demonstrate the utility of this method at varying scales of prediction. Our method produces reasonably accurate results when the effective reproduction number is distributed similarly in the future as in the past. Large deviations from the predicted results can imply that a change in policy or some other factors have occurred that have dramatically altered the disease transmission over time.\n\nConclusionWe presented a modelling approach that we believe can be easily adopted by others, and immediately useful for local or state planning.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Dominik Wodarz", - "author_inst": "University of California Irvine" + "author_name": "Hongwei Zhao", + "author_inst": "Texas A&M University" }, { - "author_name": "Natalia L. Komarova", - "author_inst": "University of California Irvine" + "author_name": "Naveed N Merchant", + "author_inst": "Texas A&M University" }, { - "author_name": "Luis M. Schang", - "author_inst": "Cornell University" + "author_name": "Alyssa McNulty", + "author_inst": "Texas A&M University" + }, + { + "author_name": "Tiffany Radcliff", + "author_inst": "Texas A&M University" + }, + { + "author_name": "Murray J Cote", + "author_inst": "Texas A&M University" + }, + { + "author_name": "Rebecca Fischer", + "author_inst": "Texas A&M University" + }, + { + "author_name": "Huiyan Sang", + "author_inst": "Texas A&M University" + }, + { + "author_name": "Marcia G Ory", + "author_inst": "Texas A&M University" } ], "version": "1", @@ -1053817,55 +1053873,79 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2020.11.24.389627", - "rel_title": "The rocaglate CR-31-B (-) inhibits SARS-CoV-2 replication at non-cytotoxic, low nanomolar concentrations in vitro and ex vivo", + "rel_doi": "10.1101/2020.11.17.386714", + "rel_title": "Mutations in SARS-CoV-2 spike protein and RNA polymerase complex are associated with COVID-19 mortality risk", "rel_date": "2020-11-24", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.11.24.389627", - "rel_abs": "Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a betacoronavirus in the subgenus Sarbecovirus causes a respiratory disease with varying symptoms referred to as coronavirus disease 2019 (COVID-19) and is responsible for a pandemic that started in early 2020. With no vaccines or effective antiviral treatments available, and infection and fatality numbers continuing to increase globally, the quest for novel therapeutic solutions remains an urgent priority. Rocaglates, a class of plant-derived cyclopenta[b]benzofurans, exhibit broad-spectrum antiviral activity against positive- and negative-sense RNA viruses. This compound class inhibits eukaryotic initiation factor 4A (eIF4A)-dependent mRNA translation initiation, resulting in strongly reduced viral RNA translation. The synthetic rocaglate CR-31-B (-) has previously been shown to inhibit the replication of human coronaviruses, such as HCoV-229E and MERS-CoV, as well as Zika-, Lassa-, Crimean Congo hemorrhagic fever virus in primary cells. Here, we assessed the antiviral activity of CR-31-B (-) against SARS-CoV-2 using both in vitro and ex vivo cell culture models. In African green monkey Vero E6 cells, CR-31-B (-) inhibited SARS-CoV-2 replication with an EC50 of ~1.8 nM. In line with this, viral protein accumulation and replication/transcription complex formation were found to be strongly reduced by this compound. In an ex vivo infection system using human airway epithelial cells, CR-31-B (-) was found to cause a massive reduction of SARS-CoV-2 titers by about 4 logs to nearly non-detectable levels. The data reveal a potent anti-SARS-CoV-2 activity by CR-31-B (-), corroborating previous results obtained for other coronaviruses and supporting the idea that rocaglates may be used in first-line antiviral intervention strategies against novel and emerging RNA virus outbreaks.", - "rel_num_authors": 9, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.11.17.386714", + "rel_abs": "BackgroundSARS-CoV-2 mortality has been extensively studied in relation to host susceptibility. How sequence variations in the SARS-CoV-2 genome affect pathogenicity is poorly understood. Whole-genome sequencing (WGS) of the virus with death in SARS-CoV-2 patients is one potential method of early identification of highly pathogenic strains to target for containment.\n\nMethodsWe analyzed 7,548 single stranded RNA-genomes of SARS-CoV-2 patients in the GISAID database (Elbe and Buckland-Merrett, 2017; Shu and McCauley, 2017) and associated variants with reported patients health status from COVID-19, i.e. deceased versus non-deceased. We probed each locus of the single stranded RNA of the SARS-CoV-2 virus for direct association with host/patient mortality using a logistic regression.\n\nResultsIn total, evaluating 29,891 loci of the viral genome for association with patient/host mortality, two loci, at 12,053bp and 25,088bp, achieved genome-wide significance (p-values of 4.09e-09 and 4.41e-23, respectively).\n\nConclusionsMutations at 25,088bp occur in the S2 subunit of the SARS-CoV-2 spike protein, which plays a key role in viral entry of target host cells. Additionally, mutations at 12,053bp are within the ORF1ab gene, in a region encoding for the protein nsp7, which is necessary to form the RNA polymerase complex responsible for viral replication and transcription. Both mutations altered amino acid coding sequences, potentially imposing structural changes that could enhance viral infectivity and symptom severity, and may be important to consider as targets for therapeutic development. Identification of these highly significant associations, unlikely to occur by chance, may assist with COVID-19 early containment of strains that are potentially highly pathogenic.", + "rel_num_authors": 15, "rel_authors": [ { - "author_name": "Christin Mueller", - "author_inst": "Justus-Liebig University Giessen" + "author_name": "Georg Hahn", + "author_inst": "Harvard T.H. Chan School of Public Health" }, { - "author_name": "Wiebke Obermann", - "author_inst": "Philipps University Marburg" + "author_name": "Chloe M. Wu", + "author_inst": "Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA" }, { - "author_name": "Nadja Karl", - "author_inst": "Justus-Liebig University Giessen" + "author_name": "Sanghun Lee", + "author_inst": "Department of Biostatistics, T.H. Chan School of Public Health, Harvard University, Boston, MA 02115, USA" }, { - "author_name": "Hans G. Wendel", - "author_inst": "Sloan-Kettering Institute" + "author_name": "Julian Hecker", + "author_inst": "Harvard Medical School, University, Boston MA 02115, USA" }, { - "author_name": "Gaspar Taroncher-Oldenburg", - "author_inst": "Gaspar Taroncher Consulting, Philadelphia" + "author_name": "Sharon M. Lutz", + "author_inst": "Department of Biostatistics, T.H. Chan School of Public Health, Harvard University, Boston, MA 02115, USA" }, { - "author_name": "Stephan Pleschka", - "author_inst": "Justus-Liebig University Giessen" + "author_name": "Sebastien Haneuse", + "author_inst": "Department of Biostatistics, T.H. Chan School of Public Health, Harvard University, Boston, MA 02115, USA" }, { - "author_name": "Roland K. Hartmann", - "author_inst": "Philipps University Marburg" + "author_name": "Dawn DeMeo", + "author_inst": "Harvard Medical School, University, Boston MA 02115, USA" }, { - "author_name": "Arnold Gruenweller", - "author_inst": "Philipps University Marburg" + "author_name": "Manish C. Choudhary", + "author_inst": "Harvard Medical School, University, Boston MA 02115, USA" }, { - "author_name": "John Ziebuhr", - "author_inst": "Justus Liebig University Giessen" + "author_name": "Behzad Etemad", + "author_inst": "Harvard Medical School, University, Boston MA 02115, USA" + }, + { + "author_name": "Abbas Mohammadi", + "author_inst": "Harvard Medical School, University, Boston MA 02115, USA" + }, + { + "author_name": "Elmira Esmaeilzadeh", + "author_inst": "Harvard Medical School, University, Boston MA 02115, USA" + }, + { + "author_name": "Rudolph E. Tanzi", + "author_inst": "Harvard Medical School, University, Boston MA 02115, USA" + }, + { + "author_name": "Nan M. Laird", + "author_inst": "Department of Biostatistics, T.H. Chan School of Public Health, Harvard University, Boston, MA 02115, USA" + }, + { + "author_name": "Katharina Ribbeck", + "author_inst": "Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA" + }, + { + "author_name": "Christoph Lange", + "author_inst": "Department of Biostatistics, T.H. Chan School of Public Health, Harvard University, Boston, MA 02115, USA" } ], "version": "1", "license": "cc_no", "type": "new results", - "category": "molecular biology" + "category": "genomics" }, { "rel_doi": "10.1101/2020.11.23.20236810", @@ -1055443,45 +1055523,37 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2020.11.20.20235812", - "rel_title": "Psychosocial Health of School-aged Children during the Initial COVID-19 Safer-At-Home School Mandates in Florida: A cross-sectional study", + "rel_doi": "10.1101/2020.11.21.20236034", + "rel_title": "Role of asymptomatic COVID-19 cases in viral transmission: Findings from a hierarchical community contact network model", "rel_date": "2020-11-23", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.20.20235812", - "rel_abs": "BackgroundGiven the emerging literature regarding the impacts of lockdown measures on mental health, this study aims to identify risk factors in school-aged children for being at risk for psychosocial disorders during the COVID-19 Safer-at-Home School mandates in Florida\n\nMethodsA cross-sectional study was conducted in April 2020 (n=280). Bivariate analysis and logistic and multinomial logistic regression models are used to examine socio-demographic and knowledge, attitude, and practice (KAP) predictors of anxiety, depression, and obsessive- compulsive disorder (OCD).\n\nResultsLoss of household income was associated with being at risk for depression [aOR=3.130, 95% CI= (1.41-6.97)], anxiety [aOR=2.531, 95%CI= (1.154-5.551)], and OCD [aOR=2.90, 95%CI= (1.32-6.36)]. Being female was associated with risk for depression [aOR=1.72, 95% CI=(1.02-2.93)], anxiety [aOR=1.75, 95% CI=(1.04-2.97)], and OCD[aOR=1.764, 95%CI= (1.027-3.028)]. Parental practices that are protective against COVID-19 were associated with children being at risk of depression [aOR=1.55, 95% CI= (1.04-2.31)]. Being at a lower school level was risk factor for anxiety and OCD.\n\nConclusionsEfforts to address mental health risk in children, as a result schools should prioritize girls, younger children, and children of families who lose income. Limiting the spread of COVID-19 through school closure may exacerbate the risk of psychosocial disorders in children, thus school administrators should move quickly to target those at greatest risk.", - "rel_num_authors": 7, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.21.20236034", + "rel_abs": "BackgroundAs part of on-going efforts to contain the COVID-19 pandemic, understanding the role of asymptomatic patients in the transmission system is essential to infection control. However, optimal approach to risk assessment and management of asymptomatic cases remains unclear.\n\nMethodsThis study involved a SEINRHD epidemic propagation model, constructed based on epidemiological characteristics of COVID-19 in China, accounting for the heterogeneity of social network. We assessed epidemic control measures for asymptomatic cases on three dimensions. Impact of asymptomatic cases on epidemic propagation was examined based on the effective reproduction number, abnormally high transmission events, and type and structure of transmission.\n\nResultsManagement of asymptomatic cases can help flatten the infection curve. Tracking 75% of asymptomatic cases corresponds to an overall reduction in new cases by 34.3% (compared to tracking no asymptomatic cases). Regardless of population-wide measures, family transmission is higher than other types of transmission, accounting for an estimated 50% of all cases.\n\nConclusionsAsymptomatic case tracking has significant effect on epidemic progression. When timely and strong measures are taken for symptomatic cases, the overall epidemic is not sensitive to the implementation time of the measures for asymptomatic cases.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Sarah Lindley McKune", - "author_inst": "University of Florida" - }, - { - "author_name": "Daniel E Acosta", - "author_inst": "University of Florida" - }, - { - "author_name": "Nick Diaz", - "author_inst": "University of Florida" + "author_name": "Tianyi Luo", + "author_inst": "University of Chinese Academy of Sciences; Institute of Automation Chinese Academy of Sciences" }, { - "author_name": "Kaitlin Brittain", - "author_inst": "University of Florida" + "author_name": "Zhidong Cao", + "author_inst": "Institute of Automation Chinese Academy of Sciences" }, { - "author_name": "Diana Joyce Beaulieu", - "author_inst": "University of Florida" + "author_name": "Yuejiao Wang", + "author_inst": "University of Chinese Academy of Sciences; Institute of Automation Chinese Academy of Sciences" }, { - "author_name": "Anthony Thomas Maurelli", - "author_inst": "University of Florida" + "author_name": "Daniel Dajun Zeng", + "author_inst": "Institute of Automation Chinese Academy of Sciences" }, { - "author_name": "Eric J. Nelson", - "author_inst": "University of Florida" + "author_name": "Qingpeng Zhang", + "author_inst": "City University of Hong Kong" } ], "version": "1", - "license": "cc_by", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "public and global health" }, @@ -1057053,55 +1057125,31 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.11.18.20232892", - "rel_title": "A follow-up study shows no new infections caused by patients with repeat positive of COVID-19 in Wuhan", + "rel_doi": "10.1101/2020.11.19.20233437", + "rel_title": "Viruses such as SARS-CoV-2 can be partially shielded from UV radiation when in particles generated by sneezing or coughing: Numerical simulations", "rel_date": "2020-11-22", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.18.20232892", - "rel_abs": "BackgroundIt has been reported that a few recovered COVID-19 patients could suffer repeat positive, testing positive for the SARS-CoV-2 virus again after they were discharged from hospital. Understanding the epidemiological characteristics of patients with repeat positive is vital in preventing a second wave of COVID-19.\n\nMethodsIn this study, the epidemiological and clinical features for 20,280 COVID-19 patients from multiple centers between 31 December 2019 and 4 August 2020 in Wuhan were collected and followed. In addition, the RT-qPCR testing results for 4,079 individuals who had close contact with the patients suffering repeat positive were also obtained.\n\nResults2,466 (12.16%) of 20,280 patients presented with a repeat positive of SARS-CoV-2 after they were discharged from hospital. 4,079 individuals had close contact with them. The PCR result were negative for the 4,079 individuals.\n\nConclusionsBy a follow-up study in Wuhan, we show the basic characteristics of patients with repeat positive and no new infections caused by patients with repeat positive of COVID-19.", - "rel_num_authors": 9, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.19.20233437", + "rel_abs": "UV radiation can inactivate viruses such as SARS-CoV-2. However, designing effective UV germicidal irradiation (UVGI) systems can be difficult because the effects of dried respiratory droplets and other fomites on UV light intensities are poorly understood. Numerical modeling of UV intensities inside virus-containing particles on surfaces can increase understanding of these possible reductions in UV intensity. We model UV intensities within spherical approximations of virions randomly positioned within spherical particles. The model virions and dried particles have sizes and optical properties to approximate SARS-CoV-2 and dried particles formed from respiratory droplets, respectively. Wavelengths used are 260 nm (germicidal UVC) and 302 nm (solar UVB). In 5- and 9-m diameter particles on a surface, illuminated by 260-nm UV light from a direction perpendicular to the surface, 10% and 18% (respectively) of simulated virions are exposed to intensities less than 1/100th of intensities in individually exposed virions (i.e., they are partially shielded). Even for 302-nm light, where the absorption is small, 11% of virions in 9-{micro}m particles have exposures 1/100th those of individually exposed virions. Calculated results show that shielding of virions in a particle can be strongly reduced by illuminating a particle either from multiple widely separated incident directions, or by illuminating a particle rotating in air (because of turbulence, Brownian diffusion, etc.) for a time sufficient to rotate through all orientations with respect to the UV illumination. Because highly UV-reflective paints and surfaces can increase the angular ranges of illumination, they appear likely to be useful for reducing shielding of virions.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Xiaomin Wu", - "author_inst": "Wuhan Center for Disease Control and Prevention, Wuhan, China" - }, - { - "author_name": "Zengmiao Wang", - "author_inst": "State Key Laboratory of Remote Sensing Science, College of Global Change and Earth System Science, Beijing Normal University, Beijing, China" - }, - { - "author_name": "Zhenyu He", - "author_inst": "Wuhan Center for Disease Control and Prevention, Wuhan, China" - }, - { - "author_name": "Yapin Li", - "author_inst": "Central Theater Center for Disease Control and Prevention of PLA, Beijing, China" - }, - { - "author_name": "Yating Wu", - "author_inst": "Wuhan Center for Disease Control and Prevention, Wuhan, China" - }, - { - "author_name": "Huaiji Wang", - "author_inst": "Wuhan Center for Disease Control and Prevention, Wuhan, China" - }, - { - "author_name": "Yonghong Liu", - "author_inst": "State Key Laboratory of Remote Sensing Science, College of Global Change and Earth System Science, Beijing Normal University, Beijing, China" + "author_name": "David C Doughty III", + "author_inst": "US Army DEVCOM Army Research Laboratory" }, { - "author_name": "Fanghua Hao", - "author_inst": "Central China Normal University, Wuhan, China" + "author_name": "Steven C Hill", + "author_inst": "US Army DEVCOM Army Research Laboratory" }, { - "author_name": "Huaiyu Tian", - "author_inst": "State Key Laboratory of Remote Sensing Science, College of Global Change and Earth System Science, Beijing Normal University, Beijing, China" + "author_name": "Daniel W Mackowski", + "author_inst": "Auburn University" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "occupational and environmental health" }, { "rel_doi": "10.1101/2020.11.19.20234567", @@ -1059463,37 +1059511,65 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.11.18.20230649", - "rel_title": "A network modelling approach to assess non-pharmaceutical disease controls in a worker population: An application to SARS-CoV-2", + "rel_doi": "10.1101/2020.11.18.20234104", + "rel_title": "Clinical evaluation of the Roche/SD Biosensor rapid antigen test with symptomatic, non-hospitalized patients in a municipal health service drive-through testing site.", "rel_date": "2020-11-20", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.18.20230649", - "rel_abs": "BackgroundAs part of a concerted pandemic response to protect public health, businesses can enact non-pharmaceutical controls to minimise exposure to pathogens in workplaces and premises open to the public. Amendments to working practices can lead to the amount, duration and/or proximity of interactions being changed, ultimately altering the dynamics of disease spread. These modifications could be specific to the type of business being operated.\n\nMethodsWe use a data-driven approach to parameterise an individual-based network model for transmission of SARS-CoV-2 amongst the working population, stratified into work sectors. The network is comprised of layered contacts to consider the risk of spread in multiple encounter settings (workplaces, households, social and other). We analyse several interventions targeted towards working practices: mandating a fraction of the population to work from home; using temporally asynchronous work patterns; and introducing measures to create COVID-secure workplaces. We also assess the general role of adherence to (or effectiveness of) isolation and test and trace measures and demonstrate the impact of all these interventions across a variety of relevant metrics.\n\nResultsThe progress of the epidemic can be significantly hindered by instructing a significant proportion of the workforce to work from home. Furthermore, if required to be present at the workplace, asynchronous work patterns can help to reduce infections when compared with scenarios where all workers work on the same days, particularly for longer working weeks. When assessing COVID-secure workplace measures, we found that smaller work teams and a greater reduction in transmission risk reduced the probability of large, prolonged outbreaks. Finally, following isolation guidance and engaging with contact tracing without other measures is an effective tool to curb transmission, but is highly sensitive to adherence levels.\n\nConclusionsIn the absence of sufficient adherence to non-pharmaceutical interventions, our results indicate a high likelihood of SARS-CoV-2 spreading widely throughout a worker population. Given the heterogeneity of demographic attributes across worker roles, in addition to the individual nature of controls such as contact tracing, we demonstrate the utility of a network model approach to investigate workplace-targeted intervention strategies and the role of test, trace and isolation in tackling disease spread.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.18.20234104", + "rel_abs": "BackgroundRapid detection of infectious individuals is essential in stopping the further spread of SARS-CoV-2. Although rapid antigen test is not as sensitive as the gold standard RT-PCR, the time to result is decreased by day(s), strengthening the effectiveness of contact tracing.\n\nMethodsThe Roche/SD Biosensor lateral flow antigen rapid test was evaluated in a mild symptomatic population at a large drive through testing site. A second nasopharyngeal swab was directly tested with the rapid test on site and results were compared to RT-PCR and virus culture. Date of onset and symptoms were analysed using data from a clinical questionnaire.\n\nResultsWe included 970 persons with complete data. Overall sensitivity and specificity were 84.9% (CI95% 79.1-89.4) and 99.5% (CI95% 98.7-99.8) which translated into a positive predictive value of 97.5% (CI95% 94.0-99.5) under the current regional PCR positivity of 19.2%. Sensitivity for people with high loads of viral RNA (ct <30, 2.17E+05 E gene copy/ml) and who presented within 7 days since symptom onset increased to 95.8% (CI95% 90.5-98.2). Band intensity and time to result correlated strongly with viral load thus strong positive bands could be read before the recommended time. Around 98% of all viable specimen with ct <30 were detected successfully indicating that the large majority of infectious people can be captured with this test.\n\nConclusionAntigen rapid tests can detect mildly symptomatic cases in the early phase of disease thereby identifying the most infectious individuals. Using this assay can have a significant value in the speed and effectiveness of SARS-CoV-2 outbreak management.\n\nSummaryO_LIPeople with early onset and high viral load were detected with 98.2% sensitivity.\nC_LIO_LI97% of individuals in which virus could be cultured were detected by the rapid test.\nC_LIO_LIThis test is suitable to detect mild symptomatic cases.\nC_LI", + "rel_num_authors": 12, "rel_authors": [ { - "author_name": "Edward M Hill", - "author_inst": "University of Warwick" + "author_name": "Zsofia Igloi", + "author_inst": "Department of Viroscience, Erasmus MC, Rotterdam" }, { - "author_name": "Benjamin D Atkins", - "author_inst": "University of Warwick" + "author_name": "Jans Velzing", + "author_inst": "Department of Viroscience, Erasmus MC, Rotterdam" }, { - "author_name": "Matt J Keeling", - "author_inst": "University of Warwick" + "author_name": "Janko van Beek", + "author_inst": "Department of Viroscience, Erasmus MC, Rotterdam" }, { - "author_name": "Louise Dyson", - "author_inst": "University of Warwick" + "author_name": "David van de Vijver", + "author_inst": "Department of Viroscience, Erasmus MC, Rotterdam" }, { - "author_name": "Michael J Tildesley", - "author_inst": "University of Warwick" + "author_name": "Georgina Aron", + "author_inst": "Department of Viroscience, Erasmus MC, Rotterdam" + }, + { + "author_name": "Roel Ensing", + "author_inst": "Public Health Service Rotterdam-Rijnmond" + }, + { + "author_name": "Kimberley Benschop", + "author_inst": "Centre for infectious Disease Control (Cib), National Public Health Institute (RIVM)" + }, + { + "author_name": "Wanda Han", + "author_inst": "Centre for infectious Disease Control (Cib), National Public Health Institute (RIVM)" + }, + { + "author_name": "Timo Boelsums", + "author_inst": "Public Health Service Rotterdam-Rijnmond, Rotterdam" + }, + { + "author_name": "Marion Koopmans", + "author_inst": "Department of Viroscience, Erasmus MC, Rotterdam" + }, + { + "author_name": "Corine Geurtsvankessel", + "author_inst": "Department of Viroscience, Erasmus MC, Rotterdam" + }, + { + "author_name": "Richard Molenkamp", + "author_inst": "Department of Viroscience, Erasmus MC, Rotterdam" } ], "version": "1", - "license": "cc_by", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1061309,33 +1061385,77 @@ "category": "geriatric medicine" }, { - "rel_doi": "10.1101/2020.11.16.20232512", - "rel_title": "5-Alpha-Reductase Inhibitors Reduce Remission Time of COVID-19: Results From a Randomized Double Blind Placebo Controlled Interventional Trial in 130 SARS-CoV-2 Positive Men", + "rel_doi": "10.1101/2020.11.16.20231514", + "rel_title": "Low Dose Radiation Therapy for COVID-19 Pneumonia: A Pilot Study", "rel_date": "2020-11-18", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.16.20232512", - "rel_abs": "BackgroundSARS-CoV-2 entry into type II pneumocytes is depended on the TMPRSS2 proteolytic enzyme. The only known promoter of TMPRSS2 in humans is an androgen response element. As such, androgen sensitivity may be a risk factor for COVID-19. Previously, we have reported a retrospective cohort analysis demonstrating the protective effect of 5-alpha-reductase inhibitors (5ARis) in COVID-19. Men using 5ARis were less likely to be admitted to the ICU than men not taking 5ARis. Additionally, men using 5ARis had drastically reduced frequency of symptoms compared to men not using 5ARis in an outpatient setting. Here we aim to determine if 5ARis will be a beneficial treatment if given after SARS-CoV-2 infection.\n\nMethodsA double-blinded, randomized, prospective, investigational study of dutasteride for the treatment of COVID-19 (NCT04446429). Subjects confirmed positive for SARS-CoV-2 were treated in an outpatient setting. Endpoints for the study were remission times for a predetermined set of symptoms: fever or feeling feverish, cough, shortness of breath, sore throat, body pain or muscle pain/ache, fatigue, headache, nasal congestion, nasal discharge (runny nose), nausea or vomiting, diarrhea, loss of appetite, and loss of taste or smell (Ageusia or Anosmia).\n\nResultsA total of 130 SARS-CoV-2 positive men were included in the study, 64 subjects in the dutasteride arm and 66 subjects in the placebo-controlled group. The differences in the average remission times for fatigue and anosmia or ageusia was statistically different between the groups (5.8 versus 10.1 days for fatigue and 7.3 versus 13.4 days for anosmia or ageusia, in dutasteride and placebo groups, respectively), however, the total remission time was significantly reduced for the men given dutasteride; 9.0 days versus 15.6 days in the placebo group (p < 0.001). Excluding loss of taste and smell the average total remission time was 7.3 days in the dutasteride group versus 11.7 in the placebo arm (p < 0.001).\n\nConclusionThe total remission time for men using 5ARis was significantly reduced compared to men not taking 5ARis.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.16.20231514", + "rel_abs": "BackgroundThe World Health Organization (WHO) has declared coronavirus disease 2019 (COVID-19) as pandemic in March 2020. Currently there is no vaccine or specific effective treatment for COVID-19. The major cause of death in COVID-19 is severe pneumonia leading to respiratory failure. Radiation in low doses (<100 cGy) has been known for its anti-inflammatory effect and therefore, low dose radiation therapy (LDRT) to lungs can potentially mitigate the severity of pneumonia and reduce mortality. We conducted a pilot trial to study the feasibility and clinical efficacy of LDRT to lungs in the management of patients with COVID-19.\n\nMethodsFrom June to Aug 2020, we enrolled 10 patients with COVID-19 having moderate to severe risk disease [National Early Warning Score (NEWS) of [≥]5]. Patients were treated as per the standard COVID-19 management guidelines along with LDRT to both lungs with a dose of 70cGy in single fraction. Response assessment was done based on the clinical parameters using the NEWS.\n\nResultsAll patients completed the prescribed treatment. Nine patients had complete clinical recovery mostly within a period ranging from 3-7 days. One patient, who was a known hypertensive, showed clinical deterioration and died 24 days after LDRT. No patients showed the signs of acute radiation toxicity.\n\nConclusionResults of our study (90% response rate) suggest the feasibility and clinical effectiveness of LDRT in COVID-19 patients having moderate to severe risk disease. This mandates a randomized controlled trial to establish the clinical efficacy of LDRT in COVID-19 pneumonia.", + "rel_num_authors": 15, "rel_authors": [ { - "author_name": "Flavio A Cadegiani", - "author_inst": "Federal University of Sao Paulo" + "author_name": "Daya Nand Sharma", + "author_inst": "AIIMS, New Delhi" }, { - "author_name": "John McCoy", - "author_inst": "Applied Biology, Inc. Irvine, CA, USA" + "author_name": "Randeep Guleria", + "author_inst": "All India Institute of Medical Sciences, New Delhi 110029 India" }, { - "author_name": "Carlos Gustavo Wambier", - "author_inst": "Department of Dermatology, Alpert Medical School of Brown University, Providence, RI, USA." + "author_name": "Naveet Wig", + "author_inst": "All India Institute of Medical Sciences, New Delhi 110029 India" }, { - "author_name": "Andy Goren", - "author_inst": "Applied Biology, Inc. Irvine, CA, USA." + "author_name": "Anant Mohan", + "author_inst": "All India Institute of Medical Sciences, New Delhi 110029 India" + }, + { + "author_name": "Goura Kisor Rath", + "author_inst": "All India Institute of Medical Sciences, New Delhi 110029 India" + }, + { + "author_name": "Vellaiyan Subramani", + "author_inst": "All India Institute of Medical Sciences, New Delhi 110029 India" + }, + { + "author_name": "Sushma Bhatnagar", + "author_inst": "All India Institute of Medical Sciences, New Delhi 110029 India" + }, + { + "author_name": "Supriya Mallick", + "author_inst": "All India Institute of Medical Sciences, New Delhi 110029 India" + }, + { + "author_name": "Aman Sharma", + "author_inst": "All India Institute of Medical Sciences, New Delhi 110029 India" + }, + { + "author_name": "Pritee Patil", + "author_inst": "All India Institute of Medical Sciences, New Delhi 110029 India" + }, + { + "author_name": "Karan Madan", + "author_inst": "All India Institute of Medical Sciences, New Delhi 110029 India" + }, + { + "author_name": "Manish Soneja", + "author_inst": "All India Institute of Medical Sciences, New Delhi 110029 India" + }, + { + "author_name": "Sanjay Thulkar", + "author_inst": "All India Institute of Medical Sciences, New Delhi 110029 India" + }, + { + "author_name": "Angel Rajan Singh", + "author_inst": "All India Institute of Medical Sciences, New Delhi 110029 India" + }, + { + "author_name": "Sheetal Singh", + "author_inst": "All India Institute of Medical Sciences, New Delhi 110029 India" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1062731,51 +1062851,43 @@ "category": "oncology" }, { - "rel_doi": "10.1101/2020.11.17.20231498", - "rel_title": "Impact of a public policy restricting staff mobility between long-term care homes in Ontario, Canada during the COVID-19 pandemic", + "rel_doi": "10.1101/2020.11.17.20232983", + "rel_title": "COHD-COVID: Columbia Open Health Data for COVID-19 Research", "rel_date": "2020-11-18", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.17.20231498", - "rel_abs": "ObjectivesTo assess changes in the mobility of staff between long-term care homes in Ontario, Canada before and after enactment of public policy restricting staff from working at multiple homes.\n\nDesignPre-post observational study.\n\nSetting and Participants623 long-term cares homes in Ontario, Canada between March 2020 and June 2020.\n\nMethodsWe used anonymized mobile device location data to approximate connectivity between all 623 long-term care homes in Ontario during the 7 weeks before (March 1 - April 21) and after (April 22 - June 13) the policy restricting staff movement was implemented. We visualized connectivity between long-term care homes in Ontario using an undirected network and calculated the number of homes that had a connection with another long-term care home and the average number of connections per home in each period. We calculated the relative difference in these mobility metrics between the two time periods and compared within-home changes using McNemars test and the Wilcoxon rank-sum test.\n\nResultsIn the period preceding restrictions, 266 (42.7%) long-term care homes had a connection with at least one other home, compared to 79 (12.7%) homes during the period after restrictions, a drop of 70.3% (p <0.001). The average number of connections in the before period was 3.90 compared to 0.77 in after period, a drop of 80.3% (p < 0.001). In both periods, mobility between long-term care homes was higher in homes located in larger communities, those with higher bed counts, and those part of a large chain.\n\nConclusions and ImplicationsMobility between long-term care homes in Ontario fell sharply after an emergency order by the Ontario government limiting long-term care staff to a single home, though some mobility persisted. Reducing this residual mobility should be a focus of efforts to reduce risk within the long-term care sector during the COVID-19 pandemic.", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.17.20232983", + "rel_abs": "Massive research efforts have been made in response to the COVID-19 (coronavirus disease-2019) pandemic. Utilization of clinical data can accelerate these research efforts to fight against the pandemic since important characteristics of the patients are often found by examining the clinical data. To provide shareable clinical data to catalyze COVID-19 research, we present Columbia Open Health Data for COVID-19 Research (COHD-COVID), a publicly accessible database providing clinical concept prevalence, clinical concept co-occurrence, and clinical symptom prevalence for hospitalized COVID-19 patients. COHD-COVID also provides data on hospitalized influenza patients and general hospitalized patients as comparator cohorts. The data used in COHD-COVID were obtained from Columbia University Irving Medical Centers electronic health records. We expect COHD-COVID will provide researchers and clinicians quantitative measures of COVID-19 related clinical features to better understand and fight against the pandemic.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Aaron Jones", - "author_inst": "McMaster University" - }, - { - "author_name": "Alexander G Watts", - "author_inst": "BlueDot" - }, - { - "author_name": "Salah Uddin Khan", - "author_inst": "BlueDot" + "author_name": "Junghwan Lee", + "author_inst": "Columbia University" }, { - "author_name": "Jack Forsyth", - "author_inst": "BlueDot" + "author_name": "Jae Hyun Kim", + "author_inst": "Columbia University" }, { - "author_name": "Kevin A Brown", - "author_inst": "Public Health Ontario" + "author_name": "Cong Liu", + "author_inst": "Columbia University" }, { - "author_name": "Andrew P Costa", - "author_inst": "McMaster University" + "author_name": "George Hripcsak", + "author_inst": "Columbia University" }, { - "author_name": "Isaac I Bogoch", - "author_inst": "BlueDot" + "author_name": "Casey Ta", + "author_inst": "Columbia University" }, { - "author_name": "Nathan M Stall", - "author_inst": "University of Toronto" + "author_name": "Chunhua Weng", + "author_inst": "Columbia University" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "geriatric medicine" + "category": "health informatics" }, { "rel_doi": "10.1101/2020.11.18.20233973", @@ -1064249,43 +1064361,35 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2020.11.17.387571", - "rel_title": "In-vitro virucidal activity of hypothiocyanite and hypothiocyanite/lactoferrin mix against SARS-CoV-2", + "rel_doi": "10.1101/2020.11.18.388645", + "rel_title": "Formulation of a composite nasal spray enabling enhanced surface coverage and prophylaxis of SARS-COV-2", "rel_date": "2020-11-18", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.11.17.387571", - "rel_abs": "SARS-CoV-2 replicates efficiently in the upper airway during prodromal stage with resulting viral shedding into the environment from patients with active disease as well as from asymptomatic individuals. So far, virus spread has been exclusively contained by non-pharmacological interventions (social distancing, face masks, hand washing and several measures limiting business activities or movement of individuals)1,2. There is a need to find pharmacological interventions to mitigate the viral spread, supporting yet limiting the existing health protection measures while an effective and safe vaccine will hopefully become available. Hypothiocyanite and lactoferrin as part of the innate human immune system were shown to have a large spectrum of cidal activity against bacteria, fungi and viruses2,3. To test their virucidal activity against SARS-CoV-2 we conducted an in-vitro study. Here we show a dose-dependent virucidal activity of hypothiocyanite at micromolar concentrations, slightly improved by the presence of lactoferrin. The two substances are devoid of any cytotoxicity and may be administered combined by aerosol to exploit their antiviral activity at the port of entry (mouth, nasal cavity, conjunctiva) or exit (mouth, through emission of respiratory droplets) of SARS-CoV-2 in the human body. Furthermore, aerosol with hypothiocyanite and lactoferrin combined could also have a therapeutic effect in the lower respiratory tract, at the level of gas exchange units of the lung, preventing the devastating infection of alveolar type II cells where ACE2 is highly expressed. An in-vivo validation of in-vitro results is urgently required.", - "rel_num_authors": 6, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.11.18.388645", + "rel_abs": "Airborne pathogens pose high risks in terms of both contraction and transmission within the respiratory pathways, in particular the nasal region. Although knowledge of airborne transmission has long been known, there is little in the way of adequate intervention that can protect the individual, or even prevent further spread. This study focuses on a nasal applicant with the capacity to combat such issues, by focussing on the SARS-CoV-2 virus. Formulation of a spray containing polysaccharides known for their mucoadhesive properties was undertaken and characterised for their mechanical, spray patterns and antiviral properties. The ability to engineer key behaviours such as yielding have been shown, through systematic understanding of a composite mixture containing two polymers: gellan and {lambda}carrageenan. Furthermore, spray systems demonstrated highly potent antiviral capacities, resulting in complete inhibition of the virus when studied for both prophylaxis and prevention of spread. Finally, a mechanism has been proposed to explain such findings. Therefore, demonstrating the first fully preventative device, targeted to protect the lining of the upper respiratory pathways.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Luca Cegolon", - "author_inst": "Local Health Unit N.2 \"Marca Trevigiana\", Public Health Department, Treviso, Italy" - }, - { - "author_name": "Mattia Mirandola", - "author_inst": "Padua University, Department of Molecular Medicine, Padua, Italy" - }, - { - "author_name": "Claudio Salaris", - "author_inst": "Padua University, Department of Molecular Medicine, Padua, Italy" + "author_name": "Richard J. A. Moakes", + "author_inst": "University of Birmingham" }, { - "author_name": "Maria Vittoria Salvati", - "author_inst": "Padua University, Department of Molecular Medicine, Padua, Italy" + "author_name": "Scott P. Davies", + "author_inst": "University of Birmingham" }, { - "author_name": "Cristiano Salata", - "author_inst": "Padua University, Department of Molecular Medicine, Padua, Italy" + "author_name": "Zania Stamataki", + "author_inst": "University of Birmingham" }, { - "author_name": "Giuseppe Mastrangelo", - "author_inst": "Padua University, Department of Cardiac, Thoracic, Vascular Sciences & Public Health, Padua, Italy" + "author_name": "Liam M. Grover", + "author_inst": "University of Birmingham" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by_nc_nd", "type": "new results", - "category": "microbiology" + "category": "bioengineering" }, { "rel_doi": "10.1101/2020.11.18.388983", @@ -1066303,37 +1066407,109 @@ "category": "health informatics" }, { - "rel_doi": "10.1101/2020.11.13.20231431", - "rel_title": "Racial and Ethnic Differentials in COVID-19-Related Job Exposures by Occupational Status in the US", + "rel_doi": "10.1101/2020.11.13.20231217", + "rel_title": "Intra-host evolution during SARS-CoV-2 persistent infection", "rel_date": "2020-11-16", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.13.20231431", - "rel_abs": "Researchers and journalists have argued that work-related factors may be partly responsible for disproportionate COVID-19 infection and death rates among vulnerable groups. We evaluate these claims by examining racial and ethnic differences in the likelihood of work-related exposure to COVID-19. We extend previous studies by considering 12 racial and ethnic groups and five types of potential occupational exposure to the virus: exposure to infection, physical proximity to others, face-to-face discussions, interactions with external customers and the public, and working indoors. Most importantly, we stratify our results by occupational standing, defined as the proportion of workers within each occupation with at least some college education. This measure serves as a proxy for whether workplaces and workers employ significant COVID-19-related risk reduction strategies. We use the 2018 American Community Survey to identify recent workers by occupation, and link 409 occupations to information on work context from the Occupational Information Network to identify potential COVID-related risk factors. We then examine the racial/ethnic distribution of all frontline workers and frontline workers at highest potential risk of COVID-19, by occupational standing and by sex. The results indicate that, contrary to expectation, White frontline workers are often overrepresented in high-risk jobs while Black and Latino frontline workers are generally underrepresented in these jobs. However, disaggregation of the results by occupational standing shows that, in contrast to Whites and several Asian groups, Latino and Black frontline workers are overrepresented in lower status occupations overall and in lower status occupations associated with high risk, and are thus less likely to have adequate COVID-19 protections. Our findings suggest that greater work exposures likely contribute to a higher prevalence of COVID-19 among Latino and Black adults and underscore the need for measures to reduce potential exposure for workers in low status occupations and for the development of programs outside the workplace.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.13.20231217", + "rel_abs": "Prolonged infection of SARS-CoV-2 represents a challenge to the development of effective public health policies to control the COVID-19 pandemic. The reason why some people have persistent infection and how the virus survives for so long are still not fully understood. For this reason, we aimed to investigate the intra-host evolution of SARS-CoV-2 during persistent infection. Thirty-three patients who remained RT-PCR positive in the nasopharynx for at least 16 days were included in this study. Complete SARS-CoV-2 sequences were obtained for each patient at two time points. Phylogenetic, populational, and computational analysis of viral sequences confirmed persistent infection with evidence for a transmission cluster in health care professionals that shared the same workplace. A high number of missense variants targeting crucial structural and non-structural proteins such as Spike and Helicase was found. Interestingly, longitudinal acquisition of substitutions in Spike protein mapped many SARS-CoV-2 predicted T cell epitopes. Furthermore, the mutational profiles observed were suggestive of RNA editing enzyme activities, indicating innate immune mechanisms of the host cell. Viral quasispecies analysis corroborates persistent infection mainly by increasing richness and nucleotide diversity over time. Altogether, our findings highlight a dynamic and complex landscape of host and pathogen interaction during persistent infection suggesting that the hosts innate immunity shapes the increase of intra-host diversity with possible implications for therapeutic strategies and public health decisions during the COVID-19 pandemic.", + "rel_num_authors": 23, "rel_authors": [ { - "author_name": "Noreen Goldman", - "author_inst": "Princeton University" + "author_name": "Carolina M Voloch", + "author_inst": "Universidade Federal do Rio de Janeiro" }, { - "author_name": "Anne R Pebley", - "author_inst": "University of California, Los Angeles" + "author_name": "Ronaldo Da Silva F Jr.", + "author_inst": "Laboratorio Nacional de Computacao Cientifica" }, { - "author_name": "Keunbok Lee", - "author_inst": "University of California, Los Angeles" + "author_name": "Luiz G P de Almeida", + "author_inst": "Laboratorio Nacional de Computacao Cientifica" }, { - "author_name": "Theresa Andrasfay", - "author_inst": "University of Southern California" + "author_name": "Otavio J Brustolini", + "author_inst": "Laboratorio Nacional de Computacao Cientifica" }, { - "author_name": "Boriana Pratt", - "author_inst": "Princeton University" + "author_name": "Cynthia C Cardoso", + "author_inst": "Universidade Federal do Rio de Janeiro" + }, + { + "author_name": "Alexandra L Gerber", + "author_inst": "Laboratorio Nacional de Computacao Cientifica" + }, + { + "author_name": "Ana Paula de C Guimaraes", + "author_inst": "Laboratorio Nacional de Computacao Cientifica" + }, + { + "author_name": "Isabela C Leitao", + "author_inst": "Universidade Federal do Rio de Janeiro" + }, + { + "author_name": "Diana Mariani", + "author_inst": "Universidade Federal do Rio de Janeiro" + }, + { + "author_name": "Victor Akira Ota", + "author_inst": "Universidade Federal do Rio de Janeiro" + }, + { + "author_name": "- Covid19-UFRJ Workgroup", + "author_inst": "" + }, + { + "author_name": "- LNCC-Workgroup", + "author_inst": "" + }, + { + "author_name": "Cristiano Xavier Lima", + "author_inst": "Universidade Federal de Minas Gerais & Simile Instituto de Imunologia Aplicada Ltda." + }, + { + "author_name": "Mauro M Teixeira", + "author_inst": "Universidade Federal de Minas Gerais" + }, + { + "author_name": "Ana Carolina F Dias", + "author_inst": "Universidade Federal de Minas Gerais & Simile Instituto de Imunologia Aplicada Ltda." + }, + { + "author_name": "Rafael Mello Galliez", + "author_inst": "Universidade Federal do Rio de Janeiro" + }, + { + "author_name": "Debora Souza Faffe", + "author_inst": "Universidade Federal do Rio de Janeiro" + }, + { + "author_name": "Luis Cristovao Porto", + "author_inst": "Universidade do Estado do Rio de Janeiro" + }, + { + "author_name": "Renato S Aguiar", + "author_inst": "Universidade Federal do Rio de Janeiro" + }, + { + "author_name": "Terezinha M P P Castineira", + "author_inst": "Universidade Federal do Rio de Janeiro" + }, + { + "author_name": "Orlando C Ferreira Jr.", + "author_inst": "Universidade Federal do Rio de Janeiro" + }, + { + "author_name": "Amilcar Tanuri", + "author_inst": "Universidade Federal do Rio de Janeiro" + }, + { + "author_name": "Ana Tereza R de Vasconcelos", + "author_inst": "Laboratorio Nacional de Computacao Cientifica" } ], "version": "1", - "license": "cc_by", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1067953,25 +1068129,105 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.11.13.20230862", - "rel_title": "Lack of immune homology with vaccine preventable pathogens suggests childhood immunizations do not protect against SARS-CoV-2 through adaptive cross-immunity", + "rel_doi": "10.1101/2020.11.13.20231373", + "rel_title": "Dysregulated immunity in SARS-CoV-2 infected pregnant women", "rel_date": "2020-11-16", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.13.20230862", - "rel_abs": "Abstract (Summary)Recent epidemiological studies have investigated the potential effects of childhood immunization history on COVID-19 severity. Specifically, prior exposure to Bacillus Calmette-Guerin (BCG) vaccine, oral poliovirus vaccine (OPV), or measles vaccine have been postulated to reduce COVID-19 severity - putative mechanism is via stimulation of the innate immune system to provide broader protection against non-specific pathogens. While these epidemiological results remain inconclusive, we sought to investigate the potential role of adaptive immunity via cross-reactivity between vaccine preventable diseases (VPDs) with SARS-CoV-2. We implemented a comprehensive exploration of immune homology (including sequence homology, immune epitopes, and glycosylation patterns) between SARS-CoV-2 and all pathogens with FDA-approved vaccines. Sequence homology did not reveal significant alignments of protein sequences between SARS-CoV-2 with any VPD pathogens, including BCG-related strains. We also could not identify any shared T or B cell epitopes between SARS-CoV-2 and VPD pathogens among either experimentally validated epitopes or predicted immune epitopes. For N-glycosylation (N-glyc), while sites with the same tripeptides could be found between SARS-CoV-2 and certain VPD pathogens, their glycosylation potentials and positions were different. In summary, lack of immune homology between SARS-CoV-2 and VPD pathogens suggests that childhood immunization history (i.e., BCG vaccination or others) does not provide protection from SARS-CoV-2 through adaptive cross-immunity.\n\nHighlightsO_LIComprehensive exploration of immune homology for SARS-CoV-2 with 34 vaccine preventable pathogens covering all FDA-approved vaccines.\nC_LIO_LILittle to no immune homology between SARS-CoV-2 and VPD pathogens: insignificant aligned protein sequences, unmapped immune epitopes, or matched N-glycosylation sites with different glycosylation potentials and positions.\nC_LIO_LIBCG vaccination is unlikely to confer SARS-CoV-2 protection through adaptive cross-immunity.\nC_LI\n\nGraphic summary\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=107 SRC=\"FIGDIR/small/20230862v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (53K):\norg.highwire.dtl.DTLVardef@1f07e88org.highwire.dtl.DTLVardef@316caorg.highwire.dtl.DTLVardef@cd4794org.highwire.dtl.DTLVardef@11664bb_HPS_FORMAT_FIGEXP M_FIG C_FIG", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.13.20231373", + "rel_abs": "ImportanceThe effects of SARS-CoV-2 infection on immune responses during pregnancy have not been systematically evaluated.\n\nObjectiveTo assess the impact of SARS-CoV-2 infection during pregnancy on inflammatory and humoral responses in maternal and fetal samples and compare antibody responses to SARS-CoV-2 among pregnant and non-pregnant women.\n\nDesignImmune responses to SARS-CoV-2 were analyzed using samples from pregnant and non-pregnant women who had either tested positive or negative for SARS-CoV-2. We measured, proinflammatory and placental cytokine mRNAs, neonatal Fc receptor (FcRn) receptor expression, and tetanus antibody transfer in maternal and cord blood samples. Additionally, we measured anti-spike (S) IgG, anti-S-receptor binding domain (RBD) IgG, and neutralizing antibody (nAb) responses to SARS-CoV-2 in serum or plasma collected from non-pregnant women, pregnant women, and cord blood.\n\nSettingJohns Hopkins Hospital (JHH)\n\nParticipantsPregnant women were recruited through JHH outpatient obstetric clinics and the JHH Labor & Delivery unit. Non-pregnant women were recruited after receiving outpatient SARS-CoV-2 testing within Johns Hopkins Health System, USA. Adult non-pregnant women with positive RT-PCR results for SARS-CoV-2, within the age range of 18-48 years, were included in the study.\n\nExposuresSARS-CoV-2\n\nMain Outcomes and MeasuresParticipant demographic characteristics, antibody titers, cytokine mRNA expression, and FcRn receptor expression.\n\nResultsSARS-COV-2 positive pregnant women expressed more IL1{beta}, but not IL6, in blood samples collected within 14 days versus > 14 days after a confirmed SARS-CoV-2 test, with similar patterns observed in the fetal side of placentas, particularly among asymptomatic pregnant women. Pregnant women with confirmed SARS-CoV-2 infection also had reduced anti-S-RBD IgG titers and were less likely to have detectable nAb as compared with non-pregnant women. Although SARS-CoV-2 infection did not disrupt FcRn expression in the placenta, maternal transfer of nAb was inhibited by SARS-CoV-2 infection during pregnancy.\n\nConclusions and RelevanceSARS-CoV-2 infection during pregnancy was characterized by placental inflammation and reduced antiviral antibody responses, which may impact the efficacy of COVID-19 therapeutics in pregnancy. The long-term implications of placental inflammation for neonatal health also requires greater consideration.", + "rel_num_authors": 23, "rel_authors": [ { - "author_name": "Weihua Guo", - "author_inst": "City of Hope Cancer Center" + "author_name": "Morgan L. Sherer", + "author_inst": "Johns Hopkins Bloomberg School of Public Health" }, { - "author_name": "Kyle O. Lee", - "author_inst": "NA" + "author_name": "Jun Lei", + "author_inst": "Johns Hopkins School of Medicine" }, { - "author_name": "Peter P. Lee", - "author_inst": "City of Hope Cancer Center" + "author_name": "Patrick Creisher", + "author_inst": "Johns Hopkins Bloomberg School of Public Health" + }, + { + "author_name": "Minyoung Jang", + "author_inst": "Johns Hopkins School of Medicine" + }, + { + "author_name": "Ramya Reddy", + "author_inst": "Johns Hopkins School of Medicine" + }, + { + "author_name": "Kristin Voegtline", + "author_inst": "Johns Hopkins School of Medicine" + }, + { + "author_name": "Sarah Olson", + "author_inst": "Johns Hopkins School of Medicine" + }, + { + "author_name": "Kirsten Littlefield", + "author_inst": "Johns Hopkins Bloomberg School of Public Health" + }, + { + "author_name": "Han-Sol Park", + "author_inst": "Johns Hopkins Bloomberg School of Public Health" + }, + { + "author_name": "Rebecca L. Ursin", + "author_inst": "Johns Hopkins Bloomberg School of Public Health" + }, + { + "author_name": "Abhinaya Ganesan", + "author_inst": "Johns Hopkins Bloomberg School of Public Health" + }, + { + "author_name": "Theresa Boyer", + "author_inst": "Johns Hopkins Bloomberg School of Public Health" + }, + { + "author_name": "Diane M. Brown", + "author_inst": "Johns Hopkins School of Medicine" + }, + { + "author_name": "Samantha Walch", + "author_inst": "Johns Hopkins School of Medicine" + }, + { + "author_name": "Annukka A.R. Antar", + "author_inst": "Johns Hopkins School of Medicine" + }, + { + "author_name": "Yukari C Manabe", + "author_inst": "Johns Hopkins University School of Medicine" + }, + { + "author_name": "Kimberly Jones-Beatty", + "author_inst": "Johns Hopkins School of Medicine" + }, + { + "author_name": "William Christopher Golden", + "author_inst": "Johns Hopkins School of Medicine" + }, + { + "author_name": "Andrew J. Satin", + "author_inst": "Johns Hopkins School of Medicine" + }, + { + "author_name": "Jeanne S. Sheffield", + "author_inst": "Johns Hopkins School of Medicine" + }, + { + "author_name": "Andrew Pekosz", + "author_inst": "Johns Hopkins Bloomberg School of Public Health" + }, + { + "author_name": "Sabra Klein", + "author_inst": "Johns Hopkins Bloomberg School of Public Health" + }, + { + "author_name": "Irina Burd", + "author_inst": "Johns Hopkins School of Medicine" } ], "version": "1", @@ -1069551,63 +1069807,131 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.11.12.20229823", - "rel_title": "COVID-19 COGNITIVE DEFICITS AFTER RESPIRATORY ASSISTANCE IN THE SUBACUTE PHASE:A COVID-REHABILITATION UNIT EXPERIENCE", + "rel_doi": "10.1101/2020.11.12.20229955", + "rel_title": "Mobile consulting (mConsulting) as an option for accessing healthcare services for communities in remote rural areas and urban slums in low- and middle- income countries: A mixed methods study", "rel_date": "2020-11-15", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.12.20229823", - "rel_abs": "IntroductionCOVID-19 complications can include neurological, psychiatric, psychological, and psychosocial impairments. Little is known on the consequences of SARS-COV-2 on cognitive functions of patients in the sub-acute phase of the disease. We aimed to investigate the impact of COVID-19 on cognitive functions of patients admitted to the COVID-19 Rehabilitation Unit of the San Raffaele Hospital (Milan, Italy).\n\nMaterial and Methods87 patients admitted to the COVID-19 Rehabilitation Unit from March 27th to June 20th 2020 were included. Patients underwent Mini Mental State Evaluation (MMSE), Montreal Cognitive Assessment (MoCA), Hamilton Rating Scale for Depression, and Functional Independence Measure (FIM). Data were divided in 4 groups according to the respiratory assistance in the acute phase: Group1 (orotracheal intubation), Group2 (non-invasive ventilation using Biphasic Positive Airway Pressure), Group3 (Venturi Masks), Group4 (no oxygen therapy). Follow-ups were performed at one month after home-discharge.\n\nResultsOut of the 87 patients (62 Male, mean age 67.23 {+/-} 12.89 years), 80% had neuropsychological deficits (MoCA and MMSE) and 40% showed mild-to-moderate depression. Group1 had higher scores than Group3 for visuospatial/executive functions (p=0.016), naming (p=0.024), short- and long-term memory (p=0.010, p=0.005), abstraction (p=0.024), and orientation (p=0.034). Group1 was younger than Groups2 and 3. Cognitive impairments correlated with patients age. Only 18 patients presented with anosmia. Their data did not differ from the other patients. FIM (<100) did not differ between groups. Patients partly recovered at one-month follow-up and 43% showed signs of post-traumatic stress disorder.\n\nConclusionPatients with severe functional impairments had important cognitive and emotional deficits which might have been influenced by the choice of ventilatory therapy, but mostly appeared to be related to aging, independently of FIM scores. These findings should be integrated for decision-making in respiratory and neuropsychiatric assistance of COVID-19 patients in the subacute phase of the disease, and show the need for long-term support and psychological treatment of post-COVID-19 patients.", - "rel_num_authors": 11, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.12.20229955", + "rel_abs": "ObjectiveRemote or mobile consulting (mConsulting) is being promoted to strengthen health systems, deliver universal health coverage and facilitate safe clinical communication during COVID-19 and beyond. We explored whether mConsulting is a viable option for communities with minimal resources in low- and middle-income countries (LMICs).\n\nMethodsWe reviewed evidence published since 2018 about mConsulting in LMICs and undertook a scoping study (pre-COVID) in two rural settings (Pakistan, Tanzania) and five urban slums (Kenya, Nigeria, Bangladesh), using policy/document review, secondary analysis of survey data (from the urban sites), and thematic analysis of interviews/workshops with community members, healthcare workers, digital/telecommunications experts, mConsulting providers, local and national decision-makers. Project advisory groups guided the study in each country.\n\nResultsWe reviewed five empirical studies and seven reviews, analysed data from 5,219 urban slum households and engaged with 419 stakeholders in rural and urban sites. Regulatory frameworks are available in each country. mConsulting services are operating through provider platforms (n=5-17) and, at community-level, some direct experience of mConsulting with healthcare workers using their own phones was reported - for emergencies, advice and care follow-up. Stakeholder willingness was high, provided challenges are addressed in technology, infrastructure, data security, confidentiality, acceptability and health system integration. mConsulting can reduce affordability barriers and facilitate care-seeking practices.\n\nConclusionsThere are indications of readiness for mConsulting in communities with minimal resources. However, wider system strengthening is needed to bolster referrals, specialist services, laboratories and supply-chains to fully realise the continuity of care and responsiveness that mConsulting services offer, particularly during/beyond COVID-19.", + "rel_num_authors": 28, "rel_authors": [ { - "author_name": "Federica Alemanno", - "author_inst": "IRCCS Ospedale San Raffaele" + "author_name": "Bronwyn Harris", + "author_inst": "Warwick Medical School, University of Warwick, UK" }, { - "author_name": "Elise Houdayer", - "author_inst": "IRCCS San Raffaele Hospital" + "author_name": "Motunrayo Ajisola", + "author_inst": "Department of Sociology, Faculty of Social Sciences, University of Ibadan, Ibadan, Oyo State, Nigeria" }, { - "author_name": "Anna Parma", - "author_inst": "IRCCS Ospedale San Raffaele" + "author_name": "Raisa Alam", + "author_inst": "Centre for Health, Population and Development, Independent University Bangladesh, Dhaka, Bangladesh" }, { - "author_name": "Alfio Spina", - "author_inst": "IRCCS Ospedale San Raffaele" + "author_name": "Jocelyn Antsley Watkins", + "author_inst": "Warwick Medical School, University of Warwick, UK" }, { - "author_name": "Alessandra Del Forno", - "author_inst": "IRCCS Ospedale San Raffaele" + "author_name": "Theodoros N Arvanitis", + "author_inst": "Institute of Digital Healthcare, WMG, University of Warwick, UK" }, { - "author_name": "Alessandra Scatolini", - "author_inst": "IRCCS Ospedale San Raffaele" + "author_name": "Pauline Bakibinga", + "author_inst": "African Population and Health Research Center, Nairobi, Kenya" }, { - "author_name": "Sara Angelone", - "author_inst": "IRCCS Ospedale San Raffaele" + "author_name": "Beatrice Chipwaza", + "author_inst": "St Francis University College of Health and Allied Sciences, Tanzania" }, { - "author_name": "Luigia Brugliera", - "author_inst": "IRCCS Ospedale San Raffaele" + "author_name": "Nazratun Nayeem Choudhury", + "author_inst": "Centre for Health, Population and Development, Independent University Bangladesh, Dhaka, Bangladesh" }, { - "author_name": "Andrea Tettamanti", - "author_inst": "IRCCS Ospedale San Raffaele" + "author_name": "Olufunke Fayhun", + "author_inst": "Department of Sociology, Faculty of Social Sciences, University of Ibadan, Ibadan, Oyo State, Nigeria" }, { - "author_name": "Luigi Beretta", - "author_inst": "IRCCS Ospedale San Raffaele" + "author_name": "Peter Kibe", + "author_inst": "African Population and Health Research Center, Nairobi, Kenya" }, { - "author_name": "Sandro Iannaccone", - "author_inst": "IRCCS Ospedale San Raffaele" + "author_name": "Akinyinka Omigbodun", + "author_inst": "Department of Obstetrics and Gynaecology, Faculty of Clinical Sciences, College of Medicine, University of Ibadan, Ibadan, Oyo State, Nigeria" + }, + { + "author_name": "Eme Owoaje", + "author_inst": "Department of Community Medicine, Faculty of Public Health, College of Medicine, University of Ibadan, Ibadan, Oyo State, Nigeria" + }, + { + "author_name": "Senga Pemba", + "author_inst": "St Francis University College of Health and Allied Sciences, Tanzania" + }, + { + "author_name": "Rachel Potter", + "author_inst": "Clinical Trials Unit Warwick Medical School, University of Warwick, University of Warwick, UK" + }, + { + "author_name": "Narjis Rizvi", + "author_inst": "Community Health Sciences Department, Aga Khan University, Karachi, Pakistan" + }, + { + "author_name": "Jackie Sturt", + "author_inst": "King's College London, Florence Nightingale Faculty of Nursing and Midwifery, London, UK" + }, + { + "author_name": "Jonathan A.K Cave", + "author_inst": "Department of Economics, University of Warwick, UK" + }, + { + "author_name": "Romaina Iqbal", + "author_inst": "Community Health Sciences Department, Aga Khan University, Karachi, Pakistan" + }, + { + "author_name": "Caroline Kabaria", + "author_inst": "African Population and Health Research Center, Nairobi, Kenya" + }, + { + "author_name": "Albino Kalolo", + "author_inst": "St Francis University College of Health and Allied Sciences, Tanzania" + }, + { + "author_name": "Catherine Kyobutungi", + "author_inst": "African Population and Health Research Center, Nairobi, Kenya" + }, + { + "author_name": "Richard J Lilford", + "author_inst": "Institute of Applied Health Research, College of Medical and Dental Sciences, University of Birmingham, Birmingham, UK" + }, + { + "author_name": "Titus Mashanya", + "author_inst": "St Francis University College of Health and Allied Sciences, Tanzania" + }, + { + "author_name": "Sylvester Ndegese", + "author_inst": "St Francis University College of Health and Allied Sciences, Tanzania" + }, + { + "author_name": "Omar Rahman", + "author_inst": "University of Liberal Arts Bangladesh, Dhaka, Bangladesh" + }, + { + "author_name": "Saleem Sayani", + "author_inst": "Aga Khan Development Network Digital Health Resource Centre (Asia and Africa), Aga Khan University, Karachi, Pakistan" + }, + { + "author_name": "Rita Yusuf", + "author_inst": "Centre for Health, Population and Development, Independent University Bangladesh, Dhaka, Bangladesh" + }, + { + "author_name": "Frances Griffiths", + "author_inst": "Warwick Medical School, University of Warwick, UK" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "psychiatry and clinical psychology" + "category": "public and global health" }, { "rel_doi": "10.1101/2020.11.12.20230136", @@ -1071441,43 +1071765,83 @@ "category": "cell biology" }, { - "rel_doi": "10.1101/2020.11.13.381319", - "rel_title": "Plasma irradiation efficiently inactivates the coronaviruses mouse hepatitis virus and SARS-CoV-2", + "rel_doi": "10.1101/2020.11.13.381335", + "rel_title": "A Whole Virion Vaccine for COVID-19 Produced Via a Novel Inactivation Method: Results from Animal Challenge Model Studies", "rel_date": "2020-11-13", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.11.13.381319", - "rel_abs": "Many inactivation methods have been shown to inactivate SARS-CoV-2 for safe and efficient diagnostic methods. COVID-19 is caused by airborne infection of SARS-CoV-2, and therefore, methods of inactivating the virus efficiently and safely are crucial for reducing the risk of airborne infection. In this regard, the effect of plasma discharge on the infectivity of the coronaviruses mouse hepatitis virus (MHV) and SARS-CoV-2 was tested. Plasma discharge efficiently reduced the infectivity of both coronaviruses. Treatment of SARS-CoV-2 in culture medium with a plasma discharge resulted in 95.17% viral inactivation after plasma irradiation after 1 hour (hr), 99.54% inactivation after 2 hrs and 99.93% inactivation after 3 hrs. Similar results were obtained for MHV. The results indicated that plasma discharge effectively and safely inactivated the airborne coronaviruses and may be useful in minimizing the risk of airborne infection of SARS-CoV-2.", - "rel_num_authors": 6, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.11.13.381335", + "rel_abs": "The COVID-19 pandemic has generated intense interest in the rapid development and evaluation of vaccine candidates for this disease and other emerging diseases. Several novel methods for preparing vaccine candidates are currently undergoing clinical evaluation in response to the urgent need to prevent the spread of COVID-19. In many cases, these methods rely on new approaches for vaccine production and immune stimulation. We report on the use of a novel method (SolaVAX) for production of an inactivated vaccine candidate and the testing of that candidate in a hamster animal model for its ability to prevent infection upon challenge with SARS-CoV-2 virus. The studies employed in this work included an evaluation of the levels of neutralizing antibody produced post-vaccination, levels of specific antibody sub-types to RBD and spike protein that were generated, evaluation of viral shedding post-challenge, flow cytometric and single cell sequencing data on cellular fractions and histopathological evaluation of tissues post-challenge. The results from this study provide insight into the immunological responses occurring as a result of vaccination with the proposed vaccine candidate and the impact that adjuvant formulations, specifically developed to promote Th1 type immune responses, have on vaccine efficacy and protection against infection following challenge with live SARS-CoV-2. This data may have utility in the development of effective vaccine candidates broadly. Furthermore, the results suggest that preparation of a whole virion vaccine for COVID-19 using this specific photochemical method may have utility in the preparation of one such vaccine candidate.\n\nAuthor SummaryWe have developed a vaccine for COVID-19 which is prepared by a novel method for inactivation of a whole virion particle and tested it in a hamster animal model for its ability to protect against SARS-CoV-2 infection.", + "rel_num_authors": 16, "rel_authors": [ { - "author_name": "Shigeru Morikawa", - "author_inst": "Okayama University of Science" + "author_name": "Izabela K Ragan", + "author_inst": "Colorado State University" }, { - "author_name": "Shunpei Watanabe", - "author_inst": "Okayama University of Science" + "author_name": "Lindsay M Hartson", + "author_inst": "Colorado State University" }, { - "author_name": "Hikaru Fujii", - "author_inst": "Okayama University of Science: Okayama Rika Daigaku" + "author_name": "Taru S. Dutt", + "author_inst": "Colorado State University" }, { - "author_name": "Toshio Tanaka", - "author_inst": "Daikin Industries, Ltd." + "author_name": "Andres Obregon-Henao", + "author_inst": "Colorado State University" }, { - "author_name": "Junichirou Arai", - "author_inst": "Daikin Industries, Ltd." + "author_name": "Rachel M Maison", + "author_inst": "Colorado State University" }, { - "author_name": "Shigeru Kyuwa", - "author_inst": "The University of Tokyo: Tokyo Daigaku" + "author_name": "Paul Gordy", + "author_inst": "Colorado State University" + }, + { + "author_name": "Amy Fox", + "author_inst": "Colorado State University" + }, + { + "author_name": "Burton R Karger", + "author_inst": "Colorado State University" + }, + { + "author_name": "Shaun T Cross", + "author_inst": "Colorado State University" + }, + { + "author_name": "Marylee L Kapuscinski", + "author_inst": "Colorado State University" + }, + { + "author_name": "Sarah K Cooper", + "author_inst": "Colorado State University" + }, + { + "author_name": "Brendan K Podell", + "author_inst": "Colorado State University" + }, + { + "author_name": "Mark D Stenglein", + "author_inst": "Colorado State University" + }, + { + "author_name": "Richard A Bowen", + "author_inst": "Colorado State University" + }, + { + "author_name": "Marcela Henao-Tamayo", + "author_inst": "Colorado State University" + }, + { + "author_name": "Raymond Goodrich", + "author_inst": "Colorado State University" } ], "version": "1", "license": "cc_by", "type": "new results", - "category": "microbiology" + "category": "immunology" }, { "rel_doi": "10.1101/2020.11.10.20228759", @@ -1073211,25 +1073575,213 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.11.11.20224030", - "rel_title": "Gender- and age-related differences in misuse of face masks in COVID-19 prevention in central European cities", + "rel_doi": "10.1101/2020.11.11.20220962", + "rel_title": "Short-term forecasts to inform the response to the COVID-19 epidemic in the UK", "rel_date": "2020-11-13", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.11.20224030", - "rel_abs": "1ObjectiveCorrect use of face masks is required for their efficacy in preventing possible droplet infections with SARS-CoV-2. We tried to provide information about differences in the distribution of gender and age groups wearing face masks incorrectly.\n\nDesignPilot field study\n\nMethodsVisual observation of mask use in public, not age- and gender-related places in central European large cities regarding incorrect mask-wearing (n=523); statistical analysis (nominal scale) in terms of gender and estimated age group using the total numbers, binomial test and chi-square test.\n\nResultsThere is no significant difference (binomial test: p-value = 0.43) in mask misuse between the genders (female: 271 (51.8%), male: 252 (48.2%) and 0 non-binary individuals (0%)). There is a significant difference (chi-square test: p-value < 2.2e-16) in age group distribution (170 young 10-29 years (32.5%), 261 middle-aged 30-59 years (49.9%), 92 older adults [≥] 60 years (17.6%)). In total numbers, the highest counts were observed in middle-aged persons with 261 counts (49.9%).\n\nConclusionOur study shows an uneven age-distribution of people wearing the face mask in public improperly.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.11.20220962", + "rel_abs": "BackgroundShort-term forecasts of infectious disease can aid situational awareness and planning for outbreak response. Here, we report on multi-model forecasts of Covid-19 in the UK that were generated at regular intervals starting at the end of March 2020, in order to monitor expected healthcare utilisation and population impacts in real time.\n\nMethodsWe evaluated the performance of individual model forecasts generated between 24 March and 14 July 2020, using a variety of metrics including the weighted interval score as well as metrics that assess the calibration, sharpness, bias and absolute error of forecasts separately. We further combined the predictions from individual models into ensemble forecasts using a simple mean as well as a quantile regression average that aimed to maximise performance. We compared model performance to a null model of no change.\n\nResultsIn most cases, individual models performed better than the null model, and ensembles models were well calibrated and performed comparatively to the best individual models. The quantile regression average did not noticeably outperform the mean ensemble.\n\nConclusionsEnsembles of multi-model forecasts can inform the policy response to the Covid-19 pandemic by assessing future resource needs and expected population impact of morbidity and mortality.", + "rel_num_authors": 49, "rel_authors": [ { - "author_name": "Linda Eckl", - "author_inst": "Department of Medicine, University of Regensburg, 93040 Regensburg, Germany" + "author_name": "Sebastian Funk", + "author_inst": "London School of Hygiene & Tropical Medicine" + }, + { + "author_name": "Sam Abbott", + "author_inst": "London School of Hygiene & Tropical Medicine" }, { - "author_name": "Stefan Hansch", - "author_inst": "Department of Medicine, University of Regensburg, 93040 Regensburg, Germany" + "author_name": "Benjamin D Atkins", + "author_inst": "University of Warwick" + }, + { + "author_name": "Marc Baguelin", + "author_inst": "Imperial College" + }, + { + "author_name": "J Kenneth Baillie", + "author_inst": "Roslin Institute, University of Edinburgh" + }, + { + "author_name": "Paul J Birrell", + "author_inst": "Public Health England" + }, + { + "author_name": "Joshua Blake", + "author_inst": "University of Cambridge" + }, + { + "author_name": "Nikos I Bosse", + "author_inst": "London School of Hygiene & Tropical Medicine" + }, + { + "author_name": "Joshua Burton", + "author_inst": "University of Manchester" + }, + { + "author_name": "Jonathan Carruthers", + "author_inst": "Public Health England" + }, + { + "author_name": "Nicholas G Davies", + "author_inst": "London School of Hygiene and Tropical Medicine" + }, + { + "author_name": "Daniela de Angelis", + "author_inst": "University of Cambridge" + }, + { + "author_name": "Louise Dyson", + "author_inst": "University of Warwick" + }, + { + "author_name": "W. John Edmunds", + "author_inst": "London School of Hygiene & Tropical Medicine" + }, + { + "author_name": "Rosalind M Eggo", + "author_inst": "London School of Hygiene & Tropical Medicine" + }, + { + "author_name": "Neil M Ferguson", + "author_inst": "Imperial College" + }, + { + "author_name": "Katy A M Gaythorpe", + "author_inst": "Imperial College London" + }, + { + "author_name": "Erin Gorsich", + "author_inst": "University of Warwick" + }, + { + "author_name": "Glen Guyver-Fletcher", + "author_inst": "University of Warwick" + }, + { + "author_name": "Joel Hellewell", + "author_inst": "London School of Hygiene & Tropical Medicine" + }, + { + "author_name": "Edward M Hill", + "author_inst": "University of Warwick" + }, + { + "author_name": "Alexander Holmes", + "author_inst": "University of Warwick" + }, + { + "author_name": "Thomas A House", + "author_inst": "University of Manchester" + }, + { + "author_name": "Chris Jewell", + "author_inst": "Lancaster University" + }, + { + "author_name": "Mark Jit", + "author_inst": "London School of Hygiene & Tropical Medicine" + }, + { + "author_name": "Thibaut Jombart", + "author_inst": "London School of Hygiene & Tropical Medicine" + }, + { + "author_name": "Indra Joshi", + "author_inst": "NHSX" + }, + { + "author_name": "Matt J Keeling", + "author_inst": "University of Warwick" + }, + { + "author_name": "Edward Kendall", + "author_inst": "NHS England & NHS Improvement" + }, + { + "author_name": "Edward S Knock", + "author_inst": "Imperial College" + }, + { + "author_name": "Adam J Kucharski", + "author_inst": "London School of Hygiene & Tropical Medicine" + }, + { + "author_name": "Katrina A Lythgoe", + "author_inst": "University of Oxford" + }, + { + "author_name": "Sophie R Meakin", + "author_inst": "London School of Hygiene & Tropical Medicine" + }, + { + "author_name": "James D Munday", + "author_inst": "London School of Hygiene and Tropical Medicine" + }, + { + "author_name": "Peter JM Openshaw", + "author_inst": "Imperial College London" + }, + { + "author_name": "Christopher Overton", + "author_inst": "Manchester University" + }, + { + "author_name": "Filippo Pagani", + "author_inst": "Manchester University" + }, + { + "author_name": "Jonathan Pearson", + "author_inst": "NHSX" + }, + { + "author_name": "Pablo N Perez-Guzman", + "author_inst": "Imperial College" + }, + { + "author_name": "Lorenzo Pellis", + "author_inst": "The University of Manchester" + }, + { + "author_name": "Francesca Scarabel", + "author_inst": "York University" + }, + { + "author_name": "Malcolm Gracie Semple", + "author_inst": "University of Liverpool" + }, + { + "author_name": "Ming Tang", + "author_inst": "NHS England & NHSE Improvement" + }, + { + "author_name": "Michael Tildesley", + "author_inst": "University of Warwick" + }, + { + "author_name": "Edwin van Leeuwen", + "author_inst": "Public Health England" + }, + { + "author_name": "Lilith Whittles", + "author_inst": "Imperial College" + }, + { + "author_name": "- CMMID COVID-19 Working Group", + "author_inst": "" + }, + { + "author_name": "- Imperial College COVID-19 Response Team", + "author_inst": "" + }, + { + "author_name": "- ISARIC4C Investigators", + "author_inst": "" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1074809,125 +1075361,261 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.11.09.20228023", - "rel_title": "Diagnosis and Tracking of Past SARS-CoV-2 Infection in a Large Study of Vo', Italy Through T-Cell Receptor Sequencing", + "rel_doi": "10.1101/2020.11.09.20228015", + "rel_title": "A time-resolved proteomic and diagnostic map characterizes COVID-19 disease progression and predicts outcome", "rel_date": "2020-11-12", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.09.20228023", - "rel_abs": "In viral diseases T cells exert a prominent role in orchestrating the adaptive immune response and yet a comprehensive assessment of the T-cell repertoire, compared and contrasted with antibody response, after severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is currently lacking. A prior population-scale study of the municipality of Vo', Italy, conducted after the initial SARS-CoV-2 outbreak uncovered a high frequency of asymptomatic infected individuals and their role in transmission in this town. Two months later, we sampled the same population's T-cell receptor repertoire structure in terms of both diversity (breadth) and frequency (depth) to SARS-CoV-2 antigens to identify associations with both humoral response and protection. For this purpose, we analyzed T-cell receptor and antibody signatures from over 2,200 individuals, including 76 PCR-confirmed SARS-CoV-2 cases (25 asymptomatic, 42 symptomatic, 9 hospitalized). We found that 97.4% (74/76) of PCR confirmed cases had elevated levels of T-cell receptors specific for SARS-CoV-2 antigens. The depth and breadth of the T-cell receptor repertoire were both positively associated with neutralizing antibody titers; helper CD4+ T cells directed towards viral antigens from spike protein were a primary factor in this correlation. Higher clonal depth of the T-cell response to the virus was also significantly associated with more severe disease course. A total of 40 additional suspected infections were identified based on T-cell response from the subjects without confirmatory PCR tests, mostly among those reporting symptoms or having household exposure to a PCR-confirmed infection. Taken together, these results establish that T cells are a sensitive, reliable and persistent measure of past SARS-CoV-2 infection that are differentially activated depending on disease morbidity.", - "rel_num_authors": 28, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.09.20228015", + "rel_abs": "COVID-19 is highly variable in its clinical presentation, ranging from asymptomatic infection to severe organ damage and death. There is an urgent need for predictive markers that can guide clinical decision-making, inform about the effect of experimental therapies, and point to novel therapeutic targets. Here, we characterize the time-dependent progression of COVID-19 through different stages of the disease, by measuring 86 accredited diagnostic parameters and plasma proteomes at 687 sampling points, in a cohort of 139 patients during hospitalization. We report that the time-resolved patient molecular phenotypes reflect an initial spike in the systemic inflammatory response, which is gradually alleviated and followed by a protein signature indicative of tissue repair, metabolic reconstitution and immunomodulation. Further, we show that the early host response is predictive for the disease trajectory and gives rise to proteomic and diagnostic marker signatures that classify the need for supplemental oxygen therapy and mechanical ventilation, and that predict the time to recovery of mildly ill patients. In severely ill patients, the molecular phenotype of the early host response predicts survival, in two independent cohorts and weeks before outcome. We also identify age-specific molecular response to COVID-19, which involves increased inflammation and lipoprotein dysregulation in older patients. Our study provides a deep and time resolved molecular characterization of COVID-19 disease progression, and reports biomarkers for risk-adapted treatment strategies and molecular disease monitoring. Our study demonstrates accurate prognosis of COVID-19 outcome from proteomic signatures recorded weeks earlier.", + "rel_num_authors": 62, "rel_authors": [ { - "author_name": "Rachel M Gittelman", - "author_inst": "Adaptive Biotechnologies" + "author_name": "Vadim Demichev", + "author_inst": "The Francis Crick Institute" }, { - "author_name": "Enrico Lavezzo", - "author_inst": "University of Padua" + "author_name": "Pinkus Tober-Lau", + "author_inst": "Charit\u00e9 - Universit\u00e4tsmedizin Berlin" }, { - "author_name": "Thomas M Snyder", - "author_inst": "Adaptive Biotechnologies" + "author_name": "Tatiana Nazarenko", + "author_inst": "University College London" }, { - "author_name": "H Jabran Zahid", - "author_inst": "Microsoft Research" + "author_name": "Charlotte Thibeault", + "author_inst": "Charite Universitaetsmedizin Berlin" }, { - "author_name": "Rebecca Elyanow", - "author_inst": "Adaptive Biotechnologies" + "author_name": "Harry Whitwell", + "author_inst": "Imperial College London" }, { - "author_name": "Sudeb Dalai", - "author_inst": "Adaptive Biotechnologies" + "author_name": "Oliver Lemke", + "author_inst": "Charit\u00e9 - Universit\u00e4tsmedizin Berlin" }, { - "author_name": "Ilan Kirsch", - "author_inst": "Adaptive Biotechnologies" + "author_name": "Annika R\u00f6hl", + "author_inst": "Charit\u00e9 - Universit\u00e4tsmedizin Berlin" }, { - "author_name": "Lance Baldo", - "author_inst": "Adaptive Biotechnologies" + "author_name": "Anja Freiwald", + "author_inst": "Charit\u00e9 - Universit\u00e4tsmedizin Berlin" }, { - "author_name": "Laura Manuto", - "author_inst": "University of Padua" + "author_name": "Lukasz Szyrwiel", + "author_inst": "The Francis Crick Institute" }, { - "author_name": "Elisa Franchin", - "author_inst": "University of Padua" + "author_name": "Daniela Ludwig", + "author_inst": "Charit\u00e9 - Universit\u00e4tsmedizin Berlin" }, { - "author_name": "Claudia Del Vecchio", - "author_inst": "University of Padua" + "author_name": "Clara Correia-Melo", + "author_inst": "The Francis Crick Institute" }, { - "author_name": "Monia Pacenti", - "author_inst": "Azienda Ospedale Padova" + "author_name": "Elisa Theresa Helbig", + "author_inst": "Charit\u00e9 - Universit\u00e4tsmedizin Berlin" }, { - "author_name": "Caterina Boldrin", - "author_inst": "Azienda Ospedale Padova" + "author_name": "Paula Stubbemann", + "author_inst": "Charit\u00e9 - Universit\u00e4tsmedizin Berlin" }, { - "author_name": "Margherita Cattai", - "author_inst": "Azienda Ospedale Padova" + "author_name": "Nana-Maria Gr\u00fcning", + "author_inst": "Charit\u00e9 - Universit\u00e4tsmedizin Berlin" }, { - "author_name": "Francesca Saluzzo", - "author_inst": "University of Padua" + "author_name": "Oleg Blyuss", + "author_inst": "Lobachevsky University" }, { - "author_name": "Andrea Padoan", - "author_inst": "University of Padua" + "author_name": "Spyros Vernardis", + "author_inst": "The Francis Crick Institute" }, { - "author_name": "Mario Plebani", - "author_inst": "University of Padua" + "author_name": "Matthew White", + "author_inst": "The Francis Crick Institute" }, { - "author_name": "Fabio Simeoni", - "author_inst": "IRCCS Ospedale San Raffaele" + "author_name": "Christoph B. Messner", + "author_inst": "Charit\u00e9 - Universit\u00e4tsmedizin Berlin" }, { - "author_name": "Jessica Bordini", - "author_inst": "IRCCS Ospedale San Raffaele" + "author_name": "Michael Joannidis", + "author_inst": "Medical University of Innsbruck" }, { - "author_name": "Nicola I Lor\u00e8", - "author_inst": "IRCCS Ospedale San Raffaele" + "author_name": "Thomas Sonnweber", + "author_inst": "Medical University of Innsbruck" }, { - "author_name": "Dejan Lazarevic", - "author_inst": "IRCCS Ospedale San Raffaele" + "author_name": "Sebastian J. Klein", + "author_inst": "Medical University of Innsbruck" }, { - "author_name": "Daniela M Cirillo", - "author_inst": "IRCCS Ospedale San Raffaele" + "author_name": "Alex Pizzini", + "author_inst": "Medical University of Innsbruck" }, { - "author_name": "Paolo Ghia", - "author_inst": "IRCCS Ospedale San Raffaele" + "author_name": "Yvonne Wohlfarter", + "author_inst": "Medical University of Innsbruck" }, { - "author_name": "Stefano Toppo", - "author_inst": "University of Padua" + "author_name": "Sabina Sahanic", + "author_inst": "Medical University of Innsbruck" }, { - "author_name": "Jonathan M Carlson", - "author_inst": "Microsoft Research" + "author_name": "Richard Hilbe", + "author_inst": "Medical University of Innsbruck" }, { - "author_name": "Harlan S Robins", - "author_inst": "Adaptive Biotechnologies" + "author_name": "Benedikt Schaefer", + "author_inst": "Medical University of Innsbruck" }, { - "author_name": "Giovanni Tonon", - "author_inst": "IRCCS Ospedale San Raffaele" + "author_name": "Sonja Wagner", + "author_inst": "Medical University of Innsbruck" }, { - "author_name": "Andrea Crisanti", - "author_inst": "University of Padua" + "author_name": "Mirja Mittermaier", + "author_inst": "Charit\u00e9 - Universit\u00e4tsmedizin Berlin" + }, + { + "author_name": "Felix Machleidt", + "author_inst": "Charit\u00e9 - Universit\u00e4tsmedizin Berlin" + }, + { + "author_name": "Carmen Garcia", + "author_inst": "Charit\u00e9 - Universit\u00e4tsmedizin Berlin" + }, + { + "author_name": "Christoph Ruwwe-Gl\u00f6senkamp", + "author_inst": "Charit\u00e9 - Universit\u00e4tsmedizin Berlin" + }, + { + "author_name": "Tilman Lingscheid", + "author_inst": "Charit\u00e9 - Universit\u00e4tsmedizin Berlin" + }, + { + "author_name": "Laure Bosquillon de Jarcy", + "author_inst": "Charit\u00e9 - Universit\u00e4tsmedizin Berlin" + }, + { + "author_name": "Miriam S. Stegemann", + "author_inst": "Charit\u00e9 - Universit\u00e4tsmedizin Berlin" + }, + { + "author_name": "Moritz Pfeiffer", + "author_inst": "Charit\u00e9 - Universit\u00e4tsmedizin Berlin" + }, + { + "author_name": "Linda J\u00fcrgens", + "author_inst": "Charit\u00e9 - Universit\u00e4tsmedizin Berlin" + }, + { + "author_name": "Sophy Denker", + "author_inst": "Charit\u00e9 - Universit\u00e4tsmedizin Berlin" + }, + { + "author_name": "Daniel Zickler", + "author_inst": "Charit\u00e9 - Universit\u00e4tsmedizin Berlin" + }, + { + "author_name": "Philipp Enghard", + "author_inst": "Charit\u00e9 - Universit\u00e4tsmedizin Berlin" + }, + { + "author_name": "Aleksej Zelezniak", + "author_inst": "The Francis Crick Institute" + }, + { + "author_name": "Archie Campbell", + "author_inst": "The University of Edinburgh" + }, + { + "author_name": "Caroline Hayward", + "author_inst": "The University of Edinburgh" + }, + { + "author_name": "David J. Porteous", + "author_inst": "The University of Edinburgh" + }, + { + "author_name": "Riccardo Marioni", + "author_inst": "University of Edinburgh" + }, + { + "author_name": "Alexander Uhrig", + "author_inst": "Charit\u00e9 - Universit\u00e4tsmedizin Berlin" + }, + { + "author_name": "Holger M\u00fcller-Redetzky", + "author_inst": "Charit\u00e9 - Universit\u00e4tsmedizin Berlin" + }, + { + "author_name": "Heinz Zoller", + "author_inst": "Medical University of Innsbruck" + }, + { + "author_name": "Judith L\u00f6ffler-Ragg", + "author_inst": "Medical University of Innsbruck" + }, + { + "author_name": "Markus A. Keller", + "author_inst": "Medical University of Innsbruck" + }, + { + "author_name": "Ivan Tancevski", + "author_inst": "Medical University of Innsbruck" + }, + { + "author_name": "John F. Timms", + "author_inst": "University College London" + }, + { + "author_name": "Alexey Zaikin", + "author_inst": "University College London" + }, + { + "author_name": "Stefan Hippenstiel", + "author_inst": "Charit\u00e9 - Universit\u00e4tsmedizin Berlin" + }, + { + "author_name": "Michael Ramharter", + "author_inst": "Bernhard Nocht Institute for Tropical Medicine" + }, + { + "author_name": "Martin Witzenrath", + "author_inst": "Charit\u00e9 - Universit\u00e4tsmedizin Berlin" + }, + { + "author_name": "Norbert Suttorp", + "author_inst": "Charit\u00e9 - Universit\u00e4tsmedizin Berlin" + }, + { + "author_name": "Kathryn Lilley", + "author_inst": "The University of Cambridge" + }, + { + "author_name": "Michael M\u00fclleder", + "author_inst": "Charit\u00e9 - Universit\u00e4tsmedizin Berlin" + }, + { + "author_name": "Leif Erik Sander", + "author_inst": "Charit\u00e9 - Universit\u00e4tsmedizin Berlin" + }, + { + "author_name": "- PA-COVID-19 Study group", + "author_inst": "" + }, + { + "author_name": "Markus Ralser", + "author_inst": "Charite University Medicine" + }, + { + "author_name": "Florian Kurth", + "author_inst": "Charit\u00e9 - Universit\u00e4tsmedizin Berlin" } ], "version": "1", @@ -1077027,41 +1077715,137 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2020.11.10.377366", - "rel_title": "Unification of the M/ORF3-related proteins points to a diversified role for ion conductance in pathogenesis of coronaviruses and other nidoviruses", + "rel_doi": "10.1101/2020.11.10.377333", + "rel_title": "Characterization and structural basis of a lethal mouse-adapted SARS-CoV-2", "rel_date": "2020-11-11", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.11.10.377366", - "rel_abs": "The new coronavirus, SARS-CoV-2, responsible for the COVID-19 pandemic has emphasized the need for a better understanding of the evolution of virus-host conflicts. ORF3a in both SARS-CoV-1 and SARS-CoV-2 are ion channels (viroporins) and involved in virion assembly and membrane budding. Using sensitive profile-based homology detection methods, we unify the SARS-CoV ORF3a family with several families of viral proteins, including ORF5 from MERS-CoVs, proteins from beta-CoVs (ORF3c), alpha-CoVs (ORF3b), most importantly, the Matrix (M) proteins from CoVs, and more distant homologs from other nidoviruses. By sequence analysis and structural modeling, we show that these viral families utilize specific conserved polar residues to constitute an ion-conducting pore in the membrane. We reconstruct the evolutionary history of these families, objectively establish the common origin of the M proteins of CoVs and Toroviruses. We show that the divergent ORF3a/ORF3b/ORF5 families represent a duplication stemming from the M protein in alpha- and beta-CoVs. By phyletic profiling of major structural components of primary nidoviruses, we present a model for their role in virion assembly of CoVs, ToroVs and Arteriviruses. The unification of diverse M/ORF3 ion channel families in a wide range of nidoviruses, especially the typical M protein in CoVs, reveal a conserved, previously under-appreciated role of ion channels in virion assembly, membrane fusion and budding. We show that the M and ORF3 are under differential evolutionary pressures; in contrast to the slow evolution of M as core structural component, the CoV-ORF3 clade is under selection for diversification, which indicates it is likely at the interface with host molecules and/or immune attack.\n\nIMPORTANCECoronaviruses (CoVs) have become a major threat to human welfare as the causative agents of several severe infectious diseases, namely Severe Acute Respiratory Syndrome (SARS), Middle Eastern Respiratory Syndrome (MERS), and the recently emerging human coronavirus disease 2019 (COVID-19). The rapid spread, severity of these diseases, as well as the potential re-emergence of other CoV-associated diseases have imposed a strong need for a thorough understanding of function and evolution of these CoVs. By utilizing robust domain-centric computational strategies, we have established homologous relationships between many divergent families of CoV proteins, including SARS-CoV/SARS-CoV-2 ORF3a, MERS-CoV ORF5, proteins from both beta-CoVs (ORF3c) and alpha-CoVs (ORF3b), the typical CoV Matrix proteins, and many distant homologs from other nidoviruses. We present evidence that they are active ion channel proteins, and the Cov-specific ORF3 clade proteins are under selection for rapid diversification, suggesting they might have been involved in interfering host molecules and/or immune attack.", - "rel_num_authors": 6, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.11.10.377333", + "rel_abs": "The ongoing SARS-CoV-2 pandemic has brought an urgent need for animal models to study the pathogenicity of the virus. Herein, we generated and characterized a novel mouse-adapted SARS-CoV-2 strain, named MASCp36, that causes severe acute respiratory symptoms and mortality in standard laboratory mice. Particularly, this model exhibits age and gender related skewed distribution of mortality akin to severe COVID-19, and the 50% lethal dose (LD50) of MASCp36 was 58 PFU in 9-month-old, male BALB/c mice. Deep sequencing identified three amino acid substitutions, N501Y, Q493H, and K417N, subsequently emerged at the receptor binding domain (RBD) of MASCp36, during in vivo passaging. All three mutations in RBD significantly enhanced the binding affinity to its endogenous receptor, mouse ACE2 (mACE2). Cryo-electron microscopy (cryo-EM) analysis of human ACE2 (hACE2) or mACE2 in complex with the RBD of MASCp36 at 3.1 to 3.7 angstrom resolution elucidates molecular basis for the receptor-binding switch driven by specific amino acid substitutions. Interestingly, N501Y and Q493H enhanced the binding affinity to human ACE2 (hACE2); while triple mutations N501Y/Q493H/K417N decreased affinity to hACE2, thus led to the reduced infectivity of MASCp36 to human cells. Our study not only provides a robust platform for studying the pathogenesis of severe COVID-19 and rapid evaluation of coutermeasures against SARS-CoV-2, but also unveils the molecular mechanism for the rapid adaption and evolution of SARS-CoV-2 in human and animals.\n\nOne sentence summaryA mouse adapted SARS-CoV-2 strain that harbored specific amino acid substitutions in the RBD of S protein showed 100% mortality in aged, male BALB/c mice.", + "rel_num_authors": 30, "rel_authors": [ { - "author_name": "Yongjun Tan", - "author_inst": "Saint Louis University" + "author_name": "Shihui Sun", + "author_inst": "State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology" }, { - "author_name": "Theresa Schneider", - "author_inst": "Saint Louis University" + "author_name": "Hongjing Gu", + "author_inst": "State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology" }, { - "author_name": "Prakash Shukla", - "author_inst": "University of Utah School of Medicine" + "author_name": "Lei Cao", + "author_inst": "Institute of Biophysics, Chinese Academy of Sciences" }, { - "author_name": "Mahesh Chandrasekharan", - "author_inst": "University of Utah School of Medicine" + "author_name": "Qi Chen", + "author_inst": "State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology" }, { - "author_name": "L. Aravind", - "author_inst": "National Center of Biotechnology Information" + "author_name": "Qing Ye", + "author_inst": "State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology" }, { - "author_name": "Dapeng Zhang", - "author_inst": "Saint Louis University" + "author_name": "Guan Yang", + "author_inst": "State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing" + }, + { + "author_name": "Rui-Ting Li", + "author_inst": "State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology" + }, + { + "author_name": "Hang Fan", + "author_inst": "State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology" + }, + { + "author_name": "Yong-Qiang Deng", + "author_inst": "State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology" + }, + { + "author_name": "Xiaopeng Song", + "author_inst": "State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics" + }, + { + "author_name": "Yini Qi", + "author_inst": "State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics" + }, + { + "author_name": "Min Li", + "author_inst": "State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology" + }, + { + "author_name": "Jun Lan", + "author_inst": "The Ministry of Education Key Laboratory of Protein Science, Beijing Advanced Innovation Center for Structural Biology, Beijing Frontier Research Center for Bio" + }, + { + "author_name": "Rui Feng", + "author_inst": "CAS Key Laboratory of Infection and Immunity, National Laboratory of Macromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China" + }, + { + "author_name": "Guo Yan", + "author_inst": "State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology" + }, + { + "author_name": "Na Zhu", + "author_inst": "National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention (China CDC)" + }, + { + "author_name": "Si Qin", + "author_inst": "State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology" + }, + { + "author_name": "Lei Wang", + "author_inst": "CAS Key Laboratory of Infection and Immunity, National Laboratory of Macromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China" + }, + { + "author_name": "Yifei Zhang", + "author_inst": "State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology" + }, + { + "author_name": "Chao Zhou", + "author_inst": "State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology" + }, + { + "author_name": "Lingna Zhao", + "author_inst": "State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology" + }, + { + "author_name": "Yuehong Chen", + "author_inst": "State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology" + }, + { + "author_name": "Meng Shen", + "author_inst": "State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology" + }, + { + "author_name": "Yujun Cui", + "author_inst": "State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology" + }, + { + "author_name": "Xiao Yang", + "author_inst": "State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics" + }, + { + "author_name": "Xinquan Wang", + "author_inst": "Tsinghua University" + }, + { + "author_name": "Wenjie Tan", + "author_inst": "National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention (China CDC)" + }, + { + "author_name": "Hui Wang", + "author_inst": "State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology" + }, + { + "author_name": "Xiangxi Wang", + "author_inst": "CAS Key Laboratory of Infection and Immunity, National Laboratory of Macromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China" + }, + { + "author_name": "Chengfeng Qin", + "author_inst": "Beijing Institute of Microbiology and Epidemiology" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "new results", "category": "microbiology" }, @@ -1078565,23 +1079349,123 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.11.07.370726", - "rel_title": "In Vitro Efficacy of \"Essential Iodine Drops\" Against Severe Acute Respiratory Syndrome-Coronavirus 2 (SARS-CoV-2)", + "rel_doi": "10.1101/2020.11.10.374587", + "rel_title": "Susceptibility of well-differentiated airway epithelial cell cultures from domestic and wildlife animals to SARS-CoV-2", "rel_date": "2020-11-10", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.11.07.370726", - "rel_abs": "BackgroundAerosolization of respiratory droplets is considered the main route of coronavirus disease 2019 (COVID-19). Therefore, reducing the viral load of Severe Acute Respiratory Syndrome-Coronavirus 2 (SARS-CoV-2) shed via respiratory droplets is potentially an ideal strategy to prevent the spread of the pandemic. The in vitro virucidal activity of intranasal Povidone-Iodine (PVP-I) has been demonstrated recently to reduce SARS-CoV-2 viral titres. This study evaluated the virucidal activity of the aqueous solution of Iodine-V (a clathrate complex formed by elemental iodine and fulvic acid) as in Essential Iodine Drops (EID) with 200 g elemental iodine/ml content against SARS-CoV-2 to ascertain whether it is a better alternative to PVP-I.\n\nMethodsSARS-CoV-2 (USAWA1/2020 strain) virus stock was prepared by infecting Vero 76 cells (ATCC CRL-1587) until cytopathic effect (CPE). The virucidal activity of EID against SARS-CoV-2 was tested in three dilutions (1:1; 2:1 and 3:1) in triplicates by incubating at room temperature (22 {+/-} 2{degrees}C) for either 60 or 90 seconds. The surviving viruses from each sample were quantified by a standard end-point dilution assay.\n\nResultsEID (200 g iodine/ml) after exposure for 60 and 90 seconds was compared to controls. In both cases, the viral titre was reduced by 99% (LRV 2.0). The 1:1 dilution of EID with virus reduced SARS-CoV-2 virus from 31,623 cell culture infectious dose 50% (CCCID50) to 316 CCID50 within 90 seconds.\n\nConclusionSubstantial reductions in LRV by Iodine-V in EID confirmed the activity of EID against SARS-CoV-2 in vitro, demonstrating that Iodine-V in EID is effective at inactivating the virus in vitro and therefore suggesting its potential application intranasally to reduce SARS-CoV-2 transmission from known or suspected COVID-19 patients.", - "rel_num_authors": 1, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.11.10.374587", + "rel_abs": "Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has spread globally, and the number of cases continues to rise all over the world. Besides humans, the zoonotic origin, as well as intermediate and potential spillback host reservoirs of SARS-CoV-2 are unknown. To circumvent ethical and experimental constraints, and more importantly, to reduce and refine animal experimentation, we employed our airway epithelial cell (AEC) culture repository composed of various domesticated and wildlife animal species to assess their susceptibility to SARS-CoV-2. In this study, we inoculated well-differentiated animal AEC cultures of monkey, cat, ferret, dog, rabbit, pig, cattle, goat, llama, camel, and two neotropical bat species with SARS-CoV-2. We observed that SARS-CoV-2 only replicated efficiently in monkey and cat AEC culture models. Whole-genome sequencing of progeny virus revealed no obvious signs of nucleotide transitions required for SARS-CoV-2 to productively infect monkey and cat epithelial airway cells. Our findings, together with the previously reported human-to-animal spillover events warrants close surveillance to understand the potential role of cats, monkeys, and closely related species as spillback reservoirs for SARS-CoV-2.", + "rel_num_authors": 26, "rel_authors": [ { - "author_name": "Zoltan Kontos", - "author_inst": "IOI Investment Zrt." + "author_name": "Mitra Gultom", + "author_inst": "Institute of Virology and Immunology (IVI), Bern, Switzerland" + }, + { + "author_name": "Matthias Licheri", + "author_inst": "Institute for Infectious Diseases, University of Bern, Bern, Switzerland" + }, + { + "author_name": "Laura Laloli", + "author_inst": "Institute for Infectious Diseases, University of Bern, Bern, Switzerland" + }, + { + "author_name": "Manon Wider", + "author_inst": "Institute for Infectious Diseases, University of Bern, Bern, Switzerland" + }, + { + "author_name": "Marina Straessle", + "author_inst": "Institute of Virology and Immunology (IVI), Bern, Switzerland" + }, + { + "author_name": "Silvio Steiner", + "author_inst": "Institute of Virology and Immunology (IVI), Bern, Switzerland" + }, + { + "author_name": "Annika Kratzel", + "author_inst": "Institute of Virology and Immunology (IVI), Bern, Switzerland" + }, + { + "author_name": "Tran Thi Nhu Thao", + "author_inst": "Institute of Virology and Immunology (IVI), Bern, Switzerland" + }, + { + "author_name": "Hanspeter Stalder", + "author_inst": "Institute of Virology and Immunology (IVI), Bern, Switzerland" + }, + { + "author_name": "Jasmine Portmann", + "author_inst": "Institute of Virology and Immunology (IVI), Bern, Switzerland" + }, + { + "author_name": "Melle Holwerda", + "author_inst": "Institute of Virology and Immunology (IVI), Bern, Switzerland" + }, + { + "author_name": "Nadine Ebert", + "author_inst": "Institute of Virology and Immunology (IVI), Bern, Switzerland" + }, + { + "author_name": "Nadine Stokar - Regenscheit", + "author_inst": "Institute of Animal Pathology, University of Bern, Bern, Switzerland" + }, + { + "author_name": "Corinne Gurtner", + "author_inst": "Institute of Animal Pathology, University of Bern, Bern, Switzerland" + }, + { + "author_name": "Patrik Zanolari", + "author_inst": "Clinic for Ruminants, Vetsuisse Faculty, University of Bern, Bern, Switzerland" + }, + { + "author_name": "Horst Posthaus", + "author_inst": "Institute of Animal Pathology, University of Bern, Bern, Switzerland" + }, + { + "author_name": "Simone Schuller", + "author_inst": "Small animal clinic, University of Bern, Bern, Switzerland" + }, + { + "author_name": "Andres Moreira - Soto", + "author_inst": "Virology-Research Center for tropical diseases (CIET), University of Costa Rica, Costa Rica" + }, + { + "author_name": "Amanda Vicente - Santos", + "author_inst": "Virology-Research Center for tropical diseases (CIET), University of Costa Rica, Costa Rica" + }, + { + "author_name": "Eugenia Corrales - Aguilar", + "author_inst": "Virology-Research Center for tropical diseases (CIET), University of Costa Rica, Costa Rica" + }, + { + "author_name": "Nicolas Ruggli", + "author_inst": "Institute of Virology and Immunology (IVI), Mittelhaeusern, Bern, Switzerland" + }, + { + "author_name": "Gergely Tekes", + "author_inst": "Institute of Virology, Justus Liebig University Giessen, 35390 Giessen, Germany" + }, + { + "author_name": "Veronika von Messling", + "author_inst": "Division of Veterinary Medicine, Paul-Ehrlich-Institut, Federal Institute for Vaccines and Biomedicines, Langen, Germany" + }, + { + "author_name": "Bevan Sawatsky", + "author_inst": "Division of Veterinary Medicine, Paul-Ehrlich-Institut, Federal Institute for Vaccines and Biomedicines, Langen, Germany" + }, + { + "author_name": "Volker Thiel", + "author_inst": "Institute of Virology and Immunology (IVI), Bern, Switzerland" + }, + { + "author_name": "Ronald Dijkman", + "author_inst": "Institute for Infectious Diseases, University of Bern, Bern, Switzerland" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "new results", - "category": "pharmacology and toxicology" + "category": "microbiology" }, { "rel_doi": "10.1101/2020.11.10.375022", @@ -1080023,97 +1080907,16 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2020.11.09.374769", - "rel_title": "Neutrophil extracellular traps induce the epithelial-mesenchymal transition: implications in post-COVID-19 fibrosis", + "rel_doi": "10.1101/2020.11.09.373449", + "rel_title": "Cloning, Expression and Biophysical Characterization of a Yeast-expressed Recombinant SARS-CoV-2 Receptor Binding Domain COVID-19 Vaccine Candidate", "rel_date": "2020-11-09", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.11.09.374769", - "rel_abs": "The release of neutrophil extracellular traps (NETs), a process termed NETosis, avoids pathogen spread but may cause tissue injury. NETs have been found in severe COVID-19 patients, but their role in disease development is still unknown. The aim of this study is to assess the capacity of NETs to drive epithelial-mesenchymal transition (EMT) of lung epithelial cells and to analyze the involvement of NETs in COVID-19.\n\nNeutrophils activated with PMA (PMA-Neu), a stimulus known to induce NETs formation, induce both EMT and cell death in the lung epithelial cell line, A549. Notably, NETs isolated from PMA-Neu induce EMT without cell damage. Bronchoalveolar lavage fluid of severe COVID-19 patients showed high concentration of NETs. Thus, we tested in an in vitro alveolar model the hypothesis that virus-induced NET may drive EMT. Co-culturing A549 at air-liquid interface with alveolar macrophages, neutrophils and SARS-CoV2, we demonstrated a significant induction of the EMT in A549 together with high concentration of NETs, IL8 and IL1{beta}, best-known inducers of NETosis. Lung tissues of COVID-19 deceased patients showed that epithelial cells are characterized by increased mesenchymal markers. These results show for the first time that NETosis plays a major role in triggering lung fibrosis in COVID-19 patients.", - "rel_num_authors": 20, - "rel_authors": [ - { - "author_name": "Laura Pandolfi", - "author_inst": "Fondazione IRCCS Policlinico San Matteo" - }, - { - "author_name": "Sara Bozzini", - "author_inst": "IRCCS Policlinico San Matteo Foundation" - }, - { - "author_name": "Frangipane Vanessa", - "author_inst": "IRCCS Policlinico San Matteo Foundation" - }, - { - "author_name": "Elena Percivalle", - "author_inst": "Fondazione IRCCS Policlinico San Matteo" - }, - { - "author_name": "Ada De Luigi", - "author_inst": "Istituto di Ricerche Farmacologiche Mario Negri IRCCS" - }, - { - "author_name": "Martina Bruna Violatto", - "author_inst": "Istituto di Ricerche Farmacologiche Mario Negri IRCCS" - }, - { - "author_name": "Gianluca Lopez", - "author_inst": "ASST Fatebenefratelli Sacco" - }, - { - "author_name": "Elisa Gabanti", - "author_inst": "IRCCS Policlinico S. Matteo Foundation" - }, - { - "author_name": "Luca Carsana", - "author_inst": "ASST Fatebenefratelli Sacco" - }, - { - "author_name": "Monica Morosini", - "author_inst": "IRCCS Policlinico S. Matteo Foundation" - }, - { - "author_name": "Mara De Amici", - "author_inst": "IRCCS Policlinico S. Matteo Foundation" - }, - { - "author_name": "Manuela Nebuloni", - "author_inst": "ASST Fatebenefratelli Sacco" - }, - { - "author_name": "Tommaso Fossali", - "author_inst": "ASST Fatebenefratelli Sacco" - }, - { - "author_name": "Riccardo Colombo", - "author_inst": "ASST Fatebenefratelli Sacco" - }, - { - "author_name": "Veronica Codullo", - "author_inst": "IRCCS Policlinico S. Matteo Foundation" - }, - { - "author_name": "Massimiliano Gnecchi", - "author_inst": "IRCCS Policlinico S. Matteo Foundation" - }, - { - "author_name": "Paolo Bigini", - "author_inst": "Istituto di Ricerche Farmacologiche Mario Negri IRCCS" - }, - { - "author_name": "Fausto Baldanti", - "author_inst": "Molecular Virology Unit, Fondazione IRCCS Policlinico San Matteo" - }, - { - "author_name": "Daniele Lilleri", - "author_inst": "IRCCS Policlinico S. Matteo Foundation" - }, - { - "author_name": "Federica Meloni", - "author_inst": "IRCCS Policlinico S. Matteo Foundation" - } - ], + "rel_link": "https://biorxiv.org/cgi/content/short/2020.11.09.373449", + "rel_abs": "BackgroundCoronavirus disease 2019 (COVID-19) caused by SARS-CoV-2 has now spread worldwide to infect over 110 million people, with approximately 2.5 million reported deaths. A safe and effective vaccine remains urgently needed.\n\nMethodWe constructed three variants of the recombinant receptor-binding domain (RBD) of the SARS-CoV-2 spike (S) protein (residues 331-549) in yeast as follows: (1) a \"wild type\" RBD (RBD219-WT), (2) a deglycosylated form (RBD219-N1) by deleting the first N-glycosylation site, and (3) a combined deglycosylated and cysteine-mutagenized form (C538A-mutated variant (RBD219-N1C1)). We compared the expression yields, biophysical characteristics, and functionality of the proteins produced from these constructs.\n\nResults and conclusionsThese three recombinant RBDs showed similar secondary and tertiary structure thermal stability and had the same affinity to their receptor, angiotensin-converting enzyme 2 (ACE-2), suggesting that the selected deletion or mutations did not cause any significant structural changes or alteration of function. However, RBD219-N1C1 had a higher fermentation yield, was easier to purify, was not hyperglycosylated, and had a lower tendency to form oligomers, and thus was selected for further vaccine development and evaluation.\n\nGeneral significanceBy genetic modification, we were able to design a better-controlled and more stable vaccine candidate, which is an essential and important criterion for any process and manufacturing of biologics or drugs for human use.", + "rel_num_authors": 0, + "rel_authors": null, "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "new results", "category": "immunology" }, @@ -1082237,67 +1083040,39 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.11.04.20225904", - "rel_title": "Development and Validation of Early Warning Score Systems for COVID-19 Patients", + "rel_doi": "10.1101/2020.11.04.20225961", + "rel_title": "Biometric covariates and outcome in COVID-19 patients: Are we looking close enough?", "rel_date": "2020-11-06", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.04.20225904", - "rel_abs": "COVID-19 is a major, urgent, and ongoing threat to global health. Globally more than 24 million have been infected and the disease has claimed more than a million lives as of October 2020. Predicting which patients will need respiratory support is important to guiding individual patient treatment and also to ensuring sufficient resources are available. We evaluated the ability of six common Early Warning Scores (EWS) to identify respiratory deterioration defined as the need for advanced respiratory support (high-flow nasal oxygen, continuous positive airways pressure, non-invasive ventilation, intubation) within a prediction window of 24 hours. We show these scores perform sub-optimally at this specific task. Therefore, we develop an alternative Early Warning Score based on a Gradient Boosting Trees (GBT) algorithm that is able to predict deterioration within the next 24 hours with high AUROC 94% and an accuracy, sensitivity and specificity of 70%, 96%, 70%, respectively. Our GBT model outperformed the best EWS (LDTEWS:NEWS), increasing the AUROC by 14%. Our GBT model makes the prediction based on the current and baseline measures of routinely available vital signs and blood tests.", - "rel_num_authors": 12, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.04.20225961", + "rel_abs": "BackgroundThe impact of biometric covariates on risk for adverse outcomes of COVID-19 disease was assessed by numerous observational studies on unstratified cohorts, which show great heterogeneity. However, multilevel evaluations to find possible complex, e. g. non-monotonic multi-variate patterns reflecting mutual interference of parameters are missing. We used a more detailed, computational analysis to investigate the influence of biometric differences on mortality and disease evolution among severely ill COVID-19 patients.\n\nMethodsWe analyzed a group of COVID-19 patients requiring Intensive care unit (ICU) treatment. For further analysis, the study group was segmented into six subgroups according to BMI and age. To link the BMI/age derived subgroups with risk factors, we performed an enrichment analysis of diagnostic parameters and comorbidities. To suppress spurious patterns, multiple segmentations were analyzed and integrated into a consensus score for each analysis step.\n\nResultsWe analyzed 81 COVID-19 patients, of whom 67 required MV. Mean mortality was 35.8 %. We found a complex, non-monotonic interaction between age, BMI and mortality. A subcohort of patients with younger age and intermediate BMI exhibited a strongly reduced mortality risk (p < 0.001), while differences in all other groups were not significant. Univariate impacts of BMI or age on mortality were missing. Comparing MV with non-MV patients, we found an enrichment of baseline CRP, PCT and D-Dimers within the MV-group, but not when comparing survivors vs. non-survivors within the MV patient group.\n\nConclusionsThe aim of this study was to get a more detailed insight into the influence of biometric covariates on the outcome of COVID-19 patients with high degree of severity. We found that survival in MV is affected by complex interactions of covariates differing to the reported covariates, which are hidden in generic, non-stratified studies on risk factors. Hence, our study suggests that a detailed, multivariate pattern analysis on larger patient cohorts reflecting the specific disease stages might reveal more specific patterns of risk factors supporting individually adapted treatment strategies.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Alexey Youssef", - "author_inst": "Institute of Biomedical Engineering, Dept. Engineering Science, University of Oxford" - }, - { - "author_name": "Samaneh Kouchaki", - "author_inst": "Centre for Vision, Speech, and Signal Processing, University of Surrey" - }, - { - "author_name": "Farah Shamout", - "author_inst": "New York University Abu Dhabi, Engineering Division" - }, - { - "author_name": "Jacob Armstrong", - "author_inst": "Institute of Biomedical Engineering, Dept. Engineering Science, University of Oxford" - }, - { - "author_name": "Rasheed El-Bouri", - "author_inst": "Institute of Biomedical Engineering, Dept. Engineering Science, University of Oxford" - }, - { - "author_name": "Thomas Taylor", - "author_inst": "Institute of Biomedical Engineering, Dept. Engineering Science, University of Oxford" - }, - { - "author_name": "Drew Birrenkott", - "author_inst": "Stanford School of Medicine, Stanford University" - }, - { - "author_name": "Baptiste Vasey", - "author_inst": "Institute of Biomedical Engineering, Dept. Engineering Science, University of Oxford" + "author_name": "Sebastian Johannes Fritsch", + "author_inst": "University Hospital RWTH Aachen" }, { - "author_name": "Andrew Soltan", - "author_inst": "Institute of Biomedical Engineering, Dept. Engineering Science, University of Oxford" + "author_name": "Konstantin Sharafutdinov", + "author_inst": "Institute for Computational Biomedicine, RWTH Aachen University" }, { - "author_name": "Tingting Zhu", - "author_inst": "Institute of Biomedical Engineering, Dept. Engineering Science, University of Oxford" + "author_name": "Gernot Marx", + "author_inst": "University Hospital RWTH Aachen" }, { - "author_name": "David A Clifton", - "author_inst": "Institute of Biomedical Engineering, Dept. Engineering Science, University of Oxford" + "author_name": "Andreas Schuppert", + "author_inst": "Institute for Computational Biomedicine, RWTH Aachen University" }, { - "author_name": "David W Eyre", - "author_inst": "John Radcliffe Hospital, Oxford University Hospitals" + "author_name": "Johannes Bickenbach", + "author_inst": "University Hospital RWTH Aachen" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2020.11.04.20224758", @@ -1084019,99 +1084794,55 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2020.11.04.20225557", - "rel_title": "Spatial Profiling of Lung SARS-CoV-2 and Influenza Virus Infection Dissects Virus-Specific Host Responses and Gene Signatures", + "rel_doi": "10.1101/2020.11.06.370916", + "rel_title": "Acrylamide Fragment Inhibitors that Induce Unprecedented Conformational Distortions in Enterovirus 71 3C and SARS-CoV-2 Main Protease", "rel_date": "2020-11-06", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.04.20225557", - "rel_abs": "The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that emerged in late 2019 has spread globally, causing a pandemic of respiratory illness designated coronavirus disease 2019 (COVID-19). Robust blood biomarkers that reflect tissue damage are urgently needed to better stratify and triage infected patients. Here, we use spatial transcriptomics to generate an in-depth picture of the pulmonary transcriptional landscape of COVID-19 (10 patients), pandemic H1N1 (pH1N1) influenza (5) and uninfected control patients (4). Host transcriptomics showed a significant upregulation of genes associated with inflammation, type I interferon production, coagulation and angiogenesis in the lungs of COVID-19 patients compared to non-infected controls. SARS-CoV-2 was non-uniformly distributed in lungs with few areas of high viral load and these were largely only associated with an increased type I interferon response. A very limited number of genes were differentially expressed between the lungs of influenza and COVID-19 patients. Specific interferon-associated genes (including IFI27) were identified as candidate novel biomarkers for COVID-19 differentiating this COVID-19 from influenza. Collectively, these data demonstrate that spatial transcriptomics is a powerful tool to identify novel gene signatures within tissues, offering new insights into the pathogenesis of SARS-COV-2 to aid in patient triage and treatment.", - "rel_num_authors": 20, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2020.11.06.370916", + "rel_abs": "RNA viruses are critically dependent upon virally encoded proteases that cleave the viral polyproteins into functional mature proteins. Many of these proteases are structurally conserved with an essential catalytic cysteine and this offers the opportunity to irreversibly inhibit these enzymes with electrophilic small molecules. Here we describe the successful application of quantitative irreversible tethering (qIT) to identify acrylamide fragments that selectively target the active site cysteine of the 3C protease (3Cpro) of Enterovirus 71, the causative agent of hand, foot and mouth disease in humans, altering the substrate binding region. Further, we effectively re-purpose these hits towards the main protease (Mpro) of SARS-CoV-2 which shares the 3C-like fold as well as similar catalytic-triad. We demonstrate that the hit fragments covalently link to the catalytic cysteine of Mpro to inhibit its activity. In addition, we provide the first demonstration that targeting the active site cysteine of Mpro can also have profound allosteric effects, distorting secondary structures required for formation of the active dimeric unit of Mpro. These new data provide novel mechanistic insights into the design of EV71 3Cpro and SARS-CoV-2 Mpro inhibitors and identify acrylamide-tagged pharmacophores for elaboration into more selective agents of therapeutic potential.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Arutha Kulasinghe", - "author_inst": "Queensland University" - }, - { - "author_name": "Chin Wee Tan", - "author_inst": "The Walter and Eliza Hall Institute of Medical Research" - }, - { - "author_name": "Anna Flavia Ribeiro dos Santos Miggiolaro", - "author_inst": "Pontificia Universidade Catolica do Parana" - }, - { - "author_name": "James Monkman", - "author_inst": "Queensland University of Technology" - }, - { - "author_name": "Dharmesh Bhuva", - "author_inst": "The Walter and Eliza Hall Institute of Medical Research" - }, - { - "author_name": "Jarbas da Silva Motta Junior", - "author_inst": "Pontifical Catholic University of Parana" - }, - { - "author_name": "Caroline Busatta Vaz de Paula", - "author_inst": "Pontifical Catholic University of Parana" - }, - { - "author_name": "Seigo Nagashima", - "author_inst": "Pontifical Catholic University of Parana" - }, - { - "author_name": "Cristina Pellegrino Baena", - "author_inst": "Pontifical Catholic University of Parana" - }, - { - "author_name": "Paulo Souza-Fonseca Guimaraes", - "author_inst": "Pontifical Catholic University of Parana" - }, - { - "author_name": "Lucia Noronha", - "author_inst": "Pontifical Catholic University of Parana" - }, - { - "author_name": "Timothy McCulloch", - "author_inst": "University of Queensland Diamantina Institute" + "author_name": "Bo Qin", + "author_inst": "Institute of Pathogen Biology" }, { - "author_name": "Gustavo Rodrigues Rossi", - "author_inst": "University of Queensland Diamantina Institute" + "author_name": "Gregory B Craven", + "author_inst": "Imperial College London" }, { - "author_name": "Caroline Cooper", - "author_inst": "University of Queensland" + "author_name": "Pengjiao Hou", + "author_inst": "Institute of Pathogen Biology" }, { - "author_name": "Benjamin Tang", - "author_inst": "University of Syndey" + "author_name": "Xinran Lu", + "author_inst": "Imperial College London" }, { - "author_name": "Kirsty Short", - "author_inst": "University of Queensland" + "author_name": "Emma S Child", + "author_inst": "Imperial College London" }, { - "author_name": "Melissa J Davis", - "author_inst": "The Walter and Eliza Hall Institute of Medical Research" + "author_name": "Rhodri M L Morgan", + "author_inst": "Imperial College London" }, { - "author_name": "Fernando Souza-Fonseca Guimaraes", - "author_inst": "University of Queensland Diamantina Institute" + "author_name": "Alan Armstrong", + "author_inst": "Imperial College London" }, { - "author_name": "Gabrielle T Belz", - "author_inst": "University of Queensland Diamantina Institute" + "author_name": "David J Mann", + "author_inst": "Imperial College London" }, { - "author_name": "Ken O'Byrne", - "author_inst": "Queensland University of Technology" + "author_name": "Sheng Cui", + "author_inst": "Institute of Pathogen Biology" } ], "version": "1", "license": "cc_by_nc_nd", - "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "type": "new results", + "category": "biochemistry" }, { "rel_doi": "10.1101/2020.11.06.369439", @@ -1086068,61 +1086799,325 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.11.03.20225565", - "rel_title": "COVID-19 surveillance - a descriptive study on data quality issues", + "rel_doi": "10.1101/2020.11.03.20225409", + "rel_title": "COVID-19 reopening strategies at the county level in the face of uncertainty: Multiple Models for Outbreak Decision Support", "rel_date": "2020-11-05", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.03.20225565", - "rel_abs": "BackgroundHigh-quality data is crucial for guiding decision making and practicing evidence-based healthcare, especially if previous knowledge is lacking. Nevertheless, data quality frailties have been exposed worldwide during the current COVID-19 pandemic. Focusing on a major Portuguese surveillance dataset, our study aims to assess data quality issues and suggest possible solutions.\n\nMethodsOn April 27th 2020, the Portuguese Directorate-General of Health (DGS) made available a dataset (DGSApril) for researchers, upon request. On August 4th, an updated dataset (DGSAugust) was also obtained. The quality of data was assessed through analysis of data completeness and consistency between both datasets.\n\nResultsDGSAugust has not followed the data format and variables as DGSApril and a significant number of missing data and inconsistencies were found (e.g. 4,075 cases from the DGSApril were apparently not included in DGSAugust). Several variables also showed a low degree of completeness and/or changed their values from one dataset to another (e.g. the variable underlying conditions had more than half of cases showing different information between datasets). There were also significant inconsistencies between the number of cases and deaths due to COVID-19 shown in DGSAugust and by the DGS reports publicly provided daily.\n\nConclusionsThe low quality of COVID-19 surveillance datasets limits its usability to inform good decisions and perform useful research. Major improvements in surveillance datasets are therefore urgently needed - e.g. simplification of data entry processes, constant monitoring of data, and increased training and awareness of health care providers - as low data quality may lead to a deficient pandemic control.", - "rel_num_authors": 12, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.03.20225409", + "rel_abs": "Policymakers make decisions about COVID-19 management in the face of considerable uncertainty. We convened multiple modeling teams to evaluate reopening strategies for a mid-sized county in the United States, in a novel process designed to fully express scientific uncertainty while reducing linguistic uncertainty and cognitive biases. For the scenarios considered, the consensus from 17 distinct models was that a second outbreak will occur within 6 months of reopening, unless schools and non-essential workplaces remain closed. Up to half the population could be infected with full workplace reopening; non-essential business closures reduced median cumulative infections by 82%. Intermediate reopening interventions identified no win-win situations; there was a trade-off between public health outcomes and duration of workplace closures. Aggregate results captured twice the uncertainty of individual models, providing a more complete expression of risk for decision-making purposes.", + "rel_num_authors": 78, "rel_authors": [ { - "author_name": "Cristina Costa-Santos", - "author_inst": "Department of Community Medicine, Information and Health Decision Sciences-MEDCIDS, Faculty of Medicine, University of Porto" + "author_name": "Katriona Shea", + "author_inst": "Department of Biology and Center for Infectious Disease Dynamics, The Pennsylvania State University" }, { - "author_name": "Ana Luisa Neves", - "author_inst": "Department of Community Medicine, Information and Health Decision Sciences-MEDCIDS, Faculty of Medicine, University of Porto" + "author_name": "Rebecca K Borchering", + "author_inst": "Department of Biology and Center for Infectious Disease Dynamics, The Pennsylvania State University" }, { - "author_name": "Ricardo Correia", - "author_inst": "Department of Community Medicine, Information and Health Decision Sciences-MEDCIDS, Faculty of Medicine, University of Porto" + "author_name": "William JM Probert", + "author_inst": "Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford" }, { - "author_name": "Paulo Santos", - "author_inst": "Department of Community Medicine, Information and Health Decision Sciences-MEDCIDS, Faculty of Medicine, University of Porto" + "author_name": "Emily Howerton", + "author_inst": "Department of Biology and Center for Infectious Disease Dynamics, The Pennsylvania State University, University Park" }, { - "author_name": "Matilde Monteiro-Soares", - "author_inst": "Department of Community Medicine, Information and Health Decision Sciences-MEDCIDS, Faculty of Medicine, University of Porto" + "author_name": "Tiffany L Bogich", + "author_inst": "Department of Biology and Center for Infectious Disease Dynamics, The Pennsylvania State University, University Park" }, { - "author_name": "Alberto Freitas", - "author_inst": "Department of Community Medicine, Information and Health Decision Sciences-MEDCIDS, Faculty of Medicine, University of Porto" + "author_name": "Shouli Li", + "author_inst": "State Key Laboratory of Grassland Agro-ecosystems, Center for Grassland Microbiome, and College of Pastoral, Agriculture Science and Technology, Lanzhou Univers" }, { - "author_name": "Ines Ribeiro-Vaz", - "author_inst": "Department of Community Medicine, Information and Health Decision Sciences-MEDCIDS, Faculty of Medicine, University of Porto" + "author_name": "Willem G. van Panhuis", + "author_inst": "Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh" }, { - "author_name": "Teresa Henriques", - "author_inst": "Department of Community Medicine, Information and Health Decision Sciences-MEDCIDS, Faculty of Medicine, University of Porto" + "author_name": "Cecile Viboud", + "author_inst": "NIH" }, { - "author_name": "Pedro Pereira Rodrigues", - "author_inst": "Department of Community Medicine, Information and Health Decision Sciences-MEDCIDS, Faculty of Medicine, University of Porto" + "author_name": "Ricardo Aguas", + "author_inst": "Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford" }, { - "author_name": "Altamiro Costa-Pereira", - "author_inst": "Department of Community Medicine, Information and Health Decision Sciences-MEDCIDS, Faculty of Medicine, University of Porto" + "author_name": "Artur Belov", + "author_inst": "Office of Biostatistics & Epidemiology, FDA - Center for Biologics Evaluation and Research, Silver Spring" }, { - "author_name": "Ana Margarida Pereira", - "author_inst": "Department of Community Medicine, Information and Health Decision Sciences-MEDCIDS, Faculty of Medicine, University of Porto" + "author_name": "Sanjana H Bhargava", + "author_inst": "Department of Biology, University of Florida, Gainesville," }, { - "author_name": "Joao Fonseca", - "author_inst": "Department of Community Medicine, Information and Health Decision Sciences-MEDCIDS, Faculty of Medicine, University of Porto" + "author_name": "Sean Cavany", + "author_inst": "Department of Biological Sciences, University of Notre Dame" + }, + { + "author_name": "Joshua C Chang", + "author_inst": "Epidemiology and Biostatistics Section, Rehabilitation Medicine, Clinical Center, National Institutes of Health and Medeterra" + }, + { + "author_name": "Cynthia Chen", + "author_inst": "Department of Civil & Environmental Engineering, University of Washington" + }, + { + "author_name": "Jinghui Chen", + "author_inst": "Department of Computer Science, University of California, Los Angeles" + }, + { + "author_name": "Shi Chen", + "author_inst": "Department of Public Health Sciences, University of North Carolina at Charlotte and School of Data Science, University of North Carolina at Charlotte" + }, + { + "author_name": "YangQuan Chen", + "author_inst": "Mechatronics, Embedded Systems and Automation Laboratory, Dept. of Engineering University of California, Merced" + }, + { + "author_name": "Lauren M Childs", + "author_inst": "Department of Mathematics, Virginia Tech" + }, + { + "author_name": "Carson C Chow", + "author_inst": "Mathematical Biology Section, LBM, NIDDK, National Institutes of Health" + }, + { + "author_name": "Isabel Crooker", + "author_inst": "Los Alamos National Laboratory" + }, + { + "author_name": "Sara Y Del Valle", + "author_inst": "Los Alamos National Laboratory" + }, + { + "author_name": "Guido Espana", + "author_inst": "Department of Biological Sciences, University of Notre Dame" + }, + { + "author_name": "Geoffrey Fairchild", + "author_inst": "Los Alamos National Laboratory" + }, + { + "author_name": "Richard C Gerkin", + "author_inst": "School of Life Sciences, Arizona State University" + }, + { + "author_name": "Timothy C Germann", + "author_inst": "Los Alamos National Laboratory" + }, + { + "author_name": "Quanquan Gu", + "author_inst": "Department of Computer Science, University of California, Los Angeles" + }, + { + "author_name": "Xiangyang Guan", + "author_inst": "Department of Civil & Environmental Engineering, University of Washington" + }, + { + "author_name": "Lihong Guo", + "author_inst": "Institute of Mathematics, Jilin University, Changchun" + }, + { + "author_name": "Gregory R Hart", + "author_inst": "Institute for Disease Modeling" + }, + { + "author_name": "Thomas J Hladish", + "author_inst": "Department of Biology and Emerging Pathogens Institute, University of Florida, Gainesville" + }, + { + "author_name": "Nathaniel Hupert", + "author_inst": "Weill Cornell Medicine, Cornell University" + }, + { + "author_name": "Daniel Janies", + "author_inst": "Department of Bioinformatics and Genomics, University of North Carolina at Charlotte" + }, + { + "author_name": "Cliff C Kerr", + "author_inst": "Institute for Disease Modeling" + }, + { + "author_name": "Daniel J Klein", + "author_inst": "Institute for Disease Modeling" + }, + { + "author_name": "Eili Klein", + "author_inst": "Department of Emergency Medicine, Johns Hopkins University and Center for Disease Dynamics, Economics, & Policy" + }, + { + "author_name": "Gary Lin", + "author_inst": "Department of Emergency Medicine, Johns Hopkins University" + }, + { + "author_name": "Carrie Manore", + "author_inst": "School of Life Sciences, Arizona State University" + }, + { + "author_name": "Lauren Ancel Meyers", + "author_inst": "Department of Integrative Biology, The University of Texas at Austin" + }, + { + "author_name": "John Mittler", + "author_inst": "Department of Microbiology, University of Washington" + }, + { + "author_name": "Kunpeng Mu", + "author_inst": "Laboratory for the Modeling of Biological and Socio-technical Systems, Northeastern University, Boston" + }, + { + "author_name": "Rafael C NUNez", + "author_inst": "Institute for Disease Modeling" + }, + { + "author_name": "Rachel Oidtman", + "author_inst": "Department of Biological Sciences, University of Notre Dame" + }, + { + "author_name": "Remy Pasco", + "author_inst": "Operations Research, The University of Texas at Austin" + }, + { + "author_name": "Ana Pastore y Piontti Pastore y Piontti", + "author_inst": "Laboratory for the Modeling of Biological and Socio-technical Systems, Northeastern University" + }, + { + "author_name": "Rajib Paul", + "author_inst": "Department of Public Health Sciences, University of North Carolina at Charlotte" + }, + { + "author_name": "Carl AB Pearson", + "author_inst": "Department of Infectious Disease Epidemiology & Centre Mathematical Modelling of Infectious Disease, London School of Hygiene and Tropical Medicine" + }, + { + "author_name": "Dianela Perdomo", + "author_inst": "Department of Biology, University of Florida, Gainesville" + }, + { + "author_name": "T Alex Perkins", + "author_inst": "Department of Biological Sciences, University of Notre Dame" + }, + { + "author_name": "Kelly Pierce", + "author_inst": "Texas Advanced Computing Center, The University of Texas at Austin" + }, + { + "author_name": "Alexander N Pillai", + "author_inst": "Department of Biology, University of Florida, Gainesville" + }, + { + "author_name": "Rosalyn Cherie Rael", + "author_inst": "Los Alamos National Laboratory" + }, + { + "author_name": "Katherine Rosenfeld", + "author_inst": "Institute for Disease Modeling" + }, + { + "author_name": "Chrysm Watson Ross", + "author_inst": "Los Alamos National Laboratory" + }, + { + "author_name": "Julie A Spencer", + "author_inst": "Los Alamos National Laboratory" + }, + { + "author_name": "Arlin B Stoltzfus", + "author_inst": "National Institute of Standards and Technology" + }, + { + "author_name": "Kok Ben Toh", + "author_inst": "School of Natural Resources and Environment, University of Florida," + }, + { + "author_name": "Shashaank Vattikuti", + "author_inst": "Mathematical Biology Section, LBM, NIDDK, National Institutes of Health" + }, + { + "author_name": "Alessandro Vespignani", + "author_inst": "Laboratory for the Modeling of Biological and Socio-technical Systems, Northeastern University" + }, + { + "author_name": "Lingxiao Wang", + "author_inst": "Department of Computer Science, University of California, Los Angeles" + }, + { + "author_name": "Lisa White", + "author_inst": "Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford" + }, + { + "author_name": "Pan Xu", + "author_inst": "Department of Computer Science, University of California, Los Angeles" + }, + { + "author_name": "Yupeng Yang", + "author_inst": "Center for Disease Dynamics, Economics, & Policy" + }, + { + "author_name": "Osman N Yogurtcu", + "author_inst": "Office of Biostatistics & Epidemiology, FDA - Center for Biologics Evaluation and Research" + }, + { + "author_name": "Weitong Zhang", + "author_inst": "Department of Computer Science, University of California, Los Angeles" + }, + { + "author_name": "Yanting Zhao", + "author_inst": "Lab of Vibration Control & Vehicle Control Department of Automation, University of Science and Technology of China" + }, + { + "author_name": "Difan Zou", + "author_inst": "Department of Computer Science, University of California, Los Angeles" + }, + { + "author_name": "Matthew Ferrari", + "author_inst": "Department of Biology and Center for Infectious Disease Dynamics, The Pennsylvania State University" + }, + { + "author_name": "David Pannell", + "author_inst": "School of Agriculture and Environment, University of Western Australia" + }, + { + "author_name": "Michael Tildesley", + "author_inst": "Life Sciences, University of Warwick" + }, + { + "author_name": "Jack Seifarth", + "author_inst": "Department of Biology and Center for Infectious Disease Dynamics, The Pennsylvania State University" + }, + { + "author_name": "Elyse Johnson", + "author_inst": "Department of Biology and Center for Infectious Disease Dynamics, The Pennsylvania State University" + }, + { + "author_name": "Matthew Biggerstaff", + "author_inst": "CDC COVID-19 Response" + }, + { + "author_name": "Michael Johansson", + "author_inst": "CDC COVID-19 Response" + }, + { + "author_name": "Rachel B Slayton", + "author_inst": "CDC COVID-19 Response" + }, + { + "author_name": "John Levander", + "author_inst": "Department of Biomedical Informatics, School of Medicine, University of Pittsburgh" + }, + { + "author_name": "Jeff Stazer", + "author_inst": "Department of Biomedical Informatics, School of Medicine, University of Pittsburgh" + }, + { + "author_name": "Jessica Salermo", + "author_inst": "Department of Biomedical Informatics, School of Medicine, University of Pittsburgh" + }, + { + "author_name": "Michael C Runge", + "author_inst": "U.S. Geological Survey, Patuxent Wildlife Research Center" } ], "version": "1", @@ -1088022,25 +1089017,77 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.11.02.20224584", - "rel_title": "The signature features of COVID-19 pandemic in a hybrid mathematical model - implications for optimal work-school lockdown policy", + "rel_doi": "10.1101/2020.11.02.20224659", + "rel_title": "The CCR5-delta32 variant might explain part of the association between COVID-19 and the chemokine-receptor gene cluster", "rel_date": "2020-11-04", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.02.20224584", - "rel_abs": "BackgroundThe coronavirus disease 2019 (COVID-19) first identified in China, spreads rapidly across the globe and is considered the fastest moving pandemic in history. The new disease has challenged policymakers and scientists on key issues such as the magnitude of the first-time problem, the susceptibility of the population, the severity of the disease, and its symptoms. Most countries have adopted \"lockdown\" policies to reduce the spatial spread of COVID-19, but they have damaged the economic and moral fabric of society. Timely action to prevent the spread of the virus is critical, and mathematical modeling in non-pharmaceutical intervention (NPI) policy management has proven to be a major weapon in this fight due to the lack of an effective COVID-19 vaccine.\n\nMethodsWe present a new hybrid model for COVID-19 dynamics using both an age-structured mathematical model and spatio-temporal model in silico, analyzing the data of COVID-19 in Israel. The age-structured mathematical model is based on SIRD two age-class model. The spatial model examines a circle of day and night (with one-hour resolution) and three main locations (work / school or home) for every individual.\n\nResultsWe determine mathematically the basic reproduction number R0 via the next-generation matrix based on Markov chain theory. Then, we analyze the stability of the equilibria and the effects of the significant differences in infection rates between children and adults. Using the hybrid model, we have introduced a method for estimating the reproduction number of an epidemic in real time from the data of daily notification of cases. The results of the proposed model are confirmed by the Israeli Lockdown experience with a mean square error of 0.205 over two weeks. The model was able to predict changes in R0 by opening schools on September 1, 2020, resulting in R0 = 2.2, which entailed a months quarantine of all areas of life. According to the model, by extending the school day to 9 hours, and assuming that children and adults go to school and work every day (except weekends), we get a significant reduction in R0 of 1.45. Finally, model-based analytical-numerical results are obtained and displayed in graphical profiles.\n\nConclusionsThe use of mathematical models promises to reduce the uncertainty in the choice of \"Lockdown\" policies. Our unique use of contact details from 2 classes (children and adults), the interaction of populations depending on the time of day (the cycle of day and night), and several physical locations, allowed a new look at the differential dynamics of the spread and control of infection. Using knowledge about how the length of the work and school day affects the dynamics of the spread of the disease can be useful for improving control programs, mitigation, and policy.\n\nAuthor summaryEverybody in the modern world understands today that the pandemics threat is not less dangerous than the wars. COVID-19 showed us that pandemics effects the economies of all the countries over the world brings to a total lockdown of social life and enormous mortality. There was no effective vaccine/treatment, to stop the spread of COVID-19 and, therefore, policymakers have taken unprecedented measures, including quarantines, public health measures, travel bans, and others, without knowing in advance the effect of these restrictions.\n\nIn this study, we develop a mathematical model of the pandemic spread taking into account the different dynamics of the disease in two age groups of children and adults. Using this model we succeeded to simulate the COVID-19 spread in Israel. The current study accurately predicts the effect of the work/school lockdown on the outbreaks. We have proven that by keeping schools open and increasing the school day to 8-9 hours, infection rates are reduced. Our results also show that if at least half of the adult population is a lockdown, the effect of childrens isolation on the infection rate is small, indicating the importance of multiple age groups of the population in the selection of restrictions.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.02.20224659", + "rel_abs": "A polymorphism in the LZTFL1 gene located in the chemokine-receptor gene cluster (chromosome 3p) has been associated with the risk of developing COVID-19. The chemokine receptor-5 (CCR5) maps to this region, and the common 32 bp deletion variant ({Delta}32) has been associated with the extent of inflammatory disease and the outcome in several viral diseases. Several studies have also suggested that the pharmacological targeting of CCR5 could reduce the impact of SARS-CoV-2 infection and the severity of COVID-19. We sought to investigate whether this polymorphism was associated with the risk of moderate-severe COVID-19.\n\nWe genotyped 294 patients who required hospitalization due to COVID-19 (85 were severe cases) and 460 controls. We found a significantly lower frequency of CCR5-{Delta}32 among the COVID-19 patients (0.10 vs 0.18 in controls; p=0.002, OR=0.48, 95%CI=0.29-0.76). The difference was mainly due to the reduced frequency of CCR5-{Delta}32 carriers in the severe, significantly lower than in the non-severe patients (p=0.036). Of note, we did not find deletion-homozygotes among the patients compared to 1% among controls. We also confirmed the association between a LZTFL1 variant and COVID-19. Our study points to CCR5 as a promising target for treatment of COVID-19, but requires validation in additional large cohorts. In confirmed by others, the genetic analysis of CCR5-variants (such as {Delta}32) might help to identify patients with a higher susceptibility to severe COVID-19.", + "rel_num_authors": 15, "rel_authors": [ { - "author_name": "Teddy Lazebnik", - "author_inst": "Bar Ilan University" + "author_name": "JUAN GOMEZ", + "author_inst": "HUCA" }, { - "author_name": "Svetlana Bunimovich-Mendrazitsky", - "author_inst": "Ariel University" + "author_name": "ELIAS CUESTA-LLAVONA", + "author_inst": "HUCA" + }, + { + "author_name": "GUILLERMO M ALBAICETA", + "author_inst": "HUCA" + }, + { + "author_name": "MARTA GARCIA-CLEMENTE", + "author_inst": "HUCA" + }, + { + "author_name": "CARLOS LOPEZ-LARREA", + "author_inst": "HUCA" + }, + { + "author_name": "LAURA AMADO", + "author_inst": "HUCA" + }, + { + "author_name": "INES LOPEZ-ALONSO", + "author_inst": "HUCA" + }, + { + "author_name": "TAMARA HERMIDA", + "author_inst": "HUCA" + }, + { + "author_name": "ANA ENRIQUEZ", + "author_inst": "HUCA" + }, + { + "author_name": "HELENA GIL", + "author_inst": "HUCA" + }, + { + "author_name": "BELEN ALONSO", + "author_inst": "HUCA" + }, + { + "author_name": "SARA IGLESIAS", + "author_inst": "HUCA" + }, + { + "author_name": "BEATRIZ SUAREZ-ALVAREZ", + "author_inst": "HUCA" + }, + { + "author_name": "VICTORIA ALVAREZ", + "author_inst": "HUCA" + }, + { + "author_name": "ELIECER COTO", + "author_inst": "HUCA" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1089424,45 +1090471,33 @@ "category": "health economics" }, { - "rel_doi": "10.1101/2020.11.03.20225284", - "rel_title": "SARS-CoV-2 transmission during team-sport: Do players develop COVID-19 after participating in rugby league matches with SARS-CoV-2 positive players?", + "rel_doi": "10.1101/2020.11.02.20224782", + "rel_title": "Prevalence Of COVID-19 In Rural Versus Urban Areas in a Low-Income Country: Findings from a State-Wide Study in Karnataka, India", "rel_date": "2020-11-04", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.03.20225284", - "rel_abs": "ObjectivesEvaluate the interactions between SARS-CoV-2 positive players and other players during rugby league matches, to determine the risk of in-game SARS-CoV-2 transmission.\n\nDesignObservational.\n\nSettingSuper League rugby league during four matches in which SARS-CoV-2 positive players were retrospectively found to have participated (2nd August and 4th October 2020).\n\nParticipants136 male elite rugby league players: eight SARS-CoV-2 positive participants, 28 identified close contacts and 100 other players who participated in any of the four matches.\n\nMain Outcome measuresClose contacts were defined by analysis of video footage for player interactions and microtechnology (GPS) data for proximity analysis. Close contacts and other players involved in the matches becoming positive for SARS-CoV-2 by RT-PCR within 14 days of the match were reported.\n\nResultsThe eight SARS-CoV-2 positive players were involved in up to 14 tackles with other individual players. SARS-CoV-2 positive players were within a 2 m proximity of other players for up to 316 secs, from 60 interactions. One identified contact returned a positive SARS-CoV-2 result within 14 days of the match (subsequently linked to an outbreak within their club environment, rather than in-match transmission), whereas the other 27 identified contacts returned negative SARS-CoV-2 follow up tests and no one developed COVID-19 symptoms. Ninety-five players returned negative and five players returned positive SARS-CoV-2 RT-PCR routine tests within 14 days of the match. Sources of transmission in the five cases were linked to internal club COVID-19 outbreaks and wider-community transmission.\n\nConclusionDespite a high number of tackle involvements and close proximity interactions between SARS-CoV-2 positive players and players on the same and opposition teams during a rugby league match, these data suggest that in-game SARS-CoV-2 transmission is limited during these types of team sport activities played outdoors.", - "rel_num_authors": 7, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.02.20224782", + "rel_abs": "Although the vast majority of confirmed cases of COVID-19 are in low- and middle-income countries, there are relatively few published studies on the epidemiology of SARS-CoV-2 in these countries. The few there are focus on disease prevalence in urban areas. We conducted state-wide surveillance for COVID-19, in both rural and urban areas of Karnataka between June 15-August 29, 2020. We tested for both viral RNA and antibodies targeting the receptor binding domain (RBD). Adjusted seroprevalence across Karnataka was 46.7% (95% CI: 43.3-50.0), including 44.1% (95% CI: 40.0-48.2) in rural and 53.8% (95% CI: 48.4-59.2) in urban areas. The proportion of those testing positive on RT-PCR, ranged from 1.5 to 7.7% in rural areas and 4.0 to 10.5% in urban areas, suggesting a rapidly growing epidemic. The relatively high prevalence in rural areas is consistent with the higher level of mobility measured in rural areas, perhaps because of agricultural activity. Overall seroprevalence in the state implies that by August at least 31.5 million residents had been infected by August, nearly an order of magnitude larger than confirmed cases.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Ben Jones", - "author_inst": "Leeds Beckett University" - }, - { - "author_name": "Gemma C Phillips", - "author_inst": "Rugby Football League" - }, - { - "author_name": "Simon PT Kemp", - "author_inst": "Rugby Football Union" - }, - { - "author_name": "Brendan Payne", - "author_inst": "Newcastle University" + "author_name": "Manoj Mohanan", + "author_inst": "Duke University" }, { - "author_name": "Brian Hart", - "author_inst": "Catapult Sports" + "author_name": "Anup Malani", + "author_inst": "University of Chicago" }, { - "author_name": "Matthew Cross", - "author_inst": "Premiership Rugby" + "author_name": "Kaushik Krishnan", + "author_inst": "Center for Monitoring Indian Economy" }, { - "author_name": "Keith Stokes", - "author_inst": "University of Bath" + "author_name": "Anu Acharya", + "author_inst": "Mapmygenome India Limited" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1091130,103 +1092165,31 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2020.10.28.20221200", - "rel_title": "Effective community screening for asymptomatic and symptomatic COVID-19 with a fast and extremely low cost COVID-Anosmia Checker tool", + "rel_doi": "10.1101/2020.10.28.20221952", + "rel_title": "Preventing COVID-19 Fatalities: State versus Federal Policies", "rel_date": "2020-11-03", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.28.20221200", - "rel_abs": "BackgroundCOVID-19 curve can be flattened by adopting mass screening protocols with aggressive testing and isolating infected populations. The current approach largely depends on RT-PCR/rapid antigen tests that require expert personnel resulting in higher costs and reduced testing frequency. Loss of smell is reported as a major symptom of COVID-19, however, a precise olfactory testing tool to identify COVID-19 patient is still lacking.\n\nMethodsTo quantitatively check for the loss of smell, we developed an odor strip, \"COVID-Anosmia checker\", spotted with gradients of coffee and lemon grass oil. We validated its efficiency in healthy and COVID-19 positive subjects. A trial screening to identify SARS-CoV-2 infected persons was also carried out to check the sensitivity and specificity of our screening tool.\n\nFindingsIt was observed that COVID positive participants were hyposmic instead of being anosmic when they were subjected to smelling higher odor concentration. Our tool identified 97% of symptomatic and 94% of asymptomatic COVID-19 positive subjects after excluding most confounding factors like concurrent chronic sinusitis. Further, it was possible to reliably predict COVID-19 infection by calculating a loss of smell score with 100% specificity. We coupled this tool with a mobile application, which takes the input response from the user, and can readily categorize the user in the appropriate risk groups.\n\nConclusionLoss of smell can be used as a reliable marker for screening for COVID-19. Our tool can be used for first-line screening to trace out COVID-19 infection effectively. It can be used in difficult to reach geographical locations.", - "rel_num_authors": 21, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.28.20221952", + "rel_abs": "Are COVID-19 fatalities large when a federal government does not enforce containment policies and instead allow states to implement their own policies? We answer this question by developing a stochastic extension of a SIRD epidemiological model for a country composed of multiple states. Our model allows for interstate mobility. We consider three policies: mask mandates, stay-at-home orders, and interstate travel bans. We fit our model to daily U.S. state-level COVID-19 death counts and exploit our estimates to produce various policy counterfactuals. While the restrictions imposed by some states inhibited a significant number of virus deaths, we find that more than two-thirds of U.S. COVID-19 deaths could have been prevented by late November 2020 had the federal government enforced federal mandates as early as some of the earliest states did. Our results quantify the benefits of early actions by a federal government for the containment of a pandemic.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Budhaditya Basu", - "author_inst": "Neuro-Stem Cell Biology Laboratory, Rajiv Gandhi Centre for Biotechnology (RGCB), Thiruvananthapuram, Kerala-695 014, India" - }, - { - "author_name": "Paul Ann Riya", - "author_inst": "Neuro-Stem Cell Biology Laboratory, Rajiv Gandhi Centre for Biotechnology (RGCB), Thiruvananthapuram, Kerala-695 014, India" - }, - { - "author_name": "Joby Issac", - "author_inst": "Cancer Biology Programs-12 (CRP-12), Rajiv Gandhi Centre for Biotechnology (RGCB), Thiruvananthapuram, Kerala-695 014, India" - }, - { - "author_name": "Surendran Parvathy", - "author_inst": "Neuro-Stem Cell Biology Laboratory, Rajiv Gandhi Centre for Biotechnology (RGCB), Thiruvananthapuram, Kerala-695 014, India" - }, - { - "author_name": "Biju Surendran Nair", - "author_inst": "Neuro-Stem Cell Biology Laboratory, Rajiv Gandhi Centre for Biotechnology (RGCB), Thiruvananthapuram, Kerala-695 014, India" - }, - { - "author_name": "Pradipta Tokdar", - "author_inst": "BioNEST, KINFRA Hi-Tech Park Campus, Rajiv Gandhi Centre for Biotechnology (RGCB), Kalamassery, Cochin, Kerala-683 503, India" - }, - { - "author_name": "Devika Sanal Kumar", - "author_inst": "Department of Biochemistry, Saveetha Medical College Hospital, Thandalam, Kanchipuram District, Tamilnadu-602 105, India" - }, - { - "author_name": "Pranav Ravi Kulkarni", - "author_inst": "Department of General Medicine, Saveetha Medical College Hospital, Thandalam, Kanchipuram District, Tamilnadu-602 105, India" - }, - { - "author_name": "Gowtham Hanumanram", - "author_inst": "Department of General Medicine, Saveetha Medical College Hospital, Thandalam, Kanchipuram District, Tamilnadu-602 105, India" - }, - { - "author_name": "Mohanan Jagadeesan", - "author_inst": "Department of General Medicine, Saveetha Medical College Hospital, Thandalam, Kanchipuram District, Tamilnadu-602 105, India" - }, - { - "author_name": "Prasanna Karthik Suthakaran", - "author_inst": "Department of General Medicine, Saveetha Medical College Hospital, Thandalam, Kanchipuram District, Tamilnadu-602 105, India" - }, - { - "author_name": "Lal Devayani Vasudevan Nair", - "author_inst": "Department of Paediatrics, Saveetha Medical College Hospital, Thandalam, Kanchipuram District, Tamilnadu-602 105, India" - }, - { - "author_name": "Rosy Vennila", - "author_inst": "Department of Microbiology, Saveetha Medical College Hospital, Thandalam, Kanchipuram District, Tamilnadu-602 105, India" - }, - { - "author_name": "Rajendran Kannan", - "author_inst": "Department of General Medicine, Saveetha Medical College Hospital, Thandalam, Kanchipuram District, Tamilnadu-602 105, India" - }, - { - "author_name": "Balarama Kaimal", - "author_inst": "Department of Biochemistry, Saveetha Medical College Hospital, Thandalam, Kanchipuram District, Tamilnadu-602 105, India" - }, - { - "author_name": "Gopa Kumar Anoop", - "author_inst": "Neologix (Wafi Technology), Office No: 4058, 4th Floor, 2xl Building, Bu Daniq, Al Qasimiyah, Post Box: 73500, UAE" - }, - { - "author_name": "Iype Joseph", - "author_inst": "Pathogen Biology, Rajiv Gandhi Centre for Biotechnology (RGCB), Thiruvananthapuram, Kerala-695 014, India" - }, - { - "author_name": "Radhakrishnan Nair", - "author_inst": "Laboratory Medicine and Molecular Diagnostics, Rajiv Gandhi Centre for Biotechnology (RGCB), Thiruvananthapuram, Kerala-695 014, India" - }, - { - "author_name": "Saji George", - "author_inst": "BioNEST, KINFRA Hi-Tech Park Campus, Rajiv Gandhi Centre for Biotechnology (RGCB), Kalamassery, Cochin, Kerala-683 503, India" + "author_name": "Jean-Paul Renne", + "author_inst": "University of Lausanne" }, { - "author_name": "Jackson James", - "author_inst": "Rajiv Gandhi Center for Biotechnology" + "author_name": "Guillaume Roussellet", + "author_inst": "McGill University" }, { - "author_name": "Madhavan Radhakrishna Pillai", - "author_inst": "Pathogen Biology, Rajiv Gandhi Centre for Biotechnology (RGCB), Thiruvananthapuram, Kerala-695 014, India" + "author_name": "Gustavo Schwenkler", + "author_inst": "Santa Clara University" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "health policy" }, { "rel_doi": "10.1101/2020.10.28.20221986", @@ -1092684,61 +1093647,201 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.10.30.20222950", - "rel_title": "Differences and similarities in diagnostic methods and treatments for Coronavirus disease 2019 (COVID-19): a scoping review", + "rel_doi": "10.1101/2020.10.30.20217364", + "rel_title": "Therapeutic efficacy of Honey and Nigella sativa against COVID-19: A multi-center randomized controlled clinical trial (HNS-COVID-PK)", "rel_date": "2020-11-03", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.30.20222950", - "rel_abs": "AimsWe investigate a range of studies related to COVID-19 with focus on scientific evidence reporting the main diagnosis and treatments of the disease.\n\nMain MethodsScoping review conducted in the databases, MEDLINE, Cochrane, Embase, LILACS, Scopus, and Web of Science, and the gray Google Scholar literature, until May 2020. We follow PRISMA-SCR and the recommendations of the Joanna Briggs Institute. The identified studies were independently selected by peers. The qualitative data extracted were synthesized and organized into categories, and the quantitative data were generated through descriptive and inferential statistics.\n\nKey-findings6060 articles were identified, of which 30 were included in this review. The publications are predominantly from China (n=22, 73.3%), and with a type of cross-sectional study (n=12, 40.0%), followed by a cohort (n=7, 23.0%). Among them, 16 studies addressed the diagnosis, and computed tomography was considered as non-invasive complementary method for detecting and evaluating the progression of COVID-19. Laboratory tests have been used to detect enzymatic or viral activities, and to monitor the inflammation associated with COVID-19. 14 studies included different therapeutic associations, such as Lopinavir/Ritonavir (LPV/r) and Arbidol, Hydroxychloroquine, Azithromycin, Tocilizumab and Remdesivir, and Corticosteroids/Plasminogen.\n\nSignificanceThe evidence related to diagnostic methods are clear, and include tomography and laboratory tests. Medicinal or associated medications for the treatment of COVID-19, although showing a reduction in signs and COVID-19-related symptoms, can cause adverse effects of mild or severe intensity depending on viral load and inflammatory activity. Additional studies should be performed to identify the most reliable treatment for COVID-19.", - "rel_num_authors": 11, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.30.20217364", + "rel_abs": "BACKGROUNDNo definitive treatment exists for Coronavirus Disease 2019 (COVID-19). Honey and Nigella sativa (HNS) have established antiviral, antibacterial, anti-inflammatory and immunomodulatory properties. Hence, we investigated efficacy of HNS against COVID-19. wide\n\nMETHODSWe conducted a multicenter, placebo-controlled, randomized clinical trial at 4 centers in Pakistan. RT-PCR confirmed COVID-19 adults showing moderate or severe disease were enrolled in the study. Patients presenting with multi-organ failure, ventilator support, and chronic diseases (except diabetes mellitus and hypertension) were excluded. Patients were randomly assigned in 1:1 ratio to receive either honey (1 gm/Kg/day) and Nigella sativa seeds (80 mg/Kg/day) or placebo up-to 13 days along with standard care. The outcomes included symptom alleviation, viral clearance, and a 30-day mortality in intention-to-treat population. This trial was registered with ClinicalTrials.gov, NCT04347382.\n\nRESULTSThree hundred and thirteen patients - 210 moderate and 103 severe - underwent randomization from April 30 to July 29, 2020. Among these, 107 were assigned to HNS whereas 103 to placebo for moderate cases. For severe cases, 50 were given HNS and 53 were given placebos. HNS resulted in [~]50% reduction in time taken to alleviate symptoms as compared to placebo (Moderate (4 versus 7 days), Hazard Ratio [HR]: 6.11; 95% Confidence Interval [CI]: 4.23-8.84, P<0.0001 and severe (6 versus 13 days) HR: 4.04; 95% CI, 2.46-6.64, P<0.0001). HNS also cleared the virus 4 days earlier than placebo group in moderate (6 versus 10 days, HR: 5.53; 95% CI: 3.76-8.14, P<0.0001) and severe cases (8.5 versus 12 days, HR: 4.32; 95% CI: 2.62-7.13, P<0.0001). HNS further led to a better clinical score on day 6 with normal activity resumption in 63.6% versus 10.9% among moderate cases (OR: 0.07; 95% CI: 0.03-0.13, P<0.0001) and hospital discharge in 50% versus 2.8% in severe cases (OR: 0.03; 95% CI: 0.01-0.09, P<0.0001). In severe cases, mortality rate was four-fold lower in HNS group than placebo (4% versus 18.87%, OR: 0.18; 95% CI: 0.02-0.92, P=0.029). No HNS-related adverse effects were observed.\n\nCONCLUSIONHNS significantly improved symptoms, viral clearance and mortality in COVID-19 patients. Thus, HNS represents an affordable over the counter therapy and can either be used alone or in combination with other treatments to achieve potentiating effects against COVID-19.\n\nFUNDINGFunded by Smile Welfare Organization, Shaikh Zayed Medical Complex, and Services Institute of Medical Sciences.", + "rel_num_authors": 46, "rel_authors": [ { - "author_name": "Alessandro Rolim Scholze Sr.", - "author_inst": "UENP" + "author_name": "Sohaib Ashraf", + "author_inst": "Shaikh Zayed Medical Complex, Lahore, Pakistan" }, { - "author_name": "Emiliana Cristina Melo", - "author_inst": "UENP" + "author_name": "Shoaib Ashraf", + "author_inst": "Wellman Center for Photomedicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA" }, { - "author_name": "Carina Bortolato Major", - "author_inst": "UENP" + "author_name": "Moneeb Ashraf", + "author_inst": "Kingedward Medical University, Mayo Hospital, Lahore, Pakistan" }, { - "author_name": "Carolina Fordellone Cruz", - "author_inst": "UENP" + "author_name": "Muhammad Ahmad Imran", + "author_inst": "Shaikh Zayed Post-Graduate Medical Institute, Lahore, Pakistan" }, { - "author_name": "Leia Regina Alcantara", - "author_inst": "UENP" + "author_name": "Larab Kalsoom", + "author_inst": "Services Institute of Medical Sciences, Lahore, Pakistan" }, { - "author_name": "Camila Dalcol", - "author_inst": "UENP" + "author_name": "Uzma Nasim Siddiqui", + "author_inst": "Shaikh Zayed Post-Graduate Medical Institute, Lahore, Pakistan" }, { - "author_name": "Fabio Rodrigues Ferreira Seiva", - "author_inst": "UENP" + "author_name": "Iqra Farooq", + "author_inst": "Services Institute of Medial Sciences, Lahore, Pakistan" }, { - "author_name": "Maria de Fatima Mantovani", - "author_inst": "UFPR" + "author_name": "Zaigham Habib", + "author_inst": "Tehsile Head Quarter, Ferozwala, Shaikhupura, Pakistan" + }, + { + "author_name": "Sidra Ashraf", + "author_inst": "University of Veterinary and Animal Sciences Lahore, Pakistan" }, { - "author_name": "Angela Mattei", - "author_inst": "Conselho Regional de Enfermagem do Parana" + "author_name": "Muhammad Ghufran", + "author_inst": "ESACHS (Empresa de Servico Externo de la Asociacion Chilena de Seguridad, Chile" }, { - "author_name": "Henrique Spaulonci Silveira", - "author_inst": "UNESP" + "author_name": "Muhammad Kiwan Akram", + "author_inst": "University of Veterinary adn Animal Sciences, Lahore, Pakistan" }, { - "author_name": "Luiz Gustavo de Almeida Chuffa Sr.", - "author_inst": "UNESP" + "author_name": "Nighat Majeed", + "author_inst": "Services Institute of Medical Sciences, Lahore, Pakistan." + }, + { + "author_name": "Zain ul Abdin", + "author_inst": "Shaikh Zayed Post-Graduate Medical Institute, Lahore, Pakistan." + }, + { + "author_name": "Rutaba Akmal", + "author_inst": "Sahara Medical College, Narowal, Pakistan." + }, + { + "author_name": "Sundas Rafique", + "author_inst": "Kingedward Medical University, Mayo Hospital, Lahore, Pakistan." + }, + { + "author_name": "Khawar Nawaz", + "author_inst": "Sunny Downstate/Kings Country Medical Center, New York, USA" + }, + { + "author_name": "Muhammad Ismail Khalid Yousaf", + "author_inst": "University of Louisville, Kentucky, USA" + }, + { + "author_name": "Sohail Ahmad", + "author_inst": "University of Veterinary and Animal Sciences, Lahore, Pakistan" + }, + { + "author_name": "Muhammad Sarmad Shahab", + "author_inst": "Allied Hospital, Faisalabad Medical University, Faisalabad, Pakistan" + }, + { + "author_name": "Muhammad Faisal Nadeem", + "author_inst": "University of Veterinary and Animal Sciences, Lahore, Pakistan" + }, + { + "author_name": "Abubakar Hilal", + "author_inst": "Shaikh Zayed Post-Graduate Medical Institute, Lahore, Pakistan" + }, + { + "author_name": "Arz Muhammad", + "author_inst": "Shaikh Zayed POST-Graduate Medical Complex, Lahore" + }, + { + "author_name": "Zeeshan Shoukat", + "author_inst": "Shaikh Zayed Post-Graduate Medical Institute, Lahore, Pakistan" + }, + { + "author_name": "Ayesha Khaqan", + "author_inst": "Shaikh Zayed Post-Graduate Medical Institute, Lahore, Pakistan" + }, + { + "author_name": "Kanwal Hayat", + "author_inst": "Shaikh Zayed Post-Graduate Medical Institute, Lahore, Pakistan" + }, + { + "author_name": "Shahroz Arshad", + "author_inst": "Shaukat Khanum Hospital, Lahore, Pakistan" + }, + { + "author_name": "Muhammad Hassan", + "author_inst": "Shaikh Zayed Post-Graduate Medical Institute, Lahore, Pakistan" + }, + { + "author_name": "Abeer bin Awais", + "author_inst": "Shaikh Zayed Post-Graduate Medical Complex, Lahore, Pakistan" + }, + { + "author_name": "Abdur Rehman Virk", + "author_inst": "Shaikh Zayed post-Graduate Medical Institute, Lahore, Pakistan." + }, + { + "author_name": "Ammara Ahmad", + "author_inst": "Shaikh Zayed Post-Graduate Medical Institute, Lahore, Pakistan" + }, + { + "author_name": "Tayyab Mughal", + "author_inst": "Shaikh Zayed Post-Graduate Medical Institute, Lahore, Pakistan" + }, + { + "author_name": "Muhammad Umer", + "author_inst": "Shaikh Zayed Post-Graduate Medical Institute, Lahore, Pakistan" + }, + { + "author_name": "Muhammad Suhail", + "author_inst": "Shaikh Zayed Post-Graduate Medical Institute, Lahore, Pakistan" + }, + { + "author_name": "Sibgha Zulfiqar", + "author_inst": "Shaikh Zayed Post-Graduate Medical Institute, Lahore, Pakistan" + }, + { + "author_name": "Saulat Sarfraz", + "author_inst": "Shaikh Zayed Post-Graduate Medical Institute, Lahore, Pakistan" + }, + { + "author_name": "Imran Anwar", + "author_inst": "Shaikh Zayed Post-Graduate Medical Institution, Lahore, Pakistan" + }, + { + "author_name": "Ayesha Humayun", + "author_inst": "Shaikh Zayed Post-Graduate Medical Institute, Lahore, Pakistan" + }, + { + "author_name": "Muhammad Azam", + "author_inst": "University of Veterinary and Animal Sciences, Lahore, Pakistan" + }, + { + "author_name": "Hui Zheng", + "author_inst": "Massachusetts General Hospital, Boston, MA, USA" + }, + { + "author_name": "Amber Malik", + "author_inst": "Evercare Hospital, Lahore, Pakistan" + }, + { + "author_name": "Mahmood Ayyaz", + "author_inst": "Services Institute of Medical Sciences, Lahore, Pakistan." + }, + { + "author_name": "Ali Ahmad", + "author_inst": "Centre Hospitalier Universitaire (CHU) Sainte Justin/University of Montreal, Montreal, Canada." + }, + { + "author_name": "Talha Mahmud", + "author_inst": "Shaikh Zayed Post-Graduate Medical Institute, Lahore, Pakistan" + }, + { + "author_name": "Qazi Abdul Saboor", + "author_inst": "Shaikh Zayed Post-Graduate Medical Institute, Lahore, Pakistan" + }, + { + "author_name": "Muhammad Ashraf", + "author_inst": "University of Veterinary and Animal Sciences, Lahore, Pakistan" + }, + { + "author_name": "Mateen Izhar", + "author_inst": "Shaikh Zayed Post-Graduate Medical Institute, Lahore, Pakistan" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1094681,43 +1095784,99 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.10.30.20223156", - "rel_title": "COVID-19 Pandemic Among Immigrant Latinx Farmworker and Non-farmworker Families: A Rural-Urban Comparison of Economic, Educational, Healthcare, and Immigration Concerns", + "rel_doi": "10.1101/2020.11.02.364729", + "rel_title": "Identification of Cross-Reactive CD8+ T Cell Receptors with High Functional Avidity to a SARS-CoV-2 Immunodominant Epitope and Its Natural Mutant Variants", "rel_date": "2020-11-03", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.30.20223156", - "rel_abs": "COVID-19 has highlighted social and health injustices in the US. Structural inequalities have increased the likelihood of immigrants contracting COVID-19, by being essential workers and through poverty that forces this population to continue working. Rural and urban immigrant families may face different concerns. Using a telephone survey in May 2020 of 105 Latinx families in an existing study, quantitative and qualitative data were gathered on work and household economics, childcare and education, healthcare, and community climate. Analyses show that, although rural and urban groups experienced substantial economic effects, impacts were more acute for urban families. Rural workers reported fewer workplace protective measures for COVID-19. For both groups, fear and worry, particularly about finances and children, dominated reports of their situations with numerous reports of experiencing stress and anxiety. The experience of the pandemic is interpreted as an example of contextual vulnerability of a population already experiencing structural violence through social injustice.", - "rel_num_authors": 6, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2020.11.02.364729", + "rel_abs": "Despite the growing knowledge of T cell responses and their epitopes in COVID-19 patients, there is a lack of detailed characterizations for T cell-antigen interactions and T cell functions. Using a peptide library predicted with HLA class I-restriction, specific CD8+ T cell responses were identified in over 75% of COVID-19 convalescent patients. Among the 15 SARS-CoV-2 epitopes identified from the S and N proteins, N361-369 (KTFPPTEPK) was the most dominant epitope. Importantly, we discovered 2 N361-369-specific T cell receptors (TCRs) with high functional avidity, and they exhibited complementary cross-reactivity to reported N361-369 mutant variants. In dendritic cells (DCs) and the lung organoid model, we found that the N361-369 epitope could be processed and endogenously presented to elicit the activation and cytotoxicity of CD8+ T cells ex vivo. Our study evidenced potential mechanisms of cellular immunity to SARS-CoV-2, illuminating natural ways of viral clearance with high relevancy in the vaccine development.", + "rel_num_authors": 20, "rel_authors": [ { - "author_name": "Sara A. Quandt", - "author_inst": "Wake Forest School of Medicine" + "author_name": "Chao Hu", + "author_inst": "1Department of Immunology, College of Basic Medicine, Chongqing Medical University, 1 Yixueyuan Road, Yuzhong District, Chongqing, 400016, China 2Chongqing Key " }, { - "author_name": "Natalie J. LaMonto", - "author_inst": "Lawrence University" + "author_name": "Meiying Shen", + "author_inst": "Department of Breast Surgery, Harbin Medical University Cancer Hospital, 150 Haping Road, Nangang District, Harbin, 150081, China" }, { - "author_name": "Dana C. Mora", - "author_inst": "Wake Forest School of Medicine" + "author_name": "XiaoJian Han", + "author_inst": "Chongqing Medical University" }, { - "author_name": "Jennifer W. Talton", - "author_inst": "Wake Forest School of Medicine" + "author_name": "Qian Chen", + "author_inst": "1Department of Immunology, College of Basic Medicine, Chongqing Medical University, 1 Yixueyuan Road, Yuzhong District, Chongqing, 400016, China 2Chongqing Key " }, { - "author_name": "Paul J. Laurienti", - "author_inst": "Wake Forest School of Medicine" + "author_name": "Luo Li", + "author_inst": "1Department of Immunology, College of Basic Medicine, Chongqing Medical University, 1 Yixueyuan Road, Yuzhong District, Chongqing, 400016, China 2Chongqing Key " }, { - "author_name": "Thomas A. Arcury", - "author_inst": "Wake Forest School of Medicine" + "author_name": "Siyin Chen", + "author_inst": "1Department of Immunology, College of Basic Medicine, Chongqing Medical University, 1 Yixueyuan Road, Yuzhong District, Chongqing, 400016, China 2Chongqing Key " + }, + { + "author_name": "Jing Zhang", + "author_inst": "1Department of Immunology, College of Basic Medicine, Chongqing Medical University, 1 Yixueyuan Road, Yuzhong District, Chongqing, 400016, China 2Chongqing Key " + }, + { + "author_name": "Fengxia Gao", + "author_inst": "1Department of Immunology, College of Basic Medicine, Chongqing Medical University, 1 Yixueyuan Road, Yuzhong District, Chongqing, 400016, China 2Chongqing Key " + }, + { + "author_name": "Wang Wang", + "author_inst": "1Department of Immunology, College of Basic Medicine, Chongqing Medical University, 1 Yixueyuan Road, Yuzhong District, Chongqing, 400016, China 2Chongqing Key " + }, + { + "author_name": "Yingming Wang", + "author_inst": "1Department of Immunology, College of Basic Medicine, Chongqing Medical University, 1 Yixueyuan Road, Yuzhong District, Chongqing, 400016, China 2Chongqing Key " + }, + { + "author_name": "Tingting Li", + "author_inst": "1Department of Immunology, College of Basic Medicine, Chongqing Medical University, 1 Yixueyuan Road, Yuzhong District, Chongqing, 400016, China 2Chongqing Key " + }, + { + "author_name": "Shenglong Li", + "author_inst": "1Department of Immunology, College of Basic Medicine, Chongqing Medical University, 1 Yixueyuan Road, Yuzhong District, Chongqing, 400016, China 2Chongqing Key " + }, + { + "author_name": "Jingjing Huang", + "author_inst": "1Department of Immunology, College of Basic Medicine, Chongqing Medical University, 1 Yixueyuan Road, Yuzhong District, Chongqing, 400016, China 2Chongqing Key " + }, + { + "author_name": "Jianwei Wang", + "author_inst": "1Department of Immunology, College of Basic Medicine, Chongqing Medical University, 1 Yixueyuan Road, Yuzhong District, Chongqing, 400016, China 2Chongqing Key " + }, + { + "author_name": "Ju Zhu", + "author_inst": "1Department of Immunology, College of Basic Medicine, Chongqing Medical University, 1 Yixueyuan Road, Yuzhong District, Chongqing, 400016, China 2Chongqing Key " + }, + { + "author_name": "Dan Chen", + "author_inst": "4Department of Cardiothoracic Surgery, The First Affiliated Hospital of Chongqing Medical University, 1 Youyi Road, Yuzhong District, Chongqing, 400016, China 5" + }, + { + "author_name": "Qingchen Wu", + "author_inst": "4Department of Cardiothoracic Surgery, The First Affiliated Hospital of Chongqing Medical University, 1 Youyi Road, Yuzhong District, Chongqing, 400016, China 5" + }, + { + "author_name": "Kun Tao", + "author_inst": "1Department of Immunology, College of Basic Medicine, Chongqing Medical University, 1 Yixueyuan Road, Yuzhong District, Chongqing, 400016, China 2Chongqing Key " + }, + { + "author_name": "Da Pang", + "author_inst": "Department of Breast Surgery, Harbin Medical University Cancer Hospital, 150 Haping Road, Nangang District, Harbin, 150081, China" + }, + { + "author_name": "Aishun Jin", + "author_inst": "1Department of Immunology, College of Basic Medicine, Chongqing Medical University, 1 Yixueyuan Road, Yuzhong District, Chongqing, 400016, China 2Chongqing Key " } ], "version": "1", - "license": "cc_by_nc_nd", - "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "license": "cc_by_nc", + "type": "new results", + "category": "immunology" }, { "rel_doi": "10.1101/2020.11.03.366138", @@ -1096415,79 +1097574,71 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2020.10.27.20220897", - "rel_title": "The effect of eviction moratoriums on the transmission of SARS-CoV-2", + "rel_doi": "10.1101/2020.10.27.20221028", + "rel_title": "Remote fingerstick blood collection for SARS-CoV-2 antibody testing", "rel_date": "2020-11-01", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.27.20220897", - "rel_abs": "Massive unemployment during the COVID-19 pandemic could result in an eviction crisis in US cities. Here we model the effect of evictions on SARS-CoV-2 epidemics, simulating viral transmission within and among households in a theoretical metropolitan area. We recreate a range of urban epidemic trajectories and project the course of the epidemic under two counterfactual scenarios, one in which a strict moratorium on evictions is in place and enforced, and another in which evictions are allowed to resume at baseline or increased rates. We find, across scenarios, that evictions lead to significant increases in infections. Applying our model to Philadelphia using locally-specific parameters shows that the increase is especially profound in models that consider realistically heterogenous cities in which both evictions and contacts occur more frequently in poorer neighborhoods. Our results provide a basis to assess municipal eviction moratoria and show that policies to stem evictions are a warranted and important component of COVID-19 control.", - "rel_num_authors": 15, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.27.20221028", + "rel_abs": "The rapid worldwide spread of SARS-CoV-2 infection has propelled the accelerated development of serological tests that can detect anti-SARS-CoV-2 antibodies. These have been used for studying the prevalence and spread of infection in different populations, helping establish a recent diagnosis of COVID-19, and will likely be used to confirm humoral immunity after infection or vaccination. However, nearly all lab-based high-throughput SARS-CoV-2 serological assays require a serum sample from venous blood draw, limiting their applications and scalability. Here, we present a method that enables large scale SARS-CoV-2 serological studies by combining self or office collection of fingerprick blood with a volumetric absorptive microsampling device (Mitra, Neoteryx, LLC) with a high-throughput electrochemiluminescence-based SARS-CoV-2 total antibody assay (Roche Elecsys, Roche Diagnostics, Inc.) that is EUA approved for use on serum samples and widely used by clinical laboratories around the world. We found that the Roche Elecsys assay has a high dynamic range that allows for accurate detection of SARS-CoV-2 antibodies in serum samples diluted 1:20 as well as contrived dried blood extracts. Extracts of dried blood from Mitra devices acquired in a community seroprevalence study showed near identical sensitivity and specificity in detection of SARS-CoV-2 antibodies as compared to neat sera using predefined thresholds for each specimen type. Overall, this study affirms the use of Mitra dried blood collection device with the Roche Elecsys SARS-CoV-2 total antibody assay for remote or at-home testing as well as large-scale community seroprevalence studies.", + "rel_num_authors": 13, "rel_authors": [ { - "author_name": "Anjalika Nande", - "author_inst": "Program for Evolutionary Dynamics, Harvard University, Cambridge, MA, 02138" - }, - { - "author_name": "Justin Sheen", - "author_inst": "Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania, Philadelphia, PA 19104" - }, - { - "author_name": "Emma L Walters", - "author_inst": "Department of Urban and Regional Planning, University of Illinois at Urbana-Champaign, Champaign, IL 61820" + "author_name": "Wilfredo F Garcia-Beltran", + "author_inst": "Massachusetts General Hospital, Department of Pathology" }, { - "author_name": "Brennan Klein", - "author_inst": "Northeastern University Network Science Institute" + "author_name": "Tyler E. Miller", + "author_inst": "Massachusetts General Hospital, Department of Pathology" }, { - "author_name": "Matteo Chinazzi", - "author_inst": "Northeastern University Network Science Institute" + "author_name": "Grace Kirkpatrick", + "author_inst": "Massachusetts General Hospital, Department of Pathology" }, { - "author_name": "Andrei Gheorghe", - "author_inst": "Program for Evolutionary Dynamics, Harvard University, Cambridge, MA, 02138" + "author_name": "Andrea Nixon", + "author_inst": "Massachusetts General Hospital, Department of Pathology" }, { - "author_name": "Ben Adlam", - "author_inst": "Program for Evolutionary Dynamics, Harvard University, Cambridge, MA, 02138" + "author_name": "Michael G. Astudillo", + "author_inst": "Massachusetts General Hospital, Department of Pathology" }, { - "author_name": "Julianna Shinnick", - "author_inst": "Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania, Philadelphia, PA 19104" + "author_name": "Diane Yang", + "author_inst": "Massachusetts General Hospital, Department of Pathology" }, { - "author_name": "Maria Florencia Tejeda", - "author_inst": "Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania, Philadelphia, PA 19104" + "author_name": "Lisa M. Mahanta", + "author_inst": "Mass General Brigham Biobank" }, { - "author_name": "Samuel V Scarpino", - "author_inst": "Northeastern University Network Science Institute" + "author_name": "Mandakolathur Murali", + "author_inst": "Massachusetts General Hospital, Department of Pathology" }, { - "author_name": "Alessandro Vespignani", - "author_inst": "Northeastern University Network Science Institute" + "author_name": "Anand Dighe", + "author_inst": "Massachusetts General Hospital, Department of Pathology" }, { - "author_name": "Andrew J Greenlee", - "author_inst": "Department of Urban and Regional Planning, University of Illinois at Urbana-Champaign, Champaign, IL 61820" + "author_name": "Jochen Lennerz", + "author_inst": "Massachusetts General Hospital, Department of Pathology" }, { - "author_name": "Daniel Schneider", - "author_inst": "Department of Urban and Regional Planning, University of Illinois at Urbana-Champaign, Champaign, IL 61820" + "author_name": "Julia Thierauf", + "author_inst": "Massachusetts General Hospital, Department of Pathology" }, { - "author_name": "Michael Z. Levy", - "author_inst": "Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104" + "author_name": "Vivek Naranbhai", + "author_inst": "Massachusetts General Hospital, Department of Pathology" }, { - "author_name": "Alison L Hill", - "author_inst": "Institute for Computational Medicine, Johns Hopkins University, Baltimore, MD 21218" + "author_name": "A. John Iafrate", + "author_inst": "Massachusetts General Hospital, Department of Pathology" } ], "version": "1", - "license": "cc_by", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "pathology" }, { "rel_doi": "10.1101/2020.10.28.20221226", @@ -1097885,57 +1099036,45 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.10.27.20220970", - "rel_title": "A Machine Learning Study of 534,023 Medicare Beneficiaries with COVID-19: Implications for Personalized Risk Prediction", + "rel_doi": "10.1101/2020.10.28.20221333", + "rel_title": "Clinical Suspicion of COVID-19 in Nursing Home residents: symptoms and mortality risk factors", "rel_date": "2020-10-30", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.27.20220970", - "rel_abs": "BackgroundGlobal demand for a COVID-19 vaccine will exceed the initial limited supply. Identifying individuals at highest risk of COVID-19 death may help allocation prioritization efforts. Personalized risk prediction that uses a broad range of comorbidities requires a cohort size larger than that reported in prior studies.\n\nMethodsMedicare claims data was used to identify patients age 65 years or older with diagnosis of COVID-19 between April 1, 2020 and August 31, 2020. Demographic characteristics, chronic medical conditions, and other patient risk factors that existed before the advent of COVID-19 were identified. A random forest model was used to empirically explore factors associated with COVID-19 death. The independent impact of factors identified were quantified using multivariate logistic regression with random effects.\n\nResultsWe identified 534,023 COVID-19 patients of whom 38,066 had an inpatient death. Demographic characteristics associated with COVID-19 death included advanced age (85 years or older: aOR: 2.07; 95% CI, 1.99-2.16), male sex (aOR, 1.88; 95% CI, 1.82-1.94), and non-white race (Hispanic: aOR, 1.74; 95% CI, 1.66-1.83). Leading comorbidities associated with COVID-19 mortality included sickle cell disease (aOR, 1.73; 95% CI, 1.21-2.47), chronic kidney disease (aOR, 1.32; 95% CI, 1.29-1.36), leukemias and lymphomas (aOR, 1.22; 95% CI, 1.14-1.30), heart failure (aOR, 1.19; 95% CI, 1.16-1.22), and diabetes (aOR, 1.18; 95% CI, 1.15-1.22).\n\nConclusionsWe created a personalized risk prediction calculator to identify candidates for early vaccine and therapeutics allocation (www.predictcovidrisk.com). These findings may be used to protect those at greatest risk of death from COVID-19.", - "rel_num_authors": 10, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.28.20221333", + "rel_abs": "ObjectivesTo describe symptomatology, mortality and risk factors for mortality in a large group of Dutch nursing home (NH) residents with clinically-suspected COVID-19 who were tested with a Reverse Transcription Polymerase Chain Reaction (RT-PCR) test.\n\nDesignProspective cohort study.\n\nSetting and participantsResidents of Dutch NHs with clinically-suspected COVID-19 and who received RT-PCR test.\n\nMethodsWe collected data of NH residents with clinically-suspected COVID-19, via electronic health records between March 18th and May 13th, 2020. Registration was performed on diagnostic status (confirmed (COVID-19+)/ruled out (COVID-19-)) and symptomatology (typical and atypical symptoms). Information on mortality and risk factors for mortality were extracted from usual care data.\n\nResultsIn our sample of residents with clinically-suspected COVID-19 (N=4007), COVID-19 was confirmed in 1538 residents (38%). Although, symptomatology overlapped between residents with COVID-19+ and COVID-19-, those with COVID-19+ were three times more likely to die within 30 days (hazard ratio (HR), 3{middle dot}1; 95% CI, 2{middle dot}7 to 3{middle dot}6). Within this group, mortality was higher for men than for women (HR, 1{middle dot}8; 95%, 1{middle dot}5-2{middle dot}2) and we observed a higher mortality for residents with dementia, reduced kidney function, and Parkinsons Disease, even when corrected for age, gender, and comorbidities.\n\nConclusions and implicationsAbout 40% of the residents with clinically-suspected COVID-19 actually had COVID-19, based on the RT-PCR test. Despite an overlap in symptomatology, mortality rate was three times higher for residents with COVID-19+. This emphasizes the importance of using low-threshold testing in NH residents which is an essential prerequisite to using limited personal protective equipment and isolation measures efficiently.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Chen Dun", - "author_inst": "Johns Hopkins University School of Medicine" - }, - { - "author_name": "Christi Walsh", - "author_inst": "Johns Hopkins University School of Medicine" - }, - { - "author_name": "Sunjae Bae", - "author_inst": "Johns Hopkins University School of Medicine" - }, - { - "author_name": "Amesh Adalja", - "author_inst": "Johns Hopkins University Center for Health Security" + "author_name": "Jeanine J.S. Rutten", + "author_inst": "Department of Medicine for Older People, Amsterdam Public Health Research Institute, Amsterdam University Medical Center" }, { - "author_name": "Eric Toner", - "author_inst": "Johns Hopkins University Center for Health Security" + "author_name": "Anouk M. van Loon", + "author_inst": "Amsterdam UMC" }, { - "author_name": "Timothy A Lash", - "author_inst": "West Health Institute" + "author_name": "Janine van Kooten", + "author_inst": "Department of Medicine for Older People, Amsterdam Public Health Research Institute, Amsterdam University Medical Center" }, { - "author_name": "Farah Hashim", - "author_inst": "Johns Hopkins University School of Medicine" + "author_name": "Laura W. van Buul", + "author_inst": "Department of Medicine for Older People, Amsterdam Public Health Research Institute, Amsterdam University Medical Center" }, { - "author_name": "Joseph Paturzo", - "author_inst": "Johns Hopkins University School of Medicine" + "author_name": "Karlijn J. Joling", + "author_inst": "Department of Medicine for Older People, Amsterdam Public Health Research Institute, Amsterdam University Medical Center" }, { - "author_name": "Dorry L Segev", - "author_inst": "Johns Hopkins University School of Medicine" + "author_name": "Martin Smalbrugge", + "author_inst": "Department of Medicine for Older People, Amsterdam Public Health Research Institute, Amsterdam University Medical Center" }, { - "author_name": "Martin A Makary", - "author_inst": "Johns Hopkins University School of Medicine" + "author_name": "Cees M.P.M. Hertogh", + "author_inst": "Department of Medicine for Older People, Amsterdam Public Health Research Institute, Amsterdam University Medical Center" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1100163,551 +1101302,135 @@ "category": "biophysics" }, { - "rel_doi": "10.1101/2020.10.26.356014", - "rel_title": "COVID-19 Disease Map, a computational knowledge repository of SARS-CoV-2 virus-host interaction mechanisms", + "rel_doi": "10.1101/2020.10.28.358614", + "rel_title": "Induced pulmonary comorbidities render CD-1 mice sensitive to SARS-CoV-2", "rel_date": "2020-10-28", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.10.26.356014", - "rel_abs": "We describe a large-scale community effort to build an open-access, interoperable, and computable repository of COVID-19 molecular mechanisms - the COVID-19 Disease Map. We discuss the tools, platforms, and guidelines necessary for the distributed development of its contents by a multi-faceted community of biocurators, domain experts, bioinformaticians, and computational biologists. We highlight the role of relevant databases and text mining approaches in enrichment and validation of the curated mechanisms. We describe the contents of the Map and their relevance to the molecular pathophysiology of COVID-19 and the analytical and computational modelling approaches that can be applied for mechanistic data interpretation and predictions. We conclude by demonstrating concrete applications of our work through several use cases and highlight new testable hypotheses.", - "rel_num_authors": 133, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.10.28.358614", + "rel_abs": "Severe manifestations of COVID-19 are mostly restricted to people with comorbidities. Here we report that induced mild pulmonary morbidities render SARS-CoV-2-refractive CD-1 mice to be susceptible to this virus. Specifically, SARS-CoV-2 infection after application of low-doses of the acute-lung-injury stimulants bleomycin or ricin caused a severe disease in CD-1 mice, manifested by sustained body weight loss and mortality rates of >50%. Further studies revealed markedly higher levels of viral RNA in the lungs, heart and serum of low-dose-ricin pretreated, as compared to non-pretreated mice. Notably, the deleterious effects of SARS-CoV-2 infection were effectively alleviated by passive transfer of polyclonal or monoclonal antibodies generated against SARS-CoV-2 RBD. Thus, viral cell entry in the sensitized mice seems to involve viral RBD binding, albeit by a mechanism other than the canonical ACE2-mediated uptake route. In summary, we present a novel mice-based animal model for the study of comorbidity-dependent severe COVID-19.", + "rel_num_authors": 29, "rel_authors": [ { - "author_name": "Marek Ostaszewski", - "author_inst": "Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg" - }, - { - "author_name": "Anna Niarakis", - "author_inst": "Department of Biology, Univ. Evry, University of Paris-Saclay, GenHotel, Genopole, 91025, Evry, France" - }, - { - "author_name": "Alexander Mazein", - "author_inst": "Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg" - }, - { - "author_name": "Inna Kuperstein", - "author_inst": "Institut Curie, PSL Research University, Paris, France." - }, - { - "author_name": "Robert Phair", - "author_inst": "Integrative Bioinformatics, Inc., 346 Paul Ave, Mountain View, CA, USA" - }, - { - "author_name": "Aurelio Orta-Resendiz", - "author_inst": "Institut Pasteur, HIV, Inflammation and Persistence Unit, Paris, France" - }, - { - "author_name": "Vidisha Singh", - "author_inst": "Laboratoire Europeen de Recherche pour la Polyarthrite Rhumatoide - Genhotel, Univ Evry, Universite Paris-Saclay, 2, rue Gaston Cremieux, 91057 EVRY-GENOPOLE ce" - }, - { - "author_name": "Sara Sadat Aghamiri", - "author_inst": "Inserm- Institut national de la sante et de la recherche medicale. Saint-Louis Hospital 1 avenue Claude Vellefaux Pavillon Bazin 75475 Paris" - }, - { - "author_name": "Marcio Luis Acencio", - "author_inst": "Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg" - }, - { - "author_name": "Enrico Glaab", - "author_inst": "Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg" - }, - { - "author_name": "Andreas Ruepp", - "author_inst": "Institute of Experimental Genetics (IEG), Helmholtz Zentrum Munchen-German Research Center for Environmental Health (GmbH), Ingolstadter Landstrasse 1, D-85764 " - }, - { - "author_name": "Gisela Fobo", - "author_inst": "Institute of Experimental Genetics (IEG), Helmholtz Zentrum Munchen-German Research Center for Environmental Health (GmbH), Ingolstadter Landstrasse 1, D-85764 " - }, - { - "author_name": "Corinna Montrone", - "author_inst": "Institute of Experimental Genetics (IEG), Helmholtz Zentrum Munchen-German Research Center for Environmental Health (GmbH), Ingolstadter Landstrasse 1, D-85764 " - }, - { - "author_name": "Barbara Brauner", - "author_inst": "Institute of Experimental Genetics (IEG), Helmholtz Zentrum Munchen-German Research Center for Environmental Health (GmbH), Ingolstadter Landstrasse 1, D-85764 " - }, - { - "author_name": "Goar Frishman", - "author_inst": "Institute of Experimental Genetics (IEG), Helmholtz Zentrum Munchen-German Research Center for Environmental Health (GmbH), Ingolstadter Landstrasse 1, D-85764 " - }, - { - "author_name": "Julia Somers", - "author_inst": "Oregong Health & Sciences Univerity; Department of Molecular and Medical Genetics; 3222 SW Research Drive, Portland, Oregon, U.S.A 97239" - }, - { - "author_name": "Matti Hoch", - "author_inst": "Department of Systems Biology and Bioinformatics, University of Rostock, 18051 Rostock, Germany" - }, - { - "author_name": "Shailendra Kumar Gupta", - "author_inst": "Department of Systems Biology and Bioinformatics, University of Rostock, 18051 Rostock, Germany" - }, - { - "author_name": "Julia Scheel", - "author_inst": "Department of Systems Biology and Bioinformatics, University of Rostock, 18051 Rostock, Germany" - }, - { - "author_name": "Hanna Borlinghaus", - "author_inst": "Department of Computer and Information Science, University of Konstanz, Konstanz, Germany" - }, - { - "author_name": "Tobias Czauderna", - "author_inst": "Monash University, Faculty of Information Technology, Department of Human-Centred Computing, Wellington Rd, Clayton VIC 3800, Australia" - }, - { - "author_name": "Falk Schreiber", - "author_inst": "Department of Computer and Information Science, University of Konstanz, Konstanz, Germany" - }, - { - "author_name": "Arnau Montagud", - "author_inst": "Barcelona Supercomputing Center (BSC), Barcelona, Spain" - }, - { - "author_name": "Miguel Ponce de Leon", - "author_inst": "Barcelona Supercomputing Center (BSC), Barcelona, Spain" - }, - { - "author_name": "Akira Funahashi", - "author_inst": "Keio University, Department of Biosciences and Informatics, 3-14-1 Hiyoshi Kouhoku-ku Yokohama Japan 223-8522" - }, - { - "author_name": "Yusuke Hiki", - "author_inst": "Keio University, Department of Biosciences and Informatics, 3-14-1 Hiyoshi Kouhoku-ku Yokohama Japan 223-8522" - }, - { - "author_name": "Noriko Hiroi", - "author_inst": "Sanyo-Onoda City University, Faculty of Pharmaceutical Sciences, University St.1-1-1, Yamaguchi, Japan 756-0884" - }, - { - "author_name": "Takahiro G Yamada", - "author_inst": "Keio University, Department of Biosciences and Informatics, 3-14-1 Hiyoshi Kouhoku-ku Yokohama Japan 223-8522" - }, - { - "author_name": "Andreas Drager", - "author_inst": "Computational Systems Biology of Infections and Antimicrobial-Resistant Pathogens, Institute for Bioinformatics and Medical Informatics (IBMI), University of Tu" - }, - { - "author_name": "Alina Renz", - "author_inst": "Computational Systems Biology of Infections and Antimicrobial-Resistant Pathogens, Institute for Bioinformatics and Medical Informatics (IBMI), University of Tu" - }, - { - "author_name": "Muhammad Naveez", - "author_inst": "Riga Technical University, Institute of Applied Computer Systems,1 Kalku Street, LV-1658 Riga, Latvia" - }, - { - "author_name": "Zsolt Bocskei", - "author_inst": "Sanofi R&D Translational Sciences" - }, - { - "author_name": "Daniela Bornigen", - "author_inst": "Bioinformatics Core Facility, Universitaetsklinikum Hamburg-Eppendorf, Martinistrasse 52, 20246 Hamburg, Germany" - }, - { - "author_name": "Liam Fergusson", - "author_inst": "The University of Edinburgh, Royal (Dick) School of Veterinary Medicine, Easter Bush Campus, Midlothian, EH25 9RG" - }, - { - "author_name": "Marta Conti", - "author_inst": "Faculty of Mathematics and Natural Sciences, University of Bonn, Bonn, Germany" - }, - { - "author_name": "Marius Rameil", - "author_inst": "University of Bonn, Germany" - }, - { - "author_name": "Vanessa Nakonecnij", - "author_inst": "Faculty of Mathematics and Natural Sciences, University of Bonn, Bonn, Germany" - }, - { - "author_name": "Jakob Vanhoefer", - "author_inst": "Faculty of Mathematics and Natural Sciences, University of Bonn, Bonn, Germany" - }, - { - "author_name": "Leonard Schmiester", - "author_inst": "Helmholtz Zentrum Munchen - German Research Center for Environmental Health, Institute of Computational Biology, 85764 Neuherberg, Germany" - }, - { - "author_name": "Muying Wang", - "author_inst": "Department of Chemical Engineering, University of Pittsburgh" - }, - { - "author_name": "Emily E Ackerman", - "author_inst": "University of Pittsburgh, Department of Chemical and Petroleum Engineering" - }, - { - "author_name": "Jason E Shoemaker", - "author_inst": "Dept. of Chemical & Petroleum Engineering, University of Pittsburgh" - }, - { - "author_name": "Jeremy Zucker", - "author_inst": "Pacific Northwest National Laboratory" - }, - { - "author_name": "Kristie L Oxford", - "author_inst": "Pacific Northwest National Laboratory" - }, - { - "author_name": "Jeremy Teuton", - "author_inst": "Pacific Northwest National Laboratory" - }, - { - "author_name": "Ebru Kocakaya", - "author_inst": "Ankara University, Stem Cell Institute, Ceyhun Atif Kansu St. No: 169 06520 Cevizlidere/ANKARA/TURKEY" - }, - { - "author_name": "Gokce Yagmur Summak", - "author_inst": "Ankara University, Stem Cell Institute, Ceyhun Atif Kansu St. No: 169 06520 Cevizlidere/ANKARA/TURKEY" - }, - { - "author_name": "Kristina Hanspers", - "author_inst": "Institute of Data Science and Biotechnology, Gladstone Institutes, San Francisco, CA 94158" - }, - { - "author_name": "Martina Kutmon", - "author_inst": "Department of Bioinformatics - BiGCaT, NUTRIM, Maastricht University, Maastricht, The Netherlands" - }, - { - "author_name": "Susan Coort", - "author_inst": "Maastricht University, NUTRIM, Bioinformatics-BiGCaT, PO Box 616, 6200 MD, Maastricht, the Netherlands" - }, - { - "author_name": "Lars Eijssen", - "author_inst": "Department of Bioninformatics-BiGCaT, NUTRIM, Maastricht University, Universiteitssingel 60, 6229 ER Maastricht, The Netherlands" - }, - { - "author_name": "Friederike Ehrhart", - "author_inst": "Maastricht University, Department of Bioinformatics, NUTRIM, Universiteitssingel 60; 6229 ER Maastricht; The Netherlands" - }, - { - "author_name": "Rex D. A. B.", - "author_inst": "Center for Systems Biology and Molecular Medicine, Yenepoya (Deemed to be University), Mangalore 575018, India" - }, - { - "author_name": "Denise Slenter", - "author_inst": "Department of Bioinformatics-BiGCaT, NUTRIM, Maastricht University, Maastricht, The Netherlands" - }, - { - "author_name": "Marvin Martens", - "author_inst": "Department of Bioinformatics - BiGCaT, NUTRIM, Maastricht University, 6229 ER Maastricht, The Netherlands" - }, - { - "author_name": "Nhung Pham", - "author_inst": "Maastricht University, NUTRIM, Bioinformatics-BiGCaT, PO Box 616, 6200 MD, Maastricht, the Netherlands" - }, - { - "author_name": "Robin Haw", - "author_inst": "Adaptive Oncology, Ontario Institute for Cancer Research, MaRS Centre, 661 University Avenue, Suite 510, Toronto, Ontario, Canada M5G 0A3" - }, - { - "author_name": "Bijay Jassal", - "author_inst": "Ontario Institute for Cancer Research (OICR), 661 University Ave Suite 510, Toronto, ON M5G 0A3, Canada" - }, - { - "author_name": "Lisa Matthews", - "author_inst": "NYU Grossman School of Medicine, New York NY 10016 USA" - }, - { - "author_name": "Marija Orlic-Milacic", - "author_inst": "Ontario Institute for Cancer Research, Department of Computational Biology, MaRS Centre, South Tower, 661 University Avenue, Suite 500, Toronto, Ontario, Canada" - }, - { - "author_name": "Andrea Senff-Ribeiro", - "author_inst": "Ontario Institute for Cancer Research (OICR) (Canada)" - }, - { - "author_name": "Karen Rothfels", - "author_inst": "Ontario Institute for Cancer Research, Department of Computational Biology, MaRS Centre, South Tower, 661 University Avenue, Suite 500, Toronto, Ontario, Canada" - }, - { - "author_name": "Veronica Shamovsky", - "author_inst": "NYU Langone Medical Center, New York, USA" - }, - { - "author_name": "Ralf Stephan", - "author_inst": "Ontario Institute for Cancer Research, MaRS Centre, 661 University Ave, Suite 510, Toronto, Ontario, Canada" - }, - { - "author_name": "Cristoffer Sevilla", - "author_inst": "EMBL-EBI, Molecular Systems, Wellcome Genome Campus, Hinxton, Cambridgeshire, CB10 1SD" - }, - { - "author_name": "Thawfeek Mohamed Varusai", - "author_inst": "Reactome, EMBL-EBI, Cambridge, UK" - }, - { - "author_name": "Jean-Marie Ravel", - "author_inst": "University of Lorraine, INSERM UMR_S 1256, Nutrition, Genetics, and Environmental Risk Exposure (NGERE), Faculty of Medicine of Nancy, F-54000 Nancy, France." - }, - { - "author_name": "Vera Ortseifen", - "author_inst": "Senior Research Group in Genome Research of Industrial Microorganisms, Center for Biotechnology, Bielefeld University, Universitaetsstrasse 27, 33615 Bielefeld," - }, - { - "author_name": "Silvia Marchesi", - "author_inst": "Uppsala University - Sweden" - }, - { - "author_name": "Piotr Gawron", - "author_inst": "Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg" - }, - { - "author_name": "Ewa Smula", - "author_inst": "Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg" - }, - { - "author_name": "Laurent Heirendt", - "author_inst": "Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg" - }, - { - "author_name": "Venkata Satagopam", - "author_inst": "Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg" - }, - { - "author_name": "Guanming Wu", - "author_inst": "Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University, 3181 S.W. Sam Jackson Park Road, Portland, OR 97239-3098, USA" - }, - { - "author_name": "Anders Riutta", - "author_inst": "Gladstone Institutes, Institute for Data Science and Biotechnology, 1650 Owens St., San Francisco, CA 94131, USA" - }, - { - "author_name": "Martin Golebiewski", - "author_inst": "Heidelberg Institute for Theoretical Studies (HITS), Schloss-Wolfsbrunnenweg 35, D-69118 Heidelberg (Germany)" - }, - { - "author_name": "Stuart Owen", - "author_inst": "The University of Manchester, Department of Computer Science, Oxford Road, Manchester, M13 9PL, UK" - }, - { - "author_name": "Carole Goble", - "author_inst": "The University of Manchester, Department of Computer Science, Oxford Road, Manchester, M13 9PL, UK" - }, - { - "author_name": "Xiaoming Hu", - "author_inst": "Heidelberg Institute for Theoretical Studies (HITS), Schloss-Wolfsbrunnenweg 35, D-69118 Heidelberg (Germany)" - }, - { - "author_name": "Rupert Overall", - "author_inst": "German Center for Neurodegenerative Diseases (DZNE) Dresden, Tatzberg 41, 01307 Dresden, Germany." - }, - { - "author_name": "Dieter Maier", - "author_inst": "Biomax Informatics AG, Robert-Koch-Str. 2, 82152 Planegg, Germany" - }, - { - "author_name": "Angela Bauch", - "author_inst": "Biomax Informatics AG, Robert-Koch-Str. 2, 82152 Planegg, Germany" - }, - { - "author_name": "Benjamin M Gyori", - "author_inst": "Harvard Medical School, Laboratory of Systems Pharmacology, 200 Longwood Avenue, Boston, MA" - }, - { - "author_name": "John A Bachman", - "author_inst": "Harvard Medical School, Laboratory of Systems Pharmacology, 200 Longwood Avenue, Boston, MA" - }, - { - "author_name": "Carlos Vega", - "author_inst": "Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg" - }, - { - "author_name": "Valentin Groues", - "author_inst": "Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg" - }, - { - "author_name": "Miguel Vazquez", - "author_inst": "Barcelona Supercomputing Center (BSC), Barcelona, Spain" - }, - { - "author_name": "Pablo Porras", - "author_inst": "EMBL-EBI, Molecular Systems, Wellcome Genome Campus, CB10 1SD, Hinxton, UK" - }, - { - "author_name": "Luana Licata", - "author_inst": "University of Rome Tor Vergata, Department of Biology, Via della Ricerca Scientifica 1, 00133 Rome, Italy" - }, - { - "author_name": "Marta Iannuccelli", - "author_inst": "University of Rome Tor Vergata, Department of Biology, Via della Ricerca Scientifica 1, 00133 Rome, Italy" - }, - { - "author_name": "Francesca Sacco", - "author_inst": "University of Rome Tor Vergata, Department of Biology, Via della Ricerca Scientifica 1, 00133 Rome, Italy" - }, - { - "author_name": "Denes Turei", - "author_inst": "Heidelberg Univarsity, Institute for Computational Biomedicine, BQ 0053, Im Neuenheimer Feld 267, 69120 Heidelberg, Germany" - }, - { - "author_name": "Augustin Luna", - "author_inst": "cBio Center, Divisions of Biostatistics and Computational Biology, Department of Data Sciences, Dana-Farber Cancer Institute, Boston, MA, 02215, USA." - }, - { - "author_name": "Ozgun Babur", - "author_inst": "University of Massachusetts Boston, Computer Science Department, 100 William T, Morrissey Blvd, Boston, MA 02125" - }, - { - "author_name": "Sylvain Soliman", - "author_inst": "Inria Saclay Ile-de-France" - }, - { - "author_name": "Alberto Valdeolivas", - "author_inst": "Heidelberg University, Faculty of Medicine and Heidelberg University Hospital, Institute of Computational Biomedicine, Bioquant, 69120 Heidelberg, Germany" - }, - { - "author_name": "Marina Esteban-Medina", - "author_inst": "Clinical Bioinformatics Area. Fundacion Progreso y Salud (FPS). CDCA, Hospital Virgen del Rocio, 41013, Sevilla, Spain." - }, - { - "author_name": "Maria Pena-Chilet", - "author_inst": "Clinical Bioinformatics Area. Fundacion Progreso y Salud (FPS). CDCA, Hospital Virgen del Rocio, 41013, Sevilla, Spain." - }, - { - "author_name": "Kinza Rian", - "author_inst": "Clinical Bioinformatics Area. Fundacion Progreso y Salud (FPS). CDCA, Hospital Virgen del Rocio, 41013, Sevilla, Spain." - }, - { - "author_name": "Tomas Helikar", - "author_inst": "University of Nebraska-Lincoln, Department of Biochemistry, 1901 Vine St., Lincoln, NE, 68588, USA" - }, - { - "author_name": "Bhanwar Lal Puniya", - "author_inst": "University of Nebraska-Lincoln, Department of Biochemistry, 1901 Vine St., Lincoln, NE, 68588, USA" - }, - { - "author_name": "Anastasia Nesterova", - "author_inst": "Elsevier, Life Science Department" - }, - { - "author_name": "Anton Yuryev", - "author_inst": "Elsevier, Professional Services, 1600 John F Kennedy Blvd #1800, Philadelphia, PA 19103" - }, - { - "author_name": "Anita de Waard", - "author_inst": "Elsevier, Research Collaborations Unit, 71 Hanley Lane, Jericho, VT 05465" - }, - { - "author_name": "Dezso Modos", - "author_inst": "Quadram Institute Bioscience, Rosalind Franklin Road, Norwich Research Park, Norwich, NR4 7UQ, United Kingdom" + "author_name": "Reut Falach", + "author_inst": "Israel Institute for Biological Research" }, { - "author_name": "Agatha Treveil", - "author_inst": "Earlham Institute, Norwich Research Park, Norwich, NR4 7UZ, United Kingdom" + "author_name": "Liat Bar-On", + "author_inst": "Israel Institute for Biological Research" }, { - "author_name": "Marton Laszlo Olbei", - "author_inst": "Earlham Institute, Norwich Research Park, Norwich, NR4 7UZ, United Kingdom" + "author_name": "Shlomi Lazar", + "author_inst": "Israel Institute for Biological Research" }, { - "author_name": "Bertrand De Meulder", - "author_inst": "Association EISBM" + "author_name": "Tamar Kadar", + "author_inst": "Israel Institute for Biological Research" }, { - "author_name": "Aurelien Naldi", - "author_inst": "Inria Saclay - Ile de France, Lifeware group, 91120 Palaiseau, France" + "author_name": "Ohad Mazor", + "author_inst": "Israel Institute for Biological Research" }, { - "author_name": "Aurelien Dugourd", - "author_inst": "Heidelberg University, Faculty of Medicine, and Heidelberg University Hospital, Institute for Computational Biomedicine, Bioquant, Heidelberg, Germany" + "author_name": "Moshe Aftalion", + "author_inst": "Israel Institute for Biological Research" }, { - "author_name": "Laurence Calzone", - "author_inst": "Institut Curie, PSL Research University, Mines Paris Tech, Inserm, U900, F-75005, Paris, France." + "author_name": "David Gur", + "author_inst": "Israel Institute for Biological Research" }, { - "author_name": "Chris Sander", - "author_inst": "cBio Center, Divisions of Biostatistics and Computational Biology, Department of Data Sciences, Dana-Farber Cancer Institute, Boston, MA, 02215, USA." + "author_name": "Ohad Shifman", + "author_inst": "Israel Institute for Biological Research" }, { - "author_name": "Emek Demir", - "author_inst": "Oregon Health and Science University, Department of Molecular and Medical Genetics, 3222 SW Research Drive, Mail Code: L103, Portland, Oregon, U.S.A. 97239" + "author_name": "Ofir Israeli", + "author_inst": "Israel Institute for Biological Research" }, { - "author_name": "Tamas Korcsmaros", - "author_inst": "Earlham Institute, Norwich Research Park, NR4 7UZ, Norwich, UK" + "author_name": "Inbar Cohen-Gihon", + "author_inst": "Israel Institute for Biological Research" }, { - "author_name": "Tom C Freeman", - "author_inst": "The Roslin Institute, University of Edinburgh EH25 9RG" + "author_name": "Galia Zaide", + "author_inst": "Israel Institute for Biological Research" }, { - "author_name": "Franck Auge", - "author_inst": "Sanofi R&D, Translational Sciences, 1 av Pierre Brossolette 91395 Chilly-Mazarin France" + "author_name": "Hila Gutman", + "author_inst": "Israel Institute for Biological Research" }, { - "author_name": "Jacques S Beckmann", - "author_inst": "University of Lausanne, Lausanne, Switzerland" + "author_name": "Yentl Evgy", + "author_inst": "Israel Institute for Biological Research" }, { - "author_name": "Jan Hasenauer", - "author_inst": "Interdisciplinary Research Unit Mathematics and Life Sciences, University of Bonn, Germany" + "author_name": "Yaron Vagima", + "author_inst": "Israel Institute for Biological Research" }, { - "author_name": "Olaf Wolkenhauer", - "author_inst": "University of Rostock, Dept of Systems Biology & Bioinformatics" + "author_name": "Efi Makdasi", + "author_inst": "Israel Institute for Biological Research" }, { - "author_name": "Egon Willighagen", - "author_inst": "Department of Bioinformatics-BiGCaT, NUTRIM, Maastricht University, Maastricht, The Netherlands" + "author_name": "Dana Stein", + "author_inst": "Israel Institute for Biological Research" }, { - "author_name": "Alexander R Pico", - "author_inst": "Institute of Data Science and Biotechnology, Gladstone Institutes, San Francisco, CA, USA" + "author_name": "Ronit Rosenfeld", + "author_inst": "Israel Institute for Biological Research" }, { - "author_name": "Chris Evelo", - "author_inst": "Dept. Bioinformatics - BiGCaT, Maastricht University, The Netherlands" + "author_name": "Ron Alcalay", + "author_inst": "Israel Institute for Biological Research" }, { - "author_name": "Lincoln D Stein", - "author_inst": "Ontario Institute for Cancer Research, Adaptive Oncology Theme, 661 University Ave, Toronto, ON M5G 1M1 Canada" + "author_name": "Eran Zahavy", + "author_inst": "Israel Institute for Biological Research" }, { - "author_name": "Henning Hermjakob", - "author_inst": "European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridgeshire, UK" + "author_name": "Haim Levy", + "author_inst": "Israel Institute for Biological Research" }, { - "author_name": "Julio Saez-Rodriguez", - "author_inst": "Institute for Computational Biomedicine Heidelberg University, Faculty of Medicine, Im Neuenheimer Feld 267, 69120 Heidelberg" + "author_name": "Itai Glinert", + "author_inst": "Israel Institute for Biological Research" }, { - "author_name": "Joaquin Dopazo", - "author_inst": "Clinical Bioinformatics Area. Fundacion Progreso y Salud (FPS). CDCA, Hospital Virgen del Rocio. 41013. Sevilla. Spain." + "author_name": "Amir Ben-Shmuel", + "author_inst": "Israel Institute for Biological Research" }, { - "author_name": "Alfonso Valencia", - "author_inst": "Barcelona Supercomputing Center (BSC), Barcelona, Spain" + "author_name": "Tomer Israely", + "author_inst": "Israel Institute for Biological Research" }, { - "author_name": "Hiroaki Kitano", - "author_inst": "Systems Biology Institute, Tokyo Japan" + "author_name": "Sharon Melamed", + "author_inst": "Israel Institute for Biological Research" }, { - "author_name": "Emmanuel Barillot", - "author_inst": "Institut Curie, PSL Research University, Paris, France." + "author_name": "Boaz Politi", + "author_inst": "Israel Institute for Biological Research" }, { - "author_name": "Charles Auffray", - "author_inst": "European Institute for Systems Biology and Medicine (EISBM), Vourles, France" + "author_name": "Hagit Achdout", + "author_inst": "Israel Institute for Biological Research" }, { - "author_name": "Rudi Balling", - "author_inst": "Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg" + "author_name": "Shmuel Yitzhaky", + "author_inst": "Israel Institute for Biological Research" }, { - "author_name": "Reinhard Schneider", - "author_inst": "Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg" + "author_name": "Chanoch Kronman", + "author_inst": "Israel Institute for Biological Research" }, { - "author_name": "- the COVID-19 Disease Map Community", - "author_inst": "-" + "author_name": "Tamar Sabo", + "author_inst": "Israel Institute for Biological Research" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "new results", - "category": "systems biology" + "category": "pathology" }, { "rel_doi": "10.1101/2020.10.28.359356", @@ -1102473,77 +1103196,37 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.10.22.20216010", - "rel_title": "Fernando de Noronha: how an island controlled the community transmission of COVID-19 in Brazil", + "rel_doi": "10.1101/2020.10.19.20215293", + "rel_title": "Adaptive COVID-19 Forecasting via Bayesian Optimization", "rel_date": "2020-10-27", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.22.20216010", - "rel_abs": "IntroductionFernando Noronha (FNA) is a small Brazilian archipelago in the Atlantic, part of the state of Pernambuco that COVID-19 has decimated. Anticipating the worst from the pandemic, Island and state authorities implemented a series of public health actions to contain the epidemic. This paper, reporting the results of the first wave of a cohort study, documents the measures and their effects through a cohort study.\n\nMethodsMeasures were documented at the time of implementation. A random sample of 904 residents were selected from the health register, interviewed and tested for COVID-19 (RT-PCR and serology). The survey explored socioeconomic variables and adherence to prevention behaviors.\n\nResultsFlights were reduced from 38 to once a week, FNA was closed to tourism, schools were closed, and testing and tracing contacts was mandated along with social distancing and use of masks. A household lockdown was briefly imposed for residents. A prevalence of 5.1% was found, and a total of 158 cases of COVID-19 was estimated, although only 28 had been reported in routine surveillance. Half of the population reported food insecurity and applied for government COVID-19 benefits. Adherence to control measures was high, except for intrahousehold mask use with family and friends.\n\nConclusionDespite high levels of COVID-19 in Pernambuco, continued exposure through the provision of essential services from the mainland, and lack of direction from national authorities, FNA was able to implement a series of prevention measures unique in Brazil that contained the epidemic on the island.", - "rel_num_authors": 16, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.19.20215293", + "rel_abs": "Accurate forecasts of infections for localized regions are valuable for policy making and medical capacity planning. Existing compartmental and agent-based models [1, 7-11] for epidemiological forecasting employ static parameter choices and cannot be readily contextualized, while adaptive solutions [4, 13] focus primarily on the reproduction number. In the current work, we propose a novel model-agnostic Bayesian optimization approach [3] for learning model parameters from observed data that generalizes to multiple application-specific fidelity criteria. Empirical results demonstrate the efficacy of the proposed approach with SEIR-like compartmental models on COVID-19 case forecasting tasks. A city-level forecasting system based on this approach is being used for COVID-19 response in a few highly impacted Indian cities.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Mozart Julio Tabosa Sales", - "author_inst": "Instituto de Medicina Integral Professor Fernando Figueira" - }, - { - "author_name": "Ligia S Kerr", - "author_inst": "Universidade Federal do Ceara" - }, - { - "author_name": "Regina Vianna Brizolara", - "author_inst": "Departamento de Doencas de Condicoes Cronicas e Infeccoes Sexualmente Transmissiveis da Secretaria de Vigilancia em Saude do Ministerio da Saude" - }, - { - "author_name": "Ivana Cristina de Holanda Cunha Barreto", - "author_inst": "Fundacao Oswaldo Cruz Ceara" - }, - { - "author_name": "Rosa Livia Freitas Almeida", - "author_inst": "Universidade de Fortaleza" - }, - { - "author_name": "Paulo Goes", - "author_inst": "Universidade de Pernambuco" - }, - { - "author_name": "Luis Odorico Monteiro de Andrade", - "author_inst": "Fundacao Oswaldo Cruz Ceara" - }, - { - "author_name": "Leuridan Torres", - "author_inst": "Instituto de Medicina Integral Prof. Fernando Figueira - IMIP" - }, - { - "author_name": "Flavia Kelly Alvarenga Pinto", - "author_inst": "Ministerio da Saude" - }, - { - "author_name": "Francisco Marto Leal Pinheiro-Junior", - "author_inst": "Universidade Federal do Ceara" - }, - { - "author_name": "Rebeca Valentim Leite", - "author_inst": "Universidade Federal de Pernambuco/Faculdade de Medicina de Olinda" + "author_name": "Nayana Bannur", + "author_inst": "Wadhwani AI" }, { - "author_name": "Amanda Carolina Abreu Felix Cavalcanti de Abreu", - "author_inst": "Secretaria Estadual de Saude de Pernambuco" + "author_name": "Harsh Maheshwari", + "author_inst": "Flipkart Internet Private Limited" }, { - "author_name": "Rebecca Lucena Theophilo", - "author_inst": "Instituto de Medicina Integral Professor Fernando Figueira; Fundacao Oswaldo Cruz Ceara" + "author_name": "Sansiddh Jain", + "author_inst": "Wadhwani AI" }, { - "author_name": "Fernando Rodrigues Magalhaes", - "author_inst": "Autarquia Territorial Distrito Estadual de Fernando de Noronha, Pernambuco" + "author_name": "Shreyas Shetty", + "author_inst": "Flipkart Internet Private Limited" }, { - "author_name": "Susane Lindinalva da Silva", - "author_inst": "Universidade Federal de Pernambuco; Faculdade de Medicina de Olinda" + "author_name": "Srujana Merugu", + "author_inst": "Independent" }, { - "author_name": "Carl Kendall", - "author_inst": "Universidade Federal do Ceara; Tulane School of Public Health" + "author_name": "Alpan Raval", + "author_inst": "Wadhwani AI" } ], "version": "1", @@ -1103847,39 +1104530,67 @@ "category": "health economics" }, { - "rel_doi": "10.1101/2020.10.24.20215061", - "rel_title": "MEGA: Machine Learning-Enhanced Graph Analytics for COVID-19 Infodemic Control", + "rel_doi": "10.1101/2020.10.23.20217901", + "rel_title": "Rapid Development of a De Novo Convalescent Plasma Program in Response to a Global Pandemic: A Large Southeastern U.S. Blood Center's Experience", "rel_date": "2020-10-27", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.24.20215061", - "rel_abs": "The COVID-19 pandemic brought not only global devastation but also an unprecedented infodemic of false or misleading information that spread rapidly through online social networks. Network analysis plays a crucial role in the science of fact-checking by modeling and learning the risk of infodemics through statistical processes and computation on mega-sized graphs. This paper proposes MEGA, Machine Learning-Enhanced Graph Analytics, a framework that combines feature engineering and graph neural networks to enhance the efficiency of learning performance involving massive graphs. Infodemic risk analysis is a unique application of the MEGA framework, which involves detecting spambots by counting triangle motifs and identifying influential spreaders by computing the distance centrality. The MEGA framework is evaluated using the COVID-19 pandemic Twitter dataset, demonstrating superior computational efficiency and classification accuracy.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.23.20217901", + "rel_abs": "BackgroundWith no vaccine or treatment for SARS-CoV-2 and its associated disease, COVID-19, convalescent plasma from recovered COVID-19 (CCP) patients offered a potential therapy. In March of 2020, the United States (US) Food and Drug Administration (FDA) authorized CCP under emergency Investigational New Drug (eIND) exemption and an IRB-approved Expanded Access Program (EAP) to treat severe COVID-19. Hospital demand grew rapidly in the Southeastern US, resulting in backlogs of CCP orders. We describe a large US blood centers (BC) rapid implementation of a CCP program in response to community needs.\n\nStudy Design and MethodsFrom April 2 to May 17, 2020 CCP was collected by whole blood or apheresis. Initial manual approaches to donor intake, collection and distribution were rapidly replaced with automated processes. All CCP donors and products underwent FDA-required screening and testing.\n\nResults619 CCP donors (299 females, 320 males) presented for CCP donation [161 (25.6%) whole blood, 466 (74.1%) plasmapheresis] resulting in 1219 CCP units. Production of CCP increased as processes were automated and streamlined, from a mean of 11 donors collected/day for the first month to a mean of 25 donors collected/day in the subsequent two weeks. Backlogged orders were cleared, and inventory began to accumulate 4 weeks after project initiation.\n\nConclusionThe BC was able to implement an effective de novo CCP collection program within 6 weeks in response to a community need in a global pandemic. Documentation of the experience may inform preparedness for future pandemics.", + "rel_num_authors": 12, "rel_authors": [ { - "author_name": "Ching Nam Hang", - "author_inst": "City University of Hong Kong" + "author_name": "Rita Reik", + "author_inst": "OneBlood" }, { - "author_name": "Pei-Duo Yu", - "author_inst": "Chung Yuan Christian University" + "author_name": "Richard Gammon", + "author_inst": "OneBlood" }, { - "author_name": "Siya Chen", - "author_inst": "City University of Hong Kong" + "author_name": "Nancy Carol", + "author_inst": "OneBlood" }, { - "author_name": "Chee Wei Tan", - "author_inst": "Nanyang Technological University" + "author_name": "Judith Smith", + "author_inst": "OneBlood" }, { - "author_name": "Guanrong Chen", - "author_inst": "City University of Hong Kong" + "author_name": "Martin Grable", + "author_inst": "OneBlood" + }, + { + "author_name": "Susan Forbes", + "author_inst": "OneBlood" + }, + { + "author_name": "YanYun Wu", + "author_inst": "University of Miami" + }, + { + "author_name": "Lance Reed", + "author_inst": "OneBlood" + }, + { + "author_name": "Michael Rogers", + "author_inst": "OneBlood" + }, + { + "author_name": "Alicia Prichard", + "author_inst": "OneBlood" + }, + { + "author_name": "Scott Paul", + "author_inst": "OneBlood" + }, + { + "author_name": "George Scholl", + "author_inst": "OneBlood" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "health informatics" + "category": "hematology" }, { "rel_doi": "10.1101/2020.10.25.20218982", @@ -1105465,63 +1106176,59 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2020.10.26.20218370", - "rel_title": "Outcomes evaluated in controlled clinical trials on the management of COVID-19: A methodological systematic review", + "rel_doi": "10.1101/2020.10.26.20219733", + "rel_title": "What does the COVID-19 pandemic mean for the next decade of onchocerciasis control and elimination?", "rel_date": "2020-10-27", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.26.20218370", - "rel_abs": "It is crucial that randomized controlled trials (RCTs) on the management of coronavirus disease 2019 (COVID-19) evaluate the outcomes that are critical to patients and clinicians, to facilitate relevance, interpretability, and comparability.\n\nThis methodological systematic review describes the outcomes evaluated in 415 RCTs on the management of COVID-19, that were registered with ClinicalTrials.gov, by 5/5/2020.\n\nSignificant heterogeneity was observed in the selection of outcomes and the instruments used to measure them. Mortality, adverse events and treatment success or failure are only evaluated in 64.4%, 48.4% and 43% of the included studies, respectively, while other outcomes are selected less often. Studies focusing on more severe presentations (hospitalized patients or requiring intensive care) most frequently evaluate mortality and adverse events, while hospital admission and viral detection/load are most frequently assessed in the community setting. Outcome measurement instruments are poorly reported and heterogeneous. In general, simple instruments that can control for important sources of bias are favoured. Follow-up does not exceed one month in 64.3% of these earlier trials, and long-term COVID-19 burden is rarely assessed.\n\nThe methodological issues identified could delay the introduction of potentially life-saving treatments in clinical practice. Our findings demonstrate the need for consensus in the design of RCTs.\n\nTake home message@ERSpublications: This systematic review describes the heterogeneity in outcomes evaluated in 415 RCTs on COVID-19 management and the instruments used to measure them. Our findings reveal a need for consensus in the design of future RCTs.", - "rel_num_authors": 11, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.26.20219733", + "rel_abs": "BackgroundMass drug administration (MDA) of ivermectin for onchocerciasis has been disrupted by the SARS-CoV-2 (COVID-19) pandemic. Mathematical modelling can help predict how missed/delayed MDA will affect short-term epidemiological trends and elimination prospects by 2030.\n\nMethodsTwo onchocerciasis transmission models (EPIONCHO-IBM and ONCHOSIM) are used to simulate microfilarial prevalence trends, elimination probabilities, and age-profiles of Onchocerca volvulus microfilarial prevalence and intensity, for different treatment histories and transmission settings, assuming no interruption, a 1-year (2020) or 2-year (2020-2021) interruption. Biannual MDA or increased coverage upon MDA resumption are investigated as remedial strategies.\n\nResultsProgrammes with shorter MDA histories and settings with high pre-intervention endemicity will be the most affected. Biannual MDA is more effective than increasing coverage for mitigating COVID-19s impact on MDA. Programmes which had already switched to biannual MDA should be minimally affected. In high transmission settings with short treatment history, a 2-year interruption could lead to increased microfilarial load in children (EPIONCHO-IBM) or adults (ONCHOSIM).\n\nConclusionsProgrammes with shorter (annual MDA) treatment histories should be prioritised for remedial biannual MDA. Increases in microfilarial load could have short- and long-term morbidity and mortality repercussions. These results can guide decision-making to mitigate the impact of COVID-19 on onchocerciasis elimination.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Alexander G. Mathioudakis", - "author_inst": "Division of Infection, Immunity and Respiratory Medicine, The University of Manchester & North West Lung Centre, Manchester University NHS Foundation Trust, Man" - }, - { - "author_name": "Markus Fally", - "author_inst": "Department of Internal Medicine, Section for Pulmonary Diseases, Herlev Gentofte Hospital, Hellerup, Denmark." + "author_name": "Jonathan I. D. Hamley", + "author_inst": "Imperial College London" }, { - "author_name": "Rola Hashad", - "author_inst": "North West Lung Centre, Wythenshawe Hospital, Manchester University NHS Foundation Trust, Southmoor Road, Manchester, UK & Department of Medical Microbiology an" + "author_name": "David J. Blok", + "author_inst": "Erasmus MC" }, { - "author_name": "Ahmed Kouta", - "author_inst": "Division of Infection, Immunity and Respiratory Medicine, School of Biological Sciences, The University of Manchester, Manchester Academic Health Science Centre" + "author_name": "Martin Walker", + "author_inst": "Royal Veterinary Collage" }, { - "author_name": "Ali Sina Hadi", - "author_inst": "Department of Respiratory Medicine, Salford Royal Infirmary NHS Foundation Trust, Manchester, UK." + "author_name": "Philip Milton", + "author_inst": "Imperial College London" }, { - "author_name": "Sean Blandin Knight", - "author_inst": "Division of Infection, Immunity and Respiratory Medicine, School of Biological Sciences, The University of Manchester, Manchester Academic Health Science Centre" + "author_name": "Adrian D. Hopkins", + "author_inst": "Adrian Hopkins Consulting" }, { - "author_name": "Nawar Diar Bakerly", - "author_inst": "Department of Respiratory Medicine, Salford Royal Infirmary NHS Foundation Trust, Manchester, UK & Manchester Metropolitan University, Manchester, UK" + "author_name": "Louise C. Hamill", + "author_inst": "Sightsavers" }, { - "author_name": "Dave Singh", - "author_inst": "Division of Infection, Immunity and Respiratory Medicine, The University of Manchester & North West Lung Centre, Manchester University NHS Foundation Trust & Me" + "author_name": "Philip Downs", + "author_inst": "Sightsavers" }, { - "author_name": "Paula R Williamson", - "author_inst": "MRC/NIHR Trials Methodology Research Partnership, Department of Health Data Science, University of Liverpool, Liverpool, UK." + "author_name": "Sake J. de Vlas", + "author_inst": "Erasmus MC" }, { - "author_name": "Timothy Felton", - "author_inst": "Division of Infection, Immunity and Respiratory Medicine, The University of Manchester & North West Lung Centre, Manchester University NHS Foundation Trust, Man" + "author_name": "Wilma A. Stolk", + "author_inst": "Erasmus MC" }, { - "author_name": "Jorgen Vestbo", - "author_inst": "Division of Infection, Immunity and Respiratory Medicine, The University of Manchester & North West Lung Centre, Manchester University NHS Foundation Trust, Man" + "author_name": "Maria-Gloria Basanez", + "author_inst": "Imperial College London" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "respiratory medicine" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2020.10.26.20219527", @@ -1107439,79 +1108146,51 @@ "category": "surgery" }, { - "rel_doi": "10.1101/2020.10.26.20218636", - "rel_title": "Lung transplantation for pulmonary fibrosis secondary to severe COVID-19", + "rel_doi": "10.1101/2020.10.27.20220061", + "rel_title": "Decline in mortality among hospitalised covid-19 patients in Sweden: a nationwide observational study", "rel_date": "2020-10-27", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.26.20218636", - "rel_abs": "Lung transplantation can potentially be a life-saving treatment for patients with non-resolving COVID-19 acute respiratory distress syndrome. Concerns limiting transplant include recurrence of SARS-CoV-2 infection in the allograft, technical challenges imposed by viral-mediated injury to the native lung, and potential risk for allograft infection by pathogens associated with ventilator-induced pneumonia in the native lung. Additionally, the native lung might recover, resulting in long-term outcomes preferable to transplant. Here, we report the results of the first two successful lung transplantation procedures in patients with non-resolving COVID-19 associated acute respiratory distress syndrome in the United States. We performed smFISH to detect both positive and negative strands of SARS-CoV-2 RNA in the explanted lung tissue, extracellular matrix imaging using SHIELD tissue clearance, and single cell RNA-Seq on explant and warm post-mortem lung biopsies from patients who died from severe COVID-19 pneumonia. Lungs from patients with prolonged COVID-19 were free of virus but pathology showed extensive evidence of injury and fibrosis which resembled end-stage pulmonary fibrosis. Single cell RNA-Seq of the explanted native lungs from transplant and paired warm post-mortem autopsies showed similarities between late SARS-CoV-2 acute respiratory distress syndrome and irreversible end-stage pulmonary fibrosis requiring lung transplantation. There was no recurrence of SARS-CoV-2 or pathogens associated with pre-transplant ventilator associated pneumonias following transplantation in either patient. Our findings suggest that some patients with severe COVID-19 develop fibrotic lung disease for which lung transplantation is the only option for survival.\n\nSingle sentence summarySome patients with severe COVID-19 develop end-stage pulmonary fibrosis for which lung transplantation may be the only treatment.", - "rel_num_authors": 15, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.27.20220061", + "rel_abs": "OBJECTIVEIt is important to know if mortality among hospitalised covid-19 patients has changed as the pandemic has progressed. The aim of this study was to describe the dynamics of mortality among patients hospitalised for covid-19 in a nationwide study.\n\nDESIGNNationwide observational cohort study of all patients hospitalised in Sweden 1 March to 30 June 2020 with SARS-CoV-2 RNA positivity 14 days before to 5 days after admission, and a discharge code for covid-19.\n\nSETTINGAll hospitals in Sweden.\n\nPARTICIPANTS15 761 hospitalised patients with covid-19, with data compiled by the Swedish National Board of Health and Welfare.\n\nMAIN OUTCOME MEASURESOutcome was 60-day all-cause mortality. Patients were stratified according to month of hospital admission. Poisson regression was used to estimate the relative risk of death by month of admission, adjusting for pre-existing conditions, age, sex, care dependency, and severity of illness (Simplified Acute Physiology, version 3), for patients in intensive care units (ICU).\n\nRESULTSThe overall 60-day mortality was 17.8% (95% confidence interval (CI), 17.2% to 18.4%), and it decreased from 24.7% (95% CI, 23.0% to 26.5%) in March to 13.3% (95% CI, 12.1% to 14.7%) in June. Adjusted relative risk (RR) of death was 0.56 (95% CI, 0.51 to 0.63) for June, using March as reference. Corresponding RR for patients not admitted to ICU and those admitted to ICU were 0.60 (95% CI, 0.53 to 0.67) and 0.61 (95% CI, 0.48 to 0.79), respectively. The proportion of patients admitted to ICU decreased from 19.5% (95% CI, 17.9% to 21.0%) in the March cohort to 11.0% (95% CI, 9.9% to 12.2%) in the June cohort.\n\nCONCLUSIONSThere was a gradual decline in mortality from March to June 2020 in Swedish hospitalised covid-19 patients, which was independent of pre-existing conditions, age, and sex. Future research is needed to explain the reasons for this decline. The changing covid-19 mortality should be taken into account when management and results of studies from the first pandemic wave are evaluated.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Ankit Bharat", - "author_inst": "Northwestern University" - }, - { - "author_name": "Melissa Querrey", - "author_inst": "Northwestern University" - }, - { - "author_name": "Nikolay S Markov", - "author_inst": "Northwestern University" - }, - { - "author_name": "Samuel S Kim", - "author_inst": "Northwestern University" - }, - { - "author_name": "Chitaru Kurihara", - "author_inst": "Northwestern University" - }, - { - "author_name": "Rafael Garza-Castillon Jr.", - "author_inst": "Northwestern University" - }, - { - "author_name": "Adwaiy Manerikar", - "author_inst": "Northwestern University" - }, - { - "author_name": "Ali Shilatifard", - "author_inst": "Northwestern University" + "author_name": "Kristoffer Stralin", + "author_inst": "Department of Infectious Diseases, Karolinska University Hospital, Stockholm, Department of Medicine, Huddinge, Karolinska Institutet, Stockholm, National Progr" }, { - "author_name": "Rade Tomic", - "author_inst": "Northwestern University" + "author_name": "Erik Wahlstrom", + "author_inst": "National Board of Health and Welfare, Sweden" }, { - "author_name": "Yuliya Politanska", - "author_inst": "Northwestern University" + "author_name": "Sten Walther", + "author_inst": "Department of Cardiothoracic and Vascular Surgery, Heart Centre, Linkoping University Hospital, Department of Health, Medicine and Caring Sciences, Linkoping Un" }, { - "author_name": "Hiam Abdala-Valencia", - "author_inst": "Northwestern University" + "author_name": "Mona Heurgren", + "author_inst": "National Board of Health and Welfare, Sweden" }, { - "author_name": "Anjana V Yeldandi", - "author_inst": "Northwestern University" + "author_name": "Anna M Bennet-Bark", + "author_inst": "National Board of Health and Welfare, Sweden" }, { - "author_name": "Jon W Lomasney", - "author_inst": "Northwestern University" + "author_name": "Thomas Linden", + "author_inst": "National Board of Health and Welfare, Sweden" }, { - "author_name": "Alexander V Misharin", - "author_inst": "Northwestern University" + "author_name": "Johanna Holm", + "author_inst": "National Board of Health and Welfare, Sweden" }, { - "author_name": "GR Scott Budinger", - "author_inst": "Northwestern University" + "author_name": "Hakan Hanberger", + "author_inst": "Division of Inflammation and Infection, Department of Biomedical and Clinical Sciences, Faculty of Medicine and Health Sciences, Linkoping University, Departmen" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "transplantation" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2020.10.26.20219907", @@ -1109085,23 +1109764,59 @@ "category": "pathology" }, { - "rel_doi": "10.1101/2020.10.26.355784", - "rel_title": "A theoretical analysis of the putative ORF10 protein in SARS-CoV-2", + "rel_doi": "10.1101/2020.10.26.355099", + "rel_title": "Structural basis of ribosomal frameshifting during translation of the SARS-CoV-2 RNA genome", "rel_date": "2020-10-26", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.10.26.355784", - "rel_abs": "Upstream of the 3-untranslated region in the SARS-CoV-2 genome is ORF10 which has been proposed to encode for the ORF10 protein. Current research is still unclear on whether this protein is synthesized, but further investigations are still warranted. Herein, this study uses multiple bioinformatic tools to biochemically and functionally characterize the ORF10 protein, along with predicting its tertiary structure. Results indicate a highly ordered, hydrophobic, and thermally stable protein that contains at least one transmembrane region. This protein also possesses high residue protein-binding propensity, primarily in the N-terminal half. An assessment of forty-one missense mutations reveal slight changes in residue flexibility, mainly in the C-terminal half. However, these same mutations do not inflict significant changes on protein stability and other biochemical features. The predicted model suggests the ORF10 protein contains a {beta}--{beta} motif with a {beta}-molecular recognition feature occurring in the first {beta}-strand. Functionally, the ORF10 protein could be a membrane protein. A single pocket was identified in this protein but found to possess low druggability. The ORF10 itself consists of two distinct lineages: the SARS-CoV lineage and the SARS-CoV-2 lineage. Evidence of strong positive selection (dN/dS = 4.01) and purifying selection (dN/dS = 0.713) were found within the SARS-CoV-2 lineage and SARS-CoV lineage, respectively. Collectively, these results continue to assess the biological relevance of ORF10 and its putatively encoded protein, thereby aiding in diagnostic and possibly vaccine development.", - "rel_num_authors": 1, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.10.26.355099", + "rel_abs": "Programmed ribosomal frameshifting is the key event during translation of the SARS-CoV-2 RNA genome allowing synthesis of the viral RNA-dependent RNA polymerase and downstream viral proteins. Here we present the cryo-EM structure of the mammalian ribosome in the process of translating viral RNA paused in a conformation primed for frameshifting. We observe that the viral RNA adopts a pseudoknot structure lodged at the mRNA entry channel of the ribosome to generate tension in the mRNA that leads to frameshifting. The nascent viral polyprotein that is being synthesized by the ribosome paused at the frameshifting site forms distinct interactions with the ribosomal polypeptide exit tunnel. We use biochemical experiments to validate our structural observations and to reveal mechanistic and regulatory features that influence the frameshifting efficiency. Finally, a compound previously shown to reduce frameshifting is able to inhibit SARS-CoV-2 replication in infected cells, establishing coronavirus frameshifting as target for antiviral intervention.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Noah Avery Schuster", - "author_inst": "DePauw University" + "author_name": "Pramod R. Bhatt", + "author_inst": "Department of Biology, Institute of Molecular Biology and Biophysics, ETH Zurich, Switzerland" + }, + { + "author_name": "Alain Scaiola", + "author_inst": "Department of Biology, Institute of Molecular Biology and Biophysics, ETH Zurich, Switzerland" + }, + { + "author_name": "Gary Loughran", + "author_inst": "Department of Biology, Schools of Biochemistry and Microbiology, University College Cork, Cork, Ireland" + }, + { + "author_name": "Marc Leibundgut", + "author_inst": "Department of Biology, Institute of Molecular Biology and Biophysics, ETH Zurich, Switzerland" + }, + { + "author_name": "Annika Kratzel", + "author_inst": "Institute of Virology and Immunology, University of Bern, Bern, Switzerland" + }, + { + "author_name": "Angus E. McMillan", + "author_inst": "Laboratorium fur Organische Chemie, Department of Chemistry and Applied Biosciences, ETH Zurich, Zurich, Switzerland" + }, + { + "author_name": "Jeffrey W. Bode", + "author_inst": "Laboratorium fur Organische Chemie, Department of Chemistry and Applied Biosciences, ETH Zurich, Zurich, Switzerland" + }, + { + "author_name": "Volker Thiel", + "author_inst": "Institute of Virology and Immunology, University of Bern, Bern, Switzerland" + }, + { + "author_name": "John F. Atkins", + "author_inst": "Schools of Biochemistry and Microbiology, University College Cork, Cork, Ireland" + }, + { + "author_name": "Nenad Ban", + "author_inst": "Department of Biology, Institute of Molecular Biology and Biophysics, ETH Zurich, Switzerland" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by_nc_nd", "type": "new results", - "category": "microbiology" + "category": "molecular biology" }, { "rel_doi": "10.1101/2020.10.26.355677", @@ -1110639,35 +1111354,35 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.10.21.20216713", - "rel_title": "COVID-19 adaptive humoral immunity models: non-neutralizing versus antibody-disease enhancement scenarios", + "rel_doi": "10.1101/2020.10.20.20216473", + "rel_title": "Mathematical Analysis of COVID-19 Transmission Dynamics. A Case Study with Nigeria", "rel_date": "2020-10-23", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.21.20216713", - "rel_abs": "The interplay between the virus, infected cells and the immune responses to SARS-CoV-2 is still under debate. Extending the basic model of viral dynamics we propose here a formal approach to describe the neutralizing versus weakly (or non-)neutralizing scenarios and compare with the possible effects of antibody-dependent enhancement (ADE). The theoretical model is consistent with data available from the literature; we show that weakly neutralizing antibodies or ADE can both give rise to either final virus clearance or disease progression, but the immuno-dynamic is different in each case. Given that a significant part of the world population is already naturally immunized or vaccinated, we also discuss the implications on secondary infections infections following vaccination or in presence of immune system dysfunctions.", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.20.20216473", + "rel_abs": "In this article, we formulated a mathematical model for the spread of the COVID-19 disease and we introduced quarantined and isolated compartments. The next generation matrix method was adopted to compute the basic reproduction number (R0) in order to assess the transmission dynamics of the COVID-19 deadly disease. Stability analysis of the disease free equilibrium is investigated based on the basic reproduction number and the result shows that it is locally and asymptotically stable for R0 less than 1. Numerical calculation of the basic reproduction number revealed that R0 < 1 which means that the disease can be eradicated from Nigeria. The study shows that isolation, quarantine and other government policies like social distancing and lockdown are the best approaches to control the pernicious nature of COVID-19 pandemic.", "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Antoine Danchin", - "author_inst": "Institut Cochin" + "author_name": "Agbata Celestine Benedict", + "author_inst": "University of Nigeria Nsukka UNN" }, { - "author_name": "Oriane Pagani-Azizi", - "author_inst": "Univerite Paris Dauphine - PSL & ESPCI Paris PSL" + "author_name": "Ogala Emmanuel", + "author_inst": "Federal University of Agriculture Makudi Nigeria" }, { - "author_name": "Gabriel TURINICI", - "author_inst": "Universite Paris Dauphine - PSL" + "author_name": "Bashir Tenuche", + "author_inst": "Kogi State University Anyigba, Nigeria" }, { - "author_name": "Ghozlane Yahiaoui", - "author_inst": "University of Oxford" + "author_name": "William William-Denteh", + "author_inst": "University of Science and Technology Kumasi, Ghana" } ], "version": "1", "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "allergy and immunology" + "category": "epidemiology" }, { "rel_doi": "10.1101/2020.10.20.20216457", @@ -1112237,105 +1112952,21 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2020.10.23.344085", - "rel_title": "Sterilizing Immunity against SARS-CoV-2 Infection in Mice by a Single-Shot and Modified Imidazoquinoline TLR7/8 Agonist-Adjuvanted Recombinant Spike Protein Vaccine", + "rel_doi": "10.1101/2020.10.22.343673", + "rel_title": "Potential Achilles heels of SARS-CoV-2 displayed by the base order-dependent component of RNA folding energy", "rel_date": "2020-10-23", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.10.23.344085", - "rel_abs": "The search for vaccines that protect from severe morbidity and mortality as a result of infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus that causes coronavirus disease 2019 (COVID-19) is a race against the clock and the virus. Several vaccine candidates are currently being tested in the clinic. Inactivated virus and recombinant protein vaccines can be safe options but may require adjuvants to induce robust immune responses efficiently. In this work we describe the use of a novel amphiphilic imidazoquinoline (IMDQ-PEG-CHOL) TLR7/8 adjuvant, consisting of an imidazoquinoline conjugated to the chain end of a cholesterol-poly(ethylene glycol) macromolecular amphiphile). This amphiphile is water soluble and exhibits massive translocation to lymph nodes upon local administration, likely through binding to albumin. IMDQ-PEG-CHOL is used to induce a protective immune response against SARS-CoV-2 after single vaccination with trimeric recombinant SARS-CoV-2 spike protein in the BALB/c mouse model. Inclusion of amphiphilic IMDQ-PEG-CHOL in the SARS-CoV-2 spike vaccine formulation resulted in enhanced immune cell recruitment and activation in the draining lymph node. IMDQ-PEG-CHOL has a better safety profile compared to native soluble IMDQ as the former induces a more localized immune response upon local injection, preventing systemic inflammation. Moreover, IMDQ-PEG-CHOL adjuvanted vaccine induced enhanced ELISA and in vitro microneutralization titers, and a more balanced IgG2a/IgG1 response. To correlate vaccine responses with control of virus replication in vivo, vaccinated mice were challenged with SARS-CoV-2 virus after being sensitized by intranasal adenovirus-mediated expression of the human angiotensin converting enzyme 2 (ACE2) gene. Animals vaccinated with trimeric recombinant spike protein vaccine without adjuvant had lung virus titers comparable to non-vaccinated control mice, whereas animals vaccinated with IMDQ-PEG-CHOL-adjuvanted vaccine controlled viral replication and infectious viruses could not be recovered from their lungs at day 4 post infection. In order to test whether IMDQ-PEG-CHOL could also be used to adjuvant vaccines currently licensed for use in humans, proof of concept was also provided by using the same IMDQ-PEG-CHOL to adjuvant human quadrivalent inactivated influenza virus split vaccine, which resulted in enhanced hemagglutination inhibition titers and a more balanced IgG2a/IgG1 antibody response. Enhanced influenza vaccine responses correlated with better virus control when mice were given a lethal influenza virus challenge. Our results underscore the potential use of IMDQ-PEG-CHOL as an adjuvant to achieve protection after single immunization with recombinant protein and inactivated vaccines against respiratory viruses, such as SARS-CoV-2 and influenza viruses.", - "rel_num_authors": 22, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.10.22.343673", + "rel_abs": "The base order-dependent component of folding energy has revealed a highly conserved region in HIV-1 genomes that associates with RNA structure. This corresponds to a packaging signal that is recognized by the nucleocapsid domain of the Gag polyprotein. Long viewed as a potential HIV-1 \"Achilles heel,\" the signal can be targeted by a new antiviral compound. Although SARS-CoV-2 differs in many respects from HIV-1, the same technology displays regions with a high base order-dependent folding energy component, which are also highly conserved. This indicates structural invariance (SI) sustained by natural selection. While the regions are often also protein-encoding (e.g. NSP3, ORF3a), we suggest that their nucleic acid level functions can be considered potential \"Achilles heels\" for SARS-CoV-2, perhaps susceptible to therapies like those envisaged for AIDS. The ribosomal frameshifting element scored well, but higher SI scores were obtained in other regions, including those encoding NSP13 and the nucleocapsid (N) protein.", + "rel_num_authors": 1, "rel_authors": [ { - "author_name": "Sonia Jangra", - "author_inst": "Icahn School of Medicine at Mount Sinai" - }, - { - "author_name": "Jana De Vrieze", - "author_inst": "Ghent University" - }, - { - "author_name": "Angela Choi", - "author_inst": "Icahn School of Medicine at Mount Sinai" - }, - { - "author_name": "Raveen Rathnasinghe", - "author_inst": "Icahn School of Medicine at Mount Sinai" - }, - { - "author_name": "Gabriel Laghlali", - "author_inst": "Icahn School of Medicine at Mount Sinai" - }, - { - "author_name": "Annemiek Uvyn", - "author_inst": "Ghent University" - }, - { - "author_name": "Simon Van Herck", - "author_inst": "Ghent University" - }, - { - "author_name": "Lutz Nuhn", - "author_inst": "Ghent University" - }, - { - "author_name": "Kim Deswarte", - "author_inst": "Ghent University/VIB Center for Inflammation Research" - }, - { - "author_name": "Zifu Zhong", - "author_inst": "Ghent University" - }, - { - "author_name": "Niek Sanders", - "author_inst": "Ghent University" - }, - { - "author_name": "Stefan Lienenklaus", - "author_inst": "Hannover Medical School" - }, - { - "author_name": "Sunil David", - "author_inst": "Virovax" - }, - { - "author_name": "Shirin Strohmeier", - "author_inst": "Icahn School of Medicine at Mount Sinai" - }, - { - "author_name": "Fatima Amanat", - "author_inst": "Icahn School of Medicine at Mount Sinai" - }, - { - "author_name": "Florian Krammer", - "author_inst": "Icahn School of Medicine at Mount Sinai" - }, - { - "author_name": "Hamida Hammad", - "author_inst": "Ghent University/VIB Center for Inflammation Research" - }, - { - "author_name": "Bart N Lambrecht", - "author_inst": "Ghent University/VIB Center for Inflammation Research/Erasmus Medical Center" - }, - { - "author_name": "Lynda Coughlan", - "author_inst": "Icahn School of Medicine at Mount Sinai" - }, - { - "author_name": "Adolfo Garcia-Sastre", - "author_inst": "Icahn School of Medicine at Mount Sinai/Global Health and Emerging Pathogens Institute/Tisch Cancer Institute" - }, - { - "author_name": "Bruno G De Geest", - "author_inst": "Ghent University" - }, - { - "author_name": "Michael Schotsaert", - "author_inst": "Icahn School of Medicine at Mount Sinai/Global Health and Emerging Pathogens Institute" + "author_name": "Chiyu Zhang", + "author_inst": "Fudan University" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by_nc_nd", "type": "new results", "category": "microbiology" }, @@ -1113855,45 +1114486,57 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.10.20.20214965", - "rel_title": "Innate Immune Response Modulation and Resistance to SARS-CoV-2 infection: A Prospective Comparative Cohort Study in High Risk Healthcare Workers", + "rel_doi": "10.1101/2020.10.20.20216127", + "rel_title": "Saliva as testing sample for SARS-CoV-2 detection by RT-PCR in low prevalence community setting.", "rel_date": "2020-10-21", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.20.20214965", - "rel_abs": "To evaluate ability of modulated innate immune response to provide resistance to development of symptomatic RT-PCR confirmed COVID-19, 96 inpatient front line health care workers (HCW) were cohorted in 1:2 ratio to receive TLR2 agonist (heat killed Mycobacterium w, Mw; n=32) as innate immune response modulator or observation (n=64). All were followed up for 100 days. The incidence of COVID-19 was 31 (32.3%) for the entire cohort, with only one developing COVID-19 in Mw group (3.1% vs 46.8%. protective efficacy - 93.33%, p=0.0001; 95% CI 53.3-99.1). Self-limiting local injection site reaction was the only side effect and was seen in 14 HCW. Findings from the study suggest the potential for providing resistance against novel pathogen like SARS-CoV-2 by modulating innate immune response.", - "rel_num_authors": 7, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.20.20216127", + "rel_abs": "ObjectivesThe number of COVID-19 cases is increasing globally and there is an urgency for a simple non-invasive method for the detection of SARS-CoV-2. Our study aimed to demonstrate that saliva can be used as a specimen for SARS-CoV-2 detection notably for the screening of extensive population groups via pooling.\n\nMethodsTo demonstrate that saliva is an appropriate specimen for SARS-CoV-2 detection a field study including 3,660 participants was performed between September 29 and October 1, 2020. We collected paired nasopharyngeal/oropharyngeal swabs (NPS) and saliva specimens and processed them within 24 hours of collection. We performed 36 serial measurements of 8 SARS-CoV-2 positive saliva samples to confirm the stability of the specimen and completed 37 pools of saliva samples by adding one positive specimen per pool.\n\nResultsSaliva specimens were stable for testing for up to 24 hours. Overall, 44 salival samples (1.2%) tested positive for SARS-CoV-2 during the field study. The results of saliva samples were consistent with those obtained from NPS from the same patient with 90% sensitivity (95% CI 68.3%-98.7%) and 100% specificity during the first two weeks after the onset of symptoms. Using pooling strategy 796 RT-PCR tests were performed. All pools showed 100% positivity in different pooling proportions.\n\nConclusionsOur findings demonstrate that saliva is an appropriate specimen for pooling and SARS-CoV-2 screening with accurate diagnostic performance. Patient-performed simple specimen collection allows testing an extensive number of people rapidly, obtaining results of the spread of SARS-CoV-2 and allowing authorities to take timely measures.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Dr Sarita Rani Jaiswal", - "author_inst": "Dharamshila Narayana Super-speciality Hospital , New Delhi" + "author_name": "Didzis Gavars", + "author_inst": "E. Gulbja Laboratorija" }, { - "author_name": "Anupama Mehta", - "author_inst": "Dharamshila Narayana Super-speciality Hospital , New Delhi" + "author_name": "Mikus Gavars", + "author_inst": "E. Gulbja Laboratorija" }, { - "author_name": "Dr. Gitali Bhagwati", - "author_inst": "Dharamshila Narayana Super-speciality Hospital , New Delhi" + "author_name": "Dmitrijs Perminovs", + "author_inst": "E. Gulbja Laboratorija" }, { - "author_name": "Mr. Rohit Lakhchaura", - "author_inst": "Dharamshila Narayana Super-speciality Hospital , New Delhi" + "author_name": "Janis Stasulans", + "author_inst": "E. Gulbja Laboratorija" }, { - "author_name": "Dr. Hemamalini Aiyer", - "author_inst": "Dharamshila Narayana Super-speciality Hospital , New Delhi" + "author_name": "Justine Stana", + "author_inst": "E. Gulbja Laboratorija" }, { - "author_name": "Dr. Bakulesh M Khamar", - "author_inst": "Cadila Pharmaceuticals Limited, Ahmedabad" + "author_name": "Zane Metla", + "author_inst": "E. Gulbja Laboratorija" }, { - "author_name": "Dr. Suparno Chakrabarti", - "author_inst": "Manashi Chakrabarti Foundation, New Delhi" + "author_name": "Jana Pavare", + "author_inst": "Childrens CIlinical University Hospital, Riga Stradins University" + }, + { + "author_name": "Eriks Tauckels", + "author_inst": "E. Gulbja Laboratorija" + }, + { + "author_name": "Egils Gulbis", + "author_inst": "E. Gulbja Laboratorija" + }, + { + "author_name": "Uga Dumpis", + "author_inst": "Pauls Stradins Clinical University Hospital, University of Latvia" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1115580,89 +1116223,73 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.10.19.20181057", - "rel_title": "Efficacy of stay-at-home policy and transmission of COVID-19 in Toronto, Canada: a mathematical modeling study", + "rel_doi": "10.1101/2020.10.19.20214916", + "rel_title": "From multiplex serology to serolomics: A novel approach to the antibody response against the SARS-CoV-2 proteome", "rel_date": "2020-10-21", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.19.20181057", - "rel_abs": "BackgroundIn many parts of the world, restrictive non-pharmaceutical interventions (NPI) that aim to reduce contact rates, including stay-at-home orders, limitations on gatherings, and closure of public places, are being lifted, with the possibility that the epidemic resurges if alternative measures are not strong enough. Here we aim to capture the combination of use of NPIs and reopening measures which will prevent an infection rebound.\n\nMethodsWe employ an SEAIR model with household structure able to capture the stay-at-home policy (SAHP). To reflect the changes in the SAHP over the course of the epidemic, we vary the SAHP compliance rate, assuming that the time to compliance of all the people requested to stay-at-home follows a Gamma distribution. Using confirmed case data for the City of Toronto, we evaluate basic and instantaneous reproduction numbers and simulate how the average household size, the stay-at-home rate, the efficiency and duration of SAHP implementation, affect the outbreak trajectory.\n\nFindingsThe estimated basic reproduction number R_0 was 2.36 (95% CI: 2.28, 2.45) in Toronto. After the implementation of the SAHP, the contact rate outside the household fell by 39%. When people properly respect the SAHP, the outbreak can be quickly controlled, but extending its duration beyond two months (65 days) had little effect. Our findings also suggest that to avoid a large rebound of the epidemic, the average number of contacts per person per day should be kept below nine. This study suggests that fully reopening schools, offices, and other activities, is possible if the use of other NPIs is strictly adhered to.\n\nInterpretationOur model confirmed that the SAHP implemented in Toronto had a great impact in controlling the spread of COVID-19. Given the lifting of restrictive NPIs, we estimated the thresholds values of maximum number of contacts, probability of transmission and testing needed to ensure that the reopening will be safe, i.e. maintaining an Rt < 1.\n\nResearch in contextO_ST_ABSEvidence before this studyC_ST_ABSA survey on published articles was made through PubMed and Google Scholar searches. The search was conducted from March 1 to August 13, 2020 and all papers published until the end of this research were considered. The following terms were used to screen articles on mathematical models: \"household structure\", \"epidemic model\", \"SARS-CoV-2\", \"COVID-19\", \"household SIR epidemic\", \"household SIS epidemic\", \"household SEIR epidemic\", \"quarantine, isolation model\", \"quarantine model dynamics\", \"structured model isolation\". Any article showing, in the title, application of epidemic models in a specific country/region or infectious diseases rather than SARS-CoV-2 were excluded. Articles in English were considered.\n\nAdded value of this studyWe develop an epidemic model with household structure to study the effects of SAHP on the infection within households and transmission of COVID-19 in Toronto. The complex model provides interesting insights into the effectiveness of SAHP, if the average number of individuals in a household changes. We found that the SAHP might not be adequate if the size of households is relatively large. We also introduce a new quantity called symptomatic diagnosis completion ratio (d_c). This indicator is defined as the ratio of cumulative reported cases and the cumulative cases by episode date at time t, and it is used in the model to inform the implementation of SAHP.\n\nIf cases are diagnosed at the time of symptom onset, isolation will be enforced immediately. A delay in detecting cases will lead to a delay in isolation, with subsequent increase in the transmission of the infection. Comparing different scenarios (before and after reopening phases), we were able to identify thresholds of these factors which mainly affect the spread of the infection: the number of daily tests, average number of contacts per individual, and probability of transmission of the virus. Our results show that if any of the three above mentioned factors is reduced, then the other two need to be adjusted to keep a reproduction number below 1. Lifting restrictive closures will require the average number of contacts a person has each day to be less than pre-COVID-19, and a high rate of case detection and tracing of contacts. The thresholds found will inform public health decisions on reopening.\n\nImplications of all the available evidenceOur findings provide important information for policymakers when planning the full reopening phase. Our results confirm that prompt implementation of SAHP was crucial in reducing the spread of COVID-19. Also, based on our analyses, we propose public health alternatives to consider in view of a full reopening. For example, for different post-reopening scenarios, the average number of contacts per person needs to be reduced if the symptomatic diagnosis completion ratio is low and the probability of transmission increases. Namely, if fewer tests are completed and the usage of NPIs decreases, then the epidemic can be controlled only if individuals can maintain contact with a maximum average number of 4-5 people per person per day. Different recommendations can be provided by relaxing/strengthening one of the above-mentioned factors.", - "rel_num_authors": 19, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.19.20214916", + "rel_abs": "BackgroundThe emerging SARS-CoV-2 pandemic entails an urgent need for specific and sensitive high-throughput serological assays to assess SARS-CoV-2 epidemiology. We therefore aimed at developing a fluorescent-bead based SARS-CoV-2 multiplex serology assay for detection of antibody responses to the SARS-CoV-2 proteome.\n\nMethodsProteins of the SARS-CoV-2 proteome and protein N of SARS-CoV-1 and common cold Coronaviruses (ccCoVs) were recombinantly expressed in E. coli or HEK293 cells. Assay performance was assessed in a Covid-19 case cohort (n=48 hospitalized patients from Heidelberg) as well as n=85 age- and sex-matched pre-pandemic controls from the ESTHER study. Assay validation included comparison with home-made immunofluorescence and commercial Enzyme-linked immunosorbent (ELISA) assays.\n\nResultsA sensitivity of 100% (95% CI: 86%-100%) was achieved in Covid-19 patients 14 days post symptom onset with dual sero-positivity to SARS-CoV-2 N and the receptor-binding domain of the spike protein. The specificity obtained with this algorithm was 100% (95% CI: 96%-100%). Antibody responses to ccCoVs N were abundantly high and did not correlate with those to SARS-CoV-2 N. Inclusion of additional SARS-CoV-2 proteins as well as separate assessment of immunoglobulin (Ig) classes M, A, and G allowed for explorative analyses regarding disease progression and course of antibody response.\n\nConclusionThis newly developed SARS-CoV-2 multiplex serology assay achieved high sensitivity and specificity to determine SARS-CoV-2 sero-positivity. Its high throughput ability allows epidemiologic SARS-CoV-2 research in large population-based studies. Inclusion of additional pathogens into the panel as well as separate assessment of Ig isotypes will furthermore allow addressing research questions beyond SARS-CoV-2 sero-prevalence.", + "rel_num_authors": 15, "rel_authors": [ { - "author_name": "Pei Yuan", - "author_inst": "York University" - }, - { - "author_name": "Juan Li", - "author_inst": "Shanxi University" - }, - { - "author_name": "Elena Aruffo", - "author_inst": "York University" - }, - { - "author_name": "Qi Li", - "author_inst": "Shanghai Normal University" - }, - { - "author_name": "Tingting Zheng", - "author_inst": "Xingjiang University" + "author_name": "Julia Butt", + "author_inst": "DKFZ" }, { - "author_name": "Nicholas Ogden", - "author_inst": "Public Health Agency of Canada" + "author_name": "Rajagopal Murugan", + "author_inst": "DKFZ" }, { - "author_name": "Beate Sander", - "author_inst": "University Health Network" + "author_name": "Theresa Hippchen", + "author_inst": "University Hospital Heidelberg" }, { - "author_name": "Jane Heffernan", - "author_inst": "York University" + "author_name": "Sylvia Olberg", + "author_inst": "University Hospital Heidelberg" }, { - "author_name": "Evgenia Gatov", - "author_inst": "Toronto Public Health" + "author_name": "Monique van Straaten", + "author_inst": "DKFZ" }, { - "author_name": "Effie Gournis", - "author_inst": "Toronto Public Health" + "author_name": "Hedda Wardemann", + "author_inst": "DKFZ" }, { - "author_name": "Sarah Collier", - "author_inst": "Toronto Public Health" + "author_name": "Erec Stebbins", + "author_inst": "DKFZ" }, { - "author_name": "Yi Tan", - "author_inst": "York University" + "author_name": "Hans-Georg Kraeusslich", + "author_inst": "University Hospital Heidelberg" }, { - "author_name": "Jun Li", - "author_inst": "Xidian University" + "author_name": "Ralf Bartenschlager", + "author_inst": "DKFZ" }, { - "author_name": "Julien Arino", - "author_inst": "University of Manitoba" + "author_name": "Hermann Brenner", + "author_inst": "DKFZ" }, { - "author_name": "Jacques Belair", - "author_inst": "University of Montreal" + "author_name": "Vibor Laketa", + "author_inst": "University Hospital Heidelberg" }, { - "author_name": "James Watmough", - "author_inst": "University of New Brunswick Fredericton" + "author_name": "Ben Schoettker", + "author_inst": "DKFZ" }, { - "author_name": "Jude Dzevela Kong", - "author_inst": "York University" + "author_name": "Barbara Mueller", + "author_inst": "University Hospital Heidelberg" }, { - "author_name": "Iain Moyles", - "author_inst": "York University" + "author_name": "Uta Merle", + "author_inst": "University Hospital Heidelberg" }, { - "author_name": "Huaiping Zhu", - "author_inst": "York University" + "author_name": "Tim Waterboer", + "author_inst": "DKFZ" } ], "version": "1", @@ -1117246,35 +1117873,55 @@ "category": "health informatics" }, { - "rel_doi": "10.1101/2020.10.16.20213769", - "rel_title": "Impact of the COVID-19 pandemic on Suicide and Self Harm among Patients Presenting to the Emergency Department of a Teaching Hospital in Nepal", + "rel_doi": "10.1101/2020.10.18.20214767", + "rel_title": "Guiding Austria through the COVID-19 Epidemics with a Forecast-Based Early Warning System", "rel_date": "2020-10-20", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.16.20213769", - "rel_abs": "BackgroundThe COVID-19 pandemic is a global challenge that is not just limited to the physical consequences but also a significant degree of a mental health crisis. Self-harm (SH) and suicide are its extreme effects. The aim of this study was to provide an overview of the impact of the COVID-19 pandemic on the occurrence and clinical profile of suicide and SH in our ED.\n\nMethodsThis is a cross-sectional observational study conducted in the ED of a tertiary care center. Records of all fatal and nonfatal SH patients presenting to the ED during the lockdown period (March 24-June 23, 2020; Period1), matching periods in the previous year (March 24-June 23,2019; Period 2) and 3 months period prior (December 24 2019-March 23, 2020; Period 3) was included by searching the electronic medical record (EMR) system. The prevalence and the clinical profile of the patients were compared between these three periods.\n\nResultsA total of 125 (periods 1=55, 2=38, and 3=32) suicide and SH cases were analyzed. The cases of suicide/SH had increased by 44% and 71.9% during the lockdown period in comparison to the period 2 and 3. Organophosphate poisoning was the most common mode. Females were predominant in all three periods with a mean age of 32 (95%CI: 29.3-34.7). There was a significant delay in arrival of the patients in period 1 (p-value=0.045) with increased hospital admission (p-value =0.009) and in-hospital mortality (18.2% vs 2.6 % and 3.1%) (p-value=.001).\n\nConclusionWe found an increase in patients presenting with suicide and SH in our ED during the pandemic which is likely to reflect an increased prevalence of mental illness in the community. We hope that the result will prime all mental health care stakeholders to initiate mental health screening and intervention for the vulnerable population during this period of crisis.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.18.20214767", + "rel_abs": "In response to the SARS-CoV-2 pandemic, the Austrian governmental crisis unit commissioned a forecast consortium with regularly projections of case numbers and demand for hospital beds. The goal was to assess how likely Austrian ICUs would become overburdened with COVID-19 patients in the upcoming weeks. We consolidated the output of three independent epidemiological models (ranging from agent-based micro simulation to parsimonious compartmental models) and published weekly short-term forecasts for the number of confirmed cases as well as estimates and upper bounds for the required hospital beds. Here, we report on three key contributions by which our forecasting and reporting system has helped shaping Austrias policy to navigate the crisis, namely (i) when and where case numbers and bed occupancy are expected to peak during multiple waves, (ii) whether to ease or strengthen non-pharmaceutical intervention in response to changing incidences, and (iii) how to provide hospital managers guidance to plan health-care capacities. Complex mathematical epidemiological models play an important role in guiding governmental responses during pandemic crises, in particular when they are used as a monitoring system to detect epidemiological change points.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Roshana Shrestha", - "author_inst": "Kathmandu University School of Medical Sciences" + "author_name": "Martin Bicher", + "author_inst": "TU Wien" + }, + { + "author_name": "Martin Zuba", + "author_inst": "Austrian National Public Health Institute" + }, + { + "author_name": "Lukas Rainer", + "author_inst": "Austrian National Public Health Institute" }, { - "author_name": "Shisir Siwakoti", - "author_inst": "Kathmandu University School of Medical Sciences" + "author_name": "Florian Bachner", + "author_inst": "Austrian National Public Health Institute" }, { - "author_name": "Saumya Singh", - "author_inst": "Kathmandu University School of Medical Sciences" + "author_name": "Claire Rippinger", + "author_inst": "dwh Simulation Services GmbH" + }, + { + "author_name": "Herwig Ostermann", + "author_inst": "Austrian National Public Health Institute" }, { - "author_name": "Anmol Purna Shrestha", - "author_inst": "Kathmandu University School of Medical Sciences" + "author_name": "Nikolas Popper", + "author_inst": "TU Wien" + }, + { + "author_name": "Stefan Thurner", + "author_inst": "Medical University of Vienna" + }, + { + "author_name": "Peter Klimek", + "author_inst": "Medical University of Vienna" } ], "version": "1", - "license": "cc_no", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "emergency medicine" + "category": "health policy" }, { "rel_doi": "10.1101/2020.10.16.20213405", @@ -1118616,43 +1119263,203 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2020.10.18.20214601", - "rel_title": "The Response of Pakistani Social Workers amid the COVID-19 Pandemic: A Qualitative Analysis of the Main Challenges", + "rel_doi": "10.1101/2020.10.20.346262", + "rel_title": "Zebrafish studies on the vaccine candidate to COVID-19, the Spike protein: Production of antibody and adverse reaction", "rel_date": "2020-10-20", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.18.20214601", - "rel_abs": "The study aimed to highlight the main challenges faced by the social workers amid the pandemic. A qualitative study was conducted between March 2020 to May 2020 in Karachi, Pakistan. All participants who belonged to a non-profit organization were eligible to participate. Open-ended questions were asked by the participants. The mean age of the participants was 24.8 {+/-} 5.9 years. The main challenges faced by the social workers were: i) resistance from the family and friends, ii) lack of personal protective equipment, iii) mistrust from public, iv) uncooperative government/authorities.", - "rel_num_authors": 6, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2020.10.20.346262", + "rel_abs": "Establishing new experimental animal models to assess the safety and immune response to the antigen used in the development of COVID-19 vaccine is an imperative issue. Based on the advantages of using zebrafish as a model in research, herein we suggest doing this to test the safety of the putative vaccine candidates and to study immune response against the virus. We produced a recombinant N-terminal fraction of the Spike SARS-CoV-2 protein and injected it into adult female zebrafish. The specimens generated humoral immunity and passed the antibodies to the eggs. However, they presented adverse reactions and inflammatory responses similar to severe cases of human COVID-19. The analysis of the structure and function of zebrafish and human Angiotensin-converting enzyme 2, the main human receptor for virus infection, presented remarkable sequence similarities. Moreover, bioinformatic analysis predicted protein-protein interaction of the Spike SARS-CoV-2 fragment and the Toll-like receptor pathway. It might help in the choice of future therapeutic pharmaceutical drugs to be studied. Based on the in vivo and in silico results presented here, we propose the zebrafish as a model for translational research into the safety of the vaccine and the immune response of the vertebrate organism to the SARS-CoV-2 virus.", + "rel_num_authors": 46, "rel_authors": [ { - "author_name": "Kiran Abbas", - "author_inst": "Jinnah Postgraduate Medical Centre" + "author_name": "Bianca H Ventura Fernandes", + "author_inst": "Laboratorio de Controle Genetico e Sanitario, Diretoria Tecnica de Apoio ao Ensino e Pesquisa, Faculdade de Medicina da Universidade de Sao Paulo" + }, + { + "author_name": "Natalia Martins Feitosa", + "author_inst": "Integrated Laboratory of Translational Bioscience (LIBT), Institute of Biodiversity and Sustainability (NUPEM), Federal University of Rio de Janeiro (UFRJ)- Mac" + }, + { + "author_name": "Ana Paula Barbosa", + "author_inst": "Department of Microbiology, Institute of Biomedical Sciences, University of Sao Paulo, Sao Paulo, Brazil." + }, + { + "author_name": "Camila Gasque Bomfim", + "author_inst": "Departamento de Bioquimica, Instituto de Quimica, Universidade de Sao Paulo, Sao Paulo, SP, Brazil, Departamento de Microbiologia, Instituto de Ciencias Biomedi" + }, + { + "author_name": "Anali MB Garnique", + "author_inst": "Department of Cell Biology, Institute of Biomedical Sciences, University of Sao Paulo, Sao Paulo, Brazil." + }, + { + "author_name": "Francisco IF Gomes", + "author_inst": "Department of Pharmacology, Center of Research in Inflammatory Diseases, Ribeirao Preto Medical School, University of Sao Paulo, Ribeirao Preto, Sao Paulo, Braz" + }, + { + "author_name": "Rafael T Nakajima", + "author_inst": "Reproductive and Molecular Biology Group, Department of Morphology, Institute of Biosciences, Sao Paulo State University, Botucatu, Sao Paulo, Brazil." + }, + { + "author_name": "Marco AA Belo", + "author_inst": "Department of Preventive Veterinary Medicine, Sao Paulo State University, Jaboticabal, Sao Paulo, Brazil / Laboratory of Animal Pharmacology and Toxicology, Br" + }, + { + "author_name": "Silas Fernandes Eto", + "author_inst": "Postgraduate Program in Health Sciences, PROCISA, Federal University of Roraima, Brazil." + }, + { + "author_name": "Dayanne Carla Fernandes", + "author_inst": "Immunochemistry Laboratory, Butantan Institute, Sao Paulo, Brazil." + }, + { + "author_name": "Guilherme Malafaia", + "author_inst": "Biological Research Laboratory, Goiano Federal Institute, Urutai Campus, GO, Brazil." + }, + { + "author_name": "Wilson G Manrique", + "author_inst": "Aquaculture Health Research and Extension Group, GRUPESA, Aquaculture Health Laboratory, LABSA, Department of Veterinary Medicine, Federal University of Rondoni" + }, + { + "author_name": "Gabriel Conde", + "author_inst": "Department of Preventive Veterinary Medicine, Sao Paulo State University, Jaboticabal, Sao Paulo, Brazil." + }, + { + "author_name": "Roberta RC Rosales", + "author_inst": "Department of Cell and Molecular Biology, Ribeirao Preto Medical School, University of Sao Paulo, Ribeirao Preto, Sao Paulo, Brazil." + }, + { + "author_name": "Iris Todeschini", + "author_inst": "Departamento de Bioquimica, Instituto de Quimica, Universidade de Sao Paulo, Brazil." }, { - "author_name": "Muhammad Inam UlHaq", - "author_inst": "Shifa College of Medicine" + "author_name": "Ilo Rivero", + "author_inst": "Pontificia Universidade Catolica de Minas Gerais" }, { - "author_name": "Wareesha Afaq Zaidi", - "author_inst": "Shifa College of Medicine" + "author_name": "Edgar Llontop", + "author_inst": "Departamento de Bioquimica, Instituto de Quimica, Universidade de Sao Paulo, Brazil." }, { - "author_name": "Ahmed Kaleem", - "author_inst": "Shifa College of Medicine" + "author_name": "German G Sgro", + "author_inst": "Departamento de Bioquimica, Instituto de Quimica, Universidade de Sao Paulo, Sao Paulo, SP, Brazil, Departamento de Ciencias Biomoleculares, Faculdade de Cienc" }, { - "author_name": "Hamza Sohail", - "author_inst": "Jinnah Sindh Medical University" + "author_name": "Gabriel Umaji Oka", + "author_inst": "Departamento de Bioquimica, Instituto de Quimica, Universidade de Sao Paulo, Brazil." }, { - "author_name": "Moiz Ahmed", - "author_inst": "Jinnah Postgraduate Medical Center" + "author_name": "Natalia Fernanda Bueno", + "author_inst": "Departamento de Bioquimica, Instituto de Quimica, Universidade de Sao Paulo, Sao Paulo, SP, Brazil; Departamento de Microbiologia, Instituto de Ciencias Biomedi" + }, + { + "author_name": "Fausto K Ferraris", + "author_inst": "Department of Pharmacology and Toxicology, Oswaldo Cruz Foundation, FIOCRUZ, Rio de Janeiro, Brazil." + }, + { + "author_name": "Mariana TQ de Magalhaes", + "author_inst": "Department of Biochemistry and Immunology, Institute of Biological Sciences , Federal University of Minas Gerais, Belo Horizonte, Brazil." + }, + { + "author_name": "Renata J Medeiros", + "author_inst": "Laboratory of Physiology, Zebrafish INCQS, Fiocruz Facility, Department of Pharmacology and Toxicology, DFT, INCQS, National Institute for Quality Control in" + }, + { + "author_name": "Juliana MM Gomes", + "author_inst": "Transplantation Immunobiology Lab, Department of Immunology, Institute of Biomedical Sciences, Universidade de Sao Paulo, Brazil." + }, + { + "author_name": "Mara Souza Junqueira", + "author_inst": "Center for Translational Research in Oncology, Cancer Institute of the State of Sao Paulo, Faculty of Medicine, University of Sao Paulo, Sao Paulo, Brazil." + }, + { + "author_name": "Katia Conceicao", + "author_inst": "Laboratory of Peptide Biochemistry, Federal University of Sao Paulo, Brazil." + }, + { + "author_name": "Leticia G. Pontes", + "author_inst": "Laboratory of Human Immunology, Department Immunology, Institute Biomedical Sciences, University Sao Paulo, Sao Paulo, Brazil." + }, + { + "author_name": "Antonio Condino Neto", + "author_inst": "Laboratory of Human Immunology, Department Immunology, Institute Biomedical Sciences, University Sao Paulo, Sao Paulo, Brazil." + }, + { + "author_name": "Andrea C Perez", + "author_inst": "Department of Pharmacology, Universidade Federal de Minas Gerais, Brazil." + }, + { + "author_name": "Leonardo G Barcellos", + "author_inst": "Graduate Program of Pharmacology, Federal University of Santa Maria, Brazil; Laboratory of Fish Physiology, Graduate Program of Bioexperimentation and of Enviro" + }, + { + "author_name": "Jose Dias Correa Junior", + "author_inst": "Laboratorio do Estudo da Interacao Quimico Biologica e da Reproducao Animal, LIQBRA, Bloco O3,174, Departamento de Morfologia Instituto de Ciencias Biologicas, " + }, + { + "author_name": "Erick Gustavo Dorlass", + "author_inst": "Department of Microbiology, Institute of Biomedical Sciences, University of Sao Paulo, Sao Paulo, Brazil." + }, + { + "author_name": "Niels OS Camara", + "author_inst": "Transplantation Immunobiology Lab, Department of Immunology, Institute of Biomedical Sciences, Universidade de Sao Paulo, Brazil." + }, + { + "author_name": "Edison Luiz Durigon", + "author_inst": "Department of Microbiology, Institute of Biomedical Sciences, University of Sao Paulo, Sao Paulo, Brazil." + }, + { + "author_name": "Fernando Q Cunha", + "author_inst": "Department of Pharmacology, Center of Research in Inflammatory Diseases, Ribeirao Preto Medical School, University of Sao Paulo, Ribeirao Preto, Sao Paulo, Braz" + }, + { + "author_name": "Rafael H Nobrega", + "author_inst": "Reproductive and Molecular Biology Group, Department of Morphology, Institute of Biosciences, Sao Paulo State University, Botucatu, Sao Paulo, Brazil." + }, + { + "author_name": "Glaucia M Machado-Santelli", + "author_inst": "Department of Cell Biology, Institute of Biomedical Sciences, University of Sao Paulo, Sao Paulo, Brazil." + }, + { + "author_name": "Chuck S Farah", + "author_inst": "Departamento de Bioquimica, Instituto de Quimica, Universidade de Sao Paulo, Brazil." + }, + { + "author_name": "Flavio P Veras", + "author_inst": "Center of Research in Inflammatory Diseases, Ribeirao Preto Medical School, University of Sao Paulo, Ribeirao Preto, Sao Paulo, Brazil; Department of Pharmacolo" + }, + { + "author_name": "Jorge Galindo-Villegas", + "author_inst": "Faculty of Biosciences and Aquaculture, Nord University, 8049 Bodo, Norway" + }, + { + "author_name": "Leticia Costa-Lotufo", + "author_inst": "Department of Pharmacology, Institute of Biomedical Sciences, Universidade de Sao Paulo, Brazil." + }, + { + "author_name": "Thiago M Cunha", + "author_inst": "Center of Research in Inflammatory Diseases, Ribeirao Preto Medical School, University of Sao Paulo, Ribeirao Preto, Sao Paulo, Brazil; Department of Pharmacolo" + }, + { + "author_name": "Roger Chammas", + "author_inst": "Laboratorio de Controle Genetico e Sanitario, Diretoria Tecnica de Apoio ao Ensino e Pesquisa, Faculdade de Medicina da Universidade de Sao Paulo; Centro de Inv" + }, + { + "author_name": "Luciani R. Carvalho", + "author_inst": "Laboratorio de Controle Genetico e Sanitario, Diretoria Tecnica de Apoio ao Ensino e Pesquisa, Faculdade de Medicina da Universidade de Sao Paulo; Disciplina de" + }, + { + "author_name": "Cristiane R. Guzzo", + "author_inst": "Department of Microbiology, Institute of Biomedical Sciences, University of Sao Paulo, Sao Paulo, Brazil." + }, + { + "author_name": "Ives Charlie-Silva", + "author_inst": "Department of Pharmacology, Institute of Biomedical Sciences, Universidade de Sao Paulo, Brazil." } ], "version": "1", - "license": "cc_by_nc_nd", - "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "license": "cc_by", + "type": "new results", + "category": "immunology" }, { "rel_doi": "10.1101/2020.10.20.346916", @@ -1120274,18 +1121081,63 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.10.16.20213967", - "rel_title": "National Routine Adult Immunization Programs among World Health Organization Member States: An Assessment of Health Systems to Deploy Future SARS-CoV-2 Vaccines", + "rel_doi": "10.1101/2020.10.16.20211029", + "rel_title": "Three-month outcomes in hospitalized COVID-19 patients", "rel_date": "2020-10-18", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.16.20213967", - "rel_abs": "IntroductionAs the SARS-CoV-2 pandemic disproportionately affects older adults, future pandemic vaccine response will rely on existing adult immunization infrastructures.\n\nMethodsWe evaluated the 2018 WHO/UNICEF Joint Reporting Form on Immunization for country reports on adult immunization programs. We described countries with programs and used multivariable regression to identify independent factors associated with having them.\n\nResultsOf 194 WHO Member States, 120 (62%) reported having any adult vaccination program. The Americas and Europe had the most adult immunization programs, most commonly Hepatitis B and influenza vaccines (>45% and >90% of countries). Africa and South-East Asia had the fewest adult immunization programs, with <11% of countries reporting any adult immunization programs for influenza or hepatitis vaccines, and none for pneumococcal vaccines. In bivariate analyses, high- or upper-middle income, introduction of new or underused vaccines, having achieved pediatric vaccine coverage goals, and meeting National Immunization Technical Advisory Groups basic functional indicators were significantly associated (p<0.001) with having any adult immunization programs. In multivariable analyses, the factor most strongly associated with adult immunization programs was country income, with high- or upper-middle income countries significantly more likely to report having a program (aOR 19.3, 95% CI 6.5, 57.7).\n\nDiscussionThat 38% of countries lack functional platforms for adult immunization has major implications for future SARS-CoV-2 vaccine deployment. Systems for vaccine storage and handling, delivery, and waste management for adult immunization do not exist in much of the world. Developing countries should strengthen immunization programs to reach adults with SARS-CoV-2 vaccines when they become available.", - "rel_num_authors": 0, - "rel_authors": null, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.16.20211029", + "rel_abs": "COVID-19 is an ongoing pandemic with a devastating impact on public health. Acute neurological symptoms have been reported after a COVID-19 diagnosis, however there is no data available on the long-term neurological symptoms. Using a prospective registry of hospitalized COVID-19 patients, we assessed the neurological assessments (including functional, cognitive and psychiatric assessments) of several hospitalized patients at 3 months. Our main finding is that 71% of the patients still experienced neurological symptoms at 3 months and the most common symptoms being fatigue (42%) and PTSD (29%). 64% of the patients report pain symptoms we well. Cognitive symptoms were found in 12%. Our preliminary findings suggests the importance of investigating long-term and rationalizes the need for further studies investigating the neurologic outcomes after COVID-19.", + "rel_num_authors": 11, + "rel_authors": [ + { + "author_name": "Jude P Savarraj", + "author_inst": "University of Texas Health Science Center at Houston" + }, + { + "author_name": "Angela B Burkett", + "author_inst": "University of Texas Health Science Center" + }, + { + "author_name": "Sarah N Hinds", + "author_inst": "University of Texas Health Science Center at Houston" + }, + { + "author_name": "Atzhiry S Paz", + "author_inst": "University of Texas Health Science Center" + }, + { + "author_name": "Andres R Assing", + "author_inst": "University of Texas Health Science Center" + }, + { + "author_name": "Shivanki Juneja", + "author_inst": "University of Texas Health Science Center" + }, + { + "author_name": "Gabriela D Colpo", + "author_inst": "University of Texas Health Science Center" + }, + { + "author_name": "Luis F Torres", + "author_inst": "University of Texas Health Science Center" + }, + { + "author_name": "Aaron M Gusdon", + "author_inst": "University of Texas Health Science Center" + }, + { + "author_name": "Louise McCullough", + "author_inst": "University of Texas Health Science Center" + }, + { + "author_name": "Huimahn A Choi", + "author_inst": "University of Texas Health Science Center" + } + ], "version": "1", - "license": "cc_by_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "neurology" }, { "rel_doi": "10.1101/2020.10.17.339051", @@ -1122063,43 +1122915,71 @@ "category": "molecular biology" }, { - "rel_doi": "10.1101/2020.10.16.342428", - "rel_title": "The Theory and Practice of the viral dose in neutralization assay: insights on SARS-CoV-2 \"doublethink\" effect.", + "rel_doi": "10.1101/2020.10.16.341883", + "rel_title": "The effect of temperature and humidity on the stability of SARS-CoV-2 and other enveloped viruses", "rel_date": "2020-10-16", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.10.16.342428", - "rel_abs": "Due to the global spread of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), there is an urgent need for reliable high-throughput serological assays in order to evaluate the immunological responses against SARS-COV-2 virus and to enable population screening, as well as vaccines and drugs efficacy testing. Several serological assays for SARS-CoV-2 are now becoming available in the market. However, it has also become extremely important to have well-established assays with desirable high sensitivity and specificity. To date, the micro-neutralization (MN) assay, is currently considered the gold-standard being capable of evaluating and detecting, functional neutralizing antibodies (nAbs). Several protocols exist for microneutralization assays which vary in several steps of the protocol: cell seeding conditions, number of cells seeded, virus amount used in the infection step, virus-serum-cells incubation period etc. These potential differences account for a high degree of variability and inconsistency of the results and using a harmonized protocol for the micro-neutralization assay could potentially solve this.\n\nGiven this situation, the main aim of our study was to carry out SARS-CoV-2 wild type virus MN assay in order to investigate which optimal tissue culture infective dose 50 (TCID50) infective dose in use is the most adequate choice for implementation in terms of reproducibility, standardization possibilities and comparability of results. Therefore, we assessed the MN by using two different viral infective doses: a standard dose of 100 TCID50/well and a lower dose of 25 TCID50/well. The results obtained, yielded by MN on using the lower infective dose (25 TCID50), were in line with those obtained with the standard infective dose; in some cases, however, we detected a titre that was one or two dilution steps higher, which maintained all negative samples negative. This suggesting that the lower dose can potentially have a positive impact on the detection and estimation of neutralizing antibodies present in a given sample, showing higher sensitivity but similar specificity and therefore, it would require a more accurate assessment and cross-laboratories standardisation especially when MN is employed as serological assay of choice for pre-clinical and clinical studies.", - "rel_num_authors": 6, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.10.16.341883", + "rel_abs": "Environmental conditions affect virus inactivation rate and transmission potential. Understanding those effects is critical for anticipating and mitigating epidemic spread. Ambient temperature and humidity strongly affect the inactivation rate of enveloped viruses, but a mechanistic, quantitative theory of those effects has been elusive. We measure the stability of the enveloped respiratory virus SARS-CoV-2 on an inert surface at nine temperature and humidity conditions and develop a mechanistic model to explain and predict how temperature and humidity alter virus inactivation. We find SARS-CoV-2 survives longest at low temperatures and extreme relative humidities; median estimated virus half-life is over 24 hours at 10 {degrees}C and 40 % RH, but approximately 1.5 hours at 27 {degrees}C and 65 % RH. Our mechanistic model uses simple chemistry to explain the increase in virus inactivation rate with increased temperature and the U-shaped dependence of inactivation rate on relative humidity. The model accurately predicts quantitative measurements from existing studies of five different human coronaviruses (including SARS-CoV-2), suggesting that shared mechanisms may determine environmental stability for many enveloped viruses. Our results indicate scenarios of particular transmission risk, point to pandemic mitigation strategies, and open new frontiers in the mechanistic study of virus transmission.", + "rel_num_authors": 13, "rel_authors": [ { - "author_name": "Eleonora Molesti", - "author_inst": "Vismederi Research s.r.l." + "author_name": "Dylan H. Morris", + "author_inst": "Princeton University" + }, + { + "author_name": "Kwe Claude H. Yinda", + "author_inst": "National Institute of Allergy and Infectious Diseases" }, { - "author_name": "Alessandro Manenti", - "author_inst": "Vismederi s.r.l. and Vismederi Research s.r.l." + "author_name": "Amandine Gamble", + "author_inst": "University of California, Los Angeles" }, { - "author_name": "Marta Maggetti", - "author_inst": "Vismederi s.r.l." + "author_name": "Fernando W. Rossine", + "author_inst": "Princeton University" }, { - "author_name": "Giulia Lapini", - "author_inst": "Vismederi s.r.l." + "author_name": "Qishen Huang", + "author_inst": "Virginia Tech" }, { - "author_name": "Alessandro Torelli", - "author_inst": "Vismederi s.r.l." + "author_name": "Trenton Bushmaker", + "author_inst": "National Institute of Allergy and Infectious Diseases" }, { - "author_name": "Emanuele Montomoli", - "author_inst": "Vismederi s.r.l. and Universita degli Studi di Siena" + "author_name": "Robert J Fischer", + "author_inst": "National Institute of Allergy and Infectious Diseases" + }, + { + "author_name": "M. Jeremiah Matson", + "author_inst": "National Institute of Allergy and Infectious Diseases" + }, + { + "author_name": "Neeltje van Doremalen", + "author_inst": "National Institute of Allergy and Infectious Diseases" + }, + { + "author_name": "Peter J Vikesland", + "author_inst": "Virginia Tech" + }, + { + "author_name": "Linsey C. Marr", + "author_inst": "Virginia Tech" + }, + { + "author_name": "Vincent Munster", + "author_inst": "NIAID" + }, + { + "author_name": "James O Lloyd-Smith", + "author_inst": "University of California Los Angeles" } ], "version": "1", - "license": "cc_by_nc_nd", - "type": "confirmatory results", - "category": "immunology" + "license": "cc_no", + "type": "new results", + "category": "microbiology" }, { "rel_doi": "10.1101/2020.10.16.342782", @@ -1123581,35 +1124461,47 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2020.10.11.20210906", - "rel_title": "High Food Insecurity in Latinx Families and Associated COVID-19 Infection in the Greater Bay Area, California", + "rel_doi": "10.1101/2020.10.12.20211342", + "rel_title": "Network Graph Representation of COVID-19 Scientific Publications to Aid Knowledge Discovery", "rel_date": "2020-10-14", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.11.20210906", - "rel_abs": "BackgroundFood insecurity impacts nearly one-in-four Latinx households in the United States and has been exacerbated by the novel coronavirus or COVID-19 pandemic.\n\nMethodsWe examined the impact of COVID-19 on household and child food security in three preexisting, longitudinal, Latinx urban cohorts in the San Francisco Bay Area (N=375 households, 1,875 individuals). Households were initially recruited during pregnancy and postpartum at Zuckerberg San Francisco General Hospital (ZSFG) and UCSF Benioff prior to the COVID-19 pandemic. For this COVID sub-study, participants responded to a 15-minute telephonic interview. Participants answered 18 questions from the US Food Security Food Module (US HFSSM), described food consumption, housing and employment status, and history of COVID-19 infection as per community or hospital-based testing. Food security and insecurity levels were compared with prior year metrics.\n\nResultsWe found low levels of household food security in Latinx families (by cohort: 29.2%; 34.2%; 60.0%) and child food security (56.9%; 54.1%; 78.0%) with differences between cohorts explained by self-reported levels of education and employment status. Food security levels were much lower than those reported previously in two cohorts where data had been recorded from prior years. Reported history of COVID-19 infection in households was 4.8% (95% Confidence Interval (CI); 1.5-14.3%); 7.2% (95%CI; 3.6-13.9%) and 3.5% (95%CI; 1.7-7.2%) by cohort and was associated with food insecurity in the two larger cohorts (p=0.03; p=0.01 respectively).\n\nConclusionsLatinx families in the Bay Area with children are experiencing a sharp rise in food insecurity levels during the COVID-19 epidemic. Food insecurity, similar to other indices of poverty, is associated with increased risk for COVID-19 infection. Comprehensive interventions are needed to address food insecurity in Latinx populations and further studies are needed to better assess independent associations between household food insecurity, poor nutritional health and risk of COVID-19 infection.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.12.20211342", + "rel_abs": "IntroductionNumerous scientific journal articles have been rapidly published related to COVID-19 making navigation and understanding of relationships difficult.\n\nMethodsA graph network was constructed from the publicly available CORD-19 database of COVID-19-related publications using an engine leveraging medical knowledgebases to identify discrete medical concepts and an open source tool (Gephi) used to visualise the network.\n\nResultsThe network shows connections between disease, medication and procedures identified from title and abstracts of 195,958 COVID-19 related publications (CORD-19 Dataset). Connections between terms with few publications, those unconnected to the main network and those irrelevant were not displayed. Nodes were coloured by knowledgebase and node size related to the number of publications containing the term. The dataset and visualisations made publicly accessible via a webtool.\n\nConclusionKnowledge management approaches (text mining and graph networks) can effectively allow rapid navigation and exploration of entity interrelationships to improve understanding of diseases such as COVID-19.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Milagro Escobar", - "author_inst": "UCSF" + "author_name": "George Cernile", + "author_inst": "Inspirata Ltd" }, { - "author_name": "Andrea DeCastro Mendez", - "author_inst": "UCSF" + "author_name": "Trevor Heritage", + "author_inst": "Inspirata Ltd" }, { - "author_name": "Maria Romer Encinas", - "author_inst": "UCSF" + "author_name": "Neil Sebire", + "author_inst": "HDRUK London UK" }, { - "author_name": "Janet Wojcicki", - "author_inst": "UCSF" + "author_name": "Ben Gordon", + "author_inst": "HDRUK London UK" + }, + { + "author_name": "Taralyn Schwering", + "author_inst": "Inspirata Ltd" + }, + { + "author_name": "Shana Kazemlou", + "author_inst": "Inspirata Ltd" + }, + { + "author_name": "Yulia Borecki", + "author_inst": "Inspirata Ltd" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "nutrition" + "category": "health informatics" }, { "rel_doi": "10.1101/2020.10.11.20211052", @@ -1125283,35 +1126175,31 @@ "category": "allergy and immunology" }, { - "rel_doi": "10.1101/2020.10.13.20212126", - "rel_title": "Epidemiologial Analysis of Patients Presenting to a West London District General Hospital Requiring Admission with Covid-19", + "rel_doi": "10.1101/2020.10.12.20211201", + "rel_title": "Mathematical Perspective of Covid-19 Pandemic: Disease Extinction Criteria in Deterministic and Stochastic Models", "rel_date": "2020-10-14", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.13.20212126", - "rel_abs": "BackgroundCoronavirus has lead to significant morbidity and mortality both within the UK and worldwide. We hypothesise there are local clusters of coronavirus which would therefore be amenable to targeted public health measures.\n\nMethodsThis is a retrospective, observational case series conducted in a West London District General Hospital. All patients admitted to hospital with a radiological or microbiological diagnosis of Covid-19 were included (children under 16 years were excluded). Consecutive sampling was used and baseline characteristics including age, sex, postcode and final patient outcome were collected from the electronic health records. Patient origin postcode was plotted to a map of the local area and an online cloud based mapping analysis system was used to generate heat maps and case density maps which were compared to living base layers. The primary outcome was identification of local clusters of cases of coronavirus. Secondary outcome was identification of population characteristics that may provide evidence for more targetted public health intervention in a second wave.\n\nResultsLocal clusters of infection were identified within the target population. These appeared to correlate with higher indices of deprivation, poorer overall health and high household occupancy suggesting a role for public health measures to target these areas.\n\nConclusionThere is a role for targeted public health measures in tackling the spread of coronavirus, paying particular attention to those who live in more deprived areas.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.12.20211201", + "rel_abs": "The world has been facing the biggest virological invasion in the form of Covid-19 pandemic since the beginning of the year 2020. In this paper, we consider a deterministic epidemic model of four compartments classified based on the health status of the populations of a given country to capture the disease progression. A stochastic extension of the deterministic model is further considered to capture the uncertainty or variation observed in the disease transmissibility. In the case of a deterministic system, the disease-free equilibrium will be globally asymptotically stable if the basic reproduction number is less than unity, otherwise, the disease persists. Using Lyapunov functional methods, we prove that the infected population of the stochastic system tends to zero exponentially almost surely if the basic reproduction number is less than unity. The stochastic system has no interior equilibrium, however, its asymptotic solution is shown to fluctuate around the endemic equilibrium of the deterministic system under some parametric restrictions, implying that the infection persists. A case study with the Covid-19 epidemic data of Spain is presented and various analytical results have been demonstrated. The epidemic curve in Spain clearly shows two waves of infection. The first wave was observed during March-April and the second wave started in the middle of July and not completed yet. A real-time basic reproduction number has been given to illustrate the epidemiological status of Spain throughout the study period. Estimated cumulative numbers of confirmed and death cases are 1,613,626 and 42,899, respectively, with case fatality rate 2.66 per cent till the deadly virus is eliminated from Spain.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Eleanor Heald", - "author_inst": "West Middlesex University Hospital" - }, - { - "author_name": "Natalie Ring", - "author_inst": "West Middlesex University Hospital" + "author_name": "Debadatta Adak", + "author_inst": "Maharaja Bir Bikram University, Tripure, Agartala, India" }, { - "author_name": "Dinesh Vatvani", - "author_inst": "None" + "author_name": "Abhijit Majumder", + "author_inst": "Centre for Mathematical Biology and Ecology, Department of Mathematics, Jadavpur University, Kolkata, India" }, { - "author_name": "David Shackleton", - "author_inst": "West Middlesex University Hospital" + "author_name": "Nandadulal Bairagi", + "author_inst": "Jadavpur University" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "emergency medicine" + "category": "epidemiology" }, { "rel_doi": "10.1101/2020.10.13.20212175", @@ -1126873,127 +1127761,55 @@ "category": "physiology" }, { - "rel_doi": "10.1101/2020.10.14.337535", - "rel_title": "Immunogenicity of novel mRNA COVID-19 vaccine MRT5500 in mice and non-human primates", + "rel_doi": "10.1101/2020.10.14.339515", + "rel_title": "The viral protein NSP1 acts as a ribosome gatekeeper for shutting down host translation and fostering SARS-CoV-2 translation", "rel_date": "2020-10-14", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.10.14.337535", - "rel_abs": "An effective vaccine to address the global pandemic of coronavirus disease 2019 (COVID-19) is an urgent public health priority1. Novel synthetic mRNA and vector-based vaccine technologies offer an expeditious development path alternative to traditional vaccine approaches. Here we describe the efforts to utilize an mRNA platform for rational design and evaluations of mRNA vaccine candidates based on Spike (S) glycoprotein of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), the virus causing COVID-19. Several mRNA constructs expressing various structural conformations of S-protein, including wild type (WT), a pre-fusion stabilized mutant (2P), a furin cleavage-site mutant (GSAS) and a double mutant form (2P/GSAS), were tested in a preclinical animal model for their capacity to elicit neutralizing antibodies (nAbs). The lead 2P/GSAS candidate was further assessed in dose-ranging studies in mice and Cynomolgus macaques. The selected 2P/GSAS vaccine formulation, now designated MRT5500, elicited potent nAbs as measured in two types of neutralization assays. In addition, MRT5500 elicited TH1-biased responses in both mouse and non-human primate species, a result that helps to address a hypothetical concern regarding potential vaccine-associated enhanced respiratory diseases associated with TH2-biased responses. These data position MRT5500 as a viable vaccine candidate for clinical development against COVID-19.", - "rel_num_authors": 27, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.10.14.339515", + "rel_abs": "SARS-CoV-2 coronavirus is responsible for Covid-19 pandemic. In the early phase of infection, the single-strand positive RNA genome is translated into non-structural proteins (NSP). One of the first proteins produced during viral infection, NSP1, binds to the host ribosome and blocks the mRNA entry channel. This triggers translation inhibition of cellular translation. In spite of the presence of NSP1 on the ribosome, viral translation proceeds however. The molecular mechanism of the so-called viral evasion to NSP1 inhibition remains elusive. Here, we confirm that viral translation is maintained in the presence of NSP1. The evasion to NSP1-inhibition is mediated by the cis-acting RNA hairpin SL1 in the 5UTR of SARS-CoV-2. NSP1-evasion can be transferred on a reporter transcript by SL1 transplantation. The apical part of SL1 is only required for viral translation. We show that NSP1 remains bound on the ribosome during viral translation. We suggest that the interaction between NSP1 and SL1 frees the mRNA accommodation channel while maintaining NSP1 bound to the ribosome. Thus, NSP1 acts as a ribosome gatekeeper, shutting down host translation or fostering SARS-CoV-2 translation depending on the presence of the SL1 5UTR hairpin. SL1 is also present and necessary for translation of sub-genomic RNAs in the late phase of the infectious program. Consequently, therapeutic strategies targeting SL1 should affect viral translation at early and late stages of infection. Therefore, SL1 might be seen as a genuine Achille heel of the virus.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Kirill V Kalnin", - "author_inst": "Sanofi Pasteur" - }, - { - "author_name": "Timothy Plitnik", - "author_inst": "Yoh Services LLC" - }, - { - "author_name": "Michael Kishko", - "author_inst": "Sanofi Pasteur" - }, - { - "author_name": "Jinrong Zhang", - "author_inst": "Sanofi Pasteur" - }, - { - "author_name": "Donghui Zhang", - "author_inst": "Sanofi Pasteur" - }, - { - "author_name": "Andrien Beauvais", - "author_inst": "Sanofi Pasteur" + "author_name": "Antonin Tidu", + "author_inst": "Institut de Biologie Moleculaire et Cellulaire, Architecture et Reactivite de l ARN CNRS UPR9002, Universite de Strasbourg, 3, allee Roetgen, F-67084 Strasbourg" }, { - "author_name": "Natalie G Anosova", - "author_inst": "Sanofi Pasteur" - }, - { - "author_name": "Timothy Tibbitts", - "author_inst": "Sanofi Pasteur" - }, - { - "author_name": "Joshua M DiNapoli", - "author_inst": "Sanofi Pasteur" - }, - { - "author_name": "Po-Wei D Huang", - "author_inst": "Sanofi Pasteur" - }, - { - "author_name": "James Huleatt", - "author_inst": "Sanofi Pasteur" - }, - { - "author_name": "Deanne Vincent", - "author_inst": "Sanofi Pasteur" - }, - { - "author_name": "Katherine Fries", - "author_inst": "Sanofi Pasteur" - }, - { - "author_name": "Shrirang Karve", - "author_inst": "Translate Bio" - }, - { - "author_name": "Rebecca Goldman", - "author_inst": "Sanofi Pasteur" - }, - { - "author_name": "Hardip Gopani", - "author_inst": "Translate Bio" - }, - { - "author_name": "Anusha Dias", - "author_inst": "Translate Bio" - }, - { - "author_name": "Khang Tran", - "author_inst": "Translate Bio" - }, - { - "author_name": "Minnie Zacharia", - "author_inst": "Translate Bio" + "author_name": "Aurelie Janvier", + "author_inst": "Institut de Biologie Moleculaire et Cellulaire, Architecture et Reactivite de l ARN CNRS UPR9002, Universite de Strasbourg, 3, allee Roetgen, F-67084 Strasbourg" }, { - "author_name": "Xiaobo Gu", - "author_inst": "Translate Bio" + "author_name": "Laure Schaeffer", + "author_inst": "Institut de Biologie Moleculaire et Cellulaire, Architecture et Reactivite de l ARN CNRS UPR9002, Universite de Strasbourg, 3, allee Roetgen, F-67084 Strasbourg" }, { - "author_name": "Lianne Boeglin", - "author_inst": "Translate Bio" + "author_name": "Piotr Sosnowski", + "author_inst": "Institut de Biologie Moleculaire et Cellulaire, Architecture et Reactivite de l ARN CNRS UPR9002, Universite de Strasbourg, 3, allee Roetgen, F-67084 Strasbourg" }, { - "author_name": "Sudha Chivukula", - "author_inst": "Sanofi Pasteur" + "author_name": "Lauriane Kuhn", + "author_inst": "Institut de Biologie Moleculaire et Cellulaire, Plateforme Proteomique Strasbourg Esplanade, CNRS FRC1589, Universite de Strasbourg, 3, allee Roetgen, F-67084 S" }, { - "author_name": "Ron Swearingen", - "author_inst": "Translate Bio" + "author_name": "Philippe Hammann", + "author_inst": "Institut de Biologie Moleculaire et Cellulaire, Plateforme Proteomique Strasbourg Esplanade, CNRS FRC1589, Universite de Strasbourg, 3, allee Roetgen, F-67084 S" }, { - "author_name": "Victoria Landolfi", - "author_inst": "Sanofi Pasteur" - }, - { - "author_name": "Tong-Ming Fu", - "author_inst": "Sanofi Pasteur" + "author_name": "Eric Westhof", + "author_inst": "Institut de Biologie Moleculaire et Cellulaire, Architecture et Reactivite de l ARN CNRS UPR9002, Universite de Strasbourg, 3, allee Roetgen, F-67084 Strasbourg" }, { - "author_name": "Frank DeRosa", - "author_inst": "Translate Bio" + "author_name": "Gilbert Eriani", + "author_inst": "Institut de Biologie Moleculaire et Cellulaire, Architecture et Reactivite de l ARN CNRS UPR9002, Universite de Strasbourg, 3, allee Roetgen, F-67084 Strasbourg" }, { - "author_name": "Danilo Casimiro", - "author_inst": "Sanofi Pasteur" + "author_name": "Franck Martin", + "author_inst": "Institut de Biologie Moleculaire et Cellulaire, Architecture et Reactivite de l ARN CNRS UPR9002, Universite de Strasbourg, 3, allee Roetgen, F-67084 Strasbourg" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "new results", - "category": "immunology" + "category": "molecular biology" }, { "rel_doi": "10.1101/2020.10.14.340091", @@ -1129006,47 +1129822,51 @@ "category": "biochemistry" }, { - "rel_doi": "10.1101/2020.10.13.308676", - "rel_title": "A 3D Structural Interactome to Explore the Impact of Evolutionary Divergence, Population Variation, and Small-molecule Drugs on SARS-CoV-2-Human Protein-Protein Interactions", + "rel_doi": "10.1101/2020.10.13.331306", + "rel_title": "Pilot production of SARS-CoV-2 related proteins in plants: a proof of concept for rapid repurposing of indoors farms into biomanufacturing facilities", "rel_date": "2020-10-13", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.10.13.308676", - "rel_abs": "The recent COVID-19 pandemic has sparked a global public health crisis. Vital to the development of informed treatments for this disease is a comprehensive understanding of the molecular interactions involved in disease pathology. One lens through which we can better understand this pathology is through the network of protein-protein interactions between its viral agent, SARS-CoV-2, and its human host. For instance, increased infectivity of SARS-CoV-2 compared to SARS-CoV can be explained by rapid evolution along the interface between the Spike protein and its human receptor (ACE2) leading to increased binding affinity. Sequence divergences that modulate other protein-protein interactions may further explain differences in transmission and virulence in this novel coronavirus. To facilitate these comparisons, we combined homology-based structural modeling with the ECLAIR pipeline for interface prediction at residue resolution, and molecular docking with PyRosetta. This enabled us to compile a novel 3D structural interactome meta-analysis for the published interactome network between SARS-CoV-2 and human. This resource includes docked structures for all interactions with protein structures, enrichment analysis of variation along interfaces, predicted {Delta}{Delta}G between SARS-CoV and SARS-CoV-2 variants for each interaction, predicted impact of natural human population variation on binding affinity, and a further prioritized set of drug repurposing candidates predicted to overlap with protein interfaces{dagger}. All predictions are available online{dagger} for easy access and are continually updated when new interactions are published.\n\n {dagger}Some sections of this pre-print have been redacted to comply with current bioRxiv policy restricting the dissemination of purely in silico results predicting potential therapies for SARS-CoV-2 that have not undergone thorough peer-review. The results section titled \"Prioritization of Candidate Inhibitors of SARS-CoV-2-Human Interactions Through Binding Site Comparison,\" Figure 4, Supplemental Table 9, and all links to our web resource have been removed. Blank headers left in place to preserve structure and item numbering. Our full manuscript will be published in an appropriate journal following peer-review.", - "rel_num_authors": 7, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.10.13.331306", + "rel_abs": "The current CoVid-19 crisis is revealing the strengths and the weaknesses of the worlds capacity to respond to a global health crisis. A critical weakness has resulted from the excessive centralization of the current biomanufacturing capacities, a matter of great concern, if not a source of nationalistic tensions. On the positive side, scientific data and information have been shared at an unprecedented speed fuelled by the preprint phenomena, and this has considerably strengthened our ability to develop new technology-based solutions. In this work we explore how, in a context of rapid exchange of scientific information, plant biofactories can serve as a rapid and easily adaptable solution for local manufacturing of bioreagents, more specifically recombinant antibodies. For this purpose, we tested our ability to produce, in the framework of an academic lab and in a matter of weeks, milligram amounts of six different recombinant monoclonal antibodies against SARS-CoV-2 in Nicotiana benthamiana. For the design of the antibodies we took advantage, among other data sources, of the DNA sequence information made rapidly available by other groups in preprint publications. mAbs were all engineered as single-chain fragments fused to a human gamma Fc and transiently expressed using a viral vector. In parallel, we also produced the recombinant SARS-CoV-2 N protein and its Receptor Binding Domain (RBD) in planta and used them to test the binding specificity of the recombinant mAbs. Finally, for two of the antibodies we assayed a simple scale-up production protocol based on the extraction of apoplastic fluid. Our results indicate that gram amounts of anti-SARS-CoV-2 antibodies could be easily produced in little more than 6 weeks in repurposed greenhouses with little infrastructure requirements using N. benthamiana as production platform. Similar procedures could be easily deployed to produce diagnostic reagents and, eventually, could be adapted for rapid therapeutic responses.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Shayne Davis Wierbowski", - "author_inst": "Cornell University" + "author_name": "Borja Diego-Martin", + "author_inst": "IBMCP-CSIC-UPV" }, { - "author_name": "Siqi Liang", - "author_inst": "Cornell University" + "author_name": "Beatriz Gonz\u00e1lez", + "author_inst": "IBMCP-CSIC-UPV" }, { - "author_name": "You Chen", - "author_inst": "Cornell University" + "author_name": "Marta Vazquez-Vilar", + "author_inst": "IBMCP-CSIC-UPV" }, { - "author_name": "Nicole Marie Andre", - "author_inst": "Cornell University" + "author_name": "Sara Selma", + "author_inst": "IBMCP-CSIC-UPV" }, { - "author_name": "Steven M Lipkin", - "author_inst": "Weill-Cornell Medicine" + "author_name": "Rub\u00e9n Mateos-Fern\u00e1ndez", + "author_inst": "IBMCP-CSIC-UPV" }, { - "author_name": "Gary R Whittaker", - "author_inst": "Cornell University" + "author_name": "Silvia Gianoglio", + "author_inst": "IBMCP-CSIC-UPV" }, { - "author_name": "Haiyuan Yu", - "author_inst": "Cornell University" + "author_name": "Asun Fern\u00e1ndez-del-Carmen", + "author_inst": "IBMCP-CSIC-UPV" + }, + { + "author_name": "Diego Orzaez", + "author_inst": "CSIC" } ], "version": "1", "license": "cc_by_nc_nd", "type": "new results", - "category": "systems biology" + "category": "synthetic biology" }, { "rel_doi": "10.1101/2020.10.11.20210799", @@ -1130687,45 +1131507,41 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.10.07.20208686", - "rel_title": "An Innovative Non-Pharmaceutical Intervention to Mitigate SARS-CoV02 Spread: Probability Sampling to Identify and Isolate Asymptomatic Cases", + "rel_doi": "10.1101/2020.10.07.20208421", + "rel_title": "Forecasting COVID-19 cases in the Philippines using various mathematical models", "rel_date": "2020-10-12", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.07.20208686", - "rel_abs": "Studies estimate that a substantial proportion of SARS-CoV-2 transmission occurs through individuals who do not exhibit symptoms. Mitigation strategies test only those who are moderately to severely symptomatic, excluding the substantial portion of cases that are asymptomatic yet still infectious and likely responsible for a large proportion of the virus spread (1-8). While isolating asymptomatic cases will be necessary to effectively control viral spread, these cases are functionally invisible and there is no current method to identify them for isolation. To address this major omission in COVID-19 control, we develop a strategy, Sampling-Testing-Quarantine (STQ), for identifying and isolating individuals with asymptomatic SARS-CoV-2 in order to mitigate the epidemic. STQ uses probability sampling in the general population, regardless of symptoms, then isolates the individuals who test positive along with their household members who are high probability for asymptomatic infections. To test the potential efficacy of STQ, we use an agent-based model, designed to computationally simulate the epidemic in the Seattle with infection parameters, like R0 and asymptomatic fraction, derived from population data. Our results suggest that STQ can substantially slow and decrease the spread of COVID-19, even in the absence of school and work shutdowns. Results also recommend which sampling techniques, frequency of implementation, and population subject to isolation are most efficient in reducing spread with limited numbers of tests.\n\nSignificance StatementA substantial portion of SARS-CoV-2 infections are spread through asymptomatic carriers. Until a vaccine is developed, research indicates an urgent need to identify these asymptomatic infections to control COVID-19, but there is currently no effective strategy to do so. In this study, we develop such a strategy, a procedure called Sampling-Testing-Quarantine (STQ), that combines techniques from survey methods for sampling from the general population and testing and isolation techniques from epidemiology. With computational simulations, we demonstrate that STQ procedures can dramatically decrease and slow COVID-19 spread, even in the absence of widespread work, school, and community lockdowns. We also find particular implementation strategies (including sampling techniques, frequencies of implementation, and people who are subject to isolation) are most efficient in mitigating spread.", - "rel_num_authors": 7, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.07.20208421", + "rel_abs": "Due to the rapid increase of COVID-19 infection cases in many countries such as the Philippines, many efforts in forecasting the daily infections have been made in order to better manage the pandemic, and respond effectively. In this study, we consider the cumulative COVID-19 infection cases in the Philippines from March 6 to July 31,2020 and forecast the cases from August 1 - 15, 2020 using various mathematical models --weighted moving average, exponential smoothing, Susceptible-Exposed-Infected-Recovered (SEIR) model, Ornstein-Uhlenbeck process, Autoregressive Integrated Moving Average (ARIMA) model, and random forest. We then compare the results to the actual data using traditional error metrics. Our results show that the ARIMA(1,2,1) model has the closest forecast values to the actual data. Policymakers can use our result in determining which forecast method to use for their community in order to have a data-based information for the preparation of their personnel and facilities.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Nathalie E Williams", - "author_inst": "University of Washington" - }, - { - "author_name": "Xiaozheng Yao", - "author_inst": "Virginia Tech" + "author_name": "Monica C Torres", + "author_inst": "University of the Philippines Los Banos" }, { - "author_name": "Ankita Pall", - "author_inst": "University of Washington" + "author_name": "Christian Alvin H Buhat", + "author_inst": "University of the Philippines Los Banos" }, { - "author_name": "Xiaolu Qian", - "author_inst": "University of Washington" + "author_name": "Ben Paul C Dela Cruz", + "author_inst": "University of the Philippines Los Banos" }, { - "author_name": "Mansi Rathod", - "author_inst": "University of Washington" + "author_name": "Edd Francis O. Felix", + "author_inst": "University of the Philippines Los Banos" }, { - "author_name": "Chang Xu", - "author_inst": "University of Washington" + "author_name": "Eleanor B Gemida", + "author_inst": "University of the Philippines Los Banos" }, { - "author_name": "Adrian Dobra", - "author_inst": "University of Washington" + "author_name": "Jonathan B. Mamplata", + "author_inst": "University of the Philippines Los Banos" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1132261,39 +1133077,55 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.10.07.20208462", - "rel_title": "Assessing the Impact of Area Deprivation Index on COVID-19 Prevalence: A Contrast Between Rural and Urban U.S. Jurisdictions", + "rel_doi": "10.1101/2020.10.07.20208702", + "rel_title": "Long-term COVID-19 symptoms in a large unselected population", "rel_date": "2020-10-11", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.07.20208462", - "rel_abs": "BackgroundThe COVID-19 pandemic has impacted communities differentially, with poorer and minority populations being more adversely affected. Prior rural health research suggests such disparities may be exacerbated during the pandemic and in remote parts of the U.S.\n\nObjectivesTo understand the spread and impact of COVID-19 across the U.S., county level data for confirmed cases of COVID-19 were examined by Area Deprivation Index (ADI) scores and Metropolitan vs. Nonmetropolitan designations from the National Center for Health Statistics (NCHS). These designations were the basis for making comparisons between Urban and Rural jurisdictions.\n\nMethodsKendalls Tau-B was used to compare effect sizes between jurisdictions on select ADI composites and well researched social determinants of health (SDH). Spearman coefficients and a moderation analysis using Poisson modeling was used to explore the relationship between ADI and COVID-19 prevalence in the context of county designation.\n\nResultsResults show that the relationship between area deprivation and COVID-19 prevalence was positive and higher for rural counties, when compared to urban ones and that family income and poverty had a stronger relationship with prevalence than other ADI component measures.\n\nConclusionsThough most Americans live in Metropolitan Areas, rural communities were found to be associated with a stronger relationship between deprivation and COVID-19 prevalence. Models for predicting COVID-19 prevalence by ADI and county type reinforced this observation but revealed no moderating effect of county type on ADI.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.07.20208702", + "rel_abs": "It is increasingly recognized that SARS-CoV-2 can produce long-term complications after recovery from the acute effects of infection. Here, we report the analysis of 32 self-reported short and long-term symptoms in a general adult population cohort comprised of 357 COVID-19+ cases, 5,497 SARS-CoV-2-negative controls, and 19,095 non-tested individuals. The majority of our COVID-19+ cases are mild, with only 9 of the 357 COVID-19+ cases having been hospitalized. Our results show that 36.1% of COVID-19+ cases have symptoms lasting longer than 30 days, and 14.8% still have at least one symptom after 90 days. These numbers are higher for COVID-19+ cases who were initially more ill, 44.9% at 30 days and 20.8% at 90 days, but even for very mild and initially asymptomatic cases, 21.3% have complications persist for 30 days or longer. In contrast, only 8.4% of participants from the general untested population develop new symptoms lasting longer than 30 days due to any illness during the same study period. The long-term symptoms most enriched in those with COVID-19 are anosmia, ageusia, difficulty concentrating, dyspnea, memory loss, confusion, chest pain, and pain with deep breaths. In addition to individuals who are initially more sick having more long-term symptoms, we additionally observe that individuals who have an initial symptom of dyspnea are significantly more likely to develop long-term symptoms. Importantly, our study finds that the overall level of illness is an important variable to account for when assessing the statistical significance of symptoms that are associated with COVID-19. Our study provides a baseline from which to understand the frequency of COVID-19 long-term symptoms at the population level and demonstrates that, although those most likely to develop long-term COVID-19 complications are those who initially have more severe illness, even those with mild or asymptomatic courses of infection are at increased risk of long-term complications.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Christopher Kitchen", - "author_inst": "Johns Hopkins, School of Public Health" + "author_name": "Elizabeth Cirulli", + "author_inst": "Helix" }, { - "author_name": "Elham Hatef", - "author_inst": "Johns Hopkins School of Public Health" + "author_name": "Kelly M Schiabor Barrett", + "author_inst": "Helix" }, { - "author_name": "Hsien Yen Chang", - "author_inst": "Johns Hopkins School of Public Health" + "author_name": "Stephen Riffle", + "author_inst": "Helix" }, { - "author_name": "Jonathan Weiner", - "author_inst": "Johns Hopkins School of Public Health" + "author_name": "Alexandre Bolze", + "author_inst": "Helix" }, { - "author_name": "Hadi Kharrazi", - "author_inst": "Johns Hopkins, School of Public Health" + "author_name": "Iva Neveux", + "author_inst": "Desert Research Institute" + }, + { + "author_name": "Shaun Dabe", + "author_inst": "Renown Health" + }, + { + "author_name": "Joseph J Grzymski", + "author_inst": "Desert Research Institute" + }, + { + "author_name": "James T Lu", + "author_inst": "Helix" + }, + { + "author_name": "Nicole L Washington", + "author_inst": "Helix" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2020.10.08.20209650", @@ -1134131,63 +1134963,47 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2020.10.07.20208587", - "rel_title": "Remote home monitoring (virtual wards) during the COVID-19 pandemic: a living systematic review", + "rel_doi": "10.1101/2020.10.07.20187641", + "rel_title": "Two-tiered SARS-CoV-2 seroconversion screening in the Netherlands and stability of nucleocapsid, spike protein domain 1 and neutralizing antibodies", "rel_date": "2020-10-09", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.07.20208587", - "rel_abs": "ObjectivesThe aim of this review was to analyse the implementation and impact of remote home monitoring models (virtual wards) during COVID-19, identifying their main components, processes of implementation, target patient populations, impact on outcomes, costs and lessons learnt.\n\nDesignA rapid systematic review to capture an evolving evidence base. We used the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) statement.\n\nSettingThe review included models led by primary and secondary care across seven countries.\n\nParticipants27 articles were included in the review.\n\nMain outcome measuresImpact of remote home monitoring on virtual length of stay, escalation, emergency department attendance/reattendance, admission/readmission and mortality.\n\nResultsThe aim of the models was to maintain patients safe in the right setting. Most models were led by secondary care and confirmation of COVID-19 was not required (in most cases). Monitoring was carried via online platforms, paper-based systems with telephone calls or (less frequently) through wearable sensors. Models based on phone calls were considered more inclusive. Patient/carer training was identified as a determining factor of success. We could not reach substantive conclusions regarding patient safety and the identification of early deterioration due to lack of standardised reporting and missing data. Economic analysis was not reported for most of the models and did not go beyond reporting resources used and the amount spent per patient monitored.\n\nConclusionsFuture research should focus on staff and patient experiences of care and inequalities in patients access to care. Attention needs to be paid to the cost-effectiveness of the models and their sustainability, evaluation of their impact on patient outcomes by using comparators, and the use of risk-stratification tools.\n\nProtocol registrationThe review protocol was published on PROSPERO (CRD: 42020202888).\n\nRESEARCH IN CONTEXTO_ST_ABSEvidence before this studyC_ST_ABSRemote home monitoring models for other conditions have been studied, but their adaptation to monitor COVID-19 patients and the analysis of their implementation constitute gaps in research.\n\nAdded value of this studyThe review covers a wide range of remote home monitoring models (pre-hospital as well as step-down wards) implemented in primary and secondary care sectors in eight countries and focuses on their implementation and impact on outcomes (including costs).\n\nImplications of all the available evidenceThe review provides a rapid overview of an emerging evidence base that can be used to inform changes in policy and practice regarding the home monitoring of patients during COVID-19. Attention needs to be paid to the cost-effectiveness of the models and their sustainability, evaluation of their impact on patient outcomes by using comparators, and the use of risk-stratification tools.", - "rel_num_authors": 11, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.07.20187641", + "rel_abs": "Serological testing in the COVID-19 pandemic is mainly implemented to gain sero-epidemiological data, but can also retrospectively inform about suspected SARS-CoV-2 infection. We verified and applied a two-tiered testing strategy combining a SARS-CoV-2 receptor-binding domain (RBD)-specific lateral flow assay (LFA) with a nucleocapsid protein (NCP) IgG ELISA to assess seroconversion in n=7241 individuals. The majority had experienced symptoms consistent with COVID-19, but had no access to RT-PCR testing. Longitudinal follow-up in n=97 LFA+ individuals was performed up to 20 weeks after initial infection using NCP and spike protein S1 domain (S1) IgG ELISAs and a surrogate virus neutralization test (sVNT). Individuals reporting symptoms from January 2020 onwards showed seroconversion, as did a considerable proportion of asymptomatic individuals. Seroconversion for symptomatic and asymptomatic individuals was higher in an area with a known infection cluster compared to a low incidence area. Overall, 94% of individuals with a positive IgG result by LFA were confirmed by NCP ELISA. The proportion of ELISA-confirmed LFA results declined over time, in line with contracting NCP IgG titers during longitudinal follow-up. Neutralizing antibody activity was considerably more stable than S1 and NCP IgG titers, and both reach a plateau after approximately 100 days. The sVNT proved to be not only highly specific, but also more sensitive than the specificity-focussed two-tiered serology approach. Our results demonstrate the high specificity of two-tiered serology testing and highlight the sVNT used as a valuable tool to support modelling of SARS-CoV-2 transmission dynamics, complement molecular testing and provide relevant information to individuals.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Cecilia Vindrola-Padros", - "author_inst": "University College London" - }, - { - "author_name": "Kelly Singh", - "author_inst": "University of Birmingham" - }, - { - "author_name": "Manbinder S Sidhu", - "author_inst": "University of Birmingham" + "author_name": "Anja Garritsen", + "author_inst": "Innatoss Laboratories. B.V." }, { - "author_name": "Theo Georghiou", - "author_inst": "Nuffield Trust" + "author_name": "Anja Scholzen", + "author_inst": "Innatoss Laboratories B.V." }, { - "author_name": "Chris Sherlaw-Johnson", - "author_inst": "Nuffield Trust" + "author_name": "Daan WA van den Nieuwenhof", + "author_inst": "Innatoss Laboratories B.V." }, { - "author_name": "Sonila M Tomini", - "author_inst": "University College London" - }, - { - "author_name": "Nathan Cohen", - "author_inst": "University College London" + "author_name": "Anke PF Smits", + "author_inst": "Innatoss Laboratories B.V." }, { - "author_name": "Matthew Inada-Kim", - "author_inst": "Hampshire Hospitals NHS Foundation Trust" + "author_name": "Esther Suzan Datema", + "author_inst": "Innatoss Laboratories B.V." }, { - "author_name": "Karen Kirkham", - "author_inst": "General Practitioner NHS Dorset" + "author_name": "Luc S van Galen", + "author_inst": "Innatoss Laboratories B.V." }, { - "author_name": "Allison Streetly", - "author_inst": "Kings College London" - }, - { - "author_name": "Naomi J Fulop", - "author_inst": "University College London" + "author_name": "Milou LCE Kouwijzer", + "author_inst": "Innatoss Laboratories B.V." } ], "version": "1", - "license": "cc_by", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "health systems and quality improvement" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2020.10.07.20208603", @@ -1135796,113 +1136612,33 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.10.06.20207472", - "rel_title": "Clinical, laboratory, and temporal predictors of neutralizing antibodies to SARS-CoV-2 after COVID-19", + "rel_doi": "10.1101/2020.10.06.20208066", + "rel_title": "Real-World Effectiveness of hydroxychloroquine, azithromycin, and ivermectin among hospitalized COVID-19 patients: Results of a target trial emulation using observational data from a nationwide Healthcare System in Peru", "rel_date": "2020-10-08", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.06.20207472", - "rel_abs": "BackgroundSARS-CoV-2-specific antibodies may protect from reinfection and disease, providing the rationale for administration of plasma containing SARS-CoV-2 neutralizing antibodies (nAb) as a treatment for COVID-19. The clinical factors and laboratory assays to streamline plasma donor selection, and the durability of nAb responses, are incompletely understood.\n\nMethodsAdults with virologically-documented SARS-CoV-2 infection in a convalescent plasma donor screening program were tested for serum IgG to SARS-CoV-2 spike protein S1 domain, nucleoprotein (NP), and for nAb.\n\nResultsAmongst 250 consecutive persons studied a median of 67 days since symptom onset, 243/250 (97%) were seropositive on one or more assays. Sixty percent of donors had nAb titers [≥]1:80. Correlates of higher nAb titer included older age (adjusted OR [AOR] 1.03/year of age, 95% CI 1.00-1.06), male sex (AOR 2.08, 95% CI 1.13-3.82), fever during acute illness (AOR 2.73, 95% CI 1.25-5.97), and disease severity represented by hospitalization (AOR 6.59, 95% CI 1.32-32.96). Receiver operating characteristic (ROC) analyses of anti-S1 and anti-NP antibody results yielded cutoffs that corresponded well with nAb titers, with the anti-S1 assay being slightly more predictive. NAb titers declined in 37 of 41 paired specimens collected a median of 98 days (range, 77-120) apart (P<0.001). Seven individuals (2.8%) were persistently seronegative and lacked T cell responses.\n\nConclusionsNab titers correlated with COVID-19 severity, age, and sex. Standard commercially available SARS-CoV-2 IgG results can serve as useful surrogates for nAb testing. Functional nAb levels were found to decline and a small proportion of COVID-19 survivors lack adaptive immune responses.", - "rel_num_authors": 24, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.06.20208066", + "rel_abs": "IntroductionPeru is one of the most impacted countries due to COVID-19. Given the authorized use of hydroxychloroquine (HCQ), azithromycin (AZIT), and ivermectin (IVM), we aimed to evaluate their effectiveness alone or combined to reduce mortality among COVID-19 hospitalized patients without life-threatening illness.\n\nMethodsRetrospective cohort emulating a target trial, using nationwide data of mid- and high-level hospitals from the Peruvian Social Health Insurance 01/April/2020-19/July/2020. Patients 18 yo and above with PCR-confirmed SARS-CoV-2, and no life-threatening illness at admission were included. Five treatment groups (HCQ alone, IVM alone, AZIT alone, HCQ+AZIT, and IVM+AZIT within 48 hours of admission) were compared with standard of care alone. Primary outcome was all-cause mortality rate; secondary outcomes were all-cause death and/or ICU transfer, and all-cause death and/or oxygen prescription. Analyses were adjusted using inverse probability of treatment weighting. Propensity scores were estimated using machine learning boosting models. Weighted hazard ratios (wHR) were calculated using Cox regression.\n\nResultsAmong 5683 patients, 200 received HCT, 203 IVM, 1600 AZIT, 692 HCQ+AZIT, 358 IVM+AZIT, and 2630 standard of care. HCQ+AZIT was associated with 84% higher all-cause death hazard compared to standard care (wHR=1.84, 95%CI 1.12-3.02). Consistently, HCQ+AZIT was also associated with higher death and/or ICU transfer (wHR=1.49, 95%CI 1.01-2.19), and death and/or oxygen prescription (wHR=1.70, 95%CI 1.07-2.69). HCQ only showed higher death and/or oxygen prescription hazard. No effect was found for AZIT or IVM+AZIT.\n\nConclusionsOur study reported no beneficial effects of hydroxychloroquine, ivermectin, azithromycin. The HCQ+AZIT treatment seems to increase risk for all-cause death.\n\nFundingInstituto de Evaluacion de Tecnologias en Salud e Investigacion - IETSI, EsSalud", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Jim Boonyaratanakornkit", - "author_inst": "Fred Hutchinon Cancer Research Center" - }, - { - "author_name": "Chihiro Morishima", - "author_inst": "University of Washington" - }, - { - "author_name": "Stacy Selke", - "author_inst": "University of Washington" - }, - { - "author_name": "Danniel Zamora", - "author_inst": "Fred Hutchinson Cancer Research Center" - }, - { - "author_name": "Sarah McGuffin", - "author_inst": "University of Washington" - }, - { - "author_name": "Adrienne E Shapiro", - "author_inst": "University of Washington" - }, - { - "author_name": "Victoria L Campbell", - "author_inst": "University of Washington" - }, - { - "author_name": "Christopher L McClurkan", - "author_inst": "University of Washington" - }, - { - "author_name": "Lichen Jing", - "author_inst": "University of Washington" - }, - { - "author_name": "Robin Gross", - "author_inst": "National Institutes of Health" - }, - { - "author_name": "Janie Liang", - "author_inst": "National Institutes of Health" - }, - { - "author_name": "Elena Postnikova", - "author_inst": "National Institutes of Health" - }, - { - "author_name": "Steven Mazur", - "author_inst": "National Institutes of Health" - }, - { - "author_name": "Anu Chaudhary", - "author_inst": "University of Washington" - }, - { - "author_name": "Marie K Das", - "author_inst": "University of Washington" - }, - { - "author_name": "Susan L Fink", - "author_inst": "University of Washington" - }, - { - "author_name": "Andrew Bryan", - "author_inst": "University of Washington" - }, - { - "author_name": "Alex L Greninger", - "author_inst": "University of Washington" - }, - { - "author_name": "Keith R Jerome", - "author_inst": "Fred Hutchinson Cancer Research Center" - }, - { - "author_name": "Michael R Holbrook", - "author_inst": "National Institutes of Health" - }, - { - "author_name": "Terry B Gernsheimer", - "author_inst": "University of Washington" + "author_name": "Percy Soto-Becerra Sr.", + "author_inst": "Instituto de Evaluacion de Tecnologias en Salud e Investigacion - IETSI, EsSalud" }, { - "author_name": "Mark H Wener", - "author_inst": "University of Washington" + "author_name": "Carlos Culquichicon", + "author_inst": "Instituto de Evaluacion de Tecnologias en Salud e Investigacion - IETSI, EsSalud" }, { - "author_name": "Anna Wald", - "author_inst": "University of Washington" + "author_name": "Yamilee Hurtado-Roca", + "author_inst": "Instituto de Evaluacion de Tecnologias en Salud e Investigacion - IETSI, EsSalud" }, { - "author_name": "David M Koelle", - "author_inst": "University of Washington" + "author_name": "Roger V Araujo-Castillo", + "author_inst": "Instituto de Evaluacion de Tecnologias en Salud e Investigacion - IETSI, EsSalud" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1137430,103 +1138166,31 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2020.10.07.307546", - "rel_title": "Making the invisible enemy visible", + "rel_doi": "10.1101/2020.10.07.330324", + "rel_title": "Mass spectrometric based detection of protein nucleotidylation in the RNA polymerase of SARS-CoV-2", "rel_date": "2020-10-07", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.10.07.307546", - "rel_abs": "During the COVID-19 pandemic, structural biologists rushed to solve the structures of the 28 proteins encoded by the SARS-CoV-2 genome in order to understand the viral life cycle and enable structure-based drug design. In addition to the 204 previously solved structures from SARS-CoV-1, 548 structures covering 16 of the SARS-CoV-2 viral proteins have been released in a span of only 6 months. These structural models serve as the basis for research to understand how the virus hijacks human cells, for structure-based drug design, and to aid in the development of vaccines. However, errors often occur in even the most careful structure determination - and may be even more common among these structures, which were solved quickly and under immense pressure.\n\nThe Coronavirus Structural Task Force has responded to this challenge by rapidly categorizing, evaluating and reviewing all of these experimental protein structures in order to help downstream users and original authors. In addition, the Task Force provided improved models for key structures online, which have been used by Folding@Home, OpenPandemics, the EU JEDI COVID-19 challenge and others.", - "rel_num_authors": 21, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.10.07.330324", + "rel_abs": "Coronaviruses, like SARS-CoV-2, encode a nucleotidyl transferase in the N-terminal NiRAN domain of the non-structural protein (nsp) 12 protein within the RNA dependent RNA polymerase (RdRP) 1-3. Though the substrate targets of the viral nucleotidyl transferase are unknown, NiRAN active sites are highly conserved and essential for viral replication 3. We show, for the first time, the detection and sequence location of GMP-modified amino acids in nidovirus RdRP-associated proteins using heavy isotope-assisted MS and MS/MS peptide sequencing. We identified lys-143 in the equine arteritis virus (EAV) protein, nsp7, as a primary site of nucleotidylation in vitro that uses a phosphoramide bond to covalently attach with GMP. In SARS-CoV-2 replicase proteins, we demonstrate a unique O-linked GMP attachment on nsp7 ser-1, whose formation required the presence of nsp12. It is clear that additional nucleotidylation sites remain undiscovered, which includes the possibility that nsp12 itself may form a transient GMP adduct in the NiRAN active site that has eluted detection in these initial studies due to instability of the covalent attachment. Our results demonstrate new strategies for detecting GMP-peptide linkages that can be adapted for higher throughput screening using mass spectrometric technologies. These data are expected to be important for a rapid and timely characterization of a new enzymatic activity in SARS-CoV-2 that may be an attractive drug target aimed at limiting viral replication in infected patients.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Tristan Croll", - "author_inst": "CIMR, University of Cambridge, UK" - }, - { - "author_name": "Kay Diederichs", - "author_inst": "University of Konstanz, Germany" - }, - { - "author_name": "Florens Fischer", - "author_inst": "HARBOR, Unversity of Hamburg, Germany" - }, - { - "author_name": "Cameron Fyfe", - "author_inst": "Paris, France" - }, - { - "author_name": "Yunyun Gao", - "author_inst": "HARBOR, Unversity of Hamburg, Germany" - }, - { - "author_name": "Sam Horrell", - "author_inst": "Diamond Lightsource, UK" - }, - { - "author_name": "Agnel Praveen Joseph", - "author_inst": "Science and Technology Facilities Council, UK" - }, - { - "author_name": "Luise Kandler", - "author_inst": "HARBOR, Unversity of Hamburg, Germany" - }, - { - "author_name": "Oliver Kippes", - "author_inst": "HARBOR, Unversity of Hamburg, Germany" - }, - { - "author_name": "Ferdinand Kirsten", - "author_inst": "HARBOR, Unversity of Hamburg, Germany" - }, - { - "author_name": "Konstantin M\u00fcller", - "author_inst": "RVZ, University of W\u00fcrzburg, Germany" - }, - { - "author_name": "Kristopher Nolte", - "author_inst": "HARBOR, Unversity of Hamburg, Germany" - }, - { - "author_name": "Alexander Payne", - "author_inst": "Memorial Sloane Kettering Cancer Center, USA" - }, - { - "author_name": "Matthew G. Reeves", - "author_inst": "RVZ, University of W\u00fcrzburg, Germany" - }, - { - "author_name": "Jane Richardson", - "author_inst": "Duke University, USA" - }, - { - "author_name": "Gianluca Santoni", - "author_inst": "European Synchrotron Radiation Facility, France" - }, - { - "author_name": "Sabrina St\u00e4b", - "author_inst": "RVZ, University of W\u00fcrzburg, Germany" - }, - { - "author_name": "Dale Tronrud", - "author_inst": "University of Oregon, USA" - }, - { - "author_name": "Lea von Soosten", - "author_inst": "HARBOR, Unversity of Hamburg, Germany" + "author_name": "Michael R Sussman", + "author_inst": "University of Wisconsin-Madison" }, { - "author_name": "Christopher Williams", - "author_inst": "Duke University, USA" + "author_name": "Brian J Conti", + "author_inst": "Univesity of Wisconsin Madison" }, { - "author_name": "Andrea Thorn", - "author_inst": "HARBOR, Unversity of Hamburg, Germany" + "author_name": "Robert N Kirchdoerfer", + "author_inst": "University of Wisconsin-Madison" } ], "version": "1", "license": "cc_no", "type": "new results", - "category": "molecular biology" + "category": "biochemistry" }, { "rel_doi": "10.1101/2020.10.07.330068", @@ -1138964,59 +1139628,55 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.10.03.20204545", - "rel_title": "SARS-CoV-2 Prevalence and Seroprevalence among Healthcare Workers in Belgian Hospitals: Baseline Results of a Prospective Cohort Study", + "rel_doi": "10.1101/2020.10.03.20206284", + "rel_title": "The excess insulin requirement in severe COVID-19 compared to non-COVID-19 viral pneumonitis is related to the severity of respiratory failure and pre-existing diabetes.", "rel_date": "2020-10-06", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.03.20204545", - "rel_abs": "BackgroundGiven the current SARS-CoV-2 pandemic and the occurrence of a second wave, assessing the burden of disease among health care workers (HCWs) is crucial. We aim to document the prevalence of SARS-CoV-2 and the seroprevalence of anti-SARS-CoV-2 IgG among HCWs in Belgian hospitals, and to study potential risk factors for the infection in order to guide infection prevention and control (IPC) measures in healthcare institutions.\n\nMethodsWe performed a cross-sectional analysis of the baseline results (April 22 - April 26) of an ongoing cohort study. All staff who were present in the hospital during the sampling period and whose profession involved contact with patients were eligible. Fourteen hospitals across Belgium and 50 HCW per hospital were randomly selected. RT-qPCR was performed to detect SARS-CoV-2 RNA on nasopharyngeal swabs, and a semi-quantitative IgG ELISA was used to detect anti-SARS-CoV-2 antibodies in sera. Individual characteristics likely to be associated with seropositivity were collected using an online questionnaire.\n\nFindings698 participants completed the questionnaire; 80.8% were women, median age was 39.5, and 58.5% were nurses. Samples were collected on all 699 participants. The weighted anti-SARS-CoV-2 IgG seroprevalence was 7.7% (95%CI, 4.7%-12.2%), while 1.1% (95%CI, 0.4%-3.0%) of PCR results were positive. Unprotected contact with a confirmed case was the only factor associated with seropositivity (PR 2.16, 95% CI, 1.4-3.2).\n\nInterpretationMost Belgian HCW did not show evidence of SARS-CoV-2 infection by late April 2020, and unprotected contact was the most important risk factor. This confirms the importance of widespread availability of protective equipment and use of adequate IPC measures in hospital settings.", - "rel_num_authors": 10, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.03.20206284", + "rel_abs": "ObjectiveSevere COVID-19 has been anecdotally associated with high insulin requirements. It has been proposed that this may be driven by a direct diabetogenic effect of the virus that is unique to SARS-CoV-2, but evidence to support this is limited. To explore this, we compared insulin requirements in patients with severe COVID-19 and non-COVID-19 viral pneumonitis.\n\nResearch DesignRetrospective cohort study of patients with severe COVID-19 admitted to our intensive care unit between March and June 2020. A historical control cohort of non-COVID-19 viral pneumonitis patients was identified from routinely collected audit data.\n\nResultsInsulin requirements were similar in patients with COVID-19 and non-COVID-19 viral pneumonitis after adjustment for pre-existing diabetes and severity of respiratory failure.\n\nConclusionsIn this single center study, we could not find evidence of a unique diabetogenic effect of COVID-19. We suggest that high insulin requirements in this disease relate to its propensity to cause severe respiratory failure in patients with pre-existing metabolic disease.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Laure Mortgat", - "author_inst": "Sciensano, Brussels; EPIET, Stockholm" + "author_name": "Sam Lockhart", + "author_inst": "1.\tMRC Metabolic Diseases Unit, Wellcome Trust-Medical Research Council Institute of Metabolic Science, University of Cambridge, Cambridge, UK." }, { - "author_name": "Cyril Barbezange", - "author_inst": "Sciensano, Brussels" + "author_name": "Harry Griffiths", + "author_inst": "John V Farman Intensive Care Unit, Addenbrooke's Hospital, Cambridge" }, { - "author_name": "Natalie Fischer", - "author_inst": "Sciensano, Brussels; EUPHEM, Stockholm" + "author_name": "Bogdan Petrisor", + "author_inst": "John V Farman Intensive Care Unit, Addenbrooke's Hospital, Cambridge" }, { - "author_name": "Leo Heyndrickx", - "author_inst": "Institute of Tropical Medicine, Antwerp" + "author_name": "Ammara Usman", + "author_inst": "John V Farman Intensive Care Unit, Addenbrooke's Hospital, Cambridge" }, { - "author_name": "Veronik Hutse", - "author_inst": "Sciensano, Brussels" - }, - { - "author_name": "Isabelle Thomas", - "author_inst": "Sciensano, Brussels" + "author_name": "Julia Calvo-Latorre", + "author_inst": "Wolfson Diabetes and Endocrinology Clinic, Cambridge University Hospital NHS Foundation Trust, Cambridge" }, { - "author_name": "Bea Vuylsteke", - "author_inst": "Institute of Tropical Medicine, Antwerp" + "author_name": "Laura Heales", + "author_inst": "John V Farman Intensive Care Unit, Addenbrooke's Hospital, Cambridge" }, { - "author_name": "Kevin Arien", - "author_inst": "Institute of Tropical Medicine, Antwerp; University of Antwerp" + "author_name": "Vishakha Bansiya", + "author_inst": "Wolfson Diabetes and Endocrinology Clinic, Cambridge University Hospital NHS Foundation Trust, Cambridge" }, { - "author_name": "Isabelle Desombere", - "author_inst": "Sciensano, Brussels" + "author_name": "Razeen Mahroof", + "author_inst": "John V Farman Intensive Care Unit, Addenbrookes Hospital, Cambridge" }, { - "author_name": "Els Duysburgh", - "author_inst": "Sciensano, Brussels" + "author_name": "Andrew Conway Morris", + "author_inst": "University of Cambridge" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "intensive care and critical care medicine" }, { "rel_doi": "10.1101/2020.10.05.20203687", @@ -1140602,31 +1141262,119 @@ "category": "molecular biology" }, { - "rel_doi": "10.1101/2020.10.06.327742", - "rel_title": "Cytoplasmic short linear motifs in ACE2 and integrin beta3 link SARS-CoV-2 host cell receptors to endocytosis and autophagy", + "rel_doi": "10.1101/2020.10.06.328369", + "rel_title": "SARS-CoV-2 infection damages airway motile cilia and impairs mucociliary clearance", "rel_date": "2020-10-06", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.10.06.327742", - "rel_abs": "The spike protein of the SARS-CoV-2 interacts with angiotensin converting enzyme 2 (ACE2) and enters the host cell by receptor-mediated endocytosis. Concomitantly, evidence is pointing to the involvement of additional host cell receptors, such as integrins. The cytoplasmic tails of ACE2 and integrin {beta}3 contain a plethora of predicted binding motifs. Here, we confirm the functionality of some of these motifs through affinity measurements. The class I PDZ binding motif in the ACE2 cytoplasmic tail binds the first PDZ domain of the scaffold protein NHERF3. The clathrin-adaptor subunit AP2 2 interacts with an endocytic motif in the ACE2 with low affinity and the interaction is abolished by phosphorylation of Tyr781. Furthermore, the C-terminal region of integrin b3 contains a LC3-interacting region, and its interaction with ATG8 domains is enhanced by phosphorylation. Together, our data provides possible molecular links between host cell receptors and endocytosis and autophagy.\n\nOne sentence summaryAffinity measurements confirmed binding of short linear motifs in the cytoplasmic tails of ACE2 and integrin {beta}3, thereby linking the receptors to endocytosis and autophagy.", - "rel_num_authors": 3, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.10.06.328369", + "rel_abs": "Understanding how SARS-CoV-2 spreads within the respiratory tract is important to define the parameters controlling the severity of COVID-19. We examined the functional and structural consequences of SARS-CoV-2 infection in a reconstituted human bronchial epithelium model. SARS-CoV-2 replication caused a transient decrease in epithelial barrier function and disruption of tight junctions, though viral particle crossing remained limited. Rather, SARS-CoV-2 replication led to a rapid loss of the ciliary layer, characterized at the ultrastructural level by axoneme loss and misorientation of remaining basal bodies. The motile cilia function was compromised, as measured in a mucociliary clearance assay. Epithelial defense mechanisms, including basal cell mobilization and interferon-lambda induction, ramped up only after the initiation of cilia damage. Analysis of SARS-CoV-2 infection in Syrian hamsters further demonstrated the loss of motile cilia in vivo. This study identifies cilia damage as a pathogenic mechanism that could facilitate SARS-CoV-2 spread to the deeper lung parenchyma.", + "rel_num_authors": 25, "rel_authors": [ { - "author_name": "Johanna Kliche", - "author_inst": "Uppsala University" + "author_name": "R\u00e9my Robinot", + "author_inst": "Institut Pasteur" }, { - "author_name": "Muhammad Ali", - "author_inst": "Uppsala University" + "author_name": "Mathieu Hubert", + "author_inst": "Institut Pasteur" }, { - "author_name": "Ylva Ivarsson", - "author_inst": "Uppsala University" + "author_name": "Guilherme Dias de Melo", + "author_inst": "Institut Pasteur" + }, + { + "author_name": "Fran\u00e7oise Lazarini", + "author_inst": "Institut Pasteur" + }, + { + "author_name": "Timoth\u00e9e Bruel", + "author_inst": "Institut Pasteur" + }, + { + "author_name": "Nika\u00efa Smith", + "author_inst": "Institut Pasteur" + }, + { + "author_name": "Sylvain Levallois", + "author_inst": "Institut Pasteur" + }, + { + "author_name": "Florence Larrous", + "author_inst": "Institut Pasteur" + }, + { + "author_name": "Julien Fernandes", + "author_inst": "Institut Pasteur" + }, + { + "author_name": "Stacy Gellenoncourt", + "author_inst": "Institut Pasteur" + }, + { + "author_name": "St\u00e9phane Rigaud", + "author_inst": "Institut Pasteur" + }, + { + "author_name": "Olivier Gorgette", + "author_inst": "Institut Pasteur" + }, + { + "author_name": "Catherine Thouvenot", + "author_inst": "Institut Pasteur" + }, + { + "author_name": "C\u00e9line Tr\u00e9beau", + "author_inst": "Institut Pasteur" + }, + { + "author_name": "Guillaume Dumenil", + "author_inst": "Institut Pasteur" + }, + { + "author_name": "Adeline Mallet", + "author_inst": "Institut Pasteur" + }, + { + "author_name": "Samy Gobaa", + "author_inst": "Institut Pasteur" + }, + { + "author_name": "Rapha\u00ebl Etournay", + "author_inst": "Institut Pasteur" + }, + { + "author_name": "Pierre-Marie Lledo", + "author_inst": "Institut Pasteur" + }, + { + "author_name": "Marc Lecuit", + "author_inst": "Institut Pasteur" + }, + { + "author_name": "Herv\u00e9 Bourhy", + "author_inst": "Institut Pasteur" + }, + { + "author_name": "Darragh Duffy", + "author_inst": "Institut Pasteur" + }, + { + "author_name": "Vincent Michel", + "author_inst": "Institut Pasteur" + }, + { + "author_name": "Olivier Schwartz", + "author_inst": "Institut Pasteur" + }, + { + "author_name": "Lisa A Chakrabarti", + "author_inst": "Institut Pasteur" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_no", "type": "new results", - "category": "biochemistry" + "category": "microbiology" }, { "rel_doi": "10.1101/2020.10.05.327528", @@ -1142104,31 +1142852,35 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.10.03.20206110", - "rel_title": "COVID-19 Viral Loads, Environment, Ventilation, Masks, Exposure Time, And Severity : A Pragmatic Guide Of Estimates", + "rel_doi": "10.1101/2020.10.04.325662", + "rel_title": "Motif Analysis in k-mer Networks: An Approach towards Understanding SARS-CoV-2 Geographical Shifts", "rel_date": "2020-10-05", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.03.20206110", - "rel_abs": "It can be shown that over 94% of COVID-19 superspreading events occurred in limited ventilation areas suggesting aerosolized transmission is a strong contributor to COVID-19 infections.\n\nThis study helps answer \"How long may a person safely remain within various environments?\" And \"What exposure levels could result in immunity without becoming ill via asymptomatic graduated inoculation?\"\n\nCOVID-19 infection likelihood, symptom severity, and immune response dependencies include viral load exposure amount. A better understanding of these relationships could help determine what Non-Pharmaceutical Interventions (NPI) would help reduce severe case counts and improve at-large epidemiologic responses in specific scenarios.\n\nThis study references peer reviewed and published studies and uses them as data sources for an estimation model that calculates infection likelihood given exposure within several example scenarios. Information from ASHRAE office ventilation standards, typical home ventilation characteristics, and an outdoor air setting are used to establish several specific examples of indoor and outdoor scenarios.\n\nThe model establishes a reference scenario using objectively measured air sample viral load concentration levels found within a carefully documented hospital environment containing 2 sick patients. The model extrapolates the reference scenario into several example scenarios that have varied exposure time duration, ventilation amount, with/without surgical mask use, activity/respiration levels, and infected subject shedding levels. It uses the reference data and scenario extrapolations to calculate an estimate of total viral load exposure dose for each scenario.\n\nThe study then interprets the various scenario total exposure dose estimates using an National Institute of Health human challenge study where volunteers were exposed to multiple specific viral quantities and observed in a clinical environment to objectively determine likelihood of infection, severity level, and immune response given each specific exposure dose. To simplify pragmatic use of the results, each example scenario presents the estimated total exposure dose alongside an intuitive severity category of Not Ill, Minor Illness, Clinical Mild Illness, and Possible Severe Illness which are based on a defined interpretation of the NIH study results. Immune response data related to these categories is also provided along with discussion related to asymptomatic infection, graduated inoculation, and immunity.\n\nWhen appropriately interpreted for individualized applications, the estimates herein could contribute to guidance for those at low-risk for a severe case that have no obvious COVID-19 co-morbidities, with the understanding that those at higher risk should seek to avoid all exposure risk. The estimates herein may help efforts to strike a balance in developing holistic epidemiologic interventions that consider the effects of these interventions on economic, civic, social, and mental health, which have pathologies within their own realms.", - "rel_num_authors": 3, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2020.10.04.325662", + "rel_abs": "With an increasing number of SARS-CoV-2 sequences available day by day, new genomic information is getting revealed to us. As SARS-CoV-2 sequences highlight wide changes across the samples, we aim to explore whether these changes reveal the geographical origin of the corresponding samples. The k-mer distributions, denoting normalized frequency counts of all possible combinations of nucleotide of size upto k, are often helpful to explore sequence level patterns. Given the SARS-CoV-2 sequences are highly imbalanced by its geographical origin (relatively with a higher number samples collected from the USA), we observe that with proper under-sampling k-mer distributions in the SARS-CoV-2 sequences predict its geographical origin with more than 90% accuracy. The experiments are performed on the samples collected from six countries with maximum number of sequences available till July 07, 2020. This comprises SARS-CoV-2 sequences from Australia, USA, China, India, Greece and France. Moreover, we demonstrate that the changes of genomic sequences characterize the continents as a whole. We also highlight that the network motifs present in the sequence similarity networks have a significant difference across the said countries. This, as a whole, is capable of predicting the geographical shift of SARS-CoV-2.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "David E. Epperly", - "author_inst": "ReallyCorrect.com" + "author_name": "Sourav Biswas", + "author_inst": "Indian Statistical Institute, Kolkata" + }, + { + "author_name": "Suparna Saha", + "author_inst": "Indian Statistical Institute, Kolkata" }, { - "author_name": "Kristopher R. Rinehart", - "author_inst": "California Mobile Physicians" + "author_name": "Sanghamitra Bandyopadhyay", + "author_inst": "Indian Statistical Institute, Kolkata" }, { - "author_name": "David N. Caney", - "author_inst": "Tahoe Blue Ltd" + "author_name": "Malay Bhattacharyya", + "author_inst": "Indian Statistical Institute, Kolkata" } ], "version": "1", "license": "cc_no", - "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "type": "new results", + "category": "bioinformatics" }, { "rel_doi": "10.1101/2020.10.01.20204495", @@ -1143790,43 +1144542,47 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.09.30.20204917", - "rel_title": "Epidemiological and clinical characteristics of COVID-19 in Brazil using digital technology", + "rel_doi": "10.1101/2020.09.30.20204842", + "rel_title": "Oil Immersed Lossless Total Analysis System (OIL-TAS): Integrated RNA Extraction and Detection for SARS-CoV-2 Testing", "rel_date": "2020-10-02", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.30.20204917", - "rel_abs": "BackgroundBrazil has the third-highest number of Coronavirus disease 2019 (COVID-19) cases worldwide. Understanding the epidemiology of COVID-19 from reported cases is challenging due to heterogeneous testing rates. We estimated the number of COVID-19 cases in Brazil on a national and regional level using digital technology.\n\nMethodsWe used a web-based application to perform a population-based survey from March 21st to August 29th, 2020 in Brazil. We obtained responses from 243 461 individuals across all federative units, who answered questions on COVID-19-related symptoms, chronic diseases and address of residence. COVID-19 was defined as at least one of the following: fever, cough, dyspnea and nasal flaring, associated with a history of close contact with a suspect or confirmed COVID-19 case in the previous 14 days. A stratified two-stage weighted survey analysis was performed to estimate the population level prevalence of COVID-19 cases.\n\nResultsAfter calibration weighing, we estimated that 10 339 461 cases of COVID-19 occurred, yielding a 2.75 estimated infection per officially reported case. Estimated/reported ratios varied across Brazilian states and were higher in states with lower human development indexes. Areas with lower income levels displayed higher rates of COVID-19 cases (66 vs 38 cases/1000 people in the lowest and highest income strata respectively, p<0.001), but presented lower rates of COVID-19 testing.\n\nConclusionIn this population-based survey using digital technology in Brazil, we estimated that the COVID-19 case rates were 2.75 times higher than officially reported. The estimated per reported case ratios were higher in areas with worse socioeconomic status.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.30.20204842", + "rel_abs": "The coronavirus disease 2019 (COVID-19) pandemic exposed difficulties in scaling current quantitative PCR (qPCR)-based diagnostic methodologies for large-scale infectious disease testing. Bottlenecks include the lengthy multi-step process of nucleic acid extraction followed by qPCR readouts, which require costly instrumentation and infrastructure, as well as reagent and plastic consumable shortages stemming from supply chain constraints. Here we report a novel Oil Immersed Lossless Total Analysis System (OIL-TAS), which integrates RNA extraction and detection onto a single device that is simple, rapid, cost effective, uses minimal supplies and requires reduced infrastructure to perform. We validated the performance of OIL-TAS using contrived samples containing inactivated SARS-CoV-2 viral particles, which show that the assay can reliably detect an input concentration of 10 copies/L and sporadically detect down to 1 copy/L. The OIL-TAS method can serve as a faster, cheaper, and easier-to-deploy alternative to current qPCR-based methods for infectious disease testing.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Faissal Nemer Hajar", - "author_inst": "Federal University of Parana" + "author_name": "Duane S Juang", + "author_inst": "University of Wisconsin-Madison" }, { - "author_name": "Miguel Morita Fernandes-Silva", - "author_inst": "Federal University of Parana" + "author_name": "Terry D Juang", + "author_inst": "University of Wisconsin-Madison" }, { - "author_name": "Gustavo S. Pereira da Cunha", - "author_inst": "Federal University of Parana" + "author_name": "Dawn M Dudley", + "author_inst": "University of Wisconsin-Madison" }, { - "author_name": "Geny Herrera", - "author_inst": "TOTVS labs" + "author_name": "Christina M Newman", + "author_inst": "University of Wisconsin-Madison" }, { - "author_name": "Ali Hamud", - "author_inst": "B.Braun Group" + "author_name": "Thomas C Friedrich", + "author_inst": "University of Wisconsin-Madison" }, { - "author_name": "Valderilio F Azevedo", - "author_inst": "Universidade Federal do Parana" + "author_name": "David H O'Connor", + "author_inst": "University of Wisconsin-Madison" + }, + { + "author_name": "David J Beebe", + "author_inst": "University of Wisconsin-Madison" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "public and global health" }, { "rel_doi": "10.1101/2020.10.01.20205187", @@ -1145648,43 +1146404,59 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.09.27.20202671", - "rel_title": "Time-series clustering for home dwell time during COVID-19: what can we learn from it?", + "rel_doi": "10.1101/2020.09.29.20202598", + "rel_title": "Passive Microwave Radiometry (MWR) for diagnostics of COVID-19 lung complications.", "rel_date": "2020-09-30", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.27.20202671", - "rel_abs": "In this study, we investigate the potential driving factors that lead to the disparity in the time-series of home dwell time, aiming to provide fundamental knowledge that benefits policy-making for better mitigation strategies of future pandemics. Taking Metro Atlanta as a study case, we perform a trend-driven analysis by conducting Kmeans time-series clustering using fine-grained home dwell time records from SafeGraph, and further assess the statistical significance of sixteen demographic/socioeconomic variables from five major categories. We find that demographic/socioeconomic variables can explain the disparity in home dwell time in response to the stay-at-home order, which potentially leads to disparate exposures to the risk from the COVID-19. The results further suggest that socially disadvantaged groups are less likely to follow the order to stay at home, pointing out the extensive gaps in the effectiveness of social distancing measures exist between socially disadvantaged groups and others. Our study reveals that the long-standing inequity issue in the U.S. stands in the way of the effective implementation of social distancing measures. Policymakers need to carefully evaluate the inevitable trade-off among different groups, making sure the outcomes of their policies reflect interests of the socially disadvantaged groups.\n\nHighlightsO_LIWe perform a trend-driven analysis by conducting Kmeans time-series clustering using fine- grained home dwell time records from SafeGraph.\nC_LIO_LIWe find that demographic/socioeconomic variables can explain the disparity in home dwell time in response to the stay-at-home order.\nC_LIO_LIThe results suggest that socially disadvantaged groups are less likely to follow the order to stay at home, potentially leading to more exposures to the COVID-19.\nC_LIO_LIPolicymakers need to make sure the outcomes of their policies reflect the interests of the disadvantaged groups.\nC_LI", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.29.20202598", + "rel_abs": "The World Health Organization (WHO) declared COVID-19 as a global pandemic. It becomes clear that the virus is spreading mostly deadly due to limited access to diagnostics tests and equipment. Traditional radiography and CT remain the main methods of the initial examination of the chest organs. Now, most of the diagnostics has been focused on PCR, chest X-Ray/CT manifestations of COVID-19. However, there are problems with CT due to infection control issues, the inefficiencies introduced in CT room decontamination, and lack of CT availability in LMIC (Low Middle Income Countries). Passive microwave radiometry (MWR) is a cheap, non-radioactive and portable technology. It has already been used for diagnostics of cancer, and other diseases. We have tested if MWR could be used for early diagnostics of pulmonary COVID-19 complications. This was a randomized controlled trial (195 subjects) to evaluate the effectiveness of diagnostics using MWR in patients with pneumonia caused by COVID-19 while they are in hospitals of Kyrgyzstan, and healthy individuals.\n\nWe have measured skin (IR) and internal (MWR) temperatures by recording passive electromagnetic radiation through the chest wall in the projection of the lungs at 30 symmetrical points on both sides. Pneumonia and lung damage were diagnosed by X-RAY/CT scan and doctor final diagnosis (pn+/pn-). COVID-19 was determined by PCR test (covid+/covid-). The best results were obtained between pn-/covid- and pn+/covid+ groups with sensitivity 92% and specificity 75%.Overall, the study suggests that the use of MWR is a convenient and safe method for screening diagnostics in COVID-19 patients with suspected pneumonia. Since MWR is an inexpensive, it will ease the financial burden for both patients and the countries, especially in LMIC\n\nSummary statementCategorization of COVID-19 caused pneumonia suspicion by MWR has good diagnostic perspectives. It could be done in clinics or for mass screening to identify potential COVID-19 patients with lung complications.\n\nBackgroundThe use of chest CT for COVID-19 and PCR diagnosis in healthcare settings with limited PCR and CT capacity is controversial. MWR categorization of the level of COVID-19 suspicion of lung complications might improve diagnostic performance.\n\nPurposeTo investigate the value of MWR in addition to CT and COVID-19 PCR scans and to determine its diagnostic performance in individuals with COVID-19 symptoms during hospital admission and rehabilitation.\n\nMaterials and MethodsIn this trial (Kyrgyz Committee Clinical Trial Number: 01-2/141 27 May 2020), from June, 1 2020 to August, 1 2020, we performed parallel MWR, PCR and CT tests, for individuals with COVID-19 admitted to the hospital for medical emergencies related to COVID-19 and pneumonia suspicion. Siemens Ecoline CT scanner, and HITACHI, Radnext 50 Chest X-Ray was used. RT-PCR test were done using \"DNA technology\" company https://www.dna-technology.ru/equipmentpr/nabory-reagentov-dlya-pcr-infekcii-respiratornogo-trakta/sars-cov-2sars-cov). For MWR and IR measurements RTM-01-RES was used MMWR LTD, UK (www.mmwr.co.uk)\n\nResultsThis was a randomized controlled trial to evaluate the effectiveness of diagnostics of COVID-19 (covid-/covid+) and pneumonia (pn+/pn-) using passive microwave radiometry (MWR) in patients while they are in hospital, and healthy individuals. We have measured internal (MWR) and skin (IR) temperature on 195 subjects. 149 of them were hospitalized with pneumonia symptoms to Medical center of KSMA and BICARD clinic. Pneumonia and lung damage were diagnosed by X-RAY/CT scans and radiologists lung damage assessment (pn+/pn-). COVID-19 was determined by PCR test (covid+/covid-). The best diagnostics results were obtained between pn-/covid- and pn+/covid+ groups with sensitivity 92% and specificity 75%.\n\nConclusionThe study suggests that the use of MWR is a convenient and safe method for screening diagnostics in COVID-19 patients with suspected pneumonia. Since MWR is inexpensive, it will ease the financial burden for both patients and the countries, especially in LMIC.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Xiao Huang", - "author_inst": "University of Arkansas" + "author_name": "Batyr Osmonov", + "author_inst": "Educational clinical scientific medical center of KSMA (KSMA)" }, { - "author_name": "Zhenlong Li", - "author_inst": "University of South Carolina" + "author_name": "Lev Ovchinnikov", + "author_inst": "Medical Microwave Radiometry LTD, UK" }, { - "author_name": "Junyu Lu", - "author_inst": "Arizona State University" + "author_name": "Christopher Galazis", + "author_inst": "University of Edinburgh" }, { - "author_name": "Sicheng Wang", - "author_inst": "Rutgers University" + "author_name": "Berik Emilov", + "author_inst": "International Medical University (IMU), Kyrgyzstan" }, { - "author_name": "Hanxue Wei", - "author_inst": "Cornell University" + "author_name": "Mustafa Karaibragimov", + "author_inst": "International Medical University (IMU), Kyrgyzstan" }, { - "author_name": "Baixu Chen", - "author_inst": "University of Michigan" + "author_name": "Meder Seitov", + "author_inst": "International Medical University (IMU), Kyrgyzstan" + }, + { + "author_name": "Sergey Vesnin", + "author_inst": "Medical Microwave Radiometry, UK" + }, + { + "author_name": "Turat Kasymbekov", + "author_inst": "Komfort Medic, Kyrgyzstan" + }, + { + "author_name": "Chingis Mustafin", + "author_inst": "Comfort Medic, Kyrgyzstan" + }, + { + "author_name": "Igor Goryanin", + "author_inst": "University of Edinburgh" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "radiology and imaging" }, { "rel_doi": "10.1101/2020.09.30.20204693", @@ -1147262,55 +1148034,35 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2020.09.29.318931", - "rel_title": "Computational identification of human biological processes and protein sequence motifs putatively targeted by SARS-CoV-2 proteins using protein-protein interaction networks", + "rel_doi": "10.1101/2020.09.30.320242", + "rel_title": "Host range projection of SARS-CoV-2: South Asia perspective", "rel_date": "2020-09-30", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.09.29.318931", - "rel_abs": "While the COVID-19 pandemic is causing important loss of life, knowledge of the effects of the causative SARS-CoV-2 virus on human cells is currently limited. Investigating protein-protein interactions (PPIs) between viral and host proteins can provide a better understanding of the mechanisms exploited by the virus and enable the identification of potential drug targets. We therefore performed an in-depth computational analysis of the interactome of SARS-CoV-2 and human proteins in infected HEK293 cells published by Gordon et al. to reveal processes that are potentially affected by the virus and putative protein binding sites. Specifically, we performed a set of network-based functional and sequence motif enrichment analyses on SARS-CoV-2-interacting human proteins and on a PPI network generated by supplementing viral-host PPIs with known interactions. Using a novel implementation of our GoNet algorithm, we identified 329 Gene Ontology terms for which the SARS-CoV-2-interacting human proteins are significantly clustered in the network. Furthermore, we present a novel protein sequence motif discovery approach, LESMoN-Pro, that identified 9 amino acid motifs for which the associated proteins are clustered in the network. Together, these results provide insights into the processes and sequence motifs that are putatively implicated in SARS-CoV-2 infection and could lead to potential therapeutic targets.", - "rel_num_authors": 9, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.09.30.320242", + "rel_abs": "Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), the causing agent of Coronavirus Disease-2019 (COVID-19), is likely to be originated from bat and transmitted through intermediate hosts. However, the immediate source species of SARS-CoV-2 has not yet been confirmed. Here, we used diversity analysis of the angiotensin I converting enzyme 2 (ACE2) that serves as cellular receptor for SARS-CoV-2 and transmembrane protease serine 2 (TMPRSS2), which has been proved to be utilized by SARS-CoV-2 for spike protein priming. We also simulated the structure of receptor binding domain of SARS-CoV-2 spike protein (SARS-CoV-2 S RBD) with the ACE2s to investigate their binding affinity to determine the potential intermediate animal hosts that could spread the SARS-CoV-2 virus to humans in South Asia. We identified cow, buffalo, goat and sheep, which are predominant species in the household farming system in South Asia that can potentially be infected by SARS-CoV-2. All the bird species studied along with rat and mouse were considered less potential to interact with SARS-CoV-2. The interaction interfaces of SARS-CoV-2 S RBD and ACE2 protein complex suggests pangolin as a potential intermediate host in SARS-CoV-2. Our results provide a valuable resource for the identification of potential hosts for SARS-CoV-2 in South Asia and henceforth reduce the opportunity for a future outbreak of COVID-19.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Rachel Nadeau", - "author_inst": "University of Ottawa" - }, - { - "author_name": "Soroush Shahryari Fard", - "author_inst": "University of Ottawa" - }, - { - "author_name": "Amit Scheer", - "author_inst": "University of Ottawa" - }, - { - "author_name": "Emily Hashimoto-Roth", - "author_inst": "University of Ottawa" - }, - { - "author_name": "Dallas Nygard", - "author_inst": "University of Ottawa" - }, - { - "author_name": "Iryna Abramchuk", - "author_inst": "University of Ottawa" + "author_name": "Rasel Ahmed", + "author_inst": "Bangladesh Jute Research Institute" }, { - "author_name": "Yun-En Chung", - "author_inst": "University of Ottawa" + "author_name": "Rajnee Hasan", + "author_inst": "Bangladesh Jute Research Institute" }, { - "author_name": "Steffany A. L. Bennett", - "author_inst": "University of Ottawa" + "author_name": "AMAM Zonaed Siddiki", + "author_inst": "Chittagong Veterinary and Animal Sciences University" }, { - "author_name": "Mathieu Lavallee-Adam", - "author_inst": "University of Ottawa" + "author_name": "Md. Shahidul Islam", + "author_inst": "Bangladesh Jute Research Institute" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "new results", - "category": "bioinformatics" + "category": "molecular biology" }, { "rel_doi": "10.1101/2020.09.29.319566", @@ -1149196,57 +1149948,73 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.09.28.20203166", - "rel_title": "Comparison of infection control strategies to reduce COVID-19 outbreaks in homeless shelters in the United States: a simulation study", + "rel_doi": "10.1101/2020.09.29.20203745", + "rel_title": "Changes to the sebum lipidome upon COVID-19 infection observed via non-invasive and rapid sampling from the skin", "rel_date": "2020-09-29", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.28.20203166", - "rel_abs": "BackgroundCOVID-19 outbreaks have occurred in homeless shelters across the US, highlighting an urgent need to identify the most effective infection control strategy to prevent future outbreaks.\n\nMethodsWe developed a microsimulation model of SARS-CoV-2 transmission in a homeless shelter and calibrated it to data from cross-sectional polymerase-chain-reaction (PCR) surveys conducted during COVID-19 outbreaks in five shelters in three US cities from March 28 to April 10, 2020. We estimated the probability of averting a COVID-19 outbreak when an exposed individual is introduced into a representative homeless shelter of 250 residents and 50 staff over 30 days under different infection control strategies, including daily symptom-based screening, twice-weekly PCR testing and universal mask wearing.\n\nResultsThe proportion of PCR-positive residents and staff at the shelters with observed outbreaks ranged from 2.6% to 51.6%, which translated to basic reproduction number (R0) estimates of 2.9-6.2. The probability of averting an outbreak diminished with higher transmissibility (R0) within the simulated shelter and increasing incidence in the local community. With moderate community incidence (~30 confirmed cases/1,000,000 people/day), the estimated probabilities of averting an outbreak in a low-risk (R0=1.5), moderate-risk (R0=2.9), and high-risk (R0=6.2) shelter were, respectively: 0.35, 0.13 and 0.04 for daily symptom-based screening; 0.53, 0.20, and 0.09 for twice-weekly PCR testing; 0.62, 0.27 and 0.08 for universal masking; and 0.74, 0.42 and 0.19 for these strategies combined.\n\nConclusionsIn high-risk homeless shelter environments and locations with high community incidence of COVID-19, even intensive infection control strategies (incorporating daily symptom-screening, frequent PCR testing and universal mask wearing) are unlikely to prevent outbreaks, suggesting a need for non-congregate housing arrangements for people experiencing homelessness. In lower-risk environments, combined interventions should be employed to reduce outbreak risk.", - "rel_num_authors": 10, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.29.20203745", + "rel_abs": "The COVID-19 pandemic has led to an urgent and unprecedented demand for testing - both for diagnosis and prognosis. Here we explore the potential for using sebum, collected via swabbing of a patients skin, as a novel sampling matrix to fulfil these requirements. In this pilot study, sebum samples were collected from 67 hospitalised patients (30 PCR positive and 37 PCR negative). Lipidomics analysis was carried out using liquid chromatography mass spectrometry. Lipid levels were found to be depressed in COVID-19 positive participants, indicative of dyslipidemia. Partial Least Squares-Discriminant Analysis (PLS-DA) modelling showed promising separation of COVID-19 positive and negative participants when comorbidities and medication were controlled for, with sensitivity of 75% and specificity of 81% in stratified subsets. Given that sebum sampling is rapid and non-invasive, this work highlights the potential of this alternative matrix for testing for COVID-19.", + "rel_num_authors": 14, "rel_authors": [ { - "author_name": "Lloyd A. C. Chapman", - "author_inst": "University of California, San Francisco" + "author_name": "Matt P Spick", + "author_inst": "University of Surrey" }, { - "author_name": "Margot Kushel", - "author_inst": "University of California, San Francisco" + "author_name": "Katie Longman", + "author_inst": "University of Surrey" }, { - "author_name": "Sarah N. Cox", - "author_inst": "San Francisco Department of Public Health" + "author_name": "Cecile Frampas", + "author_inst": "University of Surrey" }, { - "author_name": "Ashley Scarborough", - "author_inst": "San Francisco Department of Public Health" + "author_name": "Catia Costa", + "author_inst": "University of Surrey" }, { - "author_name": "Caroline Cawley", - "author_inst": "University of California, San Francisco" + "author_name": "Deborah Dunn-Walters", + "author_inst": "University of Surrey" }, { - "author_name": "Trang Nguyen", - "author_inst": "San Francisco Department of Public Health" + "author_name": "Alex Stewart", + "author_inst": "University of Surrey" }, { - "author_name": "Isabel Rodriguez-Barraquer", - "author_inst": "University of California, San Francisco" + "author_name": "Mike Wilde", + "author_inst": "University of Leicester" }, { - "author_name": "Bryan Greenhouse", - "author_inst": "University of California, San Francisco" + "author_name": "Danni Greener", + "author_inst": "Frimley Park Hospital" }, { - "author_name": "Elizabeth Imbert", - "author_inst": "University of California, San Francisco" + "author_name": "George Evetts", + "author_inst": "Frimley Park Hospital" }, { - "author_name": "Nathan C. Lo", - "author_inst": "University of California, San Francisco" + "author_name": "Drupad K Trivedi", + "author_inst": "University of Manchester" + }, + { + "author_name": "Perdita Barran", + "author_inst": "University of Manchester" + }, + { + "author_name": "Andy Pitt", + "author_inst": "University of Manchester" + }, + { + "author_name": "Melanie Bailey", + "author_inst": "University of Surrey" + }, + { + "author_name": "Holly May Lewis", + "author_inst": "University of Surrey" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1150894,29 +1151662,21 @@ "category": "health policy" }, { - "rel_doi": "10.1101/2020.09.27.20202754", - "rel_title": "Remdesivir for the treatment of COVID-19: A living systematic review", + "rel_doi": "10.1101/2020.09.27.20202556", + "rel_title": "Scrutinizing the Spread of Covid-19 in Madagascar", "rel_date": "2020-09-28", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.27.20202754", - "rel_abs": "Objective This living systematic review aims to provide a timely, rigorous and continuously updated summary of the evidence available on the role of remdesivir in the treatment of patients with COVID-19 Methods We adapted an already published common protocol for multiple parallel systematic reviews to the specificities of this question. Eligible studies were randomised trials evaluating the effect of remdesivir versus placebo or no treatment. We conducted searches in the LOVE (Living OVerview of Evidence) platform for COVID-19, a system that maps PICO questions to a repository maintained through regular searches in electronic databases, preprint servers, trial registries and other resources relevant to COVID-19. All the searches covered the period until 25 August 2020. No date or language restrictions were applied. Two reviewers independently evaluated potentially eligible studies according to predefined selection criteria, and extracted data on study characteristics, methods, outcomes, and risk of bias, using a predesigned, standardised form. We performed meta-analyses using random-effect models and assessed overall certainty in evidence using the GRADE approach. A living, web-based version of this review will be openly available during the COVID-19 pandemic. We will resubmit it every time the conclusions change or whenever there are substantial updates. Results Our search strategy yielded 574 references. Finally, we included 3 randomised trials evaluating remdesivir in addition to standard care versus standard care alone. The evidence is very uncertain about the effect of remdesivir on mortality (RR 0.7, 95% CI 0.46 to 1.05; very low certainty evidence) and the need for invasive mechanical ventilation (RR 0.69, 95% CI 0.39 to 1.24; very low certainty evidence). On the other hand, remdesivir likely results in a large reduction in the incidence of adverse effects in patients with COVID-19 (RR 1.29, 95% CI 0.58 to 2.84; moderate certainty evidence). Conclusions The evidence is insufficient for the outcomes critical for making decisions about the role of remdesivir in the treatment of patients with COVID-19, so it is not possible to balance the potential benefits, if any, with the adverse effects and costs. PROSPERO Registration number CRD42020183384 Keywords COVID-19, Coronavirus disease, Severe Acute Respiratory Syndrome Coronavirus 2, Coronavirus Infections, Systematic Review, Remdesivir, Antivirals", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.27.20202556", + "rel_abs": "We scrutinize the evolution of Covid-19 in Madagascar by comparing results from three approaches (cubic polynomial, semi-gaussian and gaussian-like models) which we use to provide an analytical form of the spread of the pandemic. In so doing, we introduce (for the first time) the ratio [Formula] of the cumulative and daily numbers of infected persons over the corresponding one of tests which are expected to be less sensitive to the number of the tests because the credibility of the results based only on the absolute numbers often raises some criticisms. We also give and compare the reproduction number Reff from different approaches and with the ones with the ones of some European countries with a small number of population (Greece, Switzerland) and some other African countries. Finally, we show and comment the evolution of the total number of deaths and of the per cent number of cured persons and discuss the performance of the medical care.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Francisca Verdugo-Paiva", - "author_inst": "Epistemonikos Foundation" - }, - { - "author_name": "Maria Paz Acuna", - "author_inst": "Unidad de Infectologia, Hospital Dr Sotero del Rio, Santiago, Chile" - }, - { - "author_name": "Ivan Sola", - "author_inst": "Biomedical Research Institute Sant Pau, Barcelona, Spain" + "author_name": "Stephan Narison", + "author_inst": "LUPM/Cnrs/In2p3 and Univ. Montpellier (FR) and iHEPMAD/Univ. Antananarivo (MG)" }, { - "author_name": "Gabriel Rada", - "author_inst": "Epistemonikos Foundation" + "author_name": "Stavros Maltezos", + "author_inst": "National Technical University of Athens (NTUA), Physics Department, Athens, Greece" } ], "version": "1", @@ -1152344,43 +1153104,51 @@ "category": "primary care research" }, { - "rel_doi": "10.1101/2020.09.25.20197061", - "rel_title": "Hearing the voices of Australian healthcare workers during the COVID-19 pandemic", + "rel_doi": "10.1101/2020.09.25.20201343", + "rel_title": "Onset, duration, and persistence of taste and smell changes and other COVID-19 symptoms: longitudinal study in Israeli patients", "rel_date": "2020-09-27", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.25.20197061", - "rel_abs": "BackgroundThe statistics of healthcare worker (HCW) COVID-19 infections do not convey the lived experience of HCWs during the pandemic. This study explores the working conditions and issues faced by Australian HCWs.\n\nMethodsQualitative analysis of free-text responses from Australian HCWs from 3 August to 5 August 2020 from an open letter calling for better respiratory protection for HCWs, transparent reporting of HCW COVID-19 infections and diversity in national infection control policy development. The open letter was sent to an email list of 23,000 HCWs from a previous campaign and promoted on social media.\n\nResultsAmong 2,733 HCWs who signed the open letter during the study period, 407 free-text responses were analysed. Doctors and nurses accounted for 58% and 35% of respondents, respectively. Most respondents came from Victoria (48%); New South Wales (18%); Queensland (12%) or Western Australia (12%). Dominant themes included concerns about: work health and safety standards; guidelines on respiratory protection including the omission of fit-testing of P2/N95 respirators; deficiencies in the availability, quality, appropriateness and training of personal protective equipment; a top-down workplace culture that enabled bullying in response to concerns about safety that culminated a loss of trust in leadership, self-reported COVID-19 infections in some respondents and moral injury.\n\nConclusionOccupational moral injury in HCWs is the consequence of lapses in leadership at policy-making and organisational levels that have violated the normative expectations of HCWs. The challenge for healthcare leaders is to address workplace culture, consultation and engagement with HCWs in order to prevent this hidden pandemic from spreading throughout the health system.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.25.20201343", + "rel_abs": "ObjectivesThe multifaceted manifestation of COVID-19 requires longitudinal characterization of symptoms, to aid with screening and disease management.\n\nMethodsPhone interviews and follow-ups were completed with 112 mostly mild COVID-19 RT-PCR-positive adult patients, over a six-months period.\n\nResultsMore than one symptom at disease onset was experienced by [~]70% of the patients. About 40% of the patients experienced fever, dry cough, headache, or muscle ache as the first symptom. Fatigue, if reported, usually was the first to appear. Smell and taste changes were experienced 3.9 {+/-} 5.4 and 4.6 {+/-} 5.7 days (mean {+/-} SD) after disease onset and emerged as first symptom in 15% and 18% of patients, respectively. Fever had the shortest duration (5.8 {+/-} 8.6 days), and taste and smell changes were the longest-lasting symptoms (17.2 {+/-} 17.6 and 18.9 {+/-} 19.7 days, durations censored at 60 days). Longer smell recovery correlated with smell change severity. Cough, taste change and smell change persisted after negative RT-PCR tests (in 20%, 26% and 29% of the patients in total). At six-months follow-up, 46% of the patients had at least one unresolved symptom, most commonly fatigue (21%), chemosensory changes (14%) or breath difficulty (9%).\n\nConclusionsMore than one symptom typically occurred at disease onset. Chemosensory changes and cough persisted after negative RT-PCR in a quarter of the patients. Almost half of the patients reported at least one unresolved symptom at six-months follow up, mainly fatigue, smell changes and breath difficulty. Our findings highlight the prevalence of long-lasting effects of COVID-19.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Michelle Ananda-Rajah", - "author_inst": "Hospital, Melbourne" + "author_name": "Hadar Klein", + "author_inst": "The Hebrew University of Jerusalem" }, { - "author_name": "Benjamin Veness", - "author_inst": "Hospital, Melbourne" + "author_name": "Kim Asseo", + "author_inst": "The Hebrew University of Jerusalem" + }, + { + "author_name": "Noam Karni", + "author_inst": "Hebrew University Hadassah Medical School" + }, + { + "author_name": "Yuval Benjamini", + "author_inst": "Hebrew University of Jerusalem" }, { - "author_name": "Danielle Berkovic", - "author_inst": "School of Public Health and Preventive Medicine, Monash University, Melbourne" + "author_name": "Ran Nir-Paz", + "author_inst": "Hadassah Hebrew University Medical Center" }, { - "author_name": "Catriona Parker", - "author_inst": "School of Public Health and Preventive Medicine, Monash University, Melbourne" + "author_name": "Mordechai Muszkat", + "author_inst": "Hadassah Hebrew University Medical Center" }, { - "author_name": "Greg Kelly", - "author_inst": "Hospital, Sydney" + "author_name": "Sarah Israel", + "author_inst": "Hadassah Hebrew University Medical Center" }, { - "author_name": "Darshini Ayton", - "author_inst": "School of Public Health and Preventive Medicine, Monash University, Melbourne" + "author_name": "Masha Y Niv", + "author_inst": "The Hebrew University of Jerusalem" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "health systems and quality improvement" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2020.09.25.20183459", @@ -1154142,71 +1154910,67 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2020.09.24.20200873", - "rel_title": "Anti-SARS-CoV-2 IgM and IgG antibodies in health workers in Sergipe, Brazil", + "rel_doi": "10.1101/2020.09.23.20199877", + "rel_title": "A low-cost, rapidly scalable, emergency use ventilator for the COVID-19 crisis", "rel_date": "2020-09-25", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.24.20200873", - "rel_abs": "BackgroundThe exponential growth of COVID-19 cases in Brazil is overloading health systems with overcrowding of hospitals and overflowing intensive care units. Increasing infection rates in health professionals can lead to the collapse of the health system and further worsen the pandemic. The aim of this study was to evaluate the seroprevalence of IgM and IgG for SARS-CoV-2 in health workers in Sergipe, Brazil.\n\nMethodsThe targeted tests involved health professionals working on the front line to combat COVID-19. The samples were collected in the month of June, in six hospital units in the state of Sergipe.\n\nResults471 health professionals were tested. Of these, 28 workers (5.95%) tested positive for IgM and 64 (13.59%) tested positive for IgG. 9 workers (1.91%) tested positive for IgM and were also positive for IgG.\n\nDiscussionHealth workers must be monitored constantly, because if they are infected, they can spread the virus to colleagues, hospitalized patients and even family members.\n\nConclusionKnowing the prevalence of antibodies to the virus in health workers is an important measure of viral spread control.", - "rel_num_authors": 13, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.23.20199877", + "rel_abs": "For the past 50 years, positive pressure ventilation has been a cornerstone of treatment for respiratory failure. Consensus surrounding the epidemiology of respiratory failure has permitted a relatively good fit between the supply of ventilators and the demand. However, the current COVID-19 pandemic has increased demand for mechanical ventilators well beyond supply. Respiratory failure complicates most critically ill patients with COVID-19 and is characterized by highly heterogeneous pulmonary parenchymal involvement, profound hypoxemia and pulmonary vascular injury. The profound increase in the incidence of respiratory failure has exposed critical shortages in the supply of mechanical ventilators, and those with the necessary skills to treat. While most traditional ventilators rely on an internal compressor and mixer to moderate and control the gas mixture delivered to a patient, the current emergency climate has catalyzed alternative designs that might enable greater flexibility in terms of supply chain, manufacturing, storage and maintenance. Design considerations of these \"emergency response\" ventilators have generally fallen into two categories: those that rely on mechanical compression of a known volume of gas and those powered by an internal compressor to deliver time cycled pressure- or volume-limited gas to the patient. The present work introduces a low-cost, ventilator designed and built in accordance with the Emergence Use guidance provided by the US Food and Drug Administration (FDA) wherein an external gas supply feeds into the ventilator and time limited flow interruption guarantees tidal volume. The goal of this device is to allow a patient to be treated by a single ventilator platform, capable of supporting the various treatment paradigms during a potential COVID-19 related hospitalization. This is a unique aspect of this design as it attempts to become a one-device-one-visit solution to the problem. The device is designed as a single use ventilator that is sufficiently robust to treat a patient being mechanically ventilated. The overall design philosophy and its applicability in this new crisis-laden world view is first described, followed by both bench top and animal testing results used to confirm the precision, capability, safety and reliability of this low cost and novel approach to mechanical ventilation during the COVID-19 pandemic. The ventilator is shown to perform in a range of critical requirements listed in the FDA emergency regulations and can safely and effectively ventilate a porcine subject. As of August 2020, only 13 emergency ventilators have been authorized by the FDA, and this work represents the first to publish animal data using the ventilator. This proof-of-concept provides support for this cost-effective, readily mass-produced ventilator that can be used to support patients when the demand for ventilators outstrips supply in hospital settings worldwide. More details for this project can be found at https://ventilator.stanford.edu/", + "rel_num_authors": 12, "rel_authors": [ { - "author_name": "MONICA SANTOS DE MELO Sr.", - "author_inst": "UNIVERSIDADE FEDERAL DE SERGIPE" - }, - { - "author_name": "LYSANDRO PINTO BORGES Sr.", - "author_inst": "UNIVERSIDADE FEDERAL DE SERGIPE" + "author_name": "Samuel J Raymond", + "author_inst": "Stanford University" }, { - "author_name": "DANIELA RAGUER VALADAO SOUZA Sr.", - "author_inst": "UNIVESIDADE FEDERAL DE SERGIPE" + "author_name": "Trevor Wesolowski", + "author_inst": "219 Design LLC" }, { - "author_name": "ALINE FAGUNDES MARTINS Sr.", - "author_inst": "UNIVESIDADE FEDERAL DE SERGIPE" + "author_name": "Sam Baker", + "author_inst": "Stanford University" }, { - "author_name": "JOSE MELQUIADES DE REZENDE NETO Sr.", - "author_inst": "UNIVESIDADE FEDERAL DE SERGIPE" + "author_name": "Yuzhe Liu", + "author_inst": "Stanford University" }, { - "author_name": "ANDERSON ALVES RIBEIRO Sr.", - "author_inst": "Federal University of the Southern Border" + "author_name": "Jordan L Edmunds", + "author_inst": "University of California, Berkeley" }, { - "author_name": "ARYANNE SANTOS Jr.", - "author_inst": "UNIVESIDADE FEDERAL DE SERGIPE" + "author_name": "Mauricio J Bustamante", + "author_inst": "University of California, Berkeley" }, { - "author_name": "GRAZIELLY BISPO DA INVENCAO Jr.", - "author_inst": "UNIVESIDADE FEDERAL DE SERGIPE" + "author_name": "Brett Ley", + "author_inst": "Kaiser Pulmonology and Critical Care" }, { - "author_name": "IGOR LEONARDO SANTOS MATOS Jr.", - "author_inst": "UNIVESIDADE FEDERAL DE SERGIPE" + "author_name": "Dwayne Free", + "author_inst": "Stanford University" }, { - "author_name": "KEZIA ALVES DO SANTOS Jr.", - "author_inst": "UNIVESIDADE FEDERAL DE SERGIPE" + "author_name": "Michel Maharbiz", + "author_inst": "University of California, Berkeley" }, { - "author_name": "NICOLAS ALESSANDRO ALVES SOUZA Jr.", - "author_inst": "UNIVESIDADE FEDERAL DE SERGIPE" + "author_name": "Ryan Van Wert", + "author_inst": "Stanford University" }, { - "author_name": "PAMELA CHAVES BORGES Jr.", - "author_inst": "UNIVESIDADE FEDERAL DE SERGIPE" + "author_name": "David N Cornfield", + "author_inst": "Stanford University" }, { - "author_name": "MAKSON GLEYDSON BRITO DE OLIVEIRA Sr.", - "author_inst": "UNIVERSIDADE FEDERAL DE SERGIPE" + "author_name": "David B Camarillo", + "author_inst": "Stanford University" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "emergency medicine" }, { "rel_doi": "10.1101/2020.09.24.20200436", @@ -1155868,29 +1156632,37 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.09.23.20150961", - "rel_title": "Prospective comparison of saliva and nasopharyngeal swab sampling for mass screening for COVID-19", + "rel_doi": "10.1101/2020.09.23.20200089", + "rel_title": "Epidemiological measures for informing the general public during the SARS-CoV-2-outbreak: simulation study about bias by incomplete case-detection", "rel_date": "2020-09-24", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.23.20150961", - "rel_abs": "Current testing for COVID-19 relies on quantitative reverse-transcriptase polymerase chain reaction from a nasopharyngeal swab specimen. Saliva samples have advantages regarding ease and painlessness of collection, which does not require trained staff and may allow self-sampling. We enrolled 776 persons at various field-testing sites and collected nasopharyngeal and pooled saliva samples. 162 had a positive COVID-19 RT-PCR, 61% were mildly symptomatic and 39% asymptomatic. The sensitivity of RT-PCR on saliva samples versus nasopharygeal swabs varied depending on the patient groups considered or on Ct thresholds. There were 10 (6.2%) patients with a positive saliva sample and a negative nasopharyngeal swab, all of whom had Ct values<25. For symptomatic patients for whom the interval between symptoms onset and sampling was <10 days sensitivity was 77% but when excluding persons with isolated Ngen positivity (54/162), sensitivity was 90%. In asymptomatic patients, the sensitivity was only 24%. When we looked at patients with Cts <30, sensitivity was 83% or 88.9% when considering 2 genes. The relatively good performance for patients with low Cts suggests that Saliva testing could be a useful and acceptable tool to identify infectious persons in mass screening contexts, a strategically important task for contact tracing and isolation in the community.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.23.20200089", + "rel_abs": "During the SARS-CoV-2 outbreak, several epidemiological measures, such as cumulative case-counts, incidence rates, effective reproduction numbers and doubling times, have been used to inform the general public and to justify interventions such as lockdown.\n\nDuring the course of the epidemic, it has been very likely that not all infectious people have been identified, which lead to incomplete case-detection. Apart from asymptomatic infections, possible reasons for incomplete case-detection are availability of test kits and changes in test policies during the course of the epidemic. So far, it has not been examined how biased the reported epidemiological measures are in the presence of incomplete case detection.\n\nIn this work, we assess the four frequently used measures with respect to incomplete case-detection: 1) cumulative case-count, 2) incidence rate, 3) effective reproduction number and 4) doubling time. We apply an age-structured SIR model to simulate a SARS-CoV-2 outbreak followed by a lockdown in a hypothetical population. Different scenarios about temporal variations in case-detection are applied to the four measures during outbreak and lockdown. The biases resulting from incomplete case-detection on the four measures are compared. It turns out that the most frequently used epidemiological measure, the cumulative case count is most prone to bias in all of our settings. The effective reproduction number is the least biased measure.\n\nWith a view to future reporting about this or other epidemics, we recommend to use of the effective reproduction number for informing the general public and policy makers.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "- COVISAL Guyane", - "author_inst": "" + "author_name": "Ralph Brinks", + "author_inst": "Department of Statistics, Ludwig-Maximilians-Universitaet Munich, Munich, Germany" }, { - "author_name": "mathieu nacher", - "author_inst": "Centre Hospitalier Andree Rosemon" + "author_name": "Helmut Kuechenhoff", + "author_inst": "Department of Statistics, Ludwig-Maximilians-Universitaet Munich, Munich, Germany" }, { - "author_name": "magalie demar", - "author_inst": "Centre Hospitalier Andree Rosemon" + "author_name": "Joerg Timm", + "author_inst": "Medical Faculty, Institute of Virology, University Hospital Duesseldorf, Duesseldorf, Germany" + }, + { + "author_name": "Tobias Kurth", + "author_inst": "Institute of Public Health, Charite - Universitaetsmedizin Berlin, Berlin, Germany" + }, + { + "author_name": "Annika Hoyer", + "author_inst": "Department of Statistics, Ludwig-Maximilians-Universitaet Munich, Munich, Germany" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1157642,37 +1158414,101 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.09.20.20198515", - "rel_title": "Efficacy and Safety of Guduchi Ghan Vati in the Management of Asymptomatic COVID-19 infection: An Open Label Feasibility Study", + "rel_doi": "10.1101/2020.09.21.20198671", + "rel_title": "T cell anergy in COVID-19 reflects virus persistence and poor outcomes", "rel_date": "2020-09-23", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.20.20198515", - "rel_abs": "BackgroundGuduchi Ghan Vati (aqueous extract of Tinospora cordifolia) is an essential herbal plant in Indian traditional medicine (Ayurveda) that is well documented as an immunomodulator and antimicrobial agent. A recent in silico study found the therapeutic efficacy of Guduchi against SARS-CoV-2. Based on available evidence, we conducted a feasibility study of the safety and efficacy of Guduchi Ghan Vati in asymptomatic patients with covid-19.\n\nPatients and methodsAn open label, feasibility trial was conducted on 46 patients in the hospital setting. A single-arm study with no control group and blinding was executed in Jodhpur, Rajasthan, India. All patients orally received 2 tablets (1000 mg) twice daily for 2 weeks. Clinical parameters were collected at baseline, day 3, day 7 and day 14. Patients were continuously monitored for side effects and adverse reactions during the study period..\n\nResultsOut of 46 asymptomatic patients included in the study, 40 completed the 14-day follow-up period. None developed any Covid-19 symptoms after admission to the hospital. On day 3 post-treatment, viral clearance was reported in 16 (32.5%) patients. By the end of D-7, 38 (95%) patients had viral load disappearance. Follow-up at D-14 showed that all participants tested negative.\n\nConclusionIn adult patients with asymptomatic Covid-19, Gudhuchi Ghan Vati could be effective. Randomized controlled trials with larger sample sizes in patients with Covid-19 are urgently needed to confirm the definite benefit with Ayurveda.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.21.20198671", + "rel_abs": "Coronavirus disease 2019 (COVID-19) can lead to severe pneumonia and hyperinflammation. So far, insufficient or excessive T cell responses were described in patients. We applied novel approaches to analyze T cell reactivity and showed that T anergy is already present in non-ventilated COVID-19 patients, very pronounced in ventilated patients, strongly associated with virus persistence and reversible with clinical recovery. T cell activation was measured by downstream effects on responder cells like basophils, plasmacytoid dendritic cells, monocytes and neutrophils in whole blood and proved to be much more meaningful than classical readouts with PBMCs. Monocytes responded stronger in males than females and IL-2 partially reversed T cell anergy. Downstream markers of T cell anergy were also found in fresh blood samples of critically ill patients with severe T cell anergy. Based on our data we were able to develop a score to predict fatal outcomes and to identify patients that may benefit from strategies to overcome T cell anergy.", + "rel_num_authors": 21, "rel_authors": [ { - "author_name": "Abhimanyu Kumar", - "author_inst": "Dr Sarvepalli Radhakrishnan Rajasthan Ayurved University, Jodhpur, India" + "author_name": "Kerstin Renner", + "author_inst": "University Hospital Regensburg" }, { - "author_name": "Govind Prasad", - "author_inst": "Dr Sarvepalli Radhakrishnan Rajasthan Ayurved University, Jodhpur, India" + "author_name": "Christine Mueller", + "author_inst": "University Hospital Regensburg" }, { - "author_name": "Sanjay Srivastav", - "author_inst": "Dr Sarvepalli Radhakrishnan Rajasthan Ayurved University Jodhpur, India" + "author_name": "Charlotte Tiefenboeck", + "author_inst": "University Hospital Regensburg" }, { - "author_name": "Vinod Kumar Gautam", - "author_inst": "Dr Sarvepalli Radhakrishnan Rajasthan Ayurved University Jodhpur, India" + "author_name": "Jan-Niklas Salewski", + "author_inst": "University Hospital Regensburg" }, { - "author_name": "Neha Sharma", - "author_inst": "Aarogyam (UK) CIC, United Kingdom" + "author_name": "Frederike Winter", + "author_inst": "University Hospital Regensburg" + }, + { + "author_name": "Simone Buchtler", + "author_inst": "University Hospital Regensburg" + }, + { + "author_name": "Maximilian V Malfertheiner", + "author_inst": "University Hospital Regensburg" + }, + { + "author_name": "Matthias Lubnow", + "author_inst": "University Hospital Regensburg" + }, + { + "author_name": "Dirk Lunz", + "author_inst": "University Hospital Regensburg" + }, + { + "author_name": "Bernhard Graf", + "author_inst": "University Hospital Regensburg" + }, + { + "author_name": "Florian Hitzenbichler", + "author_inst": "University Hospital Regensburg" + }, + { + "author_name": "Frank Hanses", + "author_inst": "University Hospital Regensburg" + }, + { + "author_name": "Hendrik Poeck", + "author_inst": "University Hospital Regensburg" + }, + { + "author_name": "Marina Kreutz", + "author_inst": "University Hospital Regensburg" + }, + { + "author_name": "Evelyn Orso", + "author_inst": "University Hospital Regensburg" + }, + { + "author_name": "Ralph Burkhardt", + "author_inst": "University Hospital Regensburg" + }, + { + "author_name": "Tanja Niedermair", + "author_inst": "University Hospital Regensburg" + }, + { + "author_name": "Christoph Brochhausen", + "author_inst": "University Hospital Regensburg" + }, + { + "author_name": "Andre Gessner", + "author_inst": "University Hospital Regensburg" + }, + { + "author_name": "Bernd Salzberger", + "author_inst": "University Hospital Regensburg" + }, + { + "author_name": "Matthias Mack", + "author_inst": "University Hospital Regensburg" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1159440,33 +1160276,65 @@ "category": "health informatics" }, { - "rel_doi": "10.1101/2020.09.21.20195537", - "rel_title": "Downregulation of Defensin genes in SARS-CoV-2 infection", + "rel_doi": "10.1101/2020.09.21.20194019", + "rel_title": "Putting (Big) Data in Action: Saving Lives with Countrywide Population Movement Monitoring Using Mobile Devices during the COVID-19 Crisis", "rel_date": "2020-09-23", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.21.20195537", - "rel_abs": "Defensins, crucial components of the innate immune system, play a vital role against infection as part of frontline immunity. Association of SARS-CoV-2 infection with defensins has not been investigated till date. In this study, we have investigated the expression of defensin genes in the buccal cavity during COVID-19 infection. Nasopharyngeal/Oropharyngeal swab samples collected for screening SARS-CoV-2 infection were analyzed for the expression of major defensin genes by the quantitative real-time reverse transcription polymerase chain reaction, qRT-PCR. 40 SARS-CoV-2 infected positive and 40 negative swab samples were selected for the study. Based on the RT-PCR analysis involving gene specific primer for defensin genes, 10 defensin genes were found to be expressed in the Nasopharyngeal/Oropharyngeal cavity. Six defensin genes were further found to be significantly downregulated in SARS-CoV-2 infected patients as against the control, negative samples based on differential expression analysis. The genes significantly downregulated were defensin beta 4A, 4B, 106B, 107B, 103A and defensin alpha 1B. Downregulation of several defensin genes suggests that innate immunity provided by defensins is or may be compromised in SARS-CoV-2 infection resulting in progression of the disease caused by the virus. Upregulation of defensin gene expression and use of defensin peptides could be attractive therapeutic interventions.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.21.20194019", + "rel_abs": "Many countries have implemented strict social distancing measures in the hope of reducing transmission of SARS-CoV-2 but the effectiveness of these measures is determined by the willingness of populations to comply with restrictions. Consequently, a system of monitoring population movement using existing data sources can inform those making decisions about policy responses to the COVID-19 pandemic. We describe a collaboration with all 3 major domestic telecommunication companies in Hungary to use aggregated anonymous mobile phone usage data to calculate two indices for assessing the effect of movement restrictions: a \"mobility-index\" and a \"stay-at-home (or resting) index\". The strengths and weaknesses of this approach are compared with the smartphone-based, COVID-19 Community Mobility Reports from Google. Data generated by mobile phones have long been identified as a potential means to analyse mass population movement, but its operationalisation raises several technical questions, such as making sense of Call Detail Records, collation of data from different mobile network providers, and personal data protection concerns. The method described here addresses these issues and offers an effective and inexpensive tool to monitor the impact of social distancing measures, achieving high levels of accuracy and resolution. Especially in populations where uptake of smartphones is modest, this method has certain advantages over app-based solutions, with greater population coverage, but it is not an alternative to smartphone-based solutions used for contact tracing and quarantine monitoring. We believe that this method can easily be adapted by other countries.", + "rel_num_authors": 12, "rel_authors": [ { - "author_name": "Mohammed M Idris", - "author_inst": "CSIR - Centre for Cellular and Molecular Biology" + "author_name": "Miklos Karoly Szocska", + "author_inst": "Semmelweis University, Faculty of Health and Public Administration, Health Services Management Training Centre, Digital Health and Data Utilisation Team" }, { - "author_name": "Sarena Banu", - "author_inst": "CSIR - Centre for Cellular and Molecular Biology" + "author_name": "Peter Pollner", + "author_inst": "Semmelweis University, Faculty of Health and Public Administration, Health Services Management Training Centre, Digital Health and Data Utilisation Team" }, { - "author_name": "Archana B Siva", - "author_inst": "CSIR - Centre for Cellular and Molecular Biology" + "author_name": "Istvan Schiszler", + "author_inst": "Semmelweis University, Faculty of Health and Public Administration, Health Services Management Training Centre, Digital Health and Data Utilisation Team" }, { - "author_name": "Ramakrishnan Nagaraj", - "author_inst": "CSIR-Centre for Cellular and Molecular Biology" + "author_name": "Tamas Joo", + "author_inst": "Semmelweis University, Faculty of Health and Public Administration, Health Services Management Training Centre, Digital Health and Data Utilisation Team" + }, + { + "author_name": "Tamas Palicz", + "author_inst": "Semmelweis University, Faculty of Health and Public Administration, Health Services Management Training Centre, Digital Health and Data Utilisation Team" + }, + { + "author_name": "Martin McKee", + "author_inst": "University of London, London School of Hygiene and Tropical Medicine, Department of Health Services Research and Policy" + }, + { + "author_name": "- Magyar Telekom Nyrt.", + "author_inst": "" + }, + { + "author_name": "- Telenor Magyarorszag Zrt.", + "author_inst": "" + }, + { + "author_name": "Adam Sohonyai", + "author_inst": "Vodafone Hungary" + }, + { + "author_name": "Jozsef Szoke", + "author_inst": "Vodafone Hungary" + }, + { + "author_name": "Adam Toth", + "author_inst": "Vodafone Hungary" + }, + { + "author_name": "Peter Gaal", + "author_inst": "Semmelweis University, Faculty of Health and Public Administration, Health Services Management Training Centre, Digital Health and Data Utilisation Team" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1161146,99 +1162014,47 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.09.16.20195925", - "rel_title": "OpenABM-Covid19 - an agent-based model for non-pharmaceutical interventions against COVID-19 including contact tracing", + "rel_doi": "10.1101/2020.09.17.20192245", + "rel_title": "Nasopharyngeal SARS-CoV2 viral loads in young children do not differ significantly from those in older children and adults", "rel_date": "2020-09-22", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.16.20195925", - "rel_abs": "SARS-CoV-2 has spread across the world, causing high mortality and unprecedented restrictions on social and economic activity. Policymakers are assessing how best to navigate through the ongoing epidemic, with models being used to predict the spread of infection and assess the impact of public health measures. Here, we present OpenABM-Covid19: an agent-based simulation of the epidemic including detailed age-stratification and realistic social networks. By default the model is parameterised to UK demographics and calibrated to the UK epidemic, however, it can easily be re-parameterised for other countries. OpenABM-Covid19 can evaluate non-pharmaceutical interventions, including both manual and digital contact tracing. It can simulate a population of 1 million people in seconds per day allowing parameter sweeps and formal statistical model-based inference. The code is open-source and has been developed by teams both inside and outside academia, with an emphasis on formal testing, documentation, modularity and transparency. A key feature of OpenABM-Covid19 is its Python interface, which has allowed scientists and policymakers to simulate dynamic packages of interventions and help compare options to suppress the COVID-19 epidemic.", - "rel_num_authors": 20, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.17.20192245", + "rel_abs": "The role of children in the spread of the SARS-CoV2 coronavirus has become a matter of urgent debate as societies in the US and abroad consider how to safely reopen schools. Small studies have suggested higher viral loads in young children. Here we present a multicenter investigation on over five thousand SARS-CoV-2 cases confirmed by real-time reverse transcription (RT) PCR assay. Notably, we found no discernable difference in amount of viral nucleic acid among young children and adults.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Robert Hinch", - "author_inst": "Big Data Institute, University of Oxford" - }, - { - "author_name": "William J M Probert", - "author_inst": "Big Data Institute, University of Oxford" - }, - { - "author_name": "Anel Nurtay", - "author_inst": "Big Data Institute, University of Oxford" - }, - { - "author_name": "Michelle Kendall", - "author_inst": "Big Data Institute, University of Oxford" - }, - { - "author_name": "Chris Wymatt", - "author_inst": "Big Data Institute, University of Oxford" + "author_name": "Sharline Madera", + "author_inst": "UCSF Medical Center" }, { - "author_name": "Matthew Hall", - "author_inst": "Big Data Institute, University of Oxford" - }, - { - "author_name": "Katrina Lythgoe", - "author_inst": "Big Data Institute, University of Oxford" - }, - { - "author_name": "Ana Bulas Cruz", - "author_inst": "Big Data Institute, University of Oxford" - }, - { - "author_name": "Lele Zhao", - "author_inst": "Big Data Institute, University of Oxford" - }, - { - "author_name": "Andrea Stewart", - "author_inst": "Big Data Institute, University of Oxford" - }, - { - "author_name": "Luca Ferritti", - "author_inst": "Big Data Institute, University of Oxford" - }, - { - "author_name": "Daniel Montero", - "author_inst": "IBM United Kingdom" - }, - { - "author_name": "James Warren", - "author_inst": "IBM United Kingdom" - }, - { - "author_name": "Nicole Mather", - "author_inst": "IBM United Kingdom" - }, - { - "author_name": "Matthew Abueg", - "author_inst": "Google Research" + "author_name": "Emily Crawford", + "author_inst": "Chan-Zuckerberg Biohub, San Francisco, CA" }, { - "author_name": "Neo Wu", - "author_inst": "Google Research" + "author_name": "Charles Langelier", + "author_inst": "University of California San Francisco" }, { - "author_name": "Anthony Finkelstein", - "author_inst": "Department of Computer Science, University College London" + "author_name": "Nam K Tran", + "author_inst": "Department of Pathology and Laboratory Medicine University of California, Davis School of Medicine, Sacramento, CA" }, { - "author_name": "David G Bonsall", - "author_inst": "Big Data Institute, University of Oxford" + "author_name": "Ed Thornborrow", + "author_inst": "Department of Laboratory Medicine University of California San Francisco, CA" }, { - "author_name": "Lucie Abeler-Dorner", - "author_inst": "Big Data Institute, University of Oxford" + "author_name": "Steve Miller", + "author_inst": "Department of Laboratory Medicine University of California San Francisco, CA" }, { - "author_name": "Christophe Fraser", - "author_inst": "Big Data Institute, University of Oxford" + "author_name": "Joseph L DeRisi", + "author_inst": "Chan-Zuckerberg Biohub, San Francisco, CA" } ], "version": "1", "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2020.09.21.299776", @@ -1162831,107 +1163647,51 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.09.18.20197327", - "rel_title": "Hydroxychloroquine as pre-exposure prophylaxis for COVID-19 in healthcare workers: a randomized trial", + "rel_doi": "10.1101/2020.09.17.20196436", + "rel_title": "Comparison of COVID-19 outcomes among shielded and non-shielded populations: A general population cohort study of 1.3 million", "rel_date": "2020-09-21", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.18.20197327", - "rel_abs": "Background: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a rapidly emerging virus causing the ongoing Covid-19 pandemic with no known effective prophylaxis. We investigated whether hydroxychloroquine could prevent SARS CoV-2 in healthcare workers at high-risk of exposure. Methods: We conducted a randomized, double-blind, placebo-controlled clinical trial of healthcare workers with ongoing exposure to persons with Covid-19, including those working in emergency departments, intensive care units, Covid-19 hospital wards, and first responders. Participants across the United States and in the Canadian province of Manitoba were randomized to hydroxychloroquine 400mg once weekly or twice weekly for 12 weeks. The primary endpoint was confirmed or probable Covid-19-compatible illness. We measured hydroxychloroquine whole blood concentrations. Results: We enrolled 1483 healthcare workers, of which 79% reported performing aerosol-generating procedures. The incidence of Covid-19 (laboratory-confirmed or symptomatic compatible illness) was 0.27 events per person-year with once-weekly and 0.28 events per person-year with twice-weekly hydroxychloroquine compared with 0.38 events per person-year with placebo. For once weekly hydroxychloroquine prophylaxis, the hazard ratio was 0.72 (95%CI 0.44 to 1.16; P=0.18) and for twice weekly was 0.74 (95%CI 0.46 to 1.19; P=0.22) as compared with placebo. Median hydroxychloroquine concentrations in whole blood were 98 ng/mL (IQR, 82-120) with once-weekly and 200 ng/mL (IQR, 159-258) with twice-weekly dosing. Hydroxychloroquine concentrations did not differ between participants who developed Covid-19 (154 ng/mL) versus participants without Covid-19 (133 ng/mL; P=0.08). Conclusions: Pre-exposure prophylaxis with hydroxychloroquine once or twice weekly did not significantly reduce laboratory-confirmed Covid-19 or Covid-19-compatible illness among healthcare workers.", - "rel_num_authors": 22, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.17.20196436", + "rel_abs": "Many western countries used shielding (extended self-isolation) of people presumed to be at high-risk from COVID-19 to protect them and reduce healthcare demand. To investigate the effectiveness of this strategy, we linked family practitioner, prescribing, laboratory, hospital and death records and compared COVID-19 outcomes among shielded and non-shielded individuals in the West of Scotland. Of the 1.3 million population, 27,747 (2.03%) were advised to shield, and 353,085 (26.85%) were classified a priori as moderate risk. COVID-19 testing was more common in the shielded (7.01%) and moderate risk (2.03%) groups, than low risk (0.73%). Referent to low-risk, the shielded group had higher confirmed infections (RR 8.45, 95% 7.44-9.59), case-fatality (RR 5.62, 95% CI 4.47-7.07) and population mortality (RR 57.56, 95% 44.06-75.19). The moderate-risk had intermediate confirmed infections (RR 4.11, 95% CI 3.82-4.42) and population mortality (RR 25.41, 95% CI 20.36-31.71) but, due to their higher prevalence, made the largest contribution to deaths (PAF 75.30%). Age [≥]70 years accounted for 49.55% of deaths. In conclusion, shielding has not been effective at preventing deaths in individuals at high risk. Also, to be effective as a population strategy, shielding criteria would need to be widely expanded to include other criteria, such as the elderly.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Radha Rajasingham", - "author_inst": "University of Minnesota" - }, - { - "author_name": "Ananta S Bangdiwala", - "author_inst": "University of Minnesota" - }, - { - "author_name": "Melanie R Nicol", - "author_inst": "University of Minnesota" - }, - { - "author_name": "Caleb P Skipper", - "author_inst": "University of Minnesota" - }, - { - "author_name": "Katelyn A Pastick", - "author_inst": "University of Minnesota" - }, - { - "author_name": "Margaret L Axelrod", - "author_inst": "Vanderbilt University Medical Center" - }, - { - "author_name": "Matthew F Pullen", - "author_inst": "University of Minnesota" - }, - { - "author_name": "Alanna A Nascene", - "author_inst": "University of Minnesota" - }, - { - "author_name": "Darlisha A Williams", - "author_inst": "University of Minnesota" - }, - { - "author_name": "Nicole W Engen", - "author_inst": "University of Minnesota" - }, - { - "author_name": "Elizabeth C Okafor", - "author_inst": "University of Minnesota" - }, - { - "author_name": "Brian I Rini", - "author_inst": "Vanderbilt University Medical Center" - }, - { - "author_name": "Ingrid A Mayer", - "author_inst": "Vanderbilt University Medical Center" - }, - { - "author_name": "Emily G McDonald", - "author_inst": "McGill University" - }, - { - "author_name": "Todd C Lee", - "author_inst": "McGill University" + "author_name": "Bhautesh D Jani", + "author_inst": "University of Glasgow" }, { - "author_name": "Peter Li", - "author_inst": "Oregon Health & Science University" + "author_name": "Frederick K Ho", + "author_inst": "University of Glasgow" }, { - "author_name": "Lauren J MacKenzie", - "author_inst": "University of Manitoba" + "author_name": "David J Lowe", + "author_inst": "NHS Greater Glasgow and Clyde" }, { - "author_name": "Justin M Balko", - "author_inst": "Vanderbilt University Medical Center" + "author_name": "Jamie P Traynor", + "author_inst": "NHS Greater Glasgow and Clyde" }, { - "author_name": "Stephen J Dunlop", - "author_inst": "Hennepin Healthcare" + "author_name": "Sean MacBride-Stewart", + "author_inst": "NHS Greater Glasgow and Clyde" }, { - "author_name": "Katherine H Hullsiek", - "author_inst": "University of Minnesota" + "author_name": "Patrick B Mark", + "author_inst": "University of Glasgow" }, { - "author_name": "David R Boulware", - "author_inst": "University of Minnesota" + "author_name": "Frances S Mair", + "author_inst": "University of Glasgow" }, { - "author_name": "SARAH M LOFGREN", - "author_inst": "UNIVERSITY OF MINNESOTA" + "author_name": "Jill P Pell", + "author_inst": "University of Glasgow" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "public and global health" }, { "rel_doi": "10.1101/2020.09.17.20196444", @@ -1164293,123 +1165053,67 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.09.15.20188896", - "rel_title": "Pre-existing T cell memory as a risk factor for severe 1 COVID-19 in the elderly", + "rel_doi": "10.1101/2020.09.14.20186494", + "rel_title": "Efficacy of commercial mouth-rinses on SARS-CoV-2 viral load in saliva: Randomized Control Trial in Singapore", "rel_date": "2020-09-18", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.15.20188896", - "rel_abs": "Coronavirus disease 2019 (COVID-19) displays high clinical variability but the parameters that determine disease severity are still unclear. Pre-existing T cell memory has been hypothesized as a protective mechanism but conclusive evidence is lacking. Here we demonstrate that all unexposed individuals harbor SARS-CoV-2-specific memory T cells with marginal cross-reactivity to common cold corona and other unrelated viruses. They display low functional avidity and broad protein target specificities and their frequencies correlate with the overall size of the CD4+ memory compartment reflecting the \"immunological age\" of an individual. COVID-19 patients have strongly increased SARS-CoV-2-specific inflammatory T cell responses that are correlated with severity. Strikingly however, patients with severe COVID-19 displayed lower TCR functional avidity and less clonal expansion. Our data suggest that a low avidity pre-existing T cell memory negatively impacts on the T cell response quality against neoantigens such as SARS-CoV-2, which may predispose to develop inappropriate immune reactions especially in the elderly. We propose the immunological age as an independent risk factor to develop severe COVID-19.\n\nKey points- Pre-existing SARS-CoV-2-reactive memory T cells are present in all humans, but have low functional avidity and broad target specificities\n- Pre-existing memory T cells show only marginal cross-reactivity to common cold corona viruses\n- Frequencies of pre-existing memory T cells increase with the size of the CD4+ memory compartment reflecting the \"immunological age\" of the individual\n- Low-avidity and polyclonal, but strongly enhanced SARS-CoV-2 specific T cell responses develop in severe COVID-19, suggesting their origin from pre-existing memory\n- The immunological age may represent a risk factor to develop severe COVID-19", - "rel_num_authors": 26, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.14.20186494", + "rel_abs": "The presence of high SARS-coronavirus 2 (SARS-CoV-2) titres in saliva may result in transmission of the virus and increase the risk of COVID-19 infection. This is particularly important as significant amounts of aerosols are generated during dental procedures, posing risk to dental care personnel and patients. Thus, reducing the titres of SARS-CoV-2 in the saliva of infected patients could be one of the key approaches to reduce the risk of COVID-19 transmission during dental procedures. In this randomised control trial, the efficacy of three commercial mouth-rinse viz. povidone-iodine (PI), chlorhexidine gluconate (CHX) and cetylpyridinium chloride (CPC), in reducing the salivary SARS-CoV-2 viral load in COVID-19 positive patients were compared with water. A total of 36 COVID-19 positive patients were recruited, of which 16 patients were randomly assigned to four groups-- PI group (n=4), CHX group (n=6), CPC group (n=4) and water as control group (n=2). Saliva samples were collected from all patients at baseline and at 5 min, 3 h and 6 h post-application of mouth-rinses/water. The samples were subjected to SARS-CoV-2 RT-PCR analysis. The fold change of Ct values were significantly increased in CPC group at 5 minutes and 6 h time points (p<0.05), while it showed significant increase at 6 h time point for PI group (p<0.01). Considering Ct values as an indirect method of arbitrarily quantifying the viral load, it can be postulated that CPC mouth-rinse can decrease the salivary SARS-CoV-2 levels within 5 minutes of use, compared to water rinsing. The effect of decreasing salivary load with CPC and PI mouth-rinsing was observed to be sustained at 6 h time point. Within the limitation of the current study, it can be concluded that use of CPC and PI formulated commercial mouth-rinses, with its sustained effect on reducing salivary SARS-CoV-2 level, may be useful as a pre-procedural rinse to help reduce the transmission of COVID-19.", + "rel_num_authors": 12, "rel_authors": [ { - "author_name": "Petra Bacher", - "author_inst": "Institute of Immunology, Christian-Albrechts-University of Kiel & UKSH Schleswig-Holstein, Kiel, Germany" - }, - { - "author_name": "Elisa Rosati", - "author_inst": "Institute of Clinical Molecular Biology, Christian-Albrechts-University of Kiel, Kiel, Germany" - }, - { - "author_name": "Daniela Esser", - "author_inst": "Neuroimmunology, Institute of Clinical Chemistry, University Hospital Schleswig-Holstein, Kiel, Germany" - }, - { - "author_name": "Gabriela Rios Martini", - "author_inst": "Institute of Clinical Molecular Biology, Christian-Albrechts-University of Kiel, Kiel, Germany" - }, - { - "author_name": "Carina Saggau", - "author_inst": "Institute of Immunology, Christian-Albrechts-University of Kiel & UKSH Schleswig-Holstein, 11 Kiel, Germany" - }, - { - "author_name": "Esther Schiminsky", - "author_inst": "Institute of Immunology, Christian-Albrechts-University of Kiel & UKSH Schleswig-Holstein, Kiel, Germany" - }, - { - "author_name": "Justina Dargvainiene", - "author_inst": "Neuroimmunology, Institute of Clinical Chemistry, University Hospital Schleswig-Holstein, Kiel, Germany" - }, - { - "author_name": "Ina Schr\u00f6der", - "author_inst": "Neuroimmunology, Institute of Clinical Chemistry, University Hospital Schleswig-Holstein, Kiel, Germany" - }, - { - "author_name": "Imke Wieters", - "author_inst": "Department of Internal Medicine, Infectious Diseases, University Hospital Frankfurt & Goethe University Frankfurt, Frankfurt am Main, Germany" - }, - { - "author_name": "Fabian Eberhardt", - "author_inst": "Department of Internal Medicine, Infectious Diseases, University Hospital Frankfurt & Goethe University Frankfurt, Frankfurt am Main, Germany" - }, - { - "author_name": "Holger Neb", - "author_inst": "Department of Anesthesiology, Intensive Care Medicine and Pain Therapy, University Hospital Frankfurt, Frankfurt am Main, Germany." - }, - { - "author_name": "Yascha Khodamoradi", - "author_inst": "Department of Internal Medicine, Infectious Diseases, University Hospital Frankfurt & Goethe University Frankfurt, Frankfurt am Main, Germany" - }, - { - "author_name": "Michael Sonntagbauer", - "author_inst": "Department of Anesthesiology, Intensive Care Medicine and Pain Therapy, University Hospital Frankfurt, Frankfurt am Main, Germany." + "author_name": "Chaminda Jayampath Seneviratne", + "author_inst": "National Dental Research Institute Singapore (NDRIS), National Dental Centre Singapore, Oral Health ACP, Duke NUS Medical School" }, { - "author_name": "Maria JGT Vehreschild", - "author_inst": "Department of Internal Medicine, Infectious Diseases, University Hospital Frankfurt & Goethe University Frankfurt, Frankfurt am Main, Germany" + "author_name": "Preethi Balan", + "author_inst": "Singapore Oral Microbiomics Initiative, National Dental Research Institute Singapore (NDRIS), National Dental Centre Singapore, Oral Health ACP, Duke NUS Medica" }, { - "author_name": "Claudio Conrad", - "author_inst": "Department of Internal Medicine, Hospital of Preetz, Preetz, Germany" + "author_name": "Karrie Ko Kwan Ki", + "author_inst": "Department of Microbiology, Singapore General Hospital, Singapore" }, { - "author_name": "Florian Tran", - "author_inst": "Institute of Clinical Molecular Biology, Christian-Albrechts-University of Kiel, Kiel, Germany." + "author_name": "Nadeeka S. Udawatte", + "author_inst": "Singapore Oral Microbiomics Initiative, National Dental Research Institute Singapore (NDRIS), National Dental Centre Singapore" }, { - "author_name": "Philip Rosenstiel", - "author_inst": "Institute of Clinical Molecular Biology, Christian-Albrechts-University of Kiel, Kiel, Germany." + "author_name": "Deborah Lai", + "author_inst": "Department of Microbiology, Singapore General Hospital, Singapore" }, { - "author_name": "Robert Markewitz", - "author_inst": "Institute of Clinical Molecular Biology, Christian-Albrechts-University of Kiel, Kiel, Germany." - }, - { - "author_name": "Klaus-Peter Wandinger", - "author_inst": "Institute of Clinical Molecular Biology, Christian-Albrechts-University of Kiel, Kiel, Germany." - }, - { - "author_name": "Jan Rybniker", - "author_inst": "University of Cologne, Medical Faculty and University Hospital Cologne, Department I of Internal Medicine, 50937 Cologne, Germany" + "author_name": "Dorothy Ng Hui Lin", + "author_inst": "Department of Infectious Diseases, Singapore General Hospital, Singapore" }, { - "author_name": "Matthias Kochanek", - "author_inst": "University of Cologne, Medical Faculty and University Hospital Cologne, Department I of Internal Medicine, 50937 Cologne, Germany" + "author_name": "Indumathi Venkatachalam", + "author_inst": "Department of Infectious Diseases, Singapore General Hospital, Singapore" }, { - "author_name": "Frank Leypoldt", - "author_inst": "Neuroimmunology, Institute of Clinical Chemistry, University Hospital Schleswig-Holstein, Kiel, Germany" + "author_name": "Jay Lim Kheng Sit", + "author_inst": "Department of Urology, Singapore General Hospital, Singapore" }, { - "author_name": "Oliver A Cornely", - "author_inst": "University of Cologne, Medical Faculty and University Hospital Cologne, Department I of Internal Medicine, 50937 Cologne, Germany" + "author_name": "Ling Moi Lin", + "author_inst": "Department of Infection Prevention and Epidemiology, Singapore General Hospital, Singapore" }, { - "author_name": "Philipp Koehler", - "author_inst": "University of Cologne, Medical Faculty and University Hospital Cologne, Department I of Internal Medicine, 50937 Cologne, Germany" + "author_name": "Lynette Oon", + "author_inst": "Department of Microbiology, Singapore General Hospital, Singapore" }, { - "author_name": "Andre Franke", - "author_inst": "Institute of Clinical Molecular Biology, Christian-Albrechts-University of Kiel, Kiel, Germany" + "author_name": "Bee Tin Goh", + "author_inst": "Singapore Oral Microbiomics Initiative, National Dental Research Institute Singapore (NDRIS), National Dental Centre Singapore, Oral Health ACP, Duke NUS Medica" }, { - "author_name": "Alexander Scheffold", - "author_inst": "Institute of Immunology, Christian Albrechts University of Kiel, Kiel, Germany" + "author_name": "Jean Sim Xiang Ying", + "author_inst": "Department of Infectious Disease, Singapore General Hospital, Singapore" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "allergy and immunology" + "category": "dentistry and oral medicine" }, { "rel_doi": "10.1101/2020.09.15.20194795", @@ -1166231,31 +1166935,39 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.09.16.20195826", - "rel_title": "Modeling the Spread and Control of COVID-19", + "rel_doi": "10.1101/2020.09.16.20188227", + "rel_title": "Parents' and guardians' views on the acceptability of a future Covid-19 vaccine: a multi-methods study in England", "rel_date": "2020-09-18", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.16.20195826", - "rel_abs": "Data-centric models of COVID-19 have been tried, but have certain limitations. In this work, we propose an agent-based model of the epidemic in a confined space of agents representing humans. An extension to the SEIR model allows us to consider the difference between the appearance (black-box view) of the spread of disease, and the real situation (glass-box view). Our model allows for simulations of lockdowns, social distancing, personal hygiene, quarantine, and hospitalization, with further considerations of different parameters such as the extent to which hygiene and social distancing are observed in a population. Our results give qualitative indications of the effects of various policies and parameters; for instance, that lockdowns by themselves are extremely unlikely to bring an end to an epidemic and may indeed make things worse, that social distancing matters more than personal hygiene, and that the growth of infection comes down significantly for moderately high levels of social distancing and hygiene, even in the absence of herd immunity.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.16.20188227", + "rel_abs": "Background: The availability of a COVID-19 vaccine has been heralded as key to controlling the COVID-19 pandemic. COVID-19 vaccination programme success will rely on public willingness to be vaccinated. Methods: We used a multi-methods approach - involving an online cross-sectional survey and semi-structured interviews - to investigate parents' and guardians' views on the acceptability of a future COVID-19 vaccine. 1252 parents and guardians (aged 16+ years) who reported living in England with a child aged 18 months or under completed the survey. Nineteen survey respondents were interviewed. Findings: Most participants reported they would definitely accept or were unsure but leaning towards accepting a COVID-19 vaccine for themselves (Definitely 55.8%; Unsure but leaning towards yes 34.3%) and their child/children (Definitely 48.2%; Unsure but leaning towards yes 40.9%). Less than 4% of participants reported that they would definitely not accept a COVID-19 vaccine for themselves or their child/children. Participants were more likely to accept a COVID-19 vaccine for themselves than for their child/children. Participants that self-reported as Black, Asian, Chinese, Mixed or Other ethnicity were almost 3 times more likely to reject a COVID-19 vaccine for themselves and their children than White British, White Irish and White Other participants. Respondents from lower income households were also more likely to reject a COVID-19 vaccine. The main reason for vaccine acceptance was for self-protection from COVID-19. Common concerns were around COVID-19 vaccine safety and effectiveness, which were largely prompted by the newness and rapid development of the vaccine. Conclusion: To alleviate concerns, information on how COVID-19 vaccines are developed and tested, including their safety and efficacy, must be communicated clearly to the public. To prevent inequalities in uptake, it is crucial to understand and address factors that may affect COVID-19 vaccine acceptability in ethnic minority and lower-income groups who are disproportionately affected by COVID-19.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Ashutosh Trivedi", - "author_inst": "Spext Co." + "author_name": "Sadie L Bell", + "author_inst": "London School of Hygiene and Tropical Medicine" }, { - "author_name": "Nanda Kishore Sreenivas", - "author_inst": "Oracle" + "author_name": "Richard Clarke", + "author_inst": "Newcastle University London" }, { - "author_name": "Shrisha Rao", - "author_inst": "International Institute of Information Technology - Bangalore" + "author_name": "Sandra Mounier-Jack", + "author_inst": "London School of Hygiene and Tropical Medicine" + }, + { + "author_name": "Jemma L Walker", + "author_inst": "London School of Hygiene and Tropical Medicine" + }, + { + "author_name": "Pauline Paterson", + "author_inst": "London School of Hygiene and Tropical Medicine" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "public and global health" }, { "rel_doi": "10.1101/2020.09.17.20192088", @@ -1167809,25 +1168521,33 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.09.15.20195487", - "rel_title": "Identification of potential biomarkers and inhibitors for SARS-CoV-2 infection", + "rel_doi": "10.1101/2020.09.16.20196170", + "rel_title": "Environmental and climatic impact on the infection and mortality of SARS-CoV-2 in Peru", "rel_date": "2020-09-18", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.15.20195487", - "rel_abs": "The COVID-19 pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has overwhelmed many health systems globally. Here, we aim to identify biological markers and associated biological processes of COVID-19 using a bioinformatics approach to elucidate their potential pathogenesis. The gene expression profile of the GSE152418 dataset was originally produced by using the high-throughput Illumina NovaSeq 6000. Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) and Gene Ontology (GO) enrichment analyses were applied to identify functional categories and biochemical pathways. KEGG and GO results suggested that biological pathways such as \"Cancer pathways\" and \"Insulin pathways\" were mostly affected in the development of COVID-19. Moreover, we identified several genes including EP300, CREBBP, and POLR2A were involved in the virus activities in COVID-19 patients. We further predicted that some inhibitors may have the potential to block the SARS-CoV-2 infection based on the L1000FWD analysis. Therefore, our study provides further insights into the underlying pathogenesis of COVID-19.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.16.20196170", + "rel_abs": "The role of the environment and climate in the transmission and case-fatality rates of SARS-CoV-2 is still being investigated. Elevation and air quality are believed to be significant factors in the current development of the pandemic, but the influence of additional environmental factors remain unclear. In this study, we explored the relationship between the cumulative number of infections and mortality cases with climate (temperature, precipitation, solar radiation, water vapor pressure, wind), environmental data (elevation, NDVI, PM2.5 and NO2 concentration), and population density in Peru. Using the data from confirmed cases of infection from 1287 districts and confirmed cases of mortality in 479 districts, we used Spearman's correlations to assess the correlation between environmental and climatic factors with cumulative infection cases, cumulative mortality and case-fatality rate. We also explored district cases by the ecozones of coast, sierra, high montane forest and lowland rainforest. Multiple linear regression models indicate elevation, mean solar radiation, air quality, population density and green cover are influential factors in the distribution of infection and mortality of SARS-CoV-2 in Peru. The case-fatality rate was weakly associated with elevation. Our results also strongly suggest that exposure to poor air quality is a significant factor in the mortality of individuals with SARS-CoV-2 below the age of 30. We conclude that environmental and climatic factors do play a significant role in the transmission and case-fatality rates in Peru, however further study is required to see if these relationships are maintained over time.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Hanming Gu", - "author_inst": "School of Electronic, Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai, China; SHU-UTS SILC Business School, Shanghai University," + "author_name": "Victor J. Samillan", + "author_inst": "Universidad Le Cordon Bleu" }, { - "author_name": "Gongsheng Yuan", - "author_inst": "Department of Physiology and Pathophysiology, School of Basic Medical Sciences, Fudan University, Shanghai, China" + "author_name": "Diana Flores-Leon", + "author_inst": "Instituto Nacional de Salud.Lima,Peru" + }, + { + "author_name": "Eduardo Rojas", + "author_inst": "School of Geography and History, University of Barcelona, Barcelona, Spain" + }, + { + "author_name": "Brian R. Zutta", + "author_inst": "Green Blue Solutions, Lima Peru" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1169771,33 +1170491,153 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.09.17.20196352", - "rel_title": "The epidemiological characteristics of COVID-19 in Libya during the ongoing-armed conflict.", + "rel_doi": "10.1101/2020.09.18.20194175", + "rel_title": "Metabolic stress and disease-stage specific basigin expression of peripheral blood immune cell subsets in COVID-19 patients", "rel_date": "2020-09-18", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.17.20196352", - "rel_abs": "Abstract Introduction: COVID-19 can have even more dire consequences in countries with ongoing armed conflict. Libya, the second largest African country, has been involved in a major conflict since 2011. This study analyzed the epidemiological situation of the COVID-19 pandemic in Libya, examined the impact of the armed conflict in Libya on the spread of the pandemic, and proposes strategies for dealing with the pandemic during this conflict. Methods: We collected the available information on all COVID-19 cases in the different regions of Libya, covering the period from March 25 to May 25, 2020. The cumulative number of cases and the daily new cases are presented in a way to illustrate the patterns and trends of COVID-19 and the effect of the ongoing armed conflict was assessed regionally. Results: A total of 698 cases of COVID-19 were reported in Libya during a period of three months. The number of cases varied from one region to another and was affected by the fighting. The largest number of cases was reported in the southern part of the country, which has been severely affected by the conflict in comparison to the eastern and western parts of the country. Conclusion: This study describes the epidemiological pattern of COVID-19 in Libya and how it has been affected by the ongoing armed conflict. This conflict seems to have hindered access to populations and thereby masked the true dimensions of the pandemic. Hence, efforts should be combined to combat these consequences.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.18.20194175", + "rel_abs": "Coronavirus disease 2019 (COVID-19) is driven by dysregulated immune responses yet the role of immunometabolism in COVID-19 pathogenesis remains unclear. By investigating 47 patients with confirmed SARS-CoV-2 infection and 16 uninfected controls, we found an immunometabolic dysregulation specific for patients with progressed disease that was reversible in the recovery phase. Specifically, T cells and monocytes exhibited increased mitochondrial mass, accumulated intracellular ROS and these changes were accompanied by disrupted mitochondrial architecture. Basigin (CD147), but not established markers of T cell activation, was up-regulated on T cells from progressed COVID-19 patients and correlated with ROS accumulation, reflected in the transcriptome. During recovery, basigin and ROS decreased to match the uninfected controls. In vitro analyses confirmed the correlation and showed a down-regulation of ROS by dexamethasone treatment. Our findings provide evidence of a basigin-related and reversible immunometabolic dysregulation in COVID-19.", + "rel_num_authors": 34, "rel_authors": [ { - "author_name": "Mohamed A Daw Sr.", - "author_inst": "University of Tripoli, Faculty of Medicine" + "author_name": "Peter J. Siska", + "author_inst": "Department of Internal Medicine III, University Hospital Regensburg, 93053 Regensburg, Germany" + }, + { + "author_name": "Katrin Singer", + "author_inst": "Department of Internal Medicine III, University Hospital Regensburg, 93053 Regensburg, Germany" + }, + { + "author_name": "Jana Klitzke", + "author_inst": "Department of Internal Medicine III, University Hospital Regensburg, 93053 Regensburg, Germany" + }, + { + "author_name": "Nathalie Kauer", + "author_inst": "Department of Internal Medicine III, University Hospital Regensburg, 93053 Regensburg, Germany" + }, + { + "author_name": "Sonja-Maria Decking", + "author_inst": "Regensburg Center for Interventional Immunology, University of Regensburg, 93053 Regensburg, Germany" + }, + { + "author_name": "Christina Bruss", + "author_inst": "Department of Internal Medicine III, University Hospital Regensburg, 93053 Regensburg, Germany" }, { - "author_name": "Abdallah Hussean El-Bouzedi", - "author_inst": "University of Tripoli, Department of Laboratory Medicine, Faculty of Biotechnology, Tripoli University, CC 82668, Tripoli, Libya" + "author_name": "Carina Matos", + "author_inst": "Department of Internal Medicine III, University Hospital Regensburg, 93053 Regensburg, Germany" }, { - "author_name": "Mohamed Omar Ahmed", - "author_inst": "Department of Microbiology & Parasitology, Faculty of Veterinary Medicine, University of Tripoli, CC 82668 Libya." + "author_name": "Kristina Kolodova", + "author_inst": "Department of Internal Medicine III, University Hospital Regensburg, 93053 Regensburg, Germany" }, { - "author_name": "Ali Ali Alejenef", - "author_inst": "Department of Medicine Faculty of Medicine, Zentan , University of Aljabel Alkarbi, Libya" + "author_name": "Alic Peuker", + "author_inst": "Department of Internal Medicine III, University Hospital Regensburg, 93053 Regensburg, Germany" + }, + { + "author_name": "Gabriele Schoenhammer", + "author_inst": "Department of Internal Medicine III, University Hospital Regensburg, 93053 Regensburg, Germany" + }, + { + "author_name": "Johanna Raithel", + "author_inst": "Regensburg Center for Interventional Immunology, University of Regensburg, 93053 Regensburg, Germany" + }, + { + "author_name": "Dirk Lunz", + "author_inst": "Department of Anesthesiology, University Hospital Regensburg, 93053 Regensburg, Germany" + }, + { + "author_name": "Bernhard Graf", + "author_inst": "Department of Anesthesiology, University Hospital Regensburg, 93053 Regensburg, Germany" + }, + { + "author_name": "Florian Geismann", + "author_inst": "Department of Internal Medicine II University Hospital Regensburg, 93053 Regensburg Germany" + }, + { + "author_name": "Matthias Lubnow", + "author_inst": "Department of Internal Medicine II University Hospital Regensburg, 93053 Regensburg Germany" + }, + { + "author_name": "Matthias Mack", + "author_inst": "Department of Nephrology, University Hospital Regensburg, 93053 Regensburg, Germany" + }, + { + "author_name": "Peter Hau", + "author_inst": "Wilhelm Sander-NeuroOncology Unit and Department of Neurology, University Hospital Regensburg, 93053 Regensburg, Germany" + }, + { + "author_name": "Christopher Bohr", + "author_inst": "Department of Otorhinolaryngology, University Hospital Regensburg, 93053 Regensburg" + }, + { + "author_name": "Ralph Burkhardt", + "author_inst": "Institute of Clinical Chemistry and Laboratory Medicine, University Hospital Regensburg, 93053" + }, + { + "author_name": "Andre Gessner", + "author_inst": "Institute for Clinical Microbiology and Hygiene, University Hospital Regensburg, Regensburg, Germany" + }, + { + "author_name": "Bernd Salzberger", + "author_inst": "Department for Infection Control and Infectious Diseases, University Hospital Regensburg, 93053 Regensburg, Germany" + }, + { + "author_name": "Frank Hanses", + "author_inst": "Department for Infection Control and Infectious Diseases, University Hospital Regensburg, 93053 Regensburg, Germany" + }, + { + "author_name": "Florian Hitzenbichler", + "author_inst": "Department for Infection Control and Infectious Diseases, University Hospital Regensburg, 93053 Regensburg, Germany" + }, + { + "author_name": "Daniel Heudobler", + "author_inst": "Department of Internal Medicine III, University Hospital Regensburg, 93053 Regensburg, Germany" + }, + { + "author_name": "Florian Lueke", + "author_inst": "Department of Internal Medicine III, University Hospital Regensburg, 93053 Regensburg, Germany" + }, + { + "author_name": "Tobias Pukrop", + "author_inst": "Department of Internal Medicine III, University Hospital Regensburg, 93053 Regensburg, Germany" + }, + { + "author_name": "Wolfgang Herr", + "author_inst": "Department of Internal Medicine III, University Hospital Regensburg, 93053 Regensburg, Germany" + }, + { + "author_name": "Daniel Wolff", + "author_inst": "Department of Internal Medicine III, University Hospital Regensburg, 93053 Regensburg, Germany" + }, + { + "author_name": "Hendrik Poeck", + "author_inst": "Department of Internal Medicine III, University Hospital Regensburg, 93053 Regensburg, Germany" + }, + { + "author_name": "Christoph Brochhausen", + "author_inst": "Institute of Pathology, Electron Microscopy Unit, University of Regensburg, Germany" + }, + { + "author_name": "Petra Hoffmann", + "author_inst": "Regensburg Center for Interventional Immunology, University of Regensburg, 93053 Regensburg, Germany" + }, + { + "author_name": "Michael Rehli", + "author_inst": "Department of Internal Medicine III, University Hospital Regensburg, 93053 Regensburg, Germany" + }, + { + "author_name": "Marina Kreutz", + "author_inst": "Department of Internal Medicine III, University Hospital Regensburg, 93053 Regensburg, Germany" + }, + { + "author_name": "Kathrin Renner", + "author_inst": "Department of Internal Medicine III, University Hospital Regensburg, 93053 Regensburg, Germany" } ], "version": "1", - "license": "cc0_ng", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1171645,47 +1172485,87 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.09.14.20191833", - "rel_title": "Variation across population subgroups of COVID-19 antibody testing performance", + "rel_doi": "10.1101/2020.09.16.299891", + "rel_title": "High affinity modified ACE2 receptors prevent SARS-CoV-2 infection", "rel_date": "2020-09-16", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.14.20191833", - "rel_abs": "Understanding variations in the performance of serological tests for SARS-CoV-2 across varying demographics is relevant to clinical interpretations and public policy derived from their results. Appropriate use of serological assays to detect anti-SARS-CoV-2 antibodies requires estimation of their accuracy over large populations and an understanding of the variance in performance over time and across demographic groups. In this manuscript we focus on anti-SARS-CoV-2 IgG, IgA, and IgM antibody tests approved under emergency use authorizations and determine the recall of the serological tests compared to RT-PCR tests by Logical Observation Identifiers Names and Codes (LOINCs). Variability in test performance was further examined over time and by demographics. The recall of the most common IgG assay (LOINC 94563-4) was 91.2% (95% CI: 90.5%, 91.9%). IgA (LOINC 94562-6) and IgM (94564-2) assays performed significantly worse than IgG assays with estimated recall rates of 20.6% and 27.3%, respectively. A statistically significant difference in recall (p = 0.019) was observed across sex with a higher recall in males than females, 92.1% and 90.4%, respectively. Recall also differed significantly by age group, with higher recall in those over 45 compared to those under 45, 92.9% and 88.0%, respectively (p< 0.001). While race was unavailable for the majority of the individuals, a significant difference was observed between recall in White individuals and Black individuals (p = 0.007) and White individuals and Hispanic individuals (p = 0.001). The estimates of recall were 89.3%, 95.9%, and 94.2% for White, Black, and Hispanic individuals respectively.", - "rel_num_authors": 7, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2020.09.16.299891", + "rel_abs": "The SARS-CoV-2 spike protein binds to the human angiotensin-converting enzyme 2 (ACE2) receptor via receptor binding domain (RBD) to enter into the cell and inhibiting this interaction is a main approach to inhibit SARS-CoV-2 infection. We engineered ACE2 to enhance the affinity with directed evolution in 293T cells. Three cycles of random mutation and cell sorting achieved 100-fold higher affinity to RBD than wild-type ACE2. The extracellular domain of modified ACE2 fused to the human IgG1-Fc region had stable structure and neutralized SARS-CoV-2 without the emergence of mutational escape. Therapeutic administration protected hamsters from SARS-CoV-2 infection, decreasing lung virus titers and pathology. Engineering ACE2 decoy receptors with human cell-based directed evolution is a promising approach to develop a SARS-CoV-2 neutralizing drug that has affinity comparable to monoclonal antibodies yet displaying resistance to escape mutations of virus.\n\nOne Sentence SummaryEngineered ACE2 decoy receptor has a therapeutic potential against COVID-19 without viral escape mutation.", + "rel_num_authors": 17, "rel_authors": [ { - "author_name": "Halley L Brantley", - "author_inst": "UnitedHealth Group" + "author_name": "Yusuke Higuchi", + "author_inst": "Department of Cardiovascular Medicine, Graduate School of Medical Science, Kyoto Prefectural University of Medicine" }, { - "author_name": "Richard M Yoo", - "author_inst": "Harvard Medical School" + "author_name": "Tatsuya Suzuki", + "author_inst": "Research Institute for Microbial Diseases, Osaka University" }, { - "author_name": "Glen I Jones", - "author_inst": "UnitedHealth Group" + "author_name": "Takao Arimori", + "author_inst": "Laboratory of Protein Synthesis and Expression, Institute for Protein Research, Osaka University" }, { - "author_name": "Marel A Stock", - "author_inst": "UnitedHealth Group" + "author_name": "Nariko Ikemura", + "author_inst": "Department of Cardiovascular Medicine, Graduate School of Medical Science, Kyoto Prefectural University of Medicine" }, { - "author_name": "Peter J Park", - "author_inst": "Harvard Medical School" + "author_name": "Yuhei Kirita", + "author_inst": "Department of Nephrology, Graduate School of Medical Science, Kyoto Prefectural University of Medicine," }, { - "author_name": "Natalie E Sheils", - "author_inst": "UnitedHealth Group" + "author_name": "Eriko Ohgitani", + "author_inst": "Department of Immunology, Graduate School of Medical Science, Kyoto Prefectural University of Medicine" }, { - "author_name": "Isaac S Kohane", - "author_inst": "Harvard Medical School" + "author_name": "Osam Mazda", + "author_inst": "Department of Immunology, Graduate School of Medical Science, Kyoto Prefectural University of Medicine" + }, + { + "author_name": "Daisuke Motooka", + "author_inst": "Osaka University Research Institute for Microbial Diseases" + }, + { + "author_name": "Shota Nakamura", + "author_inst": "Department of Infection Metagenomics, Research Institute for Microbial Diseases, Osaka University" + }, + { + "author_name": "Yusuke Sakai", + "author_inst": "Department of Veterinary Pathology, Yamaguchi University" + }, + { + "author_name": "Yumi Itoh", + "author_inst": "Institute for Advanced Co-Creation Studies, Research Institute for Microbial Diseases, Osaka University" + }, + { + "author_name": "Fuminori Sugihara", + "author_inst": "The Core Instrumentation Facility, Research Institute for Microbial Diseases, Osaka University" + }, + { + "author_name": "Yoshiharu Matsuura", + "author_inst": "Department of Molecular Virology, Research Institute for Microbial Diseases, Osaka University" + }, + { + "author_name": "Satoaki Matoba", + "author_inst": "Department of Cardiovascular Medicine, Graduate School of Medical Science, Kyoto Prefectural University of Medicine" + }, + { + "author_name": "Toru Okamoto", + "author_inst": "Research Institute for Microbial Diseases, Osaka University" + }, + { + "author_name": "Junichi Takagi", + "author_inst": "Laboratory of Protein Synthesis and Expression, Institute for Protein Research, Osaka University" + }, + { + "author_name": "Atsushi Hoshino", + "author_inst": "Department of Cardiovascular Medicine, Graduate School of Medical Science, Kyoto Prefectural University of Medicine" } ], "version": "1", - "license": "cc_no", - "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "license": "cc_by_nc_nd", + "type": "new results", + "category": "bioengineering" }, { "rel_doi": "10.1101/2020.09.10.20191619", @@ -1173503,33 +1174383,33 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.09.12.20193094", - "rel_title": "The Immune-Buffer COVID-19 Exit Strategy that Protects the Elderly", + "rel_doi": "10.1101/2020.09.12.20193284", + "rel_title": "Estimates of outbreak-specific SARS-CoV-2 epidemiological parameters from genomic data", "rel_date": "2020-09-14", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.12.20193094", - "rel_abs": "COVID-19 is a viral respiratory illness, caused by the SARS-CoV-2 virus with frequent symptoms of fever and shortness of breath. COVID-19 has a high mortality rate among elders. The virus has spread world-wide, leading to shut-down of many countries around the globe with the aim of stopping the spread of the disease. To date, there are uncertainties regarding the main factors in the disease spread, so sever social distancing measures and broad testing are required in order to protect the population at risk. With the increasing spread of the virus, there is growing fraction of the general population that may be immune to COVID-19, following infection. This immunised cohort can be uncovered via large-scale screening for the SARS-CoV-2 (Corona) virus and/or its antibodies. We propose that this immune cohort be deployed as a buffer between the general population and the population most at risk from the disease. Here we show that under a broad range of realistic scenarios deploying such an immunized buffer between the general population and the population at risk may lead to a dramatic reduction in the number of deaths from the disease. This provides an impetus for: screening for the SARS-CoV-2 virus and/or its antibodies on the largest scale possible, and organizing at the family, community, national and international levels to protect vulnerable populations by deploying immunized buffers between them and the general population wherever possible.", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.12.20193284", + "rel_abs": "We estimate the basic reproductive number and case counts for 15 distinct SARS-CoV-2 outbreaks, distributed across 10 countries and one cruise ship, based solely on phylodynamic analyses of genomic data. Our results indicate that, prior to significant public health interventions, the reproductive numbers for a majority (10) of these outbreaks are similar, with median posterior estimates ranging between 1.4 and 2.8. These estimates provide a view which is complementary to that provided by those based on traditional line listing data. The genomic-based view is arguably less susceptible to biases resulting from differences in testing protocols, testing intensity, and import of cases into the community of interest. In the analyses reported here, the genomic data primarily provides information regarding which samples belong to a particular outbreak. We observe that once these outbreaks are identified, the sampling dates carry the majority of the information regarding the reproductive number. Finally, we provide genome-based estimates of the cumulative case counts for each outbreak, which allow us to speculate on the amount of unreported infections within the populations housing each outbreak. These results indicate that for the majority (7) of the populations studied, the number of recorded cases is much bigger than the estimated cumulative case counts, suggesting the presence of unsequenced pathogen diversity in these populations.\n\nSignificance StatementSince the beginning of the COVID-19 outbreak in late 2019, researchers around the globe have sought to estimate the rate at which the disease spread through populations prior to public health intervention, as quantified by the parameter R0. This is often estimated based on case count data and may be biased due to the presence of import cases. To overcome this, we estimate R0 by applying Bayesian phylodynamic methods to SARS-CoV-2 genomes which have been made available by laboratories worldwide. We provide R0 and absolute infection count estimates for 15 distinct outbreaks. These estimates contribute to our understanding of the baseline transmission dynamics of the disease, which will be critical in guiding future public health responses to the pandemic.", "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Vered Rom-Kedar", - "author_inst": "Weizmann Institute of Science" + "author_name": "Timothy G Vaughan", + "author_inst": "ETH Zurich" }, { - "author_name": "Omer Yaniv", - "author_inst": "Weizmann Institute of Science" + "author_name": "J\u00e9r\u00e9mie Scir\u00e9", + "author_inst": "ETH Zurich" }, { - "author_name": "Roy Malka", - "author_inst": "Lynx MD" + "author_name": "Sarah A Nadeau", + "author_inst": "ETH Zurich" }, { - "author_name": "Ehud Shapiro", - "author_inst": "Weizmann Institute of Science" + "author_name": "Tanja Stadler", + "author_inst": "ETH Zurich" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1174989,55 +1175869,47 @@ "category": "neuroscience" }, { - "rel_doi": "10.1101/2020.09.14.296715", - "rel_title": "Self-assembling nanoparticles presenting receptor binding domain and stabilized spike as next-generation COVID-19 vaccines", + "rel_doi": "10.1101/2020.09.14.296814", + "rel_title": "Phylogenomic reveals multiple introductions and early spread of SARS-CoV-2 into Peru", "rel_date": "2020-09-14", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.09.14.296715", - "rel_abs": "Vaccination against SARS-CoV-2 provides an effective tool to combat the COIVD-19 pandemic. Here, we combined antigen optimization and nanoparticle display to develop vaccine candidates for SARS-CoV-2. We first displayed the receptor-binding domain (RBD) on three self-assembling protein nanoparticle (SApNP) platforms using the SpyTag/SpyCatcher system. We then identified heptad repeat 2 (HR2) in S2 as the cause of spike metastability, designed an HR2-deleted glycine-capped spike (S2G{Delta}HR2), and displayed S2G{Delta}HR2 on SApNPs. An antibody column specific for the RBD enabled tag-free vaccine purification. In mice, the 24-meric RBD-ferritin SApNP elicited a more potent neutralizing antibody (NAb) response than the RBD alone and the spike with two stabilizing proline mutations in S2 (S2P). S2G{Delta}HR2 elicited two-fold-higher NAb titers than S2P, while S2G{Delta}HR2 SApNPs derived from multilayered E2p and I3-01v9 60-mers elicited up to 10-fold higher NAb titers. The S2G{Delta}HR2-presenting I3-01v9 SApNP also induced critically needed T-cell immunity, thereby providing a promising vaccine candidate.\n\nONE-SENTENCE SUMMARYThe SARS-CoV-2 receptor binding domain and S2G{Delta}HR2 spike elicited potent immune responses when displayed on protein nanoparticles as vaccine candidates.", - "rel_num_authors": 9, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.09.14.296814", + "rel_abs": "Peru has become one of the countries with the highest mortality rate from the current severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic. To investigate early transmission event and genomic diversity of SARS-CoV-2 isolates circulating in Peru, we analyzed a total of 3472 SARS-CoV-2 genomes, from which 149 ones were from Peru. Phylogenomic analysis revealed multiple and independent introductions of the virus mainly from Europe and Asia. In addition, we found evidence for community-driven transmission of SARS-CoV-2 as suggested by clusters of related viruses found in patients living in different Peru regions.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Linling He", - "author_inst": "The Scripps Research Institute" - }, - { - "author_name": "Xiaohe Lin", - "author_inst": "The Scripps Research Institute" - }, - { - "author_name": "Ying Wang", - "author_inst": "Temple University" + "author_name": "Eduardo Juscamayta Lopez", + "author_inst": "Instituto Nacional de Salud" }, { - "author_name": "Ciril Abraham", - "author_inst": "Temple University" + "author_name": "David Tarazona", + "author_inst": "Instituto Nacional de Salud" }, { - "author_name": "Cindy Sou", - "author_inst": "The Scripps Research Institute" + "author_name": "Faviola Valdivia Guerrero", + "author_inst": "Instituto Nacional de Salud" }, { - "author_name": "Timothy Ngo", - "author_inst": "The Scripps Research Institute" + "author_name": "Nancy Rojas Serrano", + "author_inst": "Instituto Nacional de Salud" }, { - "author_name": "Yi Zhang", - "author_inst": "Temple University" + "author_name": "Dennis Carhuaricra", + "author_inst": "Universidad Nacional Mayor de San Marcos" }, { - "author_name": "Ian A. Wilson", - "author_inst": "The Scripps Research Institute" + "author_name": "Lenin Maturrano Hernandez", + "author_inst": "Universidad Nacional Mayor de San Marcos" }, { - "author_name": "Jiang Zhu", - "author_inst": "The Scripps Research Institute" + "author_name": "Ronnie Gavilan Chavez", + "author_inst": "Instituto Nacional de Salud" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by_nc_nd", "type": "new results", - "category": "microbiology" + "category": "genomics" }, { "rel_doi": "10.1101/2020.09.11.20192831", @@ -1176639,81 +1177511,29 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2020.09.11.294363", - "rel_title": "Ketogenesis restrains aging-induced exacerbation of COVID in a mouse model", + "rel_doi": "10.1101/2020.09.12.294413", + "rel_title": "Inferring MHC interacting SARS-CoV-2 epitopes recognized by TCRs towards designing T cell-based vaccines", "rel_date": "2020-09-12", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.09.11.294363", - "rel_abs": "Increasing age is the strongest predictor of risk of COVID-19 severity. Unregulated cytokine storm together with impaired immunometabolic response leads to highest mortality in elderly infected with SARS-CoV-2. To investigate how aging compromises defense against COVID-19, we developed a model of natural murine beta coronavirus (mCoV) infection with mouse hepatitis virus strain MHV-A59 (mCoV-A59) that recapitulated majority of clinical hallmarks of COVID-19. Aged mCoV-A59-infected mice have increased mortality and higher systemic inflammation in the heart, adipose tissue and hypothalamus, including neutrophilia and loss of {gamma}{delta} T cells in lungs. Ketogenic diet increases beta-hydroxybutyrate, expands tissue protective {gamma}{delta} T cells, deactivates the inflammasome and decreases pathogenic monocytes in lungs of infected aged mice. These data underscore the value of mCoV-A59 model to test mechanism and establishes harnessing of the ketogenic immunometabolic checkpoint as a potential treatment against COVID-19 in the elderly.\n\nHighlights - Natural MHV-A59 mouse coronavirus infection mimics COVID-19 in elderly.\n- Aged infected mice have systemic inflammation and inflammasome activation\n- Murine beta coronavirus (mCoV) infection results in loss of pulmonary {gamma}{delta} T cells.\n- Ketones protect aged mice from infection by reducing inflammation.\n\n\neTOC BlurbElderly have the greatest risk of death from COVID-19. Here, Ryu et al report an aging mouse model of coronavirus infection that recapitulates clinical hallmarks of COVID-19 seen in elderly. The increased severity of infection in aged animals involved increased inflammasome activation and loss of {gamma}{delta} T cells that was corrected by ketogenic diet.", - "rel_num_authors": 17, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.09.12.294413", + "rel_abs": "The coronavirus disease 2019 (COVID-19) is triggered by severe acute respiratory syndrome mediated by coronavirus 2 (SARS-CoV-2) infection and was declared by WHO as a major international public health concern. While worldwide efforts are being advanced towards vaccine development, the structural modeling of TCR-pMHC (T Cell Receptor-peptide-bound Major Histocompatibility Complex) regarding SARS-CoV-2 epitopes and the design of effective T cell vaccine based on these antigens are still unresolved. Here, we present both pMHC and TCR-pMHC interfaces to infer peptide epitopes of the SARS-CoV-2 proteins. Accordingly, significant TCR-pMHC templates (Z-value cutoff > 4) along with interatomic interactions within the SARS-CoV-2-derived hit peptides were clarified. Also, we applied the structural analysis of the hit peptides from different coronaviruses to highlight a feature of evolution in SARS-CoV-2, SARS-CoV, bat-CoV, and MERS-CoV. Peptide-protein flexible docking between each of the hit peptides and their corresponding MHC molecules were performed, and a multi-hit peptides vaccine against the S and N glycoprotein of SARS-CoV-2 was designed. Filtering pipelines including antigenicity, and also physiochemical properties of designed vaccine were then evaluated by different immunoinformatics tools. Finally, vaccine-structure modeling and immune simulation of the desired vaccine were performed aiming to create robust T cell immune responses. We anticipate that our design based on the T cell antigen epitopes and the frame of the immunoinformatics analysis could serve as valuable supports for the development of COVID-19 vaccine.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Seungjin Ryu", - "author_inst": "Yale University School of Medicine" - }, - { - "author_name": "Irina Shchukina", - "author_inst": "Washington University in St. Louis" - }, - { - "author_name": "Yun-Hee Youm", - "author_inst": "Yale University School of Medicine" - }, - { - "author_name": "Hua Qing", - "author_inst": "Yale University School of Medicine" - }, - { - "author_name": "Brandon K Hilliard", - "author_inst": "Yale University School of Medicine" - }, - { - "author_name": "Tamara Dlugos", - "author_inst": "Yale University School of Medicine" - }, - { - "author_name": "Xinbo Zhang", - "author_inst": "Yale University School of Medicine" - }, - { - "author_name": "Yuki Yasumoto", - "author_inst": "Yale University School of Medicine" - }, - { - "author_name": "Carmen J. Booth", - "author_inst": "Yale University School of Medicine" - }, - { - "author_name": "Carlos Fernandez-Hernando", - "author_inst": "Yale University School of Medicine" - }, - { - "author_name": "Yajaira Suarez", - "author_inst": "Yale University School of Medicine" - }, - { - "author_name": "Kamal M Khanna", - "author_inst": "New York University School of Medicine" - }, - { - "author_name": "Tamas Horvath", - "author_inst": "Yale University School of Medicine" - }, - { - "author_name": "Marcelo O Dietrich", - "author_inst": "Yale University School of Medicine" + "author_name": "Amir Hossein Mohseni", + "author_inst": "Shanghai Jiao Tong University" }, { - "author_name": "Maxim Artyomov", - "author_inst": "Washington University School of Medicine" + "author_name": "Sedigheh Taghinezhad-S", + "author_inst": "Shanghai Jiao Tong University" }, { - "author_name": "Andrew Wang", - "author_inst": "Yale University School of Medicine" + "author_name": "Bing Su", + "author_inst": "Shanghai Jiao Tong University" }, { - "author_name": "Vishwa Deep Dixit", - "author_inst": "Yale University School of Medicine" + "author_name": "Feng Wang", + "author_inst": "Shanghai Jiao Tong University" } ], "version": "1", @@ -1178181,29 +1179001,117 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.09.08.20190686", - "rel_title": "Mortality and risk factors among US Black, Hispanic, and White patients with COVID-19", + "rel_doi": "10.1101/2020.09.10.20186064", + "rel_title": "Mitochondrial induced T cell apoptosis and aberrant myeloid metabolic programs define distinct immune cell subsets during acute and recovered SARS-CoV-2 infection", "rel_date": "2020-09-11", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.08.20190686", - "rel_abs": "Background: Little is known about risk factors for COVID-19 outcomes, particularly across diverse racial and ethnic populations in the United States. Methods: In this prospective cohort study, we followed 3,086 COVID-19 patients hospitalized on or before April 13, 2020 within an academic health system in New York (The Mount Sinai Health System) until June 2, 2020. Multivariable logistic regression was used to evaluate demographic, clinical, and laboratory factors as independent predictors of in-hospital mortality. The analysis was stratified by self-reported race and ethnicity. Findings: A total of 3,086 COVID-19 patients were hospitalized, of whom 680 were excluded (78 due to missing race or ethnicity data, 144 were Asian, and 458 were of other unspecified race/ethnicity). Of the 2,406 patients included, 892 (37.1%) were Hispanic, 825 (34.3%) were black, and 689 (28.6%) were white. Black and Hispanic patients were younger than White patients (median age 67 and 63 vs. 73, p<0.001 for both), and they had different comorbidity profiles. Older age and baseline hypoxia were associated with increased mortality across all races. There were suggestive but non-significant interactions between Black race and diabetes (p=0.09), and obesity (p=0.10). Among inflammatory markers associated with COVID-19 mortality, there was a significant interaction between Black race and interleukin-1-beta (p=0.04), and a suggestive interactions between Hispanic ethnicity and procalcitonin (p=0.07) and interleukin-8 (p=0.09). Interpretation: In this large, racially and ethnically diverse cohort of COVID-19 patients in New York City, we identified similarities and important differences across racial and ethnic groups in risk factors for in-hospital mortality.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.10.20186064", + "rel_abs": "It remains unclear why some patients infected with SARS-CoV-2 readily resolve infection while others develop severe disease. To address this question, we employed a novel assay to interrogate immune-metabolic programs of T cells and myeloid cells in severe and recovered COVID-19 patients. Using this approach, we identified a unique population of T cells expressing high H3K27me3 and the mitochondrial membrane protein voltage-dependent anion channel (VDAC), which were expanded in acutely ill COVID-19 patients and distinct from T cells found in patients infected with hepatitis c or influenza and in recovered COVID-19. Increased VDAC was associated with gene programs linked to mitochondrial dysfunction and apoptosis. High-resolution fluorescence and electron microscopy imaging of the cells revealed dysmorphic mitochondria and release of cytochrome c into the cytoplasm, indicative of apoptosis activation. The percentage of these cells was markedly increased in elderly patients and correlated with lymphopenia. Importantly, T cell apoptosis could be inhibited in vitro by targeting the oligomerization of VDAC or blocking caspase activity. In addition to these T cell findings, we also observed a robust population of Hexokinase II+ polymorphonuclear-myeloid derived suppressor cells (PMN-MDSC), exclusively found in the acutely ill COVID-19 patients and not the other viral diseases. Finally, we revealed a unique population of monocytic MDSC (M-MDSC) expressing high levels of carnitine palmitoyltransferase 1a (CPT1a) and VDAC. The metabolic phenotype of these cells was not only highly specific to COVID-19 patients but the presence of these cells was able to distinguish severe from mild disease. Overall, the identification of these novel metabolic phenotypes not only provides insight into the dysfunctional immune response in acutely ill COVID-19 patients but also provide a means to predict and track disease severity as well as an opportunity to design and evaluate novel metabolic therapeutic regimens.\n\nGRAPHICAL ABSTRACT\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=75 SRC=\"FIGDIR/small/20186064v2_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (31K):\norg.highwire.dtl.DTLVardef@89f509org.highwire.dtl.DTLVardef@1362640org.highwire.dtl.DTLVardef@940aeorg.highwire.dtl.DTLVardef@175792b_HPS_FORMAT_FIGEXP M_FIG C_FIG", + "rel_num_authors": 26, "rel_authors": [ { - "author_name": "Tomi Jun", - "author_inst": "Icahn School of Medicine at Mount Sinai" + "author_name": "Elizabeth Thompson", + "author_inst": "Johns Hopkins University" }, { - "author_name": "Sharon Nirenberg", - "author_inst": "Icahn School of Medicine at Mount Sinai" + "author_name": "Katherine Cascino", + "author_inst": "Johns Hopkins University" }, { - "author_name": "Patricia Kovatch", - "author_inst": "Icahn School of Medicine at Mount Sinai" + "author_name": "Alvaro Ordonez", + "author_inst": "Johns Hopkins University" }, { - "author_name": "Kuan-lin Huang", - "author_inst": "Icahn School of Medicine at Mount Sinai" + "author_name": "Weiqiang Zhou", + "author_inst": "Johns Hopkins University" + }, + { + "author_name": "Ajay Vaghasia", + "author_inst": "Johns Hopkins University" + }, + { + "author_name": "Anne Hamacher-Brady", + "author_inst": "Johns Hopkins University" + }, + { + "author_name": "Nathan Brady", + "author_inst": "Johns Hopkins University" + }, + { + "author_name": "Im-Hong Sun", + "author_inst": "Johns Hopkins University" + }, + { + "author_name": "Rulin Wang", + "author_inst": "Johns Hopkins University" + }, + { + "author_name": "Avi Rosenberg", + "author_inst": "Johns Hopkins University" + }, + { + "author_name": "Michael Delanoy", + "author_inst": "Johns Hopkins University" + }, + { + "author_name": "Richard Eric Rothman", + "author_inst": "Johns Hopkins Hospital" + }, + { + "author_name": "Katherine Fenstermacher", + "author_inst": "Johns Hopkins Hospital" + }, + { + "author_name": "Lauren Sauer", + "author_inst": "Johns Hopkins Hospital" + }, + { + "author_name": "Kathryn Shaw-Saliba", + "author_inst": "Johns Hopkins Hospital" + }, + { + "author_name": "Evan M Bloch", + "author_inst": "Johns Hopkins Medicine" + }, + { + "author_name": "Andrew Redd", + "author_inst": "Johns Hopkins University School of Medicine" + }, + { + "author_name": "Aaron AR Tobian", + "author_inst": "Johns Hopkins Hospital" + }, + { + "author_name": "Maureen Horton", + "author_inst": "Johns Hopkins University" + }, + { + "author_name": "Kellie Smith", + "author_inst": "Johns Hopkins University" + }, + { + "author_name": "Andrew Pekosz", + "author_inst": "Johns Hopkins Bloomberg School of Public Health" + }, + { + "author_name": "Franco D'Alessio", + "author_inst": "Johns Hopkins University" + }, + { + "author_name": "Srinivasan Yegnasubramanian", + "author_inst": "Johns Hopkins University" + }, + { + "author_name": "Hongkai Ji", + "author_inst": "Johns Hopkins University" + }, + { + "author_name": "Andrea L Cox", + "author_inst": "Johns Hopkins University" + }, + { + "author_name": "Jonathan D Powell", + "author_inst": "Johns Hopkins University" } ], "version": "1", @@ -1179867,45 +1180775,41 @@ "category": "bioinformatics" }, { - "rel_doi": "10.1101/2020.09.08.20190629", - "rel_title": "Model-informed COVID-19 vaccine prioritization strategies by age and serostatus", + "rel_doi": "10.1101/2020.09.09.20190983", + "rel_title": "Exploring Patterns and Trends in COVID-19 Exports from China, Italy, and Iran", "rel_date": "2020-09-10", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.08.20190629", - "rel_abs": "When a vaccine for COVID-19 becomes available, limited initial supply will raise the question of how to prioritize the available doses and thus underscores the need for transparent, evidence-based strategies that relate knowledge of, and uncertainty in, disease transmission, risk, vaccine efficacy, and existing population immunity. Here, we employ a model-informed approach to vaccine prioritization that evaluates the impact of prioritization strategies on cumulative incidence and mortality and accounts for population factors such as age, contact structure, and seroprevalence, and vaccine factors including imperfect and age-varying efficacy. This framework can be used to evaluate and compare existing strategies, and it can also be used to derive an optimal prioritization strategy to minimize mortality or incidence. We find that a transmission-blocking vaccine should be prioritized to adults ages 20-49y to minimize cumulative incidence and to adults over 60y to minimize mortality. Direct vaccination of adults over 60y minimizes mortality for vaccines that do not block transmission. We also estimate the potential benefit of using individual-level serological tests to redirect doses to only seronegative individuals, improving the marginal impact of each dose. We argue that this serology-informed vaccination approach may improve the efficiency of vaccination efforts while partially addressing existing inequities in COVID-19 burden and impact.", - "rel_num_authors": 7, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.09.20190983", + "rel_abs": "This paper investigates COVID-19 exported cases by country and the time it takes between entry until case confirmation for the exported cases using publicly available data. We report that the average days from entry to confirmation is 7.7, 5.0 and 4.7 days for travelers from China, Italy, and Iran respectively. Approximately, one-third of all exported cases were confirmed within 3 days of entry suggesting these travelers were mildly symptomatic or symptomatic in arrival. We also found that earlier exported cases from each country had a longer time between entry to confirmation by an average of 3 days compared to later exports. Based upon our data, reported exported cases from South Korea were far fewer in comparison to those from China, Italy and Iran. Therefore, we suggest that careful monitoring of likely symptomatic travelers and better public awareness may lead to faster confirmation as well as reduced transmission of COVID-19 pandemic.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Kate M Bubar", - "author_inst": "University of Colorado Boulder" - }, - { - "author_name": "Kyle Reinholt", - "author_inst": "University of Colorado Boulder" + "author_name": "Ahmed Tamer Soliman", + "author_inst": "Case-Western Reserve University School of Medicine, Department of Pediatrics" }, { - "author_name": "Stephen M Kissler", - "author_inst": "Harvard T.H. Chan School of Public Health" + "author_name": "Michael L McHenry", + "author_inst": "Case Western Reserve University School of Medicine, Department of Population and Quantitative Health Sciences" }, { - "author_name": "Marc Lipsitch", - "author_inst": "Harvard T.H. Chan School of Public Health" + "author_name": "George Luo", + "author_inst": "Case-Western Reserve University School of Medicine, Case Comprehensive Cancer Center" }, { - "author_name": "Sarah Cobey", - "author_inst": "University of Chicago" + "author_name": "Brian Dailey", + "author_inst": "Case-Western Reserve University School of Medicine, Case Comprehensive Cancer Center" }, { - "author_name": "Yonatan Grad", - "author_inst": "Harvard T. H. Chan School of Public Health" + "author_name": "Toby Chen", + "author_inst": "Duke University, Trinity College of Arts and Sciences" }, { - "author_name": "Daniel B Larremore", - "author_inst": "University of Colorado Boulder" + "author_name": "John J Letterio", + "author_inst": "Case-Western Reserve University School of Medicine, Case Comprehensive Cancer Center" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1181337,27 +1182241,79 @@ "category": "bioinformatics" }, { - "rel_doi": "10.1101/2020.09.10.290841", - "rel_title": "CD8 T cell epitope generation toward the continually mutating SARS-CoV-2 spike protein in genetically diverse human population: Implications for disease control and prevention", - "rel_date": "2020-09-10", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.09.10.290841", - "rel_abs": "The ongoing pandemic of SARS-CoV-2 has brought tremendous crisis on global health care systems and industrial operations that dramatically affect the economic and social life of numerous individuals worldwide. Understanding anti-SARS-CoV-2 immune responses in population with different genetic backgrounds and tracking the viral evolution are crucial for successful vaccine design. In this study, we reported the generation of CD8 T cell epitopes by a total of 80 alleles of three major class I HLAs using NetMHC 4.0 algorithm for the spike protein of SARS-CoV-2, a key antigen that is targeted by both B cells and T cells. We found diverse capacities of S protein specific epitope presentation by different HLA alleles with very limited number of predicted epitopes for HLA-B*2705, HLA-B*4402 and HLA-B*4403 and as high as 132 epitopes for HLA-A*6601. Our analysis of 1000 S protein sequences from field isolates collected globally over the past few months identified three recurrent point mutations including L5F, D614G and G1124V. Differential effects of these mutations on CD8 T cell epitope generation by corresponding HLA alleles were observed. Finally, our multiple alignment analysis indicated the absence of seasonal CoV induced cross-reactive CD8 T cells to drive these mutations. Our findings provided molecular explanations for the observation that individuals with certain HLA alleles such as B*44 are more prone to SARS-CoV-2 infection. Studying anti-S protein specific CD8 T cell immunity in diverse genetic background is critical for better control and prevention of the SARS-CoV-2 pandemic.", - "rel_num_authors": 2, + "rel_doi": "10.1101/2020.09.02.20187096", + "rel_title": "On the Role of Artificial Intelligence in Medical Imaging of COVID-19", + "rel_date": "2020-09-09", + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.02.20187096", + "rel_abs": "The global COVID-19 pandemic has accelerated the development of numerous digital technologies in medicine from telemedicine to remote monitoring. Concurrently, the pandemic has resulted in huge pressures on healthcare systems. Medical imaging (MI) from chest radiographs to computed tomography and ultrasound of the thorax have played an important role in the diagnosis and management of the coronavirus infection.\n\nWe conducted the, to date, largest systematic review of the literature addressing the utility of Artificial Intelligence (AI) in MI for COVID-19 management. Through keyword matching on PubMed and preprint servers, including arXiv, bioRxiv and medRxiv, 463 papers were selected for a meta-analysis, with manual reviews to assess the clinical relevance of AI solutions. Further, we evaluated the maturity of the papers based on five criteria assessing the state of the field: peer-review, patient dataset size and origin, algorithmic complexity, experimental rigor and clinical deployment.\n\nIn 2020, we identified 4977 papers on MI in COVID-19, of which 872 mentioned the term AI. 2039 papers of the 4977 were specific to imaging modalities with a majority of 83.8% focusing on CT, while 10% involved CXR and 6.2% used LUS. Meanwhile, the AI literature predominantly analyzed CXR data (49.7%), with 38.7% using CT and 1.5% LUS. Only a small portion of the papers were judged as mature (2.7 %). 71.9% of AI papers centered on disease detection.\n\nThis review evidences a disparity between clinicians and the AI community, both in the focus on imaging modalities and performed tasks. Therefore, in order to develop clinically relevant AI solutions, rigorously validated on large-scale patient data, we foresee a need for improved collaboration between the two communities ensuring optimal outcomes and allocation of resources. AI may aid clinicians and radiologists by providing better tools for localization and quantification of disease features and changes thereof, and, with integration of clinical data, may provide better diagnostic performance and prognostic value.", + "rel_num_authors": 15, "rel_authors": [ { - "author_name": "Hailong Guo", - "author_inst": "none" + "author_name": "Jannis Born", + "author_inst": "IBM Research Europe" }, { - "author_name": "Elisa Guo", - "author_inst": "none" + "author_name": "David Beymer", + "author_inst": "IBM Research Almaden" + }, + { + "author_name": "Deepta Rajan", + "author_inst": "IBM Research Almaden" + }, + { + "author_name": "Adam Coy", + "author_inst": "IBM Research Almaden" + }, + { + "author_name": "Vandana V Mukherjee", + "author_inst": "IBM Research Almaden" + }, + { + "author_name": "Matteo Manica", + "author_inst": "IBM Research Europe" + }, + { + "author_name": "Prasanth Prasanna", + "author_inst": "Department of Radiology and Imaging Sciences, University of Utah Health Sciences Center, Salt Lake City, Utah" + }, + { + "author_name": "Deddeh Ballah", + "author_inst": "Department of Radiology, Seton Medical Center, Daly City, CA, USA" + }, + { + "author_name": "Michal Guindy", + "author_inst": "Ben-Gurion University Medical School, Israel" + }, + { + "author_name": "Dorith Shaham", + "author_inst": "Hadassah-Hebrew University Medical Center, Jerusalem, Israel" + }, + { + "author_name": "Pallav L Shah", + "author_inst": "NIHR Respiratory Biomedical Research Unit, Imperial College, London, UK" + }, + { + "author_name": "Emmanouil Karteris", + "author_inst": "College of Health, Medicine and Life Sciences, Brunel University London, UK" + }, + { + "author_name": "Jan Lukas Robertus", + "author_inst": "National Heart & Lung Institute, Imperial College London, UK" + }, + { + "author_name": "Maria Gabrani", + "author_inst": "IBM Research Europe" + }, + { + "author_name": "Michal Rosen-Zvi", + "author_inst": "IBM Research Haifa" } ], "version": "1", - "license": "cc_by", - "type": "new results", - "category": "immunology" + "license": "cc_by_nc_nd", + "type": "PUBLISHAHEADOFPRINT", + "category": "health informatics" }, { "rel_doi": "10.1101/2020.09.07.20189688", @@ -1183007,29 +1183963,97 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.09.07.20189779", - "rel_title": "Influenza may facilitate the spread of SARS-CoV-2", + "rel_doi": "10.1101/2020.09.08.20190504", + "rel_title": "First report on the Latvian SARS-CoV-2 isolate genetic diversity", "rel_date": "2020-09-09", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.07.20189779", - "rel_abs": "As in past pandemics, co-circulating pathogens may play a role in the epidemiology of coronavirus disease 2019 (COVID-19), caused by the novel severe acute respiratory syndrome coronavirus 2 (SARSCoV-2). Here we hypothesized that influenza interacted with SARS-CoV-2 during the early 2020 epidemic of COVID-19 in Europe. We developed a population-based model of SARS-CoV-2 transmission, combined with mortality incidence data in four European countries, to test a range of assumptions about the impact of influenza. We found consistent evidence for a 2-2.5-fold population-level increase in SARSCoV-2 transmission associated with influenza during the period of co-circulation. These results suggest the need to increase vaccination against influenza, not only to reduce the burden due to influenza viruses, but also to counteract their facilitatory impact on SARS-CoV-2.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.08.20190504", + "rel_abs": "Remaining a major healthcare concern with nearly 29 million confirmed cases worldwide at the time of writing, novel severe acute respiratory syndrome coronavirus - 2 (SARS-CoV-2) has caused more than 920 thousand deaths since its outbreak in China, December 2019. First case of a person testing positive for SARS-CoV-2 infection within the territory of the Republic of Latvia was registered on 2nd of March 2020, nine days prior to the pandemic declaration by WHO. Since then, more than 277 000 tests were carried out confirming a total of 1464 cases of COVID-19 in the country as of 12th of September 2020. Rapidly reacting to the spread of the infection, an ongoing sequencing campaign was started mid-March in collaboration with the local testing laboratories, with an ultimate goal in sequencing as much local viral isolates as possible, resulting in first full-length SARS-CoV-2 isolate genome sequences from the Baltics region being made publicly available in early April. With 133 viral isolates representing [~]9.1% of the total COVID-19 cases in the country being completely sequenced as of today, here we provide a first report on the genetic diversity of Latvian SARS-CoV-2 isolates.", + "rel_num_authors": 21, "rel_authors": [ { - "author_name": "Matthieu Domenech de Celles", - "author_inst": "Max Planck Institute for Infection Biology" + "author_name": "Nikita Zrelovs", + "author_inst": "Latvian Biomedical Research and Study Centre, Ratsupites 1, Riga, Latvia, LV-1067" }, { - "author_name": "Jean-Sebastien Casalegno", - "author_inst": "Virpath, Centre International de Recherche en Infectiologie (CIRI)" + "author_name": "Monta Ustinova", + "author_inst": "Latvian Biomedical Research and Study Centre, Ratsupites 1, Riga, Latvia, LV-1067" }, { - "author_name": "Bruno Lina", - "author_inst": "Virpath, Centre International de Recherche en Infectiologie (CIRI)" + "author_name": "Ivars Silamikelis", + "author_inst": "Latvian Biomedical Research and Study Centre, Ratsupites 1, Riga, Latvia, LV-1067" }, { - "author_name": "Lulla Opatowski", - "author_inst": "Institut Pasteur" + "author_name": "Liga Birzniece", + "author_inst": "Latvian Biomedical Research and Study Centre, Ratsupites 1, Riga, Latvia, LV-1067" + }, + { + "author_name": "Kaspars Megnis", + "author_inst": "Latvian Biomedical Research and Study Centre, Ratsupites 1, Riga, Latvia, LV-1067" + }, + { + "author_name": "Vita Rovite", + "author_inst": "Latvian Biomedical Research and Study Centre, Ratsupites 1, Riga, Latvia, LV-1067" + }, + { + "author_name": "Lauma Freimane", + "author_inst": "Latvian Biomedical Research and Study Centre, Ratsupites 1, Riga, Latvia, LV-1067" + }, + { + "author_name": "Laila Silamikele", + "author_inst": "Latvian Biomedical Research and Study Centre, Ratsupites 1, Riga, Latvia, LV-1067" + }, + { + "author_name": "Laura Ansone", + "author_inst": "Latvian Biomedical Research and Study Centre, Ratsupites 1, Riga, Latvia, LV-1067" + }, + { + "author_name": "Janis Pjalkovskis", + "author_inst": "Latvian Biomedical Research and Study Centre, Ratsupites 1, Riga, Latvia, LV-1067" + }, + { + "author_name": "Davids Fridmanis", + "author_inst": "Latvian Biomedical Research and Study Centre, Ratsupites 1, Riga, Latvia, LV-1067" + }, + { + "author_name": "Baiba Vilne", + "author_inst": "Riga Stradins University, Dzirciema 16, Riga, LV-1007" + }, + { + "author_name": "Marta Priedite", + "author_inst": "Centrala Laboratorija, Ltd, Sarlotes 1B, Riga, Latvia, LV-1001" + }, + { + "author_name": "Anastasija Caica", + "author_inst": "Centrala Laboratorija, Ltd, Sarlotes 1B, Riga, Latvia, LV-1001" + }, + { + "author_name": "Mikus Gavars", + "author_inst": "E. Gulbja Laboratorija, Ltd, Brivibas gatve 366, Riga, Latvia, LV-1006" + }, + { + "author_name": "Dmitrijs Perminovs", + "author_inst": "E. Gulbja Laboratorija, Ltd, Brivibas gatve 366, Riga, Latvia, LV-1006" + }, + { + "author_name": "Jelena Storozenko", + "author_inst": "Riga East University hospital, Laboratory Service, Latvian Centre of Infectious Diseases laboratory, National Microbiology Reference Laboratory, Molecular biolo" + }, + { + "author_name": "Oksana Savicka", + "author_inst": "Riga East University hospital, Laboratory Service, Latvian Centre of Infectious Diseases laboratory, National Microbiology Reference Laboratory, Molecular biolo" + }, + { + "author_name": "Elina Dimina", + "author_inst": "The Centre for Disease Prevention and Control (CDPC) of Latvia, Infectious Diseases Risk Analysis and Prevention Department, Infectious Diseases Surveillance an" + }, + { + "author_name": "Uga Dumpis", + "author_inst": "University of Latvia, Faculty of Medicine, Jelgavas 3, Riga, Latvia, LV-1004; Pauls Stradins Clinical University Hospital, Pilsonu 13, Riga, Latvia, LV-1002" + }, + { + "author_name": "Janis Klovins", + "author_inst": "Latvian Biomedical Research and Study Centre, Ratsupites 1, Riga, Latvia, LV-1067" } ], "version": "1", @@ -1184897,107 +1185921,35 @@ "category": "bioinformatics" }, { - "rel_doi": "10.1101/2020.09.09.285445", - "rel_title": "Evaluation of Safety and Immunogenicity of an Adjuvanted, TH-1 Skewed, Whole Virion Inactivated SARS-CoV-2 Vaccine - BBV152", + "rel_doi": "10.1101/2020.09.09.289074", + "rel_title": "Structural Genetics of circulating variants affecting the SARS CoV-2 Spike / human ACE2 complex", "rel_date": "2020-09-09", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.09.09.285445", - "rel_abs": "We report the development and evaluation of safety and immunogenicity of a whole virion inactivated SARS-COV-2 vaccine (BBV152), adjuvanted with aluminium hydroxide gel (Algel), or a novel TLR7/8 agonist adsorbed Algel. We used a well-characterized SARS-CoV-2 strain and an established vero cell platform to produce large-scale GMP grade highly purified inactivated antigen, BBV152. Product development and manufacturing were carried out in a BSL-3 facility. Immunogenicity was determined at two antigen concentrations (3g and 6g), with two different adjuvants, in mice, rats, and rabbits. Our results show that BBV152 vaccine formulations generated significantly high antigen-binding and neutralizing antibody titers, at both concentrations, in all three species with excellent safety profiles. The inactivated vaccine formulation containing TLR7/8 agonist adjuvant-induced Th1 biased antibody responses with elevated IgG2a/IgG1 ratio and increased levels of SARS-CoV-2 specific IFN-{gamma}+ CD4 T lymphocyte response. Our results support further development for Phase I/II clinical trials in humans.", - "rel_num_authors": 22, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.09.09.289074", + "rel_abs": "SARS-CoV-2 entry in human cells is mediated by the interaction between the viral Spike protein and the human ACE2 receptor. This mechanism evolved from the ancestor bat coronavirus and is currently one of the main targets for antiviral strategies. However, there currently exist several Spike protein variants in the SARS-CoV-2 population as the result of mutations, and it is unclear if these variants may exert a specific effect on the affinity with ACE2 which, in turn, is also characterized by multiple alleles in the human population. In the current study, the GBPM analysis, originally developed for highlighting host-guest interaction features, has been applied to define the key amino acids responsible for the Spike/ACE2 molecular recognition, using four different crystallographic structures. Then, we intersected these structural results with the current mutational status, based on more than 295,000 sequenced cases, in the SARS-CoV-2 population. We identified several Spike mutations interacting with ACE2 and mutated in at least 20 distinct patients: S477N, N439K, N501Y, Y453F, E484K, K417N, S477I and G476S. Among these, mutation N501Y in particular is one of the events characterizing SARS-CoV-2 lineage B.1.1.7, which has recently risen in frequency in Europe. We also identified five ACE2 rare variants that may affect interaction with Spike and susceptibility to infection: S19P, E37K, M82I, E329G and G352V.\n\nSignificance StatementWe developed a method to identify key amino acids responsible for the initial interaction between SARS-CoV-2 (the COVID-19 virus) and human cells, through the analysis of Spike/ACE2 complexes. We further identified which of these amino acids show variants in the viral and human populations. Our results will facilitate scientists and clinicians alike in identifying the possible role of present and future Spike and ACE2 sequence variants in cell entry and general susceptibility to infection.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Brunda Ganneru", - "author_inst": "Bharat Biotech" - }, - { - "author_name": "Harsh Jogdand", - "author_inst": "Bharat Biotech" - }, - { - "author_name": "Vijaya Kumar Dharam", - "author_inst": "Bharat Biotech" - }, - { - "author_name": "Narasimha Reddy", - "author_inst": "Bharat Biotech" - }, - { - "author_name": "Sai D Prasad", - "author_inst": "Bharat Biotech" - }, - { - "author_name": "Srinivas Vellimudu", - "author_inst": "Bharat Biotech" - }, - { - "author_name": "Krishna M Ella", - "author_inst": "Bharat Biotech" - }, - { - "author_name": "Rajaram Ravikrishnan", - "author_inst": "RCC Labs" - }, - { - "author_name": "Amit Awasthi", - "author_inst": "THSTI" + "author_name": "Francesco Ortuso", + "author_inst": "Department of Health Sciences, University \"Magna Graecia\" of Catanzaro, Catanzaro, Italy" }, { - "author_name": "Jomy Jose", - "author_inst": "RCC Labs" - }, - { - "author_name": "Panduranga Rao", - "author_inst": "Bharat Biotech" - }, - { - "author_name": "Deepak Kumar", - "author_inst": "Bharat Biotech" - }, - { - "author_name": "Raches Ella", - "author_inst": "Bharat Biotech International Limited" - }, - { - "author_name": "Priya Abraham", - "author_inst": "National Institute of Virology, Pune" - }, - { - "author_name": "Pragya Yadav", - "author_inst": "ICMR-National Institute of Virology" - }, - { - "author_name": "Gajanan N Sapkal", - "author_inst": "ICMR-National Institute of Virology" - }, - { - "author_name": "Anita Shete", - "author_inst": "National Institute of Virology-Indian Council of Medical Research" - }, - { - "author_name": "Gururaj Rao Desphande", - "author_inst": "National Institute of Virology-Indian Council of Medical Research" - }, - { - "author_name": "Sreelekshmy Mohandas", - "author_inst": "National Institute of Virology-Indian Council of Medical Research" - }, - { - "author_name": "Atanu Basu", - "author_inst": "National Institute of Virology-Indian Council of Medical Research" + "author_name": "Daniele Mercatelli", + "author_inst": "Department of Pharmacy and Biotechnology, University of Bologna, Bologna, Italy" }, { - "author_name": "Nievedita Gupta", - "author_inst": "Indian Council of Medical Research, India" + "author_name": "Pietro Hiram Guzzi", + "author_inst": "Department of Surgical and Medical Sciences, University \"Magna Graecia\" of Catanzaro, Catanzaro, Italy" }, { - "author_name": "Krishna Vadrevu Mohan", - "author_inst": "Bharat Biotech" + "author_name": "Federico Manuel Giorgi", + "author_inst": "Department of Pharmacy and Biotechnology, University of Bologna, Bologna, Italy" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by_nc_nd", "type": "new results", - "category": "immunology" + "category": "bioinformatics" }, { "rel_doi": "10.1101/2020.09.08.285007", @@ -1187671,17 +1188623,57 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.09.04.20188094", - "rel_title": "Regression Models for Predictions of COVID-19 New Cases and New Deaths Based on May/June Data in Ethiopia", + "rel_doi": "10.1101/2020.09.04.20188102", + "rel_title": "Modeling COVID-19 Transmission in Africa: Country-wise Projections of Total and Severe Infections Under Different Lockdown Scenarios", "rel_date": "2020-09-07", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.04.20188094", - "rel_abs": "As the 15 of June 2020, we have 7,984,067 total COVID-19 cases, globally and 435,181 total deaths. Ethiopia was ranked 2nd and 15th in the table by 176 new cases and by 3,521 total new cases from African countries. Then, this study aimed to predict COVID-19 new cases and new deaths based on May/June data in Ethiopia using regression model. In this study, I used Pearsons correlation analysis and the linear regression model to predict COVID-19 new cases and new deaths based on the available data from 12th May to 10th June 2020 in Ethiopia. There was a significant positive correlation between COVID-19 new cases and new deaths with different related variables. In the regression models, the simple linear regression model was a better fit the data of COVID-19 new cases and new deaths than as compared with quadratic and cubic regression models. In the multiple linear regression model, variables such as the number of days, the number of new laboratory tests, and the number of new cases from AA city significantly predicted the COVID-19 new cases. In this model, the number of days and new recoveries significantly predicted new deaths of COVID-19. The number of days, daily laboratory tests, and new cases from Addis Ababa city significantly predicted new COVID-19 cases, and the number of days and new recoveries significantly predicted new deaths from COVID-19. According to this analysis, if strong preventions and action are not taken in the country, the predicted values of COVID-19 new cases and new deaths will be 590 and 12 after two months (after 9th of August) from now, respectively. The researcher recommended that the Ethiopia government, Ministry of Health and Addis Ababa city administrative should give more awareness and protections for societies, and they should also open more COVID-19 laboratory testing centers. Generally, the obtained results of this study may help Ethiopian decision-makers put short-term future plans to face this epidemic.", - "rel_num_authors": 1, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.04.20188102", + "rel_abs": "ObjectivesAs of August 24th 2020, there have been 1,084,904 confirmed cases of SARS-CoV-2 and 24,683 deaths across the African continent. Despite relatively lower numbers of cases initially, many African countries are now experiencing an exponential increase in case numbers. Estimates of the progression of disease and potential impact of different interventions are needed to inform policy making decisions. Herein, we model the possible trajectory of SARS-CoV-2 in 52 African countries under different intervention scenarios.\n\nDesignWe developed a compartmental model of SARS-CoV-2 transmission to estimate the COVID-19 case burden for all African countries while considering four scenarios: no intervention, moderate lockdown, hard lockdown, and hard lockdown with continued restrictions once lockdown is lifted. We further analyzed the potential impact of COVID-19 on vulnerable populations affected by HIV/AIDS and TB.\n\nResultsIn the absence of an intervention, the most populous countries had the highest peaks in active projected number of infections with Nigeria having an estimated 645,081 severe infections. The scenario with a hard lockdown and continued post-lockdown interventions to reduce transmission was the most efficacious strategy for delaying the time to the peak and reducing the number of cases. In South Africa projected peak severe infections increase from 162,977 to 203,261, when vulnerable populations with HIV/AIDS and TB are included in the analysis.\n\nConclusionThe COVID-19 pandemic is rapidly spreading across the African continent. Estimates of the potential impact of interventions and burden of disease are essential for policy makers to make evidence-based decisions on the distribution of limited resources and to balance the economic costs of interventions with the potential for saving lives.\n\nARTICLE SUMMARY Strengths and limitations of this studyO_LIThough the rapid spread of SARS-CoV-2 through China, Europe and the United States has been well-studied, leading to a detailed understanding of its biology and epidemiology, the population and resources for combatting the spread of the disease in Africa greatly differ to those areas and require models specific to this context.\nC_LIO_LIFew models that provide estimates for policymakers, donors, and aid organizations focused on Africa to plan an effective response to the pandemic threat that optimizes the use of limited resources.\nC_LIO_LIThis is a compartmental model and as such has inherent weaknesses; including the possible overestimation of the number of infections as it is assumed people are well mixed, despite many social, physical and geographical barriers to mixing within countries.\nC_LIO_LIPeaks in transmission are likely to occur at different times in different regions, with multiple epicenters.\nC_LIO_LIThis model is not stochastic and case data are modeled from the first twenty or more cases, each behaving as an average case; in reality, there are no average cases; some individuals are likely to have many contacts, causing multiple infections, and others to have very few.\nC_LI", + "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Alemayehu Siffir Argawu Sr.", - "author_inst": "Ambo University" + "author_name": "Isabel Frost", + "author_inst": "Center for Disease Dynamics Economics & Policy" + }, + { + "author_name": "Jessica Craig", + "author_inst": "CDDEP" + }, + { + "author_name": "Gilbert Osena", + "author_inst": "Center for Disease Dynamics, Economics & Policy" + }, + { + "author_name": "Stephanie Hauck", + "author_inst": "Center for Disease Dynamics Economics & Policy" + }, + { + "author_name": "Erta Kalanxhi", + "author_inst": "Center for Disease Dynamics Economics & Policy" + }, + { + "author_name": "Emily Schueller", + "author_inst": "Center for Disease Dynamics Economics & Policy" + }, + { + "author_name": "Oliver Gatalo", + "author_inst": "Center for Disease Dynamics Economics & Policy" + }, + { + "author_name": "Yupeng Yany", + "author_inst": "Center for Disease Dynamics Economics & Policy" + }, + { + "author_name": "Katie Tseng", + "author_inst": "Center for Disease Dynamics Economics & Policy" + }, + { + "author_name": "Gary Lin", + "author_inst": "Johns Hopkins University" + }, + { + "author_name": "Eili Klein", + "author_inst": "Center for Disease Dynamics Economics & Policy" } ], "version": "1", @@ -1189373,71 +1190365,55 @@ "category": "bioinformatics" }, { - "rel_doi": "10.1101/2020.09.06.284992", - "rel_title": "Computationally validated SARS-CoV-2 CTL and HTL Multi-Patch Vaccines designed by reverse epitomics approach, shows potential to cover large ethnically distributed human population worldwide", + "rel_doi": "10.1101/2020.09.06.284695", + "rel_title": "Long-term survival of salmon-attached SARS-CoV-2 at 4 degree as a potential source of transmission in seafood markets", "rel_date": "2020-09-06", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.09.06.284992", - "rel_abs": "BackgroundThe SARS-CoV-2 (Severe Acute Respiratory Syndrome Coronavirus 2) is a positive-sense single-stranded RNA coronavirus responsible for the ongoing 2019-2020 COVID-19 outbreak. The highly contagious COVID-19 disease has spread to 216 countries in less than six months. Though several vaccine candidates are being claimed, an effective vaccine is yet to come. In present study we have designed and theoretically validated novel Multi-Patch Vaccines against SARS-CoV-2.\n\nMethodologyA novel reverse epitomics approach, \"overlapping-epitope-clusters-to-patches\" method is utilized to identify multiple antigenic regions from the SARS-CoV-2 proteome. These antigenic regions are here termed as \"Ag-Patch or Ag-Patches\", for Antigenic Patch or Patches. The identification of Ag-Patches is based on clusters of overlapping epitopes rising from a particular region of SARS-CoV-2 protein. Further, we have utilized the identified Ag-Patches to design Multi-Patch Vaccines (MPVs), proposing a novel methodology for vaccine design and development. The designed MPVs were analyzed for immunologically crucial parameters, physiochemical properties and cDNA constructs.\n\nResultsWe identified 73 CTL (Cytotoxic T-Lymphocyte), 49 HTL (Helper T-Lymphocyte) novel Ag-Patches from the proteome of SARS-CoV-2. The identified Ag-Patches utilized to design MPVs cover 768 (518 CTL and 250 HTL) overlapping epitopes targeting different HLA alleles. Such large number of epitope coverage is not possible for multi-epitope vaccines. The large number of epitopes covered implies large number of HLA alleles targeted, and hence large ethnically distributed human population coverage. The MPVs:Toll-Like Receptor ectodomain complex shows stable nature with numerous hydrogen bond formation and acceptable root mean square deviation and fluctuation. Further, the cDNA analysis favors high expression of the MPVs constructs in human cell line.\n\nConclusionHighly immunogenic novel Ag-Patches are identified from the entire proteome of SARS CoV-2 by a novel reverse epitomics approach. We conclude that the novel Multi-Patch Vaccines could be a highly potential novel approach to combat SARS-CoV-2, with greater effectiveness, high specificity and large human population coverage worldwide.\n\n\n\nO_FIG O_LINKSMALLFIG WIDTH=187 HEIGHT=200 SRC=\"FIGDIR/small/284992v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (84K):\norg.highwire.dtl.DTLVardef@176f27org.highwire.dtl.DTLVardef@82a4fcorg.highwire.dtl.DTLVardef@11db43forg.highwire.dtl.DTLVardef@12495b2_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOABSTRACT FIGURE:C_FLOATNO A Multi-Patch Vaccine design to combat SARS-CoV-2 and a method to prepare thereof.\n\nMulti-Patch Vaccine designing to combat SARS-CoV-2 infection by reverse epitomics approach, \"Overlapping-epitope-clusters-to-patches\" method.\n\nC_FIG", - "rel_num_authors": 13, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.09.06.284695", + "rel_abs": "Several outbreaks of COVID-19 were associated with seafood markets, raising concerns that fish-attached SARS-CoV-2 may exhibit prolonged survival in low-temperature environments. Here we showed that salmon-attached SARS-CoV-2 at 4{degrees}C could remain infectious for more than one week, suggesting that fish-attached SARS-CoV-2 may be a source of transmission.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Sukrit Srivastava", - "author_inst": "Indian Foundation for Fundamental Research, India" - }, - { - "author_name": "Sonia Verma", - "author_inst": "ICMR-National Institute of Malaria Research, India" - }, - { - "author_name": "Mohit Kamthania", - "author_inst": "Indian Foundation for Fundamental Research, India" - }, - { - "author_name": "Deepa Agarwal", - "author_inst": "Indian Foundation for Fundamental Research, India" - }, - { - "author_name": "Ajay Kumar Saxena", - "author_inst": "Jawaharlal Nehru University, India" + "author_name": "Manman Dai", + "author_inst": "South China Agricultural University" }, { - "author_name": "Michael Kolbe", - "author_inst": "Helmholzt-Center for Infection Research, Germany" + "author_name": "Huanan Li", + "author_inst": "South China Agricultural University" }, { - "author_name": "Sarman Singh", - "author_inst": "All India Institute of Medical Sciences, Bhopal, India" + "author_name": "Nan Yan", + "author_inst": "South China Agricultural University" }, { - "author_name": "Ashwin Kotnis", - "author_inst": "All India Institute of Medical Sciences, Bhopal, India" + "author_name": "Jinyu Huang", + "author_inst": "South China Agricultural University" }, { - "author_name": "Brijesh Rathi", - "author_inst": "Hansraj College, University of Delhi, India" + "author_name": "Li Zhao", + "author_inst": "South China Agricultural University" }, { - "author_name": "Seema A Nayar", - "author_inst": "Government Medical College, Trivandrum, India" + "author_name": "Siqi Xu", + "author_inst": "South China Agricultural University" }, { - "author_name": "Ho-Joon Shin", - "author_inst": "School of Medicine, Ajou University, South Korea" + "author_name": "Shibo Jiang", + "author_inst": "Fudan University" }, { - "author_name": "Kapil Vashisht", - "author_inst": "ICMR-National Institute of Malaria Research, India" + "author_name": "Chungen Pan", + "author_inst": "Haid Research Institute, Guangdong Haid Group Co., Ltd" }, { - "author_name": "Kailash C Pandey", - "author_inst": "ICMR-National Institute of Malaria Research, India" + "author_name": "Ming Liao", + "author_inst": "South China Agricultural University" } ], "version": "1", "license": "cc_no", "type": "new results", - "category": "immunology" + "category": "microbiology" }, { "rel_doi": "10.1101/2020.09.06.284976", @@ -1190823,87 +1191799,63 @@ "category": "genomics" }, { - "rel_doi": "10.1101/2020.09.04.283077", - "rel_title": "Improvements to the ARTIC multiplex PCR method for SARS-CoV-2 genome sequencing using nanopore", + "rel_doi": "10.1101/2020.09.04.282780", + "rel_title": "SARS-CoV-2 infection paralyzes cytotoxic and metabolic functions of immune cells", "rel_date": "2020-09-04", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.09.04.283077", - "rel_abs": "Genome sequencing has been widely deployed to study the evolution of SARS-CoV-2 with more than 90,000 genome sequences uploaded to the GISAID database. We published a method for SARS-CoV-2 genome sequencing (https://www.protocols.io/view/ncov-2019-sequencing-protocol-bbmuik6w) online on January 22, 2020. This approach has rapidly become the most popular method for sequencing SARS-CoV-2 due to its simplicity and cost-effectiveness. Here we present improvements to the original protocol: i) an updated primer scheme with 22 additional primers to improve genome coverage, ii) a streamlined library preparation workflow which improves demultiplexing rate for up to 96 samples and reduces hands-on time by several hours and iii) cost savings which bring the reagent cost down to {pound}10 per sample making it practical for individual labs to sequence thousands of SARS-CoV-2 genomes to support national and international genomic epidemiology efforts.", - "rel_num_authors": 17, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.09.04.282780", + "rel_abs": "The SARS-CoV-2 virus is the causative agent of the global COVID-19 infectious disease outbreak, which can lead to acute respiratory distress syndrome (ARDS). However, it is still unclear how the virus interferes with immune cell and metabolic functions in the human body. In this study, we investigated the immune response in acute or convalescent COVID19 patients. We characterized the peripheral blood mononuclear cells (PBMCs) using flow cytometry and found that CD8+ T cells were significantly subsided in moderate COVID-19 and convalescent patients. Furthermore, characterization of CD8+ T cells suggested that patients with a mild and moderate course of the COVID-19 disease and convalescent patients have significantly diminished expression of both perforin and granzyme A in CD8+ T cells. Using 1H-NMR spectroscopy, we characterized the metabolic status of their autologous PBMCs. We found that fructose, lactate and taurine levels were elevated in infected (mild and moderate) patients compared with control and convalescent patients. Glucose, glutamate, formate and acetate levels were attenuated in COVID-19 (mild and moderate) patients. In summary, our report suggests that SARS-CoV-2 infection leads to disrupted CD8+ T cytotoxic functions and changes the overall metabolic functions of immune cells.", + "rel_num_authors": 11, "rel_authors": [ { - "author_name": "John R Tyson", - "author_inst": "Michael Smith Laboratories and Djavad Mowafaghian Centre for Brain Health, University of British Columbia, Vancouver, Canada." - }, - { - "author_name": "Phillip James", - "author_inst": "Oxford Nanopore Technologies Ltd., Oxford, UK." - }, - { - "author_name": "David Stoddart", - "author_inst": "Oxford Nanopore Technologies Ltd., Oxford, UK." - }, - { - "author_name": "Natalie Sparks", - "author_inst": "Institute of Microbiology and Infection, University of Birmingham, Birmingham, UK." - }, - { - "author_name": "Arthur Wickenhagen", - "author_inst": "MRC-University of Glasgow Centre for Virus Research, Glasgow, UK." - }, - { - "author_name": "Grant Hall", - "author_inst": "Division of Virology, Department of Pathology, University of Cambridge, Cambridge, UK." + "author_name": "Yogesh Singh", + "author_inst": "Institute of Medical Genetics and Applied Genomics, University of Tuebingen, Calwerstrasse 7, 72076, Tuebingen, Germany" }, { - "author_name": "Ji Hyun Choi", - "author_inst": "Division of AIDS, Faculty of Medicine, University of British Columbia, Vancouver, Canada." + "author_name": "Christoph Trautwein", + "author_inst": "Werner Siemens Imaging Center, University of Tuebingen, Roentgenweg 13, 72076, Tuebingen, Germany" }, { - "author_name": "Hope Lapointe", - "author_inst": "Division of AIDS, Faculty of Medicine, University of British Columbia, Vancouver, Canada." + "author_name": "Rolf Fendel", + "author_inst": "Institute of Tropical Medicine, University Hospital of Tuebingen, Wilhelmstrasse 27, 72076, Tuebingen, Germany" }, { - "author_name": "Kimia Kamelian", - "author_inst": "British Columbia Centre for Disease Control Public Health Laboratory, Vancouver, Canada." + "author_name": "Naomi Krickeberg", + "author_inst": "Institute of Tropical Medicine, University Hospital of Tuebingen, Wilhelmstrasse 27, 72076, Tuebingen, Germany" }, { - "author_name": "Andrew D Smith", - "author_inst": "Institute of Microbiology and Infection, University of Birmingham, Birmingham, UK." + "author_name": "Georgy Berezhnoy", + "author_inst": "Werner Siemens Imaging Center, University of Tuebingen, Roentgenweg 13, 72076, Tuebingen, Germany" }, { - "author_name": "Natalie Prystajecky", - "author_inst": "British Columbia Centre for Disease Control Public Health Laboratory, Vancouver, Canada." + "author_name": "Rosi Bissinger", + "author_inst": "Department of Internal Medicine, Division of Endocrinology, Diabetology and Nephrology, University Hospital of Tuebingen, Germany" }, { - "author_name": "Ian Goodfellow", - "author_inst": "Division of Virology, Department of Pathology, University of Cambridge, Cambridge, UK." - }, - { - "author_name": "Sam J Wilson", - "author_inst": "MRC-University of Glasgow Centre for Virus Research, Glasgow, UK." + "author_name": "Stephan Ossowski", + "author_inst": "Institute of Medical Genetics and Applied Genomics, University of Tuebingen, Calwerstrasse 7, 72076, Tuebingen, Germany" }, { - "author_name": "Richard Harrigan", - "author_inst": "Division of AIDS, Faculty of Medicine, University of British Columbia, Vancouver, Canada." + "author_name": "Madhuri S Salker", + "author_inst": "Research Institute of Women Health, University of Tuebingen, Calwerstrasse 7/6, 72076, Tuebingen, Germany" }, { - "author_name": "Terrance P Snutch", - "author_inst": "Michael Smith Laboratories and Djavad Mowafaghian Centre for Brain Health, University of British Columbia, Vancouver, Canada." + "author_name": "Nicolas Casadei", + "author_inst": "NGS Competence Center Tuebingen (NCCT), University of Tuebingen, Calwerstrasse 7, 72076 Tuebingen, Germany" }, { - "author_name": "Nicholas J Loman", - "author_inst": "Institute of Microbiology and Infection, University of Birmingham, Birmingham, UK." + "author_name": "Olaf Riess", + "author_inst": "NGS Competence Center Tuebingen (NCCT), University of Tuebingen, Calwerstrasse 7, 72076 Tuebingen, Germany" }, { - "author_name": "Joshua Quick", - "author_inst": "Institute of Microbiology and Infection, University of Birmingham, Birmingham, UK." + "author_name": "- The DeCOI", + "author_inst": "-" } ], "version": "1", - "license": "cc_by", + "license": "cc_no", "type": "new results", - "category": "genomics" + "category": "immunology" }, { "rel_doi": "10.1101/2020.09.04.277426", @@ -1192489,37 +1193441,49 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.09.02.20187179", - "rel_title": "Pleotropic association between risk and prognosis of COVID-19 and gene expression in blood and lung: A Mendelian randomization analysis", + "rel_doi": "10.1101/2020.09.02.20180984", + "rel_title": "Post-Anticoagulant D-dimer as a Highly Prognostic Biomarker of COVID-19 Mortality", "rel_date": "2020-09-03", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.02.20187179", - "rel_abs": "ObjectivesCOVID-19 has caused a large global pandemic. Patients with COVID-19 exhibited considerable variation in disease behavior. Pervious genome-wide association studies have identified potential genetic variants involved in the risk and prognosis of COVID-19, but the underlying biological interpretation remains largely unclear.\n\nMethodsWe applied the summary data-based Mendelian randomization (SMR) method to identify genes that were pleiotropically associated with the risk and various outcomes of COVID-19, including severe respiratory confirmed COVID-19 and hospitalized COVID-19.\n\nResultsIn blood, we identified 2 probes, ILMN_1765146 and ILMN_1791057 tagging IFNAR2, that showed pleiotropic association with hospitalized COVID-19 ({beta} [SE] = 0.42 [0.09], P = 4.75x10-06 and {beta} [SE] = -0.48 [0.11], P = 6.76x10-06, respectively). Although no other probes were significant after correction for multiple testing in both blood and lung, multiple genes as tagged by the top 5 probes were involved in inflammation or antiviral immunity, and several other tagged genes, such as PON2 and HPS5, were involved in blood coagulation.\n\nConclusionsWe identified IFNAR2 and other potential genes that could be involved in the susceptibility or prognosis of COVID-19. These findings provide important leads to a better understanding of the mechanisms of cytokine storm and venous thromboembolism in COVID-19 and potential therapeutic targets for the effective treatment of COVID-19.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.02.20180984", + "rel_abs": "ImportanceClinical biomarkers that accurately predict mortality are needed for the effective management of patients with severe COVID-19 illness.\n\nObjectiveTo determine whether D-dimer levels after anticoagulation treatment is predictive of in-hospital mortality.\n\nDesignRetrospective study using electronic health record data.\n\nSettingA large New York City hospital network serving a diverse, urban patient population.\n\nParticipantsAdult patients hospitalized for severe COVID-19 infection who received therapeutic anticoagulation for thromboprophylaxis between February 25, 2020 and May 31, 2020.\n\nExposuresMean and trend of D-dimer levels in the 3 days following the first therapeutic dose of anticoagulation.\n\nMain OutcomesIn-hospital mortality versus discharge.\n\nResults1835 adult patients (median age, 67 years [interquartile range, 57-78]; 58% male) with PCR-confirmed COVID-19 who received therapeutic anticoagulation during hospitalization were included. 74% (1365) of patients were discharged and 26% (430) died in hospital. The study cohort was divided into four groups based on the mean D-dimer levels and its trend following anticoagulation initiation, with significantly different in-hospital mortality rates (p<0.001): 49% for the high mean-increase trend (HI) group; 27% for the high-decrease (HD) group; 21% for the low-increase (LI) group; and 9% for the low-decrease (LD) group. Using penalized logistic regression models to simultaneously analyze 67 variables (baseline demographics, comorbidities, vital signs, laboratory values, D-dimer levels), post-anticoagulant D-dimer groups had the highest adjusted odds ratios (ORadj) for predicting in-hospital mortality. The ORadj of in-hospital death among patients from the HI group was 6.58 folds (95% CI 3.81-11.16) higher compared to the LD group. The LI (ORadj: 4.06, 95% CI 2.23-7.38) and HD (ORadj: 2.37; 95% CI 1.37-4.09) groups were also associated with higher mortality compared to the LD group.\n\nConclusions and RelevanceD-dimer levels and its trend following the initiation of anticoagulation have high and independent predictive value for in-hospital mortality. This novel prognostic biomarker should be incorporated into management protocols to guide resource allocation and prospective studies for emerging treatments in hospitalized COVID-19 patients.\n\nKey PointsO_ST_ABSQuestionC_ST_ABSAre D-dimer levels following therapeutic anticoagulation predictive of mortality in hospitalized COVID-19 patients?\n\nFindingIn a retrospective study of 1835 adult COVID-19 patients who received therapeutic anticoagulation for thromboprophylaxis during hospitalization, 1365 (74%) patients were discharged and 470 (26%) died. Post-anticoagulant D-dimer levels and trends were significantly and independently predictive of mortality.\n\nMeaningActive monitoring of post-anticoagulant D-dimer levels in hospitalized COVID-19 patients is a novel strategy for stratifying individual risk of in-hospital mortality that can help guide resource allocation and prospective studies for emerging treatments for severe COVID-19 illness.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Di Liu", - "author_inst": "Capital Medical University" + "author_name": "Xiaoyu Song", + "author_inst": "Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Jingyun Yang", - "author_inst": "Rush University Medical Center" + "author_name": "Jiayi Ji", + "author_inst": "Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Bowen Feng", - "author_inst": "University of Windsor" + "author_name": "Boris Reva", + "author_inst": "Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Wenjin Lu", - "author_inst": "University College London" + "author_name": "Himanshu Joshi", + "author_inst": "Institute of Healthcare Delivery Science, Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Chuntao Zhao", - "author_inst": "Cincinnati Children Hospital Medical Center" + "author_name": "Anna Pamela Calinawan", + "author_inst": "Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Lizhuo Li", - "author_inst": "Capital Medical University" + "author_name": "Madhu Mazumdar", + "author_inst": "Icahn School of Medicine at Mount Sinai Hospital" + }, + { + "author_name": "Emanuela Taioli", + "author_inst": "Icahn School of Medicine at Mount Sinai" + }, + { + "author_name": "Pei Wang", + "author_inst": "Icahn School of Medicine at Mount Sinai" + }, + { + "author_name": "Rajwanth Veluswamy", + "author_inst": "Icahn School of Medicine at Mount Sinai" } ], "version": "1", @@ -1194063,23 +1195027,39 @@ "category": "evolutionary biology" }, { - "rel_doi": "10.1101/2020.09.03.280727", - "rel_title": "The discovery of gene mutations making SARS-CoV-2 well adapted for humans: host-genome similarity analysis of 2594 genomes from China, the USA and Europe", + "rel_doi": "10.1101/2020.09.03.280719", + "rel_title": "A Mental Health Paradox: Mental health was both a motivator and barrier to physical activity during the COVID-19 pandemic", "rel_date": "2020-09-03", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.09.03.280727", - "rel_abs": "Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a positive-sense single-stranded virus approximately 30 kb in length, causes the ongoing novel coronavirus disease-2019 (COVID-19). Studies confirmed significant genome differences between SARS-CoV-2 and SARS-CoV, suggesting that the distinctions in pathogenicity might be related to genomic diversity. However, the relationship between genomic differences and SARS-CoV-2 fitness has not been fully explained, especially for open reading frame (ORF)-encoded accessory proteins. RNA viruses have a high mutation rate, but how SARS-CoV-2 mutations accelerate adaptation is not clear. This study shows that the host-genome similarity (HGS) of SARS-CoV-2 is significantly higher than that of SARS-CoV, especially in the ORF6 and ORF8 genes encoding proteins antagonizing innate immunity in vivo. A power law relationship was discovered between the HGS of ORF3b, ORF6, and N and the expression of interferon (IFN)-sensitive response element (ISRE)-containing promoters. This finding implies that high HGS of SARS-CoV-2 genome may further inhibit IFN I synthesis and cause delayed host innate immunity. An ORF1ab mutation, 10818G>T, which occurred in virus populations with high HGS but rarely in low-HGS populations, was identified in 2594 genomes with geolocations of China, the USA and Europe. The 10818G>T caused the amino acid mutation M37F in the transmembrane protein nsp6. The results suggest that the ORF6 and ORF8 genes and the mutation M37F may play important roles in causing COVID-19. The findings demonstrate that HGS analysis is a promising way to identify important genes and mutations in adaptive strains, which may help in searching potential targets for pharmaceutical agents.", - "rel_num_authors": 1, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.09.03.280719", + "rel_abs": "The COVID-19 pandemic has impacted the mental health, physical activity, and sedentary behavior of citizens worldwide. Using an online survey with 1669 respondents, we sought to understand why and how by querying about perceived barriers and motivators to physical activity that changed because of the pandemic, and how those changes impacted mental health. Consistent with prior reports, our respondents were less physically active (aerobic activity, -11%, p <0.05; strength-based activity, -30%, p<0.01) and more sedentary (+11%, p<0.01) during the pandemic as compared to 6-months before. The pandemic also increased psychological stress (+22%, p <0.01) and brought on moderate symptoms of anxiety and depression. Respondents whose mental health deteriorated the most were also the ones who were least active (depression r = -.21, p<0.01; anxiety r = -.12, p<0.01). The majority of respondents were unmotivated to exercise because they were too anxious (+8%, p <0.01), lacked social support (+6%, p =<0.01), or had limited access to equipment (+23%, p <0.01) or space (+41%, p <0.01). The respondents who were able to stay active reported feeling less motivated by physical health outcomes such as weight loss (-7%, p<0.01) or strength (-14%, p<0.01) and instead more motivated by mental health outcomes such as anxiety relief (+14%, p <0.01). Coupled with previous work demonstrating a direct relationship between mental health and physical activity, these results highlight the potential protective effect of physical activity on mental health and point to the need for psychological support to overcome perceived barriers so that people can continue to be physically active during stressful times like the pandemic.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Weitao Sun", - "author_inst": "Tsinghua University" + "author_name": "Maryam Yvonne Marashi", + "author_inst": "McMaster University" + }, + { + "author_name": "Emma Nicholson", + "author_inst": "McMaster University" + }, + { + "author_name": "Michelle Ogrodnik", + "author_inst": "McMaster University" + }, + { + "author_name": "Barbara Fenesi", + "author_inst": "University of Western Ontario: Western University" + }, + { + "author_name": "Jennifer J Heisz", + "author_inst": "McMaster University" } ], "version": "1", "license": "cc_by", "type": "new results", - "category": "microbiology" + "category": "scientific communication and education" }, { "rel_doi": "10.1101/2020.09.02.20185199", @@ -1195521,43 +1196501,23 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.08.26.20181719", - "rel_title": "Sample Pooling is a Viable Strategy for SARS-CoV-2 Detection in Low-Prevalence Settings", + "rel_doi": "10.1101/2020.08.30.20184754", + "rel_title": "Impact of temperature on Covid 19 in India", "rel_date": "2020-09-02", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.26.20181719", - "rel_abs": "BACKGROUNDThe severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has significantly increased demand on laboratory throughput and reagents for nucleic acid extraction and polymerase chain reaction (PCR). Reagent shortages may limit the expansion of testing required to scale back isolation measures.\n\nAIMTo investigate the viability of sample pooling as a strategy for increasing test throughput and conserving PCR reagents; to report our early experience with pooling of clinical samples.\n\nMETHODSA pre-implementation study was performed to assess the sensitivity and theoretical efficiency of two, four, and eight-sample pools in a real-time reverse transcription PCR-based workflow. A standard operating procedure was developed and implemented in two laboratories during periods of peak demand, inclusive of over 29,000 clinical samples processed in our laboratory.\n\nRESULTSSensitivity decreased (mean absolute increase in cycle threshold value of 0.6, 2.3, and 3.0 for pools of two, four, and eight samples respectively) and efficiency increased as pool size increased. Gains from pooling diminished at high disease prevalence. Our standard operating procedure was successfully implemented across two laboratories. Increased workflow complexity imparts a higher risk of errors, and requires risk mitigation strategies. Turnaround time for individual samples increased, hence urgent samples should not be pooled.\n\nCONCLUSIONSPooling is a viable strategy for high-throughput testing of SARS-CoV-2 in low-prevalence settings.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.30.20184754", + "rel_abs": "The role of temperature in Covid 19 pandemic has been subjected to frequent review. An effort was made to find out such relations from three districts in India. Data were analyzed for 14 weeks. It appears that temperature could impact the spread of the pandemic.", + "rel_num_authors": 1, "rel_authors": [ { - "author_name": "Brian SW Chong", - "author_inst": "Victorian Infectious Diseases Reference Laboratory" - }, - { - "author_name": "Thomas Tran", - "author_inst": "Victorian Infectious Diseases Reference Laboratory" - }, - { - "author_name": "Julian Druce", - "author_inst": "Victorian Infectious Diseases Reference Laboratory" - }, - { - "author_name": "Susan A Ballard", - "author_inst": "The University of Melbourne at the Peter Doherty Institute for Infection and Immunity" - }, - { - "author_name": "Julie A Simpson", - "author_inst": "Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne" - }, - { - "author_name": "Mike Catton", - "author_inst": "Victorian Infectious Diseases Reference Laboratory" + "author_name": "Manas P Roy", + "author_inst": "Ministry of Health and Family Welfare" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2020.08.29.20184317", @@ -1197547,37 +1198507,17 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.08.31.20184036", - "rel_title": "Assessing the Impact of the Covid-19 Pandemic on US Mortality: A County-Level Analysis", + "rel_doi": "10.1101/2020.08.31.20185165", + "rel_title": "Estimation of a state of Corona 19 epidemic in August 2020 by multistage logistic model: a case of EU, USA, and World", "rel_date": "2020-09-02", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.31.20184036", - "rel_abs": "BackgroundCovid-19 excess deaths refer to increases in mortality over what would normally have been expected in the absence of the Covid-19 pandemic. Several prior studies have calculated excess deaths in the United States but were limited to the national or state level, precluding an examination of area-level variation in excess mortality and excess deaths not assigned to Covid-19. In this study, we take advantage of county-level variation in Covid-19 mortality to estimate excess deaths associated with the pandemic and examine how the extent of excess mortality not assigned to Covid-19 varies across subsets of counties defined by sociodemographic and health characteristics.\n\nMethods and FindingsIn this ecological, cross-sectional study, we made use of provisional National Center for Health Statistics (NCHS) data on direct Covid-19 and all-cause mortality occurring in U.S. counties from January 1 to December 31, 2020 and reported before March 12, 2021. We used data with a ten week time lag between the final day that deaths occurred and the last day that deaths could be reported to improve the completeness of data. Our sample included 2,096 counties with 20 or more Covid-19 deaths. The total number of residents living in these counties was 319.1 million. On average, the counties were 18.7% Hispanic, 12.7% non-Hispanic Black and 59.6% non-Hispanic White. 15.9% of the population was older than 65 years. We first modeled the relationship between 2020 all-cause mortality and Covid-19 mortality across all counties and then produced fully stratified models to explore differences in this relationship among strata of sociodemographic and health factors. Overall, we found that for every 100 deaths assigned to Covid-19, 120 all-cause deaths occurred (95% CI, 116 to 124), implying that 17% (95% CI, 14% to 19%) of excess deaths were ascribed to causes of death other than Covid-19 itself. Our stratified models revealed that the percentage of excess deaths not assigned to Covid-19 was substantially higher among counties with lower median household incomes and less formal education, counties with poorer health and more diabetes, and counties in the South and West. Counties with more non-Hispanic Black residents, who were already at high risk of Covid-19 death based on direct counts, also reported higher percentages of excess deaths not assigned to Covid-19. Study limitations include the use of provisional data that may be incomplete and the lack of disaggregated data on county-level mortality by age, sex, race/ethnicity, and sociodemographic and health characteristics.\n\nConclusionsIn this study, we found that direct Covid-19 death counts in the United States in 2020 substantially underestimated total excess mortality attributable to Covid-19. Racial and socioeconomic inequities in Covid-19 mortality also increased when excess deaths not assigned to Covid-19 were considered. Our results highlight the importance of considering health equity in the policy response to the pandemic.\n\nAuthors SummaryO_ST_ABSWhy Was This Study Done?C_ST_ABSO_LIThe Covid-19 pandemic has resulted in excess mortality that would not have occurred in the absence of the pandemic.\nC_LIO_LIExcess deaths include deaths assigned to Covid-19 in official statistics as well as deaths that are not assigned to Covid-19 but are attributable directly or indirectly to Covid-19.\nC_LIO_LIWhile prior studies have identified significant racial and socioeconomic inequities in directly assigned Covid-19 deaths, few studies have documented how excess mortality in 2020 has differed across sociodemographic or health factors in the United States.\nC_LI\n\nWhat Did the Researchers Do and Find?O_LILeveraging data from 2,096 counties on Covid-19 and all-cause mortality, we assessed what percentage of excess deaths were not assigned to Covid-19 and examined variation in excess deaths by county characteristics.\nC_LIO_LIIn these counties, we found that for every 100 deaths directly assigned to Covid-19 in official statistics, an additional 20 deaths occurred that were not counted as direct Covid-19 deaths.\nC_LIO_LIThe proportion of excess deaths not counted as direct Covid-19 deaths was even higher in counties with lower average socioeconomic status, counties with more comorbidities, and counties in the South and West. Counties with more non-Hispanic Black residents who were already at high risk of Covid-19 death based on direct counts, also reported a higher proportion of excess deaths not assigned to Covid-19.\nC_LI\n\nWhat Do These Findings Mean?O_LIDirect Covid-19 death counts significantly underestimate excess mortality in 2020.\nC_LIO_LIMonitoring excess mortality will be critical to gain a full picture of socioeconomic and racial inequities in mortality attributable to the Covid-19 pandemic.\nC_LIO_LITo prevent inequities in mortality from growing even larger, health equity must be prioritized in the policy response to the Covid-19 pandemic.\nC_LI", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.31.20185165", + "rel_abs": "The article provides an estimate of the size and duration of the Covid-19 epidemic in August 2020 for the European Union (EU), the United States (US), and the World using a multistage logistical epidemiological model.", + "rel_num_authors": 1, "rel_authors": [ { - "author_name": "Andrew C Stokes", - "author_inst": "Boston University School of Public Health" - }, - { - "author_name": "Dielle J Lundberg", - "author_inst": "Boston University School of Public Health" - }, - { - "author_name": "Irma T Elo", - "author_inst": "University of Pennsylvania" - }, - { - "author_name": "Katherine Hempstead", - "author_inst": "Robert Wood Johnson Foundation" - }, - { - "author_name": "Jacob Bor", - "author_inst": "Boston University School of Public Health" - }, - { - "author_name": "Samuel H Preston", - "author_inst": "University of Pennsylvania" + "author_name": "milan batista", + "author_inst": "university of ljubljana" } ], "version": "1", @@ -1199369,93 +1200309,37 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.08.27.20182493", - "rel_title": "A longitudinal study of SARS-CoV-2 infected patients shows high correlation between neutralizing antibodies and COVID-19 severity", + "rel_doi": "10.1101/2020.08.26.20182766", + "rel_title": "Modeling Dynamic Network Strategies for SARS-CoV-2 Control on a Cruise Ship", "rel_date": "2020-09-01", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.27.20182493", - "rel_abs": "Understanding the immune responses elicited by SARS-CoV-2 infection is critical in terms of protection from re-infection and, thus, for public health policy and for vaccine development against the COVID-19. Here, using either live SARS-CoV-2 particles or retroviruses pseudotyped with the SARS-CoV-2 S viral surface protein (Spike), we studied the neutralizing antibody (nAb) response in serum specimens from a cohort of 140 SARS-CoV-2 qPCR-confirmed patients, including patient with mild symptoms but also more severe form including those that require intensive care. We show that nAb titers were strongly correlated with disease severity and with anti-Spike IgG levels. Indeed, patients from intensive care units exhibited high nAb titers, whereas patients with milder disease symptoms displayed heterogenous nAb titers and asymptomatic or exclusive outpatient care patients had no or poor nAb levels. We found that the nAb activity in SARS-CoV-2-infected patients displayed a relatively rapid decline after recovery, as compared to individuals infected with alternative coronaviruses. We show the absence of cross-neutralization between endemic coronaviruses and SARS-CoV-2, indicating that previous infection by human coronaviruses may not generate protective nAb against SARS-CoV-2 infection. Finally, we found that the D614G mutation in the Spike protein, which has recently been identified as the major variant now found in Europe, does not allow neutralization escape. Altogether, our results contribute to the understanding of the immune correlate of SARS-CoV-2 induced disease and claim for a rapid evaluation of the role of the humoral response in the pathogenesis of SARS-CoV-2.", - "rel_num_authors": 19, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.26.20182766", + "rel_abs": "SARS-CoV-2 outbreaks have occurred on several nautical vessels, driven by the high-density contact networks on these ships. Optimal strategies for prevention and control that account for realistic contact networks are needed. We developed a network-based transmission model for SARS-CoV-2 on the Diamond Princess outbreak to characterize transmission dynamics and to estimate the epidemiological impact of outbreak control and prevention measures. This model represented the dynamic multi-layer network structure of passenger-passenger, passengercrew, and crew-crew contacts, both before and after the large-scale network lockdown imposed on the ship in response to the disease outbreak. Model scenarios evaluated variations in the timing of the network lockdown, reduction in contact intensity within the sub-networks, and diagnosis-based case isolation on outbreak prevention. We found that only extreme restrictions in contact patterns during network lockdown and idealistic clinical response scenarios could avert a major COVID-19 outbreak. Contact network changes associated with adequate outbreak prevention were the restriction of passengers to their cabins, with limited passenger-crew contacts. Clinical response strategies required for outbreak prevention included early mass screening with an ideal PCR test (100% sensitivity) and immediate case isolation upon diagnosis. Public health restrictions on optional leisure activities like these should be considered until longer-term effective solutions such as a COVID-19 vaccine become widely available.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Vincent Legros", - "author_inst": "Centre International de Recherche en Infectiologie and VetAgro Sup" - }, - { - "author_name": "Sol\u00e8ne Denolly", - "author_inst": "Centre International de Recherche en Infectiologie" - }, - { - "author_name": "Manon Vogrig", - "author_inst": "University-Hospital of Saint-Etienne" - }, - { - "author_name": "Bertrand Boson", - "author_inst": "Centre International de Recherche en Infectiologie" - }, - { - "author_name": "Josselin Rigaill", - "author_inst": "University-Hospital of Saint-Etienne" - }, - { - "author_name": "Sylvie Pillet", - "author_inst": "Centre International de Recherche en Infectiologie and University-Hospital of Saint-Etienne" - }, - { - "author_name": "Florence Grattard", - "author_inst": "Centre International de Recherche en Infectiologie and University-Hospital of Saint-Etienne" - }, - { - "author_name": "Sylvie Gonzalo", - "author_inst": "University-Hospital of Saint-Etienne" - }, - { - "author_name": "Paul Verhoeven", - "author_inst": "Centre International de Recherche en Infectiologie and University-Hospital of Saint-Etienne" - }, - { - "author_name": "Omran Allatif", - "author_inst": "Centre International de Recherche en Infectiologie" - }, - { - "author_name": "Philippe Berthelot", - "author_inst": "Centre International de Recherche en Infectiologie and University-Hospital of Saint-Etienne" - }, - { - "author_name": "Carole P\u00e9lissier", - "author_inst": "University-Hospital of Saint-Etienne" - }, - { - "author_name": "Guillaume Thierry", - "author_inst": "University-Hospital of Saint-Etienne" - }, - { - "author_name": "Elisabeth Botelho-Nevers", - "author_inst": "Centre International de Recherche en Infectiologie and University-Hospital of Saint-Etienne" - }, - { - "author_name": "St\u00e9phane Paul", - "author_inst": "Centre International de Recherche en Infectiologie and University-Hospital of Saint-Etienne" + "author_name": "Samuel M Jenness", + "author_inst": "Emory University" }, { - "author_name": "Thierry Walzer", - "author_inst": "Centre International de Recherche en Infectiologie" + "author_name": "Kathryn S Willebrand", + "author_inst": "Yale University" }, { - "author_name": "Fran\u00e7ois-Lo\u00efc Cosset", - "author_inst": "Centre International de Recherche en Infectiologie" + "author_name": "Amyn A Malik", + "author_inst": "Yale University" }, { - "author_name": "Thomas Bourlet", - "author_inst": "Centre International de Recherche en Infectiologie and University-Hospital of Saint-Etienne" + "author_name": "Benjamin A Lopman", + "author_inst": "Emory University" }, { - "author_name": "Bruno Pozzetto", - "author_inst": "Centre International de Recherche en Infectiologie and University-Hospital of Saint-Etienne" + "author_name": "Saad B Omer", + "author_inst": "Yale University" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1201215,53 +1202099,37 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.08.27.20183624", - "rel_title": "Inflammatory biomarkers in pregnant women with COVID-19: a retrospective cohort study", + "rel_doi": "10.1101/2020.08.27.20182956", + "rel_title": "Assessment of the Publication Trends of COVID-19 Systematic Reviews and Randomized Controlled Trials", "rel_date": "2020-09-01", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.27.20183624", - "rel_abs": "Coronavirns disease 2019 is a pandemic viral disease affecting also obstetric patients and uncertainties exist about the prognostic role of inflammatory biomarkers and hemocytometry values in patients with this infection. To clarify that, we assessed the values of several inflammatory biomarkers and hemocytometry variables in a cohort of obstetric patients hospitalized with coronavirus disease 2019 and we correlated the values at admission with the need of oxygen supplementation during the hospitalization. Overall, among 27 (61%) pregnant women and 17 (39%) post-partum women, 6 (14%) patients received oxygen supplementation and 2 (4%) required admission to intensive care unit but none died. During hospitalization neutrophils (p=0.002), neutrophils to lymphocytes ratio (p=0.037) and C reactive protein (p<0.001) decreased significantly, whereas lymphocytes (p<0.001) and platelets (p<0.001) increased. Leukocytes and lymphocytes values at admission were correlated with oxygen need, with respectively a 1% and 5% higher risk of oxygen supplementation for each 1,000 cells decrease. Overall, in obstetric patients hospitalized with coronavirus disease 2019, C reactive protein is the inflammatory biomarker that better mirrors the course of the disease whereas D-dimer or ferritin are not reliable predictors of poor outcome. Care to the need of oxygen supplementation should be reserved to patients with reduced leukocytes or lymphocytes values at admission.", - "rel_num_authors": 9, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.27.20182956", + "rel_abs": "BackgroundDuring the COVID-19 pandemic, the number of studies listed in The National Library of Medicine registry (ClinicalTrials.gov) and preprints in medRxiv for COVID-19 has grown rapidly. In this study, we clarified the publication trends of randomized controlled trials (RCTs) and systematic reviews (SRs) regarding COVID-19. Methods: We conducted a cross-sectional study by investigating the number of SRs and RCTs on topics related to COVID-19 practice published in PubMed and medRxiv between January 1 and June 30, 2020. We calculated the ratio of the number of RCTs to that of SRs for this study period, as in a previous study. Results: The SR/RCT ratio in PubMed increased from 9.0 in March to 102 in June. In medRxiv, the SR/RCT ratio rose from 7.7 in March to 16.5 in June Discussion: The SR/RCT ratio increased and was much higher than that of 0.871 in 2017 found in a previous review of all medical research. During the study period, the trend in the COVID-19 publications comprised a more rapid increase in the number of SRs than RCTs", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "ANDREA LOMBARDI", - "author_inst": "IRCCS Ca' Granda Ospedale Maggiore Policlinico Foundation" - }, - { - "author_name": "Silvia Duiella", - "author_inst": "IRCCS Ca' Granda Ospedale Maggiore Policlinico Foundation" - }, - { - "author_name": "Letizia Li Piani", - "author_inst": "IRCCS Ca' Granda Ospedale Maggiore Policlinico Foundation" - }, - { - "author_name": "Ferruccio Ceriotti", - "author_inst": "IRCCS Ca' Granda Ospedale Maggiore Policlinico Foundation" - }, - { - "author_name": "Massimo Oggioni", - "author_inst": "IRCCS Ca' Granda Ospedale Maggiore Policlinico Foundation" + "author_name": "Shunsuke Taito", + "author_inst": "Division of Rehabilitation, Department of Clinical Practice and Support, Hiroshima University Hospital" }, { - "author_name": "Antonio Muscatello", - "author_inst": "IRCCS Ca' Granda Ospedale Maggiore Policlinico Foundation" + "author_name": "Yuki Kataoka", + "author_inst": "Hospital Care Research Unit, Hyogo Prefectural Amagasaki General Medical Center" }, { - "author_name": "Alessandra Bandera", - "author_inst": "IRCCS Ca' Granda Ospedale Maggiore Policlinico Foundation" + "author_name": "Takashi Ariie", + "author_inst": "Department of Physical Therapy, School of Health Sciences at Fukuoka, International University of Health and Welfare" }, { - "author_name": "Andrea Gori", - "author_inst": "IRCCS Ca' Granda Ospedale Maggiore Policlinico Foundation" + "author_name": "Shiho Oide", + "author_inst": "Department of Gynecology, Womens center, Yotsuya Medical Cube" }, { - "author_name": "Enrico Ferrazzi", - "author_inst": "IRCCS Ca' Granda Ospedale Maggiore Policlinico Foundation" + "author_name": "Yasushi Tsujimoto", + "author_inst": "Department of Healthcare Epidemiology, Graduate School of Medicine and Public Health, Kyoto University" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1202789,83 +1203657,39 @@ "category": "intensive care and critical care medicine" }, { - "rel_doi": "10.1101/2020.08.30.20182451", - "rel_title": "Positive association of Angiotensin II Receptor Blockers, not Angiotensin-Converting Enzyme Inhibitors, with an increased vulnerability to SARS-CoV-2 infection in patients hospitalized for suspected COVID-19 pneumonia", + "rel_doi": "10.1101/2020.08.27.20179853", + "rel_title": "Predicting and interpreting COVID-19 transmission rates from the ensemble of government policies", "rel_date": "2020-09-01", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.30.20182451", - "rel_abs": "BackgroundAngiotensin converting enzyme (ACE) type 2 is the receptor of SARS-CoV-2 for entry into lungs cells. Because ACE-2 may be modulated by ACE inhibitors (ACEIs) and angiotensin II receptor blockers (ARBs), there is concern that patients treated with ACEIs and ARBs are at higher risk for COVID-19 infection.\n\nAimThis study sought to analyze the association of COVID-19 with previous treatment with ACEI and ARB.\n\nMethodsWe retrospectively reviewed 684 consecutive patients hospitalized for suspected COVID-19 pneumonia and tested by PCR. Patients were split into 2 groups, whether (group 1, n=484) or not (group 2, n=250) COVID-19 was confirmed. Multivariate adjusted comparisons included a propensity score analysis.\n\nResultsAge was 63.6{+/-}18.7 years, and 302(44%) were female. Hypertension was present in 42.6% and 38.4% patients of group 1 and 2, respectively (P=0.28). A treatment with ARBs (20.7% versus 12.0%, respectively, OR 1.92, 95% confidence interval [1.23-2.98], p=0.004) was more frequent in patients of group 1 than in group 2. No difference was found for treatment with ACEIs (12.7% vs 15.7%, respectively, OR 0.81 [0.52-1.26], p=0.35). Propensity score matched multivariate logistic regression confirmed a significant association between COVID-19 and a previous treatment with ARBs (adjusted OR 2.18 [1.29-3.67], p=0.004). Significant interaction between ARBs and ACEIs for the risk of COVID-19 was observed in patients aged>60, women, and hypertensive patients.\n\nConclusionThis study suggests that ACEIs and ARBs are not similarly associated with the COVID-19. In this retrospective series, patients with COVID-19 pneumonia received more frequently a previous treatment with ARBs, than patients without COVID-19.", - "rel_num_authors": 16, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.27.20179853", + "rel_abs": "Several questions resonate as the governments relax their COVID-19 mitigation policies - is it too early to relax them, were the policies as effective as they could have been. Answering these questions about the past or crafting newer policy decisions in the future requires a quantification of how policy choices affect the spread of the infection. Policy landscape as well as the infection trajectories from different states and countries diverged so fast that comparing and learning from them has not been easy. In this work, we standardize and pool together the ensemble of lockdown and graded re-opening policies adopted by the 50 states of USA in any given week between 9th March and 9th August. Using artificial intelligence (AI) on this pooled data, we build a predictive model ([Formula], [Formula]) for the weekly-averaged transmission rate of infections. Predictability conceptually raises the possibility of an evidence-based or data-driven mitigation policy-making by evaluating the relative merits of the different policy scenarios. Probing the predictions with interpretable AI highlights how factors such as the closing of bars or the use of masks influence transmission, effects which have been hard to decouple from the ensemble of policy instrument combinations. While acknowledging the limitations of our predictions as well as of the infection testing, we ask the theoretical question if the observed transmission rates in the states were as efficient as they could have been under various levels of restrictions, and if the mitigation policies of the states are overdesigned. The model can be further refined with a more detailed inclusion of geographies and policy compliances, as well as expanded as newer policies emerge.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Jean-Louis GEORGES", - "author_inst": "Cardiology department, Centre Hospitalier de Versailles, Le Chesnay, France" - }, - { - "author_name": "Floriane Floriane Gilles", - "author_inst": "Cardiology department, Centre Hospitalier de Versailles, Le Chesnay, France" - }, - { - "author_name": "Helene Cochet", - "author_inst": "Cardiology department, Centre Hospitalier de Versailles, Le Chesnay, France" - }, - { - "author_name": "Alisson Bertrand", - "author_inst": "Cardiology department, Centre Hospitalier de Versailles, Le Chesnay, France" - }, - { - "author_name": "Marie De Tournemire", - "author_inst": "Cardiology department, Centre Hospitalier de Versailles, Le Chesnay, France" - }, - { - "author_name": "Victorien Monguillon", - "author_inst": "Cardiology department, Centre Hospitalier de Versailles, Le Chesnay, France" - }, - { - "author_name": "Maeva Pasqualini", - "author_inst": "Cardiology department, Centre Hospitalier de Versailles, Le Chesnay, France" - }, - { - "author_name": "Alix Prevot", - "author_inst": "Cardiology department, Centre Hospitalier de Versailles, Le Chesnay, France" - }, - { - "author_name": "Guillaume Roger", - "author_inst": "Cardiology department, Centre Hospitalier de Versailles, Le Chesnay, France" - }, - { - "author_name": "Joseph Saba", - "author_inst": "Cardiology department, Centre Hospitalier de Versailles, Le Chesnay, France" - }, - { - "author_name": "Josephine Soltani", - "author_inst": "Cardiology department, Centre Hospitalier de Versailles, Le Chesnay, France" - }, - { - "author_name": "Mehrsa Koukabi-Fradelizi", - "author_inst": "Emergency department, Centre Hospitalier de Versailles, Le Chesnay, France" + "author_name": "C. K. Sruthi", + "author_inst": "Jawaharlal Nehru Centre for Advanced Scientific Research" }, { - "author_name": "Jean Paul Beressi", - "author_inst": "Department of endocrinology and diabetology, Centre Hospitalier de Versailles, Le Chesnay, France" + "author_name": "Malay Ranjan Biswal", + "author_inst": "Jawaharlal Nehru Centre for Advanced Scientific Research" }, { - "author_name": "Cecile Laureana", - "author_inst": "Department of medical information and public health, Centre Hospitalier de Versailles, Le Chesnay, France" + "author_name": "Brijesh Saraswat", + "author_inst": "Jawaharlal Nehru Centre for Advanced Scientific Research" }, { - "author_name": "Jean Fran\u00e7ois Prost", - "author_inst": "Cardiology department, Centre Hospitalier de Versailles, Le Chesnay, France" + "author_name": "Himanshu Joshi", + "author_inst": "Jawaharlal Nehru Centre for Advanced Scientific Rearch" }, { - "author_name": "Livarek Bernard", - "author_inst": "Cardiology department, Centre Hospitalier de Versailles, Le Chesnay, France" + "author_name": "Meher K Prakash", + "author_inst": "Jawaharlal Nehru Centre for Advanced Scientific Research" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "cardiovascular medicine" + "category": "epidemiology" }, { "rel_doi": "10.1101/2020.08.28.20182295", @@ -1204543,111 +1205367,39 @@ "category": "radiology and imaging" }, { - "rel_doi": "10.1101/2020.08.25.20181404", - "rel_title": "Perturbations in the mononuclear phagocyte landscape associated with COVID-19 disease severity", + "rel_doi": "10.1101/2020.08.25.20181388", + "rel_title": "Trying to Find the Answer for Two Questions in Patients with COVID-19:1. Are pulmonary infiltrates of COVID-19 infective or inflammatory in nature (Pneumonia of Pneumonitis)?2. Is Hydroxychloroquine plus Azithromycin or Favipiravir plus Dexamethasone more effective in the COVID-19 treatment?", "rel_date": "2020-08-31", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.25.20181404", - "rel_abs": "Monocytes and dendritic cells are crucial mediators of innate and adaptive immune responses during viral infection, but misdirected responses by these cells might contribute to immunopathology. A comprehensive map of the mononuclear phagocyte (MNP) landscape during SARS-CoV-2 infection and concomitant COVID-19 disease is lacking. We performed 25-color flow cytometry-analysis focusing on MNP lineages in SARS-CoV-2 infected patients with moderate and severe COVID-19. While redistribution of monocytes towards intermediate subset and decrease in circulating DCs occurred in response to infection, severe disease associated with appearance of Mo-MDSC-like cells and a higher frequency of pre-DC2. Furthermore, phenotypic alterations in MNPs, and their late precursors, were cell-lineage specific and in select cases associated with severe disease. Finally, unsupervised analysis revealed that the MNP profile, alone, could identify a cluster of COVID-19 non-survivors. This study provides a reference for the MNP response to clinical SARS-CoV-2 infection and unravel myeloid dysregulation associated with severe COVID-19.", - "rel_num_authors": 23, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.25.20181388", + "rel_abs": "BackgroundDuring the current pandemic, a great effort is made to understand the COVID-19 and find an effective treatment. As of 17 August 2020, there is no specific drug or biologic agent which have been approved by the FDA for the prevention or treatment of COVID-19.\n\nMethodsWe retrospectively analyzed the clinical and radiological findings of 211 COVID-19 in-patients that were treated between March - August 2020. Confirmation of a COVID-19 diagnosis was made according to a positive RT-PCR result with a consistent high-resolution-CT (HRCT) finding. Radiological images and the rate of clinical response of patients were investigated.\n\nResultWhile 128 patients (58.7) did not develop pneumonia, the mild, moderate and severe pneumonia ratios were 28(13.2%), 31(18.7%) and 27(22.9%). 72 patients (34.1%) whose PCR tests were positive did not show any symptom and they were followed in isolation without treatment. 52 patients (24.6%) received hydroxychloroquine plus azithromycin, 57 patients (27%) received favipiravir and 30 patients (14.2%) received favipiravir plus dexamethasone as the first line of treatment. 63.1% of pneumonia patients who received hydroxychloroquine plus azithyromycine, 28.3% of patients who received favipiravir and 10% of patients who received favipiravir plus dexamethasone showed a failure of treatment.\n\nConclusionThe pulmonary infiltrates of COVID-19 are not infective; therefore, the characteristic of the disease should be described as COVID-19 pneumonitis instead of pneumonia. The favipiravir plus dexamethasone seems to be the only drug combination to achieve the improvement of radiological presentation and clinical symptoms in COVID-19 pneumonia patients.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Egle Kvedaraite", - "author_inst": "Karolinska Institutet" - }, - { - "author_name": "Laura Hertwig", - "author_inst": "Karolinska Institutet" - }, - { - "author_name": "Indranil Sinha", - "author_inst": "Karolinska Institutet" - }, - { - "author_name": "Andrea Ponzetta", - "author_inst": "Karolinska Institutet" - }, - { - "author_name": "Ida Hed Myrberg", - "author_inst": "Karolinska Institutet" - }, - { - "author_name": "Magdalini Lourda", - "author_inst": "Karolinska Institutet" - }, - { - "author_name": "Majda Dzidic", - "author_inst": "Karolinska Institutet" - }, - { - "author_name": "Mira Akber", - "author_inst": "Karolinska Institutet" - }, - { - "author_name": "Jonas Klingstrom", - "author_inst": "Karolinska Institutet" - }, - { - "author_name": "Elin Folkesson", - "author_inst": "Karolinska University Hospital" - }, - { - "author_name": "Rao Muvva", - "author_inst": "Karolinska Institutet" - }, - { - "author_name": "Puran Chen", - "author_inst": "Karolinska Institutet" - }, - { - "author_name": "Susanna Brighenti", - "author_inst": "Karolinska Institutet" - }, - { - "author_name": "Anna Norrby-Teglund", - "author_inst": "Karolinska Institutet" - }, - { - "author_name": "Lars I. Eriksson", - "author_inst": "Karolinska Institutet" - }, - { - "author_name": "Olav Rooyackers", - "author_inst": "Karolinska Institutet" - }, - { - "author_name": "Soo Aleman", - "author_inst": "Karolinska Institutet" - }, - { - "author_name": "Kristoffer Stralin", - "author_inst": "Karolinska Institutet" - }, - { - "author_name": "Hans-Gustaf Ljunggren", - "author_inst": "Karolinska Insitutet" + "author_name": "Adem Dirican", + "author_inst": "Samsun Medicalpark Hospital, Department of Pulmonary Medicine, Samsun, Turkey." }, { - "author_name": "Florent Ginhoux", - "author_inst": "Karolinska Institutet" + "author_name": "Tugce Uzar", + "author_inst": "Bahcesehir University School of Medicine" }, { - "author_name": "Niklas Bjorkstrom", - "author_inst": "Karolinska Institutet" + "author_name": "Irem Karaman", + "author_inst": "Bahcesehir University School of Medicine" }, { - "author_name": "Jan-Inge Henter", - "author_inst": "Karolinska Institutet" + "author_name": "Aziz Uluisik", + "author_inst": "Samsun Liv Hospital, Department of Pulmonary Medicine, Samsun, Turkey." }, { - "author_name": "Mattias Svensson", - "author_inst": "Karolinska Institutet" + "author_name": "Sevket Ozkaya", + "author_inst": "Bahcesehir University,Faculty of Medicine,Department of Pulmonary Medicine, Istanbul, Turkey" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "respiratory medicine" }, { "rel_doi": "10.1101/2020.08.24.20177576", @@ -1206897,63 +1207649,31 @@ "category": "molecular biology" }, { - "rel_doi": "10.1101/2020.08.30.274464", - "rel_title": "SARS-CoV-2 infects human pluripotent stem cell-derived cardiomyocytes, impairing electrical and mechanical function", + "rel_doi": "10.1101/2020.08.30.274241", + "rel_title": "Stability of SARS-CoV-2 on surfaces", "rel_date": "2020-08-30", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.08.30.274464", - "rel_abs": "Global health has been threatened by the COVID-19 pandemic, caused by the novel severe acute respiratory syndrome coronavirus (SARS-CoV-2)1. Although considered primarily a respiratory infection, many COVID-19 patients also suffer severe cardiovascular disease2-4. Improving patient care critically relies on understanding if cardiovascular pathology is caused directly by viral infection of cardiac cells or indirectly via systemic inflammation and/or coagulation abnormalities3,5-9. Here we examine the cardiac tropism of SARS-CoV-2 using human pluripotent stem cell-derived cardiomyocytes (hPSC-CMs) and three-dimensional engineered heart tissues (3D-EHTs). We observe that hPSC-CMs express the viral receptor ACE2 and other viral processing factors, and that SARS-CoV-2 readily infects and replicates within hPSC-CMs, resulting in rapid cell death. Moreover, infected hPSC-CMs show a progressive impairment in both electrophysiological and contractile properties. Thus, COVID-19-related cardiac symptoms likely result from a direct cardiotoxic effect of SARS-CoV-2. Long-term cardiac complications might be possible sequelae in patients who recover from this illness.", - "rel_num_authors": 11, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.08.30.274241", + "rel_abs": "We report the stability of SARS-CoV-2 on various surfaces under indoor, summer and spring/fall conditions. The virus was more stable under the spring/fall condition with virus half-lives ranging from 17.11 to 31.82 hours, whereas under indoor and summer conditions the virus half-lives were 3.5-11.33 and 2.54-5.58 hours, respectively.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Silvia Marchiano", - "author_inst": "University of Washington" - }, - { - "author_name": "Tien-Ying Hsiang", - "author_inst": "University of Washington" - }, - { - "author_name": "Ty Higashi", - "author_inst": "University of Washington" - }, - { - "author_name": "Akshita Kanna", - "author_inst": "University of Washington" - }, - { - "author_name": "Hans Reinecke", - "author_inst": "University of Washington" - }, - { - "author_name": "Xiulan Yang", - "author_inst": "University of Washington" - }, - { - "author_name": "Lil Pabon", - "author_inst": "University of Washington" - }, - { - "author_name": "Nathan J Sniadecki", - "author_inst": "University of Washington" - }, - { - "author_name": "Alessandro Bertero", - "author_inst": "University of Washington" + "author_name": "Taeyong Kwon", + "author_inst": "Kansas State University" }, { - "author_name": "Michael Gale Jr.", - "author_inst": "University of Washington" + "author_name": "Natasha N Gaudreault", + "author_inst": "Kansas State University" }, { - "author_name": "Charles E Murry", - "author_inst": "University of Washington" + "author_name": "Juergen A Richt", + "author_inst": "Kansas State University" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "new results", - "category": "pathology" + "category": "microbiology" }, { "rel_doi": "10.1101/2020.08.24.20181206", @@ -1208659,18 +1209379,31 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2020.08.28.255463", - "rel_title": "Resolvin D1 and D2 reduce SARS-Cov-2-induced inflammation in cystic fibrosis macrophages", - "rel_date": "2020-08-28", + "rel_doi": "10.1101/2020.08.26.269183", + "rel_title": "Serum Amyloid P inhibits single stranded RNA-induced lung inflammation, lung damage, and cytokine storm in mice", + "rel_date": "2020-08-27", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.08.28.255463", - "rel_abs": "Resolvins (Rv) are endogenous lipid autacoids that mediate resolution of inflammation and bacterial infections. Their roles in SARS-CoV-2 and COVID-19 are of considerable interest in the context of cystic fibrosis (CF) given the paucity of data regarding the effect of this virus on immune cells from individuals with CF. Here, we provide evidence for Rv biosynthesis and regulatory actions on CF macrophage inflammatory responses.", - "rel_num_authors": 0, - "rel_authors": null, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.08.26.269183", + "rel_abs": "SARS-CoV-2 is a single stranded RNA (ssRNA) virus and contains GU-rich sequences distributed abundantly in the genome. In COVID-19, the infection and immune hyperactivation causes accumulation of inflammatory immune cells, blood clots, and protein aggregates in lung fluid, increased lung alveolar wall thickness, and upregulation of serum cytokine levels. A serum protein called serum amyloid P (SAP) has a calming effect on the innate immune system and shows efficacy as a therapeutic for fibrosis in animal models and clinical trials. In this report, we show that aspiration of the GU-rich ssRNA oligonucleotide ORN06 into mouse lungs induces all of the above COVID-19-like symptoms. Men tend to have more severe COVID-19 symptoms than women, and in the aspirated ORN06 model, male mice tended to have more severe symptoms than female mice. Intraperitoneal injections of SAP starting from day 1 post ORN06 aspiration attenuated the ORN06-induced increase in the number of inflammatory cells and formation of clot-like aggregates in the mouse lung fluid, reduced ORN06-increased alveolar wall thickness and accumulation of exudates in the alveolar airspace, and attenuated an ORN06-induced upregulation of the inflammatory cytokines IL-1{beta}, IL-6, IL-12p70, IL-23, and IL-27 in serum. Together, these results suggest that aspiration of ORN06 is a simple model for both COVID-19 as well as cytokine storm in general, and that SAP is a potential therapeutic for diseases with COVID-19-like symptoms as well as diseases that generate a cytokine storm.", + "rel_num_authors": 3, + "rel_authors": [ + { + "author_name": "Tejas R Karhadkar", + "author_inst": "Texas A&M University" + }, + { + "author_name": "Darrell Pilling", + "author_inst": "Texas A&M University" + }, + { + "author_name": "Richard H. Gomer", + "author_inst": "Texas A&M University" + } + ], "version": "1", "license": "cc_no", "type": "new results", - "category": "pathology" + "category": "immunology" }, { "rel_doi": "10.1101/2020.08.27.267716", @@ -1210104,43 +1210837,27 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.08.24.20180802", - "rel_title": "Tracheal aspirate with closed suction device: a modified technique developed during COVID-19 outbreak.", + "rel_doi": "10.1101/2020.08.25.267625", + "rel_title": "MMGB/SA Consensus Estimate of the Binding Free Energy Between the Novel Coronavirus Spike Protein to the Human ACE2 Receptor", "rel_date": "2020-08-26", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.24.20180802", - "rel_abs": "BackgroundBacterial superinfection as well as ventilation associated pneumonia (VAP) are both frequent events in critical care. During COVID-19 pandemic, usual diagnostic practices such as bronchoalveolar lavage and tracheal aspirate are limited due to their associated high risk of exposure for the operator. In order to set primary focus on the protection of health care personnel, a modified tracheal aspiration (M-TA) technique is developed and used for acquiring a lower respiratory tract of microbiological samples with a closed suction device.\n\nMethodsRetrospective observational study to evaluate effectiveness of M-TA is conducted.\n\nResultsA total of 33 M-TA samples were analyzed. In 66,6% of the cases, results led to a change in medical decision making. A 100% accuracy was achieved regarding COVID-19 diagnosis and a 56% bacterial growth-rate in cultives where VAP was suspected. No health care personnel have developed symptoms nor tested positive for COVID-19 during or after sample collection.\n\nConclusionM-TA technique presented could be considered as a safe and effective procedure with low percentage of complications.", - "rel_num_authors": 6, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2020.08.25.267625", + "rel_abs": "The ability to estimate protein-protein binding free energy in a computationally efficient via a physics-based approach is beneficial to research focused on the mechanism of viruses binding to their target proteins. Implicit solvation methodology may be particularly useful in the early stages of such research, as it can offer valuable insights into the binding process, quickly. Here we evaluate the potential of the related molecular mechanics generalized Born surface area (MMGB/SA) approach to estimate the binding free energy {Delta}Gbind between the SARS-CoV-2 spike receptor-binding domain and the human ACE2 receptor. The calculations are based on a recent flavor of the generalized Born model, GBNSR6. Two estimates of {Delta}Gbind are performed: one based on standard bondi radii, and the other based on a newly developed set of atomic radii (OPT1), optimized specifically for protein-ligand binding. We take the average of the resulting two {Delta}Gbind values as the consensus estimate. For the well-studied Ras-Raf protein-protein complex, which has similar binding free energy to that of the SARS-CoV-2/ACE2 complex, the consensus {Delta}Gbind = -11.8 {+/-} 1 kcal/mol, vs. experimental -9.7 {+/-} 0.2 kcal/mol.\n\nThe consensus estimates for the SARS-CoV-2/ACE2 complex is {Delta}Gbind = -9.4 {+/-} 1.5 kcal/mol, which is in near quantitative agreement with experiment (-10.6 kcal/mol). The availability of a conceptually simple MMGB/SA-based protocol for analysis of the SARS-CoV-2 /ACE2 binding may be beneficial in light of the need to move forward fast.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Sofia Schverdfinger", - "author_inst": "Intensive Care Unit, Hospital Italiano de Buenos Aires" - }, - { - "author_name": "Indalecio Carboni Bisso", - "author_inst": "Intensive Care Unit, Hospital Italiano de Buenos Aires" - }, - { - "author_name": "Romina Famiglietti", - "author_inst": "Rehabilitation and Respiratory Care Division - Physiotherapy Service, Hospital Italiano de Buenos Aires" - }, - { - "author_name": "Marcelo Di Grazia", - "author_inst": "Rehabilitation and Respiratory Care Division - Physiotherapy Service, Hospital Italiano de Buenos Aires" + "author_name": "Negin Forouzesh", + "author_inst": "California State University, Los Angeles" }, { - "author_name": "Sabrina Di Stefano", - "author_inst": "Intensive Care Unit, Hospital Italiano de Buenos Aires" - }, - { - "author_name": "Marcos Las Heras", - "author_inst": "Intensive Care Unit, Hospital Italiano de Buenos Aires" + "author_name": "Alexey V Onufriev", + "author_inst": "Virginia Tech" } ], "version": "1", "license": "cc_by", - "type": "PUBLISHAHEADOFPRINT", - "category": "intensive care and critical care medicine" + "type": "new results", + "category": "biophysics" }, { "rel_doi": "10.1101/2020.08.25.256339", @@ -1212398,49 +1213115,25 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.08.23.20180273", - "rel_title": "Impact of nonpharmaceutical governmental strategies for prevention and control of COVID-19 in Sao Paulo State, Brazil.", + "rel_doi": "10.1101/2020.08.23.20180356", + "rel_title": "COVID-19: Estimation of the Actual Onset of Local Epidemic Cycles, Determination of Total Number of Infective, and Duration of the Incubation Period", "rel_date": "2020-08-25", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.23.20180273", - "rel_abs": "Interrupted time series analyses (ITSA) were performed to measure the impact of social distancing policies (instituted 22/03/2020) and subsequent mandatory masking in the community (instituted 04/05/2020) on the incidence and effective reproductive number (Rt) of COVID-19 in Sao Paulo State, Brazil. Overall, the impact of social distancing both on incidence and Rt was greater than the incremental effect of mandatory masking. Those findings may reflect either a small impact of face masking or the loosening of social distancing after mandatory use of masks.", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.23.20180356", + "rel_abs": "BackgroundMost studies of the epidemic cycles of the pandemic of Sars-CoV-2, or COVID-19 as it became known, define the beginning of specific cycles in countries from the laboratory identification of the first cases of infection, however, there is the awareness that cycles may have started earlier, without proper identification. This influences all the parameters that govern the statistical models used for controlling the infection.\n\nPurposeThis work proposes two models based on experimental data. The Logistic Model it is used to obtain three parameters of the epidemic cycle of COVID-19, namely: the final count for the total infected, the daily infection rate and the lag time. Complimentary, a novel inventory model is proposed to calculate the number of infective persons, as well as to determine the incubation period.\n\nMethodsThe data on epidemic cycles of Germany, Italy, and Sweden are treated previously by the Moving Average Method with Initial value (MAMI), then a variation of the Logistic Model, obtained through curve-fitting, is used to obtain the three parameters. The inventory model is introduced to calculate the actual number of infected persons and the behavior of the incubation period is analyzed.\n\nResultsAfter comparing data from the three countries it is possible to determine the actual probable dates of the beginning of the epidemic cycles for each one, determine the size of the incubation period, as well as to determine the total number of infective persons during the cycle.\n\nConclusionsThe actual probable dates of the beginning of the epidemic cycles in the countries analyzed are determined, the total number of infected is determined, and it is statistically proven that the incubation cycle for Sars-CoV-2 is five days.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Cristiane Ravagnani Fortaleza", - "author_inst": "Department of Infectious Diseases, Botucatu School of Medicine, S\u00e3o Paulo State University (UNESP). City of Botucatu, Brazil." - }, - { - "author_name": "Thomas Nogueira Vilches", - "author_inst": "Department of Biostatistics, Botucatu Institute of Biosciences, S\u00e3o Paulo State University (UNESP). City of Botucatu, Brazil." - }, - { - "author_name": "Gabriel Berg de Almeida", - "author_inst": "Department of Infectious Diseases, Botucatu School of Medicine, S\u00e3o Paulo State University (UNESP). City of Botucatu, Brazil." - }, - { - "author_name": "Claudia Pio Ferreira", - "author_inst": "Department of Biostatistics, Botucatu Institute of Biosciences, S\u00e3o Paulo State University (UNESP). City of Botucatu, Brazil." - }, - { - "author_name": "Rejane Maria Tommasini Grotto", - "author_inst": "Faculty of Agronomical Sciences, S\u00e3o Paulo State University (UNESP). City of Botucatu, Brazil." - }, - { - "author_name": "Raul Borges Guimar\u00e3es", - "author_inst": "Department of Geography, Faculty of Science and Technology, S\u00e3o Paulo State University (UNESP). City of Presidente Prudente, Brazil." - }, - { - "author_name": "Lenice do Ros\u00e1rio de Souza", - "author_inst": "Department of Infectious Diseases, Botucatu School of Medicine, S\u00e3o Paulo State University (UNESP). City of Botucatu, Brazil." + "author_name": "Rogerio Atem De Carvalho", + "author_inst": "Instituto Federal Fluminense" }, { - "author_name": "Carlos Magno Castelo Branco Fortaleza", - "author_inst": "Department of Infectious Diseases, Botucatu School of Medicine, S\u00e3o Paulo State University (UNESP). City of Botucatu, Brazil." + "author_name": "Eduardo Atem De Carvalho", + "author_inst": "Universidade Estadual do Norte Fluminense" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1213947,89 +1214640,37 @@ "category": "bioinformatics" }, { - "rel_doi": "10.1101/2020.08.25.266775", - "rel_title": "The S1/S2 boundary of SARS-CoV-2 spike protein modulates cell entry pathways and transmission", + "rel_doi": "10.1101/2020.08.25.265223", + "rel_title": "In Vitro Inactivation of Human Coronavirus by Titania Nanoparticle Coatings and UVC Radiation: Throwing Light on SARS-CoV-2", "rel_date": "2020-08-25", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.08.25.266775", - "rel_abs": "The global spread of SARS-CoV-2 is posing major public health challenges. One unique feature of SARS-CoV-2 spike protein is the insertion of multi-basic residues at the S1/S2 subunit cleavage site, the function of which remains uncertain. We found that the virus with intact spike (Sfull) preferentially enters cells via fusion at the plasma membrane, whereas a clone (Sdel) with deletion disrupting the multi-basic S1/S2 site instead utilizes a less efficient endosomal entry pathway. This idea was supported by the identification of a suite of endosomal entry factors specific to Sdel virus by a genome-wide CRISPR-Cas9 screen. A panel of host factors regulating the surface expression of ACE2 was identified for both viruses. Using a hamster model, animal-to-animal transmission with the Sdel virus was almost completely abrogated, unlike with Sfull. These findings highlight the critical role of the S1/S2 boundary of the SARS-CoV-2 spike protein in modulating virus entry and transmission.", - "rel_num_authors": 18, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.08.25.265223", + "rel_abs": "The newly identified pathogenic human coronavirus, SARS-CoV-2, led to an atypical pneumonia-like severe acute respiratory syndrome (SARS) outbreak called coronavirus disease 2019 (COVID-19). Currently, nearly 23 million cases have been confirmed worldwide with the highest COVID-19 cases been confirmed in the United States. As there is no vaccine or any effective interventions, massive efforts to create a postential vaccine to combat COVID-19 is underway. In the meantime, safety precautions and effective disease control strategies appear to be vital for preventing the virus spread in the public places. Due to the longevity of the virus on smooth surfaces, photocatalytic properties of self-disinfecting/cleaning surfaces appear to be a promising tool to help guide disinfection policies to control infectious SAR-CoV-2 spread in high-traffic areas such as hospitals, grocery stores, airports, schools, and stadiums. Here, we explored the photocatalytic properties of nanosized TiO2 (TNPs) as induced by the UV radiation, towards virus deactivation. Our preliminary results using close genetic relative of SAR-CoV-2, HCoV-NL63, showed the virucidal efficacy of photoactive TNPs deposited on glass coverslips, as examined by quantitative RT-PCR and virus culture assays. Efforts to extrapolate the underlying concepts described in this study to SARS-CoV-2 are currently underway.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Yunkai Zhu", - "author_inst": "Fudan University Shanghai Medical College" - }, - { - "author_name": "Fei Feng", - "author_inst": "Fudan University Shanghai Medical College" - }, - { - "author_name": "Gaowei Hu", - "author_inst": "Fudan University Shanghai Medical College" - }, - { - "author_name": "Yuyan Wang", - "author_inst": "Fudan University Shanghai Medical College" - }, - { - "author_name": "Yin Yu", - "author_inst": "Fudan University Shanghai Medical College" - }, - { - "author_name": "Yuanfei Zhu", - "author_inst": "Fudan University Shanghai Medical College" - }, - { - "author_name": "Wei Xu", - "author_inst": "Fudan University Shanghai Medical College" - }, - { - "author_name": "Xia Cai", - "author_inst": "Fudan University Shanghai Medical College" - }, - { - "author_name": "Zhiping Sun", - "author_inst": "Fudan University Shanghai Medical College" - }, - { - "author_name": "Wendong Han", - "author_inst": "Fudan University Shanghai Medical College" - }, - { - "author_name": "Rong Ye", - "author_inst": "Fudan University Shanghai Medical College" - }, - { - "author_name": "Hongjun Chen", - "author_inst": "Shanghai Veterinary Research Institute" - }, - { - "author_name": "Qiang Ding", - "author_inst": "Tsinghua University" - }, - { - "author_name": "Qiliang Cai", - "author_inst": "Fudan University Shanghai Medical College" + "author_name": "Svetlana Khaiboullina", + "author_inst": "University of Nevada, Reno School of Medicine" }, { - "author_name": "Di Qu", - "author_inst": "Fudan University Shanghai Medical College" + "author_name": "Timsy Uppal", + "author_inst": "University of Nevada, Reno School of Medicine" }, { - "author_name": "Youhua Xie", - "author_inst": "Fudan University Shanghai Medical College" + "author_name": "Nikhil Dhabarde", + "author_inst": "Chemical and Materials Engineering Department, University of Nevada, Reno" }, { - "author_name": "Zhenghong Yuan", - "author_inst": "Fudan University Shanghai Medical College" + "author_name": "Vaidyanathan Subramanian", + "author_inst": "Chemical and Materials Engineering Department, University of Nevada, Reno and GenNEXT Materials and Technologies, LLC" }, { - "author_name": "Rong Zhang", - "author_inst": "Fudan University Shanghai Medical College" + "author_name": "Subhash C Verma", + "author_inst": "University of Nevada, Reno, School of Medicine" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "new results", "category": "microbiology" }, @@ -1215713,51 +1216354,27 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2020.08.21.20179473", - "rel_title": "The unintended consequences of inconsistent pandemic control policies", + "rel_doi": "10.1101/2020.08.22.20179770", + "rel_title": "The impact of COVID-19 on acute Trauma and Orthopaedic referrals and surgery in the UK: the \"golden peak weeks\" of the first national multi-centre observational study. The COVid-Emergency Related Trauma and orthopaedics (COVERT) Collaborative", "rel_date": "2020-08-24", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.21.20179473", - "rel_abs": "Controlling the spread of COVID-19 - even after a licensed vaccine is available - requires the effective use of non-pharmaceutical interventions, e.g., physical distancing, limits on group sizes, mask wearing, etc.. To date, such interventions have neither been uniformly nor systematically implemented in most countries. For example, even when under strict stay-at-home orders, numerous jurisdictions granted exceptions and/or were in close proximity to locations with entirely different regulations in place. Here, we investigate the impact of such geographic inconsistencies in epidemic control policies by coupling search and mobility data to a simple mathematical model of SARS-COV2 transmission. Our results show that while stay-at-home orders decrease contacts in most areas of the United States of America (US), some specific activities and venues often see an increase in attendance. Indeed, over the month of March 2020, between 10 and 30% of churches in the US saw increases in attendance; even as the total number of visits to churches declined nationally. This heterogeneity, where certain venues see substantial increases in attendance while others close, suggests that closure can cause individuals to find an open venue, even if that requires longer-distance travel. And, indeed, the average distance travelled to churches in the US rose by 13% over the same period. Strikingly, our mathematical model reveals that, across a broad range of model parameters, partial measures can often be worse than no measures at all. In the most severe cases, individuals not complying with policies by traveling to neighboring jurisdictions can create epidemics when the outbreak would otherwise have been controlled. Taken together, our data analysis and modelling results highlight the potential unintended consequences of inconsistent epidemic control policies and stress the importance of balancing the societal needs of a population with the risk of an outbreak growing into a large epidemic.", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.22.20179770", + "rel_abs": "ObjectivesThis is the first national study observing the impact of the COVID-19 pandemic on orthopaedic trauma with respect to referrals, operative caseload and mortality during the first six weeks (namely the \"golden peak weeks\") following the introduction of the national social distancing and lockdown measures from mid-March 2020.\n\nDesignA longitudinal, national, multi-centre, retrospective, observational, cohort study was conducted for the first six weeks from March 17, 2020 from start of the national social distancing and then lockdown compared to the same period in 2019 as a comparative baseline.\n\nSettingHospitals from seven major urban cities were recruited around the UK, including London, representing a comprehensive national picture of the impact of COVID-19 pandemic and its lockdown at its peak.\n\nParticipantsA total of 4840 clinical encounters were initially recorded. Exclusion criterion consisted of spinal pathology only. Post-exclusion, 4668 clinical encounters were recorded and analysed within the two timeframes.\n\nMain outcome measuresPrimary outcomes included the number of acute trauma referrals and those undergoing operative intervention, patient demographics, mortality rates, and the proportion of patients contracting COVID-19. Secondary outcomes consisted of the mechanism of injury, type of operative intervention and proportion of aerosolising-generating anaesthesia utilised. Demographics for each patient was recorded along with underlying medical co-morbidities. Sub-group analysis compared mortalities between both cohorts. Statistical analyses included mean ({+/-}SD), risk and odds ratios, as well as Fishers exact test to calculate the statistical significance (p[≤]0.05).\n\nResultsDuring the COVID-19 period there was a 34% reduction in acute orthopaedic trauma referrals compared to 2019 (1792 down to 1183 referrals), and 29.5% less surgical interventions (993 down to 700 operations). The mortality rate significantly (both statistically and clinically) more than doubled for both risk and odds ratios during the COVID period in all referrals (1.3% vs 3.8%, p = 0.0005) and in those undergoing operative intervention (2.2% vs 4.9%, p = 0.004). Moreover, mortality due to COVID-related complications (versus non-COVID causes) had greater odds by a factor of at least 20 times. The odds ratios of road traffic accidents, sporting injuries, infection, and lower limb injuries were significantly less (by a third to a half) during the COVID period; albeit, the odds of sustaining neck of femur fractures and having falls < 1.5m increased by more than 50%.\n\nFor the operative cohorts, there was a greater odds of aerosolising-generating anaesthesia (including those with superimposed regional blocks) by three-quarters as well as doubling of the odds of a Consultant acting as the primary surgeon. Nevertheless, the odds of open reduction and internal fixation reduced by a quarter whereas removal of metalwork or foreign bodies reduced by three-quarters. Six-week Kaplan-Meier survival probability analysis confirmed those patients with neck of femur fracture and pre-existing cardiovascular and cerebrovascular disease were most at risk of mortality during the COVID-19 era.\n\nConclusionAlthough there was a reduction of acute trauma referrals and those undergoing operative intervention, the mortality rate still more than doubled in odds during the peak of the pandemic compared to the same time interval one year ago. Elderly patients with neck of femur fractures and existing cardiovascular and cerebrovascular comorbidities were at the highest risk stratification for mortality. This was the first national study to assess impact of COVID-19 pandemic on acute Orthopaedic trauma and it will aid clinicians in counselling trauma patients of the increased risk of mortality during the era of COVID-19 as well as acting as a risk-prediction tool influencing policymaking as the pandemic continues with potential subsequent waves. Further studies after the lifting of the lockdown are also required to observe for return of standard practice.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Benjamin Muir Althouse", - "author_inst": "Institute for Disease Modeling" - }, - { - "author_name": "Brendan Wallace", - "author_inst": "University of Washington" - }, - { - "author_name": "Brendan Case", - "author_inst": "University of Vermont" - }, - { - "author_name": "Samuel V Scarpino", - "author_inst": "Northeastern University" - }, - { - "author_name": "Antoine Allard", - "author_inst": "Universite Laval" - }, - { - "author_name": "Andrew Berdhal", - "author_inst": "University of Washington" - }, - { - "author_name": "Easton R White", - "author_inst": "University of Vermont" + "author_name": "Kapil Sugand", + "author_inst": "Imperial College London" }, { - "author_name": "Laurent Hebert-Dufresne", - "author_inst": "University of Vermont" + "author_name": "- COVERT Collaborative", + "author_inst": "" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "orthopedics" }, { "rel_doi": "10.1101/2020.08.21.20178855", @@ -1217363,35 +1217980,87 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2020.08.19.20177477", - "rel_title": "Machine learning based clinical decision supportsystem for early COVID-19 mortality prediction", + "rel_doi": "10.1101/2020.08.19.20178095", + "rel_title": "Seroprevalence of Coronavirus Disease 2019 (COVID-19) Among Health Care Workers from Three Pandemic Hospitals of Turkey", "rel_date": "2020-08-22", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.19.20177477", - "rel_abs": "The coronavirus disease 2019 (COVID-19) is an acute respiratory disease that has been classified as a pandemic by World Health Organization (WHO). The sudden spike in the number of infections and high mortality rates have put immense pressure on the public medical systems. Hence, its crucial to identify the key factors of mortality that yield high accuracy and consistency to optimize patient treatment strategy. This study uses machine learning methods to identify a powerful combination of five features that help predict mortality with 96% accuracy: neutrophils, lymphocytes, lactate dehydrogenase (LDH), high-sensitivity C-reactive protein (hs-CRP) and age. Various machine learning algorithms have been compared to achieve a consistent high accuracy across the days that span the disease. Robust testing with three cases confirm the strong predictive performance of the proposed model. The model predicts with an accuracy of 90% as early as 16 days before the outcome. This study would help accelerate the decision making process in healthcare systems for focused medical treatments early and accurately.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.19.20178095", + "rel_abs": "COVID-19 is a global threat with an increasing number of infections. Research on IgG seroprevalence among health care workers (HCWs) is needed to re-evaluate health policies. This study was performed in three pandemic hospitals in Istanbul and Kocaeli. Different clusters of HCWs were screened for SARS-CoV-2 infection. Seropositivity rate among participants was evaluated by chemiluminescent microparticle immunoassay. We recruited 813 non-infected and 119 PCR-confirmed infected HCWs. Of the previously undiagnosed HCWs, 22 (2.7%) were seropositive. Seropositivity rates were highest for cleaning staff (6%), physicians (4%), nurses (2.2%) and radiology technicians (1%). Non-pandemic clinic (6.4%) and ICU (4.3%) had the highest prevalence. HCWs in \"high risk group\" had similar seropositivity rate with \"no risk\" group (2.9 vs 3.6 p=0.7), indicating the efficient implementation of protection measures in the hospitals in Turkey. These findings might lead to the re-evaluation of infection control and transmission dynamics in hospitals.", + "rel_num_authors": 17, "rel_authors": [ { - "author_name": "Akshaya Karthikeyan", - "author_inst": "Center for Computational Natural Sciences and Bioinformatics, International Institute of Information Technology, Hyderabad" + "author_name": "Gizem ALKURT", + "author_inst": "Genomic Laboratory (GLAB), Umraniye Teaching and Research Hospital, University of Health Sciences" }, { - "author_name": "Akshit Garg", - "author_inst": "Center for Computational Natural Sciences and Bioinformatics, International Institute of Information Technology, Hyderabad" + "author_name": "Ahmet MURT", + "author_inst": "Department of Nephrology, Cerrahpasa Faculty of Medicine, Istanbul University-Cerrahpasa" }, { - "author_name": "P K Vinod", - "author_inst": "Center for Computational Natural Sciences and Bioinformatics, International Institute of Information Technology, Hyderabad" + "author_name": "Zeki AYDIN", + "author_inst": "Department of Nephrology, Darica Farabi Teaching and Research Hospital" }, { - "author_name": "U. Deva Priyakumar", - "author_inst": "Center for Computational Natural Sciences and Bioinformatics, International Institute of Information Technology, Hyderabad" + "author_name": "Ozge TATLI", + "author_inst": "Department of Molecular Biology and Genetics, Istanbul Technical University" + }, + { + "author_name": "Nihat Bugra AGAOGLU", + "author_inst": "Genomic Laboratory (GLAB), Umraniye Teaching and Research Hospital, University of Health Sciences" + }, + { + "author_name": "Arzu IRVEM", + "author_inst": "Department of Microbiology, Umraniye Teaching and Research Hospital, University of Health Sciences" + }, + { + "author_name": "Mehtap AYDIN", + "author_inst": "Department of Infectious Disease, Umraniye Teaching and Research Hospital, University of Health Sciences" + }, + { + "author_name": "Ridvan KARAALI", + "author_inst": "Department of Infectious Disease, Cerrahpasa Faculty of Medicine, Istanbul University-Cerrahpasa" + }, + { + "author_name": "Mustafa GUNES", + "author_inst": "Department of Urology, Darica Farabi Teaching and Research Hospital" + }, + { + "author_name": "Batuhan YESILYURT", + "author_inst": "Health Institutes of Turkey (TUSEB)" + }, + { + "author_name": "Hasan TURKEZ", + "author_inst": "Department of Medical Biology, Faculty of Medicine, Ataturk University" + }, + { + "author_name": "Adil MARDINOGLU", + "author_inst": "Science for Life Laboratory, KTH Royal Institute of Technology, Stockholm, Sweden and Centre for Host-Microbiome Interactions, Faculty of Dentistry, Oral & Cran" + }, + { + "author_name": "Mehmet DOGANAY", + "author_inst": "Department of Infectious Diseases, Erciyes University" + }, + { + "author_name": "Filiz BASINOGLU", + "author_inst": "Department of Medical Biochemistry, Darica Farabi Teaching and Research Hospital" + }, + { + "author_name": "Nurhan SEYAHI", + "author_inst": "Department of Nephrology, Cerrahpasa Faculty of Medicine, Istanbul University-Cerrahpasa" + }, + { + "author_name": "Gizem DINLER DOGANAY", + "author_inst": "Department of Molecular Biology and Genetics, Istanbul Technical University" + }, + { + "author_name": "Levent DOGANAY", + "author_inst": "University of Health Sciences, Umraniye Teaching and Research Hospital" } ], "version": "1", "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "health informatics" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2020.08.19.20171868", @@ -1218765,63 +1219434,63 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.08.20.20178541", - "rel_title": "COVID-19 Pandemic Preparedness in a United Kingdom Tertiary and Quaternary Children`s Hospital: Tales of the Unexpected", + "rel_doi": "10.1101/2020.08.20.20178566", + "rel_title": "Development of antibodies to pan-coronavirus spike peptides in convalescent COVID-19 patients", "rel_date": "2020-08-22", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.20.20178541", - "rel_abs": "BackgroundThe paucity of data describing SARS-CoV-2 in the paediatric population necessitated a broad-arching approach to pandemic planning, with preparations put in place to manage a heterogeneous cohort. We describe a diverse group of SARS-CoV-2 positive paediatric patients treated at a large tertiary/quaternary childrens hospital in the United Kingdom and the adaptive coping strategies required.\n\nMethodsAll paediatric patients with positive RT-PCR on a respiratory sample and/or serology for SARS-CoV-2 up to 19th May 2020 were included.\n\nResults57 children met the inclusion criteria. 70% were of non-Caucasian ethnicity with a median age of 9.3 years (IQR 5.16-13.48). Four distinct groups were identified: paediatric inflammatory multisystem syndrome temporally associated with SARS-CoV-2 (PIMS-TS) (54%), primary respiratory (18%), incidental (7%), and non-specific febrile illnesses with or without extra-pulmonary organ dysfunction (21%). These groups presented in distinct chronological blocks as the pandemic unfolded.\n\nDiscussionThe diverse range of presentations of SARS-CoV-2 infection in this population exemplified the importance of preparedness for the unknown in the midst of a novel infectious pandemic. Descriptions of paediatric patients during the initial phase of the pandemic from other parts of the globe and extrapolation from adult data did not serve as an accurate representation of paediatric COVID-19 in our centre. An adaptive, multidisciplinary approach was paramount. Expanded laboratory testing and incorporation of technology platforms to facilitate remote collaboration in response to strict infection control precautions were both indispensable. Lessons learned during the preparation process will be essential in planning for a potential second wave of SARS-CoV-2.", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.20.20178566", + "rel_abs": "Coronaviruses are sharing several protein regions notable the spike protein (S) on their enveloped membrane surface, with the S1 subunit recognizing and binding to the cellular receptor, while the S2 subunit mediates viral and cellular membrane fusion. This similarity opens the question whether infection with one coronavirus will confer resistance to other coronaviruses? Investigating patient serum samples after SARS-CoV-2 infection in cross-reactivity studies of immunogenic peptides from Middle East respiratory syndrome coronavirus (MERS-CoV), we were able to detect the production of antibodies also recognizing MERS virus antigens. The cross-reactive peptide comes from the heptad repeat 2 (HR2) domain of the MERS virus spike protein. Indeed, the peptide of the HR2 domain of the MERS spike protein, previously proven to induce antibodies against MERS-CoV is sharing 74% homology with the corresponding sequence of SARS-CoV-19 virus. Sera samples of 47 convalescent SARS-CoV-2 patients, validated by RT-PCR-negative testes 30 days post-infection, and samples of 40 sera of control patients (not infected with SARS-CoV-2 previously) were used to establish eventual cross-bind reactivity with the MERS peptide antigen. Significantly stronger binding (p< 0.0001) was observed for IgG antibodies in convalescent SARS-CoV-2 patients compared to the control group. If used as an antigen, the peptide of the HR2 domain of the MERS spike protein allows discrimination between post-Covid populations from non-infected ones by the presence of antibodies in blood samples. This suggests that polyclonal antibodies established during SARS-CoV-2 infection has the ability to recognize and probably decrease infectiveness of MERS-CoV infections as well as other coronaviruses. The high homology of the spike protein domain suggests in addition that the opposite effect can also be true: coronaviral infections producing cross-reactive antibodies affective against SARS-CoV-19. The collected data prove in addition that despite the core HR2 region being hidden in the native viral conformation, its exposure during cell entry makes it highly immunogenic. Since inhibitory peptides to this region were previously described, this opens new possibilities in fighting coronaviral infections.", "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Nele Alders", - "author_inst": "Great Ormond Street Hospital" + "author_name": "Andrii Rabets", + "author_inst": "Danylo Halytsky Lviv National Medical University" }, { - "author_name": "Justin Penner", - "author_inst": "Justin.Penner@nhs.net" + "author_name": "Galyna Bila", + "author_inst": "Danylo Halytsky Lviv National Medical University" }, { - "author_name": "Karlie Grant", - "author_inst": "Department of Infectious Diseases, Great Ormond Street Hospital for Children, Great Ormond Street Hospital for Children NHS Foundation Trust, London, UK" + "author_name": "Roman Grytsko", + "author_inst": "Danylo Halytsky Lviv National Medical University" }, { - "author_name": "Charlotte Patterson", - "author_inst": "Department of Microbiology, Great Ormond Street Hospital for Children, Great Ormond Street Hospital for Children NHS Foundation Trust, London, UK" + "author_name": "Markian Samborsky", + "author_inst": "Explogen LLC" }, { - "author_name": "Jane Hassell", - "author_inst": "Department of Neurology, Great Ormond Street Hospital for Children, Great Ormond Street Hospital for Children NHS Foundation Trust, London, UK" + "author_name": "Yuriy Rebets", + "author_inst": "Explogen LLC" }, { - "author_name": "Nathalie MacDermott", - "author_inst": "Department of Infectious Diseases, Great Ormond Street Hospital for Children, Great Ormond Street Hospital for Children NHS Foundation Trust, London, UK" + "author_name": "Sandor Vari", + "author_inst": "International Research and Innovation in Medicine Program, Cedars-Sinai Medical Center" }, { - "author_name": "Sian Pincott", - "author_inst": "Department of General Paediatrics, Great Ormond Street Hospital for Children, Great Ormond Street Hospital for Children NHS Foundation Trust, London, UK" + "author_name": "Quentin Pagneux", + "author_inst": "Univ. Lille, CNRS, Centrale Lille, Univ. Polytechnique Hauts-de-France, UMR 8520 - IEMN" }, { - "author_name": "Alasdair Bamford", - "author_inst": "Department of Infectious Diseases, Great Ormond Street Hospital for Children, Great Ormond Street Hospital for Children NHS Foundation Trust, London, UK" + "author_name": "Alexandre Barras", + "author_inst": "Univ. Lille, CNRS, Centrale Lille, Univ. Polytechnique Hauts-de-France, UMR 8520 - IEMN" }, { - "author_name": "Pascale du Pre", - "author_inst": "Department of Intensive Care, Great Ormond Street Hospital for Children, Great Ormond Street Hospital for Children NHS Foundation Trust, London, UK" + "author_name": "Rabah Boukherroub", + "author_inst": "Univ. Lille, CNRS, Centrale Lille, Univ. Polytechnique Hauts-de-France, UMR 8520 - IEMN" }, { - "author_name": "Mae Johnson", - "author_inst": "Department of Intensive Care, Great Ormond Street Hospital for Children, Great Ormond Street Hospital for Children NHS Foundation Trust, London, UK" + "author_name": "Sabine Szunerits", + "author_inst": "Univ. Lille, CNRS, Centrale Lille, Univ. Polytechnique Hauts-de-France, UMR 8520 - IEMN" }, { - "author_name": "Karyn Moshal", - "author_inst": "Department of Infectious Diseases, Great Ormond Street Hospital for Children, Great Ormond Street Hospital for Children NHS Foundation Trust, London, UK" + "author_name": "Rostyslav Bilyy", + "author_inst": "Danylo Halytsky Lviv National Medical University" } ], "version": "1", "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "allergy and immunology" }, { "rel_doi": "10.1101/2020.08.20.20178558", @@ -1220571,43 +1221240,43 @@ "category": "neuroscience" }, { - "rel_doi": "10.1101/2020.08.19.257022", - "rel_title": "Targeting pentose phosphate pathway for SARS-CoV-2 therapy", + "rel_doi": "10.1101/2020.08.20.259721", + "rel_title": "Temporal landscape of mutation accumulation in SARS-CoV-2 genomes from Bangladesh: possible implications from the ongoing outbreak in Bangladesh", "rel_date": "2020-08-21", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.08.19.257022", - "rel_abs": "It becomes more and more obvious that deregulation of host metabolism play an important role in SARS-CoV-2 pathogenesis with implication for increased risk of severe course of COVID-19. Furthermore, it is expected that COVID-19 patients recovered from severe disease may experience long-term metabolic disorders. Thereby understanding the consequences of SARS-CoV-2 infection on host metabolism can facilitate efforts for effective treatment option. We have previously shown that SARS-CoV-2-infected cells undergo a shift towards glycolysis and that 2-deoxy-D-glucose (2DG) inhibits SARS-CoV-2 replication. Here, we show that also pentose phosphate pathway (PPP) is remarkably deregulated. Since PPP supplies ribonucleotides for SARS-CoV-2 replication, this could represent an attractive target for an intervention. On that account, we employed the transketolase inhibitor benfooxythiamine and showed dose-dependent inhibition of SARS-CoV-2 in non-toxic concentrations. Importantly, the antiviral efficacy of benfooxythiamine was further increased in combination with 2DG.", + "rel_link": "https://biorxiv.org/cgi/content/short/2020.08.20.259721", + "rel_abs": "Along with intrinsic evolution, adaptation to selective pressure in new environments might have resulted in the circulatory SARS-CoV-2 strains in response to the geoenvironmental conditions of a country and the demographic profile of its population. Thus the analysis of genomic mutations of these circulatory strains may give an insight into the molecular basis of SARS-CoV-2 pathogenesis and evolution favoring the development of effective treatment and containment strategies. With this target, the current study traced the evolutionary route and mutational frequency of 198 Bangladesh originated SARS-CoV-2 genomic sequences available in the GISAID platform over a period of 13 weeks as of 14 July 2020. The analyses were performed using MEGA 7, Swiss Model Repository, Virus Pathogen Resource and Jalview visualization. Our analysis identified that majority of the circulating strains in the country belong to B and/or L type among cluster A to Z and strikingly differ from both the reference genome and the first sequenced genome from Bangladesh. Mutations in Nonspecific protein 2 (NSP2), NSP3, RNA dependent RNA polymerase (RdRp), Helicase, Spike, ORF3a, and Nucleocapsid (N) protein were common in the circulating strains with varying degrees and the most unique mutations(UM) were found in NSP3 (UM-18). But no or limited changes were observed in NSP9, NSP11, E (Envelope), NSP7a, ORF 6, and ORF 7b suggesting the possible conserved functions of those proteins in SARS-CoV-2 propagation. However, along with D614G mutation, more than 20 different mutations in the Spike protein were detected basically in the S2 domain. Besides, mutations in SR-rich region of N protein and P323L in RDRP were also present. However, the mutation accumulation showed an association with sex and age of the COVID-19 positive cases. So, identification of these mutational accumulation patterns may greatly facilitate drug/ vaccine development deciphering the age and the sex dependent differential susceptibility to COVID-19.", "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Denisa Bojkova", - "author_inst": "Institute of Medical Virology" + "author_name": "Otun Saha", + "author_inst": "Dhaka University" }, { - "author_name": "Rui Costa", - "author_inst": "Department of Infectious Diseases" + "author_name": "Rokaiya Nurani Shatadru", + "author_inst": "University of Dhaka" }, { - "author_name": "Marco Bechtel", - "author_inst": "Institute of Medical Virology" + "author_name": "Nadira Naznin Rakhi", + "author_inst": "Bangabandhu Sheikh Mujibur Rahman Science and Technology University" }, { - "author_name": "Sandra Ciesek", - "author_inst": "Goethe Universtiy Frankfurt" + "author_name": "Israt Islam", + "author_inst": "University of Dhaka" }, { - "author_name": "Martin Michaelis", - "author_inst": "University of Kent" + "author_name": "Md. Shahadat Hossain", + "author_inst": "Noakhali Science and Technology University" }, { - "author_name": "Jindrich Cinatl Jr.", - "author_inst": "Klinikum der Goethe-Universitaet" + "author_name": "Md. Mizanur Rahaman", + "author_inst": "University of Dhaka" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nc", "type": "new results", - "category": "microbiology" + "category": "bioinformatics" }, { "rel_doi": "10.1101/2020.08.21.261347", @@ -1222201,35 +1222870,47 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.08.18.20177345", - "rel_title": "Time-use and mental health during the COVID-19 pandemic: a panel analysis of 55,204 adults followed across 11 weeks of lockdown in the UK", + "rel_doi": "10.1101/2020.08.19.225854", + "rel_title": "Iota carrageenan and xylitol inhibit SARS-CoV-2 in Vero cell culture", "rel_date": "2020-08-21", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.18.20177345", - "rel_abs": "There is currently major concern about the impact of the global COVID-19 outbreak on mental health. But it remains unclear how individual behaviors could exacerbate or protect against adverse changes in mental health. This study aimed to examine the associations between specific activities (or time-use) and mental health and wellbeing amongst people during the Covid-19 pandemic. Data were from the UCL COVID-19 Social Study; a panel study collecting data weekly during the COVID-19 pandemic. The analytical sample consisted of 55,204 adults living in the UK who were followed up for the strict 11-week lockdown period from 21st March to 31st May 2020. Data were analyzed using fixed-effects and Arellano-Bond models. We found that changes in time spent on a range of activities were associated with changes in mental health and wellbeing. After controlling for bidirectionality, behaviors involving outdoor activities including gardening and exercising predicted subsequent improvements in mental health and wellbeing, while increased time spent on following news about COVID-19 predicted declines in mental health and wellbeing. These results are relevant to the formulation of guidance for people obliged to spend extended periods in isolation during health emergencies, and may help the public to maintain wellbeing during future pandemics.", - "rel_num_authors": 4, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2020.08.19.225854", + "rel_abs": "COVID-19 (coronavirus disease 2019) is a pandemic caused by SARS-CoV-2 (severe acute respiratory syndrome-coronavirus 2) infection affecting millions of persons around the world. There is an urgent unmet need to provide an easy-to-produce, affordable medicine to prevent transmission and provide early treatment for this disease. The nasal cavity and the rhinopharynx are the sites of initial replication of SARS-CoV-2. Therefore, a nasal spray may be a suitable dosage form for this purpose. The main objective of our study was to test the antiviral action of three candidate nasal spray formulations against SARS-CoV-2. We have found that iota-carrageenan in concentrations as low as 6 {micro}g/ mL inhibits SARS-CoV-2 infection in Vero cell cultures. The concentrations found to be active in vitro against SARS-CoV-2 may be easily achieved by the application of nasal sprays already marketed in several countries. Xylitol at a concentration of 5 % m/V has proved to be viricidal on its own and the association with iota-carrageenan may be beneficial, as well.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Feifei Bu", - "author_inst": "University College London" + "author_name": "Julio Cesar Vega", + "author_inst": "Amcyte Pharma Inc." }, { - "author_name": "Andrew Steptoe", - "author_inst": "University College London" + "author_name": "Shruti Bansal", + "author_inst": "Regional Biocontainment laboratory, University of Tennessee Health Science Center, Memphis, Tennessee, United States of America" }, { - "author_name": "Hei Wan Mak", - "author_inst": "University College London" + "author_name": "Colleen B. Jonsson", + "author_inst": "University of Tennessee Health Science Center" }, { - "author_name": "Daisy Fancourt", - "author_inst": "University College London" + "author_name": "Shannon L. Taylor", + "author_inst": "LogixBio, Holly Springs, North Carolina, United States of America" + }, + { + "author_name": "Juan M Figueroa", + "author_inst": "Fundacion Pablo Cassara, Argentina" + }, + { + "author_name": "Andrea V. Dugour", + "author_inst": "Fundacion Pablo Cassara, Argentina" + }, + { + "author_name": "Carlos Palacios", + "author_inst": "Fundacion Pablo Cassara, Argentina" } ], "version": "1", - "license": "cc_by", - "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "license": "cc_no", + "type": "new results", + "category": "pharmacology and toxicology" }, { "rel_doi": "10.1101/2020.08.18.20175521", @@ -1224211,27 +1224892,55 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2020.08.18.256735", - "rel_title": "Identification of potential key genes for SARS-CoV-2 infected human bronchial organoids based on bioinformatics analysis", - "rel_date": "2020-08-19", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.08.18.256735", - "rel_abs": "There is an urgent need to understand the pathogenesis of the severe acute respiratory syndrome coronavirus clade 2 (SARS-CoV-2) that leads to COVID-19 and respiratory failure. Our study is to discover differentially expressed genes (DEGs) and biological signaling pathways by using a bioinformatics approach to elucidate their potential pathogenesis. The gene expression profiles of the GSE150819 datasets were originally produced using an Illumina NextSeq 500 (Homo sapiens). KEGG (Kyoto Encyclopedia of Genes and Genomes) and GO (Gene Ontology) were utilized to identify functional categories and significant pathways. KEGG and GO results suggested that the Cytokine-cytokine receptor interaction, P53 signaling pathway, and Apoptosis are the main signaling pathways in SARS-CoV-2 infected human bronchial organoids (hBOs). Furthermore, NFKBIA, C3, and CCL20 may be key genes in SARS-CoV-2 infected hBOs. Therefore, our study provides further insights into the therapy of COVID-19.", - "rel_num_authors": 2, + "rel_doi": "10.1101/2020.08.17.20176586", + "rel_title": "Risk factors associated with morbidity and mortality outcomes of COVID-19 patients on the 14th and 28th day of the disease course: a retrospective cohort study in Bangladesh", + "rel_date": "2020-08-18", + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.17.20176586", + "rel_abs": "SummaryDiverse risk factors intercede the outcomes of COVID-19. We conducted this retrospective cohort study to identify the risk factors associated with morbidity and mortality outcomes with a cohort of 1016 COVID-19 patients diagnosed in May 2020. Data were collected by telephone-interview and reviewing records using a questionnaire and checklist. Morbidity (64.4% Vs. 6.0%) and mortality (2.3% Vs. 2.5%) outcomes varied between the 14th and 28th day. Morbidity risk factors included chronic obstructive pulmonary disease (COPD) (RR=1.19, RR=2.68) both on the 14th and 18th day while elderly (AOR=2.56) and smokeless tobacco (SLT) (AOR=2.17) on the 28th day. Mortality risk factors included elderly (AOR=10.14), COPD (RR=5.93), and SLT (AOR=2.25) on the 14th day, and elderly (AOR=24.37) and COPD (RR=2.72) on the 28th day. The morbidity risk was higher with chronic kidney disease (CKD) (RR=3.33) and chronic liver disease (CLD) (RR=3.99) on the 28th day. The mortality risk was higher with coronary heart disease (RR=4.54) and CLD (RR=9.66) on the 14th while with diabetes mellitus (RR=3.08, RR=2.08), hypertension (RR=3.14, RR=2.30), CKD (RR=8.97, RR=2.71), and malignant diseases (RR=10.29) on both 14th and 28th day. We must espouse program interventions considering the morbidity and mortality risk factors to condense the aggressive outcomes of COVID-19.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Hanming Gu", - "author_inst": "SHU-UTS SILC Business School, Shanghai University, Shanghai, China; School of Electronic, Information and Electrical E" + "author_name": "Md. Ziaul Islam", + "author_inst": "National Institute of Preventive and Social Medicine (NIPSOM)" }, { - "author_name": "Gongsheng Yuan", - "author_inst": "Department of Physiology and Pathophysiology, School of Basic Medical Sciences, Fudan University, Shanghai, China" + "author_name": "Baizid Khoorshid Riaz", + "author_inst": "National Institute of Preventive and Social Medicine (NIPSOM)" + }, + { + "author_name": "ANM Shamsul Islam", + "author_inst": "National Institute of Preventive and Social Medicine (NIPSOM)" + }, + { + "author_name": "Fahmida Khanam", + "author_inst": "National Institute of Preventive and Social Medicine (NIPSOM)" + }, + { + "author_name": "Jabin Akhter", + "author_inst": "National Institute of Preventive and Social Medicine (NIPSOM)" + }, + { + "author_name": "Rafaat Choudhury", + "author_inst": "National Institute of Preventive and Social Medicine (NIPSOM)" + }, + { + "author_name": "Nasreen Farhana", + "author_inst": "National Institute of Preventive and Social Medicine (NIPSOM)" + }, + { + "author_name": "Mohammad Jamal Uddin", + "author_inst": "National Institute of Preventive and Social Medicine (NIPSOM)" + }, + { + "author_name": "Syeda Sumaiya Efa", + "author_inst": "National Institute of Preventive and Social Medicine (NIPSOM)" } ], "version": "1", "license": "cc_by_nc_nd", - "type": "new results", - "category": "bioinformatics" + "type": "PUBLISHAHEADOFPRINT", + "category": "infectious diseases" }, { "rel_doi": "10.1101/2020.08.17.20176610", @@ -1226053,45 +1226762,41 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2020.08.17.253484", - "rel_title": "Generalized linear models provide a measure of virulence for specific mutations in SARS-CoV-2 strains", + "rel_doi": "10.1101/2020.08.18.255570", + "rel_title": "Spike protein mutational landscape in India: Could Mullers ratchet be a future game-changer for COVID-19?", "rel_date": "2020-08-18", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.08.17.253484", - "rel_abs": "This study aims to highlight SARS-COV-2 mutations which are associated with increased or decreased viral virulence. We utilize, genetic data from all strains available from GISAID and countries regional information such as deaths and cases per million as well as covid-19-related public health austerity measure response times. Initial indications of selective advantage of specific mutations can be obtained from calculating their frequencies across viral strains. By applying modelling approaches, we provide additional information that is not evident from standard statistics or mutation frequencies alone. We therefore, propose a more precise way of selecting informative mutations. We highlight two interesting mutations found in genes N (P13L) and ORF3a (Q57H). The former appears to be significantly associated with decreased deaths and cases per million according to our models, while the latter shows an opposing association with decreased deaths and increased cases per million. Moreover, protein structure prediction tools show that the mutations infer conformational changes to the protein that significantly alter its structure when compared to the reference protein.", - "rel_num_authors": 8, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.08.18.255570", + "rel_abs": "The dire need of effective preventive measures and treatment approaches against SARS-CoV-2 virus, causing COVID-19 pandemic, calls for an in-depth understanding of its evolutionary dynamics with attention to specific geographic locations, since lockdown and social distancing to prevent the virus spread could lead to distinct localized dynamics of virus evolution within and between countries owing to different environmental and host-specific selection pressures. To decipher any correlation between SARS-CoV-2 evolution and its epidemiology in India, we studied the mutational diversity of spike glycoprotein, the key player for the attachment, fusion and entry of virus to the host cell. For this, we analyzed the sequences of 630 Indian isolates as available in GISAID database till June 07, 2020, and detected the spike protein variants to emerge from two major ancestors - Wuhan-Hu-1/2019 and its D614G variant. Average stability of the docked spike protein - host receptor (S-R) complexes for these variants correlated strongly (R2=0.96) with the fatality rates across Indian states. However, while more than half of the variants were found unique to India, 67% of all variants showed lower stability of S-R complex than the respective ancestral variants, indicating a possible fitness loss in recently emerged variants, despite a continuous increase in mutation rate. These results conform to the sharply declining fatality rate countrywide (>7-fold during April 11 - June 28, 2020). Altogether, while we propose the potential of S-R complex stability to track disease severity, we urge an immediate need to explore if SARS-CoV-2 is approaching mutational meltdown in India.\n\nAuthor summaryEpidemiological features are intricately linked to evolutionary diversity of rapidly evolving pathogens, and SARS-CoV-2 is no exception. Our work suggests the potential of average stability of complexes formed by the circulating spike mutational variants and the human host receptor to track the severity of SARS-CoV-2 infection in a given region. In India, the stability of these complexes for recent variants tend to decrease relative to their ancestral ones, following countrywide declining fatality rate, in contrast to an increasing mutation rate. We hypothesize such a scenario as nascent footprints of Mullers ratchet, proposing large-scale population genomics study for its validation, since this understanding could lead to therapeutic approaches for facilitating mutational meltdown of SARS-CoV-2, as experienced earlier for influenza A virus.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Anastasis Oulas", - "author_inst": "The Cyprus Institute of Neurology and Genetics" + "author_name": "Rachana Banerjee", + "author_inst": "JIS Institute of Advanced Studies and Research Kolkata" }, { - "author_name": "Maria Zanti", - "author_inst": "The Cyprus Institute of Neurology and Genetics" + "author_name": "Kausik Basak", + "author_inst": "JIS Institute of Advanced Studies and Research Kolkata" }, { - "author_name": "Marios Tomazou", - "author_inst": "The Cyprus Institute of Neurology and Genetics" + "author_name": "Anamika Ghosh", + "author_inst": "JIS Institute of Advanced Studies and Research Kolkata" }, { - "author_name": "Margarita Zachariou", - "author_inst": "The Cyprus Institute of Neurology and Genetics" + "author_name": "Vyshakh Rajachandran", + "author_inst": "JIS Institute of Advanced Studies and Research Kolkata" }, { - "author_name": "George Minadakis", - "author_inst": "The Cyprus Institute of Neurology and Genetics" - }, - { - "author_name": "Marilena M Bourdakou", - "author_inst": "The Cyprus Institute of Neurology and Genetics" + "author_name": "Kamakshi Sureka", + "author_inst": "JIS Institute of Advanced Studies and Research Kolkata" }, { - "author_name": "Pavlos Pavlidis", - "author_inst": "Foundation for Research and Technology, Hellas" + "author_name": "Debabani Ganguly", + "author_inst": "JIS Institute of Advanced Studies and Research Kolkata" }, { - "author_name": "George M Spyrou", - "author_inst": "The Cyprus Institute of Neurology and Genetics" + "author_name": "Sujay Chattopadhyay", + "author_inst": "JIS Institute of Advanced Studies & Research Kolkata" } ], "version": "1", @@ -1227647,57 +1228352,161 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.08.14.20175299", - "rel_title": "Newborn dried blood spots for serological surveys of COVID-19", + "rel_doi": "10.1101/2020.08.14.20174490", + "rel_title": "Detection, prevalence, and duration of humoral responses to SARS-CoV-2 under conditions of limited population exposure.", "rel_date": "2020-08-16", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.14.20175299", - "rel_abs": "As COVID-19 continues to spread across the globe, the need for inexpensive, large-scale prevalence surveillance testing increases. We present a method for testing newborn dried blood spots (DBS) for anti-SARS-COV-2 IgG antibodies, and demonstrate its applicability as an easily accessible proxy for measuring maternal seroprevalence.", - "rel_num_authors": 11, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.14.20174490", + "rel_abs": "We conducted an extensive serological study to quantify population-level exposure and define correlates of immunity against SARS-CoV-2. We found that relative to mild COVID-19 cases, individuals with severe disease exhibited elevated authentic virus-neutralizing titers and antibody levels against nucleocapsid (N) and the receptor binding domain (RBD) and the S2 region of spike protein. Unlike disease severity, age and sex played lesser roles in serological responses. All cases, including asymptomatic individuals, seroconverted by 2 weeks post-PCR confirmation. RBD- and S2-specific and neutralizing antibody titers remained elevated and stable for at least 2-3 months post-onset, whereas those against N were more variable with rapid declines in many samples. Testing of 5882 self-recruited members of the local community demonstrated that 1.24% of individuals showed antibody reactivity to RBD. However, 18% (13/73) of these putative seropositive samples failed to neutralize authentic SARS-CoV-2 virus. Each of the neutralizing, but only 1 of the non-neutralizing samples, also displayed potent reactivity to S2. Thus, inclusion of multiple independent assays markedly improved the accuracy of antibody tests in low seroprevalence communities and revealed differences in antibody kinetics depending on the viral antigen. In contrast to other reports, we conclude that immunity is durable for at least several months after SARS-CoV-2 infection.", + "rel_num_authors": 37, "rel_authors": [ { - "author_name": "Feimei Liu", - "author_inst": "Department of Immunobiology, Yale School of Medicine, New Haven, CT" + "author_name": "Tyler J Ripperger", + "author_inst": "University of Arizona" }, { - "author_name": "Mytien Nguyen", - "author_inst": "Department of Immunobiology, Yale School of Medicine, New Haven, CT" + "author_name": "Jennifer L Uhrlaub", + "author_inst": "University of Arizona" }, { - "author_name": "Pavithra Vijayakumar", - "author_inst": "Yale School of Medicine" + "author_name": "Makiko Watanabe", + "author_inst": "University of Arizona" }, { - "author_name": "Alanna Kaplan", - "author_inst": "Department of Immunobiology, Yale School of Medicine, New Haven, CT" + "author_name": "Rachel Wong", + "author_inst": "University of Arizona" }, { - "author_name": "Amit Meir", - "author_inst": "Boyer Center for Molecular Medicine, Department of Microbial Pathogenesis, Yale University" + "author_name": "Yvonne Castaneda", + "author_inst": "University of Arizona" }, { - "author_name": "Yile Dai", - "author_inst": "Department of Immunobiology, Yale School of Medicine, New Haven, CT" + "author_name": "Hannah A Pizzato", + "author_inst": "University of Arizona" }, { - "author_name": "Eric Wang", - "author_inst": "Department of Immunobiology, Yale School of Medicine, New Haven, CT" + "author_name": "Mallory R Thompson", + "author_inst": "University of Arizona" }, { - "author_name": "Hannah Walsh", - "author_inst": "Department of Internal Medicine (Infectious Diseases), Yale School of Medicine" + "author_name": "Christine Bradshaw", + "author_inst": "University of Arizona" }, { - "author_name": "Aaron M. Ring", - "author_inst": "Department of Immunobiology, Yale School of Medicine, New Haven, CT" + "author_name": "Craig C Weinkauf", + "author_inst": "University of Arizona" }, { - "author_name": "Saad B. Omer", - "author_inst": "Department of Internal Medicine (Infectious Diseases), Yale School of Medicine" + "author_name": "Christian Bime", + "author_inst": "University of Arizona" }, { - "author_name": "Shelli Farhadian", - "author_inst": "Department of Internal Medicine (Infectious Diseases), Yale School of Medicine" + "author_name": "Heidi L Erickson", + "author_inst": "University of Arizona" + }, + { + "author_name": "Kenneth Knox", + "author_inst": "University of Arizona" + }, + { + "author_name": "Billie Bixby", + "author_inst": "University of Arizona" + }, + { + "author_name": "Sairam Parthasarathy", + "author_inst": "University of Arizona" + }, + { + "author_name": "Sachin Chaudhary", + "author_inst": "University of Arizona" + }, + { + "author_name": "Bhupinder Natt", + "author_inst": "University of Arizona" + }, + { + "author_name": "Elaine Cristan", + "author_inst": "University of Arizona" + }, + { + "author_name": "Tammer El Aini", + "author_inst": "University of Arizona" + }, + { + "author_name": "Franz Rischard", + "author_inst": "University of Arizona" + }, + { + "author_name": "Janet Campion", + "author_inst": "University of Arizona" + }, + { + "author_name": "Madhav Chopra", + "author_inst": "University of Arizona" + }, + { + "author_name": "Michael Insel", + "author_inst": "University of Arizona" + }, + { + "author_name": "Afshin Sam", + "author_inst": "University of Arizona" + }, + { + "author_name": "James L Knepler", + "author_inst": "University of Arizona" + }, + { + "author_name": "Andrew P Capaldi", + "author_inst": "University of Arizona" + }, + { + "author_name": "Catherine M Spier", + "author_inst": "University of Arizona" + }, + { + "author_name": "Michael D Dake", + "author_inst": "University of Arizona" + }, + { + "author_name": "Taylor Edwards", + "author_inst": "University of Arizona" + }, + { + "author_name": "Matthew E Kaplan", + "author_inst": "University of Arizona" + }, + { + "author_name": "Serena Jain Scott", + "author_inst": "University of Arizona" + }, + { + "author_name": "Cameron Hypes", + "author_inst": "University of Arizona" + }, + { + "author_name": "Jarrod Mosier", + "author_inst": "University of Arizona" + }, + { + "author_name": "David T Harris", + "author_inst": "University of Arizona" + }, + { + "author_name": "Bonnie J Lafleur", + "author_inst": "University of Arizona" + }, + { + "author_name": "Ryan Sprissler", + "author_inst": "University of Arizona" + }, + { + "author_name": "Janko Nikolich-Zugich", + "author_inst": "University of Arizona" + }, + { + "author_name": "Deepta Bhattacharya", + "author_inst": "University of Arizona" } ], "version": "1", @@ -1229501,139 +1230310,47 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.08.13.20174193", - "rel_title": "CovidNudge: diagnostic accuracy of a novel lab-free point-of-care diagnostic for SARS-CoV-2", + "rel_doi": "10.1101/2020.08.13.20174466", + "rel_title": "Assessment of Infection Prevention and Control Protocols, Procedures, and Implementation in Response to the COVID-19 Pandemic in Twenty-three Long-term Care Facilities in Fulton County, Georgia", "rel_date": "2020-08-15", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.13.20174193", - "rel_abs": "3.BackgroundAccess to rapid diagnosis is key to the control and management of SARS-CoV-2. Reverse Transcriptase-Polymerase Chain Reaction (RT-PCR) testing usually requires a centralised laboratory and significant infrastructure. We describe the development and diagnostic accuracy assessment of a novel, rapid point-of-care RT-PCR test, the DnaNudge(R) platform CovidNudge test, which requires no laboratory handling or sample pre-processing.\n\nMethodsNasopharyngeal swabs are inserted directly into a cartridge which contains all reagents and components required for RT-PCR reactions, including multiple technical replicates of seven SARS-CoV-2 gene targets (rdrp1, rdrp2, e-gene, n-gene, n1, n2 and n3) and human ribonuclease P (RNaseP) as positive control. Between April and May 2020, swab samples were tested in parallel using the CovidNudge direct-to-cartridge platform and standard laboratory RT-PCR using swabs in viral transport medium. Samples were collected from three groups: self-referred healthcare workers with suspected COVID-19 (Group 1, n=280/386; 73%); patients attending the emergency department with suspected COVID-19 (Group 2, n=15/386; 4%) and hospital inpatient admissions with or without suspected COVID-19 (Group 3, n=91/386; 23%).\n\nResultsOf 386 paired samples tested across all groups, 67 tested positive on the CovidNudge platform and 71 with standard laboratory RT-PCR. The sensitivity of the test varied by group (Group 1 93% [84-98%], Group 2 100% [48-100%] and Group 3 100% [29-100%], giving an average sensitivity of 94.4% (95% confidence interval 86-98%) and an overall specificity of 100% (95%CI 99-100%; Group 1 100% [98-100%]; Group 2 100% [69-100%] and Group 3 100% [96-100%]). Point of care testing performance was comparable during a period of high (25%) and low (3%) background prevalence. Amplification of the viral nucleocapsid (n1, n2, n3) targets were most sensitive for detection of SARS-CoV2, with the assay able to detect 1x104 viral particles in a single swab.\n\nConclusionsThe CovidNudge platform offers a sensitive, specific and rapid point of care test for the presence of SARS-CoV-2 without laboratory handling or sample pre-processing. The implementation of such a device could be used to enable rapid decisions for clinical care and testing programs.\n\n4. RESEARCH IN CONTEXTO_ST_ABSEvidence before this studyC_ST_ABSThe WHO has highlighted the development of rapid, point-of-care diagnostics for detection of SARS-CoV-2 as a key priority to tackle COVID-19. The Foundation for Innovative Diagnostics (FIND) has identified over 90 point-of-care, near patient or mobile tests for viral detection of SARS-CoV-2. However, the most widely available rapid tests to date require some sample handling which limits their use at point-of-care. In addition, pressure on supply chains is restricting access to current diagnostics and alternatives are needed urgently.\n\nAdded value of this studyWe describe the development and clinical validation of COVID nudge, a novel point-of-care RT-PCR diagnostic, evaluated during the first wave of the SARS-CoV-2 epidemic. The platform is able to achieve high analytic sensitivity and specificity from dry swabs within a self-contained cartridge. The lack of downstream sample handling makes it suitable for use in a range of clinical settings, without need for a laboratory or specialized operator. Multiplexed assays within the cartridge allow inclusion of a positive human control, which reduces the false negative testing rate due to insufficient sampling.\n\nImplication of the available evidencePoint-of-care testing can relieve pressure on centralized laboratories and increase overall testing capacity, complementing existing approaches. These findings support a role for COVID Nudge as part of strategies to improve access to rapid diagnostics to SARS-CoV-2. Since May 2020, the system has been implemented in UK hospitals and is being rolled out nationwide.", - "rel_num_authors": 30, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.13.20174466", + "rel_abs": "Through infection prevention and control (IPC) site visits to 23 LTCFs in Fulton County, Georgia, comparison between the Higher- and Lower-prevalence groups revealed significant differences in PPE and Social Distancing, with five specific indicators driving these differences.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Malick M Gibani", - "author_inst": "Imperial College London" - }, - { - "author_name": "Christofer Toumazou", - "author_inst": "DnaNudge Ltd, Translation and Innovation Hub, Imperial College White City Campus, London" - }, - { - "author_name": "Mohammadreza Sohbati", - "author_inst": "DnaNudge Ltd, Translation and Innovation Hub, Imperial College White City Campus, London" - }, - { - "author_name": "Rashmita Sahoo", - "author_inst": "DnaNudge Ltd, Translation and Innovation Hub, Imperial College White City Campus, London" - }, - { - "author_name": "Maria Karvela", - "author_inst": "DnaNudge Ltd, Translation and Innovation Hub, Imperial College White City Campus, London" - }, - { - "author_name": "Tsz-Kin Hon", - "author_inst": "DnaNudge Ltd, Translation and Innovation Hub, Imperial College White City Campus, London" - }, - { - "author_name": "Sara De Mateo", - "author_inst": "DnaNudge Ltd, Translation and Innovation Hub, Imperial College White City Campus, London" - }, - { - "author_name": "Alison Burdett", - "author_inst": "DnaNudge Ltd, Translation and Innovation Hub, Imperial College White City Campus, London" - }, - { - "author_name": "K Y Felice Leung", - "author_inst": "DnaNudge Ltd, Translation and Innovation Hub, Imperial College White City Campus, London" - }, - { - "author_name": "Jake Barnett", - "author_inst": "DnaNudge Ltd, Translation and Innovation Hub, Imperial College White City Campus, London" - }, - { - "author_name": "Arman Orbeladze", - "author_inst": "DnaNudge Ltd, Translation and Innovation Hub, Imperial College White City Campus, London" - }, - { - "author_name": "Song Luan", - "author_inst": "DnaNudge Ltd, Translation and Innovation Hub, Imperial College White City Campus, London" - }, - { - "author_name": "Stavros Pournias", - "author_inst": "DnaNudge Ltd, Translation and Innovation Hub, Imperial College White City Campus, London" - }, - { - "author_name": "Jiayang Sun", - "author_inst": "DnaNudge Ltd, Translation and Innovation Hub, Imperial College White City Campus, London" - }, - { - "author_name": "Barnaby Flower", - "author_inst": "Department of Infectious Disease, Imperial College London, United Kingdom" - }, - { - "author_name": "Judith Bedzo-Nutakor", - "author_inst": "DnaNudge Ltd, Translation and Innovation Hub, Imperial College White City Campus, London" - }, - { - "author_name": "Maisarah Amran", - "author_inst": "Imperial College Healthcare NHS Trust, United Kingdom." - }, - { - "author_name": "Rachael Quinlan", - "author_inst": "Department of Infectious Disease, Imperial College London, United Kingdom" - }, - { - "author_name": "Keira Skolimowska", - "author_inst": "Imperial College Healthcare NHS Trust, United Kingdom" - }, - { - "author_name": "Robert Klaber", - "author_inst": "Imperial College Healthcare NHS Trust, United Kingdom" - }, - { - "author_name": "Gary Davies", - "author_inst": "Chelsea & Westminster NHS Foundation Trust, London" - }, - { - "author_name": "David Muir", - "author_inst": "Imperial College Healthcare NHS Trust, United Kingdom" - }, - { - "author_name": "Paul Randell", - "author_inst": "Imperial College Healthcare NHS Trust, United Kingdom" - }, - { - "author_name": "Derrick W M Crook", - "author_inst": "NIHR Oxford Biomedical Research Centre" + "author_name": "Carson T Telford", + "author_inst": "Fulton County Board of Health" }, { - "author_name": "Graham P Taylor", - "author_inst": "Department of Infectious Disease, Imperial College London, United Kingdom" + "author_name": "Cyndra Bystrom", + "author_inst": "Georgia Department of Public Health" }, { - "author_name": "Wendy Barclay", - "author_inst": "Department of Infectious Disease, Imperial College London, United Kingdom" + "author_name": "Teresa Fox", + "author_inst": "Georgia Department of Public Health" }, { - "author_name": "Nabeela Mughal", - "author_inst": "Chelsea & Westminster NHS Foundation Trust, London" + "author_name": "Sherry Wiggins-Benn", + "author_inst": "Fulton County Board of Health" }, { - "author_name": "Luke S P Moore", - "author_inst": "Chelsea & Westminster NHS Foundation Trust, London" + "author_name": "Meshell McCloud", + "author_inst": "Fulton County Board of Health" }, { - "author_name": "Katie Jeffery", - "author_inst": "Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom" + "author_name": "David P Holland", + "author_inst": "Fulton County Board of Health" }, { - "author_name": "Graham S Cooke", - "author_inst": "Department of Infectious Disease, Imperial College London, United Kingdom" + "author_name": "Sarita Shah", + "author_inst": "Emory University" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2020.08.12.20173294", @@ -1231131,61 +1231848,53 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.08.11.20171975", - "rel_title": "Clinical and Epidemiological Characteristics of the First Month of the Covid-19 Pandemic in Chile", + "rel_doi": "10.1101/2020.08.11.20172692", + "rel_title": "Clinical, Laboratory, and Imaging Features of 148 Patients with COVID-19 in Bushehr: A Report from the South of Iran", "rel_date": "2020-08-14", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.11.20171975", - "rel_abs": "IntroductionUnderstanding the clinical course and outcomes of patients with Covid-19 in underrepresented populations like Latin America is paramount. In this study, we report the clinical characteristics of Covid-19 in Chile, with a focus on subjects requiring hospitalization during the initial phases of the SARS-CoV-2 pandemic.\n\nMethodsThis is a single center study including all consecutive patients diagnosed with Covid-19 during the first month of the pandemic. Demographics, clinical characteristics and laboratory data were collected within 24 hours of admission. The primary outcome was a composite of ICU admission or all-cause, in-hospital mortality.\n\nResultsDuring the first month of the pandemic, 381 patients were confirmed as positive for SARS-CoV-2 by molecular testing; 88 (23.1%) of them eventually required hospitalization. Median age of the cohort was 39 years (IQR 31-49). Overall mortality was 0.7% and 18 (3.7%) out of the 88 subjects who required hospitalization either died and/or required ICU. Increased body mass index (BMI), C-reactive protein levels (CRP) and the SaTO2/FiO2 index on admission were independently associated with a higher risk of ICU care or death.\n\nDiscussionThe lower mortality observed in our prospective cohort during the first month of SARS-Cov-2 pandemic was lower than previously reported. This finding could be due to a lower threshold for admission, a healthcare system not yet overburdened and a younger population, among other factors. BMI, CRP on admission were strong predictors for ICU care or all-cause, in-hospital mortality. Our data provide important information regarding the clinical course of Covid-19 in Latin America.", - "rel_num_authors": 11, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.11.20172692", + "rel_abs": "AimTo investigate clinical characteristics, laboratory findings, and imaging features of patients confirmed with COVID-19 in Bushehr, a southern province of Iran.\n\nMethodDuring April 29th to May 30th 2020, a total of 148 patients confirmed with COVID-19 infection were admitted to three hospitals in Bushehr province, assigned by the Iranian Ministry of Health.\n\nResultsThe most common coexisting disease was type 2 diabetes. Levels of ESR, CRP, LDH, and AST among inpatients were higher than the outpatients (P<0.05). There were significant differences in the levels of creatinine and BUN between elderly and non-elderly patients (P<0.05).\n\nConclusionPatients with comorbidities and elderly patients are at increased risk of severe progression of COVID-19.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Macarena R Vial", - "author_inst": "Facultad de Medicina Clinica Alemana Universidad del Desarrollo" - }, - { - "author_name": "Anne Peters", - "author_inst": "Instituto de Ciencias e Innovacion en Medicina, Facultad de Medicina Clinica Alemana, Universidad del Desarrollo" - }, - { - "author_name": "Inia Perez", - "author_inst": "Facultad de Medicina Clinica Alemana Universidad del Desarrollo" + "author_name": "Mohsen Keshavarz", + "author_inst": "Bushehr University of Medical Sciences" }, { - "author_name": "Maria Spencer", - "author_inst": "Instituto de Ciencias e Innovacion en Medicina, Facultad de Medicina Clinica Alemana, Universidad del Desarrollo" + "author_name": "Ahmad Tavakoli", + "author_inst": "Iran University of Medical Sciences" }, { - "author_name": "Mario Barbe", - "author_inst": "Clinica Alemana de Santiago" + "author_name": "Sareh Zanganeh", + "author_inst": "Shiraz University of Medical Sciences" }, { - "author_name": "Mabel Aylwin", - "author_inst": "Facultad de Medicina Clinica Alemana, Universidad del Desarrollo" + "author_name": "Mohammad Javad Mousavi", + "author_inst": "Bushehr University of Medical Sciences" }, { - "author_name": "Lorena Porte", - "author_inst": "Facultad de Medicina Clinica Alemana, Universidad del Desarrollo" + "author_name": "Katayoun Vahdat", + "author_inst": "Bushehr University of Medical Sciences" }, { - "author_name": "Thomas Weitzel", - "author_inst": "Instituto de Ciencias e Innovacion en Medicina, Facultad de Medicina Clinica Alemana, Universidad del Desarrollo" + "author_name": "Mehdi Mahmudpour", + "author_inst": "Bushehr University of Medical Sciences" }, { - "author_name": "Pablo Vial", - "author_inst": "Instituto de Ciencias e Innovacion en Medicina, Facultad de Medicina Clinica Alemana, Universidad del Desarrollo" + "author_name": "Iraj Nabipour", + "author_inst": "Bushehr University of Medical Sciences" }, { - "author_name": "Rafael Araos", - "author_inst": "Instituto de Ciencias e Innovacion en Medicina, Facultad de Medicina Clinica Alemana, Universidad del Desarrollo; Millennium Initiative for Collaborative Resear" + "author_name": "Amir Hossein Darabi", + "author_inst": "Bushehr University of Medical Sciences" }, { - "author_name": "Jose M. Munita", - "author_inst": "Instituto de Ciencias e Innovacion en Medicina, Facultad de Medicina Clinica Alemana, Universidad del Desarrollo; Millennium Initiative for Collaborative Resear" + "author_name": "Saeid Keshmiri", + "author_inst": "Bushehr University of Medical Sciences" } ], "version": "1", - "license": "cc_no", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1232857,27 +1233566,59 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.08.12.20170852", - "rel_title": "knowledge, attitudes and practices (KAP) towards Covid-19 among Palestinians during the Covid-19 outbreak: a cross sectional survey", + "rel_doi": "10.1101/2020.08.11.20173120", + "rel_title": "Network reinforcement driven drug repurposing for COVID-19 by exploiting disease-gene-drug associations", "rel_date": "2020-08-14", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.12.20170852", - "rel_abs": "Coronavirus disease 2019 (COVID-19) is a highly contagious illness that spreads rapidly through human-to-human transmission. On March 5, the government of Palestine declared a state of emergency in order to curb the spread of the virus, a declaration that it extended for a fifth time on July 5th. The degree to which a population complies with corresponding safety measures is surely affected by the peoples knowledge, attitudes and practices (KAP) towards the disease. To explore this hypothesis, we gathered data from 1,731 Palestinians between April 19thand May 1st, 2020 through a KAP questionnaire. The participant pool represented a stratified sample of Palestinians living across a number of governorates in the Gaza Strip and the West Bank, with 36.5% from Gaza and (63.5%) from the West Bank. Gender was almost equally distributed within the sample with (51%) male respondents and (49%) female respondent. The questionnaire included 17 questions about participants knowledge and awareness of COVID- 19, 17 questions regarding the safety measures they had taken in the wake of the outbreak and 3 questions asking them to assess the efficacy of the governments response to the pandemic. The overall correct mean of the knowledge was 79.26+-0.35. Most participants expressed confidence that Covid-19 would be successfully controlled and that Palestine could win the battle against Covid-19, though 62% believed that stricter measurements must be applied. Based on the results of this study, we conclude that health education programs aimed at improving the publics understanding of COVID-19 are important in helping the population maintain appropriate practices, and that findings such as those discussed in this report may provide valuable feedback to lawmakers working to stop the spread of the virus.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.11.20173120", + "rel_abs": "Currently, the number of patients with COVID-19 has significantly increased. Thus, there is an urgent need for developing treatments for COVID-19. Drug repurposing, which is the process of reusing already-approved drugs for new medical conditions, can be a good way to solve this problem quickly and broadly. Many clinical trials for COVID-19 patients using treatments for other diseases have already been in place or will be performed at clinical sites in the near future. Additionally, patients with comorbidities such as diabetes mellitus, obesity, liver cirrhosis, kidney diseases, hypertension, and asthma are at higher risk for severe illness from COVID-19. Thus, the relationship of comorbidity disease with COVID-19 may help to find repurposable drugs. To reduce trial and error in finding treatments for COVID-19, we propose building a network-based drug repurposing framework to prioritize repurposable drugs. First, we utilized knowledge of COVID-19 to construct a disease-gene-drug network (DGDr-Net) representing a COVID-19-centric interactome with components for diseases, genes, and drugs. DGDr-Net consisted of 592 diseases, 26,681 human genes and 2,173 drugs, and medical information for 18 common comorbidities. The DGDr-Net recommended candidate repurposable drugs for COVID-19 through network reinforcement driven scoring algorithms. The scoring algorithms determined the priority of recommendations by utilizing graph-based semi-supervised learning. From the predicted scores, we recommended 30 drugs, including dexamethasone, resveratrol, methotrexate, indomethacin, quercetin, etc., as repurposable drugs for COVID-19, and the results were verified with drugs that have been under clinical trials. The list of drugs via a data-driven computational approach could help reduce trial-and-error in finding treatment for COVID-19.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Nouar Qutob", - "author_inst": "Arab American University" + "author_name": "Yonghyun Nam", + "author_inst": "University of Pennsylvania" }, { - "author_name": "Faisal Awartani", - "author_inst": "Arab American Universiry" + "author_name": "Jae-Seung Yun", + "author_inst": "University of Pennsylvania" + }, + { + "author_name": "Seung Mi Lee", + "author_inst": "University of Pennsylvania" + }, + { + "author_name": "Ji Won Park", + "author_inst": "University of Pennsylvania" + }, + { + "author_name": "Ziqi Chen", + "author_inst": "The Ohio State University" + }, + { + "author_name": "Brian Lee", + "author_inst": "University of Pennsylvania" + }, + { + "author_name": "Anurag Verma", + "author_inst": "University of Pennsylvania" + }, + { + "author_name": "Xia Ning", + "author_inst": "The Ohio State University" + }, + { + "author_name": "Li Shen", + "author_inst": "University of Pennsylvania" + }, + { + "author_name": "Dokyoon Kim", + "author_inst": "University of Pennsylvania" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "pharmacology and therapeutics" }, { "rel_doi": "10.1101/2020.08.12.20173468", @@ -1234239,31 +1234980,43 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2020.08.13.20174227", - "rel_title": "Long-Term Exposure to Outdoor Air Pollution and COVID-19 Mortality: an ecological analysis in England", + "rel_doi": "10.1101/2020.08.13.20174052", + "rel_title": "Knowledge, attitude and practice among Ophthalmic Health Care Personnel (HCP) towards COVID-19 pandemic in Nepal: A web-based cross-sectional study", "rel_date": "2020-08-14", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.13.20174227", - "rel_abs": "There is an urgent need to examine what individual and environmental risk factors are associated with COVID-19 mortality. This objective of this study is to investigate the association between long term exposure to air pollution and COVID-19 mortality. We conducted a nationwide, ecological study using zero-inflated negative binomial models to estimate the association between long term (2014-2018) small area level exposure to NOx, PM2.5, PM10 and SO2 and COVID-19 mortality rates in England adjusting for socioeconomic factors and infection exposure. We found that all four pollutant concentrations were positively associated with COVID-19 mortality. The increase in mortality risk ratio per inter quarter range increase was for PM2.5:11%, 95%CIs 6%-17%), PM10 (5%; 95%CIs 1%-11%), NOx (11%, 95%CIs 6%-15%) and SO2 (7%, 95%CIs 3%-11%) were respectively in adjusted models. Public health intervention may need to protect people who are in highly polluted areas from COVID-19 infections.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.13.20174052", + "rel_abs": "Background: Being an added high-risk group, ophthalmic HCP are actively providing emergency eye care services, also enthusiastically participating in prevention and control of the COVID-19 pandemic. Hence, this study aimed to assess the level of knowledge, attitude, and practice (KAP) among ophthalmic HCP towards COVID-19 pandemic. Methods: A web-based cross-sectional study was conducted during the period of lockdown among ophthalmic HCP including consultant ophthalmologist, resident, optometrist, ophthalmic assistant, nursing staff, and other paramedics of eye care centers in Nepal. The KAP questionnaire was designed and distributed online. Data were analyzed using the Chi-square test, Pearson correlation, and binary logistic regression. All tests were performed at 95% Confidence Interval (CI) and p-value <0.05 was considered statistically significant. Results: Of 694 participants, the majority were male (59.1%) from the age group 31-40 years (41.5%) and tertiary eye center (68.9%). Among ophthalmic HCP, there were 29.8% consultants ophthalmologist, 22.6% residents, 23.3% optometrist, 15% ophthalmic assistant, and 9.2% other ophthalmic paramedics, 11.7% working as front-liners in COVID-19 centers. Findings showed, 98.1% had good knowledge, 59.4% had a positive attitude and only 13.3% had good practice regarding COVID-19. Binary logistic regression analysis demonstrated the age of HCP to be a significant determinant of good knowledge (Crude Odds Ratio (COR)=0.72, 95%CI=0.62-0.82), positive attitude (COR=0.92, 95%CI=0.90-0.94) and good practice (COR=1.16, 95%CI=1.10-1.21). Lower odds of poor practice was seen among junior resident (COR=0.26, 95% CI=0.14-0.47) and higher odds of poor practice was seen among HCP with job experience of 5-10 years (COR=2.38, 95% CI=1.23-4.60) towards COVID-19 pandemic. Conclusion: The majority of ophthalmic HCP have good knowledge, insufficient positive attitude, and inadequate evidence-based practice towards the COVID-19 pandemic in Nepal. Hence, this study conclusively recommends to modify existing guidelines and formulate new policies to improve KAP among ophthalmic HCP to effectively control the spread of COVID-19.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Zhiqiang Feng", - "author_inst": "University of Edinburgh" + "author_name": "Dr Zahir Ansari", + "author_inst": "B.P. Koirala Institute of Health Sciences, Department of Ophthalmology, Dharan, Nepal" }, { - "author_name": "Mark Cherrie", - "author_inst": "University of Edinburgh" + "author_name": "Dr Babu Dhanendra Chaurasiya", + "author_inst": "Narayani Hospital, Department of Ophthalmology, Birgunj, Nepal" }, { - "author_name": "Chris DIBBEN", - "author_inst": "University of Edinburgh" + "author_name": "Dr Sirjana Adhikari", + "author_inst": "B.P. Koirala Institute of Health Sciences, School of Public Health and Community Medicine, Dharan, Nepal" + }, + { + "author_name": "Dr Uday Chandra Prakash", + "author_inst": "Nobel Medical College, Department of Ophthalmology, Biratnagar, Nepal" + }, + { + "author_name": "Bikram Adhikari", + "author_inst": "B.P. Koirala Institute of Health Sciences, School of Public and Community medicine, Dharan, Nepal" + }, + { + "author_name": "Dr Sahana Khatoon", + "author_inst": "Khasyauli Primary Health Care Center, Palpa, Nepal" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "occupational and environmental health" + "category": "ophthalmology" }, { "rel_doi": "10.1101/2020.08.13.20166975", @@ -1235933,127 +1236686,55 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2020.08.09.20170910", - "rel_title": "Acute Lung injury evolution in Covid-19", + "rel_doi": "10.1101/2020.08.09.20170985", + "rel_title": "COVID-19 in rheumatic diseases: A random cross-sectional telephonic survey", "rel_date": "2020-08-13", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.09.20170910", - "rel_abs": "BackgroundPathogenesis of Coronavirus disease 2019 (Covid-19) is poorly understood. Most histologic studies come from post-mortem analysis, with existing data indicating that histologic features of acute respiratory distress syndrome are typically present in fatal cases. However, this observation may be misleading, due to confounding factors in pre-terminal disease, including injury resulting from prolonged mechanical ventilation. Ante-mortem lung biopsy may provide major pathogenetic insights, potentially providing a basis for novel treatment approaches.\n\nAimThis comparative, multicenter, prospective, observational study was planned to identify ante-mortem histological profile and immunohistochemical features of lung tissue in patients with Covid-19 in early and late phases of the disease, including markers of inflammatory cells and major pathways involved in the cytokine storm triggering.\n\nMethodsEnrolled patients underwent lung biopsy, according to the study protocol approved by local Ethical Committee, either within 15 days of the first symptoms appearing (early phase) or after >15 days (more advanced disease). Key exclusion criteria were excessive or uncorrectable bleeding risk and cardiovascular disease with heart failure. Lung samples were obtained by conventional transbronchial biopsy, trans-bronchial lung cryobiopsy or surgical lung biopsy.\n\nResults23 patients were enrolled: 12 patients underwent lung biopsy within 15 days and 11 patients more than 15 days after the onset of symptoms. Early biopsies were characterized by spots of patchy acute lung injury (ALI) with alveolar type II cells hyperplasia and significant vascular abnormalities (disordered angiogenesis with alveolar capillary hyperplasia, luminal enlargement and thickened walls of pulmonary venules, perivascular CD4-T-cell infiltration), with no hyaline membranes. In the later stages, the alveolar architecture appeared disrupted, with areas of organizing ALI, venular congestion and capillary thromboembolic microangiopathy. Striking phenotypic features were demonstrated in hyperplastic pneumocytes and endothelial cells, including the expression of phospho-STAT3 and molecules involved in immunoinhibitory signals (PD-L1 and IDO-1). Alveolar macrophages exhibited macrophage-related markers (CD68, CD11c, CD14) together with unusual markers, such as DC-Lamp/CD208, CD206, CD123/IL3AR.\n\nConclusionA morphologically distinct \"Covid pattern\" was identified in the earlier stages of the disease, with prominent epithelial and endothelial cell abnormalities, that may be potentially reversible, differing strikingly from findings in classical diffuse alveolar damage. These observations may have major therapeutic implications, justifying studies of early interventions aimed at mitigating inflammatory organ injury.", - "rel_num_authors": 27, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.09.20170985", + "rel_abs": "ObjectiveTo describe the incidence, clinical course, and predictive factors of coronavirus 2019 (COVID-19) infection in a cohort of rheumatological patients residing in New Delhi (National Capital Region), India.\n\nMethodsWe performed a cross-sectional, random telephonic survey from 20th April to 20th July 2020 on patients with rheumatic diseases. Patients were interviewed with a predesigned questionnaire. The incidence of COVID-19 in the general population was obtained from open access government data repository. Report of reverse transcriptase polymerase chain reaction report was taken as confirmatory of COVID-19 infection.\n\nResultsAmong the 900 contacted patients 840 responded (713 with rheumatoid arthritis (RA), 100 with systemic lupus erythematosus (SLE), 20 with spondylarthritis (SpA) and 7 with others; mean age 45 {+/-}13 years, mean duration 11.3 {+/-} 6.3 years; 86% female). Among them 29 reported flu-like symptoms and four RA patients had confirmed COVID-19 infection. All of them were hospitalized with uneventful recovery. Rheumatological drugs were discontinued during the infectious episode. Disease modifying agents and biologics were equally received by those with or without COVID-19. The incidence of COVID-19 was similar to general Delhi population (0.476% vs 0.519% respectively, p=0.86). Two patients had relapse of rheumatic disease after recovery. After recovery from COVID-19 or Flu-like illness, eight patients (27.6%, 95% confidence interval 14.7-45.7) reported disease flare.\n\nConclusionPatients with rheumatic diseases in India have similar incidence of COVID-19 infection compared to the community. Relapse of underlying rheumatic disease after recovery is not uncommon and continuation of glucocorticoid through the infection should be considered.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Claudio Doglioni", - "author_inst": "Department of Pathology, University Vita-Salute, Milan and San Raffaele Scientific Institute. Milan, Italy" - }, - { - "author_name": "Claudia Ravaglia", - "author_inst": "Pulmonology Unit, Thoracic Diseases Department. G.B. Morgagni Hospital, Forli, Italy" - }, - { - "author_name": "Giulio Rossi", - "author_inst": "Department of Pathology, S. Maria delle Croci Hospital. Ravenna, Italy" - }, - { - "author_name": "Alessandra Dubini", - "author_inst": "Department of Pathology, G.B. Morgagni Hospital. Forli, Italy" - }, - { - "author_name": "Federica Pedica", - "author_inst": "Department of Pathology, San Raffaele Scientific Institute. Milan, Italy" - }, - { - "author_name": "Sara Piciucchi", - "author_inst": "Department of Radiology, G.B. Morgagni Hospital. Forli, Italy" - }, - { - "author_name": "Antonio Vizzuso", - "author_inst": "Department of Radiology, G.B. Morgagni Hospital. Forli, Italy" - }, - { - "author_name": "Lorenza Pecciarini", - "author_inst": "Department of Pathology, San Raffaele Scientific Institute. Milan, Italy" - }, - { - "author_name": "Franco Stella", - "author_inst": "Alma Mater Studiorum Universita' di Bologna. Thoracic Surgery Unit, G.B. Morgagni Hospital. Forli, Italy" - }, - { - "author_name": "Stefano Maitan", - "author_inst": "Intensive Care Unit, G.B. Morgagni Hospital. Forli, Italy" - }, - { - "author_name": "Vanni Agnoletti", - "author_inst": "Intensive Care Unit, M. Bufalini Hospital. Cesena, Italy" - }, - { - "author_name": "Emiliano Gamberini", - "author_inst": "Intensive Care Unit, M. Bufalini Hospital. Cesena, Italy" - }, - { - "author_name": "Emanuele Russo", - "author_inst": "Intensive Care Unit, M. Bufalini Hospital. Cesena, Italy" - }, - { - "author_name": "Silvia Puglisi", - "author_inst": "Pulmonology Unit, Thoracic Diseases Department. G.B. Morgagni Hospital, Forli, Italy" - }, - { - "author_name": "Antonella Arcadu", - "author_inst": "Pulmonology Unit, Thoracic Diseases Department. G.B. Morgagni Hospital, Forli, Italy" - }, - { - "author_name": "Luca Donati", - "author_inst": "Pulmonology Unit, Thoracic Diseases Department. G.B. Morgagni Hospital, Forli, Italy" - }, - { - "author_name": "Simona Di Cesare", - "author_inst": "Internal Medicine Department, G.B. Morgagni Hospital. Forli, Italy" - }, - { - "author_name": "Carmela Grosso", - "author_inst": "Infectious Diseases Unit, GB Morgagni Hospital. Forli, Italy" - }, - { - "author_name": "Giovanni Poletti", - "author_inst": "Clinical Pathology Unit, The Great Romagna Area Hub Laboratory, Pievesestina, Cesena, Italy" + "author_name": "Uma Kumar", + "author_inst": "All India Institute of Medical Sciences" }, { - "author_name": "Vittorio Sambri", - "author_inst": "1) Unit of Microbiology, The Great Romagna Area Hub Laboratory, Pievesestina, Cesena, Italy. 2) DIMES, University of Bologna, Bologna, Italy" + "author_name": "Rudra Prosad Goswami", + "author_inst": "All India Institute of Medical Sciences, New Delhi" }, { - "author_name": "Elisabetta Fabbri", - "author_inst": "Department of Research and Innovation, AUSL Romagna. Rimini, Italy." + "author_name": "Danveer Bhadu", + "author_inst": "AIIMS" }, { - "author_name": "Giovanni Pizzolo", - "author_inst": "Verona University, Verona, Italy" + "author_name": "Maumita Kanjilal", + "author_inst": "AIIMS" }, { - "author_name": "Stefano Ugel", - "author_inst": "Immunology Section, Department of Medicine, Verona University Hospital, Verona, Italy" + "author_name": "Sandeep Nagar", + "author_inst": "AIIMS" }, { - "author_name": "Vincenzo Bronte", - "author_inst": "Immunology Section, Department of Medicine, Verona University Hospital, Verona, Italy" + "author_name": "Pallavi Vij", + "author_inst": "AIIMS" }, { - "author_name": "Athol U Wells", - "author_inst": "Lung Disease Unit, Royal Brompton Hospital, London, UK." + "author_name": "Dheeraj Mittal", + "author_inst": "AIIMS" }, { - "author_name": "Marco Chilosi", - "author_inst": "Department of Pathology, Pederzoli Hospital, Peschiera del Garda, Verona, Italy" + "author_name": "Lakshman Meena", + "author_inst": "AIIMS" }, { - "author_name": "Venerino Poletti", - "author_inst": "1) Pulmonology Unit, Thoracic Diseases Department. G.B. Morgagni Hospital, Forli, Italy. 2) Department of Respiratory Diseases and Allergy, Aarhus University Ho" + "author_name": "Debaditya Roy", + "author_inst": "AIIMS" } ], "version": "1", "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "respiratory medicine" + "category": "rheumatology" }, { "rel_doi": "10.1101/2020.08.09.20171173", @@ -1237439,131 +1238120,79 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.08.10.20171413", - "rel_title": "High prevalence of SARS-CoV-2 antibodies in care homes affected by COVID-19; a prospective cohort study in England", + "rel_doi": "10.1101/2020.08.10.244350", + "rel_title": "Human Embryonic Stem Cell-derived Lung Organoids: a Model for SARS-CoV-2 Infection and Drug Test", "rel_date": "2020-08-12", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.10.20171413", - "rel_abs": "BackgroundWe investigated six London care homes experiencing a COVID-19 outbreak and found very high rates of SARS-CoV-2 infection among residents and staff. Here we report follow-up serological analysis in these care homes five weeks later.\n\nMethodsResidents and staff had a convalescent blood sample for SARS-CoV-2 antibody levels and neutralising antibodies by SARS-COV-2 RT-PCR five weeks after the primary COVID-19 outbreak investigation.\n\nResultsOf the 518 residents and staff in the initial investigation, 208/241 (86.3%) surviving residents and 186/254 (73.2%) staff underwent serological testing. Almost all SARS-CoV-2 RT-PCR positive residents and staff were antibody positive five weeks later, whether symptomatic (residents 35/35, 100%; staff, 22/22, 100%) or asymptomatic (residents 32/33, 97.0%; staff 21/22, 95.1%). Symptomatic but SARS-CoV-2 RT-PCR negative residents and staff also had high seropositivity rates (residents 23/27, 85.2%; staff 18/21, 85.7%), as did asymptomatic RT-PCR negative individuals (residents 62/92, 67.3%; staff 95/143, 66.4%). Neutralising antibody was present in 118/132 (89.4%) seropositive individuals and was not associated with age or symptoms. Ten residents (10/108, 9.3%) remained RT-PCR positive, but with lower RT-PCR cycle threshold values; all 7 tested were seropositive. New infections were detected in three residents and one staff member.\n\nConclusionsRT-PCR testing for SARS-CoV-2 significantly underestimates the true extent of an outbreak in institutional settings. Elderly frail residents and younger healthier staff were equally able to mount robust and neutralizing antibody responses to SARS-CoV-2. More than two-thirds of residents and staff members had detectable antibodies against SARS-CoV-2 irrespective of their nasal swab RT-PCR positivity or symptoms status.", - "rel_num_authors": 28, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2020.08.10.244350", + "rel_abs": "The coronavirus disease 2019 (COVID-19) pandemic is caused by infection with the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which is spread primary via respiratory droplets and infects the lungs. Currently widely used cell lines and animals are unable to accurately mimic human physiological conditions because of the abnormal status of cell lines (transformed or cancer cells) and species differences between animals and humans. Organoids are stem cell-derived self-organized three-dimensional culture in vitro and model the physiological conditions of natural organs. Here we demonstrated that SARS-CoV-2 infected and extensively replicated in human embryonic stem cells (hESCs)-derived lung organoids, including airway and alveolar organoids. Ciliated cells, alveolar type 2 (AT2) cells and rare club cells were virus target cells. Electron microscopy captured typical replication, assembly and release ultrastructures and revealed the presence of viruses within lamellar bodies in AT2 cells. Virus infection induced more severe cell death in alveolar organoids than in airway organoids. Additionally, RNA-seq revealed early cell response to SARS-CoV-2 infection and an unexpected downregulation of ACE2 mRNA. Further, compared to the transmembrane protease, serine 2 (TMPRSS2) inhibitor camostat, the nucleotide analog prodrug Remdesivir potently inhibited SARS-CoV-2 replication in lung organoids. Therefore, human lung organoids can serve as a pathophysiological model for SARS-CoV-2 infection and drug discovery.", + "rel_num_authors": 15, "rel_authors": [ { - "author_name": "Shamez N Ladhani", - "author_inst": "Public Health England" - }, - { - "author_name": "Anna J Jeffery-Smith", - "author_inst": "Public Health England" - }, - { - "author_name": "Monika Patel", - "author_inst": "Public Health England" - }, - { - "author_name": "Roshni Janarthanan", - "author_inst": "Public Health England" - }, - { - "author_name": "Jonathan Fok", - "author_inst": "Public Health England" - }, - { - "author_name": "Emma Crawley-Boevey", - "author_inst": "Public Health England" - }, - { - "author_name": "Amoolya Vusirikala", - "author_inst": "Public Health England" - }, - { - "author_name": "Elena Fernandez", - "author_inst": "Public Health England" - }, - { - "author_name": "Marina Sanchez-Perez", - "author_inst": "Public Health England" - }, - { - "author_name": "Suzanne Tang", - "author_inst": "Public Health England" - }, - { - "author_name": "Kate Dun-Campbell", - "author_inst": "Public Health England" - }, - { - "author_name": "Edward Wynne-Evans", - "author_inst": "Public Health England" - }, - { - "author_name": "Anita Bell", - "author_inst": "Public Health England" - }, - { - "author_name": "Bharat Patel", - "author_inst": "Public Health England" + "author_name": "Rongjuan Pei", + "author_inst": "Center for Biosafety Mega-Science, Wuhan Institute of Virology, Chinese Academy of Sciences, Wuhan 430071, China" }, { - "author_name": "Zahin Amin-Chowdhury", - "author_inst": "Public Health England" + "author_name": "Jianqi Feng", + "author_inst": "Cancer Research Institute, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China" }, { - "author_name": "Felicity Aiano", - "author_inst": "Public Health England" + "author_name": "Yecheng Zhang", + "author_inst": "Center for Biosafety Mega-Science, Wuhan Institute of Virology, Chinese Academy of Sciences, Wuhan 430071, China" }, { - "author_name": "Karthik Paranthaman", - "author_inst": "Public Health England" + "author_name": "Hao Sun", + "author_inst": "Center for Biosafety Mega-Science, Wuhan Institute of Virology, Chinese Academy of Sciences, Wuhan 430071, China" }, { - "author_name": "Thomas Ma", - "author_inst": "Public Health England" + "author_name": "Lian Li", + "author_inst": "Cancer Research Institute, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China" }, { - "author_name": "Maria Saavedra-Campos", - "author_inst": "Public Health England" + "author_name": "Xuejie Yang", + "author_inst": "Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou 510530, China" }, { - "author_name": "Joanna Ellis", - "author_inst": "Public Health England" + "author_name": "Jiangping He", + "author_inst": "The Centre of Cell Lineage and Atlas (CCLA), Bioland Laboratory (Guangzhou Regenerative Medicine and Health-Guangdong Laboratory), Guangzhou 510530, China" }, { - "author_name": "Meera Chand", - "author_inst": "Public Health England" + "author_name": "Shuqi Xiao", + "author_inst": "Center for Biosafety Mega-Science, Wuhan Institute of Virology, Chinese Academy of Sciences, Wuhan 430071, China" }, { - "author_name": "Kevin Brown", - "author_inst": "Public Health England" + "author_name": "Jin Xiong", + "author_inst": "Center for Biosafety Mega-Science, Wuhan Institute of Virology, Chinese Academy of Sciences, Wuhan 430071, China" }, { - "author_name": "Mary E Ramsay", - "author_inst": "Public Health England" + "author_name": "Ying Lin", + "author_inst": "Cancer Research Institute, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China" }, { - "author_name": "Susan Hopkins", - "author_inst": "Public Health England" + "author_name": "Kun Wen", + "author_inst": "Microbiome Medicine Center, Division of Laboratory Medicine, Zhujiang Hospital, Southern Medical University, Guangzhou, China" }, { - "author_name": "Nandini Shetty", - "author_inst": "Public Health England" + "author_name": "Hongwei Zhou", + "author_inst": "Microbiome Medicine Center, Division of Laboratory Medicine, Zhujiang Hospital, Southern Medical University, Guangzhou, China" }, { - "author_name": "J Yimmy Chow", - "author_inst": "Public Health England" + "author_name": "Jiekai Chen", + "author_inst": "Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou 510530, China" }, { - "author_name": "Robin Gopal", - "author_inst": "Public Health England" + "author_name": "Zhili Rong", + "author_inst": "Southern Medical University" }, { - "author_name": "Maria Zambon", - "author_inst": "Public Health England" + "author_name": "Xinwen Chen", + "author_inst": "Center for Biosafety Mega-Science, Wuhan Institute of Virology, Chinese Academy of Sciences, Wuhan 430071, China" } ], "version": "1", "license": "cc_by_nc_nd", - "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "type": "new results", + "category": "microbiology" }, { "rel_doi": "10.1101/2020.08.11.20145458", @@ -1239273,143 +1239902,35 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2020.08.06.20169573", - "rel_title": "Beneficial effects of colchicine for moderate to severe COVID-19: an interim analysis of a randomized, double-blinded, placebo controlled clinical trial", + "rel_doi": "10.1101/2020.08.07.20170035", + "rel_title": "Quantifying threat from COVID-19 infection hazard in Primary Schools in England", "rel_date": "2020-08-11", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.06.20169573", - "rel_abs": "IntroductionNeutrophilia and high levels of proinflammatory cytokines and other mediators of inflammation are common finds in patients with severe acute respiratory syndrome due to COVID-19. By its action on leukocytes, we propose colchicine as an intervention worthy of being tested.\n\nObjectiveTo evaluate whether the addition of colchicine to standard treatment for COVID-19 results in better outcomes.\n\nMethodsWe present the interim analysis of a single-center randomized, double-blinded, placebo controlled clinical trial of colchicine for the treatment of moderate to severe COVID-19, with 38 patients allocated 1:1 from April 11 to July 06, 2020. Colchicine regimen was 0.5 mg thrice daily for 5 days, then 0.5 mg twice daily for 5 days. The first dose was 1.0 mg whether body weight was [≥] 80 kg.\n\nEndpointsThe primary endpoints were the need for supplemental oxygen; time of hospitalization; need for admission and length of stay in intensive care units; and death rate and causes of mortality. As secondary endpoints, we assessed: serum C-reactive protein, serum Lactate dehydrogenase and relation neutrophil to lymphocyte of peripheral blood samples from day zero to day 7; the number, type, and severity of adverse events; frequency of interruption of the study protocol due to adverse events; and frequency of QT interval above 450 ms.\n\nResultsThirty-five patients (18 for Placebo and 17 for Colchicine) completed the study. Both groups were comparable in terms of demographic, clinical and laboratory data at baseline. Median (and interquartile range) time of need for supplemental oxygen was 3.0 (1.5-6.5) days for the Colchicine group and 7.0 (3.0-8.5) days for Placebo group (p = 0.02). Median (IQR) time of hospitalization was 6.0 (4.0-8.5) days for the Colchicine group and 8.5 (5.5-11.0) days for Placebo group (p = 0.03). At day 2, 53% vs 83% of patients maintained the need for supplemental oxygen, while at day 7 the values were 6% vs 39%, in the Colchicine and Placebo groups, respectively (log rank; p = 0.01). Hospitalization was maintained for 53% vs 78% of patients at day 5 and 6% vs 17% at day 10, for the Colchicine and Placebo groups, respectively (log rank; p = 0.01). One patient per group needed admission to ICU. No recruited patient died. At day 4, patients of Colchicine group presented significant reduction of serum C-reactive protein compared to baseline (p < 0.001). The majority of adverse events were mild and did not lead to patient withdrawal. Diarrhea was more frequent in the Colchicine group (p = 0.17). Cardiac adverse events were absent.\n\nDiscussionThe use of colchicine reduced the length of supplemental oxygen therapy and the length of hospitalization. Clinical improvement was in parallel with a reduction on serum levels of C-reactive protein. The drug was safe and well tolerated. Colchicine may be considered a beneficial and not expensive option for COVID-19 treatment. Clinical trials with larger numbers of patients should be conducted to further evaluate the efficacy and safety of colchicine as an adjunctive therapy for hospitalized patients with moderate to severe COVID-19.", - "rel_num_authors": 31, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.07.20170035", + "rel_abs": "We have constructed a COVID-19 infection hazard model for the return of pupils to the 16,769 state Primary Schools in England that takes into account uncertainties in model input parameters. The basic probabilistic model estimates likely number of primary schools with one or more infected persons under three different return-to-school circumstances. Inputs to the infection hazard model are: the inventory of children, teachers and support staff; the prevalence of COVID-19 in the general community including its spatial variation, and the ratio of adult susceptibility to that of children. Three scenarios of inventory are: the counts on 1st June when schools re-opened to Nursery, Reception, Year 1 and Year 6 children, when approximately one-third of eligible children attended; a scenario assuming a full return of eligible children in those cohorts; and a return of all primary age children, scheduled for September. With a national average prevalence, we find that for the first scenario between 178 and 924 schools out of 16,769 in total (i.e. about 1% and 5.5% respectively) may have infected individuals present, expressed as a 90% credible interval. For the second scenario, the range is between 336 (2%) and 1873 (11%) schools with one (or more) infected persons, while for the third scenario the range is 661 (4%) to 3310 (20%) schools, assuming that the prevalence is the same as it was on 5th June. The range decreases to between 381 (2%) and 900 (5%) schools with an infected person if prevalence is one-quarter that of 5th June, and increases to between 2131 (13%) and 9743 (58%) schools for the situation where prevalence increases to 4 times the 5th June level. Net prevalence of COVID-19 in schools is reduced relative to the general community because of the lower susceptibility of primary age children to infection. When regional variations in prevalence and school size distribution are taken into account there is a slight decrease in number of infected schools, but the uncertainty on these projected numbers increases markedly. The probability of having an infected school in a community is proportional to the local prevalence and school size. Analysis of a scenario equivalent to a full return to school with an average national prevalence of 1 in 1700 and spatial prevalence variations, estimated from data for late June, indicates 82% of infected schools would be located in areas where prevalence exceeds the national average. The probability of having multiple infected persons in a school increases markedly in high prevalence areas. Assuming national prevalence characteristic of early June, individual, operational and societal risk will increase if schools reopen fully in September due to both increases in numbers of children and the increased challenges of sustaining mitigation measures. Comparison between incidents in primary schools with positive tests in June and July and our estimates of number of infected schools indicates at least an order of magnitude difference. The much lower number of incidents reflects several factors, including effective reduction in transmission resulting from risk mitigation measure instigated by schools.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Maria Isabel F Lopes", - "author_inst": "Faculdade de Medicina de Ribeirao Preto - Universidade de Sao Paulo" - }, - { - "author_name": "Leticia P Bonjorno", - "author_inst": "Faculdade de Medicina de Ribeirao Preto - Universidade de Sao Paulo" - }, - { - "author_name": "Marcela C Giannini", - "author_inst": "Faculdade de Medicina de Ribeirao Preto - Universidade de Sao Paulo" - }, - { - "author_name": "Natalia B Amaral", - "author_inst": "Faculdade de Medicina de Ribeirao Preto - Universidade de Sao Paulo" - }, - { - "author_name": "Maira N Benatti", - "author_inst": "Faculdade de Medicina de Ribeirao Preto - Universidade de Sao Paulo" - }, - { - "author_name": "Uebe C Rezek", - "author_inst": "Faculdade de Medicina de Ribeirao Preto - Universidade de Sao Paulo" - }, - { - "author_name": "Laerte L Emrich-Filho", - "author_inst": "Faculdade de Medicina de Ribeirao Preto - Universidade de Sao Paulo" - }, - { - "author_name": "Betania AA Sousa", - "author_inst": "Faculdade de Medicina de Ribeirao Preto - Universidade de Sao Paulo" - }, - { - "author_name": "Sergio CL Almeida", - "author_inst": "Faculdade de Medicina de Ribeirao Preto - Universidade de Sao Paulo" - }, - { - "author_name": "Rodrigo Luppino-Assad", - "author_inst": "Faculdade de Medicina de Ribeirao Preto - Universidade de Sao Paulo" - }, - { - "author_name": "Flavio P Veras", - "author_inst": "Faculdade de Medicina de Ribeirao Preto - Universidade de Sao Paulo" - }, - { - "author_name": "Ayda Schneider", - "author_inst": "Faculdade de Medicina de Ribeirao Preto - Universidade de Sao Paulo" - }, - { - "author_name": "Tamara S Rodrigues", - "author_inst": "Faculdade de Medicina de Ribeirao Preto - Universidade de Sao Paulo" - }, - { - "author_name": "Luiz OS Leiria", - "author_inst": "Faculdade de Medicina de Ribeirao Preto - Universidade de Sao Paulo" - }, - { - "author_name": "Larissa D Cunha", - "author_inst": "Faculdade de Medicina de Ribeirao Preto - Universidade de Sao Paulo" - }, - { - "author_name": "Jose C Alves-Filho", - "author_inst": "Faculdade de Medicina de Ribeirao Preto - Universidade de Sao Paulo" - }, - { - "author_name": "Thiago M Cunha", - "author_inst": "Faculdade de Medicina de Ribeirao Preto - Universidade de Sao Paulo" - }, - { - "author_name": "Eurico Arruda Neto", - "author_inst": "Faculdade de Medicina de Ribeirao Preto - Universidade de Sao Paulo" - }, - { - "author_name": "Carlos H Miranda", - "author_inst": "Sao Paulo University" - }, - { - "author_name": "Antonio Pazin-Filho", - "author_inst": "Faculdade de Medicina de Ribeirao Preto - Universidade de Sao Paulo" - }, - { - "author_name": "Maria A Martins", - "author_inst": "Faculdade de Medicina de Ribeirao Preto - Universidade de Sao Paulo" - }, - { - "author_name": "Marcos C Borges", - "author_inst": "Faculdade de Medicina de Ribeirao Preto - Universidade de Sao Paulo" - }, - { - "author_name": "Benedito AL Fonseca", - "author_inst": "Faculdade de Medicina de Ribeirao Preto - Universidade de Sao Paulo" - }, - { - "author_name": "Valdes R Bollela", - "author_inst": "Faculdade de Medicina de Ribeirao Preto - Universidade de Sao Paulo" - }, - { - "author_name": "Cristina M Del-Ben", - "author_inst": "Ribeirao Preto Medical School, University of Sao Paulo" - }, - { - "author_name": "Fernando Q Cunha Sr.", - "author_inst": "Ribeirao Preto Medical School, University of Sao Paulo" - }, - { - "author_name": "Dario S Zamboni", - "author_inst": "Universidade de Sao Paulo, School of Medicine Ribeirao Preto" - }, - { - "author_name": "Rodrigo C Santana", - "author_inst": "Faculdade de Medicina de Ribeirao Preto - Universidade de Sao Paulo" + "author_name": "Stephen RJ Sparks", + "author_inst": "University of Bristol" }, { - "author_name": "Fernando C Vilar", - "author_inst": "Faculdade de Medicina de Ribeirao Preto - Universidade de Sao Paulo" + "author_name": "William P Aspinall", + "author_inst": "University of Bristol" }, { - "author_name": "Paulo Louzada-Junior", - "author_inst": "Faculdade de Medicina de Ribeirao Preto - Universidade de Sao Paulo" + "author_name": "Roger Cooke", + "author_inst": "Delft University of Technology" }, { - "author_name": "Rene D R Oliveira", - "author_inst": "Hospital das Clinicas de Ribeirao Preto" + "author_name": "Jane H Scarrow", + "author_inst": "University of Grenada" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2020.08.07.20169904", @@ -1241091,61 +1241612,37 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2020.08.11.20172502", - "rel_title": "The COVID-19 Early Detection in Doctors and Healthcare Workers (CEDiD) Study: study protocol for a prospective observational trial", + "rel_doi": "10.1101/2020.08.11.20172478", + "rel_title": "Clustering of age standardised COVID-19 infection fatality ratios and death trajectories", "rel_date": "2020-08-11", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.11.20172502", - "rel_abs": "BackgroundThe global COVID-19 pandemic has caused worldwide disruption with its exponential spread mandating national and international lockdown measures. Hospital-associated transmission has been identified as a major factor in the perpetuation of COVID-19, with healthcare workers at high-risk of becoming infected with SARS-CoV-2 and representing important vectors for spread, but not routinely having their clinical observations monitored or being tested for COVID-19.\n\nMethodsA single-center, prospective observational study of 60 healthcare workers will explore how many healthcare workers in high-risk areas develop COVID-19 infection over a thirty day period. High-risk areas are defined as COVID positive wards, the intensive care unit or the accident and emergency department. Healthcare workers (HCWs) will be recruited and have daily self-administered nasopharyngeal SARS-CoV-2 PCR tests. They will also be provided with a wearable medical device to measure their clinical observations during non-working hours, and be asked to complete a daily self-reported symptom questionnaire over the study period. Statistical analysis will assess the proportion of healthcare workers who develop COVID-19 infection as a primary objective, with secondary objectives exploring what symptoms are developed, time-to-event, and deviations in clinical observations.\n\nDiscussionAt present clinical observations, symptoms and COVID-19 PCR swabs are not routinely undertaken for healthcare workers. If the CEDiD (COVID-19 Early Detection in Doctors and Healthcare Workers) study is successful, it will provide useful information for workforce decisions in reducing hospital-associated transmission of COVID-19. The data will help in determining whether there are early warning signs for development of COVID-19 infections amongst healthcare workers and may contribute to the evidence base advocating for more regular testing of healthcare workers observations, symptoms and COVID-19 status.\n\nTrial registrationClinicalTrials.gov, NCT04363489. Registered on 27th July 2020", - "rel_num_authors": 11, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.11.20172478", + "rel_abs": "BackgroundAn accurate measure of the impact of COVID-19 is the infection fatality ratio, or the proportion of deaths among those infected, which does not depend on variable testing rates between nations. The risk of mortality from COVID-19 depends strongly on age and current estimates of the infection fatality ratio do not account for differences in national age profiles. Comparisons of cumulative death trajectories allow the effect and timing of public health interventions to be assessed.\n\nOur purpose is to (1) determine whether countries are clustered according to infection fatality ratios and (2) compare interventions to slow the spread of the disease by clustering death trajectories.\n\nMethodsNational age standardised infection fatality ratios were derived from age stratified estimates from China and population estimates from the World Health Organisation. The IFRs were clustered into groups using Gaussian mixture models. Trajectory analysis clustered cumulative death rates in two time windows, 50 and 100 days after the first reported death.\n\nFindingsInfection fatality ratios from 201 nations were clustered into three groups: young, medium and older, with corresponding means (SD) of 0.20% (0.03%), 0.38% (0.11%) and 0.93% (0.21%).\n\nAt 50 and 100 days after the first reported death, there were two clusters of cumulative death trajectories from 113 nations with at least 25 deaths reported at 100 days. The first group had slowly increasing or stable cumulative death rates, while the second group had accelerating rates at the end of the time window. Fifty-two nations changed group membership between the time windows.\n\nConclusionA cluster of younger nations have a lower estimated infection fatality ratio than older nations. The effect and timing of public health interventions in preventing the spread of the disease can be tracked by clustering death rate trajectories into stable or accelerating and comparing changes over time.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Alexander Zargaran", - "author_inst": "Guy's and St Thomas' NHS Foundation Trust" - }, - { - "author_name": "Dina Radenkovic", - "author_inst": "Guy's and St Thomas' NHS Foundation Trust" - }, - { - "author_name": "Iakovos Theodoulou", - "author_inst": "Guy's and St Thomas' NHS Foundation Trust" - }, - { - "author_name": "Andrea Paraboschi", - "author_inst": "Empatica" - }, - { - "author_name": "Chelsea Trengrove", - "author_inst": "Empatica" - }, - { - "author_name": "Gary Colville", - "author_inst": "Guy's and St Thomas' NHS Foundation Trust" - }, - { - "author_name": "Gill Arbane", - "author_inst": "Guy's and St Thomas' NHS Foundation Trust" + "author_name": "Thu-Lan Kelly", + "author_inst": "South Australian Health and Medical Research Institute" }, { - "author_name": "Kariem El-Boghdadly", - "author_inst": "Guy's and St Thomas' NHS Foundation Trust" + "author_name": "Caroline Miller", + "author_inst": "South Australian Health and Medical Research Institute" }, { - "author_name": "Gaia Nebbia", - "author_inst": "Guy's and St Thomas' NHS Foundation Trust" + "author_name": "Jacqueline A Bowden", + "author_inst": "University of Adelaide" }, { - "author_name": "Rocio Teresa Martinez-Nunez", - "author_inst": "King's College London" + "author_name": "Joanne Dono", + "author_inst": "South Australian Health and Medical Research Institute" }, { - "author_name": "Anne Greenough", - "author_inst": "King's College London" + "author_name": "Paddy A Phillips", + "author_inst": "SA Commission on Excellence and Innovation in Health" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", "category": "public and global health" }, @@ -1243057,55 +1243554,59 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2020.08.07.242271", - "rel_title": "SARS-CoV-2 neutralization and serology testing of COVID-19 convalescent plasma from donors with non-severe disease", + "rel_doi": "10.1101/2020.08.09.243451", + "rel_title": "Nonstructural protein 1 of SARS-CoV-2 is a potent pathogenicity factor redirecting host protein synthesis machinery toward viral RNA.", "rel_date": "2020-08-10", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.08.07.242271", - "rel_abs": "We determined the antigen binding activity of convalescent plasma units from 47 individuals with a history of non-severe COVID-19 using three clinical diagnostic serology assays (Beckman, DiaSorin, and Roche) with different SARS-CoV-2 targets. We compared these results with functional neutralization activity using a fluorescent reporter strain of SARS-CoV-2 in a microwell assay. This revealed positive correlations of varying strength (Spearman r = 0.37-0.52) between binding and neutralization. Donors age 48-75 had the highest neutralization activity. Units in the highest tertile of binding activity for each assay were enriched (75-82%) for those with the highest levels of neutralization.", - "rel_num_authors": 9, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.08.09.243451", + "rel_abs": "The COVID-19 pandemic affects millions of people worldwide with a rising death toll. The causative agent, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), uses its nonstructural protein 1 (Nsp1) to redirect host translation machinery to the viral RNA by binding to the ribosome and suppressing cellular, but not viral, protein synthesis through yet unknown mechanisms. We show here that among all viral proteins, Nsp1 has the largest impact on host viability in the cells of human lung origin. Differential expression analysis of mRNA-seq data revealed that Nsp1 broadly alters the transcriptome in human cells. The changes include repression of major gene clusters in ribosomal RNA processing, translation, mitochondria function, cell cycle and antigen presentation; and induction of factors in transcriptional regulation. We further gained a mechanistic understanding of the Nsp1 function by determining the cryo-EM structure of the Nsp1-40S ribosomal subunit complex, which shows that Nsp1 inhibits translation by plugging the mRNA entry channel of the 40S. We also determined the cryo-EM structure of the 48S preinitiation complex (PIC) formed by Nsp1, 40S, and the cricket paralysis virus (CrPV) internal ribosome entry site (IRES) RNA, which shows that this 48S PIC is nonfunctional due to the incorrect position of the 3 region of the mRNA. Results presented here elucidate the mechanism of host translation inhibition by SARS-CoV-2, provide insight into viral protein synthesis, and furnish a comprehensive understanding of the impacts from one of the most potent pathogenicity factors of SARS-CoV-2.\n\nHighlightsORF screen identified Nsp1 as a major cellular pathogenicity factor of SARS-CoV-2\n\nNsp1 broadly alters the gene expression programs in human cells\n\nNsp1 inhibits translation by blocking mRNA entry channel\n\nNsp1 prevents physiological conformation of the 48S PIC", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Thomas J. Gniadek", - "author_inst": "NorthShore University HealthSystem" + "author_name": "Shuai Yuan", + "author_inst": "Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA." }, { - "author_name": "Joshua M. Thiede", - "author_inst": "University of Minnesota" + "author_name": "Lei Peng", + "author_inst": "Department of Genetics, Yale University School of Medicine, New Haven, CT, USA; Systems Biology Institute, Yale University, West Haven, CT, USA." }, { - "author_name": "William E. Matchett", - "author_inst": "University of Minnesota" + "author_name": "Jonathan J. Park", + "author_inst": "Department of Genetics, Yale University School of Medicine, New Haven, CT, USA; Systems Biology Institute, Yale University, West Haven, CT, USA." }, { - "author_name": "Abigail R. Gress", - "author_inst": "University of Minnesota" + "author_name": "Yingxia Hu", + "author_inst": "Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA." }, { - "author_name": "Kathryn A. Pape", - "author_inst": "University of Minnesota" + "author_name": "Swapnil C. Devarkar", + "author_inst": "Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA." }, { - "author_name": "Marc K. Jenkins", - "author_inst": "University of Minnesota" + "author_name": "Matthew B. Dong", + "author_inst": "Department of Genetics, Yale University School of Medicine, New Haven, CT, USA; Systems Biology Institute, Yale University, West Haven, CT, USA." }, { - "author_name": "Vineet D Menachery", - "author_inst": "University of Texas Medical Branch" + "author_name": "Shenping Wu", + "author_inst": "Department of Pharmacology, Yale University, West Haven, CT, USA." }, { - "author_name": "Ryan A. Langlois", - "author_inst": "University of Minnesota" + "author_name": "Sidi Chen", + "author_inst": "Yale University" }, { - "author_name": "Tyler D. Bold", - "author_inst": "University of Minnesota" + "author_name": "Ivan Lomakin", + "author_inst": "Department of Dermatology, Yale university school of medicine, New Haven, CT, USA" + }, + { + "author_name": "Yong Xiong", + "author_inst": "Yale University" } ], "version": "1", "license": "cc_no", "type": "new results", - "category": "immunology" + "category": "molecular biology" }, { "rel_doi": "10.1101/2020.08.10.244756", @@ -1245103,103 +1245604,31 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.08.06.20164848", - "rel_title": "Single-cell RNA-seq reveals profound monocyte changes in Paediatric Inflammatory Multisystem Syndrome Temporally associated with SARS-CoV-2 infection (PIMS-TS)", + "rel_doi": "10.1101/2020.08.06.20164129", + "rel_title": "Associations between personal protective equipment and nursing staff stress during the COVID-19 pandemic", "rel_date": "2020-08-07", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.06.20164848", - "rel_abs": "Multisystem inflammatory syndrome in children (MIS-C) is a life-threatening disease occurring several weeks after severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. MIS-C has overlapping clinical features with Kawasaki Disease (KD), a rare childhood vasculitis. MIS-C therapy is largely based on KD treatment protocols but whether these diseases share underpinning immunological perturbations is unknown. We performed deep immune profiling on blood samples from healthy children and patients with MIS-C or KD. Acute MIS-C patients had highly activated neutrophils, classical monocytes and memory CD8+ T-cells; increased frequencies of B-cell plasmablasts and CD27-IgD-double-negative B-cells; and increased levels of pro-inflammatory (IL6, IL18, IP10, MCP1) but also anti-inflammatory (IL-10, IL1-RA, sTNFR1, sTNFR2) cytokines. Increased neutrophil count correlated with inflammation,cardiac dysfunction and disease severity. Two days after intravenous immunoglobulin (IVIG) treatment, MIS-C patients had increased CD163 expression on monocytes, expansion of a novel population of immature neutrophils, and decreased levels of pro- and anti-inflammatory cytokines in the blood accompanied by a transient increase in arginase in some patients. Our data show MIS-C and KD share substantial immunopathology and identify potential new mechanisms of action for IVIG, a widely used anti-inflammatory drug used to treat MIS-C, KD and other inflammatory diseases.", - "rel_num_authors": 21, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.06.20164129", + "rel_abs": "BackgroundThe results of several projects on the effects of personal protective equipment (PPE) have been published since the outbreak of COVID-19. It is known that wearing PPE, and specifically face masks, has physcial consequences like headache and pain, which can Increase stress among nursing staff. However, none of these studies placed a focus on PPE and nursing staff, although nurses are the only members of the health care profession who are at the patients bedsides 24/7, and PPE is the only way to protect them from a COVID-19 infection. Therefore, this study was carried out to investigate the association between the use of PPE and stress among nursing staff during the COVID-19 pandemic.\n\nMethodsAn online, cross-sectional survey was conducted, which we distributed using snowball sampling techniques. The questionnaire was developed on the basis of (inter-)national recommendations as well as the international literature. We used the perceived level of stress scale to measure the nursing staff members stress levels.\n\nResultsWe included data collected from 2600 nurses in this analysis. Nearly all nursing staff wore face masks. We showed that more than two-thirds of the nurses had moderate to high levels of stress. No statistically significant association between the use of PPE and stress was detected. However, we show a statistically significant association between the duration of mask usage and stress.\n\nDiscussion and conclusionsNearly all participating nurses wore face masks or FFP masks to protect themselves from COVID-19 infection. This observation might indicate that Austrian nurses display a high level of compliance with national and international regulations and play a key role in such pandemics. Our results also show that increased mask-wearing time led to increased stress levels. These results suggest that (international regulations on how and when to use PPE should include a maximum duration of time for wearing each type of mask. Such regulations could help to prevent work-related stress, particularly in the case of future epidemics, and avoid burnout among nursing staff or even nurses leaving their jobs. The consequences of both of these negative outcomes should be considered in light of the predicted expected future shortage of health care workers.\n\n\"Contribution of the Paper\"\n\n\"What is already known about the topic?\"\n\nO_LIAssociations between headache and pain experienced when wearing personal protective equipment (PPE), and specifically face masks, has already been investigated.\nC_LIO_LINurses are at patients bedsides 24/7, and PPE is the only way to protect them from a COVID-19 infection.\nC_LI\n\n\"What this paper adds\"\n\nO_LIThese study results show that the stress level among nursing staff during the COVID-19 pandemic ranged from moderate to high, stress levels in general, stress levels.\nC_LIO_LIWe did not find a statistically significant association between the use of PPE and the nurses stress levels in general.\nC_LIO_LIThis study identified an association between the duration of wearing PPE and the nurses stress levels.\nC_LI", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Eleni Syrimi", - "author_inst": "University of Birmingham" - }, - { - "author_name": "Eanna Fennell", - "author_inst": "University of Limerick" - }, - { - "author_name": "Alex Richter", - "author_inst": "University of Birmingham" - }, - { - "author_name": "Pavle Vrljicak", - "author_inst": "University of Warwick" - }, - { - "author_name": "Richard Stark", - "author_inst": "University of Warwick" - }, - { - "author_name": "Sascha Ott", - "author_inst": "University of Warwick" - }, - { - "author_name": "Paul G Murray", - "author_inst": "University of Birmingham and University of Limerick" - }, - { - "author_name": "Eslam Al-abadi", - "author_inst": "Birmingham Womens and Childrens NHS Foundation Trust" - }, - { - "author_name": "Ashish Chikermane", - "author_inst": "Birmingham Womens and Childrens NHS foundation trust" - }, - { - "author_name": "Pamela Dawson", - "author_inst": "Birmingham Womens and Childrens NHS foundation trust" - }, - { - "author_name": "Scott Hackett", - "author_inst": "University Hospitals Birmingham NHS foundation trust" - }, - { - "author_name": "Deepthi Jyothish", - "author_inst": "Birmingham Womens and Childrens NHS foundation trust" - }, - { - "author_name": "Hari Krishnan Kanthimathinathan", - "author_inst": "Birmingham Womens and Childrens NHS foundation trust" - }, - { - "author_name": "Sean Monaghan", - "author_inst": "Birmingham Womens and Childrens hospital NHS foundation trust" - }, - { - "author_name": "Prasad Nagakumar", - "author_inst": "Birmingham Womens and Childrens NHS foundation trust and University of Birmingham" - }, - { - "author_name": "Naeem Khan", - "author_inst": "Clinical Immunology Service, Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham," - }, - { - "author_name": "Sian Faustini", - "author_inst": "Clinical Immunology Service, Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham," - }, - { - "author_name": "Barnaby R Scholefield", - "author_inst": "Birmingham Womens and Childrens NHS foundation trust and University of Birmingham" - }, - { - "author_name": "Steven Welch", - "author_inst": "University Hospitals Birmingham NHS Foundation Trust" + "author_name": "Manuela Hoedl", + "author_inst": "Institute of Nursing Sience, Medical University of Graz" }, { - "author_name": "Pamela Kearns", - "author_inst": "NIHR Birmingham Biomedical Research Centre and Institute of Cancer and Genomic Sciences, University of Birmingham" + "author_name": "Doris Eglseer", + "author_inst": "Institute of Nursing Sience, Medical University of Graz" }, { - "author_name": "Graham Taylor", - "author_inst": "University of Birmingham" + "author_name": "Silvia Bauer", + "author_inst": "Institute of Nursing Sience, Medical University of Graz" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "pediatrics" + "category": "nursing" }, { "rel_doi": "10.1101/2020.08.06.20168294", @@ -1247133,35 +1247562,39 @@ "category": "urology" }, { - "rel_doi": "10.1101/2020.08.04.20167650", - "rel_title": "Measurement lessons of a repeated cross-sectional household food insecurity survey during the COVID-19 pandemic in Mexico", + "rel_doi": "10.1101/2020.08.04.20168237", + "rel_title": "Short-term change in air pollution following the COVID-19 state of emergency: A national analysis for the United States", "rel_date": "2020-08-06", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.04.20167650", - "rel_abs": "ObjectiveTo validate the telephone modality of the Latin American and Caribbean Food Security Scale (ELCSA) included in three waves of a phone survey to estimate the monthly household food insecurity (HFI) prevalence during the COVID-19 pandemic in Mexico.\n\nDesignWe examined the reliability and internal validity of the ELCSA scale in three repeated waves of a cross-sectional surveys with Rasch models. We estimated the monthly prevalence of food insecurity in the general population and in households with and without children, and compared them with a national 2018 survey. We tested concurrent validity by testing associations of HFI with socioeconomic status and anxiety.\n\nSettingENCOVID-19 is a monthly telephone cross-sectional survey collecting information on the well-being of Mexican households during the pandemic lockdown. Surveys used probabilistic samples and we used data from April (n=833), May (n=850), and June 2020 (n=1,674).\n\nParticipantsMexicans 18 years or older who had a mobile telephone.\n\nResultsELCSA had adequate model fit and HFI was associated, within each wave, with more poverty and anxiety. The COVID-19 lockdown was associated with an important reduction in food security; decreasing stepwise from 38.9% in 2018 to 24.9% in June 2020 in households with children.\n\nConclusionsTelephone surveys are a feasible strategy to monitor food insecurity with ELCSA", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.04.20168237", + "rel_abs": "Lockdown measures taken in response to the COVID-19 pandemic produced sudden social and economic changes. We examined the extent of air pollution reduction that was attained under these extreme circumstances, whether these reductions occurred everywhere in the US, and the local factors that drove them. Employing counterfactual time series analysis based on seasonal autoregressive integrated moving average models, we found that these extreme lockdown measures led to a reduction in the weekly PM2.5 average by up to 3.4 {micro}g m-3 and the weekly NO2 average by up to 11 ppb. These values represent a substantial fraction of the annual mean NAAQS values of 12 {micro}g m-3 and 53 ppb, respectively. We found evidence of a statistically significant decline in NO2 concentrations following the state-level emergency declaration in almost all states. However, statistically significant declines in PM2.5 occurred mostly in the West Coast and the Northeast. Certain states experienced a decline in NO2 but an increase in PM2.5 concentrations, indicating that these two pollutants arise from dissimilar sources in these states. Finally, we found evidence that states with a higher percentage of mobile source emissions prior to the emergency measures experienced a greater decline in NO2 levels during the pandemic. Although the current social and economic restrictions are not sustainable, our results provide a benchmark to estimate the extent to which air pollution reductions can be achieved. We also identify factors that contributed to the magnitude of pollutant reductions, which can help guide future state-level policies to sustainably reduce air pollution.\n\nSignificance statementWe quantified the reduction in air pollution levels achieved under the extreme social and economic measures that were put into place as part of COVID-19 state-level emergency declarations. We found a reduction in the weekly average PM2.5 of up to 3.4 {micro}g m-3 and the weekly average of NO2 of up to 11 ppb. These values represent a substantial fraction of the annual mean NAAQS values of 12 {micro}g m-3 and 53 ppb, respectively. States with a larger fraction of mobile source emissions (e.g., air and road traffic) prior to the pandemic experienced larger declines in NO2 emissions, whereas PM2.5 decline was seen in areas with a higher pre-pandemic proportion of emissions from mobile, stationary (e.g., industrial) and fire sources.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Pablo Gaitan-Rossi", - "author_inst": "Universidad Iberoamericana" + "author_name": "Pooja Tyagi", + "author_inst": "Harvard University" }, { - "author_name": "Mireya Vilar-Compte", - "author_inst": "Universidad Iberoamericana" + "author_name": "Danielle Braun", + "author_inst": "Harvard University" }, { - "author_name": "Graciela Teruel", - "author_inst": "Universidad Iberoamericana" + "author_name": "Benjamin Sabath", + "author_inst": "Harvard University" }, { - "author_name": "Rafael Perez-Escamilla", - "author_inst": "Yale" + "author_name": "Lucas Henneman", + "author_inst": "Harvard University" + }, + { + "author_name": "Francesca Dominici", + "author_inst": "Harvard TH Chan School of Public Health" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "nutrition" + "category": "health policy" }, { "rel_doi": "10.1101/2020.08.05.20168781", @@ -1248775,133 +1249208,197 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.08.05.20168435", - "rel_title": "First-in-Human Trial of a SARS CoV 2 Recombinant Spike Protein Nanoparticle Vaccine", + "rel_doi": "10.1101/2020.08.05.20168872", + "rel_title": "Inflammasome activation in COVID-19 patients", "rel_date": "2020-08-06", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.05.20168435", - "rel_abs": "BackgroundNVX-CoV2373 is a recombinant nanoparticle vaccine composed of trimeric full-length SARS-CoV-2 spike glycoproteins. We present the Day 35 primary analysis of our trial of NVX-CoV2373 with or without the saponin-based Matrix-M1 adjuvant in healthy adults.\n\nMethodsThis is a randomized, observer-blinded, placebo-controlled, phase 1 trial in 131 healthy adults. Trial vaccination comprised two intramuscular injections, 21 days apart. Primary outcomes were reactogenicity, safety labs, and immunoglobulin G (IgG) anti-spike protein response. Secondary outcomes included adverse events, wild-type virus neutralizing antibody, and T-cell responses.\n\nResultsParticipants received NVX-CoV2373 with or without Matrix-M1 (n=106) or placebo (n=25). There were no serious adverse events. Reactogenicity was mainly mild in severity and of short duration (mean [≤]2 days), with second vaccinations inducing greater local and systemic reactogenicity. The adjuvant significantly enhanced immune responses and was antigen dose-sparing, and the two-dose 5g NVX-CoV2373/Matrix-M1 vaccine induced mean anti-spike IgG and neutralizing antibody responses that exceeded the mean responses in convalescent sera from COVID-19 patients with clinically significant illnesses. The vaccine also induced antigen-specific T cells with a largely T helper 1 (Th1) phenotype.\n\nConclusionsNVX-CoV2373/Matrix-M1 was well tolerated and elicited robust immune responses (IgG and neutralization) four-fold higher than the mean observed in COVID-19 convalescent serum from participants with clinical symptoms requiring medical care and induced CD4+ T-cell responses biased toward a Th1 phenotype. These findings suggest that the vaccine may confer protection and support transition to efficacy evaluations to test this hypothesis. (Funded by the Coalition for Epidemic Preparedness Innovations; ClinicalTrials.gov number, NCT04368988).", - "rel_num_authors": 29, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.05.20168872", + "rel_abs": "Severe cases of COVID-19 are characterized by a strong inflammatory process that may ultimately lead to organ failure and patient death. The NLRP3 inflammasome is a molecular platform that promotes inflammation via cleavage and activation of key inflammatory molecules including active caspase-1 (Casp1p20), IL-1{beta} and IL-18. Although the participation of the inflammasome in COVID-19 has been highly speculated, the inflammasome activation and participation in the outcome of the disease is unknown. Here we demonstrate that the NLRP3 inflammasome is activated in response to SARS-CoV-2 infection and it is active in COVID-19, influencing the clinical outcome of the disease. Studying moderate and severe COVID-19 patients, we found active NLRP3 inflammasome in PBMCs and tissues of post-mortem patients upon autopsy. Inflammasome-derived products such as Casp1p20 and IL-18 in the sera correlated with the markers of COVID-19 severity, including IL-6 and LDH. Moreover, higher levels of IL-18 and Casp1p20 are associated with disease severity and poor clinical outcome. Our results suggest that the inflammasome is key in the pathophysiology of the disease, indicating this platform as a marker of disease severity and a potential therapeutic target for COVID-19.", + "rel_num_authors": 45, "rel_authors": [ { - "author_name": "Cheryl Keech", - "author_inst": "Novavax, Inc." + "author_name": "Tamara S Rodrigues", + "author_inst": "Departamento de Biologia Celular e Molecular e Bioagentes Patogenicos. Faculdade de Medicina de Ribeirao Preto, Universidade de Sao Paulo." }, { - "author_name": "Gary Albert", - "author_inst": "Novavax, Inc." + "author_name": "Keyla SG Sa", + "author_inst": "Departamento de Biologia Celular e Molecular e Bioagentes Patogenicos. Faculdade de Medicina de Ribeirao Preto, Universidade de Sao Paulo." }, { - "author_name": "Patricia Reed", - "author_inst": "Novavax, Inc." + "author_name": "Adriene Y Ishimoto", + "author_inst": "Departamento de Biologia Celular e Molecular e Bioagentes Patogenicos. Faculdade de Medicina de Ribeirao Preto, Universidade de Sao Paulo." }, { - "author_name": "Susan Neal", - "author_inst": "Novavax, Inc." + "author_name": "Amanda Becerra", + "author_inst": "Departamento de Biologia Celular e Molecular e Bioagentes Patogenicos. Faculdade de Medicina de Ribeirao Preto, Universidade de Sao Paulo." }, { - "author_name": "Joyce S. Plested", - "author_inst": "Novavax, Inc." + "author_name": "Samuel Oliveira", + "author_inst": "Departamento de Biologia Celular e Molecular e Bioagentes Patogenicos. Faculdade de Medicina de Ribeirao Preto, Universidade de Sao Paulo." }, { - "author_name": "Mingzhu Zhu", - "author_inst": "Novavax, Inc." + "author_name": "Leticia Almeida", + "author_inst": "Departamento de Biologia Celular e Molecular e Bioagentes Patogenicos. Faculdade de Medicina de Ribeirao Preto, Universidade de Sao Paulo." }, { - "author_name": "Shane Cloney-Clark", - "author_inst": "Novavax, Inc." + "author_name": "Augusto V Goncalves", + "author_inst": "Departamento de Biologia Celular e Molecular e Bioagentes Patogenicos. Faculdade de Medicina de Ribeirao Preto, Universidade de Sao Paulo." }, { - "author_name": "Haixia Zhou", - "author_inst": "Novavax, Inc." + "author_name": "Debora B Perucello", + "author_inst": "Departamento de Biologia Celular e Molecular e Bioagentes Patogenicos. Faculdade de Medicina de Ribeirao Preto, Universidade de Sao Paulo." }, { - "author_name": "Nita Patel", - "author_inst": "Novavax, Inc." + "author_name": "Warrison A Andrade", + "author_inst": "Departamento de Biologia Celular e Molecular e Bioagentes Patogenicos. Faculdade de Medicina de Ribeirao Preto, Universidade de Sao Paulo." }, { - "author_name": "Matthew B. Frieman", - "author_inst": "University of Maryland School of Medicine" + "author_name": "Ricardo Castro", + "author_inst": "Departamento de Analises Clinicas, Toxicologicas e Bromatologia. Faculdade de Ciencias Farmaceuticas de Ribeirao Preto, Universidade de Sao Paulo." }, { - "author_name": "Robert E. Haupt", - "author_inst": "University of Maryland School of Medicine" + "author_name": "Flavio P Veras", + "author_inst": "Departamento de Farmacologia, Faculdade de Medicina de Ribeirao Preto, Universidade de Sao Paulo." }, { - "author_name": "James Logue", - "author_inst": "University of Maryland School of Medicine" + "author_name": "Juliana E Toller-Kawahisa", + "author_inst": "Departamento de Farmacologia, Faculdade de Medicina de Ribeirao Preto, Universidade de Sao Paulo." }, { - "author_name": "Marisa McGrath", - "author_inst": "University of Maryland School of Medicine" + "author_name": "Daniele C Nascimento", + "author_inst": "Departamento de Farmacologia, Faculdade de Medicina de Ribeirao Preto, Universidade de Sao Paulo." }, { - "author_name": "Stuart Weston", - "author_inst": "University of Maryland School of Medicine" + "author_name": "Mikhael HF de Lima", + "author_inst": "Departamento de Farmacologia, Faculdade de Medicina de Ribeirao Preto, Universidade de Sao Paulo." }, { - "author_name": "Pedro A. Piedra", - "author_inst": "Baylor University College of Medicine" + "author_name": "Camila MS Silva", + "author_inst": "Departamento de Farmacologia, Faculdade de Medicina de Ribeirao Preto, Universidade de Sao Paulo." }, { - "author_name": "Iksung Cho", - "author_inst": "Novavax, Inc." + "author_name": "Diego B Caetite", + "author_inst": "Departamento de Farmacologia, Faculdade de Medicina de Ribeirao Preto, Universidade de Sao Paulo." }, { - "author_name": "Andreana Robertson", - "author_inst": "Novavax, Inc." + "author_name": "Ronaldo B Martins", + "author_inst": "Departamento de Biologia Celular e Molecular e Bioagentes Patogenicos. Faculdade de Medicina de Ribeirao Preto, Universidade de Sao Paulo." }, { - "author_name": "Chinar Desai", - "author_inst": "Novavax, Inc." + "author_name": "Italo A Castro", + "author_inst": "Departamento de Biologia Celular e Molecular e Bioagentes Patogenicos. Faculdade de Medicina de Ribeirao Preto, Universidade de Sao Paulo." }, { - "author_name": "Kathleen Callahan", - "author_inst": "Novavax, Inc." + "author_name": "Marjorie C Pontelli", + "author_inst": "Departamento de Biologia Celular e Molecular e Bioagentes Patogenicos. Faculdade de Medicina de Ribeirao Preto, Universidade de Sao Paulo." }, { - "author_name": "Maggie Lewis", - "author_inst": "Novavax, Inc." + "author_name": "Fabio C de Barros", + "author_inst": "Departamento de Ecologia e Biologia Evolutiva, Instituto de Ciencias Ambientais, Quimicas e Farmaceuticas, Universidade Federal de Sao Paulo" }, { - "author_name": "Patricia Price-Abbott", - "author_inst": "Novavax, Inc." + "author_name": "Natalia B do Amaral", + "author_inst": "Divisao de Imunologia Clinica, Emergencia, Doencas Infecciosas e Unidade de Terapia Intensiva, Faculdade de Medicina de Ribeirao Preto, Universidade de Sao Paul" }, { - "author_name": "Neil Formica", - "author_inst": "Novavax, Inc." + "author_name": "Marcela C Giannini", + "author_inst": "Divisao de Imunologia Clinica, Emergencia, Doencas Infecciosas e Unidade de Terapia Intensiva, Faculdade de Medicina de Ribeirao Preto, Universidade de Sao Paul" }, { - "author_name": "Vivek Shinde", - "author_inst": "Novavax, Inc." + "author_name": "Leticia P Bonjorno", + "author_inst": "Divisao de Imunologia Clinica, Emergencia, Doencas Infecciosas e Unidade de Terapia Intensiva, Faculdade de Medicina de Ribeirao Preto, Universidade de Sao Paul" }, { - "author_name": "Louis Fries", - "author_inst": "Novavax, Inc." + "author_name": "Maria Isabel F Lopes", + "author_inst": "Divisao de Imunologia Clinica, Emergencia, Doencas Infecciosas e Unidade de Terapia Intensiva, Faculdade de Medicina de Ribeirao Preto, Universidade de Sao Paul" }, { - "author_name": "Jason D. Linkliter", - "author_inst": "Nucleus Network Pty Ltd" + "author_name": "Maira N Benatti", + "author_inst": "Divisao de Imunologia Clinica, Emergencia, Doencas Infecciosas e Unidade de Terapia Intensiva, Faculdade de Medicina de Ribeirao Preto, Universidade de Sao Paul" }, { - "author_name": "Paul Griffin", - "author_inst": "Q-Pharm" + "author_name": "Rodrigo C Santana", + "author_inst": "Divisao de Imunologia Clinica, Emergencia, Doencas Infecciosas e Unidade de Terapia Intensiva, Faculdade de Medicina de Ribeirao Preto, Universidade de Sao Paul" }, { - "author_name": "Bethanie Wilkinson", - "author_inst": "Novavax, Inc." + "author_name": "Fernando C Vilar", + "author_inst": "Divisao de Imunologia Clinica, Emergencia, Doencas Infecciosas e Unidade de Terapia Intensiva, Faculdade de Medicina de Ribeirao Preto, Universidade de Sao Paul" }, { - "author_name": "Gale Smith", - "author_inst": "Novavax, Inc." + "author_name": "Maria Auxiliadora-Martins", + "author_inst": "Divisao de Medicina Intensiva, Departamento de Cirurgia e Anatomia, Faculdade de Medicina de Ribeirao Preto, Universidade de Sao Paulo." }, { - "author_name": "Gregory M. Glenn", - "author_inst": "Novavax, Inc." + "author_name": "Rodrigo Luppino-Assad", + "author_inst": "Divisao de Imunologia Clinica, Emergencia, Doencas Infecciosas e Unidade de Terapia Intensiva, Faculdade de Medicina de Ribeirao Preto, Universidade de Sao Paul" + }, + { + "author_name": "Sergio CL de Almeida", + "author_inst": "Divisao de Imunologia Clinica, Emergencia, Doencas Infecciosas e Unidade de Terapia Intensiva, Faculdade de Medicina de Ribeirao Preto, Universidade de Sao Paul" + }, + { + "author_name": "Fabiola R de Oliveira", + "author_inst": "Divisao de Imunologia Clinica, Emergencia, Doencas Infecciosas e Unidade de Terapia Intensiva, Faculdade de Medicina de Ribeirao Preto, Universidade de Sao Paul" + }, + { + "author_name": "Sabrina S Batah", + "author_inst": "Departamento de Patologia e Medicina Legal, Faculdade de Medicina de Ribeirao Preto, Universidade de Sao Paulo." + }, + { + "author_name": "Li Siyuan", + "author_inst": "Departamento de Patologia e Medicina Legal, Faculdade de Medicina de Ribeirao Preto, Universidade de Sao Paulo." + }, + { + "author_name": "Maira N Benatti", + "author_inst": "Departamento de Patologia e Medicina Legal, Faculdade de Medicina de Ribeirao Preto, Universidade de Sao Paulo." + }, + { + "author_name": "Thiago M Cunha", + "author_inst": "Departamento de Farmacologia, Faculdade de Medicina de Ribeirao Preto, Universidade de Sao Paulo." + }, + { + "author_name": "Jose C Alves-Filho", + "author_inst": "Departamento de Farmacologia, Faculdade de Medicina de Ribeirao Preto, Universidade de Sao Paulo." + }, + { + "author_name": "Fernando Q Cunha", + "author_inst": "Departamento de Farmacologia, Faculdade de Medicina de Ribeirao Preto, Universidade de Sao Paulo." + }, + { + "author_name": "Larissa D Cunha", + "author_inst": "Departamento de Biologia Celular e Molecular e Bioagentes Patogenicos. Faculdade de Medicina de Ribeirao Preto, Universidade de Sao Paulo." + }, + { + "author_name": "Fabiani G Frantz", + "author_inst": "Departamento de Analises Clinicas, Toxicologicas e Bromatologia. Faculdade de Ciencias Farmaceuticas de Ribeirao Preto, Universidade de Sao Paulo." + }, + { + "author_name": "Tiana Kohlsdorf", + "author_inst": "Departamento de Biologia, Faculdade de Filosofia Ciencias e Letras de Ribeirao Preto, Universidade de Sao Paulo." + }, + { + "author_name": "Alexandre T Fabro", + "author_inst": "Departamento de Patologia e Medicina Legal, Faculdade de Medicina de Ribeirao Preto, Universidade de Sao Paulo." + }, + { + "author_name": "Eurico Arruda", + "author_inst": "Departamento de Biologia Celular e Molecular e Bioagentes Patogenicos. Faculdade de Medicina de Ribeirao Preto, Universidade de Sao Paulo." + }, + { + "author_name": "Rene DR de Oliveira", + "author_inst": "Divisao de Imunologia Clinica, Emergencia, Doencas Infecciosas e Unidade de Terapia Intensiva, Faculdade de Medicina de Ribeirao Preto, Universidade de Sao Paul" + }, + { + "author_name": "Paulo Louzada-Junior", + "author_inst": "Divisao de Imunologia Clinica, Emergencia, Doencas Infecciosas e Unidade de Terapia Intensiva, Faculdade de Medicina de Ribeirao Preto, Universidade de Sao Paul" + }, + { + "author_name": "Dario S Zamboni", + "author_inst": "Departamento de Biologia Celular e Molecular e Bioagentes Patogenicos. Faculdade de Medicina de Ribeirao Preto, Universidade de Sao Paulo." } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1250657,43 +1251154,31 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.07.26.20156380", - "rel_title": "The Impact of COVID-19 on Medical Practice: A Nationwide Survey of Dermatologists and Healthcare Providers", + "rel_doi": "10.1101/2020.07.31.20165696", + "rel_title": "Paradoxical Case Fatality Rate dichotomy of Covid-19 among rich and poor nations points to the hygiene hypothesis.", "rel_date": "2020-08-04", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.26.20156380", - "rel_abs": "BackgroundThe COVID-19 pandemic has dramatically changed medical practice worldwide. It posed a significant impact on different health services, including dermatology.\n\nMethodsA Cross-sectional observational study of 200 healthcare providers and 100 dermatologists (survey 1 and 2, respectively) were conducted.\n\nObjectivesTo determine the prevalence of occupational skin diseases among healthcare providers working amid the pandemic, and to demonstrate the outbreaks impact on dermatology practice.\n\nResultsMost healthcare providers (83%) reported hygiene-related hand dermatitis. The rates of PPE-related dermatoses were estimated to be 73%, including pressure injuries (51.9%), acne (33.1%), non-gloves contact dermatitis (29.9%), nonspecific rash (17.5%), urticaria (9.1%) and skin infections (3.2%). The emerging COVID-19-related cutaneous manifestations were recognized by 20% of surveyed dermatologists, including maculopapular rash (41.67%), urticaria (37.50%), chilblain (25%) and vasculitis (16.67). Telemedicine was provided by 73% of the dermatologists, and 89% reported minimal use of immunosuppressive drugs amid the pandemic.\n\nConclusionsThis article highlights the emergence of hygiene-related hand dermatitis and PPE-related dermatoses among healthcare providers working in the COVID-19 era. It also provides an appreciation of the major impact of COVID-19 on different aspects of dermatology practice in Iraq, and how the dermatologists adapt to these unfamiliar circumstances to meet the challenges.\n\nHighlightsO_LICOVID-19 is associated with an ongoing emergence of occupational skin disease among healthcare providers\nC_LIO_LICOVID-19 posed a significant impact on medical practice, including the epidemiology of diseases, the use of telemedicine, and modification of management plans\nC_LIO_LIDermatologists play a crucial role in recognizing the cutaneous manifestations associated with COVID-19 infection.\nC_LI", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.31.20165696", + "rel_abs": "In the first six months of its deadly spread across the world, the Covid-19 incidence has exhibited interesting dichotomy between the rich and the poor countries. Surprisingly, the incidence and the Case Fatality Rate has been much higher in the richer countries compared with the poorer countries. However, the reasons behind this dichotomy have not been explained based on data or evidence, although some of the factors for the susceptibility of populations to SARS-CoV-2 infections have been proposed. We have taken into consideration all publicly available data and mined for the possible explanations in order to understand the reasons for this phenomenon. The data included many parameters including demography of nations, prevalence of communicable and non-communicable diseases, sanitation parameters etc. Results of our analyses suggest that demography, improved sanitation and hygiene, and higher incidence of autoimmune disorders as the most plausible factors to explain higher death rates in the richer countries Thus, the much debated \"hygiene hypothesis\" appears to lend credence to the Case Fatality Rate dichotomy between the rich and the poor countries.\n\nSignificanceThe current COVID-19 epidemic has emerged as one of the deadliest of all infectious diseases in recent times and has affected all nations, especially the developed ones. In such times it is imperative to understand the most significant factor contributing towards higher mortality. Our analysis shows a higher association of demography, sanitation & autoimmunity to COVID-19 mortality as compared to the developmental parameters such as the GDP and the HDI globally. The dependence of sanitation parameters as well as autoimmunity upon the mortality gives direct evidences in support of the lower deaths in nations whose population do not confer to higher standards of hygiene practices and have lower prevalence of autoimmune diseases. This study calls attention to immune training and strengthening through various therapeutic interventions across populations.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Mohammed Shanshal", - "author_inst": "Baghdad Teaching Hospital" - }, - { - "author_name": "Hayder Saad Ahmed", - "author_inst": "University of Tikrit, College of Medicine, Department of Dermatology and Venereology" - }, - { - "author_name": "Hayder Asfoor", - "author_inst": "University of Kerbala, College of Medicine, Department of Medicine" - }, - { - "author_name": "Raad Ibrahim Salih", - "author_inst": "University of Tikrit, College of Medicine, Department of Dermatology and Venereology" + "author_name": "Bithika Chatterjee", + "author_inst": "National Centre For Cell Sciences" }, { - "author_name": "Shehab Ahmed Ali", - "author_inst": "Al- iskandria Hospital, Department of Dermatology and Venereology" + "author_name": "Rajeeva Laxman Karandikar", + "author_inst": "Chennai Mathematical Institute" }, { - "author_name": "Yusif k. Aldabouni", - "author_inst": "Baghdad Teaching Hospital" + "author_name": "Shekhar C. Mande", + "author_inst": "Council of Scientific and Industrial Research (CSIR)" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "dermatology" + "category": "epidemiology" }, { "rel_doi": "10.1101/2020.07.31.20165662", @@ -1252659,29 +1253144,37 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.07.31.20166298", - "rel_title": "Estimating the reproductive number R0 of SARS-CoV-2 in the United States and eight European countries and implications for vaccination", + "rel_doi": "10.1101/2020.07.31.20166348", + "rel_title": "Containing the Spread of Infectious Disease on College Campuses", "rel_date": "2020-08-04", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.31.20166298", - "rel_abs": "SARS-CoV-2 rapidly spread from a regional outbreak to a global pandemic in just a few months. Global research efforts have focused on developing effective vaccines against SARS-CoV-2 and the disease it causes, COVID-19. However, some of the basic epidemiological parameters, such as the exponential epidemic growth rate and the basic reproductive number, R0, across geographic areas are still not well quantified. Here, we developed and fit a mathematical model to case and death count data collected from the United States and eight European countries during the early epidemic period before broad control measures were implemented. Results show that the early epidemic grew exponentially at rates between 0.19-0.29/day (epidemic doubling times between 2.4-3.6 days). We discuss the current estimates of the mean serial interval, and argue that existing evidence suggests that the interval is between 6-8 days in the absence of active isolation efforts. Using parameters consistent with this range, we estimated the median R0 value to be 5.8 (confidence interval: 4.7-7.3) in the United States and between 3.6 and 6.1 in the eight European countries. This translates to herd immunity thresholds needed to stop transmission to be between 73% and 84%. We further analyze how vaccination schedules depends on R0, the duration of vaccine-induced immunity to SARS-CoV-2, and show that individual-level heterogeneity in vaccine induced immunity can significantly affect vaccination schedules.\n\nSignificanceWith the global efforts to develop vaccines for COVID-19, it is important to understand the contagiousness of the virus to design regional vaccination policy. To that end, we fit a mathematical model to data collected from the early epidemic period in the United States and eight European countries, estimating that the early epidemic doubles between 2.4-3.6 days. This suggests that SARS-CoV-2 is highly transmissible in the absence of strong control measures irrespective of heterogeneity in geographic and social settings. We estimated the median basic reproduction number, R0 to be 5.8 (confidence interval: 4.7-7.3) in the United States and between 3.6 and 6.1 in the eight European countries. The herd immunity needed to stop transmission is high (between 73% and 84%).", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.31.20166348", + "rel_abs": "College campuses are highly vulnerable to infectious disease outbreaks, and there is a pressing need to develop better strategies to mitigate their size and duration, particularly as educational institutions around the world reopen to in-person instruction during the COVID-19 pandemic. Towards addressing this need, we applied a stochastic compartmental model to quantify the impact of university-level responses to past mumps outbreaks in college campuses and used it to determine which control interventions are most effective. Mumps is a very relevant disease in such settings, given its airborne mode of transmission, high infectivity, and recurrence of outbreaks despite availability of a vaccine. Our model allows for stochastic variation in small populations, missing or unobserved case data, and changes in disease transmission rates post-intervention. We tested the model and assessed various interventions using data from the 2014 and 2016 mumps outbreaks at Ohio State University and Harvard University, respectively. Our results suggest that in order to decrease infectious disease incidence on their campuses, universities should apply diagnostic protocols that address false negatives from molecular tests, stricter quarantine policies, and effective awareness campaigns among their students and staff. However, one needs to be careful about the assumptions implicit in the model to ensure that the estimated parameters have a reasonable interpretation. This modeling approach could be applied to data from other outbreaks in college campuses and similar small-population settings.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Ruian Ke", - "author_inst": "Los Alamos National Laboratory" + "author_name": "Mirai Shah", + "author_inst": "Harvard College" }, { - "author_name": "Ethan Obie Romero-Severson", - "author_inst": "Los Alamos National Laboratory" + "author_name": "Gabrielle Ferra", + "author_inst": "Brown University" }, { - "author_name": "Steven Sanche", - "author_inst": "Los Alamos National Laboratory" + "author_name": "Susan Fitzgerald", + "author_inst": "Harvard University Health Services" }, { - "author_name": "Nick Hengartner", - "author_inst": "Los Alamos National Laboratory" + "author_name": "Paul Barreira", + "author_inst": "Harvard Medical School" + }, + { + "author_name": "Pardis Sabeti", + "author_inst": "Harvard University; The Broad Institute or MIT and Harvard; Howard Hughes Medical Institute" + }, + { + "author_name": "Andres Colubri", + "author_inst": "Harvard University; The Broad Institute or MIT and Harvard; Howard Hughes Medical Institute; University of Massachusetts Medical School" } ], "version": "1", @@ -1253961,97 +1254454,169 @@ "category": "radiology and imaging" }, { - "rel_doi": "10.1101/2020.08.01.20163733", - "rel_title": "Characteristics of 24,516 Patients Diagnosed with COVID-19 Illness in a National Clinical Research Network: Results from PCORnet", + "rel_doi": "10.1101/2020.08.02.20166876", + "rel_title": "SARS-CoV-2 Seroprevalence in Relation to Timing of Symptoms", "rel_date": "2020-08-04", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.01.20163733", - "rel_abs": "BackgroundNational data from diverse institutions across the United States are critical for guiding policymakers as well as clinical and public health leaders. This study characterized a large national cohort of patients diagnosed with COVID-19 in the U.S., compared to patients diagnosed with viral pneumonia and influenza.\n\nMethods and FindingsWe captured cross-sectional information from 36 large healthcare systems in 29 U.S. states, participating in PCORnet(R), the National Patient-Centered Clinical Research Network. Patients included were those diagnosed with COVID-19, viral pneumonia and influenza in any care setting, starting from January 1, 2020. Using distributed queries executed at each participating institution, we acquired information for patients on care setting (any, ambulatory, inpatient or emergency department, mechanical ventilator), age, sex, race, state, comorbidities (assessed with diagnostic codes), and medications used for treatment of COVID-19 (hydroxychloroquine with or without azithromycin; corticosteroids, anti-interleukin-6 agents).\n\nDuring this time period, 24,516 patients were diagnosed with COVID-19, with 42% in an emergency department or inpatient hospital setting; 79,639 were diagnosed with viral pneumonia (53% inpatient/ED) and 163,984 with influenza (41% inpatient/ED). Among COVID-19 patients, 68% were 20 to <65 years of age, with more of the hospitalized/ED patients in older age ranges (23% 65+ years vs. 12% for COVID-19 patients in the ambulatory setting). Patients with viral pneumonia were of a similar age, and patients with influenza were much younger. Comorbidities were common, especially for patients with COVID-19 and viral pneumonia, with hypertension (32% for COVID-19 and 46% for viral pneumonia), arrhythmias (20% and 35%), and pulmonary disease (19% and 40%) the most common. Hydroxychloroquine was used in treatment for 33% and tocilizumab for 11% of COVID-19 patients on mechanical ventilators (25% received azithromycin as well).\n\nConclusion and RelevancePCORnet leverages existing data to capture information on one of the largest U.S. cohorts to date of patients diagnosed with COVID-19 compared to patients diagnosed with viral pneumonia and influenza.", - "rel_num_authors": 20, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.02.20166876", + "rel_abs": "Of individuals with SARS-CoV-2 IgG antibody testing performed, those who contemporaneously experienced a cluster of Covid-19 relevant symptoms in the 1-2 months preceding the antibody assay were more likely to test positive whereas those who experienced the symptom clustering in the prior 3-6 months were more likely to test negative. These findings suggest that antibodies likely wane over a period of months, particularly in relation to the timing of symptoms.", + "rel_num_authors": 38, "rel_authors": [ { - "author_name": "Jason P Block", - "author_inst": "Harvard Pilgrim Health Care Institute/Harvard Medical School" + "author_name": "Joseph Ebinger", + "author_inst": "Cedars-Sinai Medical Center" }, { - "author_name": "Keith A. Marsolo", - "author_inst": "Duke University" + "author_name": "Gregory J. Botwin", + "author_inst": "Cedars-Sinai Medical Center" }, { - "author_name": "Kshema Nagavedu", - "author_inst": "Harvard Pilgrim Health Care Institute" + "author_name": "Christine M. Albert", + "author_inst": "Cedars-Sinai Medical Center" }, { - "author_name": "L Charles Bailey", - "author_inst": "Childrens Hospital of Philadelphia" + "author_name": "Mona Alotaibi", + "author_inst": "University of California, San Diego" }, { - "author_name": "Henry Cruz", - "author_inst": "PCORnet" + "author_name": "Moshe Arditi", + "author_inst": "Cedars-Sinai Medical Center" }, { - "author_name": "Christopher B. Forrest", - "author_inst": "Childrens Hospital of Philadelphia" + "author_name": "Anders H. Berg", + "author_inst": "Cedars-Sinai Medical Center" }, { - "author_name": "Kevin Haynes", - "author_inst": "HealthCore" + "author_name": "Aleksandra Binek", + "author_inst": "Cedars-Sinai Medical Center" }, { - "author_name": "Adrian F. Hernandez", - "author_inst": "Duke Clinical Research Institute" + "author_name": "Patrick Botting", + "author_inst": "Cedars-Sinai Medical Center" }, { - "author_name": "Rainu Kaushal", - "author_inst": "Weill Cornell Medicine" + "author_name": "Justyna Fert-Bober", + "author_inst": "Cedars-Sinai Medical Center" }, { - "author_name": "Abel Kho", - "author_inst": "Northwestern University" + "author_name": "Jane C. Figueiredo", + "author_inst": "Cedars-Sinai Medical Center" }, { - "author_name": "Kathleen M. McTigue", - "author_inst": "University of Pittsburgh" + "author_name": "Jonathan D. Grein", + "author_inst": "Cedars-Sinai Medical Center" }, { - "author_name": "Vinit P. Nair", - "author_inst": "PRACnet" + "author_name": "Wohaib Hasan", + "author_inst": "Cedars-Sinai Medical Center" }, { - "author_name": "Richard Platt", - "author_inst": "Harvard Pilgrim Health Care Institute/Harvard Medical School" + "author_name": "Mir Henglin", + "author_inst": "Cedars-Sinai Medical Center" }, { - "author_name": "Jon Puro", - "author_inst": "OCHIN, Inc" + "author_name": "Shehnaz K. Hussain", + "author_inst": "Cedars-Sinai Medical Center" }, { - "author_name": "Russell L. Rothman", - "author_inst": "Vanderbilt University Medical Center" + "author_name": "Mohit Jain", + "author_inst": "University of California, San Diego" }, { - "author_name": "Elizabeth Shenkman", - "author_inst": "College of Medicine, University of Florida" + "author_name": "Sandy Joung", + "author_inst": "Cedars-Sinai Medical Center" }, { - "author_name": "Lemuel Russell Waitman", - "author_inst": "University of Kansas Medical Center" + "author_name": "Michael Karin", + "author_inst": "University of California, San Diego" }, { - "author_name": "Mark G. Weiner", - "author_inst": "Weill Cornell Medicine" + "author_name": "Elizabeth H. Kim", + "author_inst": "Cedars-Sinai Medical Center" }, { - "author_name": "Neely Williams", - "author_inst": "Community Partners Network Inc" + "author_name": "Dalin Li", + "author_inst": "Cedars-Sinai Medical Center" }, { - "author_name": "Thomas W. Carton", - "author_inst": "Louisiana Public Health Institute" + "author_name": "Yunxian Liu", + "author_inst": "Cedars-Sinai Medical Center" + }, + { + "author_name": "Eric Luong", + "author_inst": "Cedars-Sinai Medical Center" + }, + { + "author_name": "Dermot P.B. McGovern", + "author_inst": "Cedars-Sinai Medical Center" + }, + { + "author_name": "Akil Merchant", + "author_inst": "Cedars-Sinai Medical Center" + }, + { + "author_name": "Noah Merin", + "author_inst": "Cedars-Sinai Medical Center" + }, + { + "author_name": "Peggy B. Miles", + "author_inst": "Cedars-Sinai Medical Center" + }, + { + "author_name": "Trevor-Trung Nguyen", + "author_inst": "Cedars-Sinai Medical Center" + }, + { + "author_name": "Koen Raedschelders", + "author_inst": "Cedars-Sinai Medical Center" + }, + { + "author_name": "Mohamad A. Rashid", + "author_inst": "Cedars-Sinai Medical Center" + }, + { + "author_name": "Celine E. Riera", + "author_inst": "Cedars-Sinai Medical Center" + }, + { + "author_name": "Richard V. Riggs", + "author_inst": "Cedars-Sinai Medical Center" + }, + { + "author_name": "Sonia Sharma", + "author_inst": "La Jolla Institute for Allergy and Immunology" + }, + { + "author_name": "Kimia Sobhani", + "author_inst": "Cedars-Sinai Medical Center" + }, + { + "author_name": "Sarah Sternbach", + "author_inst": "Cedars-Sinai Medical Center" + }, + { + "author_name": "Nancy Sun", + "author_inst": "Cedars-Sinai Medical Center" + }, + { + "author_name": "Warren G. Tourtellotte", + "author_inst": "Cedars-Sinai Medical Center" + }, + { + "author_name": "Jennifer E. Van Eyk", + "author_inst": "Cedars-Sinai Medical Center" + }, + { + "author_name": "Jonathan G. Braun", + "author_inst": "Cedars-Sinai Medical Center" + }, + { + "author_name": "Susan Cheng", + "author_inst": "Cedars-Sinai Medical Center" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1255603,49 +1256168,153 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.08.04.20163782", - "rel_title": "Fitting models to the COVID-19 outbreak and estimating R", + "rel_doi": "10.1101/2020.08.03.20167791", + "rel_title": "SalivaDirect: Simple and sensitive molecular diagnostic test for SARS-CoV-2 surveillance", "rel_date": "2020-08-04", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.04.20163782", - "rel_abs": "The COVID-19 pandemic has brought to the fore the need for policy makers to receive timely and ongoing scientific guidance in response to this recently emerged human infectious disease. Fitting mathematical models of infectious disease transmission to the available epidemiological data provides a key statistical tool for understanding the many quantities of interest that are not explicit in the underlying epidemiological data streams. Of these, the effective reproduction number, R, has taken on special significance in terms of the general understanding of whether the epidemic is under control (R < 1). Unfortunately, none of the epidemiological data streams are designed for modelling, hence assimilating information from multiple (often changing) sources of data is a major challenge that is particularly stark in novel disease outbreaks.\n\nHere, focusing on the dynamics of the first-wave (March-June 2020), we present in some detail the inference scheme employed for calibrating the Warwick COVID-19 model to the available public health data streams, which span hospitalisations, critical care occupancy, mortality and serological testing. We then perform computational simulations, making use of the acquired parameter posterior distributions, to assess how the accuracy of short-term predictions varied over the timecourse of the outbreak. To conclude, we compare how refinements to data streams and model structure impact estimates of epidemiological measures, including the estimated growth rate and daily incidence.", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.03.20167791", + "rel_abs": "Current bottlenecks for improving accessibility and scalability of SARS-CoV-2 testing include diagnostic assay costs, complexity, and supply chain shortages. To resolve these issues, we developed SalivaDirect, which received Emergency Use Authorization (EUA) from the U.S. Food and Drug Administration on August 15th, 2020. The critical component of our approach is to use saliva instead of respiratory swabs, which enables non-invasive frequent sampling and reduces the need for trained healthcare professionals during collection. Furthermore, we simplified our diagnostic test by (1) not requiring nucleic acid preservatives at sample collection, (2) replacing nucleic acid extraction with a simple proteinase K and heat treatment step, and (3) testing specimens with a dualplex quantitative reverse transcription PCR (RT-qPCR) assay. We validated SalivaDirect with reagents and instruments from multiple vendors to minimize the risk for supply chain issues. Regardless of our tested combination of reagents and instruments from different vendors, we found that SalivaDirect is highly sensitive with a limit of detection of 6-12 SARS-CoV-2 copies/L. When comparing SalivaDirect to paired nasopharyngeal swabs using the authorized ThermoFisher Scientific TaqPath COVID-19 combo kit, we found high agreement in testing outcomes (>94%). In partnership with the National Basketball Association (NBA) and Players Association, we conducted a large-scale (n = 3,779) SalivaDirect usability study and comparison to standard nasal/oral tests for asymptomatic and presymptomatic SARS-CoV-2 detection. From this cohort of healthy NBA players, staff, and contractors, we found that 99.7% of samples were valid using our saliva collection techniques and a 89.5% positive and >99.9% negative test agreement to swabs, demonstrating that saliva is a valid and noninvasive alternative to swabs for large-scale SARS-CoV-2 testing. SalivaDirect is a flexible and inexpensive ($1.21-$4.39/sample in reagent costs) option to help improve SARS-CoV-2 testing capacity. Register to become a designated laboratory to use SalivaDirect under our FDA EUA on our website: publichealth.yale.edu/salivadirect/.", + "rel_num_authors": 34, "rel_authors": [ { - "author_name": "Matt J Keeling", - "author_inst": "University of Warwick" + "author_name": "Chantal B.F. Vogels", + "author_inst": "Yale School of Public Health" }, { - "author_name": "Louise Dyson", - "author_inst": "University of Warwick" + "author_name": "Anne E. Watkins", + "author_inst": "Yale School of Public Health" }, { - "author_name": "Glen Guyver-Fletcher", - "author_inst": "University of Warwick" + "author_name": "Christina A. Harden", + "author_inst": "Yale School of Public Health" }, { - "author_name": "Alex Holmes", - "author_inst": "University of Warwick" + "author_name": "Doug Brackney", + "author_inst": "Connecticut Agricultural Experiment Station" }, { - "author_name": "Malcolm G Semple", - "author_inst": "University of Liverpool" + "author_name": "Jared Shafer", + "author_inst": "Drug Free Sport International" }, { - "author_name": "- ISARIC4C Investigators", + "author_name": "Jianhui Wang", + "author_inst": "Yale School of Medicine" + }, + { + "author_name": "Cesar Caraballo", + "author_inst": "Yale School of Medicine" + }, + { + "author_name": "Chaney C Kalinich", + "author_inst": "Yale School of Public health" + }, + { + "author_name": "Isabel Ott", + "author_inst": "Yale School of Public Health" + }, + { + "author_name": "Joseph R. Fauver", + "author_inst": "Yale School of Public Health" + }, + { + "author_name": "Eriko Kudo", + "author_inst": "Yale School of Medicine" + }, + { + "author_name": "Peiwen Lu", + "author_inst": "Yale School of Medicine" + }, + { + "author_name": "Arvind Venkataraman", + "author_inst": "Yale School of Medicine" + }, + { + "author_name": "Maria Tokuyama", + "author_inst": "Yale School of Medicine" + }, + { + "author_name": "Adam J Moore", + "author_inst": "Yale School of Public Health, Yale University" + }, + { + "author_name": "M. Catherine Muenker", + "author_inst": "Yale School of Public Health" + }, + { + "author_name": "Arnau Casanovas-Massana", + "author_inst": "Yale School of Public Health" + }, + { + "author_name": "John Fournier", + "author_inst": "Yale School of Medicine" + }, + { + "author_name": "Santos Bermejo", + "author_inst": "Yale School of Medicine" + }, + { + "author_name": "Melissa Campbell", + "author_inst": "Yale School of Medicine" + }, + { + "author_name": "Rupak Datta", + "author_inst": "Yale School of Medicine" + }, + { + "author_name": "Allison Nelson", + "author_inst": "Yale School of Medicine" + }, + { + "author_name": "- Yale IMPACT Research Team", "author_inst": "" }, { - "author_name": "Michael J Tildesley", - "author_inst": "University of Warwick" + "author_name": "Charles Dela Cruz", + "author_inst": "Yale School of Medicine" }, { - "author_name": "Edward M Hill", - "author_inst": "University of Warwick" + "author_name": "Albert Ko", + "author_inst": "Yale University School of Public Health" + }, + { + "author_name": "Akiko Iwasaki", + "author_inst": "Yale University School of Medicine" + }, + { + "author_name": "Harlan M. Krumholz", + "author_inst": "Yale School of Medicine" + }, + { + "author_name": "JD Matheus", + "author_inst": "Drug Free Sport International" + }, + { + "author_name": "Pei Hui", + "author_inst": "Yale School of Medicine" + }, + { + "author_name": "Chen Liu", + "author_inst": "Yale School of Medicine" + }, + { + "author_name": "Shelli Farhadian", + "author_inst": "Yale School of Medicine" + }, + { + "author_name": "Robby Sikka", + "author_inst": "Minnesota Timberwolves" + }, + { + "author_name": "Anne L Wyllie", + "author_inst": "Yale School of Public Health" + }, + { + "author_name": "Nathan Grubaugh", + "author_inst": "Yale School of Public Health" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1257724,37 +1258393,21 @@ "category": "genetics" }, { - "rel_doi": "10.1101/2020.07.30.20158790", - "rel_title": "Real-Time Monitoring of COVID-19 in Scotland", + "rel_doi": "10.1101/2020.07.30.20165399", + "rel_title": "Covid-19 mortality rates in Northamptonshire UK: initial sub-regional comparisons and provisional SEIR model of disease spread", "rel_date": "2020-08-02", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.30.20158790", - "rel_abs": "To manage the public health risk posed by COVID-19 and assess the impact of interventions, policy makers must be able to closely monitor the epidemics trajectory. Here we present a simple methodology based on basic surveillance metrics for monitoring the spread of COVID-19 and its burden on health services in Scotland. We illustrate how this has been used throughout the epidemic in Scotland and explore the underlying biases that have affected its interpretation.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.30.20165399", + "rel_abs": "ObjectivesWe analysed mortality rates in a nonmetropolitan UK subregion (Northamptonshire) to understand SARSCoV2 disease fatalities at sub 1,000,000 population levels. A numerical (SEIR) model was then developed to predict the spread of Covid19 in Northamptonshire.\n\nMethodsA combined approach using statistically-weighted data to fit the start of the epidemic to the mortality record. Parameter estimates were then derived for the transmission rate and basic reproduction number.\n\nResultsAge standardised mortality rates are highest in Northampton (urban) and lowest in semi-rural districts. Northamptonshire has a statistically higher Covid-19 mortality rate than for the East Midlands and England as a whole. Model outputs suggest the number of infected individuals exceed official estimates, meaning less than 40% of the population may require immunisation.\n\nConclusionsCombining published (sub-regional) mortality rate data with deterministic models on disease spread has the potential to help public health practitioners develop bespoke mitigations, guided by local population demographics.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Giles David Calder-Gerver", - "author_inst": "The Usher Institute, College of Medicine and Veterinary Medicine, The University of Edinburgh" - }, - { - "author_name": "Stella Mazeri", - "author_inst": "The Roslin Institute, Royal (Dick) School of Veterinary Studies, The University of Edinburgh" - }, - { - "author_name": "Samuel Haynes", - "author_inst": "The Institute for Cell Biology, School of Biological Sciences, The University of Edinburgh" - }, - { - "author_name": "Camille Anna Simonet", - "author_inst": "The Institute of Evolutionary Biology, School of Biological Sciences, The University of Edinburgh" - }, - { - "author_name": "Mark EJ Woolhouse", - "author_inst": "The Usher Institute, College of Medicine and Veterinary Medicine, The University of Edinburgh" + "author_name": "Nick Petford", + "author_inst": "University of Northampton" }, { - "author_name": "Helen K Brown", - "author_inst": "The Roslin Institute, Royal (Dick) School of Veterinary Studies, The University of Edinburgh" + "author_name": "Jackie Campbell", + "author_inst": "University of Northampton" } ], "version": "1", @@ -1259694,41 +1260347,37 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.07.29.20164814", - "rel_title": "Whether the Weather Will Help Us Weather the COVID-19 Pandemic: Using Machine Learning to Measure Twitter Users' Perceptions", + "rel_doi": "10.1101/2020.07.30.20164855", + "rel_title": "SABCoM: A Spatial Agent-Based Covid-19 Model", "rel_date": "2020-08-01", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.29.20164814", - "rel_abs": "ObjectiveThe potential ability for weather to affect SARS-CoV-2 transmission has been an area of controversial discussion during the COVID-19 pandemic. Individuals perceptions of the impact of weather can inform their adherence to public health guidelines; however, there is no measure of their perceptions. We quantified Twitter users perceptions of the effect of weather and analyzed how they evolved with respect to real-world events and time.\n\nMaterials and MethodsWe collected 166,005 tweets posted between January 23 and June 22, 2020 and employed machine learning/natural language processing techniques to filter for relevant tweets, classify them by the type of effect they claimed, and identify topics of discussion.\n\nResultsWe identified 28,555 relevant tweets and estimate that 40.4% indicate uncertainty about weathers impact, 33.5% indicate no effect, and 26.1% indicate some effect. We tracked changes in these proportions over time. Topic modeling revealed major latent areas of discussion.\n\nDiscussionThere is no consensus among the public for weathers potential impact. Earlier months were characterized by tweets that were uncertain of weathers effect or claimed no effect; later, the portion of tweets claiming some effect of weather increased. Tweets claiming no effect of weather comprised the largest class by June. Major topics of discussion included comparisons to influenzas seasonality, President Trumps comments on weathers effect, and social distancing.\n\nConclusionThere is a major gap between scientific evidence and public opinion of weathers impacts on COVID-19. We provide evidence of publics misconceptions and topics of discussion, which can inform public health communications.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.30.20164855", + "rel_abs": "This paper studies the effects of social learning on the transmission of Covid-19 in a network model. We calibrate our model to detailed data for Cape Town, South Africa and show that the inclusion of social learning improves the prediction of excess fatalities, reducing the best-fit squared difference from 19.34 to 11.40. The inclusion of social learning both flattens and shortens the curves for infections, hospitalizations, and excess fatalities, which is qualitatively different from flattening the curve by reducing the contact rate or transmission probability through non-pharmaceutical interventions. While social learning reduces infections, this alone is not sufficient to curb the spread of the virus because learning is slower than the disease spreads. We use our model to study the efficacy of different vaccination strategies and find that vaccinating vulnerable groups first leads to a 72% reduction in fatalities and 5% increase in total infections compared to a random-order benchmark. By contrast, using a contact-based vaccination strategy reduces infections by only 0.9% but results in 42% more fatalities relative to the benchmark.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Marichi Gupta", - "author_inst": "Harvard Medical School" - }, - { - "author_name": "Adity Bansal", - "author_inst": "Indian Institute of Technology Delhi" + "author_name": "Allan Davids", + "author_inst": "University of Cape Town" }, { - "author_name": "Bhav Jain", - "author_inst": "MIT" + "author_name": "Gideon Du Rand", + "author_inst": "Stellenbosch University" }, { - "author_name": "Jillian Rochelle", - "author_inst": "Harvard Medical School" + "author_name": "Co-Pierre Georg", + "author_inst": "University of Cape Town" }, { - "author_name": "Atharv Oak", - "author_inst": "MIT" + "author_name": "Tina Koziol", + "author_inst": "University of Cape Town" }, { - "author_name": "Mohammad S. Jalali", - "author_inst": "Harvard Medical School" + "author_name": "Joeri Anton Schasfoort", + "author_inst": "University of Cape Town" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1261400,87 +1262049,83 @@ "category": "bioinformatics" }, { - "rel_doi": "10.1101/2020.07.30.228460", - "rel_title": "Phylogenomic analysis of SARS-CoV-2 genomes from western India reveals unique linked mutations", + "rel_doi": "10.1101/2020.07.30.229120", + "rel_title": "A Newcastle disease virus (NDV) expressing membrane-anchored spike as a cost-effective inactivated SARS-CoV-2 vaccine", "rel_date": "2020-07-31", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.07.30.228460", - "rel_abs": "India has become the third worst-hit nation by the COVID-19 pandemic caused by the SARS-CoV-2 virus. Here, we investigated the molecular, phylogenomic, and evolutionary dynamics of SARS-CoV-2 in western India, the most affected region of the country. A total of 90 genomes were sequenced. Four nucleotide variants, namely C241T, C3037T, C14408T (Pro4715Leu), and A23403G (Asp614Gly), located at 5UTR, Orf1a, Orf1b, and Spike protein regions of the genome, respectively, were predominant and ubiquitous (90%). Phylogenetic analysis of the genomes revealed four distinct clusters, formed owing to different variants. The major cluster (cluster 4) is distinguished by mutations C313T, C5700A, G28881A are unique patterns and observed in 45% of samples. We thus report a newly emerging pattern of linked mutations. The predominance of these linked mutations suggests that they are likely a part of the viral fitness landscape. A novel and distinct pattern of mutations in the viral strains of each of the districts was observed. The Satara district viral strains showed mutations primarily at the 3' end of the genome, while Nashik district viral strains displayed mutations at the 5' end of the genome. Characterization of Pune strains showed that a novel variant has overtaken the other strains. Examination of the frequency of three mutations i.e., C313T, C5700A, G28881A in symptomatic versus asymptomatic patients indicated an increased occurrence in symptomatic cases, which is more prominent in females. The age-wise specific pattern of mutation is observed. Mutations C18877T, G20326A, G24794T, G25563T, G26152T, and C26735T are found in more than 30% study samples in the age group of 10-25. Intriguingly, these mutations are not detected in the higher age range 61-80. These findings portray the prevalence of unique linked mutations in SARS-CoV-2 in western India and their prevalence in symptomatic patients.\n\nImportanceElucidation of the SARS-CoV-2 mutational landscape within a specific geographical location, and its relationship with age and symptoms, is essential to understand its local transmission dynamics and control. Here we present the first comprehensive study on genome and mutation pattern analysis of SARS-CoV-2 from the western part of India, the worst affected region by the pandemic. Our analysis revealed three unique linked mutations, which are prevalent in most of the sequences studied. These may serve as a molecular marker to track the spread of this viral variant to different places.", - "rel_num_authors": 17, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.07.30.229120", + "rel_abs": "A successful SARS-CoV-2 vaccine must be not only safe and protective but must also meet the demand on a global scale at low cost. Using the current influenza virus vaccine production capacity to manufacture an egg-based inactivated Newcastle disease virus (NDV)/SARS-CoV-2 vaccine would meet that challenge. Here, we report pre-clinical evaluations of an inactivated NDV chimera stably expressing the membrane-anchored form of the spike (NDV-S) as a potent COVID-19 vaccine in mice and hamsters. The inactivated NDV-S vaccine was immunogenic, inducing strong binding and/or neutralizing antibodies in both animal models. More importantly, the inactivated NDV-S vaccine protected animals from SARS-CoV-2 infections or significantly attenuated SARS-CoV-2 induced disease. In the presence of an adjuvant, antigen-sparing could be achieved, which would further reduce the cost while maintaining the protective efficacy of the vaccine.", + "rel_num_authors": 16, "rel_authors": [ { - "author_name": "Dhiraj Paul", - "author_inst": "National Centre for Cell Science Pune" - }, - { - "author_name": "Kunal Jani", - "author_inst": "National Centre for Cell Science Pune" + "author_name": "Weina Sun", + "author_inst": "Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Janesh Kumar", - "author_inst": "National Centre for Cell Science Pune" + "author_name": "Stephen McCroskery", + "author_inst": "Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Radha Chauhan", - "author_inst": "National Centre for Cell Science Pune" + "author_name": "Wen-Chun Liu", + "author_inst": "Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Vasudevan Seshadri", - "author_inst": "National Centre for Cell Science Pune" + "author_name": "Sarah R. Leist", + "author_inst": "University of North Carolina" }, { - "author_name": "Girdhari Lal", - "author_inst": "National Centre for Cell Science Pune" + "author_name": "Yonghong Liu", + "author_inst": "Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Rajesh Karyakarte", - "author_inst": "B. J. Government Medical College, Pune" + "author_name": "Randy A. Albrecht", + "author_inst": "Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Suvarna Joshi", - "author_inst": "B. J. Government Medical College, Pune" + "author_name": "Stefan Slamanig", + "author_inst": "Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Murlidhar Tambe", - "author_inst": "B. J. Government Medical College, Pune" + "author_name": "Justine Oliva", + "author_inst": "Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Sourav Sen", - "author_inst": "Armed Forces Medical College Pune" + "author_name": "Fatima Amanat", + "author_inst": "Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Santosh Karade", - "author_inst": "Armed Forces Medical College Pune" + "author_name": "Alexandra Schaefer", + "author_inst": "University of North Carolina" }, { - "author_name": "Kavita Bala Anand", - "author_inst": "Armed Forces Medical College Pune" + "author_name": "Kenneth H. Dinnon III", + "author_inst": "University of North Carolina at Chapel Hill" }, { - "author_name": "Shelinder Pal Singh Shergill", - "author_inst": "Armed Forces Medical College Pune" + "author_name": "Bruce L. Innis", + "author_inst": "PATH" }, { - "author_name": "Rajiv Mohan Gupta", - "author_inst": "Armed Forces Medical College Pune" + "author_name": "Adolfo Garcia-Sastre", + "author_inst": "Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Manoj Kumar Bhat", - "author_inst": "National Centre for Cell Science Pune" + "author_name": "Florian Krammer", + "author_inst": "Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Arvind Sahu", - "author_inst": "National Centre for Cell Science Pune" + "author_name": "Ralph S. Baric", + "author_inst": "University of North Carolina at Chapel Hill" }, { - "author_name": "Yogesh S Shouche", - "author_inst": "National Centre for Cell Science Pune" + "author_name": "Peter Palese", + "author_inst": "Icahn School of Medicine at Mount Sinai" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "new results", - "category": "genomics" + "category": "microbiology" }, { "rel_doi": "10.1101/2020.07.31.230607", @@ -1263030,33 +1263675,65 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.07.28.20154153", - "rel_title": "Quality controlled SARS-CoV-2 duplex procedure to reduce time and scarce molecular biology diagnosis reagents", + "rel_doi": "10.1101/2020.07.20.20156018", + "rel_title": "Transmission of SARS-CoV-2 following exposure in school settings: experience from two Helsinki area exposure incidents.", "rel_date": "2020-07-30", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.28.20154153", - "rel_abs": "The aim of this study was to provide validated procedures allowing to detect the SARS-CoV-2 and an internal control in a unique one-step duplex RT-qPCR. Two internal controls were tested, targeting either the Schmallenberg virus RNA provided by the NARILIS laboratory (University of Namur) with a HEX-labelled probe or a Diagenode Diagnostics internal control with a Cy5-labelled probe. Our results showed that Ct values of the RT-qPCR duplex assay were even smaller in the optimized working conditions, allowing to use the optimized qPCR conditions in routine diagnosis.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.20.20156018", + "rel_abs": "BackgroundThe role of children in SARS-CoV-2 transmission is unclear. We investigated two COVID-19 school exposure incidents in the Helsinki area.\n\nMethodsWe conducted two retrospective cohort studies after schools exposures, with a household transmission extension. We defined a case as an exposed person with either a positive RT-PCR, or positive microneutralisation testing (MNT) as confirmation of SARS-CoV-2 nucleoprotein IgG antibodies detection via fluorescent microsphere immunoassay (FMIA). We recruited close school contacts and families of school cases, calculated attack rates (AR) on school level and families, and identified transmission chains.\n\nFindingsIn incident A, the index was a pupil. Participation rate was 74% (89/121), and no cases were identified. In incident B, the index was a member of school personnel. Participation rate was 81% (51/63). AR was 16% (8/51): 6 pupils and 1 member of school personnel were MNT and FMIA positive; 1 pupil had a positive RT-PCR, but negative serology samples. We visited all school cases families (n=8). The AR among close household contacts was 42% (9/20 in 3/8 families) but other plausible sources were always reported. At three months post-exposure, 6/8 school cases were re-sampled and still MNT positive.\n\nInterpretationWhen the index was a child, no school transmission was identified, while the occurrence of an adult case led to a 16% AR. Further cases were evidenced in 3 families, but other transmission chains were plausible. It is likely that transmission from children to adults is limited.\n\nFundingThe Finnish Institute for Health and Welfare funded this study.\n\nResearch in contextO_ST_ABSEvidence before the studyC_ST_ABSThe first autochthonous case of COVID-19 in Finland was identified on February 29th. Transmission of the virus has led to more than 7250 cases and over 300 deaths (As of July 12th 2020). On March 16th, assuming that children might have a role in transmission, the Finnish government ordered school closures, to the exclusion of pre-school and grades 1-3. Schools were closed from March 18 and reopened on May 14th. At the stage of closure, a very limited number of reports of school related COVID-19 clusters or exposure incidents had been published, and the potential extent of transmission in a school setting was unknown.\n\nAdded value of this studyWe investigated two exposure incidents in two different schools from the Helsinki area to assess transmission among pupils, school personnel and household contacts of identified cases. In school A, contact with a COVID-19 pupil did not lead to further transmission, while in school B, out of 51 recruited contacts, eight (16%) were proved to have had COVID-19 infection, including one member of staff. Among the close household contacts of pupils who were tested positive, COVID-19 attack rate was 31% (5/16). However, in all investigated households, other sources of infections were plausible; hence household transmission following a pediatric COVID-19 case appears to be limited.\n\nImplications of all of the available evidenceIncidence of COVID-19 infections in children following school related exposure was limited, as well as secondary transmission within their household. We hope our findings will help prioritize mitigation measures as well as reduce worry among parents of school aged children as most EU countries are preparing for the start of a new school year in autumn.", + "rel_num_authors": 12, "rel_authors": [ { - "author_name": "Anaelle Collin", - "author_inst": "IFAC VIVALIA" + "author_name": "Timothee Dub", + "author_inst": "Finnish Institute for Health and Welfare" }, { - "author_name": "Carole Chaboteaux", - "author_inst": "IFAC VIVALIA" + "author_name": "Elina Erra", + "author_inst": "City of Helsinki" }, { - "author_name": "Veronique Fontaine", - "author_inst": "ULB" + "author_name": "Lotta Hagberg", + "author_inst": "Finnish Institute for Health and Welfare" + }, + { + "author_name": "Emmi Sarvikivi", + "author_inst": "Finnish Institute for Health and Welfare" + }, + { + "author_name": "Camilla Virta", + "author_inst": "Finnish Institute for Health and Welfare" + }, + { + "author_name": "Asko Jarvinen", + "author_inst": "Helsinki University Hospital and Helsinki University" }, { - "author_name": "Philippe Lefevre", - "author_inst": "IFAC VIVALIA" + "author_name": "Pamela Osterlund", + "author_inst": "Finnish Institute for Health and Welfare" + }, + { + "author_name": "Niina Ikonen", + "author_inst": "Finnish Institute for Health and Welfare" + }, + { + "author_name": "Anu Haveri", + "author_inst": "Finnish Institute for Health and Welfare" + }, + { + "author_name": "Merit Melin", + "author_inst": "Finnish Institute for Health and Welfare" + }, + { + "author_name": "Timo J Lukkarinen", + "author_inst": "City of Helsinki" + }, + { + "author_name": "Hanna Nohynek", + "author_inst": "Finnish Institute for Health and Welfare" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1264712,51 +1265389,43 @@ "category": "bioinformatics" }, { - "rel_doi": "10.1101/2020.07.30.228221", - "rel_title": "Immuno-informatics Design of a Multimeric Epitope Peptide Based Vaccine Targeting SARS-CoV-2 Spike Glycoprotein", + "rel_doi": "10.1101/2020.07.30.228478", + "rel_title": "Substrate specificity of SARS-CoV-2 nsp10-nsp16 methyltransferase", "rel_date": "2020-07-30", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.07.30.228221", - "rel_abs": "Developing an efficacious vaccine to SARS-CoV-2 infection is critical to stem COVID-19 fatalities and providing the global community with immune protection. We have used a bioinformatic approach to aid in the design of an epitope peptide-based vaccine against the spike protein of the virus. Five antigenic B cell epitopes with viable antigenicity and a total of 27 discontinuous B cell epitopes were mapped out structurally in the spike protein for antibody recognition. We identified eight CD8+ T cell 9-mers along with 12 CD4+ T cell 14-15-mer as promising candidate epitopes putatively restricted by a large number of MHC-I and II alleles respectively. We used this information to construct an in silico chimeric peptide vaccine whose translational rate was highly expressed when cloned in pET28a (+) vector. The vaccine construct was predicted to elicit high antigenicity and cell-mediated immunity when given as a homologous prime-boost, with triggering of toll-like receptor 5 by the adjuvant linker. The vaccine was characterized by an increase in IgM and IgG and an array of Th1 and Th2 cytokines. Upon in silico challenge with SARS-CoV-2, there was a decrease in antigen levels using our immune simulations. We therefore propose that potential vaccine designs consider this approach.", - "rel_num_authors": 8, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.07.30.228478", + "rel_abs": "The ongoing COVID-19 pandemic exemplifies the general need to better understand viral infections. The positive single strand RNA genome of its causative agent, the SARS coronavirus 2 (SARS-CoV-2) encodes all viral enzymes. In this work, we focus on one particular methyltransferase (MTase), nsp16, which in complex with nsp10 is capable of methylating the first nucleotide of a capped RNA strand at the 2'-O position. This process is part of a viral capping system and is crucial for viral evasion of the innate immune reaction. In light of recently discovered non-canonical RNA caps, we tested various dinucleoside polyphosphate-capped RNAs as substrates for nsp10-nsp16 MTase. We developed an LC-MS-based method and discovered five types of capped RNA (m7Gp3A(G)-, Gp3A(G)- and Gp4A-RNA) that are substrates of the nsp10-nsp16 MTase. Our technique is an alternative to the classical isotope labelling approach for measurement of 2'-O-MTase activity. Further, we determined the IC50 value of sinefungin (286 {+/-} 66 nM) to illustrate the value of our approach for inhibitor screening. In the future, this approach can be used for screening inhibitors of any type of 2'-O-MTase.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Onyeka S. Chukwudozie", - "author_inst": "University of Lagos" - }, - { - "author_name": "Clive M. Gray", - "author_inst": "University of Capetown" - }, - { - "author_name": "Tawakalt A. Fagbayi", - "author_inst": "University of Lagos" + "author_name": "Roberto Benoni", + "author_inst": "Institute of Organic Chemistry and Biochemistry of the Czech Academy of Sciences" }, { - "author_name": "Rebecca C. Chukwuanukwu", - "author_inst": "Nnamdi Azikiwe University, Nnewi Campus, Nigeria" + "author_name": "Petra Krafcikova", + "author_inst": "Institute of Organic Chemistry and Biochemistry of the Czech Academy of Sciences" }, { - "author_name": "Victor O. Oyebanji", - "author_inst": "University of Ibadan" + "author_name": "Marek Baranowski", + "author_inst": "Division of Biophysics, Institute of Experimental Physics, Faculty of Physics, University of Warsaw" }, { - "author_name": "Taiwo T. Bankole", - "author_inst": "University of Lagos" + "author_name": "Joanna Kowalska", + "author_inst": "Division of Biophysics, Institute of Experimental Physics, Faculty of Physics, University of Warsaw, Ludwika Pasteura 5, 02-093 Warsaw" }, { - "author_name": "Richard A Adewole", - "author_inst": "University of Lagos" + "author_name": "Evzen Boura", + "author_inst": "Institute of Organic Chemistry and Biochemistry of the Czech Academy of Sciences," }, { - "author_name": "Daniel M Eze", - "author_inst": "University of Ibadan" + "author_name": "Hana Cahova", + "author_inst": "Institute of Organic Chemistry and Biochemistry of the Czech Academy of Sciences" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "new results", - "category": "immunology" + "category": "molecular biology" }, { "rel_doi": "10.1101/2020.07.30.229187", @@ -1266374,23 +1267043,43 @@ "category": "psychiatry and clinical psychology" }, { - "rel_doi": "10.1101/2020.07.27.20162677", - "rel_title": "An Analysis of Territorial Patterns in COVID-19 Mortality in France, Spain, Italy and the UK", + "rel_doi": "10.1101/2020.07.27.20161430", + "rel_title": "Transport effect of COVID-19 pandemic in France", "rel_date": "2020-07-29", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.27.20162677", - "rel_abs": "This paper provides an overview of territorial patterns of COVID-19 deaths in four European countries severely affected by the pandemic, Spain, France, Italy, and the United Kingdom. The analysis focuses on cumulated COVID-19 mortality at the sub-regional level, following the territorial subdivision of countries adopted by the European Union. The paper builds upon a dataset with highly granular information on COVID- 19 deaths assembled from various sources. The analysis shows remarkable differences in territorial patterns of COVID-19 mortality, both within and across the four countries reviewed. Results somewhat differ depending on the aspect considered (concentration of deaths or mortality rates) but, in general, Italy, France and Spain display significant territorial disparities, with selected sub-regions being disproportionately affected by the pandemic. Instead, the picture is more uniform in the UK, with comparatively lower differences across the various sub- regions. These findings suggest that analyses of COVID-19 mortality at the national level (and, sometimes, even at the regional level) may conceal major differences and therefore be of limited use, both analytically and from an operational viewpoint.", - "rel_num_authors": 1, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.27.20161430", + "rel_abs": "An extension of the classical pandemic SIRD model is considered for the regional spread of COVID-19 in France under lockdown strategies. This compartment model divides the infected and the recovered individuals into undetected and detected compartments respectively. By fitting the extended model to the real detected data during the lockdown, an optimization algorithm is used to derive the optimal parameters, the initial condition and the epidemics start date of regions in France. Considering all the age classes together, a network model of the pandemic transport between regions in France is presented on the basis of the regional extended model and is simulated to reveal the transport effect of COVID-19 pandemic after lockdown. Using the the measured values of displacement of people mobilizing between each city, the pandemic network of all cities in France is simulated by using the same model and method as the pandemic network of regions. Finally, a discussion on an integro-differential equation is given and a new model for the network pandemic model of each age class is provided.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Roberto Zavatta", - "author_inst": "Economisti Associati" + "author_name": "Lina Guan", + "author_inst": "Beijing University of Technology and Univ. Grenoble Alpes" + }, + { + "author_name": "Christophe Prieur", + "author_inst": "Univ. Grenoble Alpes, CNRS, Grenoble INP, GIPSA-lab, F-38000 Grenoble, France" + }, + { + "author_name": "Liguo Zhang", + "author_inst": "Beijing University of Technology" + }, + { + "author_name": "Clementine Prieur", + "author_inst": "Univ. Grenoble Alpes, CNRS, Inria, Grenoble INP, LJK, 38000 Grenoble, France" + }, + { + "author_name": "Didier Georges", + "author_inst": "Univ. Grenoble Alpes, CNRS, Grenoble INP, GIPSA-lab, F-38000 Grenoble, France" + }, + { + "author_name": "Pascal Bellemain", + "author_inst": "Univ. Grenoble Alpes, CNRS, Grenoble INP, GIPSA-lab, F-38000 Grenoble, France" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2020.07.26.20162529", @@ -1268036,153 +1268725,57 @@ "category": "health policy" }, { - "rel_doi": "10.1101/2020.07.28.20163022", - "rel_title": "Eleven Routine Clinical Features Predict COVID-19 Severity", + "rel_doi": "10.1101/2020.07.28.20162735", + "rel_title": "Age-severity matched cytokine profiling reveals specific signatures in Covid-19 patients", "rel_date": "2020-07-29", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.28.20163022", - "rel_abs": "Severity prediction of COVID-19 remains one of the major clinical challenges for the ongoing pandemic. Here, we have recruited a 144 COVID-19 patient cohort consisting of training, validation, and internal test sets, longitudinally recorded 124 routine clinical and laboratory parameters, and built a machine learning model to predict the disease progression based on measurements from the first 12 days since the disease onset when no patient became severe. A panel of 11 routine clinical factors, including oxygenation index, basophil counts, aspartate aminotransferase, gender, magnesium, gamma glutamyl transpeptidase, platelet counts, activated partial thromboplastin time, oxygen saturation, body temperature and days after symptom onset, constructed a classifier for COVID-19 severity prediction, achieving accuracy of over 94%. Validation of the model in an independent cohort containing 25 patients achieved accuracy of 80%. The overall sensitivity, specificity, PPV and NPV were 0.70, 0.99, 0.93 and 0.93, respectively. Our model captured predictive dynamics of LDH and CK while their levels were in the normal range. This study presents a practical model for timely severity prediction and surveillance for COVID-19, which is freely available at webserver https://guomics.shinyapps.io/covidAI/.", - "rel_num_authors": 34, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.28.20162735", + "rel_abs": "A global effort is currently undertaken to restrain the COVID-19 pandemic. Host immunity has come out as a determinant for COVID-19 clinical outcome, and several studies investigated the immune profiling of SARS-CoV-2 infected people to properly direct the clinical management of the disease. Thus, lymphopenia, T-cell exhaustion, and the increased levels of inflammatory mediators have been described in COVID-19 patients, in particular in severe cases1. Age represents a key factor in COVID-19 morbidity and mortality2. Understanding age-associated immune signatures of patients is therefore important to identify preventive and therapeutic strategies. In this study, we investigated the immune profile of COVID-19 hospitalized patients identifying a distinctive age-dependent immune signature associated with disease severity. Indeed, defined circulating factors - CXCL8, IL-10, IL-15, IL-27 and TNF- - positively correlate with older age, longer hospitalization, and a more severe form of the disease and may thus represent the leading signature in critical COVID-19 patients.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Kai Zhou", - "author_inst": "Taizhou Hospital of Zhejiang Province affiliated to Wenzhou Medical University, Linhai, China" - }, - { - "author_name": "Yaoting Sun", - "author_inst": "Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, China; Institute of Basic Medical Sciences, W" - }, - { - "author_name": "Lu Li", - "author_inst": "Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, China; Institute of Basic Medical Sciences, W" - }, - { - "author_name": "Zelin Zang", - "author_inst": "School of Engineering, Westlake University, Hangzhou, China" - }, - { - "author_name": "Jing Wang", - "author_inst": "Taizhou Hospital of Zhejiang Province affiliated to Wenzhou Medical University, Linhai, China" - }, - { - "author_name": "Jun Li", - "author_inst": "Taizhou Hospital of Zhejiang Province affiliated to Wenzhou Medical University, Linhai, China" - }, - { - "author_name": "Junbo Liang", - "author_inst": "Taizhou Hospital of Zhejiang Province affiliated to Wenzhou Medical University, Linhai, China" - }, - { - "author_name": "Fangfei Zhang", - "author_inst": "Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, China; Institute of Basic Medical Sciences, W" - }, - { - "author_name": "Qiushi Zhang", - "author_inst": "Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, China; Institute of Basic Medical Sciences, W" - }, - { - "author_name": "Weigang Ge", - "author_inst": "Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, China; Institute of Basic Medical Sciences, W" - }, - { - "author_name": "Hao Chen", - "author_inst": "Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, China; Institute of Basic Medical Sciences, W" - }, - { - "author_name": "Xindong Sun", - "author_inst": "Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, China; Institute of Basic Medical Sciences, W" - }, - { - "author_name": "Liang Yue", - "author_inst": "Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, China; Institute of Basic Medical Sciences, W" - }, - { - "author_name": "Xiaomai Wu", - "author_inst": "Taizhou Hospital of Zhejiang Province affiliated to Wenzhou Medical University, Linhai, China" - }, - { - "author_name": "Bo Shen", - "author_inst": "Taizhou Hospital of Zhejiang Province affiliated to Wenzhou Medical University, Linhai, China" - }, - { - "author_name": "Jiaqin Xu", - "author_inst": "Taizhou Hospital of Zhejiang Province affiliated to Wenzhou Medical University, Linhai, China" - }, - { - "author_name": "Hongguo Zhu", - "author_inst": "Taizhou Hospital of Zhejiang Province affiliated to Wenzhou Medical University, Linhai, China" - }, - { - "author_name": "Shiyong Chen", - "author_inst": "Taizhou Hospital of Zhejiang Province affiliated to Wenzhou Medical University, Linhai, China" - }, - { - "author_name": "Hai Yang", - "author_inst": "Taizhou Hospital of Zhejiang Province affiliated to Wenzhou Medical University, Linhai, China" - }, - { - "author_name": "Shigao Huang", - "author_inst": "Institute of Translational Medicine, Faculty of Health Sciences, University of Macau 999078, Macau SAR, China." - }, - { - "author_name": "Minfei Peng", - "author_inst": "Taizhou Hospital of Zhejiang Province affiliated to Wenzhou Medical University, Linhai, China" - }, - { - "author_name": "Dongqing Lv", - "author_inst": "Taizhou Hospital of Zhejiang Province affiliated to Wenzhou Medical University, Linhai, China" - }, - { - "author_name": "Chao Zhang", - "author_inst": "Taizhou Hospital of Zhejiang Province affiliated to Wenzhou Medical University, Linhai, China" - }, - { - "author_name": "Haihong Zhao", - "author_inst": "Taizhou Hospital of Zhejiang Province affiliated to Wenzhou Medical University, Linhai, China" - }, - { - "author_name": "Luxiao Hong", - "author_inst": "Taizhou Hospital of Zhejiang Province affiliated to Wenzhou Medical University, Linhai, China" + "author_name": "Roberta Angioni", + "author_inst": "Fondazione Istituto di Ricerca Pediatrica - Citta della Speranza, Padova, Italy" }, { - "author_name": "Zhehan Zhou", - "author_inst": "Taizhou Hospital of Zhejiang Province affiliated to Wenzhou Medical University, Linhai, China" + "author_name": "Ricardo Sanchez-Rodriguez", + "author_inst": "Fondazione Istituto di Ricerca Pediatrica - Citta della Speranza, Padova, Italy" }, { - "author_name": "Haixiao Chen", - "author_inst": "Taizhou Hospital of Zhejiang Province affiliated to Wenzhou Medical University, Linhai, China" + "author_name": "Fabio Munari", + "author_inst": "Fondazione Istituto di Ricerca Pediatrica - Citta della Speranza, Padova, Italy" }, { - "author_name": "Xuejun Dong", - "author_inst": "Shaoxing People's Hospital (Shaoxing Hospital, Zhejiang University School of Medicine), Shaoxing, Zhejiang, 312000" + "author_name": "Nicole Bertoldi", + "author_inst": "Fondazione Istituto di Ricerca Pediatrica - Citta della Speranza, Padova, Italy" }, { - "author_name": "Chunyu Tu", - "author_inst": "Shaoxing People's Hospital (Shaoxing Hospital, Zhejiang University School of Medicine), Shaoxing, Zhejiang, 312000" + "author_name": "Diletta Arcidiacono", + "author_inst": "Istituto Oncologico Veneto- IOV-IRCCS, Padova, Italy" }, { - "author_name": "Minghui Li", - "author_inst": "Shaoxing People's Hospital (Shaoxing Hospital, Zhejiang University School of Medicine), Shaoxing, Zhejiang, 312000" + "author_name": "Silvia Cavinato", + "author_inst": "Infectious Disease Unit, Padova University Hospital, Padova, Italy" }, { - "author_name": "Yi Zhu", - "author_inst": "Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, China; Institute of Basic Medical Sciences, W" + "author_name": "Davide Marturano", + "author_inst": "Department of Medicine, Nephrology, Dialysis and Transplantation Unit, University of Padova, Padova, Italy;" }, { - "author_name": "Baofu Chen", - "author_inst": "Taizhou Hospital of Zhejiang Province affiliated to Wenzhou Medical University, Linhai, China" + "author_name": "Annamaria Cattelan", + "author_inst": "Infectious Disease Unit, Padova University Hospital, Padova, Italy" }, { - "author_name": "Stan Z. Li", - "author_inst": "School of Engineer, Westlake University, Hangzhou, China" + "author_name": "Antonella Viola", + "author_inst": "Fondazione Istituto di Ricerca Pediatrica - Citta della Speranza, Padova, Italy;" }, { - "author_name": "Tiannan Guo", - "author_inst": "Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, China; Institute of Basic Medical Sciences, W" + "author_name": "Barbara Molon", + "author_inst": "Fondazione Istituto di Ricerca Pediatrica - Citta della Speranza, Padova, Italy;" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1269790,75 +1270383,59 @@ "category": "neurology" }, { - "rel_doi": "10.1101/2020.07.27.224089", - "rel_title": "Antibodies that potently inhibit or enhance SARS-CoV-2 spike protein-ACE2 interaction isolated from synthetic single-chain antibody libraries", + "rel_doi": "10.1101/2020.07.28.225102", + "rel_title": "Pyronaridine and artesunate are potential antiviral drugs against COVID-19 and influenza", "rel_date": "2020-07-28", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.07.27.224089", - "rel_abs": "Antibodies with high affinity against the receptor binding domain (RBD) of the SARS-CoV-2 S1 ectodomain were identified from screens using the Retained Display (ReD) platform employing a 1 x 1011 clone single-chain antibody (scFv) library. Numerous unique scFv clones capable of inhibiting binding of the viral S1 ectodomain to the ACE2 receptor in vitro were characterized. To maximize avidity, selected clones were reformatted as bivalent diabodies and monoclonal antibodies (mAb). The highest affinity mAb completely neutralized live SARS-CoV-2 virus in cell culture for four days at a concentration of 6.7 nM, suggesting potential therapeutic and/or prophylactic use. Furthermore, scFvs were identified that greatly increased the interaction of the viral S1 trimer with the ACE2 receptor, with potential implications for vaccine development.", - "rel_num_authors": 14, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.07.28.225102", + "rel_abs": "Since the first human case was reported in Wuhan Province, China in December 2019, SARS-CoV-2 has caused millions of human infections in more than 200 countries worldwide with an approximately 4.01% case-fatality rate (as of 27 July, 2020; based on a WHO situation report), and COVID-19 pandemic has paralyzed our global community. Even though a few candidate drugs, such as remdesivir (a broad antiviral prodrug) and hydroxychloroquine, have been investigated in human clinical trials, their therapeutic efficacy needs to be clarified further to be used to treat COVID-19 patients. Here we show that pyronaridine and artesunate, which are the chemical components of anti-malarial drug Pyramax(R), exhibit antiviral activity against SARS-CoV-2 and influenza viruses. In human lung epithelial (Calu-3) cells, pyronaridine and artesunate were highly effective against SARS-CoV-2 while hydroxychloroquine did not show any effect at concentrations of less than 100 M. In viral growth kinetics, both pyronaridine and artesunate inhibited the growth of SARS-CoV-2 and seasonal influenza A virus in Calu-3 cells. Taken together, we suggest that artesunate and pyronaridine might be effective drug candidates for use in human patients with COVID-19 and/or influenza, which may co-circulate during this coming winter season.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Matthew D Beasley", - "author_inst": "Affinity Biosciences" - }, - { - "author_name": "Sanja Aracic", - "author_inst": "Affinity Biosciences Pty. Ltd." - }, - { - "author_name": "Fiona M Gracey", - "author_inst": "Affinity Biosciences Pty. Ltd" - }, - { - "author_name": "Ruban Kannan", - "author_inst": "Affinity Biosciences Pty. Ltd." - }, - { - "author_name": "Avisa Masarati", - "author_inst": "Affinity Biosciences Pty. Ltd." + "author_name": "Joon-Yong Bae", + "author_inst": "Department of Microbiology, Korea University College of Medicine" }, { - "author_name": "S. R. Premaratne", - "author_inst": "Affinity Biosciences Pty. Ltd." + "author_name": "Gee Eun Lee", + "author_inst": "Department of Microbiology, Korea University College of Medicine" }, { - "author_name": "Madhara Udawela", - "author_inst": "Affinity Biosciences Pty. Ltd." + "author_name": "Heedo Park", + "author_inst": "Department of Microbiology, Korea University College of Medicine" }, { - "author_name": "Rebecca E Wood", - "author_inst": "Affinity Biosciences Pty. Ltd." + "author_name": "Juyoung Cho", + "author_inst": "Department of Microbiology, Korea University College of Medicine" }, { - "author_name": "Shereen Jabar", - "author_inst": "Affinity Biosciences Pty. Ltd." + "author_name": "Yung-Eui Kim", + "author_inst": "Korea National Institute of Health, Korea Centers for Disease Control and Prevention" }, { - "author_name": "Nicole Church", - "author_inst": "Affinity Biosciences Pty. Ltd." + "author_name": "Joo-Yeon Lee", + "author_inst": "Korea National Institute of Health, Korea Centers for Disease Control and Prevention" }, { - "author_name": "Thien-Kim Le", - "author_inst": "Affinity Biosciences Pty. Ltd." + "author_name": "Chung Ju", + "author_inst": "Shin Poong Pharmaceutical" }, { - "author_name": "Dahna Makris", - "author_inst": "Affinity Biosciences Pty. Ltd." + "author_name": "Won-Ki Kim", + "author_inst": "Department of Neuroscience, Korea University College of Medicine" }, { - "author_name": "Bradley K McColl", - "author_inst": "Affinity Biosciences Pty. Ltd." + "author_name": "Jin Il Kim", + "author_inst": "Department of Microbiology, Korea University College of Medicine" }, { - "author_name": "Ben R Kiefel", - "author_inst": "Affinity Biosciences Pty. Ltd." + "author_name": "Man-Seong Park", + "author_inst": "Department of Microbiology, Korea University College of Medicine" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "new results", - "category": "immunology" + "category": "microbiology" }, { "rel_doi": "10.1101/2020.07.28.223784", @@ -1271528,139 +1272105,31 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.07.24.20161828", - "rel_title": "Covid-19 automated diagnosis and risk assessment through Metabolomics and Machine-Learning", + "rel_doi": "10.1101/2020.07.25.20161885", + "rel_title": "Mathematical modelling based study and prediction of COVID-19 epidemic dissemination under the impact of lockdown in India", "rel_date": "2020-07-27", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.24.20161828", - "rel_abs": "COVID-19 is still placing a heavy health and financial burden worldwide. Impairments in patient screening and risk management play a fundamental role on how governments and authorities are directing resources, planning reopening, as well as sanitary countermeasures, especially in regions where poverty is a major component in the equation. An efficient diagnostic method must be highly accurate, while having a cost-effective profile.\n\nWe combined a machine learning-based algorithm with instrumental analysis using mass spectrometry to create an expeditious platform that discriminate COVID-19 in plasma samples within minutes, while also providing tools for risk assessment, to assist healthcare professionals in patient management and decision-making. A cross-sectional study with 728 patients (369 confirmed COVID-19 and 359 controls) was enrolled from three Brazilian epicentres (Sao Paulo capital, Sao Paulo countryside and Manaus) in the months of April, May, June and July 2020.\n\nWe were able to elect and identify 21 molecules that are related to the diseases pathophysiology and 26 features to patients health-related outcomes. With specificity >97% and sensitivity >83% from blinded data, this screening approach is understood as a tool with great potential for real-world application.", - "rel_num_authors": 30, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.25.20161885", + "rel_abs": "COVID-19 (SARS-CoV-2) is rapidly spreading in South Asian countries especially in India. India is the fourth most COVID-19 affected country at present (as on July 10, 2020). With limited medical facilities and high transmission rate, study of COVID-19 progression and its subsequence trajectory need to be analyzed in India. Epidemiologic mathematical models have the potential to predict the epidemic peak of COVID-19 under different scenario. Lockdown is one of the most effective mitigation policy adapted worldwide to control the transmission rate of COVID-19 cases. In this study, we use an improvised five compartment mathematical model i.e. Susceptible (S) - exposed (E)- infected (I)- recovered (R)- death (D) (SEIRD) to investigate the progression of COVID-19 and predict the epidemic peak under the impact of lockdown in India. The aim of this study to provide the most accurate prediction of epidemic peak and to evaluate the impact of lockdown on epidemic peak shift in India. For this purpose, we examine most recent data (up to July 10, 2020) to enhance the accuracy of outcomes from the proposed model. The obtained results indicate that COVID-19 epidemic peak would appear on around mid-August 2020 in India and corresponding estimated cases would be 2.5x106 under current scenario. In addition, our study indicates that existence of under-reported cases ([~]105) during post-lockdown period in India. It is expected that nationwide lockdown would lead to epidemic peak suppression in India. The obtained results would be beneficial for determining further COVID-19 mitigation policies not only in India but globally.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Jeany Delafiori", - "author_inst": "Innovare Biomarkers Laboratory, School of Pharmaceutical Sciences, University of Campinas, Campinas, Brazil" - }, - { - "author_name": "Luiz Claudio Navarro", - "author_inst": "RECOD Laboratory, Computing Institute, University of Campinas, Campinas, Brazil" - }, - { - "author_name": "Rinaldo Focaccia Siciliano", - "author_inst": "Instituto do Coracao (InCor), Hospital das Clinicas HCFMUSP, Faculdade de Medicina, Universidade de Sao Paulo, Sao Paulo, Brazil" - }, - { - "author_name": "Gisely Cardoso de Melo", - "author_inst": "Tropical Medicine Foundation Dr. Heitor Vieira Dourado, Manaus, Brazil and Amazonas State University, Manaus, Brazil" - }, - { - "author_name": "Estela Natacha Brandt Busanello", - "author_inst": "Innovare Biomarkers Laboratory, School of Pharmaceutical Sciences, University of Campinas, Campinas, Brazil" - }, - { - "author_name": "Jos\u00e9 Carlos Nicolau", - "author_inst": "Instituto do Coracao (InCor), Hospital das Clinicas HCFMUSP, Faculdade de Medicina, Universidade de Sao Paulo, Sao Paulo, Brazil" - }, - { - "author_name": "Geovana Manzan Sales", - "author_inst": "Innovare Biomarkers Laboratory, School of Pharmaceutical Sciences, University of Campinas, Campinas, Brazil" - }, - { - "author_name": "Arthur Noin de Oliveira", - "author_inst": "Innovare Biomarkers Laboratory, School of Pharmaceutical Sciences, University of Campinas, Campinas, Brazil" - }, - { - "author_name": "Fernando Fonseca Almeida Val", - "author_inst": "Tropical Medicine Foundation Dr. Heitor Vieira Dourado, Manaus, Brazil and Amazonas State University, Manaus, Brazil" - }, - { - "author_name": "Diogo Noin de Oliveira", - "author_inst": "Innovare Biomarkers Laboratory, School of Pharmaceutical Sciences, University of Campinas, Campinas, Brazil" - }, - { - "author_name": "Adriana Eguti", - "author_inst": "Sumar\u00e9 State Hospital, Sumar\u00e9, Brazil" - }, - { - "author_name": "Luiz Augusto dos Santos", - "author_inst": "Paul\u00ednia Municipal Hospital, Paul\u00ednia, Brazil" - }, - { - "author_name": "Talia Falc\u00e3o Dal\u00e7\u00f3quio", - "author_inst": "Instituto do Coracao (InCor), Hospital das Clinicas HCFMUSP, Faculdade de Medicina, Universidade de Sao Paulo, Sao Paulo, Brazil" - }, - { - "author_name": "Adriadne Justi Bertolin", - "author_inst": "Instituto do Coracao (InCor), Hospital das Clinicas HCFMUSP, Faculdade de Medicina, Universidade de Sao Paulo, Sao Paulo, Brazil" - }, - { - "author_name": "Jo\u00e3o Carlos Cardoso Alonso", - "author_inst": "Paul\u00ednia Municipal Hospital, Paul\u00ednia, Brazil and Laboratory of Urogenital Carcinogenesis and Immunotherapy, University of Campinas, Campinas, Brazil" - }, - { - "author_name": "Rebeca Linhares Abreu-Netto", - "author_inst": "Tropical Medicine Foundation Dr. Heitor Vieira Dourado, Manaus, Brazil and Amazonas State University, Manaus, Brazil" - }, - { - "author_name": "Rocio Salsoso", - "author_inst": "Instituto do Coracao (InCor), Hospital das Clinicas HCFMUSP, Faculdade de Medicina, Universidade de Sao Paulo, Sao Paulo, Brazil" - }, - { - "author_name": "Djane Ba\u00eda-da-Silva", - "author_inst": "Tropical Medicine Foundation Dr. Heitor Vieira Dourado, Manaus, Brazil and Amazonas State University, Manaus, Brazil" - }, - { - "author_name": "Vanderson Souza Sampaio", - "author_inst": "Tropical Medicine Foundation Dr. Heitor Vieira Dourado, Manaus, Brazil and Health Surveillance Foundation of Amazonas State, Manaus, Brazil" - }, - { - "author_name": "Carla Cristina Judice", - "author_inst": "Laboratory of Tropical Diseases, Institute of Biology, University of Campinas, Campinas, Brazil" - }, - { - "author_name": "Fabio Maranh\u00e3o Trindade Costa", - "author_inst": "Laboratory of Tropical Diseases, Institute of Biology, University of Campinas, Campinas, Brazil" - }, - { - "author_name": "Nelson Dur\u00e1n", - "author_inst": "Laboratory of Urogenital Carcinogenesis and Immunotherapy, University of Campinas, Campinas, Brazil" - }, - { - "author_name": "Maur\u00edcio Wesley Perroud", - "author_inst": "Sumar\u00e9 State Hospital, Sumar\u00e9, Brazil" - }, - { - "author_name": "Ester Cerdeira Sabino", - "author_inst": "Institute of Tropical Medicine, University of S\u00e3o Paulo, S\u00e3o Paulo, Brazil" - }, - { - "author_name": "Marcus Vinicius Guimar\u00e3es Lacerda", - "author_inst": "Tropical Medicine Foundation Dr. Heitor Vieira Dourado, Manaus, Brazil and Le\u00f4nidas and Maria Deane Institute, FIOCRUZ, Manaus, Brazil" - }, - { - "author_name": "Leonardo Oliveira Reis", - "author_inst": "UroScience Laboratory, University of Campinas, Campinas, Brazil" - }, - { - "author_name": "Wagner Jos\u00e9 F\u00e1varo", - "author_inst": "Laboratory of Urogenital Carcinogenesis and Immunotherapy, University of Campinas, Campinas, Brazil" - }, - { - "author_name": "Wuelton Marcelo Monteiro", - "author_inst": "Tropical Medicine Foundation Dr. Heitor Vieira Dourado, Manaus, Brazil and Amazonas State University, Manaus, Brazil" + "author_name": "Vipin Tiwari", + "author_inst": "Department of Physics, KU, SSJ campus Almora (263601), Uttarakhand, India" }, { - "author_name": "Anderson Rezende Rocha", - "author_inst": "RECOD Laboratory, Computing Institute, University of Campinas, Campinas, Brazil" + "author_name": "Nandan Bisht", + "author_inst": "Department of Physics, KU, SSJ campus Almora (263601), Uttarakhand, India" }, { - "author_name": "Rodrigo Ramos Catharino", - "author_inst": "Innovare Biomarkers Laboratory, School of Pharmaceutical Sciences, University of Campinas, Campinas, Brazil" + "author_name": "Namrata Deyal", + "author_inst": "Department of Physics, KU, SSJ campus Almora (263601), Uttarakhand, India" } ], "version": "1", "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2020.07.25.20161968", @@ -1273614,49 +1274083,21 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.07.20.20157818", - "rel_title": "Optimal Testing Strategy for the Identification of COVID-19 Infections", + "rel_doi": "10.1101/2020.07.20.20157826", + "rel_title": "A logistic model of CoV-2 propagation", "rel_date": "2020-07-26", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.20.20157818", - "rel_abs": "The systematic identification of infectious, yet unreported, individuals is critical for the containment of the COVID-19 pandemic. We present a strategy for identifying the location, timing and extent of testing that maximizes information gain for such infections. The optimal testing strategy relies on Bayesian experimental design and forecasting epidemic models that account for time dependent interventions. It is applicable at the onset and spreading of the epidemic and can forewarn for a possible recurrence of the disease after relaxation of interventions. We examine its application in Switzerland and show that it can provide timely and systematic guidance for the effective identification of infectious individuals with finite testing resources. The methodology and the open source code are readily adaptable to countries around the world.\n\nWe present a strategy for the optimal allocation of testing resources in order to detect COVID-19 infections in a countrys population.", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.20.20157826", + "rel_abs": "We describe an elemental logistic model for the propagation of CoV-2 in a community and illustrate the sensitivity of the model to key parameters such as R0, the initial rate of infections per infected person, and A0, the fraction of infected people developing neutralizing antibodies. We demonstrate the importance of the duration of immunity in the population, the development of waves of new cases of infection, and the effect of premature opening of local economies.", + "rel_num_authors": 1, "rel_authors": [ { - "author_name": "Michail Chatzimanolakis", - "author_inst": "ETH Zurich" - }, - { - "author_name": "Pascal Weber", - "author_inst": "ETH Zurich" - }, - { - "author_name": "Georgios Arampatzis", - "author_inst": "ETH Zurich" - }, - { - "author_name": "Daniel W\u00e4lchli", - "author_inst": "ETH Zurich" - }, - { - "author_name": "Petr Karnakov", - "author_inst": "ETH Zurich" - }, - { - "author_name": "Ivica Ki\u010di\u0107", - "author_inst": "ETH Zurich" - }, - { - "author_name": "Costas Papadimitriou", - "author_inst": "University of Thessaly" - }, - { - "author_name": "Petros Koumoutsakos", - "author_inst": "ETH Zurich" + "author_name": "Robert F Weiss", + "author_inst": "Back Bay Biosciences" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1275944,25 +1276385,37 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.07.22.20159798", - "rel_title": "The Epidemiology Workbench: a Tool for Communities to Strategize in Response to COVID-19 and other Infectious Diseases", + "rel_doi": "10.1101/2020.07.24.20159947", + "rel_title": "Effect of manual and digital contact tracing on COVID-19 outbreaks: a study on empirical contact data", "rel_date": "2020-07-25", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.22.20159798", - "rel_abs": "COVID-19 poses a dramatic challenge to health, community life, and the economy of communities across the world. While the properties of the virus are similar from place to place, the impact has been dramatically different from place to place, due to such factors as population density, mobility, age distribution, etc. Thus, optimum testing and social distancing strategies may also be different from place to place. The Epidemiology Workbench provides access to an agent-based model in which a communitys demographic, geographic, and public health information together with a social distancing and testing strategy may be input, and a range of possible outcomes computed, to inform local authorities on coping strategies. The model is adaptable to other infectious diseases, and to other strains of coronavirus. The tool is illustrated by scenarios for the cities of Urbana and Champaign, Illinois, the home of the University of Illinois at Urbana-Champaign. Our calculations suggest that massive testing is the most effective strategy to combat the likely increase in local cases due to mass ingress of a student population carrying a higher viral load than that currently present in the community.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.24.20159947", + "rel_abs": "In the fight against the COVID-19 pandemic, lockdowns have succeeded in limiting contagions in many countries, at however heavy societal costs: more targeted non-pharmaceutical interventions are desirable to contain or mitigate potential resurgences. Contact tracing, by identifying and quarantining people who have been in prolonged contact with an infectious individual, has the potential to stop the spread where and when it occurs, with thus limited impact. The limitations of manual contact tracing (MCT), due to delays and imperfect recall of contacts, might be compensated by digital contact tracing (DCT) based on smartphone apps, whose impact however depends on the app adoption. To assess the efficiency of such interventions in realistic settings, we use here datasets describing contacts between individuals in several contexts, with high spatial and temporal resolution, to feed numerical simulations of a compartmental model for COVID-19. We find that the obtained reduction of epidemic size has a robust behavior: this benefit is linear in the fraction of contacts recalled during MCT, and quadratic in the app adoption, with no threshold effect. The combination of tracing strategies can yield important benefits, and the cost (number of quarantines) vs. benefit curve has a typical parabolic shape, independent on the type of tracing, with a high benefit and low cost if app adoption and MCT efficiency are high enough. Our numerical results are qualitatively confirmed by analytical results on simplified models. These results may inform the inclusion of MCT and DCT within COVID-19 response plans.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Santiago N\u00fa\u00f1ez-Corrales", - "author_inst": "University of Illinois at Urbana-Champaign" + "author_name": "Alain Barrat", + "author_inst": "Aix Marseille Univ, Universite de Toulon, CNRS, CPT" }, { - "author_name": "Eric Jakobsson", - "author_inst": "University of Illinois at Urbana-Champaign" + "author_name": "Ciro Cattuto", + "author_inst": "University of Turin, Turin, Italy" + }, + { + "author_name": "Mikko Kivel\u00e4", + "author_inst": "Aalto University, Finland" + }, + { + "author_name": "Sune Lehmann", + "author_inst": "Technical University of Denmark, Copenhagen, Denmark" + }, + { + "author_name": "Jari Saram\u00e4ki", + "author_inst": "Aalto University, Finland" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1277502,61 +1277955,65 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.07.20.20157933", - "rel_title": "A data-driven metapopulation model for the Belgian COVID-19 epidemic: assessing the impact of lockdown and exit strategies", + "rel_doi": "10.1101/2020.07.24.20157982", + "rel_title": "Dynamics of SARS-CoV-2 with Waning Immunity in the UK Population", "rel_date": "2020-07-25", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.20.20157933", - "rel_abs": "BackgroundIn response to the ongoing COVID-19 pandemic, several countries adopted measures of social distancing to a different degree. For many countries, after successfully curbing the initial wave, lockdown measures were gradually lifted. In Belgium, such relief started on May 4th with phase 1, followed by several subsequent phases over the next few weeks.\n\nMethodsWe analysed the expected impact of relaxing stringent lockdown measures taken according to the phased Belgian exit strategy. We developed a stochastic, data-informed, meta-population model that accounts for mixing and mobility of the age-structured population of Belgium. The model is calibrated to daily hospitalization data and serological data and is able to reproduce the outbreak at the national level. We consider different scenarios for relieving the lockdown, quantified in terms of relative reductions in pre-pandemic social mixing and mobility. We validate our assumptions by making comparisons with social contact data collected during and after the lockdown.\n\nResultsOur model is able to successfully describe the initial wave of COVID-19 in Belgium and identifies interactions during leisure/other activities as pivotal in the exit strategy. Indeed, we find a smaller impact of school re-openings as compared to restarting leisure activities and re-openings of work places. We also assess the impact of case isolation of new (suspected) infections, and find that it allows re-establishing relatively more social interactions while still ensuring epidemic control. Scenarios predicting a second wave of hospitalizations were not observed, suggesting that the per-contact probability of infection has changed with respect to the pre-lockdown period.\n\nConclusionsCommunity contacts are found to be most influential, followed by professional contacts and school contacts, respectively, for an impending second wave of COVID-19. Regular re-assessment is crucial to adjust to evolving behavioral changes that can affect epidemic diffusion. In addition to social distancing, sufficient capacity for extensive testing and contact tracing is essential for successful mitigation.", - "rel_num_authors": 11, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.24.20157982", + "rel_abs": "The dynamics of immunity are crucial to understanding the long-term patterns of the SARS-CoV-2 pandemic. Several cases of reinfection with SARS-CoV-2 have been documented 48-142 days after the initial infection and immunity to seasonal circulating coronaviruses is estimated to be shorter than one year. Using an age-structured, deterministic model, we explore potential immunity dynamics using contact data from the UK population. In the scenario where immunity to SARS-CoV-2 lasts an average of three months for non-hospitalised individuals, a year for hospitalised individuals, and the effective reproduction number after lockdown ends is 1.2 (our worst case scenario), we find that the secondary peak occurs in winter 2020 with a daily maximum of 387,000 infectious individuals and 125,000 daily new cases; three-fold greater than in a scenario with permanent immunity. Our models suggests that longitudinal serological surveys to determine if immunity in the population is waning will be most informative when sampling takes place from the end of the lockdown in June until autumn 2020. After this period, the proportion of the population with antibodies to SARS-CoV-2 is expected to increase due to the secondary wave. Overall, our analysis presents considerations for policy makers on the longer term dynamics of SARS-CoV-2 in the UK and suggests that strategies designed to achieve herd immunity may lead to repeated waves of infection as immunity to reinfection is not permanent.", + "rel_num_authors": 12, "rel_authors": [ { - "author_name": "Pietro Coletti", - "author_inst": "Data Science Institute, I-BioStat, UHasselt" + "author_name": "Thomas Crellen", + "author_inst": "University of Oxford" }, { - "author_name": "Pieter Libin", - "author_inst": "Data Science Institute, I-BioStat, UHasselt" + "author_name": "Li Pi", + "author_inst": "University of Oxford" }, { - "author_name": "Oana Petrof", - "author_inst": "Data Science Institute, I-BioStat, UHasselt" + "author_name": "Emma Davis", + "author_inst": "University of Oxford" }, { - "author_name": "Lander Willem", - "author_inst": "Antwerp University" + "author_name": "Timothy M Pollington", + "author_inst": "University of Warwick" }, { - "author_name": "Abrams Steven", - "author_inst": "Data Science Institute, I-BioStat, UHasselt" + "author_name": "Tim C D Lucas", + "author_inst": "University of Oxford" }, { - "author_name": "Sereina A. Herzog", - "author_inst": "Antwerp University" + "author_name": "Diepreye Ayabina", + "author_inst": "University of Oxford" }, { - "author_name": "Christel Faes", - "author_inst": "Data Science Institute, I-BioStat, UHasselt" + "author_name": "Anna Borlase", + "author_inst": "University of Oxford" }, { - "author_name": "James Wambua", - "author_inst": "Data Science Institute, I-BioStat, UHasselt" + "author_name": "Jaspreet Toor", + "author_inst": "University of Oxford" }, { - "author_name": "Elise J. Kuylen", - "author_inst": "Universiteit Antwerpen" + "author_name": "Kiesha Prem", + "author_inst": "London School of Hygiene and Tropical Medicine" }, { - "author_name": "Philippe Beutels", - "author_inst": "University of Antwerp" + "author_name": "Graham F Medley", + "author_inst": "London School of Hygiene and Tropical Medicine" }, { - "author_name": "Niel Hens", - "author_inst": "Hasselt University and University of Antwerp" + "author_name": "Petra Klepac", + "author_inst": "London School of Hygiene and Tropical Medicine" + }, + { + "author_name": "T Deirdre Hollingsworth", + "author_inst": "University of Oxford" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1279100,31 +1279557,31 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.07.23.217083", - "rel_title": "An in-silico study on SARS-CoV-2: Its compatibility with human tRNA pool, and the polymorphism arising in a single lineage over a month", + "rel_doi": "10.1101/2020.07.19.20157362", + "rel_title": "On the effect of age on the transmission of SARS-CoV-2 in households, schools and the community", "rel_date": "2020-07-24", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.07.23.217083", - "rel_abs": "SARS-CoV-2 has caused a global pandemic that has costed enormous human lives in the recent past. The present study is an investigation of the viral codon adaptation, ORFs stability and tRNA co-adaptation with humans. We observed that for the codon usage bias in viral ssRNA, ORFs have near values of folding free energies and codon adaptation index with mRNAs of the human housekeeping CDS. However, the correlation between the stability of the ORFs in ssRNA and CAI is stronger than the mRNA stability and CAI of HKG, suggesting a greater expression capacity of SARS-CoV-2. Mutational analysis reflects polymorphism in the virus for ORF1ab, surface glycoprotein and nucleocapsid phosphoprotein ORFs. Non-synonymous mutations have shown non-polar substitutions. Out of the twelve mutations nine are for a higher t-RNA copy number. Viruses in general have high mutation rates. To understand the chances of survival for the mutated SARS-CoV-2 we did simulation for synonymous mutations. It resulted in 50% ORFs with higher stability than their native equivalents. Thus, considering only the synonymous mutations the virus can exhibit a lot of polymorphism. Collectively our data provides new insights for SARS-CoV-2 mutations and the human t-RNA compatibility.\n\nSignificanceSurvivability of SARS-CoV-2 in humans is essential for its spread. It has overlapping genes exhibiting a high codon optimization with humans even after a higher codon usage bias. They seem to possess cognizance for high copy number t-RNA (cognate or near-cognate) in humans, while mutating. Even though, it has been well established that native transcripts posses the highest stability, our in-silico studies show that SARS-CoV-2 under mutations give rise to ORFs with higher stability. These results significantly present the viruss ability and the credibility of survival for the mutants. Despite its focus on a geographical location it explains the ongoing behavior of SARS-CoV-2 for a steady existence in humans as all the different lineages have a common origin. Wuhan, China.", + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.19.20157362", + "rel_abs": "BackgroundThere is limited information on the effect of age on the transmission of SARS-CoV-2 infection in different settings, including primary, secondary and high schools, households, and the whole community. We undertook a literature review of published studies/data on detection of SARS-CoV-2 infection in contacts of COVID-19 cases, as well as serological studies, and studies of infections in the school setting to examine those issues.\n\nResultsOur literature review presents evidence for significantly lower susceptibility to infection for children aged under 10 years compared to adults given the same exposure, for elevated susceptibility to infection in adults aged over 60y compared to younger/middle aged adults, and for the risk of SARS-CoV-2 infection associated with sleeping close to an infected individual. Published serological studies also suggest that younger adults (particularly those aged under 35y) often have high cumulative rates of SARS-CoV-2 infection in the community. Additionally, there is some evidence of robust spread of SARS-CoV-2 in secondary/high schools, and there appears to be more limited spread in primary schools. Some countries with relatively large class sizes in primary schools (e.g.Chile and Israel) reported sizeable outbreaks in some of those schools, though routes of transmission of infection to both students and staff are not clear from current reports.\n\nConclusionsOpening secondary/high schools is likely to contribute to the spread of SARS-CoV-2, and, if implemented, it should require both lower levels of community transmission and greater safeguards to reduce transmission. Compared to secondary/high schools, opening primary schools and daycare facilities may have a more limited effect on the spread of SARS-CoV-2 in the community, particularly under smaller class sizes and in the presence of mitigation measures. Efforts to avoid crowding in the classroom and other mitigation measures should be implemented, to the extent possible, when opening primary schools. Efforts should be undertaken to diminish the mixing in younger adults to mitigate the spread of the epidemic in the whole community.", "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Manish Victor", - "author_inst": "Bose Institute" + "author_name": "Edward Goldstein", + "author_inst": "Harvard TH Chan School of Public Health" }, { - "author_name": "Rohit Das", - "author_inst": "Bose Institute" + "author_name": "Marc Lipsitch", + "author_inst": "Harvard T.H. Chan School of Public Health" }, { - "author_name": "Tapash Ghosh", - "author_inst": "Bose Institute" + "author_name": "Muge Cevik", + "author_inst": "University of St Andrews" } ], "version": "1", - "license": "cc_no", - "type": "new results", - "category": "bioinformatics" + "license": "cc_by_nc", + "type": "PUBLISHAHEADOFPRINT", + "category": "epidemiology" }, { "rel_doi": "10.1101/2020.07.22.20159673", @@ -1280534,85 +1280991,41 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.07.23.20160820", - "rel_title": "Clinical Impact, Costs, and Cost-Effectiveness of Expanded SARS-CoV-2 Testing in Massachusetts", + "rel_doi": "10.1101/2020.07.23.20160895", + "rel_title": "ASSESSING THE AGE SPECIFICITY OF INFECTION FATALITY RATES FOR COVID-19: META-ANALYSIS & PUBLIC POLICY IMPLICATIONS", "rel_date": "2020-07-24", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.23.20160820", - "rel_abs": "BackgroundWe projected the clinical and economic impact of alternative testing strategies on COVID-19 incidence and mortality in Massachusetts using a microsimulation model.\n\nMethodsWe compared five testing strategies: 1) PCR-severe-only: PCR testing only patients with severe/critical symptoms; 2) Self-screen: PCR-severe-only plus self-assessment of COVID-19-consistent symptoms with self-isolation if positive; 3) PCR-any-symptom: PCR for any COVID-19-consistent symptoms with self-isolation if positive; 4) PCR-all: PCR-any-symptom and one-time PCR for the entire population; and, 5) PCR-all-repeat: PCR-all with monthly re-testing. We examined effective reproduction numbers (Re, 0.9-2.0) at which policy conclusions would change. We used published data on disease progression and mortality, transmission, PCR sensitivity/specificity (70/100%) and costs. Model-projected outcomes included infections, deaths, tests performed, hospital-days, and costs over 180-days, as well as incremental cost-effectiveness ratios (ICERs, $/quality-adjusted life-year [QALY]).\n\nResultsIn all scenarios, PCR-all-repeat would lead to the best clinical outcomes and PCR-severe-only would lead to the worst; at Re 0.9, PCR-all-repeat vs. PCR-severe-only resulted in a 63% reduction in infections and a 44% reduction in deaths, but required >65-fold more tests/day with 4-fold higher costs. PCR-all-repeat had an ICER <$100,000/QALY only when Re [≥]1.8. At all Re values, PCR-any-symptom was cost-saving compared to other strategies.\n\nConclusionsTesting people with any COVID-19-consistent symptoms would be cost-saving compared to restricting testing to only those with symptoms severe enough to warrant hospital care. Expanding PCR testing to asymptomatic people would decrease infections, deaths, and hospitalizations. Universal screening would be cost-effective when paired with monthly retesting in settings where the COVID-19 pandemic is surging.", - "rel_num_authors": 17, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.23.20160895", + "rel_abs": "Structured AbstractO_ST_ABSObjectiveC_ST_ABSDetermine age-specific infection fatality rates for COVID-19 to inform public health policies and communications that help protect vulnerable age groups.\n\nMethodsStudies of COVID-19 prevalence were collected by conducting an online search of published articles, preprints, and government reports. A total of 111 studies were reviewed in depth and screened. Studies of 33 locations satisfied the inclusion criteria and were included in the meta-analysis. Age-specific IFRs were computed using the prevalence data in conjunction with reported fatalities four weeks after the midpoint date of the study, reflecting typical lags in fatalities and reporting. Meta-regression procedures in Stata were used to analyze IFR by age.\n\nResultsOur analysis finds a exponential relationship between age and IFR for COVID-19. The estimated age-specific IFRs are very low for children and younger adults but increase progressively to 0.4% at age 55, 1.3% at age 65, 4.2% at age 75, and 14% at age 85. We find that differences in the age structure of the population and the age-specific prevalence of COVID-19 explain nearly 90% of the geographical variation in population IFR.\n\nDiscussionThese results indicate that COVID-19 is hazardous not only for the elderly but also for middle-aged adults, for whom the infection fatality rate is two orders of magnitude greater than the annualized risk of a fatal automobile accident and far more dangerous than seasonal influenza. Moreover, the overall IFR for COVID-19 should not be viewed as a fixed parameter but as intrinsically linked to the age-specific pattern of infections. Consequently, public health measures to mitigate infections in older adults could substantially decrease total deaths.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Anne M Neilan", - "author_inst": "Massachusetts General Hospital" - }, - { - "author_name": "Elena Losina", - "author_inst": "Brigham and Women's Hospital" - }, - { - "author_name": "Audrey C. Bangs", - "author_inst": "Massachusetts General Hospital" - }, - { - "author_name": "Clare Flanagan", - "author_inst": "Massachusetts General Hospital" - }, - { - "author_name": "Christopher Panella", - "author_inst": "Massachusetts General Hospital" - }, - { - "author_name": "G. Ege Eskibozkurt", - "author_inst": "Massachusetts General Hospital" - }, - { - "author_name": "Amir M. Mohareb", - "author_inst": "Massachusetts General Hospital" - }, - { - "author_name": "Emily P. Hyle", - "author_inst": "Massachusetts General Hospital" - }, - { - "author_name": "Justine A. Scott", - "author_inst": "Massachusetts General Hospital" + "author_name": "Andrew T Levin", + "author_inst": "Dartmouth College" }, { - "author_name": "Milton C. Weinstein", + "author_name": "William P. Hanage", "author_inst": "Harvard T.H. Chan School of Public Health" }, { - "author_name": "Mark J. Siedner", - "author_inst": "Massachusetts General Hospital" - }, - { - "author_name": "Krishna P Reddy", - "author_inst": "Massachusetts General Hospital" - }, - { - "author_name": "Guy Harling", - "author_inst": "University College London" - }, - { - "author_name": "Kenneth A. Freedberg", - "author_inst": "Massachusetts General Hospital" + "author_name": "Nana Owusu-Boaitey", + "author_inst": "Case Western Reserve University School of Medicine" }, { - "author_name": "Fatma M. Shebl", - "author_inst": "Massachusetts General Hospital" + "author_name": "Kensington B. Cochran", + "author_inst": "Dartmouth College" }, { - "author_name": "Pooyan Kazemian", - "author_inst": "Massachusetts General Hospital" + "author_name": "Seamus P. Walsh", + "author_inst": "Dartmouth College" }, { - "author_name": "Andrea L. Ciaranello", - "author_inst": "Massachusetts General Hospital" + "author_name": "Gideon Meyerowitz-Katz", + "author_inst": "University of Wollongong" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1281844,29 +1282257,37 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.07.22.20160028", - "rel_title": "Evidence for immunity to SARS-CoV-2 from epidemiological data series", + "rel_doi": "10.1101/2020.07.22.20159855", + "rel_title": "Renin-Angiotensin-Aldosterone-System inhibitor use in patients with COVID-19 infection and prevention of serious events: a cohort study in commercially insured patients in the US", "rel_date": "2020-07-24", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.22.20160028", - "rel_abs": "The duration of immunity to SARS-CoV-2 is uncertain. Delineating immune memory typically requires longitudinal serological studies that track antibody prevalence in the same cohort for an extended time. However, this information is needed in faster timescales. Notably, the dynamics of an epidemic where recovered patients become immune for any period should differ significantly from those of one where the recovered promptly become susceptible. Here, we exploit this difference to provide a reliable protocol that can estimate immunity early in an epidemic. We verify this protocol with synthetic data, discuss its limitations, and then apply it to evaluate human immunity to SARS-CoV-2 in mortality data series from New York City. Our results indicate that New Yorks mortality figures are incompatible with immunity lasting anything below 105 or above 211 days (90% CI.), and set an example on how to assess immune memory in emerging pandemics before serological studies can be deployed.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.22.20159855", + "rel_abs": "ObjectivesThere is lack of clarity regarding the role of angiotensin receptor blockers (ARB) or angiotensin converting enzyme inhibitors (ACEi) in interfering with the SARS-COV-2 binding on human cells and the resulting change in disease severity. We sought to assess the risk of hospitalization for COVID-19 and serious complications in current users of ARB or ACEi compared to users of dihydropyridine calcium channel blockers (dhpCCB).\n\nDesignCohort study\n\nSettingThe analysis used de-identified, patient level data from HealthVerity, linking longitudinal data from US medical and pharmacy claims, which contain information on inpatient or outpatient diagnoses, procedures and medication dispensing.\n\nParticipantsWe identified patients aged 40+ and free of chronic kidney disease (CKD) who were newly diagnosed COVID-19, between March 1, 2020 and May 30, 2020, and adherent to ACEi, ARB, or dhpCCB therapy.\n\nInterventionsCurrent use of an ACEi, ARB, or dhpCCB.\n\nMain outcome measuresWe compared the 30-day risk of hospitalization for COVID-19 and serious complications.\n\nResultsOf 24,708 patients identified, 7,571 were current users of an ARB, 8,484 of an ACEi, and 8,653 of a dhpCCB. The unadjusted 30-day risk of hospitalization for COVID-19 was 2.66% among ARB users, and 2.90% among ACEi users and 3.68% in dhpCCB users. In the PS-matched cohort, the risk of hospitalization among ARB users was 17% lower as compared to dhpCCB (RR=0.83; 0.68-1.00), and the risk among ACE users was 10% lower as compared to dhpCCB (RR=0.90; 0.76-1.07). When including patients with pre-existing CKD, the protective effect of ARB (RR= 0.74; 0.62-0.88) and ACEi (RR=0.84; 0.71-0.99) was more pronounced.\n\nConclusionsThis cohort study showed that neither ARB nor ACEi use increase the risk of severe COVID-19 disease among those infected, and instead suggests that current use of ARB may offer a protective effect. This study found no evidence to support the discontinuation of ARB/ACEi therapy.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Pablo Yubero", - "author_inst": "Spanish National Biotechnology Center (CNB-CSIC)" + "author_name": "Maria C Schneeweiss", + "author_inst": "Brigham and Women's Hospital" + }, + { + "author_name": "Sandra Leonard", + "author_inst": "HealthVerity Inc." }, { - "author_name": "Alvar A. Lavin", - "author_inst": "Spanish National Biotechnology Center (CNB-CSIC)" + "author_name": "Andrew Weckstein", + "author_inst": "Aetion, Inc." }, { - "author_name": "Juan F Poyatos", - "author_inst": "Spanish National Biotechnology Center (CNB-CSIC)" + "author_name": "Sebastian Schneeweiss", + "author_inst": "Brigham and Women's Hospital and Harvard Medical School" + }, + { + "author_name": "Jeremy Rassen", + "author_inst": "Aetion, Inc." } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1283522,23 +1283943,27 @@ "category": "intensive care and critical care medicine" }, { - "rel_doi": "10.1101/2020.07.21.20158972", - "rel_title": "Invasive pulmonary aspergillosis in critically ill patients with severe COVID-19 pneumonia: results from the prospective AspCOVID-19 study", + "rel_doi": "10.1101/2020.07.20.20158576", + "rel_title": "Assessing the relative contributions of healthcare protocols for epidemic control: an example with network transmission model for COVID-19", "rel_date": "2020-07-22", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.21.20158972", - "rel_abs": "BackgroundSuperinfections, including invasive pulmonary aspergillosis (IPA), are well-known complications of critically ill patients with severe viral pneumonia. Aim of this study was to evaluate the incidence, risk factors and outcome of IPA in critically ill patients with severe COVID-19 pneumonia.\n\nMethodsWe prospectively screened 32 critically ill patients with severe COVID-19 pneumonia for a time period of 28 days using a standardized study protocol for oberservation of developement of COVID-19 associated invasive pulmonary aspergillosis (CAPA). We collected laboratory, microbiological, virological and clinical parameters at defined timepoints in combination with galactomannan-antigen-detection from bronchial aspirates. We used logistic regression analyses to assess if COVID-19 was independently associated with IPA and compared it with matched controls.\n\nFindingsCAPA was diagnosed at a median of 4 days after ICU admission in 11/32 (34%) of critically ill patients with severe COVID-19 pneumonia as compared to 8% in the control cohort.\n\nIn the COVID-19 cohort, mean age, APACHE II score and ICU mortality were higher in patients with CAPA than in patients without CAPA (36% versus 9.5%; p<0.001). ICU stay (21 versus 17 days; p=0.340) and days of mechanical ventilation (20 versus 15 days; p=0.570) were not different between both groups. In regression analysis COVID-19 and APACHE II score were independently associated with IPA.\n\nInterpretationCAPA is highly prevalent and associated with a high mortality rate. COVID-19 is independently associated with invasive pulmonary aspergillosis. A standardized screening and diagnostic approach as presented in our study can help to identify affected patients at an early stage.\n\nFundingNone", - "rel_num_authors": 1, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.20.20158576", + "rel_abs": "The increasing number of COVID-19 cases threatens human life and requires retainment actions that control the spread of the virus in the absence of effective medical therapy or a reliable vaccine. There is a general consensus that the most efficient health protocol in the actual state is to disrupt the infection chain through social distancing, although economic interests stand against closing non-essential activities and poses a debatable tradeoff. In this study, we used an individual-based age-structured network model to assess the effective roles of different healthcare protocols such as the use of personal protection equipment and social distancing at neighbor- and city-level scales. Using as much as empirical data available in the literature, we calibrated a city model and simulated low, medium, and high parameters representing these protocols. Our results revealed that the model was more sensitive to changes in the parameter representing the rate of contact among people from different neighborhoods, which defends the social distancing at the city-level as the most effective protocol for the control of the disease outbreak. Another important identified parameter represented the use of individual equipment such as masks, face shields, and hand sanitizers like alcohol-based solutions and antiseptic products. Interestingly, our simulations suggest that some periodical activities such as going to the supermarket, gas station, and pharmacy would have little contribution to the SARS-CoV-2 spread once performed within the same neighborhood. As we can see nowadays, there is an inevitable context-dependency and economic pressure on the level of social distancing recommendations, and we reinforce that every decision must be a welfare-oriented science-based decision.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Tobias Lahmer", - "author_inst": "Klinikum rechts der Isar, TU Muenchen" + "author_name": "Matheus T Baumgartner", + "author_inst": "State University of Maring" + }, + { + "author_name": "Fernando M Lansac-Toha", + "author_inst": "State University of Maring" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "intensive care and critical care medicine" + "category": "epidemiology" }, { "rel_doi": "10.1101/2020.07.20.20158436", @@ -1285208,17 +1285633,37 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.07.18.20156893", - "rel_title": "Do low TB prevalence or lack of BCG VaccinationContribute to Emergence Multisystem Inflammatory Syndrome?", + "rel_doi": "10.1101/2020.07.19.20157453", + "rel_title": "Recurrent SARS-CoV-2 RNA positivity after COVID-19: A systematic review and meta analysis", "rel_date": "2020-07-21", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.18.20156893", - "rel_abs": "BackgroundEmergence of new multisystem inflammatory syndrome in children (MIS-C) is thought to be associated with COVID-19 pandemic. Covid-19 morbidity and mortality variances among countries have been suggested by previous works to be influenced by BCG and previous latent TB infection (which is reflected by TB prevalence) possibly through inducing heterogeneous immunity against SARS-CoV-2.\n\nAimTo examine influence of BCG status and TB prevalence on variances among countries which report new multisystem inflammatory syndrome in children (MIS-C).\n\nMethodsWe choose all countries which report MIS-C till 23/6/2020, number of cases for each 10 million inhabitants was examined among 3 categories of countries classified according to BCG program status. TB prevalence, MIS-C no. / 10 million (M) population and Covid-19 deaths/M are taken as markers. Receiver operation characteristic - (ROC) curve, with some relative indicators such as (sensitivity and specificity rates), estimation area of trade - off between sensitivity and specificity, and cutoff points are used with different studied markers for discriminating different three pairs of countries (which have different BCG practices).\n\nResultsBCG vaccinations and high TB prevalence are found to be associated with decrease MIS-C no. and COVID-19 deaths\n\nConclusionsFindings might explain variances in MIS-C incidence and in COVID-19 mortality among countries worldwide. Further studies to confirm this relation and to confirm possible similar relations in Kawasaki disease(KD) in previous epidemics is recommended.\n\nWhat is Known- Although the etiology for KD remains unknown, available evidence supports the hypothesis that the pathogenesis is closely associated with dysregulation of immune responses to an infectious agent.\n- BCG and / or Latent TB have heterogeneous beneficial effects.\n\n\nWhat is NewOur study shows that TB prevalence and implementing BCG vaccination have negative statistical association with MIS-C cases and COVID-19 mortality.", - "rel_num_authors": 1, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.19.20157453", + "rel_abs": "BackgroundPrevious studies reported recurrent SARS-CoV-2 RNA positivity in individuals who had recovered from COVID-19 infections. However, little is known regarding the systematic review of recurrent SARS-CoV-2 RNA positivity. The current study conducted a systematic review and meta-analysis, aimed to estimate the incidence of recurrent SARS-CoV-2 RNA positivity after recovery from COVID-19 and to determine the factors associated with recurrent positivity.\n\nMethodsWe searched the PubMed, MedRxiv, BioRxiv, the Cochrane Library, ClinicalTrials.gov, and the World Health Organization International Clinical Trials Registry for studies published to June 12, 2020. Studies were reviewed to determine the risk of bias. A random-effects model was used to pool results. Heterogeneity was assessed using I2.\n\nResultsFourteen studies of 2,568 individuals were included. The incidence of recurrent SARS-CoV-2 positivity was 14.81% (95% confidence interval [CI]: 11.44-18.19%). The pooled estimate of the interval from disease onset to recurrence was 35.44 days (95% CI: 32.65-38.24 days), and from the last negative to recurrent positive result was 9.76 days (95% CI: 7.31-12.22 days). Patients with younger age (mean difference [MD]=-2.27, 95% CI: -2.95 to -1.80) and a longer initial illness (MD=8.24 days; 95% CI: 7.54 - 8.95; I2=98.9%) were more likely to experience recurrent SARS-CoV-2 positivity, while patients with diabetes (RR=0.52; 95% CI: 0.30-0.90; I2=53%), severe disease (RR=0.54; 95% CI: 0.35-0.84; I2=70%), and a low lymphocyte count (RR=0.58; 95% CI: 0.39 - 0.86; I2=48%) were less likely to experience recurrent SARS-CoV-2 positivity.\n\nConclusionsThe incidence of recurrent SARS-CoV-2 positivity was 14.81%. The estimated interval from disease onset to repeat positivity was 35.44 days, and the estimated interval from the last negative result to recurrent positive result duration was 9.76 days.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Tareef F Raham", - "author_inst": "MOH IRAQ" + "author_name": "Mahalul Azam", + "author_inst": "Universitas Negeri Semarang" + }, + { + "author_name": "Rina Sulistana", + "author_inst": "Universitas Negeri Semarang" + }, + { + "author_name": "Martha Ratnawati", + "author_inst": "SMC Tlogorejo Hospital" + }, + { + "author_name": "Arulita Ika Fibriana", + "author_inst": "Universitas Negeri Semarang" + }, + { + "author_name": "Udin Bahrudin", + "author_inst": "Diponegoro University" + }, + { + "author_name": "Syed Mohamed Aljunid", + "author_inst": "Kuwait University" } ], "version": "1", @@ -1286866,43 +1287311,75 @@ "category": "health economics" }, { - "rel_doi": "10.1101/2020.07.19.211110", - "rel_title": "The short and long-range RNA-RNA Interactome of SARS-CoV-2", + "rel_doi": "10.1101/2020.07.19.210955", + "rel_title": "Interferons and viruses induce a novel primate-specific isoform dACE2 and not the SARS-CoV-2 receptor ACE2", "rel_date": "2020-07-20", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.07.19.211110", - "rel_abs": "The Coronaviridae is a family of positive-strand RNA viruses that includes SARS-CoV-2, the etiologic agent of the COVID-19 pandemic. Bearing the largest single-stranded RNA genomes in nature, coronaviruses are critically dependent on long-distance RNA-RNA interactions to regulate the viral transcription and replication pathways. Here we experimentally mapped the in vivo RNA-RNA interactome of the full-length SARS-CoV-2 genome and subgenomic mRNAs. We uncovered a network of RNA-RNA interactions spanning tens of thousands of nucleotides. These interactions reveal that the viral genome and subgenomes adopt alternative topologies inside cells, and engage in different interactions with host RNAs. Notably, we discovered a long-range RNA-RNA interaction - the FSE-arch - that encircles the programmed ribosomal frameshifting element. The FSE-arch is conserved in the related MERS-CoV and is under purifying selection. Our findings illuminate RNA structure based mechanisms governing replication, discontinuous transcription, and translation of coronaviruses, and will aid future efforts to develop antiviral strategies.", - "rel_num_authors": 6, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.07.19.210955", + "rel_abs": "Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), which causes COVID-19, utilizes angiotensin-converting enzyme 2 (ACE2) for entry into target cells. ACE2 has been proposed as an interferon-stimulated gene (ISG). Thus, interferon-induced variability in ACE2 expression levels could be important for susceptibility to COVID-19 or its outcomes. Here, we report the discovery of a novel, primate-specific isoform of ACE2, which we designate as deltaACE2 (dACE2). We demonstrate that dACE2, but not ACE2, is an ISG. In vitro, dACE2, which lacks 356 N-terminal amino acids, was non-functional in binding the SARS-CoV-2 spike protein and as a carboxypeptidase. Our results reconcile current knowledge on ACE2 expression and suggest that the ISG-type induction of dACE2 in IFN-high conditions created by treatments, inflammatory tumor microenvironment, or viral co-infections is unlikely to affect the cellular entry of SARS-CoV-2 and promote infection.", + "rel_num_authors": 14, "rel_authors": [ { - "author_name": "Omer Ziv", - "author_inst": "Wellcome Trust/Cancer Research UK Gurdon Institute, University of Cambridge, Cambridge, CB2 1QN, UK" + "author_name": "Olusegun O Onabajo", + "author_inst": "Laboratory of Translational Genomics, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA" }, { - "author_name": "Jonathan Price", - "author_inst": "Wellcome Trust/Cancer Research UK Gurdon Institute, University of Cambridge, Cambridge, CB2 1QN, UK" + "author_name": "A Rouf Banday", + "author_inst": "Laboratory of Translational Genomics, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA" }, { - "author_name": "Lyudmila Shalamova", - "author_inst": "Institute for Virology, FB10-Veterinary Medicine, Justus-Liebig University, Giessen 35392, Germany" + "author_name": "Wusheng Yan", + "author_inst": "Laboratory of Translational Genomics, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA" }, { - "author_name": "Tsveta Kamenova", - "author_inst": "Wellcome Trust/Cancer Research UK Gurdon Institute, University of Cambridge, Cambridge, CB2 1QN, UK" + "author_name": "Adeola Obajemu", + "author_inst": "Laboratory of Translational Genomics, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA" }, { - "author_name": "Friedemann Weber", - "author_inst": "Institute for Virology, FB10-Veterinary Medicine, Justus-Liebig University, Giessen 35392, Germany" + "author_name": "Megan L Stanifer", + "author_inst": "Department of Infectious Diseases, Molecular Virology, University Hospital Heidelberg, Heidelberg, Germany" }, { - "author_name": "Eric A. Miska", - "author_inst": "Wellcome Trust/Cancer Research UK Gurdon Institute and Department of Genetics, University of Cambridge, Cambridge, CB2 1QN, UK" + "author_name": "Deanna M Santer", + "author_inst": "Li Ka Shing Institute of Virology and Department of Medical Microbiology and Immunology, University of Alberta, Edmonton, Alberta, Canada." + }, + { + "author_name": "Oscar Florez-Vargas", + "author_inst": "Laboratory of Translational Genomics, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA" + }, + { + "author_name": "Helen Piontkivska", + "author_inst": "Department of Biological Sciences and Brain Health Research Institute, Kent State University, Kent, OH, USA" + }, + { + "author_name": "Joselin Vargas", + "author_inst": "Laboratory of Translational Genomics, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA" + }, + { + "author_name": "Carmon Kee", + "author_inst": "Division of Cellular Polarity and Viral Infection, German Cancer Research Center (DKFZ); Department of Infectious Diseases, Virology, University Hospital Heidel" + }, + { + "author_name": "D Lorne Tyrrell", + "author_inst": "Li Ka Shing Institute of Virology and Department of Medical Microbiology and Immunology, University of Alberta, Edmonton, Alberta, Canada." + }, + { + "author_name": "Juan L Mendoza", + "author_inst": "Pritzker School of Molecular Engineering and Department of Biochemistry and Molecular Biology, University of Chicago, Chicago, IL, USA" + }, + { + "author_name": "Steeve Boulant", + "author_inst": "Division of Cellular Polarity and Viral Infection, German Cancer Research Center (DKFZ); Department of Infectious Diseases, Virology, University Hospital Heidel" + }, + { + "author_name": "Ludmila Prokunina-Olsson", + "author_inst": "National Cancer Institute" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc0", "type": "new results", - "category": "molecular biology" + "category": "genetics" }, { "rel_doi": "10.1101/2020.07.20.211789", @@ -1288508,31 +1288985,27 @@ "category": "evolutionary biology" }, { - "rel_doi": "10.1101/2020.07.20.212563", - "rel_title": "In silico comparative genomics of SARS-CoV-2 to determine the source and diversity of the pathogen in Bangladesh", + "rel_doi": "10.1101/2020.07.20.212068", + "rel_title": "Computational optimization of the SARS-CoV-2 receptor-binding-motif affinity for human ACE2", "rel_date": "2020-07-20", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.07.20.212563", - "rel_abs": "The COVID19 pandemic caused by SARS-CoV-2 virus has severely affected most countries of the world including Bangladesh. We conducted comparative analysis of publicly available whole-genome sequences of 64 SARS-CoV-2 isolates in Bangladesh and 371 isolates from another 27 countries to predict possible transmission routes of COVID19 to Bangladesh and genomic variations among the viruses. Phylogenetic analysis indicated that the pathogen was imported in Bangladesh from multiple countries. The viruses found in the southern district of Chattogram were closely related to strains from Saudi Arabia whereas those in Dhaka were similar to that of United Kingdom and France. The 64 SARS-CoV-2 sequences from Bangladesh belonged to three clusters. Compared to the ancestral SARS-CoV-2 sequence reported from China, the isolates in Bangladesh had a total of 180 mutations in the coding region of the genome, and 110 of these were missense. Among these, 99 missense mutations (90%) were predicted to destabilize protein structures. Remarkably, a mutation that leads to an I300F change in the nsp2 protein and a mutation leading to D614G change in the spike protein were prevalent in SARS-CoV-2 genomic sequences, and might have influenced the epidemiological properties of the virus in Bangladesh.", - "rel_num_authors": 3, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.07.20.212068", + "rel_abs": "The coronavirus SARS-CoV-2, that is responsible for the COVID-19 pandemic, and the closely related SARS-CoV coronavirus enter cells by binding at the human angiotensin converting enzyme 2 (hACE2). The stronger hACE2 affinity of SARS-CoV-2 has been connected with its higher infectivity. In this work, we study hACE2 complexes with the receptor binding domains (RBDs) of the human SARS-CoV-2 and human SARS-CoV viruses, using all-atom molecular dynamics (MD) simulations and Computational Protein Design (CPD) with a physics-based energy function. The MD simulations identify charge-modifying substitutions between the CoV-2 and CoV RBDs, which either increase or decrease the hACE2 affinity of the SARS-CoV-2 RBD. The combined effect of these mutations is small, and the relative affinity is mainly determined by substitutions at residues in contact with hACE2. Many of these findings are in line and interpret recent experiments. Our CPD calculations redesign positions 455, 493, 494 and 501 of the SARS-CoV-2 RBM, which contact hACE2 in the complex and are important for ACE2 recognition. Sampling is enhanced by an adaptive importance sampling Monte Carlo method. Sequences with increased affinity replace CoV-2 glutamine by a negative residue at position 493, and serine by nonpolar, aromatic or a threonine at position 494. Substitutions at positions positions 455 and 501 have a smaller effect on affinity. Substitutions suggested by our design are seen in viral sequences encountered in other species, including bat and pangolin. Our results might be used to identify potential virus strains with higher human infectivity and assist in the design of peptide-based or peptidomimetic compounds with the potential to inhibit SARS-CoV-2 binding at hACE2.\n\nSIGNIFICANCEThe coronavirus SARS-CoV-2 is responsible for the current COVID-19 pandemic. SARS-CoV-2 and the earlier, closely related SARS-CoV virus bind at the human angiotensin converting enzyme 2 (hACE2) receptor at the cell surface. The higher human infectivity of SARS-CoV-2 may be linked to its stronger affinity for hACE2. Here, we study by computational methods complexes of hACE2 with the receptor binding domains (RBDs) of viruses SARS-CoV-2 and SARS-CoV. We identify residues affecting the affinities of the two domains for hACE2. We also propose mutations at key SARS-CoV-2 positions, which might enhance hACE2 affinity. Such mutations may appear in viral strains with increased human infectivity and might assist the design of peptide-based compounds that inhibit infection of human cells by SARS-CoV-2.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Tushar A Shishir", - "author_inst": "Brac University, Bangladesh" - }, - { - "author_name": "Iftekhar Bin Naser", - "author_inst": "Brac University, Bangladesh" + "author_name": "Savvas Polydorides", + "author_inst": "University of Cyprus" }, { - "author_name": "Shah M Faruque", - "author_inst": "Independent University, Bangladesh" + "author_name": "Georgios Archontis", + "author_inst": "University of Cyprus" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by_nc_nd", "type": "new results", - "category": "bioinformatics" + "category": "biophysics" }, { "rel_doi": "10.1101/2020.07.17.20156505", @@ -1290306,29 +1290779,29 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.07.16.20155812", - "rel_title": "A Contact-Explicit Covid-19 Epidemic and Response Assessment Model", + "rel_doi": "10.1101/2020.07.16.20155358", + "rel_title": "The risk of severe COVID-19: hospital and ICU admission rates in Norway", "rel_date": "2020-07-18", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.16.20155812", - "rel_abs": "We formulate a refined SEIR epidemic model that explicitly includes a contact class C that either thwarts pathogen invasion and returns to the susceptible class S or progresses successively through latent, asymptomatic, and symptomatic classes L, A, and I. Individuals in both A and I may go directly to an immune class V, and in I to a dead class D. We extend this SCLAIV formulation by including a set of drivers that can be used to develop policy to manage current Covid-19 and similar type disease outbreaks. These drivers include surveillance, social distancing (rate and efficacy), social relaxation, quarantining (linked to contact tracing), patient treatment/isolation and vaccination processes, each of which can be represented by a non-negative constant or an s-shaped switching flow. The latter are defined in terms of onset and switching times, initial and final values, and abruptness of switching. We built a Covid-19NMB-DASA web app to generate both deterministic and stochastic solutions to our SCLAIV and drivers model and use incidence and mortality data to provide both maximum-likelihood estimation (MLE) and Bayesian MCMC fitting of parameters. In the context of South African and English Covid-19 incidence data we demonstrate how to both identify and evaluate the role of drivers in ongoing outbreaks. In particular, we show that early social distancing in South Africa likely averted around 80,000 observed cases (actual number is double if only half the cases are observed) during the months of June and July. We also demonstrated that incidence rates in South Africa will increase to between a conservative estimate of 15 and 30 thousand observed cases per day (at a 50% surveillance level) by the end of August if stronger social distancing measures are not effected during July and August, 2020. On different a note, we show that comparably good local MLE fits of the English data using surveillance, social distancing and social relaxation drivers can represent very different kinds of outbreaks--one with close to 90% and another with under 8% immune individuals. This latter result provides a cautionary tale of why fitting SEIR-like models to incidence or prevalence data can be extremely problematic when not anchored by other critical measures, such as levels of immunity in the population. Our presentation illustrates how our SCLAIV formulation can be used to carry out forensic and scenario analyses of disease outbreaks such as Covid-19 in well defined regions.", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.16.20155358", + "rel_abs": "BackgroundEpidemiological studies of COVID-19 with population based information may add to the knowledge needed to prioritise resources and advice on how restrictive measures should be targeted. This study provides admission rates to hospitals and intensive care units (ICU) in Norway, aiming to better understand the risk of severe COVID-19 infection.\n\nMethodsData from official reports from The Norwegian Institute of Public Health (NIPH) and the Norwegian Directorate of Health were used to calculate admission rates to hospitals and to ICU per 100 000 inhabitants. We compared rates of hospitalisation between the four health regions and provide separate rates for Oslo. We also assessed national admissions to ICU stratified by age.\n\nResultsThe admission rate in the south-eastern region was 3.1 per 100 000, and the rate for Oslo was 5.8. Compared to the western region (reference), the Oslo rate was 4.0 times (confidence interval (CI) 3.0-5.5) higher. In Norway as a whole, the rate of ICU admissions was 3.9 per 100 000, and in the age groups 60-69 and 70-79, ICU rates were 10.3 and 11.5, respectively. These rates were 9.5 (CI 6.3-14.3) and 10.6 (CI 6.9-16.2) times higher compared to people younger than 50 years.\n\nConclusionHospital admissions due to Covid-19 are much higher in Oslo than anywhere else in Norway, and in the country as a whole, ICU admissions are highest among people 60-79 years of age. These results and more detailed data could provide better advice on how restrictions can be safely lessened.", "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Wayne M Getz", - "author_inst": "University of California, Berkeley, Dept ESPM" + "author_name": "Morten Munkvik", + "author_inst": "University of Stavanger" }, { - "author_name": "Ludovica Luisa-Vissat", - "author_inst": "University of California, Berkeley, Dept ESPM" + "author_name": "Ingvild Vatten Alsnes", + "author_inst": "University og Stavanger" }, { - "author_name": "Richard Salter", - "author_inst": "Oberlin College, Dept Computer Science" + "author_name": "Lars Vatten", + "author_inst": "Norwegian University of Science and Technology" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1292344,35 +1292817,43 @@ "category": "rheumatology" }, { - "rel_doi": "10.1101/2020.07.15.20126730", - "rel_title": "Acute Demyelinating Encephalomyelitis (ADEM) in COVID-19 infection: A Case Series.", + "rel_doi": "10.1101/2020.07.14.20153429", + "rel_title": "COVID-19 Pandemic among Latinx Farmworker and Non-farmworker Families in North Carolina: Knowledge, Risk Perceptions, and Preventive Behaviors", "rel_date": "2020-07-17", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.15.20126730", - "rel_abs": "ObjectiveTo report three patients infected with COVID-19 with severe respiratory syndrome requiring intubation, who developed acute demyelinating encephalomyelitis (ADEM).\n\nMethodPatient data were obtained from medical records from the North Memorial Health Hospital, Robbinsdale, MN, USA\n\nResultsThree patients (two men and one woman, aged 38 - 63) presented with fatigue, cough and fever leading to development of acute respiratory distress syndrome secondary to COVID-19 infection requiring intubation and ventilatory support. Two patients were unresponsive, one with strong eye deviation to the left and the third patient had severe diffuse weakness. MRI in all patients showed findings consistent with ADEM. CSF showed elevated protein in all patients with normal cell count and no evidence of infection, including negative COVID-19 PCR. All three of the patients received Convalescent plasma therapy for COVID-19. All patients were treated with intravenous corticosteroids and improved, although two responded minimally. Two patients treated with IVIG showed no further improvement.\n\nConclusionNeurological complications from COVID-19 are being rapidly recognized. Our three cases highlight the occurrence of ADEM as a postinfectious/immune mediated complication of COVID-19 infection, which may be responsive to corticosteroid treatment. Early recognition of this complication and treatment is important to avoid long term complications.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.14.20153429", + "rel_abs": "(1) BackgroundThe COVID-19 pandemic poses substantial threats to Latinx farmworkers and other immigrants in food production and processing. Classified as essential, such workers cannot shelter at home. Therefore, knowledge and preventive behaviors are important to reduce COVID-19 spread in the community.\n\n(2) MethodsRespondents for 67 families with at least one farmworker (FWF) and 38 comparable families with no farmworkers (non-FWF) in North Carolina completed a telephone survey in May, 2020. The survey queried knowledge of COVID-19, perceptions of its severity, self-efficacy, and preventive behaviors. Detailed data were collected to document household members social interaction and use of face coverings.\n\n(3) ResultsKnowledge of COVID-19 and prevention methods was high in both groups, as was its perceived severity. Non-FWF had higher self-efficacy for preventing infection. Both groups claimed to practice preventive behaviors, though FWF emphasized social avoidance and non-FWF emphasized personal hygiene. Detailed social interactions showed high rates of inter-personal contact at home, at work, and in the community with more mask use in non-FWF than FWF.\n\n(4) ConclusionsDespite high levels of knowledge and perceived severity for COVID-19, these immigrant families were engaged in frequent interpersonal contact that could expose community members and themselves to COVID-19.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Michaela McCuddy", - "author_inst": "Department of Family Medicine, University of Minnesota" + "author_name": "Sara A. Quandt", + "author_inst": "Wake Forest School of MEdicine" }, { - "author_name": "Praful Kelkar", - "author_inst": "Minneapolis Clinic of Neurology" + "author_name": "Natalie J. LaMonto", + "author_inst": "Lawrence University" }, { - "author_name": "Yu Zhao", - "author_inst": "Minneapolis Clinic of Neurology" + "author_name": "Dana C. Mora", + "author_inst": "Wake Forest School of Medicine" + }, + { + "author_name": "Jennifer W. Talton", + "author_inst": "Wake Forest School of Medicine" + }, + { + "author_name": "Paul J. Laurienti", + "author_inst": "Wake Forest School of Medicine" }, { - "author_name": "David Wicklund", - "author_inst": "Minneapolis Radiology" + "author_name": "Thomas A. Arcury", + "author_inst": "Wake Forest School of Medicine" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", - "category": "neurology" + "category": "occupational and environmental health" }, { "rel_doi": "10.1101/2020.07.15.20149559", @@ -1294254,55 +1294735,47 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.07.17.20155226", - "rel_title": "Impact of climatic, demographic and disease control factors on the transmission dynamics of COVID-19 in large cities worldwide", + "rel_doi": "10.1101/2020.07.08.20148692", + "rel_title": "Confirmed central olfactory system lesions on brain MRI in COVID-19 patients with anosmia: a case-series", "rel_date": "2020-07-17", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.17.20155226", - "rel_abs": "We are now over seven months into a pandemic of COVID-19 caused by the SARS-CoV-2 virus and global incidence continues to rise. In some regions such as the temperate northern hemisphere there are fears of \"second waves\" of infections over the coming months, while in other, vulnerable regions such as Africa and South America, concerns remain that cases may still rise, further impacting local economies and livelihoods. Despite substantial research efforts to date, it remains unresolved as to whether COVID-19 transmission has the same sensitivity to climate and seasonality observed for other common respiratory viruses such as seasonal influenza. Here we investigate any empirical evidence of seasonality using a robust estimation framework. For 304 large cities across the world, we estimated the basic reproduction number (R0) using logistic growth curves fitted to cumulative case data. We then assessed evidence for association with climatic variables through mixed-effects and ordinary least squares (OLS) regression while adjusting for city-level variation in demographic and disease control factors. We find evidence of association between temperature and R0 during the early phase of the epidemic in China only. During subsequent pandemic spread outside China, we instead find evidence of seasonal change in R0, with greater R0 within cities experiencing shorter daylight hours (direct effect coefficient = -0.247, p = 0.006), after separating out effects of calendar day. The effect of daylight hours may be driven by levels of UV radiation, which is known to have detrimental effects on coronaviruses, including SARS-CoV-2. In the global analysis excluding China, climatic variables had weaker explanatory power compared to demographic or disease control factors. Overall, we find a weak but detectable signal of climate variables on the transmission of COVID-19. As seasonal changes occur later in 2020, it is feasible that the transmission dynamics of COVID-19 may shift in a detectable manner. However, rates of transmission and health burden of the pandemic in the coming months will be ultimately determined by population factors and disease control policies.", - "rel_num_authors": 9, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.08.20148692", + "rel_abs": "ObjectiveAnosmia has been listed as a key-symptom associated with the COVID-19 infection. Because it often occurs without any sign of rhinitis, lesions of the central olfactory system have been suspected. To date, however, there is no evidence that anosmia caused by SARS-CoV2 could be the result of brain damage.\n\nMethodsWe conducted a case-series on 10 consecutive COVID-19 patients who reported anosmia. Each patient prospectively underwent a validated olfactory test (Sniffin Sticks test) and a brain MRI. Results Hypersignal intensity lesions of the central olfactory system were found in 3 subjects on 3D T2 FLAIR and 2D T2 High Resolution images with a lesion involving the olfactory bulbs and/or the orbitofrontal cortex. These 3 subjects showed a severe and persistent loss of smell on the olfactory test. Mucosal hyperplasia of the upper nasal cavities was found in two other subjects with significant smell disorders. There was no MRI anomaly in two subjects with good smell restoration.\n\nConclusionsAnomalies of the central olfactory system could be responsible for anosmia in patients with COVID-19 infection. Further studies are needed to assess the impact on long-term functional prognosis of these lesions.\n\nKey ResultCentral anomalies of the olfactory bulb and cortex could be responsible for anosmia in COVID-19 infection", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Soeren Metelmann", - "author_inst": "University of Liverpool" - }, - { - "author_name": "Karan Pattni", - "author_inst": "University of Liverpool" - }, - { - "author_name": "Liam Brierley", - "author_inst": "University of Liverpool" + "author_name": "Yannick Girardeau", + "author_inst": "Department of Medical Informatics, Biostatistics and Public Health, AP-HP, Hopital Europeen Georges Pompidou, Paris, France" }, { - "author_name": "Lisa Cavalerie", - "author_inst": "University of Liverpool / International Livestock Research Institute" + "author_name": "Yoan GALLOIS", + "author_inst": "Service d Otologie, Otoneurologie et ORL pediatrique, Hopital Pierre-Paul Riquet, CHU Toulouse Purpan - Brain & Cognition Research Centre, UMR 5549, Universite " }, { - "author_name": "Cyril Caminade", - "author_inst": "University of Liverpool" + "author_name": "Guillaume DE BONNECAZE", + "author_inst": "Service d ORL et de chirurgie cervico-faciale, Hopital Larrey, CHU Toulouse, France" }, { - "author_name": "Marcus SC Blagrove", - "author_inst": "University of Liverpool" + "author_name": "Bernard ESCUDE", + "author_inst": "Centre de Radiologie, Clinique Pasteur, Toulouse, France" }, { - "author_name": "Joanne Turner", - "author_inst": "University of Liverpool" + "author_name": "Clarisse LAFONT", + "author_inst": "Centre de Radiologie, Clinique du Mont-Louis, Paris, France" }, { - "author_name": "Kieran J Sharkey", - "author_inst": "University of Liverpool" + "author_name": "Gilles CHATELLIER", + "author_inst": "Department of Medical Informatics, Biostatistics and Public Health, AP-HP, Hopital Europeen Georges Pompidou, Paris, France - Universite de Paris, Faculte de Me" }, { - "author_name": "Matthew Baylis", - "author_inst": "University of Liverpool" + "author_name": "Mathieu MARX", + "author_inst": "Service d Otologie, Otoneurologie et ORL pediatrique, Hopital Pierre-Paul Riquet, CHU Toulouse Purpan - Service d ORL et de chirurgie cervico-faciale, Hopital L" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "neurology" }, { "rel_doi": "10.1101/2020.07.16.205799", @@ -1296232,29 +1296705,29 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2020.07.15.20154997", - "rel_title": "Associations between Demographic Characteristics, Perceived Threat, Perceived Stress, Coping Responses and Adherence to COVID-19 Prevention Measures among Healthcare Students in China: A Cross-Sectional Survey with Implications for the Control of COVID-19", + "rel_doi": "10.1101/2020.07.16.20155036", + "rel_title": "Are the upper bounds for new SARS-CoV-2 infections in Germany useful?", "rel_date": "2020-07-16", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.15.20154997", - "rel_abs": "ObjectivesTo investigate the associations between demographic characteristics, perceived threat, perceived stress, coping responses and adherence to COVID-19 prevention measures in Chinese Healthcare students.\n\nDesignA cross-sectional survey collecting data in Hong Kong and Fujian Province of China. Self-administered questionnaires were collected via online platform in April 2020.\n\nParticipantsA convenience and snowball sample of 2706 students aged 18 years or older and studying a healthcare programme in Hong Kong or Fujian.\n\nSettingStudents were recruited in tertiary education institutions/universities in Hong Kong and Putian (a prefecture-level city in eastern Fujian province). The institutions offered various healthcare programmes in degree or sub-degree levels.\n\nMain outcome measuresCompliances to social distancing and personal hygiene measures were assessed by 10-item Social Distancing Scale and 5-item Personal Hygiene Scale respectively. Path analysis was performed to identify factors associated with the compliance outcomes.\n\nResultsThe participants reported high compliances to both social distancing and personal hygiene measures. Confidence to manage the current situation, wishful thinking and empathetic responding directly predicted compliance to social distancing ({beta}=-0.31, p<0.001; {beta}=0.35, p=0.015; {beta}=0.33, p<0.001 respectively) and personal hygiene measures ({beta}==-0.16, p<0.001; {beta}=0.21, p<0.001; {beta}=0.16, p<0.001 respectively). Gender, geographical location, and clinical experience were the only three demographic variables having direct and/or indirect effects on social distancing and personal hygiene measures. The final model constructed demonstrated a very good fit to the data (Chi-square X2=27.27, df=17, P=0.044; X2/df=1.61; GFI=0.998, CFI=0.997, TLI=0.992, RMSEA=0.015).\n\nConclusionsThe predictive model constructed in this study is the first one to explore factors associating with the compliance to infection control measures in healthcare students amid the COVID-19 outbreak. The findings suggest that students who are male, habituate in Hong Kong, have more clinical experience and weak confidence to manage the threat tend to have lower compliance to social distancing and personal hygiene measures. Wishful thinking, contrasting to previous studies, was first found to positively associate with adherence to COVID-19 control measures.", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.16.20155036", + "rel_abs": "At the end of 2019, an outbreak of a new coronavirus, called SARS-CoV-2, was reported in China and later in other parts of the world. First infections were reported in Germany by the end of January and on March 16th the federal government announced a partial lockdown in order to mitigate the spread. Since the dynamics of new infections started to slow down, German states started to relax the confinement measures as to the beginning of May. As a fall back option, a limit of 50 new infections per 100,000 inhabitants within seven days was introduced for each city or district in Germany. If a district exceeds this limit, measures to control the spread of the virus should be taken. Based on a multi- patch SEAIRD-type model, we will simulate the effect of choosing a specific upper limit for new infections. We investigate, whether the politically motivated bound is low enough to detect new outbreaks at an early stage. Subsequently, we introduce an optimal control problem to tackle the multi-criteria problem of finding a bound for new infections that is low enough to avoid new outbreaks, which might lead to an overload of the health care system, but is large enough to curb the expected economic losses.", "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Anson Chui Yan Tang", - "author_inst": "Tung Wah College" + "author_name": "Wolfgang Bock", + "author_inst": "Technische Universitaet Kaiserslautern" }, { - "author_name": "Enid Wai Yung Kwong", - "author_inst": "Putian College" + "author_name": "Thomas Goetz", + "author_inst": "University Koblenz" }, { - "author_name": "Liangying Chen", - "author_inst": "Putian College" + "author_name": "Yashika Jayathunga", + "author_inst": "University Koblenz" }, { - "author_name": "Winnie Lai Sheung Cheng", - "author_inst": "Tung Wah College" + "author_name": "Robert Rockenfeller", + "author_inst": "University Koblenz" } ], "version": "1", @@ -1297762,51 +1298235,63 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.07.15.20154047", - "rel_title": "Early Improvement of Acute Respiratory Distress Syndrome in Patients with COVID-19: Insights from the Data of ICU Patients in Chongqing, China", + "rel_doi": "10.1101/2020.07.14.20153734", + "rel_title": "Place and causes of acute cardiovascular mortality during the COVID19 pandemic: retrospective cohort study of 580,972 deaths in England and Wales, 2014 to 2020", "rel_date": "2020-07-16", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.15.20154047", - "rel_abs": "Acute respiratory distress syndrome (ARDS) may be the main cause of death in patients with coronavirus disease 2019 (COVID-19). Herein, we retrospect clinical features, outcomes and ARDS characteristics of 75 intensive care unit (ICU) patients with COVID-19 in Chongqing, China. We found a 5.3% case fatality rate of the ICU patients in Chongqing. 93% patients developed ARDS during the intensive care, and more than half were moderate. However, most of the patients (55%) supported with high flow nasal cannula (HFNC) oxygen therapy, but not mechanical ventilation. Nearly one third of patients with ARDS got an early improvement (eiARDS), and the rate is much higher than the other causes of ARDS in a previous study. Patients with eiARDS had a higher survival rate and lower length of ICU stay. The age (< 55 years) is an independent predictor for the eiARDS, and stratification of COVID-19 patients by age is recommended.", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.14.20153734", + "rel_abs": "ImportanceThe COVID-19 pandemic has resulted in a decline in admissions with cardiovascular (CV) emergencies. The fatal consequences of this are unknown.\n\nObjectivesTo describe the place and causes of acute CV death during the COVID-19 pandemic.\n\nDesignRetrospective nationwide cohort.\n\nSettingEngland and Wales.\n\nParticipantsAll adult (age [≥]18 years) acute CV deaths (n=580,972) between 1st January 2014 and 2nd June 2020.\n\nExposureThe COVID-19 pandemic (defined as from the onset of the first COVID-19 death in England on 2nd March 2020).\n\nMain outcomesPlace (hospital, care home, home) and acute CV events directly contributing to death as stated on the first part of the Medical Certificate of Cause of Death.\n\nResultsAfter 2nd March 2020, there were 22,820 acute CV deaths of which 5.7% related to COVID-19, and an excess acute CV mortality of 1752 (+8%) compared with the expected daily deaths in the same period. Deaths in the community accounted for nearly half of all deaths during this period. Care homes had the greatest increase in excess acute CV deaths (1065, +40%), followed by deaths at home (1728, +34%) and in hospital (57, +0%). The most frequent cause of acute CV death during this period was stroke (8,290, 36.3%), followed by acute coronary syndrome (ACS) (5,532, 24.2%), heart failure (5,280, 23.1%), pulmonary embolism (2,067, 9.1%) and cardiac arrest (1,037, 4.5%). Deep vein thrombosis had the greatest increase in cause of excess acute CV death (18, +25%), followed pulmonary embolism (340, +19%) and stroke (782, +10%). The greatest cause of excess CV death in care homes was stroke (700, +48%), compared with cardiac arrest (80, +56%) at home, and pulmonary embolism (126, +14%) and cardiogenic shock (41, +14%) in hospital.\n\nConclusions and relevanceThe COVID-19 pandemic has resulted in an inflation in acute CV deaths above that expected for the time of year, nearly half of which occurred in the community. The most common cause of acute CV death was stroke followed by acute coronary syndrome and heart failure. This is key information to optimise messaging to the public and enable health resource planning.", + "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Zhu Zhan", - "author_inst": "The Second Affiliated Hospital of Chongqing Medical University" + "author_name": "Jianhua Wu", + "author_inst": "University of Leeds" }, { - "author_name": "Xin Yang", - "author_inst": "The First Affiliated Hospital of Chongqing Medical University" + "author_name": "Mamas Mamas", + "author_inst": "Keele University" }, { - "author_name": "Hu Du", - "author_inst": "The Second Affiliated Hospital of Chongqing Medical University" + "author_name": "Mohamed Mohamed", + "author_inst": "Keele University" }, { - "author_name": "Chuanlai Zhang", - "author_inst": "The Second Affiliated Hospital of Chongqing Medical University" + "author_name": "Chun Shing Kwok", + "author_inst": "Keele University" }, { - "author_name": "Yuyan Song", - "author_inst": "Chongqing public health medical center" + "author_name": "Chris Roebuck", + "author_inst": "NHS Digital" }, { - "author_name": "Xiaoyun Ran", - "author_inst": "The Second Affiliated Hospital of Chongqing Medical University" + "author_name": "Ben Humberstone", + "author_inst": "ONS" }, { - "author_name": "An Zhang", - "author_inst": "The Second Affiliated Hospital of Chongqing Medical University" + "author_name": "Tom Denwood", + "author_inst": "NHS Digital" }, { - "author_name": "Mei Yang", - "author_inst": "Chongqing Sixth People's Hospital" + "author_name": "Tom Luescher", + "author_inst": "Imperial College" + }, + { + "author_name": "Mark De Belder", + "author_inst": "Barts Health NHS Trust" + }, + { + "author_name": "John Deanfield", + "author_inst": "UCL" + }, + { + "author_name": "Chris Gale", + "author_inst": "University of Leeds" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "intensive care and critical care medicine" + "category": "cardiovascular medicine" }, { "rel_doi": "10.1101/2020.07.14.20153858", @@ -1299316,81 +1299801,25 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.07.13.20153171", - "rel_title": "Connecting in COVID 19: Neurology tele-follow-up experience", + "rel_doi": "10.1101/2020.07.13.20152959", + "rel_title": "Dissemination and co-circulation of SARS-CoV2 subclades exhibiting enhanced transmission associated with increased mortality in Western Europe and the United States", "rel_date": "2020-07-15", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.13.20153171", - "rel_abs": "IntroductionThe lockdown due to COVID-19 pandemic led to temporary closure of routine hospital services. This prompted the initiation of teleconsult follow-up in our department. The study outlines the experience of tele-follow-up at a tertiary care teaching hospital in India, and the perspective of neurologists about this novel approach.\n\nMethodsThe tele-follow-up was started from 26th March 2020. Data of follow up appointments was provided by the medical record section. The faculty and senior residents conducted the tele-follow-up. Communication was made via voice calls. The data for initial ten days was analyzed to find the utility and experience of the new service.\n\nResultsIn the initial ten working days, data of 968 patients was provided for tele-follow-up. A successful communication was made in 50.3% patients (contact with patients: 27.7% and family members 22.6%). The phone numbers which were not contactable/invalid/not available constituted 36.8% of the data. A total of 35 faculty and residents conducted the tele-follow-up. The utility of tele-follow-up was perceived as good by 71.4% of neurologists. Majority of neurologists (71.4%) observed that >90% of patients were continuing medications. Patients outside the city constituted 50-75% of the list. The survey revealed that all neurologists felt the need to continue tele-follow-up for far off stable patients post lock down and resumption of regular outpatient services.\n\nConclusionThe survey established the feasibility and utility of teleconsult for follow up of patients with neurological diseases who were attending the regular outpatient services before the lock down.", - "rel_num_authors": 16, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.13.20152959", + "rel_abs": "Mechanisms underlying the acute respiratory distress syndrome (ARDS)-like clinical manifestations leading to deaths in patients who develop COVID-19 remain uncharacterized. While multiple factors could influence these clinical outcomes, we explored if differences in transmissibility and pathogenicity of SARS-CoV2 variants could contribute to these terminal clinical consequences of COVID-19. We analyzed 34,412 SARS-CoV2 sequences deposited in the Global Initiative for Sharing All Influenza Data (GISAID) SARS-CoV2 sequence database to determine if regional differences in circulating strain variants correlated with increased mortality in Europe, the United States, and California. We found two subclades descending from the Wuhan HU-1 strain that rapidly became dominant in Western Europe and the United States. These variants contained nonsynonymous nucleotide mutations in the Orf1ab segment encoding RNA-dependent RNA polymerase (C14408T), the spike protein gene (A23403G), and Orf1a (G25563T), which resulted in non-conservative amino acid substitutions P323L, D614G, and Q57H, respectively. In Western Europe, the A23403G-C14408T subclade dominated, while in the US, the A23403G-C14408T-G25563T mutant became the dominant strain in New York and parts of California. The high cumulative frequencies of both subclades showed inconsistent but significant association with high cumulative CFRs in some of the regions. When the frequencies of the subclades were analyzed by their 7-day moving averages across each epidemic, we found co-circulation of both subclades to temporally correlate with peak mortality periods. We postulate that in areas with high numbers of these co-circulating subclades, a person may get serially infected. The second infection may trigger a hyperinflammatory response similar to the antibody-dependent enhancement (ADE) response, which could explain the ARDS-like manifestations observed in people with co-morbidity, who may not mount sufficient levels of neutralizing antibodies against the first infection. Further studies are necessary but the implication of such a mechanism will need to be considered for all current COVID-19 vaccine designs.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Deepti Vibha", - "author_inst": "All India Institute of Medical Sciences, New Delhi, India" - }, - { - "author_name": "MV Padma Srivastava", - "author_inst": "All India Institute of Medical Sciences, New Delhi, India" - }, - { - "author_name": "Kameshwar Prasad", - "author_inst": "All India Institute of Medical Sciences, New Delhi, India" - }, - { - "author_name": "Manjari Tripathi", - "author_inst": "All India Institute of Medical Sciences, New Delhi, India" - }, - { - "author_name": "Achal Kumar Srivastava", - "author_inst": "All India Institute of Medical Sciences, New Delhi, India" - }, - { - "author_name": "Rohit Bhatia", - "author_inst": "All India Institute of Medical Sciences, New Delhi, India" - }, - { - "author_name": "Mamta Bhushan Singh", - "author_inst": "All India Institute of Medical Sciences, New Delhi, India" - }, - { - "author_name": "Vishnu VY", - "author_inst": "All India Institute of Medical Sciences, New Delhi, India" - }, - { - "author_name": "Roopa Rajan", - "author_inst": "All India Institute of Medical Sciences, New Delhi, India" - }, - { - "author_name": "Rajesh Kumar Singh", - "author_inst": "All India Institute of Medical Sciences, New Delhi, India" - }, - { - "author_name": "Anu Gupta", - "author_inst": "All India Institute of Medical Sciences, New Delhi, India" - }, - { - "author_name": "Animesh Das", - "author_inst": "All India Institute of Medical Sciences, New Delhi, India" - }, - { - "author_name": "Elavarsi A", - "author_inst": "All India Institute of Medical Sciences, New Delhi, India" - }, - { - "author_name": "Divya MR", - "author_inst": "All India Institute of Medical Sciences, New Delhi, India" - }, - { - "author_name": "Bhargavi Ramanujam", - "author_inst": "All India Institute of Medical Sciences, New Delhi, India" + "author_name": "Yuan Hu", + "author_inst": "University of California, Berkeley" }, { - "author_name": "Ahmadullah Shariff", - "author_inst": "All India Institute of Medical Sciences, New Delhi, India" + "author_name": "Lee W Riley", + "author_inst": "University of California, Berkeley" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1301026,125 +1301455,61 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.07.13.20153106", - "rel_title": "The prevalence of antibodies to SARS-CoV-2 among blood donors in China", + "rel_doi": "10.1101/2020.07.13.20152447", + "rel_title": "O Group is a protective factor for COVID19 in Basque population", "rel_date": "2020-07-14", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.13.20153106", - "rel_abs": "ObjectivesThe prevalence of antibodies to SARS-CoV-2 among blood donors in China remains unknown. To reveal the missing information, we investigated the seroprevalence of SARS-CoV-2 antibodies among blood donors in the cities of Wuhan, Shenzhen, and Shijiazhuang of China.\n\nDesignCross-sectional study\n\nSettingThree blood centers, located in the central, south and north China, respectively, recruiting from January to April 2020.\n\nParticipants38,144 healthy blood donors donated in Wuhan, Shenzhen and Shijiazhuang were enrolled, who were all met the criteria for blood donation during the COVID-19 pandemic in China.\n\nMain outcome measuresSpecific antibodies against SARS-CoV-2 including total antibody (TAb), IgG antibody against receptor-binding domain of spike protein (IgG-RBD) and nucleoprotein (IgG-N), and IgM. Pseudotype lentivirus-based neutralization test was performed on all TAb-positive samples. In addition, anonymous personal demographic information, including gender, age, ethnicity, occupation and educational level, and blood type were collected.\n\nResultsA total of 519 samples from 410 donors were confirmed by neutralization tests. The SARS-CoV-2 seroprevalence among blood donors was 2.29% (407/17,794, 95%CI: 2.08% to 2.52%) in Wuhan, 0.029% (2/6,810, 95%CI: 0.0081% to 0.11%) in Shenzhen, and 0.0074% (1/13,540, 95%CI: 0.0013% to 0.042%) in Shijiazhuang, respectively. The earliest emergence of SARS-CoV-2 seropositivity in blood donors was identified on January 20, 2020 in Wuhan. The weekly prevalence of SARS-CoV-2 antibodies in Wuhans blood donors changed dynamically and were 0.08% (95%CI: 0.02% to 0.28%) during January 15 to 22 (before city lockdown), 3.08% (95%CI: 2.67% to 3.55%) during January 23 to April 7 (city quarantine period) and 2.33% (95%CI: 2.06% to 2.63%) during April 8 to 30 (after lockdown easing). Female and older-age were identified to be independent risk factors for SARS-CoV-2 seropositivity among donors in Wuhan.\n\nConclusionsThe prevalence of antibodies to SARS-CoV-2 among blood donors in China was low, even in Wuhan city. According to our data, the earliest emergence of SARS-CoV-2 in Wuhans donors should not earlier than January, 2020. As most of the population of China remained uninfected during the early wave of COVID-19 pandemic, effective public health measures are still certainly required to block viral spread before a vaccine is widely available.", - "rel_num_authors": 27, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.13.20152447", + "rel_abs": "ABO blood groups have been related to COVID19 infection. ABO blood groups are slightly differently distributed in the populations and therefore these results should be replicated in the specific areas with a proper control population. In this work, we present data from 412 COVID19 patients and 17796 blood donors from Gipuzkoa, a region in Northern Spain. Our data shows the importance of group O as a protective factor.", + "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Le Chang", - "author_inst": "National Center for Clinical Laboratories, Beijing Hospital" - }, - { - "author_name": "Wanghen Hou", - "author_inst": "School of Public Health, Xiamen University" - }, - { - "author_name": "Lei Zhao", - "author_inst": "Department of Laboratory, Wuhan Blood Center" + "author_name": "Maider Munoz-Culla", + "author_inst": "Multiple Sclerosis Unit, Biodonostia Health Research Institute" }, { - "author_name": "Yali Zhang", - "author_inst": "School of Public Health, Xiamen University" + "author_name": "Andres Roncancio-Clavijo", + "author_inst": "Immunology Department, Hospital Universitario Donostia." }, { - "author_name": "Yanbin Wang", - "author_inst": "Blood Screenning Laboratory, Hebei Province Blood Center" + "author_name": "Bruno Martinez", + "author_inst": "UGC Laboratories Gipuzkoa, Osakidetza" }, { - "author_name": "Linfeng Wu", - "author_inst": "Shenzhen Blood Center" + "author_name": "Miriam Gorostidi", + "author_inst": "Multiple Sclerosis Unit, Biodonostia Health Research Institute." }, { - "author_name": "Tingting Xu", - "author_inst": "Department of Laboratory, Wuhan Blood Center" + "author_name": "Luis D Pineiro", + "author_inst": "Microbiology Department, Hospital Universitario Donostia." }, { - "author_name": "Lilin Wang", - "author_inst": "Shenzhen Blood Center" + "author_name": "Arkaitz Azcune", + "author_inst": "Infectious disease Department, Hospital Universitario Donostia" }, { - "author_name": "Juan Wang", - "author_inst": "School of Public Health, Xiamen University" + "author_name": "Ainhoa Alberro", + "author_inst": "Multiple Sclerosis Unit, Biodonostia Health Research Institute" }, { - "author_name": "Jian Ma", - "author_inst": "School of Public Health, Xiamen University" + "author_name": "Jorge Monge-Ruiz", + "author_inst": "Osakidetza, Basque Center for Blood Transfusion and Human Tissues, Galdakao" }, { - "author_name": "Lan Wang", - "author_inst": "Wuhan Blood Center" + "author_name": "Tamara Castillo-Trivino", + "author_inst": "Multiple Sclerosis Unit, Biodonostia Health Research Institute" }, { - "author_name": "Junpeng Zhao", - "author_inst": "Shenzhen Blood Center" - }, - { - "author_name": "Jing Xu", - "author_inst": "Wuhan Blood Center" - }, - { - "author_name": "Juan Dong", - "author_inst": "Department of Laboratory, Wuhan Blood Center" - }, - { - "author_name": "Ying Yan", - "author_inst": "National Center for Clinical Laboratories, Beijing Hospital" - }, - { - "author_name": "Ru Yang", - "author_inst": "Department of Transfusion Research, Wuhan Blood Center" - }, - { - "author_name": "Yu Li", - "author_inst": "Department of Laboratory, Wuhan Blood Center" - }, - { - "author_name": "Fei Guo", - "author_inst": "National Center for Clinical Laboratories, Beijing Hospital" - }, - { - "author_name": "Wenjuan Cheng", - "author_inst": "Department of Laboratory, Wuhan Blood Center" - }, - { - "author_name": "Yingying Su", - "author_inst": "School of Public Health, Xiamen University" - }, - { - "author_name": "Jinfeng Zeng", - "author_inst": "Shenzhen Blood Center" - }, - { - "author_name": "Wei Han", - "author_inst": "Blood Screenning Laboratory, Hebei Province Blood Center" - }, - { - "author_name": "Tong Cheng", - "author_inst": "School of Public Health, Xiamen University" - }, - { - "author_name": "Jun Zhang", - "author_inst": "School of Public Health, Xiamen University" - }, - { - "author_name": "Quan Yuan", - "author_inst": "School of Public Health, Xiamen University" - }, - { - "author_name": "Xia Ningshao", - "author_inst": "School of Public Health, Xiamen University" + "author_name": "Alvaro Prada", + "author_inst": "Immunology Department, Hospital Universitario Donostia" }, { - "author_name": "Lunan Wang", - "author_inst": "National Center for Clinical Laboratories, Beijing Hospital" + "author_name": "David Otaegui", + "author_inst": "Multiple Sclerosis Unit, Biodonostia Health Research Institute" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1302696,27 +1303061,59 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.07.11.20151217", - "rel_title": "Impact of COVID-19 Second Wave on Healthcare Networks in the United States", + "rel_doi": "10.1101/2020.07.11.20151464", + "rel_title": "Multidisciplinary approach to COVID-19 risk communication: A framework and tool for individual and regional risk assessment", "rel_date": "2020-07-14", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.11.20151217", - "rel_abs": "The risk of overwhelming healthcare systems from a second wave of COVID-19 is yet to be quantified. Here, we investigate the impact of different reopening scenarios of states around the U.S. on COVID-19 hospitalized cases and the risk of overwhelming the healthcare system while considering resources at the county level. We show that the second wave might involve an unprecedented impact on the healthcare system if an increasing number of the population becomes susceptible and/or if the various protective measures are discontinued. Furthermore, we explore the ability of different mitigation strategies in providing considerable relief to the healthcare system. The results can aid healthcare planners, policymakers, and state officials in making decisions on additional resources required and on when to return to normalcy.\n\nOne Sentence SummaryA second wave of COVID-19 will have an unprecedented impact on the healthcare system.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.11.20151464", + "rel_abs": "The COVID-19 pandemic has exceeded over ten million cases globallywith no vaccine available yet. Different approaches are followed to mitigate its impact and reduce its spreading in different countries, but limiting mobility and exposure have been de-facto precaution to reduce transmission. However, a full lockdown cannot be sustained for a prolonged period. Evidence-based, multidisciplinary approach on risk zoning, personal and transmission risk assessment on a near real-time, and risk communication would support the optimized decisions to minimize the impact of coronavirus on our lives. This paper presents a framework to assess the individual and regional risk of COVID-19 along with risk communication tools and mechanisms. Relative risk scores on a scale of 100 represent the integrated risk of influential factors. The personal risk model incorporates: age, exposure history, symptoms, local risk and existing health condition, whereas regional risk is computed through the actual cases of COVID-19, public health risk factors, socioeconomic condition of the region, and immigration statistics. A web application tool (www.covira.info) has been developed, where anyone can assess their risk and find the guided information links primarily for Nepal. This study provides regional risk for Nepal, but the framework is scalable across the world. However, personal risk can be assessed immediately from anywhere.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Emad M. Hassan", - "author_inst": "Colorado State University" + "author_name": "Rishi Ram Parajuli", + "author_inst": "University of Bristol" }, { - "author_name": "Hussam Mahmoud", - "author_inst": "Colorado State University" + "author_name": "Bhogendra Mishra", + "author_inst": "Science Hub, Nepal" + }, + { + "author_name": "Amrit Banstola", + "author_inst": "Centre for Academic Child Health, University of the West of England, UK" + }, + { + "author_name": "Bhoj Raj Ghimire", + "author_inst": "Nepal Open University, Nepal" + }, + { + "author_name": "Shobha Poudel", + "author_inst": "Science Hub, Nepal" + }, + { + "author_name": "Kusum Sharma", + "author_inst": "Science Hub, Nepal" + }, + { + "author_name": "Sameer Mani Dixit", + "author_inst": "Center for Molecular Dynamics Nepal, Nepal" + }, + { + "author_name": "Sunil Kumar Shah", + "author_inst": "Mid Yorkshire Hospitals NHS Trust, Leeds Teaching Hospital, UK" + }, + { + "author_name": "Padam Simkhada", + "author_inst": "School of Human and Health Sciences, University of Huddersfield, UK" + }, + { + "author_name": "Edwin van Teijlingen", + "author_inst": "Faculty of Health and Social Sciences, Bournemouth University, UK" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "public and global health" }, { "rel_doi": "10.1101/2020.07.11.20151035", @@ -1304418,47 +1304815,63 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2020.07.13.198630", - "rel_title": "Tobacco, but not nicotine and flavor-less electronic cigarettes, induces ACE2 and immune dysregulation", + "rel_doi": "10.1101/2020.07.12.199505", + "rel_title": "PT150 is a modulator of glucocorticoid and androgen receptors with antiviral activity against SARS-CoV-2.", "rel_date": "2020-07-13", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.07.13.198630", - "rel_abs": "COVID-19, caused by the virus SARS-CoV-2, has infected millions worldwide. This pandemic overlaps with the ongoing epidemics of cigarette smoking and electronic cigarette (e-cig) vaping, with over 1 billion smokers and vapers worldwide. However, there is scarce data relating COVID-19 risks and outcome with cigarette or e-cig use. In this study, we mined 3 independent RNA expression datasets from smokers and vapers to understand the potential relationship between vaping/smoking and the dysregulation of key genes and pathways related to COVID-19. We found that smoking, but not vaping, upregulates ACE2, the cellular receptor that SARS-CoV-2 requires for infection. Both smoking and use of nicotine and flavor-containing e-cig led to upregulations of pro-inflammatory cytokine production and expression of genes related to inflammasomes. Vaping flavor-less and nicotine-less e-cig, however, did not lead to significant cytokine dysregulation and inflammasome activation. Release of inflammasome products, such as IL-1B, and cytokine storms are hallmarks of COVID-19 infection, especially in severe cases. Therefore, our findings demonstrated that smoking or vaping, specifically use of flavored or nicotine-containing e-cigs, may critically exacerbate COVID-19-related inflammation or increase susceptibility to the disease. Further scientific and public health investigations should be undertaken to address these concerning links between COVID-19 and e-cig/smoking.", - "rel_num_authors": 7, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.07.12.199505", + "rel_abs": "PT150 is a clinical stage molecule, taken orally, with a strong safety profile having completed Phase 1 and Phase 2 clinical trials for its original use as an anti-depressant. It has an active IND for COVID-19. Antiviral activities have been found for PT150 and other members of its class in a variety of virus families; thus, it was now tested against SARS-CoV-2 in human bronchial epithelial lining cells and showed effective 90% inhibitory antiviral concentration (EC90) of 5.55 M. PT150 is a member of an extended platform of novel glucocorticoid receptor (GR) and androgen receptor (AR) binding molecules. In vivo, their predominant net effect is one of systemic glucocorticoid antagonism, but they also show direct downregulation of AR and minor GR agonism at the cellular level. We hypothesize that anti-SARS-CoV-2 activity depends in part on this AR downregulation through diminished TMPRSS2 expression and modulation of ACE2 activity. Given that hypercortisolemia is now suggested to be a significant co-factor for COVID-19 progression, we also postulate an additive role for its potent immunomodulatory effects through systemic antagonism of cortisol.", + "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Abby C. Lee", - "author_inst": "UC San Diego; VA San Diego Healthcare System" + "author_name": "Neil D. Theise", + "author_inst": "New York University Grossman School of Medicine" + }, + { + "author_name": "Anthony R. Arment", + "author_inst": "United States Air Force Academy, Colorado Springs CO USA." }, { - "author_name": "Jaideep Chakladar", - "author_inst": "UC San Diego; VA San Diego Healthcare System" + "author_name": "Dimple Chakravarty", + "author_inst": "Icahn School of Medicine at Mount Sinai, New York NY USA" }, { - "author_name": "Wei Tse Li", - "author_inst": "UC San Diego; VA San Diego Healthcare System" + "author_name": "John M. H. Gregg", + "author_inst": "Palisades Therapeutics/Pop Test Oncology LLC, Cliffside Park NJ USA" }, { - "author_name": "Chengyu Chen", - "author_inst": "UC San Diego; VA San Diego Healthcare System" + "author_name": "Ira M. Jacobson", + "author_inst": "New York University Grossman School of Medicine, New York NY USA" }, { - "author_name": "Eric Y. Chang", - "author_inst": "UC San Diego; VA San Diego Healthcare System" + "author_name": "Kie Hoon Jung", + "author_inst": "Department of Animal, Dairy, and Veterinary Sciences, Utah State University, Logan UT USA" }, { - "author_name": "Jessica Wang-Rodriguez", - "author_inst": "UC San Diego; VA San Diego Healthcare System" + "author_name": "Sujit S. Nair", + "author_inst": "Icahn School of Medicine at Mount Sinai, New York NY USA" }, { - "author_name": "Weg M. Ongkeko", - "author_inst": "UC San Diego; VA San Diego Healthcare System" + "author_name": "Ashutosh Tiwari", + "author_inst": "Icahn School of Medicine at Mount Sinai, New York NY USA" + }, + { + "author_name": "Archie W. Thurston Jr.", + "author_inst": "ADME Solutions, INc, San Diego CA USA." + }, + { + "author_name": "John Van Drie", + "author_inst": "Van Drie Research, N. Andover MA USA" + }, + { + "author_name": "Jonna B. Westover", + "author_inst": "Utah State University, Logan UT USA" } ], "version": "1", "license": "cc_no", "type": "new results", - "category": "immunology" + "category": "microbiology" }, { "rel_doi": "10.1101/2020.07.13.200188", @@ -1305780,25 +1306193,37 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.07.10.20150813", - "rel_title": "Societal heterogeneity contributes to complex dynamic patterns of the COVID-19 pandemics: insights from a novel Stochastic Heterogeneous Epidemic Model (SHEM)", + "rel_doi": "10.1101/2020.07.10.20151001", + "rel_title": "Estimating the Effect of Social Distancing Interventions on COVID-19 in the United States", "rel_date": "2020-07-11", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.10.20150813", - "rel_abs": "As of August 2020, it has become evident that regional infection curves of COVID-19 exhibit complex patterns which often differ from curves predicted by forecasting models. We hypothesized that this may be due to social heterogeneity not accounted for by regional models. Here we present a new Stochastic Heterogeneous Epidemic Model (SHEM) to investigate the role of heterogenous societal structure. SHEM is intended to be a general tool with which to explore scenarios and determine the expected consequences of various interventions. We represent a society by an arbitrary network of sub-populations that could represent social as well as geographical strata. We created several scenarios with large clusters of people with R0 of COVID-19 interacting with multiple smaller local clusters that have larger internal R0. We find that isolation or embedding of these vulnerable sub-clusters generate complex infection patterns which includes multiple peaks and growth periods, an extended plateau, a prolonged tail, or a delayed second wave of infection, which may or may not form due to stochasticity. We also show that local clusters can either be driving or driven forces in infection progression. Embedded vulnerable groups become hotspots that drive infection despite efforts of the main population to socially distance, while isolated areas suffer delayed but intense infection. Social heterogeneity is a key factor in the formation of complex infection curves. Vulnerable subgroups that cannot implement mitigation strategies can spread infection to socially distanced populations, defeating mitigations. This implies that mitigation of vulnerable groups is essential to control the epidemic.\n\nSignificance StatementWe developed a new multiscale Stochastic Heterogeneous Epidemic Model (SHEM) and demonstrated major roles for social heterogeneity and stochasticity in pandemic development. We simulated viral infection in a theoretical society where small communities that cannot socially distance link to large clusters representing urban populations. Depending on the model parameters, our simulations of COVID-19 infection generated a large variety of dynamic patterns, including multimodal growth periods observed now in the US and worldwide. Infection of small, vulnerable clusters of people defeated mitigation efforts by the main population. The importance of protecting vulnerable subgroups suggests policy implications. Our abstract model could be applied at multiple scales of human societal organization.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.10.20151001", + "rel_abs": "Since its global emergence in 2020, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused multiple epidemics in the United States. Because medical treatments for the virus are still emerging and a vaccine is not yet available, state and local governments have sought to limit its spread by enacting various social distancing interventions such as school closures and lockdown, but the effectiveness of these interventions is unknown. We applied an established, semi-mechanistic Bayesian hierarchical model of these interventions on SARS-CoV-2 spread in Europe to the United States. We estimated the effect of interventions across all states, contrasted the estimated reproduction number, Rt, for each state before and after lockdown, and contrasted predicted future fatalities with actual fatalities as a check on the models validity. Overall, school closures and lockdown are the only interventions modeled that have a reliable impact on Rt, and lockdown appears to have played a key role in reducing Rt below 1.0. We conclude that reversal of lockdown, without implementation of additional, equally effective interventions, will enable continued, sustained transmission of SARS-CoV-2 in the United States.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Alexander V Maltsev", - "author_inst": "National Institute on Aging, NIH" + "author_name": "Andrew M. Olney", + "author_inst": "University of Memphis" + }, + { + "author_name": "Jesse Smith", + "author_inst": "Innovate Memphis" + }, + { + "author_name": "Saunak Sen", + "author_inst": "University of Tennessee" }, { - "author_name": "Michael D Stern", - "author_inst": "National Institute on Aging, NIH" + "author_name": "Fridtjof Thomas", + "author_inst": "University of Tennessee" + }, + { + "author_name": "H. Juliette T. Unwin", + "author_inst": "Imperial College London" } ], "version": "1", - "license": "cc0", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1307446,59 +1307871,43 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.07.10.20147777", - "rel_title": "COVID-19 severity is predicted by earlier evidence of accelerated aging", + "rel_doi": "10.1101/2020.07.07.20146332", + "rel_title": "Clinical and epidemiological characteristics of children with SARS-CoV-2 infection: case series in Sinaloa", "rel_date": "2020-07-11", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.10.20147777", - "rel_abs": "With no known treatments or vaccine, COVID-19 presents a major threat, particularly to older adults, who account for the majority of severe illness and deaths. The age-related susceptibility is partly explained by increased comorbidities including dementia and type II diabetes [1]. While it is unclear why these diseases predispose risk, we hypothesize that increased biological age, rather than chronological age, may be driving disease-related trends in COVID-19 severity with age. To test this hypothesis, we applied our previously validated biological age measure (PhenoAge) [2] composed of chronological age and nine clinical chemistry biomarkers to data of 347,751 participants from a large community cohort in the United Kingdom (UK Biobank), recruited between 2006 and 2010. Other data included disease diagnoses (to 2017), mortality data (to 2020), and the UK national COVID-19 test results (to May 31, 2020) [3]. Accelerated aging 10-14 years prior to the start of the COVID-19 pandemic was associated with test positivity (OR=1.15 per 5-year acceleration, 95% CI: 1.08 to 1.21, p=3.2x10-6) and all-cause mortality with test-confirmed COVID-19 (OR=1.25, per 5-year acceleration, 95% CI: 1.09 to 1.44, p=0.002) after adjustment for demographics including current chronological age and pre-existing diseases or conditions. The corresponding areas under the curves were 0.669 and 0.803, respectively. Biological aging, as captured by PhenoAge, is a better predictor of COVID-19 severity than chronological age, and may inform risk stratification initiatives, while also elucidating possible underlying mechanisms, particularly those related to inflammaging.", - "rel_num_authors": 10, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.07.20146332", + "rel_abs": "BackgroundThe SARS-CoV-2 virus may affect both adults and children. Although the disease, named COVID-19, has a lower prevalence in infancy and has been described as mild, the clinical characteristics may vary and there is a possibility of complications.\n\nObjectivesTo describe the clinical and epidemiological characteristics of pediatric cases confirmed in the state of Sinaloa, Mexico, during the first three months of the pandemic, and of children admitted with COVID-19 to a secondary hospital.\n\nMethodsThis case series includes all patients with SARS-CoV-2 infection confirmed by PCR testing, identified in the state epidemiological surveillance system between March 1 and May 31, 2020. Confirmed patients admitted to the Sinaloa Pediatric Hospital (HPS) during the same dates are also described.\n\nResultsFifty one children with SARS-CoV-2 were included, 10 of the admitted to HPS. The median age was 10 years. The more frequent symptoms were fever (78%), cough (67%) and headache (57%). Most cases were mild or asymptomatic. Three patients with comorbidities died. Only 4 of 10 patients identified in HPS had been admitted with the diagnosis of possible COVID-19.\n\nConclusionsSARS-CoV-2 infection in children was mostly mild or asymptomatic, but with a wide range of clinical presentations.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Chia-Ling Kuo", - "author_inst": "University of Connecticu Health" - }, - { - "author_name": "Luke C Pilling", - "author_inst": "University of Exeter" - }, - { - "author_name": "Janice C Atkins", - "author_inst": "University of Exeter" - }, - { - "author_name": "Jane Masoli", - "author_inst": "University of Exeter" - }, - { - "author_name": "Joao Delgado", - "author_inst": "University of Exeter" + "author_name": "Giordano Perez Gaxiola", + "author_inst": "Sinaloa Pediatric Hospital" }, { - "author_name": "Christopher Tignanelli", - "author_inst": "University of Minnesota" + "author_name": "Rosalino Flores Rocha", + "author_inst": "Sinaloa Pediatric Hospital" }, { - "author_name": "George Kuchel", - "author_inst": "University of Connecticut" + "author_name": "Julio Cesar Valadez Vidarte", + "author_inst": "Sinaloa Pediatric Hospital" }, { - "author_name": "David Melzer", - "author_inst": "University of Exeter" + "author_name": "Melissa Hernandez Alcaraz", + "author_inst": "Sinaloa Pediatric Hospital - UAD" }, { - "author_name": "Kenneth B Beckman", - "author_inst": "University of Minnesota" + "author_name": "Gilberto Herrera Mendoza", + "author_inst": "Sinaloa Pediatric Hospital - UAS" }, { - "author_name": "Morgan Levine", - "author_inst": "Yale University" + "author_name": "Miguel Alejandro Del Real Lugo", + "author_inst": "Epidemiological Intelligence Unit. Servicios de Salud de Sinaloa" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "pediatrics" }, { "rel_doi": "10.1101/2020.07.10.20133801", @@ -1309276,103 +1309685,35 @@ "category": "obstetrics and gynecology" }, { - "rel_doi": "10.1101/2020.07.09.20149856", - "rel_title": "SARS-CoV-2 spread across the Colombian-Venezuelan border", + "rel_doi": "10.1101/2020.07.09.20149955", + "rel_title": "A Poorly Understood Disease? The Unequal Distribution of Excess Mortality Due to COVID-19 Across French Municipalities", "rel_date": "2020-07-10", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.09.20149856", - "rel_abs": "IntroductionVenezuela and Colombia both adopted measures of containment early in response to the COVID-19 pandemic. However, Venezuelas ongoing humanitarian crisis has decimated its health care system, and forced millions of Venezuelans to flee through its porous border with Colombia. The extensive shared border, and illegal cross-border transit through improvised trails between the two countries are major challenges for public health authorities. We report the first SARS-CoV-2 genomes from Venezuela, and present a snapshot of the SARS-CoV-2 epidemiologic landscape in the Colombian-Venezuelan border region.\n\nMethodsWe sequenced and assembled viral genomes from total RNA extracted from nasopharyngeal (NP) clinical specimens using a custom reference-based analysis pipeline. Three assemblies obtained were subjected to typing using the Phylogenetic Assignment of Named Global Outbreak LINeages Pangolin tool. A total of 376 publicly available SARS-CoV-2 genomes from South America were obtained from the GISAID database to perform comparative genomic analyses. Additionally, the Wuhan-1 strain was used as reference.\n\nResultsWe found that two of the SARS-CoV-2 genomes from Venezuela belonged to the B1 lineage, and the third to the B.1.13 lineage. We observed a point mutation in the Spike protein gene (D614G substitution), previously reported to be associated with increased infectivity, in all three Venezuelan genomes. An additional three mutations (R203K/G204R substitution) were present in the nucleocapsid (N) gene of one Venezuelan genome.\n\nConclusionsGenomic sequencing demonstrates similarity between SARS-CoV-2 lineages from Venezuela and viruses collected from patients in bordering areas in Colombia and from Brazil, consistent with cross-border transit despite administrative measures including lockdowns. The presence of mutations associated with increased infectivity in the 3 Venezuelan genomes we report and Colombian SARS-CoV-2 genomes from neighboring borders areas may pose additional challenges for control of SARS-CoV-2 spread in the complex epidemiological landscape in Latin American countries. Public health authorities should carefully follow the progress of the pandemic and its impact on displaced populations within the region.", - "rel_num_authors": 21, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.09.20149955", + "rel_abs": "While COVID-19 was already responsible for more than 500,000 deaths worldwide as of July 3, 2020, very little is known on the socio-economic heterogeneity of its impact on mortality. In this paper, we combine several administrative data sources to estimate the relationship between mortality due to COVID-19 and poverty at a very local level (i.e. the municipality level) in France, one of the most severely hit country in the world. We find strong evidence of an income gradient in the impact of the pandemic on mortality: it is twice as large in the poorest municipalities compared to other municipalities. We then show that both poor housing conditions and higher occupational exposure are likely mechanisms. Overall, these mechanisms accounts for up to 60% of the difference observed between rich and poor municipalities.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Alberto Paniz-Mondolfi", - "author_inst": "Icahn School of medicina at Mount Sinai" - }, - { - "author_name": "Marina Munoz", - "author_inst": "Universidad del Rosario" - }, - { - "author_name": "Carolina Florez", - "author_inst": "Instituto Nacional de Salud" - }, - { - "author_name": "Sergio Gomez", - "author_inst": "Instituto Nacional de Salud" - }, - { - "author_name": "Angelica Rico", - "author_inst": "Instituto Nacional de Salud" - }, - { - "author_name": "Lisseth Pardo", - "author_inst": "Instituto Nacional de Salud" - }, - { - "author_name": "Esther C Barros", - "author_inst": "Instituto Nacional de Salud" - }, - { - "author_name": "Carolina Hernandez", - "author_inst": "Universidad del Rosario" - }, - { - "author_name": "Lourdes Delgado", - "author_inst": "Universidad del Rosario" - }, - { - "author_name": "Jesus Jaimes", - "author_inst": "Universidad del Rosario" - }, - { - "author_name": "Luis Perez", - "author_inst": "Universidad del Rosario" - }, - { - "author_name": "Anibal Teheran", - "author_inst": "Fundacion Universitaria Juan N Corpas" - }, - { - "author_name": "Hala Alshammary", - "author_inst": "Icahn School of Medicine at Mount Sinai" - }, - { - "author_name": "Ajay Obla", - "author_inst": "Ichan School of Medicine at Mount Sinai" - }, - { - "author_name": "Zenab Khan", - "author_inst": "Icahn School of Medicine at Mount Sinai" - }, - { - "author_name": "Ana Gonzalez-Reiche", - "author_inst": "Icahn School of Medicina at Mount Sinai" - }, - { - "author_name": "Matthew Hernandez", - "author_inst": "Icahn School of Medicine at Mount Sinai" + "author_name": "Paul Brandily", + "author_inst": "Paris School of Economics" }, { - "author_name": "Emilia Sordillo", - "author_inst": "Icahn School of Medicine at Mount Sinai" + "author_name": "Clement Brebion", + "author_inst": "Centre d'Etudes de l'Emploi et du Travail" }, { - "author_name": "Viviana Simon", - "author_inst": "Icahn School of Medicine" + "author_name": "Simon Briole", + "author_inst": "Paris School of Economics & J-PAL Europe" }, { - "author_name": "Harm van Bakel", - "author_inst": "Icahn School of Medicine at Mount Sinai" - }, - { - "author_name": "Juan David Ramirez", - "author_inst": "Universidad del Rosario" + "author_name": "Laura Khoury", + "author_inst": "Norwegian School of Economics" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "genetic and genomic medicine" + "category": "health economics" }, { "rel_doi": "10.1101/2020.07.09.20149849", @@ -1311134,37 +1311475,53 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2020.07.07.20148551", - "rel_title": "Assessment of N95 and K95 respirator decontamination: fiber integrity, filtration efficiency, and dipole charge density.", + "rel_doi": "10.1101/2020.07.08.20141218", + "rel_title": "Diagnostic and prognostic value of hematological and immunological markers in COVID-19 infection: A meta-analysis of 6320 patients", "rel_date": "2020-07-09", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.07.20148551", - "rel_abs": "Personal protective equipment (PPE) including N95 respirators are critical for persons exposed to SARS-CoV-2. KN95 respirators and N95 decontamination protocols have been described as solutions to a lack of such PPE. However, there are a few materials science studies that characterize the charge distribution and physical changes accompanying disinfection treatments particularly heating. Here, we report the filtration efficiency, dipole charge density, and fiber integrity of pristine N95 and KN95 respirators before and after various decontamination methods. We found that the filter layer of N95 is 8-fold thicker than that of KN95, which explains its 10% higher filtration efficiency (97.03 %) versus KN95 (87.76 %) under pristines condition. After 60 minutes of 70 {degrees}C treatment, the filtration efficiency and dipole charge density of N95 became 97.16% and 12.48 C/m2, while those of KN95 were 83.64% and 1.48 C/m2; moreover, fit factor of N95 was 55 and that of KN95 was 2.7. In conclusion, the KN95 respirator is an inferior alternative of N95 respirator. In both systems, a loss of electrostatic charge does not directly correlate to a decrease in performance.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.08.20141218", + "rel_abs": "ObjectiveEvidence-based characterization of the diagnostic and prognostic value of the hematological and immunological markers related to the epidemic of Coronavirus Disease 2019 (COVID-19) is critical to understand the clinical course of the infection and to assess in development and validation of biomarkers.\n\nMethodsBased on systematic search in Web of Science, PubMed, Scopus, and Science Direct up to April 22, 2020, a total of 52 eligible articles with 6,320 laboratory-confirmed COVID-19 cohorts were included. Pairwise comparison between severe versus mild disease, Intensive Care Unit (ICU) versus general ward admission, and expired versus survivors were performed for 36 laboratory parameters. The pooled standardized mean difference (SMD) and 95% confidence intervals (CI) were calculated using the DerSimonian Laird method/random effects model and converted to Odds ratio (OR). The decision tree algorithm was employed to identify the key risk factor(s) attributed to severe COVID-19 disease.\n\nResultsCohorts with elevated levels of white blood cells (WBCs) (OR=1.75), neutrophil count (OR=2.62), D-dimer (OR=3.97), prolonged prothrombin time (PT) (OR=1.82), fibrinogen (OR=3.14), erythrocyte sedimentation rate (OR=1.60), procalcitonin (OR=4.76), IL-6 (OR=2.10), and IL-10 (OR=4.93) had higher odds of progression to severe phenotype. Decision tree model (sensitivity=100%, specificity=81%) showed the high performance of neutrophil count at a cut-off value of more than 3.74{square}x109/L for identifying patients at high risk of severe COVID{square}19. Likewise, ICU admission was associated with higher levels of WBCs (OR=5.21), neutrophils (OR=6.25), D-dimer (OR=4.19), and prolonged PT (OR=2.18). Patients with high IL-6 (OR=13.87), CRP (OR=7.09), D-dimer (OR=6.36), and neutrophils (OR=6.25) had the highest likelihood of mortality.\n\nConclusionsSeveral hematological and immunological markers, in particular neutrophilic count, could be helpful to be included within the routine panel for COVID-19 infection evaluation to ensure risk stratification and effective management.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Wonjun Yim", - "author_inst": "University of California Sandiego" + "author_name": "Rami M Elshazli", + "author_inst": "Horus University - Egypt" + }, + { + "author_name": "Eman Ali Toraih", + "author_inst": "Tulane Medical Center" + }, + { + "author_name": "Abdelaziz Elgaml", + "author_inst": "Mansoura University and Horus University - Egypt" + }, + { + "author_name": "Mohammed El-Mowafy", + "author_inst": "Mansoura University" + }, + { + "author_name": "Mohamed El-Mesery", + "author_inst": "Mansoura University" }, { - "author_name": "Diyi Cheng", - "author_inst": "University of California Sandiego" + "author_name": "Mohamed N Amin", + "author_inst": "Mansoura University" }, { - "author_name": "Shiv Patel", - "author_inst": "University of California Sandiego" + "author_name": "Mohammad H Hussein", + "author_inst": "Tulane University" }, { - "author_name": "Rui Kui", - "author_inst": "University of California Sandiego" + "author_name": "Mary T Killackey", + "author_inst": "Tulane University" }, { - "author_name": "Ying Shirley Meng", - "author_inst": "University of California Sandiego" + "author_name": "Manal S Fawzy", + "author_inst": "Suez Canal University" }, { - "author_name": "Jesse V. Jokerst", - "author_inst": "University of California Sandiego" + "author_name": "Emad Kandil", + "author_inst": "Tulane University" } ], "version": "1", @@ -1313415,23 +1313772,83 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.07.05.20145805", - "rel_title": "Optimally Pooled Viral Testing", + "rel_doi": "10.1101/2020.07.07.20147413", + "rel_title": "A national cross-sectional survey of public perceptions, knowledge, and behaviors during the COVID-19 pandemic", "rel_date": "2020-07-08", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.05.20145805", - "rel_abs": "It has long been known that pooling samples may be used to minimize the total number of tests required in order to identify each infected individual in a population. Pooling is most advantageous in populations with low infection (positivity) rates, but is expected to remain better than non-pooled testing in populations with infection rates up to 30%. For populations with infection rates lower than 10%, additional testing efficiency may be realized by performing a second round of pooling to test all the samples in the positive first-round pools. The present predictions are validated by recent COVID-19 (SARS-CoV-2) pooled testing and detection sensitivity measurements performed using non-optimal pool sizes, and quantify the additional improvement in testing efficiency that could have been obtained using optimal pooling. Although large pools are most advantageous for testing populations with very low infection rates, they are predicted to become highly non-optimal with increasing infection rate, while pool sizes smaller than 10 remain near-optimal over a broader range of infection rates.", - "rel_num_authors": 1, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.07.20147413", + "rel_abs": "IntroductionEfforts to mitigate the global spread of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have largely relied on broad compliance with public health recommendations yet navigating the high volume of evolving information and misinformation related to SARS-CoV-2 can be challenging. We assessed national public perceptions (e.g., severity, concerns, health), knowledge (e.g., transmission, information sources), and behaviors (e.g., physical distancing) related to COVID-19 in Canada to understand public perspectives and inform future public health initiatives.\n\nMethodsWe administered a national online survey with the goal of obtaining responses from 2000 adults residing in Canada. Respondent sampling was stratified by age, sex, and region. We used descriptive statistics to summarize respondent characteristics and tested for significant overall regional differences using chi-squared tests and t-tests, as appropriate.\n\nResultsWe collected 1,996 eligible questionnaires between April 26th and May 1st, 2020. One-fifth (20%) of respondents knew someone diagnosed with COVID-19, but few had tested positive themselves (0.6%). Negative impacts of pandemic conditions were evidenced in several areas, including concerns about healthcare (e.g. sufficient equipment, 52%), pandemic stress (45%), and worsening social (49%) and mental/emotional (39%) health. Most respondents (88%) felt they had good to excellent knowledge of virus transmission, and predominantly accessed (74%) and trusted (60%) Canadian news television, newspapers/magazines, or non-government news websites for COVID-19 information. We found high compliance with distancing measures (80% either self-isolating or always physical distancing). We identified regional differences in perceptions, knowledge, and behaviors related to COVID-19.\n\nDiscussionWe found that knowledge about COVID-19 is largely acquired through domestic news sources, which may explain high self-reported compliance with prevention measures. The results highlight the broader impact of a pandemic on the general publics overall health and wellbeing, outside of personal infection. The study findings should be used to inform public health communications during COVID-19 and future pandemics.", + "rel_num_authors": 16, "rel_authors": [ { - "author_name": "Dor Ben-Amotz", - "author_inst": "Purdue University" + "author_name": "Jeanna Parsons Leigh", + "author_inst": "Dalhousie University" + }, + { + "author_name": "Kirsten Fiest", + "author_inst": "University of Calgary" + }, + { + "author_name": "Rebecca Brundin-Mather", + "author_inst": "University of Calgary" + }, + { + "author_name": "Kara Plonikoff", + "author_inst": "University of Calgary" + }, + { + "author_name": "Andrea Soo", + "author_inst": "University of Calgary" + }, + { + "author_name": "Emma E. Sypes", + "author_inst": "University of Calgary" + }, + { + "author_name": "Liam Whalen-Browne", + "author_inst": "University of Calgary" + }, + { + "author_name": "Sofia B. Ahmed", + "author_inst": "University of Calgary" + }, + { + "author_name": "Karen E.A. Burns", + "author_inst": "University of Toronto" + }, + { + "author_name": "Alison Fox-Robichaud", + "author_inst": "McMaster University" + }, + { + "author_name": "Shelly Kupsch", + "author_inst": "University of Calgary" + }, + { + "author_name": "Shelly Longmore", + "author_inst": "University of Calgary" + }, + { + "author_name": "Srinivas Murthy", + "author_inst": "University of British Columbia" + }, + { + "author_name": "Daniel J. Niven", + "author_inst": "University of Calgary" + }, + { + "author_name": "Bram Rochwerg", + "author_inst": "McMaster University" + }, + { + "author_name": "Henry T. Stelfox", + "author_inst": "University of Calgary" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "public and global health" }, { "rel_doi": "10.1101/2020.07.06.20147181", @@ -1315249,59 +1315666,43 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.07.06.20147256", - "rel_title": "Early Diagnosis and Clinical Significance of Acute Cardiac Injury - Under the Iceberg: A Retrospective Cohort Study of 619 Non-critically Ill Hospitalized COVID-19 Pneumonia Patients", + "rel_doi": "10.1101/2020.07.06.20147124", + "rel_title": "Does sub-Saharan Africa truly defy the forecasts of the COVID-19 pandemic? Response from population data", "rel_date": "2020-07-07", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.06.20147256", - "rel_abs": "RationaleCoronavirus disease 2019 (COVID-19) can cause a viral pneumonia together with other extrapulmonary complications. Acute cardiac related injury (ACRI) is common in hospitalized COVID-19 patients.\n\nObjectiveTo explain the pathological mechanism of ACRI and improve the treatment strategy by retrospectively observing the factors associated with ACRI and factors affecting the prognosis of ACRI with COVID-19 at an early stage.\n\nMethods619 COVID-19 patients were from Tongji Hospital, Wuhan. Students t test was used for continuous variables while Pearson {chi}2 test for categorical factors. Univariable and multivariable logistic regression models were applied to estimate odds ratio (OR) with 95% confidence interval (CI).\n\nResultsAmong the 619 OOS Level-I hospitalized COVID-19 patients, 102 (16.5%) were defined as ACRI (stage-1: 59 cases, stage-2: 43 cases). 50% of ACRI patients developed into severe cases and 25 patients died(CFR=24.5%), 42 times that of non-ACRI patients. Elderly (OR=2.83, P<0.001), HTN (OR=2.09, P=0.005), {gamma}-globulin (OR=2.08, P=0.004), TCM (OR=0.55, P=0.017), PLT (OR=2.94, P<0.001) and NLR (OR=2.20, P=0.004) were independently correlated with ACRI. SBP [>=] 140, dyspnea, DM, smoking history were correlated with ACRI-stage2 only. In the prognostic subgroup analysis of ACRI patients, {gamma}-globulin treatment could prolong LOS (29.0 {+/-} 7.2 days Vs 23.5 {+/-} 8.1 days, P=0.004). TCM (OR=0.26, P=0.006), SBP [>=] 160 (OR= 22.70, P=0.005), male (OR=2.66, P=0.044) were associated with severe illness while corticosteroids treatment (OR=3.34, P=0.033) and male (OR=4.303, P=0.008) with death. Surprisingly, we found the mortality of non-elderly patients is higher than elderly (32.4% VS 20.0%, P=0.164), and both IKF and RASI treatment were not correlated with any prognostic indicators including severe, death and LOS.\n\nConclusionThis study observed that several non-traditional issues were associated with early cardiac injury in COVID-19 while many traditional cardiovascular risk factors were not. Besides elderly and male, hypertension was confirmed to be the most important risk factor.", - "rel_num_authors": 10, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.06.20147124", + "rel_abs": "IntroductionSince its identification, the COVID-19 infection has caused substantial mortality and morbidity worldwide, but sub-Saharan Africa seems to defy the predictions. We aimed to verify this hypothesis using strong statistical methods.\n\nMethodsWe conducted a cross-sectional study comparing the projected and actual numbers as well as population proportions of COVID-19 cases in the 46 sub-Saharan African countries on May 1st, May 29th (4 weeks later) and June 26th (8 weeks later). The source of the projected number of cases was a publication by scientists from the Center for Mathematical Modeling of Infectious Diseases of the London School of Hygiene & Tropical Medicine, whereas the actual number of cases was obtained from the WHO situation reports. We calculated the percentage difference between the projected and actual numbers of cases per country. Further, \"N-1\" chi-square tests with Bonferroni correction were used to compare the projected and actual population proportion of COVID-19 cases, along with the 95% confidence interval of the difference between these population proportions. All statistical tests were 2-sided, with 0.05 used as threshold for statistical significance.\n\nResultsOn May 1st, May 29th and June 26th, respectively 40 (86.95%), 45 (97.82%) and 41 (89.13%) of the sub-Saharan African countries reported a number of confirmed cases that was lower than the predicted number of 1000 cases for May 1st and 10000 for both May 29th and June 26th. At these dates, the population proportions of confirmed Covid-19 cases were significantly lower (p-value <0.05) than the projected proportions of cases. Across all these dates, South-Africa always exceeded the predicted number and population proportion of COVID-19 infections.\n\nConclusionSub-Saharan African countries did defy the dire predictions of the COVID-19 burden. Preventive measures should be further enforced to preserve this positive outcome.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Yang Xie", - "author_inst": "Department of Cardiovascular Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology" + "author_name": "Fokoua Maxime Christophe Dongmo", + "author_inst": "University of New York State - University at Albany School of Public Health" }, { - "author_name": "Sichun Chen", - "author_inst": "Medical Research Institute, Wuhan University Renmin Hospital, Wuhan University, Wuhan, China" + "author_name": "Amor Ndjabo Monique", + "author_inst": "School of Health Sciences, Catholic University of Central Africa, Yaounde, Cameroon" }, { - "author_name": "Xueli Wang", - "author_inst": "Institute of Central China Development, Wuhan University" + "author_name": "Ankobil Amandus", + "author_inst": "University of New York State - University at Albany School of Public Health, Albany, USA" }, { - "author_name": "Baige Li", - "author_inst": "Medical Research Institute, Wuhan University Renmin Hospital, Wuhan University, Wuhan, China" + "author_name": "Kiyung Victor Momah", + "author_inst": "School of Health Sciences, Catholic University of Central Africa, Yaounde, Cameroon" }, { - "author_name": "Tianlu Zhang", - "author_inst": "zhangtianlu99@163.com" - }, - { - "author_name": "Xingwei He", - "author_inst": "Department of Cardiovascular Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology" - }, - { - "author_name": "NingLing Sun", - "author_inst": "Department of Hypertension at Heart Center, People's Hospital, Peking University" - }, - { - "author_name": "Luyan Wang", - "author_inst": "Heart Center, Peking University Peoples Hospital" - }, - { - "author_name": "Hesong Zeng", - "author_inst": "Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology" + "author_name": "Metomb Franck Steve", + "author_inst": "Regional Delegation of Public Health for the Center Region, Ministry of Public Health, Yaounde, Cameroon" }, { - "author_name": "Yin Shen", - "author_inst": "Eye Center, Wuhan University Renmin Hospital, Wuhan University" + "author_name": "Choukem Simeon Pierre", + "author_inst": "Department of Internal Medicine and Specialties, Faculty of Medicine and Pharmaceutical Sciences, University of Dschang, Dschang, Cameroon" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "cardiovascular medicine" + "category": "epidemiology" }, { "rel_doi": "10.1101/2020.07.06.20147264", @@ -1316631,25 +1317032,25 @@ "category": "intensive care and critical care medicine" }, { - "rel_doi": "10.1101/2020.07.06.20147223", - "rel_title": "Predicting the second wave of COVID-19 in Washtenaw County, MI", + "rel_doi": "10.1101/2020.07.05.20146969", + "rel_title": "Partial Prediction of the Virus COVID-19 Spread in Russia Based on SIR and SEIR Models", "rel_date": "2020-07-07", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.06.20147223", - "rel_abs": "The COVID-19 pandemic has highlighted the patchwork nature of disease epidemics, with infection spread dynamics varying wildly across countries and across states within the US. These heterogeneous patterns are also observed within individual states, with patches of concentrated outbreaks. Data is being generated daily at all of these spatial scales, and answers to questions regarded reopening strategies are desperately needed. Mathematical modeling is useful in exactly these cases, and using modeling at a county scale may be valuable to further predict disease dynamics for the purposes of public health interventions. To explore this issue, we study and predict the spread of COVID-19 in Washtenaw County, MI, the home to University of Michigan, Eastern Michigan University, and Google, as well as serving as a sister city to Detroit, MI where there has been a serious outbreak. Here, we apply a discrete and stochastic network-based modeling framework allowing us to track every individual in the county. In this framework, we construct contact networks based on synthetic population datasets specific for Washtenaw County that are derived from US Census datasets. We assign individuals to households, workplaces, schools, and group quarters (such as prisons). In addition, we assign casual contacts to each individual at random. Using this framework, we explicitly simulate Michigan-specific government-mandated workplace and school closures as well as social distancing measures. We also perform sensitivity analyses to identify key model parameters and mechanisms contributing to the observed disease burden in the three months following the first observed cases on COVID-19 in Michigan. We then consider several scenarios for relaxing restrictions and reopening workplaces to predict what actions would be most prudent. In particular, we consider the effects of 1) different timings for reopening, and 2) different levels of workplace vs. casual contact re-engagement. Through simulations and sensitivity analyses, we explore mechanisms driving magnitude and timing of a second wave of infections upon re-opening. This model can be adapted to other US counties using synthetic population databases and data specific to those regions.", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.05.20146969", + "rel_abs": "The possibility to predict the spread of COVID-19 in Russia is studied. Particular goal is to predict the time instant when the number of infected achieves its maximum (peak). Such a partial prediction allows one to use simple epidemoics models: SIR and SEIR. Simplicity and small number of parameters are significant advantages of SIR and SEIR models under conditions of a lack of numerical initial data and structural incompleteness of models. The prediction is carried out according to public WHO datasets from March 10 to April 20, 2020. Comparison of forecast results by SIR and SEIR models are given. In both cases, the peak number of infected persons while maintaining the current level of quarantine measures is forecasted at the end of May 2020 or later. It coincides with the real data obtained in May-June, 2020. The results confirm usefulness of simple nonlinear dynamical models for partial prediction of complex epidemic processes.", "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Marissa Renardy", - "author_inst": "University of Michigan Medical School" + "author_name": "Dmitry Tomchin", + "author_inst": "Institute for Problems of Mechanical Engineering" }, { - "author_name": "Denise E. Kirschner", - "author_inst": "University of Michigan Medical School" + "author_name": "Alexander L. Fradkov", + "author_inst": "Saint Petersburg University" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1317885,27 +1318286,23 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2020.07.01.20136317", - "rel_title": "Who is dying from Covid-19 in the United Kingdom? A review of cremation authorisations from a single South Wales' crematorium.", + "rel_doi": "10.1101/2020.07.02.20145219", + "rel_title": "Computational fluid dynamic (CFD), air flow-droplet dispersion, and indoor CO2 analysis for healthy public space configuration to complywith COVID 19 protocol", "rel_date": "2020-07-06", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.01.20136317", - "rel_abs": "BackgroundCovid 19 is pandemic in the UK. To date only studies in the UK on hospital deaths have been published in the peer reviewed literature. Legal requirements for cremation in England and Wales require the collection of information that can be used to improve understanding of Covid 19 deaths in both hospital and community settings.\n\nAimTo document demographic and clinical characteristics, including likely place of infection, of individuals dying of Covid 19 to inform public health policy\n\nDesignA comprehensive case series of deaths from Covid 19 between 6 April and 30 May.\n\nSettingA crematorium in South Wales\n\nParticipantsIndividuals for whom an application was made for cremation.\n\nMain outcome measuresAge, sex, date and place of death, occupation, comorbidities, where infection acquired.\n\nResultsOf 752 cremations, 215(28.6%) were Covid-19 of which 115 (53.5%) were male and 100 (46.5%) female. The median age was 82 years, with the youngest patient being 47 years and the oldest 103 years. Over half the deaths (121/215: 56.3%) were over 80 years. Males odds of dying in hospital, rather than the community were 1.96 times that of females (95% Confidence Intervals (CI) 1.03 -3.74, p=0.054) despite being of similar age and having a similar number of comorbidities. Only 21(9.8%) of 215 patients had no comorbidities recorded. Patients dying in nursing homes were significantly older than those dying in hospital(median 88y (IQ range 82-93y) v 80y (IQ range 71-87y): p<0.0001). Patients dying in hospital had significantly more comorbidities than those dying in nursing homes (median 2: IQ range 1-3 v. 1: IQ range 1-2: p <0.001).\n\nConclusionsIn a representative series, comprising both hospital and community deaths, persons over 80 with an average 2 comorbidities predominated. Although men and women were represented in similar proportions, men were more likely to die in hospital. Over half the infections were acquired in either hospitals or nursing and residential homes with implications for the management of the pandemic, historically and in the future.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.02.20145219", + "rel_abs": "The droplet has a limited travel distance. Nonetheless, especially in the indoor public space the air flow can propagate the droplet to travel long distance. Based on this situation, this paper aims to study the relationships of seat configuration-social distance-air flow-droplet dispersions. The analysis was based on the computational fluid dynamic (CFD) using lattice-Boltzmann model (LBM). The result confirms that by modifying public space configuration in this case by providing more space and increasing seating distance can reduce the vulnerability towards droplet dispersions. Whereas, providing shield including adding protection is far more effective in avoiding dispersions. The public space reconfiguration including increasing seat distance and reducing seating capacity also has an effect in reducing the indoor CO2. Capacity reduction from full capacity to 30% can decrease the CO2 from 5722 to 2144 ppm.", + "rel_num_authors": 1, "rel_authors": [ { - "author_name": "Roland L. Salmon", - "author_inst": "Retired" - }, - { - "author_name": "Stephen P. Monaghan", - "author_inst": "Public Health Wales" + "author_name": "Andrio Adwibowo", + "author_inst": "University of Indonesia" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "occupational and environmental health" }, { "rel_doi": "10.1101/2020.07.04.20146530", @@ -1319275,29 +1319672,21 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.06.29.20143180", - "rel_title": "Safe contact tracing for COVID-19: A method without privacy breach using functional encryption techniques based-on spatio-temporal trajectory data", + "rel_doi": "10.1101/2020.07.02.20144840", + "rel_title": "The reproduction number R for COVID-19 in England: Why hasn't ''lockdown'' been more effective?", "rel_date": "2020-07-05", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.29.20143180", - "rel_abs": "The COVID-19 pandemic has spread all over the globe. In the absence of a vaccine, a small number of countries have managed to control the diffusion of viruses by early detection and early quarantine. South Korea, one of the countries which have kept the epidemics well-controlled, has opened the infected patients trajectory to the public. Such a reaction has been regarded as an effective method, however, serious privacy breach cases have been issued in South Korea. Furthermore, some suspected contacts have refused to take infection tests because they are afraid of being exposed. To solve this problem, we propose a privacy-preserving contact tracing method based on spatio-temporal trajectory which can be practically used in many quarantine systems. In addition, we develop a system to visualize the contact tracing workflow.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.02.20144840", + "rel_abs": "The reproduction number R, the average number of people that a single individual with a contagious disease infects, is central to understanding the dynamics of the COVID-19 epidemic. Values greater than one correspond to increasing rates of infection, and values less than one indicate that control measures are being effective. Here, we summarise how changes in the behaviour of individuals alter the value of R. We also use matrix models that correctly recreate distributions of times that individuals spend incubating the disease and being infective to demonstrate the accuracy of a simple approximation to estimate R directly from time series of case numbers, hospital admissions or deaths. The largest uncertainty is that the generation time of the infection is not precisely known, but this challenge also affects most of the more complex methods of calculating R. We use this approximation to examine changes in R in response to the introduction of \"lockdown\" restrictions in England. This suggests that there was a substantial reduction in R before large scale compulsory restrictions on economic and social activity were imposed on 23rd March 2020. From mid-April to mid-June decline of the epidemic at national and regional level has been relatively slow, despite these restrictions (R values clustered around 0.81). However, these estimates of R are consistent with the relatively high average numbers of close contacts reported by confirmed cases combined with directly measured attack rates via close interactions. This implies that a significant portion of transmission is occurring in workplaces; overcrowded housing or through close contacts that are not currently lawful, routes on which nationwide lockdown will have limited impact.", + "rel_num_authors": 1, "rel_authors": [ { - "author_name": "Wooil Kim", - "author_inst": "Korea University" - }, - { - "author_name": "Hyubjin Lee", - "author_inst": "Korea University" - }, - { - "author_name": "Yon Dohn Chung", - "author_inst": "Korea University" + "author_name": "Alastair Grant", + "author_inst": "University of East Anglia" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1320733,71 +1321122,63 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.07.03.20145722", - "rel_title": "Kinetics and performance of the Abbott Architect SARS-CoV-2 IgG antibody assay", + "rel_doi": "10.1101/2020.07.02.20145565", + "rel_title": "Efficacy of Corticosteroids in Non-Intensive Care Unit Patients with COVID-19 Pneumonia from the New York Metropolitan region", "rel_date": "2020-07-04", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.03.20145722", - "rel_abs": "ObjectivesTo assess the performance (sensitivity and specificity) of the Abbott Architect SARS-CoV-2 IgG antibody assay across three clinical settings.\n\nMethodsAntibody testing was performed on three clinical cohorts of COVID-19 disease: hospitalised patients with PCR confirmation, hospitalized patients with a clinical diagnosis but negative PCR, and symptomatic healthcare workers (HCWs). Pre-pandemic respiratory infection sera were tested as negative controls. The sensitivity of the assay was calculated at different time points (<5 days, 5-9 days, 10-14 days, 15-19 days, >20 days, >42 days), and compared between cohorts.\n\nResultsPerformance of the Abbot Architect SARS-CoV-2 assay varied significantly between cohorts. For PCR confirmed hospitalised patients (n = 114), early sensitivity was low: <5 days: 44.4% (95%CI: 18.9%-73.3%), 5-9 days: 32.6% (95%CI, 20.5%-47.5%), 10-14 days: 65.2% (95% CI 44.9%-81.2%), 15-20 days: 66.7% (95% CI: 39.1%-86.2%) but by day 20, sensitivity was 100% (95%CI, 86.2-100%).\n\nIn contrast, 17 out of 114 symptomatic healthcare workers tested at >20 days had negative results, generating a sensitivity of 85.1% (95%CI, 77.4% - 90.5%). All pre-pandemic sera were negative, a specificity of 100%. Seroconversion rates were similar for PCR positive and PCR negative hospitalised cases.\n\nConclusionsThe sensitivity of the Abbot Architect SARS-CoV-2 IgG assay increases over time, with sensitivity not peaking until 20 days post symptoms. Performance varied markedly by setting, with sensitivity significantly worse in symptomatic healthcare workers than in the hospitalised cohort. Clinicians, policymakers, and patients should be aware of the reduced sensitivity in this setting.", - "rel_num_authors": 13, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.02.20145565", + "rel_abs": "IntroductionThe role of systemic corticosteroid as a therapeutic agent for patients with COVID-19 pneumonia is controversial.\n\nObjectiveThe purpose of this study was to evaluate the effect of corticosteroids in non-intensive care unit (ICU) patients with COVID-19 pneumonia complicated by acute hypoxemic respiratory failure (AHRF).\n\nMethodsThis was a single-center retrospective cohort study, from the 16th March, 2020 to 30th April, 2020; final follow-up on 10th May, 2020. 265 patients consecutively admitted to the non-ICU wards with laboratory-confirmed COVID-19 pneumonia were screened for inclusion. 205 patients who developed AHRF (SpO2/FiO2 [≤] 440 or PaO2/FiO2 [≤] 300) were only included in the final study. Direct admission to the Intensive care unit (ICU), patients developing composite primary outcome within 24 hours of admission, and patients who never became hypoxic during their stay in the hospital were excluded. Patients divided into two cohort based on corticosteroid. The primary outcome was a composite of ICU transfer, intubation, or in-hospital mortality. Secondary outcomes were ICU transfer, intubation, in-hospital mortality, discharge, length of stay and daily trend of SpO2/FiO2 (SF) ratio from the index date. Cox-proportional hazard regression was implemented to analyze the time to event outcomes.\n\nResultAmong 205 patients, 60 (29.27%) were treated with corticosteroid. The mean age was [~]57 years, and [~]75% were men. Thirteen patients (22.41%) developed a primary composite outcome in the corticosteroid cohort vs. 54 (37.5%) patients in the non-corticosteroid cohort (P=0.039). The adjusted hazard ratio (HR) for the development of the composite primary outcome was 0.15 (95% CI, 0.07 - 0.33; P <0.001). The adjusted hazard ratio for ICU transfer was 0.16 (95% CI, 0.07 to 0.34; P < 0.001), intubation was 0.31 (95% CI, 0.14 to 0.70; P - 0.005), death was 0.53 (95% CI, 0.22 to 1.31; P - 0.172), and discharge was 3.65 (95% CI, 2.20 to 6.06; P<0.001). The corticosteroid cohort had increasing SpO2/FiO2 over time compared to the non-corticosteroid cohort who experience decreasing SpO2/FiO2 over time.\n\nConclusionAmong non-ICU patients hospitalized with COVID-19 pneumonia complicated by AHRF, treatment with corticosteroid was associated with a significantly lower risk of the primary composite outcome of ICU transfer, intubation, or in-hospital death.", + "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Fergus Hamilton", - "author_inst": "University of Bristol" - }, - { - "author_name": "Peter Muir", - "author_inst": "Public Health England" + "author_name": "Monil Majmundar", + "author_inst": "New York Medical College, Metropolitan Hospital" }, { - "author_name": "Marie Attwood", - "author_inst": "North Bristol NHS Trust" + "author_name": "Tikal Kansara", + "author_inst": "New York Medical College, Metropolitan Hospital" }, { - "author_name": "Alan Noel", - "author_inst": "North Bristol NHS Trust" + "author_name": "Joanna M Lenik", + "author_inst": "New York Medical College, Metropolitan Hospital" }, { - "author_name": "Barry Vipond", - "author_inst": "Public Heath England" + "author_name": "Hansang Park", + "author_inst": "New York Medical College, Metropolitan Hospital" }, { - "author_name": "Richard Hopes", - "author_inst": "Public Health England" + "author_name": "Kuldeep Ghosh", + "author_inst": "New York Medical College, Metropolitan Hospital" }, { - "author_name": "Ed Moran", - "author_inst": "North Bristol NHS Trust" + "author_name": "Rajkumar Doshi", + "author_inst": "University of Nevada, Reno School of Medicine" }, { - "author_name": "Nick Maskell", - "author_inst": "University of Bristol" + "author_name": "Palak Shah", + "author_inst": "SBKS Medical College and Research Institute, Dhiraj General Hospital, Vadodara, Gujarat, India" }, { - "author_name": "Deborah Warwick", - "author_inst": "North Bristol NHS Trust" + "author_name": "Ashish Kumar", + "author_inst": "Saint John's Medical College, Banglore, Karnataka, India" }, { - "author_name": "Mahableshwar Albur", - "author_inst": "North Bristol NHS Trust" + "author_name": "Hossam Amin", + "author_inst": "New York Medical College, Metropolitan Hospital" }, { - "author_name": "Jonathan Turner", - "author_inst": "Public Health England" + "author_name": "Shobhana Chaudhari", + "author_inst": "New York Medical College, Metropolitan Hospital" }, { - "author_name": "Alasdair P MacGowan", - "author_inst": "North Bristol NHS Trust" - }, - { - "author_name": "David T Arnold", - "author_inst": "University of Bristol" + "author_name": "Imnette Habtes", + "author_inst": "New York Medical College, Metropolitan Hospital" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "intensive care and critical care medicine" }, { "rel_doi": "10.1101/2020.07.02.20145391", @@ -1322147,35 +1322528,59 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.06.30.20135343", - "rel_title": "Non-Adherence Tree Analysis (NATA) - an adherence improvement framework: a COVID-19 case study", + "rel_doi": "10.1101/2020.07.01.20144683", + "rel_title": "Bronchoscopy in critically ill COVID-19 Patients: microbiological profile and factors related to nosocomial respiratory infection", "rel_date": "2020-07-03", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.30.20135343", - "rel_abs": "Poor adherence to medication is a global phenomenon that has received a significant amount of research attention yet remains largely unsolved. Medication non-adherence can blur drug efficacy results in clinical trials, lead to substantial financial losses, increase the risk of relapse and hospitalisation, or lead to death. The most common methods measuring adherence are post-treatment measures; that is, adherence is usually measured after the treatment has begun. What the authors are proposing in this multidisciplinary study is a technique for analysing the factors that can cause non-adherence before or during medication treatment.\n\nFault Tree Analysis (FTA), allows system analysts to determine how combinations of simple faults of a system can propagate to cause a total system failure. Monte Carlo simulation is a mathematical algorithm that depends heavily on repeated random sampling to predict the behaviour of a system. In this study, the authors propose the use of Non-Adherence Tree Analysis (NATA), based on the FTA and Monte Carlo simulation techniques, to improve adherence. Firstly, the non-adherence factors of a medication treatment lifecycle are translated into what is referred to as a Non-Adherence Tree (NAT). Secondly, the NAT is coded into a format that is translated into the GoldSim software for performing dynamic system modelling and analysis using Monte Carlo. Finally, the GoldSim model is simulated and analysed to predict the behaviour of the NAT.\n\nThis study produces a framework for improving adherence by analysing social and non-social adherence barriers. The results reveal that the biggest factor that could contribute to non-adherence to a COVID-19 treatment is a therapy-related factor (the side effects of the medication). This is closely followed by a condition-related factor (asymptomatic nature of the disease) then patient-related factors (forgetfulness and other causes). With this information, clinicians can implement relevant measures and allocate resources appropriately to minimise non-adherence.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.01.20144683", + "rel_abs": "BackgroundNosocomial co-infections are a cause of morbidity and mortality in Intensive Care Units (ICU).\n\nObjectivesOur aim was to describe bronchoscopy findings and analyse co-infection through bronchial aspirate (BA) samples in patients with COVID-19 pneumonia requiring ICU admission.\n\nMethodsWe conducted a retrospective observational study, analysing the BA samples collected from intubated patients with COVID-19 to diagnose nosocomial respiratory infection.\n\nResultsOne-hundred and fifty-five consecutive BA samples were collected from 75 patients. Of them, 90 (58%) were positive cultures for different microorganisms, 11 (7.1%) were polymicrobial, and 37 (23.7%) contained resistant microorganisms. There was a statistically significant association between increased days of orotracheal intubation (OTI) and positive BA (18.9 days versus 10.9 days, p<0.01), polymicrobial infection (22.11 versus 13.54, p<0.01) and isolation of resistant microorganisms (18.88 versus 10.94, p<0.01). In 88% of the cases a change in antibiotic treatment was made.\n\nConclusionNosocomial respiratory infection in intubated COVID-19 patients seems to be higher than in non-epidemic periods. The longer the intubation period, the greater the probability of co-infection, isolation of resistant microorganisms and polymicrobial infection. Microbiological sampling through BA is an essential tool to manage these patients appropriately.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Ernest E Edifor", - "author_inst": "Manchester Metropolitan University" + "author_name": "Pere Serra Mitja", + "author_inst": "Hospital Germans Trias i Pujol" }, { - "author_name": "Regina Brown", - "author_inst": "University of Massachusetts Medical School" + "author_name": "Carmen Centeno Clemente", + "author_inst": "Hospital Universitari Germans Trias i Pujol" }, { - "author_name": "Paul Smith", - "author_inst": "Manchester Metropolitan University" + "author_name": "Ignasi Garcia-Olive", + "author_inst": "Hospital Universitari Germans Trias i Pujol" + }, + { + "author_name": "Adria Antuori Torres", + "author_inst": "Hospital Universitari Germans Trias i Pujol" + }, + { + "author_name": "Maria Casadella Fontdevila", + "author_inst": "IrsiCaixa AIDS Research Institute" + }, + { + "author_name": "Rachid Tazi Mezalek", + "author_inst": "Hospital Universitari Germans Trias i Pujol" }, { - "author_name": "Rick Kossik", - "author_inst": "GoldSim Technology Group" + "author_name": "Fernando Armestar", + "author_inst": "Hospital Universitari Germans Trias i Pujol" + }, + { + "author_name": "Esther Fernandez Araujo", + "author_inst": "Hospital Universitari Germans Trias i Pujol" + }, + { + "author_name": "Felipe Andreo Garcia", + "author_inst": "Hospital Universitari Germans Trias i Pujol" + }, + { + "author_name": "Antoni Rosell Gratacos", + "author_inst": "Hospital Universitari Germans Trias i Pujol" } ], "version": "1", "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "respiratory medicine" }, { "rel_doi": "10.1101/2020.06.30.20143347", @@ -1323613,51 +1324018,39 @@ "category": "intensive care and critical care medicine" }, { - "rel_doi": "10.1101/2020.07.01.20144386", - "rel_title": "Clinical characterization of respiratory droplet production during common airway procedures using high-speed imaging", + "rel_doi": "10.1101/2020.06.30.20143727", + "rel_title": "Twitter and Census Data Analytics to Explore Socioeconomic Factors for Post-COVID-19 Reopening Sentiment", "rel_date": "2020-07-02", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.01.20144386", - "rel_abs": "BackgroundDuring the COVID-19 pandemic, a significant number of healthcare workers have been infected with SARS-CoV-2. However, there remains little knowledge regarding droplet dissemination during airway management procedures in real life settings.\n\nMethods12 different airway management procedures were investigated during routine clinical care. A high-speed video camera (1000 frames/second) was for imaging. Quantitative droplet characteristics as size, distance traveled, and velocity were computed.\n\nResultsDroplets were detected in 8/12 procedures. The droplet trajectories could be divided into two distinctive patterns (type 1/2). Type 1 represented a ballistic trajectory with higher speed droplets whereas type 2 represented a random trajectory of slower particles that persisted longer in air. Speaking and coughing lead to a larger amount of droplets than non-invasive ventilation therapy. The use of tracheal cannula filters reduced the amount of droplets.\n\nConclusionsRespiratory droplet patterns generated during airway management procedures follow two distinctive trajectories based on the influence of aerodynamic forces. Speaking and coughing produce more droplets than non-invasive ventilation therapy confirming these behaviors as exposure risks. Even large droplets may exhibit patterns resembling the fluid dynamics smaller airborne aerosols that follow the airflow convectively and may place the healthcare provider at risk.", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.30.20143727", + "rel_abs": "Investigating and classifying sentiments of social media users (e.g., positive, negative) towards an item, situation, and system are very popular among the researchers. However, they rarely discuss the underlying socioeconomic factor associations for such sentiments. This study attempts to explore the factors associated with positive and negative sentiments of the people about reopening the economy, in the United States (US) amidst the COVID-19 global crisis. It takes into consideration the situational uncertainties (i.e., changes in work and travel pattern due to lockdown policies), economic downturn and associated trauma, and emotional factors such as depression. To understand the sentiment of the people about the reopening economy, Twitter data was collected, representing the 51 states including Washington DC of the US. State-wide socioeconomic characteristics of the people (e.g., education, income, family size, and employment status), built environment data (e.g., population density), and the number of COVID-19 related cases were collected and integrated with Twitter data to perform the analysis. A binary logit model was used to identify the factors that influence people toward a positive or negative sentiment. The results from the logit model demonstrate that family households, people with low education levels, people in the labor force, low-income people, and people with higher house rent are more interested in reopening the economy. In contrast, households with a high number of members and high income are less interested to reopen the economy. The accuracy of the model is good (i.e., the model can correctly classify 56.18% of the sentiments). The Pearson chi2 test indicates that overall this model has high goodness-of-fit. This study provides a clear indication to the policymakers where to allocate resources and what policy options they can undertake to improve the socioeconomic situations of the people and mitigate the impacts of pandemics in the current situation and as well as in the future.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Sarina K Mueller", - "author_inst": "Friedrich-Alexander-Universitat Erlangen-Nurnberg Medizinische Fakultat (FAU)" - }, - { - "author_name": "Reinhard Veltrup", - "author_inst": "Friedrich-Alexander-Universitat Erlangen-Nurnberg Medizinische Fakultat (FAU)" - }, - { - "author_name": "Bernhard Jakubass", - "author_inst": "Friedrich-Alexander-Universitat Erlangen-Nurnberg Medizinische Fakultat (FAU)" - }, - { - "author_name": "Stefan Kniesburges", - "author_inst": "Friedrich-Alexander-Universitat Erlangen-Nurnberg Medizinische Fakultat (FAU)" + "author_name": "Md Mokhlesur Rahman", + "author_inst": "The University of North Carolina at Charlotte" }, { - "author_name": "Judith Kempfle", - "author_inst": "Massachusetts Eye Ear, Harvard Medical School" + "author_name": "G. G. Md. Nawaz Ali", + "author_inst": "University of Charleston" }, { - "author_name": "Matthias J. Huebner", - "author_inst": "Friedrich-Alexander-Universitat Erlangen-Nurnberg Medizinische Fakultat (FAU)" + "author_name": "Xue Jun Li", + "author_inst": "Auckland University of Technology" }, { - "author_name": "Heinrich Iro", - "author_inst": "Friedrich-Alexander-Universitat Erlangen-Nurnberg Medizinische Fakultat (FAU)" + "author_name": "Kamal Chandra Paul", + "author_inst": "University of North Carolina at Charlotte" }, { - "author_name": "Michael Doellinger", - "author_inst": "Friedrich-Alexander-Universitat Erlangen-Nurnberg Medizinische Fakultat (FAU)" + "author_name": "Peter H.J. Chong", + "author_inst": "Auckland University of Technology" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "intensive care and critical care medicine" + "category": "public and global health" }, { "rel_doi": "10.1101/2020.07.01.20144105", @@ -1325155,35 +1325548,55 @@ "category": "molecular biology" }, { - "rel_doi": "10.1101/2020.07.01.182964", - "rel_title": "Using iCn3D and the World Wide Web for structure-based collaborative research: Analyzing molecular interactions at the root of COVID-19", + "rel_doi": "10.1101/2020.07.01.182220", + "rel_title": "Association between neutralizing antibodies to SARS-CoV-2 and commercial serological assays", "rel_date": "2020-07-02", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.07.01.182964", - "rel_abs": "ABSTRACTThe COVID-19 pandemic took us ill-prepared and tackling the many challenges it poses in a timely manner requires world-wide collaboration. Our ability to study the SARS-COV-2 virus and its interactions with its human host in molecular terms efficiently and collaboratively becomes indispensable and mission-critical in the race to develop vaccines, drugs, and neutralizing antibodies. There is already a significant corpus of 3D structures related to SARS and MERS coronaviruses, and the rapid generation of new structures demands the use of efficient tools to expedite the sharing of structural analyses and molecular designs and convey them in their native 3D context in sync with sequence data and annotations. We developed iCn3D (pronounced \u201cI see in 3D\u201d) 1 to take full advantage of web technologies and allow scientists of different backgrounds to perform and share sequence-structure analyses over the Internet and engage in collaborations through a simple mechanism of exchanging \u201clifelong\u201d web links (URLs). This approach solves the very old problem of \u201csharing of molecular scenes\u201d in a reliable and convenient manner. iCn3D links are sharable over the Internet and make data and entire analyses findable, accessible, and reproducible, with various levels of interoperability. Links and underlying data are FAIR 2 and can be embedded in preprints and papers, bringing a 3D live and interactive dimension to a world of text and static images used in current publications, eliminating at the same time the need for arcane supplemental materials. This paper exemplifies iCn3D capabilities in visualization, analysis, and sharing of COVID-19 related structures, sequence variability, and molecular interactions.Competing Interest StatementThe authors have declared no competing interest.View Full Text", - "rel_num_authors": 4, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.07.01.182220", + "rel_abs": "Introduction Commercially available SARS-CoV-2 serological assays based on different viral antigens have been approved for the qualitative determination of anti-SARS-CoV-2 antibodies. However, there is limited published data associating the results from commercial assays with neutralizing antibodies.Methods 67 specimens from 48 patients with PCR-confirmed COVID-19 and a positive result by the Roche Elecsys SARS-CoV-2, Abbott SARS-CoV-2 IgG, or EUROIMMUN SARS-CoV-2 IgG assays and 5 control specimens were analyzed for the presence of neutralizing antibodies to SARS-CoV-2. Correlation, concordance, positive percent agreement (PPA), and negative percent agreement (NPA) were calculated at several cutoffs. Results were compared in patients categorized by clinical outcomes.Results The correlation between SARS-CoV-2 neutralizing titer (EC50) and the Roche, Abbott, and EUROIMMUN assays was 0.29, 0.47, and 0.46 respectively. At an EC50 of 1:32, the concordance kappa with Roche was 0.49 (95% CI; 0.23-0.75), with Abbott was 0.52 (0.28-0.77), and with EUROIMMUN was 0.61 (0.4-0.82). At the same neutralizing titer, the PPA and NPA for the Roche was 100% (94-100) & 56% (30-80); Abbott was 96% (88-99) & 69% (44-86); and EUROIMMUN was 91% (80-96) & 81% (57-93) for distinguishing neutralizing antibodies. Patients who died, were intubated, or had a cardiac injury from COVID-19 infection had significantly higher neutralizing titers relative to those with mild symptoms.Conclusion COVID-19 patients generate an antibody response to multiple viral proteins such that the calibrator ratios on the Roche, Abbott, and EUROIMMUN assays are all associated with SARS-CoV-2 neutralization. Nevertheless, commercial serological assays have poor NPA for SARS-CoV-2 neutralization, making them imperfect proxies for neutralization.Competing Interest StatementThe authors have declared no competing interest.View Full Text", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Philippe Youkharibache", - "author_inst": "National Institute of Health" + "author_name": "Mei San Tang", + "author_inst": "Washington University- St. Louis, MO" }, { - "author_name": "Raul Edouardo Cachau", - "author_inst": "Frederick National Laboratory for Cancer Research: Frederick, MD, US" + "author_name": "James Brett Case", + "author_inst": "Washington University- St. Louis, MO" }, { - "author_name": "Thomas Madej", - "author_inst": "National Institute of Health" + "author_name": "Caroline E Franks", + "author_inst": "Washington University- St. Louis, MO" }, { - "author_name": "Jiyao Wang", - "author_inst": "National Institutes of Health" + "author_name": "Rita E Chen", + "author_inst": "Washington University- St. Louis, MO" + }, + { + "author_name": "Neil W Anderson", + "author_inst": "Washington University- St. Louis, MO" + }, + { + "author_name": "Jeffrey P Henderson", + "author_inst": "Washington University- St. Louis, MO" + }, + { + "author_name": "Michael S Diamond", + "author_inst": "Washington University- St. Louis, MO" + }, + { + "author_name": "Ann M Gronowski", + "author_inst": "Washington University- St. Louis, MO" + }, + { + "author_name": "Christopher W Farnsworth", + "author_inst": "Washington University - St. Louis, MO" } ], "version": "1", - "license": "cc0", + "license": "cc_no", "type": "new results", - "category": "bioinformatics" + "category": "immunology" }, { "rel_doi": "10.1101/2020.07.02.184093", @@ -1327013,151 +1327426,27 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2020.07.01.181867", - "rel_title": "periscope: sub-genomic RNA identification in SARS-CoV-2 ARTIC Network Nanopore Sequencing Data", + "rel_doi": "10.1101/2020.07.01.182659", + "rel_title": "High affinity binding of SARS-CoV-2 spike protein enhances ACE2 carboxypeptidase activity", "rel_date": "2020-07-01", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.07.01.181867", - "rel_abs": "We have developed periscope, a tool for the detection and quantification of sub-genomic RNA (sgRNA) in SARS-CoV-2 genomic sequence data. The translation of the SARS-CoV-2 RNA genome for most open reading frames (ORFs) occurs via RNA intermediates termed \"sub-genomic RNAs\". sgRNAs are produced through discontinuous transcription which relies on homology between transcription regulatory sequences (TRS-B) upstream of the ORF start codons and that of the TRS-L which is located in the 5 UTR. TRS-L is immediately preceded by a leader sequence. This leader sequence is therefore found at the 5 end of all sgRNA. We applied periscope to 1,155 SARS-CoV-2 genomes from Sheffield, UK and validated our findings using orthogonal datasets and in vitro cell systems. Using a simple local alignment to detect reads which contain the leader sequence we were able to identify and quantify reads arising from canonical and non-canonical sgRNA. We were able to detect all canonical sgRNAs at expected abundances, with the exception of ORF10. A number of recurrent non-canonical sgRNAs are detected. We show that the results are reproducible using technical replicates and determine the optimum number of reads for sgRNA analysis. In VeroE6 ACE2+/- cell lines, periscope can detect the changes in the kinetics of sgRNA in orthogonal sequencing datasets. Finally, variants found in genomic RNA are transmitted to sgRNAs with high fidelity in most cases. This tool can be applied to all sequenced COVID-19 samples worldwide to provide comprehensive analysis of SARS-CoV-2 sgRNA.", - "rel_num_authors": 33, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.07.01.182659", + "rel_abs": "A novel coronavirus (SARS-CoV-2) has emerged to a global pandemic and caused significant damages to public health. Human angiotensin-converting enzyme 2(ACE2) was identified as the entry receptor for SARS-CoV-2. As a carboxypeptidase, ACE2 cleaves many biological substrates besides Ang II to control vasodilatation and permeability. Given the nanomolar high affinity between ACE2 and SARS-CoV-2 spike protein, we wonder how this interaction would affect the enzymatic activity of ACE2. Surprisingly, SARS-CoV-2 trimeric spike protein increased ACE2 proteolytic activity ~3-10 fold when fluorogenic caspase-1 substrate and Bradykinin-analog peptides were used to characterize ACE2 activity. In addition, the enhancement was mediated by ACE2 binding of RBD domain of SARS-CoV-2 spike. These results highlighted the altered activity of ACE2 during SARS-CoV-2 infection and would shed new lights on the pathogenesis of COVID-19 and its complications for better treatments.Competing Interest StatementThe authors have declared no competing interest.View Full Text", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Matthew Daniel Parker", - "author_inst": "Sheffield Bioinformatics Core, Neuroscience Institute, The University of Sheffield, Sheffield, UK" - }, - { - "author_name": "Benjamin B Lindsey", - "author_inst": "The Florey Institute, Department of Infection, Immunity and Cardiovascular Disease, Medical School, University of Sheffield. Sheffield Teaching Hospitals NHS Fo" - }, - { - "author_name": "Shay Leary", - "author_inst": "Institute for Immunology and Infectious Diseases, Murdoch University, Murdoch, Western Australia, Australia" - }, - { - "author_name": "Silvana Gaudieri", - "author_inst": "School of Human Sciences, University of Western Australia, Crawley, Western Australia, Australia" - }, - { - "author_name": "Abha Chopra", - "author_inst": "Institute for Immunology & Infectious Diseases Discovery Way, Murdoch University, Murdoch, Western Australia" - }, - { - "author_name": "Matthew Wyles", - "author_inst": "Sheffield Institute of Translational Neuroscience, Neuroscience Institute, The University of Sheffield, Sheffield, UK" - }, - { - "author_name": "Adrienn Angyal", - "author_inst": "The Florey Institute, Department of Infection, Immunity and Cardiovascular Disease, Medical School, University of Sheffield, Sheffield, UK." - }, - { - "author_name": "Luke R Green", - "author_inst": "The Florey Institute, Department of Infection, Immunity and Cardiovascular Disease, Medical School, University of Sheffield, Sheffield, UK" - }, - { - "author_name": "Paul Parsons", - "author_inst": "Department of Animal and Plant Sciences, Alfred Denny Building, The University of Sheffield, S10 2TN" - }, - { - "author_name": "Rachel M Tucker", - "author_inst": "Department of Animal and Plant Sciences, Alfred Denny Building, The University of Sheffield, S10 2TN" - }, - { - "author_name": "Rebecca Brown", - "author_inst": "The Florey Institute, Department of Infection, Immunity and Cardiovascular Disease, Medical School, University of Sheffield, Sheffield, UK." - }, - { - "author_name": "Danielle Groves", - "author_inst": "The Florey Institute, Department of Infection, Immunity and Cardiovascular Disease, Medical School, University of Sheffield, Sheffield, UK." - }, - { - "author_name": "Katie Johnson", - "author_inst": "Sheffield Teaching Hospitals NHS Foundation Trust, Department of Virology/Microbiology, Sheffield, UK." - }, - { - "author_name": "Laura Carrilero", - "author_inst": "Department of Animal and Plant Sciences, Alfred Denny Building, The University of Sheffield, S10 2TN" - }, - { - "author_name": "Joe Heffer", - "author_inst": "IT Services, The University of Sheffield, Sheffield, UK" - }, - { - "author_name": "David Partridge", - "author_inst": "Sheffield Teaching Hospitals NHS Foundation Trust, Department of Virology/Microbiology, The Florey Institute, Department of Infection, Immunity and Cardiovascul" - }, - { - "author_name": "Cariad Evans", - "author_inst": "Sheffield Teaching Hospitals NHS Foundation Trust, Department of Virology/Microbiology, Sheffield, UK." - }, - { - "author_name": "Mohammad Razza", - "author_inst": "Sheffield Teaching Hospitals NHS Foundation Trust, Department of Virology/Microbiology, Sheffield, UK." - }, - { - "author_name": "Alexanda J Keeley", - "author_inst": "Sheffield Teaching Hospitals NHS Foundation Trust, Department of Virology/Microbiology, The Florey Institute, Department of Infection, Immunity and Cardiovascul" - }, - { - "author_name": "Nikki Smith", - "author_inst": "The Florey Institute, Department of Infection, Immunity and Cardiovascular Disease, Medical School, University of Sheffield, Sheffield, UK." - }, - { - "author_name": "Ana Da Silva Filipe", - "author_inst": "Centre for Virus Research, The University of Glasgow, Glasgow, UK" - }, - { - "author_name": "James G Shepherd", - "author_inst": "Centre for Virus Research, The University of Glasgow, Glasgow, UK" - }, - { - "author_name": "Chris Davis", - "author_inst": "Centre for Virus Research, The University of Glasgow, Glasgow, UK" - }, - { - "author_name": "Sahan Bennett", - "author_inst": "Centre for Virus Research, The University of Glasgow, Glasgow, UK" - }, - { - "author_name": "Alain Kohl", - "author_inst": "Centre for Virus Research, The University of Glasgow, Glasgow, UK" - }, - { - "author_name": "Elihu Aranday-Cortes", - "author_inst": "Centre for Virus Research, The University of Glasgow, Glasgow, UK" - }, - { - "author_name": "Lily Tong", - "author_inst": "Centre for Virus Research, The University of Glasgow, Glasgow, UK" - }, - { - "author_name": "Jenna Nichols", - "author_inst": "Centre for Virus Research, The University of Glasgow, Glasgow, UK" - }, - { - "author_name": "Emma C Thomson", - "author_inst": "Centre for Virus Research, The University of Glasgow, Glasgow, UK" - }, - { - "author_name": "- The COVID-19 Genomics UK (COG-UK) consortium", - "author_inst": "-" - }, - { - "author_name": "Dennis Wang", - "author_inst": "Sheffield Bioinformatics Core, Department of Computer Science, The University of Sheffield, Sheffield, UK." - }, - { - "author_name": "Simon Mallal", - "author_inst": "Division of Infectious Diseases, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA" + "author_name": "Jinghua Lu", + "author_inst": "National Institute of Allergy and Infectious Diseases" }, { - "author_name": "Thushan I de Silva", - "author_inst": "The Florey Institute, Department of Infection, Immunity and Cardiovascular Disease, Medical School, University of Sheffield, Sheffield Teaching Hospitals NHS Fo" + "author_name": "Peter D. Sun", + "author_inst": "National Institute of Allergy and Infectious Diseases" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc0", "type": "new results", - "category": "bioinformatics" + "category": "biochemistry" }, { "rel_doi": "10.1101/2020.06.30.181446", @@ -1329095,33 +1329384,41 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.06.29.20142513", - "rel_title": "Epidemic Trend Analysis of SARS-CoV-2 in SAARC Countries Using Modified SIR (M-SIR) Predictive Model", + "rel_doi": "10.1101/2020.06.29.20142463", + "rel_title": "Epidemiological investigation of the first 135 COVID-19 cases in Brunei: Implications for surveillance, control, and travel restrictions", "rel_date": "2020-06-30", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.29.20142513", - "rel_abs": "A novel coronavirus causing the severe and fatal respiratory syndrome was identified in China, is now producing outbreaks in more than two hundred countries around the world, and became pandemic by the time. In this article, a modified version of the well known mathematical epidemic model Susceptible (S)- Infected (I)- Recovered (R) is used to analyze the epidemics course of COVID-19 in eight different countries of the South Asian Association for Regional Cooperation (SAARC). To achieve this goal, the parameters of the SIR model are identified by using publicly available data for the corresponding countries: Afghanistan, Bangladesh, Bhutan, India, the Maldives, Nepal, Pakistan and Sri Lanka. Based on the prediction model we estimated the epidemic trend of COVID-19 outbreak in SAARC countries for 20 days, 90 days, and 180 days respectively. An SML (short-mid-long) term prediction model has been designed to understand the early dynamics of COVID-19 Epidemic in the south-east Asian region. The maximum and minimum basic reproduction number (R0 = 1.33 and 1.07) for SAARC countries are predicted to be in Pakistan and Bhutan. We equate simulation results with real data in the SAARC countries on the COVID-19 outbreak, and model potential countermeasure implementation scenarios. Our results should provide policymakers with a method for evaluating the impacts of possible interventions, including lockdown and social distancing, as well as testing and contact tracking.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.29.20142463", + "rel_abs": "BackgroundStudies on the early introduction of SARS-CoV-2 in a naive population have important epidemic control implications. We report findings from the epidemiological investigation of the initial 135 COVID-19 cases in Brunei and describe the impact of control measures and travel restrictions.\n\nMethodsEpidemiological and clinical information were obtained for all confirmed COVID-19 cases in Brunei, whose symptom onset was from March 9 to April 5, 2020 (covering the initial 5 weeks of the epidemic). Transmission-related measures such as reproduction number (R), incubation period, serial interval were estimated. Time-varying R was calculated to assess the effectiveness of control measures.\n\nResultsA total of 135 cases were detected, of which 53 (39.3%) were imported. The median age was 36 years (range = 0.5 to 72). 41 (30.4%) and 13 (9.6%) were presymptomatic and asymptomatic cases respectively. The median incubation period was 5 days (IQR = 5, range = 1 to 11), and the mean serial interval was 5.39 days (sd = 4.47; 95% CI: 4.25, 6.53). R0 was between 3.88 and 5.96, and the doubling time was 1.3 days. By the 13th day of the epidemic, the Rt was under one (Rt = 0.91; 95% credible interval: 0.62, 1.32) and the epidemic was under control.\n\nConclusionEpidemic control was achieved through a combination of public health measures, with emphasis on a test-isolate-trace approach supplemented by travel restrictions and moderate physical distancing measures but no actual lockdown. To maintain suppression, regular and ongoing testing of high-risk groups can supplement the existing surveillance program.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Samrat Kumar Dey", - "author_inst": "Dhaka International University (DIU)" + "author_name": "Justin Wong", + "author_inst": "Disease Control Division, Ministry of Health, Brunei Darussalam" }, { - "author_name": "Md. Mahbubur Rahman", - "author_inst": "Military Institute of Science and Technology (MIST)" + "author_name": "Liling Chaw", + "author_inst": "Universiti Brunei Darussalam" }, { - "author_name": "Kabid Hassan Shibly", - "author_inst": "Dhaka International University (DIU)" + "author_name": "Wee Chian Koh", + "author_inst": "Centre for Strategic and Policy Studies" }, { - "author_name": "Umme Raihan Siddiqi", - "author_inst": "Shaheed Suhrawardy Medical College (ShSMC)" + "author_name": "Mohammad Fathi Alikhan", + "author_inst": "Disease Control Division, Ministry of Health, Brunei Darussalam" }, { - "author_name": "Arpita Howlader", - "author_inst": "Patuakhali Science and Technology University (PSTU)" + "author_name": "Sirajul Adli Jamaludin", + "author_inst": "Environmental Health Division, Ministry of Health, Brunei Darussalam" + }, + { + "author_name": "Wan Wen Patricia Poh", + "author_inst": "Department of Dental Services, Ministry of Health, Brunei Darussalam" + }, + { + "author_name": "Lin Naing", + "author_inst": "Universiti Brunei Darussalam, Brunei" } ], "version": "1", @@ -1330993,85 +1331290,61 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.06.26.20135715", - "rel_title": "Genomic epidemiology of SARS-CoV-2 in Colombia", + "rel_doi": "10.1101/2020.06.26.20140806", + "rel_title": "Combination of Antibody based rapid diagnostic tests used in an algorithm may improve their performance in SARS CoV-2 diagnosis.", "rel_date": "2020-06-29", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.26.20135715", - "rel_abs": "Coronavirus disease 2019 (COVID-19) was first diagnosed in Colombia from a traveler arriving from Italy on February 26, 2020. To date, available data on the origins and number or introductions of SARS-CoV-2 into the country are limited. Here, we sequenced SARS-CoV-2 from 43 clinical samples and--together with other 73 genomes sequences available from the country--we investigated the emergence and the routes of importation of COVID-19 into Colombia using epidemiological, historical air travel and phylogenetic observations. Our study provided evidence of multiple introductions, mostly from Europe, with at least 12 lineages being documented. Phylogenetic findings validated the lineage diversity, supported multiple importation events and the evolutionary relationship of epidemiologically-linked transmission chains. Our results reconstruct the early evolutionary history of SARS-CoV-2 in Colombia and highlight the advantages of genome sequencing to complement COVID-19 outbreak investigation.", - "rel_num_authors": 17, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.26.20140806", + "rel_abs": "BackgroundGlobally response to the SARS-CoV-2 pandemic is highly limited by diagnostic methods. Currently, World Health Organization (WHO) recommends the use of molecular assays for confirmation of SARS-CoV-2 infection which are highly expensive and require specialized laboratory equipment. This is a limitation in mass testing and in low resource settings. SARS CoV-2 IgG/IgM antibody tests have had poor diagnostic performance that do not guarantee their use in diagnostics. In this study we demonstrate a concept of using a combination of RDTs in an algorithm to improve their performance for diagnostics.\n\nMethodEighty six (86) EDTA whole blood samples were collected from SARS-CoV-2 positive cases admitted at Masaka and Mbarara Regional Referral Hospitals in Uganda. These were categorized from day when confirmed positive as follows; category A (0-3 days, 10 samples), category B (4-7 days, 20 samples), Category C (8-17 days, 11 samples) and Category D (18-28 days, 20 samples). Plasma was prepared, transported to the testing laboratory and stored at -200C prior to testing. A total of 13 RDTS were tested following manufacturers instructions. Data was entered in Microsoft Excel exported to STATA for computation of sensitivity and specificity. We computed for all possible combinations of 2 of the 13 RDTS (13C2) that were evaluated in parallel algorithm.\n\nResultsThe individual sensitives of the RDTs ranged between 74% and 18% and there was a general increasing trend across the categories with days since PCR confirmation. A total of 78 possible combinations of the RDTs to be used in parallel was computated. The combinations of the 2 RDTS improved the sensitivities to 90%.\n\nDiscussionWe demonstrate that use of RDTs in combinations can improve their overall sensitivity. This approach when used on a wider range of combination of RDTs may yield combinations that can give sensitivities that are of diagnostics relevance in mass testing and low resource setting.", + "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Katherine Laiton-Donato", - "author_inst": "Instituto Nacional de Salud" - }, - { - "author_name": "Christian Julian Villabona Arenas", - "author_inst": "London School of Hygiene & Tropical Medicine" - }, - { - "author_name": "Jose A Usme Ciro", - "author_inst": "Universidad Cooperativa de Colombia" - }, - { - "author_name": "Carlos Franco Munoz", - "author_inst": "Instituto Nacional de Salud" - }, - { - "author_name": "Diego Alejandro Alvarez-Diaz", - "author_inst": "Instituto Nacional de Salud" - }, - { - "author_name": "Liz S Villabona-Arenas", - "author_inst": "Universidad Industrial de Santander" - }, - { - "author_name": "Susy Echeverria-Londono", - "author_inst": "Imperial College-London" + "author_name": "Grace Esther Kushemererwa", + "author_inst": "Central Public Health Laboratories" }, { - "author_name": "Nicolas D Franco-Sierra", - "author_inst": "Instituto de Investigacion de Recursos Biologicos Alexander von Humboldt" + "author_name": "Ismail Kayongo", + "author_inst": "Central Public Health Laboratories" }, { - "author_name": "Zulma M Cucunuba", - "author_inst": "Imperial College London" + "author_name": "Patrick Semanda", + "author_inst": "Central Public Health Laboratories" }, { - "author_name": "Astrid Carolina Florez-Sanchez", - "author_inst": "Instituto Nacional de Salud" + "author_name": "Hellen Nansumba", + "author_inst": "Central Public Health Laboratories" }, { - "author_name": "Carolina Ferro", - "author_inst": "Instituto Nacional de Salud" + "author_name": "Christine Namulindwa", + "author_inst": "Central Public Health Laboratories" }, { - "author_name": "Nadim J Ajami", - "author_inst": "Baylor College of Medicine" + "author_name": "Iga Tadeo", + "author_inst": "Central Public Health Laboratories" }, { - "author_name": "Diana M Walteros", - "author_inst": "Instituto Nacional de Salud" + "author_name": "Wilson Nyegenye", + "author_inst": "Central Public Health Laboratories" }, { - "author_name": "Franklin E Prieto-Alvarado", - "author_inst": "Instituto Nacional de Salud" + "author_name": "Charles Kiyaga", + "author_inst": "Central Public Health Laboratories" }, { - "author_name": "Carlos A Duran-Camacho", - "author_inst": "Instituto Nacional de Salud" + "author_name": "Patrick Agwa Ogwok", + "author_inst": "Ministry of Health" }, { - "author_name": "Martha L Ospina-Martinez", - "author_inst": "Instituto Nacional de Salud" + "author_name": "Susan Nabadda", + "author_inst": "Ministry of Health" }, { - "author_name": "Marcela M Mercado-Reyes", - "author_inst": "Instiuto Nacional de Salud" + "author_name": "Isaac Ssewanyana", + "author_inst": "Central Public Health Laboratories and Infectious Diseases Research Institute" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1332631,29 +1332904,37 @@ "category": "psychiatry and clinical psychology" }, { - "rel_doi": "10.1101/2020.06.27.20141770", - "rel_title": "Readability of selected governmental and popular health organization websites on Covid-19 public health information: A descriptive analysis", + "rel_doi": "10.1101/2020.06.29.20142307", + "rel_title": "Temperature and Humidity Do Not Influence Global COVID-19 Incidence as Inferred from Causal Models", "rel_date": "2020-06-29", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.27.20141770", - "rel_abs": "BackgroundThe U.S. Department of Health & Human Services (USDHHS) recommends that health material be written at or below a sixth-grade reading level to ensure readability. The aim of this study was to examine the readability of international and national health organizations on Covid-19 information in their websites employing a previously validated tool.\n\nMethodsA purposive sample of publicly accessible governmental and popular international health organization websites was selected. The readability of the websites Covid-19 public health information was estimated using the previously validated SMOG readability formula, which determined reading level by correlating the number of polysyllabic words.\n\nResultsOf the 10 websites included in the analysis, none had Covid-19 public health information at the USDHHSs recommended reading level. The material ranged in reading level at undergraduate level or above.\n\nDiscussionThe findings indicate that the online Covid-19 materials need to be modified in order to reach recommended reading levels. This study can be of practical use to policy makers and public health government officials when designing, modifying, and evaluating Covid-19 materials. We recommend using simple, non-polysyllable words to ensure that Covid-19 public health information materials are written at the recommended reading levels.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.29.20142307", + "rel_abs": "The relationship between meteorological factors such as temperature and humidity with COVID-19 incidence is still unclear after 6 months of the beginning of the pandemic. Some literature confirms the association of temperature with disease transmission while some oppose the same. This work intends to determine whether there is a causal association between temperature, humidity and Covid-19 cases. Three different causal models were used to capture stochastic, chaotic and symbolic natured time-series data and to provide a robust & unbiased analysis by constructing networks of causal relationships between the variables. Granger-Causality method, Transfer Entropy method & Convergent Cross-Mapping (CCM) was done on data from regions with different temperatures and cases greater than 50,000 as of 13th May 2020. From the Granger-Causality test we found that in only Canada, the United Kingdom, temperature and daily new infections are causally linked. The same results were obtained from Convergent Cross Mapping for India. Again using Granger-Causality test, we found that in Russia only, relative humidity is causally linked to daily new cases. Thus, a Generalized Additive Model with a smoothing spline function was fitted for these countries to understand the directionality. Using the combined results of the said models, we were able to conclude that there is no evidence of a causal association between temperature, humidity and Covid-19 cases.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Patricia Moyinoluwa Ojo", - "author_inst": "University College Cork" + "author_name": "Raghav Awasthi", + "author_inst": "IIIT-Delhi" }, { - "author_name": "Tolulope Omowonuola Okeowo", - "author_inst": "University College Cork" + "author_name": "Aditya Nagori", + "author_inst": "CSIR-Institute of Genomics and Integrative Biology" }, { - "author_name": "Ann Mary Thampy", - "author_inst": "University College Cork" + "author_name": "Pradeep Singh", + "author_inst": "IIIT-Delhi" }, { - "author_name": "Zubair Kabir", - "author_inst": "University College Cork" + "author_name": "Ridam Pal", + "author_inst": "IIIT-Delhi" + }, + { + "author_name": "Vineet Joshi", + "author_inst": "IIIT-Delhi" + }, + { + "author_name": "Tavpritesh Sethi", + "author_inst": "IIIT-Delhi" } ], "version": "1", @@ -1334117,47 +1334398,31 @@ "category": "health economics" }, { - "rel_doi": "10.1101/2020.06.26.20140905", - "rel_title": "Forecasting COVID-19 Dynamics and Endpoint in Bangladesh: A Data-driven Approach", + "rel_doi": "10.1101/2020.06.26.20141077", + "rel_title": "Analyses and Forecast for COVID-19 epidemic in India", "rel_date": "2020-06-28", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.26.20140905", - "rel_abs": "On December 31, 2019, the World Health Organization (WHO) was informed that atypical pneumonia-like cases have emerged in Wuhan City, Hubei province, China. WHO identified it as a novel coronavirus and declared a global pandemic on March 11th, 2020. At the time of writing this, the COVID-19 claimed more than 440 thousand lives worldwide and led to the global economy and social life into an abyss edge in the living memory. As of now, the confirmed cases in Bangladesh have surpassed 100 thousand and more than 1343 deaths putting startling concern on the policymakers and health professionals; thus, prediction models are necessary to forecast a possible number of cases in the future. To shed light on it, in this paper, we presented data-driven estimation methods, the Long Short-Term Memory (LSTM) networks, and Logistic Curve methods to predict the possible number of COVID-19 cases in Bangladesh for the upcoming months. The results using Logistic Curve suggests that Bangladesh has passed the inflection point on around 28-30 May 2020, a plausible end date to be on the 2nd of January 2021 and it is expected that the total number of infected people to be between 187 thousand to 193 thousand with the assumption that stringent policies are in place. The logistic curve also suggested that Bangladesh would reach peak COVID-19 cases at the end of August with more than 185 thousand total confirmed cases, and around 6000 thousand daily new cases may observe. Our findings recommend that the containment strategies should immediately implement to reduce transmission and epidemic rate of COVID-19 in upcoming days.\n\nHighlightsO_LIAccording to the Logistic curve fitting analysis, the inflection point of the COVID-19 pandemic has recently passed, which was approximately between May 28, 2020, to May 30, 2020.\nC_LIO_LIIt is estimated that the total number of confirmed cases will be around 187-193 thousand at the end of the epidemic. We expect that the actual number will most likely to in between these two values, under the assumption that the current transmission is stable and improved stringent policies will be in place to contain the spread of COVID-19.\nC_LIO_LIThe estimated total death toll will be around 3600-4000 at the end of the epidemic.\nC_LIO_LIThe epidemic of COVID-19 in Bangladesh will be mostly under control by the 2nd of January 2021 if stringent measures are taken immediately.\nC_LI", - "rel_num_authors": 7, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.26.20141077", + "rel_abs": "COVID-19 is a highly infectious disease that is causing havoc to the entire world due to the newly discovered coronavirus SARS-CoV-2. In this study, the dynamics of COVID-19 for India and a few selected states with different demographic structures have been analyzed using a SEIRD epidemiological model. A systematic estimation of the basic reproductive ratio R0 is made for India and for each of the selected states. The study has analysed and predicted the dynamics of the temporal progression of the disease in Indian and the selected eight states: Andhra Pradesh, Chhattisgarh, Delhi, Gujarat, Madhya Pradesh, Maharashtra, Tamil Nadu, and Uttar Pradesh. For India, the most optimistic scenario with respect to duration of the epidemic shows, the peak of infection will appear before mid September with the estimated R0 = 1.917, from the SEIRD model. Further, we show, a Gaussian fit of the daily incidences also indicates the peak will appear around middle of August this year. Our analyses suggest, the earliest dates when the epidemic will start to decline in most states are between Jun-August. For India, the number of infected people at the time of peak will be around 1.6 million including asymptomatic people. If the community transmission is prohibited, then the epidemic will infect not more than 3.1 million people in India. We also compared Indias position in containing the disease with two countries with higher and lower number of infections than India and show the early imposition of lockdown has reduced the number of infected cases significantly.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Al-Ekram Elahee Hridoy", - "author_inst": "Department of Geography and Environmental Studies, University of Chittagong, Chittagong 4331, Bangladesh" - }, - { - "author_name": "Mohammad Naim", - "author_inst": "Department of Electrical and Computer Engineering, North South University, Dhaka 1229, Bangladesh" - }, - { - "author_name": "Nazim Uddin Emon", - "author_inst": "3Department of Pharmacy, Faculty of Science and Engineering, International Islamic University Chittagong, Chittagong 4318, Bangladesh" - }, - { - "author_name": "Imrul Hasan Tipo", - "author_inst": "Department of Biochemistry and Molecular Biology, University of Chittagong, Chittagong 4331, Bangladesh" - }, - { - "author_name": "Safayet Alam", - "author_inst": "Department of Pharmaceutical Chemistry, Faculty of Pharmacy, University of Dhaka, Dhaka 1000, Bangladesh" + "author_name": "Rudra Banerjee", + "author_inst": "Indian Institute of Information Technology (IIIT), Allahabad" }, { - "author_name": "Abdullah Al Mamun", - "author_inst": "Department of Computer Science and Engineering, Chittagong University of Engineering and Technology, Chittagong 4349, Bangladesh" + "author_name": "Srijit Bhattacharjee", + "author_inst": "Indian Institute of Information Technology (IIIT), Allahabad" }, { - "author_name": "Mohammad Safiqul Islam", - "author_inst": "Department of Pharmacy, Faculty of Science, Noakhali Science and Technology University, Noakhali 3814, Bangladesh" + "author_name": "Pritish Kumar Varadwaj", + "author_inst": "Indian Institute of Information Technology (IIIT), Allahabad" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "health informatics" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2020.06.26.20141085", @@ -1335591,29 +1335856,49 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.06.24.20139188", - "rel_title": "COVID-19 Antibody in Thai Community Hospitals", + "rel_doi": "10.1101/2020.06.24.20135673", + "rel_title": "Seroprevalence of SARS-CoV-2 IgG Specific Antibodies among Healthcare Workers in the Northern Metropolitan Area of Barcelona, Spain, after the first pandemic wave", "rel_date": "2020-06-26", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.24.20139188", - "rel_abs": "BackgroundCOVID-19 seroprevalence data has been scarce, especially in less developed countries with a relatively low infection rate.\n\nMethodsA locally developed rapid IgM/IgG test kit was used for screening hospital staff and patients who required procedural treatment or surgery in 52 hospitals in Thailand from April 8 to June 26, 2020. A total of 857 participants were tested--675 were hospital staff and 182 were pre-procedural patients. (Thai Clinical Trials Registry: TCTR20200426002)\n\nResultsOverall, 5.5% of the participants (47 of 857) had positive immunoglobulin M (IgM), 0.2% (2 of 857) had positive immunoglobulin G (IgG) and IgM. Hospitals located in the Central part of Thailand had the highest IgM seroprevalence (11.9%). Preprocedural patients had a higher rate of positive IgM than the hospital staff (12.1% vs. 3.7%). Participants with present upper respiratory tract symptoms had a higher rate of positive IgM than those without (9.6% vs. 4.5%). Three quarters (80.5%, 690 of 857) of the participants were asymptomatic, of which, 31 had positive IgM (4.5%) which consisted of 20 of 566 healthcare workers (3.5%) and 11 of 124 preprocedural patients (8.9%).\n\nConclusionsCOVID-19 antibody test could detect a substantial number of potential silent spreaders in Thai community hospitals. Antibody testing should be encouraged for mass screening, especially in asymptomatic individuals.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.24.20135673", + "rel_abs": "BackgroundThe rapid spread of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) around the world has caused a global pandemic, infecting millions of individuals worldwide, with an unprecedented impact in health care systems worldwide. Healthcare workers are one of the risk groups that need to be well characterized due to their strategic role in the management of patients, presently and in prevention of healthcare needs for future outbreaks. This study presents the results of the first SARS-CoV-2 seroprevalence study in the Northern Metropolitan Area of Barcelona, Spain.\n\nMethodsIgG SARS-CoV2 antibodies were analyzed in serum samples from 7563 healthcare workers of the Northern Metropolitan Area of Barcelona taken during the pandemia (from May 4th to May 22nd, 2020) by chemiluminescence assays.\n\nResultsA total of 779 of 7563 (10.3%) healthcare workers had detectable anti-SARS-CoV-2 IgG (specific for either S1/S2 or N antigens). No significant differences were observed between those working at primary care or at the reference hospital.\n\nInterestingly, in 29 (8.53%) of the previously confirmed positive reverse-transcriptase polymerase chain reaction (rRT-PCR) patients SARS-CoV-2 IgG (S1/S2 or recombinant N antigen) were negative.\n\nConclusionSeroprevalence of anti-SARS-CoV-2 IgG in the healthcare workers of the Nord Metropolitan Area of Barcelona was significantly increased in comparison with the general population in the same geographical area. These results give us an important insight for a better understanding of SARS-CoV-2 epidemiology, in a collective that is essential for the response against this pandemic.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Tanawin Nopsopon", - "author_inst": "Chulalongkorn University Faculty of Medicine" + "author_name": "Gema Fern\u00e1ndez-Rivas", + "author_inst": "Hospital Germans Trias. Gerencia Territorial Metropolitana Nord. Institut Catal\u00e0 de la Salut." }, { - "author_name": "Krit Pongpirul", - "author_inst": "Chulalongkorn University Faculty of Medicine" + "author_name": "Biviana Quirant-S\u00e1nchez", + "author_inst": "Hospital Germans Trias. Gerencia Territorial Metropolitana Nord. Institut Catal\u00e0 de la Salut." }, { - "author_name": "Korn Chotirosniramit", - "author_inst": "Chulalongkorn University Faculty of Medicine" + "author_name": "Vicky Gonz\u00e1lez", + "author_inst": "Hospital Germans Trias. Gerencia Territorial Metropolitana Nord. Institut Catal\u00e0 de la Salut." }, { - "author_name": "Narin Hiransuthikul", - "author_inst": "Chulalongkorn University Faculty of Medicine" + "author_name": "Maria Dolad\u00e9", + "author_inst": "Hospital Germans Trias. Gerencia Territorial Metropolitana Nord. Institut Catal\u00e0 de la Salut." + }, + { + "author_name": "Eva Martinez-Caceres", + "author_inst": "Hospital Germans Trias. Gerencia Territorial Metropolitana Nord. Institut Catal\u00e0 de la Salut." + }, + { + "author_name": "Monica Pi\u00f1a", + "author_inst": "Gerencia Territorial Metropolitana Nord. Institut Catal\u00e0 de la Salut." + }, + { + "author_name": "Joan Matllo", + "author_inst": "Hospital Germans Trias. Gerencia Territorial Metropolitana Nord. Institut Catal\u00e0 de la Salut." + }, + { + "author_name": "Oriol Estrada", + "author_inst": "Gerencia Territorial Metropolitana Nord. Institut Catal\u00e0 de la Salut." + }, + { + "author_name": "Ignacio Blanco", + "author_inst": "Hospital Germans Trias. Gerencia Territorial Metropolitana Nord. Institut Catal\u00e0 de la Salut." } ], "version": "1", @@ -1337041,33 +1337326,41 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.06.25.20140434", - "rel_title": "Effects of social distancing on the spreading of COVID-19 inferred from mobile phone data", + "rel_doi": "10.1101/2020.06.24.20139444", + "rel_title": "Modelling lockdown-induced 2nd COVID waves in France", "rel_date": "2020-06-26", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.25.20140434", - "rel_abs": "A better understanding of how the COVID-19 epidemic responds to social distancing efforts is required for the control of future outbreaks and to calibrate partial lock-downs. We present quantitative relationships between key parameters characterizing the COVID-19 epidemiology and social distancing efforts of nine selected European countries. Epidemiological parameters were extracted from the number of daily deaths data, while mitigation efforts are estimated from mobile phone tracking data. The decrease of the basic reproductive number (R0) as well as the duration of the initial exponential expansion phase of the epidemic strongly correlates with the magnitude of mobility reduction. Utilizing these relationships we decipher the relative impact of the timing and the extent of social distancing on the total death burden of the epidemic.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.24.20139444", + "rel_abs": "As with the Spanish Flu a century ago, authorities have responded to the current COVID-19 pandemic with extraordinary public health measures. In particular, lockdown and related social distancing policies are motivated in some countries by the need to slow virus propagation--so that the primary wave of patients suffering from severe forms of COVID infection do not exceed the capacity of intensive care units. But unlocking poses a critical issue because relaxing social distancing may, in principle, generate secondary waves. Ironically however, the dynamic repertoire of established epidemiological models that support this kind of reasoning is limited to single epidemic outbreaks. In turn, predictions regarding secondary waves are tautologically derived from imposing assumptions about changes in the so-called \"effective reproduction number\". In this work, we depart from this approach and extend the LIST (Location-Infection-Symptom-Testing) model of the COVID pandemic with realistic nonlinear feedback mechanisms that under certain conditions, cause lockdown-induced secondary outbreaks. The original LIST model captures adaptive social distancing, i.e. the transient reduction of the number of person-to-person contacts (and hence the rate of virus transmission), as a societal response to salient public health risks. Here, we consider the possibility that such pruning of socio-geographical networks may also temporarily isolate subsets of local populations from the virus. Crucially however, such unreachable people will become susceptible again when adaptive social distancing relaxes and the density of contacts within socio-geographical networks increases again. Taken together, adaptive social distancing and network unreachability thus close a nonlinear feedback loop that endows the LIST model with a mechanism that can generate autonomous (lockdown-induced) secondary waves. However, whether and how secondary waves arise depend upon the interaction with other nonlinear mechanisms that capture other forms of transmission heterogeneity. We apply the ensuing LIST model to numerical simulations and exhaustive analyses of regional French epidemiological data. In brief, we find evidence for this kind of nonlinear feedback mechanism in the empirical dynamics of the pandemic in France. However, rather than generating catastrophic secondary outbreaks (as is typically assumed), the model predicts that the impact of lockdown-induced variations in population susceptibility and transmission may eventually reduce to a steady-state endemic equilibrium with a low but stable infection rate.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Hamid Khataee", - "author_inst": "The University of Queensland" + "author_name": "Jean Daunizeau", + "author_inst": "INSERM, France" }, { - "author_name": "Istvan Scheuring", - "author_inst": "Hungarian Academy of Sciences" + "author_name": "Rosalyn Moran", + "author_inst": "King's College, UK" }, { - "author_name": "Andras Czirok", - "author_inst": "University of Kansas Medical Center" + "author_name": "Jules Brochard", + "author_inst": "Paris Brain Institute, France" }, { - "author_name": "Zoltan Neufeld", - "author_inst": "University of Queensland" + "author_name": "Jeremie Mattout", + "author_inst": "INSERM, France" + }, + { + "author_name": "Richard Frackowiak", + "author_inst": "EPFL, Switzerland" + }, + { + "author_name": "Karl Friston", + "author_inst": "UCL, UK" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1338627,23 +1338920,23 @@ "category": "molecular biology" }, { - "rel_doi": "10.1101/2020.06.25.20139956", - "rel_title": "COVID-19 Confirmed Cases and Fatalities in 883 U.S. Counties with a Population of 50,000 or More: Predictions Based on Social, Economic, Demographic Factors and Shutdown Days", + "rel_doi": "10.1101/2020.06.26.173146", + "rel_title": "Air and surface measurements of SARS-CoV-2 inside a bus during normal operation", "rel_date": "2020-06-26", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.25.20139956", - "rel_abs": "The spread of the COVID-19 virus is highly variable among U.S. counties. Seventeen factors known or thought to be related to spread of the COVID-19 virus were studied by Poisson regression analysis of confirmed cases and deaths in 883 U.S. counties with a population of 50,000 or more as of May 31, 2020. With little exception, each factor was predictive of incidence and mortality. The regression equation can be used to identify priority locations for preventive efforts and preparation for medical care caseloads when prevention is unsuccessful. Based on the correlation of cases and deaths to days since stay-at-home orders were issued, the orders reduced the cases about 48 percent and deaths about 50 percent. Focusing preventive efforts on the more vulnerable counties may be more effective and less economically damaging than statewide shutdowns.", + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2020.06.26.173146", + "rel_abs": "Transmission pathways of SARS-CoV-2 are through aerosol, droplet and touching infected material. Indoor locations are more likely environments for the diffusion of the virus contagion among people, but direct detection of SARS-CoV-2 in air or on surfaces is quite sparse, especially regarding public transport. In fact, an important demand is to know how and if it is safe to use them. To understand the possible spreading of COVID-19 inside a city bus during normal operation and the effectiveness of the protective measures adopted for transportation, we analysed the air and the surfaces most usually touched by passengers. The measurements were carried out across the last week of the lockdown and the first week when gradually all the travel restrictions were removed.", "rel_num_authors": 1, "rel_authors": [ { - "author_name": "Leon S. Robertson", - "author_inst": "Yale University" + "author_name": "Claudio Ucciferri", + "author_inst": "Ospedale Civile Santissima Annunziata" } ], "version": "1", - "license": "cc_by_nc_nd", - "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "license": "cc_by", + "type": "new results", + "category": "biochemistry" }, { "rel_doi": "10.1101/2020.06.26.173203", @@ -1340056,95 +1340349,107 @@ "category": "nephrology" }, { - "rel_doi": "10.1101/2020.06.24.20138859", - "rel_title": "Using Machine Learning of Clinical Data to Diagnose COVID-19", + "rel_doi": "10.1101/2020.06.24.167049", + "rel_title": "SARS-CoV-2 infection and replication in human fetal and pediatric gastric organoids", "rel_date": "2020-06-24", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.24.20138859", - "rel_abs": "The recent pandemic of Coronavirus Disease 2019 (COVID-19) has placed severe stress on healthcare systems worldwide, which is amplified by the critical shortage of COVID-19 tests. In this study, we propose to generate a more accurate diagnosis model of COVID-19 based on patient symptoms and routine test results by applying machine learning to reanalyzing COVID-19 data from 151 published studies. We aimed to investigate correlations between clinical variables, cluster COVID-19 patients into subtypes, and generate a computational classification model for discriminating between COVID -19 patients and influenza patients based on clinical variables alone. We discovered several novel associations between clinical variables, including correlations between being male and having higher levels of serum lymphocytes and neutrophils. We found that COVID-19 patients could be clustered into subtypes based on serum levels of immune cells, gender, and reported symptoms. Finally, we trained an XGBoost model to achieve a sensitivity of 92.5% and a specificity of 97.9% in discriminating COVID-19 patients from influenza patients. We demonstrated that computational methods trained on large clinical datasets could yield ever more accurate COVID-19 diagnostic models to mitigate the impact of lack of testing. We also presented previously unknown COVID-19 clinical variable correlations and clinical subgroups.", - "rel_num_authors": 19, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2020.06.24.167049", + "rel_abs": "Coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is a global public health emergency. COVID-19 typically manifests as a respiratory illness but an increasing number of clinical reports describe gastrointestinal (GI) symptoms. This is particularly true in children in whom GI symptoms are frequent and viral shedding outlasts viral clearance from the respiratory system. By contrast, fetuses seem to be rarely affected by COVID-19, although the virus has been detected in placentas of affected women. These observations raise the question of whether the virus can infect and replicate within the stomach once ingested. Moreover, it is not yet clear whether active replication of SARS-CoV-2 is possible in the stomach of children or in fetuses at different developmental stages. Here we show the novel derivation of fetal gastric organoids from 8-21 post-conception week (PCW) fetuses, and from pediatric biopsies, to be used as an in vitro model for SARS-CoV-2 gastric infection. Gastric organoids recapitulate human stomach with linear increase of gastric mucin 5AC along developmental stages, and expression of gastric markers pepsinogen, somatostatin, gastrin and chromogranin A. In order to investigate SARS-CoV-2 infection with minimal perturbation and under steady-state conditions, we induced a reversed polarity in the gastric organoids (RP-GOs) in suspension. In this condition of exposed apical polarity, the virus can easily access viral receptor angiotensin-converting enzyme 2 (ACE2). The pediatric RP-GOs are fully susceptible to infection with SARS-CoV-2, where viral nucleoprotein is expressed in cells undergoing programmed cell death, while the efficiency of infection is significantly lower in fetal organoids. The RP-GOs derived from pediatric patients show sustained robust viral replication of SARS-CoV-2, compared with organoids derived from fetal stomachs. Transcriptomic analysis shows a moderate innate antiviral response and the lack of differentially expressed genes belonging to the interferon family. Collectively, we established the first expandable human gastric organoid culture across fetal developmental stages, and we support the hypothesis that fetal tissue seems to be less susceptible to SARS-CoV-2 infection, especially in early stages of development. However, the virus can efficiently infect gastric epithelium in pediatric patients, suggesting that the stomach might have an active role in fecal-oral transmission of SARS-CoV-2.", + "rel_num_authors": 22, "rel_authors": [ { - "author_name": "Wei Tse Li", - "author_inst": "UC San Diego" + "author_name": "Giovanni Giuseppe Giobbe", + "author_inst": "University College London - GOS Institute of Child Health" }, { - "author_name": "Jiayan Ma", - "author_inst": "UC San Diego" + "author_name": "Francesco Bonfante", + "author_inst": "izsvenezie" }, { - "author_name": "Neil Shende", - "author_inst": "UC San Diego" + "author_name": "Elisa Zambaiti", + "author_inst": "University College London - GOS Institute of Child Health" }, { - "author_name": "Grant Castaneda", - "author_inst": "UC San Diego" + "author_name": "Onelia Gagliano", + "author_inst": "VIMM" }, { - "author_name": "Jaideep Chakladar", - "author_inst": "UC San Diego" + "author_name": "Brendan C. Jones", + "author_inst": "University College London - GOS Institute of Child Health" }, { - "author_name": "Joseph C. Tsai", - "author_inst": "UC San Diego" + "author_name": "Camilla Luni", + "author_inst": "ShanghaiTech University" }, { - "author_name": "Lauren Apostol", - "author_inst": "UC San Diego" + "author_name": "Cecilia Laterza", + "author_inst": "VIMM" }, { - "author_name": "Christine O. Honda", - "author_inst": "UC San Diego" + "author_name": "Silvia Perin", + "author_inst": "University College London - GOS Institute of Child Health" }, { - "author_name": "Jingyue Xu", - "author_inst": "UC San Diego" + "author_name": "Hannah T. Stuart", + "author_inst": "VIMM" }, { - "author_name": "Lindsay M. Wong", - "author_inst": "UC San Diego" + "author_name": "Matteo Pagliari", + "author_inst": "izsvenezie.it" }, { - "author_name": "Tianyi Zhang", - "author_inst": "UC San Diego" + "author_name": "Alessio Bortolami", + "author_inst": "izsvenezie" }, { - "author_name": "Abby Lee", - "author_inst": "UC San Diego" + "author_name": "Eva Mazzetto", + "author_inst": "izsvenezie" }, { - "author_name": "Aditi Gnanasekar", - "author_inst": "UC San Diego" + "author_name": "Anna Manfredi", + "author_inst": "TIGEM" }, { - "author_name": "Thomas K. Honda", - "author_inst": "UC San Diego" + "author_name": "Chiara Colantuono", + "author_inst": "TIGEM" }, { - "author_name": "Selena Z. Kuo", - "author_inst": "Columbia University Medical Center" + "author_name": "Lucio Di Filippo", + "author_inst": "Next Generation Diagnostic srl" }, { - "author_name": "Michael Andrew Yu", - "author_inst": "Emory University School of Medicine" + "author_name": "Alessandro Filippo Pellegata", + "author_inst": "University College London - GOS Institute of Child Health" + }, + { + "author_name": "Vivian S.W. Li", + "author_inst": "The Francis Crick Institute" }, { - "author_name": "Eric Y. Chang", - "author_inst": "VA San Diego" + "author_name": "Simon Eaton", + "author_inst": "University College London - GOS Institute of Child Health" }, { - "author_name": "Mahadevan R. Rajasekaran", - "author_inst": "VA San Diego" + "author_name": "Nikhil Thapar", + "author_inst": "University College London - GOS Institute of Child Health" }, { - "author_name": "Weg M. Ongkeko", - "author_inst": "UC San Diego" + "author_name": "Davide Cacchiarelli", + "author_inst": "TIGEM" + }, + { + "author_name": "Nicola Elvassore", + "author_inst": "University College London - GOS Institute of Child Health" + }, + { + "author_name": "Paolo De Coppi", + "author_inst": "University College London - GOS Institute of Child Health" } ], "version": "1", "license": "cc_no", - "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "type": "new results", + "category": "cell biology" }, { "rel_doi": "10.1101/2020.06.24.162156", @@ -1341529,47 +1341834,43 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.06.23.20137455", - "rel_title": "Sensitivity of different RT-qPCR solutions for SARS-CoV-2 detection", + "rel_doi": "10.1101/2020.06.24.20138867", + "rel_title": "Associations of ambient air pollutants and meteorological factors with COVID-19 transmission in 31 Chinese provinces: A time-series study", "rel_date": "2020-06-24", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.23.20137455", - "rel_abs": "ObjectiveThe ongoing COVID-19 pandemic continues imposing a demand for diagnostic screening. In anticipation that the recurrence of outbreaks and the measures for lifting the lockdown worldwide may cause supply chain issues over the coming months, we assessed the sensitivity of a number of one-step retrotranscription and quantitative PCR (RT-qPCR) solutions to detect SARS-CoV-2.\n\nMethodsWe evaluated six different RT-qPCR alternatives for SARS-CoV-2/COVID-19 diagnosis based on standard RNA extractions. That of best sensitivity was also assessed with direct nasopharyngeal swab viral transmission medium (VTM) heating, overcoming the RNA extraction step.\n\nResultsWe found a wide variability in the sensitivity of RT-qPCR solutions that associated with a range of false negatives from as low as 2% (0.3-7.9%) to as much as 39.8% (30.2-50.2). Direct preheating of VTM combined with the best solution provided a sensitivity of 72.5% (62.5-81.0), in the range of some of the solutions based on standard RNA extractions.\n\nConclusionsWe evidenced sensitivity limitations of currently used RT-qPCR solutions. Our results will help to calibrate the impact of false negative diagnoses of COVID-19, and to detect and control new SARS-CoV-2 outbreaks and community transmissions.", - "rel_num_authors": 7, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.24.20138867", + "rel_abs": "BackgroundEvidence regarding the effects of ambient air pollutants and meteorological factors on COVID-19 transmission is limited.\n\nObjectivesTo explore the associations of air pollutants and meteorological factors with COVID-19 confirmed cases across 31 Chinese provinces during the outbreak period.\n\nMethodsThe number of COVID-19 confirmed cases, air pollutant concentrations and meteorological factors in 31 Chinese provinces from January 25 to February 29, 2020 were extracted from authoritative electronic databases. The associations were estimated for a single-day lag (lag0-lag6) as well as moving averages lag (lag01-lag05) using generalized additive mixed models (GAMMs), adjusted for time trends, day of the week, holidays and meteorological variables. Region-specific analyses and meta-analysis were conducted in five selected regions with diverse air pollution levels and weather conditions. Nonlinear exposure-response analyses were performed.\n\nResultsWe examined 77,578 COVID-19 confirmed cases across 31 Chinese provinces during the study period. An increase of each interquartile range in PM2.5, PM10, SO2, NO2, O3 and CO at lag4 corresponded to 1.40 (1.37-1.43), 1.35 (1.32-1.37), 1.01 (1.00-1.02), 1.08 (1.07-1.10), 1.28 (1.27-1.29) and 1.26 (1.24-1.28) odds ratios (ORs) of daily COVID-19 confirmed new cases, respectively. For 1 {degrees}C, 1% and 1 m/s increase in temperature, relative humidity and wind velocity, the ORs were 0.97 (0.97-0.98), 0.96 (0.96-0.97), and 0.94 (0.92-0.95), respectively. The estimates of PM2.5, PM10, NO2 and all meteorological factors remained statistically significant after meta-analysis for the five selected regions. The exposure-response relationships showed that higher concentrations of air pollutants and lower meteorological factors were associated with daily COVID-19 confirmed new cases increasing.\n\nConclusionsHigher air pollutant concentrations and lower temperature, relative humidity and wind velocity may favor COVID-19 transmission. As summer months are arriving in the Northern Hemisphere, the environmental factors and implementation of public health control measures may play an optimistic role in controlling COVID-19 epidemic.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Julia Alcoba-Florez", - "author_inst": "Servicio de Microbiologia, Hospital Universitario N. S. de Candelaria" - }, - { - "author_name": "Helena Gil-Campesino", - "author_inst": "Servicio de Microbiologia, Hospital Universitario N. S. de Candelaria" + "author_name": "Han Cao", + "author_inst": "Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, and Beijing Municipal Key Laboratory of Clinical Epidemio" }, { - "author_name": "Diego Garcia-Martinez de Artola", - "author_inst": "Servicio de Microbiologia, Hospital Universitario N. S. de Candelaria" + "author_name": "Bingxiao Li", + "author_inst": "Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, and Beijing Municipal Key Laboratory of Clinical Epidemio" }, { - "author_name": "Rafaela Gonzalez-Montelongo", - "author_inst": "Genomics Division, Instituto Tecnologico y de Energias Renovables" + "author_name": "Tianlun Gu", + "author_inst": "Department of Customer Advisory, SAS institute, Inc., Beijing, China." }, { - "author_name": "Agustin Valenzuela-Fernandez", - "author_inst": "Laboratorio de Inmunologia Celular y Viral, Unidad de Farmacologia, Facultad de Medicina & IUETSPC, Universidad de La Laguna" + "author_name": "Xiaohui Liu", + "author_inst": "Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, and Beijing Municipal Key Laboratory of Clinical Epidemio" }, { - "author_name": "Laura Ciuffreda", - "author_inst": "Research Unit, Hospital Universitario N. S. de Candelaria" + "author_name": "Kai Meng", + "author_inst": "Department of Health Management and Policy, School of Public Health, Capital Medical University, Beijing, China." }, { - "author_name": "Carlos Flores", - "author_inst": "Research Unit, Hospital Universitario N.S. de Candelaria" + "author_name": "Ling ZHANG", + "author_inst": "Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, and Beijing Municipal Key Laboratory of Clinical Epidemio" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2020.06.24.20138800", @@ -1342903,39 +1343204,63 @@ "category": "pediatrics" }, { - "rel_doi": "10.1101/2020.06.21.20137000", - "rel_title": "Health Condition and Test Availability as Predictors of Adults' Mental Health during the COVID-19 Pandemic", + "rel_doi": "10.1101/2020.06.21.20136820", + "rel_title": "Mental health and health behaviours before and during the COVID-19 lockdown: Longitudinal analyses of the UK Household Longitudinal Study", "rel_date": "2020-06-23", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.21.20137000", - "rel_abs": "BackgroundResearch identifying adults mental health during the COVID-19 pandemic relies solely on demographic predictors without examining adults health status during the COVID-19 pandemic as a potential predictor.\n\nMethodsAn online survey of 669 adults in Malaysia was conducted during May 2-8, 2020, six weeks after a Movement Control Order (MCO) was issued.\n\nFindingsAdults health condition had curvilinear relationships (horizontally reversed J-shaped) with insomnia, anxiety, depression and distress. Reported test availability for COVID-19 (from \"strongly disagree\" to \"strongly agree\") also had curvilinear relationships (horizontally reversed J-shaped) with anxiety and depression. Younger adults reported worse mental health, but people from various religions and ethnic groups did not differ significantly in reported mental health.\n\nInterpretationAdults with worse health conditions had more mental health problems, especially adults at the lower end of the health spectrum. Test availability negatively predicted anxiety and depression, especially for adults experiencing poor COVID-19 test availability. The significant predictions of health condition and COVID-19 test availability suggest a new direction for the literature to identify psychiatric risk factors directly from health related variables during a pandemic.\n\nFundingTsinghua University-INDITEX Sustainable Development Fund (Project No. TISD201904).", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.21.20136820", + "rel_abs": "BackgroundThere are concerns that COVID-19 mitigation measures, including the \"lockdown\", may have unintended health consequences. We examined trends in mental health and health behaviours in the UK before and during the initial phase of the COVID-19 lockdown and differences across population subgroups.\n\nMethodsRepeated cross-sectional and longitudinal analysis of the UK Household Longitudinal Study, including representative samples of adults (aged 18+) interviewed in four survey waves between 2015 and 2020 (n=48,426). 9,748 adults had complete data for longitudinal analyses. Outcomes included psychological distress (General Health Questionnaire-12 (GHQ)), loneliness, current cigarette smoking, use of e-cigarettes and alcohol consumption. Cross-sectional prevalence estimates were calculated and multilevel Poisson regression assessed associations between time period and the outcomes of interest, as well as differential associations by age, gender, education level and ethnicity.\n\nResultsPsychological distress increased one month into lockdown with the prevalence rising from 19.4% (95% CI 18.7%-20.0%) in 2017-19 to 30.3% (95% CI 29.1%-31.6%) in April 2020 (RR=1.3, 95% CI: 1.1,1.4). Groups most adversely affected included women, young adults, people from an Asian background and those who were degree educated. Loneliness remained stable overall (RR=0.9, 95% CI: 0.6,1.5). Smoking declined (RR=0.9, 95% CI=0.8,1.0) and the proportion of people drinking four or more times per week increased (RR=1.4, 95% CI: 1.3,1.5), as did binge drinking (RR=1.5, 95% CI: 1.3,1.7).\n\nConclusionsPsychological distress increased one month into lockdown, particularly among women and young adults. Smoking declined, but adverse alcohol use generally increased. Effective measures are required to mitigate adverse impacts on health.\n\nO_LSTWhat is already known on this topicC_LSTO_LICountries around the world have implemented radical COVID-19 lockdown measures, with concerns that these may have unintended consequences for a broad range of health outcomes.\nC_LIO_LIEvidence on the impact of lockdown measures on mental health and health-related behaviours remains limited.\nC_LI\n\nO_LSTWhat this study addsC_LSTO_LIIn the UK, psychological distress markedly increased during lockdown, with women particularly adversely affected.\nC_LIO_LICigarette smoking fell, but adverse drinking behaviour generally increased.\nC_LI", + "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Huiyang Dai", - "author_inst": "Tsinghua University" + "author_name": "Claire L Niedzwiedz", + "author_inst": "University of Glasgow" }, { - "author_name": "Stephen X. Zhang", - "author_inst": "University of Adelaide" + "author_name": "Michael Green", + "author_inst": "University of Glasgow" }, { - "author_name": "Kim Hoe Looi", - "author_inst": "Xiamen University - Malaysia" + "author_name": "Michaela Benzeval", + "author_inst": "University of Essex" }, { - "author_name": "Rui Su", - "author_inst": "Xiamen University - Malaysia" + "author_name": "Desmond Campbell", + "author_inst": "University of Glasgow" }, { - "author_name": "Jizhen Li", - "author_inst": "Tsinghua Univerisity" + "author_name": "Peter Craig", + "author_inst": "University of Glasgow" + }, + { + "author_name": "Evangelia Demou", + "author_inst": "University of Glasgow" + }, + { + "author_name": "Alastair H Leyland", + "author_inst": "University of Glasgow" + }, + { + "author_name": "Anna Pearce", + "author_inst": "University of Glasgow" + }, + { + "author_name": "Rachel M Thomson", + "author_inst": "University of Glasgow" + }, + { + "author_name": "Elise Whitley", + "author_inst": "University of Glasgow" + }, + { + "author_name": "Srinivasa Vittal Katikireddi", + "author_inst": "University of Glasgow" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "psychiatry and clinical psychology" + "category": "public and global health" }, { "rel_doi": "10.1101/2020.06.22.20137075", @@ -1344421,37 +1344746,21 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.06.23.20138099", - "rel_title": "Age-structured non-pharmaceutical interventions for optimal control of COVID-19 epidemic", + "rel_doi": "10.1101/2020.06.22.20137810", + "rel_title": "On Dynamical Analysis of the Data-DrivenSIR model (COVID-19 Outbreak in Indonesia)", "rel_date": "2020-06-23", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.23.20138099", - "rel_abs": "In an epidemic, individuals can widely differ in the way they spread the infection, for instance depending on their age or on the number of days they have been infected for. The latter allows to take into account the variation of infectiousness as a function of time since infection. In the absence of pharmaceutical interventions such as a vaccine or treatment, non-pharmaceutical interventions (e.g. social distancing) are of great importance to mitigate the pandemic. We propose a model with a double continuous structure by host age and time since infection. By applying optimal control theory to our age-structured model, we identify a solution minimizing deaths and costs associated with the implementation of the control strategy itself. This strategy depends on the age heterogeneity between individuals and consists in a relatively high isolation intensity over the older populations during a hundred days, followed by a steady decrease in a way that depends on the cost associated to a such control. The isolation of the younger population is weaker and occurs only if the cost associated with the control is relatively low. We show that the optimal control strategy strongly outperforms other strategies such as uniform constant control over the whole populations or over its younger fraction. These results bring new facts the debate about age-based control interventions and open promising avenues of research, for instance of age-based contact tracing.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.22.20137810", + "rel_abs": "An archipelago country such as Indonesia has a different beginning of the outbreak, therefore the management of epidemics not uniform. For this reason, the results in the data of confirmed cases COVID-19 to fluctuate and difficult to predict. We use the data-driven SIR model to analyze the dynamics and behavior of the evolution of the disease. We run the data-driven SIR model gradually and found that there are shifting of the peak and the distance of saturation point. We found that a transmission acceleration of the outbreak occurring in Indonesia where it could be seen from increasing of the time the saturation and the confirmed cases. It is finally argued that a new parameter can be used to guidance the condition when the new normal begins.", + "rel_num_authors": 1, "rel_authors": [ { - "author_name": "Quentin Richard", - "author_inst": "IRD" - }, - { - "author_name": "Samuel Alizon", - "author_inst": "CNRS" - }, - { - "author_name": "Marc Choisy", - "author_inst": "IRD" - }, - { - "author_name": "Mircea T. Sofonea", - "author_inst": "Univ. Montpellier" - }, - { - "author_name": "Ramses Djidjou-Demasse", - "author_inst": "The French National Research Institute for Development (IRD)" + "author_name": "Albert Sulaiman", + "author_inst": "Badan Pengkajian dan Penerapan Teknologi" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1345963,27 +1346272,59 @@ "category": "pathology" }, { - "rel_doi": "10.1101/2020.06.19.20135640", - "rel_title": "On Linear Growth in COVID-19 Cases", + "rel_doi": "10.1101/2020.06.18.20115873", + "rel_title": "Thrombotic microvascular injury is not mediated by thrombotic microangiopathy despite systemic complement activation in Covid-19 patients", "rel_date": "2020-06-22", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.19.20135640", - "rel_abs": "We present an elementary model of COVID-19 propagation that makes explicit the connection between testing strategies and rates of transmission and the linear growth in new cases observed in many parts of the world. An essential feature of the model is that it captures the population-level response to the infection statistics information provided by governments and other organisations. The conclusions from this model have important implications regarding benefits of wide-spread testing for the presence of the virus, something that deserves greater attention.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.18.20115873", + "rel_abs": "Hypoxemia and coagulopathy are common in severe symptomatic patients of coronavirus disease 2019 (COVID-19). Histological evidence shows implication of complement activation and lung injury. We research sign of complement activation and presence of thrombotic microangiopathy in 8 severe patients. Six of them presented moderate elevation of final pathway of complement - sC5b-9 (median value : 350 ng/mL [IQR : 300,5 - 514,95 ng/mL]). Two patients have been autopsied and presence of thrombotic microvascular injury have been found. Interestingly, none the 8 patients had signs of mechanical hemolytic anemia (median value of hemoglobin : 10,5 gr/dL[IQR : 8,1 - 11,9], median value of haptoglobuline 4,49 [IQR 3,55-4,66], none of the patients has schistocyte) and thrombocytopenia (median value: 348000/mL [IQR : 266 000 - 401 000). Finally, all 8 patients had elevated d-dimer (median value : 2226 {micro}gr/l [IQR : 1493 - 2362]) and soluble fibrin monomer complex (median value : 8.5 mg/mL, IQR[<6 - 10.6]). In summary, this study show moderate activation of complement and coagulation with presence of thrombotic microvascular injury in patients with severe COVID-19 without evidence of systemic thrombotic microangiopathy.\n\nKey pointsO_LISevere covid-19 patients show moderate elevation of final activation of complement\nC_LIO_LINo sign of Thrombotic microangiopathy is found in severe covid-19 patients\nC_LI", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Michael Grinfeld", - "author_inst": "University of Strathclyde" + "author_name": "Adrien De Voeght", + "author_inst": "University Hospital of Liege" }, { - "author_name": "Paul A Mulheran", - "author_inst": "University of Strathclyde" + "author_name": "Doriane Calmes", + "author_inst": "University Hospital of Liege" + }, + { + "author_name": "Floran Beck", + "author_inst": "University Hospital of Liege" + }, + { + "author_name": "Jean-Baptiste Sylvestre", + "author_inst": "University Hospital of Liege" + }, + { + "author_name": "Philippe Delvenne", + "author_inst": "University Hospital of Liege" + }, + { + "author_name": "Pierre Peters", + "author_inst": "University Hospital of Liege" + }, + { + "author_name": "Gaelle Vertenoeil", + "author_inst": "University Hospital of Liege" + }, + { + "author_name": "Frederic Baron", + "author_inst": "University Hospital of Liege" + }, + { + "author_name": "Nathalie Layios", + "author_inst": "University Hospital of Liege" + }, + { + "author_name": "Jean-Luc Canivet", + "author_inst": "University Hospital of Liege" } ], "version": "1", - "license": "cc_by", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2020.06.21.20129049", @@ -1347321,65 +1347662,33 @@ "category": "genetics" }, { - "rel_doi": "10.1101/2020.06.22.164384", - "rel_title": "Functional characterization of SARS-CoV-2 infection suggests a complex inflammatory response and metabolic alterations", + "rel_doi": "10.1101/2020.06.21.163550", + "rel_title": "Mathematical modeling explains differential SARS CoV-2 kinetics in lung and nasal passages in remdesivir treated rhesus macaques", "rel_date": "2020-06-22", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.06.22.164384", - "rel_abs": "Covid-19, caused by the SARS-CoV-2 virus, has reached the category of a worldwide pandemic. Even though intensive efforts, no effective treatments or a vaccine are available. Molecular characterization of the transcriptional response in Covid-19 patients could be helpful to identify therapeutic targets. In this study, RNAseq data from peripheral blood mononuclear cell samples from Covid-19 patients and healthy controls was analyzed from a functional point of view using probabilistic graphical models. Two networks were built: one based on genes differentially expressed between healthy and infected individuals and another one based on the 2,000 most variable genes in terms of expression in order to make a functional characterization. In the network based on differentially expressed genes, two inflammatory response nodes with different tendencies were identified, one related to cytokines and chemokines, and another one related to bacterial infections. In addition, differences in metabolism, which were studied in depth using Flux Balance Analysis, were identified. SARS-CoV2-infection caused alterations in glutamate, methionine and cysteine, and tetrahydrobiopterin metabolism. In the network based on 2,000 most variable genes, also two inflammatory nodes with different tendencies between healthy individuals and patients were identified. Similar to the other network, one was related to cytokines and chemokines. However, the other one, lower in Covid-19 patients, was related to allergic processes and self-regulation of the immune response. Also, we identified a decrease in T cell node activity and an increase in cell division node activity. In the current absence of treatments for these patients, functional characterization of the transcriptional response to SARS-CoV-2 infection could be helpful to define targetable processes. Therefore, these results may be relevant to propose new treatments.", - "rel_num_authors": 12, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.06.21.163550", + "rel_abs": "Remdesivir was recently demonstrated to decrease recovery time in hospitalized patients with SARS-CoV-2 infection. In rhesus macaques, early initiation of remdesivir therapy prevented pneumonia and lowered viral loads in the lung, but viral loads increased in the nasal passages five days after therapy. We developed mathematical models to explain these results. We identified that 1) drug potency is slightly higher in nasal passages than in lungs, 2) viral load decrease in lungs relative to nasal passages during therapy because of infection-dependent generation of refractory cells in the lung, 3) incomplete drug potency in the lung that decreases viral loads even slightly may allow substantially less lung damage, and 4) increases in nasal viral load may occur due to a slight blunting of peak viral load and subsequent decrease of the intensity of the innate immune response, as well as a lack of refractory cells. We also hypothesize that direct inoculation of the trachea in rhesus macaques may not recapitulate natural infection as lung damage occurs more abruptly in this model than in human infection. We demonstrate with sensitivity analysis that a drug with higher potency could completely suppress viral replication and lower viral loads abruptly in the nasal passages as well as the lung.\n\nOne Sentence SummaryWe developed a mathematical model to explain why remdesivir has a greater antiviral effect on SARS CoV-2 in lung versus nasal passages in rhesus macaques.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Lucia Trilla-Fuertes", - "author_inst": "Biomedica Molecular Medicine SL." - }, - { - "author_name": "Ricardo Ramos-Ruiz", - "author_inst": "Parque Cientifico de Madrid" - }, - { - "author_name": "Natalia Blanca-Lopez", - "author_inst": "Hospital Infanta Leonor" - }, - { - "author_name": "Elena Lopez-Camacho", - "author_inst": "Biomedica Molecular Medicine SL" - }, - { - "author_name": "Laura Martin-Pedraza", - "author_inst": "Hospital Infanta Leonor" - }, - { - "author_name": "Pablo Ryan Murua", - "author_inst": "Hospital Infanta Leonor" - }, - { - "author_name": "Mariana Diaz-Almiron", - "author_inst": "Hospital Universitario La Paz" - }, - { - "author_name": "Carlos Llorens", - "author_inst": "Biotechvana, Parc Cientific, Universitat de Valencia" - }, - { - "author_name": "Toni Gabaldon", - "author_inst": "BSC-IRB" + "author_name": "Ashish Goyal", + "author_inst": "Fred Hutchinson Cancer Research Center" }, { - "author_name": "Andres Moya", - "author_inst": "Universitat de Valencia" + "author_name": "Elizabeth R Duke", + "author_inst": "Fred Hutchinson Cancer Research Center" }, { - "author_name": "Juan Angel Fresno", - "author_inst": "Hospital Universitario La Paz" + "author_name": "Erwing Fabian Cardozo-Ojeda", + "author_inst": "Fred Hutchinson Cancer Research Center" }, { - "author_name": "Angelo Gamez-Pozo", - "author_inst": "Hospital Universitaio La Paz" + "author_name": "Joshua T Schiffer", + "author_inst": "Fred Hutchinson Cancer Research Center" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "new results", "category": "microbiology" }, @@ -1349250,85 +1349559,45 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.06.20.20136234", - "rel_title": "Belgian Covid-19 Mortality, Excess Deaths, Number of Deaths per Million, and Infection Fatality Rates (8 March - 9 May 2020)", + "rel_doi": "10.1101/2020.06.19.20136069", + "rel_title": "Global years of life lost to COVID-19", "rel_date": "2020-06-20", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.20.20136234", - "rel_abs": "ObjectiveScrutiny of COVID-19 mortality in Belgium over the period 8 March - 9 May 2020 (Weeks 11-19), using number of deaths per million, infection fatality rates, and the relation between COVID-19 mortality and excess death rates.\n\nDataPublicly available COVID-19 mortality (2020); overall mortality (2009 - 2020) data in Belgium and demographic data on the Belgian population; data on the nursing home population; results of repeated sero-prevalence surveys in March-April 2020.\n\nStatistical methodsReweighing, missing-data handling, rate estimation, visualization.\n\nResultsBelgium has virtually no discrepancy between COVID-19 reported mortality (confirmed and possible cases) and excess mortality. There is a sharp excess death peak over the study period; the total number of excess deaths makes April 2020 the deadliest month of April since WWII, with excess deaths far larger than in early 2017 or 2018, even though influenza-induced January 1951 and February 1960 number of excess deaths were similar in magnitude. Using various sero-prevalence estimates, infection fatality rates (IFRs; fraction of deaths among infected cases) are estimated at 0.38 - 0.73% for males and 0.20 - 0.39% for females in the non-nursing home population (non-NHP), and at 0.79 - 1.52% for males and 0.88 - 1.31% for females in the entire population. Estimates for the NHP range from 38 to 73% for males and over 22 to 37% for females. The IFRs rise from nearly 0% under 45 years, to 4.3% and 13.2% for males in the non-NHP and the general population, respectively, and to 1.5% and 11.1% for females in the non-NHP and general population, respectively.\n\nThe IFR and number of deaths per million is strongly influenced by extensive reporting and the fact that 66.0% of the deaths concerned NH residents. At 764 (our re-estimation of the figure 735, presented by \"Our World in Data\"), the number of COVID-19 deaths per million led the international ranking on May 9, 2020, but drops to 262 in the non-NHP. The NHP is very specific: age-related increased risk; highly prevalent comorbidities that, while non-fatal in themselves, exacerbate COVID-19; larger collective households that share inadvertent vectors such as caregivers and favor clustered outbreaks; initial lack of protective equipment, etc. High-quality health care countries have a relatively older but also more frail population [1], which is likely to contribute to this result.\n\nThumbnail summary: What this paper addsCOVID-19 mortality and its relation to excess deaths, case fatality rates (CFRs), infection fatality rates (IFRs), and number of deaths per million are constantly being reported for a large number of countries globally.\n\nThis study adds detailed insight in the Belgian situation over the period 8 March - 9 May 2020 (Week 11-Week 19).\n\nBelgium has virtually no discrepancy between COVID-19 reported mortality (confirmed and possible cases) and excess mortality. This, combined with a high fraction of possible cases that is COVID-19 related [2] provides a basis for using all COVID-19 cases and thus not only the confirmed ones, in IFR estimation.\n\nAgainst each of the years from 2009 and 2019 and the average thereof, there is a strong excess death peak in 2020, which nearly entirely coincides with confirmed plus possible COVID-19 cases. The excess death/COVID-19 peak rises well above seasonal fluctuations seen in the first trimester during the most recent decade (induced in part by seasonal influenza). In the second week of April 2020, twice as many people died than in the corresponding week of the reference year. April 2020 was the deadliest month of April since WWII, although January 1951 and February 1960 saw similar figures. More recently, in the winter of 2017-2018, there was 4.6% excess mortality in Belgium (70,215 actual deaths; 3093 more than the Be-MOMO-model prediction). In the winter of 2016-2017, there was an excess of 3284 deaths (4.9% excess mortality) https://epistat.wiv-isp.be/docs/momo/Be-MOMO%20winter%202017-18%20report_FR.pdf.\n\nAt 764 (our estimate), the number of COVID-19 deaths per million leads the international ranking, but drops sharply to 262 in the non-nursing home population.\n\nCFR is not a good basis for international comparison, except as a tool in estimating global infection fatality rates [2]. These authors used asymptotic models to derive IFR as a limit of CFR. CFR is strongly influenced by testing strategy, and in several studies the delay between case confirmation and deaths is not accounted for. The handling of possible cases is ambiguous at best. We do not consider it here.\n\nBias and precision in estimation of IFR is influenced by difficulties surrounding the estimation of sero-prevalence, such as sensitivity and specificity of the tests used [3], time to IgM and in particular IgG seroconversion [4], and potential selection bias occurring in data from residual sample surveys. A sensitivity analysis is undertaken by augmenting one primary with three auxiliary estimates of sero-prevalence.\n\nBecause in Belgium there is a very close agreement between excess mortality on the one hand and confirmed and possible COVID-19 cases combined on the other, and because an international study [2] suggested that a fraction as high as 0.9 of possible cases could be attributable to COVID-19 [5], it is a reasonable choice to use all COVID-19 cases in IFR estimation. This encompasses a large fraction of deaths occurring in nursing homes. The IFR values obtained align with international values [2]. Using various sero-prevalence estimates, IFRs across all ages are estimated at 0.38 - 0.73% for males and 0.20 - 0.39% for females in the non-nursing home population (non-NHP), and at 0.79 - 1.52% for males and 0.88 - 1.31% for females in the entire population. Estimates for the NHP range from 38 to 73% for males and over 22 to 37% for females. The IFRs rise from nearly 0% under 45 years, to 4.3% and 13.2% for males in the non-NHP and the general population, respectively, and to 1.5% and 11.1% for females in the non-NHP and general population, respectively.\n\nThe IFR is strongly influenced by extensive death cases reporting and the fact that 66.0% of the deaths concerned NH residents. Apart from a strong age-related gradient, also for each age category, IFRs are substantially higher in males than in females Because of these dependencies, IFRs should be considered in an age, gender, and sub-population specific manner. The same proviso is made for the number of deaths per million.\n\nAn important such population is the NHP because of a specific cocktail: age-related increased risk; highly prevalent comorbidities that, while non-fatal in themselves, exacerbate COVID-19; larger collective households that share inadvertent vectors such as caregivers; initial lack of protective equipment, etc. High-quality health care countries have a relatively older but also more frail population [1], which might contribute.", - "rel_num_authors": 17, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.19.20136069", + "rel_abs": "Understanding the mortality impact of COVID-19 requires not only counting the dead, but analyzing how premature the deaths are. We calculate years of life lost (YLL) across 42 countries due to COVID-19 attributable deaths, and also conduct an analysis based on estimated excess deaths. As of June 13th 2020, YLL in heavily affected countries are 2 to 6 times the average seasonal influenza; over two thirds of the YLL result from deaths in ages below 75 and one quarter from deaths below 55; and men have lost 47% more life years than women. The results confirm the large mortality impact of COVID-19 among the elderly. They also call for heightened awareness in devising policies that protect vulnerable demographics losing the largest number of life-years.\n\nOne Sentence SummaryAcross 42 countries, the years of life lost due to COVID-19 are up to 6 times that of the average seasonal flu.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Geert Molenberghs", - "author_inst": "Universiteit Hasselt and KU Leuven" - }, - { - "author_name": "Christel Faes", - "author_inst": "Universiteit Hasselt" - }, - { - "author_name": "Johan Verbeeck", - "author_inst": "Universiteit Hasselt" - }, - { - "author_name": "Patrick Deboosere", - "author_inst": "Vrije Universiteit Brussel" - }, - { - "author_name": "Steven Abrams", - "author_inst": "Universiteit Hasselt and Universiteit Antwerpen" - }, - { - "author_name": "Lander Willem", - "author_inst": "Universiteit Antwerpen" - }, - { - "author_name": "Jan Aerts", - "author_inst": "Universiteit Hasselt" - }, - { - "author_name": "Heidi Theeten", - "author_inst": "Universiteit Antwerpen" - }, - { - "author_name": "Brecht Devleesschauwer", - "author_inst": "Sciensano" - }, - { - "author_name": "Natalia Bustos Sierra", - "author_inst": "Sciensano" - }, - { - "author_name": "Francoise Renard", - "author_inst": "Sciensano" + "author_name": "H\u00e9ctor Pifarr\u00e9 i Arolas", + "author_inst": "Center for Research in Health and Economics - Universitat Pompeu Fabra" }, { - "author_name": "Sereina Herzog", - "author_inst": "Universiteit Antwerpen" + "author_name": "Mikko Myrskyl\u00e4", + "author_inst": "Max Planck Institute for Demographic Research" }, { - "author_name": "Patrick Lusyne", - "author_inst": "Statistics Belgium" + "author_name": "Adeline Lo", + "author_inst": "University of Wisconsin Madison" }, { - "author_name": "Johan Van der Heyden", - "author_inst": "Sciensano" + "author_name": "Enrique Acosta", + "author_inst": "Max Planck Institute for Demographic Research" }, { - "author_name": "Herman Van Oyen", - "author_inst": "Sciensano" + "author_name": "Guillem Lop\u00e9z Casasnovas", + "author_inst": "Center for Research in Health and Economics - Universitat Pompeu Fabra" }, { - "author_name": "Pierre Van Damme", - "author_inst": "Universiteit Antwerpen" + "author_name": "Catia Nicodemo", + "author_inst": "Centre of Organisation, Department of Primary Economics, University of Oxford" }, { - "author_name": "Niel Hens", - "author_inst": "Hasselt University and University of Antwerp" + "author_name": "Tim Riffe", + "author_inst": "Max Planck Institute for Demographic Research" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1350676,109 +1350945,25 @@ "category": "health informatics" }, { - "rel_doi": "10.1101/2020.06.19.20134767", - "rel_title": "Clinical practice guidelines and recommendations in the context of the COVID-19 pandemic: systematic review and critical appraisal", + "rel_doi": "10.1101/2020.06.18.20134486", + "rel_title": "Covid-19 Pandemic- Pits and falls of major states of India.", "rel_date": "2020-06-20", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.19.20134767", - "rel_abs": "BackgroundThe number of published clinical practice guidelines and recommendations related to SARS-CoV-2 infections causing COVID-19 has rapidly increased. However, insufficient consideration of appropriate methodologies in the guideline development could lead to misleading information, uncertainty among professionals, and potentially harmful actions for patients.\n\nPurposeRapid systematic review of clinical practice guidelines and recommendations in the context of COVID-19 to explore if basic methodological standards of guideline development have been met.\n\nData sourcesMEDLINE [PubMed], CINAHL [Ebsco], Trip and manual search; from Feb 1st 2020 until April 27th 2020.\n\nStudy selectionAll types of healthcare workers providing any kind of healthcare to any patient population in any setting.\n\nData extractionAt least two reviewers independently extracted guideline characteristics, conducted critical appraisal according to The Appraisal of Guidelines for Research and Evaluation Instrument (AGREE II) and classified the guidelines using the Association of the Scientific Medical Societies (AWMF) Guidance Manual and Rules for Guideline Development. We plan six-month updates (living review).\n\nData synthesisThere were 1342 titles screened and 188 guidelines included. The highest average AGREE II domain score was 89% for scope and purpose, the lowest for rigor of development (25%). Only eight guidelines (4%) were based on a systematic literature search and a structured consensus process by representative experts (classified as the highest methodological quality, S3 according to AWMF). Patients were only included in the development of one guideline. A process for regular updates was described in 27 guidelines (14%).\n\nLimitationsMethodological focus only.\n\nConclusionsDespite clear scope, most publications fell short of basic methodological standards of guideline development. Future research should monitor the evolving methodological quality of the guidelines and their updates over time.\n\nRegistration/PublicationThe protocol was published at www.researchgate.net, DOI: 10.13140/RG.2.2.21293.51689. Preliminary results are publicly available on medRxiv.", - "rel_num_authors": 23, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.18.20134486", + "rel_abs": "Covid-19, just like SARS and MERS before it, is a disease caused by corona virus and can lead to severe respiratory diseases in humans. With the outbreak of novel corona virus, WHO on 30th January 2020 declared it a Public Health Emergency and further on 11th March 2020, Covid-19 disease was declared a pandemic. India in the initial stages of the pandemic dealt with it in a very effective manner. With timely implementation of lockdown, India was able to contain the spread of Covid-19 to some extent. However with the recently announced Unlock 1.0, the SARS CoV-2 is expected to spread. This study aims to track and analyze the Covid-19 situation in major states that constitute of 70 percent of the total cases. Thus the states selected for the study are: Maharashtra, Delhi, Tamil Nadu, Gujarat, Uttar Pradesh and Rajasthan. These are the states which had more than ten thousand Covid-19 patients as/on June 10th 2020. The analysis period is from March 25th to June 10th and the data source is Indias Covid-19 tracker. To assess the previous and current Covid-19 situations in these states indicators such as Active rates, Recovery rate, Case fatality rate, Test positivity rate, tests per million, cases per million, test per confirmed case has been used. The study finds that although the absolute number of active cases may be rising, however it is showing a decreasing trend with an increase in recovery rates. With increasing number of Covid-19 cases, testing also has increased however not in the similar proportion and thus by developed nation standard we are lagging. With increasing TPR and cases per million, Delhi is well on its way to surpass even Mumbai which till now has proven to be worst hit in this pandemic. An interesting finding is that of test per confirmed case which shows that every 6th person in Maharashtra and every 8th in Delhi is showing positive result of Covid-19 test. Given such an increase and unlocked India, Delhi might soon enter into the third stage of community transmission where source of 50 percent or more cases would be unknown. There has been an increase in the Covid-19 related health infrastructure with the public-private partnership which involved both private hospitals and lab joining hands to battle Covid-19, however, affordability still remains an issue. If experts are to be believed, pandemic isnt over because weve unlocked. The worst is yet to come as Covid-19 is predicted to peak in mid-July to August in India. Thus, itd be advisable to not venture out unnecessarily just because restrictions have been lifted. Also, following the guidelines-hand-washing, avoiding public gathering, social distancing and covering nose and mouth has now become imperative.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Tanja A Stamm", - "author_inst": "Medical University of Vienna, Austria" - }, - { - "author_name": "Margaret R Andrews", - "author_inst": "Medical University of Vienna, Austria" - }, - { - "author_name": "Erika Mosor", - "author_inst": "Medical University of Vienna, Austria" - }, - { - "author_name": "Valentin Ritschl", - "author_inst": "Medical University of Vienna, Austria" - }, - { - "author_name": "Linda C Li", - "author_inst": "University of British Columbia, Canada" - }, - { - "author_name": "Jasmin K Ma", - "author_inst": "University of British Columbia, Canada" - }, - { - "author_name": "Adalberto Campo Arias", - "author_inst": "University of Magdalena, Santa Marta, Colombia" - }, - { - "author_name": "Sarah Baker", - "author_inst": "University of Sheffield, UK" - }, - { - "author_name": "Nicola W Burton", - "author_inst": "Griffith University, Mt. Gravatt, Australia" - }, - { - "author_name": "Mohammad Eghbali", - "author_inst": "University of Social Welfare and Rehabilitation Sciences, Tehran, Iran" - }, - { - "author_name": "Natalia Fernandez", - "author_inst": "University of Michigan, United States" - }, - { - "author_name": "Ricardo Ferreira", - "author_inst": "Centro Hospitalar e Universitario de Coimbra, Portugal" - }, - { - "author_name": "Gabriele Gaebler", - "author_inst": "Austrian Association of Dietitians, Vienna, Austria" - }, - { - "author_name": "Souzi Makri", - "author_inst": "The Cyprus League Against Rheumatism and Platform Organization for People for Rheumatic diseases in Southern Europe, Nicosia, Cyprus" + "author_name": "Abhinesh Singh", + "author_inst": "Tata Institute of Social Sciences, Mumbai." }, { - "author_name": "Sandra Mintz", - "author_inst": "Children's Hospital Los Angeles, Los Angeles, CA, United States" - }, - { - "author_name": "Rikke Moe", - "author_inst": "Diakonhjemmet Hospital, Oslo, Norway" - }, - { - "author_name": "Elizabeth Morasso", - "author_inst": "UCLA Health, Los Angeles, CA, United States" - }, - { - "author_name": "Susan L Murphy", - "author_inst": "University of Michigan, MI, United States" - }, - { - "author_name": "Simiso Ntuli", - "author_inst": "University of Johannesburg, Johannesburg, Gauteng, South Africa" - }, - { - "author_name": "Maisa Omara", - "author_inst": "Medical University of Vienna, Austria" - }, - { - "author_name": "Miguel Simancas Pallares", - "author_inst": "University of North Carolina at Chapel Hill, NC, United States" - }, - { - "author_name": "Jen Horonieff", - "author_inst": "Savvy Cooperative, Queens, NY, USA" - }, - { - "author_name": "Gerald Gartlehner", - "author_inst": "Cochrane Austria, Department for Evidence-based Medicine and Evaluation, Danube University Krems, Austria" + "author_name": "Samriddhi S Gupte", + "author_inst": "International Institute for Population Sciences, Mumbai" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "health systems and quality improvement" }, @@ -1352762,131 +1352947,55 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.06.18.160614", - "rel_title": "Mechanism and inhibition of SARS-CoV-2 PLpro", + "rel_doi": "10.1101/2020.06.18.160671", + "rel_title": "Identification of a critical horseshoe-shaped region in the nsp5 (Mpro, 3CLpro) protease interdomain loop (IDL) of coronavirus mouse hepatitis virus (MHV)", "rel_date": "2020-06-19", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.06.18.160614", - "rel_abs": "Coronaviruses, including SARS-CoV-2, encode multifunctional proteases that are essential for viral replication and evasion of host innate immune mechanisms. The papain-like protease PLpro cleaves the viral polyprotein, and reverses inflammatory ubiquitin and anti-viral ubiquitin-like ISG15 protein modifications1,2. Drugs that target SARS-CoV-2 PLpro (hereafter, SARS2 PLpro) may hence be effective as treatments or prophylaxis for COVID-19, reducing viral load and reinstating innate immune responses3. We here characterise SARS2 PLpro in molecular and biochemical detail. SARS2 PLpro cleaves Lys48-linked polyubiquitin and ISG15 modifications with high activity. Structures of PLpro bound to ubiquitin and ISG15 reveal that the S1 ubiquitin binding site is responsible for high ISG15 activity, while the S2 binding site provides Lys48 chain specificity and cleavage efficiency. We further exploit two strategies to target PLpro. A repurposing approach, screening 3727 unique approved drugs and clinical compounds against SARS2 PLpro, identified no compounds that inhibited PLpro consistently or that could be validated in counterscreens. More promisingly, non-covalent small molecule SARS PLpro inhibitors were able to inhibit SARS2 PLpro with high potency and excellent antiviral activity in SARS-CoV-2 infection models.", - "rel_num_authors": 28, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.06.18.160671", + "rel_abs": "Human coronaviruses are enveloped, positive-strand RNA viruses which cause respiratory diseases ranging in severity from the seasonal common cold to SARS and COVID-19. Of the 7 human coronaviruses discovered to date, 3 emergent and severe human coronavirus strains (SARS-CoV, MERS-CoV, and SARS-CoV-2) have recently jumped to humans in the last 20 years. The COVID-19 pandemic spawned by the emergence of SARS-CoV-2 in late 2019 has highlighted the importance for development of effective therapeutics to target emerging coronaviruses. Upon entry, the replicase genes of coronaviruses are translated and subsequently proteolytically processed by virus-encoded proteases. Of these proteases, nonstructural protein 5 (nsp5, Mpro, or 3CLpro), mediates the majority of these cleavages and remains a key drug target for therapeutic inhibitors. Efforts to develop nsp5 active-site inhibitors for human coronaviruses have thus far been unsuccessful, establishing the need for identification of other critical and conserved non-active-site regions of the protease. In this study, we describe the identification of an essential, conserved horseshoe-shaped region in the nsp5 interdomain loop (IDL) of mouse hepatitis virus (MHV), a common coronavirus replication model. Using site-directed mutagenesis and replication studies, we show that several residues comprising this horseshoe-shaped region either fail to tolerate mutagenesis or were associated with viral temperature-sensitivity. Structural modeling and sequence analysis of these sites in other coronaviruses, including all 7 human coronaviruses, suggests that the identified structure and sequence of this horseshoe regions is highly conserved and may represent a new, non-active-site regulatory region of the nsp5 (3CLpro) protease to target with coronavirus inhibitors.\n\nImportanceIn December 2019, a novel coronavirus (SARS-CoV-2) emerged in humans and triggered a pandemic which has to date resulted in over 8 million confirmed cases of COVID-19 across more than 180 countries and territories (June 2020). SARS-CoV-2 represents the third emergent coronavirus in the past 20 years and the future emergence of new coronaviruses in humans remains certain. Critically, there remains no vaccine nor established therapeutics to treat cases of COVID-19. The coronavirus nsp5 protease is a conserved and indispensable virus-encoded enzyme which remains a key target for therapeutic design. However, past attempts to target the active site of nsp5 with inhibitors have failed stressing the need to identify new conserved non-active-site targets for therapeutic development. This study describes the discovery of a novel conserved structural region of the nsp5 protease of coronavirus mouse hepatitis virus (MHV) which may provide a new target for coronavirus drug development.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Theresa Klemm", - "author_inst": "The Walter and Eliza Hall Institute of Medical Research and Department of Medical Biology, University of Melbourne, 1G Royal Parade, Parkville, Victoria 3052, A" - }, - { - "author_name": "Gregor Ebert", - "author_inst": "The Walter and Eliza Hall Institute of Medical Research and Department of Medical Biology, University of Melbourne, 1G Royal Parade, Parkville, Victoria 3052, A" - }, - { - "author_name": "Dale J Calleja", - "author_inst": "The Walter and Eliza Hall Institute of Medical Research and Department of Medical Biology, University of Melbourne, 1G Royal Parade, Parkville, Victoria 3052, A" - }, - { - "author_name": "Cody C Allison", - "author_inst": "The Walter and Eliza Hall Institute of Medical Research and Department of Medical Biology, University of Melbourne, 1G Royal Parade, Parkville, Victoria 3052, A" - }, - { - "author_name": "Lachlan W Richardson", - "author_inst": "The Walter and Eliza Hall Institute of Medical Research and Department of Medical Biology, University of Melbourne, 1G Royal Parade, Parkville, Victoria 3052, A" - }, - { - "author_name": "Jonathan P Bernardini", - "author_inst": "The Walter and Eliza Hall Institute of Medical Research and Department of Medical Biology, University of Melbourne, 1G Royal Parade, Parkville, Victoria 3052, A" - }, - { - "author_name": "Bernadine G C Lu", - "author_inst": "The Walter and Eliza Hall Institute of Medical Research and Department of Medical Biology, University of Melbourne, 1G Royal Parade, Parkville, Victoria 3052, A" - }, - { - "author_name": "Nathan W Kuchel", - "author_inst": "The Walter and Eliza Hall Institute of Medical Research and Department of Medical Biology, University of Melbourne, 1G Royal Parade, Parkville, Victoria 3052, A" + "author_name": "Benjamin C. Nick", + "author_inst": "Butler University" }, { - "author_name": "Christoph Grohmann", - "author_inst": "The Walter and Eliza Hall Institute of Medical Research and Department of Medical Biology, University of Melbourne, 1G Royal Parade, Parkville, Victoria 3052, A" + "author_name": "Mansi C. Pandya", + "author_inst": "Butler University" }, { - "author_name": "Yuri Shibata", - "author_inst": "The Walter and Eliza Hall Institute of Medical Research and Department of Medical Biology, University of Melbourne, 1G Royal Parade, Parkville, Victoria 3052, A" - }, - { - "author_name": "Zhong Yan Gan", - "author_inst": "The Walter and Eliza Hall Institute of Medical Research and Department of Medical Biology, University of Melbourne, 1G Royal Parade, Parkville, Victoria 3052, A" - }, - { - "author_name": "James P Cooney", - "author_inst": "The Walter and Eliza Hall Institute of Medical Research and Department of Medical Biology, University of Melbourne, 1G Royal Parade, Parkville, Victoria 3052, A" - }, - { - "author_name": "Marcel Doerflinger", - "author_inst": "The Walter and Eliza Hall Institute of Medical Research and Department of Medical Biology, University of Melbourne, 1G Royal Parade, Parkville, Victoria 3052, A" - }, - { - "author_name": "Amanda E Au", - "author_inst": "The Walter and Eliza Hall Institute of Medical Research and Department of Medical Biology, University of Melbourne, 1G Royal Parade, Parkville, Victoria 3052, A" - }, - { - "author_name": "Timothy R Blackmore", - "author_inst": "The Walter and Eliza Hall Institute of Medical Research and Department of Medical Biology, University of Melbourne, 1G Royal Parade, Parkville, Victoria 3052, A" - }, - { - "author_name": "Paul P Geurink", - "author_inst": "Oncode Institute and Department of Chemical Immunology, Leiden University Medical Centre, Einthovenweg 20, 2333 ZC, Leiden, The Netherlands." - }, - { - "author_name": "Huib Ovaa", - "author_inst": "Oncode Institute and Department of Chemical Immunology, Leiden University Medical Centre, Einthovenweg 20, 2333 ZC, Leiden, The Netherlands." - }, - { - "author_name": "Janet Newman", - "author_inst": "Commonwealth Scientific and Industrial Research Organisation (CSIRO), Biomedical Program, Parkville, Victoria 3052, Australia." - }, - { - "author_name": "Alan Riboldi-Tunnicliffe", - "author_inst": "Australian Synchrotron, ANSTO, 800 Blackburn Road, Clayton, VIC 3168, Australia." - }, - { - "author_name": "Peter E Czabotar", - "author_inst": "The Walter and Eliza Hall Institute of Medical Research and Department of Medical Biology, University of Melbourne, 1G Royal Parade, Parkville, Victoria 3052, A" - }, - { - "author_name": "Jeffrey P Mitchell", - "author_inst": "The Walter and Eliza Hall Institute of Medical Research and Department of Medical Biology, University of Melbourne, 1G Royal Parade, Parkville, Victoria 3052, A" - }, - { - "author_name": "Rebecca Feltham", - "author_inst": "The Walter and Eliza Hall Institute of Medical Research and Department of Medical Biology, University of Melbourne, 1G Royal Parade, Parkville, Victoria 3052, A" + "author_name": "Xiaotao Lu", + "author_inst": "Vanderbilt University Medical Center" }, { - "author_name": "Bernhard C Lechtenberg", - "author_inst": "The Walter and Eliza Hall Institute of Medical Research and Department of Medical Biology, University of Melbourne, 1G Royal Parade, Parkville, Victoria 3052, A" + "author_name": "Megan E. Franke", + "author_inst": "Butler University" }, { - "author_name": "Kym N Lowes", - "author_inst": "The Walter and Eliza Hall Institute of Medical Research and Department of Medical Biology, University of Melbourne, 1G Royal Parade, Parkville, Victoria 3052, A" + "author_name": "Sean M. Callahan", + "author_inst": "Butler University" }, { - "author_name": "Grant Dewson", - "author_inst": "The Walter and Eliza Hall Institute of Medical Research and Department of Medical Biology, University of Melbourne, 1G Royal Parade, Parkville, Victoria 3052, A" + "author_name": "Emily F. Hasik", + "author_inst": "Butler University" }, { - "author_name": "Marc Pellegrini", - "author_inst": "The Walter and Eliza Hall Institute of Medical Research and Department of Medical Biology, University of Melbourne, 1G Royal Parade, Parkville, Victoria 3052, A" + "author_name": "Sean T. Berthrong", + "author_inst": "Butler University" }, { - "author_name": "Guillaume Lessene", - "author_inst": "The Walter and Eliza Hall Institute of Medical Research and Department of Medical Biology, University of Melbourne, 1G Royal Parade, Parkville, Victoria 3052, A" + "author_name": "Mark R. Denison", + "author_inst": "Vanderbilt University Medical Center" }, { - "author_name": "David Komander", - "author_inst": "The Walter and Eliza Hall Institute of Medical Research and Department of Medical Biology, University of Melbourne, 1G Royal Parade, Parkville, Victoria 3052, A" + "author_name": "Christopher C. Stobart", + "author_inst": "Butler University" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "new results", - "category": "biochemistry" + "category": "microbiology" }, { "rel_doi": "10.1101/2020.06.18.160655", @@ -1354564,35 +1354673,55 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.06.15.20132308", - "rel_title": "Trace, Quarantine, Test, Isolate and Treat: A Kerala Model of Covid-19 Response", + "rel_doi": "10.1101/2020.06.16.20132803", + "rel_title": "Development and validation of the Elecsys Anti-SARS-CoV-2 immunoassay as a highly specific tool for determining past exposure to SARS-CoV-2", "rel_date": "2020-06-19", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.15.20132308", - "rel_abs": "Kerala reported the first three cases of coronavirus in India in late January. Kerala, one of the Indias most densely populated states, which makes its success in fighting the Covid-19 all the more commendable. Moreover, an estimated 17% of its 35 million population employed or lives elsewhere, more than 1 million tourists visit each year, and hundreds of students study abroad, including in China. All of this mobility makes the state more vulnerable to contagious outbreaks. What is the strategy behind the success story? This paper compares the situation of COVID-19 pandemic in major states and Kerala by the different phase of lockdown, and also highlights Keralas fight against the pandemic. We used publicly available data from https://www.covid19india.org/ and Covid-19 Daily Bulletin (Jan 31-May 31), Directorate of Health Services, Kerala (https://dashboard.kerala.gov.in/). We calculate the phase-wise period prevalence rate (PPR) and the case fatality rate (CFR) of the last phase. Compared to other major states, Kerala showed better response in preventing pandemic. The equation for the Keralas success has been simple, prioritized testing, widespread contact tracing, and promoting social distance. They also imposed uncompromising controls, were supported by an excellent healthcare system, government accountability, transparency, public trust, civil rights and importantly the decentralized governance and strong grass-root level institutions. The \"proactive\" measures taken by Kerala such as early detection of cases and extensive social support measures can be a \"model for India and the world\".", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.16.20132803", + "rel_abs": "BackgroundThe Elecsys(R) Anti-SARS-CoV-2 immunoassay (Roche Diagnostics) was developed to provide an accurate and reliable method for the detection of antibodies to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We evaluated the sensitivity, specificity, and cross-reactivity of the Elecsys Anti-SARS-CoV-2 immunoassay.\n\nMethodsThe performance of the Elecsys Anti-SARS-CoV-2 immunoassay was assessed at Roche Diagnostics (Penzberg, Germany). Sensitivity was evaluated using anonymised residual frozen samples from patients who had previously tested positive for SARS-CoV-2 infection by polymerase chain reaction (PCR); one or more consecutive samples were collected from patients at various timepoints after PCR confirmation. Specificity was evaluated using anonymised unselected residual frozen samples from routine diagnostic testing or from blood donors; all samples were collected before December 2019 and thus deemed negative for SARS-CoV-2-specific antibodies. Cross-reactivity was evaluated using anonymised frozen samples containing a wide range of potentially cross-reacting analytes, which were purchased from commercial vendors. For sensitivity and specificity, point estimates and 95% confidence intervals (CIs) were calculated.\n\nResultsSensitivity of the Elecsys Anti-SARS-CoV-2 immunoassay in 496 samples from 102 patients with prior PCR-confirmed SARS-CoV-2 infection was 99.5% (95% CI 97.0-100.0) at [≥]14 days after PCR confirmation. Overall specificity in 10,453 samples from routine diagnostic testing (n = 6305) and blood donors (n = 4148) was 99.80% (95% CI 99.69-99.88). Only 4/752 samples containing potential cross-reacting analytes were reactive with the Elecsys Anti-SARS-CoV-2 immunoassay, resulting in an overall specificity in this cohort of 99.5% (95% CI 98.6-99.9).\n\nConclusionThe Elecsys Anti-SARS-CoV-2 immunoassay demonstrated a sensitivity of 99.5% at [≥]14 days after PCR confirmation and a very high specificity of 99.80%. Our findings support the use of the Elecsys Anti-SARS-CoV-2 immunoassay as a tool for the identification of past SARS-CoV-2 infection, including in populations with a low disease prevalence.\n\nRequired information for submission systemO_ST_ABSEthical guidelinesC_ST_ABSThe study was conducted in accordance with applicable regulations, including relevant European Union directives and regulations, and the principles of the Declaration of Helsinki. All samples, excluding the specimens that were provided by commercial sample vendors, were transferred to Roche following anonymisation. For studies with anonymised leftover specimens, no ethics committee vote is required. A statement was obtained from the Ethics Committee of the Landesa rztekammer Bayern confirming that there are no objections against the transfer and the coherent use of the anonymised leftover samples.\n\nResearch reporting guidelinesPlease see separate STARD checklist\n\nData availability statementQualified researchers may request access to individual patient level data through the clinical study data request platform (https://vivli.org/). Further details on Roches criteria for eligible studies are available here: https://vivli.org/members/ourmembers/. For further details on Roches Global Policy on the Sharing of Clinical Information and how to request access to related clinical study documents, see here: https://www.roche.com/research_and_development/who_we_are_how_we_work/clinical_trials/our_commitment_to_data_sharing.htm.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Sulaiman KM", - "author_inst": "International institute for Population Sciences- Mumbai" + "author_name": "Peter Muench", + "author_inst": "Roche Diagnostics GmbH, Penzberg, Germany" }, { - "author_name": "Muhammad T", - "author_inst": "International Institute for Population Sciences, Mumbai" + "author_name": "Simon Jochum", + "author_inst": "Roche Diagnostics GmbH, Penzberg, Germany" + }, + { + "author_name": "Verena Wenderoth", + "author_inst": "Roche Diagnostics GmbH, Penzberg, Germany" + }, + { + "author_name": "Beatus Ofenloch-Haehnle", + "author_inst": "Roche Diagnostics GmbH, Penzberg, Germany" + }, + { + "author_name": "Michael Hombach", + "author_inst": "Roche Diagnostics International Ltd, Rotkreuz, Switzerland" + }, + { + "author_name": "Matthias Strobl", + "author_inst": "Roche Diagnostics GmbH, Penzberg, Germany" }, { - "author_name": "Muhammad Rishad AP", - "author_inst": "International institute for Population Sciences- Mumbai" + "author_name": "Henrik Sadlowski", + "author_inst": "Labor Berlin - Charite Vivantes Services GmbH, Berlin, Germany" }, { - "author_name": "Afsal K", - "author_inst": "International institute for Population Sciences- Mumbai" + "author_name": "Christopher Sachse", + "author_inst": "KRH Labor GmbH, Hannover, Germany" + }, + { + "author_name": "Alexander Riedel", + "author_inst": "Roche Diagnostics GmbH, Penzberg, Germany" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "health policy" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2020.06.16.156166", @@ -1355966,79 +1356095,47 @@ "category": "genetic and genomic medicine" }, { - "rel_doi": "10.1101/2020.06.16.20132688", - "rel_title": "Assessing the impact of coordinated COVID-19 exit strategies across Europe", + "rel_doi": "10.1101/2020.06.18.20131417", + "rel_title": "Leveraging wearable technology to predict the risk of COVID-19 infection.", "rel_date": "2020-06-19", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.16.20132688", - "rel_abs": "As rates of new COVID-19 cases decline across Europe due to non-pharmaceutical interventions such as social distancing policies and lockdown measures, countries require guidance on how to ease restrictions while minimizing the risk of resurgent outbreaks. Here, we use mobility and case data to quantify how coordinated exit strategies could delay continental resurgence and limit community transmission of COVID-19. We find that a resurgent continental epidemic could occur as many as 5 weeks earlier when well-connected countries with stringent existing interventions end their interventions prematurely. Further, we found that appropriate coordination can greatly improve the likelihood of eliminating community transmission throughout Europe. In particular, synchronizing intermittent lockdowns across Europe meant half as many lockdown periods were required to end community transmission continent-wide.\n\nOne Sentence SummaryEU coordination in easing restrictions is key to preventing resurgent COVID-19 outbreaks and stopping community transmission.", - "rel_num_authors": 15, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.18.20131417", + "rel_abs": "COVID-19, the disease caused by the SARS-CoV-2 virus, can cause shortness of breath, lung damage, and impaired respiratory function. Containing the virus has proven difficult, in large part due to its high transmissibility during the pre-symptomatic incubation. The studys aim was to determine if changes in respiratory rate could serve as a leading indicator of SARS-CoV-2 infections. A total of 271 individuals (age = 37.3 {+/-} 9.5, 190 male, 81 female) who experienced symptoms consistent with COVID-19 were included - 81 tested positive for SARS-CoV-2 and 190 tested negative; these 271 individuals collectively contributed 2672 samples (days) of data (1856 healthy days, 231 while infected with COVID-19 and 585 while infected with something other than COVID-19). To train a novel algorithm, individuals were segmented as follows; (1) a training dataset of individuals who tested positive for COVID-19 (n=57 people, 537 samples); (2) a validation dataset of individuals who tested positive for COVID-19 (n=24 people, 320 samples) ; (3) a validation dataset of individuals who tested negative for COVID-19 (n=190 people, 1815 samples). All data was extracted from the WHOOP system, which uses data from a wrist-worn strap to produce validated estimates of respiratory rate and other physiological measures. Using the training dataset, a model was developed to estimate the probability of SARS-CoV-2 infection based on changes in respiratory rate during night-time sleep. The models ability to identify COVID-positive individuals not used in training and robustness against COVID-negative individuals with similar symptoms were examined for a critical six-day period spanning the onset of symptoms. The model identified 20% of COVID-19 positive individuals in the validation dataset in the two days prior to symptom onset, and 80% of COVID-19 positive cases by the third day of symptoms.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Nick Warren Ruktanonchai", - "author_inst": "University of Southampton" - }, - { - "author_name": "Jessica Floyd", - "author_inst": "University of Southampton" - }, - { - "author_name": "Shengjie Lai", - "author_inst": "University of Southampton" - }, - { - "author_name": "Corrine Warren Ruktanonchai", - "author_inst": "University of Southampton" - }, - { - "author_name": "Adam Sadilek", - "author_inst": "Google, Inc" - }, - { - "author_name": "Pedro Rente-Lourenco", - "author_inst": "Vodafone, Inc" - }, - { - "author_name": "Xue Ben", - "author_inst": "Google, Inc" - }, - { - "author_name": "Alessandra Carioli", - "author_inst": "University of Southampton" - }, - { - "author_name": "Joshua Gwinn", - "author_inst": "University of Kentucky" + "author_name": "Dean J Miller", + "author_inst": "CQUniversity" }, { - "author_name": "Jessica Steele", - "author_inst": "University of Southampton" + "author_name": "John V Capodilupo", + "author_inst": "Whoop Inc." }, { - "author_name": "Olivia Prosper", - "author_inst": "University of Tennessee" + "author_name": "Michele Lastella", + "author_inst": "CQUniversity" }, { - "author_name": "Aaron Schneider", - "author_inst": "Google, Inc" + "author_name": "Charli Sargent", + "author_inst": "CQUniversity" }, { - "author_name": "Andrew Oplinger", - "author_inst": "Google, Inc" + "author_name": "Gregory D Roach", + "author_inst": "CQUniversity" }, { - "author_name": "Paul Eastham", - "author_inst": "Google, Inc" + "author_name": "Victoria H Lee", + "author_inst": "Whoop Inc." }, { - "author_name": "Andrew J Tatem", - "author_inst": "University of Southampton" + "author_name": "Emily R Capodilupo", + "author_inst": "Whoop Inc." } ], "version": "1", "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2020.06.16.20132597", @@ -1357832,111 +1357929,83 @@ "category": "biochemistry" }, { - "rel_doi": "10.1101/2020.06.17.158006", - "rel_title": "Genomic surveillance of SARS-CoV-2 reveals community transmission of a major lineage during the early pandemic phase in Brazil", + "rel_doi": "10.1101/2020.06.18.159202", + "rel_title": "Divergent SARS-CoV-2-specific T and B cell responses in severe but not mild COVID-19", "rel_date": "2020-06-18", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.06.17.158006", - "rel_abs": "Despite all efforts to control the COVID-19 spread, the SARS-CoV-2 reached South America within three months after its first detection in China, and Brazil became one of the hotspots of COVID-19 in the world. Several SARS-CoV-2 lineages have been identified and some local clusters have been described in this early pandemic phase in Western countries. Here we investigated the genetic diversity of SARS-CoV-2 during the early phase (late February to late April) of the epidemic in Brazil. Phylogenetic analyses revealed multiple introductions of SARS-CoV-2 in Brazil and the community transmission of a major B.1.1 lineage defined by two amino acid substitutions in the Nucleocapsid and ORF6. This SARS-CoV-2 Brazilian lineage was probably established during February 2020 and rapidly spread through the country, reaching different Brazilian regions by the middle of March 2020. Our study also supports occasional exportations of this Brazilian B.1.1 lineage to neighboring South American countries and to more distant countries before the implementation of international air travels restrictions in Brazil.", - "rel_num_authors": 23, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.06.18.159202", + "rel_abs": "Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of the current coronavirus disease 2019 (COVID-19) pandemic. Understanding both the immunological processes providing specific immunity and potential immunopathology underlying the pathogenesis of this disease may provide valuable insights for potential therapeutic interventions. Here, we quantified SARS-CoV-2 specific immune responses in patients with different clinical courses. Compared to individuals with a mild clinical presentation, CD4+ T cell responses were qualitatively impaired in critically ill patients. Strikingly, however, in these patients the specific IgG antibody response was remarkably strong. The observed disparate T and B cell responses could be indicative of a deregulated immune response in critically ill COVID-19 patients.", + "rel_num_authors": 16, "rel_authors": [ { - "author_name": "Paola Cristina Resende", - "author_inst": "Laboratory of Respiratory Viruses and Measles, Oswaldo Cruz Institute (IOC), FIOCRUZ, Rio de Janeiro, Brazil" - }, - { - "author_name": "Edson Delatorre", - "author_inst": "Departamento de Biologia. Centro de Ciencias Exatas, Naturais e da Saude, Universidade Federal do Espirito Santo, Alegre, Brazil" - }, - { - "author_name": "Tiago Graf", - "author_inst": "Instituto Goncalo Moniz, FIOCRUZ, Salvador, Brazil." - }, - { - "author_name": "Daiana Mir", - "author_inst": "Unidad de Genomica y Bioinformatica, Centro Universitario Regional del Litoral Norte, Universidad de la Republica, Salto, Uruguay" - }, - { - "author_name": "Fernando C Motta", - "author_inst": "Laboratory of Respiratory Viruses and Measles, Oswaldo Cruz Institute (IOC), FIOCRUZ, Rio de Janeiro, Brazil" - }, - { - "author_name": "Luciana Appolinario", - "author_inst": "Laboratory of Respiratory Viruses and Measles, Oswaldo Cruz Institute (IOC), FIOCRUZ, Rio de Janeiro, Brazil" + "author_name": "Anna E. Oja", + "author_inst": "Department of Hematopoiesis, Sanquin Research and Landsteiner Laboratory, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands" }, { - "author_name": "Anna Carolina D Paixao", - "author_inst": "Laboratory of Respiratory Viruses and Measles, Oswaldo Cruz Institute (IOC), FIOCRUZ, Rio de Janeiro, Brazil" - }, - { - "author_name": "Maria Ogrzewalska", - "author_inst": "Laboratory of Respiratory Viruses and Measles, Oswaldo Cruz Institute (IOC), FIOCRUZ, Rio de Janeiro, Brazil" - }, - { - "author_name": "Braula Caetano", - "author_inst": "Laboratory of Respiratory Viruses and Measles, Oswaldo Cruz Institute (IOC), FIOCRUZ, Rio de Janeiro, Brazil" + "author_name": "Anno Saris", + "author_inst": "Centre for Experimental and Molecular Medicine, Amsterdam UMC, Amsterdam, the Netherlands" }, { - "author_name": "Mirleide C Santos", - "author_inst": "Instituto Evandro Chagas, Belem, Para" + "author_name": "Cherien A. Ghandour", + "author_inst": "Department of Hematopoiesis, Sanquin Research and Landsteiner Laboratory, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands" }, { - "author_name": "Jessylene Almeida Ferreira", - "author_inst": "Instituto Evandro Chagas, Belem, Para" + "author_name": "Natasja A.M. Kragten", + "author_inst": "Department of Hematopoiesis, Sanquin Research and Landsteiner Laboratory, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands" }, { - "author_name": "Edivaldo C Souza Junior", - "author_inst": "Instituto Evandro Chagas, Belem, Para" + "author_name": "Boris M. Hogema", + "author_inst": "Sanquin Diagnostic Services and Sanquin Research, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands" }, { - "author_name": "Sandro Patroca Silva", - "author_inst": "Instituto Evandro Chagas, Belem, Para" + "author_name": "Esther J Nossent", + "author_inst": "Department of Pulmonary Medicine, Amsterdam UMC, Amsterdam, the Netherlands" }, { - "author_name": "Sandra B Fernandes", - "author_inst": "Laboratorio Central de Saude Publica do Estado de Santa Catarina (LACEN-SC), Florianopolis, Santa Catarina, Brazil" + "author_name": "Leo M.A. Heunks", + "author_inst": "Department of Intensive Care Medicine, Amsterdam UMC, Amsterdam, the Netherlands" }, { - "author_name": "Lucas Alves Vianna", - "author_inst": "Laboratorio Central de Saude Publica do Estado Espirito Santo (LACEN-ES). Vitoria, Espirito Santo, Brazil" + "author_name": "Susan Cuvalay", + "author_inst": "Unit of Transfusion Medicine, Sanquin Blood Supply, Amsterdam, the Netherlands" }, { - "author_name": "Larissa Costa", - "author_inst": "Laboratorio Central de Saude Publica do Distrito Federal (LACEN-DF). Brasilia, Distrito Federal, Brazil" + "author_name": "Ed Slot", + "author_inst": "Laboratory of Blood-borne Infections, Sanquin Blood Supply, Amsterdam, the Netherlands" }, { - "author_name": "Jean Ferro", - "author_inst": "Laboratorio Central de Saude Publica de Alagoas (LACEN-AL). Maceio, Alagoas, Brazil" + "author_name": "Francis H. Swaneveld", + "author_inst": "Unit of Transfusion Medicine, Sanquin Blood Supply, Amsterdam, the Netherlands" }, { - "author_name": "Vanessa Nardy", - "author_inst": "Laboratorio Central de Saude Publica da Bahia (LACEN-BA). Salvador, Bahia, Brazil" + "author_name": "Hans Vrielink", + "author_inst": "Unit of Transfusion Medicine, Sanquin Blood Supply, Amsterdam, the Netherlands" }, { - "author_name": "Julio Croda", - "author_inst": "Fiocruz Mato Grosso do Sul, Campo Grande, Mato Grosso do Sul, Brazil" + "author_name": "Theo Rispens", + "author_inst": "Department of Immunopathology, Sanquin Research and Landsteiner Laboratory, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands" }, { - "author_name": "Wanderson K Oliveira", - "author_inst": "Hospital das Forcas Armadas, Ministerio da Defesa, Brasilia, Distrito Federal, Brazil" + "author_name": "Ellen van der Schoot", + "author_inst": "Department of Experimental Immunohematology, Sanquin Research and Landsteiner Laboratory, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands" }, { - "author_name": "Andr\u00e9 Luis de Abreu", - "author_inst": "Coordenadoria Geral de Laboratorios - Ministerio da Saude, Brasilia, Distrito Federal, Brazil" + "author_name": "Rene A.W. van Lier", + "author_inst": "Department of Hematopoiesis, Sanquin Research and Landsteiner Laboratory, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands" }, { - "author_name": "Gonzalo Bello", - "author_inst": "Laboratorio de AIDS e Imunologia Molecular, Instituto Oswaldo Cruz, FIOCRUZ, Rio de Janeiro, Brazil" + "author_name": "Anja Ten Brinke", + "author_inst": "Department of Immunopathology, Sanquin Research and Landsteiner Laboratory, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands" }, { - "author_name": "Marilda M Siqueira", - "author_inst": "Laboratory of Respiratory Viruses and Measles, Oswaldo Cruz Institute (IOC), FIOCRUZ, Rio de Janeiro, Brazil" + "author_name": "Pleun Hombrink", + "author_inst": "Department of Hematopoiesis, Sanquin Research and Landsteiner Laboratory, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "new results", - "category": "evolutionary biology" + "category": "immunology" }, { "rel_doi": "10.1101/2020.06.17.156554", @@ -1359626,49 +1359695,45 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.06.15.20132050", - "rel_title": "Modeling the Post-Containment Elimination of Transmission of COVID-19", + "rel_doi": "10.1101/2020.06.15.20131979", + "rel_title": "Mobility network modeling explains higher SARS-CoV-2 infection rates among disadvantaged groups and informs reopening strategies", "rel_date": "2020-06-17", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.15.20132050", - "rel_abs": "Roughly six months into the COVID-19 pandemic, many countries have managed to contain the spread of the virus by means of strict containment measures including quarantine, tracing and isolation of patients as well strong restrictions on population mobility. Here we propose an extended SEIR model to explore the dynamics of containment and then explore scenarios for the local extinction of the disease. We present both the deterministic and stochastic version fo the model and derive the [R]0 and the probability of local extinction after relaxation (elimination of transmission) of containment, [P]0. We show that local extinctions are possible without further interventions, with reasonable probability, as long as the number of active cases is driven to single digits and strict control of case importation is maintained. The maintenance of defensive behaviors, such as using masks and avoiding agglomerations are also important factors. We also explore the importance of population immunity even when above the herd immunity threshold.", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.15.20131979", + "rel_abs": "Fine-grained epidemiological modeling of the spread of SARS-CoV-2--capturing who is infected at which locations--can aid the development of policy responses that account for heterogeneous risks of different locations as well as the disparities in infections among different demographic groups. Here, we develop a metapopulation SEIR disease model that uses dynamic mobility networks, derived from US cell phone data, to capture the hourly movements of millions of people from local neighborhoods (census block groups, or CBGs) to points of interest (POIs) such as restaurants, grocery stores, or religious establishments. We simulate the spread of SARS-CoV-2 from March 1-May 2, 2020 among a population of 98 million people in 10 of the largest US metropolitan statistical areas. We show that by integrating these mobility networks, which connect 57k CBGs to 553k POIs with a total of 5.4 billion hourly edges, even a relatively simple epidemiological model can accurately capture the case trajectory despite dramatic changes in population behavior due to the virus. Furthermore, by modeling detailed information about each POI, like visitor density and visit length, we can estimate the impacts of fine-grained reopening plans: we predict that a small minority of \"superspreader\" POIs account for a large majority of infections, that reopening some POI categories (like full-service restaurants) poses especially large risks, and that strategies restricting maximum occupancy at each POI are more effective than uniformly reducing mobility. Our models also predict higher infection rates among disadvantaged racial and socio-economic groups solely from differences in mobility: disadvantaged groups have not been able to reduce mobility as sharply, and the POIs they visit (even within the same category) tend to be smaller, more crowded, and therefore more dangerous. By modeling who is infected at which locations, our model supports fine-grained analyses that can inform more effective and equitable policy responses to SARS-CoV-2.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Flavio Codeco Coelho", - "author_inst": "Fundacao Getulio Vargas" - }, - { - "author_name": "Luiz Max Carvalho", - "author_inst": "Fundacao Getulio Vargas" + "author_name": "Serina Y Chang", + "author_inst": "Stanford University" }, { - "author_name": "Raquel M Lana", - "author_inst": "Fundacao Oswaldo Cruz" + "author_name": "Emma Pierson", + "author_inst": "Stanford University" }, { - "author_name": "Oswaldo G Cruz", - "author_inst": "Fundacao Oswaldo Cruz" + "author_name": "Pang Wei Koh", + "author_inst": "Stanford University" }, { - "author_name": "Leonardo S Bastos", - "author_inst": "Fundacao Oswaldo Cruz" + "author_name": "Jaline Gerardin", + "author_inst": "Northwestern University" }, { - "author_name": "Claudia T Codeco", - "author_inst": "Fundacao Oswaldo Cruz" + "author_name": "Beth Redbird", + "author_inst": "Northwestern University" }, { - "author_name": "Marcelo F C Gomes", - "author_inst": "Fundacao Oswaldo Cruz" + "author_name": "David Grusky", + "author_inst": "Stanford University" }, { - "author_name": "Daniel Villela", - "author_inst": "Fundacao Oswaldo Cruz" + "author_name": "Jure Leskovec", + "author_inst": "Stanford University" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1361212,65 +1361277,109 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.06.13.20129841", - "rel_title": "Field-deployable, rapid diagnostic testing of saliva samples for SARS-CoV-2.", + "rel_doi": "10.1101/2020.06.14.20128876", + "rel_title": "Snapshot PCR Surveillance for SARS-CoV-2 in Hospital Staff in England", "rel_date": "2020-06-16", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.13.20129841", - "rel_abs": "Rapid, scalable, point-of-need, COVID-19 diagnostic testing is necessary to safely re-open economies and prevent future outbreaks. We developed an assay that detects single copies of SARS-CoV-2 virus directly from saliva and swab samples in 30 min using a simple, one-step protocol that utilizes only a heat block and microcentrifuge tube prefilled with a mixture containing the necessary reagents and has a sensitivity and specificity of 97% and 100%, respectively.", - "rel_num_authors": 12, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.14.20128876", + "rel_abs": "BackgroundSignificant nosocomial transmission of SARS-CoV-2 has been demonstrated. Understanding the prevalence of SARS-CoV-2 carriage amongst HCWs at work is necessary to inform the development of HCW screening programmes to control nosocomial spread.\n\nMethodsCross-sectional snapshot survey from April-May 2020; HCWs recruited from six UK hospitals. Participants self-completed a health questionnaire and underwent a combined viral nose and throat swab, tested by Polymerase Chain Reaction (PCR) for SARS-CoV-2 with viral culture on majority of positive samples.\n\nFindingsPoint prevalence of SARS-CoV-2 carriage across the sites was 2{middle dot}0% (23/1152 participants), median cycle threshold value 35{middle dot}70 (IQR:32{middle dot}42-37{middle dot}57). 17 were previously symptomatic, two currently symptomatic (isolated anosmia and sore throat); the remainder declared no prior or current symptoms. Symptoms in the past month were associated with threefold increased odds of testing positive (aOR 3{middle dot}46, 95%CI 1{middle dot}38-8{middle dot}67; p=0{middle dot}008). SARS-CoV-2 virus was isolated from only one (5%) of nineteen cultured samples. A large proportion (39%) of participants reported symptoms in the past month.\n\nInterpretationThe point-prevalence is similar to previous estimates for HCWs in April 2020, though a magnitude higher than in the general population. Based upon interpretation of symptom history and testing results including viral culture, the majority of those testing positive were unlikely to be infectious at time of sampling. Development of screening programmes must balance the potential to identify additional cases based upon likely prevalence, expanding the symptoms list to encourage HCW testing, with resource implications and risks of excluding those unlikely to be infectious with positive tests.\n\nFundingPublic Health England.\n\nWord CountO_ST_ABSResearch in contextC_ST_ABSEvidence before this studyA search of PubMed was performed on 29th April 2020 to identify other major works in this field, using the search terms (\"novel coronavirus\" OR \"SARS-CoV-2\" OR \"COVID-19\" OR \"coronavirus\") AND (\"workers\" OR \"staff\") AND (\"testing\" OR \"screening\") from 31st December 2019 onwards with no other limits. This search was updated on 10th May 2020, and in addition reference lists were checked and pre-print papers were shared with us through professional networks. We found three papers commenting on prevalence of asymptomatic/pauci-symptomatic SARS-CoV-2 infection in healthcare workers, with prevalence estimates ranging from 1{middle dot}1 to 8%. One of these studies explored previous symptoms in depth, though this was based upon a retrospective questionnaire and thus subject to recall bias. None of these studies explored exposures to the SARS-CoV-2 virus, commented on whether participants had been tested prior to the start of the study, or broke down results by staff role. Only one reported on estimated viral load (as inferred from cycle threshold [Ct] value), and none reported attempting viral culture.\n\nAdded value of this studyThis is the first published study of which we are aware that has been conducted across multiple sites in England and is therefore potentially more representative of the overall prevalence of SARS-CoV-2 infectivity amongst HCWs in the workplace. We explored symptoms in the preceding month in more depth than previous studies and in addition asked about previous test results and various exposures, also not commented on in other studies. Additionally, we attempted to isolate virus from some PCR-positive samples to look for evidence of infectious virus.\n\nImplications of all the available evidenceAuthors of previous studies have proposed that screening asymptomatic HCWs for SARS-CoV-2 RNA may be beneficial, in addition to screening symptomatic HCWs. Our findings suggest that when prevalence of COVID-19 is very low, routine and repeated screening would be unlikely to have significant value, especially given the majority of participants testing positive in this study were unlikely to be infectious. However, in situations where prevalence levels are high in a particular population or setting, for example in a hospital outbreak, widening the case definition, or screening all HCWs irrespective of symptoms, may be of benefit.", + "rel_num_authors": 23, "rel_authors": [ { - "author_name": "Shan Wei", - "author_inst": "Columbia University Irving Medical Center" + "author_name": "Colin Brown", + "author_inst": "Public Health England" }, { - "author_name": "Esther Kohl", - "author_inst": "Columbia University Irving Medical Center" + "author_name": "Kathryn Clare", + "author_inst": "Public Health England" }, { - "author_name": "Alexandre Djandji", - "author_inst": "Columbia University Irving Medical Center" + "author_name": "Meera Chand", + "author_inst": "Public Health England" }, { - "author_name": "Stephanie Morgan", - "author_inst": "Columbia University Irving Medical Center" + "author_name": "Julie Andrews", + "author_inst": "Whittington Health NHS Trust" }, { - "author_name": "Susan Whittier", - "author_inst": "Columbia University Irving Medical Center" + "author_name": "Cressida Auckland", + "author_inst": "Royal Devon & Exeter NHS Foundation Trust" }, { - "author_name": "Mahesh Mansukhani", - "author_inst": "Columbia University Irving Medical Center" + "author_name": "Sarah Beshir", + "author_inst": "The Hospital of St John & St Elizabeth" }, { - "author_name": "Raymond Yeh", - "author_inst": "Columbia University Irving Medical Center" + "author_name": "Saher Choudhry", + "author_inst": "Leeds Teaching Hospitals NHS Trust & University of Leeds" }, { - "author_name": "Juan Carlos Alejaldre", - "author_inst": "Columbia University Irving Medical Center" + "author_name": "Kerrie Davies", + "author_inst": "Leeds Teaching Hospitals NHS Trust" }, { - "author_name": "Elaine Fleck", - "author_inst": "Columbia University Irving Medical Center" + "author_name": "Jane Freeman", + "author_inst": "Leeds Teaching Hospitals NHS Trust & University of Leeds" }, { - "author_name": "Mary D'Alton", - "author_inst": "Columbia University Irving Medical Center" + "author_name": "Andrew Gallini", + "author_inst": "The Hospital of St John & St Elizabeth" }, { - "author_name": "Yousin Suh", - "author_inst": "Columbia University Irving Medical Center" + "author_name": "Rachel Moores", + "author_inst": "The Royal Free London NHS Foundation Trust" }, { - "author_name": "Zev Williams", - "author_inst": "Columbia University Irving Medical Center" + "author_name": "Trupti Patel", + "author_inst": "Whittington Health NHS Trust" + }, + { + "author_name": "Gosia Poznalska", + "author_inst": "Royal Devon & Exeter NHS Foundation Trust" + }, + { + "author_name": "Alison Rodger", + "author_inst": "The Royal Free London NHS Foundation Trust & Institute for Global Health, UCL London" + }, + { + "author_name": "Stella Roberts", + "author_inst": "Royal Devon & Exeter NHS Foundation Trust" + }, + { + "author_name": "Christopher Rooney", + "author_inst": "Leeds Teaching Hospitals NHS Trust & University of Leeds" + }, + { + "author_name": "Mark Wilcox", + "author_inst": "Leeds Teaching Hospitals NHS Trust & University of Leeds" + }, + { + "author_name": "Simon Warren", + "author_inst": "The Royal Free London NHS Foundation Trust & The Royal National Orthopaedic Hospital, Stanmore" + }, + { + "author_name": "Joanna Ellis", + "author_inst": "Public Health England" + }, + { + "author_name": "Robin Gopal", + "author_inst": "Public Health England" + }, + { + "author_name": "Jake Dunning", + "author_inst": "Public Health England & The Royal Free London NHS Foundation Trust" + }, + { + "author_name": "Maria Zambon", + "author_inst": "Public Health England" + }, + { + "author_name": "Susan Hopkins", + "author_inst": "Public Health England" } ], "version": "1", - "license": "cc_no", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1362406,85 +1362515,25 @@ "category": "primary care research" }, { - "rel_doi": "10.1101/2020.06.14.20130682", - "rel_title": "Development and validation of a tool to appraise guidelines on SARS-CoV-2 infection prevention strategies in healthcare workers", + "rel_doi": "10.1101/2020.06.13.20130294", + "rel_title": "Impact of social distancing measures for preventing coronavirus disease 2019 : A systematic review and meta-analysis protocol", "rel_date": "2020-06-16", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.14.20130682", - "rel_abs": "BackgroundClinical guidelines on infection prevention strategies in healthcare workers (HCWs) play an important role in protecting them during the SARS-CoV-2 pandemic. Poorly constructed guidelines that are not comprehensive and are ambiguous may compromise HCWs safety. We aimed to develop and validate a tool to appraise guidelines on infection prevention strategies in HCWs.\n\nMethodsA 3-stage, web-based, Delphi consensus-building process among a panel of diverse HCWs and healthcare managers was utilised. We validated the tool by appraising 40 international, specialty-specific and procedure-specific guidelines along with national guidelines from countries with a wide range of gross national income.\n\nResultsOverall consensus ([≥]75%) was reached at the end of three rounds for all six domains included in the tool. The chosen domains allowed appraisal of guidelines in relation to general characteristics (domain-1), recommendations on engineering (domain-2) and administrative aspects (domain 4-6) of infection prevention, as well as personal protection equipment (PPE) use (domain-3). The appraisal tool performed well across all domains and inter-rater agreement was excellent. All included guidelines performed relatively better in domains 1-3 compared with domains 4-6 and this was more evident in guidelines originating from lower income countries.\n\nConclusionThe guideline appraisal tool was robust and easy to use. Recommendations on engineering aspects of infection prevention, administrative measures that promote optimal PPE use and HCW wellbeing were generally lacking in assessed guidelines. This tool may enable health systems to adopt high quality HCW infection prevention guidelines during SARS-CoV-2 pandemic and may also provide a framework for future guideline development.\n\nFundingNo funding received.\n\nKey SummaryWe developed and validated a guideline-appraisal tool by appraising 40 different guidelines from countries with varying GNI. This tool may help healthcare systems to adopt high-quality HCW infection-prevention guidelines during COVID-19 pandemic and may also provide a guideline development framework.", - "rel_num_authors": 17, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.13.20130294", + "rel_abs": "IntroductionSocial distancing measures (SDMs) protect public health from the outbreak of coronavirus disease 2019 (COVID-19). However, the impact of SDMs has been inconsistent and unclear. This study aims to assess the effects of SDMs (e.g. isolation, quarantine) for reducing the transmission of COVID-19.\n\nMethods and analysisWe will conduct a systematic review meta-analysis research of both randomised controlled trials and non-randomised controlled trials. We will search MEDLINE, EMBASE, Allied & Complementary Medicine, COVID-19 Research and WHO database on COVID-19 for primary studies assessing the effects of SDMs (e.g. isolation, quarantine) for reducing the transmission of COVID-19, and will be reported in accordance with PRISMA statement. The PRISMA-P checklist will be used while preparing this protocol. We will use Joanna Briggs Institute guidelines (JBI Critical Appraisal Checklists) to assess the methodological qualities and synthesised performing thematic analysis. Two reviewers will independently screen the papers and extracted data. If sufficient data are available, the random-effects model for meta-analysis will be performed to measure the effect size of SDMs or the strengths of relationships. To assess the heterogeneity of effects, I2 together with the observed effects (Q-value, with degrees of freedom) will be used to provide the true effects in the analysis.\n\nEthics and disseminationEthics approval and consent will not be required for this systematic review of the literature as it does not involve human participation. We will be able to disseminate the study findings using the following strategies: we will be publishing at least one paper in peer-reviewed journals, and an abstract will be presented at suitable national/international conferences or workshops. We will also share important information with public health authorities as well as with the World Health Organization. In addition, we may post the submitted manuscript under review to bioRxiv, medRxiv, or other relevant pre-print servers.\n\nStrengths and limitations of this studyO_LITo our knowledge, this study will be the first systematic review to examine the impact of social distancing measures to reduce transmission of COVID-19.\nC_LIO_LIThis study will offer highest level of evidence for informed decisions, drawing a broader framework.\nC_LIO_LIThis protocol reduces the possibility of duplication, provides transparency to the methods and procedures that will be used, minimise potential biases and allows peer-review.\nC_LIO_LIThis research is not externally funded, and therefore time and resource will be constrained.\nC_LIO_LIIf included studies will be variable in sample size, quality and population, which may open to bias, and the heterogeneity of data will preclude a meaningful meta-analysis to measure the impact of specific SDMs\nC_LI", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Ashwin Subramaniam", - "author_inst": "Peninsula Health" - }, - { - "author_name": "Mallikarjuna Reddy", - "author_inst": "Peninsula Health, Calvary Hospital" - }, - { - "author_name": "Alexander Zubarev", - "author_inst": "Peninsula Health" - }, - { - "author_name": "Umesh Kadam", - "author_inst": "Werribee Hospital, Casey Hospital" - }, - { - "author_name": "Zheng Jie Lim", - "author_inst": "Ballarat Base Hospital" - }, - { - "author_name": "Chris Anstey", - "author_inst": "Griffith University University of Queensland" + "author_name": "Krishna Regmi", + "author_inst": "Institute for Health Research, University of Bedfordshire, UK; Centre for Medical Education, School of Medicine, University of Dundee, UK" }, { - "author_name": "Shailesh Bihari", - "author_inst": "Flinders University andMedical Centre" - }, - { - "author_name": "Jumana Haji", - "author_inst": "Aster CMI Hospital Bangalore" - }, - { - "author_name": "Subhathra Karunanithi", - "author_inst": "Valley Medical Group, New Jersey" - }, - { - "author_name": "Jinghang Luo", - "author_inst": "Western Health" - }, - { - "author_name": "Neil Mara", - "author_inst": "NHS" - }, - { - "author_name": "Saikat Mitra", - "author_inst": "National University Hospital, Singapore" - }, - { - "author_name": "Kollengode Ramanathan", - "author_inst": "National University Hospital Singapore" - }, - { - "author_name": "Arvind Rajamani", - "author_inst": "Nepean Clinical School University of Sydney" - }, - { - "author_name": "Francesca Rubulotta", - "author_inst": "Imperial College London" - }, - { - "author_name": "Erik Svensk", - "author_inst": "Sundsvall hospital, Sundsvall, Sweden" - }, - { - "author_name": "Kiran Shekar", - "author_inst": "The Prince Charles Hospital" + "author_name": "Cho Mar Lwin", + "author_inst": "University of Medicine Mandalay, Chan Aye Thar Zan, Mandalay, 05024, Myanmar" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "public and global health" }, @@ -1364068,35 +1364117,47 @@ "category": "genetics" }, { - "rel_doi": "10.1101/2020.06.15.20131375", - "rel_title": "COVID-19 IN INDIA: MODELLING, FORECASTING AND STATE-WISE COMPARISON", + "rel_doi": "10.1101/2020.06.11.147025", + "rel_title": "COVID-19-related coagulopathy, is transferrin a missing link?", "rel_date": "2020-06-16", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.15.20131375", - "rel_abs": "COVID-19 has turned the whole world upside down economically and socially. COVID-19 pandemic has caused around five crores of cases and three lakhs deaths globally as of 27 May 2020. This paper adopts four mathematical growth models. Basic models are encouraged because these models can make predictions with the available data and variables in the current scenario of COVID-19 pandemic. The best-fitted model is identified in accordance with the value of the coefficient of determination. As per the best model, there might be greater than 16 lakhs cases at the infection end in India. After predicting the future size of the pandemic, we analyzed how the disease severity varies among the Indian states and union territories using Case Fatality Rates (CFR).", - "rel_num_authors": 4, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2020.06.11.147025", + "rel_abs": "SARS-CoV-2 is the causative agent of COVID-19. Severe COVID-19 disease has been associated with disseminated intravascular coagulation and thrombosis, but the mechanisms underlying COVID-19-related coagulopathy remain unknown. Since the risk of severe COVID-19 disease is higher in males than in females and increases with age, we combined proteomics data from SARS-CoV-2-infected cells with human gene expression data from the Genotype-Tissue Expression (GTEx) database to identify gene products involved in coagulation that change with age, differ in their levels between females and males, and are regulated in response to SARS-CoV-2 infection. This resulted in the identification of transferrin as a candidate coagulation promoter, whose levels increases with age and are higher in males than in females and that is increased upon SARS-CoV-2 infection. A systematic investigation of gene products associated with the GO term \"blood coagulation\" did not reveal further high confidence candidates, which are likely to contribute to COVID-19-related coagulopathy. In conclusion, the role of transferrin should be considered in the course of COVID-19 disease and further examined in ongoing clinic-pathological investigations.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Ankitha Jose", - "author_inst": "St. Thomas College, Palai" + "author_name": "Katie-May McLaughlin", + "author_inst": "University of Kent" }, { - "author_name": "Ashid Salim", - "author_inst": "St.Thomas College , Palai" + "author_name": "Marco Bechtel", + "author_inst": "Goethe-University" }, { - "author_name": "Noel George", - "author_inst": "p value solutions , palai" + "author_name": "Denisa Bojkova", + "author_inst": "Goethe-University" + }, + { + "author_name": "Sandra Ciesek", + "author_inst": "Goethe Universtiy Frankfurt" }, { - "author_name": "Silpa Subhash", - "author_inst": "Cochin University of Science and Technology, Kerala, India" + "author_name": "Mark N Wass", + "author_inst": "University of Kent" + }, + { + "author_name": "Martin Michaelis", + "author_inst": "University of Kent" + }, + { + "author_name": "Jindrich N Cinatl Jr.", + "author_inst": "Klinikum der Goethe-Universitaet" } ], "version": "1", - "license": "cc_no", - "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "license": "cc_by_nc_nd", + "type": "new results", + "category": "microbiology" }, { "rel_doi": "10.1101/2020.06.13.150243", @@ -1365934,63 +1365995,127 @@ "category": "neuroscience" }, { - "rel_doi": "10.1101/2020.06.15.151647", - "rel_title": "Genome-wide mapping of therapeutically-relevant SARS-CoV-2 RNA structures", + "rel_doi": "10.1101/2020.06.15.152587", + "rel_title": "Microscopy-based assay for semi-quantitative detection of SARS-CoV-2 specific antibodies in human sera", "rel_date": "2020-06-15", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.06.15.151647", - "rel_abs": "SARS-CoV-2 is a betacoronavirus with a linear single-stranded, positive-sense RNA genome of [~]30 kb, whose outbreak caused the still ongoing COVID-19 pandemic. The ability of coronaviruses to rapidly evolve, adapt, and cross species barriers makes the development of effective and durable therapeutic strategies a challenging and urgent need. As for other RNA viruses, genomic RNA structures are expected to play crucial roles in several steps of the coronavirus replication cycle. Despite this, only a handful of functionally conserved structural elements within coronavirus RNA genomes have been identified to date.\n\nHere, we performed RNA structure probing by SHAPE-MaP to obtain a single-base resolution secondary structure map of the full SARS-CoV-2 coronavirus genome. The SHAPE-MaP probing data recapitulate the previously described coronavirus RNA elements (5' UTR, ribosomal frameshifting element, and 3' UTR), and reveal new structures. Secondary structure-restrained 3D modeling of highly-structured regions across the SARS-CoV-2 genome allowed for the identification of several putative druggable pockets. Furthermore, [~]8% of the identified structure elements show significant covariation among SARS-CoV-2 and other coronaviruses, hinting at their functionally-conserved role. In addition, we identify a set of persistently single-stranded regions having high sequence conservation, suitable for the development of antisense oligonucleotide therapeutics.\n\nCollectively, our work lays the foundation for the development of innovative RNA-targeted therapeutic strategies to fight SARS-related infections.", - "rel_num_authors": 11, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.06.15.152587", + "rel_abs": "Emergence of the novel pathogenic coronavirus SARS-CoV-2 and its rapid pandemic spread presents numerous questions and challenges that demand immediate attention. Among these is the urgent need for a better understanding of humoral immune response against the virus as a basis for developing public health strategies to control viral spread. For this, sensitive, specific and quantitative serological assays are required. Here we describe the development of a semi-quantitative high-content microscopy-based assay for detection of three major classes (IgG, IgA and IgM) of SARS-CoV-2 specific antibodies in human samples. The possibility to detect antibodies against the entire viral proteome together with a robust semi-automated image analysis workflow resulted in specific, sensitive and unbiased assay which complements the portfolio of SARS-CoV-2 serological assays. The procedure described here has been used for clinical studies and provides a general framework for the application of quantitative high-throughput microscopy to rapidly develop serological assays for emerging virus infections.", + "rel_num_authors": 27, "rel_authors": [ { - "author_name": "Ilaria Manfredonia", - "author_inst": "University of Groningen" + "author_name": "Constantin Pape", + "author_inst": "HCI/IWR, Heidelberg University, Heidelberg, Germany and European Molecular Biology Laboratory, Heidelberg, Germany" }, { - "author_name": "Chandran Nithin", - "author_inst": "International Institute of Molecular and Cell Biology (Warsaw)" + "author_name": "Roman Remme", + "author_inst": "HCI/IWR, Heidelberg University, Heidelberg, Germany" }, { - "author_name": "Almudena Ponce-Salvatierra", - "author_inst": "International Institute of Molecular and Cell Biology (Warsaw)" + "author_name": "Adrian Wolny", + "author_inst": "HCI/IWR, Heidelberg University, Heidelberg, Germany and European Molecular Biology Laboratory, Heidelberg, Germany" }, { - "author_name": "Pritha Ghosh", - "author_inst": "Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology" + "author_name": "Sylvia Olberg", + "author_inst": "Department of Infectious Diseases, Virology, University Hospital Heidelberg, Heidelberg, Germany" }, { - "author_name": "Tomasz K. Wirecki", - "author_inst": "Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology" + "author_name": "Steffen Wolf", + "author_inst": "HCI/IWR, Heidelberg University, Heidelberg, Germany" }, { - "author_name": "Tycho Marinus", - "author_inst": "University of Groningen" + "author_name": "Lorenzo Cerrone", + "author_inst": "HCI/IWR, Heidelberg University, Heidelberg, Germany" }, { - "author_name": "Natacha S. Ogando", - "author_inst": "Leiden University Medical Center" + "author_name": "Mirko Cortese", + "author_inst": "Department of Infectious Diseases, Molecular Virology, University Hospital Heidelberg, Heidelberg, Germany" }, { - "author_name": "Eric J Snijder", - "author_inst": "Leiden University Medical Center" + "author_name": "Severina Klaus", + "author_inst": "Department of Infectious Diseases, Parasitology, University Hospital Heidelberg, Heidelberg, Germany" }, { - "author_name": "Martijn J van Hemert", - "author_inst": "Leiden University Medical Center" + "author_name": "Bojana Lucic", + "author_inst": "Department of Infectious Diseases, Integrative Virology, University Hospital Heidelberg, Heidelberg, Germany" }, { - "author_name": "Janusz M. Bujnicki", - "author_inst": "International Institute of Molecular and Cell Biology (Warsaw)" + "author_name": "Stephanie Ullrich", + "author_inst": "Department of Infectious Diseases, Virology, University Hospital Heidelberg, Heidelberg, Germany" + }, + { + "author_name": "Maria Anders-\u00d6sswein", + "author_inst": "Department of Infectious Diseases, Virology, University Hospital Heidelberg, Heidelberg, Germany" }, { - "author_name": "Danny Incarnato", - "author_inst": "Groningen Biomolecular Sciences and Biotechnology Institute (GBB), University of Groningen" + "author_name": "Stefanie Wolf", + "author_inst": "Department of Infectious Diseases, Virology, University Hospital Heidelberg, Heidelberg, Germany" + }, + { + "author_name": "Cerikan Berati", + "author_inst": "Department of Infectious Diseases, Molecular Virology, University Hospital Heidelberg, Heidelberg, Germany" + }, + { + "author_name": "Christopher J. Neufeldt", + "author_inst": "Department of Infectious Diseases, Molecular Virology, University Hospital Heidelberg, Heidelberg, Germany" + }, + { + "author_name": "Markus Ganter", + "author_inst": "Department of Infectious Diseases, Parasitology, University Hospital Heidelberg, Heidelberg, Germany" + }, + { + "author_name": "Paul Schnitzler", + "author_inst": "Department of Infectious Diseases, Virology, University Hospital Heidelberg, Heidelberg, Germany" + }, + { + "author_name": "Uta Merle", + "author_inst": "Department of Gastroenterology and Hepatology, University Hospital of Heidelberg, Heidelberg, Germany" + }, + { + "author_name": "Marina Lusic", + "author_inst": "Department of Infectious Diseases, Integrative Virology, University Hospital Heidelberg, Heidelberg, Germany" + }, + { + "author_name": "Steeve Boulant", + "author_inst": "Department of Infectious Diseases, Virology, University Hospital Heidelberg, Heidelberg, Germany and Research Group Cellular polarity and viral infection, Germa" + }, + { + "author_name": "Megan Stanifer", + "author_inst": "Department of Infectious Diseases, Molecular Virology, University Hospital Heidelberg, Heidelberg, Germany and Research Group Cellular polarity and viral infect" + }, + { + "author_name": "Ralf Bartenschlager", + "author_inst": "Department of Infectious Diseases, Molecular Virology, University Hospital Heidelberg, Heidelberg, Germany and German Center for Infection Research, Heidelberg," + }, + { + "author_name": "Fred A. Hamprecht", + "author_inst": "HCI/IWR, Heidelberg University, Heidelberg, Germany" + }, + { + "author_name": "Anna Kreshuk", + "author_inst": "European Molecular Biology Laboratory, Heidelberg, Germany" + }, + { + "author_name": "Christian Tischer", + "author_inst": "European Molecular Biology Laboratory, Heidelberg, Germany" + }, + { + "author_name": "Hans-Georg Kr\u00e4usslich", + "author_inst": "Department of Infectious Diseases, Virology, University Hospital Heidelberg, Heidelberg, Germany and German Center for Infection Research, Heidelberg, Germany" + }, + { + "author_name": "Barbara M\u00fcller", + "author_inst": "Department of Infectious Diseases, Virology, University Hospital Heidelberg, Heidelberg, Germany" + }, + { + "author_name": "Vibor Laketa", + "author_inst": "Department of Infectious Diseases, Virology, University Hospital Heidelberg, Heidelberg, Germany and German Center for Infection Research, Heidelberg, Germany" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by_nc_nd", "type": "new results", - "category": "genetics" + "category": "microbiology" }, { "rel_doi": "10.1101/2020.06.15.151779", @@ -1367576,35 +1367701,51 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.06.12.20129536", - "rel_title": "High Incidence of Venous Thrombosis in Patients with Moderate to Severe COVID-19", + "rel_doi": "10.1101/2020.06.12.20129213", + "rel_title": "ASSESSING THE POTENTIAL IMPACT OF TRANSMISSION DURING PROLONGED VIRAL SHEDDING ON THE EFFECT OF LOCKDOWN RELAXATION ON COVID-19", "rel_date": "2020-06-14", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.12.20129536", - "rel_abs": "COVID-19 predisposes to venous thromboembolism and there are multiple data regarding high incidence of venous thrombosis in critical COVID-19 patients, however reports on this complication in less severe patients are not widely available.\n\nThe aim of this study was to investigate the incidence of deep-vein thrombosis (DVT) in patients with moderate to severe COVID-19 and to assess the prevalence of DVT with lung computerized tomography (lung CT) exams, clinical information and lab data. This study examined 75 consecutive patients with moderate to severe COVID-19, with specific exclusions.\n\nMETHODSAlmost all patients (pts) admitted to our hospital in the first half of May underwent comprehensive vein ultrasonography. 75 pts (aged 27-92 y, median - 63 y, 36 males and 39 females) with moderate to severe COVID-19 were included in our study.\n\nRESULTSSpontaneous echo contrast (decreased blood velocity and blood stasis) was detected in common femoral veins in 53 pts (70.7%). DVT was found in 15 pts (20%). The vast majority of those with DVT (13 pts, 86.7%) had thrombi only in calf veins and ileofemoral thrombosis was detected in 2 pts with DVT (13.3%). There was no significant observed difference between DVT and non-DVT patients with respect to age, underlying diseases, lung CT scores and SpaO2 at admission. There was also no significant observed difference between DVT and non-DVT patients with respect to both \"time from symptoms onset to admission\" and with respect to the majority of lab data.\n\nHowever, a significant difference was observed in D-dimer level (1.87 {+/-} 1.62 vs 0.51 {+/-} 0,4 mcg/mL p<0.0001) and C-reactive protein (116.9 {+/-} 83,6 and 65.1 {+/-} 64.98 mg/L, p = 0.014) for patients with DVT and patients without DVT respectably (Receiver operating characteristics (ROC) curve analysis revealed that the level of D-dimer [≥] 0.69 mcg/mL is the predictor of DVT with a sensitivity of 76.9%, a specificity of 77.6%, p < 0.001 (AUC area under curve = 0.7944). Logistic regression confirmed that D-dimer is an independent predictor of DVT and patients with D-dimer [≥] 0.69 mcg/mL have odds ratio (OR) of developing DVT = 5.1 (confidence interval [CI] 1.9 - 13.5)).\n\nCONCLUSIONPatients with moderate to severe COVID-19 show high incidence of DVT, indicating that moderate to severe COVID-19 patients may require an early administration of anticoagulation therapy as part of their treatment. Such therapy may be continued after hospital discharge. Based on these findings, these patients may also require a follow-up with vein ultrasonography after recovery to rule out DVT.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.12.20129213", + "rel_abs": "AO_SCPLOWBSTRACTC_SCPLOWA key parameter in epidemiological modeling which characterizes the spread of an infectious disease is the mean serial interval. There is increasing evidence supporting a prolonged viral shedding window for COVID-19, but the transmissibility in this phase is unclear. Based on this, we build a model including an additional compartment of infectious individuals who stay infectious for a longer duration than the reported serial interval, but with infectivity reduced to varying degrees. We find that such an assumption also yields a plausible model in explaining the data observed so far, but has different implications for the future predictions in case of a gradual easing on the lockdown measures. Considering the role of modeling in important decisions such as easing lockdown measures and adjusting hospital capacity, we believe that it is critically important to consider a chronically infectious population as an alternative modeling approach to better interpret the transmission dynamics of COVID-19.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Oleg B Kerbikov", - "author_inst": "Federal State Clinical Research Hospital FMBA of Russia" + "author_name": "Burcu Tepekule", + "author_inst": "University Hospital Zurich, University of Zurich Zurich, Switzerland" }, { - "author_name": "Pavel Yu Orekhov", - "author_inst": "Federal State Clinical Research Hospital FMBA of Russia" + "author_name": "Anthony Hauser", + "author_inst": "Institute of Social and Preventive Medicine, University of Bern, Switzerland" }, { - "author_name": "Ekaterina N Borskaya", - "author_inst": "Burnasyan Federal Medical Biophysical Center FMBA of Russia" + "author_name": "Viacheslav Nikolaevich Kachalov", + "author_inst": "University of Zurich, University Hospital of Zurich" }, { - "author_name": "Natalia S Nosenko", - "author_inst": "Federal State Clinical Research Hospital FMBA of Russia" + "author_name": "Sara Andresen", + "author_inst": "University Hospital Zurich, University of Zurich Zurich, Switzerland" + }, + { + "author_name": "Thomas Scheier", + "author_inst": "University Hospital Zurich Zurich, Switzerland" + }, + { + "author_name": "Peter W. Schreiber", + "author_inst": "University Hospital Zurich, University of Zurich Zurich, Switzerland" + }, + { + "author_name": "Huldrych F. Guenthard", + "author_inst": "University Hospital Zurich Zurich, Switzerland" + }, + { + "author_name": "Roger D. Kouyos", + "author_inst": "University Hospital Zurich, University of Zurich Zurich, Switzerland" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2020.06.12.20129197", @@ -1368934,31 +1369075,39 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.06.12.20129791", - "rel_title": "Dynamics of psychological responses to Covid-19 in India: A longitudinal study", + "rel_doi": "10.1101/2020.06.12.20129650", + "rel_title": "Burnout among healthcare professionals during COVID-19 pandemic: a cross-sectional study", "rel_date": "2020-06-13", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.12.20129791", - "rel_abs": "To curb the spread of the novel coronavirus, India announced a nationwide lockdown on 24th March 2020 for 21 days, later extended for a longer time. This long period of lockdown greatly disrupted routine life and likely affecting citizens psychological well-being. The psychological toll of the pandemic on Indians is documented. However, no study has assessed whether the psychological toll changed over time due to repeated extensions of the lockdown. We followed up 159 Indian adults during the first two months of the lockdown to assess any change in their anxiety, stress, and depressive symptoms. Multilevel linear regression models of repeated observations nested within individuals, adjusted for socio-demographic covariates, showed that anxiety ({beta}=0.81, CI: 0.03, 1.60), stress ({beta}=0.51, CI: 0.32, 0.70), and depressive symptoms ({beta}=0.37, CI: 0.13, 0.60) increased over time during the lockdown. This increase was higher among women than men independent of covariates. Individual resilience was negatively associated with the psychological outcomes. This suggests that the state needs to address the current mental health impacts of a long-drawn out lockdown and its long-term sequelae. Disproportionate burden on women needs immediate attention. Sustainable change requires addressing the root causes driving the gender inequalities in psychological distress during such crises.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.12.20129650", + "rel_abs": "BackgroundThe unpredictable nature of the new COVID-19 pandemic and the already alarming incidence of healthcare workers being affected can have a significant impact on the psychological well-being of the staff.\n\nObjectiveTo describe the prevalence of burnout among healthcare professionals and the associated factors.\n\nDesignCross-sectional survey.\n\nSettingEight university affiliated hospitals in the capital city of Tehran, Iran.\n\nParticipantsAll healthcare workers at the study sites who had been taking care of COVID-19 patients.\n\nMeasurementsAge, gender, marital status, having children, hospital, job category, experience, and work load, as well as the level of burnout in each subscale.\n\nResults326 persons (53.0%) experienced high levels of burnout. The average score in emotional exhaustion, depersonalization and lack of personal accomplishment was 26.6, 10.2, and 27.3, respectively. The level of burnout in the three subscales varied based on the personal as well as work related factors and gender was the only variable that was associated with high levels of all three domains.\n\nLimitationsThere was no control group and thus we cannot claim a causal relationship between COVID-19 and the observed level of burnout. Not all confounding factors might have been accounted for.\n\nConclusionsBurnout is prevalent among healthcare workers caring for COVID-19 patients. Age, gender, job category, and site of practice contribute to the level of burnout that the staff experience.\n\nFunding sourceNone", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Anvita Gopal", - "author_inst": "Indian Institute of Technology Gandhinagar" + "author_name": "Mohammad Jalili", + "author_inst": "Tehran University of Medical Sciences" }, { - "author_name": "Anupam Joya Sharma", - "author_inst": "IIT Gandhinagar" + "author_name": "Mahtab Niroomand", + "author_inst": "Shahid Beheshti University of Medical Sciences" }, { - "author_name": "Malavika Ambale Subramanyam", - "author_inst": "IIT Gandhinagar" + "author_name": "Fahimeh Hadavand", + "author_inst": "Shahid Beheshti University of Medical Sciences" + }, + { + "author_name": "Kataun Zeinali", + "author_inst": "Shahid Beheshti Universityof Medical Sciences" + }, + { + "author_name": "Akbar Fotouhi", + "author_inst": "Tehran University of Medical Sciences" } ], "version": "1", - "license": "cc_by", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "occupational and environmental health" }, { "rel_doi": "10.1101/2020.06.12.20129908", @@ -1370316,25 +1370465,25 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.06.09.20126573", - "rel_title": "Retarded logistic equation as a universal dynamic model for the spread of COVID-19", + "rel_doi": "10.1101/2020.06.11.20091322", + "rel_title": "A study on the appropriate use of topdown approachfor stepping up economic activities in districts ofdifferent States/Union Territories in India", "rel_date": "2020-06-12", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.09.20126573", - "rel_abs": "In this work we propose the retarded logistic equation as a dynamic model for the spread of COVID-19 all over the world. This equation accounts for asymptomatic transmission, pre-symptomatic or latent transmission as well as contact tracing and isolation, and leads to a transparent definition of the instantaneous reproduction number R. For different parameter values, the model equation admits different classes of solutions. These solution classes correspond to, inter alia, containment of the outbreak via public health measures, exponential growth despite public health measures, containment despite reopening and second wave following reopening. We believe that the spread of COVID in every localized area such as a city, district or county can be accounted for by one of our solution classes. In regions where R > 1 initially despite aggressive epidemic management efforts, we find that if the mitigation measures are sustained, then it is still possible for R to dip below unity when far less than the regions entire population is affected, and from that point onwards the outbreak can be driven to extinction in time. We call this phenomenon partial herd immunity. Our analysis indicates that COVID-19 is an extremely vicious and unpredictable disease which poses unique challenges for public health authorities, on account of which \"case races\" among various countries and states do not serve any purpose and present delusive appearances while ignoring significant determinants.", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.11.20091322", + "rel_abs": "At the beginning of phase 4.0 of lockdown, every State /Union Territories(UT) needs to take appropriate mitigation efforts (lockdown and testing) that may change red zones to orange and even to green zones by May 31, 2020. On the contrary, negligence in following the guidelines (for interventions) strictly, may be alarming and may change green zone status to even the worst red zone status. This has been established through a Statistical model based study here. From the present investigation, the Government can decide the right measures to take up so as to reduce the transmission of the virus and to open partial economic activities in different districts of a state. The whole idea can also be extended to containment zones in a district with sufficient data at hand.", "rel_num_authors": 2, "rel_authors": [ { - "author_name": "B Shayak", - "author_inst": "Cornell University" + "author_name": "Arindom Chakraborty", + "author_inst": "Visva-Bharati University" }, { - "author_name": "Mohit M Sharma", - "author_inst": "Weill Cornell Medicine" + "author_name": "Kalyan Das", + "author_inst": "Indian Institute of Technology Bombay" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1371730,37 +1371879,97 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.06.10.20127837", - "rel_title": "Persistent SARS-CoV-2 replication in severe COVID-19", + "rel_doi": "10.1101/2020.06.08.20125369", + "rel_title": "First Clinical Use of Lenzilumab to Neutralize GM-CSF in Patients with Severe and Critical COVID-19 Pneumonia", "rel_date": "2020-06-12", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.10.20127837", - "rel_abs": "BackgroundThe diagnosis of SARS-CoV-2 infection is based on viral RNA detection by real-time RT-PCR (rRT-PCR) in respiratory samples. This detection can remain positive for weeks without implying virus viability.\n\nMethodsWe have performed cell culture to assess viral replication in 106 respiratory samples rRT-PCR positive for SARS-CoV-2 from 105 patients with COVID-19. Fifty were samples from 50 patients with mild forms of COVID-19 who did not require hospital admission. Fifty-six samples were obtained from 55 hospitalized patients with severe pneumonia. Samples were obtained at different time points covering the time from clinical diagnosis to the follow up during hospital care.\n\nResultsIn 49 samples (49/106, 46.2%) a cytopathic effect (CPE) was detected in cell culture. Our study demonstrates that while in patients with mild COVID-19, viral viability is maintained in fact up to 10 days in patients with severe COVID-19 the virus can remain viable for up to 32 days after the onset of symptoms. Patients with severe COVID-19 as compared with mild cases, presented infective virus in a significantly higher proportion in samples with moderate or low viral load (Ct value > 26): 22/46 (47.8%) versus 7/38 (18.4%), (p <0.01), respectively.\n\nConclusionsPersistent SARS-CoV-2 replication could be demonstrated in severe COVID-19 cases for periods up to 32 days after the onset of symptoms and even at high Ct values. COVID-19 severity is a more determining factor for viral viability than the time elapsed since the onset of symptoms or the Ct value obtained in the RT-PCR assay.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.08.20125369", + "rel_abs": "BackgroundIn COVID-19, high levels of granulocyte macrophage-colony stimulating factor (GM-CSF) and inflammatory myeloid cells correlate with disease severity, cytokine storm, and respiratory failure. With this rationale, we used lenzilumab, an anti-human GM-CSF monoclonal antibody, to treat patients with severe and critical COVID-19 pneumonia.\n\nMethodsHospitalized patients with COVID-19 pneumonia and risk factors for poor outcomes were treated with lenzilumab 600 mg intravenously for three doses through an emergency single-use IND application. Patient characteristics, clinical and laboratory outcomes, and adverse events were recorded. All patients receiving lenzilumab through May 1, 2020 were included in this report.\n\nResultsTwelve patients were treated with lenzilumab. Clinical improvement was observed in 11 out of 12 (92%), with a median time to discharge of 5 days. There was a significant improvement in oxygenation: The proportion of patients with SpO2/FiO2 < 315 at the end of observation was 8% vs. compared to 67% at baseline (p=0.00015). A significant improvement in mean CRP and IL-6 values on day 3 following lenzilumab administration was also observed (137.3 mg/L vs 51.2 mg/L, p = 0.040; 26.8 pg/mL vs 16.1 pg/mL, p = 0.035; respectively). Cytokine analysis showed a reduction in inflammatory myeloid cells two days after lenzilumab treatment. There were no treatment-emergent adverse events attributable to lenzilumab, and no mortality in this cohort of patients with severe and critical COVID-19 pneumonia.\n\nConclusionsIn high-risk COVID-19 patients with severe and critical pneumonia, GM-CSF neutralization with lenzilumab was safe and associated with improved clinical outcomes, oxygen requirement, and cytokine storm.", + "rel_num_authors": 20, "rel_authors": [ { - "author_name": "Maria Dolores Folgueira", - "author_inst": "Hospital Universitario 12 de Octubre" + "author_name": "Zelalem Temesgen", + "author_inst": "Division of Infectious Diseases, Mayo Clinic, Rochester, MN" }, { - "author_name": "Joanna Luczkowiak", - "author_inst": "Instituto de Investigacion Hospital 12 de Octubre" + "author_name": "Mariam Assi", + "author_inst": "Division of Infectious Diseases, Mayo Clinic, Rochester, MN" }, { - "author_name": "Fatima Lasala", - "author_inst": "Instituto de Investigacion Hospital 12 de Octubre" + "author_name": "Paschalis Vergidis", + "author_inst": "Division of Infectious Diseases, Mayo Clinic, Rochester, MN" }, { - "author_name": "Alfredo Perez-Rivilla", - "author_inst": "Hospital Universitario 12 de Octubre" + "author_name": "Stacey A. Rizza", + "author_inst": "Division of Infectious Diseases, Mayo Clinic, Rochester, MN" }, { - "author_name": "Rafael Delgado", - "author_inst": "Hospital Universitario 12 de Octubre" + "author_name": "Philippe R. Bauer", + "author_inst": "Division of Pulmonary and Critical Care Medicine, Mayo Clinic, Rochester, MN" + }, + { + "author_name": "Brian W. Pickering", + "author_inst": "Department of Anesthesia and Critical Care Medicine, Mayo Clinic, Rochester, MN" + }, + { + "author_name": "Raymund R. Razonable", + "author_inst": "Division of Infectious Diseases, Mayo Clinic, Rochester, MN" + }, + { + "author_name": "Claudia R. Libertin", + "author_inst": "Division of Infectious Diseases, Mayo Clinic, Jacksonville, FL" + }, + { + "author_name": "Charles D. Burger", + "author_inst": "Division of Pulmonary Medicine, Mayo Clinic, Jacksonville, FL" + }, + { + "author_name": "Robert Orenstein", + "author_inst": "Division of Infectious Diseases, Mayo Clinic, Scottsdale, AZ" + }, + { + "author_name": "Hugo E. Vargas", + "author_inst": "Division of Gastroenterology and Hepatology, Mayo Clinic, Scottsdale, AZ" + }, + { + "author_name": "Bharath Raj Varatharaj Palraj", + "author_inst": "Division of Infectious Diseases, Mayo Clinic, Rochester, MN" + }, + { + "author_name": "Ala S. Dababneh", + "author_inst": "Division of Infectious Diseases, Mayo Clinic, Rochester, MN" + }, + { + "author_name": "Gabrielle Chappell", + "author_inst": "Humanigen, Inc. Burlingame, CA" + }, + { + "author_name": "Dale Chappell", + "author_inst": "Humanigen, Inc. Burlingame, CA" + }, + { + "author_name": "Omar Ahmed", + "author_inst": "Humanigen, Inc." + }, + { + "author_name": "Reona Sakemura", + "author_inst": "T Cell Engineering, Mayo Clinic, Rochester, MN; Division of Hematology, Mayo Clinic, Rochester, MN" + }, + { + "author_name": "Cameron Durrant", + "author_inst": "Humanigen, Inc. Burlingame, CA" + }, + { + "author_name": "Saad S. Kenderian", + "author_inst": "T Cell Engineering, Division of Hematology, Department of Immunology, Department of Molecular Medicine; Mayo Clinic, Rochester, MN" + }, + { + "author_name": "Andrew Badley", + "author_inst": "Division of Infectious Diseases, Mayo Clinic, Rochester, MN; Department of Molecular Medicine, Mayo Clinic, Rochester, MN" } ], "version": "1", - "license": "cc_by", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1373048,47 +1373257,75 @@ "category": "pediatrics" }, { - "rel_doi": "10.1101/2020.06.11.20128132", - "rel_title": "The curvilinear relationship between the age of adults and their mental health in Iran after its peak of COVID-19 cases", + "rel_doi": "10.1101/2020.06.11.20127936", + "rel_title": "Corona Virus Disease 2019 (COVID-19): Knowledge, attitudes, practices (KAP) and misconceptions in the general population of Katsina State, Nigeria", "rel_date": "2020-06-12", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.11.20128132", - "rel_abs": "The emerging body of research on the predictors of mental health in the COVID-19 pandemic has revealed contradictory findings, which prevent effective psychiatry screening for mental health assistance. This study aims to identify the predictors of nonsomatic pain, depression, anxiety, and distress, especially focusing on age as a nonlinear predictor. We conducted a survey of 474 adults in Iran during April 1-10, 2020, when Iran had just passed its first peak of the COVID-19 pandemic with new confirmed cases. We found that Age had a curvilinear relationship with nonsomatic pain, depression, and anxiety. Age was associated with pain, depression, and anxiety disorders negatively among adults younger than 45 years, but positively among seniors older than 70 years. Adults who were female, unsure about their chronic diseases, and exercised less per day were more likely to have mental health issues. This study advances the use of age as an effective predictor by uncovering a curvilinear relationship between individuals age and mental health issues by using a sample of adults across a wide spectrum of ages. We hope future research on mental health during COVID-19 pays more attention to nonlinear predictors.", - "rel_num_authors": 7, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.11.20127936", + "rel_abs": "IntroductionOver six million cases of Coronavirus Disease 2019 (COVID-19) were reported globally by the second quarter of 2020. The various forms of interventions and measures adopted to control the disease affected peoples social and behavioural practices.\n\nAimThis study aims to investigate COVID-19 related knowledge, attitudes and practices (KAP) as well as misconceptions in Katsina state, one of the largest epicentres of the COVID-19 outbreak in Nigeria.\n\nMethodsThe study is a cross-sectional survey of 722 respondents using an electronic questionnaire through the WhatsApp media platform.\n\nResultsOne thousand five hundred (1500) questionnaires were sent to the general public with a response rate of 48% (i.e. 722 questionnaires completed and returned). Among the respondents, 60% were men, 45% were 25-39 years of age, 56% held bachelors degree/equivalent and above and 54% were employed. The study respondents correct rate in the knowledge questionnaire was 80% suggesting high knowledge of the disease. A significant correlation (P < 0.05) exists between the average knowledge score of the respondents and their level of education ({tau}b = 0.16). Overall, most of the respondents agreed that the COVID-19 will be successfully controlled (84%) and the Nigerian government would win the fight against the pandemic (71%). Men were more likely than female (P < 0.05) to have recently attended a crowded place. Being more educated (bachelors degree or equivalent and above vs diploma or equivalent and below) is associated with good COVID-19 related practices. Among the respondents, 83% held at least one misconception related to COVID-19, with the most frequent being that the virus was created in a laboratory (36%). Respondents with a lower level of education received and trust COVID-19 related information from local radio and television stations and respondents at all levels of education selected that they would trust health unit and health care workers for relevant COVID-19 information.\n\nConclusionAlthough there is high COVID-19 related knowledge among the sample, misconceptions are widespread among the respondents. These misconceptions have consequences on the short- and long-term control efforts against the disease and hence should be incorporated in targeted campaigns. Health care related personnel should be at the forefront of the campaign.", + "rel_num_authors": 14, "rel_authors": [ { - "author_name": "Jiyao Chen", - "author_inst": "Oregon State University" + "author_name": "Murtala Bindawa Isah", + "author_inst": "Umaru Musa Yar'adua University" }, { - "author_name": "Stephen X. Zhang", - "author_inst": "University of Adelaide" + "author_name": "Mahmud Abdulsalam", + "author_inst": "Umaru Musa Yar'adua University" }, { - "author_name": "Yifei Wang", - "author_inst": "Tongji University" + "author_name": "Abubakar Bello", + "author_inst": "Umaru Musa Yar'adua University" }, { - "author_name": "Asghar Afshar Jahanshahi", - "author_inst": "Pontificia Universidad Catolica del Peru" + "author_name": "Muawiyya Idris Ibrahim", + "author_inst": "Umaru Musa yar'adua University" }, { - "author_name": "Maryam Mokhtari Dinani", - "author_inst": "Alzahra University" + "author_name": "Aminu Usman", + "author_inst": "Umaru Musa Yar'adua University" }, { - "author_name": "Abbas Nazarian Madavani", - "author_inst": "Shahid Rajaee Teacher Training University" + "author_name": "Abdullahi Nasir", + "author_inst": "Umaru Musa Yar'adua University" }, { - "author_name": "Khaled Nawaser", - "author_inst": "Arvandan Non-profit Higher Education Institute" + "author_name": "Bashir Abdulkadir", + "author_inst": "Umaru Musa Yar'adua University" + }, + { + "author_name": "Ahmed Rufai Usman", + "author_inst": "Umaru Musa Yar'adua University" + }, + { + "author_name": "Kabir Ibrahim Matazu", + "author_inst": "Umaru Musa Yar'adua University" + }, + { + "author_name": "Aminu Sani", + "author_inst": "Nigeria Defence Academy" + }, + { + "author_name": "Ma'awuya Aliu", + "author_inst": "Katsina State Ministry of Health, Katsina State, Nigeria" + }, + { + "author_name": "Shema'u Abba Kabir", + "author_inst": "Katsina State Primary Healthcare Agency, Katsina State, Nigeria" + }, + { + "author_name": "Abdullahi Shuaibu", + "author_inst": "National Polio Emergency Operations Center, Abuja, Nigeria" + }, + { + "author_name": "Shafique Sani Nass", + "author_inst": "World Health Organization, North-West Zonal Office, Nigeria" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", - "category": "psychiatry and clinical psychology" + "category": "public and global health" }, { "rel_doi": "10.1101/2020.06.11.20128561", @@ -1374890,47 +1375127,51 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2020.06.12.148692", - "rel_title": "Structural basis for potent neutralization of SARS-CoV-2 and role of antibody affinity maturation", + "rel_doi": "10.1101/2020.06.12.148726", + "rel_title": "The D614G mutation in the SARS-CoV-2 spike protein reduces S1 shedding and increases infectivity", "rel_date": "2020-06-12", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.06.12.148692", - "rel_abs": "SARS-CoV-2 is a betacoronavirus virus responsible for the COVID-19 pandemic. Here, we determined the X-ray crystal structure of a potent neutralizing monoclonal antibody, CV30, isolated from a patient infected with SARS-CoV-2, in complex with the receptor binding domain (RBD). The structure reveals CV30s epitope overlaps with the human ACE2 receptor binding site thus providing the structural basis for its neutralization by preventing ACE2 binding.", - "rel_num_authors": 7, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.06.12.148726", + "rel_abs": "SARS coronavirus 2 (SARS-CoV-2) isolates encoding a D614G mutation in the viral spike (S) protein predominate over time in locales where it is found, implying that this change enhances viral transmission. We therefore compared the functional properties of the S proteins with aspartic acid (SD614) and glycine (SG614) at residue 614. We observed that retroviruses pseudotyped with SG614 infected ACE2-expressing cells markedly more efficiently than those with SD614. This greater infectivity was correlated with less S1 shedding and greater incorporation of the S protein into the pseudovirion. Similar results were obtained using the virus-like particles produced with SARS-CoV-2 M, N, E, and S proteins. However, SG614 did not bind ACE2 more efficiently than SD614, and the pseudoviruses containing these S proteins were neutralized with comparable efficiencies by convalescent plasma. These results show SG614 is more stable than SD614, consistent with epidemiological data suggesting that viruses with SG614 transmit more efficiently.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Nicholas K Hurlburt", - "author_inst": "Fred Hutchinson Cancer Research Center" + "author_name": "Lizhou Zhang", + "author_inst": "The Scripps Research Institute" }, { - "author_name": "Yu-Hsin Wan", - "author_inst": "Fred Hutchinson Cancer Research Center" + "author_name": "Cody B Jackson", + "author_inst": "The Scripps Research Institute" }, { - "author_name": "Andrew B Stuart", - "author_inst": "Fred Hutchinson Cancer Research Center" + "author_name": "Huihui Mou", + "author_inst": "The Scripps Research Institute" }, { - "author_name": "Junli Feng", - "author_inst": "Fred Hutchinson Cancer Research Center" + "author_name": "Amrita Ojha", + "author_inst": "The Scripps Research Institute" }, { - "author_name": "Andrew T McGuire", - "author_inst": "Fred Hutchinson Cancer Research Center" + "author_name": "Erumbi S Rangarajan", + "author_inst": "The Scripps Research Institute" }, { - "author_name": "Leonidas Stamatatos", - "author_inst": "Fred Hutchinson Cancer Research Center" + "author_name": "Tina Izard", + "author_inst": "The Scripps Research Institute" }, { - "author_name": "Marie Pancera", - "author_inst": "Fred Hutchinson Cancer Research Center" + "author_name": "Michael Farzan", + "author_inst": "The Scripps Research Institute" + }, + { + "author_name": "Hyeryunc Choe", + "author_inst": "The Scripps Research Institute" } ], "version": "1", "license": "cc_by_nc_nd", "type": "new results", - "category": "immunology" + "category": "microbiology" }, { "rel_doi": "10.1101/2020.06.11.146332", @@ -1376568,157 +1376809,49 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.06.09.20126813", - "rel_title": "Population-scale Longitudinal Mapping of COVID-19 Symptoms, Behavior, and Testing Identifies Contributors to Continued Disease Spread in the United States", + "rel_doi": "10.1101/2020.06.09.20126292", + "rel_title": "COVID-19 and associations with frailty and multimorbidity: a prospective analysis of UK Biobank participants", "rel_date": "2020-06-11", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.09.20126813", - "rel_abs": "Summary ParagraphDespite social distancing and shelter-in-place policies, COVID-19 continues to spread in the United States. A lack of timely information about factors influencing COVID-19 spread and testing has hampered agile responses to the pandemic. We developed How We Feel, an extensible web and mobile application that aggregates self-reported survey responses, to fill gaps in the collection of COVID-19-related data. How We Feel collects longitudinal and geographically localized information on users health, behavior, and demographics. Here we report results from over 500,000 users in the United States from April 2, 2020 to May 12, 2020. We show that self-reported surveys can be used to build predictive models of COVID-19 test results, which may aid in identification of likely COVID-19 positive individuals. We find evidence among our users for asymptomatic or presymptomatic presentation, as well as for household and community exposure, occupation, and demographics being strong risk factors for COVID-19. We further reveal factors for which users have been SARS-CoV-2 PCR tested, as well as the temporal dynamics of self-reported symptoms and self-isolation behavior in positive and negative users. These results highlight the utility of collecting a diverse set of symptomatic, demographic, and behavioral self-reported data to fight the COVID-19 pandemic.", - "rel_num_authors": 36, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.09.20126292", + "rel_abs": "BackgroundFrailty and multimorbidity have been suggested as risk factors for severe COVID-19 disease.\n\nAimsWe investigated whether frailty and multimorbidity were associated with risk of hospitalisation with COVID-19 in the UK Biobank.\n\nMethods502,640 participants aged 40-69 years at baseline (54-79 years at COVID-19 testing) were recruited across UK 2006-10. A modified assessment of frailty using Frieds classification was generated from baseline data. COVID-19 test results (England) were available 16/03/2020-01/06/2020, mostly taken in hospital settings. Logistic regression was used to discern associations between frailty, multimorbidity and COVID-19 diagnoses, adjusting for sex, age, BMI, ethnicity, education, smoking and number of comorbidity groupings, comparing COVID-19 positive, COVID-19 negative and non-tested groups.\n\nResults4,510 participants were tested for COVID-19 (positive=1,326, negative=3,184). 497,996 participants were not tested. Compared to the non-tested group, after adjustment, COVID-19 positive participants were more likely to be frail (OR=1.3 [95% CI=1.1, 1.7]), report slow walking speed (OR=1.3 [1.1, 1.6]), report two or more falls in the past year (OR=1.3 [1.0, 1.5]) and be multimorbid ([≥]4 comorbidity groupings vs 0-1: OR=1.9 [1.5, 2.3]). However, similar strength of associations were apparent when comparing COVID-19 negative and non-tested groups. Furthermore, frailty and multimorbidity were not associated with COVID-19 diagnoses, when comparing COIVD-19 positive and COVID-19 negative participants.\n\nDiscussion and conclusionsFrailty and multimorbidity do not appear to aid risk stratification, in terms of a positive versus negative results of COVID-19 testing. Investigation of the prognostic value of these markers for adverse clinical sequelae following COVID-19 disease is urgently needed.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "William E Allen", - "author_inst": "Harvard University" - }, - { - "author_name": "Han Altae-Tran", - "author_inst": "MIT" - }, - { - "author_name": "James Briggs", - "author_inst": "Broad Institute of MIT and Harvard" - }, - { - "author_name": "Xin Jin", - "author_inst": "Broad Institute of MIT and Harvard" - }, - { - "author_name": "Glen McGee", - "author_inst": "Harvard University" - }, - { - "author_name": "Rumya Raghavan", - "author_inst": "Broad Institute of MIT and Harvard" - }, - { - "author_name": "Andy Shi", - "author_inst": "Harvard University" - }, - { - "author_name": "Mireille Kamariza", - "author_inst": "Harvard University" - }, - { - "author_name": "Nicole Nova", - "author_inst": "Stanford University" - }, - { - "author_name": "Albert Pereta", - "author_inst": "The How We Feel Project" - }, - { - "author_name": "Chris Danford", - "author_inst": "The How We Feel Project" - }, - { - "author_name": "Amine Kamel", - "author_inst": "The How We Feel Project" - }, - { - "author_name": "Patrik Gothe", - "author_inst": "The How We Feel Project" - }, - { - "author_name": "Evrhet Milam", - "author_inst": "The How We Feel Project" - }, - { - "author_name": "Jean Aurambault", - "author_inst": "The How We Feel Project" - }, - { - "author_name": "Thorben Primke", - "author_inst": "The How We Feel Project" - }, - { - "author_name": "Claire Li", - "author_inst": "The How We Feel Project" - }, - { - "author_name": "Josh Inkenbrandt", - "author_inst": "The How We Feel Project" - }, - { - "author_name": "Tuan Huynh", - "author_inst": "The How We Feel Project" - }, - { - "author_name": "Evan Chen", - "author_inst": "The How We Feel Project" - }, - { - "author_name": "Christina Lee", - "author_inst": "The How We Feel Project" - }, - { - "author_name": "Michael Croatto", - "author_inst": "The How We Feel Project" - }, - { - "author_name": "Helen Bentley", - "author_inst": "The How We Feel Project" - }, - { - "author_name": "Wendy Lu", - "author_inst": "The How We Feel Project" - }, - { - "author_name": "Robert Murray", - "author_inst": "The How We Feel Project" - }, - { - "author_name": "Mark Travassos", - "author_inst": "University of Maryland School of Medicine" - }, - { - "author_name": "John Openshaw", - "author_inst": "Stanford University" - }, - { - "author_name": "Brent Coull", - "author_inst": "Harvard University" + "author_name": "S J Woolford", + "author_inst": "MRC Lifecourse Epidemiology Unit" }, { - "author_name": "Casey Greene", - "author_inst": "University of Pennsylvania" + "author_name": "S D'angelo", + "author_inst": "MRC Lifecourse Epidemiology Unit" }, { - "author_name": "Ophir Shalem", - "author_inst": "University of Pennsylvania" + "author_name": "E M Curtis", + "author_inst": "MRC Lifecourse Epidemiology Unit" }, { - "author_name": "Gary King", - "author_inst": "Harvard University" + "author_name": "C M Parsons", + "author_inst": "MRC Lifecourse Epidemiology Unit" }, { - "author_name": "Ryan Probasco", - "author_inst": "The How We Feel Project" + "author_name": "K A Ward", + "author_inst": "MRC Lifecourse Epidemiology Unit" }, { - "author_name": "David Cheng", - "author_inst": "The How We Feel Project" + "author_name": "E M Dennison", + "author_inst": "MRC Lifecourse Epidemiology Unit" }, { - "author_name": "Ben Silbermann", - "author_inst": "The How We Feel Project" + "author_name": "H P Patel", + "author_inst": "MRC Lifecourse Epidemiology Unit" }, { - "author_name": "Feng Zhang", - "author_inst": "MIT" + "author_name": "C Cooper", + "author_inst": "MRC Lifecourse Epidemiology Unit" }, { - "author_name": "Xihong Lin", - "author_inst": "Harvard University" + "author_name": "N C Harvey", + "author_inst": "MRC Lifecourse Epidemiology Unit" } ], "version": "1", @@ -1378406,49 +1378539,25 @@ "category": "bioinformatics" }, { - "rel_doi": "10.1101/2020.06.09.142125", - "rel_title": "Unravelling the debate on heme effects in COVID-19 infections", + "rel_doi": "10.1101/2020.06.09.143271", + "rel_title": "Differential expression of COVID-19-related genes in European Americans and African Americans", "rel_date": "2020-06-10", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.06.09.142125", - "rel_abs": "The SARS-CoV-2 outbreak was recently declared a worldwide pandemic. Infection triggers the respiratory tract disease COVID-19, which is accompanied by serious changes of clinical biomarkers such as hemoglobin and interleukins. The same parameters are altered during hemolysis, which is characterized by an increase in labile heme. We present two approaches that aim at analyzing a potential link between available heme and COVID-19 pathogenesis. Four COVID-19 related proteins, i.e. the host cell proteins ACE2 and TMPRSS2 as well as the viral protein 7a and S protein, were identified as potential heme binders. We also performed a detailed analysis of the common pathways induced by heme and SARS-CoV-2 by superimposition of knowledge graphs covering heme biology and COVID-19 pathophysiology. Herein, focus was laid on inflammatory pathways, and distinct biomarkers as the linking elements. Finally, the results substantially improve our understanding of COVID-19 infections and disease progression of patients with different clinical backgrounds and expand the diagnostic and treatment options.", - "rel_num_authors": 8, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.06.09.143271", + "rel_abs": "The Coronavirus disease 2019 (COVID-19) pandemic has affected African American populations disproportionately in regards to both morbidity and mortality. A multitude of factors likely account for this discrepancy. Gene expression represents the interaction of genetics and environment. To elucidate whether levels of expression of genes implicated in COVID-19 vary in African Americans as compared to European Americans, we re-mine The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) RNA-Seq data. Multiple genes integral to infection, inflammation and immunity are differentially regulated across the two populations. Most notably, F8A2 and F8A3, which encode the HAP40 protein that mediates early endosome movement in Huntingtons Disease, are more highly expressed by up to 24-fold in African Americans. Such differences in gene expression can establish prognostic signatures and have critical implications for precision treatment of diseases such as COVID-19. We advocate routine inclusion of information such as postal code, education level, and profession (as a proxies for socioeconomic condition) and race in the metadata about each individual sampled for sequencing studies. This relatively simple change would enable large-scale data-driven approaches to dissect relationships among race, socio-economic factors, and disease.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Marie-Therese Hopp", - "author_inst": "Pharmaceutical Biochemistry and Bioanalytics, Pharmaceutical Institute, University of Bonn" - }, - { - "author_name": "Daniel Domingo-Fernandez", - "author_inst": "Fraunhofer SCAI" - }, - { - "author_name": "Yojana Gadiya", - "author_inst": "Fraunhofer Institute for Algorithms and Scientific Computing" - }, - { - "author_name": "Milena S Detzel", - "author_inst": "Pharmaceutical Biochemistry and Bioanalytics, Pharmaceutical Institute, University of Bonn" - }, - { - "author_name": "Benjamin F Schmalohr", - "author_inst": "Pharmaceutical Biochemistry and Bioanalytics, Pharmaceutical Institute, University of Bonn" - }, - { - "author_name": "Francel Steinbock", - "author_inst": "Pharmaceutical Biochemistry and Bioanalytics, Pharmaceutical Institute, University of Bonn" - }, - { - "author_name": "Diana Imhof", - "author_inst": "Pharmaceutical Biochemistry and Bioanalytics, Pharmaceutical Institute, University of Bonn" + "author_name": "Urminder Singh", + "author_inst": "Iowa State University" }, { - "author_name": "Martin Hofmann-Apitius", - "author_inst": "Fraunhofer SCAI" + "author_name": "Eve Syrkin Wurtele", + "author_inst": "Iowa State University" } ], "version": "1", - "license": "cc_by", + "license": "cc_no", "type": "new results", "category": "bioinformatics" }, @@ -1380248,87 +1380357,35 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2020.06.08.139329", - "rel_title": "The hypothalamus as a hub for putative SARS-CoV-2 brain infection", + "rel_doi": "10.1101/2020.06.08.107011", + "rel_title": "Molecular modelling predicts SARS-CoV-2 ORF8 protein and human complement Factor 1 catalytic domain sharing common binding site on complement C3b", "rel_date": "2020-06-09", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.06.08.139329", - "rel_abs": "Most patients with COVID-19, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), display neurological symptoms, and respiratory failure in certain cases could be of extra-pulmonary origin. Hypothalamic neural circuits play key roles in sex differences, diabetes, hypertension, obesity and aging, all risk factors for severe COVID-19, besides being connected to olfactory/gustative and brainstem cardiorespiratory centers. Here, human brain gene-expression analyses and immunohistochemistry reveal that the hypothalamus and associated regions express angiotensin-converting enzyme 2 and transmembrane proteinase, serine 2, which mediate SARS-CoV-2 cellular entry, in correlation with genes or pathways involved in physiological functions or viral pathogenesis. A post-mortem patient brain shows viral invasion and replication in both the olfactory bulb and the hypothalamus, while animal studies indicate that sex hormones and metabolic diseases influence this susceptibility.", - "rel_num_authors": 17, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.06.08.107011", + "rel_abs": "Pathogens are often known to use host factor mimicry to take evolutionary advantage. As the function of the non-structural ORF8 protein of SARS-CoV-2 in the context of host-pathogen relationship is still obscure, we investigated its role in host factor mimicry using computational protein modelling techniques. Modest sequence similarity of ORF8 of SARS-CoV-2 with the substrate binding site within the C-terminus serine-protease catalytic domain of human complement factor 1 (F1; PDB ID: 2XRC), prompted us to verify their resemblance at the structural level. The modelled ORF8 protein was found to superimpose on the F1 fragment. Further, protein-protein interaction simulation confirmed ORF8 binding to C3b, an endogenous substrate of F1, via F1-interacting region on C3b. Docking results suggest ORF8 to occupy the binding groove adjacent to the conserved \"arginine-serine\" (RS) F1-mediated cleavage sites on C3b. Comparative H-bond interaction dynamics indicated ORF8/C3b binding to be of higher affinity than the F1/C3b interaction. Hence, ORF8 is predicted to inhibit C3b proteolysis by competing with F1 for C3b binding using molecular mimicry with a possibility of triggering unregulated complement activation. This could offer a mechanistic premise for the unrestrained complement activation observed in large number of SARS-CoV-2 infected patients.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Sreekala Nampoothiri", - "author_inst": "Inserm UMR-S 1172" - }, - { - "author_name": "Florent Sauve", - "author_inst": "Inserm UMR-S 1172" - }, - { - "author_name": "Gaetan Ternier", - "author_inst": "Inserm UMR-S 1172" - }, - { - "author_name": "Daniela Fernandois", - "author_inst": "Inserm UMR-S 1172" - }, - { - "author_name": "Caio Coelho", - "author_inst": "Inserm UMR-S 1172" - }, - { - "author_name": "Monica Imbernon", - "author_inst": "Inserm UMR-S 1172" - }, - { - "author_name": "Eleonora Deligia", - "author_inst": "Inserm UMR-S 1172" - }, - { - "author_name": "Romain Perbet", - "author_inst": "Inserm UMR-S 1172" - }, - { - "author_name": "Vincent Florent", - "author_inst": "Inserm UMR-S 1172" - }, - { - "author_name": "Marc Baroncini", - "author_inst": "Inserm UMR-S 1172" - }, - { - "author_name": "Florence Pasquier", - "author_inst": "Inserm UMR-S 1172" - }, - { - "author_name": "Francois Trottein", - "author_inst": "Institut Pasteur de Lille" - }, - { - "author_name": "Claude-Alain Maurage", - "author_inst": "Inserm UMR-S 1172" - }, - { - "author_name": "Virginie Mattot", - "author_inst": "Inserm UMR-S 1172" + "author_name": "Jasdeep Singh", + "author_inst": "Institute of Molecular Medicine-Jamia Hamdard, New Delhi, India" }, { - "author_name": "Paolo Giacobini", - "author_inst": "Inserm UMR-S 1172" + "author_name": "Sudeshna Kar", + "author_inst": "Institute of Molecular Medicine, Jamia Hamdard, New Delhi, India" }, { - "author_name": "S. Rasika", - "author_inst": "Inserm UMR-S 1172" + "author_name": "Seyed Ehtesham Hasnain", + "author_inst": "Institute of Molecular Medicine, Jamia Hamdard, New Delhi, India." }, { - "author_name": "Vincent Prevot", - "author_inst": "Inserm UMR-S 1172" + "author_name": "Surajit Ganguly", + "author_inst": "Institute of Molecular Medicine-Jamia Hamdard, New Delhi, India" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "new results", - "category": "neuroscience" + "category": "bioinformatics" }, { "rel_doi": "10.1101/2020.06.08.141267", @@ -1382265,93 +1382322,45 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.06.08.20124792", - "rel_title": "Serological Analysis of New York City COVID19 Convalescent Plasma Donors", + "rel_doi": "10.1101/2020.06.08.20125245", + "rel_title": "Effects of Tocilizumab on Mortality in Hospitalized Patients with COVID-19: A Multicenter Cohort Study", "rel_date": "2020-06-09", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.08.20124792", - "rel_abs": "The development of neutralizing antibodies (nAb) against SARS-CoV-2, following infection or vaccination, is likely to be critical for the development of sufficient population immunity to drive cessation of the COVID19 pandemic. A large number of serologic tests, platforms and methodologies are being employed to determine seroprevalence in populations to select convalescent plasmas for therapeutic trials, and to guide policies about reopening. However, tests have substantial variability in sensitivity and specificity, and their ability to quantitatively predict levels of nAb is unknown. We collected 370 unique donors enrolled in the New York Blood Center Convalescent Plasma Program between April and May of 2020. We measured levels of antibodies in convalescent plasma using commercially available SARS-CoV-2 detection tests and in-house ELISA assays and correlated serological measurements with nAb activity measured using pseudotyped virus particles, which offer the most informative assessment of antiviral activity of patient sera against viral infection. Our data show that a large proportion of convalescent plasma samples have modest antibody levels and that commercially available tests have varying degrees of accuracy in predicting nAb activity. We found the Ortho Anti-SARS-CoV-2 Total Ig and IgG high throughput serological assays (HTSAs), as well as the Abbott SARS-CoV-2 IgG assay, quantify levels of antibodies that strongly correlate with nAb assays and are consistent with gold-standard ELISA assay results. These findings provide immediate clinical relevance to serology results that can be equated to nAb activity and could serve as a valuable roadmap to guide the choice and interpretation of serological tests for SARS-CoV-2.", - "rel_num_authors": 20, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.08.20125245", + "rel_abs": "BackgroundWhile there are no treatments with proven efficacy for patients with severe coronavirus disease 2019 (COVID-19), tocilizumab has been proposed as a candidate therapy, especially among patients with higher systemic inflammation.\n\nMethodsWe conducted a cohort study of patients hospitalized with COVID-19 in Spain. The primary outcome was time to death and the secondary outcome time to intensive care unit admission (ICU) or death. We used inverse-probability weighting to fit marginal structural models adjusted for time-varying covariates to determine the causal relationship between tocilizumab use and the outcomes.\n\nResultsA total of 1,229 and 10,673 person/days were analyzed. In the adjusted marginal structural models, a significant interaction between tocilizumab use and high C- reactive protein (CRP) levels was detected. Tocilizumab was associated with decreased risk of death (aHR 0.34, 95% CI 0.16-0.72, p=0.005) and ICU admission or death (aHR 0.38, 95% CI 0.19-0.81, p=0.011) among patients with baseline CRP >150 mg/L, but not among those with CRP [≤]150 mg/L. Exploratory subgroup analyses yielded point estimates that were consistent with these findings.\n\nConclusionsIn this large observational study, tocilizumab was associated with a lower risk of death or ICU or death in patients with higher CRP levels. While the results of ongoing clinical trials of tocilizumab in patients with COVID-19 will be important to establish its safety and efficacy, our findings have implications for the design of future clinical trials and support the use of tocilizumab among subjects with higher CRP levels.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Larry L Luchsinger", - "author_inst": "New York Blood Center" - }, - { - "author_name": "Brett Ransegnola", - "author_inst": "New York Blood Center" - }, - { - "author_name": "Daniel Jin", - "author_inst": "New York Blood Center" - }, - { - "author_name": "Frauke Muecksch", - "author_inst": "Rockefeller University" - }, - { - "author_name": "Yiska Weisblum", - "author_inst": "Rockefeller University" - }, - { - "author_name": "Weili Bao", - "author_inst": "New York Blood Center" - }, - { - "author_name": "Parakkal Jovvian George", - "author_inst": "New York Blood Center" - }, - { - "author_name": "Marilis Rodriguez", - "author_inst": "New York Blood Center" - }, - { - "author_name": "Nancy Tricoche", - "author_inst": "New York Blood Center" - }, - { - "author_name": "Fabian Schmidt", - "author_inst": "Rockefeller University" - }, - { - "author_name": "Chengjie Gao", - "author_inst": "New York Blood Center" - }, - { - "author_name": "Shabnam Jawahar", - "author_inst": "New York Blood Center" - }, - { - "author_name": "Mouli Pal", - "author_inst": "New York Blood Center" + "author_name": "Javier Martinez-Sanz", + "author_inst": "Hospital Universitario Ramon y Cajal" }, { - "author_name": "Emily Schnall", - "author_inst": "New York Blood Center" + "author_name": "Alfonso Muriel", + "author_inst": "Clinical Biostatistic Unit, Hospital Universitario Ramon y Cajal, Departamento de Enfermeria y Fisioterapia, Universidad de Alcala, IRYCIS, CIBERESP, Madrid, Sp" }, { - "author_name": "Huan Zhang", - "author_inst": "New York Blood Center" + "author_name": "Raquel Ron", + "author_inst": "Department of Infectious Diseases, Hospital Universitario Ramon y Cajal, Facultad de Medicina, Universidad de Alcala, IRYCIS, Madrid, Spain." }, { - "author_name": "Donna Strauss", - "author_inst": "New York Blood Center" + "author_name": "Sabina Herrera", + "author_inst": "Department of Infectious Diseases, Hospital Universitario Ramon y Cajal, Facultad de Medicina, Universidad de Alcala, IRYCIS, Madrid, Spain." }, { - "author_name": "Karina Yazdanbakhsh", - "author_inst": "New York Blood Center" + "author_name": "Raquel Ron", + "author_inst": "Department of Infectious Diseases, Hospital Universitario Ramon y Cajal, Facultad de Medicina, Universidad de Alcala, IRYCIS, Madrid, Spain." }, { - "author_name": "Christopher D Hillyer", - "author_inst": "New York Blood Center" + "author_name": "Jose A Perez-Molina", + "author_inst": "Department of Infectious Diseases, Hospital Universitario Ramon y Cajal, Facultad de Medicina, Universidad de Alcala, IRYCIS, Madrid, Spain." }, { - "author_name": "Paul D Bieniasz", - "author_inst": "Rockefeller University" + "author_name": "Santiago Moreno", + "author_inst": "Department of Infectious Diseases, Hospital Universitario Ramon y Cajal, Facultad de Medicina, Universidad de Alcala, IRYCIS, Madrid, Spain." }, { - "author_name": "Theodora Hatziioannou", - "author_inst": "Rockefeller University" + "author_name": "Sergio Serrano-Villar", + "author_inst": "Department of Infectious Diseases, Hospital Universitario Ramon y Cajal, Facultad de Medicina, Universidad de Alcala, IRYCIS, Madrid, Spain." } ], "version": "1", @@ -1383583,31 +1383592,43 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.06.03.20120261", - "rel_title": "Association Between ACEIs or ARBs Use and Clinical Outcomes in COVID-19 Patients: A Systematic Review and Meta-analysis", + "rel_doi": "10.1101/2020.06.04.20119131", + "rel_title": "Social distancing across vulnerability, race, politics, and employment: How different Americans changed behaviors before and after major COVID-19 policy announcements", "rel_date": "2020-06-08", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.03.20120261", - "rel_abs": "ImportanceThere is a controversy regarding whether or not to continue angiotensin-converting enzyme inhibitors (ACEIs) and angiotensin receptor blockers (ARBs) in patients with coronavirus disease 2019 (COVID-19).\n\nObjectiveTo evaluate the association between ACEIs or ARBs use and clinical outcomes in COVID-19 patients.\n\nData SourcesSystematic search of the PubMed, Embase, Scopus, Web of Science, and Cochrane Central Register of Controlled Trials from database inception to May 31, 2020. We also searched the preprint servers medRxiv and SSNR for additional studies.\n\nStudy SelectionObservational studies and randomized controlled trials reporting the effect of ACEIs or ARBs use on clinical outcomes of adult patients with COVID-19.\n\nData Extraction and SynthesisRisk of bias of observational studies were evaluated using the Newcastle-Ottawa Scale. Meta-analyses were performed using a random-effects models and effects expressed as Odds ratios (OR) and mean differences with their 95% confidence interval (95%CI). If available, adjusted effects were pooled.\n\nMain Outcomes and MeasuresThe primary outcome was all-cause mortality and secondary outcomes were COVID-19 severity, hospital discharge, hospitalization, intensive care unit admission, mechanical ventilation, length of hospital stay, and troponin, creatinine, procalcitonin, C-reactive protein (CRP), interleukin-6 (IL-6), and D-dimer levels.\n\nResults40 studies (21 cross-sectional, two case-control, and 17 cohorts) involving 50615 patients were included. ACEIs or ARBs use was not associated with all-cause mortality overall (OR 1.11, 95%CI 0.77-1.60, p=0.56), in subgroups by study design and using adjusted effects. ACEI or ARB use was independently associated with lower COVID-19 severity (aOR 0.56, 95%CI 0.37-0.87, p<0.01). No significant associations were found between ACEIs or ARBs use and hospital discharge, hospitalization, mechanical ventilation, length of hospital stay, and biomarkers.\n\nConclusions and RelevanceACEIs or ARBs use was not associated with higher all-cause mortality in COVID-19. However, ACEI or ARB use was independently associated with lower COVID-19 severity. Our results support the current international guidelines to continue the use of ACEIs and ARBs in COVID-19 patients with hypertension.\n\nKey pointsO_ST_ABSQuestionC_ST_ABSWhat is the association between angiotensin-converting enzyme inhibitors (ACEIs) or angiotensin receptor blockers (ARBs) use and clinical outcomes in coronavirus disease 2019 (COVID-19) patients?\n\nFindingsIn this systematic review and meta-analysis of 40 observational studies, the use of ACEIs or ARBs was not associated with higher all-cause mortality in COVID-19 patients. Additionally, ACEIs or ARBs use was independently associated with lower COVID-19 severity.\n\nMeaningThese results support the current international guidelines to continue the use of ACEIs and ARBs in COVID-19 patients with hypertension.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.04.20119131", + "rel_abs": "BackgroundAs states reopen in May 2020, the United States is still trying to curb the spread of the COVID-19 pandemic. To appropriately design policies and anticipate behavioral change, it is important to understand how different Americans social distancing behavior shifts in relation to policy announcements according to individual characteristics, and community vulnerability.\n\nMethodsThis cross-sectional study used Unacasts social distancing data from February 24th - May 10th, 2020 to study how social distancing changed before and after: 1) The World Health Organizations declaration of a global pandemic, 2) White House announcement of \"Opening Up America Again\" (OUAA) guidelines, and 3) the week of April 27 when several states reopened. To measure intention to social distance, we assessed the difference between weekday and weekend behavior as more individuals have more control over weekend leisure time. To investigate social distancings sensitivity to different population characteristics, we compared social distancing time-series data across county vulnerability as measured by the COVID-19 Community Vulnerability Index (CCVI) which defines vulnerability across socioeconomic, household composition, minority status, epidemiological, and healthcare-system related factors. We also compared social distancing across population groupings by race, 2016 presidential election voting choice, and employment sectors.\n\nResultsMovement reduced significantly throughout March reaching peak reduction on April 12th (-56.1%) prior the enactment of any reopening policies. Shifts in social distancing began after major announcements but prior to specific applied policies: Following the WHO declaration, national social distancing significantly increased on weekdays and weekends (-18.6% and -41.3% decline in mobility, respectively). Social distancing significantly declined on weekdays and weekends after OUAA guidelines (i.e. before state reopening) (+1.1% and +5.3% increase in mobility, respectively) with additional significant decline after state reopening (+10.0% and +20.9% increase in mobility, respectively). Social distancing was significantly greater on weekends than weekdays throughout March, however, the trend reversed by early May with significantly less social distancing on weekends, suggesting a shift in intent to social distance during leisure time. In general, vulnerable counties social distanced less than non-vulnerable counties, and had a greater difference between weekday and weekend behavior until state reopening. This may be driven by structural barriers that vulnerable communities face, such as higher rates of employment in particular sectors. At all time periods studied, the average black individual in the US social distanced significantly more than the average white individual, and the average 2016 Clinton voter social distanced significantly more than the average 2016 Trump voter. Social distancing behavior differed across industries with three clusters of employment sectors.\n\nConclusionBoth signaling of a policy change and implementation of a policy are important factors that seem to influence social distancing. Behaviors shifted with national announcements prior to mandates, though social distancing further declined nationwide as the first states reopened. The variation in behavioral drivers including vulnerability, race, political affiliation, and employment industry demonstrates the need for targeted policy messaging and interventions tailored to address specific barriers for improved social distancing and mitigation.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Carlos Diaz-Arocutipa", - "author_inst": "Universidad San Ignacio de Loyola" + "author_name": "Vincent S Huang", + "author_inst": "Surgo Foundation" }, { - "author_name": "Jose Saucedo-Chinchay", - "author_inst": "Programa de Atencion Domiciliaria - Essalud" + "author_name": "Staci Sutermaster", + "author_inst": "Surgo Foundation" }, { - "author_name": "Adrian V. Hernandez", - "author_inst": "University of Connecticut" + "author_name": "Yael Caplan", + "author_inst": "Surgo Foundation" + }, + { + "author_name": "Hannah Kemp", + "author_inst": "Surgo Foundation" + }, + { + "author_name": "Danielle Schmutz", + "author_inst": "Surgo Foundation" + }, + { + "author_name": "Sema K Sgaier", + "author_inst": "Surgo Foundation" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "cardiovascular medicine" + "category": "public and global health" }, { "rel_doi": "10.1101/2020.06.05.20116624", @@ -1385465,63 +1385486,47 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2020.06.06.138339", - "rel_title": "SARS-CoV-2 Whole Genome Amplification and Sequencing for Effective Population-Based Surveillance and Control of Viral Transmission", + "rel_doi": "10.1101/2020.06.08.137331", + "rel_title": "Effects of Renin-Angiotensin Inhibition on ACE2 and TMPRSS2 Expression", "rel_date": "2020-06-08", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.06.06.138339", - "rel_abs": "BackgroundWith the gradual reopening of economies and resumption of social life, robust surveillance mechanisms should be implemented to control the ongoing COVID-19 pandemic. Unlike RT-qPCR, SARS-CoV-2 Whole Genome Sequencing (cWGS) has the added advantage of identifying cryptic origins of the virus, and the extent of community-based transmissions versus new viral introductions, which can in turn influence public health policy decisions. However, practical and cost considerations of cWGS should be addressed before it can be widely implemented.\n\nMethodsWe performed shotgun transcriptome sequencing using RNA extracted from nasopharyngeal swabs of patients with COVID-19, and compared it to targeted SARS-CoV-2 full genome amplification and sequencing with respect to virus detection, scalability, and cost-effectiveness. To track virus origin, we used open-source multiple sequence alignment and phylogenetic tools to compare the assembled SARS-CoV-2 genomes to publicly available sequences.\n\nResultsWe show a significant improvement in whole genome sequencing data quality and viral detection using amplicon-based target enrichment of SARS-CoV-2. With enrichment, more than 99% of the sequencing reads mapped to the viral genome compared to an average of 0.63% without enrichment. Consequently, a dramatic increase in genome coverage was obtained using significantly less sequencing data, enabling higher scalability and significant cost reductions. We also demonstrate how SARS-CoV-2 genome sequences can be used to determine their possible origin through phylogenetic analysis including other viral strains.\n\nConclusionsSARS-CoV-2 whole genome sequencing is a practical, cost-effective, and powerful approach for population-based surveillance and control of viral transmission in the next phase of the COVID-19 pandemic.", - "rel_num_authors": 11, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.06.08.137331", + "rel_abs": "Angiotensin-converting enzyme 2 (ACE2), a component of the renin-angiotensin system, is a receptor for SARS-CoV-2, the virus that causes COVID-19. To determine whether the renin-angiotensin inhibition regulates ACE2 expression, either enalapril (an angiotensin-converting enzyme inhibitor) or losartan (an AT1 receptor blocker) was infused subcutaneously to male C57BL/6J mice for two weeks. Neither enalapril nor losartan changed abundance of ACE2 mRNA in lung, ileum, kidney, and heart. Viral entry also depends on transmembrane protease serine 2 (TMPRSS2) to prime the S protein. TMPRSS2 mRNA was abundant in lungs and ileum, modest in kidney, but barely detectable in heart. TMPRSS2 mRNA abundance was not altered by either enalapril or losartan in any of the 4 tissues. Next, we determined whether depletion of angiotensinogen (AGT), the unique substrate of the renin-angiotensin system, changes ACE2 and TMPRSS2 mRNA abundance. AGT antisense oligonucleotides (ASO) were injected subcutaneously to male C57BL/6J mice for 3 weeks. Abundance of ACE2 mRNA was unchanged in any of the 4 tissues, but TMPRSS2 mRNA was significantly decreased in lungs. Our data support that the renin-angiotensin inhibition does not regulate ACE2 and hence are not likely to increase risk for COVID-19.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Divinlal Harilal", - "author_inst": "Al Jalila Genomics Center, Al Jalila Childrens Hospital, Dubai, United Arab Emirates" - }, - { - "author_name": "Sathishkumar Ramaswamy", - "author_inst": "Al Jalila Genomics Center, Al Jalila Childrens Hospital, Dubai, United Arab Emirates" - }, - { - "author_name": "Tom Loney", - "author_inst": "College of Medicine, Mohammed Bin Rashid University of Medicine and Health Sciences, Dubai, United Arab Emirates." - }, - { - "author_name": "Hanan Alsuwaidi", - "author_inst": "Mohammed Bin Rashid University of Medicine and Health Sciences" - }, - { - "author_name": "Hamda Khansaheb", - "author_inst": "Dubai Health Authority" + "author_name": "Congqing Wu", + "author_inst": "University of Kentucky" }, { - "author_name": "Abdulmajeed AlKhajeh", - "author_inst": "Dubai Health Authority" + "author_name": "Dien Ye", + "author_inst": "University of Kentucky" }, { - "author_name": "Rupa Varghese", - "author_inst": "Microbiology and Infection Control Unit, Pathology and Genetics Department, Latifa Women and Children Hospital, Dubai Health Authority, Dubai, United Arab Emira" + "author_name": "Adam E Mullick", + "author_inst": "Ionis" }, { - "author_name": "Zulfa Deesi", - "author_inst": "Microbiology and Infection Control Unit, Pathology and Genetics Department, Latifa Women and Children Hospital, Dubai Health Authority, Dubai, United Arab Emira" + "author_name": "Zhenyu Li", + "author_inst": "University of Kentucky" }, { - "author_name": "Norbert Nowotny", - "author_inst": "Institute of Virology, University of Veterinary Medicine Vienna, Vienna, Austria." + "author_name": "A.H. Jan Danser", + "author_inst": "Erasmus MC" }, { - "author_name": "Alawi Alsheikh-Ali", - "author_inst": "College of Medicine, Mohammed Bin Rashid University of Medicine and Health Sciences, Dubai, United Arab Emirates." + "author_name": "Alan Daugherty", + "author_inst": "University of Kentucky" }, { - "author_name": "Ahmad Abou Tayoun", - "author_inst": "Al Jalila Genomics Center, Al Jalila Childrens Hospital, and College of Medicine, Mohammed Bin Rashid University of Medicine and Health Sciences, Dubai, United " + "author_name": "Hong S. Lu", + "author_inst": "University of Kentucky" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "new results", - "category": "genomics" + "category": "molecular biology" }, { "rel_doi": "10.1101/2020.06.08.140459", @@ -1386735,31 +1386740,31 @@ "category": "health policy" }, { - "rel_doi": "10.1101/2020.06.04.20122606", - "rel_title": "COVID-19 and HIV co-infection: a living systematic evidence map of current research", + "rel_doi": "10.1101/2020.06.05.20122820", + "rel_title": "A systematic review of convalescent plasma treatment for COVID19", "rel_date": "2020-06-07", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.04.20122606", - "rel_abs": "The world currently faces two ongoing devastating pandemics. These are the new severe acute respiratory syndrome coronavirus 2/coronavirus disease 2019 (SARS-CoV-2/COVID-19) and the prior human immunodeficiency virus/acquired immune deficiency syndrome (HIV/AIDS) pandemics. The literature regarding the confluence of these global plagues expands at pace. A systematic search of the literature considering COVID-19 and HIV co-infection was performed.\n\nAfter five months, from the beginning of the COVID-19 pandemic, there were at least thirty-five studies reported from thirteen countries. These ranged from individual case reports and series to cohort studies. Based on studies that could be extrapolated to the general population, co-infected individuals with suppressed HIV viral loads did not have disproportionate COVID-19 sickness and death. At least four patients, newly diagnosed with HIV recovered from COVID-19. Current evidence suggests that co-infected patients should be treated like the general population.\n\nThis ongoing living systematic evidence map of contemporary primary SARS-CoV-2 and HIV co-infection research provides a platform for researchers, policy makers, clinicians and others to more quickly discover and build relevant insights.", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.05.20122820", + "rel_abs": "BackgroundTransfusion of convalescent immune plasma (CP) is commonly used in epidemics. Several articles now describe clinical report data of CP for treatment of SARS-CoV-2-induced COVID-19 disease.\n\nMethodsA systematic literature review was conducted using the NCBI curated COVID-19 related open-resource literature database LitCovid to identify studies using CP as treatment for COVID-19 patients. We retrieved and curated all COVID-19 related patient and treatment characteristics from previously reported studies. A Poisson model was developed to evaluate the association between age of the patients, older age being the most common risk factor for COVID-19 mortality, and recovery time since CP treatment using data extracted from the literature.\n\nResultsFrom 18,293 identified COVID-19 related articles, we included ten studies reporting results of CP treatment for COVID-19 from a total of 61 patients. Decreased symptoms of severe COVID-19 and clearance of SARS-CoV-2 RNA were the most direct observations. We found that patients over the age of sixty who received CP treatment for COVID-19 had a significantly prolonged recovery estimated by viral clearance (from 10 to 29 days since first dose of CP) compared to younger patients, who recovered from the infection in less than a week after receiving CP treatment.\n\nConclusionsLimited published results on plasma transfusion treatment for COVID-19 disease with concomitant treatments suggest that CP therapy for COVID-19 is well tolerated and effective. First randomized clinical trial results, however, revealed no improvements in recovery time for elderly patients with severe COVID-19 between standard treatment alone and added with convalescent plasma. Accordingly, we argue that older patients may need a significantly longer time for recovery. Further randomized clinical trial data for COVID-19 with rigorous ethical standards is urgently needed.", "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Gwinyai Masukume", - "author_inst": "Division of Epidemiology and Biostatistics, University of the Witwatersrand, School of Public Health, Johannesburg, South Africa" + "author_name": "Ville N Pimenoff", + "author_inst": "Karolinska Institutet" }, { - "author_name": "Witness Mapanga", - "author_inst": "Non-Communicable Diseases Research (NCDR) Division of the Wits Health Consortium, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, Sou" + "author_name": "Miriam Elfstrom", + "author_inst": "Karolinska Institutet" }, { - "author_name": "Doreen Sindisiwe van Zyl", - "author_inst": "Private practitioner, Johannesburg, South Africa" + "author_name": "Joakim Dillner", + "author_inst": "Karolinska Institutet" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "hiv aids" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2020.06.06.20122689", @@ -1388673,49 +1388678,57 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.06.02.20119834", - "rel_title": "Decontamination of face masks and filtering facepiece respirators via ultraviolet germicidal irradiation, hydrogen peroxide vaporisation, and use of dry heat inactivates an infectious SARS-CoV-2 surrogate virus.", + "rel_doi": "10.1101/2020.06.02.20120220", + "rel_title": "Overview on COVID-19 outbreak indicators across Brazilian federative units", "rel_date": "2020-06-05", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.02.20119834", - "rel_abs": "BackgroundIn the context of the ongoing severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic, the supply of personal protective equipment remains under severe strain. To address this issue, re-use of surgical face masks and filtering facepiece respirators has been recommended; prior decontamination is paramount to their re-use.\n\nAimWe aim to provide information on the effects of three decontamination procedures on porcine respiratory coronavirus (PRCV)-contaminated masks and respirators, presenting a stable model for infectious coronavirus decontamination of these typically single-use-only products.\n\nMethodsSurgical masks and filtering facepiece respirator coupons and straps were inoculated with infectious PRCV and submitted to three decontamination treatments, UV irradiation, vaporised H2O2, and dry heat treatment. Viruses were recovered from sample materials and viral titres were measured in swine testicle cells.\n\nFindingsUV irradiation, vaporised H2O2 and dry heat reduced infectious PRCV by more than three orders of magnitude on mask and respirator coupons and rendered it undetectable in all decontamination assays.\n\nConclusionThis is the first description of stable disinfection of face masks and filtering facepiece respirators contaminated with an infectious SARS-CoV-2 surrogate using UV irradiation, vaporised H2O2 and dry heat treatment. The three methods permit demonstration of a loss of infectivity by more than three orders of magnitude of an infectious coronavirus in line with the FDA policy regarding face masks and respirators. It presents advantages of uncomplicated manipulation and utilisation in a BSL2 facility, therefore being easily adaptable to other respirator and mask types.", - "rel_num_authors": 9, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.02.20120220", + "rel_abs": "BackgroundThe 2019 coronavirus disease pandemic (COVID-19) spread rapidly across Brazil. The country has 27 federative units, with wide regional differences related to climate, lifestyle habits, socioeconomic characteristics and population density. Therefore, we aimed to document and monitor the increase in COVID-19 cases across each federative unit in Brazil, by tracking its progression from inception to 15 May 2020.\n\nMethodsObservational study.\n\nResultsThe first confirmed COVID-19 case in the country was notified in Sao Paulo on 26 February, while the first death occurred on 17 March, in Rio de Janeiro. Since then, there has been a dramatic increase in both confirmed cases and deaths from the disease. Sao Paulo, in the Southeast region, was initially considered the COVID-19 epidemic epicentre in Brazil. However, 10 states in the North and Northeast regions were ranked among the 14 highest incidences (over 100 cases per 100,000 people) observed on 15 May. Higher incidence rates (>100 cases per 100,000) were associated to higher rates of inadequate water supply and sewerage (OR, 5.83 (95% CI, 1.08-29.37, P=0.041)). North and Northeast states with the highest social vulnerability index scores had higher increases in the incidence rate between 14 April and 15 May. States with medium human development index (HDI) showed higher incidence increases from 14 April to 15 May, being seven of them with ratios in the range from 27.49 to 63.73 times.\n\nConclusionSpreading of COVID-19 in Brazil differs across both regions and federative units, being influenced by different socioeconomic contexts.", + "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Louisa F Ludwig-Begall", - "author_inst": "Veterinary Virology and Animal Viral Diseases, Department of Infectious and Parasitic Diseases, FARAH Research Centre, Faculty of Veterinary Medicine, Liege Uni" + "author_name": "Elvira Maria Guerra-Shinohara", + "author_inst": "Universidade Federal de Mato Grosso do Sul, Campo Grande, MS, Brazil" }, { - "author_name": "Constance Wielick", - "author_inst": "Veterinary Virology and Animal Viral Diseases, Department of Infectious and Parasitic Diseases, FARAH Research Centre, Faculty of Veterinary Medicine, Liege Uni" + "author_name": "Simone Schneider Weber", + "author_inst": "Universidade Federal de Mato Grosso do Sul, Campo Grande, MS, Brazil" }, { - "author_name": "Lorene Dams", - "author_inst": "Veterinary Virology and Animal Viral Diseases, Department of Infectious and Parasitic Diseases, FARAH Research Centre, Faculty of Veterinary Medicine, Liege Uni" + "author_name": "Clovis Paniz", + "author_inst": "Universidade Federal de Santa Maria, Santa Maria , RS, Brazil" }, { - "author_name": "Hans Nauwynck", - "author_inst": "Laboratory of Virology, Faculty of Veterinary Medicine, Ghent University, Merelbeke, Belgium" + "author_name": "Guilherme Wataru Gomes", + "author_inst": "Universidade de Sao Paulo, Sao Paulo, SP, Brazil" }, { - "author_name": "Pierre-Francois Demeuldre", - "author_inst": "Department of Hospital Pharmacy, The University Hospital Center, University of Liege, Liege, Belgium" + "author_name": "Eduardo Jun Shinohara", + "author_inst": "Companhia Ambiental do Estado de Sao Paulo, CETESB, Sao Paulo, SP, Brazil" }, { - "author_name": "Aurore Napp", - "author_inst": "Department of Hospital Pharmacy, The University Hospital Center, University of Liege, Liege, Belgium" + "author_name": "Tiago Borges Ribeiro Gandra", + "author_inst": "Instituto Federal de Educacao Ciencia e Tecnologia do Rio Grande do Sul, Rio Grande, RS, Brazil" }, { - "author_name": "Jan Laperre", - "author_inst": "Centexbel Textile Research Centre, Grace-Hollogne, Belgium" + "author_name": "Indiara Correia Pereira", + "author_inst": "Universidade Federal de Mato Grosso do Sul, Campo Grande, MS, Brazil" }, { - "author_name": "Eric Haubruge", - "author_inst": "TERRA Research Centre, Gembloux Agro-Bio Tech, University of Liege, Gembloux, Belgium" + "author_name": "Karine Gomes Jarcem", + "author_inst": "Universidade Federal de Mato Grosso do Sul, Campo Grande, MS, Brazil" }, { - "author_name": "Etienne Thiry", - "author_inst": "Veterinary Virology and Animal Viral Diseases, Department of Infectious and Parasitic Diseases, FARAH Research Centre, Faculty of Veterinary Medicine, Liege Uni" + "author_name": "Renato Ferreira de Almeida Zanre", + "author_inst": "Universidade Federal de Mato Grosso do Sul, Campo Grande, MS, Brazil" + }, + { + "author_name": "Acacia Gimenez Barreto", + "author_inst": "Universidade Federal de Mato Grosso do Sul, Campo Grande, MS, Brazil" + }, + { + "author_name": "Alessandro Diogo De Carli", + "author_inst": "Universidade Federal de Mato Grosso do Sul, Campo Grande, MS, Brazil" } ], "version": "1", @@ -1390047,21 +1390060,21 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.06.02.20120568", - "rel_title": "A Model for the Testing and Tracing Needed to Suppress COVID-19", + "rel_doi": "10.1101/2020.06.02.20117341", + "rel_title": "Analysis of the outbreak of COVID-19 in Japan on the basis of an SIQR model", "rel_date": "2020-06-05", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.02.20120568", - "rel_abs": "This paper presents the first analytical model for calculating how many tests and tracing needed to suppress COVID-19 transmission. The number of people needs to be tested daily is given by: O_FD O_INLINEFIG[Formula 1]C_INLINEFIGM_FD(1)C_FD Where\n\nN is the size of the population in consideration\n\nAr is the attack rate at any given time\n\nTp is the test-positive rate\n\n {rho}is the percentage of infectious people that have to be detected per day. To make the effective reproduction number Re below 1,{rho} must satisfy the following equation: O_FD O_INLINEFIG[Formula 2]C_INLINEFIGM_FD(2)C_FD\n\nWhere\n\nR0 is the basic reproduction number,\n\nS/N is the percentage of the susceptible population over the entire population,\n\nD is the length of the infectious period, and\n\n{eta}is the percentage of close contacts that have to be traced.\n\nThis model provides insights and guidance to deploy the testing and tracing resources optimally. An Excel model is attached to facilitate easy calculation of the number of tests and tracing needed. This model is also applicable to any infectious disease that can be suppressed by testing and tracing.", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.02.20117341", + "rel_abs": "The SIR model is modified, which may be called an SIQR model, so as to be appropriate for COVID-19 which has the following characteristics: [1] a long incubation period, [2] transmission of the virus by asymptomatic patients and [3] quarantine of patients identified through PCR testing. It is assumed that the society consists of four compartments; susceptibles (S), infecteds at large (simply called infecteds) (I), quarantined patients (Q) and recovered individuals (R), and the time evolution of the pandemic is described by a set of ordinary differential equations. It is shown that the quarantine rate can be determined from the time dependence of the daily confirmed new cases, from which the number of the infecteds at large can be estimated. The number of daily confirmed new cases is shown to be proportional to the number of infecteds a characteristic time earlier, and the infection rate and quarantine rate are determined for the period from mid-February to mid-April in Japan, and transmission characteristics of the initial stages of the outbreak in Japan are analyzed. The effectiveness of different measures is discussed for controlling the outbreak and it is shown that identifying patients through PCR testing and isolating them in a quarantine is more effective than lockdown measures aimed at inhibiting social interactions of the general population. An effective reproduction number for infecteds at large is introduced which is appropriate to epidemics controlled by quarantine measures.", "rel_num_authors": 1, "rel_authors": [ { - "author_name": "Victor Wang", - "author_inst": "Aimtop Ventures" + "author_name": "Takashi Odagaki", + "author_inst": "Research Institute for Science Education Inc." } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1391897,163 +1391910,251 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2020.06.05.135921", - "rel_title": "SARS-CoV-2 neutralizing human recombinant antibodies selected from pre-pandemic healthy donors binding at RBD-ACE2 interface", + "rel_doi": "10.1101/2020.06.05.136481", + "rel_title": "SARS-CoV-2 infection leads to acute infection with dynamic cellular and inflammatory flux in the lung that varies across nonhuman primate species", "rel_date": "2020-06-05", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.06.05.135921", - "rel_abs": "COVID-19 is a severe acute respiratory disease caused by SARS-CoV-2, a novel betacoronavirus discovered in December 2019 and closely related to the SARS coronavirus (CoV). Both viruses use the human ACE2 receptor for cell entry, recognizing it with the Receptor Binding Domain (RBD) of the S1 subunit of the viral spike (S) protein. The S2 domain mediates viral fusion with the host cell membrane. Experience with SARS and MERS coronaviruses has shown that potent monoclonal neutralizing antibodies against the RBD can inhibit the interaction with the virus cellular receptor (ACE2 for SARS) and block the virus cell entry. Assuming that a similar strategy would be successful against SARS-CoV-2, we used phage display to select from the human naive universal antibody gene libraries HAL9/10 anti-SARS-CoV-2 spike antibodies capable of inhibiting interaction with ACE2. 309 unique fully human antibodies against S1 were identified. 17 showed more than 75% inhibition of spike binding to cells expressing ACE2 in the scFv-Fc format, assessed by flow cytometry and several antibodies showed even an 50% inhibition at a molar ratio of the antibody to spike protein or RBD of 1:1. All 17 scFv-Fc were able to bind the isolated RBD, four of them with sub-nanomolar EC50. Furthermore, these scFv-Fc neutralized active SARS-CoV-2 virus infection of VeroE6 cells. In a final step, the antibodies neutralizing best as scFv-Fc were converted into the IgG format. The antibody STE73-2E9 showed neutralization of active SARS-CoV-2 with an IC50 0.43 nM and is binding to the ACE2-RBD interface. Universal libraries from healthy human donors offer the advantage that antibodies can be generated quickly and independent from the availability of material from recovered patients in a pandemic situation.", - "rel_num_authors": 36, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.06.05.136481", + "rel_abs": "There are no known cures or vaccines for COVID-19, the defining pandemic of this era. Animal models are essential to fast track new interventions and nonhuman primate (NHP) models of other infectious diseases have proven extremely valuable. Here we compare SARS-CoV-2 infection in three species of experimentally infected NHPs (rhesus macaques, baboons, and marmosets). During the first 3 days, macaques developed clinical signatures of viral infection and systemic inflammation, coupled with early evidence of viral replication and mild-to-moderate interstitial and alveolar pneumonitis, as well as extra-pulmonary pathologies. Cone-beam CT scans showed evidence of moderate pneumonia, which progressed over 3 days. Longitudinal studies showed that while both young and old macaques developed early signs of COVID-19, both groups recovered within a two-week period. Recovery was characterized by low-levels of viral persistence in the lung, suggesting mechanisms by which individuals with compromised immune systems may be susceptible to prolonged and progressive COVID-19. The lung compartment contained a complex early inflammatory milieu with an influx of innate and adaptive immune cells, particularly interstitial macrophages, neutrophils and plasmacytoid dendritic cells, and a prominent Type I-interferon response. While macaques developed moderate disease, baboons exhibited prolonged shedding of virus and extensive pathology following infection; and marmosets demonstrated a milder form of infection. These results showcase in critical detail, the robust early cellular immune responses to SARS-CoV-2 infection, which are not sterilizing and likely impact development of antibody responses. Thus, various NHP genera recapitulate heterogeneous progression of COVID-19. Rhesus macaques and baboons develop different, quantifiable disease attributes making them immediately available essential models to test new vaccines and therapies.", + "rel_num_authors": 58, "rel_authors": [ { - "author_name": "Federico Bertoglio", - "author_inst": "TU Braunschweig" + "author_name": "Dhiraj K. Singh", + "author_inst": "Texas Biomedical Research Institute" }, { - "author_name": "Doris Meier", - "author_inst": "TU Braunschweig" + "author_name": "Shashank R. Ganatra", + "author_inst": "Texas Biomedical Research Institute" }, { - "author_name": "Nora Langreder", - "author_inst": "TU Braunschweig" + "author_name": "Bindu Singh", + "author_inst": "Texas Biomedical Research Institute" }, { - "author_name": "Stephan Steinke", - "author_inst": "TU Braunschweig" + "author_name": "Journey Cole", + "author_inst": "Texas Biomedical Research Institute" }, { - "author_name": "Ulfert Rand", - "author_inst": "Helmholtz Centre for Infection Research" + "author_name": "Kendra J. Alfson", + "author_inst": "Texas Biomedical Research Institute" }, { - "author_name": "Luca Simonelli", - "author_inst": "Istituto di Ricerca in Biomedicina, Universita della Svizzera italiana" + "author_name": "Elizabeth Clemmons", + "author_inst": "Texas Biomedical Research Institute" }, { - "author_name": "Philip Alexander Heine", - "author_inst": "TU Braunschweig" + "author_name": "Michal Gazi", + "author_inst": "Texas Biomedical Research Institute" }, { - "author_name": "Rico Ballmann", - "author_inst": "TU Braunschweig" + "author_name": "Olga Gonzalez", + "author_inst": "Texas Biomedical Research Institute" }, { - "author_name": "Kai-Thomas Schneider", - "author_inst": "TU Braunschweig" + "author_name": "Ruby Escabedo", + "author_inst": "Texas Biomedical Research Institute" }, { - "author_name": "Kristian Daniel Ralph Roth", - "author_inst": "TU Braunschweig" + "author_name": "Tae-Hyung Lee", + "author_inst": "Texas Biomedical Research Institute" }, { - "author_name": "Maximilian Ruschig", - "author_inst": "TU Braunschweig" + "author_name": "Ayan Chatterjee", + "author_inst": "Texas Biomedical Research Institute" }, { - "author_name": "Peggy Riese", - "author_inst": "Helmholtz Centre for Infection Research" + "author_name": "Yenny Goez-Gazi", + "author_inst": "Texas Biomedical Research Institute" }, { - "author_name": "Kathrin Eschke", - "author_inst": "Helmholtz Centre for Infection Research" + "author_name": "Riti Sharan", + "author_inst": "Texas Biomedical Research Institute" }, { - "author_name": "Yeonsu Kim", - "author_inst": "Helmholtz Centre for Infection Research" + "author_name": "Rajesh Thippeshappa", + "author_inst": "Texas Biomedical Research Institute" }, { - "author_name": "Dorina Schaeckermann", - "author_inst": "TU Braunschweig" + "author_name": "Maya Gough", + "author_inst": "Texas Biomedical Research Institute" }, { - "author_name": "Mattia Pedotti", - "author_inst": "Istituto di Ricerca in Biomedicina, Universita della Svizzera italiana" + "author_name": "Cynthia Alvarez", + "author_inst": "Texas Biomedical Research Institute" }, { - "author_name": "Philipp Kuhn", - "author_inst": "YUMAB GmbH" + "author_name": "Alyssa Blakely", + "author_inst": "Texas Biomedical Research Institute" }, { - "author_name": "Susanne Zock-Emmenthal", - "author_inst": "TU Braunschweig" + "author_name": "Justin Ferdin", + "author_inst": "Texas Biomedical Research Institute" }, { - "author_name": "Johannes Woehrle", - "author_inst": "BioCopy GmbH" + "author_name": "Carmen Bartley", + "author_inst": "Texas Biomedical Research Institute" }, { - "author_name": "Normann Kilb", - "author_inst": "BioCopy GmbH" + "author_name": "Hilary Staples", + "author_inst": "Texas Biomedical Research Institute" }, { - "author_name": "Tobias Herz", - "author_inst": "BioCopy GmbH" + "author_name": "Laura Parodi", + "author_inst": "Texas Biomedical Research Institute" }, { - "author_name": "Marlies Becker", - "author_inst": "TU Braunschweig" + "author_name": "Jessica Callery", + "author_inst": "Texas Biomedical Research Institute" }, { - "author_name": "Martina Grashoff", - "author_inst": "Helmholtz Centre for Infection Research" + "author_name": "Amanda Mannino", + "author_inst": "Texas Biomedical Research Institute" }, { - "author_name": "Esther Veronika Wenzel", - "author_inst": "TU Braunschweig" + "author_name": "Benjamin Klaffke", + "author_inst": "Texas Biomedical Research Institute" }, { - "author_name": "Giulio Russo", - "author_inst": "TU Braunschweig" + "author_name": "Priscilla Escareno", + "author_inst": "Texas Biomedical Research Institute" }, { - "author_name": "Andrea Kroeger", - "author_inst": "Helmholtz Centre for Infection Research" + "author_name": "Roy N Platt", + "author_inst": "Texas Biomedical Research Institute" }, { - "author_name": "Linda Brunotte", - "author_inst": "Westfaelische Wilhelms-Universitaet Muenster" + "author_name": "Vida Hodara", + "author_inst": "Texas Biomedical Research Institute" }, { - "author_name": "Stephan Ludwig", - "author_inst": "Westfaelische Wilhelms-Universitaet Muenster" + "author_name": "Julia Scordo", + "author_inst": "Texas Biomedical Research Institute" }, { - "author_name": "Viola Fuehner", - "author_inst": "TU Braunschweig" + "author_name": "Adelekan Oyejide", + "author_inst": "Regeneron Pharmaceuticals, Inc." }, { - "author_name": "Stefan Daniel Kraemer", - "author_inst": "BioCopy GmbH" + "author_name": "Dharani K. Ajithdoss", + "author_inst": "Regeneron Pharmaceuticals, Inc." }, { - "author_name": "Stefan Duebel", - "author_inst": "TU Braunschweig" + "author_name": "Richard Copin", + "author_inst": "Regeneron Pharmaceuticals, Inc." }, { - "author_name": "Luca Varani", - "author_inst": "Istituto di Ricerca in Biomedicina" + "author_name": "Alina Baum", + "author_inst": "Regeneron Pharmaceuticals, Inc.," }, { - "author_name": "Guenter Roth", - "author_inst": "BioCopy GmbH" + "author_name": "Christos Kyratsous", + "author_inst": "Regeneron Pharmaceuticals, Inc." }, { - "author_name": "Luka Cicin-Sain", - "author_inst": "Helmholtz Centre for Infection Research" + "author_name": "Xavier Alvarez", + "author_inst": "Texas Biomedical Research Institute" }, { - "author_name": "Maren Schubert", - "author_inst": "TU Braunschweig" + "author_name": "Bruce Rosa", + "author_inst": "Washington University in St. Louis School of Medicine" }, { - "author_name": "Michael Hust", - "author_inst": "TU Braunschweig" + "author_name": "Mushtaq Ahmed", + "author_inst": "Washington University in St. Louis School of Medicine" + }, + { + "author_name": "Anna Goodroe", + "author_inst": "Texas Biomedical Research Institute" + }, + { + "author_name": "John Dutton", + "author_inst": "Texas Biomedical Research Institute" + }, + { + "author_name": "Shannan Hall-Ursone", + "author_inst": "Texas Biomedical Research Institute" + }, + { + "author_name": "Patrice Frost", + "author_inst": "Texas Biomedical Research Institute" + }, + { + "author_name": "Andra K. Voges", + "author_inst": "Veterinary Imaging Consulting of South Texas" + }, + { + "author_name": "Corinna N. Ross", + "author_inst": "Texas Biomedical Research Institute" + }, + { + "author_name": "Ken Sayers", + "author_inst": "Texas Biomedical Research Institute" + }, + { + "author_name": "Christopher Chen", + "author_inst": "Texas Biomedical Research Institute" + }, + { + "author_name": "Cory Hallam", + "author_inst": "Texas Biomedical Research Institute" + }, + { + "author_name": "Shabaana A Khader", + "author_inst": "Washington University School of Medicine" + }, + { + "author_name": "Makedonka Mitreva", + "author_inst": "Washington University School of Medicine" + }, + { + "author_name": "Tim Anderson", + "author_inst": "Texas Biomedical Research Institute" + }, + { + "author_name": "Luis Martinez-Sobrido", + "author_inst": "Texas Biomedical Research Institute" + }, + { + "author_name": "Jean Patterson", + "author_inst": "Texas Biomedical Research Institute" + }, + { + "author_name": "Joanne Turner", + "author_inst": "Texas Biomedical Research Institute" + }, + { + "author_name": "Jordi B. Torrelles", + "author_inst": "Texas Biomedical Research Institute" + }, + { + "author_name": "Edward J. Dick", + "author_inst": "Texas Biomedical Research Institute" + }, + { + "author_name": "Kathleen Brasky", + "author_inst": "Texas Biomedical Research Institute" + }, + { + "author_name": "Larry S. Schlesinger", + "author_inst": "Texas Biomedical Research Institute" + }, + { + "author_name": "Luis Giavedoni", + "author_inst": "Texas Biomedical Research Institute" + }, + { + "author_name": "Deepak Kaushal", + "author_inst": "Texas Biomedical Research Institute" + }, + { + "author_name": "Ricardo Carrion", + "author_inst": "Texas Biomedical Research Institute" } ], "version": "1", "license": "cc_by_nc_nd", "type": "new results", - "category": "biochemistry" + "category": "immunology" }, { "rel_doi": "10.1101/2020.06.05.135699", @@ -1393310,27 +1393411,31 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.06.02.20120352", - "rel_title": "Testing the effects of the timing of application of preventative procedures against COVID-19: An insight for future measures such as local emergency brakes.", + "rel_doi": "10.1101/2020.05.31.126615", + "rel_title": "An exploration of the SARS-CoV-2 spike receptor binding domain (RBD), a complex palette of evolutionary and structural features", "rel_date": "2020-06-04", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.02.20120352", - "rel_abs": "As many countries plan to lift lockdown measures aimed at suppression of COVID-19, data from early regional epidemics in Italy were analysed to ascertain the effectiveness of the timing of preventative measures. The cumulative caseload data were extracted from regional epidemics in Italy. Epidemic features in regions where lockdown was applied early were compared to those where lockdown was applied later for statistical differences. There were statistically significant differences in the timing of the peak, the cumulative incidence at peak and the case/km2 at peak between regions where the lockdown had been applied early and those where it was applied late. The peak occurred 7 days earlier with four times less cases/km2 in regions where the lockdown was applied within 10 days of the start of the epidemic. Cumulative caseloads, cases/km2 and/or the number of days into an epidemic can be used to plan future localised suppression measures as part of a national post-lockdown policy. There were 350 (95% confidence interval (CI) 203) cumulative cases and 2.4 (CI 1.1) cases/km2 on day 8 of the regional epidemics.", - "rel_num_authors": 2, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.31.126615", + "rel_abs": "SARS-CoV-2 spike protein (S) is associated with the entry of virus inside the host cell by recruiting its loop dominant receptor binding domain (RBD) and interacting with the host ACE2 receptor. Our study deploying a two-tier approach encompassing evolutionary and structural analysis provides a comprehensive picture of the RBD, which could be of potential use for better understanding the RBD and address its druggability issues. Resorting to an ensemble of sequence space exploratory tools including co-evolutionary analysis and deep mutational scans we provide a quantitative insight into the evolutionarily constrained subspace of the RBD sequence space. Guided by structure network analysis and Monte Carlo simulation we highlight regions inside the RBD, which are critical for providing structural integrity and conformational flexibility of the binding cleft. We further deployed fuzzy C-means clustering by plugging the evolutionary and structural features of discrete structure blocks of RBD to understand which structure blocks share maximum overlap based on their evolutionary and structural features. Deploying this multi-tier interlinked approach, which essentially distilled the evolutionary and structural features of RBD, we highlight discrete region, which could be a potential druggable pocket thereby destabilizing the structure and addressing evolutionary routes.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Francis Scullion", - "author_inst": "Veterinary Services" + "author_name": "Dwipanjan Sanyal", + "author_inst": "CSIR-Indian Institute of Chemical Biology" }, { - "author_name": "Geraldine Scullion", - "author_inst": "Veterinary Services" + "author_name": "Sourav Chowdhury", + "author_inst": "Harvard University" + }, + { + "author_name": "Krishnananda Chattopadhyay", + "author_inst": "CSIR-Indian Institute of Chemical Biology" } ], "version": "1", - "license": "cc_by_nc_nd", - "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "license": "cc_no", + "type": "new results", + "category": "biophysics" }, { "rel_doi": "10.1101/2020.06.03.132506", @@ -1395020,35 +1395125,71 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2020.06.02.20120147", - "rel_title": "Estimating critical care capacity needs and gaps in Africa during the COVID-19 pandemic", + "rel_doi": "10.1101/2020.06.02.20120295", + "rel_title": "Increased serum levels of sCD14 and sCD163 indicate a preponderant role for monocytes in COVID-19 immunopathology", "rel_date": "2020-06-04", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.02.20120147", - "rel_abs": "ObjectiveThe purpose of this analysis was to describe national critical care capacity shortages for 52 African countries and to outline needs for each country to adequately respond to the COVID-19 pandemic.\n\nMethodsA modified SECIR compartment model was used to estimate the number of severe COVID-19 cases at the peak of the outbreak. Projections of the number of hospital beds, ICU beds, and ventilators needed at outbreak peak were generated for four scenarios - if 30, 50, 70, or 100% of patients with severe COVID-19 symptoms seek health services--assuming that all people with severe infections would require hospitalization, that 4.72% would require ICU admission, and that 2.3% would require mechanical ventilation.\n\nFindingsAcross the 52 countries included in this analysis, the average number of severe COVID-19 cases projected at outbreak peak was 138 per 100,000 (SD: 9.6). Comparing current national capacities to estimated needs at outbreak peak, we found that 31of 50 countries (62%) do not have a sufficient number of hospital beds per 100,000 people if 100% of patients with severe infections seek out health services and assuming that all hospital beds are empty and available for use by patients with COVID-19. If only 30% of patients seek out health services then 10 of 50 countries (20%) do not have sufficient hospital bed capacity. The average number of ICU beds needed at outbreak peak across the 52 included countries ranged from 2 per 100,000 people (SD: 0.1) when 30% of people with severe COVID-19 infections access health services to 6.5 per 100,000 (SD: 0.5) assuming 100% of people seek out health services. Even if only 30% of severely infected patients seek health services at outbreak peak, then 34 of 48 countries (71%) do not have a sufficient number of ICU beds per 100,000 people to handle projected need. Only four countries (Cabo Verde, Egypt, Gabon, and South Africa) have a sufficient number of ventilators to meet projected national needs if 100% of severely infected individuals seek health services assuming all ventilators are functioning and available for COVID-19 patients, while 35 other countries require two or more additional ventilators per 100,000 people.\n\nConclusionThe majority of countries lack sufficient ICU bed and ventilator capacity to care for the projected number of patients with severe COVID-19 infections at outbreak peak even if only 30% of severely infected patients seek health services.\n\nThis analysis reveals there is an urgent need to allocate resources and increase critical care capacity in these countries.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.02.20120295", + "rel_abs": "BackgroundEmerging evidence indicates a potential role for monocyte in COVID-19 immunopathology. We investigated two soluble markers of monocyte activation, sCD14 and sCD163, in covid19 patients with the aim of characterizing their potential role in monocyte-macrophage disease immunopathology. To the best of our knowledge, this is the first study of its kind.\n\nMethodsFifty-nine SARS-Cov-2 positive hospitalized patients, classified according to ICU or non-ICU admission requirement, were prospectively recruited and analyzed by ELISA for levels of sCD14 and sCD163, along with other laboratory parameters, and compared to a healthy control group.\n\nResultssCD14 and sCD163 levels were significantly higher among COVID-19 patients, independently of ICU admission requirement, compared to the control group. We found a significant correlation between sCD14 levels and other inflammatory markers, particularly Interleukin-6, in the non-ICU patients group. sCD163 showed a moderate positive correlation with the time at sampling from admission, increasing its value over time, independently of severity group.\n\nConclusionsMonocyte-macrophage activation markers are increased and correlate with other inflammatory markers in SARS-Cov-2 infection, in association to hospital admission. These data suggest a potentially preponderant role for monocyte-macrophage activation in the development of immunopathology of covid19 patients.", + "rel_num_authors": 13, "rel_authors": [ { - "author_name": "Jessica Craig", - "author_inst": "CDDEP" + "author_name": "Jose Gomez Rial", + "author_inst": "Hospital Clinico Universitario Santiago de Compostela" }, { - "author_name": "Erta Kalanxhi", - "author_inst": "CDDEP" + "author_name": "Maria Jose Curras Tuala", + "author_inst": "Hospital Clinico Universitario Santiago de Compostela" }, { - "author_name": "Gilbert Osena", - "author_inst": "CDDEP" + "author_name": "Irene Rivero Calle", + "author_inst": "Hospital Clinico Universitario Santiago de Compostela" }, { - "author_name": "Isabel Frost", - "author_inst": "CDDEP" + "author_name": "Alberto Gomez Carballa", + "author_inst": "Hospital Clinico Universitario Santiago de Compostela" + }, + { + "author_name": "Miriam Cebey Lopez", + "author_inst": "Hospital Clinico Universitario Santiago de Compostela" + }, + { + "author_name": "Carmen Rodriguez Tenreiro", + "author_inst": "Hospital Clinico Universitario Santiago de Compostela" + }, + { + "author_name": "Ana Dacosta Urbieta", + "author_inst": "Hospital Clinico Universitario Santiago de Compostela" + }, + { + "author_name": "Carmen Rivero Velasco", + "author_inst": "Hospital Clinico Universitario Santiago de Compostela" + }, + { + "author_name": "Nuria Rodriguez Nunez", + "author_inst": "Hospital Clinico Universitario Santiago de Compostela" + }, + { + "author_name": "Rocio Trastoy Pena", + "author_inst": "Hospital Clinico Universitario Santiago de Compostela" + }, + { + "author_name": "Javier Rodriguez Garcia", + "author_inst": "Hospital Clinico Universitario Santiago de Compostela" + }, + { + "author_name": "Antonio Salas", + "author_inst": "Universidad Santiago de Compostela" + }, + { + "author_name": "Federico Martinon Torres", + "author_inst": "Hospital Clinico Universitario Santiago de Compostela" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "health systems and quality improvement" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2020.06.02.20120774", @@ -1396118,37 +1396259,69 @@ "category": "health economics" }, { - "rel_doi": "10.1101/2020.06.01.20119230", - "rel_title": "Who do not wash their hands during the Covid-19 pandemic? Social media use as a potential predictor", + "rel_doi": "10.1101/2020.05.30.20118109", + "rel_title": "Development and Prospective Validation of a Transparent Deep Learning Algorithm for Predicting Need for Mechanical Ventilation", "rel_date": "2020-06-03", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.01.20119230", - "rel_abs": "This study predicts handwashing behavior during the Covid-19 pandemic. An analysis of 674 adults in Malaysia identifies their time spent on social media per day as a key predictor of handwashing. The association between time spent on social media and handwashing substantially depends on gender and the number of children in the same household. Additional predictors include age and health condition. This study helps identify specific target groups for health communication on hand hygiene via peoples use of social media, which can be a key channel for health communication campaigns during a pandemic.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.30.20118109", + "rel_abs": "IMPORTANCEObjective and early identification of hospitalized patients, and particularly those with novel coronavirus disease 2019 (COVID-19), who may require mechanical ventilation is of great importance and may aid in delivering timely treatment.\n\nOBJECTIVETo develop, externally validate and prospectively test a transparent deep learning algorithm for predicting 24 hours in advance the need for mechanical ventilation in hospitalized patients and those with COVID-19.\n\nDESIGNObservational cohort study\n\nSETTINGTwo academic medical centers from January 01, 2016 to December 31, 2019 (Retrospective cohorts) and February 10, 2020 to May 4, 2020 (Prospective cohorts).\n\nPARTICIPANTSOver 31,000 admissions to the intensive care units (ICUs) at two hospitals. Additionally, 777 patients with COVID-19 patients were used for prospective validation. Patients who were placed on mechanical ventilation within four hours of their admission were excluded.\n\nMAIN OUTCOME(S) and MEASURE(S)Electronic health record (EHR) data were extracted on an hourly basis, and a set of 40 features were calculated and passed to an interpretable deep-learning algorithm to predict the future need for mechanical ventilation 24 hours in advance. Additionally, commonly used clinical criteria (based on heart rate, oxygen saturation, respiratory rate, FiO2 and pH) was used to assess future need for mechanical ventilation. Performance of the algorithms were evaluated using the area under receiver-operating characteristic curve (AUC), sensitivity, specificity and positive predictive value.\n\nRESULTSAfter applying exclusion criteria, the external validation cohort included 3,888 general ICU and 402 COVID-19 patients. The performance of the model (AUC) with a 24-hour prediction horizon at the validation site was 0.882 for the general ICU population and 0.918 for patients with COVID-19. In comparison, commonly used clinical criteria and the ROX score achieved AUCs in the range of 0.773 - 0.782 and 0.768 - 0.810 for the general ICU population and patients with COVID-19, respectively.\n\nCONCLUSIONS and RELEVANCEA generalizable and transparent deep-learning algorithm improves on traditional clinical criteria to predict the need for mechanical ventilation in hospitalized patients, including those with COVID-19. Such an algorithm may help clinicians with optimizing timing of tracheal intubation, better allocation of mechanical ventilation resources and staff, and improve patient care.", + "rel_num_authors": 13, "rel_authors": [ { - "author_name": "Stephen X. Zhang", - "author_inst": "University of Adelaide" + "author_name": "Supreeth P. Shashikumar", + "author_inst": "UCSD" }, { - "author_name": "Lorenz Graf-Vlachy", - "author_inst": "ESCP" + "author_name": "Gabriel Wardi", + "author_inst": "UCSD" }, { - "author_name": "Rui Su", - "author_inst": "Xiamen University Malaysia" + "author_name": "Paulina Paul", + "author_inst": "UCSD" }, { - "author_name": "Jizhen Li", - "author_inst": "Tsinghua University" + "author_name": "Morgan Carlile", + "author_inst": "UCSD" }, { - "author_name": "Kim Hoe Looi", - "author_inst": "Xiamen University Malaysia" + "author_name": "Laura N. Brenner", + "author_inst": "MGH" + }, + { + "author_name": "Kathryn A Hibbert", + "author_inst": "MGH" + }, + { + "author_name": "Crystal M North", + "author_inst": "MGH" + }, + { + "author_name": "Shibani Mukerji", + "author_inst": "MGH" + }, + { + "author_name": "Gregory Robbins", + "author_inst": "MGH" + }, + { + "author_name": "Yu-Ping Shao", + "author_inst": "MGH" + }, + { + "author_name": "Atul Malhotra", + "author_inst": "UCSD" + }, + { + "author_name": "Brandon Westover", + "author_inst": "MGH" + }, + { + "author_name": "Shamim Nemati", + "author_inst": "UCSD" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "health informatics" }, @@ -1397420,23 +1397593,39 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.05.31.20118414", - "rel_title": "Dynamics and Prediction of the COVID-19 Epidemics in the US:a Compartmental Model with Deep Learning Enhancement", + "rel_doi": "10.1101/2020.06.02.131102", + "rel_title": "Brief Communication: Magnetic Immuno-Detection of SARS-CoV-2 specific Antibodies", "rel_date": "2020-06-03", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.31.20118414", - "rel_abs": "BackgroundCompartmental models dominate epidemic modeling. Estimations of transmission parameters between compartments are typically done through stochastic parameterization processes that depend upon detailed statistics on transmission characteristics, which are economically and resource-wide expensive to collect. We apply deep learning techniques as a lower data dependency alternative to estimate transmission parameters of a customized compartmental model, for the purposes of simulating the dynamics of the US COVID-19 epidemics and projecting its further development.\n\nMethodsWe construct a compartmental model. We develop a multistep deep learning methodology to estimate the models transmission parameters. We then feed the estimated transmission parameters to the model to predict the development of the US COVID-19 epidemics for 35 and 42 days. Epidemics are considered suppressed when the basic reproduction number (R0) becomes less than one.\n\nResultsThe deep learning-enhanced compartmental model predicts that R0 will become less than one around June 19 to July 3, 2020, at which point the epidemics will effectively start to die out, and that the US \"Infected\" population will peak round June 18 to July 2, 2020 between 1{middle dot}34 million and 1{middle dot}41 million individual cases. The models also predict that the number of accumulative confirmed cases will cross the 2 million mark around June 10 to 11, 2020.\n\nConclusionsCurrent compartmental models require stochastic parameterization to estimate the transmission parameters. These models effectiveness depends upon detailed statistics on transmission characteristics. As an alternative, deep learning techniques are effective in estimating these stochastic parameters with greatly reduced dependency on data particularity.", - "rel_num_authors": 1, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2020.06.02.131102", + "rel_abs": "SARS-CoV-2 causes ongoing infections worldwide, and identifying people with immunity is becoming increasingly important. Available point-of-care diagnostic systems as lateral flow assays have high potential for fast and easy on-site antibody testing but are lacking specificity, sensitivity or possibility for quantitative measurements. Here, a new point-of-care approach for SARS-CoV-2 specific antibody detection in human serum based on magnetic immuno-detection is described and compared to standard ELISA. For magnetic immuno-detection, immunofiltration columns were coated with a SARS-CoV-2 spike protein peptide. SARS-CoV-2 peptide reactive antibodies, spiked at different concentrations into PBS and human serum, were rinsed through immunofiltration columns. Specific antibodies were retained within the IFC and labelled with an isotype specific biotinylated antibody. Streptavidin-functionalized magnetic nanoparticles were applied to label the secondary antibodies. Enriched magnetic nanoparticles were then detected by means of frequency magnetic mixing detection technology, using a portable magnetic read-out device. Measuring signals corresponded to the amount of SARS-CoV-2 specific antibodies in the sample. Our preliminary magnetic immuno-detection setup resulted in a higher sensitivity and broader detection range and was four times faster than ELISA. Further optimizations could reduce assay times to that of a typical lateral flow assay, enabling a fast and easy approach, well suited for point-of-care measurements without expensive lab equipment.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "QI DENG", - "author_inst": "Zhejiang Normal University; Cofintelligence Fintech Co. Ltd." + "author_name": "Jan Pietschmann", + "author_inst": "Fraunhofer Institute for Molecular Biology and Applied Ecology IME, Forckenbeckstrasse 6, 52074 Aachen" + }, + { + "author_name": "Nadja Voepel", + "author_inst": "Fraunhofer Institute for Molecular Biology and Applied Ecology IME, Forckenbeckstrasse 6, 52074 Aachen" + }, + { + "author_name": "Holger Spiegel", + "author_inst": "Fraunhofer Institute for Molecular Biology and Applied Ecology IME, Forckenbeckstrasse 6, 52074 Aachen" + }, + { + "author_name": "Hans-Joachim Krause", + "author_inst": "Institute of Biological Information Processing, Bioelectronics IBI-3, Forschungszentrum Juelich, 52428 Juelich" + }, + { + "author_name": "Florian Schroeper", + "author_inst": "Fraunhofer Institute for Molecular Biology and Applied Ecology IME, Forckenbeckstrasse 6, 52074 Aachen" } ], "version": "1", "license": "cc_no", - "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "type": "new results", + "category": "molecular biology" }, { "rel_doi": "10.1101/2020.06.03.131474", @@ -1398886,23 +1399075,59 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.05.31.20118703", - "rel_title": "The Mathematics of Testing with Application to Prevalence of COVID-19", + "rel_doi": "10.1101/2020.06.01.20118935", + "rel_title": "Trauma-spectrum symptoms among the Italian general population in the time of the COVID-19 outbreak.", "rel_date": "2020-06-02", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.31.20118703", - "rel_abs": "We formulate three basic assumptions that should ideally guide any well-designed COVID-19 prevalence study. We provide, on the basis of these assumptions alone, a full derivation of mathematical formulas required for statistical analysis of testing data. In particular, we express the disease prevalence in a population through those for its homogeneous subpopulations. Although some of these formulas are routinely employed in prevalence studies, the study design often contravenes the assumptions upon which these formulas vitally depend. We also designed a natural prevalence estimator from the testing data and studied some of its properties. The results are equally valid for diseases other than COVID-19 as well as in non-epidemiological settings.", - "rel_num_authors": 1, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.01.20118935", + "rel_abs": "BackgroundRecent evidence showed substantial negative mental health outcomes associated with the current COVID-19 pandemic, including trauma-related symptoms although the effects on the Italian population who were subjected to unprecedented nationwide lockdown measure remains unknown. The Global Psychotrauma Screen (GPS) is a brief instrument designed to assess a broad range of trauma-related symptoms with no available validation in the Italian population.\n\nAimsThis study aimed at examining the factor structure of the Italian version of the GPS in a general population sample exposed to the COVID-19 pandemic and at evaluating trauma-related symptoms in the Italian population in the context of specific COVID-19 related risk factors associated with the implementation of lockdown measures and social distancing.\n\nMethodsCross-sectional web-based observational study, as part of a long-term monitoring programme of mental health outcomes in the general population. 18147 participants completed a self-report online questionnaire to collect key demographic data and to evaluate trauma-related symptoms using the GPS, PHQ-9, GAD-7, ISI and PSS. Validation analyses included both exploratory and confirmatory factor analysis, and correlation analyses.\n\nResultsExploratory factor analyses supported both a two-factor and a three-factor model. Confirmatory factor analysis showed that a one-factor solution that was used as a baseline comparison showed acceptable fit indices, the two-factor solution showed good fit indices, but the best fitting model was a three-factor solution, with Negative Affect (symptoms of depressed mood, anxiety, irritability), core Post-traumatic Stress Symptoms (PTSS) (avoidance, re-experiencing, hyperarousal and insomnia) and Dissociative symptoms. GPS Risk factors as well as specific COVID-19 related stressful events, were associated with GPS total as well as the three factor scores.\n\nConclusionsOur data suggest that a wide range of trauma-spectrum symptoms were reported by a large Italian sample during the COVID-19 pandemic. The GPS symptoms clustered best in three factors: Negative Affect symptoms, Core PTSS, and Dissociative symptoms. In particular high rates of core PTSS and negative affect symptoms were associated with the COVID-19 pandemic in Italy and should be routinely assessed in clinical practice.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Leonid Hanin", - "author_inst": "Idaho State University" + "author_name": "Rodolfo Rossi", + "author_inst": "University of Rome Tor Vergata" + }, + { + "author_name": "Valentina Socci", + "author_inst": "University of L'Aquila" + }, + { + "author_name": "Dalila Talevi", + "author_inst": "University of L'Aquila" + }, + { + "author_name": "Cinzia Niolu", + "author_inst": "University of Rome Tor Vergata" + }, + { + "author_name": "Francesca Pacitti", + "author_inst": "University of L'Aquila" + }, + { + "author_name": "Antinisca Di Marco", + "author_inst": "University of L'Aquila" + }, + { + "author_name": "Alessandro Rossi", + "author_inst": "University of L'Aquila" + }, + { + "author_name": "Alberto Siracusano", + "author_inst": "University of Rome Tor Vergata" + }, + { + "author_name": "Giorgio Di Lorenzo", + "author_inst": "University of Rome Tor Vergata" + }, + { + "author_name": "Miranda Olff", + "author_inst": "Department of Psychiatry, Amsterdam Neuroscience & Public Health, Amsterdam UMC, Amsterdam, The Netherlands" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "psychiatry and clinical psychology" }, { "rel_doi": "10.1101/2020.06.01.20118943", @@ -1400424,43 +1400649,59 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.06.01.20119768", - "rel_title": "Association between NSAIDs use and adverse clinical outcomes among adults hospitalised with COVID-19 in South Korea: A nationwide study", + "rel_doi": "10.1101/2020.05.27.20114538", + "rel_title": "COVID-19 containment in the Caribbean: the experience of Small Island Developing States", "rel_date": "2020-06-02", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.01.20119768", - "rel_abs": "BACKGROUNDNon-steroidal anti-inflammatory drugs (NSAIDs) may exacerbate COVID-19 and worsen associated outcomes by upregulating the enzyme that SARS-CoV-2 binds to enter cells. However, to our knowledge, no study has examined the association between NSAID use and the risk of COVID-19-related outcomes among hospitalised patients.\n\nMETHODSWe conducted a population-based cohort study using South Koreas nationwide healthcare database, which contains data of all subjects who received a test for COVID-19 (n=69,793) as of April 8, 2020. We identified a cohort of adults hospitalised with COVID-19, where cohort entry was the date of hospitalisation. NSAIDs users were those prescribed NSAIDs in the 7 days before and including the date of cohort entry and non-users were those not prescribed NSAIDs during this period. Our primary outcome was a composite of in-hospital death, intensive care unit admission, mechanical ventilation use, and sepsis; our secondary outcome was cardiovascular or renal complications. We conducted logistic regression analysis to estimate odds ratio (OR) with 95% confidence intervals (CI) using inverse probability of treatment weighting to minimize potential confounding.\n\nFINDINGSOf 1,824 adults hospitalised with COVID-19 (mean age 490 years, standard deviation 19 0 years; female 59%), 354 were NSAIDs users and 1,470 were non-users. Compared with non-use, NSAIDs use was associated with increased risks of the primary composite outcome (OR 1 65, 95% CI 1-21-2-24) and of cardiovascular or renal complications (OR 187, 95% CI 1-25-2-80). Our main findings remained consistent when we extended the exposure ascertainment window to include the first three days of hospitalisation (OR 187, 95% CI 1 06-3 29).\n\nINTERPRETATIONUse of NSAIDs, compared with non-use, is associated with worse outcomes among hospitalised COVID-19 patients. While awaiting the results of confirmatory studies, we suggest NSAIDs be used with caution among patients with COVID-19 as the harms associated with their use may outweigh their benefits in this population.\n\nFUNDINGGovernment-wide R&D Fund for Infectious Disease Research (HG18C0068).", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.27.20114538", + "rel_abs": "BackgroundSmall island developing states (SIDS) have limited absolute resources for responding to national disasters, including health emergencies. Since the first confirmed case of COVID-19 in the Caribbean on 1st March 2020, non-pharmaceutical interventions (NPIs) have been widely used to control the resulting COVID-19 outbreak. We document the variety of government measures introduced across the Caribbean and explore their impact on aspects of outbreak control.\n\nMethodsDrawing on publically available information, we present confirmed cases and confirmed deaths to describe the extent of the Caribbean outbreak. We document the range of outbreak containment measures implemented by national Governments, focussing on measures to control movement and gatherings. We explore the temporal association of containment measures with the start of the outbreak in each country, and with aggregated information on human movement, using smartphone positioning data. We include a set of comparator countries to provide an international context.\n\nResultsAs of 25th May, the Caribbean reported 18,755 confirmed cases and 631 deaths. There have been broad similarities but also variation in the number, the type, the intensity, and particularly the timing of the NPIs introduced across the Caribbean. On average, Caribbean governments began controlling movement into countries 27 days before their first confirmed case and 23 days before comparator countries. Controls on movement within country were introduced 9 days after the first case and 36 days before comparators. Controls on gatherings were implemented 1 day before the first confirmed case and 30 days before comparators. Confirmed case growth rates and numbers of deaths have remained low across much the Caribbean. Stringent Caribbean curfews and stay-at-home orders coincided with large reductions in community mobility, regularly above 60%, and higher than most international comparator countries.\n\nConclusionStringent controls to limit movement, and specifically the early timing of those controls has had an important impact on containing the spread of COVID-19 across much of the Caribbean. Very early controls to limit movement into countries may well be particularly effective for small island developing states. With much of the region economically reliant on international tourism, and with steps to open borders now being considered, it is critical that the region draws on a solid evidence-base to balance the competing demands of economics and public health.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Han Eol Jeong", - "author_inst": "School of Pharmacy, Sungkyunkwan University" + "author_name": "Madhuvanti M Murphy", + "author_inst": "The University of the West Indies" }, { - "author_name": "Hyesung Lee", - "author_inst": "School of Pharmacy, Sungkyunkwan University" + "author_name": "Selvi M Jeyaseelan", + "author_inst": "The University of the West Indies" }, { - "author_name": "Hyun Joon Shin", - "author_inst": "Division of General Internal Medicine, Department of Medicine, Brigham and Women's Hospital, Department of Global Health and Social Medicine, Harvard Medical Sc" + "author_name": "Christina Howitt", + "author_inst": "The University of the West Indies" }, { - "author_name": "Young June Choe", - "author_inst": "Hallym University College of Medicine" + "author_name": "Natalie Greaves", + "author_inst": "The University of the West Indies" }, { - "author_name": "Kristian B Filion", - "author_inst": "Departments of Medicine and Epidemiology, Biostatistics and Occupational Health, McGill University and Centre for Clinical Epidemiology, Lady Davis Institute" + "author_name": "Heather Harewood", + "author_inst": "The University of the West Indies" }, { - "author_name": "Ju-Young Shin", - "author_inst": "School of Pharmacy, Sungkyunkwan University" + "author_name": "Kim R Quimby", + "author_inst": "The University of the West Indies" + }, + { + "author_name": "Natasha Sobers", + "author_inst": "The University of the West Indies" + }, + { + "author_name": "R Clive Landis", + "author_inst": "The University of the West Indies" + }, + { + "author_name": "Kern Rocke", + "author_inst": "The University of the West Indies" + }, + { + "author_name": "Ian R Hambleton", + "author_inst": "The University of the West Indies" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "public and global health" }, { "rel_doi": "10.1101/2020.05.31.20115196", @@ -1402606,67 +1402847,59 @@ "category": "biophysics" }, { - "rel_doi": "10.1101/2020.06.02.130161", - "rel_title": "An alpaca nanobody neutralizes SARS-CoV-2 by blocking receptor interaction", + "rel_doi": "10.1101/2020.06.02.129775", + "rel_title": "Optimizing the molecular diagnosis of Covid-19 by combining RT-PCR and a pseudo-convolutional machine learning approach to characterize virus DNA sequences", "rel_date": "2020-06-02", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.06.02.130161", - "rel_abs": "SARS-CoV-2 is the etiologic agent of COVID-19, currently causing a devastating pandemic for which pharmacological interventions are urgently needed. The virus enters host cells through an interaction between the spike glycoprotein and the angiotensin converting enzyme 2 (ACE2) receptor. Directly preventing this interaction presents an attractive possibility for suppressing SARS-CoV-2 replication. Here we report the isolation and characterization of an alpaca-derived single domain antibody fragment, Ty1, that specifically targets the receptor binding domain (RBD) of the SARS-CoV-2 spike, directly preventing ACE2 engagement. The nanobody binds with high affinity in the low nM range to the RBD, occluding ACE2. A cryo-electron microscopy structure of the bound complex at 2.9 \u00c5 resolution reveals that Ty1 binds to an epitope on the RBD accessible in both the \u2018up\u2019 and \u2018down\u2019 conformations and that Ty1 sterically hinders RBD-ACE2 binding. This 12.8 kDa nanobody does not need an Fc domain to neutralize SARS-CoV-2, and can be expressed in high quantities in bacteria, presenting opportunities for manufacturing at scale. Ty1 is therefore an excellent candidate as an intervention against COVID-19.Competing Interest StatementThe authors have declared no competing interest.View Full Text", - "rel_num_authors": 12, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.06.02.129775", + "rel_abs": "The proliferation of the SARS-Cov-2 virus to the whole world caused more than 250,000 deaths worldwide and over 4 million confirmed cases. The severity of Covid-19, the exponential rate at which the virus proliferates, and the rapid exhaustion of the public health resources are critical factors. The RT-PCR with virus DNA identification is still the benchmark Covid-19 diagnosis method. In this work we propose a new technique for representing DNA sequences: they are divided into smaller sequences with overlap in a pseudo-convolutional approach, and represented by co-occurrence matrices. This technique analyzes the DNA sequences obtained by the RT-PCR method, eliminating sequence alignment. Through the proposed method, it is possible to identify virus sequences from a large database: 347,363 virus DNA sequences from 24 virus families and SARS-Cov-2. Experiments with all 24 virus families and SARS-Cov-2 (multi-class scenario) resulted 0.822222 {+/-} 0.05613 for sensitivity and 0.99974 {+/-} 0.00001 for specificity using Random Forests with 100 trees and 30% overlap. When we compared SARS-Cov-2 with similar-symptoms virus families, we got 0.97059 {+/-} 0.03387 for sensitivity, and 0.99187 {+/-} 0.00046 for specificity with MLP classifier and 30% overlap. In the real test scenario, in which SARS-Cov-2 is compared to Coronaviridae and healthy human DNA sequences, we got 0.98824 {+/-} 001198 for sensitivity and 0.99860 {+/-} 0.00020 for specificity with MLP and 50% overlap. Therefore, the molecular diagnosis of Covid-19 can be optimized by combining RT-PCR and our pseudo-convolutional method to identify SARS-Cov-2 DNA sequences faster with higher specificity and sensitivity.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Leo Hanke", - "author_inst": "Karolinska Institutet" - }, - { - "author_name": "Maria Laura Perez Vidakovics", - "author_inst": "Karolinska Institutet" - }, - { - "author_name": "Daniel Sheward", - "author_inst": "Karolinska Institutet" + "author_name": "Juliana Carneiro Gomes", + "author_inst": "Escola Politecnica da Universidade de Pernambuco" }, { - "author_name": "Hrishikesh Das", - "author_inst": "Karolinska Institutet" + "author_name": "Aras Ismael Masood", + "author_inst": "Sulaimani Polytechnic University" }, { - "author_name": "Tim Schulte", - "author_inst": "Karolinska Institutet" + "author_name": "Leandro Honorato de S. Silva", + "author_inst": "Instituto Federal de Educacao, Ciencia e Tecnologia da Paraiba" }, { - "author_name": "Ainhoa Moliner Morro", - "author_inst": "Karolinska Institutet" + "author_name": "Janderson Ferreira", + "author_inst": "Escola Politecnica da Universidade de Pernambuco" }, { - "author_name": "Martin Corcoran", - "author_inst": "Karolinska Institutet" + "author_name": "Agostinho A. F. Junior", + "author_inst": "Escola Politecnica da Universidade de Pernambuco" }, { - "author_name": "Adnane Achour", - "author_inst": "Karolinska Institutet" + "author_name": "Allana Lais dos Santos Rocha", + "author_inst": "Escola Politecnica da Universidade de Pernambuco" }, { - "author_name": "Gunilla Karlsson Hedestam", - "author_inst": "Karolinska Institutet" + "author_name": "Leticia Castro", + "author_inst": "Escola Politecnica da Universidade de Pernambuco" }, { - "author_name": "B. Martin H\u00e4llberg", - "author_inst": "Karolinska Institutet" + "author_name": "Nathalia R. C. da Silva", + "author_inst": "Escola Politecnica da Universidade de Pernambuco" }, { - "author_name": "Ben Murrell", - "author_inst": "Karolinska Institutet" + "author_name": "Bruno Jose T. Fernandes", + "author_inst": "Escola Politecnica da Universidade de Pernambuco" }, { - "author_name": "Gerald M McInerney", - "author_inst": "Karolinska Institutet" + "author_name": "Wellington Pinheiro dos Santos", + "author_inst": "Universidade Federal de Pernambuco" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nd", "type": "new results", - "category": "microbiology" + "category": "bioinformatics" }, { "rel_doi": "10.1101/2020.05.10.20097634", @@ -1404000,55 +1404233,27 @@ "category": "molecular biology" }, { - "rel_doi": "10.1101/2020.06.01.127589", - "rel_title": "Reconstructing SARS-CoV-2 response signaling and regulatory networks", + "rel_doi": "10.1101/2020.05.31.126813", + "rel_title": "Covid-19 pandemic and the unprecedented mobilisation of scholarly efforts prompted by a health crisis: Scientometric comparisons across SARS, MERS and 2019-nCov literature", "rel_date": "2020-06-01", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.06.01.127589", - "rel_abs": "Several molecular datasets have been recently compiled to characterize the activity of SARS-CoV-2 within human cells. Here we extend computational methods to integrate several different types of sequence, functional and interaction data to reconstruct networks and pathways activated by the virus in host cells. We identify key proteins in these networks and further intersect them with genes differentially expressed at conditions that are known to impact viral activity. Several of the top ranked genes do not directly interact with virus proteins. We experimentally tested treatments for a number of the predicted targets. We show that blocking one of the predicted indirect targets significantly reduces viral loads in stem cell-derived alveolar epithelial type II cells (iAT2s).\n\nSoftware and interactive visualizationhttps://github.com/phoenixding/sdremsc", - "rel_num_authors": 9, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.31.126813", + "rel_abs": "During the current century, each major coronavirus outbreak has triggered a quick and immediate surge of academic publications on this topic. The spike in research publications following the 2019 Novel Coronavirus (Covid-19) outbreak, however, has been like no other. The global crisis caused by the Covid-19 pandemic has mobilised scientific efforts in an unprecedented way. In less than five months, more than 12,000 research items have been indexed while the number increasing every day. With the crisis affecting all aspects of life, research on Covid-19 seems to have become a focal point of interest across many academic disciplines. Here, scientometric aspects of the Covid-19 literature are analysed and contrasted with those of the two previous major Coronavirus diseases, i.e. Severe Acute Respiratory Syndrome (SARS) and Middle East Respiratory Syndrome (MERS). The focus is on the co-occurrence of key-terms, bibliographic coupling and citation relations of journals and collaborations between countries. Certain recurring patterns across all three literatures were discovered. All three outbreaks have commonly generated three distinct and major cohort of studies: (i) studies linked to the public health response and epidemic control, (ii) studies associated with the chemical constitution of the virus and (iii) studies related to treatment, vaccine and clinical care. While studies affiliated with the category (i) seem to have been the first to emerge, they overall received least numbers of citations compared to those of the two other categories. Covid-19 studies seem to have been distributed across a broader variety of journals and subject areas. Clear links are observed between the geographical origins of each outbreak or the local geographical severity of each outbreak and the magnitude of research originated from regions. Covid-19 studies also display the involvement of authors from a broader variety of countries compared to SARS and MRS.Competing Interest StatementThe authors have declared no competing interest.View Full Text", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Jun Ding", - "author_inst": "McGill University" - }, - { - "author_name": "Jose Lugo-Martinez", - "author_inst": "Carnegie Mellon University" - }, - { - "author_name": "Ye Yuan", - "author_inst": "Shanghai Jiao Tong University" - }, - { - "author_name": "Jessie Huang", - "author_inst": "Boston University" - }, - { - "author_name": "Adam Joseph Hume", - "author_inst": "Boston University" - }, - { - "author_name": "Ellen L Suder", - "author_inst": "Boston University" - }, - { - "author_name": "Elke Muhlberger", - "author_inst": "Boston University" - }, - { - "author_name": "Darrell N. Kotton", - "author_inst": "Boston University" + "author_name": "Milad Haghani", + "author_inst": "The University of Sydney" }, { - "author_name": "Ziv Bar-Joseph", - "author_inst": "Carnegie Mellon University" + "author_name": "Michiel C. J. Bliemer", + "author_inst": "The University of Sydney" } ], "version": "1", - "license": "cc_by", + "license": "cc_no", "type": "new results", - "category": "systems biology" + "category": "scientific communication and education" }, { "rel_doi": "10.1101/2020.06.01.127605", @@ -1405669,103 +1405874,27 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.05.30.20117291", - "rel_title": "EasyCOV : LAMP based rapid detection of SARS-CoV-2 in saliva", + "rel_doi": "10.1101/2020.05.28.20115741", + "rel_title": "Chloroquine, hydroxychloroquine, and COVID-19: systematic review and narrative synthesis of efficacy and safety", "rel_date": "2020-05-30", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.30.20117291", - "rel_abs": "Covid-19 crisis showed us that rapid massive virus detection campaign is a key element in SARS-CoV-2 pandemic response. The classical RT-PCR laboratory platforms must be complemented with rapid and simplified technologies to enhance efficiency of large testing strategies.\n\nTo this aim, we developed EasyCOV, a direct saliva RT-LAMP based SARS-CoV-2 virus detection assay that do not requires any RNA extraction step. It allows robust and rapid response under safe and easy conditions for healthcare workers and patients.\n\nEasyCOV test was assessed under double blind clinical conditions (93 asymptomatic healthcare worker volonteers, 10 actively infected patients, 20 former infected patients tested during late control visit). EasyCOV results were compared with classical laboratory RT-PCR performed on nasopharyngeal samples.\n\nOur results show that compared with nasopharyngeal laboratory RT-PCR, EasyCOV SARS-CoV-2 detection test has a sensitivity of 72.7%. Measured on healthcare worker population the specificity was 95.7%. LAMP technology on saliva is clearly able to identify subjects with infectivity profile. Among healthcare worker population EasyCOV test detected one presymptomatic subject.\n\nBecause it is simple, rapid and painless for patients, EasyCOV saliva SARS-Cov-2 detection test may be useful for large screening of general population.", - "rel_num_authors": 21, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.28.20115741", + "rel_abs": "BackgroundThe COVID-19 pandemic has required clinicians to urgently identify new treatment options or the repurposing of existing drugs. Several drugs are now being repurposed with the aim of identifying if these drugs provide some level of disease resolution. Of particular interest are chloroquine (CQ) and hydroxychloroquine (HCQ), first developed as an antimalarial therapy. There is increasing concern with regards to the efficacy and safety of these agents. The aims of this review are to systematically identify and collate studies describing the use of CQ and HCQ in human clinical trials and provide a detailed synthesis of evidence of its efficacy and safety.\n\nMethods and FindingsSearches for (\"COVID\" AND \"chloroquine\"[title/abstract] AND \"outcomes\"[full text]) and two (\"COVID\" AND \"hydroxychloroquine\"[title/abstract] AND \"outcomes\"[full text]) yielded 272 unique articles. Unique articles were manually checked for inclusion and exclusion criteria and also subjected to a quality appraisal assessment. A total of 19 articles were included in the systematic review. Seventy-five percent of observational studies employing an endpoint specific to efficacy recorded no significant difference in the attainment of outcomes, between COVID-19 patients given a range of CQ and/or HCQ doses, and the control groups. All clinical trials and 82% of observational studies examining an indicator unique to drug safety discovered a higher probability of adverse events in those treated patients suspected of, and diagnosed with, COVID-19. Seventy-five percent of the total papers focusing on cardiac side-effects found a greater incidence among patients administered a wide range of CQ and/or HCQ doses, with QTc prolongation the most common finding, in addition to its consequences of VT and cardiac arrest. Of the total studies using mortality rate as an end-point, 60% reported no significant change in the risk of death, while 30% showed an elevation, and 10% a depression, in treated relative to control patients.\n\nConclusionThe strongest available evidence suggests that, relative to standard in-hospital management of symptoms, the use of CQ and HCQ to treat hospitalised COVID-19 patients has likely been unsafe. At the very least, the poor quality of data failing to find any significant changes in the risk of VT should preclude definitive judgment on drug safety until the completion of high-quality randomised clinical trials.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Nicolas L'Helgouach", - "author_inst": "Sys2diag CNRS / ALCEDIAG" - }, - { - "author_name": "Pierre Champigneux", - "author_inst": "Sys2diag CNRS / ALCEDIAG" - }, - { - "author_name": "Francisco Santos-Schneider", - "author_inst": "Sys2diag CNRS / ALCEDIAG" - }, - { - "author_name": "Laurence Molina", - "author_inst": "Sys2diag CNRS / ALCEDIAG" - }, - { - "author_name": "Julien Espeut", - "author_inst": "Sys2diag CNRS / ALCEDIAG" - }, - { - "author_name": "Mellis Alali", - "author_inst": "Sys2diag CNRS / ALCEDIAG" - }, - { - "author_name": "Julie Baptiste", - "author_inst": "Sys2diag CNRS / ALCEDIAG" - }, - { - "author_name": "Lise Cardeur", - "author_inst": "Sys2diag CNRS / ALCEDIAG" - }, - { - "author_name": "Benjamin Dubuc", - "author_inst": "Sys2diag CNRS / ALCEDIAG" - }, - { - "author_name": "Vincent Foulongne", - "author_inst": "Virology Dpt University Hospital Montpellier" - }, - { - "author_name": "Florence Galtier", - "author_inst": "CIC University Hospital Montpellier" - }, - { - "author_name": "Alain Makinson", - "author_inst": "Infectious diseases dpt University Hospital Montpellier" - }, - { - "author_name": "Gregory Marin", - "author_inst": "DIM clinical research unit University Hospital Montpellier" - }, - { - "author_name": "Marie-Chritine Picot", - "author_inst": "DIM clinical research unit University Hospital Montpellier" - }, - { - "author_name": "Alexandra Prieux-Lejeune", - "author_inst": "Sys2diag CNRS / ALCEDIAG, Montpellier, France" - }, - { - "author_name": "Marine Quenot", - "author_inst": "Sys2diag CNRS / ALCEDIAG, Montpellier, France" - }, - { - "author_name": "Francisco Jesus Checa-Robles", - "author_inst": "Sys2diag CNRS / ALCEDIAG, Montpellier, France" - }, - { - "author_name": "Nicolas Salvetat", - "author_inst": "Sys2diag CNRS / ALCEDIAG, Montpellier, France" - }, - { - "author_name": "Diana Vetter", - "author_inst": "Sys2diag CNRS / ALCEDIAG, Montpellier, France" - }, - { - "author_name": "Jacques Reynes", - "author_inst": "Infectious diseases dpt University Hospital Montpellier" + "author_name": "Micheal takla", + "author_inst": "Cambridge" }, { - "author_name": "Franck Molina", - "author_inst": "Sys2diag CNRS / ALCEDIAG, Montpellier, France" + "author_name": "Kamalan Jeevaratnam", + "author_inst": "Surrey" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "pharmacology and therapeutics" }, { "rel_doi": "10.1101/2020.05.28.20115311", @@ -1407287,27 +1407416,23 @@ "category": "cardiovascular medicine" }, { - "rel_doi": "10.1101/2020.05.28.20115832", - "rel_title": "COVID-19 higher morbidity and mortality in Chinese regions with lower air quality", - "rel_date": "2020-05-30", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.28.20115832", - "rel_abs": "We investigated the geographical character of the COVID-19 infection in China and correlated it with satellite- and ground-based measurements of air quality. Controlling for population size, we found more viral infections in those areas afflicted by high Carbon Monoxide, formaldehyde, PM 2.5, and Nitrogen Dioxide values. Higher mortality was also correlated with relatively poor air quality. Air pollution appears to be a risk factor for the incidence of this disease, similar to smoking. This suggests the detrimental impact of air pollution in these types of respiratory epidemics.\n\nShort summaryO_LIThere is a significant correlation between air pollution and COVID-19 spread and mortality in China.\nC_LIO_LIThe correlation stands at a second-order administration level, after controlling for varying population densities and removing Wuhan and Hubei from the dataset.\nC_LIO_LILiving in an area with low air quality is a risk factor for becoming infected and dying from this new form of coronavirus.\nC_LI", - "rel_num_authors": 2, + "rel_doi": "10.1101/2020.05.29.123455", + "rel_title": "The representation of women as authors of submissions to ecology journals during the COVID-19 pandemic", + "rel_date": "2020-05-29", + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.29.123455", + "rel_abs": "Observations made from papers submitted to preprint servers, and the speculation of editors on social media platforms, suggest that women are submitting fewer papers to scholarly journals than are men during the COVID-19 pandemic. Here I examine whether submissions by men and women to six ecology journals (all published by the British Ecological Society) have changed since the start of COVID disruptions. At these six ecology journals there is no evidence of a decline in the proportion of submissions that are authored by women (as either first or submitting author) since the start of the COVID-19 disruptions; the proportion of papers authored by women in the post-COVID period of 2020 has increased relative to the same period in 2019, and is higher than in the period pre-COVID in 2020. There is also no evidence of a change in the geographic pattern of submissions from across the globe.Competing Interest StatementCharles Fox is Executive Editor of Functional Ecology, one of the journals that contributed data for the analyses presented in this paper.View Full Text", + "rel_num_authors": 1, "rel_authors": [ { - "author_name": "Riccardo Pansini", - "author_inst": "Yunnan University of Finance and Economics" - }, - { - "author_name": "Davide Fornacca", - "author_inst": "Institute of Eastern-Himalaya Biodiversity Research, Dali University, Yunnan, China" + "author_name": "Charles W Fox", + "author_inst": "University of Kentucky" } ], "version": "1", "license": "cc_by_nc_nd", - "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "type": "new results", + "category": "scientific communication and education" }, { "rel_doi": "10.1101/2020.05.29.124123", @@ -1408581,29 +1408706,29 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.05.27.20114371", - "rel_title": "Covid19db -- An online database of trials of medicinal products to prevent or treat COVID-19, with a specific focus on drug repurposing", + "rel_doi": "10.1101/2020.05.27.20114983", + "rel_title": "A call for governments to pause Twitter censorship: a cross-sectional study using Twitter data as social-spatial sensors of COVID-19/SARS-CoV-2 research diffusion", "rel_date": "2020-05-29", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.27.20114371", - "rel_abs": "BackgroundThe global pandemic caused by SARS-CoV-2 virus has prompted an unprecedented international effort to seek medicines for prevention and treatment of infection. Drug repurposing has played a key part in this response. The rapid increase in trial activity has raised questions about efficiency and lack of coordination. Our objective was to develop a user-friendly, open access database to monitor and rapidly identify trials of medicinal products.\n\nMethodsUsing the US clinicaltrials.gov (NCT) registry, the EU Clinical Trials Register (EUCTR) and the WHO International Clinical Trials Registry Platform (WHO ICTRP), we identified all COVID-19 trials of medicinal products. Trials that were out of scope and duplicates were excluded. A manual encoding was performed to ascertain key information (e.g. trial aim, type of intervention etc). The database, Covid19db, is published online at: http://www.redo-project.org/covid19db/.\n\nResultsDescriptive statistics of the database from April 4th 2020 through to August 18th show an increase from 186 to 1618 trials, or an average of 10.5 new trials registered per day. Over this period, the proportion of trials including a repurposing arm decreased slightly (from a maximum of 75% to 64% at the end of the covered period) as did the proportion of trials aiming to prevent infection (from a maximum of 16% to 13%). The most popular trial intervention is hydroxychloroquine (212 trials), followed by azithromycin (64 trials), tocilizumab, favipiravir and chloroquine (145 trials). Total planned enrolment is 1064556 participants as of 18th August 2020.\n\nConclusionswe have developed an open access and regularly updated tool to monitor clinical trials of medicinal products to prevent or treat infection by SARS-CoV-2 globally. Our analysis shows a high number of me-too trials, in particular for some repurposed drugs, such as hydroxychloroquine, azithromycin and tocilizumab, substantiating calls for better coordination and better use of trial resources.", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.27.20114983", + "rel_abs": "ObjectivesTo determine whether Twitter data can be used as social-spatial sensors to show how research on COVID-19/SARS-CoV-2 diffuses through the population to reach the people that are especially affected by the disease.\n\nDesignCross-sectional bibliometric analysis conducted between 23rd March and 14th April 2020.\n\nSettingThree sources of data were used in the analysis: (1) deaths per number of population for COVID-19/SARS-CoV-2 retrieved from Coronavirus Resource Center at John Hopkins University and Worldometer, (2) publications related to COVID-19/SARS-CoV-2 retrieved from WHO COVID-19 database of global publications, and (3) tweets of these publications retrieved from Altmetric.com and Twitter.\n\nMain Outcome(s) and Measure(s)To map Twitter activity against number of publications and deaths per number of population worldwide and in the USA states. To determine the relationship between number of tweets as dependent variable and deaths per number of population and number of publications as independent variables.\n\nResultsDeaths per one hundred thousand population for countries ranged from 0 to 104, and deaths per one million population for USA states ranged from 2 to 513. Total number of publications used in the analysis was 1761, and total number of tweets used in the analysis was 751,068. Mapping of worldwide data illustrated that high Twitter activity was related to high numbers of COVID-19/SARS-CoV-2 deaths, with tweets inversely weighted with number of publications. Poisson regression models of worldwide data showed a positive correlation between the national deaths per number of population and tweets when holding the countrys number of publications constant (coefficient 0.0285, S.E. 0.0003, p<0.001). Conversely, this relationship was negatively correlated in USA states (coefficient -0.0013, S.E. 0.0001, p<0.001).\n\nConclusionsThis study shows that Twitter can play a crucial role in the rapid research response during the COVID-19/SARS-CoV-2 global pandemic, especially to spread research with prompt public scrutiny. Governments are urged to pause censorship of social media platforms during these unprecedented times to support the scientific communitys fight against COVID-19/SARS-CoV-2.\n\nSUMMARY BOXO_ST_ABSWhat is already known on this topicC_ST_ABSO_LITwitter is progressively being used by researchers to share information and knowledge transfer.\nC_LIO_LITweets can be used as social sensors, which is the concept of transforming a physical sensor in the real world through social media analysis.\nC_LIO_LIPrevious studies have shown that social sensors can provide insight into major social and physical events.\nC_LI\n\nWhat this study addsO_LIUsing Twitter data used as social-spatial sensors, we demonstrated that Twitter activity was significantly positively correlated to the numbers of COVID-19/SARS-CoV-2 deaths, when holding the countrys number of publications constant.\nC_LIO_LITwitter can play a crucial role in the rapid research response during the COVID-19/SARS-CoV-2 global pandemic.\nC_LI", "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Pan Pantziarka", - "author_inst": "Anticancer Fund" + "author_name": "Vanash Patel", + "author_inst": "Imperial College London" }, { - "author_name": "Liese Vandeborne", - "author_inst": "Anticancer Fund" + "author_name": "Robin Haunschild", + "author_inst": "Max Planck Institute for Solid State Research" }, { - "author_name": "Lydie Meheus", - "author_inst": "Anticancer Fund" + "author_name": "Lutz Bornmann", + "author_inst": "Max Planck Society" }, { - "author_name": "Gauthier Bouche", - "author_inst": "Anticancer Fund" + "author_name": "George Garas", + "author_inst": "Imperial College London" } ], "version": "1", @@ -1409779,51 +1409904,51 @@ "category": "genomics" }, { - "rel_doi": "10.1101/2020.05.29.123612", - "rel_title": "SARS-CoV-2 transmission chains from genetic data: a Danish case study", + "rel_doi": "10.1101/2020.05.28.122366", + "rel_title": "Evidence of significant natural selection in the evolution of SARS-CoV-2 in bats, not humans", "rel_date": "2020-05-29", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.29.123612", - "rel_abs": "Background The COVID-19 pandemic caused by the SARS-CoV-2 virus started in China in December 2019 and has since spread globally. Information about the spread of the virus in a country can inform the gradual reopening of a country and help to avoid a second wave of infections. Denmark is currently opening up after a lockdown in mid-March.Methods We perform a phylogenetic analysis of 742 publicly available Danish SARS-CoV-2 genome sequences and put them into context using sequences from other countries.Result Our findings are consistent with several introductions of the virus to Denmark from independent sources. We identify several chains of mutations that occurred in Denmark and in at least one case find evidence that the virus spread from Denmark to other countries. A number of the mutations found in Denmark are non-synonymous, and in general there is a considerable variety of strains. The proportions of the most common haplotypes is stable after lockdown.Conclusion Our work shows how genetic data can be used to identify routes of introduction of a virus into a region and provide alternative means for verifying existing assumptions. For example, our analysis supports the hypothesis that the virus was brought to Denmark by skiers returning from Ischgl. On the other hand, we identify transmission chains suggesting that Denmark was part of a network of countries among which the virus was being transmitted; thus challenging the common narrative that Denmark only got infected from abroad. Our analysis does not indicate that the major haplotypes appearing in Denmark have a different degree of virality. Our methods can be applied to other countries, regions or even highly localised outbreaks. When used in real-time, we believe they can serve to identify transmission events and supplement traditional methods such as contact tracing.Competing Interest StatementThe authors have declared no competing interest.View Full Text", + "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.28.122366", + "rel_abs": "RNA viruses are proficient at switching host species, and evolving adaptations to exploit the new hosts cells efficiently. Surprisingly, SARS-CoV-2 has apparently required no significant adaptation to humans since the start of the COVID-19 pandemic, with no observed selective sweeps since genome sampling began. Here we assess the types of natural selection taking place in Sarbecoviruses in horseshoe bats versus SARS-CoV-2 evolution in humans. While there is moderate evidence of diversifying positive selection in SARS-CoV-2 in humans, it is limited to the early phase of the pandemic, and purifying selection is much weaker in SARS-CoV-2 than in related bat Sarbecoviruses. In contrast, our analysis detects significant positive episodic diversifying selection acting on the bat virus lineage SARS-CoV-2 emerged from, accompanied by an adaptive depletion in CpG composition presumed to be linked to the action of antiviral mechanisms in ancestral hosts. The closest bat virus to SARS-CoV-2, RmYN02 (sharing an ancestor [~]1976), is a recombinant with a structure that includes differential CpG content in Spike; clear evidence of coinfection and evolution in bats without involvement of other species. Collectively our results demonstrate the progenitor of SARS-CoV-2 was capable of near immediate human-human transmission as a consequence of its adaptive evolutionary history in bats, not humans.", "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Andreas Bluhm", - "author_inst": "University of Copenhagen" + "author_name": "Oscar A MacLean", + "author_inst": "University of Glasgow" }, { - "author_name": "Matthias Christandl", - "author_inst": "University of Copenhagen" + "author_name": "Spyros Lytras", + "author_inst": "University of Glasgow" }, { - "author_name": "Fulvio Gesmundo", - "author_inst": "University of Copenhagen" + "author_name": "Steven Weaver", + "author_inst": "Temple University" }, { - "author_name": "Frederik Ravn Klausen", - "author_inst": "University of Copenhagen" + "author_name": "Joshua B Singer", + "author_inst": "University of Glasgow" }, { - "author_name": "Laura Mancinska", - "author_inst": "University of Copenhagen" + "author_name": "Maciej F Boni", + "author_inst": "Pennsylvania State University" }, { - "author_name": "Vincent Steffan", - "author_inst": "University of Copenhagen" + "author_name": "Philippe Lemey", + "author_inst": "KU Leuven" }, { - "author_name": "Daniel Stilck Franca", - "author_inst": "University of Copenhagen" + "author_name": "Sergei L Kosakovsky Pond", + "author_inst": "Temple University" }, { - "author_name": "Albert Werner", - "author_inst": "University of Copenhagen" + "author_name": "David L Robertson", + "author_inst": "University of Glasgow" } ], "version": "1", "license": "cc_by", "type": "new results", - "category": "genomics" + "category": "evolutionary biology" }, { "rel_doi": "10.1101/2020.05.28.122291", @@ -1411249,103 +1411374,39 @@ "category": "genomics" }, { - "rel_doi": "10.1101/2020.05.28.121640", - "rel_title": "Single-dose replicating RNA vaccine induces neutralizing antibodies against SARS-CoV-2 in nonhuman primates", + "rel_doi": "10.1101/2020.05.26.118190", + "rel_title": "Comparison of the NeuMoDX, Diasorin Simplexa, Cepheid and Roche CDC SARS-CoV 2 EUA assays using nasopharyngeal/nasal swabs in universal transport media (UTM) and sputum and tracheal aspirates", "rel_date": "2020-05-28", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.28.121640", - "rel_abs": "The ongoing COVID-19 pandemic, caused by infection with SARS-CoV-2, is having a dramatic and deleterious impact on health services and the global economy. Grim public health statistics highlight the need for vaccines that can rapidly confer protection after a single dose and be manufactured using components suitable for scale-up and efficient distribution. In response, we have rapidly developed repRNA-CoV2S, a stable and highly immunogenic vaccine candidate comprised of an RNA replicon formulated with a novel Lipid InOrganic Nanoparticle (LION) designed to enhance vaccine stability, delivery and immunogenicity. We show that intramuscular injection of LION/repRNA-CoV2S elicits robust anti-SARS-CoV-2 spike protein IgG antibody isotypes indicative of a Type 1 T helper response as well as potent T cell responses in mice. Importantly, a single-dose administration in nonhuman primates elicited antibody responses that potently neutralized SARS-CoV-2. These data support further development of LION/repRNA-CoV2S as a vaccine candidate for prophylactic protection from SARS-CoV-2 infection.", - "rel_num_authors": 21, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.26.118190", + "rel_abs": "In March 2019 the outbreak of SARS-CoV 2 was officially defined as a pandemic by the World Health Organization and shortly after, the United States Food and Drug Administration (FDA) granted Emergency Use Authorization (EUA) to the Centers for Disease Control (CDC) for reverse transcription polymerase chain reaction (rtPCR) molecular testing for the detection of the SARS-CoV-2 virus from NP swabs. Since then, EUA with relaxed regulations were granted to numerous manufacturers and clinical microbiology laboratories to implement in-house testing assays with nasopharyngeal swabs (NP) and subsequently additional specimen types. Because of supply chain shortages leading to competition for reagents, sustaining any significant volume of testing soon became problematic. As a countermeasure, within several weeks the Henry Ford Microbiology Laboratory validated 4 different rtPCR assays and multiple specimen types using NeuMoDX, Diasorin Simplexa, Cepheid and Roche platforms. The purpose of this study was to analyze the analytic sensitivity of these rtPCR assays with NP/nasal swabs and sputum/tracheal aspirates. Qualitative analytic agreement between the 4 platforms for NP/nasal swabs ranged 95% - 100% overall with no statistically significant difference in threshold cT values. Similar results were obtained with the sputum/tracheal aspirates. These data demonstrate the high accuracy and reproducibility in detection of SARS-CoV 2 between the rtPCR assays performed on 4 different platforms with numerous specimen types.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Jesse H Erasmus", - "author_inst": "University of Washington" - }, - { - "author_name": "Amit P Khandhar", - "author_inst": "HDT Bio Corp" - }, - { - "author_name": "Alexandra C Walls", - "author_inst": "University of Washington" - }, - { - "author_name": "Emily A Hemann", - "author_inst": "University of Washington" - }, - { - "author_name": "Patience Murapa", - "author_inst": "University of Washington" - }, - { - "author_name": "Jacob Archer", - "author_inst": "University of Washington" - }, - { - "author_name": "Shanna Leventhal", - "author_inst": "National Institute of Allergy and Infectious Diseases" - }, - { - "author_name": "Jim Fuller", - "author_inst": "University of Washington" - }, - { - "author_name": "Thomas Lewis", - "author_inst": "University of Washington" - }, - { - "author_name": "Kevin E Draves", - "author_inst": "University of Washington" - }, - { - "author_name": "Samantha Randall", - "author_inst": "PAI Life Sciences" - }, - { - "author_name": "Kathryn A Guerriero", - "author_inst": "University of Washington" - }, - { - "author_name": "Malcolm S Duthie", - "author_inst": "HDT Bio Corp" - }, - { - "author_name": "Darrick Carter", - "author_inst": "HDT Bio Corp" - }, - { - "author_name": "Steven G Reed", - "author_inst": "HDT Bio Corp" - }, - { - "author_name": "David W Hawman", - "author_inst": "National Institute of Allergy and Infectious Diseases" - }, - { - "author_name": "Heinz Feldmann", - "author_inst": "National Institute of Allergy and Infectious Diseases" + "author_name": "Robert J Tibbetts", + "author_inst": "Henry Ford Health System" }, { - "author_name": "Michael Gale Jr.", - "author_inst": "University of Washington" + "author_name": "Kathy Callahan", + "author_inst": "Henry Ford Health System" }, { - "author_name": "David Veesler", - "author_inst": "University of Washington" + "author_name": "Kareem Rofoo", + "author_inst": "Henry Ford Health System" }, { - "author_name": "Peter Berglund", - "author_inst": "HDT Bio Corp" + "author_name": "Richard J Zarbo", + "author_inst": "Henry Ford Health System" }, { - "author_name": "Deborah Heydenburg Fuller", - "author_inst": "University of Washington" + "author_name": "Linoj Philip Samuel", + "author_inst": "Henry Ford Health System" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "new results", - "category": "immunology" + "category": "microbiology" }, { "rel_doi": "10.1101/2020.05.28.120709", @@ -1412687,151 +1412748,91 @@ "category": "bioinformatics" }, { - "rel_doi": "10.1101/2020.05.27.118117", - "rel_title": "Crystallographic and electrophilic fragment screening of the SARS-CoV-2 main protease", + "rel_doi": "10.1101/2020.05.27.117184", + "rel_title": "Morphological Cell Profiling of SARS-CoV-2 Infection Identifies Drug Repurposing Candidates for COVID-19", "rel_date": "2020-05-27", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.27.118117", - "rel_abs": "COVID-19, caused by SARS-CoV-2, lacks effective therapeutics. Additionally, no antiviral drugs or vaccines were developed against the closely related coronavirus, SARS-CoV-1 or MERS-CoV, despite previous zoonotic outbreaks. To identify starting points for such therapeutics, we performed a large-scale screen of electrophile and non-covalent fragments through a combined mass spectrometry and X-ray approach against the SARS-CoV-2 main protease, one of two cysteine viral proteases essential for viral replication. Our crystallographic screen identified 71 hits that span the entire active site, as well as 3 hits at the dimer interface. These structures reveal routes to rapidly develop more potent inhibitors through merging of covalent and non-covalent fragment hits; one series of low-reactivity, tractable covalent fragments was progressed to discover improved binders. These combined hits offer unprecedented structural and reactivity information for on-going structure-based drug design against SARS-CoV-2 main protease.", - "rel_num_authors": 33, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.27.117184", + "rel_abs": "The global spread of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and the associated disease COVID-19, requires therapeutic interventions that can be rapidly identified and translated to clinical care. Traditional drug discovery methods have a >90% failure rate and can take 10-15 years from target identification to clinical use. In contrast, drug repurposing can significantly accelerate translation. We developed a quantitative high-throughput screen to identify efficacious agents against SARS-CoV-2. From a library of 1,425 FDA-approved compounds and clinical candidates, we identified 17 dose-responsive compounds with in vitro antiviral efficacy in human liver Huh7 cells and confirmed antiviral efficacy in human colon carcinoma Caco-2, human prostate adenocarcinoma LNCaP, and in a physiologic relevant model of alveolar epithelial type 2 cells (iAEC2s). Additionally, we found that inhibitors of the Ras/Raf/MEK/ERK signaling pathway exacerbate SARS-CoV-2 infection in vitro. Notably, we discovered that lactoferrin, a glycoprotein classically found in secretory fluids, including mammalian milk, inhibits SARS-CoV-2 infection in the nanomolar range in all cell models with multiple modes of action, including blockage of virus attachment to cellular heparan sulfate and enhancement of interferon responses. Given its safety profile, lactoferrin is a readily translatable therapeutic option for the management of COVID-19.\n\nIMPORTANCESince its emergence in China in December 2019, SARS-CoV-2 has caused a global pandemic. Repurposing of FDA-approved drugs is a promising strategy for identifying rapidly deployable treatments for COVID-19. Herein, we developed a pipeline for quantitative high-throughput image-based screening of SARS-CoV-2 infection in human cells that led to the identification of several FDA-approved drugs and clinical candidates with in vitro antiviral activity.", + "rel_num_authors": 18, "rel_authors": [ { - "author_name": "Alice Douangamath", - "author_inst": "Diamond Light Source Ltd." - }, - { - "author_name": "Daren Fearon", - "author_inst": "Diamond Light Source Ltd." - }, - { - "author_name": "Paul Gehrtz", - "author_inst": "Weizmann Institute of Science" - }, - { - "author_name": "Tobias Krojer", - "author_inst": "University of Oxford" - }, - { - "author_name": "Petra Lukacik", - "author_inst": "Diamond Light Source Ltd." - }, - { - "author_name": "C. David Owen", - "author_inst": "Diamond Light Source Ltd." - }, - { - "author_name": "Efrat Resnick", - "author_inst": "Weizmann Institute of Science" - }, - { - "author_name": "Claire Strain-Damerell", - "author_inst": "Diamond Light Source Ltd" - }, - { - "author_name": "Anthony aimon", - "author_inst": "Diamond Light Source Ltd. & Research Complex at Harwell" - }, - { - "author_name": "P\u00e9ter \u00c1br\u00e1nyi-Balogh", - "author_inst": "Hungarian Academy of Sciences Research Centre for Natural Sciences" - }, - { - "author_name": "Jose Branda\u00f5-Neto", - "author_inst": "Diamond Light Source Ltd., Research Complex at Harwell" - }, - { - "author_name": "Anna Carberry", - "author_inst": "Diamond Light Source Ltd." - }, - { - "author_name": "Gemma Davison", - "author_inst": "Cancer Research UK Drug Discovery Unit, Newcastle University Centre for Cancer" - }, - { - "author_name": "Alexandre Dias", - "author_inst": "Diamond Light Source Ltd." - }, - { - "author_name": "Thomas D Downes", - "author_inst": "University of York" - }, - { - "author_name": "Louise Dunnett", - "author_inst": "Diamond Light Source Ltd." + "author_name": "Carmen Mirabelli", + "author_inst": "University of Michigan, Ann Arbor" }, { - "author_name": "Michael Fairhead", - "author_inst": "University of Oxford" + "author_name": "Jesse W. Wotring", + "author_inst": "University of Michigan, Ann Arbor" }, { - "author_name": "James D Firth", - "author_inst": "University of York" + "author_name": "Charles J. Zhang", + "author_inst": "University of Michigan, Ann Arbor" }, { - "author_name": "S. Paul Jones", - "author_inst": "University of York" + "author_name": "Sean M. McCarty", + "author_inst": "University of Michigan, Ann Arbor" }, { - "author_name": "Aaron Keely", - "author_inst": "Hungarian Academy of Sciences Research Centre for Natural Sciences" + "author_name": "Reid Fursmidt", + "author_inst": "University of Michigan, Ann Arbor" }, { - "author_name": "Gy\u00f6rgy M Keser\u00fc", - "author_inst": "Hungarian Academy of Sciences Research Centre for Natural Sciences" + "author_name": "Tristan Frum", + "author_inst": "University of Michigan, Ann Arbor" }, { - "author_name": "Hanna F Klein", - "author_inst": "University of York" + "author_name": "Namrata S. Kadambi", + "author_inst": "University of Michigan, Ann Arbor" }, { - "author_name": "Matthew P Martin", - "author_inst": "Cancer Research UK Drug Discovery Unit, Newcastle University Centre for Cancer" + "author_name": "Anya T. Amin", + "author_inst": "University of Michigan, Ann Arbor" }, { - "author_name": "Martin E.M. Noble", - "author_inst": "Cancer Research UK Drug Discovery Unit, Newcastle University Centre for Cancer" + "author_name": "Carla D. Pretto-Kernahan", + "author_inst": "University of Michigan, Ann Arbor" }, { - "author_name": "Ailsa Powell", - "author_inst": "Diamond Light Source Ltd." + "author_name": "Jason R. Spence", + "author_inst": "University of Michigan, Ann Arbor" }, { - "author_name": "Rambabu Reddi", - "author_inst": "Weizmann Institute of Science" + "author_name": "Jessie Huang", + "author_inst": "Boston University" }, { - "author_name": "Rachael Skyner", - "author_inst": "Diamond Light Source Ltd." + "author_name": "Konstantinos D. Alysandratos", + "author_inst": "Boston University" }, { - "author_name": "Matthew Snee", - "author_inst": "Diamond Light Source Ltd." + "author_name": "Darrell N. Kotton", + "author_inst": "Boston University" }, { - "author_name": "Michael J Waring", - "author_inst": "Cancer Research UK Drug Discovery Unit, Newcastle University Centre for Cancer" + "author_name": "Samuel K. Handelman", + "author_inst": "University of Michigan, Ann Arbor" }, { - "author_name": "Conor Wild", - "author_inst": "Diamond Light Source Ltd" + "author_name": "Christiane E Wobus", + "author_inst": "University of Michigan, Ann Arbor" }, { - "author_name": "Nir London", - "author_inst": "Weizmann Institute of Science" + "author_name": "Kevin J. Weatherwax", + "author_inst": "University of Michigan, Ann Arbor" }, { - "author_name": "Frank von Delft", - "author_inst": "Diamond Light Source Ltd., Research Complex at Harwell, University of Oxford, University of Johannesburg" + "author_name": "George A. Mashour", + "author_inst": "University of Michigan, Ann Arbor" }, { - "author_name": "Martin A Walsh", - "author_inst": "Diamond Light Source Ltd., Research Complex at Harwell" + "author_name": "Jonathan Z. Sexton", + "author_inst": "University of Michigan, Ann Arbor" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "new results", - "category": "biophysics" + "category": "cell biology" }, { "rel_doi": "10.1101/2020.05.26.115261", @@ -1414361,35 +1414362,67 @@ "category": "oncology" }, { - "rel_doi": "10.1101/2020.05.22.20106476", - "rel_title": "The impact of lockdown measures on COVID-19: a worldwide comparison", + "rel_doi": "10.1101/2020.05.18.20106245", + "rel_title": "SARS-CoV-2-reactive interferon-\u03b3-producing CD8+ T cells in patients hospitalized with Coronavirus viral disease-2019", "rel_date": "2020-05-26", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.22.20106476", - "rel_abs": "ObjectiveWe aimed to determine which aspects of the COVID-19 national response are independent predictors of COVID-19 mortality and case numbers.\n\nDesignComparative observational study between nations using publicly available data.\n\nSettingWorldwide Participants Covid-19 patients\n\nInterventionsStringency of 11 lockdown policies recorded by the Blavatnik School of Government database and earliness of each policy relative to first recorded national cases\n\nMain outcome measuresAssociation with log10 National deaths (LogD) and log10 National cases (LogC) on the 29th April 2020 corrected for predictive demographic variables\n\nResultsEarly introduction was associated with reduced mortality (n=137) and case numbers (n=150) for every policy aside from testing policy, contact tracing and workplace closure. Maximum policy stringency was only found to be associated with reduced mortality (p=0{middle dot}003) or case numbers (p=0{middle dot}010) for international travel restrictions. A multivariate model, generated using demographic parameters (r2=0{middle dot}72 for LogD and r2=0{middle dot}74 for LogC), was used to assess the timing of each policy. Early introduction of first measure (significance p=0{middle dot}048, regression coefficient {beta}=-0{middle dot}004, 95% confidence interval 0 to -0{middle dot}008), early international travel restrictions (p=0{middle dot}042, {beta}=-0{middle dot}005, -0{middle dot}001 to - 0{middle dot}009) and early public information (p=0{middle dot}021, {beta}=-0{middle dot}005, -0{middle dot}001 to -0{middle dot}009) were associated with reduced LogC. Early introduction of first measure (p=0{middle dot}003, {beta}=-0{middle dot}007, -0{middle dot}003 to -0{middle dot}011), early international travel restrictions (p=0{middle dot}003, {beta}=-0{middle dot}008, -0{middle dot}004 to-0{middle dot}012), early public information (p=0{middle dot}003, {beta}=-0{middle dot}007, 0{middle dot}003 to -0{middle dot}011), early generalised workplace closure (p=0{middle dot}031, {beta}=-0{middle dot}012, -0{middle dot}002 to -0{middle dot}022) and early generalised school closure (p=0{middle dot}050, {beta}=-0{middle dot}012, 0 to -0{middle dot}024) were associated with reduced LogC.\n\nConclusionsAt this stage in the pandemic, early institution of public information, international travel restrictions, and workplace closure are associated with reduced COVID-19 mortality and maintaining these policies may help control the pandemic.\n\nWhat is already known on this topicThe COVID-19 pandemic has spread rapidly throughout the world and presented vast healthcare, economic and political challenges. Many nations have recently passed the peak of their infection rate, and are weighing up relaxation of lockdown strategies. Though the effect of individual lockdown policies can be estimated by modelling, little is known about the impact of individual policies on population case numbers or mortality through comparison of differing strategies between nations. A PubMed search was carried out on the 14/5/20 using keywords including \"novel coronavirus-infected pneumonia\", \"2019-nCoV\", \"Sars-Cov-2\", \"Covid-19\", \"lockdown\",\" policy\", \"social distancing\", \"isolation\", \"quarantine\" and \"contact tracing\" returned 258 studies in total. Following scanning of the above results, we found 19 studies that have examined the effect of lockdown within a region, which have demonstrated a reduction in case numbers after the introduction of a lockdown. There are no previous studies that have compared the effectiveness of government lockdowns between nations to determine the effectiveness of specific policies.\n\nWhat this study addsThis study examines the corollary between government policy and COVID-19 case numbers and mortality, correct as of the 29th of April 2020, for every nation that there is available date within the Blavatnik School of Government database on COVID-19 policy. The study demonstrates that early generalised school closure, early generalised workplace closure, early restriction of international travel and early public information campaigns are independently associated with reduced national COVID-19 mortality. The maximum stringency of individual lockdown policies were not associated with reduced case numbers or mortality. Early reintroduction of these policies may be most effective in a relapse of the pandemic, though, school closure, workplace closure and restriction of international travel carry heavy politico-economic implications. There was no measurable effect of maximum stringency of lockdown policy on outcome at this point in time, indicating that early timing of lockdown introduction is of greater importance than its stringency, provided that the resultant viral reproductive rate is less than 1.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.18.20106245", + "rel_abs": "There is limited information on SARS-CoV-2 T-cell immune responses in patients with Covid-19. Both CD4+ and CD8+ T cells may be instrumental in the resolution of and protection from SARS-CoV-2 infection. Here, we tested 25 hospitalized patients with either microbiologically documented Covid-19 (n=19) or highly suspected of having the disease (n=6) for the presence of SARS-CoV-2-reactive-CD69+-expressing interferon--producing-(IFN-) CD8+ T cells by a flow-cytometry for intracelular cytokine staining assay. Two sets of overlapping peptides encompassing the SARS-CoV-2 Spike glycoprotein N-terminal 1-643 amino acid sequence and the entire sequence of SARS-CoV-2 M protein were used simultaneously as antigenic stimulus. Ten patients (40%) had detectable responses, displaying frequencies ranging from 0.15 to 2.7% (median of 0.57 cells/L; range, 0.43-9.98 cells/L). The detection rate of SARS-CoV-2-reactive IFN-{gamma} CD8+ T cells in patients admitted to intensive care was comparable (P=0.28) to that in patients hospitalized in other medical wards. No correlation was found between SARS-CoV-2-reactive IFN-{gamma} CD8+ T-cell counts and SARS-CoV-2 S-specific antibody levels. Likewise, no correlation was observed between either SARS-CoV-2-reactive IFN-{gamma} CD8+ T cells or S-specific IgG-antibody titers and blood cell count or levels of inflammatory biomarkers. In summary, in this descriptive, preliminary study we showed that SARS-CoV-2-reactive IFN-{gamma} CD8+ T cells can be detected in a non-negligible percentage of patients with moderate to severe forms of Covid-19. Further studies are warranted to determine whether quantitation of these T-cell subsets may provide prognostic information on the clinical course of Covid-19.", + "rel_num_authors": 12, "rel_authors": [ { - "author_name": "Dimitris I Papadopoulos", - "author_inst": "Chelsea and Westminister NHS Trust" + "author_name": "Estela Gimenez", + "author_inst": "Microbiology Service, Clinic University Hospital, INCLIVA Health Research Institute, Valencia, Spain." }, { - "author_name": "Ivo Donkov", - "author_inst": "Chelsea and Westminister NHS Trust" + "author_name": "Eliseo Albert", + "author_inst": "Microbiology Service, Clinic University Hospital, INCLIVA Health Research Institute, Valencia, Spain." }, { - "author_name": "Konstantinos Charitopoulos", - "author_inst": "Chelsea and Westminister NHS Trust" + "author_name": "Ignacio Torres", + "author_inst": "Microbiology Service, Clinic University Hospital, INCLIVA Health Research Institute, Valencia, Spain." }, { - "author_name": "Samuel Bishara", - "author_inst": "Chelsea and Westminister NHS Trust" + "author_name": "Maria Jose Remigia", + "author_inst": "Hematology Service, Clinic University Hospital, INCLIVA Health Research Institute, Valencia, Spain." + }, + { + "author_name": "Maria Jesus Alcaraz", + "author_inst": "Microbiology Service, Clinic University Hospital, INCLIVA Health Research Institute, Valencia, Spain." + }, + { + "author_name": "Maria Jose Galindo", + "author_inst": "Internal Medicine Department, Clinic University Hospital, INCLIVA Health Research Institute, Valencia, Spain." + }, + { + "author_name": "Maria Luisa Blasco", + "author_inst": "Medical Intensive Care Unit, Clinic University Hospital, INCLIVA Health Research Institute, Valencia, Spain." + }, + { + "author_name": "Carlos Solano", + "author_inst": "Hematology Service, Clinic University Hospital, INCLIVA Health Research Institute, Valencia, Spain.Department of Medicine, School of Medicine, University of Val" + }, + { + "author_name": "Maria Jose Forner", + "author_inst": "Internal Medicine Department, Clinic University Hospital, INCLIVA Health Research Institute, Valencia, Spain. Department of Medicine, School of Medicine, Univer" + }, + { + "author_name": "Josep Redon", + "author_inst": "Internal Medicine Department, Clinic University Hospital, INCLIVA Health Research Institute, Valencia, Spain. Department of Medicine, School of Medicine, Univer" + }, + { + "author_name": "Jaime Signes-Costa", + "author_inst": "Pneumology Service, Clinic University Hospital, INCLIVA Health Research Institute, Valencia, Spain" + }, + { + "author_name": "David Navarro", + "author_inst": "Microbiology Service, Clinic University Hospital, INCLIVA Health Research Institute, Valencia, Spain. Department of Microbiology, School of Medicine, University" } ], "version": "1", "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "health policy" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2020.05.22.20106294", @@ -1415899,101 +1415932,25 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.05.19.20106997", - "rel_title": "Hydroxychloroquine alone or in combination with azithromycin to prevent major clinical events in hospitalised patients with coronavirus infection (COVID-19): rationale and design of a randomised, controlled clinical trial", + "rel_doi": "10.1101/2020.05.19.20106906", + "rel_title": "Efficacy and Safety of Hydroxychloroquine and Chloroquine for COVID-19: A systematic review", "rel_date": "2020-05-26", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.19.20106997", - "rel_abs": "IntroductionHydroxychloroquine and its combination with azithromycin have been suggested to improve viral clearance in patients with COVID-19, but its effect on clinical outcomes remains uncertain.\n\nMethods and analysisWe describe the rationale and design of an open-label pragmatic multicentre randomised (concealed) clinical trial of 7 days of hydroxychloroquine (400 mg BID) plus azithromycin (500 mg once daily), hydroxychloroquine 400 mg BID, or standard of care for moderately severe hospitalised patients with suspected or confirmed COVID-19 (in-patients with up to 4L/minute oxygen supply through nasal catheter). Patients are randomised in around 50 recruiting sites and we plan to enrol 630 patients with COVID-19. The primary endpoint is a 7-level ordinal scale measured at 15-days: 1)not hospitalised, without limitations on activities; 2)not hospitalised, with limitations on activities; 3)hospitalised, not using supplementary oxygen; 4)hospitalised, using supplementary oxygen; 5)hospitalised, using high-flow nasal cannula or non-invasive ventilation; 6)hospitalised, on mechanical ventilation; 7)death. Secondary endpoints are the ordinal scale at 7 days, need for mechanical ventilation and rescue therapies during 15 days, need of high-flow nasal cannula or non-invasive ventilation during 15 days, length of hospital stay, in-hospital mortality, thromboembolic events, occurrence of acute kidney injury, and number of days free of respiratory support at 15 days. Secondary safety outcomes include prolongation of QT interval on electrocardiogram, ventricular arrhythmias, and liver toxicity. The main analysis will consider all patients with confirmed COVID-19 in the groups they were randomly assigned.\n\nEthics and disseminationThis study has been approved by Brazils National Ethic Committee (CONEP) and National Health Surveillance Agency (ANVISA). An independent data monitoring committee will perform interim analyses and evaluate adverse events throughout the trial. Results will be submitted for publication after enrolment and follow-up are complete, as well as presented and reported to local health agencies.\n\nClinicalTrials.gov identifierNCT04322123\n\nO_LSTStrengths and limitations of this studyC_LSTO_LIPragmatic randomised controlled trial of 7 days of hydroxychloroquine plus azithromycin, hydroxychloroquine or standard of care for moderately severe in-patients with suspected or confirmed COVID-19\nC_LIO_LIMulticentre: around 50 recruiting sites in Brazil with planned enrolment of 630 patients (1:1:1)\nC_LIO_LIThe primary endpoint is a 7-level ordinal scale ([1] not hospitalised, without limitations on activities; [2] not hospitalised, with limitations on activities; [3] hospitalised, not using supplementary oxygen; [4] hospitalised, using supplementary oxygen; [5] hospitalised, using high-flow nasal cannula or non-invasive ventilation; [6] hospitalised, on mechanical ventilation; [7] death) measured at 15 days.\nC_LIO_LIOpen label design (no placebo)\nC_LI", - "rel_num_authors": 21, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.19.20106906", + "rel_abs": "BACKGROUNDHydroxychloroquine and chloroquine are widely used to treat hospitalized COVID-19 patients primarily based on antiviral activity in in vitro studies. Our objective was to systematically evaluate their efficacy and safety in hospitalized patients with COVID-19.\n\nMETHODSWe systematically reviewed PubMed, ClinicalTrials.gov, and Medrxviv for studies of hydroxychloroquine and chloroquine in COVID-19 hospitalized patients on April 26, 2020. We evaluated the quality of trials and observational studies using the Jadad criteria and Newcastle Ottawa Scale, respectively.\n\nRESULTSAfter a review of 175 citations, we included 5 clinical trials (total of 345 patients), 9 observational studies (n = 2529), and 6 additional studies (n = 775) reporting on the QT interval. Three studies reported treatment benefits including two studies reporting benefit on virologic outcomes, which was statistically significant in one study, and another reported significant improvement on cough symptoms. Three studies reported that treatment was potentially harmful, including an significantly increased risk of mortality in two studies and increased need for respiratory support in another. Eight studies were unable to detect improvements on virologic outcomes (n = 3) or pneumonia or transfer to ICU/death (n = 5). The proportion of participants with critical QTc intervals of [≥] 500 ms or an increase of [≥] 60 ms from baseline ranged from 8.3% to 36% (n = 8). One clinical trial and six observational studies were of good quality. The remaining studies were of poor quality.\n\nCONCLUSIONSOur systematic review of reported clinical studies did not identify substantial evidence to support the efficacy of hydroxychloroquine or chloroquine in hospitalized COVID-19 patients and raises questions about potential harm from QT prolongation and increased mortality.\n\nO_LSTKey PointsC_LSTO_LIWe conducted a systematic review of the efficacy and safety of hydroxychloroquine and chloroquine among patients hospitalized with COVID-19 and identified 14 studies reporting on clinical or virologic outcomes and 6 additional studies reporting on the QT interval.\nC_LIO_LIWe conducted a systematic review of the efficacy and safety of hydroxychloroquine and chloroquine among patients hospitalized with COVID-19 and identified 14 studies reporting on clinical or virologic outcomes and 6 additional studies reporting on the QT interval.\nC_LIO_LIHydroxychloroquine or chloroquine improved virologic outcomes in 2 clinical studies and cough in another study.\nC_LIO_LIWe conducted a systematic review of the efficacy and safety of hydroxychloroquine and chloroquine among patients hospitalized with COVID-19 and identified 14 studies reporting on clinical or virologic outcomes and 6 additional studies reporting on the QT interval.\nC_LIO_LIHydroxychloroquine or chloroquine improved virologic outcomes in 2 clinical studies and cough in another study.\nC_LI", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Alexandre B Cavalcanti", - "author_inst": "HCor Research Institute, Sao Paulo, Brazil" - }, - { - "author_name": "Fernando G Zampieri", - "author_inst": "HCor" - }, - { - "author_name": "Luciani CP Azevedo", - "author_inst": "Hospital Sirio Libanes Research and Education Institute, Sao Paulo, Brazil" - }, - { - "author_name": "Regis G Rosa", - "author_inst": "Hospital Moinhos de Vento, Porto Alegre,Brazil" - }, - { - "author_name": "Alvaro Avezum", - "author_inst": "Hospital Alemao Oswaldo Cruz, Sao Paulo, Brazil" - }, - { - "author_name": "Viviane C Veiga", - "author_inst": "BP - A Beneficencia Portuguesa de Sao Paulo, Sao Paulo, Brazil" - }, - { - "author_name": "Renato D Lopes", - "author_inst": "Duke University Medical Center - Duke Clinical Research Institute - Durham, North Carolina, USA." - }, - { - "author_name": "Leticia Kawano-Dourado", - "author_inst": "HCor Research Institute, Sao Paulo, Brazil" - }, - { - "author_name": "Lucas P Damiani", - "author_inst": "HCor Research Institute, Sao Paulo, Brazil" - }, - { - "author_name": "Adriano J Pereira", - "author_inst": "Academic Research Organization, Hospital Israelita Albert Einstein, Sao Paulo, Brazil" - }, - { - "author_name": "Ary Serpa Neto", - "author_inst": "Intensive Care Unit, Hospital Israelita Albert Einstein, Sao Paulo, Brazil" + "author_name": "Sonal Singh", + "author_inst": "Department of Family Medicine and Community Health, Meyers Primary Care Institute and Quantitative Health Sciences, University of Massachusetts Medical School, " }, { - "author_name": "Remo Furtado", - "author_inst": "Intensive Care Unit, Hospital Israelita Albert Einstein, Sao Paulo, Brazil" - }, - { - "author_name": "Bruno Tomazini", - "author_inst": "Hospital Sirio Libanes Research and Education Institute, Sao Paulo, Brazil" - }, - { - "author_name": "Fernando A Bozza", - "author_inst": "Brazilian Research in Intensive Care Network (BRICNet), Sao Paulo, Brazil." - }, - { - "author_name": "Israel S Maia", - "author_inst": "Brazilian Research in Intensive Care Network (BRICNet), Sao Paulo, Brazil." - }, - { - "author_name": "Maicon Falavigna", - "author_inst": "Hospital Moinhos de Vento, Porto Alegre, Brazil" - }, - { - "author_name": "Thiago C Lisboa", - "author_inst": "HCor Research Institute, Sao Paulo, Brazil" - }, - { - "author_name": "Henrique Fonseca", - "author_inst": "Academic Research Organization, Hospital Israelita Albert Einstein, Sao Paulo, Brazil" - }, - { - "author_name": "Flavia R Machado", - "author_inst": "Brazilian Research in Intensive Care Network (BRICNet), Sao Paulo, Brazil." - }, - { - "author_name": "Otavio Berwanger", - "author_inst": "Academic Research Organization, Hospital Israelita Albert Einstein, Sao Paulo, Brazil" - }, - { - "author_name": "COALITION COVID-19 Brazil I Investigators", - "author_inst": "" + "author_name": "Thomas J Moore", + "author_inst": "Center for Drug Safety and Effectiveness, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA and Department of Epidemiology, The George Washi" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1417297,37 +1417254,77 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.05.24.20111724", - "rel_title": "COVID-19: Impact of Obesity and Diabetes in Disease Severity", + "rel_doi": "10.1101/2020.05.19.20107391", + "rel_title": "Syndromic Surveillance for COVID-19 in Canada", "rel_date": "2020-05-26", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.24.20111724", - "rel_abs": "BackgroundThe Coronavirus disease 2019 (COVID-19) pandemic is straining the healthcare system, particularly for patients with severe outcomes who require admittance to the intensive care unit (ICU). This study aimed to investigate the potential associations of obesity and diabetes with COVID-19 severe outcomes, assessed as ICU admittance.\n\nSubjectsDemographic and patient characteristics from a retrospective cohort of 1158 patients hospitalized with COVID-19 in a single center in Kuwait, along with their medical history, were analyzed. Univariate and multivariate analyses were performed to explore the associations between different variables and ICU admittance.\n\nResultsFrom the 1158 hospitalized patients, 271 (23.4%) had diabetes, 236 (20.4%) had hypertension and 104 (9%) required admittance into the ICU. From patients with available measurements, 157 (21.6%) had body mass index (BMI)[≥]25 kg/m2. Univariate analysis showed that overweight (BMI=25.0-29.9 kg/m2), obesity class I (BMI=30-34.9 kg/m2) and morbid obesity (BMI[≥]40 kg/m2) associated with ICU admittance (odds ratio (OR) [95% confidence intervals (CI)]: 2.45 [1.26-4.74] p-value=0.008; OR [95% CI]: 3.51 [1.60-7.69] p-value=0.002; and OR [95% CI]: 5.18 [1.50-17.85] p-value=0.009], respectively). Patients with diabetes were more likely to be admitted to ICU (OR [95% CI]: 9.38 [5.49-16.02]). Two models for multivariate regression analysis were used, assessing either BMI or diabetes on ICU outcomes. In the BMI model, class I obesity and morbid obesity were associated with ICU admittance (adjusted OR (AOR) [95% CI]: 2.7 [1.17-6.20] p-value=0.019 and AOR [95% CI]: 3.95 [1.00-15.20] p-value=0.046, respectively). In the diabetes model, diabetes was associated with higher ICU admittance (AOR [95% CI]: 5.49 [3.13-9.65] p-value<0.001) whereas hypertension had a protective effect on ICU admittance (AOR [95% CI]: 0.51 (0.28-0.91).\n\nConclusionsIn our cohort, overweight, obesity and diabetes in patients with COVID-19 were associated with ICU admittance, putting these patients at higher risk of poor outcomes.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.19.20107391", + "rel_abs": "BackgroundSyndromic surveillance through web or phone-based polling has been used to track the course of infectious diseases worldwide. Our study objective was to describe the characteristics, symptoms, and self-reported testing rates of respondents in three different COVID-19 symptom surveys in Canada.\n\nMethodsData sources consisted of two distinct Canada-wide web-based surveys, and phone polling in Ontario. All three sources contained self-reported information on COVID-19 symptoms and testing. In addition to describing respondent characteristics, we examined symptom frequency and the testing rate among the symptomatic, as well as rates of symptoms and testing across respondent groups.\n\nResultsWe found that 1.6% of respondents experienced a symptom on the day of their survey, 15% of Ontario households had a symptom in the previous week, and 44% of Canada-wide respondents had a symptom in the previous month over March-April 2020. Across the three surveys, SARS-CoV-2-testing was reported in 2-9% of symptomatic responses. Women, younger and middle-aged adults (versus older adults) and Indigenous/First nations/Inuit/Metis were more likely to report at least one symptom, and visible minorities were more likely to report the combination of fever with cough or shortness of breath.\n\nInterpretationThe low rate of testing among those reporting symptoms suggests significant opportunity to expand testing among community-dwelling residents of Canada. Syndromic surveillance data can supplement public health reports and provide much-needed context to gauge the adequacy of current SARS-CoV-2 testing rates.", + "rel_num_authors": 15, "rel_authors": [ { - "author_name": "Salman K. Al-Sabah", - "author_inst": "COVID-19 Research Group, Jaber Al-Ahmad Al-Sabah Hospital, Kuwait" + "author_name": "Lauren Lapointe-Shaw", + "author_inst": "University of Toronto" }, { - "author_name": "Mohannad Al-Haddad", - "author_inst": "COVID-19 Research Group, Jaber Al-Ahmad Al-Sabah Hospital, Kuwait" + "author_name": "Benjamin Rader", + "author_inst": "Boston University" }, { - "author_name": "Sarah Al Youha", - "author_inst": "Jaber Al-Ahmad Al-Sabah Hospital" + "author_name": "Christina M. Astley", + "author_inst": "Boston Children's Hospital" }, { - "author_name": "Mohammad H. Jamal", - "author_inst": "COVID-19 Research Group, Jaber Al-Ahmad Al-Sabah Hospital, Kuwait" + "author_name": "Jared B. Hawkins", + "author_inst": "Boston Children's Hospital" }, { - "author_name": "Sulaiman AlMazeedi", - "author_inst": "COVID-19 Research Group, Jaber Al-Ahmad Al-Sabah Hospital, Kuwait" + "author_name": "Deepit Bhatia", + "author_inst": "Unaffiliated" + }, + { + "author_name": "William J. Schatten", + "author_inst": "Forum Research" + }, + { + "author_name": "Todd C. Lee", + "author_inst": "McGill University Health Centre" + }, + { + "author_name": "Jessica J. Liu", + "author_inst": "University of Toronto" + }, + { + "author_name": "Noah M. Ivers", + "author_inst": "Women's College Hospital" + }, + { + "author_name": "Nathan M. Stall", + "author_inst": "University of Toronto" + }, + { + "author_name": "Effie Gournis", + "author_inst": "Toronto Public Health" + }, + { + "author_name": "Ashleigh R. Tuite", + "author_inst": "University of Toronto" + }, + { + "author_name": "David N. Fisman", + "author_inst": "University of Toronto" + }, + { + "author_name": "Isaac I. Bogoch", + "author_inst": "University of Toronto" + }, + { + "author_name": "John S. Brownstein", + "author_inst": "Boston Children's Hospital" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1418987,33 +1418984,41 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.05.24.20111799", - "rel_title": "Effect of various treatment modalities on the novel coronavirus (nCOV-2019) infection in humans: a systematic review & meta-analysis", + "rel_doi": "10.1101/2020.05.25.20110239", + "rel_title": "In Vitro Efficacy of Povidone-Iodine Nasal And Oral Antiseptic Preparations Against Severe Acute Respiratory Syndrome-Coronavirus 2 (SARS-CoV-2)", "rel_date": "2020-05-26", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.24.20111799", - "rel_abs": "Background and aimSeveral therapeutic agents have been investigated for the treatment of novel Coronavirus-2019 (nCOV-2019). We aimed to conduct a systematic review and meta-analysis to assess the effect of various treatment modalities in nCOV-2019 patients.\n\nMethodsAn extensive literature search was conducted before 22 May 2020 in PubMed, Google Scholar, Cochrane library databases. Quality assessment was performed using Newcastle Ottawa Scale. A fixed-effect model was applied if I2 <50%, else the results were combined using random-effect model. Risk Ratio (RR) or Standardized Mean Difference (SMD) along-with 95% Confidence Interval (95%CI) were used to pool the results. Between study heterogeneity was explored using influence and sensitivity analyses & publication bias was assessed using funnel plots. Entire statistical analysis was conducted in R version 3.6.2.\n\nResultsEighty-one studies involving 44 in vitro and 37 clinical studies including 8662 nCOV-2019 patients were included in the review. Lopinavir-Ritonavir compared to controls was significantly associated with shorter mean time to clinical improvement (SMD -0.32; 95%CI -0.57 to -0.06) and Remdesivir compared to placebo was significantly associated with better overall clinical improvement (RR 1.17; 95%CI 1.07 to 1.29). Hydroxychloroquine was associated with less overall clinical improvement (RR 0.88; 95%CI 0.79 to 0.98) and longer time to clinical improvement (SMD 0.64; 95%CI 0.33 to 0.94), It additionally had higher all-cause mortality (RR 1.6; 95%CI 1.26 to 2.03) and more total adverse events (RR 1.84; 95% CI 1.58 to 2.13).\n\nConclusionOur meta-analysis suggests that except in vitro studies, no treatment till now has shown clear-cut benefit on nCOV-2019 patients. Lopinavir-Ritonavir and Remdesivir have shown some benefits in terms less time to clinical improvement and better overall clinical improvement. Hydroxychloroquine use has a risk of higher mortality and adverse events. Results from upcoming large clinical trials must be awaited to draw any profound conclusions.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.25.20110239", + "rel_abs": "IntroductionSevere Acute Respiratory Syndrome-Coronavirus 2 (SARS-CoV-2) is the pathogen responsible for the global pandemic of Coronavirus disease-2019 (COVID-19). From the first reported cases in December 2019, the virus has spread to over 4 million people worldwide. Human-to-human transmission occurs mainly through the aerosolization of respiratory droplets. Transmission also occurs through contact with contaminated surfaces and other fomites. Improved antisepsis of human and non-human surfaces has been identified as a key feature of transmission reduction. There are no previous studies of povidone-iodine (PVP-I) against SARS-CoV-2. This study evaluated nasal and oral antiseptic formulations of povidone-iodine (PVP-I) for virucidal activity against SARS-CoV-2. This is the first report on the efficacy of PVP-I against the virus that causes COVID-19.\n\nMethodsPVP-I nasal antiseptic formulations and PVP-I oral rinse antiseptic formulations from 1-5% concentrations as well as controls were studied for virucidal efficacy against the SARS-CoV-2 virus. Test compounds were evaluated for ability to inactivate SARS-CoV-2 as measured in a virucidal assay. SARS-CoV-2 was exposed directly to the test compound for 60 seconds, compounds were then neutralized and surviving virus was quantified.\n\nResultsAll concentrations of nasal antiseptics and oral rinse antiseptics evaluated completely inactivated the SARS-CoV-2 virus.\n\nConclusionsNasal and oral PVP-I antiseptic solutions are effective at inactivating the SARS-CoV-2 virus at a variety of concentrations after 60s exposure times. The formulations tested may help to reduce the transmission of SARS-CoV-2 if used for nasal decontamination, oral decontamination or surface decontamination in known or suspected cases of COVID-19.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Shubham Misra", - "author_inst": "All India Institute of Medical Sciences, New Delhi, India" + "author_name": "Jesse Pelletier", + "author_inst": "Ocean Ophthalmology Group (Miami, FL)" }, { - "author_name": "Manabesh Nath", - "author_inst": "All India Institute of Medical Sciences, New Delhi, India" + "author_name": "Belachew Tessema", + "author_inst": "ProHealth Physicians Ear, Nose and Throat (Farmington, CT), University of Connecticut, Department of Otolaryngology (Farmington, CT)" }, { - "author_name": "Vijay Hadda", - "author_inst": "All India Institute of Medical Sciences, New Delhi, India" + "author_name": "Jonna Westover", + "author_inst": "The Institute for Antiviral Research at Utah State University (Logan, UT)" }, { - "author_name": "Deepti Vibha", - "author_inst": "All India Institute of Medical Sciences, New Delhi, India" + "author_name": "Samantha Frank", + "author_inst": "University of Connecticut, Department of Otolaryngology (Farmington, CT)" + }, + { + "author_name": "Seth Brown", + "author_inst": "University of Connecticut, Department of Otolaryngology (Farmington, CT) , The Institute for Antiviral Research at Utah State University (Logan, UT)" + }, + { + "author_name": "Joseph Capriotti", + "author_inst": "Veloce BioPharma (Fort Lauderdale, FL)" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1420249,39 +1420254,59 @@ "category": "intensive care and critical care medicine" }, { - "rel_doi": "10.1101/2020.05.24.20112318", - "rel_title": "Utility of Pan-Family Assays for Rapid Viral Screening: Reducing Delays in Public Health Responses During Pandemics", + "rel_doi": "10.1101/2020.05.24.20111245", + "rel_title": "IgG serology in health care and administrative staff populations from 7 hospital representative of different exposures to SARS-CoV-2 in Lombardy, Italy", "rel_date": "2020-05-26", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.24.20112318", - "rel_abs": "BackgroundThe SARS-CoV-2 pandemic has highlighted deficiencies in the testing capacity of many developed countries during the early stages of emerging pandemics. Here we describe the potential for pan-family viral assays to improve early accessibility of large-scale nucleic acid testing.\n\nMethodsCoronaviruses and SARS-CoV-2 were used as a case-study for investigating the utility of pan-family viral assays during the early stages of a novel pandemic. Specificity of a pan-coronavirus (Pan-CoV) assay for viral detection was assessed using the frequency of common human coronavirus (HCoV) species in key populations. A reported Pan-CoV assay was assessed to determine sensitivity to SARS-CoV-2 and 59 other coronavirus species. The resilience of the primer target regions of this assay to mutation was assessed in 8893 high quality SARS-CoV-2 genomes to predict ongoing utility during pandemic progression.\n\nFindingsDue to infection with common HCoV species, a Pan-CoV assay would return a false positive for as few as 1% of asymptomatic adults, but up to 30% of immunocompromised patients displaying symptoms of respiratory disease. Two of the four reported pan-coronavirus assays would have identified SARS-CoV-2 and we demonstrate that with small adjustments to the primers, these assays can accommodate novel variation observed in animal coronaviruses. The assay target region of one well established Pan-CoV assay is highly resistant to mutation compared to regions targeted by other widely applied SARS-CoV-2 RT-PCR assays.\n\nInterpretationPan-family assays have the potential to greatly assist management of emerging public health emergencies through prioritization of high-resolution testing or isolation measures, despite limitations in test specificity due to cross-reactivity with common pathogens. Targeting highly conserved genomic regions make pan-family assays robust and resilient to mutation of a given virus. This approach may be applicable to other viral families and has utility as part of a strategic stockpile of tests maintained to better contain spread of novel diseases prior to the widespread availability of specific assays.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.24.20111245", + "rel_abs": "Lombardy is one of the regions in Italy most affected by COVID-19. We assessed the diffusion of the virus via testing plasma anti-SARS-CoV-2 IgG antibodies in 3985 employees of 7 different hospitals, located across the Lombardy region in areas with different exposure to the epidemic. Subjects filled an anamnestic questionnaire to self-report on COVID-19 symptoms, co-morbidities, smoking, regular or smart-working, and the exposure to COVID-19-infected individuals. We show that the number of individuals exposed to the virus depended on the geographical area where the hospital was located and ranged between 3 to 43% which correlated with the incidence of COVID-19 in Lombardy. There was a higher prevalence of females than males positive for IgG, however the level of antibodies was similar, suggesting a comparable magnitude of the response. We observed 10% of IgG positive asymptomatic individuals and another 20% with one or two symptoms. 81% of individuals presenting both anosmia/ageusia and fever resulted SARS-CoV-2 infected. IgG positivity correlated with family contacts.\n\nIn conclusion, the frequency of IgG positivity and SARS-CoV-2 infection is dependent on the geographical exposure to the virus and to extra-hospital exposure.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Michael Erlichster", - "author_inst": "MX3 Diagnostics" + "author_name": "Maria Teresa Sandri", + "author_inst": "Humanitas Clinical and Research Center" + }, + { + "author_name": "Elena Azzolini", + "author_inst": "Humanitas Clinical and Research Center" }, { - "author_name": "Gursharan Chana", - "author_inst": "MX3 Diagnostics" + "author_name": "Valter Torri", + "author_inst": "Istituto di Ricerche Farmacologiche Mario Negri" }, { - "author_name": "Daniela Zantomio", - "author_inst": "Austin Health" + "author_name": "Sara Carloni", + "author_inst": "Humanitas University" + }, + { + "author_name": "Chiara Pozzi", + "author_inst": "Humanitas Clinical and Research Center, IRCCS, Rozzano, Milan, Italy" + }, + { + "author_name": "Michela Salvatici", + "author_inst": "Humanitas Clinical and Research Center, IRCCS, Rozzano, Milan, Italy" + }, + { + "author_name": "Michele Tedeschi", + "author_inst": "Humanitas Clinical and Research Center" + }, + { + "author_name": "Massimo Castoldi", + "author_inst": "Humanitas Gavazzeni and Castelli" }, { - "author_name": "Benjamin Goudey", - "author_inst": "IBM Research Australia" + "author_name": "Alberto Mantovani", + "author_inst": "Humanitas Clinical and Research Center" }, { - "author_name": "Efstratios Skafidas", - "author_inst": "MX3 Diagnostics" + "author_name": "Maria Rescigno", + "author_inst": "Humanitas University" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "allergy and immunology" }, { "rel_doi": "10.1101/2020.05.26.20113191", @@ -1421583,33 +1421608,25 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.05.20.20095406", - "rel_title": "Modeling the dynamics of COVID-19 using Q-SEIR model with age-stratified infection probability", + "rel_doi": "10.1101/2020.05.22.20098350", + "rel_title": "A phenomenological algorithm for short-range predictions of the Covid-19 pandemics 2020", "rel_date": "2020-05-26", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.20.20095406", - "rel_abs": "We explore the advantage of age-stratifying the population as an improvement on the quarantine-modified SEIR model. We hypothesize that this would project lower cases of infection for the Philippines because of our countrys low median age. We introduce the variable U that is multiplied to the incubation rate{sigma} when exposed individuals become infected. U is the dot product of the proxy infection probabilities stratified per age group (F) and the population stratified per age group (P) divided by the total population, similar to calculating mathematical expectation. Proxies were taken from two data sets: Hubei, China with a calculated value of UCHN = 0.4447 and Quezon City, Philippines with UQC = 0.5074. When the majority age group, represented by the median age, is far from the age group with the highest number of infections the number of infected individuals decreases and produces a delayed peaking effect. This new method gives a much lower estimate on peak number of infected cases by 65.2% compared with age-stratification alone; and by 75.2% compared with Q-SEIR alone.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.22.20098350", + "rel_abs": "We present an algorithm for dynamical fitting of a logistic curve to the Covid-19 epidemics data, with fit-parameters linearly evolving to the future. We show that the algorithm would have given reasonable short- and medium-range predictions for the mid-range evolution of the epidemics for several countries. We introduce the double-logistic curve, which provides a very good description of the epidemics data at any given time of the epidemics. We analyse the predictability properties of some naive models.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Joshua Frankie Rayo", - "author_inst": "University of the Philippines Diliman" - }, - { - "author_name": "Romulo de Castro", - "author_inst": "Center for Informatics, University of San Agustin, Philippines" - }, - { - "author_name": "Jesus Emmanuel Sevilleja", - "author_inst": "National Center for Mental Health, Philippines" + "author_name": "Piotr T. Chrusciel", + "author_inst": "Faculty of Physics, University of Vienna" }, { - "author_name": "Vena Pearl Bongolan", - "author_inst": "University of the Philippines Diliman" + "author_name": "Sebastian J. Szybka", + "author_inst": "Obserwatorium Astronomiczne UJ, Krakow, Poland" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1422921,17 +1422938,45 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.05.20.20107797", - "rel_title": "Spread of COVID-19: Investigation of universal features in real data", + "rel_doi": "10.1101/2020.05.20.20108449", + "rel_title": "Risk factors affecting COVID-19 case fatality rate: A quantitative analysis of top 50 affected countries", "rel_date": "2020-05-25", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.20.20107797", - "rel_abs": "We present results on the existence of various common patterns in the growth of the total number of patients affected by COVID-19, a disease acquired through infection by a novel coronavirus, in different countries. For this purpose we propose a scaling model that can have general applicability in the understanding of real data of epidemics. This is analogous to the finite-size scaling, a technique used in the literature of phase transition to identify universality classes. In the disease model, the size of a system is proportional to the volume of the population, within a geographical region, that have been infected at the death of the epidemic or are eventually going to be infected when an epidemic ends. Outcome of our study, for COVID-19, via application of this model, suggests that in most of the countries, after the onset of spread, the growths are described by rapid exponential function, for significantly long periods. In addition to accurately identifying this superuniversal feature, we point out that the model is helpful in grouping countries into universality classes, based on the late time behavior, characterized by physical distancing practices, in a natural way. This feature of the model can provide direct comparative understanding of the effectiveness of lockdown-like social measures adopted in different places.", - "rel_num_authors": 1, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.20.20108449", + "rel_abs": "BackgroundLatest clinical data on treatment on coronavirus disease 2019 (COVID-19) indicated that older patients and those with underlying history of smoking, hypertension or diabetes mellitus might have poorer prognosis of recovery from COVID-19. We aimed to examine the relationship of various prevailing population-based risk factors in comparison with mortality rate and case fatality rate (CFR) of COVID-19.\n\nMethodsDemography and epidemiology data which have been identified as verified or postulated risk factors for mortality of adult inpatients with COVID-19 were used. The number of confirmed cases and the number of deaths until April 16, 2020 for all affected countries were extracted from Johns Hopkins University COVID-19 websites. Datasets for indicators that are fitting with the factors of COVID-19 mortality were extracted from the World Bank database. Out of about 185 affected countries, only top 50 countries were selected to be analyzed in this study. The following seven variables were included in the analysis, based on data availability and completeness: 1) proportion of people aged 65 above, 2) proportion of male in the population, 3) diabetes prevalence, 4) smoking prevalence, 5) current health expenditure, 6) number of hospital beds and 7) number of nurses and midwives. Quantitative analysis was carried out to determine the correlation between CFR and the aforementioned risk factors.\n\nResultsUnited States shows about 0.20% of confirmed cases in its country and it has about 4.85% of CFR. Luxembourg shows the highest percentage of confirmed cases of 0.55% but a low 2.05% of CFR, showing that a high percentage of confirmed cases does not necessarily lead to high CFR. There is a significant correlation between CFR, people aged 65 and above (p = 0.35) and diabetes prevalence (p = 0.01). However, in our study, there is no significant correlation between CFR of COVID-19, male gender (p = 0.26) and smoking prevalence (p = 0.60).\n\nConclusionOlder people above 65 years old and diabetic patients are significant risk factors for COVID-19. Nevertheless, gender differences and smoking prevalence failed to prove a significant relationship with COVID-19 mortality rate and CFR.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Subir K. Das", - "author_inst": "Jawaharlal Nehru Centre for Advanced Scientific Research" + "author_name": "Hui Poh Goh", + "author_inst": "PAPRSB Institute of Health Sciences, Universiti Brunei Darussalam" + }, + { + "author_name": "Wafiah Ilyani Mahari", + "author_inst": "PAPRSB Institute of Health Sciences, Universiti Brunei Darussalam" + }, + { + "author_name": "Norhadyrah Izazie Ahad", + "author_inst": "PAPRSB Institute of Health Sciences, Universiti Brunei Darussalam" + }, + { + "author_name": "Liling Chaw", + "author_inst": "PAPRSB Institute of Health Sciences, Universiti Brunei Darussalam" + }, + { + "author_name": "Nurolaini Kifli", + "author_inst": "PAPRSB Institute of Health Sciences, Universiti Brunei Darussalam" + }, + { + "author_name": "Bey Hing Goh", + "author_inst": "Monash University Malaysia" + }, + { + "author_name": "Siang Fei Yeoh", + "author_inst": "Department of Pharmacy, National University Health System, Singapore" + }, + { + "author_name": "Long Chiau Ming", + "author_inst": "PAPRSB Institute of Health Sciences, Universiti Brunei Darussalam" } ], "version": "1", @@ -1424543,29 +1424588,53 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.05.24.20112045", - "rel_title": "Reaching collective immunity for COVID-19: an estimate with a heterogeneous model based on the data for Italy", + "rel_doi": "10.1101/2020.05.24.20112094", + "rel_title": "Sociodemographic predictors of outcomes in COVID-19: examining the impact of ethnic disparities in Northern Nevada", "rel_date": "2020-05-25", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.24.20112045", - "rel_abs": "BackgroundAt the current stage of COVID-19 pandemic, forecasts become particularly important regarding the possibility that the total incidence could reach the level where the disease stops spreading because a considerable portion of the population has become immune and collective immunity could be reached. Such forecasts are valuable because the currently undertaken restrictive measures prevent mass morbidity but do not result in the development of a robust collective immunity. Thus, in the absence of efficient vaccines and medical treatments, lifting restrictive measures carries the risk that a second wave of the epidemic could occur.\n\nMethodsWe developed a heterogeneous model of COVID-19 dynamics. The model accounted for the differences in the infection risk across subpopulations, particularly the age-depended susceptibility to the disease. Based on this model, an equation for the minimal number of infections was calculated as a condition for the epidemic to start declining. The basic reproductive number of 2.5 was used for the disease spread without restrictions. The model was applied to COVID-19 data from Italy.\n\nFindingsWe found that the heterogeneous model of epidemic dynamics yielded a lower proportion, compared to a homogeneous model, for the minimal incidence needed for the epidemic to stop. When applied to the data for Italy, the model yielded a more optimistic assessment of the minimum total incidence needed to reach collective immunity: 43% versus 60% estimated with a homogeneous model.\n\nInterpretationBecause of the high heterogeneity of COVID-19 infection risk across the different age groups, with a higher susceptibility for the elderly, homogeneous models overestimate the level of collective immunity needed for the disease to stop spreading. This inaccuracy can be corrected by the homogeneous model introduced here. To improve the estimate even further additional factors should be considered that contribute to heterogeneity, including social and professional activity, gender and individual resistance to the pathogen.\n\nFundingThis work was supported by a grant from the Ministry of Education and Science of the Russian Federation, a unique project identifier RFMEFI60819X0278.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.24.20112094", + "rel_abs": "BackgroundOn March 11, 2020, the World Health Organization declared coronavirus disease-19 (COVID-19) a pandemic. Nearly five million individuals have since been diagnosed with this increasingly common and potentially lethal viral infection. Emerging evidence suggests a disproportionate burden of illness and death among minority communities. We aimed to evaluate the effect of ethnicity on outcomes among patients diagnosed with COVID-19 in Northern Nevada.\n\nDesignSingle-center, retrospective observational study\n\nMaterials and methodsThe electronic health records of 172 patients diagnosed with COVID-19 were obtained from a 946-bed tertiary referral center serving Northern Nevada. Demographic and clinical characteristics were compared by ethnic group (Hispanic versus non-Hispanic). Logistic regression was used to determine predictors of mortality.\n\nResultsAmong 172 patients who were diagnosed with COVID-19 between March 12th and May 8th, 2020, 87 (50.6%) identified as Hispanic and 81 (47.1%) as non-Hispanic. The mean age was 46.0 among Hispanics and 55.8 among non-Hispanics. Comorbidities linked to increased COVID-19-related mortality - hypertension, obesity, and chronic obstructive pulmonary disease - were more common among the non-Hispanic population. Hispanic individuals were significantly more likely to be uninsured and to live in low-income communities as compared to their non-Hispanic counterparts (27.6% versus 8.2% and 52.9% versus 30.6%, respectively). Hispanic patients were also less likely than non-Hispanics to have a primary care provider (42.5% versus 61.2%). However, mortality was significantly higher among the non-Hispanic population (15.3% versus 5.8%).\n\nConclusionThe COVID-19 pandemic has disproportionately affected Hispanic individuals in Northern Nevada, who account for only 25.7% of the population but over half of the confirmed cases. Hispanic individuals were younger and had fewer comorbidities than their non-Hispanic counterparts; consequently, despite considerable socioeconomic disadvantage, mortality was lower among the Hispanic population. The underlying causes of ethnic disparities in COVID-19 incidence remain to be established, but further investigation may lead to more effective community- and systems-based interventions.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Andrey Gerasimov", - "author_inst": "I.M. Sechenov First Moscow State Medical University" + "author_name": "Daniel Antwi-Amoabeng", + "author_inst": "University of Nevada, Reno School of Medicine" }, { - "author_name": "Georgy Lebedev", - "author_inst": "I.M. Sechenov First Moscow State Medical University; Federal Research Institute for Health Organization and Informatics, Moscow, Russia" + "author_name": "Bryce David Beutler", + "author_inst": "University of Nevada, Reno School of Medicine" }, { - "author_name": "Mikhail Lebedev", - "author_inst": "I.M. Sechenov First Moscow State Medical University; National Research University Higher School of Economics, Moscow, Russia" + "author_name": "Munadel Awad", + "author_inst": "University of Nevada, Reno School of Medicine" }, { - "author_name": "Irina Semenycheva", - "author_inst": "I.M. Sechenov First Moscow State Medical University" + "author_name": "Zahara Kanji", + "author_inst": "University of Nevada, Reno School of Medicine" + }, + { + "author_name": "Sumaiya Mahboob", + "author_inst": "University of Nevada, Reno School of Medicine" + }, + { + "author_name": "Jasmine Ghuman", + "author_inst": "University of Nevada, Reno School of Medicine" + }, + { + "author_name": "Sri Harsha Boppana", + "author_inst": "University of Nevada, Reno School of Medicine" + }, + { + "author_name": "Mohammad Salman Sheikh", + "author_inst": "University of Nevada, Reno School of Medicine" + }, + { + "author_name": "Mark B. Ulanja", + "author_inst": "University of Nevada, Reno School of Medicine" + }, + { + "author_name": "Nageshwara Gullapalli", + "author_inst": "University of Nevada, Reno School of Medicine" } ], "version": "1", @@ -1426069,31 +1426138,47 @@ "category": "bioinformatics" }, { - "rel_doi": "10.1101/2020.05.23.104919", - "rel_title": "In silico Proteome analysis of Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)", + "rel_doi": "10.1101/2020.05.22.20110809", + "rel_title": "Succumbing to the COVID-19 Pandemic: Healthcare Workers not Satisfied and Intend to Leave Their Jobs", "rel_date": "2020-05-24", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.23.104919", - "rel_abs": "Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (2019-nCoV), is a positive-sense, single-stranded RNA coronavirus. The virus is the causative agent of coronavirus disease 2019 (COVID-19) and is contagious through human-to-human transmission. The present study reports sequence analysis, complete coordinate tertiary structure prediction and in silico sequence-based and structure-based functional characterization of full SARS-CoV-2 proteome based on the NCBI reference sequence NC_045512 (29903 bp ss-RNA) which is identical to GenBank entry MN908947 and MT415321. The proteome includes 12 major proteins namely orf1ab polyprotein (includes 15 proteins), surface glycoprotein, ORF3a protein, envelope protein, membrane glycoprotein, ORF6 protein, ORF7a protein, orf7b, ORF8, Nucleocapsid phosphoprotein and ORF10 protein. Each protein of orf1ab polyprotein group has been studied separately. A total of 25 polypeptides have been analyzed out of which 15 proteins are not yet having experimental structures and only 10 are having experimental structures with known PDB IDs. Out of 15 newly predicted structures six (6) were predicted using comparative modeling and nine (09) proteins having no significant similarity with so far available PDB structures were modeled using ab-initio modeling. Structure verification using recent tools QMEANDisCo 4.0.0 and ProQ3 for global and local (per-residue) quality estimates indicate that the all-atom model of tertiary structure of high quality and may be useful for structure-based drug designing targets. The study has identified nine major targets (spike protein, envelop protein, membrane protein, nucleocapsid protein, 2-O-ribose methyltransferase, endoRNAse, 3-to-5 exonuclease, RNA-dependent RNA polymerase and helicase) for which drug design targets could be considered. There are other 16 nonstructural proteins (NSPs), which may also be percieved from the drug design angle. The protein structures have been deposited to ModelArchive. Tunnel analysis revealed the presence of large number of tunnels in NSP3, ORF 6 protein and membrane glycoprotein indicating a large number of transport pathways for small ligands influencing their reactivity.", - "rel_num_authors": 3, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.22.20110809", + "rel_abs": "BackgroundHealthcare workers are under such a tremendous amount of pressure during the COVID-19 pandemic that many have become concerned about their jobs and even intend to leave them. It is paramount for healthcare workers to feel satisfied with their jobs and lives during a pandemic.\n\nMethodsBetween 10 to 30 April, 2020, 240 healthcare workers in Bolivia completed a cross-sectional online survey, which assessed their job satisfaction, life satisfaction, and turnover intention in the ongoing COVID-19 pandemic.\n\nResultsThe results revealed that their number of office days predicted job satisfaction, life satisfaction, and turnover intention, but the relationships varied by their age. For example, healthcare workers office days negatively predicted job satisfaction for the young (e.g. at 25 years old: b=-0.21; 95% CI: -0.36 to -0.60) but positively predicted job satisfaction for the old (e.g. at 65 years old: b=0.25; 95% CI: 0.06 to 0.44).\n\nConclusionsThese findings provide evidence to enable healthcare organizations to identify staff concerned about job satisfaction, life satisfaction, and turnover intention to enable early actions so that these staff can remain motivated to fight the prolonged COVID-19 pandemic.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Chittaranjan Baruah", - "author_inst": "Post Graduate Department of Zoology, Darrang College, Tezpur-784001, Assam, India" + "author_name": "Stephen X. Zhang", + "author_inst": "University of Adelaide" }, { - "author_name": "Papari Devi", - "author_inst": "TCRP Foundation Guwahati-781005, Assam, India" + "author_name": "Jiyao Chen", + "author_inst": "Oregon State University" + }, + { + "author_name": "Asghar Afshar Jahanshahi", + "author_inst": "Pontifical Catholic University of Peru" + }, + { + "author_name": "Aldo Alvarez-Risco", + "author_inst": "University of Lima" + }, + { + "author_name": "Huiyang Dai", + "author_inst": "Tsinghua University" + }, + { + "author_name": "Jizhen Li", + "author_inst": "Tsinghua University" }, { - "author_name": "Dhirendra K Sharma", - "author_inst": "School of Biological Science, University of Science & Technology, Meghalaya-793101, India" + "author_name": "Ross Patty-Tito", + "author_inst": "Caja Petrolera de Salud" } ], "version": "1", - "license": "cc_by_nc_nd", - "type": "new results", - "category": "bioinformatics" + "license": "cc_by_nc", + "type": "PUBLISHAHEADOFPRINT", + "category": "psychiatry and clinical psychology" }, { "rel_doi": "10.1101/2020.05.22.20110700", @@ -1427211,23 +1427296,51 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.05.21.20108621", - "rel_title": "A pandemic at the Tunisian scale. Mathematical modelling of reported and unreported COVID-19 infected cases", + "rel_doi": "10.1101/2020.05.21.108035", + "rel_title": "Methods of inactivation of SARS-CoV-2 for downstream biological assays", "rel_date": "2020-05-23", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.21.20108621", - "rel_abs": "Starting from the city of Wuhan in China in late December 2019, the pandemic quickly spread to the rest of the world along the main intercontinental air routes. At the time of writing this article, there are officially about five million infections and more than 300 000 deaths. Statistics vary widely from country to country, revealing significant differences in anticipation and management of the crisis. We propose to examine the COVID-19 epidemic in Tunisia through mathematical models, which aim to determine the actual number of infected cases and to predict the course of the epidemic. As of May 11, 2020, there are officially 1032 COVID-19 infected cases in Tunisia. 45 people have died. Using a mathematical model based on the number of reported infected cases, the number of deaths, and the effect of the 18-day delay between infection and death, this study estimates the actual number of COVID-19 cases in Tunisia as 2555 cases. This paper analyses the evolution of the epidemic in Tunisia using population dynamics with an SEIR model combining susceptible cases S(t), asymptomatic infected cases A(t), reported infected cases V(t), and unreported infected cases U(t). This work measures the basic reproduction number [Formula], which is the average number of people infected by a COVID-19 infected person. The model predicts an [Formula]. Strict containment measures have led to a significant reduction in the reproduction rate. Contact tracing and respect for isolation have an impact: at the current time, we compute that Tunisia has an [Formula] (95% CI 0.14-0.70). These values depend on physical separation and can vary over time depending on the management of suspicious cases. Their objective estimation and the study of their evolution are however necessary to understand the pandemic and to reduce their unintended damage (due to an absence of symptoms, or the confusion of certain symptoms with less contagious diseases, or unavailable or unreliable tests).", - "rel_num_authors": 1, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.21.108035", + "rel_abs": "The scientific community has responded to the COVID-19 pandemic by rapidly undertaking research to find effective strategies to reduce the burden of this disease. Encouragingly, researchers from a diverse array of fields are collectively working towards this goal. Research with infectious SARS-CoV-2 is undertaken in high containment laboratories, however, it is often desirable to work with samples at lower containment levels. To facilitate the transfer of infectious samples from high containment laboratories, we have tested methods commonly used to inactivate virus and prepare the sample for additional experiments. Incubation at 80{degrees}C, and a range of detergents and UV energies were successful at inactivating a high titre of SARS-CoV-2. These protocols can provide a framework for in house inactivation of SARS-CoV-2 in other laboratories, ensuring the safe use of samples in lower containment levels.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Ines Abdeljaoued-Tej", - "author_inst": "BIMS Laboratory, LR16IPT09, Institut Pasteur de Tunis, University of Tunis El Manar, Tunisia" + "author_name": "Edward I Patterson", + "author_inst": "Liverpool School of Tropical Medicine" + }, + { + "author_name": "Tessa Prince", + "author_inst": "University of Liverpool" + }, + { + "author_name": "Enyia R Anderson", + "author_inst": "Liverpool School of Tropical Medicine" + }, + { + "author_name": "Aitor Casas-Sanchez", + "author_inst": "Liverpool School of Tropical Medicine" + }, + { + "author_name": "Shirley L Smith", + "author_inst": "University of Liverpool" + }, + { + "author_name": "Cintia Cansado-Utrilla", + "author_inst": "Liverpool School of Tropical Medicine" + }, + { + "author_name": "Lance Turtle", + "author_inst": "University of Liverpool" + }, + { + "author_name": "Grant L Hughes", + "author_inst": "Liverpool School of Tropical Medicine" } ], "version": "1", - "license": "cc_by_nc_nd", - "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "license": "cc_no", + "type": "new results", + "category": "microbiology" }, { "rel_doi": "10.1101/2020.05.21.108308", @@ -1429017,25 +1429130,25 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.05.21.20109678", - "rel_title": "Flattening the curve and the effect of atypical events on mitigation measures in Mexico: a modeling perspective", + "rel_doi": "10.1101/2020.05.21.20109389", + "rel_title": "COVID-19 Confirmed Case Incidence Age Shift to Young Persons Age 0-19 and 20-39 Years Over Time: Washington State March - April 2020", "rel_date": "2020-05-23", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.21.20109678", - "rel_abs": "On 23 and 30 March 2020 the Mexican Federal government implemented social distancing measures to mitigate the COVID-19 epidemic. We use a mathematical model to explore atypical transmission events within the confinement period, triggered by the timing and strength of short time perturbations of social distancing. We show that social distancing measures were successful in achieving a significant reduction of the effective contact rate in the early weeks of the intervention. However, \"flattening the curve\" had an undesirable effect, since the epidemic peak was delayed too far, almost to the government preset day for lifting restrictions (01 June 2020). If the peak indeed occurs in late May or early June, then the events of childrens day and mothers day may either generate a later peak (worst case scenario), a long plateau with relatively constant but high incidence (middle case scenario) or the same peak date as in the original baseline epidemic curve, but with a post-peak interval of slower decay.", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.21.20109389", + "rel_abs": "BackgroundAs the coronavirus (COVID-19) epidemic passes the peak infection rate in some states and counties a phased re-opening with changes of stay-at-home restrictions and social distancing recommendations may lead to an increase of nonessential work, social activities and gathering, especially among younger persons.\n\nMethodsA longitudinal cohort analysis of Washington State Department of Health COVID-19 confirmed case age distribution March 1-April 19 2020 for proportional change over time using chi square tests for significance (N = 13,934).\n\nResultsFrom March 1st to April 19, 2020 age distribution shifted with a 10% decline in cases age 60 years and older and a 20% increase in age 0-19/20-39 years (chi-square = 223.10, p <.001). Number of cases over the eight-week analysis period were 0-19 years n = 515, 20-39 years n = 4078, 40-59 years n =4788, 60-79 years n = 3221, 80+ years n = 1332. New cases increased steadily among 0-19 and 20-39-year olds. After the peak (March 22, 2020), there was no decline among age 0-19 and a lesser decline among age 20-39 than older groups. As incidence declined in older age groups, the combined percentage of cases age 0-19 and 20-39 increased from 20% to 40% of total cases.\n\nConclusionsIncreased COVID-19 infection among children and young adults is not without serious morbidity and mortality risk to them and others they may come in contact with, indicating a targeted approach for awareness and safety measures is advisable to reduce incidence among the supposedly less vulnerable but more mobile young population age 0-19 and 20-39 years.", "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Mario Santana-Cibrian", - "author_inst": "CONACYT - Instituto de Matematicas UNAM-Juriquilla" + "author_name": "Judith Malmgren", + "author_inst": "University of Washington" }, { - "author_name": "Manuel Adrian Acuna-Zegarra", - "author_inst": "Departamento de Matematicas, Universidad de Sonora" + "author_name": "Boya Guo", + "author_inst": "University of Washington" }, { - "author_name": "Jorge X. Velasco-Hernandez", - "author_inst": "Universidad Nacional Autonoma de Mexico" + "author_name": "Henry G Kaplan", + "author_inst": "Swedish Cancer Institute" } ], "version": "1", @@ -1430543,47 +1430656,91 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2020.05.21.109546", - "rel_title": "A high-throughput neutralizing antibody assay for COVID-19 diagnosis and vaccine evaluation", + "rel_doi": "10.1101/2020.05.20.107243", + "rel_title": "A modular framework for the development of targeted Covid-19 blood transcript profiling panels", "rel_date": "2020-05-22", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.21.109546", - "rel_abs": "Virus neutralization remains the gold standard for determining antibody efficacy. Therefore, a high-throughput assay to measure SARS-CoV-2 neutralizing antibodies is urgently needed for COVID-19 serodiagnosis, convalescent plasma therapy, and vaccine development. Here we report on a fluorescence-based SARS-CoV-2 neutralization assay that detects SARS-CoV-2 neutralizing antibodies in COVID-19 patient specimens and yields comparable results to plaque reduction neutralizing assay, the gold standard of serological testing. Our approach offers a rapid platform that can be scaled to screen people for antibody protection from COVID-19, a key parameter necessary to safely reopen local communities.", - "rel_num_authors": 7, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.20.107243", + "rel_abs": "Covid-19 morbidity and mortality are associated with a dysregulated immune response. Tools are needed to enhance existing immune profiling capabilities in affected patients. Here we aimed to develop an approach to support the design of focused blood transcriptome panels for profiling the immune response to SARS-CoV-2 infection. We designed a pool of candidates based on a pre-existing and well-characterized repertoire of blood transcriptional modules. Available Covid-19 blood transcriptome data was also used to guide this process. Further selection steps relied on expert curation. Additionally, we developed several custom web applications to support the evaluation of candidates. As a proof of principle, we designed three targeted blood transcript panels, each with a different translational connotation: therapeutic development relevance, SARS biology relevance and immunological relevance. Altogether the work presented here may contribute to the future expansion of immune profiling capabilities via targeted profiling of blood transcript abundance in Covid-19 patients.", + "rel_num_authors": 18, "rel_authors": [ { - "author_name": "Antonio E. Muruato", - "author_inst": "University of Texas Medical Branch, Galveston TX, USA" + "author_name": "Darawan Rinchai", + "author_inst": "Sidra Medicine, Doha, Qatar" }, { - "author_name": "Camila R. Fontes-Garfias", - "author_inst": "University of Texas Medical Branch, Galveston TX, USA" + "author_name": "Basirudeen Kabeer", + "author_inst": "Sidra Medicine, Doha, Qatar" }, { - "author_name": "Ping Ren", - "author_inst": "University of Texas Medical Branch, Galveston TX, USA" + "author_name": "Mohammed Toufiq", + "author_inst": "Sidra Medicine, Doha, Qatar" }, { - "author_name": "Mariano A Garcia-Blanco", - "author_inst": "University of Texas Medical Branch" + "author_name": "Zohreh Calderone", + "author_inst": "Sidra Medicine, Doha, Qatar" }, { - "author_name": "Vineet D Menachery", - "author_inst": "University of Texas Medical Branch" + "author_name": "Sara Deola", + "author_inst": "Sidra Medicine, Doha, Qatar" }, { - "author_name": "Xuping D Xie", - "author_inst": "University of Texas Medical Branch" + "author_name": "Tobias Brummaier", + "author_inst": "Shoklo Malaria Research Unit, Mahidol-Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Mae Sot, Thailand" }, { - "author_name": "Pei-Yong Shi", - "author_inst": "University of Texas Medical Branch" + "author_name": "Mathieu Garand", + "author_inst": "Sidra Medicine, Doha, Qatar" + }, + { + "author_name": "Ricardo Branco", + "author_inst": "Sidra Medicine, Doha, Qatar" + }, + { + "author_name": "Nicole Baldwin", + "author_inst": "Baylor Institute for Immunology Research and Baylor Research Institute, Dallas, Texas, USA" + }, + { + "author_name": "Mohamed Alfaki", + "author_inst": "Sidra Medicine, Doha, Qatar" + }, + { + "author_name": "Matthew Altman", + "author_inst": "Division of Allergy and Infectious Diseases, University of Washington and Systems Immunology, Benaroya Research Institute, Seattle, Washington, USA" + }, + { + "author_name": "Alberto Ballestrero", + "author_inst": "Department of Internal Medicine, Universita degli Studi di Genova and IRCCS Ospedale Policlinico San Martino, Genoa IT" + }, + { + "author_name": "Matteo Bassetti", + "author_inst": "Division of Infectious and Tropical Diseases, IRCCS Ospedale Policlinico San Martino, Genoa, Italy, and Department of Health Sciences, University of Genoa, Ital" + }, + { + "author_name": "Gabriele Zoppoli", + "author_inst": "Department of Internal Medicine, Universita degli Studi di Genova and IRCCS Ospedale Policlinico San Martino, Genoa IT" + }, + { + "author_name": "Andrea De Maria", + "author_inst": "Division of Infectious and Tropical Diseases, IRCCS Ospedale Policlinico San Martino, Genoa, Italy, and Department of Health Sciences, University of Genoa, Ital" + }, + { + "author_name": "Benjamin Tang", + "author_inst": "Nepean Clinical School, University of Sydney, Sydney, NSW, Australia" + }, + { + "author_name": "Davide Bedognetti", + "author_inst": "Sidra Medicine, Doha, Qatar" + }, + { + "author_name": "Damien Chaussabel", + "author_inst": "Sidra Medicine, Doha, Qatar" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "new results", - "category": "microbiology" + "category": "immunology" }, { "rel_doi": "10.1101/2020.05.21.108043", @@ -1432053,23 +1432210,47 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.05.17.20104554", - "rel_title": "The true case fatality of COVID19: An analytical solution", + "rel_doi": "10.1101/2020.05.19.20103788", + "rel_title": "Prevalence of Mental Health Problems During Virus Epidemics in the General Public, Health Care Workers and Survivors: A Rapid Review of the Evidence", "rel_date": "2020-05-22", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.17.20104554", - "rel_abs": "The exact risk of dying from COVID-19 has remained elusive and a topic of debate. In this study, the observed case fatality rates of 46 different countries are hypothesized to be dependent on their testing rates. An analytical test to this hypothesis suggests that the case fatality rate of COVID-19 could be consistent to a certain degree across all countries and states. The current global fatality rate is estimated to be around 1% and expected to converge between 1-3% when the pandemic ends. This model can be helpful to estimate the true infection rate for individual countries.", - "rel_num_authors": 1, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.19.20103788", + "rel_abs": "BackgroundThe swift spread of SARS-CoV-2 provides a challenge worldwide. As a consequence of restrictive public health measures like isolation, quarantine, and community containment, the provision of mental health services is a major challenge. Evidence from past virus epidemics and the current SARS-CoV-2 outbreak indicate high prevalence rates of mental health problems (MHP) as short- and long-term consequences. However, a broader picture of MHP among different populations is still lacking.\n\nMethodsWe conducted a rapid review on MHP prevalence rates published since 2000, during and after epidemics, including the general public, health care workers, and survivors. Any quantitative articles reporting on MHP rates were included. Out of 2855 articles screened, a total of 74 were included in this review.\n\nResultsMost original studies on MHP were conducted in China in the context of SARS-CoV-1, and reported on anxiety, depression, post-traumatic stress symptoms/disorder, general psychiatric morbidity, and psychological symptoms. The MHP rates across studies, populations, and epidemics vary substantially. While some studies show high and persistent rates of MHP in populations directly affected by isolation, quarantine, threat of infection, infection, or life-threatening symptoms (e.g. health care workers), other studies report minor effects. Furthermore, even less affected populations (e.g. distant to epidemic epicenter, no contact history with suspected or confirmed cases) can show high rates of MHP.\n\nDiscussionMHP vary largely across countries and risk-groups in reviewed studies. The results call attention to potentially high MHP during epidemics. Individuals affected directly by an epidemic might be at a higher risk of short or even long-term mental health impairments. This study delivers insights stemming from a wide range of psychiatric instruments and questionnaires. The results call for the use of validated and standardized instruments, reference norms, and pre-post measurements to better understand the magnitude of the MHP during and after the epidemics. Nevertheless, emerging MHP should be considered during epidemics including the provision of access to mental health care to mitigate potential mental impairments.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Syamantak Khan", - "author_inst": "Stanford University" + "author_name": "Simeon J Zuercher Jr.", + "author_inst": "Center for Psychiatric Rehabilitation, University Hospital for Mental Health (UPD), Bern, Switzerland and University Hospital of Psychiatry and Psychotherapy, U" + }, + { + "author_name": "Philipp Kerksieck Jr.", + "author_inst": "Epidemiology, Biostatistics and Prevention Institute, Public and Organizational Health, University of Zurich, Zurich, Switzerland" + }, + { + "author_name": "Christine Adamus Jr.", + "author_inst": "Center for Psychiatric Rehabilitation, University Hospital for Mental Health (UPD), Bern, Switzerland and University Hospital of Psychiatry and Psychotherapy, U" + }, + { + "author_name": "Christian Burr Jr.", + "author_inst": "Center for Psychiatric Rehabilitation, University Hospital for Mental Health (UPD), Bern, Switzerland and University Hospital of Psychiatry and Psychotherapy, U" + }, + { + "author_name": "Anja I Lehmann Jr.", + "author_inst": "Epidemiology, Biostatistics and Prevention Institute, Public and Organizational Health, University of Zurich, Zurich, Switzerland" + }, + { + "author_name": "Flavia K Huber Jr.", + "author_inst": "University Hospital of Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland" + }, + { + "author_name": "Dirk Richter Sr.", + "author_inst": "Center for Psychiatric Rehabilitation, University Hospital for Mental Health (UPD), Bern, Switzerland and University Hospital of Psychiatry and Psychotherapy, U" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "psychiatry and clinical psychology" }, { "rel_doi": "10.1101/2020.05.16.20104422", @@ -1433655,29 +1433836,41 @@ "category": "health policy" }, { - "rel_doi": "10.1101/2020.05.17.20104885", - "rel_title": "Extension of a SIR model for modelling the propagation of Covid-19 in several countries.", + "rel_doi": "10.1101/2020.05.17.20104976", + "rel_title": "A structured model for COVID-19 spread: modelling age and healthcare inequities", "rel_date": "2020-05-21", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.17.20104885", - "rel_abs": "BackgroundSeveral epidemiologic models have been published to forecast the spread of the COVID-19 pandemic yet there are still uncertainties regarding their accuracy. We report the main features of the development of a novel freely accessible model intended to urgently help researchers and decision makers to predict the evolution of the pandemic in their country.\n\nMethods and findingsWe built a SIR-type compartmental model with additional compartments and features. We made the hypothesis that the number of contagious individuals in the population was negligible as compared to the population size. We introduced a compartment D corresponding to the deceased patients and a compartment L representing the group of individuals who will die but who will not infect anybody (due to social or medical isolation). Our model integrated a time-dependent transmission rate, whose variations can be thought to be related to the public measures taken by each country and a cosine function to incorporate a periodic weekly component linked to the way in which numbers of cases and deaths are counted and reported, which can change from day to day.\n\nThe model was able to accurately capture the different changes in the dynamics of the pandemic for nine different countries whatever the type of pandemic spread or containment measures. The model provided very accurate forecasts in the relatively short term (10 days).\n\nConclusionsIn early evaluation of the performance of our model, we found a high level of accuracy between prediction and observed data, regardless of the country. The model should be used by the community to help public health decisions as we will refine it over time and further investigate its performance.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.17.20104976", + "rel_abs": "We use a stochastic branching process model, structured by age and level of healthcare access, to look at the heterogeneous spread of COVID-19 within a population. We examine the effect of control scenarios targeted at particular groups, such as school closures or social distancing by older people. Although we currently lack detailed empirical data about contact and infection rates between age groups and groups with different levels of healthcare access within New Zealand, these scenarios illustrate how such evidence could be used to inform specific interventions. We find that an increase in the transmission rates amongst children from reopening schools is unlikely to significantly increase the number of cases, unless this is accompanied by a change in adult behaviour. We also find that there is a risk of undetected outbreaks occurring in communities that have low access to healthcare and that are socially isolated from more privileged communities. The greater the degree of inequity and extent of social segregation, the longer it will take before any outbreaks are detected. Well-established evidence for health inequities, particularly in accessing primary healthcare and testing, indicates that Maori and Pacific peoples are at higher risk of undetected outbreaks in Aotearoa New Zealand. This highlights the importance of ensuring that community needs for access to healthcare, including early proactive testing, rapid contact tracing, and the ability to isolate, are being met equitably. Finally, these scenarios illustrate how information concerning contact and infection rates across different demographic groups may be useful in informing specific policy interventions.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Marc Lavielle", - "author_inst": "Inria" + "author_name": "Alex James", + "author_inst": "University of Canterbury" }, { - "author_name": "Matthieu Faron", - "author_inst": "Gustave Roussy" + "author_name": "Michael J Plank", + "author_inst": "University of Canterbury" }, { - "author_name": "jeremie lefevre", - "author_inst": "sorbonne universite" + "author_name": "Rachelle N Binny", + "author_inst": "Manaaki Whenua" }, { - "author_name": "Jean-David Zeitoun", - "author_inst": "Centre Epidemiologie Clinique, Hotel Dieu" + "author_name": "Kate Hannah", + "author_inst": "University of Auckland" + }, + { + "author_name": "Shaun C Hendy", + "author_inst": "University of Auckland" + }, + { + "author_name": "Audrey Lustig", + "author_inst": "Manaaki Whenua" + }, + { + "author_name": "Nicholas Steyn", + "author_inst": "University of Auckland" } ], "version": "1", @@ -1435277,33 +1435470,25 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.05.19.20107268", - "rel_title": "A simple criterion to design optimal nonpharmaceutical interventions for epidemic outbreaks", + "rel_doi": "10.1101/2020.05.19.20107433", + "rel_title": "Analyzing the Effect of Temperature on the Outspread of COVID-19 around the Globe", "rel_date": "2020-05-21", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.19.20107268", - "rel_abs": "To mitigate the COVID-19 pandemic, much emphasis exists on implementing non-pharmaceutical interventions to keep the reproduction number below one. But using that objective ignores that some of these interventions, like bans of public events or lockdowns, must be transitory and as short as possible because of their significative economic and societal costs. Here we derive a simple and mathematically rigorous criterion for designing optimal transitory non-pharmaceutical interventions. We find that reducing the reproduction number below one is sufficient but not necessary. Instead, our criterion prescribes the required reduction in the reproduction number according to the maximum health services capacity. To explore the implications of our theoretical results, we study the non-pharmaceutical interventions implemented in 16 cities during the COVID-19 pandemic. In particular, we estimate the minimal reduction of the contact rate in each city that is necessary to control the epidemic optimally. We also compare the optimal start of the intervention with the start of the actual interventions applied in each city. Our results contribute to establishing a rigorous methodology to guide the design of non-pharmaceutical intervention policies.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.19.20107433", + "rel_abs": "The emergence of the pandemic around the world owing to COVID-19 is putting the world into a big threat. Many factors may be involved in the transmission of this deadly disease but not much-supporting data are available. Till now no proper evidences has been reported supporting that temperature changes can affect COVID-19 transmission. This work aims to correlate the effect of temperature with that of Total Cases, Recovery, Death, and Critical cases all around the globe. All the data were collected in April and the maximum and minimum temperature and the average temperature were collected from January to April (i.e the months during which the disease was spread). Regression was conducted to find a non-linear relationship between Temperate and the cases. It was evident that indeed temperature does have a significant effect on the total cases and recovery rate around the globe. It was also evident from the study that the countries with lower temperatures are the hotspots for COVID-19. The Study depicted a non-linear dose-response between temperature and the transmission, indicating the existence of the best temperature for its transmission. This study can indeed put some light on how temperature can be a significant factor in COVID-19 transmission.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Marco Tulio Angulo", - "author_inst": "CONACyT - Institute of Mathematics, UNAM." - }, - { - "author_name": "Fernando Casta\u00f1os", - "author_inst": "Department of Automatic Control, CINVESTAV-IPN" - }, - { - "author_name": "Rodrigo Moreno-Morton", - "author_inst": "Universidad Nacional Autonoma de Mexico, Faculty of Sciences" + "author_name": "Pratik Das", + "author_inst": "Jadavpur University" }, { - "author_name": "Jorge X. Velasco-Hernandez", - "author_inst": "Universidad Nacional Autonoma de Mexico" + "author_name": "Suvendu Manna", + "author_inst": "University of Petroleum and Energy Studies" }, { - "author_name": "Jaime A. Moreno", - "author_inst": "Institute of Engineering, UNAM." + "author_name": "Piyali Basak", + "author_inst": "Jadavpur University" } ], "version": "1", @@ -1436379,107 +1436564,35 @@ "category": "molecular biology" }, { - "rel_doi": "10.1101/2020.05.20.106609", - "rel_title": "Tiger team: a panel of human neutralizing mAbs targeting SARS-CoV-2 spike at multiple epitopes", + "rel_doi": "10.1101/2020.05.19.104513", + "rel_title": "Prediction of the virus incubation period for COVID-19 and future outbreaks", "rel_date": "2020-05-20", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.20.106609", - "rel_abs": "The novel highly transmissible human coronavirus SARS-CoV-2 is the causative agent of the COVID-19 pandemic. Thus far, there is no approved therapeutic drug, specifically targeting this emerging virus. Here we report the isolation and characterization of a panel of human neutralizing monoclonal antibodies targeting the SARS-CoV-2 receptor binding domain (RBD). These antibodies were selected from a phage display library constructed using peripheral circulatory lymphocytes collected from patients at the acute phase of the disease. These neutralizing antibodies are shown to recognize distinct epitopes on the viral spike RBD, therefore they represent a promising basis for the design of efficient combined post-exposure therapy for SARS-CoV-2 infection.", - "rel_num_authors": 22, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.19.104513", + "rel_abs": "A crucial factor in mitigating respiratory viral outbreaks is early determination of the duration of the incubation period and, accordingly, the required quarantine time for potentially exposed individuals. Here, we explore different genomic features of RNA viruses that correlate with the incubation times and provide a predictive model that accurately estimates the upper limit incubation time for diverse viruses including SARS-CoV-2, and thus, could help control future outbreaks.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Tal Noy-Porat", - "author_inst": "Israel Institute for Biological Research" - }, - { - "author_name": "Efi Makdasi", - "author_inst": "Israel Institute for Biological Research" - }, - { - "author_name": "Ron Alcalay", - "author_inst": "Israel Institute for Biological Research" - }, - { - "author_name": "Adva Mechaly", - "author_inst": "Israel Institute for Biological Research" - }, - { - "author_name": "Yinon Levy", - "author_inst": "Israel Institute for Biological Research" - }, - { - "author_name": "Adi Bercovich-Kinori", - "author_inst": "Israel Institute for Biological Research" - }, - { - "author_name": "Ayelet Zauberman", - "author_inst": "Israel Institute for Biological Research" - }, - { - "author_name": "Hadas Tamir", - "author_inst": "Israel Institute for Biological Research" - }, - { - "author_name": "Yfat Yahalom-Ronen", - "author_inst": "Israel Institute for Biological Research" - }, - { - "author_name": "Eyal Epstein", - "author_inst": "Israel Institute for Biological Research" - }, - { - "author_name": "Hagit Achdout", - "author_inst": "Israel Institute for Biological Research" - }, - { - "author_name": "Sharon Melamed", - "author_inst": "Israel Institute for Biological Research" - }, - { - "author_name": "Theodor Chitlaru", - "author_inst": "Israel Institute for Biological Research" - }, - { - "author_name": "Shay Weiss", - "author_inst": "Israel Institute for Biological Research" - }, - { - "author_name": "Eldar Peretz", - "author_inst": "Israel Institute for Biological Research" - }, - { - "author_name": "Osnat Rosen", - "author_inst": "Israel Institute for Biological Research" - }, - { - "author_name": "Nir Paran", - "author_inst": "Israel Institute for Biological Research" - }, - { - "author_name": "Shmuel Yitzhaki", - "author_inst": "Israel Institute for Biological Research" - }, - { - "author_name": "Shmuel C. Shapira", - "author_inst": "Israel Institute for Biological Research" + "author_name": "Ayal B. Gussow", + "author_inst": "NIH" }, { - "author_name": "Tomer Israely", - "author_inst": "Israel Institute for Biological Research" + "author_name": "Noam Auslander", + "author_inst": "NIH" }, { - "author_name": "Ohad Mazor", - "author_inst": "Israel Institute for Biological Research" + "author_name": "Yuri I. Wolf", + "author_inst": "NIH" }, { - "author_name": "Ronit Rosenfeld", - "author_inst": "Israel Institute for Biological Research" + "author_name": "Eugene V. Koonin", + "author_inst": "NIH" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nc", "type": "new results", - "category": "immunology" + "category": "microbiology" }, { "rel_doi": "10.1101/2020.05.20.107052", @@ -1438037,33 +1438150,29 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.05.18.20097220", - "rel_title": "Hyperpyrexia leading to death in a patient with severe COVID-19 disease", + "rel_doi": "10.1101/2020.05.16.20099408", + "rel_title": "Serological prevalence of antibodies to SARS CoV-2 amongst cancer centre staff", "rel_date": "2020-05-20", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.18.20097220", - "rel_abs": "We describe here the clinical course of a 42 year old male with severe COVID 19 disease treated at a private hospital in Mumbai, India. This patient with very high inflammatory markers at admission was treated with supportive care, mechanical ventilation, anticoagulation, hydroxychloroquine, corticosteroids, tocilizumab, intravenous insulin, antibiotics, sedation and paralysis. There was sustained improvement in his respiratory status and decline in ventilator settings with decline and normalization of CRP, D dimer and PCT. However high fever persisted that did not respond to paracetamol and NSAIDS. On day 8 of admission his axillary temperature touched 107F followed by rapid clinical deterioration and death within the next 12 hours, Blood cultures were consistently sterile. While death was related to hyperpyrexia, the cause of this hyperpyrexia is uncertain.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.16.20099408", + "rel_abs": "Objectivesthe aim of this study was to test Rutherford Health (RH) staff for the presence of SARS CoV-2 antibodies to reduce the risk of infection to cancer patients.\n\nSettingBetween 14 and 24 April 2020 we tested 161 staff at four locations: our cancer centres in Reading - Berkshire, Newport - S Wales, Liverpool - Merseyside, and Bedlington in Northumberland.\n\nParticipantsTesting was available to all staff who were on site at the four locations named above at the time the study was carried out. 161 staff (80 men, 81 women) gave voluntary consent to have the tests and all testing gave rise to valid results.\n\nInterventionsWe used the South Korean test for antibodies to SARS CoV-2: Sugentech SGTi-flex COVID-19 IgM/IgG1. For each test, blood was collected and added to the sample well of the test cassette and buffer solution added. The test result was legible after 15 minutes. Outcome measures: The number of tests positive for the presence of antibodies was the primary outcome measure. The ratio of tests positive for the presence of IgM antibodies versus IgG antibodies was the secondary outcome measure.\n\nResultsBetween 14 and 24 April 2020, 161 staff (age m = 43) were tested at four Rutherford Cancer Care centres that offer proton beam therapy, radiotherapy and chemotherapy. Out of 161, 12 samples (7.50%) tested positive of which 7 samples (4.35%) detected IgM only, 2 samples (1.24%) detected IgG only and 3 samples (1.86%) detected both IgM and IgG.\n\nConclusionsThe low seroconversion rate in the sample population limits the current utility of the test as a way of reducing risk to vulnerable patient populations but longitudinal retesting will provide further data.\n\nO_LSTStrengths and limitations of the studyC_LSTO_LIThis is the first UK study on SARS CoV-2 antibody testing using the Sugentech SGTi-flex COVID-19 IgM/IgG in the workplace;\nC_LIO_LIThis is the first UK study testing a population of cancer centre staff for SARS CoV-2 antibodies;\nC_LIO_LIThis study builds on similar studies in other countries3-4, albeit with a smaller sample;\nC_LIO_LIData on previous clinical symptoms is not included. We are in the process of revising consent paperwork for the test to include a question about previous symptoms like temperature, dry/persistent cough;\nC_LIO_LIPatient data is not included. We will consider testing patients once the pilot test with staff has reached conclusions about the efficacy and value of the test.\nC_LI", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Tanu Singhal", - "author_inst": "Kokilaben Dhirubhai Ambani Hospital and Medical Research Institute" + "author_name": "Karol Sikora", + "author_inst": "Rutherford Health" }, { - "author_name": "Sourabh Phadtare", - "author_inst": "Kokilaben Dhirubhai Ambani Hospital and Medical Research Institute" - }, - { - "author_name": "Sunil Pai", - "author_inst": "Kokilaben Dhirubhai Ambani Hospital and Medical Research Institute" + "author_name": "Ian Barwick", + "author_inst": "Rutherford Health" }, { - "author_name": "Amit Raodeo", - "author_inst": "Kokilaben Dhirubhai Ambani Hospital and Medical Research Institute" + "author_name": "Ceri Hamilton", + "author_inst": "Rutherford Health" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1439299,41 +1439408,37 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.05.12.20098970", - "rel_title": "Agent-Based Simulation for Evaluation of Contact-Tracing Policies Against the Spread of SARS-CoV-2", + "rel_doi": "10.1101/2020.05.12.20099036", + "rel_title": "Stepping out of lockdown should start with school re-openings while maintaining distancing measures. Insights from mixing matrices and mathematical models.", "rel_date": "2020-05-19", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.12.20098970", - "rel_abs": "BackgroundMany countries have already gone through several infection waves and mostly managed to successfully stop the exponential spread of SARS-CoV-2 through bundles of restrictive measures. Still, the danger of further waves of infections is omnipresent and it is apparent that every containment policy must be carefully evaluated and possibly replaced by a different, less restrictive policy, before it can be lifted. Tracing of contacts and consequential breaking of infection chains is a promising strategy to help containing the disease, although its precise impact on the epidemic is unknown.\n\nObjectiveIn this work we aim to quantify the impact of tracing on the containment of the disease and investigate the dynamic effects involved.\n\nDesignWe developed an agent-based model that validly depicts the spread of the disease and allows for exploratory analysis of containment policies. We apply this model to quantify the impact of divverent variants of contact tracing in Austria and to derive general conclusions on contract tracing.\n\nResultsThe study displays that strict tracing can supplement up to 5% reduction of infectivity and that household quarantine comes at the smallest price regarding preventively quarantined people.\n\nLimitationsThe results are limited by the validity of the modeling assumptions, model parameter estimates, and the quality of the parametrization data.\n\nConclusionsThe study shows that tracing is indeed an efficient measure to keep case numbers low but comes at a high price if the disease is not well contained. Therefore, contact tracing must be executed strictly and adherence within the population must be held up to prevent uncontrolled outbreaks of the disease.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.12.20099036", + "rel_abs": "Australia is one of a few countries which has managed to control COVID-19 epidemic before a major epidemic took place. Currently with just under 7000 cases and 100 deaths, Australia is seeing less than 20 new cases per day. This is a positive outcome but makes estimation of current effective reproduction numbers difficult to estimate. Australia, like much of the world is poised to step out of lockdown and looking at which measures to relax first.\n\nWe use age-based contact matrices, calibrated to Chinese data on reproduction numbers and difference in infectiousness and susceptibility of children to generate next generation matrices (NGMs) for Australia. These matrices have a spectral radius of 2.49, which is hence our estimated basic reproduction number for Australia. The effective reproduction number (Reff) for Australia during the April/May lockdown period is estimated by other means to be around 0.8. We simulate the impact of lockdown on the NGM by first applying observations through Google Mobility Report for Australia at 3 locations: home (increased contacts by 18%), work (reduced contacts by 34%) and other (reduced contacts by 40%), and we reduce schools to 3% reflecting attendance rates during lockdown. Applying macro-distancing to the NGM leads to a spectral radius of 1.76. We estimate that the further reduction of the reproduction number to current levels of Reff = 0.8 is achieved by a micro-distancing factor of 0.26. That is, in a given location, people are 26% as likely as usual to have an effective contact with another person.\n\nWe apply both macro and micro-distancing to the NGMs to examine the impact of different exit strategies. We find that reopening schools is estimated to reduce Reff from 0.8 to 0.78. This is because increase in school contact is offset by decrease in home contact. The NGMs all estimate that adults aged 30-50 are responsible for the majority of transmission. We also find that micro-distancing is critically important to maintain Reff <1. There is considerable uncertainty in these estimates and a sensitivity and uncertainty analysis is presented.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Martin Richard Bicher", - "author_inst": "TU Wien" - }, - { - "author_name": "Claire Rippinger", - "author_inst": "dwh GmbH" + "author_name": "Emma Sue McBryde", + "author_inst": "James Cook University" }, { - "author_name": "Christoph Urach", - "author_inst": "dwh GmbH" + "author_name": "James M Trauer", + "author_inst": "Monash University" }, { - "author_name": "Dominik Brunmeir", - "author_inst": "dwh GmbH" + "author_name": "Adeshina Adekunle", + "author_inst": "James Cook University" }, { - "author_name": "Uwe Siebert", - "author_inst": "UMIT University for Health Sciences, Institute of Public Health, Medical Decision Making and Health Technology Assessment" + "author_name": "Romain Ragonnet", + "author_inst": "Monash University" }, { - "author_name": "Niki Popper", - "author_inst": "TU Wien" + "author_name": "Michael T Meehan", + "author_inst": "James Cook University" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1440641,49 +1440746,37 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.05.14.20101675", - "rel_title": "Reproducing SARS-CoV-2 epidemics byregion-specific variables and modeling contacttracing App containment", + "rel_doi": "10.1101/2020.05.14.20101642", + "rel_title": "Knowledge of novel coronavirus (SARS-COV-2) among a Georgian population", "rel_date": "2020-05-19", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.14.20101675", - "rel_abs": "Targeted contact-tracing through mobile phone apps has been proposed as an instrument to help contain the spread of COVID-19 and manage the lifting of nation-wide lockdowns currently in place in USA and Europe. However, there is an ongoing debate on its potential efficacy, especially in the light of region-specific demographics.\n\nWe built an expanded SIR model of COVID-19 epidemics that accounts for region-specific population densities, and we used it to test the impact of a contact-tracing app in a number of scenarios. Using demographic and mobility data from Italy and Spain, we used the model to simulate scenarios that vary in baseline contact rates, population densities and fraction of app users in the population.\n\nOur results show that, in support of efficient isolation of symptomatic cases, app-mediated contact-tracing can successfully mitigate the epidemic even with a relatively small fraction of users, and even suppress altogether with a larger fraction of users. However, when regional differences in population density are taken into consideration, the epidemic can be significantly harder to contain in higher density areas, highlighting potential limitations of this intervention in specific contexts.\n\nThis work corroborates previous results in favor of app-mediated contact-tracing as mitigation measure for COVID-19, and draws attention on the importance of region-specific demographic and mobility factors to achieve maximum efficacy in containment policies.", - "rel_num_authors": 9, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.14.20101642", + "rel_abs": "IntroductionGeorgia confirmed its first case of SARS-COV-2 infection on February 26, 2020. Despite the governments proactive measures during the early stages of the epidemic, number of new infections of SARS-COV-2 is increasing and by March 31, a total of 110 cases have been reported. Limited understanding about epidemics can lead to panic and disrupt public health efforts to contain transmission. Thus, it is very important to understand the perceptions of the population regarding the disease and perceived level of government preparedness to fight against the spread of infection. This study reports results of a survey designed to understand attitudes and knowledge regarding SARS-COV-2 virus among Georgian population, including health care workers (HCWs).\n\nMaterials and methodsThe online survey was conducted using a Facebook advertisement. The target was the whole country and the language used was Georgian. We collected information on demographic data, knowledge of symptoms and transmission modes of coronavirus, perceived differences between coronavirus and influenza, availability of antiviral medication and vaccination. We also included questions to capture the Georgian populations perceptions about government preparedness to combat the new coronavirus.\n\nResultsThe survey was open for three days (March 2-4, 2020). 5228 participants completed the survey. Of these, 40.3% were 25-45 years old and 58.2% were female. 20.7% of respondents had university degree and 10.3% were HCWs. For 25.8% of respondents, COVID-19 and influenza are the same diseases; 10.9% did not know if they are different. The majority correctly identified the transmission route and symptoms (96.9% and 98.0%, respectively). Regarding physical distancing, 13.2% indicated they would attend public events if needed even if they had COVID-19 symptoms. 19.1% think that Georgia is ready for COVID 19 epidemic, while according to 55% the county is not ready, but HCWs are trying hard to respond to this challenge properly. For 18% response is inadequate. There was no difference in knowledge between HCWs, non-HCWs and unemployed. 20% of HCWs as well as other study subjects believe that SARS-COV-2 vaccine and medications do exist but are simply not available in Georgia.\n\nConclusionOne in five Georgians believe that there is a vaccine and medication to treat coronavirus, but that it is not available in the country. Given that information regarding coronavirus is changing very rapidly, the need to reach people with time-sensitive educational messages as well as prevention strategies is vital.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Alberto Ferrari", - "author_inst": "FROM research foundation" - }, - { - "author_name": "Enrico Santus", - "author_inst": "Bayer, Decision Science & Advanced Analytics for MA, PV & RA Division." + "author_name": "Maia Butsashvili", + "author_inst": "Health Research Union" }, { - "author_name": "Davide Cirillo", - "author_inst": "Barcelona Supercomputing Center (BSC), C/ Jordi Girona 29, 08034, Barcelona,Spain." - }, - { - "author_name": "Miguel Ponce-de-Leon", - "author_inst": "Barcelona Supercomputing Center (BSC), C/ Jordi Girona 29, 08034, Barcelona,Spain." - }, - { - "author_name": "Nicola Marino", - "author_inst": "Women's Brain Project (WBP), Gunterhausen, Switzerland" + "author_name": "Lasha Gulbiani", + "author_inst": "Data Research Group" }, { - "author_name": "Maria Teresa Ferretti", - "author_inst": "Women's Brain Project (WBP), Gunterhausen, Switzerland" + "author_name": "George Kanchelashvili", + "author_inst": "Data Research Group" }, { - "author_name": "Antonella Santuccione Chadha", - "author_inst": "Women's Brain Project (WBP), Gunterhausen, Switzerland" + "author_name": "Marika Kochlamazashvili", + "author_inst": "Health Research Group" }, { - "author_name": "Nikolaos Mavridis", - "author_inst": "Interactive Robots and Media Laboratory (IRLM), United Arab Emirates." + "author_name": "George Nioradze", + "author_inst": "Health Research Union" }, { - "author_name": "Alfonso Valencia", - "author_inst": "Barcelona Supercomputing Center (BSC), C/ Jordi Girona 29, 08034, Barcelona,Spain." + "author_name": "George Kamkamidze", + "author_inst": "Clinic Neolab" } ], "version": "1", @@ -1442063,47 +1442156,111 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2020.05.16.20098657", - "rel_title": "Empirical Assessment of COVID-19 Crisis Standards of Care Guidelines", + "rel_doi": "10.1101/2020.05.18.20105171", + "rel_title": "Upper airway gene expression differentiates COVID-19 from other acute respiratory illnesses and reveals suppression of innate immune responses by SARS-CoV-2", "rel_date": "2020-05-19", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.16.20098657", - "rel_abs": "BackgroundSeveral states have released Crisis Standards of Care (CSC) guidelines for the allocation of scarce critical care resources. Most guidelines rely on Sequential Organ Failure Assessment (SOFA) scores to maximize lives saved, but states have adopted different stances on whether to maximize long-term outcomes (life-years saved) by accounting for patient comorbidities.\n\nMethodsWe compared 4 representative state guidelines with varying approaches to comorbidities and analyzed how CSC prioritization correlates with clinical outcomes. We included 27 laboratory-confirmed COVID-19 patients admitted to ICUs at Brigham and Womens Hospital from March 12 to April 3, 2020. We compared prioritization algorithms from New York, which assigns priority based on SOFA alone; Maryland, which uses SOFA plus severe comorbidities; Pennsylvania, which uses SOFA plus major and severe comorbidities; and Colorado, which uses SOFA plus a modified Charlson comorbidity index.\n\nResultsIn pairwise comparisons across all possible pairs, we found that state guidelines frequently resulted in tie-breakers based on age or lottery: New York 100% of the time (100% resolved by lottery), Pennsylvania 86% of the time (18% by lottery), Maryland 93% of the time (35% by lottery), and Colorado: 32% of the time (10% by lottery). The prioritization algorithm with the strongest correlation with 14-day outcomes was Colorado (rs = -0.483. p = 0.011) followed by Maryland (rs = -0. 394, p =0.042), Pennsylvania (rs = -0.382, p = 0.049), and New York (rs = 0). An alternative model using raw SOFA scores alone was moderately correlated with outcomes (rs = -0.448, p = 0.019).\n\nConclusionsState guidelines for scarce resource allocation frequently resulted in identical priority scores, requiring tie-breakers based on age or lottery. These findings suggest that state CSC guidelines should be further assessed empirically to understand whether they meet their goals.", - "rel_num_authors": 7, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.18.20105171", + "rel_abs": "We studied the host transcriptional response to SARS-CoV-2 by performing metagenomic sequencing of upper airway samples in 238 patients with COVID-19, other viral or non-viral acute respiratory illnesses (ARIs). Compared to other viral ARIs, COVID-19 was characterized by a diminished innate immune response, with reduced expression of genes involved in toll-like receptor and interleukin signaling, chemokine binding, neutrophil degranulation and interactions with lymphoid cells. Patients with COVID-19 also exhibited significantly reduced proportions of neutrophils and macrophages, and increased proportions of goblet, dendritic and B-cells, compared to other viral ARIs. Using machine learning, we built 26-, 10- and 3-gene classifiers that differentiated COVID-19 from other acute respiratory illnesses with AUCs of 0.980, 0.950 and 0.871, respectively. Classifier performance was stable at low viral loads, suggesting utility in settings where direct detection of viral nucleic acid may be unsuccessful. Taken together, our results illuminate unique aspects of the host transcriptional response to SARS-CoV-2 in comparison to other respiratory viruses and demonstrate the feasibility of COVID-19 diagnostics based on patient gene expression.", + "rel_num_authors": 23, "rel_authors": [ { - "author_name": "Julia L. Jezmir", - "author_inst": "Brigham and Women's Hospital" + "author_name": "Eran Mick", + "author_inst": "University of California, San Francisco; Chan Zuckerberg Biohub" }, { - "author_name": "Maheetha Bharadwaj", - "author_inst": "Harvard Medical School" + "author_name": "Jack Kamm", + "author_inst": "Chan Zuckerberg Biohub" }, { - "author_name": "Sandeep P. Kishore", - "author_inst": "Brigham and Women's Hospital" + "author_name": "Angela Oliveira Pisco", + "author_inst": "Chan Zuckerberg Biohub" }, { - "author_name": "Marisa Winkler", - "author_inst": "Brigham and Women's Hospital" + "author_name": "Kalani Ratnasiri", + "author_inst": "Chan Zuckerberg Biohub" }, { - "author_name": "Bradford Diephuis", - "author_inst": "Brigham and Women's Hospital" + "author_name": "Jennifer M Babik", + "author_inst": "University of California, San Francisco" }, { - "author_name": "Edy Y. Kim", - "author_inst": "Brigham and Women's Hospital" + "author_name": "Carolyn S Calfee", + "author_inst": "University of California, San Francisco" }, { - "author_name": "William B. Feldman", - "author_inst": "Brigham and Women's Hospital" + "author_name": "Gloria Castaneda", + "author_inst": "Chan Zuckerberg Biohub" + }, + { + "author_name": "Joseph L DeRisi", + "author_inst": "University of California, San Francisco; Chan Zuckerberg Biohub" + }, + { + "author_name": "Angela M Detweiler", + "author_inst": "Chan Zuckerberg Biohub" + }, + { + "author_name": "Samantha Hao", + "author_inst": "Chan Zuckerberg Biohub" + }, + { + "author_name": "Kirsten N Kangelaris", + "author_inst": "University of California, San Francisco" + }, + { + "author_name": "G Renuka Kumar", + "author_inst": "Chan Zuckerberg Biohub" + }, + { + "author_name": "Lucy M Li", + "author_inst": "Chan Zuckerberg Biohub" + }, + { + "author_name": "Sabrina A Mann", + "author_inst": "University of California, San Francisco; Chan Zuckerberg Biohub" + }, + { + "author_name": "Norma Neff", + "author_inst": "Chan Zuckerberg Biohub" + }, + { + "author_name": "Priya A Prasad", + "author_inst": "University of California, San Francisco" + }, + { + "author_name": "Paula Hayakawa Serpa", + "author_inst": "University of California, San Francisco; Chan Zuckerberg Biohub" + }, + { + "author_name": "Sachin J Shah", + "author_inst": "University of California, San Francisco" + }, + { + "author_name": "Natasha Spottiswoode", + "author_inst": "University of California, San Francisco" + }, + { + "author_name": "Michelle Tan", + "author_inst": "Chan Zuckerberg Biohub" + }, + { + "author_name": "Stephanie A Christenson", + "author_inst": "University of California, San Francisco" + }, + { + "author_name": "Amy Kistler", + "author_inst": "Chan Zuckerberg Biohub" + }, + { + "author_name": "Charles Langelier", + "author_inst": "University of California, San Francisco; Chan Zuckerberg Biohub" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "medical ethics" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2020.05.15.20084293", @@ -1443973,115 +1444130,43 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.05.11.20092916", - "rel_title": "Prevalence of SARS-CoV-2 infection in the Luxembourgish population: the CON-VINCE study.", + "rel_doi": "10.1101/2020.05.15.20102798", + "rel_title": "The effect of ambient temperature on worldwide COVID-19 cases and deaths - an epidemiological study", "rel_date": "2020-05-18", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.11.20092916", - "rel_abs": "BACKGROUNDThe World Health Organization declared the outbreak of coronavirus disease to be a public health emergency of international concern on January 30, 2020. The first SARS-CoV-2 infection was subsequently detected in Luxembourg on February 29, 2020. Representative population-based data, including asymptomatic individuals for assessing the viral spread and immune response was, however, lacking worldwide.\n\nMETHODSUsing a panel-based method, we recruited a representative sample of the Luxembourgish population based on age, gender and residency for testing for SARS-CoV-2 infection and antibody status in order to define prevalence irrespective of clinical symptoms. Participants were contacted via email to fill an online questionnaire before biosampling at local laboratories. Participants provided information related to clinical symptoms, epidemiology, socioeconomic and psychological assessments and underwent biosampling, rRT-PCR testing and serology for SARS-CoV-2.\n\nRESULTSA total of 1862 individuals were included for our representative sample of the general Luxembourgish population. We detected an ongoing SARS-CoV-2 infection based on rRT-PCR in 5 participants. h Four of the SARS-CoV-2 infected participants were oligosymptomatic and one was asymptomatic. Overall, 35 participants (1.97%) had developed a positive IgG response, of whom 11 self-reported to have previously received a positive rRT-PCR diagnosis of SARS-CoV-2 infection. Our data indicate a prevalence of 0.3% for active SARS-CoV-2 infection in the Luxembourgish population between 18 and 79 years of age.\n\nCONCLUSIONSLuxembourgish residents show a low rate of acute infections after 7 weeks of confinement and present with an antibody profile indicative of a more recent immune response to SARS-CoV-2. All infected individuals were oligo- or asymptomatic. Bi-weekly follow-up visits over the next 2 months will inform about the viral spread by oligo- and asymptomatic carriers and the individual changes in the immune profile.", - "rel_num_authors": 24, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.15.20102798", + "rel_abs": "BackgroundThe role of ambient temperature in the spread of SARS-CoV-2 infections and subsequent deaths due to COVID-19 remains contentious. Coronaviruses such as the 2003 SARS-CoV showed an increased risk of transmission during cooler days. We sought to analyse the effects of ambient temperature on SARS-COV-2 transmission and deaths related to the virus.\n\nMethodsThe world population of COVID-19 cases and attributable deaths from the 23rd January 2020 to 11th April 2020 were analysed. Temperature 5 days before cases and 23 days prior to deaths (to account for the time lag of incubation period and time from symptoms to death) was compared to the average temperature experienced by the world population.\n\nResultsThe total number of cases during this period was 1,605,788 and total number of deaths was 103,471. The median temperature at the time of COVID-19 infection was 9.12{degrees}C (10-90th percentile 4.29-17.97{degrees}C) whilst the median temperature of the world population for the same period was 9.61{degrees}C warmer at 18.73{degrees}C (10-90th percentile 4.09-28.49{degrees}C) with a notional p-value =5.1 x10-11. The median temperature at the time of a COVID-19 death was 9.72{degrees}C (10-90th percentile 5.39-14.11{degrees}C) whilst the median temperature of the world population was 7.55{degrees}C warmer at 17.27{degrees}C (10-90th percentile 2.57{degrees}C-27.76{degrees}C) with a notional p-value = 1.1 x10-10. 80% of all COVID-19 related cases and deaths occurred between 4.29{degrees}C and 17.97{degrees}C.\n\nConclusionA definitive association between infection rate and death from COVID-19 and ambient temperature exists, with the highest risk occurring around 9{degrees}C. Governments should maintain vigilance with containment strategies when the ambient temperatures correspond to this highest risk.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Chantal J. Snoeck", - "author_inst": "Department of Infection and Immunity, Luxembourg Institute of Health, Esch-sur-Alzette, L-4354 Luxembourg" - }, - { - "author_name": "Michel Vaillant", - "author_inst": "Competence Center for Methodology and Statistics, Luxembourg Institute of Health. Strassen L-1445 Luxembourg" - }, - { - "author_name": "Tamir Abdelrahman", - "author_inst": "Department of Microbiology, Laboratoire national de sant\u00e9, Dudelange, L-3555, Luxembourg" - }, - { - "author_name": "Venkata P. Satagopam", - "author_inst": "Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Esch-Belval, Luxembourg" - }, - { - "author_name": "Jonathan D. Turner", - "author_inst": "Department of Infection and Immunity, Luxembourg Institute of Health, Esch-sur-Alzette, L-4354 Luxembourg" - }, - { - "author_name": "Katy Beaumont", - "author_inst": "Integrated Biobank of Luxembourg (IBBL), Dudelange, L-3555 Luxembourg" - }, - { - "author_name": "Clarissa P. C. Gomes", - "author_inst": "Clinical and Experimental Neuroscience, Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Esch-Belval, Luxembourg" - }, - { - "author_name": "Joelle Veronique Fritz", - "author_inst": "Luxembourg Institute of Health" - }, - { - "author_name": "Valerie E. Schr\u00f6der", - "author_inst": "Department of Neurology, Centre Hospitalier de Luxembourg, Luxembourg, L-1210 Clinical and Experimental Neuroscience, Luxembourg Centre for Systems Biomedicine" - }, - { - "author_name": "Anne Kaysen", - "author_inst": "Clinical and Experimental Neuroscience, Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Esch-Belval, Luxembourg" - }, - { - "author_name": "Lukas Pavelka", - "author_inst": "Department of Neurology, Centre Hospitalier de Luxembourg, Luxembourg, L-1210 Clinical and Experimental Neuroscience, Luxembourg Centre for Systems Biomedicine " - }, - { - "author_name": "Lara Stute", - "author_inst": "Department of Neurology, Centre Hospitalier de Luxembourg, Luxembourg, L-1210 Clinical and Experimental Neuroscience, Luxembourg Centre for Systems Biomedicine " - }, - { - "author_name": "Guilherme Ramos Meyers", - "author_inst": "Clinical and Experimental Neuroscience, Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Esch-Belval, Luxembourg" - }, - { - "author_name": "Laure Pauly", - "author_inst": "Clinical and Experimental Neuroscience, Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Esch-Belval, Luxembourg" - }, - { - "author_name": "Maxime Hansen", - "author_inst": "Department of Neurology, Centre Hospitalier de Luxembourg, Luxembourg, L-1210 Transversal Translational Medicine, Luxembourg Institute of Health, Strassen, Luxe" - }, - { - "author_name": "Claire Pauly", - "author_inst": "Department of Neurology, Centre Hospitalier de Luxembourg, Luxembourg, L-1210 Clinical and Experimental Neuroscience, Luxembourg Centre for Systems Biomedicine " - }, - { - "author_name": "Gloria A. Aguayo", - "author_inst": "Population Health Department, Luxembourg Institute of Health. Strassen L-1445 Luxembourg" - }, - { - "author_name": "Magali Perquin", - "author_inst": "Population Health Department, Luxembourg Institute of Health. Strassen L-1445 Luxembourg" - }, - { - "author_name": "Anne-Marie Hanff", - "author_inst": "Transversal Translational Medicine, Luxembourg Institute of Health, Strassen, Luxembourg" + "author_name": "Anver Sethwala", + "author_inst": "Royal Melbourne Hospital" }, { - "author_name": "Soumyabrata Ghosh", - "author_inst": "Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Esch-Belval, Luxembourg" + "author_name": "Mohamed Akbarally", + "author_inst": "University of Melbourne" }, { - "author_name": "Manon Gantenbein", - "author_inst": "Clinical and Epidemiological Investigation Center (CIEC), Luxembourg Institute of Health. Strassen L-1445 Luxembourg" + "author_name": "Nathan Better", + "author_inst": "Royal Melbourne Hospital" }, { - "author_name": "Laetitia Huiart", - "author_inst": "Population Health Department, Luxembourg Institute of Health. Strassen L-1445 Luxembourg" + "author_name": "Jeffrey Lefkovits", + "author_inst": "Royal Melbourne Hospital" }, { - "author_name": "Markus Ollert", - "author_inst": "Department of Infection and Immunity, Luxembourg Institute of Health, Esch-sur-Alzette, L-4354 Luxembourg Department of Dermatology and Allergy Center, Odense R" + "author_name": "Leeanne Grigg", + "author_inst": "Royal Melbourne Hospital" }, { - "author_name": "Rejko Kr\u00fcger", - "author_inst": "Transversal Translational Medicine, Luxembourg Institute of Health, Strassen, Luxembourg Department of Neurology, Centre Hospitalier de Luxembourg, Luxembourg, " + "author_name": "Huzefa Akbarally", + "author_inst": "Sri Lanka Association for the Advancement of Science" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2020.05.12.20095562", @@ -1445483,29 +1445568,77 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2020.05.14.20102459", - "rel_title": "Early transmission of COVID-19 has an optimal temperature but late transmission decreases in warm climate", + "rel_doi": "10.1101/2020.05.13.20096826", + "rel_title": "Transmission dynamics of the COVID-19 epidemic in India, and evaluating the impact of asymptomatic carriers and role of expanded testing in the lockdown exit strategy: a modelling approach", "rel_date": "2020-05-18", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.14.20102459", - "rel_abs": "The COVID-19 novel virus, as an emerging highly pathogenic agent, has caused a pandemic. Revealing the influencing factors affecting transmission of COVID-19 is essential to take effective control measures. Several previous studies suggested that the spread of COVID-19 was likely associated with temperature and/or humidity. But, a recent extensive review indicated that conclusions on associations between climate and COVID-19 were elusive with high uncertainty due to caveats in most previous studies, such as limitations in time and space, data quality and confounding factors. In this study, by using a more extensive global dataset covering 578 time series from China, USA, Europe and the rest of the world, we show that climate show distinct impacts on early and late transmission of COVID-19 in the world after excluding the confounding factors. The early transmission ability of COVID-19 peakedaround 6.3{degrees}C without or with little human intervention, but the later transmission ability was reduced in high temperature conditions under human intervention, probably driven by increased control efficiency of COVID-19. The transmission ability was positively associated with the founding population size of early reported cases and population size of a location. Our study suggested that with the coming summer seasons, the transmission risk of COVID-19 would increase in the high-latitude or high-altitude regions but decrease in low-latitude or low-altitude regions; human intervention is essential in containing the spread of COVID-19 around the world.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.13.20096826", + "rel_abs": "BackgroundThe SARS-CoV-2 pandemic has quickly become an unprecedented global health threat. India with its unique challenges in fighting this pandemic, imposed one of the worlds strictest and largest population-wide lockdown on 25 March 2020. Here, we estimated key epidemiological parameters and evaluated the effect of control measures on the COVID-19 epidemic in India. Through a modelling approach, we explored various strategies to exit the lockdown.\n\nMethodsWe obtained data from 140 confirmed COVID-19 patients at a tertiary care hospital in India to estimate the delay from symptom onset to confirmation and the proportion of cases without symptoms. We estimated the basic reproduction number (R0) and time-varying effective reproduction number (Rt) after adjusting for imported cases and reporting lag, using incidence data from 4 March to 25 April 2020 for India. We built upon the SEIR model to account for underreporting, reporting delays, and varying asymptomatic proportion and infectivity. Using this model, we simulated lockdown relaxation under various scenarios to evaluate its effect on the second wave, and also modelled increased detection through testing. We hypothesised that increased testing after lockdown relaxation will decrease the epidemic growth enough to allow for greater resumption of normal social mixing thus minimising the social and economic fallout.\n\nResultsThe median delay from symptom onset to confirmation (reporting lag) was estimated to be 2{middle dot}68 days (95%CI 2{middle dot}00-3{middle dot}00) with an IQR of 2{middle dot}03 days (95%CI 1{middle dot}00-3{middle dot}00). 60{middle dot}7% of confirmed COVID-19 cases (n=140) were found to be asymptomatic. The R0 for India was estimated to be 2{middle dot}083 (95%CI 2{middle dot}044-2{middle dot}122; R2 = 0{middle dot}972), while the Rt gradually down trended from 1{middle dot}665 (95%CI 1{middle dot}539-1{middle dot}789) on 30 March to 1{middle dot}159 (95%CI 1{middle dot}128-1{middle dot}189) on 22 April. In the modelling, we observed that the time lag from date of lockdown relaxation to start of second wave increases as lockdown is extended farther after the first wave peak. This benefit was greater for a gradual relaxation as compared to a sudden lifting of lockdown. We found that increased detection through testing decreases the number of total infections and symptomatic cases, and the benefit of detecting each extra case was higher when prevailing transmission rates were higher (as when restrictions are relaxed). Lower levels of social restrictions when coupled with increased testing, could achieve similar outcomes as an aggressive social distancing regime where testing was not increased.\n\nConclusionsThe aggressive control measures in India since 25 March have produced measurable reductions in transmission, although suppression needs to be maintained to achieve sub-threshold Rt. Additional benefits for mitigating the second wave can be achieved if lockdown can be feasibly extended farther after the peak of active cases has passed. Aggressive measures like lockdowns may inherently be enough to suppress the epidemic, however other measures need to be scaled up as lockdowns are relaxed. Expanded testing is expected to play a pivotal role in the lockdown exit strategy and will determine the degree of return to normalcy that will be possible. Increased testing coverage will also ensure rapid feedback from surveillance systems regarding any resurgence in cases, so that geo-temporally targeted measures can be instituted at the earliest. Considering that asymptomatics play an undeniable role in transmission of COVID-19, it may be prudent to reduce the dependence on presence of symptoms for implementing control strategies, behavioral changes and testing.", + "rel_num_authors": 15, "rel_authors": [ { - "author_name": "xinru wan", - "author_inst": "State Key Laboratory of Integrated Management on Pest Insects and Rodents in Agriculture, Institute of Zoology, Chinese Academy of Sciences" + "author_name": "Mohak Gupta", + "author_inst": "All India Institute of Medical Sciences (AIIMS), New Delhi, India" + }, + { + "author_name": "Saptarshi Soham Mohanta", + "author_inst": "Indian Institute of Science Education and Research (IISER), Pune, India" + }, + { + "author_name": "Aditi Rao", + "author_inst": "All India Institute of Medical Sciences (AIIMS), New Delhi, India" + }, + { + "author_name": "Giridara Gopal Parameswaran", + "author_inst": "All India Institute of Medical Sciences (AIIMS), New Delhi, India" + }, + { + "author_name": "Mudit Agarwal", + "author_inst": "All India Institute of Medical Sciences (AIIMS), New Delhi, India" }, { - "author_name": "Chaoyuan Cheng", - "author_inst": "State Key Laboratory of Integrated Management on Pest Insects and Rodents in Agriculture, Institute of Zoology, Chinese Academy of Sciences" + "author_name": "Mehak Arora", + "author_inst": "All India Institute of Medical Sciences (AIIMS), New Delhi, India" + }, + { + "author_name": "Archisman Mazumder", + "author_inst": "All India Institute of Medical Sciences (AIIMS), New Delhi, India" + }, + { + "author_name": "Ayush Lohiya", + "author_inst": "Super Specialty Cancer Institute & Hospital, Lucknow, India" + }, + { + "author_name": "Priyamadhaba Behera", + "author_inst": "All India Institute of Medical Sciences (AIIMS), Bhubaneswar, India" }, { - "author_name": "zhibin zhang", - "author_inst": "State Key Laboratory of Integrated Management on Pest Insects and Rodents in Agriculture, Institute of Zoology, Chinese Academy of Sciences" + "author_name": "Agam Bansal", + "author_inst": "Cleveland Clinic, Ohio, USA" + }, + { + "author_name": "Rohit Kumar", + "author_inst": "All India Institute of Medical Sciences (AIIMS), New Delhi, India" + }, + { + "author_name": "Ved Prakash Meena", + "author_inst": "All India Institute of Medical Sciences (AIIMS), New Delhi, India" + }, + { + "author_name": "Pawan Tiwari", + "author_inst": "All India Institute of Medical Sciences (AIIMS), New Delhi, India" + }, + { + "author_name": "Anant Mohan", + "author_inst": "All India Institute of Medical Sciences (AIIMS), New Delhi, India" + }, + { + "author_name": "Sushma Bhatnagar", + "author_inst": "All India Institute of Medical Sciences (AIIMS), New Delhi, India" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", "category": "public and global health" }, @@ -1446693,81 +1446826,45 @@ "category": "ophthalmology" }, { - "rel_doi": "10.1101/2020.05.11.20098442", - "rel_title": "SARS-CoV-2 seroprevalence trends in healthy blood donors during the COVID-19 Milan outbreak", + "rel_doi": "10.1101/2020.05.12.20098921", + "rel_title": "Behavioural change towards reduced intensity physical activity is disproportionately prevalent among adults with serious health issues or self-perception of high risk during the UK COVID-19 lockdown.", "rel_date": "2020-05-18", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.11.20098442", - "rel_abs": "ObjectivesThe Milan metropolitan area in Northern Italy was among the most severely hit by the SARS-CoV-2 outbreak. The epidemiological trends of mild COVID-19 are however still unknown. The aim of this study was to examine the seroprevalence of SARS-CoV-2 infection in healthy asymptomatic adults, the risk factors, and laboratory correlates.\n\nDesignWe conducted a cross-sectional study during the outbreak. Presence of anti-SARS-CoV-2 IgM/IgG antibodies against the Nucleocapsid protein was assessed by a lateral flow immunoassay.\n\nSettingBlood center at a leading academic hospital serving as COVID-19 referral center.\n\nParticipantsWe considered a random sample of blood donors since the start of the outbreak (February 24th to April 8th 2020, n=789).\n\nMain outcome measuresThe main outcome was the prevalence of IgG/IgM anti-SARS-CoV-2 antibodies.\n\nResultsThe test had a 98.3% specificity and 100% sensitivity, and for IgG+ was validated in a subset by an independent ELISA against the Spike protein (N=34, P<0.001). At the start of the outbreak, the overall seroprevalence of SARS-CoV-2 was 4.6% (2.3 to 7.9; P<0.0001 vs. 120 historical controls). During the study period characterized by a gradual implementation of social distancing measures, there was a progressive increase in seroprevalence to 7.1% (4.4 to 10.8), due to a rise in IgG+ to 5% (2.8 to 8.2; P=0.004 for trend, adjusted weekly increase 2.7{+/-}1.3%), but not of IgM+ (P=NS). At multivariate logistic regression analysis, seroconversion to IgG+ was more frequent in younger (P=0.043), while recent infections (IgM+) in older individuals (P=0.002). IgM+ was independently associated with higher triglycerides, eosinophils, and lymphocytes (P<0.05).\n\nConclusionsSARS-CoV-2 infection was already circulating in Milan at the outbreak start. Social distancing may have been more effective in younger individuals, and by the end of April 4.4-10.8% of healthy adults had evidence of seroconversion. Asymptomatic infection may affect lipid profile and blood count.\n\nSUMMARY BOXO_ST_ABSWhat is already know on this topicC_ST_ABSO_LISARS-CoV-2 causes COVID-19, associated with a high mortality rate, but may be asymptomatic in a still undefined fraction of individuals.\nC_LIO_LICOVID-19 is associated with altered hematological, inflammatory and biochemical parameters, but the laboratory correlates of non-severe infection are unknown.\nC_LIO_LIA severe COVID-19 outbreak severely hit Milan at the end of February 2020, but the number of infected individuals and risk factors remain unclear.\nC_LI\n\nWhat this study addsO_LISARS-CoV-2 was already circulating in Milan at the COVID-19 outbreak start on February 2020, with only 1 in 20 infected individuals being symptomatic and diagnosed.\nC_LIO_LISocial distancing may have been more effective in reducing new infections in younger individuals, and by the end of April 4.4-10.8% of healthy asymptomatic adults had evidence of seroconversion.\nC_LIO_LIAsymptomatic infection may affect lipid profile and be associated with higher circulating lymphocytes and eosinophils.\nC_LI", - "rel_num_authors": 16, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.12.20098921", + "rel_abs": "ImportanceThere are growing concerns that the UK COVID-19 lockdown has reduced opportunities to maintain health through physical activity, placing individuals at higher risk of chronic disease and leaving them more vulnerable to severe sequelae of COVID-19.\n\nObjectiveTo examine whether the UKs lockdown measures have had disproportionate impacts on intensity of physical activity in groups who are, or who perceive themselves to be, at heightened risk from COVID-19.\n\nDesigns, Setting, ParticipantsUK-wide survey of adults aged over 20, data collected between 2020-04-06 and 2020-04-22.\n\nExposuresSelf-reported doctor-diagnosed obesity, hypertension, type I/II diabetes, lung disease, cancer, stroke, heart disease. Self-reported disabilities and depression. Sex, gender, educational qualifications, household income, caring for school-age children. Narrative data on coping strategies.\n\nMain Outcomes and MeasuresChange in physical activity intensity after implementation of UK COVID-19 lockdown (self-reported).\n\nResultsMost (60%) participants achieved the same level of intensity of physical activity during the lockdown as before the epidemic. Doing less intensive physical activity during the lockdown was associated with obesity (OR 1.21, 95% CI 1.02-1.41), hypertension (OR 1.52, 1.33-1.71), lung disease (OR 1.31,1.13-1.49), depression (OR 2.02, 1.82-2.22) and disability (OR 2.34, 1.99-2.69). Participants who reduced their physical activity intensity also had higher odds of being female, living alone or having no garden, and more commonly expressed sentiments about personal or household risks in narratives on coping.\n\nConclusions and relevanceGroups who reduced physical activity intensity included disproportionate numbers of people with either heightened objective clinical risks or greater tendency to express subjective perceptions of risk. Policy on exercise for health during lockdowns should include strategies to facilitate health promoting levels of physical activity in vulnerable groups, including those with both objective and subjective risks.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Luca Valenti", - "author_inst": "University of Milan" - }, - { - "author_name": "Annalisa Bergna", - "author_inst": "University of Milan" - }, - { - "author_name": "Serena Pelusi", - "author_inst": "University of Milan" - }, - { - "author_name": "Federica Facciotti", - "author_inst": "Istituto Europeo di Oncologia" - }, - { - "author_name": "Alessia Lai", - "author_inst": "University of Milan" - }, - { - "author_name": "Maciej Tarkowski", - "author_inst": "University of Milan" - }, - { - "author_name": "Alessandra Berzuini", - "author_inst": "Fondazione IRCCS Ca' Granda" - }, - { - "author_name": "Flavio Caprioli", - "author_inst": "University of Milan" - }, - { - "author_name": "Luigi Santoro", - "author_inst": "Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico" - }, - { - "author_name": "Guido Baselli", - "author_inst": "Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico" + "author_name": "Nina Trivedy Rogers", + "author_inst": "University College London (UCL)" }, { - "author_name": "Carla Della Ventura", - "author_inst": "University of Milan" + "author_name": "Naomi Waterlow", + "author_inst": "London School of Hygiene & Tropical Medicine" }, { - "author_name": "Elisa Erba", - "author_inst": "Fondazione IRCCS Ca' Granda" + "author_name": "Hannah E Brindle", + "author_inst": "London School of Hygiene & Tropical Medicine" }, { - "author_name": "Silvano Bosari", - "author_inst": "Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico" + "author_name": "Luisa Enria", + "author_inst": "University of Bath" }, { - "author_name": "Massimo Galli", - "author_inst": "University of Milan" + "author_name": "Rosalind M Eggo", + "author_inst": "London School of Hygiene & Tropical Medicine" }, { - "author_name": "Gianguglielmo Zehender", - "author_inst": "University of Milan" + "author_name": "Shelley Lees", + "author_inst": "London School of Hygiene & Tropical Medicine" }, { - "author_name": "Daniele Prati", - "author_inst": "Fondazione IRCCS Ca' Granda Ospedale Policlinico Milano" + "author_name": "Chrissy h Roberts", + "author_inst": "London School of Hygiene & Tropical Medicine" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1448079,29 +1448176,37 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.05.13.20099796", - "rel_title": "Adjusted fatality rates of COVID19 pandemic: a comparison across countries", + "rel_doi": "10.1101/2020.05.13.20099838", + "rel_title": "COVID-19 Healthcare Demand Projections: Arizona", "rel_date": "2020-05-16", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.13.20099796", - "rel_abs": "BackgroundA key impact measure of COVID-19 pandemic is the case fatality rate (CFR), but estimating it during an epidemic is challenging as the true number of cases may remain elusive.\n\nObjectiveTo estimate the CFR applying a delay-adjusted method across countries, exploring differences to simple methods and potential correlation to country level variables.\n\nMethodsSecondary analysis of publicly available data from countries with [≥]500 cases by April 30th. We calculated CFR adjusting for delay time from diagnosis to death and using simple methods for comparison. We performed a random effects meta-analysis to pooling CFRs for all countries and for those with high testing coverage and low positivity rate. We explored correlation of adjusted CFR with age structure and health care resources at country level.\n\nResultsWe included 107 countries and the Diamond Princess cruise-ship. The overall delay adjusted CFR was 2.8% (95%CI: 2.1 to 3.1) while naive CFR was 5.1% (95%CI: 4.1 to 6.2). In countries with high testing coverage/low positivity rate the pooled adjusted CFR was 2.1% (95%CI: 1.5 to 3.0), there was a correlation with age over 65 years ({beta} = 0.12; 95%CI: 0.06 to 0.18), but not with number of physician or critical care beds. Naive method underestimated the CFR of the CFR with a median of 1.3% across countries.\n\nConclusionOur best estimation of CFR across countries is 2% and varies according to the aged population size. Modelers and policy makers may consider these results to assess the impact of lockdowns or other mitigation policies.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.13.20099838", + "rel_abs": "Beginning in March 2020, the United States emerged as the global epicenter for COVID-19 cases. In the ensuing weeks, American jurisdictions attempted to manage disease spread on a regional basis using non-pharmaceutical interventions (i.e., social distancing), as uneven disease burden across the expansive geography of the United States exerted different implications for policy management in different regions. While Arizona policymakers relied initially on state-by-state national modeling projections from different groups outside of the state, we sought to create a state-specific model using a mathematical framework that ties disease surveillance with the future burden on Arizonas healthcare system. Our framework uses a compartmental system dynamics model using a SEIRD framework that accounts for multiple types of disease manifestations for the COVID-19 infection, as well as the observed time delay in epidemiological findings following public policy enactments. We use a bin initialization logic coupled with a fitting technique to construct projections for key metrics to guide public health policy, including exposures, infections, hospitalizations, and deaths under a variety of social reopening scenarios.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Carlos Canelo-Aybar", - "author_inst": "Cochrane Iberoamerican" + "author_name": "Esma Gel", + "author_inst": "Arizona State University" + }, + { + "author_name": "Megan Jehn", + "author_inst": "Arizona State University" }, { - "author_name": "Jessica Beltran", - "author_inst": "Cochrane Iberoamerica" + "author_name": "Timothy Lant", + "author_inst": "Arizona State University" }, { - "author_name": "Marilina Santero", - "author_inst": "Cochrane Iberoamerica" + "author_name": "Anna Muldoon", + "author_inst": "Arizona State University" }, { - "author_name": "Pablo Alonso-Coello", - "author_inst": "Cochrane Iberoamerica" + "author_name": "Trisalyn Nelson", + "author_inst": "Arizona State University" + }, + { + "author_name": "Heather M Ross", + "author_inst": "Arizona State University" } ], "version": "1", @@ -1449261,41 +1449366,65 @@ "category": "health policy" }, { - "rel_doi": "10.1101/2020.05.12.20099358", - "rel_title": "SARS-CoV-2 Detection in Istanbul Wastewater Treatment Plant Sludges", + "rel_doi": "10.1101/2020.05.12.20099739", + "rel_title": "Progression, recovery and fatality in patients with SARS-CoV-2 related pneumonia in Wuhan, China: a single-centered, retrospective, observational study", "rel_date": "2020-05-16", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.12.20099358", - "rel_abs": "Following the announcement of SARS-CoV-2 worldwide pandemic spread by WHO on March 11, 2020, wastewater based epidemiology received great attention in several countries: The Netherlands [Medama et al., 2020; K-Lodder et al., 2020], USA [Wu et al., 2020; Memudryi et al., 2020], Australia [Ahmed et al., 2020], France [Wurtzer et al., 2020], China [Wang et al., 2020], Spain [Randazzo et al., 2020; Walter et al., 2020], Italy (La Rosa et al., 2020; Rimoldi et al., 2020) and Israel [Or et al., 2020], performed analysis in wastewaters by using different virus concentration techniques. Turkey took its place among these countries on 7th of May, 2020 by reporting SARS-CoV-2 RT-qPCR levels at the inlet of seven (7) major municipal wastewater treatment plants (WWTPs) of Istanbul [Alpaslan Kocamemi et al., 2020], which is a metropole with 15.5 million inhabitants and a very high population density (2987 persons/km2) and having about 65 % of Covid-19 cases in Turkey. Sludges that are produced in WWTPs should be expected to contain SARS-CoV-2 virus as well. There has not yet been any study for the fate of SAR-CoV-2 in sludges generated from WWTPs. Knowledge about the existing of SARS-CoV-2 in sludge may be useful for handling the sludge during its dewatering, stabilizing and disposal processes. This information will also be valuable in case of sludges that are used as soil conditioners in agriculture or sent to landfill disposal.\n\nIn wastewater treatment plants, generally two different types of sludges are generated; primary sludge (PS) and waste activated sludge (WAS). PS forms during the settling of wastewater by gravity in the primary settling tanks. Little decomposition occurs during primary sludge formation. Since most of the inorganic part of the wastewater is removed in the earlier grit removal process, the PS consists of mainly organic material that settles. The PS is about 1-2 % solids by weight. In the biological treatment part of the WWTPs, the biomass that forms in the anaerobic, anoxic and oxic zones of the process is settled in final clarifiers by gravity and returned to the beginning of the biological process so that it is not washed off. The waste activated sludge (WAS) is the excess part of the biomass that grows in this secondary treatment process. It has to be removed from the process not to increase the mixed liquor suspended solids concentration (bacteria concentration) in the secondary process more than a fixed value. The WAS is about 0.6 - 0.9 % solids by weight.\n\nThis work aims to find whether SARS-CoV-19 is present in the PS and WAS before it is dewatered and sent to anaerobic or aerobic digester processes or to thermal drying operations.\n\nFor this purpose, on the 7th of May 2020, two (2) PS samples were collected from Ambarli and Tuzla WWTPs, seven (7) WAS samples were collected from Terkos, Ambarli, Atakoy I & II, Pasakoy II, Buyukcekmece and Tuzla I WWTPs. Polyethylene glycol 8000 (PEG 8000) adsorption [Wu et al., 2020] SARS-Cov-2 concentration method was used for SARS-CoV-2 concentration after optimization. [Alpaslan Kocamemi et al., 2020]. Real time RT-PCR diagnostic panel validated by US was used to quantify SARS-CoV-2 RNA in primary and waste activated sludge samples taken from WWTPs in Istanbul. All samples were tested positive. Titers of SARS-CoV-2 have been detected ranging copies between 1.17x104 to 4.02x104 per liter.\n\nO_LSTValue of the DataC_LSTO_LIThe dataset provides information about SARS-CoV-19 in primary and waste activated sludges generated in WWTPs.\nC_LIO_LIAs being the first study in the world, the dataset presented is expected to be beneficial in handling the sludge during its dewatering, stabilizing and disposal processes\nC_LI\n\nData DescriptionSARS-CoV-2 copy numbers per liter measured for sludge samples from WWTPs were summarized in Table 1 and shown in Figure 1 together with SARS-CoV-2 copy numbers observed in an earlier study [Alpaslan Kocamemi et al., 2020] in the influent of the WWTPs from which the sludge samples were taken.\n\nO_TBL View this table:\norg.highwire.dtl.DTLVardef@1647aa7org.highwire.dtl.DTLVardef@1b09df2org.highwire.dtl.DTLVardef@518f39org.highwire.dtl.DTLVardef@92061forg.highwire.dtl.DTLVardef@cfe4b2_HPS_FORMAT_FIGEXP M_TBL O_FLOATNOTable 1.C_FLOATNO O_TABLECAPTIONSARS-CoV-2 RT-qPCR results of sludges taken from Istanbul WWTPs\n\nC_TABLECAPTION C_TBL O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=129 SRC=\"FIGDIR/small/20099358v1_fig1.gif\" ALT=\"Figure 1\">\nView larger version (18K):\norg.highwire.dtl.DTLVardef@af6ccaorg.highwire.dtl.DTLVardef@10f7150org.highwire.dtl.DTLVardef@d83bbborg.highwire.dtl.DTLVardef@3980c8_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFigure 1.C_FLOATNO SAR-CoV-2 Levels in primary and waste activated sludges of Istanbul WWTPs.\n\nC_FIG To the best of our knowledge, no study has yet been reported the presence of SARS-CoV-2 in primary sludge (PS) and waste activated sludge (WAS) samples. Herein we report the results of SARS-CoV-2 presence in two (2) PS and seven (7) WAS samples from WWTPs in Istanbul. A total of nine (9) sludge samples were collected on the 7th May of 2020 and investigated for presence of SARS-CoV-2 with RT-qPCR methodology. SARS-CoV-2 genome was detected quantitatively from all samples. Sludge samples presented CT ranging from 33.5 to 35.8. Titers of SARS-CoV-2 have been detected ranging from 1.17x104 to 4.02x104 per liter.\n\nThe detected numbers of SARS-CoV-2 in PS samples were found similar to those observed for WAS samples. SARS-CoV-2 copy numbers detected in PS and WAS on 7th of May, 2020 are greater than the copy numbers observed in the influent of these WWTPs on 21st April, 2020 [Alpaslan Kocamemi, 2020]. By considering the fact that the number of cases reported for Istanbul on the 7th of May, 2020 is less than the cases reported for the 21st April, 2020, it may be concluded that SARS-CoV-2 concentrations are more in both primary and waste activated sludge.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.12.20099739", + "rel_abs": "ObjectivesTo determine the case fatality rates and death risk factors.\n\nDesignRetrospective case series.\n\nSettingA COVID-19 ward of a secondary Hospital in Wuhan, China.\n\nParticipantsConsecutively hospitalized COVID-19 patients between Jan 3, 2020 and Feb 27, 2020. Outcomes were followed up to discharge or death.\n\nResultsOf 121 patients included, 66 (54.6%) were males. The median age was 59 (IQR: 46 to 67) years, and hypertension (33 patients; 27.3%) the leading comorbidity. Lymphopenia (83 of 115 patients; 72.2%) frequently occurred and then normalized on day 4 (IQR: 3 to 6) after admission in the survivors, with lung lesion absorbed gradually on day 8 (IQR: 6 to10) after onset (33 of 57 patients; 57.9%). The real-time polymerase chain reaction (RT-PCR) assays for SARS-CoV-2 were positive in 78 (78/108; 72.2%) patients, and a false-negative RT-PCR occurred in 15 (13.9%) patients. Hypoxemia occurred in 94 (94/117; 80.3%) patients, and supplemental oxygen was given in 88 (72.7%) patients, and mon-invasive or invasive ventilation in 20 (16.5%) cases. Corticosteroid use might link to death. The case fatality rates were 4.4% (one of 23 patients), 29.3% (12/41), 22.8% (13/57) or 45% (9/20) for patients with moderate, severe, critical illness or on ventilator. The length of hospital stay was 14 (IQR: 10 to 20) days, and selfcare ability worsened in 21 patients (21/66; 31.8%) cases. Patients over 60 years were most likely to have poorer outcomes, and increasing in age by one-year increased risk for death by 18% (CI: 1.04-1.32).\n\nConclusionsIn management of patients with SARS-CoV-2 pneumonia, especially the elderly with hypertension, close monitoring and appropriate supportive treatment should be taken earlier and aggressively to prevent from developing severe or critical illness. Corticosteroid use might link to death. Repeated RT-PCR tests or novel detection methods for SARS-CoV-2 should be adopted to improve diagnostic efficiency.\n\nStrengths and limitations of this study[tpltrtarr] Eight case series reported mortality of 6.2% to 61.5% in COVID-19 patients in Wuhan, China. However, outcomes were inadequately followed and the risk factors for death unrevealed.\n[tpltrtarr]The case fatality rates were 4.4%, 29.3%, 22.8% or 45% for patients with moderate, severe, critical illness or on ventilator.\n[tpltrtarr]Age was the independent factor for death, and an increase by one-year increased risk for death by 18% (odds ratio: 1.18; 95% CI: 1.04-1.32; P < .01).\n[tpltrtarr]Case fatality rates calculated might be affected by small patient subset size and non-prospective data collection.", + "rel_num_authors": 12, "rel_authors": [ { - "author_name": "Bilge Alpaslan Kocamemi", - "author_inst": "Marmara University" + "author_name": "Hua Wang", + "author_inst": "Department of Intensive Care Medicine, Southern Medical University Zhujiang Hospital" }, { - "author_name": "Halil Kurt", - "author_inst": "Saglik Bilimleri University" + "author_name": "Yirong Lu", + "author_inst": "Department of Respiratory and Critical Care Medicine, Southern Medical University Zhujiang Hospital" }, { - "author_name": "Ahmet Sait", - "author_inst": "Ministry of Agriculture and Forestry, Republic of Turkey" + "author_name": "Qingquan Lv", + "author_inst": "Department of Medical Affairs, Hankou Hospital" }, { - "author_name": "Fahriye Sarac", - "author_inst": "Ministry of Agriculture and Forestry, Republic of Turkey" + "author_name": "Xiping Wu", + "author_inst": "Department of Respiratory and Critical Care Medicine, Southern Medical University Zhujiang Hospital" }, { - "author_name": "Ahmet Mete Saatci", - "author_inst": "Turkish Water Institute" + "author_name": "Tian Hu", + "author_inst": "Department of Respiratory Medicine, Hankou Hospital" }, { - "author_name": "Bekir Pakdemirli", - "author_inst": "Ministry of Agriculture and Forestry" + "author_name": "Kai Wang", + "author_inst": "Department of Intensive Care Medicine, Southern Medical University Zhujiang Hospital" + }, + { + "author_name": "Yumei Liu", + "author_inst": "Department of Respiratory Medicine, Hankou Hospital" + }, + { + "author_name": "Yuhai Hu", + "author_inst": "Department of Laboratory Medicine, Hankou Hospital" + }, + { + "author_name": "Lan Yu", + "author_inst": "Department of Radiology, Hankou Hospital" + }, + { + "author_name": "Hexuan Fei", + "author_inst": "Department of Radiology, Hankou Hospital" + }, + { + "author_name": "Zheng Ba", + "author_inst": "Department of Intensive Care Medicine, Southern Medical University Zhujiang Hospital" + }, + { + "author_name": "Xiaohua Lin", + "author_inst": "Department of Intensive Care Medicine, Southern Medical University Zhujiang Hospital" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1450931,37 +1451060,37 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.05.09.20096677", - "rel_title": "Depression and anxiety during 2019 coronavirus disease pandemic in Saudi Arabia: a cross-sectional study", + "rel_doi": "10.1101/2020.05.10.20093161", + "rel_title": "Psychological Distress during the COVID-19 pandemic in France: a national assessment of at-risk populations", "rel_date": "2020-05-15", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.09.20096677", - "rel_abs": "AimsThe emergence of the COVID-19 global pandemic, with a high transmission and mortality rate, has created an extraordinary crisis worldwide. Such an unusual situation may have an undesirable impact on the mental health of individuals which, in turn, may influence their outcomes. This study aimed to explore the influence of the COVID-19 pandemic on the psychological disposition of residents of the Kingdom of Saudi Arabia.\n\nMethodsA cross-sectional study using an online survey was conducted in Saudi Arabia between 27 March and 27 April 2020. The Patient Health Questionnaire (PHQ-9) and Generalised Anxiety Disorder-7 (GAD-7) were used to assess depression and anxiety. Logistic regression analysis was used to identify predictors of these.\n\nResultsA total of 2,081 individuals participated in the study. The prevalence of depression and anxiety among the study participants was 9.4% and 7.3%, respectively. Non-Saudi residents, individuals aged 50 years and above, divorced people, retired people, university students, and those with an income between 2,000 and 10,000 SR were at higher risk of developing depression. Saudi individuals, married people, the unemployed, and those with a high income (> 10,000 RS) were at higher risk of developing anxiety.\n\nConclusionWe found that there is a wide range of Saudi residents who are at higher risk of developing mental illness during the current COVID-19 pandemic. Policymakers and mental healthcare providers are advised to provide continuous monitoring of the psychological consequences during this pandemic and provide the required health support.\n\nWhat is already known about this subject?- The emergence of the COVID-19 global pandemic, with a high transmission and mortality rate, has created an extraordinary crisis worldwide.\n- The COVID-19 pandemic might have an undesirable impact on the mental health of individuals.\n\n\nWhat does this article add?- Depression and anxiety are common among the Saudi population.\n- A considerable proportion of the Saudi population is concerned about contracting COVID-19 or transmitting it to family members.\n- Unemployed individuals and university students are at higher risk of depression and anxiety.", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.10.20093161", + "rel_abs": "BackgroundMore than 2.5 billion people in the world are currently in lockdowns to limit the spread of the novel coronavirus disease 2019 (COVID-19). Psychological Distress (PD) and Post-Traumatic Stress Disorder have been reported after traumatic events, but the specific effect of pandemics is not well known.\n\nObjectivesThe aim of this study was to assess PD in France, a country where COVID-19 had such a dramatic impact that it required a country-wide lockdown.\n\nMethodsThis study was a survey conducted in France between 31 March 2020 and 7 April 2020. We recruited patients in 4 groups of chatbot users followed for breast cancer, asthma, depression and migraine. We used the Psychological Distress Index (PDI), a validated scale to measure PD during traumatic events, and correlated PD risk with patients characteristics in order to better identify the one who were the most at-risk.\n\nResultsThe study included 1771 participants. 91.25% (1616) were female with a mean age of 32.8 years (SD=13,71), 7.96% (141) were male with a mean age of 28.0 years (SD=8,14). In total, 38.06% (674) of the respondents had psychological distress (PDI [≥]15). An ANOVA analysis showed that sex (p=0.00132), unemployment (p=7.16x10-6) and depression (p=7.49x10-7) were significantly associated with a higher PDI score. Patients using their smartphone or computer more than one hour a day also had a higher PDI score (p=0.02588).\n\nConclusionPrevalence of PD in at-risk patients is high. These patients are also at increased risk to develop Post-Traumatic Stress Disorder. Specific steps should be implemented to monitor and prevent PD through dedicated mental health policies if we want to limit the public health impact of COVID-19 in time.", "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Hamad S Alyami", - "author_inst": "Department of Pharmaceutics, College of Pharmacy, Najran University, Najran, Saudi Arabia." + "author_name": "Benjamin Chaix", + "author_inst": "Hospital Gui de Chauliac, Montpellier" }, { - "author_name": "Abdallah Y Naser", - "author_inst": "Faculty of Pharmacy, Isra University, Amman, Jordan." + "author_name": "Guillaume Delamon", + "author_inst": "Wefight, Brain & Spine Institute, Paris" }, { - "author_name": "Eman Zmaily Dahmash", - "author_inst": "Faculty of Pharmacy, Isra University, Amman, Jordan." + "author_name": "Arthur Guillemasse", + "author_inst": "Wefight, Brain & Spine Institute, Paris" }, { - "author_name": "Mohammed H Alyami", - "author_inst": "Department of Pharmaceutics, College of Pharmacy, Najran University, Najran, Saudi Arabia." + "author_name": "Benoit Brouard", + "author_inst": "Wefight, Brain & Spine Institute, Paris" }, { - "author_name": "Musfer S Alyami", - "author_inst": "King Khalid University" + "author_name": "Jean-Emmanuel Bibault", + "author_inst": "Department of Radiation Oncology, Hopital Europeen Georges Pompidou, AP-HP, Paris" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "psychiatry and clinical psychology" }, @@ -1452580,31 +1452709,59 @@ "category": "geriatric medicine" }, { - "rel_doi": "10.1101/2020.05.11.20097725", - "rel_title": "A Systems Approach to Assess Transport and Diffusion of Hazardous Airborne Particles in a Large Surgical Suite: Potential Impacts on Viral Airborne Transmission", + "rel_doi": "10.1101/2020.05.11.20097790", + "rel_title": "COVID-19: a retrospective cohort study with focus on the over-80s and hospital-onset disease", "rel_date": "2020-05-15", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.11.20097725", - "rel_abs": "Airborne transmission of viruses, such as the coronavirus 2 (SARS-CoV-2), in hospital systems are under debate: it has been shown that transmission of SARS-CoV-2 virus goes beyond droplet dynamics that is limited to 3-6 feet, but it is unclear if the airborne viral load is significant enough to ensure transmission of the disease. Surgical smoke can act as a carrier for tissue particles, viruses, and bacteria. To quantify airborne transmission from a physical point of view, we consider surgical smoke produced by thermal destruction of tissue during the use of electrosurgical instruments as a marker of airborne particle diffusion-transportation. Surgical smoke plumes are also known to be dangerous for human health, especially to surgical staff who receive long-term exposure over the years. There are limited quantified metrics reported on long-term effects of surgical smoke on staffs health. The purpose of this paper is to provide a mathematical framework and experimental protocol to assess the transport and diffusion of hazardous airborne particles in every large operating room suite. Measurements from a network of air quality sensors gathered during a clinical study provide validation for the main part of the model. Overall, the model estimates staff exposure to airborne contamination from surgical smoke and biological material. To address the clinical implication over a long period of time, the systems approach is built upon previous work on multi-scale modeling of surgical flow in a large operating room suite and takes into account human behavior factors.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.11.20097790", + "rel_abs": "ObjectivesTo describe the presenting features and outcomes of patients with COVID-19 in a UK hospital, with a focus on those patients over 80 years and patients with hospital onset infection.\n\nDesignRetrospective cohort study with data extracted from the electronic records of patients with PCR-confirmed COVID-19 admitted to our institution.\n\nSettingSuburban general hospital serving Londons most populous borough.\n\nParticipantsThe first 450 inpatients admitted to our hospital with swab-confirmed COVID-19 infection.\n\nPrimary outcomeThe primary outcome measure was death during the index hospital admission.\n\nResultsThe median (IQR) age was 72 (56, 83), with 150 (33%) over 80 years old and 60% male. Presenting clinical and biochemical features were consistent with those reported elsewhere. The ethnic breakdown of patients admitted was similar to that of our underlying local population with no excess of BAME deaths. Inpatient mortality was high at 38%.\n\nPatients over 80 presented earlier in their disease course and were significantly less likely to present with the typical features of cough, breathlessness and fever. Cardiac co-morbidity and markers of cardiac dysfunction were more common, but not those of bacterial infection. Mortality was significantly higher in this group (60% vs 28%, p < 0.001).\n\n31 (7%) of patients were classified as having hospital-onset COVID-19 infection. The peak of hospital-onset infections occurred at the same time as the overall peak of admitted infections. Despite being older and more frail, the outcomes for this cohort were no worse.\n\nConclusionsInpatient mortality was high, especially among the over-80s, who were more likely to present atypically. The ethnic composition of our caseload was similar to the underlying population. While a significant number of patients presented with COVID-19 while already in hospital, their outcomes were no worse.\n\nStrengths and Limitations of this StudyO_LIThis study captures almost 80% of the admitted cases in our institution providing an accurate representation of the experiences of a London hospital during the early peak of the COVID-19 pandemic\nC_LIO_LIThe focus on the clinical and biochemical presentation and outcomes in patients over 80 years of age has a high relevance to UK population which is older and frailer than previously reported cohorts from elsewhere\nC_LIO_LIThe ethnicity of patients admitted to our hospital was similar to that of the underlying local population\nC_LIO_LITo our knowledge this study is the first to report the prevalence and outcomes of hospital onset disease in the UK\nC_LIO_LIThis study is subject to the usual limitations of retrospective observational research, including a proportion of missing data\nC_LI", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Marc Garbey", - "author_inst": "The Houston Methodist Research Institute" + "author_name": "Simon E Brill", + "author_inst": "Royal Free London NHS Foundation Trust" }, { - "author_name": "Guillaume Joerger", - "author_inst": "ORintelligence, GEPROVAS" + "author_name": "Hannah Jarvis", + "author_inst": "Royal Free London NHS Foundation Trust" }, { - "author_name": "Shannon Furr", - "author_inst": "ORintelligence" + "author_name": "Ezgi Ozcan", + "author_inst": "Royal Free London NHS Foundation Trust" + }, + { + "author_name": "Thomas Burns", + "author_inst": "Royal Free London NHS Foundation Trust" + }, + { + "author_name": "Rabia Warraich", + "author_inst": "Royal Free London NHS Foundation Trust" + }, + { + "author_name": "Lisa Amani", + "author_inst": "Royal Free London NHS Foundation Trust" + }, + { + "author_name": "Amina Jaffer", + "author_inst": "Royal Free London NHS Foundation Trust" + }, + { + "author_name": "Stephanie Paget", + "author_inst": "Royal Free London NHS Foundation Trust" + }, + { + "author_name": "Anand Sivaramakrishnan", + "author_inst": "Royal Free London NHS Foundation Trust" + }, + { + "author_name": "Dean Creer", + "author_inst": "Royal Free London NHS Foundation Trust" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "health systems and quality improvement" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2020.05.11.20096727", @@ -1454598,43 +1454755,23 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2020.05.14.095661", - "rel_title": "Growth factor receptor signaling inhibition prevents SARS-CoV-2 replication", + "rel_doi": "10.1101/2020.05.13.094839", + "rel_title": "Patient DNA cross-reactivity of CDC SARS-nCoV2 extraction control leads to potential false negative results", "rel_date": "2020-05-14", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.14.095661", - "rel_abs": "SARS-CoV-2 infections are rapidly spreading around the globe. The rapid development of therapies is of major importance. However, our lack of understanding of the molecular processes and host cell signaling events underlying SARS-CoV-2 infection hinder therapy development. We employed a SARS-CoV-2 infection system in permissible human cells to study signaling changes by phospho-proteomics. We identified viral protein phosphorylation and defined phosphorylation-driven host cell signaling changes upon infection. Growth factor receptor (GFR) signaling and downstream pathways were activated. Drug-protein network analyses revealed GFR signaling as key pathway targetable by approved drugs. Inhibition of GFR downstream signaling by five compounds prevented SARS-CoV-2 replication in cells, assessed by cytopathic effect, viral dsRNA production, and viral RNA release into the supernatant. This study describes host cell signaling events upon SARS-CoV-2 infection and reveals GFR signaling as central pathway essential for SARS-CoV-2 replication. It provides with novel strategies for COVID-19 treatment.", - "rel_num_authors": 6, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.13.094839", + "rel_abs": "Testing for RNA viruses such as SARS-CoV-2 requires careful handling of inherently labile RNA during sample collection, clinical processing, and molecular analysis. Tests must include fail-safe controls that affirmatively report the presence of intact RNA and demonstrate success of all steps of the assay. A result of \"no virus signal\" is insufficient for clinical interpretation: controls must also say \"The reaction worked as intended and would have found virus if present.\" Unfortunately, a widely used test specified by the US Centers for Disease Control and Prevention (CDC) incorporates a control that does not perform as intended and claimed. Detecting SARS-CoV-2 with this assay requires both intact RNA and successful reverse transcription. The CDC-specified control does not require either of these, due to its inability to differentiate human genomic DNA from reverse-transcribed RNA. Patient DNA is copurified from nasopharyngeal swabs during clinically-approved RNA extraction and is sufficient to return an \"extraction control success\" signal using the CDC design. As such, this assay fails-unsafe: truly positive patient samples return a false-negative result of \"no virus detected, control succeeded\" following any of several readily-encountered mishaps. This problem affects tens-of-millions of patients worth of shipped assays, but many of these flawed reagents have not yet been used. There is an opportunity to improve this important diagnostic tool. As demonstrated here, a re-designed transcript-specific control correctly monitors sample collection, extraction, reverse transcription, and qPCR detection. This approach can be rapidly implemented and will help reduce truly positive patients from being incorrectly given the all-clear.\n\nOne Sentence SummaryA widely-used COVID-19 diagnostic is mis-designed and generates false-negative results, dangerously confusing \"No\" with \"Dont know\" - but its fixable", + "rel_num_authors": 1, "rel_authors": [ { - "author_name": "Kevin Klann", - "author_inst": "Institute of Biochemistry II, Faculty of Medicine, Goethe University, Frankfurt am Main, Germany" - }, - { - "author_name": "Denisa Bojkova", - "author_inst": "Institute of Medical Virology, University Hospital Frankfurt, Frankfurt am Main, Germany" - }, - { - "author_name": "Georg Tascher", - "author_inst": "Institute of Biochemistry II, Faculty of Medicine, Goethe University, Frankfurt am Main, Germany" - }, - { - "author_name": "Sandra Ciesek", - "author_inst": "Institute of Medical Virology, University Hospital Frankfurt, Frankfurt am Main, Germany; German Centre for Infection Research (DZIF), External partner site Fra" - }, - { - "author_name": "Christian Muench", - "author_inst": "Institute of Biochemistry II, Faculty of Medicine, Goethe University, Frankfurt am Main, Germany; Frankfurt Cancer Institute, Frankfurt am Main, Germany; Cardio" - }, - { - "author_name": "Jindrich Cinatl", - "author_inst": "Institute of Medical Virology, University Hospital Frankfurt, Frankfurt am Main, Germany" + "author_name": "Adam P Rosebrock", + "author_inst": "Stony Brook Medicine" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "new results", - "category": "systems biology" + "category": "molecular biology" }, { "rel_doi": "10.1101/2020.05.13.093088", @@ -1456092,155 +1456229,23 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.05.12.20099879", - "rel_title": "Early Safety Indicators of COVID-19 ConvalescentPlasma in 5,000 Patients", + "rel_doi": "10.1101/2020.05.10.20097147", + "rel_title": "Hidden periods, duration and final size of COVID-19 pandemic", "rel_date": "2020-05-14", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.12.20099879", - "rel_abs": "BackgroundConvalescent plasma is the only antibody based therapy currently available for COVID-19 patients. It has robust historical precedence and sound biological plausibility. Although promising, convalescent plasma has not yet been shown to be safe as a treatment for COVID-19.\n\nMethodsThus, we analyzed key safety metrics after transfusion of ABO-compatible human COVID-19 convalescent plasma in 5,000 hospitalized adults with severe or life-threatening COVID-19, with 66% in the intensive care unit, as part of the US FDA Expanded Access Program for COVID-19 convalescent plasma.\n\nResultsThe incidence of all serious adverse events (SAEs) in the first four hours after transfusion was <1%, including mortality rate (0.3%). Of the 36 reported SAEs, there were 25 reported incidences of related SAEs, including mortality (n=4), transfusion-associated circulatory overload (TACO; n=7), transfusion-related acute lung injury (TRALI; n=11), and severe allergic transfusion reactions (n=3). However, only 2 (of 36) SAEs were judged as definitely related to the convalescent plasma transfusion by the treating physician. The seven-day mortality rate was 14.9%.\n\nConclusionGiven the deadly nature of COVID-19 and the large population of critically-ill patients included in these analyses, the mortality rate does not appear excessive. These early indicators suggest that transfusion of convalescent plasma is safe in hospitalized patients with COVID-19.\n\nBrief SummaryAfter transfusion of COVID-19 convalescent plasma in 5,000 patients, the incidence of serious adverse events was <1% and the seven-day incidence of mortality was 14.9%.", - "rel_num_authors": 34, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.10.20097147", + "rel_abs": "The SIR (susceptible-infected-removed) model, statistical approach for the parameter identification and the official WHO data about the confirmed cumulative number of cases were used to estimate the characteristics of COVID-19 pandemic in USA, Germany, UK, South Korea and in the world. Epidemic in every country has rather long hidden period before fist cases were confirmed. In particular, the pandemic began in China no later than October, 2019. If current trends continue, the end of the pandemic should be expected no earlier than March 2021, the global number of cases will exceed 5 million.", + "rel_num_authors": 1, "rel_authors": [ { - "author_name": "Michael Joyner", - "author_inst": "Mayo Clinic" - }, - { - "author_name": "R. Scott Wright", - "author_inst": "Mayo Clinic" - }, - { - "author_name": "DeLisa Fairweather", - "author_inst": "Mayo Clinic" - }, - { - "author_name": "Jonathon Senefeld", - "author_inst": "Mayo Clinic" - }, - { - "author_name": "Katelyn Bruno", - "author_inst": "Mayo Clinic" - }, - { - "author_name": "Stephen Klassen", - "author_inst": "Mayo Clinic" - }, - { - "author_name": "Rickey Carter", - "author_inst": "Mayo Clinic" - }, - { - "author_name": "Allan Klompas", - "author_inst": "Mayo Clinic" - }, - { - "author_name": "Chad Wiggins", - "author_inst": "Mayo Clinic" - }, - { - "author_name": "John RA Shepherd", - "author_inst": "Mayo Clinic" - }, - { - "author_name": "Robert Rea", - "author_inst": "Mayo Clinic" - }, - { - "author_name": "Emily Whelan", - "author_inst": "Mayo Clinic" - }, - { - "author_name": "Andrew Clayburn", - "author_inst": "Mayo Clinic" - }, - { - "author_name": "Matthew Spiegel", - "author_inst": "Mayo Clinic" - }, - { - "author_name": "Patrick Johnson", - "author_inst": "Mayo Clinic" - }, - { - "author_name": "Elizabeth Lesser", - "author_inst": "Mayo Clinic" - }, - { - "author_name": "Sarah Baker", - "author_inst": "Mayo Clinic" - }, - { - "author_name": "Kathryn Larson", - "author_inst": "Mayo Clinic" - }, - { - "author_name": "Juan Ripoll Sanz", - "author_inst": "Mayo Clinic" - }, - { - "author_name": "Kylie Andersen", - "author_inst": "Mayo Clinic" - }, - { - "author_name": "David Hodge", - "author_inst": "Mayo Clinic" - }, - { - "author_name": "Katie Kunze", - "author_inst": "Mayo Clinic" - }, - { - "author_name": "Matthew Buras", - "author_inst": "Mayo Clinic" - }, - { - "author_name": "Matthew Vogt", - "author_inst": "Mayo Clinic" - }, - { - "author_name": "Vitaly Herasevich", - "author_inst": "Mayo Clinic" - }, - { - "author_name": "Joshua Dennis", - "author_inst": "Mayo Clinic" - }, - { - "author_name": "Riley Regimbal", - "author_inst": "Mayo Clinic" - }, - { - "author_name": "Philippe Bauer", - "author_inst": "Mayo Clinic" - }, - { - "author_name": "Janis Blair", - "author_inst": "Mayo Clinic" - }, - { - "author_name": "Camille van Buskirk", - "author_inst": "Mayo Clinic" - }, - { - "author_name": "Jeffrey Winters", - "author_inst": "Mayo Clinic" - }, - { - "author_name": "James Stubbs", - "author_inst": "Mayo Clinic" - }, - { - "author_name": "Nigel Paneth", - "author_inst": "Michigan State University" - }, - { - "author_name": "Arturo Casadevall", - "author_inst": "Johns Hopkins University" + "author_name": "Igor Nesteruk", + "author_inst": "Institute of Hydromechanics National Academy of sciences of Ukraine" } ], "version": "1", "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2020.05.10.20097550", @@ -1457634,43 +1457639,47 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.05.08.20095893", - "rel_title": "Association of Vitamin D Deficiency and Treatment with COVID-19 Incidence", + "rel_doi": "10.1101/2020.05.11.20092114", + "rel_title": "Systemic hypoferraemia and severity of hypoxaemic respiratory failure in COVID-19", "rel_date": "2020-05-13", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.08.20095893", - "rel_abs": "ImportanceVitamin D treatment has been found to decrease incidence of viral respiratory tract infection, especially in vitamin D deficiency. It is unknown whether COVID-19 incidence is associated with vitamin D deficiency and treatment.\n\nObjectiveTo examine whether vitamin D deficiency and treatment are associated with testing positive for COVID-19.\n\nDesignRetrospective cohort study\n\nSettingUniversity of Chicago Medicine\n\nParticipantsPatients tested for COVID-19 from 3/3/2020-4/10/2020. Vitamin D deficiency was defined by the most recent 25-hydroxycholecalciferol <20ng/ml or 1,25-dihydroxycholecalciferol <18pg/ml within 1 year before COVID-19 testing. Treatment was defined by the most recent vitamin D type and dose, and treatment changes between the time of the most recent vitamin D level and time of COVID-19 testing. Vitamin D deficiency and treatment changes were combined to categorize vitamin D status at the time of COVID-19 testing as likely deficient (last-level-deficient/treatment-not-increased), likely sufficient(last-level-not-deficient/treatment-not-decreased), or uncertain deficiency(last-level-deficient/treatment-increased or last-level-not-deficient/treatment-decreased).\n\nMain Outcomes and MeasuresThe main outcome was testing positive for COVID-19. Multivariable analysis tested whether the most recent vitamin D level and treatment changes after that level were associated with testing positive for COVID-19 controlling for demographic and comorbidity indicators. Bivariate analyses of associations of treatment with vitamin D deficiency and COVID-19 were performed.\n\nResultsAmong 4,314 patients tested for COVID-19, 499 had a vitamin D level in the year before testing. Vitamin D status at the time of COVID-19 testing was categorized as likely deficient for 127(25%) patients, likely sufficient for 291(58%) patients, and uncertain for 81(16%) patients. In multivariate analysis, testing positive for COVID-19 was associated with increasing age(RR(age<50)=1.05,p<0.021;RR(age[≥]50)=1.02,p<0.064)), non-white race(RR=2.54,p<0.01) and being likely vitamin D deficient (deficient/treatment-not-increased:RR=1.77,p<0.02) as compared to likely vitamin D sufficient(not-deficient/treatment-not-decreased), with predicted COVID-19 rates in the vitamin D deficient group of 21.6%(95%CI[14.0%-29.2%]) versus 12.2%(95%CI[8.9%-15.4%]) in the vitamin D sufficient group. Vitamin D deficiency declined with increasing vitamin D dose, especially of vitamin D3. Vitamin D dose was not significantly associated with testing positive for COVID-19.\n\nConclusions and RelevanceVitamin D deficiency that is not sufficiently treated is associated with COVID-19 risk. Testing and treatment for vitamin D deficiency to address COVID-19 warrant aggressive pursuit and study.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.11.20092114", + "rel_abs": "Coronavirus disease 2019 (COVID-19) mortality is associated with hypoxaemia, multiorgan failure, and thromboinflammation. However severity of disease varies considerably and understanding physiological changes that may link to poor outcomes is important. Although increased serum ferritin has been observed in COVID-19 patients consistent with inflammation, other iron parameters have not been examined to our knowledge. Because iron is required for immunity and oxygen utilisation, and dysregulated iron homeostasis has been observed in COPD, we investigated serum iron concentrations in 30 patients with COVID-19 requiring ICU admission. All patients had low serum iron but patients with severe hypoxemic respiratory failure had more profound hypoferraemia. The area under the curve for receiver operating characteristic curves for serum iron to identify severe hypoxemia was 0{middle dot}95; the optimal Youden Index for distinguishing between severe and non-severe hypoxemia was a serum iron concentration of 2{middle dot}9 mol/L. By linear regression, serum iron was associated with lymphocyte count and PaO2/FiO2. In conclusion, profound hypoferraemia identifies COVID-19 patients with severe hypoxaemia. Serum iron is a simple biomarker that could be usefully employed to stratify patients and monitor disease. Severe hypoferraemia may plausibly impair critical iron-dependent processes such as lymphocyte responses and hypoxia sensing, contributing to pathology, and is potentially treatable.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "David O Meltzer", - "author_inst": "The University of Chicago" + "author_name": "Akshay Shah", + "author_inst": "University of Oxford" }, { - "author_name": "Thomas J Best", - "author_inst": "The University of Chicago" + "author_name": "Joe Frost", + "author_inst": "University of Oxford" }, { - "author_name": "Hui Zhang", - "author_inst": "The University of Chicago" + "author_name": "Louise Aaron", + "author_inst": "Oxford University Hospitals NHS Foundation Trust" }, { - "author_name": "Tamara Vokes", - "author_inst": "The University of Chicago" + "author_name": "Killian Donovan", + "author_inst": "Oxford University Hospitals NHS Foundation Trust" }, { - "author_name": "Vineet Arora", - "author_inst": "The University of Chicago" + "author_name": "Stuart McKechnie", + "author_inst": "Oxford University Hospitals NHS Foundation Trust" }, { - "author_name": "Julian Solway", - "author_inst": "The University of Chicago" + "author_name": "Simon Stanworth", + "author_inst": "Oxford University Hospitals NHS Foundation Trust" + }, + { + "author_name": "Hal Drakesmith", + "author_inst": "University of Oxford" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "intensive care and critical care medicine" }, { "rel_doi": "10.1101/2020.05.09.20096768", @@ -1458908,79 +1458917,51 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2020.05.12.092387", - "rel_title": "Comparison of SARS-CoV-2 Indirect and Direct Detection Methods", + "rel_doi": "10.1101/2020.05.13.093609", + "rel_title": "Evaluation Of SYBR Green Real Time PCR For Detecting SARS-CoV-2 From Clinical Samples", "rel_date": "2020-05-13", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.12.092387", - "rel_abs": "The COVID-19 pandemic caused by the SARS-CoV-2 virus has placed extensive strain on RNA isolation and RT-qPCR reagents. Rapid development of new test kits has helped to alleviate these shortages. However, comparisons of these new detection systems are largely lacking. Here, we compare indirect methods that require RNA extraction, and direct RT-qPCR on patient samples. For RNA isolation we compared four different companies (Qiagen, Invitrogen, BGI and Norgen Biotek). For detection we compared two recently developed Taqman-based modules (BGI and Norgen Biotek), a SYBR green-based approach (NEB Luna Universal One-Step Kit) with published and newly-developed primers, and clinical results (Seegene STARMag RNA extraction system and Allplex 2019-nCoV RT-qPCR assay). Most RNA isolation procedures performed similarly, and while all RT-qPCR modules effectively detected purified viral RNA, the BGI system proved most sensitive, generating comparable results to clinical diagnostic data, and identifying samples ranging from 65 copies - 2.1x105 copies of viral Orf1ab/l. However, the BGI detection system is [~]4x more expensive than other options tested here. With direct RT-qPCR we found that simply adding RNase inhibitor greatly improved sensitivity, without need for any other treatments (e.g. lysis buffers or boiling). The best direct methods were [~]10 fold less sensitive than indirect methods, but reduce sample handling, as well as assay time and cost. These studies will help guide the selection of COVID-19 detection systems and provide a framework for the comparison of additional systems.", - "rel_num_authors": 15, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.13.093609", + "rel_abs": "The pandemic caused by SARS-CoV-2 has triggered an extraordinary collapse of healthcare systems and hundred thousand of deaths worldwide. Following the declaration of the outbreak as a Public Health Emergency of International Concern by the World Health Organization (WHO) on January 30th, 2020, it has become imperative to develop diagnostic tools to reliably detect the virus in infected patients. Several methods based on real time reverse transcription polymerase chain reaction (RT-qPCR) for the detection of SARS-CoV-2 genomic RNA have been developed. In addition, these methods have been recommended by the WHO for laboratory diagnosis. Since all these protocols are based on the use of fluorogenic probes and one-step reagents (cDNA synthesis followed by PCR amplification in the same tube), these techniques can be difficult to perform given the limited supply of reagents in low and middle income countries. In the interest of economy, time and availability of chemicals and consumables, the SYBR Green-based detection was implemented to establish a convenient assay. Therefore, we adapted one of WHO recommended Taqman-based one-step real time PCR protocols (from the University of Hong Kong) to SYBR Green. Our results suggest that SYBR-Green detection represents a reliable cost-effective alternative to increase the testing capacity.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Rod Bremner", - "author_inst": "Lunefeld Tanenbaum Research Institute" - }, - { - "author_name": "Joel D Pearson", - "author_inst": "Lunenfeld Tanenbaum Research Institute" - }, - { - "author_name": "Daniel Trcka", - "author_inst": "Lunenfeld Tanenbaum Research Institute" - }, - { - "author_name": "Sharon J Hyduk", - "author_inst": "Toronto General Hospital Research Institute, University Health Network" - }, - { - "author_name": "Marie-Ming Aynaud", - "author_inst": "Lunenfeld Tanenbaum Research Institute" - }, - { - "author_name": "J. Javier Hernandez", - "author_inst": "Lunenfeld Tanenbaum Research Institute" - }, - { - "author_name": "Filippos Peidis", - "author_inst": "Lunenfeld Tanenbaum Research Institute" - }, - { - "author_name": "Suying Lu", - "author_inst": "Lunenfeld Tanenbaum Research Institute" + "author_name": "Alvaro Fajardo", + "author_inst": "Laboratorio de Virologia Molecular, Centro de Investigaciones Nucleares, Facultad de Ciencias, Universidad de la Republica, Montevideo, Uruguay; Laboratorio de " }, { - "author_name": "Kin Chan", - "author_inst": "Lunenfeld Tanenbaum Research Institute" + "author_name": "Marianoel Pereira-Gomez", + "author_inst": "Laboratorio de Virologia Molecular, Centro de Investigaciones Nucleares, Facultad de Ciencias, Universidad de la Republica, Montevideo, Uruguay; Laboratorio de " }, { - "author_name": "Jim Woodgett", - "author_inst": "Lunenfeld Tanenbaum Research Institute" + "author_name": "Natalia Echeverria", + "author_inst": "Laboratorio de Virologia Molecular, Centro de Investigaciones Nucleares, Facultad de Ciencias, Universidad de la Republica, Montevideo, Uruguay; Laboratorio de " }, { - "author_name": "Tony Mazzulli", - "author_inst": "Department of Microbiology, Sinai Health System/University Health Network" + "author_name": "Fernando Lopez-Tort", + "author_inst": "Laboratorio de Virologia Molecular, Sede Salto, Centro Universitario Regional Litoral Norte, Universidad de la Republica, Salto, Uruguay." }, { - "author_name": "Liliana Attisano", - "author_inst": "University of Toronto" + "author_name": "Paula Perbolianachis", + "author_inst": "Laboratorio de Virologia Molecular, Centro de Investigaciones Nucleares, Facultad de Ciencias, Universidad de la Republica, Montevideo, Uruguay; Laboratorio de " }, { - "author_name": "Laurence Pelletier", - "author_inst": "Lunenfeld Research Institute" + "author_name": "Fabian Aldunate", + "author_inst": "Laboratorio de Virologia Molecular, Centro de Investigaciones Nucleares, Facultad de Ciencias, Universidad de la Republica, Montevideo, Uruguay; Laboratorio de " }, { - "author_name": "Myron I Cybulsky", - "author_inst": "Toronto General Hospital Research Institute, University Health Network" + "author_name": "Pilar Moreno", + "author_inst": "Laboratorio de Virologia Molecular, Centro de Investigaciones Nucleares, Facultad de Ciencias, Universidad de la Republica, Montevideo, Uruguay; Laboratorio de " }, { - "author_name": "Jeffrey L Wrana", - "author_inst": "Samuel Lunenfeld Research Inst." + "author_name": "Gonzalo Moratorio", + "author_inst": "Laboratorio de Virologia Molecular, Centro de Investigaciones Nucleares, Facultad de Ciencias, Universidad de la Republica, Montevideo, Uruguay; Laboratorio de " } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by_nc_nd", "type": "new results", - "category": "microbiology" + "category": "molecular biology" }, { "rel_doi": "10.1101/2020.05.12.091462", @@ -1460390,25 +1460371,29 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.05.08.20094953", - "rel_title": "Predicting Long-term Evolution of COVID-19 by On-going Data using Bayesian Susceptible-Infected-Removed Model", + "rel_doi": "10.1101/2020.05.08.20095489", + "rel_title": "COVID-19: Predictive Mathematical Models for the Number of Deaths in South Korea, Italy, Spain, France, UK, Germany, and USA", "rel_date": "2020-05-12", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.08.20094953", - "rel_abs": "In this study, we propose a novel statistical method to predict a long-term epidemic evolution based on a on-going data. We developed a Bayesian framework for the Susceptible-Infected-Removed model (Bayesian SIR), and estimated its underlying parameters based on day-by-day timeseries of the cumulative number of infectious individuals. The new Baysian framework extends the deterministic SIR model to a probabilistic form, which provides an accurate estimation of the underlying system by a short and noisy data. We applied it to the data reported on the Coronavirus Disease 2019 (COVID-19), and made a month long prediction on its evolution. Our simulated test using past timeseries to predict the current data gives a reasonable reliablity of the proposed method. Our analysis of the current data detected and warned a rising trend in the countries in Central Asia, Middle East, and South America, while United States or European countries, which have already experienced large numbers of infected cases, are predicted to slow down in the increase.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.08.20095489", + "rel_abs": "We have recently introduced two novel mathematical models for characterizing the dynamics of the cumulative number of individuals in a given country reported to be infected with COVID-19. Here we show that these models can also be used for determining the time-evolution of the associated number of deaths. In particular, using data up to around the time that the rate of deaths reaches a maximum, these models provide estimates for the time that a plateau will be reached signifying that the epidemic is approaching its end, as well as for the cumulative number of deaths at that time. The plateau is defined to occur when the rate of deaths is 5% of the maximum rate. Results are presented for South Korea, Italy, Spain, France, UK, Germany, and USA. The number of COVID-19 deaths in other counties can be analyzed similarly.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Shohei Hidaka", - "author_inst": "Japan Advanced Institute of Science and Technology" + "author_name": "Athanasios S Fokas", + "author_inst": "University of Cambridge" + }, + { + "author_name": "Nikolaos Dikaios", + "author_inst": "University of Surrey" }, { - "author_name": "Takuma Torii", - "author_inst": "Japan Advanced Institute of Science and Technology" + "author_name": "George A Kastis", + "author_inst": "Academy of Athens" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1461971,57 +1461956,77 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.05.08.20037556", - "rel_title": "A Research on the Results of Viral Nucleic Acid Tests and CT Imaging Variation of Patients with COVID-19", + "rel_doi": "10.1101/2020.05.05.20092064", + "rel_title": "Evaluating the serological status of COVID-19 patients using an indirect immunofluorescent assay, France.", "rel_date": "2020-05-12", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.08.20037556", - "rel_abs": "BackgroundCoronavirus disease 2019 (COVID-19) has become a global health problem. We aim to investigate the changes in the results of viral nucleic acid tests on pharyngeal swabs and feces of patients with COVID-19 and CT imaging of lungs as the disease progresses.\n\nMethodsSeven patients with COVID-19 in the third affiliated hospital of Sun Yat-sen University Yuedong Hospital were retrospectively enrolled with clinical features, including imaging staging, and performance characteristics of viral nucleic acid test results of pharyngeal swabs and feces. The dynamic changes of these features were observed during hospitalization, and therapeutic effect and prognosis of patients were evaluated.\n\nResultsThe results of seven cases with COVID-19 were positive for viral nucleic acid tests on pharyngeal swabs early after the onset of symptoms, and then turned negative; while the results of viral nucleic acid tests on feces were persistently positive in the mid-term clinical treatment and recovery period. And the viral nucleic acid test results were capricious in three cases. Pulmonary CT imaging showed characteristic changes in early, advanced and recovery phases.\n\nConclusionThe application of viral nucleic acid detection and pulmonary CT imaging can be used for screening of suspected cases. Fecal nucleic acid test should be recommended as the reference of discharge standard, in order to minimize the risk of transmission from digestive tract.", - "rel_num_authors": 10, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.05.20092064", + "rel_abs": "An indirect immunofluorescent assay was developed in order to assess the serological status of 888 RT-PCR-confirmed COVID-19 patients (1,302 serum samples) and controls in Marseille, France. Incorporating an inactivated clinical SARS CoV-2 isolate as the antigen, the specificity of the assay was measured as 100% for IgA titre [≥] 1:200; 98.6% for IgM titre [≥] 1:200; and 96.3% for IgG titre [≥] 1:100 after testing a series of negative controls as well as 150 serums collected from patients with non-SARS-CoV-2 Coronavirus infection, non-Coronavirus pneumonia and infections known to elicit false-positive serology. Seroprevalence was then measured at 3% before a five-day evolution up to 47% after more than 15 days of evolution. We observed that the seroprevalence as well as the titre of specific antibodies were both significantly higher in patients with a poor clinical outcome than in patients with a favourable evolution. These data, which have to be integrated into the ongoing understanding of the immunological phase of the infection, suggest that serotherapy may not be a therapeutic option in patients with severe COVID-19 infection. The IFA assay reported here is useful for monitoring SARS-CoV-2 exposure at the individual and population levels.", + "rel_num_authors": 15, "rel_authors": [ { - "author_name": "Meng Xu", - "author_inst": "the Third Affiliated Hospital of Sun Yat-sen University Yuedong Hospital" + "author_name": "Sophie EDOUARD", + "author_inst": "IHU" }, { - "author_name": "Xun Liu", - "author_inst": "the Third Affiliated Hospital of Sun Yat-sen University" + "author_name": "Philippe COLSON", + "author_inst": "IHU" }, { - "author_name": "Chuhong Su", - "author_inst": "Southern Medical University, Guangzhou, China" + "author_name": "Clea melenotte", + "author_inst": "IHU" }, { - "author_name": "Yuping Zeng", - "author_inst": "the Third Affiliated Hospital of Sun Yat-sen University Yuedong Hospital, Meizhou, China;" + "author_name": "Fabrizio De Pinto", + "author_inst": "IHU" }, { - "author_name": "Jinqian Zhang", - "author_inst": "the Third Affiliated Hospital of Sun Yat-sen University Yuedong Hospital, Meizhou, China" + "author_name": "Laurence THOMAS", + "author_inst": "IHU" }, { - "author_name": "Xuwen Li", - "author_inst": "the Third Affiliated Hospital of Sun Yat-sen University Yuedong Hospital, Meizhou, China" + "author_name": "Bernard LA SCOLA", + "author_inst": "IHU" }, { - "author_name": "Guirong Liu", - "author_inst": "The Third Affiliated Hospital of Sun Yat-sen University Yuedong Hospital, Meizhou, China" + "author_name": "Matthieu MILLION", + "author_inst": "IHU" }, { - "author_name": "Jinjun Xie", - "author_inst": "The Third Affiliated Hospital of Sun Yat-sen University Yuedong Hospital, Meizhou, China" + "author_name": "Herve TISSOT DUPONT", + "author_inst": "IHU" }, { - "author_name": "Hongyong Liu", - "author_inst": "the Third Affiliated Hospital of Sun Yat-sen University Yuedong Hospital, Meizhou, China" + "author_name": "Philippe GAUTRET", + "author_inst": "IHU" }, { - "author_name": "Yusheng Jie", - "author_inst": "the third affiliated hospital of Sun Yat-sen university" + "author_name": "Andreas STEIN", + "author_inst": "IHU" + }, + { + "author_name": "Philippe BROUQUI", + "author_inst": "IHU" + }, + { + "author_name": "Philippe PAROLA", + "author_inst": "IHU" + }, + { + "author_name": "Jean-Christophe LAGIER", + "author_inst": "IHU" + }, + { + "author_name": "Didier RAOULT", + "author_inst": "IHU" + }, + { + "author_name": "Michel Drancourt", + "author_inst": "Aix Marseille Universite-IHU Mediterranee Infection" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1463493,41 +1463498,45 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.05.07.20092353", - "rel_title": "Social Distancing is Effective at Mitigating COVID-19 Transmission in the United States", + "rel_doi": "10.1101/2020.05.04.20091272", + "rel_title": "Spread of Covid-19 in the United States is controlled", "rel_date": "2020-05-11", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.07.20092353", - "rel_abs": "COVID-19 is present in every state and over 90 percent of all counties in the United States. Decentralized government efforts to reduce spread, combined with the complex dynamics of human mobility and the variable intensity of local outbreaks makes assessing the effect of large-scale social distancing on COVID-19 transmission in the U.S.a challenge. We generate a novel metric to represent social distancing behavior derived from mobile phone data and examine its relationship with COVID-19 case reports at the county level. Our analysis reveals that social distancing is strongly correlated with decreased COVID-19 case growth rates for the 25 most affected counties in the United States, with a lag period consistent with the incubation time of SARS-CoV-2. We also demonstrate evidence that social distancing was already under way in many U.S. counties before state or local-level policies were implemented. This study strongly supports social distancing as an effective way to mitigate COVID-19 transmission in the United States.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.04.20091272", + "rel_abs": "As of May 1, 2020, the number of cases of Covid-19 in the US passed 1,062,446, interventions to slow down the spread of Covid-19 curtailed most social activities. Meanwhile, an economic crisis and resistance to the strict intervention measures are rising. Some researchers proposed intermittent social distancing that may drive the outbreak of Covid-19 into 2022. Questions arise about whether we should maintain or relax quarantine measures. We developed novel artificial intelligence and causal inference integrated methods for real-time prediction and control of nonlinear epidemic systems. We estimated that the peak time of the Covid-19 in the US would be April 24, 2020 and its outbreak in the US will be over by the end of July and reach 1,551,901 cases. We evaluated the impact of relaxing the current interventions for reopening economy on the spread of Covid-19. We provide tools for balancing the risks of workers and reopening economy.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Hamada Badr", - "author_inst": "Johns Hopkins University" + "author_name": "Zixin Hu", + "author_inst": "Fudan University" }, { - "author_name": "Hongru Du", - "author_inst": "Johns Hopkins University" + "author_name": "Qiyang Ge", + "author_inst": "Fudan University" }, { - "author_name": "Max Marshall", - "author_inst": "Johns Hopkins University" + "author_name": "Shudi Li", + "author_inst": "Health Science Center at Houston" }, { - "author_name": "Ensheng Dong", - "author_inst": "Johns Hopkins University" + "author_name": "Tao Xu", + "author_inst": "Health Science Center at Houston" }, { - "author_name": "Marietta Squire", - "author_inst": "Johns Hopkins University" + "author_name": "Eric Boerwinkle", + "author_inst": "Health Science Center at Houston" }, { - "author_name": "Lauren Marie Gardner", - "author_inst": "Johns Hopkins University" + "author_name": "Li Jin", + "author_inst": "Fudan University" + }, + { + "author_name": "Momiao Xiong", + "author_inst": "Health Science Center at Houston" } ], "version": "1", - "license": "cc_no", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1465191,83 +1465200,115 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2020.05.07.20094102", - "rel_title": "Observer agreement and clinical significance of chest CT reporting in patients suspected of COVID-19", + "rel_doi": "10.1101/2020.05.08.20093393", + "rel_title": "Voices from the frontline: findings from a thematic analysis of a rapid online global survey of maternal and newborn health professionals facing the COVID-19 pandemic", "rel_date": "2020-05-11", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.07.20094102", - "rel_abs": "ObjectivesTo assess inter-observer agreement and clinical significance of chest CT reporting in patients suspected of COVID-19.\n\nMethodsFrom 16th to 24th March 2020, 241 consecutive patients addressed to hospital for COVID-19 suspicion had both chest CT and SARS-CoV-2 RT-PCR. Eight observers (2 thoracic and 2 general senior radiologists, 2 junior radiologists and 2 emergency physicians) retrospectively categorized each CT into one out of 3 categories (evocative, compatible for COVID-19 pneumonia, and not evocative or normal). Observer agreement for categorization between all readers and pairs of readers with similar experience was evaluated with the Kappa coefficient. The results of a consensus categorization were correlated to RT-PCR.\n\nResultsObserver agreement across the 3 categories was good between all readers ({kappa} value 0.68 95%CI 0.67-0.70) and good to very good between pairs of readers (0.64-0.85). It was very good ({kappa} 0.81 95%CI 0.79-0.83), fair ({kappa} 0.32 95%CI 0.29-0.34) and good ({kappa} 0.74 95%CI 0.71-0.76) for the categories evocative, compatible and not evocative or normal, respectively. RT-PCR was positive in 97%, 50% and 27% of cases classified in the respective categories. Observer agreement was lower (p=0.045) and RT-PCR positive cases were less frequently categorized evocative in presence of an underlying pulmonary disease (p<0.001).\n\nConclusionInter-observer agreement for chest CT reporting using categorization of findings is good in patients suspected of COVID-19. Among patients considered for hospitalization in an epidemic context, CT categorized evocative is highly predictive of COVID-19, whereas the predictive value of CT decreases between the categories compatible and not evocative.\n\nKey resultsO_LIInter-observer agreement for chest CT reporting into categories is good in patients suspected of COVID-19\nC_LIO_LIChest CT can participate in estimating the likelihood of COVID-19 in patients presenting to hospital during the outbreak, CT categorized <> being highly predictive of the disease whereas up to a quarter of patients with CT <> had a positive RT-PCR in our study.\nC_LIO_LIObserver agreement is lower and CTs of positive RT-PCR cases less frequently \"evocative\" in presence of an underlying pulmonary disease\nC_LI", - "rel_num_authors": 16, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.08.20093393", + "rel_abs": "ObjectiveTo prospectively document experiences of frontline maternal and newborn healthcare providers during the COVID-19 pandemic.\n\nDesignCross-sectional study via an online survey disseminated through professional networks and social media in 12 languages. We analysed responses using descriptive statistics and qualitative thematic analysis disaggregating by low- and middle-income countries (LMICs) and high-income countries (HICs).\n\nSetting81 countries, between March 24 and April 10, 2020.\n\nParticipants714 maternal and newborn healthcare providers.\n\nMain outcome measuresPreparedness for and response to COVID-19, experiences of health workers providing care to women and newborns, and adaptations to 17 outpatient and inpatient care processes during the pandemic.\n\nResultsOnly one third of respondents received training on COVID-19 from their health facility and nearly all searched for information themselves. Half of respondents in LMICs received updated guidelines for care provision compared with 82% in HICs. Overall, only 47% of participants in LMICs, and 69% in HICs felt mostly or completely knowledgeable in how to care for COVID-19 maternity patients. Facility-level responses to COVID-19 (signage, screening, testing, and isolation rooms) were more common in HICs than LMICs. Globally, 90% of respondents reported somewhat or substantially higher levels of stress. There was a widespread perception of reduced use of routine maternity care services, and of modification in care processes, some of which were not evidence-based.\n\nConclusionsSubstantial knowledge gaps exist in guidance on management of maternity cases with or without COVID-19. Formal information sharing channels for providers must be established and mental health support provided. Surveys of maternity care providers can help track the situation, capture innovations, and support rapid development of effective responses.\n\nKey MessagesO_LSTWhat is already knownC_LSTO_LIIn addition to lack of healthcare worker protection, staffing shortages, heightened risk of nosocomial transmission and decreased healthcare use described in previous infectious disease outbreaks, maternal and newborn care during the COVID-19 pandemic has also been affected by large-scale lockdowns/curfews.\nC_LIO_LIThe two studies assessing the indirect effects of COVID-19 on maternal and child health have used models to estimate mortality impacts.\nC_LIO_LIExperiences of frontline health professionals providing maternal and newborn care during the COVID-19 pandemic have not been empirically documented to date.\nC_LI\n\nO_LSTWhat this study addsC_LSTO_LIRespondents in high-income countries more commonly reported available/updated guidelines, access to COVID-19 testing, and dedicated isolation rooms for confirmed/suspected COVID-19 maternity patients.\nC_LIO_LILevels of stress increased among health professionals globally, including due to changed working hours, difficulties in reaching health facilities, and staff shortages.\nC_LIO_LIHealthcare providers were worried about the impact of rapidly changing care practices on health outcomes: reduced access to antenatal care, fewer outpatient visits, shorter length-of-stay in facilities after birth, banning birth companions, separating newborns from COVID-19 positive mothers, and postponing routine immunisations.\nC_LIO_LICOVID-19 illustrates the susceptibility of maternity care services to emergencies, including by reversing hard-won gains in healthcare utilisation and use of evidence-based practices. These rapid findings can inform countries of the main issues emerging and help develop effective responses.\nC_LI", + "rel_num_authors": 24, "rel_authors": [ { - "author_name": "Marie-Pierre Debray", - "author_inst": "APHP, Hopital Bichat, Paris, France" + "author_name": "Aline T Semaan", + "author_inst": "Department of Public Health, Institute of Tropical Medicine, Antwerp Belgium and Center for Research on Population and Health, Faculty of Health Sciences, Ameri" }, { - "author_name": "Helena Tarabay", - "author_inst": "APHP, Hopital Bichat, Paris, France" + "author_name": "Constance Audet", + "author_inst": "Department of Public Health, Institute of Tropical Medicine, Antwerp Belgium" }, { - "author_name": "Lisa Males", - "author_inst": "APHP, Hopital Bichat, Paris, France" + "author_name": "Elise Huysmans", + "author_inst": "Department of Public Health, Institute of Tropical Medicine, Antwerp Belgium" }, { - "author_name": "Nisrine Chalhoub", - "author_inst": "APHP, Hopital Bichat, Paris, France" + "author_name": "Bosede B Afolabi", + "author_inst": "Department of Obstetrics and Gynaecology, College of Medicine, University of Lagos, Lagos, Nigeria" }, { - "author_name": "Elyas Mahdjoub", - "author_inst": "APHP, Hopital Bichat, Paris, France" + "author_name": "Bouchra Assarag", + "author_inst": "National School of Public Health, Ministry of Health, Morocco" }, { - "author_name": "Thomas Pavlovsky", - "author_inst": "APHP, Hopital Bichat, Paris, France" + "author_name": "Aduragbemi Banke-Thomas", + "author_inst": "LSE Health, London School of Economics and Political Sciences, London, United Kingdom" }, { - "author_name": "Benoit Visseaux", - "author_inst": "APHP, Hopital Bichat, Paris, France" + "author_name": "Hannah Blencowe", + "author_inst": "Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London United Kingdom" }, { - "author_name": "Donia Bouzid", - "author_inst": "APHP, Hopital Bichat, Paris, France" + "author_name": "Severine Caluwaerts", + "author_inst": "Department of Public Health, Institute of Tropical Medicine, Antwerp Belgium" }, { - "author_name": "Raphael Borie", - "author_inst": "APHP, Hopital Bichat, Paris, France" + "author_name": "Oona M R Campbell", + "author_inst": "Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London United Kingdom" }, { - "author_name": "Catherine Wackenheim", - "author_inst": "APHP, Hopital Bichat, Paris, France" + "author_name": "Francesca L Cavallaro", + "author_inst": "Institute of Child Health, University College London, London United Kingdom" }, { - "author_name": "Bruno Crestani", - "author_inst": "APHP, Hopital Bichat, Paris, France" + "author_name": "Leonardo Chavane", + "author_inst": "Department of Community Health, Faculty of Medicine, Eduardo Mondlane University, Maputo, Mozambique" }, { - "author_name": "Christophe Rioux", - "author_inst": "APHP, Hopital Bichat, Paris, France" + "author_name": "Louise Tina Day", + "author_inst": "Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London United Kingdom" }, { - "author_name": "Loukbi Saker", - "author_inst": "APHP, Hopital Bichat, Paris, France" + "author_name": "Alexandre Delamou", + "author_inst": "Africa Centre of Excellence for Prevention and Control of Transmissible Diseases (CEA-PCMT), University Gamal Abdel Nasser, Conakry, Guinea" }, { - "author_name": "Christophe Choquet", - "author_inst": "APHP, Hopital Bichat, Paris, France" + "author_name": "Therese Delvaux", + "author_inst": "Department of Public Health, Institute of Tropical Medicine, Antwerp Belgium" }, { - "author_name": "Jimmy Mullaert", - "author_inst": "APHP, Hopital Bichat, Paris, France" + "author_name": "Wendy Graham", + "author_inst": "Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London United Kingdom" }, { - "author_name": "Antoine Khalil", - "author_inst": "APHP, Hopital Bichat, Paris, France" + "author_name": "Giorgia Gon", + "author_inst": "Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London United Kingdom" + }, + { + "author_name": "Peter Kascak", + "author_inst": "Trencin University Hospital, Trencin Slovakia" + }, + { + "author_name": "Mitsuaki Matsui", + "author_inst": "Department of Global Health, Nagasaki University School of Tropical Medicine and Global Health, Nagasaki, Japan" + }, + { + "author_name": "Sarah G Moxon", + "author_inst": "Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London United Kingdom" + }, + { + "author_name": "Annettee Nakimuli", + "author_inst": "Department of Obstetrics and Gynaecology, Makerere University and Mulago Specialized Women and Neonatal Hospital, Kampala Uganda" + }, + { + "author_name": "Andrea B Pembe", + "author_inst": "Department of Obstetrics and Gynaecology, Muhimbili University of Health and Allied Sciences, Dar es Salaam Tanzania" + }, + { + "author_name": "Emma Radovich", + "author_inst": "Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London United Kingdom" + }, + { + "author_name": "Thomas van den Akker", + "author_inst": "Department of Obstetrics and Gynaecology, Leiden University Medical Centre and Athena Institute, Vrije Universiteit Amsterdam, Netherlands" + }, + { + "author_name": "Lenka Benova", + "author_inst": "Institute of Tropical Medicine" } ], "version": "1", - "license": "cc_no", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "radiology and imaging" + "category": "sexual and reproductive health" }, { "rel_doi": "10.1101/2020.05.07.20094409", @@ -1466649,35 +1466690,115 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.05.06.20091900", - "rel_title": "Predicting the Growth and Trend of COVID-19 Pandemic using Machine Learning and Cloud Computing", - "rel_date": "2020-05-11", + "rel_doi": "10.1101/2020.05.06.20093377", + "rel_title": "The RBD Of The Spike Protein Of SARS-Group Coronaviruses Is A Highly Specific Target Of SARS-CoV-2 Antibodies But Not Other Pathogenic Human and Animal Coronavirus Antibodies", + "rel_date": "2020-05-10", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.06.20091900", - "rel_abs": "AO_SCPLOWBSTRACTC_SCPLOWThe outbreak of COVID-19 Coronavirus, namely SARS-CoV-2, has created a calamitous situation throughout the world. The cumulative incidence of COVID-19 is rapidly increasing day by day. Machine Learning (ML) and Cloud Computing can be deployed very effectively to track the disease, predict growth of the epidemic and design strategies and policy to manage its spread. This study applies an improved mathematical model to analyse and predict the growth of the epidemic. An ML-based improved model has been applied to predict the potential threat of COVID-19 in countries worldwide. We show that using iterative weighting for fitting Generalized Inverse Weibull distribution, a better fit can be obtained to develop a prediction framework. This can be deployed on a cloud computing platform for more accurate and real-time prediction of the growth behavior of the epidemic. A data driven approach with higher accuracy as here can be very useful for a proactive response from the government and citizens. Finally, we propose a set of research opportunities and setup grounds for further practical applications. Predicted curves for some of the most affected countries can be seen at https://collaboration.coraltele.com/covid/.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.06.20093377", + "rel_abs": "A new Severe Acute Respiratory Syndrome Coronavirus variant (SARS-CoV-2) that first emerged in late 2019 is responsible for a pandemic of severe respiratory illness. People infected with this highly contagious virus present with clinically inapparent, mild or severe disease. Currently, the presence of the virus in individual patients and at the population level is being monitored by testing symptomatic cases by PCR for the presence of viral RNA. There is an urgent need for SARS-CoV-2 serologic tests to identify all infected individuals, irrespective of clinical symptoms, to conduct surveillance and implement strategies to contain spread. As the receptor binding domain (RBD) of the viral spike (S) protein is poorly conserved between SARS-CoVs and other pathogenic human coronaviruses, the RBD represents a promising antigen for detecting CoV specific antibodies in people. Here we use a large panel of human sera (70 SARS-CoV-2 patients and 71 control subjects) and hyperimmune sera from animals exposed to zoonotic CoVs to evaluate the performance of the RBD as an antigen for accurate detection of SARS-CoV-2-specific antibodies. By day 9 after the onset of symptoms, the recombinant SARS-CoV-2 RBD antigen was highly sensitive (98%) and specific (100%) to antibodies induced by SARS-CoVs. We observed a robust correlation between levels of RBD binding antibodies and SARS-CoV-2 neutralizing antibodies in patients. Our results, which reveal the early kinetics of SARS-CoV-2 antibody responses, strongly support the use of RBD-based antibody assays for population-level surveillance and as a correlate of neutralizing antibody levels in people who have recovered from SARS-CoV-2 infections.", + "rel_num_authors": 24, "rel_authors": [ { - "author_name": "Shreshth Tuli", - "author_inst": "IIT Delhi" + "author_name": "Lakshmanane Premkumar", + "author_inst": "Department of Microbiology and Immunology, University of North Carolina School of Medicine, Chapel Hill NC 27599, USA" }, { - "author_name": "Shikhar Tuli", - "author_inst": "IIT Delhi" + "author_name": "Bruno Segovia-Chumbez", + "author_inst": "Department of Microbiology and Immunology, University of North Carolina School of Medicine, Chapel Hill NC 27599, USA" }, { - "author_name": "Rakesh Tuli", - "author_inst": "UIET, Panjab University" + "author_name": "Ramesh Jadi", + "author_inst": "Department of Microbiology and Immunology, University of North Carolina School of Medicine, Chapel Hill NC 27599, USA" }, { - "author_name": "Sukhpal Singh Gill", - "author_inst": "Queen Mary University London" + "author_name": "David R. Martinez", + "author_inst": "Department of Epidemiology, UNC Chapel Hill School of Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA" + }, + { + "author_name": "Rajendra Raut", + "author_inst": "Department of Microbiology and Immunology, University of North Carolina School of Medicine, Chapel Hill NC 27599, USA" + }, + { + "author_name": "Alena Markmann", + "author_inst": "Departments of Medicine, University of North Carolina School of Medicine, Chapel Hill NC 27599, USA" + }, + { + "author_name": "Caleb Cornaby", + "author_inst": "Immunology/Histocompatibility and Immunogenetics Laboratories, University of North Carolina School of Medicine, Chapel Hill NC 27599, USA" + }, + { + "author_name": "Luther Bartelt", + "author_inst": "Departments of Medicine, University of North Carolina School of Medicine, Chapel Hill NC 27599, USA" + }, + { + "author_name": "Susan Weiss", + "author_inst": "Departments of Medicine, University of North Carolina School of Medicine, Chapel Hill NC 27599, USA" + }, + { + "author_name": "Yara Park", + "author_inst": "Departments of Medicine, University of North Carolina School of Medicine, Chapel Hill NC 27599, USA" + }, + { + "author_name": "Caitlin E. Edwards", + "author_inst": "Department of Epidemiology, UNC Chapel Hill School of Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA" + }, + { + "author_name": "Eric Weimer", + "author_inst": "Department of Pathology & Laboratory Medicine, University of North Carolina School of Medicine, Chapel Hill NC 27599, USA" + }, + { + "author_name": "Erin M. Scherer", + "author_inst": "Hope Clinic of the Emory Vaccine Center, Division of Infectious Diseases, Department of Medicine, School of Medicine, Emory University, Decatur, Georgia, USA" + }, + { + "author_name": "Nadine Roupael", + "author_inst": "Hope Clinic of the Emory Vaccine Center, Division of Infectious Diseases, Department of Medicine, School of Medicine, Emory University, Decatur, Georgia, USA" + }, + { + "author_name": "Sri Edupuganti", + "author_inst": "Hope Clinic of the Emory Vaccine Center, Division of Infectious Diseases, Department of Medicine, School of Medicine, Emory University, Decatur, Georgia, USA" + }, + { + "author_name": "Daniela Weiskopf", + "author_inst": "Center for Infectious Disease and Vaccine Research, La Jolla Institute for Immunology (LJI), La Jolla, CA 92037, USA" + }, + { + "author_name": "Longping V. Tse", + "author_inst": "Department of Epidemiology, UNC Chapel Hill School of Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA" + }, + { + "author_name": "Yixuan J. Hou", + "author_inst": "Department of Epidemiology, UNC Chapel Hill School of Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA" + }, + { + "author_name": "David Margolis", + "author_inst": "Department of Microbiology and Immunology, University of North Carolina School of Medicine, Chapel Hill NC 27599, USA" + }, + { + "author_name": "Alessandro Sette", + "author_inst": "Center for Infectious Disease and Vaccine Research, La Jolla Institute for Immunology (LJI), La Jolla, CA 92037, USA" + }, + { + "author_name": "Matthew H. Collins", + "author_inst": "Hope Clinic of the Emory Vaccine Center, Division of Infectious Diseases, Department of Medicine, School of Medicine, Emory University, Decatur, Georgia, USA" + }, + { + "author_name": "John Schmitz", + "author_inst": "Department of Pathology & Laboratory Medicine, University of North Carolina School of Medicine, Chapel Hill NC 27599, USA" + }, + { + "author_name": "Ralph S. Baric", + "author_inst": "Department of Microbiology and Immunology, University of North Carolina School of Medicine, Chapel Hill NC 27599, USA" + }, + { + "author_name": "Aravinda M. de Silva", + "author_inst": "Department of Microbiology and Immunology, University of North Carolina School of Medicine, Chapel Hill NC 27599, USA" } ], "version": "1", "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2020.05.06.20093336", @@ -1467987,75 +1468108,55 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.05.06.20093070", - "rel_title": "Neutrophil calprotectin identifies severe pulmonary disease in COVID-19", - "rel_date": "2020-05-10", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.06.20093070", - "rel_abs": "Severe cases of coronavirus disease 2019 (COVID-19) are regularly complicated by respiratory failure. While it has been suggested that elevated levels of blood neutrophils associate with worsening oxygenation in COVID-19, it is unknown whether neutrophils are drivers of the thrombo-inflammatory storm or simple bystanders. To better understand the potential role of neutrophils in COVID-19, we measured levels of the neutrophil activation marker S100A8/A9 (calprotectin) in hospitalized patients and determined its relationship to severity of illness and respiratory status. Patients with COVID-19 (n=172) had markedly elevated levels of calprotectin in their blood. Calprotectin tracked with other acute phase reactants including C-reactive protein, ferritin, lactate dehydrogenase, and absolute neutrophil count, but was superior in identifying patients requiring mechanical ventilation. In longitudinal samples, calprotectin rose as oxygenation worsened. When tested on day 1 or 2 of hospitalization (n=94 patients), calprotectin levels were significantly higher in patients who progressed to severe COVID-19 requiring mechanical ventilation (8039 {+/-} 7031 ng/ml, n=32) as compared to those who remained free of intubation (3365 {+/-} 3146, p<0.0001). In summary, serum calprotectin levels track closely with current and future COVID-19 severity, implicating neutrophils as potential perpetuators of inflammation and respiratory compromise in COVID-19.", - "rel_num_authors": 14, + "rel_doi": "10.1101/2020.05.07.083139", + "rel_title": "Pre-treatment of the clinical sample with Proteinase K allows detection of SARS-CoV-2 in the absence of RNA extraction", + "rel_date": "2020-05-09", + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.07.083139", + "rel_abs": "COVID-19 (Coronavirus Disease 2019) outbreak was declared a pandemic, by World Health Organization, on March 11, 2020. Viral detection using RT-qPCR has been among the most important factors helping to control local spread of SARS-CoV-2 and it is considered the \"gold standard\" for diagnosis. Nevertheless, the RNA extraction step is both laborious and expensive, thus hampering the diagnosis in many places where there are not laboratory staff of funds enough to contribute for diagnosis efforts. Thus, the need to simplify procedures, reduce costs of the techniques used, and expand the capacity of the number of diagnostics of COVID-19 is imperative. In this study, detection of SARS-CoV-2 in the absence of RNA extraction has been successfully achieved through pre-treatment of the clinical sample with Proteinase K. The results show that only the use of proteinase K, without the need to perform the whole standard protocol for sample extraction and purification, can be an efficient technique for the diagnosis of COVID-19, since 91% of the samples matched the results with the standard procedure, with an average increase of 5.64 CT in the RT-qPCR.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Hui Shi", - "author_inst": "University of Michigan" - }, - { - "author_name": "Yu Zuo", - "author_inst": "University of Michigan" - }, - { - "author_name": "Srilakshmi Yalavarthi", - "author_inst": "University of Michigan" - }, - { - "author_name": "Kelsey Gockman", - "author_inst": "University of Michigan" - }, - { - "author_name": "Melanie Zuo", - "author_inst": "University of Michigan" - }, - { - "author_name": "Jacqueline A. Madison", - "author_inst": "University of Michigan" + "author_name": "Larissa Mallmann", + "author_inst": "Universidade Feevale" }, { - "author_name": "Christopher N. Blair", - "author_inst": "University of Michigan" + "author_name": "Karoline Schallenberger", + "author_inst": "Universidade Feevale" }, { - "author_name": "Wrenn Woodard", - "author_inst": "University of Michigan" + "author_name": "Meriane Demoliner", + "author_inst": "Universidade Feevale" }, { - "author_name": "Sean P. Lezak", - "author_inst": "University of Michigan" + "author_name": "Ana Karolina Antunes Eisen", + "author_inst": "Universidade Feevale" }, { - "author_name": "Njira L. Lugogo", - "author_inst": "University of MIchigan" + "author_name": "Bruna Saraiva Hermann", + "author_inst": "Universidade Feevale" }, { - "author_name": "Robert J. Woods", - "author_inst": "University of Michigan" + "author_name": "Fagner Henrique Heldt", + "author_inst": "Universidade Feevale" }, { - "author_name": "Christian Lood", - "author_inst": "University of Michigan" + "author_name": "Alana Witt Hansen", + "author_inst": "Universidade Feevale" }, { - "author_name": "Jason S. Knight", - "author_inst": "University of Michigan" + "author_name": "Fernando R Spilki", + "author_inst": "Universidade Feevale" }, { - "author_name": "Yogendra Kanthi", - "author_inst": "University of Michigan" + "author_name": "Juliane Deise Fleck", + "author_inst": "Universidade Feevale" } ], "version": "1", - "license": "cc_no", - "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "license": "cc_by_nc_nd", + "type": "new results", + "category": "microbiology" }, { "rel_doi": "10.1101/2020.05.08.084806", @@ -1469633,21 +1469734,29 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.05.05.20092155", - "rel_title": "A Divide and Conquer Strategy against the Covid-19 Pandemic?!", + "rel_doi": "10.1101/2020.05.05.20092221", + "rel_title": "Containing Covid-19 outbreaks with spatiallytargeted short-term lockdowns and mass-testing", "rel_date": "2020-05-09", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.05.20092155", - "rel_abs": "The concern about (socio-)economic consequences of collective lockdowns in the Covid-19 pandemic calls for alternative strategies. We consider a divide and conquer strategy in which a high risk group (HRG) is put on strict isolation, whereas the remainder of the population is exposed to the virus, building up immunity against Covid-19. The question is whether this strategy may suppress the effective reproduction number below the critical value of [Formula] without further lockdown once the HRG is released from isolation. While this proposal appears already rather academic, we show that [Formula] can only be obtained provided that the HRG is less than ~ 20 - 30% of the total population. Hence, this strategy is likely to fail in countries with a HRG larger than the given upper bound. In addition, we argue that the maximum infection rate occurring in this strategy is likely to exceed realistic capacities of most health care systems. While the conclusion is rather negative in this regard, we emphasise that the strategy of stopping the curve at an early stage of the Covid-19 pandemic has a chance to work out. The required duration of the lockdown is estimated to be {tau} ~ 14 days/[Formula] (up to some order one factor) for [Formula], provided a systematic tracing strategy of new infections exists for the subsequent relaxation phase. In this context we also argue why [Formula] remains the crucial parameter which needs to be accurately monitored and controlled.", - "rel_num_authors": 1, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.05.20092221", + "rel_abs": "We assess the efficacy of spatially targeted lockdown or mass-testing and case-isolation in individual communities, as a compliment to contact-tracing and social-distancing, for containing SARS-CoV-2 outbreaks. Using the UK as a case study, we construct a stochastic branching process model for the virus transmission, embedded on a network interaction model encoding mobility patterns in the UK. The network model is based on commuter data from the 2011 census, a catchment area model for schools, and a phenomenological model for mobility and interactions outside of work, school, and the home. We show that for outbreak scenarios where contact-tracing and moderate social distancing alone provide suppression but do not contain the spread, targeted lockdowns or mass-testing interventions at the level of individual communities (with just a few thousand inhabitants) can be effective at containing outbreaks. For spatially targeted mass-testing, a moderate increase in testing capacity would be required (typically < 40000 additional tests per day), while for local lockdowns we find that only a small fraction (typically < 0.1%) of the population needs to be locked down at any one time (assuming that one third of transmission occurs in the home, at work or school, and out in the wider community respectively). The efficacy of spatially targeted interventions is contingent on an appreciable fraction of transmission events occurring within (relative to across) communities. Confirming the efficacy of community-level interventions therefore calls for detailed investigation of spatial transmission patterns for SARS-CoV-2, accounting for sub-community-scale transmission dynamics, and changes in mobility patterns due to the presence of other containment measures (such as social distancing and travel restrictions).\n\nDisclaimer: We stress that this is a working paper where results are preliminary and subject to change. In particular, we note that the efficacy of spatially targeted interventions are sensitive to the relative proportions of intra-versus inter-community transmission (for a given definition of community boundaries), which in turn is sensitive to the assumptions about the transmission dynamics across different contexts. Whilst the assumptions made here about transmission across contexts are motivated, we are currently updating our model to make the estimated inter- and intra-community transmission rates as robust as possible, as well as running a comprehensive suite of sensitivity tests and different outbreak scenarios.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Patrick S. Mangat", - "author_inst": "Mannheim University of Applied Science" + "author_name": "Justin Alsing", + "author_inst": "Oskar Klein Centre, Stockholm University" + }, + { + "author_name": "Nairi Usher", + "author_inst": "None" + }, + { + "author_name": "Philip JD Crowley", + "author_inst": "Department of Physics, Boston University, Boston, MA 02215, USA" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1471311,65 +1471420,29 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2020.05.04.20090274", - "rel_title": "Assessing Differential Impacts of COVID-19 on Black Communities", + "rel_doi": "10.1101/2020.05.03.20089839", + "rel_title": "Assessing COVID-19 Risk, Vulnerability and Infection Prevalence in Communities", "rel_date": "2020-05-08", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.04.20090274", - "rel_abs": "PurposeGiven incomplete data reporting by race, we used data on COVID-19 cases and deaths in US counties to describe racial disparities in COVID-19 disease and death and associated determinants.\n\nMethodsUsing publicly available data (accessed April 13, 2020), predictors of COVID-19 cases and deaths were compared between disproportionately ([≥]13%) black and all other (<13% black) counties. Rate ratios were calculated and population attributable fractions (PAF) were estimated using COVID-19 cases and deaths via zero-inflated negative binomial regression model. National maps with county-level data and an interactive scatterplot of COVID-19 cases were generated.\n\nResultsNearly ninety-seven percent of disproportionately black counties (656/677) reported a case and 49% (330/677) reported a death versus 81% (1987/2,465) and 28% (684/ 2465), respectively, for all other counties. Counties with higher proportions of black people have higher prevalence of comorbidities and greater air pollution. Counties with higher proportions of black residents had more COVID-19 diagnoses (RR 1.24, 95% CI 1.17-1.33) and deaths (RR 1.18, 95% CI 1.00-1.40), after adjusting for county-level characteristics such as age, poverty, comorbidities, and epidemic duration. COVID-19 deaths were higher in disproportionally black rural and small metro counties. The PAF of COVID-19 diagnosis due to lack of health insurance was 3.3% for counties with <13% black residents and 4.2% for counties with [≥]13% black residents.\n\nConclusionsNearly twenty-two percent of US counties are disproportionately black and they accounted for 52% of COVID-19 diagnoses and 58% of COVID-19 deaths nationally. County-level comparisons can both inform COVID-19 responses and identify epidemic hot spots. Social conditions, structural racism, and other factors elevate risk for COVID-19 diagnoses and deaths in black communities.", - "rel_num_authors": 12, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.03.20089839", + "rel_abs": "BackgroundThe spread of coronavirus in the United States with nearly one million confirmed cases and over 53,000 deaths has strained public health and health care systems. While many have focused on clinical outcomes, less attention has been paid to vulnerability and risk of infection. In this study, we developed a planning tool that examines factors that affect vulnerability to COVID-19.\n\nMethodsAcross 46 variables, we defined five broad categories: 1) access to medical, 2) underlying health conditions, 3) environmental exposures, 4) vulnerability to natural disasters, and 5) sociodemographic, behavioral, and lifestyle factors. We also used reported rates for morbidity, hospitalization, and mortality in other regions to estimate risk at the county (Harris County) and census tract levels.\n\nAnalysisA principal component analysis was undertaken to reduce the dimensions. Then, to identify vulnerable census tracts, we conducted rank-based exceedance and K-means cluster analyses.\n\nResultsOur study showed a total of 722,357 (~17% of the County population) people, including 171,403 between the ages of 45-65 (~4% of Countys population), and 76,719 seniors (~2% of County population), are at a higher risk based on the aforementioned categories. The exceedance and K-means cluster analysis demonstrated that census tracts in the northeastern, eastern, southeastern and northwestern regions of the county are at highest risk. The results of age-based estimations of hospitalization rates showed the western part of the County might be in greater need of hospital beds. However, cross-referencing the vulnerability model with the estimation of potential hospitalized patients showed that part of the County has the least access to medical facilities.\n\nConclusionPolicy makers can use this planning tool to identify neighborhoods at high risk for becoming hot spots; efficiently match community resources with needs, and ensure that the most vulnerable have access to equipment, personnel, and medical interventions.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Greg Millett", - "author_inst": "amfAR" - }, - { - "author_name": "Austin T Jones", - "author_inst": "amfAR" - }, - { - "author_name": "David Benkeser", - "author_inst": "Emory University" - }, - { - "author_name": "Stefan D Baral", - "author_inst": "Johns Hopkins University" - }, - { - "author_name": "Laina Mercer", - "author_inst": "PATH" - }, - { - "author_name": "Chris Beyrer", - "author_inst": "Johns Hopkins University" - }, - { - "author_name": "Brian Honnermann", - "author_inst": "amfAR" - }, - { - "author_name": "Elise Lankiewicz", - "author_inst": "amfAR" - }, - { - "author_name": "Lenandro Mena", - "author_inst": "University of Mississippi Medical Center" - }, - { - "author_name": "Jeffrey S Crowley", - "author_inst": "O'Neill Institute for National and Global Health Law, Georgetown University" + "author_name": "Amin Kiaghadi", + "author_inst": "University of Houston" }, { - "author_name": "Jennifer Sherwood", - "author_inst": "amfAR" + "author_name": "Hanadi S Rifai", + "author_inst": "University of Houston" }, { - "author_name": "Patrick S Sullivan", - "author_inst": "Emory University" + "author_name": "Winston Liaw", + "author_inst": "University of Houston College of Medicine" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "public and global health" }, @@ -1473229,59 +1473302,27 @@ "category": "pediatrics" }, { - "rel_doi": "10.1101/2020.05.05.20091587", - "rel_title": "Acceptability of app-based contact tracing for COVID-19: Cross-country survey evidence", + "rel_doi": "10.1101/2020.05.03.20089557", + "rel_title": "The Impact of Coronavirus Disease 2019 (COVID-19) on Liver Injury in China: A Systematic Review and Meta-analysis", "rel_date": "2020-05-08", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.05.20091587", - "rel_abs": "BackgroundThe COVID-19 pandemic is the greatest public health crisis of the last 100 years. Countries have responded with various levels of lockdown to save lives and stop health systems from being overwhelmed. At the same time, lockdowns entail large socio-economic costs. One exit strategy under consideration is a mobile phone app that traces close contacts of those infected with COVID-19. Recent research has demonstrated the theoretical effectiveness of this solution in different disease settings. However, concerns have been raised about such apps because of the potential privacy implications. This could limit the acceptability of app-based contact tracing among the general population. As the effectiveness of this approach increases strongly with app take-up, it is crucial to understand public support for this intervention.\n\nObjectivesThe objective of this study is to investigate user acceptability of a contact-tracing app in five countries hit by the pandemic.\n\nMethodsWe conducted a multi-country, large-scale (N = 5995) study to measure public support for digital contact tracing of COVID-19 infections. We ran anonymous online surveys in France, Germany, Italy, the UK and the US. We measured intentions to use a contact-tracing app across different installation regimes (voluntary installation vs. automatic installation by mobile phone providers), and studied how these intentions vary across individuals and countries.\n\nResultsWe found strong support for the app under both regimes, in all countries, across all sub-groups of the population, and irrespective of regional-level COVID-19 mortality rates. We investigated the main factors that may hinder or facilitate take-up and found that concerns about cyber security and privacy, together with lack of trust in government, are the main barriers to adoption.\n\nConclusionsEpidemiological evidence shows that app-based contact-tracing can suppress the spread of COVID-19 if a high enough proportion of the population uses the app and that it can still reduce the number of infections if take-up is moderate. Our findings show that the willingness to install the app is very high. The available evidence suggests that app-based contact tracing may be a viable approach to control the diffusion of COVID-19.", - "rel_num_authors": 10, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.03.20089557", + "rel_abs": "BackgroundThe evidence for the incidence and severity of liver injury in Chinese patients with COVID-19 is still controversial.\n\nAimsThe purpose of this study was to summarize the incidence of liver injury and the differences between liver injury markers among different patients with COVID-19 in China.\n\nMethodsComputer searches of PubMed, Embase, CNKI and medRxiv were used to obtain reports on the incidence and markers of liver injury in Chinese patients with COVID-19, from January 1, 2020 to April 10, 2020. (No. CRD42020181350)\n\nResultsA total of 57 reports from China were included, including 9889 confirmed cases of COVID-19 infection. The results of the meta-analysis showed that among the patients with early COVID-19 infection in China, the incidence of liver injury events was 24.7% (95% CI, 23.4%-26.4%). Liver injury in severe patients was more common than that in non-severe patients, with a risk ratio of 2.07 (95% CI, 1.77 to 2.43). Quantitative analysis showed that the severe the coronavirus infection, the higher the level of AST, ALT, TB, ALP, GGT and the lower the level of ALB. The changing trend of the appeal index was similar in ICU patients and dead patients.\n\nConclusionThere is a certain risk of liver injury in Chinese patients with COVID-19, and the risk and degree of liver injury are related to the severity of COVID-19.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Samuel Altmann", - "author_inst": "University of Oxford" - }, - { - "author_name": "Luke Milsom", - "author_inst": "University of Oxford" - }, - { - "author_name": "Hannah Zillessen", - "author_inst": "University of Oxford" - }, - { - "author_name": "Raffaele Blasone", - "author_inst": "University of Oxford" - }, - { - "author_name": "Frederic Gerdon", - "author_inst": "University of Mannheim" - }, - { - "author_name": "Ruben Bach", - "author_inst": "University of Mannheim" - }, - { - "author_name": "Frauke Kreuter", - "author_inst": "University of Mannheim" - }, - { - "author_name": "Daniele Nosenzo", - "author_inst": "University of Nottingham" - }, - { - "author_name": "Severine Toussaert", - "author_inst": "University of Oxford" + "author_name": "Xin Zhao", + "author_inst": "1. People,s Hospital of Leshan 2. 2.Diagnosis and Treatment Center for Liver, Gallbladder, Pancreas and Spleen System Diseases, Leshan City" }, { - "author_name": "Johannes Abeler", - "author_inst": "University of Oxford" + "author_name": "Zehua Lei", + "author_inst": "1. People,s Hospital of Leshan 2.Diagnosis and Treatment Center for Liver, Gallbladder, Pancreas and Spleen System Diseases, Leshan City" } ], "version": "1", - "license": "cc_by", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "epidemiology" }, { "rel_doi": "10.1101/2020.05.02.20080036", @@ -1474891,79 +1474932,59 @@ "category": "nutrition" }, { - "rel_doi": "10.1101/2020.05.03.20082818", - "rel_title": "Contact tracing and isolation of asymptomatic spreaders to successfully control the COVID-19 epidemic among healthcare workers in Milan (Italy)", + "rel_doi": "10.1101/2020.05.03.20088526", + "rel_title": "Objective Olfactory Evaluation of Self-reported Olfactory Dysfunction in a Case Series of 86 COVID-19 Patients", "rel_date": "2020-05-08", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.03.20082818", - "rel_abs": "ObjectiveTo study the source, symptoms, and duration of infection, preventive measures, contact tracing and their effects on SARS-CoV-2 epidemic among healthcare workers (HCW) in 2 large hospitals and 40 external healthcare services in Milan (Italy) to propose effective measures to control the COVID-19 epidemic among healthcare workers.\n\nDesignEpidemiological observational study.\n\nSettingTwo large hospitals and 40 territorial healthcare units, with a total of 5700 workers.\n\nParticipants143 HCWs with a SARS-CoV-2 positive nasopharyngeal (NF) swab in a population made of 5,700 HCWs.\n\nMain outcome measuresClinical data on the history of exposure, contacts inside and outside of the hospital, NF swab dates and results. A daily online self-reported case report form consisting of the morning and evening body temperature and 11 other symptoms (cough, dyspnoea, discomfort, muscle pain, headache, sore throat, vomiting, diarrhoea, anosmia, dysgeusia, conjunctival hyperaemia).\n\nResultsMost workers were tested and found positive due to a close contact with a positive colleague (49%), followed by worker-initiated testing due to symptoms (and unknown contact, 28%), and a SARS-CoV-2 positive member of the family (9.8%). 10% of NF swabs performed in the framework of contact tracing resulted positive, compared to only 2.6% through random testing. The first (index) case caused a cluster of 7 positive HCWs discovered through contact tracing and testing of 250 asymptomatic HCWs. HCWs rarely reported symptoms of a respiratory infection, and up to 90% were asymptomatic or with mild symptoms in the days surrounding the positive NF swab. During the 15-day follow-up period, up to 40% of HCWs reported anosmia and dysgeusia/ageusia as moderate or heavy, more frequently than any other symptom. The time necessary for 95% of HCWs to be considered cured (between the positive and two negative NF swabs) was 30 days.\n\nConclusionHCWs represent the main source of infection in healthcare institutions, 90% are asymptomatic or with symptoms not common in a respiratory infection. The time needed to overcome the infection in 95% of workers was 30 days. Contact tracing allows identifying asymptomatic workers which would spread SARS-CoV-2 in the hospital and is a more successful strategy than random testing.\n\nWhat is already known on this topic?There are more than 3 million SARS-CoV-2 positive cases and more than 200,000 deaths attributed to coronavirus disease (COVID-19) worldwide.\n\nCommonly reported symptoms of COVID-19 include fever, cough, dyspnea, sore throat, muscle pain, discomfort, and many prevention strategies are based on identifying these symptoms of infection.\n\nThe virus can be spread even by asymptomatic patients or patients with mild symptoms, and healthcare workers (HCWs) represent 10% of overall cases and often more than 10% of hospital personnel are commonly infected.\n\nHCWs represent both a vulnerable population and an irreplaceable resource in the fight against this epidemic and further analysis is needed to show how and why they get infected and introduce successful prevention measures.\n\nWhat this study adds?The first (index) case in our study was infected by a family member, but due to close contacts with colleagues managed to infect other 7 HCWs. Contrary to a common expectation that HCWs get infected from patients, they regularly get infected by other HCWs.\n\nUp to 90% of HCWs were asymptomatic or had only mild symptoms. Random testing for SARS-CoV-2 was not efficient. Active search for suspect cases through contact tracing is the strategy of choice to identify most of the positive HCWs.\n\nMost HCWs remained asymptomatic during the 15-day follow-up period, and even in the days prior to the positive NF swab. Anosmia and ageusia/dysgeusia were reported more commonly than classic symptoms of a respiratory infection.\n\nContrary to the recommended quarantine of 14 days, 30 days were necessary for 95% of the workers to be declared cured (two negative NF swabs)", - "rel_num_authors": 15, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.03.20088526", + "rel_abs": "ObjectiveTo investigate olfactory dysfunction (OD) in patients with mild COVID-19 through patient-reported outcome questionnaires and objective psychophysical testing.\n\nMethodsCOVID-19 patients with self-reported sudden-onset OD were recruited. Epidemiological and clinical data were collected. Nasal complaints were evaluated with the sino-nasal outcome-22 (SNOT-22). Subjective olfactory and gustatory status was evaluated with the National Health and Nutrition Examination Survey (NHNES). Objective OD was evaluated using psychophysical tests.\n\nResultsEighty-six patients completed the study. The most common symptoms were fatigue (72.9%), headache (60.0%), nasal obstruction (58.6%) and postnasal drip (48.6%). Total loss of smell was self-reported by 61.4% of patients. Objective olfactory testings identified 41 anosmic (47.7%), 12 hyposmic (14.0%), and 33 normosmic (38.3%) patients. There was no correlation between the objective test results and subjective reports of nasal obstruction or postnasal drip.\n\nConclusionA significant proportion of COVID-19 patients reporting OD do not have OD on objective testing.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Stefan Mandi\u0107-Raj\u010devi\u0107", - "author_inst": "Department of Health Sciences, University of Milan, Occupational Health Unit, International Centre for Rural Health and Central Health Care Management of the Sa" - }, - { - "author_name": "Federica Masci", - "author_inst": "Department of Health Sciences, University of Milan, Occupational Health Unit, International Centre for Rural Health and Central Health Care Management of the Sa" - }, - { - "author_name": "Eleonora Crespi", - "author_inst": "Department of Health Sciences, University of Milan, Occupational Health Unit, International Centre for Rural Health and Central Health Care Management of the Sa" - }, - { - "author_name": "Sara Franchetti", - "author_inst": "Department of Health Sciences, University of Milan, Occupational Health Unit, International Centre for Rural Health and Central Health Care Management of the Sa" - }, - { - "author_name": "Anna Longo", - "author_inst": "Department of Health Sciences, University of Milan, Occupational Health Unit, International Centre for Rural Health and Central Health Care Management of the Sa" - }, - { - "author_name": "Ilaria Bollina", - "author_inst": "Department of Health Sciences, University of Milan, Occupational Health Unit, International Centre for Rural Health and Central Health Care Management of the Sa" + "author_name": "Pierre Cabaraux", + "author_inst": "CHU Charleroi" }, { - "author_name": "Serena Veloci", - "author_inst": "Department of Health Sciences, University of Milan, Occupational Health Unit, International Centre for Rural Health and Central Health Care Management of the Sa" + "author_name": "Jerome R. Lechien", + "author_inst": "UMONS" }, { - "author_name": "Alessandro Amorosi", - "author_inst": "Department of Health Sciences, University of Milan, Occupational Health Unit, International Centre for Rural Health and Central Health Care Management of the Sa" + "author_name": "sven saussez", + "author_inst": "University of Mons" }, { - "author_name": "Riccardo Baldelli", - "author_inst": "Department of Health Sciences, University of Milan, Occupational Health Unit, International Centre for Rural Health and Central Health Care Management of the Sa" + "author_name": "Carlos M Chiesa-Estomba", + "author_inst": "Hospital Universitario Donostia" }, { - "author_name": "Luisa Boselli", - "author_inst": "Department of Health Sciences, University of Milan, Occupational Health Unit, International Centre for Rural Health and Central Health Care Management of the Sa" + "author_name": "Mohamad Khalife", + "author_inst": "Epicura Hospital" }, { - "author_name": "Lucia Negroni", - "author_inst": "Department of Health Sciences, University of Milan, Occupational Health Unit, International Centre for Rural Health and Central Health Care Management of the Sa" + "author_name": "Stephane Hans", + "author_inst": "Foch Hospital" }, { - "author_name": "Alessandro Z\u00e0", - "author_inst": "Department of Health Sciences, University of Milan, Occupational Health Unit, International Centre for Rural Health and Central Health Care Management of the Sa" + "author_name": "Delphine Martiny", + "author_inst": "ULB" }, { - "author_name": "Nicola Vincenzo Orfeo", - "author_inst": "Department of Health Sciences, University of Milan, Occupational Health Unit, International Centre for Rural Health and Central Health Care Management of the Sa" + "author_name": "Fabrice Journe", + "author_inst": "Umons" }, { - "author_name": "Giusepe Ortisi", - "author_inst": "Department of Health Sciences, University of Milan, Occupational Health Unit, International Centre for Rural Health and Central Health Care Management of the Sa" + "author_name": "Christian Calvo Henriquez", + "author_inst": "Hospital Santiago de Compostela" }, { - "author_name": "Claudio Colosio", - "author_inst": "Department of Health Sciences, University of Milan, Occupational Health Unit, International Centre for Rural Health and Central Health Care Management of the Sa" + "author_name": "Leigh Sowerby", + "author_inst": "University of Western Ontario" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "occupational and environmental health" + "category": "otolaryngology" }, { "rel_doi": "10.1101/2020.05.04.20090779", @@ -1476701,37 +1476722,81 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.05.07.20055947", - "rel_title": "A 5-min RNA preparation method for COVID-19 detection with RT-qPCR", + "rel_doi": "10.1101/2020.05.04.20076349", + "rel_title": "Intensive care risk estimation in COVID-19 pneumonia based on clinical and imaging parameters: experiences from the Munich cohort", "rel_date": "2020-05-08", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.07.20055947", - "rel_abs": "RNA extraction has become a bottleneck for detection of COVID-19, in part because of reagent shortages. We present here a rapid protocol that circumvents the need for RNA extraction that is compatible with RT-qPCR-based detection methods.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.04.20076349", + "rel_abs": "The evolving dynamics of coronavirus disease 2019 (COVID-19) and the increasing infection numbers require diagnostic tools to identify patients at high risk for a severe disease course. Here we evaluate clinical and imaging parameters for estimating the need of intensive care unit (ICU) treatment. We collected clinical, laboratory and imaging data from 65 patients with confirmed COVID-19 infection based on PCR testing. Two radiologists evaluated the severity of findings in computed tomography (CT) images on a scale from 1 (no characteristic signs of COVID-19) to 5 (confluent ground glass opacities in over 50% of the lung parenchyma). The volume of affected lung was quantified using commercially available software. Machine learning modelling was performed to estimate the risk for ICU treatment. Patients with a severe course of COVID-19 had significantly increased IL-6, CRP and leukocyte counts and significantly decreased lymphocyte counts. The radiological severity grading was significantly increased in ICU patients. Multivariate random forest modelling showed a mean {+/-} standard deviation sensitivity, specificity and accuracy of 0.72 {+/-} 0.1, 0.86 {+/-} 0.16 and 0.80 {+/-} 0.1 and a ROC-AUC of 0.79 {+/-} 0.1.\n\nThe need for ICU treatment is independently associated with affected lung volume, radiological severity score, CRP and IL-6.", + "rel_num_authors": 16, "rel_authors": [ { - "author_name": "Alim Ladha", - "author_inst": "Broad Institute of MIT and Harvard; MIT" + "author_name": "Egon Burian", + "author_inst": "Klinikum rechts der Isar" }, { - "author_name": "Julia Joung", - "author_inst": "Broad Institute of MIT and Harvard; MIT" + "author_name": "Friederike Jungmann", + "author_inst": "Department of Diagnostic and Interventional Radiology, Technical University of Munich, Ismaninger Str. 22, 81675 Munich, Germany" }, { - "author_name": "Omar Abudayyeh", - "author_inst": "MIT" + "author_name": "Georgios A. Kaissis", + "author_inst": "Department of Diagnostic and Interventional Radiology, Technical University of Munich, Ismaninger Str. 22, 81675 Munich, Germany" }, { - "author_name": "Jonathan Gootenberg", - "author_inst": "MIT" + "author_name": "Fabian K. Lohoefer", + "author_inst": "Department of Diagnostic and Interventional Radiology, Technical University of Munich, Ismaninger Str. 22, 81675 Munich, Germany" }, { - "author_name": "Feng Zhang", - "author_inst": "HHMI; Broad Institute of MIT and Harvard; and McGovern Institute, MIT" + "author_name": "Christoph D. Spinner", + "author_inst": "Department of Internal Medicine II, Technical University of Munich, Ismaninger Str. 22, 81675 Munich, Germany" + }, + { + "author_name": "Tobias Lahmer", + "author_inst": "Department of Internal Medicine II, Technical University of Munich, Ismaninger Str. 22, 81675 Munich, Germany" + }, + { + "author_name": "Matthias Treiber", + "author_inst": "Department of Internal Medicine II, Technical University of Munich, Ismaninger Str. 22, 81675 Munich, Germany" + }, + { + "author_name": "Michael Dommasch", + "author_inst": "Department of Internal Medicine I, Technical University of Munich, Ismaninger Str. 22, 81675 Munich, Germany" + }, + { + "author_name": "Gerhard Schneider", + "author_inst": "Clinic for Anesthesiology and Intensive Care Medicine, Technical University of Munich, Ismaninger Str. 22, 81675 Munich, Germany" + }, + { + "author_name": "Fabian Geisler", + "author_inst": "Department of Internal Medicine II, Technical University of Munich, Ismaninger Str. 22, 81675 Munich, Germany" + }, + { + "author_name": "Wolfgang Huber", + "author_inst": "Department of Internal Medicine II, Technical University of Munich, Ismaninger Str. 22, 81675 Munich, Germany" + }, + { + "author_name": "Ulrike Protzer", + "author_inst": "Institute of Virology, Technical University of Munich, Ismaninger Str. 22, 81675 Munich, Germany" + }, + { + "author_name": "Roland M. Schmid", + "author_inst": "Department of Internal Medicine II, Technical University of Munich, Ismaninger Str. 22, 81675 Munich, Germany" + }, + { + "author_name": "Markus Schwaiger", + "author_inst": "Dean, School of Medicine Technical University of Munich, Ismaninger Str. 22, 81675 Munich, Germany" + }, + { + "author_name": "Marcus R. Makowski", + "author_inst": "Department of Diagnostic and Interventional Radiology, Technical University of Munich, Ismaninger Str. 22, 81675 Munich, Germany" + }, + { + "author_name": "Rickmer F. Braren", + "author_inst": "Department of Diagnostic and Interventional Radiology, Technical University of Munich, Ismaninger Str. 22, 81675 Munich, Germany" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1477843,143 +1477908,131 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.05.06.20092999", - "rel_title": "OpenSAFELY: factors associated with COVID-19-related hospital death in the linked electronic health records of 17 million adult NHS patients.", + "rel_doi": "10.1101/2020.05.01.20053413", + "rel_title": "Development of a Clinical Decision Support System for Severity Risk Prediction and Triage of COVID-19 Patients at Hospital Admission: an International Multicenter Study", "rel_date": "2020-05-07", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.06.20092999", - "rel_abs": "BackgroundEstablishing who is at risk from a novel rapidly arising cause of death, and why, requires a new approach to epidemiological research with very large datasets and timely data. Working on behalf of NHS England we therefore set out to deliver a secure and pseudonymised analytics platform inside the data centre of a major primary care electronic health records vendor establishing coverage across detailed primary care records for a substantial proportion of all patients in England. The following results are preliminary.\n\nData sourcesPrimary care electronic health records managed by the electronic health record vendor TPP, pseudonymously linked to patient-level data from the COVID-19 Patient Notification System (CPNS) for death of hospital inpatients with confirmed COVID-19, using the new OpenSAFELY platform.\n\nPopulation17,425,445 adults.\n\nTime period1st Feb 2020 to 25th April 2020.\n\nPrimary outcomeDeath in hospital among people with confirmed COVID-19.\n\nMethodsCohort study analysed by Cox-regression to generate hazard ratios: age and sex adjusted, and multiply adjusted for co-variates selected prospectively on the basis of clinical interest and prior findings.\n\nResultsThere were 5683 deaths attributed to COVID-19. In summary after full adjustment, death from COVID-19 was strongly associated with: being male (hazard ratio 1.99, 95%CI 1.88-2.10); older age and deprivation (both with a strong gradient); uncontrolled diabetes (HR 2.36 95% CI 2.18-2.56); severe asthma (HR 1.25 CI 1.08-1.44); and various other prior medical conditions. Compared to people with ethnicity recorded as white, black people were at higher risk of death, with only partial attenuation in hazard ratios from the fully adjusted model (age-sex adjusted HR 2.17 95% CI 1.84-2.57; fully adjusted HR 1.71 95% CI 1.44-2.02); with similar findings for Asian people (age-sex adjusted HR 1.95 95% CI 1.73-2.18; fully adjusted HR 1.62 95% CI 1.431.82).\n\nConclusionsWe have quantified a range of clinical risk factors for death from COVID-19, some of which were not previously well characterised, in the largest cohort study conducted by any country to date. People from Asian and black groups are at markedly increased risk of in-hospital death from COVID-19, and contrary to some prior speculation this is only partially attributable to pre-existing clinical risk factors or deprivation; further research into the drivers of this association is therefore urgently required. Deprivation is also a major risk factor with, again, little of the excess risk explained by co-morbidity or other risk factors. The findings for clinical risk factors are concordant with policies in the UK for protecting those at highest risk. Our OpenSAFELY platform is rapidly adding further NHS patients records; we will update and extend these results regularly.", - "rel_num_authors": 31, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.01.20053413", + "rel_abs": "Key pointsO_ST_ABSQuestionC_ST_ABSHow do nomograms and machine-learning algorithms of severity risk prediction and triage of COVID-19 patients at hospital admission perform?\n\nFindingsThis model was prospectively validated on six test datasets comprising of 426 patients and yielded AUCs ranging from 0.816 to 0.976, accuracies ranging from 70.8% to 93.8%, sensitivities ranging from 83.7% to 100%, and specificities ranging from 41.0% to 95.7%. The cut-off probability values for low, medium, and high-risk groups were 0.072 and 0.244.\n\nMeaningThe findings of this study suggest that our models performs well for the diagnosis and prediction of progression to severe or critical illness of COVID-19 patients and could be used for triage of COVID-19 patients at hospital admission.\n\nIMPORTANCEThe outbreak of the coronavirus disease 2019 (COVID-19) has globally strained medical resources and caused significant mortality for severely and critically ill patients. However, the availability of validated nomograms and the machine-learning model to predict severity risk and triage of affected patients is limited.\n\nOBJECTIVETo develop and validate nomograms and machine-learning models for severity risk assessment and triage for COVID-19 patients at hospital admission.\n\nDESIGN, SETTING, AND PARTICIPANTSA retrospective cohort of 299 consecutively hospitalized COVID-19 patients at The Central Hospital of Wuhan, China, from December 23, 2019, to February 13, 2020, was used to train and validate the models. Six cohorts with 426 patients from eight centers in China, Italy, and Belgium, from February 20, 2020, to March 21, 2020, were used to prospectively validate the models.\n\nMAIN OUTCOME AND MEASURESThe main outcome was the onset of severe or critical illness during hospitalization. Model performances were quantified using the area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, and specificity.\n\nRESULTSOf the 299 hospitalized COVID-19 patients in the retrospective cohort, the median age was 50 years ((interquartile range, 35.5-63.0; range, 20-94 years) and 137 (45.8%) were men. Of the 426 hospitalized COVID-19 patients in the prospective cohorts, the median age was 62.0 years ((interquartile range, 50.0-72.0; range, 19-94 years) and 236 (55.4%) were men. The model was prospectively validated on six cohorts yielding AUCs ranging from 0.816 to 0.976, with accuracies ranging from 70.8% to 93.8%, sensitivities ranging from 83.7% to 100%, and specificities ranging from 41.0% to 95.7%. The cut-off values of the low, medium, and high-risk probabilities were 0.072 and 0.244. The developed online calculators can be found at https://covid19risk.ai/.\n\nCONCLUSION AND RELEVANCEThe machine learning models, nomograms, and online calculators might be useful for the prediction of onset of severe and critical illness among COVID-19 patients and triage at hospital admission. Further prospective research and clinical feedback are necessary to evaluate the clinical usefulness of this model and to determine whether these models can help optimize medical resources and reduce mortality rates compared with current clinical practices.", + "rel_num_authors": 28, "rel_authors": [ { - "author_name": "- The OpenSAFELY Collaborative", - "author_inst": "" - }, - { - "author_name": "Elizabeth Williamson", - "author_inst": "London School of Hygiene and Tropical Medicine" - }, - { - "author_name": "Alex J Walker", - "author_inst": "University of Oxford" - }, - { - "author_name": "Krishnan J Bhaskaran", - "author_inst": "London School of Hygiene and Tropical Medicine" + "author_name": "Guangyao Wu", + "author_inst": "Maastricht university" }, { - "author_name": "Seb Bacon", - "author_inst": "University of Oxford" + "author_name": "Pei Yang", + "author_inst": "The Central Hospital of Wuhan" }, { - "author_name": "Chris Bates", - "author_inst": "TPP" + "author_name": "Henry C. Woodruff", + "author_inst": "Maastricht University" }, { - "author_name": "Caroline E Morton", - "author_inst": "University of Oxford" + "author_name": "Xiangang Rao", + "author_inst": "The Central Hospital of Huangshi" }, { - "author_name": "Helen J Curtis", - "author_inst": "University of Oxford" + "author_name": "Julien Guiot", + "author_inst": "CHU of Liege" }, { - "author_name": "Amir Mehrkar", - "author_inst": "University of Oxford" + "author_name": "Anne-Noelle Frix", + "author_inst": "CHU of Liege" }, { - "author_name": "David Evans", - "author_inst": "University of Oxford" + "author_name": "Michel Moutschen", + "author_inst": "CHU of Liege" }, { - "author_name": "Peter Inglesby", - "author_inst": "University of Oxford" + "author_name": "Renaud Louis", + "author_inst": "CHU of Liege" }, { - "author_name": "Jonathan Cockburn", - "author_inst": "TPP" + "author_name": "Jiawei Li", + "author_inst": "China Resources Wuhan Iron and Steel Hospital" }, { - "author_name": "Helen I Mcdonald", - "author_inst": "London School of Hygiene and Tropical Medicine" + "author_name": "Jing Li", + "author_inst": "The Central Hospital of Shaoyang" }, { - "author_name": "Brian MacKenna", - "author_inst": "University of Oxford" + "author_name": "Chenggong Yan", + "author_inst": "Maastricht University" }, { - "author_name": "Laurie Tomlinson", - "author_inst": "London School of Hygiene and Tropical Medicine" + "author_name": "Dan Du", + "author_inst": "The Central Hospital of Wuhan" }, { - "author_name": "Ian J Douglas", - "author_inst": "London School of Hygiene and Tropical Medicine" + "author_name": "Shengchao Zhao", + "author_inst": "The Central Hospital of Wuhan" }, { - "author_name": "Christopher T Rentsch", - "author_inst": "London School of Hygiene and Tropical Medicine" + "author_name": "Yi Ding", + "author_inst": "The Central Hospital of Wuhan" }, { - "author_name": "Rohini Mathur", - "author_inst": "London School of Hygiene and Tropical Medicine" + "author_name": "Bin Liu", + "author_inst": "The Central Hospital of Wuhan" }, { - "author_name": "Angel Wong", - "author_inst": "London School of Hygiene and Tropical Medicine" + "author_name": "Wenwu Sun", + "author_inst": "The Central Hospital of Wuhan" }, { - "author_name": "Richard Grieve", - "author_inst": "London School of Hygiene and Tropical Medicine" + "author_name": "Fabrizio Albarello", + "author_inst": "IRCCS, Lazzaro Spallanzani, Via Portuense" }, { - "author_name": "David Harrison", - "author_inst": "ICNARC" + "author_name": "Vincenzo Schinina", + "author_inst": "IRCCS, Lazzaro Spallanzani, Via Portuense" }, { - "author_name": "Harriet Forbes", - "author_inst": "London School of Hygiene and Tropical Medicine" + "author_name": "Emanuele Nicastri", + "author_inst": "IRCCS, Lazzaro Spallanzani, Via Portuense" }, { - "author_name": "Anna Schultze", - "author_inst": "London School of Hygiene and Tropical Medicine" + "author_name": "Mariaelena Occhipinti", + "author_inst": "Clinical and Experimental Sciences \"Mario Serio\", University of Florence" }, { - "author_name": "Richard T Croker", - "author_inst": "University of Oxford" + "author_name": "Giovanni Barisione", + "author_inst": "IRCCS Ospedale Policlinico San Martino" }, { - "author_name": "John Parry", - "author_inst": "TPP" + "author_name": "Emanuela Barisione", + "author_inst": "IRCCS Ospedale Policlinico San Martino" }, { - "author_name": "Frank Hester", - "author_inst": "TPP" + "author_name": "Iva Halilaj", + "author_inst": "Maastricht University" }, { - "author_name": "Sam Harper", - "author_inst": "TPP" + "author_name": "Yuanliang Xie", + "author_inst": "The Central Hospital of Wuhan" }, { - "author_name": "Rafael Perera", - "author_inst": "University of Oxford" + "author_name": "Xiang Wang", + "author_inst": "The Central Hospital of Wuhan" }, { - "author_name": "Stephen Evans", - "author_inst": "London School of Hygiene and Tropical Medicine" + "author_name": "Pierre Lovinfosse", + "author_inst": "CHU of Liege" }, { - "author_name": "Liam Smeeth", - "author_inst": "London School of Hygiene and Tropical Medicine" + "author_name": "Jianlin Wu", + "author_inst": "Affiliated Zhongshan Hospital of Dalian University" }, { - "author_name": "Ben Goldacre", - "author_inst": "University of Oxford" + "author_name": "Philippe Lambin", + "author_inst": "Maastricht University" } ], "version": "1", - "license": "cc_by", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2020.05.01.20087239", @@ -1479416,41 +1479469,49 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.05.01.20087809", - "rel_title": "Time-adjusted Analysis Shows Weak Associations Between BCG Vaccination Policy and COVID-19 Disease Progression", + "rel_doi": "10.1101/2020.05.02.20088344", + "rel_title": "A new role for Biofoundries in rapid prototyping, development, and validation of automated clinical diagnostic tests for SARS-CoV-2", "rel_date": "2020-05-06", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.01.20087809", - "rel_abs": "In this study, we ascertain the associations between BCG vaccination policies and progression of COVID-19 through analysis of various time-adjusted indicators either directly extracted from the incidence and death reports, or estimated as parameters of disease progression models. We observe weak correlation between BCG vaccination status and indicators related to disease reproduction characteristics. We did not find any associations with case fatality rates (CFR), but the differences in CFR estimates are at present likely dominated by differences in testing and case reporting between countries.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.02.20088344", + "rel_abs": "The SARS-CoV-2 pandemic has shown how the rapid rise in demand for patient and community sample testing, required for tracing and containing a highly infectious disease, has quickly overwhelmed testing capability globally. With most diagnostic infrastructure dependent on specialised instruments, their exclusive reagent supplies quickly become bottlenecks in times of peak demand, creating an urgent need for novel approaches to boost testing capacity. We address this challenge by refocusing the full synthetic biology stack available at the London Biofoundry onto the development of alternative patient sample testing pipelines. We present a reagent-agnostic automated SARS-CoV-2 testing platform that can be quickly deployed and scaled, and that accepts a diverse range of reagents. Using an in-house-generated, open-source, MS2-virus-like-particle-SARS-CoV-2 standard, we validate RNA extraction and RT-qPCR workflows as well as two novel detection assays based on CRISPR-Cas and Loop-mediated isothermal Amplification (LAMP) approaches. In collaboration with an NHS diagnostic testing lab, we report the performance of the overall workflow and benchmark SARS-CoV-2 detection in patient samples via RT-qPCR, CRISPR-Cas, and LAMP against clinical test sets. The validated RNA extraction and RT-qPCR platform has been installed in NHS diagnostic labs with a testing capacity of 1000 samples per day and now contributes to increased patient sample processing in the UK while we continue to refine and develop novel high-throughput diagnostic methods. Finally, our workflows and protocols can be quickly implemented and adapted by members of the Global Biofoundry Alliance and the wider scientific and medical diagnostics community.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Katarina Bodova", - "author_inst": "Comenius University in Bratislava" + "author_name": "Michael A Crone", + "author_inst": "Imperial College London" }, { - "author_name": "Vladimir Boza", - "author_inst": "Comenius University in Bratislava" + "author_name": "Miles Priestman", + "author_inst": "Imperial College London" }, { - "author_name": "Brona Brejova", - "author_inst": "Comenius University in Bratislava" + "author_name": "Marta Ciechonska", + "author_inst": "Imperial College London" }, { - "author_name": "Richard Kollar", - "author_inst": "Comenius University in Bratislava" + "author_name": "Kirsten Jensen", + "author_inst": "Imperial College London" }, { - "author_name": "Katarina Mikusova", - "author_inst": "Comenius University in Bratislava" + "author_name": "David J Sharp", + "author_inst": "Imperial College London" }, { - "author_name": "Tomas Vinar", - "author_inst": "Comenius University in Bratislava" + "author_name": "Paul Randell", + "author_inst": "Imperial College Healthcare NHS Trust" + }, + { + "author_name": "Marko Storch", + "author_inst": "Imperial College London" + }, + { + "author_name": "Paul Freemont", + "author_inst": "Imperial College London" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1480822,45 +1480883,25 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.05.03.20089482", - "rel_title": "The importance of the timing of quarantine measures before symptom onset to prevent COVID-19 outbreaks - illustrated by Hong Kong's intervention model", + "rel_doi": "10.1101/2020.05.03.20089854", + "rel_title": "A systematic review and meta-analysis of published research data on COVID-19 infection-fatality rates", "rel_date": "2020-05-06", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.03.20089482", - "rel_abs": "BackgroundThe rapid expansion of the current COVID-19 outbreak has caused a global pandemic but how quarantine-based measures can prevent or suppress an outbreak without other more intrusive interventions has not yet been determined. Hong Kong had a massive influx of travellers from mainland China, where the outbreak began, during the early expansion period coinciding with the Lunar New Year festival; however, the spread of the virus has been relatively limited even without imposing severe control measures, such as a full city lockdown. Understanding how quarantine measures in Hong Kong were effective in limiting community spread can provide us with valuable insights into how to suppress an outbreak. However, challenges exist in evaluating the effects of quarantine on COVID-19 transmission dynamics in Hong Kong due to the fact that the effects of border control have to be also taken into account.\n\nMethodsWe have developed a two-layered susceptible-exposed-infectious-quarantined-recovered (SEIQR) meta-population model which can estimate the effects of quarantine on virus transmissibility after stratifying infections into imported and subsequent community infections, in a region closely connected to the outbreaks source. We fitted the model to both imported and local confirmed case data with symptom onset from 18 January to 29 February 2020 in Hong Kong, together with daily transportation data and the transmission dynamics of COVID-19 from Wuhan and mainland China. After model fitting, epidemiological parameters and the timing of the start of quarantine for infected cases were estimated.\n\nResultsThe model estimated that the reproduction number of COVID-19 in Hong Kong was 0.76 (95% CI, 0.66 to 0.86), achieved through quarantining infected cases -0.57 days (95% CI, -4.21 - 3.88) relative to symptom onset, with an estimated incubation time of 5.43 days (95% CI, 1.30 - 9.47). However, if delaying the quarantine start by more than 1.43 days, the reproduction number would be greater than one, making community spread more likely. The model also determined the timing of the start of quarantine necessary in order to suppress an outbreak in the presence of population immunity.\n\nConclusionThe results suggest that the early quarantine for infected cases before symptom onset is a key factor to prevent COVID-19 outbreak.", - "rel_num_authors": 7, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.03.20089854", + "rel_abs": "An important unknown during the COVID-19 pandemic has been the infection-fatality rate (IFR). This differs from the case-fatality rate (CFR) as an estimate of the number of deaths as a proportion of the total number of cases, including those who are mild and asymptomatic. While the CFR is extremely valuable for experts, IFR is increasingly being called for by policy-makers and the lay public as an estimate of the overall mortality from COVID-19.\n\nMethodsPubmed, Medline, SSRN, and Medrxiv were searched using a set of terms and Boolean operators on 25/04/2020 and re-searched 14/05/2020, 21/05/2020, and 16/06/2020. Articles were screened for inclusion by both authors. Meta-analysis was performed in Stata 15.1 using the metan command, based on IFR and confidence intervals extracted from each study. Google/Google Scholar was used to assess the grey literature relating to government reports.\n\nResultsAfter exclusions, there were 24 estimates of IFR included in the final meta-analysis, from a wide range of countries, published between February and June 2020.\n\nThe meta-analysis demonstrated a point-estimate of IFR of 0.68% (0.53-0.82%) with high heterogeneity (p<0.001).\n\nConclusionBased on a systematic review and meta-analysis of published evidence on COVID-19 until May, 2020, the IFR of the disease across populations is 0.68% (0.53-0.82%). However, due to very high heterogeneity in the meta-analysis, it is difficult to know if this represents the true point estimate. It is likely that, due to age and perhaps underlying comorbidities in the population, different places will experience different IFRs due to the disease. Given issues with mortality recording, it is also likely that this represents an underestimate of the true IFR figure. More research looking at age-stratified IFR is urgently needed to inform policy-making on this front.\n\nKey messages- COVID-19 infection-fatality rate (IFR) is an important statistic for policy about the disease\n- Published estimates vary, with a true fatality rate hard to calculate\n- Systematically reviewing the literature and meta-analyzing the results shows an IFR of 0.68% (0.53-0.82%)", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Hsiang-Yu Yuan", - "author_inst": "City University of Hong Kong" - }, - { - "author_name": "Guiyuan Han", - "author_inst": "City University of Hong Kong" - }, - { - "author_name": "Hsiangkuo Yuan", - "author_inst": "Thomas Jefferson University Hospital" - }, - { - "author_name": "Susanne Pfeiffer", - "author_inst": "City University of Hong Kong" - }, - { - "author_name": "Axiu Mao", - "author_inst": "City University of Hong Kong" - }, - { - "author_name": "Lindsey Wu", - "author_inst": "London School of Hygiene and Tropical Medicine" + "author_name": "Gideon Meyerowitz-Katz", + "author_inst": "University of Wollongong" }, { - "author_name": "Dirk Pfeiffer", - "author_inst": "City University of Hong Kong" + "author_name": "Lea Merone", + "author_inst": "James Cook University" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1482384,21 +1482425,25 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.05.01.20087759", - "rel_title": "Effect of Temperature on the Transmission of COVID-19: A Machine Learning Case Study in Spain", + "rel_doi": "10.1101/2020.05.01.20087478", + "rel_title": "Antibodies to SARS/CoV-2 in arbitrarily-selected Atlanta residents", "rel_date": "2020-05-06", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.01.20087759", - "rel_abs": "The novel coronavirus (COVID-19) has already spread to almost every country in the world and has infected over 3 million people. To understand the transmission mechanism of this highly contagious virus, it is necessary to study the potential factors, including meteorological conditions. Here, we present a machine learning approach to study the effect of temperature, humidity and wind speed on the number of infected people in the three most populous autonomous communities in Spain. We find that there is a moderate inverse correlation between temperature and the daily number of infections. This correlation manifests for temperatures recorded up to 6 days before the onset, which corresponds well to the known mean incubation period of COVID-19. We also show that the correlation for humidity and wind speed is not significant.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.01.20087478", + "rel_abs": "We quantitated anti-SARS/CoV-2 IgG and IgM by ELISA in self-collected blood samples (n=142) in arbitrarily-selected metro Atlanta residents, primarily acquaintances of the authors lab members from 4/17-4/27, 2020. Archived serum (n=34), serum from nucleic acid test (NAT)-positive subjects (n=4), and samples collected from NAT-positive community members (n=4) served to validate the assay. The range of anti-SARS/CoV-2 antibodies in archived and NAT-positive sera indicated need to compromise sensitivity or specificity. Accordingly, we set a cutoff of 4 SD above the mean for IgG and 3 SD above the mean for IgM to indicate that an individual had been exposed, and developed some degree of immunity, to SARS/CoV-2. The IgG cutoff clearly compromised sensitivity but offered high specificity, both of which were harder to gauge for IgM. Based on these cutoffs, excluding subjects whose participation resulted from self-suspected SARS/CoV-2 infection, we found 7.1% positivity for anti-SARS/CoV-2 IgG (3 of 127 subjects) or IgM (6 of 127). While we do not claim this small immune survey is broadly representative of metro Atlanta, and we have greater confidence in the IgG results, which had only 2.4% positivity, it nonetheless demonstrates that persons with antibodies to SARS/CoV-2, whove not suspected theyd been exposed to this virus, can readily be found in various Atlanta area neighborhoods (9 positives were in 8 zip codes). Accordingly, these results support the notion that dissemination of the virus is more widespread than testing would indicate but also suggests that most persons in metro Atlanta remain vulnerable to this virus. More generally, these results support the general utility of sero-surveillance to guide public policy but also highlight the difficulty of discerning if individuals have immunity to SARS/CoV-2.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Amir Abdollahi", - "author_inst": "Universitat Politecnica de Catalunya" + "author_name": "Jun Zou", + "author_inst": "Georgia State University" }, { - "author_name": "Maryam Rahbaralam", - "author_inst": "Barcelona Supercomputing Center" + "author_name": "Alexis Bretin", + "author_inst": "Georgia State University" + }, + { + "author_name": "Andrew Gewirtz", + "author_inst": "Georgia State University" } ], "version": "1", @@ -1483886,27 +1483931,59 @@ "category": "cardiovascular medicine" }, { - "rel_doi": "10.1101/2020.05.02.20088492", - "rel_title": "Simulations of the spread of COVID-19 and control policies in Tunisia", - "rel_date": "2020-05-06", + "rel_doi": "10.1101/2020.04.30.20084780", + "rel_title": "COVID-19 length of hospital stay: a systematic review and data synthesis", + "rel_date": "2020-05-05", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.02.20088492", - "rel_abs": "We develop and analyze in this work an epidemiological model for COVID-19 using Tunisian data. Our aims are first to evaluate Tunisian control policies for COVID-19 and secondly to understand the effect of different screening, quarantine and containment strategies and the rule of the asymptomatic patients on the spread of the virus in the Tunisian population. With this work, we show that Tunisian control policies are efficient in screening infected and asymptomatic individuals and that if containment and curfew are maintained the epidemic will be quickly contained.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.30.20084780", + "rel_abs": "BackgroundThe COVID-19 pandemic has placed an unprecedented strain on health systems, with rapidly increasing demand for healthcare in hospitals and intensive care units (ICUs) worldwide. As the pandemic escalates, determining the resulting needs for healthcare resources (beds, staff, equipment) has become a key priority for many countries. Projecting future demand requires estimates of how long patients with COVID-19 need different levels of hospital care.\n\nMethodsWe performed a systematic review to gather data on length of stay (LoS) of patients with COVID-19 in hospital and in ICU. We subsequently developed a method to generate LoS distributions which combines summary statistics reported in multiple studies, accounting for differences in sample sizes. Applying this approach we provide distributions for general hospital and ICU LoS from studies in China and elsewhere, for use by the community.\n\nResultsWe identified 52 studies, the majority from China (46/52). Median hospital LoS ranged from 4 to 53 days within China, and 4 to 21 days outside of China, across 45 studies. ICU LoS was reported by eight studies - four each within and outside China - with median values ranging from 6 to 12 and 4 to 19 days, respectively. Our summary distributions have a median hospital LoS of 14 (IQR: 10-19) days for China, compared with 5 (IQR: 3-9) days outside of China. For ICU, the summary distributions are more similar (median (IQR) of 8 (5-13) days for China and 7 (4-11) days outside of China). There was a visible difference by discharge status, with patients who were discharged alive having longer LoS than those who died during their admission, but no trend associated with study date.\n\nConclusionPatients with COVID-19 in China appeared to remain in hospital for longer than elsewhere. This may be explained by differences in criteria for admission and discharge between countries, and different timing within the pandemic. In the absence of local data, the combined summary LoS distributions provided here can be used to model bed demands for contingency planning and then updated, with the novel method presented here, as more studies with aggregated statistics emerge outside China.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Slimane Ben Miled", - "author_inst": "Institut Pasteur de Tunis, University of Tunis el Manar" + "author_name": "Eleanor M Rees", + "author_inst": "London School of Hygiene and Tropical Medicine" + }, + { + "author_name": "Emily S Nightingale", + "author_inst": "London School of Hygiene and Tropical Medicine" }, { - "author_name": "Amira Kebir", - "author_inst": "Institut Pasteur de Tunis. University of Tunis el Manar" + "author_name": "Yalda Jafari", + "author_inst": "London School of Hygiene and Tropical Medicine" + }, + { + "author_name": "Naomi Waterlow", + "author_inst": "London School of Hygiene and Tropical Medicine" + }, + { + "author_name": "Samuel Clifford", + "author_inst": "London School of Hygiene and Tropical Medicine" + }, + { + "author_name": "Carl A B Pearson", + "author_inst": "London School of Hygiene and Tropical Medicine" + }, + { + "author_name": "CMMID Working Group", + "author_inst": "" + }, + { + "author_name": "Thibaut Jombert", + "author_inst": "London School of Hygiene and Tropical Medicine" + }, + { + "author_name": "Simon R Procter", + "author_inst": "London School of Hygiene and Tropical Medicine" + }, + { + "author_name": "Gwenan M Knight", + "author_inst": "London School of Hygiene and Tropical Medicine" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2020.04.29.20084277", @@ -1485304,29 +1485381,41 @@ "category": "cardiovascular medicine" }, { - "rel_doi": "10.1101/2020.04.30.20086611", - "rel_title": "Mathematical Model with Social Distancing Parameter for Early Estimation of COVID-19 Spread", + "rel_doi": "10.1101/2020.04.30.20086348", + "rel_title": "Beyond predicting the number of infections: predicting who is likely to be COVID negative or positive", "rel_date": "2020-05-05", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.30.20086611", - "rel_abs": "COVID-19 is well known to everyone in the world. It has spread around the world. No vaccine or antiviral treatment is available till now. COVID-19 patients are increasing day by day. All countries have adopted social distancing as a preventive measure to reduce spread. It becomes necessary to estimate the number of peoples going to be affected with COVID-19 in advance so that necessary arrangements can be done. Mathematical models are used to provide early disease estimation based on limited parameters. In the present manuscript, a novel mathematical model with a social distancing parameter has been proposed to provide early COVID-19 spread estimation. The model has been validated with real data set. It has been observed that the proposed model is more accurate in spread estimation.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.30.20086348", + "rel_abs": "This study provides the first attempt to identify people at greater risk of COVID-19 infection, enabling more targeted infectious disease prevention and control, which are especially important in the ongoing shortage of COVID-19 testing.\n\nWe conducted a primary survey of 521 adults on April 1-10, 2020 in Iran, where the official infection rate was 0{middle dot}08%. In our sample, 3% reported being COVID-19 positive and 15% were unsure of their status. This relatively high positive rate enabled us to conduct the analysis at the 5% significance level.\n\nAt the time of the survey, 44% of the adults worked from home; 26% still went to work in their workplaces; 27% had stopped working due to the COVID-19 pandemic; and 3% were unemployed. Adults who exercised more were more likely to be COVID-19 negative. Each additional hour of exercise per day predicted a 78% increase in the likelihood of being COVID-19 negative. Adults with chronic medical illnesses were 48% more likely to be COVID-19 negative. In terms of work situation, those who worked from home were the most likely to be COVID-19 negative, and those who had stopped working were the most likely to be COVID-19 positive. Individuals in larger organizations were less likely to be COVID-19 positive.\n\nGiven the testing shortage in many countries, we identify a novel approach to predict the likelihood of COVID-19 infection by a set of personal and work situation characteristics, in order to help to identify individuals with more or less risk of contracting the virus. We hope this research opens a new research avenue to identify the individual risk factors of COVID-19 infection to enable more targeted infectious disease prevention, communication, testing, and control to complement the effort to expand testing capacity.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Saroj Kumar Chandra", - "author_inst": "IIITDM, Jabalpur, India" + "author_name": "Stephen X. Zhang", + "author_inst": "University of Adelaide" }, { - "author_name": "Avaneesh Singh", - "author_inst": "IIITDMJ" + "author_name": "Shuhua Sun", + "author_inst": "Tulane University" }, { - "author_name": "Manish Kumar Bajpai", - "author_inst": "IIITDMJ" + "author_name": "Asghar Afshar Jahanshahi", + "author_inst": "Pontifical Catholic University of Peru" + }, + { + "author_name": "Yifei Wang", + "author_inst": "Tongji University" + }, + { + "author_name": "Abbas Nazarian Madavani", + "author_inst": "Shahid Rajaee University" + }, + { + "author_name": "Maryam Mokhtari Dinani", + "author_inst": "Alzahra University" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1486562,51 +1486651,59 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2020.05.04.075911", - "rel_title": "Global Spread of SARS-CoV-2 Subtype with Spike Protein Mutation D614G is Shaped by Human Genomic Variations that Regulate Expression of TMPRSS2 and MX1 Genes", + "rel_doi": "10.1101/2020.05.04.077842", + "rel_title": "SARS-CoV-2 Spike Glycoprotein Receptor Binding Domain is Subject to Negative Selection with Predicted Positive Selection Mutations", "rel_date": "2020-05-05", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.04.075911", - "rel_abs": "COVID-19 pandemic is a major human tragedy. Worldwide, SARS-CoV-2 has already infected over 3 million and has killed about 230,000 people. SARS-CoV-2 originated in China and, within three months, has evolved to an additional 10 subtypes. One particular subtype with a non-silent (Aspartate to Glycine) mutation at 614th position of the Spike protein (D614G) rapidly outcompeted other pre-existing subtypes, including the ancestral. We assessed that D614G mutation generates an additional serine protease (Elastase) cleavage site near the S1-S2 junction of the Spike protein. We also identified that a single nucleotide deletion (delC) at a known variant site (rs35074065) in a cis-eQTL of TMPRSS2, is extremely rare in East Asians but is common in Europeans and North Americans. The delC allele facilitates entry of the 614G subtype into host cells, thus accelerating the spread of 614G subtype in Europe and North America where the delC allele is common. The delC allele at the cis-eQTL locus rs35074065 of TMPRSS2 leads to overexpression of both TMPRSS2 and a nearby gene MX1. The cis-eQTL site, rs35074065 overlaps with a transcription factor binding site of an activator (IRF1) and a repressor (IRF2). IRF1 activator can bind to variant delC allele, but IRF2 repressor fails to bind. Thus, in an individual carrying the delC allele, there is only activation, but no repression. On viral entry, IRF1 mediated upregulation of MX1 leads to neutrophil infiltration and processing of 614G mutated Spike protein by neutrophil Elastase. The simultaneous processing of 614G spike protein by TMPRSS2 and Elastase serine proteases facilitates the entry of the 614G subtype into host cells. Thus, SARS-CoV-2, particularly the 614G subtype, has spread more easily and with higher frequency to Europe and North America where the delC allele regulating expression of TMPRSS2 and MX1 host proteins is common, but not to East Asia where this allele is rare.", - "rel_num_authors": 8, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.04.077842", + "rel_abs": "COVID-19 is a highly contagious disease caused by a novel coronavirus SARS-CoV-2. The interaction between SARS-CoV-2 spike protein and the host cell surface receptor ACE2 is responsible for mediating SARS-CoV-2 infection. By analyzing the spike-hACE2 interacting surface, we predicted many hot spot residues that make major contributions to the binding affinity. Mutations on most of these residues are likely to be deleterious, leading to less infectious virus strains that may suffer from negative selection. Meanwhile, several residues with mostly advantageous mutations have been predicted. It is more probable that mutations on these residues increase the transmission ability of the virus by enhancing spike-hACE2 interaction. So far, only a limited number of mutations has been reported in this region. However, the list of hot spot residues with predicted downstream effects from this study can still serve as a tracking list for SARS-CoV-2 evolution studies. Coincidentally, one advantageous mutation, p.476G>S, started to surge in the last couple of weeks based on the data submitted to the public domain, indicating that virus strains with increased transmission ability may have already spread.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Chandrika Bhattacharyya", - "author_inst": "National Institute of Biomedical Genomics, Kalyani, West Bengal, India" + "author_name": "You Li", + "author_inst": "HitGen Inc." + }, + { + "author_name": "Ye Wang", + "author_inst": "HitGen Inc." + }, + { + "author_name": "Yaping Qiu", + "author_inst": "HitGen Inc." }, { - "author_name": "Chitrarpita Das", - "author_inst": "National Institute of Biomedical Genomics, Kalyani, West Bengal, India" + "author_name": "Zhen Gong", + "author_inst": "HitGen Inc." }, { - "author_name": "Arnab Ghosh", - "author_inst": "National Institute of Biomedical Genomics, Kalyani, West Bengal, India" + "author_name": "Lei Deng", + "author_inst": "HitGen Inc." }, { - "author_name": "Animesh K Singh", - "author_inst": "National Institute of Biomedical Genomics, Kalyani, West Bengal, India" + "author_name": "Min Pan", + "author_inst": "Sichuan Provincial Center for Disease Control and Prevention" }, { - "author_name": "Souvik Mukherjee", - "author_inst": "National Institute of Biomedical Genomics, Kalyani, West Bengal, India" + "author_name": "Huiping Yang", + "author_inst": "Sichuan Provincial Center for Disease Control and Prevention" }, { - "author_name": "Partha P Majumder", - "author_inst": "National Institute of Biomedical Genomics, Kalyani, West Bengal, India" + "author_name": "Jianan Xu", + "author_inst": "Sichuan Provincial Center for Disease Control and Prevention" }, { - "author_name": "Analabha Basu", - "author_inst": "National Institute of Biomedical Genomics, Kalyani, West Bengal, India" + "author_name": "Li Yang", + "author_inst": "HitGen Inc." }, { - "author_name": "Nidhan K Biswas", - "author_inst": "National Institute of Biomedical Genomics, Kalyani, West Bengal, India" + "author_name": "Jin Li", + "author_inst": "HitGen Inc." } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "new results", - "category": "genomics" + "category": "bioinformatics" }, { "rel_doi": "10.1101/2020.05.03.075549", @@ -1488132,31 +1488229,91 @@ "category": "sexual and reproductive health" }, { - "rel_doi": "10.1101/2020.04.28.20083261", - "rel_title": "A Simple Early Warning Signal for COVID-19", + "rel_doi": "10.1101/2020.05.01.20081026", + "rel_title": "Sensitivity of nasopharyngeal swabs and saliva for the detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)", "rel_date": "2020-05-05", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.28.20083261", - "rel_abs": "The paper provides some initial evidence that daily mortality rates (for any cause) by municipality or province can be used as a statistically reliable predictor of looming COVID-19 crises. Using recently published deaths figures for 1,689 Italian municipalities, we estimate the growth in daily mortality rates between the period 2015-2019 and 2020 by province. All provinces that experienced a major COVID-19 shock in mid-March 2020 had increases in mortality rates of 100% or above already in early February 2020. This increase was particularly strong for males and older people, two recognizable features of COVID-19. Using a panel fixed effect model, we show that the association between these early increases in mortality for any cause and the March 2020 COVID-19 shock is strong and significant. We conclude that the growth in mortality rates can be used as a statistically reliable predictor of COVID-19 crises.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.01.20081026", + "rel_abs": "We enrolled 53 consecutive in-patients with COVID-19 at six hospitals in Toronto, Canada, and tested one nasopharyngeal swab/saliva sample pair from each patient for SARS-CoV-2. Overall, sensitivity was 89% for nasopharyngeal swabs and 77% for saliva (p=NS); difference in sensitivity was greatest for sample pairs collected later in illness.", + "rel_num_authors": 18, "rel_authors": [ { - "author_name": "Lidia Ceriani", - "author_inst": "Georgetown University, USA" + "author_name": "Alainna J. Jamal", + "author_inst": "University of Toronto" }, { - "author_name": "Carlos Hernandez-Suarez", - "author_inst": "Colima University, Mexico" + "author_name": "Mohammad Mohammad", + "author_inst": "Sinai Health System" }, { - "author_name": "Paolo Verme", - "author_inst": "World bank group" + "author_name": "Eric Coomes", + "author_inst": "University of Toronto" + }, + { + "author_name": "Jeff Powis", + "author_inst": "Michael Garron Hospital" + }, + { + "author_name": "Angel Li", + "author_inst": "Sinai Health System" + }, + { + "author_name": "Aimee Paterson", + "author_inst": "Sinai Health System" + }, + { + "author_name": "Sofia Anceva-Sami", + "author_inst": "Sinai Health System" + }, + { + "author_name": "Shiva Barati", + "author_inst": "Sinai Health System" + }, + { + "author_name": "Gloria Crowl", + "author_inst": "Sinai Health System" + }, + { + "author_name": "Amna Faheem", + "author_inst": "Sinai Health System" + }, + { + "author_name": "Lubna Farooqi", + "author_inst": "Sinai Health System" + }, + { + "author_name": "Saman Khan", + "author_inst": "Sinai Health System" + }, + { + "author_name": "Karren Prost", + "author_inst": "Sunnybrook Health Sciences Centre" + }, + { + "author_name": "Susan Poutanen", + "author_inst": "susan.poutanen@sinaihealth.ca" + }, + { + "author_name": "Lily Yip", + "author_inst": "Sunnybrook Health Sciences Centre" + }, + { + "author_name": "Zoe Zhong", + "author_inst": "Sinai Health System" + }, + { + "author_name": "Allison J McGeer", + "author_inst": "Sinai Health System" + }, + { + "author_name": "Samira Mubareka", + "author_inst": "Sunnybrook Health Sciences Centre" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "health economics" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2020.04.30.20081257", @@ -1489706,35 +1489863,59 @@ "category": "health informatics" }, { - "rel_doi": "10.1101/2020.04.28.20080838", - "rel_title": "COVID-19 Pandemic Response Simulation: Impact of Non-pharmaceutical Interventions on Ending Lockdowns", + "rel_doi": "10.1101/2020.04.28.20081844", + "rel_title": "Enzyme immunoassay for SARS-CoV-2 antibodies in dried blood spot samples: A minimally-invasive approach to facilitate community- and population-based screening", "rel_date": "2020-05-04", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.28.20080838", - "rel_abs": "As many federal and state governments are starting to ease restrictions on non-pharmaceutical interventions (NPIs) used to flatten the curve, we developed an agent-based simulation to model the incidence of COVID-19 in King County, WA under several scenarios. While NPIs were effective in flattening the curve, any relaxation of social distancing strategies yielded a second wave. Even if daily confirmed cases dropped to one digit, daily incidence can peak again to 874 cases without import cases. Therefore, policy makers should be very cautious in reopening society.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.28.20081844", + "rel_abs": "BackgroundSerological testing for SARS-CoV-2 IgG antibodies is needed to document the community prevalence and distribution of the virus, particularly since many individuals have mild symptoms and cannot access molecular diagnostic testing of naso-pharyngeal swabs. However, the requirement for serum/plasma limits serological testing to clinical settings where it is feasible to collect and process venous blood. To address this problem we developed a serological test for SARS-CoV-2 IgG antibodies that requires only a single drop of capillary whole blood, collected from a simple finger prick and dried on filter paper (dried blood spot, DBS).\n\nMethodsEnzyme linked immunosorbent assay (ELISA) was optimized to detect SARS-CoV-2 IgG antibodies against the receptor-binding domain (RBD) of the spike protein. DBS samples were eluted overnight and transferred to a 96-well plate coated with antigen, and anti-human IgG-HRP was used to generate signal in proportion to bound antibody. DBS samples spiked with anti-SARS IgG antibody, and samples from known positive and negative cases, were compared to evaluate assay performance.\n\nResultsAnalysis of samples with known concentrations of anti-SARS IgG produced the expected pattern of dose-response. Optical density (OD) values were significantly elevated for known positive cases in comparison with samples from unexposed individuals.\n\nDiscussionDBS ELISA provides a minimally-invasive alternative to venous blood collection that combines the convenience of sample collection in the home or non-clinical setting with the quantitation of ELISA in the lab. Serological testing for SARS-CoV-2 IgG antibodies in DBS samples should facilitate research across a wide range of community- and population-based settings on seroprevalence, predictors and duration of antibody responses, as well as correlates of protection from reinfection, each of which is critically important for pandemic control.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Serin Lee", - "author_inst": "University of Washington" + "author_name": "Thomas W McDade", + "author_inst": "Northwestern University" }, { - "author_name": "Zelda B Zabinsky", - "author_inst": "University of Washington" + "author_name": "Elizabeth McNally", + "author_inst": "Northwestern University" }, { - "author_name": "Stephen M Kofsky", - "author_inst": "UW Healthcare Analytics Lab" + "author_name": "Richard Thomas D'Aquila", + "author_inst": "Northwestern University" }, { - "author_name": "Shan Liu", - "author_inst": "University of Washington" + "author_name": "Brian Mustanski", + "author_inst": "Northwestern University" + }, + { + "author_name": "Aaron Miller", + "author_inst": "Northwestern University" + }, + { + "author_name": "Lauren Vaught", + "author_inst": "Northwestern University" + }, + { + "author_name": "Nina Reiser", + "author_inst": "Northwestern University" + }, + { + "author_name": "Elena Bogdanovic", + "author_inst": "Northwestern University" + }, + { + "author_name": "Aaron Zelikovich", + "author_inst": "Northwestern University" + }, + { + "author_name": "Alexis Demonbreun", + "author_inst": "Northwestern University" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "health policy" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2020.04.26.20081059", @@ -1491448,47 +1491629,95 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.05.03.074930", - "rel_title": "Design of an Epitope-Based Peptide Vaccine against the Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2): A Vaccine Informatics Approach", + "rel_doi": "10.1101/2020.05.03.074567", + "rel_title": "Large scale genomic analysis of 3067 SARS-CoV-2 genomes reveals a clonal geodistribution and a rich genetic variations of hotspots mutations", "rel_date": "2020-05-03", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.03.074930", - "rel_abs": "The recurrent and recent global outbreak of SARS-CoV-2 has turned into a global concern which has infected more than 19-million people all over the globe, and this number is increasing in hours. Unfortunate no vaccine or specific treatment is available, which make it more deadly. A vaccine-informatics approach has shown significant breakthrough in peptide-based epitope mapping and opens the new horizon in vaccine development. In this study, we have identified a total of 15 antigenic peptides (including T and B cells) in the surface glycoprotein of SARS-CoV-2 which showed non-toxic nature, non-allergenic, highly antigenic and non-mutated in other SARS-CoV-2 virus strains. The population coverage analysis has found that CD4+ T-cell peptides showed higher cumulative population coverage over to CD8+ peptides in the 16 different geographical regions of the world. We identified twelve peptides (LTDEMIAQY, WTAGAAAYY, WMESEFRVY, IRASANLAA, FGAISSVLN, VKQLSSNFG, FAMQMAYRF, FGAGAALQI, YGFQPTNGVGYQ, LPDPSKPSKR, QTQTNSPRRARS and VITPGTNTSN) that are 80% - 90% identical with experimentally determined epitopes of SARS-CoV, and this will likely be beneficial for a quick progression of the vaccine design. Moreover, docking analysis suggested that identified peptides are tightly bound in the groove of HLA molecules which can induce the T-cell response. Overall this study allows us to determine potent peptide antigen targets in surface glycoprotein on intuitive grounds which open up a new horizon in COVID-19 research. However, this study needs experimental validation by in vitro and in vivo.", - "rel_num_authors": 7, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.03.074567", + "rel_abs": "In late December 2019, an emerging viral infection COVID-19 was identified in Wuhan, China, and became a global pandemic. Characterization of the genetic variants of SARS-CoV-2 is crucial in following and evaluating it spread across countries. In this study, we collected and analyzed 3,067 SARS-CoV-2 genomes isolated from 55 countries during the first three months after the onset of this virus. Using comparative genomics analysis, we traced the profiles of the whole-genome mutations and compared the frequency of each mutation in the studied population. The accumulation of mutations during the epidemic period with their geographic locations was also monitored. The results showed 782 variant sites, of which 512 (65.47%) had a non-synonymous effect. Frequencies of mutated alleles revealed the presence of 38 recurrent non-synonymous mutations, including ten hotspot mutations with a prevalence higher than 0.10 in this population and distributed in six SARS-CoV-2 genes. The distribution of these recurrent mutations on the world map revealed certain genotypes specific to the geographic location. We also found co-occurring mutations resulting in the presence of several haplotypes. Moreover, evolution over time has shown a mechanism of mutation co-accumulation which might affect the severity and spread of the SARS-CoV-2.\n\nOn the other hand, analysis of the selective pressure revealed the presence of negatively selected residues that could be taken into considerations as therapeutic targets\n\nWe have also created an inclusive unified database (http://genoma.ma/covid-19/) that lists all of the genetic variants of the SARS-CoV-2 genomes found in this study with phylogeographic analysis around the world.", + "rel_num_authors": 19, "rel_authors": [ { - "author_name": "Aftab Alam", - "author_inst": "Center for Interdisciplinary Research in Basic Sciences, JMI University, New Delhi-110025." + "author_name": "Meriem Laamarti", + "author_inst": "Medical Biotechnology Laboratory (MedBiotech), Bioinova Research Center, Rabat Medical & Pharmacy School, Mohammed Vth University in Rabat, Morocco." }, { - "author_name": "Arbaaz Khan", - "author_inst": "Department of Computer Science, Jamia Millia Islamia, New Delhi-110025" + "author_name": "Tarek Alouane", + "author_inst": "Medical Biotechnology Laboratory (MedBiotech), Bioinova Research Center, Rabat Medical & Pharmacy School, Mohammed Vth University in Rabat, Morocco." }, { - "author_name": "Nikhat Imam", - "author_inst": "Institute of Computer Science & Information Technology, Department of Mathematics, Magadh University, Bodh Gaya (Bihar, India)." + "author_name": "Souad Kartti", + "author_inst": "Medical Biotechnology Laboratory (MedBiotech), Bioinova Research Center, Rabat Medical & Pharmacy School, Mohammed Vth University in Rabat, Morocco." }, { - "author_name": "Mohd Faizan Siddiqui", - "author_inst": "International Medical Faculty, Osh State University, Osh City, 723500, Kyrgyz Republic (Kyrgyzstan)" + "author_name": "M.W. Chemao-Elfihri", + "author_inst": "Medical Biotechnology Laboratory (MedBiotech), Bioinova Research Center, Rabat Medical & Pharmacy School, Mohammed Vth University in Rabat, Morocco" }, { - "author_name": "Mohd Waseem", - "author_inst": "School of Computational & Integrative Sciences, Jawaharlal Nehru University, New Delhi, India" + "author_name": "Mohammed Hakmi", + "author_inst": "Medical Biotechnology Laboratory (MedBiotech), Bioinova Research Center, Rabat Medical & Pharmacy School, Mohammed Vth University in Rabat, Morocco." }, { - "author_name": "Md. Zubbair Malik", - "author_inst": "Jawaharlal Nehru University" + "author_name": "Abdelomunim Essabbar", + "author_inst": "Medical Biotechnology Laboratory (MedBiotech), Bioinova Research Center, Rabat Medical & Pharmacy School, Mohammed Vth University in Rabat, Morocco." + }, + { + "author_name": "Mohamed Laamarti", + "author_inst": "Medical Biotechnology Laboratory (MedBiotech), Bioinova Research Center, Rabat Medical & Pharmacy School, Mohammed Vth University in Rabat, Morocco." + }, + { + "author_name": "Haitam Hlali", + "author_inst": "Medical Biotechnology Laboratory (MedBiotech), Bioinova Research Center, Rabat Medical & Pharmacy School, Mohammed Vth University in Rabat, Morocco." + }, + { + "author_name": "Loubna Allam", + "author_inst": "Medical Biotechnology Laboratory (MedBiotech), Bioinova Research Center, Rabat Medical & Pharmacy School, Mohammed Vth University in Rabat, Morocco." + }, + { + "author_name": "Naima El Hafidi", + "author_inst": "Medical Biotechnology Laboratory (MedBiotech), Bioinova Research Center, Rabat Medical & Pharmacy School, Mohammed Vth University in Rabat, Morocco." + }, + { + "author_name": "Rachid El Jaoudi", + "author_inst": "Medical Biotechnology Laboratory (MedBiotech), Bioinova Research Center, Rabat Medical & Pharmacy School, Mohammed Vth University in Rabat, Morocco." + }, + { + "author_name": "Imane Allali", + "author_inst": "Laboratory of Human Pathologies Biology, Department of Biology, Faculty of Sciences, and Genomic Center of Human Pathologies, Faculty of Medicine and Pharmacy, " + }, + { + "author_name": "Nabila Marchoudi", + "author_inst": "Anoual Laboratory of Radio-Immuno Analysis, Casablanca, Morocco." + }, + { + "author_name": "Jamal Fekkak", + "author_inst": "Anoual Laboratory of Radio-Immuno Analysis, Casablanca, Morocco." + }, + { + "author_name": "Houda Benrahma Sr.", + "author_inst": "Faculty of Medicine, Mohammed VI University of Health Sciences (UM6SS), Casablanca, Morocco." + }, + { + "author_name": "Chakib Nejjari", + "author_inst": "International School of Public Health, Mohammed VI University of Health Sciences (UM6SS), Casablanca, Morocco." + }, + { + "author_name": "Saaid Amzazi", + "author_inst": "Laboratory of Human Pathologies Biology, Department of Biology, Faculty of Sciences, and Genomic Center of Human Pathologies, Faculty of Medicine and Pharmacy, " + }, + { + "author_name": "Lahcen Belyamani", + "author_inst": "Emergency Department, Military Hospital Mohammed V, Rabat Medical & Pharmacy School, Mohammed Vth University in Rabat, Morocco." }, { - "author_name": "Romana Ishrat", - "author_inst": "Center for Interdisciplinary Research in Basic Sciences, JMI University, New Delhi-110025." + "author_name": "Azeddine Ibrahimi", + "author_inst": "Medical Biotechnology Laboratory (MedBiotech), Bioinova Research Center, Rabat Medical & Pharmacy School, Mohammed Vth University in Rabat, Morocco." } ], "version": "1", "license": "cc_no", "type": "new results", - "category": "bioinformatics" + "category": "genomics" }, { "rel_doi": "10.1101/2020.05.03.074914", @@ -1493418,51 +1493647,171 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.04.27.20082180", - "rel_title": "Hydroxychloroquine is associated with slower viral clearance in clinical COVID-19 patients with mild to moderate disease: A retrospective study", + "rel_doi": "10.1101/2020.04.27.20082289", + "rel_title": "Seroprevalence of antibodies against SARS-CoV-2 among health care workers in a large Spanish reference hospital", "rel_date": "2020-05-02", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.27.20082180", - "rel_abs": "BackgroundThere is conflicting data regarding the use of hydroxychloroquine (HCQ) in COVID-19 hospitalized patients\n\nObjectiveTo assess the efficacy of HCQ in increasing SARS-CoV-2 viral clearance\n\nDesignRetrospective observational study\n\nSettingCleveland Clinic Abu Dhabi\n\nParticipantsHospitalized adult patients with confirmed SARS-CoV-2 infection\n\nInterventionNone\n\nMeasurementsThe primary outcome was the time from a confirmed positive nasopharyngeal swab to turn negative. A negative nasopharyngeal swab conversion was defined as a confirmed SARS-CoV-2 case followed by two negative results using RT-PCR assay with samples obtained 24 hours apart\n\nResults34 confirmed COVID-19 patients were included. Nineteen (55.9%) patients presented with symptoms, and 14 (41.2%) had pneumonia. Only 21 (61.8%) patients received HCQ. The time to SARS-CoV-2 negativity nasopharyngeal test was significantly longer in patients who received HCQ compared to those who did not receive HCQ (17 [13-21] vs. 10 [4-13] days, p=0.023). HCQ was independently associated with time to negativity test after adjustment for potential confounders (symptoms, pneumonia or oxygen therapy) in multivariable linear regression analysis. On day 14, 47.8% (14/23) patients tested negative in the HCQ group compared to 90.9% (10/11) patients who did not receive HCQ (p=0.016).\n\nLimitationsSmall sample size and retrospective design with a potential risk of selection bias\n\nConclusionHCQ was associated with a slower viral clearance in COVID-19 patients with mild to moderate disease. Data from ongoing randomized clinical trials with HCQ should provide a definitive answer regarding the efficacy and safety of this treatment.", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.27.20082289", + "rel_abs": "BackgroundHealth care workers (HCW) are a high-risk population to acquire SARS-CoV-2 infection from patients or other fellow HCW. At the same time, they can be contagious to highly vulnerable individuals seeking health care. This study aims at estimating the seroprevalence of antibodies against SARS-CoV-2 and associated factors in HCW from a large referral hospital in Barcelona, Spain, one of the countries hardest hit by COVID-19 in the world.\n\nMethodsFrom 28 March to 9 April 2020, we recruited a random sample of 578 HCW from the human resources database of Hospital Clinic in Barcelona. We collected a nasopharyngeal swab for direct SARS-CoV-2 detection through real time reverse-transcriptase polymerase chain reaction (rRT-PCR), as well as blood for plasma antibody quantification. IgM, IgG and IgA antibodies to the receptor-binding domain of the spike protein were measured by Luminex. The cumulative prevalence of infection (past or current) was defined by a positive SARS-CoV-2 rRT-PCR and/or antibody seropositivity.\n\nResultsOf the 578 total participants, 39 (6.7%, 95% CI: 4.8-9.1) had been previously diagnosed with COVID-19 by rRT-PCR, 14 (2.4%, 95% CI: 1.4-4.3) had a positive rRT-PCR at recruitment, and 54 (9.3%, 95% CI: 7.2-12.0) were seropositive for IgM and/or IgG and/or IgA against SARS-CoV-2. Of the 54 seropositive HCW, 21 (38.9%) had not been previously diagnosed with COVID-19, although 10 of them (47.6%) reported past COVID-19-compatible symptoms. The cumulative prevalence of SARS-CoV-2 infection was 11.2% (65/578, 95% CI: 8.9-14.1). Among those with evidence of past or current infection, 40.0% (26/65) had not been previously diagnosed with COVID-19, of which 46.2% (12/26) had history of COVID-19-compatible symptoms. The odds of being seropositive was higher in participants who reported any COVID-19 symptom (OR: 8.84, 95% CI: 4.41-17.73). IgM levels positively correlated with age (rho=0.36, p-value=0.031) and were higher in participants with more than 10 days since onset of symptoms (p-value=0.022), and IgA levels were higher in symptomatic than asymptomatic subjects (p-value=0.041).\n\nConclusionsThe seroprevalence of antibodies against SARS-CoV-2 among HCW was lower than expected. Thus, being a high-risk population, we anticipate these estimates to be an upper limit to the seroprevalence of the general population. Forty per cent of those with past or present infection had not been previously diagnosed with COVID-19, which calls for active periodic rRT-PCR testing among all HCW to minimize potential risk of hospital-acquired SARS-CoV-2 infections.", + "rel_num_authors": 38, "rel_authors": [ { - "author_name": "Jihad Mallat", - "author_inst": "Cleveland Clinic Abu Dhabi" + "author_name": "Alberto L Garcia-Basteiro", + "author_inst": "Barcelona Institute for Global Health" }, { - "author_name": "Fadi Hamed", - "author_inst": "Cleveland Clinic Abu Dhabi" + "author_name": "Gemma Moncunill", + "author_inst": "Barcelona Institute for Global Health" }, { - "author_name": "Maher Balkis", - "author_inst": "Cleveland Clinic Abu Dhabi" + "author_name": "Marta Tortajada", + "author_inst": "Hospital Clinic Barcelona" }, { - "author_name": "Mohamed A Mohamed", - "author_inst": "Cleveland Clinic Abu Dhabi" + "author_name": "Marta Vidal", + "author_inst": "Barcelona Institute for Global Health" }, { - "author_name": "Mohamad Mooty", - "author_inst": "Cleveland Clinic Abu Dhabi" + "author_name": "Caterina Guinovart", + "author_inst": "Barcelona Institute for Global Health" }, { - "author_name": "Asim Malik", - "author_inst": "Cleveland Clinic Abu Dhabi" + "author_name": "Alfons Jimenez", + "author_inst": "Barcelona Institute for Global Health" }, { - "author_name": "Ahmad Nusair", - "author_inst": "Cleveland Clinic Abu Dhabi" + "author_name": "Rebeca Santano", + "author_inst": "Barcelona Institute for Global Health" }, { - "author_name": "Fernanda Bonilla", - "author_inst": "Cleveland Clinic Abu Dhabi" + "author_name": "Sergi Sanz", + "author_inst": "Barcelona Institute for Global Health" + }, + { + "author_name": "Susana Mendez", + "author_inst": "Barcelona Institute for Global Health" + }, + { + "author_name": "Anna Llupia", + "author_inst": "Hospital Clinic Barcelona" + }, + { + "author_name": "Rugh Aguilar", + "author_inst": "Barcelona Institute for Global Health" + }, + { + "author_name": "Selena Alonso", + "author_inst": "Barcelona Institute for Global Health" + }, + { + "author_name": "Diana Barrios", + "author_inst": "Barcelona Institute for Global Health" + }, + { + "author_name": "Carlo Carolis", + "author_inst": "CRG" + }, + { + "author_name": "Pau Cistero", + "author_inst": "Barcelona Institute for Global Health" + }, + { + "author_name": "Eugenia Choliz", + "author_inst": "Faculty of Medicine and Health Sciences, Universitat de Barcelona, Spain." + }, + { + "author_name": "Angeline Cruz", + "author_inst": "Barcelona Institute for Global Health" + }, + { + "author_name": "Silvia Fochs", + "author_inst": "Barcelona Institute for Global Health" + }, + { + "author_name": "Chenjerai Jairoce", + "author_inst": "Barcelona Institute for Global Health" + }, + { + "author_name": "Jochen Hecht", + "author_inst": "Centre for Genomic Regulation" + }, + { + "author_name": "Montserrat Lamoglia", + "author_inst": "Barcelona Institute for Global Health" + }, + { + "author_name": "Mikel J Martinez", + "author_inst": "Barcelona Institute for Global Health" + }, + { + "author_name": "Robert Mitchell", + "author_inst": "Barcelona Institute for Global Health" + }, + { + "author_name": "Natalia Ortega", + "author_inst": "Barcelona Institute for Global Health" + }, + { + "author_name": "Nuria Pey", + "author_inst": "Barcelona Institute for Global Health" + }, + { + "author_name": "Laura Puyol", + "author_inst": "Barcelona Institute for Global Health" + }, + { + "author_name": "Marta Ribes", + "author_inst": "Barcelona Institute for Global Health" + }, + { + "author_name": "Neus Rosell", + "author_inst": "Barcelona Institute for Global Health" + }, + { + "author_name": "Patricia Sotomayor", + "author_inst": "Barcelona Institute for Global Health" + }, + { + "author_name": "Sara Torres", + "author_inst": "Barcelona Institute for Global Health" + }, + { + "author_name": "Sarah Williams", + "author_inst": "Barcelona Institute for Global Health" + }, + { + "author_name": "Sonia Barroso", + "author_inst": "Hospital Clinic Barcelona" + }, + { + "author_name": "Anna Vilella", + "author_inst": "Hospital Clinic Barcelona" + }, + { + "author_name": "Jose Munoz", + "author_inst": "Barcelona Institute for Global Health" + }, + { + "author_name": "Pilar Varela", + "author_inst": "Hospital Clinic Barcelona" + }, + { + "author_name": "Antoni Trilla", + "author_inst": "Hospital Clinic Barcelona" + }, + { + "author_name": "Alfredo Mayor", + "author_inst": "Barcelona Institute for Global Health" + }, + { + "author_name": "Carlota Dobano", + "author_inst": "Barcelona Institute for Global Health" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2020.04.27.20082206", @@ -1494864,33 +1495213,45 @@ "category": "health policy" }, { - "rel_doi": "10.1101/2020.04.29.20084475", - "rel_title": "Reduced COVID-19-Related Critical Illness and Death, and High Risk of Epidemic Resurgence, After Physical Distancing in Ontario, Canada", + "rel_doi": "10.1101/2020.04.29.20084863", + "rel_title": "Inflammatory markers in Covid-19 Patients: a systematic review and meta-analysis.", "rel_date": "2020-05-02", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.29.20084475", - "rel_abs": "BackgroundInsights from epidemiological models have helped to both guide and better understand COVID-19 mitigation policies that have been adopted across the globe. Many early models focussed on initial control options and were less reliant on fitting to observed data. As the pandemic progresses, models can be used to quantify the impact that control measures have had and what may unfold when such measures are relaxed.\n\nObjectiveTo explore the impact of physical distancing measures on COVID-19 transmission in the population of Ontario, Canada.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.29.20084863", + "rel_abs": "IntroductionDiagnosis of COVID-19 is based on clinical manifestation, history of exposure, positive findings on chest CT and laboratory tests. It has been shown that inflammation plays a role in pathogenesis of COVID-19.\n\nMethodWe used the necessary transformations to convert the median and IQR to mean and SD Random-effect model using Der Simonian, and Laird methods was used if heterogeneity between studies was significant, the homogeneity among studies was assessed with I2 Statistic, values above 50%, and for the chi-square test, P-values <0.1 was supposed statistically significant\n\nResultsTwelve studies were included in the analysis that all of which were conducted in China in the year 2020. The result of combining 12 articles with 772 participants showed that the pooled estimate of the mean of lymphocyte with 95% CI was (Mean: 1.01; 95% CI (0.76-1.26); p-value<0.001). About WBC the pooled result of 9 studies with 402 participants was (Mean: 5.11; 95% CI (3.90-6.32); p-value<0.001) Also the pooled mean estimate of 9 studies with 513 patients for the ratio of Neutrophil/lymphocyte was (Mean: 3.62; 95% CI (1.48-5.77); p-value=0.001). The pooled mean from the combination of 7 studies with 521 patients on CRP was (Mean: 28.75; 95% CI (8.04-49.46).\n\nConclusionInflammatory Markers increase in patients with Covid-19, which can be a good indicator to find patients.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Ashleigh Tuite", - "author_inst": "University of Toronto" + "author_name": "Golnaz Vaseghi", + "author_inst": "Isfahan Cardiovascular research center, cardiovascular research institute, Isfahan University of Medical Sciences, Isfahan, Iran" }, { - "author_name": "Amy L Greer", - "author_inst": "University of Guelph" + "author_name": "Marjan Mansourian", + "author_inst": "Department of Epidemiology and Biostatistics, School of Health, Isfahan University of Medical Sciences, Isfahan, Iran" }, { - "author_name": "Steven De Keninck", - "author_inst": "Matrix Factory bvba" + "author_name": "Raheleh Karimi", + "author_inst": "Department of Epidemiology and Biostatistics, School of Health, Isfahan University of Medical Sciences, Isfahan, Iran" }, { - "author_name": "David N Fisman", - "author_inst": "University of Toronto" + "author_name": "kIYAN Heshmat-Ghahdarijani", + "author_inst": "Department of Cardiology, Isfahan Cardiovascular Research Center, Isfahan University of Medical Sciences, Iran" + }, + { + "author_name": "Paria Rouhi", + "author_inst": "Student Research Committee, School of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran" + }, + { + "author_name": "Mahfam Shariati", + "author_inst": "Department of Microbiology, School of Biology, College of Science, University of Tehran" + }, + { + "author_name": "Shaghayegh Haghjoo Javanmard", + "author_inst": "Applied physiology research center, cardiovascular research institute, Isfahan University of Medical Sciences, Isfahan, Iran" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1496614,35 +1496975,43 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.04.27.20075085", - "rel_title": "How urgent do intravitreal anti-VEGF injections need to be to justify the risk of transmitting COVID-19? Proof-of-concept calculations to determine the Health Adjusted Life-Year (HALY) trade-off.", + "rel_doi": "10.1101/2020.04.28.20075119", + "rel_title": "Cohort profile: Preliminary experience of 500 COVID-19 postive cases at a South West London District General Hospital.", "rel_date": "2020-05-01", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.27.20075085", - "rel_abs": "BackgroundClinical ophthalmological guidelines encourage the assessment of potential benefits and harms when deciding whether to perform elective ophthalmology procedures during the COVID-19 pandemic, in order to minimize the risk of disease transmission.\n\nMethodWe performed probability calculations to estimate COVID-19 infection status and likelihood of disease transmission among neovascular age-related macular degeneration patients and health care workers during anti-VEGF procedures, at various community prevalence levels of COVID-19. We then applied the expected burden of COVID-19 illness and death expressed through health-adjusted life-years (HALYs) lost. We compared these results to the expected disease burden of severe visual impairment if sight protecting anti-VEGF injections were not performed.\n\nResultsOur calculations suggest a wide range of contexts where the benefits of treatment to prevent progression to severe visual impairment or blindness are greater than the expected harms to the patient and immediate health care team due to COVID-19. For example, with appropriate protective equipment the benefits of treatment outweigh harms when the chance of progression to severe visual impairment is >0.044% for all scenarios where COVID-19 prevalence was one per thousand, even when the attack rate in the clinical setting is very high (5-43%).\n\nConclusionUnless COVID-19 prevalence is very high, the reduced disease burden from avoiding visual impairment outweighs the expected HALYs lost from COVID-19 transmission. This finding is driven by the fact that HALYs lost when someone suffers severe visual impairment for 5 years are equivalent to nearly 400 moderate cases of infectious disease lasting 2 weeks each.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.28.20075119", + "rel_abs": "This retrospective cohort analysis, reports the demographic data and early outcome of the first 500 patients who were admitted to a District General Hospital in South West London, UK and tested positive to COVID-19. The patients were admitted between 10 January and 10 April 2020; with the first COVID-19 positive diagnosis on 6 March. A surge in admissions started around the 15 March and peaked at the beginning of April.\n\n56.8% of the admissions were male and 43.2% were female. The average age of the 500 admissions was 69.32 years (SD 19.23 years, range 1 week to 99.21 years). By the morning of 14 April 2020, 199 patients had been discharged (Female 89, Male 111), 163 patients had died (female 61, male 102) and 131 remained as in-patients (female 66, male 71).\n\nFewer than one in twenty deaths occurred in patients below the age of 50 years, in either gender. Mortality rose dramatically, for both genders, after the age of sixty with males being almost twice as vulnerable to dying, as females, during the 7th decade. Males older than their mid-fifties were more likely to die than leave hospital. The same applied to females beyond their mid seventies. We did not see any evidence of a poorer outcome associated with a lower decile for Index of Multiple Deprivation or convincing evidence that any Ethnic minority groups were more likely to die than the White subgroups. When compared to the equivalent medical conditions, normally treated in the early spring, COVID-19 has an increased mortality, adversely affecting more men and an older population.\n\nThe mean duration from admission to discharge was 11.29 days (SD 11.50 days). For admission to death, the mean interval was 11.72 days (SD 11.05 days). 62 of the 500 admissions required ventilator support. Of this subgroup, 71% were male and 29% were female. By the morning of the 14 April, no female over the age of 60 had left the intensive care unit alive and no male over the age of 50 had left the intensive care unit alive. At this time-point, 1.2% of the 500 admitted patients had returned alive from the intensive care units, following a period of ventilator support. This figure will rise if prolonged ventilator and renal support proves effective.\n\nWhile only providing a snapshot of a relatively small number of patients, reviewed over a short time period, from a small geographic area, the data supports the view that the younger members of society are less vulnerable to the adverse sequelae of COVID-19 infection and that any return to normal work and social activities should be considered initially for the individuals who are less than 40-50 years of age. There is an ongoing need for analyses on larger patient cohorts using both demographic and detailed clinical data.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Matt James Boyd", - "author_inst": "Adapt Research Ltd, Reefton, New Zealand" + "author_name": "Richard E Field", + "author_inst": "Epsom and St Helier University Hospitals NHS Trust" }, { - "author_name": "Daniel Andrew Richard Scott", - "author_inst": "Department of Ophthalmology, Gisborne Hospital, Hauora Tairawhiti, Gisborne, New Zealand" + "author_name": "Irrum Afzal", + "author_inst": "Epsom and St Helier University Hospitals NHS Trust" }, { - "author_name": "David Michael Squirrell", - "author_inst": "Department of Ophthalmology, Greenlane Clinical Centre, Auckland District Health Board, Auckland, New Zealand" + "author_name": "John Dixon", + "author_inst": "Epsom and St Helier University Hospitals NHS Trust" + }, + { + "author_name": "Vipul R Patel", + "author_inst": "Epsom and St Helier University Hospitals NHS Trust" }, { - "author_name": "Graham Ashley Wilson", - "author_inst": "Matai Lab, Gisborne, New Zealand" + "author_name": "Putul Sarkar", + "author_inst": "Epsom and St Helier University Hospitals NHS Trust" + }, + { + "author_name": "James E Marsh", + "author_inst": "Epsom and St Helier University Hospitals NHS Trust" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "ophthalmology" + "category": "public and global health" }, { "rel_doi": "10.1101/2020.04.27.20082503", @@ -1497948,17 +1498317,21 @@ "category": "genetics" }, { - "rel_doi": "10.1101/2020.04.26.20081109", - "rel_title": "Modeling Return of the Epidemic: Impact of Population Structure, Asymptomatic Infection, Case Importation and Personal Contacts", + "rel_doi": "10.1101/2020.04.27.20081281", + "rel_title": "A fundamental model and predictions for the spread of the COVID-19 epidemic", "rel_date": "2020-05-01", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.26.20081109", - "rel_abs": "BackgroundProactive interventions have halted the pandemic of coronavirus infected disease in some regions. However, without reaching herd immunity, the return of epidemic is possible. We investigate the impact of population structure, case importation, asymptomatic cases, and the number of contacts on a possible second wave of epidemic through mathematical modelling.\n\nMethodswe built a modified Susceptible-exposed-Infectious-Removed (SEIR) model with parameters mirroring those of the COVID-19 pandemic and reported simulated characteristics of epidemics for incidence, hospitalizations and deaths under different scenarios.\n\nResultsA larger percent of elderly people leads to higher number of hospitalizations, while a large percent of prior infection will effectively curb the epidemic. The number of imported cases and the speed of importation have small impact on the epidemic progression. However, a higher percent of asymptomatic cases slows the epidemic down and reduces the number of hospitalizations and deaths at the epidemic peak. Finally, reducing the number of contacts among young people alone has moderate effects on themselves, but little effects on the elderly population. However, reducing the number of contacts among elderly people alone can mitigate the epidemic significantly in both age groups, even though young people remain active within themselves.\n\nConclusionReducing the number of contacts among high risk populations alone can mitigate the burden of epidemic in the whole society. Interventions targeting high risk groups may be more effective in containing or mitigating the epidemic.", - "rel_num_authors": 1, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.27.20081281", + "rel_abs": "The spread of the novel coronavirus is characterized by two phases: (I) a natural exponential growth phase that occurs in the absence of intervention and (II) a regulated growth phase that is affected by enforcing social distancing and isolation. We have developed a fundamental spreading model for the COVID-19 epidemic that has two parameters: the community transmission rate and a metric describing the degree of isolation and social distancing in a given community or region (country, state, county, or city). These two parameters are calibrated to data from the community, so the model uncertainty depends on the quality of the data and ability to test for COVID-19. The model shows that social distancing significantly reduces the epidemic spread and flattens the curve. The model predicts well the spreading trajectory and peak time of new infections for a community of any size and provides an upper estimate for the total number of infections and daily new infection rate for weeks into the future, providing the vital information and lead time needed to prepare for and mitigate the epidemic. The theory has immediate and far-reaching applications for ongoing outbreaks or similar future outbreaks of other emergent infectious diseases (LA-UR-20-22877).\n\nDisclaimerThis material is not final and is subject to be updated any time. Contact information: bcheng@lanl.gov.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Xinhua Yu", - "author_inst": "University of Memphis" + "author_name": "Baolian Cheng", + "author_inst": "Los Alamos National Laboratory" + }, + { + "author_name": "Yi-Ming Wang", + "author_inst": "Retired from Los Alamos National Laboratory" } ], "version": "1", @@ -1499378,83 +1499751,39 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.04.28.20082552", - "rel_title": "Can Nebulised Heparin Reduce Time to Extubation in SARS CoV 2 The CHARTER Study Protocol", + "rel_doi": "10.1101/2020.04.28.20082859", + "rel_title": "COVID-19 and Inflammatory Bowel Diseases: risk assessment, shared molecular pathways and therapeutic challenges", "rel_date": "2020-05-01", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.28.20082552", - "rel_abs": "IntroductionCOVID-19 is associated with the development of ARDS displaying the typical features of diffuse alveolar damage with extensive pulmonary coagulation activation resulting in fibrin deposition in the microvasculature and formation of hyaline membranes in the air sacs. The anti-coagulant actions of nebulised heparin limit fibrin deposition and progression of lung injury. Serendipitously, unfractionated heparin also inactivates the SARS-CoV-2 virus and prevents its entry into mammalian cells. Nebulisation of heparin may therefore limit both fibrin-mediated lung injury and inhibit pulmonary infection by SARS-CoV-2. For these reasons we have initiated a multi-centre international trial of nebulised heparin in patients with COVID-19.\n\nMethods and interventionMechanically ventilated patients with confirmed or strongly suspected SARS-CoV-2 infection, hypoxaemia and an acute pulmonary opacity in at least one lung quadrant on chest X-ray, will be randomised to nebulised heparin 25,000 Units every 6 hours or standard care for up to 10 days while mechanically ventilated. The primary outcome is the time to separation from invasive ventilation to day 28, where non-survivors to day 28 are treated as though not separated from invasive ventilation.\n\nEthics and disseminationThe study protocol has been submitted to the human research and ethics committee of St Vincents Hospital, Melbourne, Australia. Submission is pending in other jurisdictions. Results of this study will be published in scientific journals and presented at scientific meetings.\n\nTrial RegistrationACTRN: 12620000517976", - "rel_num_authors": 16, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.28.20082859", + "rel_abs": "BackgroundThe novel coronavirus SARS-CoV-2 causing COVID-19 disease is yielding a global outbreak with serious threats to public health. In this paper, we aimed to review the current knowledge about COVID-19 infectious risk status in inflammatory bowel disease (IBD) patients requiring immunosuppressive medication. Also, we focused on several molecular insights that could explain why IBD patients appear to not have higher risks of infection and worse outcome in COVID-19 than the general population, in attempt to provide scientific support for safer decisions in IBD patient care.\n\nMethodsPubMed electronic database was interogated for relevant articles involving data about common molecular pathways and shared treatment strategies between SARS-CoV-2, SARS-CoV-1, MERS-CoV and inflammatory bowel diseases. In addition, Neural Covidex, an artificial intelligence tool, was used to answer queries about pathogenic coronaviruses and possible IBD interactions using the COVID-19 Open Research Dataset (CORD-19).\n\nDiscussionsFew molecular and therapeutic interactions between IBD and pathogenic coronaviruses were explored. First, we showed how the activity of soluble angiotensin-converting enzyme 2, CD209L alternate receptor and phosphorylated subunit of eukaryotic translation initiation factor 2 might exert protective impact in IBD in case of coronavirus infection. Second, IBD medication was discussed in the context of possible beneficial effects on COVID-19 pathogeny including \"cytokine storm\" prevention and treatment, immunomodulation, interferon signaling blocking, viral endocytosis inhibition.\n\nConclusionsUsing current understanding of SARS-CoV-2 as well as other pathogenic coronaviruses immunopathology, we showed why IBD patients should not be considered at an increased risk of infection or more severe outcomes. Whether our findings are entirely applicable to the pathogenesis, disease susceptibility and treatment management of SARS-CoV-2 infection in IBD must be further explored.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Barry Dixon", - "author_inst": "St.Vincents Hospital Melbourne" - }, - { - "author_name": "Roger Smith", - "author_inst": "Department of Critical Care Medicine, St Vincents Hospital (Melbourne), Victoria, Australia." - }, - { - "author_name": "Antonio Artigas", - "author_inst": "Critical Care Center, Corporaco Sanitaria Universitaria Parc Tauli CIBER Enfermedades Respiratorias, Autonomous University of Barcelona, Sabadell, Spain" - }, - { - "author_name": "John Laffey", - "author_inst": "Centre for Medical Devices, National University of Ireland Galway; Department of Intensive Care Medicine, University Hospital, Galway, Ireland" - }, - { - "author_name": "Bairbre McNicholas", - "author_inst": "Centre for Medical Devices, National University of Ireland Galway; Department of Intensive Care Medicine, University Hospital, Galway, Ireland" - }, - { - "author_name": "Eric Schmidt", - "author_inst": "Department of Critical Care Medicine, Denver Medical Centre, University of Colorado, USA." - }, - { - "author_name": "Quentin Nunes", - "author_inst": "Department of Surgery, University of Liverpool, Aintree University Hospital, UK" - }, - { - "author_name": "Mark Andrew Skidmore", - "author_inst": "Molecular & Structural Biosciences, Keele University, Staffordshire, UK" - }, - { - "author_name": "Marcelo Andrade de Lome", - "author_inst": "Molecular & Structural Biosciences, Keele University, Staffordshire, UK" - }, - { - "author_name": "John Moran", - "author_inst": "Department of Intensive Care Medicine, The Queen Elizabeth Hospital, South Australia." - }, - { - "author_name": "Frank Van Haren", - "author_inst": "Department of Intensive Care Medicine, Canberra Hospital, Australia" - }, - { - "author_name": "Gordon Doig", - "author_inst": "Northern Clinical School Intensive Care Research Unit, University of Sydney, Australia" + "author_name": "Iolanda Valentina Popa", + "author_inst": "Institute of Gastroenterology and Hepatology, Iasi, Romania and 'Grigore T. Popa' University of Medicine, Iasi, Romania" }, { - "author_name": "Sachin Gupta", - "author_inst": "Intensive Care Unit, Frankston Hospital, Melbourne, Australia" + "author_name": "Mircea Diculescu", + "author_inst": "Department of Gastroenterology, Fundeni Clinical Institute, Bucharest, Romania and 'Carol Davila' University of Medicine and Pharmacy, Bucharest, Romania" }, { - "author_name": "Angajendra Ghosh", - "author_inst": "Intensive Care Unit, The Northern Hospital, Melbourne, Australia" + "author_name": "Catalina Mihai", + "author_inst": "Institute of Gastroenterology and Hepatology, Iasi, Romania and 'Grigore T. Popa' University of Medicine, Iasi, Romania" }, { - "author_name": "Simone Said", - "author_inst": "Intensive Care Unit, The Northern Hospital, Melbourne, Australia" + "author_name": "Cristina Cijevschi-Prelipcean", + "author_inst": "Institute of Gastroenterology and Hepatology, Iasi, Romania and 'Grigore T. Popa' University of Medicine, Iasi, Romania" }, { - "author_name": "John Santamaria", - "author_inst": "Department of Critical Care Medicine, St Vincents Hospital, Melbourne, Victoria, Australia." + "author_name": "Alexandru Burlacu", + "author_inst": "Head of Department of Interventional Cardiology - Cardiovascular Diseases Institute and 'Grigore T. Popa' University of Medicine, Iasi, Romania" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "intensive care and critical care medicine" + "category": "gastroenterology" }, { "rel_doi": "10.1101/2020.04.24.20073924", @@ -1500632,31 +1500961,31 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.04.20.20072942", - "rel_title": "Estimating COVID-19 Prevalence in the United States: A Sample Selection Model Approach", + "rel_doi": "10.1101/2020.04.24.20073296", + "rel_title": "Emergency Medical Services resource capacity and competency amid COVID-19 in the United States: Preliminary findings from a national survey", "rel_date": "2020-04-30", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.20.20072942", - "rel_abs": "BackgroundPublic health efforts to determine population infection rates from coronavirus disease 2019 (COVID-19) have been hampered by limitations in testing capabilities and the large shares of mild and asymptomatic cases. We developed a methodology that corrects observed positive test rates for non-random sampling to estimate population infection rates across U.S. states from March 31 to April 7.\n\nMethodsWe adapted a sample selection model that corrects for non-random testing to estimate population infection rates. The methodology compares how the observed positive case rate vary with changes in the size of the tested population, and applies this gradient to infer total population infection rates. Model identification requires that variation in testing rates be uncorrelated with changes in underlying disease prevalence. To this end, we relied on data on day-to-day changes in completed tests across U.S. states for the period March 31 to April 7, which were primarily influenced by immediate supply-side constraints. We used this methodology to construct predicted infection rates across each state over the sample period. We also assessed the sensitivity of the results to controls for state-specific daily trends in infection rates.\n\nResultsThe median population infection rate over the period March 31 to April 7 was 0.9% (IQR 0.64 1.77). The three states with the highest prevalence over the sample period were New York (8.5%), New Jersey (7.6%), and Louisiana (6.7%). Estimates from mod-els that control for state-specific daily trends in infection rates were virtually identical to the baseline findings. The estimates imply a nationwide average of 12 population infections per diagnosed case. We found a negative bivariate relationship (corr. = -0.51) between total per capita state testing and the ratio of population infections per diagnosed case.\n\nInterpretationThe effectiveness of the public health response to the coronavirus pandemic will depend on timely information on infection rates across different regions. With increasingly available high frequency data on COVID-19 testing, our methodology could be used to estimate population infection rates for a range of countries and subnational districts. In the United States, we found widespread undiagnosed COVID-19 infection. Expansion of rapid diagnostic and serological testing will be critical in preventing recurrent unobserved community transmission and identifying the large numbers individuals who may have some level of viral immunity.\n\nFundingSocial Sciences and Humanities Research Council.", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.24.20073296", + "rel_abs": "OBJECTIVEThis study aimed to investigate available resources, Personal Protective Equipment (PPE) availability, sanitation practices, institutional policies, and opinions among EMS professionals in the United States amid the COVID-19 pandemic using a self-report survey questionnaire.\n\nMETHODSAn online 42-question multiple choice survey was randomly distributed between April 1, 2020, and April 12, 2020 to various active Emergency Medical Services (EMS) paid personnel in all 50 U.S. states including the District of Columbia (n=165). We approximate a 95% confidence interval ({+/-} 0.0755).\n\nRESULTSAn overwhelming number of EMS providers report having limited access to N95 respirators, receiving little or no benefits from COVID-19 related work, and report no institutional policy on social distancing practices despite CDC recommendations. For providers who do have access to N95 respirators, 31% report having to use the same mask for 1 week or longer. Approximately [1/3] of the surveyed participants were unsure of when a COVID-19 patient is infectious. The data suggests regular decontamination of EMS equipment after each patient contact is not a regular practice.\n\nDISCUSSIONCurrent practices to educate EMS providers on appropriate response to the novel coronavirus may not be sufficient, and future patients may benefit from a nationally established COVID-19 EMS response protocol. Further investigation on whether current EMS practices are contributing to the spread of infection is warranted. The data reveals concerning deficits in COVID-19 related education and administrative protocols which pose as a serious public health concern that should be urgently addressed.\n\nKey MessagesO_ST_ABSWhat is already known on this subjectC_ST_ABSO_LICOVID-19 presents as a national emergency in the United States, and all efforts to mitigate the spread of disease should be considered\nC_LIO_LIEmergency Medical Services personnel play a pivotal role in patient outcomes and are often the first healthcare providers to make contact with COVID-19 patients\nC_LIO_LIThe CDC has provided an Interim guidance for EMS professionals amid the COVID-19 pandemic\nC_LI\n\nWhat this study addsO_LIDue to varied decontamination practices and administrative protocols that are non-compliant with CDC recommendations, EMS providers may inadvertently contribute to the spread of infection\nC_LIO_LIDue to varied knowledge and opinions of EMS providers on COVID-19, current pandemic education approaches may need to be revisited\nC_LI", "rel_num_authors": 3, "rel_authors": [ { - "author_name": "David Benatia", - "author_inst": "CREST - ENSAE" + "author_name": "Christian Ventura", + "author_inst": "Health Advocacy and Medical Exploration Society, Bard College at Simon's Rock" }, { - "author_name": "Raphael Godefroy", - "author_inst": "University of Montreal" + "author_name": "Cody V Gibson", + "author_inst": "Health Advocacy and Medical Exploration Society, Calhoun Community College" }, { - "author_name": "Joshua Lewis", - "author_inst": "University of Montreal" + "author_name": "George Donald Collier", + "author_inst": "Calhoun Community College" } ], "version": "1", "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "emergency medicine" }, { "rel_doi": "10.1101/2020.04.25.20080127", @@ -1502070,39 +1502399,27 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.04.24.20078105", - "rel_title": "A Nationwide Survey of UK cardiac surgeons view on clinical decision making during the COVID-19 pandemic", + "rel_doi": "10.1101/2020.04.22.20075093", + "rel_title": "COVID-19 containment policies through time may cost more lives at metapopulation level", "rel_date": "2020-04-29", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.24.20078105", - "rel_abs": "BackgroundNo firm recommendations are currently available to guide decision making for patients requiring cardiac surgery during the COVID-19 pandemic. Systematic appraisal of national expert consensus can be used to generate interim recommendations until data from clinical observations will become available. Hence, we aimed to collect and quantitatively appraise nationwide UK senior surgeons opinion on clinical decision making for patients requiring cardiac surgery during the COVID-19 pandemic.\n\nMethodsWe mailed a web-based questionnaire to all consultant cardiac surgeons through the Society for Cardiothoracic Surgery in Great Britain and Ireland (SCTS) mailing list on the 17th April 2020 and we pre-determined to close the survey on the 21st April 2020. This survey was primarily designed to gather information on UK surgeons opinion using 12 items. Strong consensus was predefined as an opinion shared by at least 60% of responding consultants.\n\nResultsA total of 86 consultant surgeons undertook the survey. All UK cardiac units were represented by at least one consultant. Strong consensus was achieved for the following key questions:1) before hospital admission every patient should receive nasopharyngeal swab, PCR and chest CT; 2) the use of full PPE should to be adopted in every case by the theatre team regardless patients COVID-19 status; 3) the risk of COVID-19 exposure for patients undergoing heart surgery should be considered moderate to high and likely to increase mortality if it occurs; 4) cardiac procedure should be decided based on ad-hoc multidisciplinary team discussion for every patient. The majority believed that both aortic and mitral surgery should be considered in selected cases. The role of CABG surgery during the pandemic was more controversial.\n\nConclusionsIn the current unprecedented scenario, the present survey provides information for generating interim recommendations until data from clinical observations will become available.\n\nPerspective statementSystematic appraisal of national expert consensus can be used to generate interim recommendations for patients undergoing cardiac surgery during COVID-19 pandemic until data from clinical observations will become available.\n\nCentral messageNo firm recommendations are currently available to guide decision making for patients requiring cardiac surgery during the pandemic. This can translate into significant variability in clinical practice and patients outcomes across cardiac units. Systematic appraisal of national expert consensus can represent a rapid and efficient instrument to provide support to heath policy makers and other stakeholders in generating interim recommendations until data from clinical observations will become available.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.22.20075093", + "rel_abs": "The rapid and pandemic spread of COVID-19 has led to unprecedented containment policies in response to overloaded health care systems. Disease mitigation strategies require informed decision-making to ensure a balance between the protection of the vulnerable from disease and the maintenance of global economies. We show that temporally restricted containment efforts, that have the potential to flatten epidemic curves, can result in wider disease spread and larger epidemic sizes in metapopulations. Longer-term rewiring of metapopulation networks or the enforcement of feasible long-term measures that decrease disease transmissions appear to be more efficient than temporarily restricted intensive mitigation strategies (e.g. short-term mass quarantine). Our results may inform balanced containment strategies for short-term disease spread mitigation in response to overloaded health care systems and longer-term epidemiological sizes.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Umberto Benedetto", - "author_inst": "Bristol Heart Institute, University Hospitals bristol NHS Foundation Trust" - }, - { - "author_name": "Andrew Goodwin", - "author_inst": "South Tees Hospitals NHS Trust" - }, - { - "author_name": "Simon Kendall", - "author_inst": "South Tees Hospitals NHS Trust" - }, - { - "author_name": "Rakesh Uppal", - "author_inst": "Barts Health NHS Turst" + "author_name": "Konstans Wells", + "author_inst": "Swansea University" }, { - "author_name": "Enoch Akowuah", - "author_inst": "South Tees Hospitals NHS Trust" + "author_name": "Miguel Lurgi", + "author_inst": "Swansea University" } ], "version": "1", - "license": "cc_by", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "cardiovascular medicine" + "category": "epidemiology" }, { "rel_doi": "10.1101/2020.04.24.20078345", @@ -1503128,51 +1503445,47 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.04.25.20079863", - "rel_title": "Interim Analysis of Pandemic Coronavirus Disease 2019 (COVID-19) and the SARS-CoV-2 virus in Latin America and the Caribbean: Morbidity, Mortality and Molecular Testing Trends in the Region", + "rel_doi": "10.1101/2020.04.25.20079640", + "rel_title": "COVID-19 Outcomes in Saudi Arabia and the UK: A Tale of Two Kingdoms", "rel_date": "2020-04-29", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.25.20079863", - "rel_abs": "BackgroundThe relentless advance of the SARS-CoV-2 virus pandemic has resulted in a significant burden on countries, regardless of their socio-economic conditions. The virus has infected more than 2.5 million people worldwide, causing to date more than 150,000 deaths in over 210 countries.\n\nObjectiveThe aim of this study was to describe the trends in cases, tests and deaths related to novel coronavirus disease (COVID-19) in Latin American and Caribbean (LAC) countries.\n\nMethodologyData were retrieved from the WHO-Coronavirus Disease (COVID-2019) situation reports and the Center for Systems Science and Engineering (CSSE) databases from Johns Hopkins University. Descriptive statistics including death rates, cumulative mortality and incidence rates, as well as testing rates per population at risk were performed. A comparison analysis among countries with [≥]50 confirmed cases was performed from February 26th, 2020 to April 8th, 2020.\n\nResultsBrazil had the greatest number of cases and deaths in the region. Panama experienced a rapid increase in the number of confirmed cases with Trinidad and Tobago, Bolivia and Honduras having the highest case fatality rates. Panama and Chile conducted more tests per million inhabitants and more tests per day per million inhabitants, followed by Uruguay and El Salvador. Dominican Republic, Bolivia, Ecuador and Brazil had the highest positive test rates.\n\nConclusionsThe COVID-19 disease pandemic caused by the SARS-CoV-2 virus has progressed rapidly in LAC countries. Some countries have been affected more severely than others, with some adopting similar disease control methods to help slow down the spread of the virus. With limited testing and other resources, social distancing is needed to help alleviate the strain on already stretched health systems.", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.25.20079640", + "rel_abs": "BackgroundWhile the number of COVID-19 cases and deaths around the world is starting to peak, it is essential to point out how different countries manage the outbreak and how different measures and experience resulted in different outcomes. This study aimed to compare the effect of the measures taken by Saudi Arabia and the United Kingdom (UK) governments on the outcome of the COVID-19 pandemic as predicted by a mathematical model.\n\nMethodData on the numbers of cases, deaths and government measures were collected from Saudis Ministry of Health and Public Health England. A prediction of the trend of cases, deaths and days to peak was then modelled using the mathematical technique, Exponential Logistic Growth and Susceptible Infectious Recovered (SIR) model. The measures taken by the governments and the predicted outcomes were compared to assess effectiveness.\n\nResultWe found over three months that 22 fast and extreme measures had been taken in Saudi Arabia compared to eight slow and late measures in the UK. This resulted in a decline in numbers of current infected cases per day and mortality in Saudi Arabia compared to the UK. Based on the SIR model, the predicted number of COVID-19 cases in Saudi as of 31st of March was 2,064, while the predicted number of cases was 63012 in the UK. In addition, the pandemic is predicted to peak earlier on the 27th of March in Saudi Arabia compared to the 2nd of May 2020 in the UK. The end of transition phases for Saudi and UK according to the model, were predicted to be on 18th of April and 24th of May, respectively. These numbers relate to early and decisive measures adopted by the Saudi government.\n\nConclusionWe show that early extreme measures, informed by science and guided by experience, helped reduce the spread and related deaths from COVID-19 in Saudi. Actions were taken by Saudi under the national slogan \"We are all responsible\" resulted in the observed reduced number of current and predicted cases and deaths compared to the UK approach \"keep calm and carry on\".", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Katherine Simbana-Rivera", - "author_inst": "OneHealth Global Research Group, Universidad de las Americas, Quito, Ecuador" + "author_name": "Saleh Komies", + "author_inst": "Faculty of Engineering, Department of Electrical and Electronic Engineering, Imperial College London, London, UK" }, { - "author_name": "Lenin Gomez-Barreno", - "author_inst": "OneHealth Global Research group, Universidad de las Americas, Quito, Ecuador" + "author_name": "Abdulelah M Aldhahir", + "author_inst": "UCL Respiratory, University College London, London, UK" }, { - "author_name": "Jhon Guerrero", - "author_inst": "Scientific Association of Medical Students, Universidad Central del Ecuador, Quito, Ecuador" + "author_name": "Mater Almehmadi", + "author_inst": "UCL Institute for Risk and Disaster, London, UK" }, { - "author_name": "Fernanda Simbana-Guaycha", - "author_inst": "Scientific Association of Medical Students, Universidad Central del Ecuador, Quito, Ecuador" + "author_name": "Saeed M Alghamdi", + "author_inst": "National Heart and Lung Institute, Imperial College London, London, UK" }, { - "author_name": "Raul Fernandez", - "author_inst": "One Health Global research group, Universidad de las Americas, Quito, Ecuador" + "author_name": "Ali Alqarni", + "author_inst": "Centre of Host Microbe Interaction (CHMI), Faculty of Dentistry, Oral & Craniofacial Sciences, Kings College London, United Kingdom" }, { - "author_name": "Andres Lopez-Cortes Sr.", - "author_inst": "Universidad UTE" - }, - { - "author_name": "Alex Lister", - "author_inst": "University of Southampton, Southampton, United Kingdom." + "author_name": "Tope Oyelade", + "author_inst": "UCL Institute for Liver and Digestive Health, London, UK" }, { - "author_name": "Esteban Ortiz-Prado", - "author_inst": "OneHealth Global Research Group, Universidad De Las Americas" + "author_name": "Jaber S Alqahtani", + "author_inst": "UCL Respiratory, University College London, London, UK" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "respiratory medicine" }, { "rel_doi": "10.1101/2020.04.24.20078907", @@ -1504718,41 +1505031,25 @@ "category": "health informatics" }, { - "rel_doi": "10.1101/2020.04.25.20078311", - "rel_title": "Demographic and Socio-Economic Factors, and Healthcare Resource Indicators Associated with the Rapid Spread of COVID-19 in Northern Italy: An Ecological Study", + "rel_doi": "10.1101/2020.04.23.20077321", + "rel_title": "COVID-19 Growth Rate Decreases with Social Capital", "rel_date": "2020-04-29", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.25.20078311", - "rel_abs": "BackgroundCOVID-19 rapidly escalated into a pandemic, threatening 213 countries, areas, and territories the world over. We aimed to identify potential province-level socioeconomic determinants of the viruss dissemination, and explain between-province differences in the speed of its spread, based on data from 36 provinces of Northern Italy.\n\nMethodsThis is an ecological study. We included all confirmed cases of SARS-CoV-2 reported between February 24th and March 30th, 2020. For each province, we calculated the trend of contagion as the relative increase in the number of individuals infected between two time endpoints, assuming an exponential growth. Pearsons test was used to correlate the trend of contagion with a set of healthcare-associated, economic, and demographic parameters by province. The viruss spread was input as a dependent variable in a stepwise OLS regression model to test the association between rate of spread and province-level indicators.\n\nFindingsMultivariate analysis showed that the spread of COVID-19 was correlated negatively with aging index (p-value=0.003), and positively with public transportation per capita (p-value=0.012), the % of private long-term care hospital beds and, to a lesser extent (p-value=0.070), the % of private acute care hospital beds (p-value=0.006).\n\nInterpretationDemographic and socioeconomic factors, and healthcare organization variables were found associated with a significant difference in the rate of COVID-19 spread in 36 provinces of Northern Italy. An aging population seemed to naturally contain social contacts. The availability of healthcare resources and their coordination could play an important part in spreading infection.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.23.20077321", + "rel_abs": "BackgroundSocial capital has been associated with many public health variables including mortality, obesity, diabetes, and sexually-transmitted disease rates. However, the relationship of social capital to the spread of infectious disease like COVID-19 is lacking. The COVID-19 pandemic presents an unprecedented threat to global health and economy, for which control strategies have relied on aggressive social distancing. However, an understanding of how social capital is related to changes in human mobility patterns for adherence to social distancing is lacking.\n\nObjectiveThis study examines the association between state- and county-level social capital indices and community health indices in the United States, and the growth rate of COVID-19 cases. It also examines changes in human mobility.\n\nMethodsUsing publicly available state- and county-specific time series data for COVID-19 cases from March 13 to March 31, we used exponential fits to determine growth rate. We obtained publicly available mobility change data, originally measured from GPS-enabled mobile devices. The design was then state- and county-level correlation analysis with social capital and community health indices from the Social Capital Project (United States Senate).\n\nResultsIn bivariate linear correlation analyses, we find social capital and community health indices were negatively associated with COVID-19 growth rates at both the state and county levels. The correlation was strongest at the county level for the community health index: a one-unit increase in the county community health index was associated with a decrease in the COVID-19 growth rate exponent by 0.045. In further bivariate correlation analyses, we find that social capital indices were negatively associated with retail/recreation movement and positively associated with residential movement. That is, an increase in social capital is correlated with slower COVID-19 infection spread and more adherence to social distancing protocols.\n\nConclusionOur results indicate the potential benefit of incorporating social capital concepts in planning policies to control the spread of COVID-19, e.g. different social distancing requirements in different communities. The results also indicate a need for further research into this potentially causal relationship, including examining interventions to increase social capital, community health, and institutional health.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Alessandra Buja", - "author_inst": "Department of Cardiologic, Vascular and Thoracic Sciences, and Public Health, University of Padova. Via Loredan, 18, 35131, Padova, Italy." - }, - { - "author_name": "Matteo Paganini", - "author_inst": "Department of Biomedical Sciences, University of Padova." - }, - { - "author_name": "Silvia Cocchio", - "author_inst": "Department of Cardiologic, Vascular and Thoracic Sciences, and Public Health, University of Padova. Via Loredan, 18, 35131, Padova, Italy." - }, - { - "author_name": "Manuela Scioni", - "author_inst": "Statistics Department, University of Padova. Via C. Battisti, 241, 35121, Padova, Italy." - }, - { - "author_name": "Vincenzo Rebba", - "author_inst": "'Marco Fanno' Department of Economics and Management, University of Padova. Via U. Bassi, 1, 35131, Padova, Italy." + "author_name": "Lav R. Varshney", + "author_inst": "Salesforce" }, { - "author_name": "Vincenzo Baldo", - "author_inst": "Department of Cardiologic, Vascular and Thoracic Sciences, and Public Health, University of Padova. Via Loredan, 18, 35131, Padova, Italy." + "author_name": "Richard Socher", + "author_inst": "Salesforce" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "public and global health" }, @@ -1506268,37 +1506565,41 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.04.23.20077297", - "rel_title": "Quantifying early COVID-19 outbreak transmission in South Africa and exploring vaccine efficacy scenarios", + "rel_doi": "10.1101/2020.04.23.20077545", + "rel_title": "Influence of socio-ecological factors on COVID-19 risk: a cross-sectional study based on 178 countries/regions worldwide", "rel_date": "2020-04-29", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.23.20077297", - "rel_abs": "BackgroundCOVID-19 has emerged and spread at great speed globally and has presented one of the greatest public health challenges in modern times with no proven cure or vaccine. Africa is still early in this epidemic, therefore the spectrum of disease severity is not yet clear.\n\nMethodsWe used a mathematical model to fit to the observed cases of COVID-19 in South Africa to estimate the basic reproductive number and critical vaccination coverages to control the disease for different hypothetical vaccine efficacy scenarios. We also estimated the percentage reduction in effective contacts due to the social distancing measures implemented.\n\nResultsEarly model estimates show that COVID-19 outbreak in South Africa had a basic re-productive number of 2.95 (95% credible interval [CrI] 2.83-3.33). A vaccine with 70% efficacy had the capacity to contain COVID-19 outbreak but at very higher vaccination coverage 94.44% (95% Crl 92.44-99.92%) with a vaccine of 100% efficacy requiring 66.10% (95% Crl 64.72-69.95%) coverage. Social distancing measures put in place have so far reduced the number of social contacts by 80.31% (95% Crl 79.76-80.85%).\n\nConclusionsFindings suggest a highly efficacious vaccine would have been required to contain COVID-19 in South Africa. Therefore, the current social distancing measures to reduce contacts will remain key in controlling the infection in the absence of vaccines and other therapeutics.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.23.20077545", + "rel_abs": "BackgroundThe initial outbreak of COVID-19 caused by SARS-CoV-2 in China in 2019 has been severely tested in other countries worldwide. We aimed to describe the spatial distribution of the COVID-19 pandemic worldwide and assess the effects of various socio-ecological factors on COVID-19 risk.\n\nMethodsWe collected COVID-19 pandemic infection data and social-ecological data of 178 countries/regions worldwide from three database. We used spatial econometrics method to assess the global and local correlation of COVID-19 risk indicators for COVID-19. To estimate the adjusted incidence rate ratio (IRR), we modelled negative binomial regression analysis with spatial information and socio-ecological factors.\n\nFindingsThe study indicated that 37, 29 and 39 countries/regions were strongly opposite from the IR, CMR and DCI index \"spatial autocorrelation hypothesis\", respectively. The IRs were significantly positively associated with GDP per capita, the use of at least basic sanitation services and social insurance program coverage, and were significantly negatively associated with the proportion of the population spending more than 25% of household consumption or income on out-of-pocket health care expenses and the poverty headcount ratio at the national poverty lines. The CMR was significantly positively associated with urban populations, GDP per capita and current health expenditure, and was significantly negatively associated with the number of hospital beds, number of nurses and midwives, and poverty headcount ratio at the national poverty lines. The DCI was significantly positively associated with urban populations, population density and researchers in R&D, and was significantly negatively associated with the number of hospital beds, number of nurses and midwives and poverty headcount ratio at the national poverty lines. We also found that climatic factors were not significantly associated with COVID-19 risk.\n\nConclusionCountries/regions should pay more attention to controlling population flow, improving diagnosis and treatment capacity, and improving public welfare policies.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Zindoga Mukandavire", - "author_inst": "Coventry University" + "author_name": "Dai Su", + "author_inst": "Huazhong University of Science and Technology" }, { - "author_name": "Farai Nyabadza", - "author_inst": "University of Johannesburg" + "author_name": "Yingchun Chen", + "author_inst": "Huazhong University of Science and Technology" }, { - "author_name": "Noble J Malunguza", - "author_inst": "National University of Science and Technology, Bulawayo, Zimbabwe" + "author_name": "Kevin He", + "author_inst": "University of Michigan School of Public Health" }, { - "author_name": "Diego F Cuadros", - "author_inst": "University of Cincinnati" + "author_name": "Tao Zhang", + "author_inst": "West China School of Public Health and West China fourth Hospital, Sichuan University" }, { - "author_name": "Tinevimbo Shiri", - "author_inst": "Liverpool School of Tropical Medicine" + "author_name": "Min Tan", + "author_inst": "Huazhong University of Science and Technology" }, { - "author_name": "Godfrey Musuka", - "author_inst": "ICAP at Columbia University, Harare, Zimbabwe" + "author_name": "Yunfan Zhang", + "author_inst": "Huazhong University of Science and Technology" + }, + { + "author_name": "Xingyu Zhang", + "author_inst": "University of Michigan" } ], "version": "1", @@ -1508034,47 +1508335,91 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.04.24.20075838", - "rel_title": "Vitamin D Insufficiency is Prevalent in Severe COVID-19", + "rel_doi": "10.1101/2020.04.23.20076851", + "rel_title": "Heparin-induced thrombocytopenia is associated with a high risk of mortality in critical COVID-19 patients receiving heparin-involved treatment", "rel_date": "2020-04-28", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.24.20075838", - "rel_abs": "BackgroundCOVID-19 is a major pandemic that has killed more than 196,000 people. The COVID-19 disease course is strikingly divergent. Approximately 80-85% of patients experience mild or no symptoms, while the remainder develop severe disease. The mechanisms underlying these divergent outcomes are unclear. Emerging health disparities data regarding African American and homeless populations suggest that vitamin D insufficiency (VDI) may be an underlying driver of COVID-19 severity. To better define the VDI-COVID-19 link, we determined the prevalence of VDI among our COVID-19 intensive care unit (ICU) patients.\n\nMethodsIn an Institutional Review Board approved study performed at a single, tertiary care academic medical center, the medical records of COVID-19 patients were retrospectively reviewed. Subjects were included for whom serum 25-hydroxycholecalcifoerol (25OHD) levels were determined. COVID-19-relevant data were compiled and analyzed. We determined the frequency of VDI among COVID-19 patients to evaluate the likelihood of a VDI-COVID-19 relationship.\n\nResultsTwenty COVID-19 patients with serum 25OHD levels were identified; 65.0% required ICU admission.The VDI prevalence in ICU patients was 84.6%, vs. 57.1% in floor patients. Strikingly, 100% of ICU patients less than 75 years old had VDI. Coagulopathy was present in 62.5% of ICU COVID-19 patients, and 92.3% were lymphocytopenic.\n\nConclusionsVDI is highly prevalent in severe COVID-19 patients. VDI and severe COVID-19 share numerous associations including hypertension, obesity, male sex, advanced age, concentration in northern climates, coagulopathy, and immune dysfunction. Thus, we suggest that prospective, randomized controlled studies of VDI in COVID-19 patients are warranted.", - "rel_num_authors": 7, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.23.20076851", + "rel_abs": "BackgroundCoronavirus infectious disease 2019 (COVID-19) has developed into a global pandemic. It is essential to investigate the clinical characteristics of COVID-19 and uncover potential risk factors for severe disease to reduce the overall mortality rate of COVID-19.\n\nMethodsSixty-one critical COVID-19 patients admitted to the intensive care unit (ICU) and 93 severe non-ICU patients at Huoshenshan Hospital (Wuhan, China) were included in this study. Medical records, including demographic, platelet counts, heparin-involved treatments, heparin-induced thrombocytopenia-(HIT) related laboratory tests, and fatal outcomes of COVID-19 patients were analyzed and compared between survivors and nonsurvivors.\n\nFindingsSixty-one critical COVID-19 patients treated in ICU included 15 survivors and 46 nonsurvivors. Forty-one percent of them (25/61) had severe thrombocytopenia, with a platelet count (PLT) less than 50x109/L, of whom 76% (19/25) had a platelet decrease of >50% compared to baseline; 96% of these patients (24/25) had a fatal outcome. Among the 46 nonsurvivors, 52{middle dot}2% (24/46) had severe thrombocytopenia, compared to 6{middle dot}7% (1/15) among survivors. Moreover, continuous renal replacement therapy (CRRT) could induce a significant decrease in PLT in 81{middle dot}3% of critical CRRT patients (13/16), resulting in a fatal outcome. In addition, a high level of anti-heparin-PF4 antibodies, a marker of HIT, was observed in most ICU patients. Surprisingly, HIT occurred not only in patients with heparin exposure, such as CRRT, but also in heparin-naive patients, suggesting that spontaneous HIT may occur in COVID-19.\n\nInterpretationAnti-heparin-PF4 antibodies are induced in critical COVID-19 patients, resulting in a progressive platelet decrease. Exposure to a high dose of heparin may trigger further severe thrombocytopenia with a fatal outcome. An alternative anticoagulant other than heparin should be used to treat COVID-19 patients in critical condition.\n\nFundingThis investigation was supported by grants 2016CB02400 and 2017YFC1201103 from the National Major Research and Development Program of China.", + "rel_num_authors": 18, "rel_authors": [ { - "author_name": "Frank H. Lau", - "author_inst": "Louisiana State Univ. Health Sciences Center New Orleans" + "author_name": "Xuan Liu", + "author_inst": "Beijing Institute of Biotechnology" }, { - "author_name": "Rinku Majumder", - "author_inst": "Louisiana State University Health Sciences Center New Orleans" + "author_name": "Xiaopeng Zhang", + "author_inst": "Beijing Institute of Biotechnology" }, { - "author_name": "Radbeh Torabi", - "author_inst": "Louisiana State University Health Sciences Center New Orleans" + "author_name": "Yongjiu Xiao", + "author_inst": "The 940th Hospital of the People Liberation Army" }, { - "author_name": "Fouad Saeg", - "author_inst": "Tulane University School of Medicine" + "author_name": "Ting Gao", + "author_inst": "Beijing Institute of Biotechnology" }, { - "author_name": "Ryan Hoffman", - "author_inst": "Louisiana State University Health Sciences Center New Orleans" + "author_name": "Guangfei Wang", + "author_inst": "Beijing Institute of Biotechnology" }, { - "author_name": "Jeffrey D. Cirillo", - "author_inst": "Texas A&M College of Medicine" + "author_name": "Zhongyi Wang", + "author_inst": "Beijing Institute of Biotechnology" }, { - "author_name": "Patrick Greiffenstein", - "author_inst": "Louisiana State University Health Sciences Center New Orleans" + "author_name": "Zhang Zhang", + "author_inst": "Beijing Institute of Biotechnology" + }, + { + "author_name": "Yong Hu", + "author_inst": "Beijing Institute of Biotechnology" + }, + { + "author_name": "Qincai Dong", + "author_inst": "Beijing Institute of Biotechnology" + }, + { + "author_name": "Songtao Zhao", + "author_inst": "First Affiliated Hospital, Army Medical University" + }, + { + "author_name": "Li Yu", + "author_inst": "the 969th Hospital of Chinese People's Liberation Army Joint Logistics Support Force" + }, + { + "author_name": "Shuwei Zhang", + "author_inst": "Beijing Institute of Biotechnology" + }, + { + "author_name": "Hongzhen Li", + "author_inst": "Joinn Laboratories (China) Co. Ltd" + }, + { + "author_name": "Kaitong Li", + "author_inst": "Joinn Laboratories (China) Co. Ltd" + }, + { + "author_name": "Wei Chen", + "author_inst": "Beijing Institute of Biotechnology" + }, + { + "author_name": "Xiuwu Bian", + "author_inst": "First Affiliated Hospital, Army Medical University" + }, + { + "author_name": "Qing Mao", + "author_inst": "First Affiliated Hospital, Army Medical University" + }, + { + "author_name": "Cheng Cao", + "author_inst": "Beijing Institute of Biotechnology" } ], "version": "1", "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "intensive care and critical care medicine" }, { "rel_doi": "10.1101/2020.04.23.20076976", @@ -1509504,35 +1509849,43 @@ "category": "genomics" }, { - "rel_doi": "10.1101/2020.04.19.20070722", - "rel_title": "Between-centre differences for COVID-19 ICU mortality from early data in England", + "rel_doi": "10.1101/2020.04.24.20074559", + "rel_title": "Comparison of Commercially Available and Laboratory Developed Assays for in vitro Detection of SARS-CoV-2 in Clinical Laboratories", "rel_date": "2020-04-27", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.19.20070722", - "rel_abs": "The high numbers of COVID-19 patients developing severe respiratory failure has placed exceptional demands on ICU capacity around the world. Understanding the determinants of ICU mortality is important for surge planning and shared decision making. We used early data from the COVID-19 Hospitalisation in England Surveillance System (from the start of data collection 8th February -22nd May 2020) to look for factors associated with ICU outcome in the hope that information from such timely analysis may be actionable before the outbreak peak. Immunosuppressive disease, chronic cardiorespiratory/renal disease and age were key determinants of ICU mortality in a proportional hazards mixed effects model. However variation in site-stratified random effects were comparable in magnitude suggesting substantial between-centre variability in mortality. Notwithstanding possible ascertainment and lead-time effects, these early results motivate comparative effectiveness research to understand the origin of such differences and optimise surge ICU provision.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.24.20074559", + "rel_abs": "Multiple laboratory developed tests and commercially available assays have emerged to meet diagnostic needs related to the SARS-CoV-2 pandemic. To date, there is limited comparison data for these different testing platforms. We compared the analytical performance of a laboratory developed test (LDT) developed in our clinical laboratory based on CDC primer sets and four commercially available, FDA emergency use authorized assays for SARS-CoV-2 (Cepheid, DiaSorin, Hologic Panther, and Roche Cobas) on a total of 169 nasopharyngeal swabs. The LDT and Cepheid Xpert Xpress SARS-CoV-2 assays were the most sensitive assays for SARS-CoV-2 with 100% agreement across specimens. The Hologic Panther Fusion, DiaSorin Simplexa, and Roche Cobas 6800 only failed to detect positive specimens near the limit of detection of our CDC-based LDT assay. All assays were 100% specific, using our CDC-based LDT as the gold standard. Our results provide initial test performance characteristics for SARS-CoV-2 RT-PCR and highlight the importance of having multiple viral detection testing platforms available in a public health emergency.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Zhaozhi Qian", - "author_inst": "University of Cambridge" + "author_name": "Joshua Lieberman", + "author_inst": "University of Washington" }, { - "author_name": "Ahmed M Alaa", - "author_inst": "University of California, Los Angeles" + "author_name": "Gregory Pepper", + "author_inst": "University of Washington" }, { - "author_name": "Mihaela van der Schaar", - "author_inst": "University of Cambridge" + "author_name": "Samia N Naccache", + "author_inst": "LabCorp" }, { - "author_name": "Ari Ercole", - "author_inst": "University of Cambridge" + "author_name": "Meeili Huang", + "author_inst": "University of Washington" + }, + { + "author_name": "Keith R. Jerome", + "author_inst": "University of Washington" + }, + { + "author_name": "Alexander L. Greninger", + "author_inst": "University of Washington" } ], "version": "1", "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "intensive care and critical care medicine" + "category": "pathology" }, { "rel_doi": "10.1101/2020.04.22.20071050", @@ -1510610,27 +1510963,23 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.04.21.20073791", - "rel_title": "Understanding the asymmetric spread and case fatality rate (CFR) for COVID-19 among countries", + "rel_doi": "10.1101/2020.04.20.20072488", + "rel_title": "A statistical forecast of LOW mortality and morbidity due to COVID-19, in ARGENTINA and other Southern Hemisphere countries.", "rel_date": "2020-04-26", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.21.20073791", - "rel_abs": "The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections are rising rapidly every day in the world, causing the disease COVID-19 with around 2 million people infected and more than 100,000 people died so far, in more than 200 countries. One of the baffling aspects of this pandemic is the asymmetric increase in cases and case fatality rate (CFR) among countries. We analyze the time series of the infection and fatality numbers and found two interesting aspects. Firstly, the rate of spread in a region is directly connected to the population density of the region where the virus is spreading. For example, the high rate of increase in cases in the United States of America (USA) is related to the high population density of New York City. This is shown by scaling the cumulative number of cases with a measure of the population density of the affected region in countries such as Italy, Spain, Germany, and the USA and we see that the curves are coinciding. Secondly, we analyzed the CFR number as a function of the number of days, since the first death, and we found that there are two clear categories among countries: one category with high CFR numbers (around 10%) and the other category with low CFR numbers (2% to 4%). When we analyzed the results, we see that countries with lower CFR numbers more or less tend to have implemented active control measures such as aggressive testing, tracking down possible infections, effective quarantine measures, etc. Moreover, we did not see any convincing correlation between mortality rates and the median age of the population.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.20.20072488", + "rel_abs": "A set of open source programs in Python is devised to fit a parametric integrated Gaussian equation to cumulative deaths due to COVID-19 in Southern Hemisphere countries. The programs were successfully tested using data from advanced outbreak trajectories (Italy and Spain). The procedure was applied to data reported by Argentina. The projected total death toll will be 182 (277-182) with a peak of deaths (6(+/-2)) the 14 of April. The outbreak begins the 9th of March and end completely the 20th of May. However, already on 1st of May, 2 s (95.45%) of the deaths have occurred. The death toll arises from a number of infected individuals between 36412 and 2275. Then, they were to use to process data from several Southern Hemisphere countries: Argentina, Brazil, Mexico, Peru, Colombia, Ecuador, Cuba, Chile, Panama, Australia, Bolivia, Honduras, New Zealand, Paraguay, Guatemala, Venezuela, Uruguay, El Salvador, Jamaica, Haiti, Costa Rica and Nicaragua. The trend is to show low number of total deaths compared with other disease outbreaks. A total projected number of deaths between 15148 and 9939 deaths for a total population of ca. 664 M inhabitants. The projected death toll is much lower (5-10 times) than those forecasted by the Imperial College Group (ICG) even considering the best scenario of total suppression of virus transmission. Using actual mortality rates it is possible to back calculate which number of infected individuals would produce such mortality. The calculated number of infected individuals (worst case scenario) is below 2.5 million. This is significantly lower than that calculated by ICG (> 45 millions). In most countries the outbreak will end in May or early June. The dynamics of the outbreaks seems to do not saturate the health services (hospital beds) but only Peru, Ecuador and Panama should have not enough ICU beds for grave COVID-19 patients.", + "rel_num_authors": 1, "rel_authors": [ { - "author_name": "Eldhose Iype", - "author_inst": "BITS Pilani, Dubai Campus" - }, - { - "author_name": "Sadhya Gulati", - "author_inst": "BITS Pilani, Dubai Campus" + "author_name": "cesar a barbero", + "author_inst": "IITEMA-UNRC" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2020.04.21.20074070", @@ -1511988,29 +1512337,41 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2020.04.22.20074989", - "rel_title": "Heat treatment for reuse of disposable respirators during Covid-19 pandemic: Is filtration and fit adversely affected?", + "rel_doi": "10.1101/2020.04.22.20075200", + "rel_title": "SARS-CoV-2 RNA titers in wastewater anticipated COVID-19 occurrence in a low prevalence area", "rel_date": "2020-04-25", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.22.20074989", - "rel_abs": "A number of methods for decontaminating disposable filtering face piece respirators have been explored for use in health care settings during epidemics where respirators are in short supply, such as the current Covid-19 pandemic. Heating to temperatures above 65{degrees}C has been shown to successfully inactivate the SARS-CoV-2 virus on various surfaces. Ovens or similar heating devices are likely already widely available in hospitals globally. We did a quantitative fit test on nine models of FFP2 and FFP3 respirators before and after heat treatment in an oven. These included both flat fold and moulded cup styles. All passed the initial fit test, and all but two passed the post-treatment fit test. This study demonstrates that FFP respirators can still retain both filtration efficiency and fit after wear and heat treatment, but that it is necessary to understand the probability for failure of fit after decontamination. Heat shows promise as a simple and effective way of treating FFP respirators. Further evaluation of longer-term wear and disinfection effectiveness of heat treatment should be done before widespread use.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.22.20075200", + "rel_abs": "Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused more than 200,000 reported COVID-19 cases in Spain resulting in more than 20,800 deaths as of April 21, 2020. Faecal shedding of SARS-CoV-2 RNA from COVID-19 patients has extensively been reported. Therefore, we investigated the occurrence of SARS-CoV-2 RNA in six wastewater treatments plants (WWTPs) serving the major municipalities within the Region of Murcia (Spain), the area with the lowest COVID-19 prevalence within Iberian Peninsula. Firstly, an aluminum hydroxide adsorption-precipitation concentration method was tested using a porcine coronavirus (Porcine Epidemic Diarrhea Virus, PEDV) and mengovirus (MgV). The procedure resulted in average recoveries of 10.90 {+/-} 3.54% and 10.85 {+/-} 2.11% in influent water and 3.29 {+/-} 1.58% and 6.19 {+/-} 1.00% in effluent water samples for PEDV and MgV, respectively. Then, the method was used to monitor the occurrence of SARS-CoV-2 from March 12 to April 14, 2020 in influent, secondary and tertiary effluent water samples. By using the real-time RT-PCR (RT-qPCR) Diagnostic Panel validated by US CDC that targets three regions of the virus nucleocapsid (N) gene, we estimated quantification of SARS-CoV-2 RNA titers in untreated wastewater waters of 5.38 {+/-} 0.21 log genomic copies/L on average. Two secondary water samples resulted positive (2 out of 18) and all tertiary water samples tested as negative (0 out 12). This environmental surveillance data were compared to declared COVID-19 cases at municipality level, revealing that SARS-CoV-2 was circulating among the population even before the first cases were reported by local or national authorities in many of the cities where wastewaters have been sampled. The detection of SARS-CoV-2 in wastewater in early stages of the spread of COVID-19 highlights the relevance of this strategy as an early indicator of the infection within a specific population. At this point, this environmental surveillance could be implemented by municipalities right away as a tool, designed to help authorities to coordinate the exit strategy to gradually lift its coronavirus lockdown.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Miranda Loh", - "author_inst": "Institute of Occupational Medicine" + "author_name": "Walter Randazzo", + "author_inst": "Department of Microbiology and Ecology, University of Valencia, Av. Dr. Moliner, 50, Burjassot, 46100 Valencia, Spain;" }, { - "author_name": "Ross Clark", - "author_inst": "Institute of Occupational Medicine" + "author_name": "Pilar Truchado", + "author_inst": "Research Group on Quality, Safety and Bioactivity of Plant Foods, Department of Food Science and Technology, CEBAS-CSIC, Campus Universitario de Espinardo, 25, " }, { - "author_name": "John W Cherrie", - "author_inst": "Institute of Occupational Medicine" + "author_name": "Enric Cuevas Ferrando", + "author_inst": "Department of Preservation and Food Safety Technologies, Institute of Agrochemistry and Food Technology, IATA-CSIC, Av. Agustin Escardino 7, Paterna, 46980, Val" + }, + { + "author_name": "Pedro Simon", + "author_inst": "ESAMUR, Avenida Juan Carlos, s/n - Edificio Torre Jemeca, Murcia, Spain." + }, + { + "author_name": "Ana Allende", + "author_inst": "Research Group on Quality, Safety and Bioactivity of Plant Foods, Department of Food Science and Technology, CEBAS-CSIC, Campus Universitario de Espinardo, 25, " + }, + { + "author_name": "Gloria Sanchez", + "author_inst": "Department of Preservation and Food Safety Technologies, Institute of Agrochemistry and Food Technology, IATA-CSIC, Av. Agustin Escardino 7, Paterna, 46980, Val" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "occupational and environmental health" }, @@ -1513358,55 +1513719,59 @@ "category": "genetics" }, { - "rel_doi": "10.1101/2020.04.22.056747", - "rel_title": "Comparison of commercial RT-PCR diagnostic kits for COVID-19", + "rel_doi": "10.1101/2020.04.20.20067512", + "rel_title": "Rapid identification of SARS-CoV-2-infected patients at the emergency department using routine testing", "rel_date": "2020-04-24", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.04.22.056747", - "rel_abs": "The final months of 2019 witnessed the emergence of a novel coronavirus in the human population. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has since spread across the globe and is posing a major burden on society. Measures taken to reduce its spread critically depend on timely and accurate identification of virus-infected individuals by the most sensitive and specific method available, i.e. real-time reverse transcriptase PCR (RT-PCR). Many commercial kits have recently become available, but their performance has not yet been independently assessed.\n\nThe aim of this study was to compare basic analytical and clinical performance of selected RT-PCR kits from seven different manufacturers (Altona Diagnostics, BGI, CerTest Biotec, KH Medical, PrimerDesign, R-Biopharm AG, and Seegene).\n\nWe used serial dilutions of viral RNA to establish PCR efficiency and estimate the 95% limit of detection (LOD95%). Furthermore, we ran a panel of SARS-CoV-2-positive clinical samples (n=16) for a preliminary evaluation of clinical sensitivity. Finally, we used clinical samples positive for non-coronavirus respiratory viral infections (n=6) and a panel of RNA from related human coronaviruses to evaluate assay specificity.\n\nPCR efficiency was [≥]96% for all assays and the estimated LOD95% varied within a 6-fold range. Using clinical samples, we observed some variations in detection rate between kits. Importantly, none of the assays showed cross-reactivity with other respiratory (corona)viruses, except as expected for the SARS-CoV-1 E-gene.\n\nWe conclude that all RT-PCR kits assessed in this study may be used for routine diagnostics of COVID-19 in patients by experienced molecular diagnostic laboratories.", - "rel_num_authors": 9, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.20.20067512", + "rel_abs": "BackgroundThe novel coronavirus disease 19 (COVID-19), caused by SARS-CoV-2, spreads rapidly across the world. The exponential increase in the number of cases has resulted in overcrowding of emergency departments (ED). Detection of SARS-CoV-2 is based on an RT-PCR of nasopharyngeal swab material. However, RT-PCR testing is time-consuming and many hospitals deal with a shortage of testing materials. Therefore, we aimed to develop an algorithm to rapidly evaluate an individuals risk of SARS-CoV-2 infection at the ED.\n\nMethodsIn this multicenter retrospective study, routine laboratory parameters (C-reactive protein, lactate dehydrogenase, ferritin, absolute neutrophil and lymphocyte counts), demographic data and the chest X-ray/CT result from 967 patients entering the ED with respiratory symptoms were collected. Using these parameters, an easy-to-use point-based algorithm, called the corona-score, was developed to discriminate between patients that tested positive for SARS-CoV-2 by RT-PCR and those testing negative. Computational sampling was used to optimize the corona-score. Validation of the model was performed using data from 592 patients.\n\nResultsThe corona-score model yielded an area under the receiver operating characteristic curve of 0.91 in the validation population. Patients testing negative for SARS-CoV-2 showed a median corona-score of 3 versus 11 (scale 0-14) in patients testing positive for SARS-CoV-2 (p<0.001). Using cut-off values of 4 and 11 the model has a sensitivity and specificity of 96% and 95%, respectively.\n\nConclusionThe corona-score effectively predicts SARS-CoV-2 RT-PCR outcome based on routine parameters. This algorithm provides the means for medical professionals to rapidly evaluate SARS-CoV-2 infection status of patients presenting at the ED with respiratory symptoms.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Puck B van Kasteren", - "author_inst": "National Institute for Public Health and the Environment (RIVM)" + "author_name": "Steef Kurstjens", + "author_inst": "Jeroen Bosch Ziekenhuis" }, { - "author_name": "Bas van der Veer", - "author_inst": "National Institute for Public Health and the Environment" + "author_name": "Armando van der Horst", + "author_inst": "Jeroen Bosch Hospital" }, { - "author_name": "Sharon van den Brink", - "author_inst": "National Institute for Public Health and the Environment" + "author_name": "Robert Herpers", + "author_inst": "Bernhoven Hospital" }, { - "author_name": "Lisa Wijsman", - "author_inst": "National Institute for Public Health and the Environment" + "author_name": "Mick W.L. Geerits", + "author_inst": "Abnormal Design Ltd" }, { - "author_name": "Jorgen de Jonge", - "author_inst": "National Institute for Public Health and the Environment" + "author_name": "Yvette C.M. Kluiters-de Hingh", + "author_inst": "Elisabeth TweeSteden Hospital" }, { - "author_name": "Anne-Marie van den Brandt", - "author_inst": "National Institute for Public Health and the Environment (RIVM)" + "author_name": "Eva-Leonne G\u00f6ttgens", + "author_inst": "Amphia Hospital" }, { - "author_name": "Richard Molenkamp", - "author_inst": "Erasmus University Medical Center" + "author_name": "Martinus J.T. Blaauw", + "author_inst": "Bernhoven Hospital" }, { - "author_name": "Chantal B.E.M. Reusken", - "author_inst": "National Institute for Public Health and the Environment" + "author_name": "Marc H.M. Thelen", + "author_inst": "Amphia Hospital" }, { - "author_name": "Adam Meijer", - "author_inst": "National Institute for Public Health and the Environment" + "author_name": "Marc G.L.M. Elisen", + "author_inst": "Elisabeth TweeSteden Hospital" + }, + { + "author_name": "Ron Kusters", + "author_inst": "Jeroen Bosch Ziekenhuis" } ], "version": "1", - "license": "cc_by_nc_nd", - "type": "new results", - "category": "microbiology" + "license": "cc_no", + "type": "PUBLISHAHEADOFPRINT", + "category": "infectious diseases" }, { "rel_doi": "10.1101/2020.04.24.060376", @@ -1515276,339 +1515641,27 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.04.19.20071373", - "rel_title": "Scalable and Resilient SARS-CoV2 testing in an Academic Centre", + "rel_doi": "10.1101/2020.04.21.20073890", + "rel_title": "Data-driven modeling reveals a universal dynamic underlying the COVID-19 pandemic under social distancing", "rel_date": "2020-04-24", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.19.20071373", - "rel_abs": "The emergence of the novel coronavirus SARS-CoV-2 has led to a pandemic infecting more than two million people worldwide in less than four months, posing a major threat to healthcare systems. This is compounded by the shortage of available tests causing numerous healthcare workers to unnecessarily self-isolate. We provide a roadmap instructing how a research institute can be repurposed in the midst of this crisis, in collaboration with partner hospitals and an established diagnostic laboratory, harnessing existing expertise in virus handling, robotics, PCR, and data science to derive a rapid, high throughput diagnostic testing pipeline for detecting SARS-CoV-2 in patients with suspected COVID-19. The pipeline is used to detect SARS-CoV-2 from combined nose-throat swabs and endotracheal secretions/ bronchoalveolar lavage fluid. Notably, it relies on a series of in-house buffers for virus inactivation and the extraction of viral RNA, thereby reducing the dependency on commercial suppliers at times of global shortage. We use a commercial RT-PCR assay, from BGI, and results are reported with a bespoke online web application that integrates with the healthcare digital system. This strategy facilitates the remote reporting of thousands of samples a day with a turnaround time of under 24 hours, universally applicable to laboratories worldwide.", - "rel_num_authors": 80, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.21.20073890", + "rel_abs": "We show that the COVID-19 pandemic under social distancing exhibits universal dynamics. The cumulative numbers of both infections and deaths quickly cross over from exponential growth at early times to a longer period of power law growth, before eventually slowing. In agreement with a recent statistical forecasting model by the IHME, we show that this dynamics is well described by the erf function. Using this functional form, we perform a data collapse across countries and US states with very different population characteristics and social distancing policies, confirming the universal behavior of the COVID-19 outbreak. We show that the predictive power of statistical models is limited until a few days before curves flatten, forecast deaths and infections assuming current policies continue and compare our predictions to the IHME models. We present simulations showing this universal dynamics is consistent with disease transmission on scale-free networks and random networks with non-Markovian transmission dynamics.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Jim Aitken", - "author_inst": "The Francis Crick Institute" - }, - { - "author_name": "Karen Ambrose", - "author_inst": "The Francis Crick Institute" - }, - { - "author_name": "Sam Barrell", - "author_inst": "The Francis Crick Institute" - }, - { - "author_name": "Rupert Beale", - "author_inst": "The Francis Crick Institute" - }, - { - "author_name": "Ganka Bineva-Todd", - "author_inst": "The Francis Crick Institute" - }, - { - "author_name": "Dhruva Biswas", - "author_inst": "University College London" - }, - { - "author_name": "Richard Byrne", - "author_inst": "The Francis Crick Institute" - }, - { - "author_name": "Simon Caidan", - "author_inst": "The Francis Crick Institute" - }, - { - "author_name": "Peter Cherepanov", - "author_inst": "The Francis Crick Institute" - }, - { - "author_name": "Laura Churchward", - "author_inst": "University College London Hospitals, NHS Foundation Trust" - }, - { - "author_name": "Graham Clark", - "author_inst": "The Francis Crick Institute" - }, - { - "author_name": "Marg Crawford", - "author_inst": "The Francis Crick Institute" - }, - { - "author_name": "Laura Cubitt", - "author_inst": "The Francis Crick Institute" - }, - { - "author_name": "Vicky Dearing", - "author_inst": "The Francis Crick Institute" - }, - { - "author_name": "Christopher Earl", - "author_inst": "The Francis Crick Institute" - }, - { - "author_name": "Amelia Edwards", - "author_inst": "The Francis Crick Institute" - }, - { - "author_name": "Chris Ekin", - "author_inst": "Health Services Laboratories" - }, - { - "author_name": "Efthymios Fidanis", - "author_inst": "The Francis Crick Institute" - }, - { - "author_name": "Alessandra Gaiba", - "author_inst": "The Francis Crick Institute" - }, - { - "author_name": "Steve Gamblin", - "author_inst": "The Francis Crick Institute" - }, - { - "author_name": "Sonia Gandhi", - "author_inst": "The Francis Crick Institute" - }, - { - "author_name": "Jacki Goldman", - "author_inst": "The Francis Crick Institute" - }, - { - "author_name": "Robert Goldstone", - "author_inst": "The Francis Crick Institute" - }, - { - "author_name": "Paul R Grant", - "author_inst": "Health Services Laboratories" - }, - { - "author_name": "Maria Greco", - "author_inst": "The Francis Crick Institute" - }, - { - "author_name": "Judith Heaney", - "author_inst": "University College London Hospitals, NHS Foundation Trust" - }, - { - "author_name": "Steve Hindmarsh", - "author_inst": "The Francis Crick Institute" - }, - { - "author_name": "Catherine F Houlihan", - "author_inst": "University College London Hospitals, NHS Foundation Trust" - }, - { - "author_name": "Michael Howell", - "author_inst": "The Francis Crick Institute" - }, - { - "author_name": "Michael Hubank", - "author_inst": "The Institute of Cancer Research" - }, - { - "author_name": "Debbie Hughes", - "author_inst": "The Institute of Cancer Research" - }, - { - "author_name": "Rachel Instrell", - "author_inst": "The Francis Crick Institute" - }, - { - "author_name": "Deb Jackson", - "author_inst": "The Francis Crick Institute" - }, - { - "author_name": "Mariam Jamal-Hanjani", - "author_inst": "University College London" - }, - { - "author_name": "Ming Jiang", - "author_inst": "The Francis Crick Institute" - }, - { - "author_name": "Mark Johnson", - "author_inst": "The Francis Crick Institute" - }, - { - "author_name": "Leigh Jones", - "author_inst": "The Francis Crick Institute" - }, - { - "author_name": "Nnennaya Kanu", - "author_inst": "University College London" - }, - { - "author_name": "George Kassiotis", - "author_inst": "The Francis Crick Institute" - }, - { - "author_name": "Stuart Kirk", - "author_inst": "Health Services Laboratories" - }, - { - "author_name": "Svend Kjaer", - "author_inst": "The Francis Crick Institute" - }, - { - "author_name": "Andrew Levett", - "author_inst": "Health Services Laboratories" - }, - { - "author_name": "Lisa Levett", - "author_inst": "Health Services Laboratories" - }, - { - "author_name": "Marcel Levi", - "author_inst": "University College London Hospitals, NHS Foundation Trust" - }, - { - "author_name": "Wei-Ting Lu", - "author_inst": "The Francis Crick Institute" - }, - { - "author_name": "James I MacRae", - "author_inst": "The Francis Crick Institute" - }, - { - "author_name": "John Matthews", - "author_inst": "Health Services Laboratories" - }, - { - "author_name": "Laura McCoy", - "author_inst": "University College London" - }, - { - "author_name": "Catherine Moore", - "author_inst": "Public Health Wales" - }, - { - "author_name": "David Moore", - "author_inst": "University College London" - }, - { - "author_name": "Eleni Nastouli", - "author_inst": "University College London Hospitals, NHS Foundation Trust" - }, - { - "author_name": "Jerome Nicod", - "author_inst": "The Francis Crick Institute" - }, - { - "author_name": "Luke Nightingale", - "author_inst": "The Francis Crick Institute" - }, - { - "author_name": "Jessica Olsen", - "author_inst": "The Francis Crick Institute" - }, - { - "author_name": "Nicola OReilly", - "author_inst": "The Francis Crick Institute" - }, - { - "author_name": "Amar Pabari", - "author_inst": "Health Services Laboratories" - }, - { - "author_name": "Venizelos Papayannopoulos", - "author_inst": "The Francis Crick Institute" - }, - { - "author_name": "Namita Patel", - "author_inst": "The Francis Crick Institute" - }, - { - "author_name": "Nigel Peat", - "author_inst": "The Francis Crick Institute" - }, - { - "author_name": "Marc Pollitt", - "author_inst": "The Francis Crick Institute" - }, - { - "author_name": "Peter Ratcliffe", - "author_inst": "The Francis Crick Institute" - }, - { - "author_name": "Caetano Reis e Sousa", - "author_inst": "The Francis Crick Institute" - }, - { - "author_name": "Annachiara Rosa", - "author_inst": "The Francis Crick Institute" - }, - { - "author_name": "Rachel Rosenthal", - "author_inst": "The Francis Crick Institute" - }, - { - "author_name": "Chloe Roustan", - "author_inst": "The Francis Crick Institute" - }, - { - "author_name": "Andrew Rowan", - "author_inst": "The Francis Crick Institute" - }, - { - "author_name": "Gee Yen Shin", - "author_inst": "Health Services Laboratories" - }, - { - "author_name": "Daniel M Snell", - "author_inst": "The Francis Crick Institute" - }, - { - "author_name": "Ok-Ryul Song", - "author_inst": "The Francis Crick Institute" - }, - { - "author_name": "Moria Spyer", - "author_inst": "University College London" - }, - { - "author_name": "Amy Strange", - "author_inst": "The Francis Crick Institute" - }, - { - "author_name": "Charles Swanton", - "author_inst": "The Francis Crick Institute" - }, - { - "author_name": "James M A Turner", - "author_inst": "The Francis Crick Institute" - }, - { - "author_name": "Melanie Turner", - "author_inst": "Health Services Laboratories" - }, - { - "author_name": "Andreas Wack", - "author_inst": "The Francis Crick Institute" - }, - { - "author_name": "Philip A Walker", - "author_inst": "The Francis Crick Institute" - }, - { - "author_name": "Sophie Ward", - "author_inst": "The Francis Crick Institute" - }, - { - "author_name": "Wai Keong Wong", - "author_inst": "University College London Hospitals, NHS Foundation Trust" - }, - { - "author_name": "Joshua Wright", - "author_inst": "The Francis Crick Institute" + "author_name": "Robert Marsland III", + "author_inst": "Boston University" }, { - "author_name": "Mary Wu", - "author_inst": "The Francis Crick Institute" + "author_name": "Pankaj Mehta", + "author_inst": "Boston University" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", - "category": "health systems and quality improvement" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2020.04.20.20071423", @@ -1516906,49 +1516959,85 @@ "category": "endocrinology" }, { - "rel_doi": "10.1101/2020.04.21.20073536", - "rel_title": "Population modeling of early COVID-19 epidemic dynamics in French regions and estimation of the lockdown impact on infection rate", + "rel_doi": "10.1101/2020.04.20.20072413", + "rel_title": "Estimating the burden of SARS-CoV-2 in France", "rel_date": "2020-04-24", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.21.20073536", - "rel_abs": "We developed a multi-level model of the French COVID-19 epidemic at the regional level. We rely on a global extended Susceptible-Exposed-Infectious-Recovered (SEIR) mechanistic model as a simplified representation of the average epidemic process, with the addition of region specific random effects. Combining several French public datasets on the early dynamics of the epidemic, we estimate region-specific key parameters conditionally on this mechanistic model through Stochastic Approximation Expectation Maximization (SAEM) optimization using Monolix software. We thus estimate the basic reproductive numbers by region before lockdown (with a national average at 2.81 with 95% Confidence Interval [2.58; 3.07]), attack rates (i.e. percentages of infected people) over time per region which range between 1.9% and 9.9% as of May 11th, 2020, and the impact of nationwide lockdown on the infection rate which decreased the transmission rate by 76% towards reproductive numbers ranging from 0.63 to 0.73 at the end of lockdown across regions. These results confirm the low population immunity, the strong effect of the lockdown on the dynamics of the epidemics and the need for further intervention when lifting the lockdown to avoid an epidemic rebound.", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.20.20072413", + "rel_abs": "France has been heavily affected by the SARS-CoV-2 epidemic and went into lockdown on the 17th March 2020. Using models applied to hospital and death data, we estimate the impact of the lockdown and current population immunity. We find 2.6% of infected individuals are hospitalized and 0.53% die, ranging from 0.001% in those <20y to 8.3% in those >80y. Across all ages, men are more likely to be hospitalized, enter intensive care, and die than women. The lockdown reduced the reproductive number from 3.3 to 0.5 (84% reduction). By 11 May, when interventions are scheduled to be eased, we project 3.7 million (range: 2.3-6.7) people, 5.7% of the population, will have been infected. Population immunity appears insufficient to avoid a second wave if all control measures are released at the end of the lockdown.", + "rel_num_authors": 17, "rel_authors": [ { - "author_name": "Melanie Prague", - "author_inst": "Univ. Bordeaux - INRIA - Inserm U1219 - SISTM Team - Vaccine Research Institute" + "author_name": "Henrik Salje", + "author_inst": "University of Cambridge" }, { - "author_name": "Linda Wittkop", - "author_inst": "Univ. Bordeaux - Inria - Inserm U1219 - Vaccine Research Institute - CHU Bordeaux" + "author_name": "Cecile Tran Kiem", + "author_inst": "Institut Pasteur" }, { - "author_name": "Annabelle COLLIN", - "author_inst": "Inria Bordeaux Sud-Ouest, IMB, Bordeaux INP" + "author_name": "Noemie Lefrancq", + "author_inst": "Institut Pasteur" }, { - "author_name": "Quentin Clairon", - "author_inst": "Univ. Bordeaux - INRIA - Inserm U1219 - SISTM Team - Vaccine Research Institute" + "author_name": "Noemie Courtejoie", + "author_inst": "DREES, Ministere des Solidarites et de la Sante, Paris, France" }, { - "author_name": "Dan Dutartre", - "author_inst": "Inria Bordeaux" + "author_name": "Paolo Bosetti", + "author_inst": "Institut Pasteur" }, { - "author_name": "Philippe Moireau", - "author_inst": "Inria Paris Saclay, LMS, Ecole Polytechnique, CNRS, Institut Polytechnique" + "author_name": "Juliette Paireau", + "author_inst": "Institut Pasteur" }, { - "author_name": "Rodolphe Thiebaut", - "author_inst": "Univ. Bordeaux - INRIA - Inserm U1219 - SISTM Team - Vaccine Research Institute - CHU Bordeaux" + "author_name": "Alessio Andronico", + "author_inst": "Institut Pasteur" + }, + { + "author_name": "Nathanael Hoze", + "author_inst": "Institut Pasteur" + }, + { + "author_name": "Jehanne Richet", + "author_inst": "DREES, Ministere des Solidarites et de la Sante" + }, + { + "author_name": "Claire-Lise Dubost", + "author_inst": "DREES, Ministrer des Solidarites et de la Sante" + }, + { + "author_name": "Yann Le Strat", + "author_inst": "Sante Publique France" + }, + { + "author_name": "Justin Lessler", + "author_inst": "Johns Hopkins Bloomberg School of Public Health" + }, + { + "author_name": "Daniel Levy Bruhl", + "author_inst": "Sante Publique France" + }, + { + "author_name": "Arnaud Fontanet", + "author_inst": "Institut Pasteur" + }, + { + "author_name": "Lulla Opatowski", + "author_inst": "Institut Pasteur" + }, + { + "author_name": "Pierre-Yves Boelle", + "author_inst": "Sante Publique France" }, { - "author_name": "Boris Pierre Hejblum", - "author_inst": "Univ. Bordeaux - INRIA - Inserm U1219 - SISTM Team - Vaccine Research Institute" + "author_name": "Simon Cauchemez", + "author_inst": "Institut Pasteur" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1518252,25 +1518341,37 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.04.22.20076018", - "rel_title": "Optimal control of the COVID-19 pandemic with non-pharmaceutical interventions", + "rel_doi": "10.1101/2020.04.19.20071415", + "rel_title": "Impact of control strategies on COVID-19 pandemic and the SIR model based forecasting in Bangladesh.", "rel_date": "2020-04-23", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.22.20076018", - "rel_abs": "The COVID-19 pandemic has forced societies across the world to resort to social distancing to slow the spread of the SARS-CoV-2 virus. Due to the economic impacts of social distancing, there is growing desire to relax these measures. To characterize a range of possible strategies for control and to understand their consequences, we performed an optimal control analysis of a mathematical model of SARS-CoV-2 transmission. Given that the pandemic is already underway and controls have already been initiated, we calibrated our model to data from the US and focused our analysis on optimal controls from May 2020 through December 2021. We found that a major factor that differentiates strategies that prioritize lives saved versus reduced time under control is how quickly control is relaxed once social distancing restrictions expire in May 2020. Strategies that maintain control at a high level until summer 2020 allow for tapering of control thereafter and minimal deaths, whereas strategies that relax control in the short term lead to fewer options for control later and a higher likelihood of exceeding hospital capacity. Our results also highlight that the potential scope for controlling COVID-19 until a vaccine is available depends on epidemiological parameters about which there is still considerable uncertainty, including the basic reproduction number and the effectiveness of social distancing. In light of those uncertainties, our results do not constitute a quantitative forecast and instead provide a qualitative portrayal of possible outcomes from alternative approaches to control.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.19.20071415", + "rel_abs": "BackgroundCOVID-19 is transmitting worldwide drastically and infected nearly two and half million of people so far. Till date 2144 cases of COVID-19 is confirmed in Bangladesh till 18th April though the stage-3/4 transmission is not validated yet.\n\nMethodsTo project the final infection numbers in Bangladesh we used the SIR mathematical model. Confirmed cases of infection data were obtained from Institute of Epidemiology, Disease Control and Research (IEDCR) of Bangladesh\n\nResultsThe confirmed cases in Bangladesh follow our SIR model prediction cases. By the end of April the predicted cases of infection will be 17450 to 21616 depending on the control strategies. Due to large population and socio-economic characteristics, we assumed 60% social distancing and lockdown can be possible. Assuming that, the predicated final size of infections will be 3782558 on the 92th day from the first infections and steadily decrease to zero infection after 193 days\n\nConclusionTo estimate the impact of social distancing we assumed eight different scenarios, the predicted results confirmed the positive impact of this type of control strategies suggesting that by strict social distancing and lockdown, COVID-19 infection can be under control and then the infection cases will steadily decrease down to zero.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Alex Perkins", - "author_inst": "University of Notre Dame" + "author_name": "Mohammad Mahmudur Rahman", + "author_inst": "Department of Medical Biotechnology, Bangladesh University of Health Sciences, Dhaka, Bangladesh" }, { - "author_name": "Guido Espana", - "author_inst": "University of Notre Dame" + "author_name": "Asif Ahmed", + "author_inst": "Biotechnology and Genetic Engineering Discipline, Khulna Univesity, Khulna, Bangladesh" + }, + { + "author_name": "Khondoker Moazzem Hossain", + "author_inst": "Biotechnology and Genetic Engineering Discipline, Khulna University, Khulna, Bangladesh" + }, + { + "author_name": "Tasnima Haque", + "author_inst": "BIHS General Hospital, Dhaka, Bangladesh" + }, + { + "author_name": "Md. Anwar Hossain", + "author_inst": "Faculty of Public Health, Bangladesh University of Health Sciences, Dhaka, Bangladesh" } ], "version": "1", - "license": "cc_by", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1519994,59 +1520095,59 @@ "category": "gastroenterology" }, { - "rel_doi": "10.1101/2020.04.19.20071340", - "rel_title": "Are German endoscopy units prepared for the COVID-19 pandemic? A nationwide survey", + "rel_doi": "10.1101/2020.04.18.20070755", + "rel_title": "Detection of SARS-CoV-2 RNA by direct RT-qPCR on nasopharyngeal specimens without extraction of viral RNA", "rel_date": "2020-04-23", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.19.20071340", - "rel_abs": "ObjectiveThe COVID-19 pandemic challenges health care systems worldwide. In this situation, guidelines for health care professionals in endoscopy units with increased risk of infection from inhalation of airborne droplets, conjunctival contact and faeces are urgently needed. Recently, the European Society of Gastrointestinal Endoscopy (ESGE) and the German Society for Pneumology (DGP) issued recommendations. However, real-world data on the conditions and requirements of endoscopy units to adhere to this guidance are missing.\n\nDesignWe conducted an internet-based survey among German endoscopy units from all levels of care from April 1st to 7th, 2020. The survey comprised 33 questions and was distributed electronically by the German Society of Gastroenterology, Digestive and Metabolic Diseases (DGVS) and the DGP.\n\nResultsIn total, 656 endoscopy units completed the survey. Overall, 253 units (39%) cancelled fewer than 40% of their procedures. Of note, private practices cancelled less procedures than hospital-based units. Complete separation of high-risk and COVID-19 positive patients was achieved in only 20% of the units. Procedural measures were well adopted, with 91% of the units systematically identifying patients at risk and 85% using risk-adapted personal protective equipment (PPE). For the future, shortages in PPE (81%), staff (69%) and relevant financial losses (77%) were expected.\n\nConclusionConcise definitions of non-urgent, elective interventions and endoscopic surveillance strategies are needed to better guide endoscopic activity and intervention cancellations. In the short term, a lack of PPE can constitute considerable impairment of endoscopy units operability and patient outcomes.\n\nSUMMARY BOXO_LIWhat is already known about this subject?\n- Recent data indicate a potentially important role of the gastrointestinal tract in the spreading of COVID-19.\n- Endoscopy units and their personnel are at high risk to be exposed to and to distribute COVID-19 infections.\n- Several societies have formulated guidance for endoscopy units in the current situation, but their feasibility is unclear.\n\nC_LIO_LIWhat are the new findings?\n- Endoscopic activity seems not to be limited to urgent interventions across all units as 39% of all endoscopy units cancelled less than 40% of procedures.\n- For most endoscopy units, structural conditions are insufficient to realize a complete separation of high-risk patients, which can be guaranteed by only 20% of the units.\n- The willingness to adhere to the recommendations is very high, as most endoscopy units adopted their procedures accordingly. Shortage of personal protective equipment is a critical concern in many units.\n\nC_LIO_LIHow might it impact on clinical practice in the foreseeable future?\n- An update of the current recommendations to refine practicable measures for the majority of endoscopic units is warranted.\n- A concise definition of non-urgent or elective procedures as well as postponement strategies and intervals are of utmost importance, since current data implicate that transmission of SARS-CoV-2 via the respiratory and gastrointestinal tract may be critical for public health.\n\nC_LI", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.18.20070755", + "rel_abs": "To circumvent the limited availability of RNA extraction reagents, we aimed to develop a protocol for direct RT-qPCR to detect SARS-CoV-2 in nasopharyngeal swabs without RNA extraction. Nasopharyngeal specimens positive for SARS-CoV-2 and other coronaviruses collected in universal viral transport (UVT) medium were pre-processed by several commercial and laboratory-developed methods and tested by RT-qPCR assays without RNA extraction using different RT-qPCR master mixes. The results were compared to that of standard approach that involves RNA extraction. Incubation of specimens at 65{degrees}C for 10 minutes along with the use of TaqPath 1-Step RT-qPCR Master Mix provides higher analytical sensitivity for detection of SARS-CoV-2 RNA than many other conditions tested. The optimized direct RT-qPCR approach demonstrated a limit of detection of 6.6x103 copy/ml and high reproducibility (co-efficient of variation = 1.2%). In 132 nasopharyngeal specimens submitted for SARS-CoV-2 testing, the sensitivity, specificity and accuracy of our optimized approach were 95%, 99% and 98.5%, respectively, with reference to the standard approach. Also, the RT-qPCR CT values obtained by the two methods were positively correlated (Pearson correlation coefficient r=0.6971, p=0.0013). The rate of PCR inhibition by the direct approach was 8% compared to 9% by the standard approach. Our simple approach to detect SARS-CoV-2 RNA by direct RT-qPCR may help laboratories continue testing for the virus despite reagent shortages or expand their testing capacity in resource limited settings.", "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Jakob Garbe", - "author_inst": "University Hospital Halle (Saale), Department for Internal Medicine I, Germany" + "author_name": "Mohammad Rubayet Hasan", + "author_inst": "Sidra Medicine" }, { - "author_name": "Stephan Eisenmann", - "author_inst": "University Hospital Halle (Saale), Department for Internal Medicine I, Germany" + "author_name": "Faheem Mirza", + "author_inst": "Sidra Medicine" }, { - "author_name": "Clara Sophie Heidemann", - "author_inst": "University Hospital Halle (Saale), Department for Internal Medicine I, Germany" + "author_name": "Hamad Al-Hail", + "author_inst": "Sidra Medicine" }, { - "author_name": "Marko Damm", - "author_inst": "University Hospital Halle (Saale), Department for Internal Medicine I, Germany" + "author_name": "Sathyavathi Sundararaju", + "author_inst": "Sidra Medicine" }, { - "author_name": "Sebastian Krug", - "author_inst": "University Hospital Halle (Saale), Department for Internal Medicine I, Germany" + "author_name": "Thabisile Xaba", + "author_inst": "Sidra Medicine" }, { - "author_name": "Steffen Walter", - "author_inst": "University Hospital Ulm, Department for Medical Psychology, Ulm, Germany" + "author_name": "Muhammad Iqbal", + "author_inst": "Sidra Medicine" }, { - "author_name": "Frank Lammert", - "author_inst": "Saarland University Hospital, Department for Medicine II, Homburg, Germany" + "author_name": "Hashim Alhussain", + "author_inst": "Qatar University" }, { - "author_name": "Kaid Darwiche", - "author_inst": "Ruhrland Hospital, West German Lung Center, Essen, Nordrhein-Westfalen, DE" + "author_name": "Hadi Mohamad Yassine", + "author_inst": "Qatar University" }, { - "author_name": "Patrick Michl", - "author_inst": "University Hospital Halle (Saale), Department for Internal Medicine I, Germany" + "author_name": "Andres Perez Lopez", + "author_inst": "Sidra Medicine" }, { - "author_name": "Jonas Rosendahl", - "author_inst": "University Hospital Halle (Saale), Department for Internal Medicine I, Germany" + "author_name": "Patrick Tang", + "author_inst": "Sidra Medicine" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "gastroenterology" + "category": "pathology" }, { "rel_doi": "10.1101/2020.04.19.20069997", @@ -1521968,35 +1522069,59 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.04.17.20059535", - "rel_title": "Modeling projections for COVID-19 pandemic by combining epidemiological, statistical, and neural network approaches", + "rel_doi": "10.1101/2020.04.16.20067975", + "rel_title": "LONG-TERM CLINICAL OUTCOMES IN SURVIVORS OF CORONAVIRUS OUTBREAKS AFTER HOSPITALISATION OR ICU ADMISSION: A SYSTEMATIC REVIEW AND META-ANALYSIS OF FOLLOW-UP STUDIES", "rel_date": "2020-04-22", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.17.20059535", - "rel_abs": "As the number of people affected by COVID-19 disease caused by the novel coronavirus SARS-CoV-2 ebbs and flows in different national and sub-national regions across the world, it is evident that our lifestyle and socio-economic trajectories will have to be adapted and adjusted to the changing scenarios. Novel forecasting tools and frameworks provide an arguable advantage to facilitate this adapting and adjusting process, by promoting efficient resource management at individual and institutional levels. Based on deterministic compartment models we propose an empirical top-down modeling approach to provide epidemic forecasts and risk calculations for (local) outbreaks. We use neural networks to develop leading indicators based on available data for different regions. These indicators are not only used to assess the risk of a (new) outbreak or to determine the effectiveness of a measure at an early stage, but also in parametric models to determine an effective forecast, along with the associated uncertainty. Based on initial results, we show the performance of such an approach and its robustness against inherent disturbances in epidemiological surveillance data. We foresee such a statistical framework to drive web-based automatic platforms to democratize the dissemination of prognosis results.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.16.20067975", + "rel_abs": "ObjectiveTo determine the long-term clinical problems in adult survivors of coronavirus (CoV) infection [Coronavirus disease 2019 (COVID-19), Severe Acute Respiratory Syndrome (SARS) and Middle East Respiratory Syndrome (MERS)] after hospitalisation or Intensive Care Unit (ICU) admission.\n\nDesignSystematic review and meta-analysis of the literature.\n\nData sourcesOvid MEDLINE, EMBASE, CINAHL Plus and PsycINFO were searched using the strategy: (Coronavirus OR Coronavirus Infections OR COVID OR SARS virus OR Severe acute respiratory syndrome OR MERS OR Middle east respiratory syndrome) AND (Follow-up OR Follow-up studies OR Prevalence). Original studies reporting the clinical outcomes of adult survivors of coronavirus outbreaks two months after discharge or three months after admission were included. The quality of the studies was assessed using the Oxford Centre for Evidence-Based Medicine (OCEBM) 2009 Level of Evidence Tool. Meta-analysis was conducted to derive pooled estimates of prevalence and severity for different outcomes at time points up to 6 months follow-up and beyond 6 months follow-up.\n\nResultsThe search yielded 1169 studies of which 28 were included in this review. There were 15 Level 1b, 8 Level 2b, 2 Level 3b and 3 Level 4 studies by OCEBM grading. Pooled analysis of studies revealed that complications commonly observed were impaired diffusing capacity for carbon monoxide (DLCO) [prevalence of 27.26%, 95% CI 14.87 to 44.57] and reduced exercise capacity [(6-minute walking distance (6MWD) mean 461m, 95% CI 449.66 to 472.71] at 6 months with limited improvement beyond 6 months. Coronavirus survivors had considerable prevalence of psychological disorders such as post-traumatic stress disorder (PTSD) [38.80%, CI 30.93 to 47.31], depression [33.20%, CI 19.80 to 50.02] and anxiety [30.04%, CI 10.44 to 61.26) beyond 6 months. These complications were accompanied by low Short Form 36 (SF-36) scores at 6 months and beyond indicating reduced quality of life which is present long-term.\n\nConclusionsThe long term clinical problems in survivors of CoV infections (SARS and MERS) after hospitalisation or Intensive Care Unit (ICU) admission include respiratory dysfunction, reduced exercise capacity, psychological problems such as PTSD, depression and anxiety, and reduced quality of life. Critical care, rehabilitation and mental health services should anticipate a high prevalence of these problems following COVID-19 and ensure their adequate and timely management with the aim of restoring premorbid quality of life.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Steffen Uhlig", - "author_inst": "QuoData GmbH" + "author_name": "Hassaan Ahmed", + "author_inst": "University of Manchester" }, { - "author_name": "Kapil Nichani", - "author_inst": "QuoData GmbH" + "author_name": "Kajal Patel", + "author_inst": "University of Manchester" }, { - "author_name": "Carsten Uhlig", - "author_inst": "Akees GmbH" + "author_name": "Darren Greenwood", + "author_inst": "University of Leeds" }, { - "author_name": "Kirsten Simon", - "author_inst": "QuoData GmbH" + "author_name": "Stephen Halpin", + "author_inst": "University of Leeds" + }, + { + "author_name": "Penny Lewthwaite", + "author_inst": "Leeds Teaching Hospitals NHS Trust" + }, + { + "author_name": "Abayomi Salawu", + "author_inst": "Hull University Teaching Hospitals NHS Trust" + }, + { + "author_name": "Lorna Eyre", + "author_inst": "Leeds Teaching Hospitals NHS Trust" + }, + { + "author_name": "Andrew Breen", + "author_inst": "Leeds Teaching Hospitals NHS Trust" + }, + { + "author_name": "Anthony Jones", + "author_inst": "University of Manchester" + }, + { + "author_name": "Manoj Sivan", + "author_inst": "University of Leeds" } ], "version": "1", "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2020.04.18.20070367", @@ -1523378,33 +1523503,25 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.04.17.20069773", - "rel_title": "The role of corticosteroids in the management of critically ill patients with coronavirus disease 2019 (COVID-19): A meta-analysis", + "rel_doi": "10.1101/2020.04.17.20069237", + "rel_title": "Forecasting of COVID-19 Cases and Deaths Using ARIMA Models", "rel_date": "2020-04-22", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.17.20069773", - "rel_abs": "ObjectiveThere are no controlled studies on the role of systemic corticosteroids (CS) in patients with coronavirus disease 2019 (COVID-19). In the absence of high-quality evidence, understandably the recommendations from various organizations are cautious. Several randomized controlled trials are underway but shall take time to conclude. We therefore undertook a meta-analysis to ascertain the role of CS in the management of critically ill patients with COVID-19.\n\nData SourcesElectronic databases, including Pubmed, Cochrane library and Embase, were searched, using the keywords of interest and the PICO search technique, from inception to 12th April 2020.\n\nStudy SelectionStudies highlighting the use of CS in coronavirus infection with severe acute respiratory syndrome (SARS), Middle East Respiratory Syndrome (MERS) and COVID-19 were selected based on pre-determined inclusion criteria.\n\nData extractionData was extracted into an excel sheet and transferred to comprehensive meta-analysis software version 3, Biostat Inc., Englewood, NJ, USA, for analysis.\n\nData synthesisFive studies with SARS-CoV-2 infection were included in the meta-analysis. The rate ratio (RR) for mortality in patients with SARS-CoV-2 infection was 1.26 (95% CI: 0.96-1.65, I2: 74.46), indicating lack of benefit of CS therapy on mortality in critically ill patients with COVID-19. The RR for mortality on analysis of the three studies that particularly reported on patients with significant pulmonary compromise secondary to SARS-CoV-2 infection was neutral (RR: 0.91, 95% CI: 0.63-1.33, I2: 63.38).\n\nConclusionsThe use of CS in critically ill patients with COVID-19 did not improve or worsen mortality. Pending further information from controlled studies, CS can be used in critically ill patients with COVID-19 with critical illness related corticosteroid insufficiency and moderate to severe ARDS without the risk of increased mortality.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.17.20069237", + "rel_abs": "After the outbreak of severe acute respiratory syndrome (SARS-2002/2003) and middle east respiratory syndrome (MERS-2012/2014) in the world, new public health crisis, called new coronavirus disease (COVID-19), started in China in December 2019 and has spread all over countries. COVID-19 coronavirus has been global threat of the disease and infected humans rapidly. Control of the pandemi is urgently essential, and science community have continued to research treatment agents. Support therapy and intensive care units in hospitals are also efective to overcome of COVID-19. Statistic forecasting models could aid to healthcare system in preventation of COVID-19. This study aimed to compose of forecasting model that could be practical to predict the spread of COVID-19 in Italy, Spain and Turkey. For this purpose, we performed Auto Regressive Integrated Moving Average (ARIMA) model on the European Centre for Disease Prevention and Control COVID-19 data to predict the number of cases and deaths in COVID-19. According to the our results, while number of cases in Italy and Spain is expected to decrease as of July, in Turkey is expected to decline as of September. The number of deaths in Italy and Spain is expected to be the lowest in July. In Turkey, this number is expected to reach the highest in July. In addition, it is thought that if studies in which the sensitivity and validity of this method are tested with more cases, they will contribute to researchers working in this field.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Kalyan Kumar Gangopadhyay", - "author_inst": "Fortis and Peerless Hospital, Kolkata, India" + "author_name": "Lutfi Bayyurt", + "author_inst": "Tokat Gaziosmanpasa University" }, { - "author_name": "Jagat J Mukherjee", - "author_inst": "Apollo Gleneagles Hospital, Kolkata, India" - }, - { - "author_name": "Binayak Sinha", - "author_inst": "AMRI Hospitals, Kolkata, India" - }, - { - "author_name": "SAMIT GHOSAL", - "author_inst": "Nightingale Hospital" + "author_name": "Burcu Bayyurt", + "author_inst": "Sivas Cumhuriyet University" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1524824,17 +1524941,25 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.04.17.20069245", - "rel_title": "Importance of Social Distancing: Modeling the spread of 2019-nCoV using Susceptible-Infected-Quarantined-Recovered-t model", + "rel_doi": "10.1101/2020.04.17.20069161", + "rel_title": "Mortality from COVID-19 in 12 countries and 6 states of the United States", "rel_date": "2020-04-22", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.17.20069245", - "rel_abs": "BackgroundThe Novel Coronavirus that originated in Wuhan, Hubei, China, has raised global concerns and has been declared a pandemic. The infection shows the primary symptoms of pneumonia and has an incubation period, with the majority of people showing symptoms within 14 days. Online Social Networks are the closest simulations of real-world networks and have similar topology characteristics. This article simulates the spread and control of the nCoV-19 using the SIQR-t model to highlight the importance of self-quarantine and exercise of proper health care as a method to prevent the spread of the virus.\n\nMethodThe article uses the Susceptible-Infected-Quarantined-Recovered model with modification, introducing 14 different Infected states depending on the number of days the host has been carrying the infection. We simulate the spread of 2019-nCoV on human interaction similar graph taken from Online Social Network Epinions, of about 75000 nodes, similar to a small town or settlement. The infection rates depend on the sanitation and cleanliness these people exercise.\n\nResultsWhen people practice self-quarantine and hygiene, aided by the governmental efforts of testing and quarantine, the cumulative number of affected people fall drastically. The decrease is apparent in time-based simulations of the spread received from the study.\n\nConclusionThe 2019-nCoV is a highly infectious zoonotic virus. It has spread like a pandemic, and governments across the world have launched quarantines. The results of the SIQR-t model indicate that hygiene and social-distancing can reduce its impact and sharply decrease the infection scale. Individual efforts are key to the control.", - "rel_num_authors": 1, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.17.20069161", + "rel_abs": "ImportanceReliable estimates of COVID-19 mortality are crucial to aid control strategies and to assess the effectiveness of interventions.\n\nObjectiveProject COVID-19 mortality trends to October 1, 2020, in 12 countries or regions that constitute >90% of the global COVID-19 deaths reported as of April 12, 2020.\n\nDesign, Setting, and ParticipantsThe Global COVID-19 Assessment of Mortality (GCAM) is an open, transparent, and continuously updated (www.cghr.org/covid) statistical model that combines actual COVID-19 mortality counts with Bayesian inference to forecast COVID-19 deaths, the date of peak deaths, and the duration of excess mortality. The analyses covered a total of 700 million population above age 20 in 12 countries or regions: USA; Italy; Spain; France; UK; Iran; Belgium; a province of China (Hubei, which accounted for 90% of reported Chinese deaths); Germany; the Netherlands; Switzerland; and Canada; and six US states: New York, New Jersey, Michigan, Louisiana, California, and Washington.\n\nResultsForecasted deaths across the 12 current high-burden countries sum 167,000 to 593,000 (median 253,000). The trajectory of US deaths (49,000-249,000 deaths; median 86,000)--over half of which are expected in states beyond the initial six states analysed in this study--will have the greatest impact on the eventual total. Mortality ranges are 25,000-109,000 (median 46,000) in the UK; 23,000-31,000 (median 26,000) in Italy; 21,000-37,000 (median 26,000) in France and 21,000-32,000 (median 25,000) in Spain. Estimates are most precise for Hubei, China--where the epidemic curve is complete--and least precise in California, where it is ongoing. New York has the highest cumulative median mortality rate per million (1135), about 12-fold that of Germany. Mortality trajectories are notably flatter in Germany, California, and Washington State, each of which took physical distancing and testing strategies seriously. Using past country-specific mortality as a guide, GCAM predicts surge capacity needs, reaching more than twice existing capacity in a number of places., In every setting, the results might be sensitive to undercounts of COVID-19 deaths, which are already apparent.\n\nConclusion and RelevanceMortality from COVID-19 will be substantial across many settings, even in the best case scenario. GCAM will provide continually updated and increasingly precise estimates as the pandemic progresses.\n\nThe coronavirus disease (COVID-19) pandemic has already caused over 115,000 deaths, with global deaths doubling every week.1-3 Mortality is less biased than case reporting, which is affected by testing policies. However, the daily reporting of COVID-19 deaths is already known to undercount actual deaths, varying over time and place.4-6\n\nReliable estimates of total COVID-19 mortality, the date of peak deaths, and of the duration of excess mortality are crucial to aid responses to the current and potential future pandemics. We have developed the Global COVID-19 Assessment of Mortality (GCAM), a statistical model to project COVID-19 mortality trends to October 1 2020 in 12 countries or regions that constitute >90% of the global COVID-19 deaths reported as of April 12th. We report also on six US states that account for 70% of the American totals to date (Supplementary Appendix).1 We quantify the COVID-19 mortality trajectory ranges in each setting. A semi-automated website (www.cghr.org/covid) provides daily updates. GCAM is open, transparent, and uses a reasonably simple method that employs publicly reported mortality data to make plausible projections. The method is designed to improve as more mortality data become available over longer time periods.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Nipun aggarwal", - "author_inst": "Delhi Technological University" + "author_name": "Patrick Brown", + "author_inst": "University of Toronto" + }, + { + "author_name": "Prabhat Jha", + "author_inst": "University of Toronto" + }, + { + "author_name": "CGHR COVID Mortality Consortium", + "author_inst": "" } ], "version": "1", @@ -1526178,21 +1526303,61 @@ "category": "physiology" }, { - "rel_doi": "10.1101/2020.04.20.052217", - "rel_title": "SARS-CoV-2 Encodes a PPxY Late Domain Motif that is Known to Enhance 1 Budding and Spread in Enveloped RNA Viruses", + "rel_doi": "10.1101/2020.04.21.052084", + "rel_title": "Artificial intelligence predicts the immunogenic landscape of SARS-CoV-2: toward universal blueprints for vaccine designs", "rel_date": "2020-04-21", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.04.20.052217", - "rel_abs": "The current COVID-19 (Coronavirus Disease-2019) pandemic is affecting the health and/or socioeconomic welfare of almost everyone in the world. Finding vaccines and therapeutics is therefore urgent, but elucidation of the molecular mechanisms that allow some viruses to cross host species boundaries, becoming a threat to human health, must also be given close attention. Here, analysis of all proteins of SARS-CoV-2 revealed a unique PPxY Late (L) domain motif, 25PPAY28, in a spike (S) protein inside a predicted hot disordered loop subject to phosphorylation and binding. PPxY motifs in enveloped RNA viruses are known to recruit Nedd4 E3 ubiquitin ligases and ultimately the ESCRT complex to enhance virus budding and release, resulting in higher viral loads, hence facilitating new infections. Interestingly, proteins of SARS-CoV-1 do not feature PPxY motifs, which could explain why SARS-CoV-2 is more contagious than SARS-CoV-1. Should an experimental assessment of this hypothesis show that the PPxY motif plays the same role in SARS-CoV-2 as it does in other enveloped RNA viruses, this motif will become a promising target for the development of novel host-oriented antiviral therapeutics for preventing S proteins from recruiting Nedd4 E3 ubiquitin ligase partners.", - "rel_num_authors": 1, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.04.21.052084", + "rel_abs": "The global population is at present suffering from a pandemic of Coronavirus disease 2019 (COVID-19), caused by the novel coronavirus Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). The goals of this study were to use artificial intelligence (AI) to predict blueprints for designing universal vaccines against SARS-CoV-2, that contain a sufficiently broad repertoire of T-cell epitopes capable of providing coverage and protection across the global population. To help achieve these aims, we profiled the entire SARS-CoV-2 proteome across the most frequent 100 HLA-A, HLA-B and HLA-DR alleles in the human population, using host-infected cell surface antigen presentation and immunogenicity predictors from the NEC Immune Profiler suite of tools, and generated comprehensive epitope maps. We then used these epitope maps as input for a Monte Carlo simulation designed to identify statistically significant \"epitope hotspot\" regions in the virus that are most likely to be immunogenic across a broad spectrum of HLA types. We then removed epitope hotspots that shared significant homology with proteins in the human proteome to reduce the chance of inducing off-target autoimmune responses. We also analyzed the antigen presentation and immunogenic landscape of all the nonsynonymous mutations across 3400 different sequences of the virus, to identify a trend whereby SARS-COV-2 mutations are predicted to have reduced potential to be presented by host-infected cells, and consequently detected by the host immune system. A sequence conservation analysis then removed epitope hotspots that occurred in less-conserved regions of the viral proteome. Finally, we used a database of the HLA genotypes of approximately 22 000 individuals to develop a \"digital twin\" type simulation to model how effective different combinations of hotspots would work in a diverse human population, and used the approach to identify an optimal constellation of epitopes hotspots that could provide maximum coverage in the global population. By combining the antigen presentation to the infected-host cell surface and immunogenicity predictions of the NEC Immune Profiler with a robust Monte Carlo and digital twin simulation, we have managed to profile the entire SARS-CoV-2 proteome and identify a subset of epitope hotspots that could be harnessed in a vaccine formulation to provide a broad coverage across the global population.", + "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Halim Maaroufi", - "author_inst": "Universite Laval" + "author_name": "Brandon Malone", + "author_inst": "NEC Laboratories Europe GmbH" + }, + { + "author_name": "Boris Simovski", + "author_inst": "NEC OncoImmunity AS" + }, + { + "author_name": "Clement Moline", + "author_inst": "NEC OncoImmunity AS" + }, + { + "author_name": "Jun Cheng", + "author_inst": "NEC Laboratories Europe GmbH" + }, + { + "author_name": "Marius Gheorghe", + "author_inst": "NEC OncoImmunity AS" + }, + { + "author_name": "Hugues Fontenelle", + "author_inst": "NEC OncoImmunity AS" + }, + { + "author_name": "Ioannis Vardaxis", + "author_inst": "NEC OncoImmunity AS" + }, + { + "author_name": "Simen Tennoe", + "author_inst": "NEC OncoImmunity AS" + }, + { + "author_name": "Jenny-Ann Malmberg", + "author_inst": "NEC OncoImmunity AS" + }, + { + "author_name": "Richard Stratford", + "author_inst": "NEC OncoImmunity AS" + }, + { + "author_name": "Trevor Clancy", + "author_inst": "NEC OncoImmunity AS" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "new results", "category": "bioinformatics" }, @@ -1527948,429 +1528113,21 @@ "category": "scientific communication and education" }, { - "rel_doi": "10.1101/2020.04.19.049254", - "rel_title": "Integrated analyses of single-cell atlases reveal age, gender, and smoking status associations with cell type-specific expression of mediators of SARS-CoV-2 viral entry and highlights inflammatory programs in putative target cells", + "rel_doi": "10.1101/2020.04.20.046920", + "rel_title": "Leverging Deep Learning to Simulate Coronavirus Spike proteins has the potential to predict future Zoonotic sequences", "rel_date": "2020-04-20", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.04.19.049254", - "rel_abs": "The COVID-19 pandemic, caused by the novel coronavirus SARS-CoV-2, creates an urgent need for identifying molecular mechanisms that mediate viral entry, propagation, and tissue pathology. Cell membrane bound angiotensin-converting enzyme 2 (ACE2) and associated proteases, transmembrane protease serine 2 (TMPRSS2) and Cathepsin L (CTSL), were previously identified as mediators of SARS-CoV2 cellular entry. Here, we assess the cell type-specific RNA expression of ACE2, TMPRSS2, and CTSL through an integrated analysis of 107 single-cell and single-nucleus RNA-Seq studies, including 22 lung and airways datasets (16 unpublished), and 85 datasets from other diverse organs. Joint expression of ACE2 and the accessory proteases identifies specific subsets of respiratory epithelial cells as putative targets of viral infection in the nasal passages, airways, and alveoli. Cells that co-express ACE2 and proteases are also identified in cells from other organs, some of which have been associated with COVID-19 transmission or pathology, including gut enterocytes, corneal epithelial cells, cardiomyocytes, heart pericytes, olfactory sustentacular cells, and renal epithelial cells. Performing the first meta-analyses of scRNA-seq studies, we analyzed 1,176,683 cells from 282 nasal, airway, and lung parenchyma samples from 164 donors spanning fetal, childhood, adult, and elderly age groups, associate increased levels of ACE2, TMPRSS2, and CTSL in specific cell types with increasing age, male gender, and smoking, all of which are epidemiologically linked to COVID-19 susceptibility and outcomes. Notably, there was a particularly low expression of ACE2 in the few young pediatric samples in the analysis. Further analysis reveals a gene expression program shared by ACE2+TMPRSS2+ cells in nasal, lung and gut tissues, including genes that may mediate viral entry, subtend key immune functions, and mediate epithelial-macrophage cross-talk. Amongst these are IL6, its receptor and co-receptor, IL1R, TNF response pathways, and complement genes. Cell type specificity in the lung and airways and smoking effects were conserved in mice. Our analyses suggest that differences in the cell type-specific expression of mediators of SARS-CoV-2 viral entry may be responsible for aspects of COVID-19 epidemiology and clinical course, and point to putative molecular pathways involved in disease susceptibility and pathogenesis.", - "rel_num_authors": 103, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.04.20.046920", + "rel_abs": "MotivationCoronaviridae are a family of positive-sense RNA viruses capable of infecting humans and animals. These viruses usually cause a mild to moderate upper respiratory tract infection, however, they can also cause more severe symptoms, gastrointestinal and central nervous system diseases. These viruses are capable of flexibly adapting to new environments, hence health threats from coronavirus are constant and long-term. Immunogenic spike proteins are glyco-proteins found on the surface of Coronaviridae particles that mediate entry to host cells. The aim of this study was to train deep learning neural networks to produce simulated spike protein sequences, which may be able to aid in knowledge and/or vaccine design by creating alternative possible spike sequences that could arise from zoonotic sources in future.\n\nResultsHere we have trained deep learning recurrent neural networks (RNN) to provide computer-simulated coronavirus spike protein sequences in the style of previously known sequences and examine their characteristics. Training used a dataset of alpha, beta, gamma and delta coronavirus spike sequences. In a test set of 100 simulated sequences, all 100 had most significant BLAST matches to Spike proteins in searches against NCBI non-redundant dataset (NR) and also possessed concomitant Pfam domain matches.\n\nConclusionsSimulated sequences from the neural network may be able to guide us in future with prospective targets for vaccine discovery in advance of a potential novel zoonosis. We may effectively be able to fast-forward through evolution using neural networks to investigate sequences that could arise.", + "rel_num_authors": 1, "rel_authors": [ { - "author_name": "Christoph Muus", - "author_inst": "Broad Institute" - }, - { - "author_name": "Malte D Luecken", - "author_inst": "Institute of Computational Biology, Helmholtz Zentrum Munchen, Munich, Germany" - }, - { - "author_name": "Gokcen Eraslan", - "author_inst": "Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA" - }, - { - "author_name": "Avinash Waghray", - "author_inst": "Center for Regenerative Medicine, Massachusetts General Hospital, Boston, MA, USA Departments of Internal Medicine and Pediatrics, Pulmonary and Critical Care U" - }, - { - "author_name": "Graham Heimberg", - "author_inst": "Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA" - }, - { - "author_name": "Lisa Sikkema", - "author_inst": "Institute of Computational Biology, Helmholtz Zentrum Munchen, Munich, Germany" - }, - { - "author_name": "Yoshihiko Kobayashi", - "author_inst": "Department of Cell Biology, Duke University Medical School, Durham, NC 27710, USA" - }, - { - "author_name": "Eeshit Dhaval Vaishnav", - "author_inst": "Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA Department of Biology, Massachusetts Institute of Technology, Cambridge," - }, - { - "author_name": "Ayshwarya Subramanian", - "author_inst": "Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA" - }, - { - "author_name": "Christopher Smillie", - "author_inst": "Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA" - }, - { - "author_name": "Karthik Jagadeesh", - "author_inst": "Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA" - }, - { - "author_name": "Elizabeth Thu Duong", - "author_inst": "University of California San Diego Department of Pediatrics, Division of Respiratory Medicine" - }, - { - "author_name": "Evgenij Fiskin", - "author_inst": "Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA" - }, - { - "author_name": "Elena Torlai Triglia", - "author_inst": "Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA" - }, - { - "author_name": "Christophe Becavin", - "author_inst": "Universite Cote dAzur, CNRS, IPMC, Sophia-Antipolis, 06560, France" - }, - { - "author_name": "Meshal Ansari", - "author_inst": "Comprehensive Pneumology Center (CPC) / Institute of Lung Biology and Disease (ILBD), Helmholtz Zentrum Munchen, Member of the German Center for Lung Research (" - }, - { - "author_name": "Peiwen Cai", - "author_inst": "Department of Genetics and Genomic Sciences, Icahn School of Medicineat Mount Sinai, New York, NY 10029, USA" - }, - { - "author_name": "Brian Lin", - "author_inst": "Center for Regenerative Medicine, Massachusetts General Hospital, Boston, MA, USA Departments of Internal Medicine and Pediatrics, Pulmonary and Critical Care U" - }, - { - "author_name": "Justin Buchanan", - "author_inst": "Center for Epigenomics, University of California-San Diego School of Medicine, La Jolla, CA, 92093. Department of Cellular and Molecular Medicine, University of" - }, - { - "author_name": "Jian Shu", - "author_inst": "Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA Whitehead Institute for Biomedical Research, Cambridge, MA, 02142, USA" - }, - { - "author_name": "Adam L Haber", - "author_inst": "Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA 02215, USA. Klarman Cell Observatory, Broad Institute of MIT and Harv" - }, - { - "author_name": "Hattie Chung", - "author_inst": "Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA" - }, - { - "author_name": "Daniel T Montoro", - "author_inst": "Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA" - }, - { - "author_name": "Taylor Adams", - "author_inst": "Pulmonary, Critical Care and Sleep Medicine, Yale University School of Medicine" - }, - { - "author_name": "Hananeh Aliee", - "author_inst": "Institute of Computational Biology, Helmholtz Zentrum Munchen, Member of the German Center for Lung Research (DZL), Munich, Germany" - }, - { - "author_name": "Samuel J Allon", - "author_inst": "Institute for Medical Engineering and Science & Department of Chemistry, MIT; Ragon Institute of MGH, MIT and Harvard; Broad Institute of MIT and Harvard" - }, - { - "author_name": "Zaneta Andrusivova", - "author_inst": "SciLifeLab, Department of Gene Technology, KTH Royal Institute of Technology" - }, - { - "author_name": "Ilias Angelidis", - "author_inst": "Comprehensive Pneumology Center (CPC) / Institute of Lung Biology and Disease (ILBD), Helmholtz Zentrum Munchen, Member of the German Center for Lung Research (" - }, - { - "author_name": "Orr Ashenberg", - "author_inst": "Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA" - }, - { - "author_name": "Kevin Bassler", - "author_inst": "Department for Genomics & Immunoregulation, LIMES-Institute, University of Bonn, 53115 Bonn, Germany" - }, - { - "author_name": "Inbal Benhar", - "author_inst": "Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA Center for Brain Science, Harvard University, Cambridge, MA 02138 Depart" - }, - { - "author_name": "Joseph Bergenstrahle", - "author_inst": "SciLifeLab, Department of Gene Technology, KTH Royal Institute of Technology" - }, - { - "author_name": "Ludvig Bergenstrahle", - "author_inst": "SciLifeLab, Department of Gene Technology, KTH Royal Institute of Technology" - }, - { - "author_name": "Liam Bolt", - "author_inst": "Wellcome Sanger Institute, Hinxton, Cambridgeshire, CB10 1SA, UK" - }, - { - "author_name": "Emelie Braun", - "author_inst": "Division of Molecular Neurobiology, Department of Medical Biochemistry and Biophysics, Karolinska Institute" - }, - { - "author_name": "Linh T Bui", - "author_inst": "Translational Genomics Research Institute, Phoenix, AZ" - }, - { - "author_name": "Mark Chaffin", - "author_inst": "Precision Cardiology Laboratory, The Broad Institute, Cambridge, MA, USA 02142" - }, - { - "author_name": "Evgeny Chichelnitskiy", - "author_inst": "Institute of Transplant Immunology, Hannover Medical School, MHH, Carl-Neuberg Str. 1, 30625 Hannover, Germany, phone +40 511 532 9745; fax +40 511 532 8090; Ge" - }, - { - "author_name": "Joshua Chiou", - "author_inst": "Biomedical Sciences Graduate Program, University of California-San Diego, La Jolla, CA, 92093" - }, - { - "author_name": "Thomas M Conlon", - "author_inst": "Comprehensive Pneumology Center (CPC) / Institute of Lung Biology and Disease (ILBD), Helmholtz Zentrum Munchen, Member of the German Center for Lung Research (" - }, - { - "author_name": "Michael S Cuoco", - "author_inst": "Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA" - }, - { - "author_name": "Marie Deprez", - "author_inst": "Universite Cote dAzur, CNRS, IPMC, Sophia-Antipolis, 06560, France" - }, - { - "author_name": "David S Fischer", - "author_inst": "Institute of Computational Biology, Helmholtz Zentrum Munchen, Munich, Germany" - }, - { - "author_name": "Astrid Gillich", - "author_inst": "Department of Biochemistry and Howard Hughes Medical Institute, Stanford University School of Medicine, Stanford, CA." - }, - { - "author_name": "Joshua Gould", - "author_inst": "Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA" - }, - { - "author_name": "Austin J Gutierrez", - "author_inst": "Translational Genomics Research Institute, Phoenix, AZ" - }, - { - "author_name": "Arun C Habermann", - "author_inst": "Division of Allergy, Pulmonary and Critical Care Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN" - }, - { - "author_name": "Tyler Harvey", - "author_inst": "Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA" - }, - { - "author_name": "Peng He", - "author_inst": "Wellcome Sanger Institute, Hinxton, Cambridgeshire, CB10 1SA, UK" - }, - { - "author_name": "Xiaomeng Hou", - "author_inst": "Center for Epigenomics, University of California-San Diego School of Medicine, La Jolla, CA, 92093. Department of Cellular and Molecular Medicine, University of" - }, - { - "author_name": "Lijuan Hu", - "author_inst": "Division of Molecular Neurobiology, Department of Medical Biochemistry and Biophysics, Karolinska Institute" - }, - { - "author_name": "Alok Jaiswal", - "author_inst": "Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA" - }, - { - "author_name": "Peiyong Jiang", - "author_inst": "Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong SAR, China" - }, - { - "author_name": "Theodoros Kapellos", - "author_inst": "Department for Genomics & Immunoregulation, LIMES-Institute, University of Bonn, 53115 Bonn, Germany" - }, - { - "author_name": "Christin S Kuo", - "author_inst": "Department of Pediatrics, Pulmonary Medicine, Stanford University School of Medicine, Stanford, CA." - }, - { - "author_name": "Ludvig Larsson", - "author_inst": "SciLifeLab, Department of Gene Technology, KTH Royal Institute of Technology" - }, - { - "author_name": "Michael A Leney-Greene", - "author_inst": "Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA" - }, - { - "author_name": "Kyungtae Lim", - "author_inst": "Gurdon Institute, University of Cambridge, Cambridge, CB2 1QN, UK" - }, - { - "author_name": "Monika Litvinukova", - "author_inst": "Cellular Genetics Programme, Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, United Kingdom.; Cardiovascular and Metabolic Scien" - }, - { - "author_name": "Ji Lu", - "author_inst": "Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong SAR, China" - }, - { - "author_name": "Leif S Ludwig", - "author_inst": "Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA Division of Hematology / Oncology, Boston Childrens Hospital and Departm" - }, - { - "author_name": "Wendy Luo", - "author_inst": "Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA" - }, - { - "author_name": "Henrike Maatz", - "author_inst": "Cardiovascular and Metabolic Sciences, Max Delbruck Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin, Germany" - }, - { - "author_name": "Elo Maddissoon", - "author_inst": "Wellcome Sanger Institute, Hinxton, Cambridgeshire, CB10 1SA, UK" - }, - { - "author_name": "Lira Mamanova", - "author_inst": "Wellcome Sanger Institute, Hinxton, Cambridgeshire, CB10 1SA, UK" - }, - { - "author_name": "Kasidet Manakongtreecheep", - "author_inst": "Broad Institute of MIT and Harvard, Cambridge, MA, USA Center for Cancer Research, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA Cente" - }, - { - "author_name": "Ian Mbano", - "author_inst": "Africa Health Research Institute, Durban, South Africa" - }, - { - "author_name": "Alexi M McAdams", - "author_inst": "Department of Ophthalmology, Harvard Medical School and Massachusetts Eye and Ear, Boston, MA 02114" - }, - { - "author_name": "Ross J Metzger", - "author_inst": "Vera Moulton Wall Center for Pulmonary Vascular Disease, Department of Pediatrics, Division of Cardiology, Stanford University School of Medicine, Stanford, CA" - }, - { - "author_name": "Ahmad N Nabhan", - "author_inst": "Department of Biochemistry and Howard Hughes Medical Institute, Stanford University School of Medicine, Stanford, CA." - }, - { - "author_name": "Sarah K Nyquist", - "author_inst": "Computational and Systems Biology, CSAIL, Institute for Medical Engineering and Science & Department of Chemistry, MIT; Ragon Institute of MGH, MIT and Harvard;" - }, - { - "author_name": "Jose Ordovas-Montanes", - "author_inst": "Division of Gastroenterology Boston Childrens Hospital; Program in Immunology Harvard Medical School; Harvard Stem Cell Institute; Broad Institute of MIT and Ha" - }, - { - "author_name": "Lolita Penland", - "author_inst": "Chan Zuckerberg Biohub, San Francisco, CA, USA." - }, - { - "author_name": "Olivier B Poirion", - "author_inst": "Center for Epigenomics, University of California-San Diego School of Medicine, La Jolla, CA, 92093. Department of Cellular and Molecular Medicine, University of" - }, - { - "author_name": "Segio Poli", - "author_inst": "Division of Internal Medicine - Mount Sinai Medical Center, Miami Beach, FL" - }, - { - "author_name": "CanCan Qi", - "author_inst": "Dept. of Pediatric Pulmonology and Pediatric Allergology, Beatrix Childrens Hospital, University of Groningen, University Medical Center Groningen, Groningen, T" - }, - { - "author_name": "Daniel Reichart", - "author_inst": "Department of Genetics, Harvard Medical School, Boston, MA, United States.; Department of Cardiology, University Heart&Vascular Center, University of Hamburg, H" - }, - { - "author_name": "Ivan Rosas", - "author_inst": "Pulmonary, Critical Care and Sleep Medicine, Yale University School of Medicine" - }, - { - "author_name": "Jonas Schupp", - "author_inst": "Pulmonary, Critical Care and Sleep Medicine, Yale University School of Medicine" - }, - { - "author_name": "Rahul Sinha", - "author_inst": "Institute for Stem Cell Biology and Regenerative Medicine, Department of Pathology, Stanford University School of Medicine, Stanford, CA" - }, - { - "author_name": "Rene V Sit", - "author_inst": "Chan Zuckerberg Biohub, San Francisco, CA, USA." - }, - { - "author_name": "Kamil Slowikowski", - "author_inst": "Broad Institute of MIT and Harvard, Cambridge, MA, USA Center for Cancer Research, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA Cente" - }, - { - "author_name": "Michal Slyper", - "author_inst": "Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA" - }, - { - "author_name": "Neal Smith", - "author_inst": "Broad Institute of MIT and Harvard, Cambridge, MA, USA Center for Cancer Research, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA Cente" - }, - { - "author_name": "Alex Sountoulidis", - "author_inst": "Stockholm University, Department of Molecular Biosciences, The Wenner-Gren Institute" - }, - { - "author_name": "Maximilian Strunz", - "author_inst": "Comprehensive Pneumology Center (CPC) / Institute of Lung Biology and Disease (ILBD), Helmholtz Zentrum Munchen, Member of the German Center for Lung Research (" - }, - { - "author_name": "Dawei Sun", - "author_inst": "Gurdon Institute, University of Cambridge, Cambridge, CB2 1QN, UK" - }, - { - "author_name": "Carlos Talavera-Lopez", - "author_inst": "Cellular Genetics Programme, Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, United Kingdom" - }, - { - "author_name": "Peng Tan", - "author_inst": "Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA" - }, - { - "author_name": "Jessica Tantivit", - "author_inst": "Broad Institute of MIT and Harvard, Cambridge, MA, USA Center for Cancer Research, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA Cente" - }, - { - "author_name": "Kyle J Travaglini", - "author_inst": "Department of Biochemistry and Howard Hughes Medical Institute, Stanford University School of Medicine, Stanford, CA." - }, - { - "author_name": "Nathan R Tucker", - "author_inst": "Precision Cardiology Laboratory, The Broad Institute, Cambridge, MA, USA 02142 Masonic Medical Research Institute, Utica, NY, USA 13501" - }, - { - "author_name": "Katherine Vernon", - "author_inst": "Department of Medicine, Brigham and Womens Hospital and Harvard Medical School, Boston, MA, USA Broad Institute of MIT and Harvard, Cambridge, MA, USA" - }, - { - "author_name": "Marc H Wadsworth III", - "author_inst": "Institute for Medical Engineering and Science, Department of Chemistry & Koch Institute for Integrative Cancer Research, MIT; Ragon Institute of MGH, MIT and Ha" - }, - { - "author_name": "Julia Waldman", - "author_inst": "Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA" - }, - { - "author_name": "Xiuting Wang", - "author_inst": "Department of Genetics and Genomic Sciences, Icahn School of Medicineat Mount Sinai, New York, NY 10029, USA" - }, - { - "author_name": "Wenjun Yan", - "author_inst": "Center for Brain Science, Harvard University, Cambridge, MA 02138 Department of Molecular and Cellular Biology, Harvard University, Cambridge, MA 02138" - }, - { - "author_name": "Ali Onder Yildirim", - "author_inst": "Comprehensive Pneumology Center (CPC) / Institute of Lung Biology and Disease (ILBD), Helmholtz Zentrum Munchen, Member of the German Center for Lung Research (" - }, - { - "author_name": "William Zhao", - "author_inst": "Department of Genetics and Genomic Sciences, Icahn School of Medicineat Mount Sinai, New York, NY 10029, USA" - }, - { - "author_name": "Carly G K Ziegler", - "author_inst": "Harvard-MIT Health Sciences and Technology, Institute for Medical Engineering and Science, Koch Institute for Integrative Cancer Research, MIT; Broad Institute " - }, - { - "author_name": "Aviv Regev", - "author_inst": "MIT and Broad Inst. of MIT & Harvard" - }, - { - "author_name": "- The NHLBI LungMAP Consortium", - "author_inst": "-" - }, - { - "author_name": "- The Human Cell Atlas Lung Biological Network", - "author_inst": "-" + "author_name": "Lisa Caroline Crossman", + "author_inst": "SequenceAnalysis.co.uk & University of East Anglia, Norwich" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by_nc", "type": "new results", "category": "bioinformatics" }, @@ -1529914,87 +1529671,79 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.04.14.20065276", - "rel_title": "Hydroxychloroquine Versus COVID-19: A Rapid Systematic Review and Meta-Analysis", + "rel_doi": "10.1101/2020.04.15.20067157", + "rel_title": "Epidemiology, clinical course, and outcomes of critically ill adults with COVID-19 in New York City: a prospective cohort study", "rel_date": "2020-04-20", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.14.20065276", - "rel_abs": "BackgroundCoronavirus Disease 2019 (COVID-19) has become a major global issue with rising the number of infected individuals and mortality in recent months. Among all therapeutic approaches, arguments have raised about hydroxychloroquine (HCQ) efficacy in the treatment of COVID-19. We carried out a systematic review and meta-analysis overcome the controversies regarding the effectiveness of hydroxychloroquine in the treatment of COVID-19.\n\nMethodsA systematic search was performed in PubMed, Scopus, Embase, Cochrane Library, Web of Science, Google Scholar and medRxiv pre-print database using all available MeSH terms for COVID-19 and hydroxychloroquine up to July 19, 2020. Studies focused on the effectiveness of HCQ with/without azithromycin (AZM) in confirmed COVID-19 patients were entered into the study. Two researchers have independently evaluated quality assessment of the studies and abstracted data for data extraction. Extracted data were analyzed using CMA v. 2.2.064. Heterogeneity was assessed using the I-squared (I2) test, and fixed/random-effects model was used when appropriate for pooling of studies.\n\nResultsOut of 26 studies entered into our systematic review, 21 studies including 14 comparative studies with control group and seven observational studies containing 103,486 participants have entered into the meta-analysis. The results of the meta-analysis on comparative studies indicated no significant clinical effectiveness (negative in RT-PCR evaluation) for HCQ regimen in the treatment of COVID-19 in comparison to control group (RR: 1.03, 95% CI, 0.79-1.34). The same result was observed for the combination of HCQ+azithromycin (RR: 1.26, 95% CI, 0.91-1.74). No significant differences were found for both HCQ (RR: 0.92, 95% CI, 0.72-1.16) and HCQ+AZM (RR: 1.72, 95% CI, 0.86-3.42) mortality rate; however, mortality was affected by age differences according to meta-regression analysis (P<0.000001). No substantial difference was observed for disease exacerbation (RR: 1.23, 95% CI, 0.65-2.30) between HCQ group and controls. Also, radiological findings significantly improved in the HCQ group (OR: 0.32, 95% CI, 0.11-0.98). Odds of known HCQ adverse effects (diarrhea, vomiting, blurred vision, rash, headache, etc.) occurred in the HCQ regimen group was approximately 3.5 times of control group (OR: 3.40, 95% CI, 1.65-6.98), but no substantial differences were found regarding intubation odds between HCQ group and control group (OR: 2.11, 95% CI, 0.31-14.03). Meta-analysis indicated no significant prophylactic effects for HCQ (OR: 0.40, 95% CI, 0.04-3.65)\n\nConclusionThis systematic review and meta-analysis showed no clinical benefits regarding HCQ treatment with/without azithromycin for COVID-19 patients. Although mortality rate was not significantly different between cases and controls, frequency of adverse effects was substantially higher in HCQ regimen group. However, due to that most of the studies were non-randomized and results were not homogenous, selection bias was unavoidable and further large randomized clinical trials following comprehensive meta-analysis should be taken into account in order to achieve more reliable findings. Also, it is worth mentioning that if this work does not allow to quantify a \"value\" of the HCQ, it allows at least to know what is not the HCQ and that it would be prudent not to continue investing in this direction.", - "rel_num_authors": 17, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.15.20067157", + "rel_abs": "BackgroundNearly 30,000 patients with coronavirus disease-2019 (COVID-19) have been hospitalized in New York City as of April 14th, 2020. Data on the epidemiology, clinical course, and outcomes of critically ill patients with COVID-19 in this setting are needed.\n\nMethodsWe prospectively collected clinical, biomarker, and treatment data on critically ill adults with laboratory-confirmed-COVID-19 admitted to two hospitals in northern Manhattan between March 2nd and April 1st, 2020. The primary outcome was in-hospital mortality.\n\nSecondary outcomes included frequency and duration of invasive mechanical ventilation, frequency of vasopressor use and renal-replacement-therapy, and time to clinical deterioration following hospital admission. The relationship between clinical risk factors, biomarkers, and in-hospital mortality was modeled using Cox-proportional-hazards regression. Each patient had at least 14 days of observation.\n\nResultsOf 1,150 adults hospitalized with COVID-19 during the study period, 257 (22%) were critically ill. The median age was 62 years (interquartile range [IQR] 51-72); 170 (66%) were male. Two-hundred twelve (82%) had at least one chronic illness, the most common of which were hypertension (63%; 162/257) and diabetes mellitus (36%; 92/257). One-hundred-thirty-eight patients (54%) were obese, and 13 (5%) were healthcare workers. As of April 14th, 2020, in-hospital mortality was 33% (86/257); 47% (122/257) of patients remained hospitalized. Two-hundred-one (79%) patients received invasive mechanical ventilation (median 13 days [IQR 9-17]), and 54% (138/257) and 29% (75/257) required vasopressors and renal-replacement-therapy, respectively. The median time to clinical deterioration following hospital admission was 3 days (IQR 1-6). Older age, hypertension, chronic lung disease, and higher concentrations of interleukin-6 and d-dimer at admission were independently associated with in-hospital mortality.\n\nConclusionsCritical illness among patients hospitalized with COVID-19 in New York City is common and associated with a high frequency of invasive mechanical ventilation, extra-pulmonary organ dysfunction, and substantial in-hospital mortality.", + "rel_num_authors": 15, "rel_authors": [ { - "author_name": "Amir Shamshirian", - "author_inst": "Mazandaran University of Medical Sciences" - }, - { - "author_name": "Amirhossein Hessami", - "author_inst": "Mazandaran University of Medical Sciences" - }, - { - "author_name": "Keyvan Heydari", - "author_inst": "Mazandaran University of Medical Sciences" + "author_name": "Matthew J Cummings", + "author_inst": "Columbia University" }, { - "author_name": "Reza Alizadeh-Navaei", - "author_inst": "Mazandaran University of Medical Sciences" + "author_name": "Matthew R Baldwin", + "author_inst": "Columbia University" }, { - "author_name": "Mohammad Ali Ebrahimzadeh", - "author_inst": "Mazandaran University of Medical Sciences" + "author_name": "Darryl Abrams", + "author_inst": "Columbia University" }, { - "author_name": "George W YIP", - "author_inst": "National University of Singapore" + "author_name": "Samuel D Jacobson", + "author_inst": "Columbia University" }, { - "author_name": "Roya Ghasemian", - "author_inst": "Mazandaran University of Medical Sciences" + "author_name": "Benjamin J Meyer", + "author_inst": "Columbia University" }, { - "author_name": "Meghdad Sedaghat", - "author_inst": "Shahid Beheshti University of Medical Sciences" + "author_name": "Elizabeth M Balough", + "author_inst": "Columbia University" }, { - "author_name": "Hananeh Baradaran", - "author_inst": "Tehran university of medical sciences" + "author_name": "Justin G Aaron", + "author_inst": "Columbia University" }, { - "author_name": "Soheil Mohammadi Yazdi", - "author_inst": "Kashan University of Medical Sciences" + "author_name": "Jan Claassen", + "author_inst": "Columbia University" }, { - "author_name": "Elham Aboufazeli", - "author_inst": "IRAN NAJO Pharmaceutical Company" + "author_name": "LeRoy E Rabbani", + "author_inst": "Columbia University" }, { - "author_name": "Hamed Jafarpour", - "author_inst": "Mazandaran University of Medical Sciences" + "author_name": "Jonathan Hastie", + "author_inst": "Columbia University" }, { - "author_name": "Ehsan Dadgostar", - "author_inst": "Halal research center of IRI" + "author_name": "Beth R Hochman", + "author_inst": "Columbia University" }, { - "author_name": "Behnaz Tirandazi", - "author_inst": "Iran University of Medical Sciences" + "author_name": "John Salazar-Schicchi", + "author_inst": "Columbia University" }, { - "author_name": "Keyvan Karimifar", - "author_inst": "Mashhad University of Medical Sciences" + "author_name": "Natalie H Yip", + "author_inst": "Columbia University" }, { - "author_name": "Aida Eftekhari", - "author_inst": "Mashhad University of Medical Sciences" + "author_name": "Daniel Brodie", + "author_inst": "Columbia University" }, { - "author_name": "Danial Shamshirian", - "author_inst": "Shahid Beheshti University of Medical Sciences" + "author_name": "Max R O'Donnell", + "author_inst": "Columbia University" } ], "version": "1", "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "intensive care and critical care medicine" }, { "rel_doi": "10.1101/2020.04.15.20066860", @@ -1531560,97 +1531309,29 @@ "category": "pathology" }, { - "rel_doi": "10.1101/2020.04.13.20063784", - "rel_title": "Comparative dynamic aerosol efficiencies of three emergent coronaviruses and the unusual persistence of SARS-CoV-2 in aerosol suspensions", + "rel_doi": "10.1101/2020.04.13.20064162", + "rel_title": "Mesenchymal stromal cells for COVID-19: A living systematic review protocol", "rel_date": "2020-04-18", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.13.20063784", - "rel_abs": "The emergent coronavirus, designated severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), is a zoonotic pathogen that has demonstrated remarkable transmissibility in the human population and is the etiological agent of a current global pandemic called COVID-191. We measured the dynamic (short-term) aerosol efficiencies of SARS-CoV-2 and compared the efficiencies with two other emerging coronaviruses, SARS-CoV (emerged in 2002) and Middle Eastern respiratory syndrome CoV (MERS-CoV; emerged starting in 2012). We also quantified the long-term persistence of SARS-CoV-2 and its ability to maintain infectivity when suspended in aerosols for up to 16 hours.", - "rel_num_authors": 20, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.13.20064162", + "rel_abs": "ObjectiveTo determine the impact of mesenchymal stromal cells outcomes important to patients with COVID-19.\n\nDesignThis is the protocol of a living systematic review.\n\nData sourcesWe will conduct searches in PubMed/Medline, Embase, Cochrane Central Register of Controlled Trials (CENTRAL), grey literature and in a centralised repository in L{middle dot}OVE (Living OVerview of Evidence). L{middle dot}OVE is a platform that maps PICO questions to evidence from Epistemonikos database. In response to the COVID-19 emergency, L{middle dot}OVE was adapted to expand the range of evidence it covers and customised to group all COVID-19 evidence in one place. The search will cover the period until the day before submission to a journal.\n\nEligibility criteria for selecting studies and methodsWe adapted an already published common protocol for multiple parallel systematic reviews to the specificities of this question.\n\nWe will include randomised trials evaluating the effect of mesenchymal stromal cells versus placebo or no treatment in patients with COVID-19. Randomised trials evaluating other coronavirus infections, such as MERS-CoV and SARS-CoV, and non-randomised studies in COVID-19 will be searched in case we find no direct evidence from randomised trials, or if the direct evidence provides low- or very low-certainty for critical outcomes.\n\nTwo reviewers will independently screen each study for eligibility, extract data, and assess the risk of bias. We will pool the results using meta-analysis and will apply the GRADE system to assess the certainty of the evidence for each outcome.\n\nA living, web-based version of this review will be openly available during the COVID-19 pandemic. We will resubmit it every time the conclusions change or whenever there are substantial updates.\n\nEthics and disseminationNo ethics approval is considered necessary. The results of this review will be widely disseminated via peer-reviewed publications, social networks and traditional media.\n\nPROSPERO RegistrationSubmitted to PROSPERO (awaiting ID allocation).", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Alyssa C Fears", - "author_inst": "Tulane School of Medicine, Tulane National Primate Research Center" - }, - { - "author_name": "William B Klimstra", - "author_inst": "University of Pittsburgh" - }, - { - "author_name": "Paul Duprex", - "author_inst": "University of Pittsburgh" - }, - { - "author_name": "Amy Hartman", - "author_inst": "University of Pittsburgh" - }, - { - "author_name": "Scott C. Weaver", - "author_inst": "World Reference Center for Emerging Viruses and Arboviruses, Institute for Human Infections and Immunity, University of Texas Medical Branch" - }, - { - "author_name": "Ken S. Plante", - "author_inst": "World Reference Center for Emerging Viruses and Arboviruses, Institute for Human Infections and Immunity, University of Texas Medical Branch" - }, - { - "author_name": "Divya Mirchandani", - "author_inst": "World Reference Center for Emerging Viruses and Arboviruses, Institute for Human Infections and Immunity, University of Texas Medical Branch G" - }, - { - "author_name": "Jessica Plante", - "author_inst": "World Reference Center for Emerging Viruses and Arboviruses, Institute for Human Infections and Immunity, University of Texas Medical Branch G" - }, - { - "author_name": "Patricia V. Aguilar", - "author_inst": "Department of Pathology and Center for Tropical Diseases, University of Texas Medical Branch" - }, - { - "author_name": "Diana Fernandez", - "author_inst": "Department of Pathology and Center for Tropical Diseases, University of Texas Medical Branch" - }, - { - "author_name": "Aysegul Nalca", - "author_inst": "USAMRIID" - }, - { - "author_name": "Allison Totura", - "author_inst": "USAMRIID" - }, - { - "author_name": "David Dyer", - "author_inst": "USAMRIID" - }, - { - "author_name": "Brian Kearney", - "author_inst": "USAMRIID" - }, - { - "author_name": "Matthew Lackemeyer", - "author_inst": "National Institutes of Health, National Institute of Allergy and Infectious Diseases, Integrated Research Facility" - }, - { - "author_name": "J. Kyle Bohannon", - "author_inst": "National Institutes of Health, National Institute of Allergy and Infectious Diseases, Integrated Research Facility" - }, - { - "author_name": "Reed Johnson", - "author_inst": "National Institutes of Health, National Institute of Allergy and Infectious Diseases, Integrated Research Facility" - }, - { - "author_name": "Robert F Garry", - "author_inst": "Tulane School of Medicine, Tulane National Primate Research Center" + "author_name": "Gabriel Rada", + "author_inst": "Epistemonikos Foundation" }, { - "author_name": "Doug S Reed", - "author_inst": "University of Pittsburgh" + "author_name": "Javiera Corbalan", + "author_inst": "Institute of Public Health, Faculty of Medicine, Universidad Austral de Chile" }, { - "author_name": "Chad J Roy", - "author_inst": "Tulane School of Medicine, Tulane National Primate Research Center" + "author_name": "Patricio Rojas", + "author_inst": "Hematology and Oncology Department, Faculty of Medicine, Pontificia Universidad Catolica de Chile, Santiago, Chile. University Hospital, Cleveland Medical Cente" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1533294,55 +1532975,27 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.04.11.037473", - "rel_title": "Multiscale three-dimensional pathology findings of COVID-19 diseased lung using high-resolution cleared tissue microscopy", + "rel_doi": "10.1101/2020.04.14.20064766", + "rel_title": "The end of the social confinement in Spain and the COVID-19 re-emergence risk", "rel_date": "2020-04-17", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.04.11.037473", - "rel_abs": "The study of pulmonary samples from individuals who have died as a direct result of COVID-19 infection is vital to our understanding of the pathogenesis of this disease. Histopathologic studies of lung tissue from autopsy of patients with COVID-19 specific mortality are only just emerging. All existing reports have relied on traditional 2-dimensional slide-based histological methods for specimen preparation. However, emerging methods for high-resolution, massively multiscale imaging of tissue microstructure using fluorescence labeling and tissue clearing methods enable the acquisition of tissue histology in 3-dimensions, that could open new insights into the nature of SARS-Cov-2 infection and COVID-19 disease processes. In this article, we present the first 3-dimensional images of lung autopsy tissues taken from a COVID-19 patient, including 3D \"virtual histology\" of cubic-millimeter volumes of the diseased lung, providing unique insights into disease processes contributing to mortality that could inform frontline treatment decisions.", - "rel_num_authors": 9, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.14.20064766", + "rel_abs": "After the spread of SARS-CoV-2 epidemic out of China, the world approaches the 2 million declared infected cases and death toll rises well above the 100 thousand. The course of pandemic evolution has shown great differences among countries and not much is yet known about the level of generated immunity, which might appear not to be long-lasting. In this situation, management of a recurrent disease seems to be a plausible scenario that countries worldwide will have to face, before effective drugs or a vaccine appear. Spain in Europe, appears to be the first country deciding to partly lift the strict social distancing regulations imposed. Whether this action may lead to further epidemic recrudescence, to a following second wave of cases or conversely, help return to previous normality, is a subject of great debate and interest to all other countries affected by COVID-19. Here we applied a modified SEIR compartmental model accounting for the spread of infection during the latent period, in which we had also incorporated effects of social confinement. We now modify this previous model configuration to mimic potential post-confinement scenarios, by simulating from instant massive liberation of different portions of the confined population, up to a more gradual incorporation of people to work. Results show how current lockdown conditions should be extended at least two weeks more to prevent a new escalation in cases and deaths, as well as a larger second wave occurring in just a few months. Conversely, best-case scenario in terms of lower COVID-19 incidence and casualties should gradually incorporate workers back in a daily proportion at most 30 percent higher than that of previous confinement. The former should begin not earlier than by the end of April and it would represent approximately 600 thousand people or a 3.75% rate for the whole of Spain.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Guang Li", - "author_inst": "Tulane University" - }, - { - "author_name": "Sharon E Fox", - "author_inst": "LSU Health Sciences Center - New Orleans" - }, - { - "author_name": "Brian Summa", - "author_inst": "Tulane University" - }, - { - "author_name": "Bihe Hu", - "author_inst": "Tulane University" - }, - { - "author_name": "Carola Wenk", - "author_inst": "Tulane University" - }, - { - "author_name": "Aibek Akmatbekov", - "author_inst": "LSU Health Sciences Center - New Orleans" - }, - { - "author_name": "Jack L Harbert", - "author_inst": "LSU Health Sciences Center - New Orleans" - }, - { - "author_name": "Richard S. Vander Heide", - "author_inst": "LSU Health Sciences Center - New Orleans" + "author_name": "Leonardo Lopez", + "author_inst": "ISGlobal" }, { - "author_name": "J. Quincy Brown", - "author_inst": "Tulane University" + "author_name": "Xavier Rodo", + "author_inst": "ISGlobal" } ], "version": "1", "license": "cc_no", - "type": "new results", - "category": "pathology" + "type": "PUBLISHAHEADOFPRINT", + "category": "epidemiology" }, { "rel_doi": "10.1101/2020.04.15.043364", @@ -1535020,93 +1534673,37 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.04.14.20065664", - "rel_title": "Application of Telemedicine During the Coronavirus Disease Epidemics: A Rapid Review and Meta-Analysis", + "rel_doi": "10.1101/2020.04.14.20065557", + "rel_title": "Failing our Most Vulnerable: COVID-19 and Long-Term Care Facilities in Ontario", "rel_date": "2020-04-17", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.14.20065664", - "rel_abs": "BackgroundAs COVID-19 has become a global pandemic, early prevention and control of the epidemic is extremely important. Telemedicine, which includes medical advice given over telephone, Internet, mobile phone applications or other similar ways, may be an efficient way to reduce transmission and pressure on medical institutions.\n\nMethodsWe searched MEDLINE, Web of science, Embase, Cochrane, CBM, CNKI and Wanfang databases for literature on the use of telemedicine for COVID-19, SARS and MERS. from their inception to March 31st, 2020. We included studies about the content of the consultation (such as symptoms, therapy and prevention, policy, public service), screening of suspected cases, the provision of advice given to those people who may have symptoms or contact history. We conducted meta-analyses on the main outcomes of the studies.\n\nResultsA total of 2041 articles were identified after removing duplicates. After reading the full texts, we finally included nine studies. People were most concerned about symptoms (64.2%), epidemic situation and public problems (14.5%), and psychological problems (10.3%) during COVID-19 epidemic. During the SARS epidemic, the proportions of people asking for consultation for symptoms, prevention and therapy, and psychological problems were 35.0%, 22.0%, and 23.0%, respectively. Two studies demonstrated that telemedicine can be used to screen the suspected patients and give advice. One study emphasized the limited possibilities to follow up people calling hotlines and difficulties in identifying all suspect cases.\n\nConclusionsTelemedicine services should focus on the issues that the public is most concerned about, such as then symptoms, prevention and treatment of the disease, and provide reasonable advice to patients with symptoms or people with epidemic history.", - "rel_num_authors": 19, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.14.20065557", + "rel_abs": "BackgroundThe COVID-19 epidemic has taken a fearsome toll on individuals residing in long-term care facilities (LTC). As of April 10, 2020 half of Canadas COVID-19 deaths had occurred in LTC. We sought to better understand trends and risk factors for COVID-19 death in LTC in Ontario.\n\nMethodsWe analyzed a COVID-19 outbreak database created by the Ontario Ministry of Health, for the period March 29-April 7, 2020. Mortality incidence rate ratios for LTC were calculated with community living Ontarians aged > 69 used as the comparator group. Count-based regression methods were used to model temporal trends and identify associations between infection risk in staff and residents, and subsequent LTC resident death.\n\nResultsConfirmed or suspected cases of COVID-19 were identified in 272/627 LTC by April 7, 2020. The incidence rate ratio for COVID-19 death was 13.1 (9.9-17.3) relative to community living adults over 69. Incidence rate ratio increased over time and was 87.28 (90% CrI 9.98 to 557.08) by April 7, 2020. Lagged infection in staff was a strong predictor of death in residents (e.g., adjusted IRR for death per infected staff member 1.17, 95% CI 1.11 to 1.26 at a 6-day lag).\n\nInterpretationMortality risk in elders in Ontario is currently concentrated in LTC, and this risk has increased sharply over a short period of time. Early identification of risk requires a focus on testing and provision of personal protective equipment to staff, and restructuring the LTC workforce to prevent movement of COVID-19 between LTC.\n\nFundingThe research was supported by a grant to DNF from the Canadian Institutes for Health Research (2019 COVID-19 rapid researching funding OV4-170360).", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Yelei Gao", - "author_inst": "Children's Hospital of Chongqing Medical University, Chongqing, China" - }, - { - "author_name": "Rui Liu", - "author_inst": "Children's Hospital of Chongqing Medical University, Chongqing 400014, China" - }, - { - "author_name": "Qi Zhou", - "author_inst": "The First School of Clinical Medicine, Lanzhou University, Lanzhou 730000, China" - }, - { - "author_name": "Xingmei Wang", - "author_inst": "Department of Respiratory Medicine, Children's Hospital of Chongqing Medical University" - }, - { - "author_name": "Liping Huang", - "author_inst": "Children's Hospital of Chongqing Medical University, Chongqing 400014, China" - }, - { - "author_name": "Qianling Shi", - "author_inst": "The First School of Clinical Medicine,Lanzhou University,Lanzhou 730000,China" - }, - { - "author_name": "Zijun Wang", - "author_inst": "Lanzhou University" - }, - { - "author_name": "Shuya Lu", - "author_inst": "Department of Pediatric, Sichuan Provincial People's Hospital, University of Electronic Science a" - }, - { - "author_name": "Weiguo Li", - "author_inst": "Children's Hospital of Chongqing Medical University, Chongqing 400014, China" - }, - { - "author_name": "Yanfang Ma", - "author_inst": "Evidence-based Medicine Center,School of Basic Medical Sciences,Lanzhou University,Lanzhou 730000,China" - }, - { - "author_name": "Xufei Luo", - "author_inst": "School of Public Health, Lanzhou University, Lanzhou 730000, China" - }, - { - "author_name": "Toshio Fukuoka", - "author_inst": "Emergency and Critical Care Center, the Department of General Medicine, Department of Research and Medical Education at Kurashiki Central Hospital, Japan" - }, - { - "author_name": "Hyeong Sik Ahn", - "author_inst": "Department of Preventive Medicine, Korea University College of Medicine, Seoul, Korea" - }, - { - "author_name": "Myeong Soo Lee", - "author_inst": "Korea Institute of Oriental Medicine, Daejeon, Korea" - }, - { - "author_name": "Zhengxiu Luo", - "author_inst": "Children's Hospital of Chongqing Medical University, Chongqing 400014, China" + "author_name": "David Fisman", + "author_inst": "University of Toronto" }, { - "author_name": "Enmei Liu", - "author_inst": "Children's Hospital of Chongqing Medical University,Chongqing 400014,China" + "author_name": "Lauren Lapointe-Shaw", + "author_inst": "University of Toronto" }, { - "author_name": "Yaolong Chen", - "author_inst": "School of Public Health, Lanzhou University, Lanzhou 730000, China" + "author_name": "Isaac Bogoch", + "author_inst": "University of Toronto" }, { - "author_name": "Chang Shu", - "author_inst": "Department of Respiratory Medicine, Children's Hospital of Chongqing Medical University, Chongqing 400014, China" + "author_name": "Janine McCready", + "author_inst": "Michael Garron Hospital" }, { - "author_name": "Daiyin Tian", - "author_inst": "Department of Respiratory Medicine, Children's Hospital of Chongqing Medical University, Chongqing 400014, China" + "author_name": "Ashleigh Tuite", + "author_inst": "University of Toronto" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1536266,37 +1535863,65 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.04.12.20060079", - "rel_title": "Serum Mycoplasma Pneumoniae IgG in COVID-19: A Protective Factor", + "rel_doi": "10.1101/2020.04.15.20057786", + "rel_title": "RAPID SEROLOGICAL TESTS HAVE A ROLE IN ASYMPTOMATIC HEALTH WORKERS COVID-19 SCREENING", "rel_date": "2020-04-17", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.12.20060079", - "rel_abs": "BackgroundA correlation between prior exposure to Mycoplasma pneumoniae (IgG positive) and better clinical response to COVID-19 was elusive.\n\nMethodsA retrospective review of all COVID-19 infected patients treated at Wuhan Union Hospital from Feb 1 to Mar 20 was carried out. Continuous variables were described as mean, median, and interquartile range (IQR), while categorical variables were compared by X2 test or Fishers exact test between COVID-19 infected patients with mycoplasma lgG (-) and mycoplasma lgG (+).\n\nResultsStatistically significant differences were shown in terms of laboratory test results. COVID-19 infected patients with mycoplasma lgG positivity had a higher lymphocyte count and percentage (p=0.026, p=0.017), monocyte count and percentage (p=0.028, p=0.006) and eosinophil count and percentage (p=0.039, p=0.007), and a lower neutrophil count and percentage (p=0.044, p=0.006) than COVID-19 infected patients without mycoplasma lgG. Other routine blood tests, including coagulation tests, blood biochemistry and infection-related biomarkers did not significantly differ except for thrombin time (p=0.001) and lactate dehydrogenase (p=0.008). Furthermore, requirement and use of a nasal catheter or oxygen mask was significantly lower in COVID-19 infected patients with mycoplasma lgG positivity (p=0.029).\n\nConclusionsOur findings indicate that mycoplasma IgG positivity is a potential protective factor for SARS-CoV-2 infection.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.15.20057786", + "rel_abs": "Health workers are at high risk for SARS-CoV-2 infection and, if asymptomatic, for transmitting the virus on to fragile cancer patients. We screened 525 health workers of our Cancer Institute with rapid serological test Viva-Diag analyzingCOVID-19 associated-IgG/IgM. Six subjects (1,1%) resulted with Viva-Diag test not-negative for IgM. All 6 cases had RT-PCR SARS-CoV-2 test negative; repeating analysis ofIgG/IgM expression by CLIA assay also, 2 cases resulted IgM positive and 1 case IgG/IgM positive. This latter subject reported a contact with an infected SARS-CoV-2 person, a month earlier.In conclusion our study seems to suggest: a) a different analytical sensitivity inIgG/IgM evaluation for Viva-Diag and CLIA assays needing to be further determined; b) the ability of Viva-Diagrapid COVID-19 test to evidence health workers positive for Immunoglobulins expression. Discordant results of rapid serological tests with respect to RT-PCR stress the different clinical meaning the two assays can have, question clearly referring to further studies to optimize the utilization of rapid serological test in asymptomatic subjects at high risk for infection.", + "rel_num_authors": 12, "rel_authors": [ { - "author_name": "Bobin Mi", - "author_inst": "Wuhan Union Hospital" + "author_name": "Angelo Virgilio Paradiso", + "author_inst": "IRCCS Istituto Tumori Giovanni Paolo II" }, { - "author_name": "Lang Chen", - "author_inst": "Wuhan Union Hospital" + "author_name": "simona De Summa", + "author_inst": "IRCCS-Istituto Tumori Giovanni Paolo II" }, { - "author_name": "Adriana C. Panayi", - "author_inst": "Brigham and Women's Hospital" + "author_name": "Nicola Silvestris", + "author_inst": "IRCCS Istituto Tumori Giovanni Paolo II" }, { - "author_name": "Yuan Xiong", - "author_inst": "Wuhan Union Hospital" + "author_name": "Stefania Tommasi", + "author_inst": "IRCCS Istituto Tumori Giovanni Paolo II" }, { - "author_name": "Guohui Liu", - "author_inst": "Wuhan Union Hospital" + "author_name": "Antonio Tufaro", + "author_inst": "IRCCS Istituto Tumori Giovanni Paolo II" + }, + { + "author_name": "Giuseppe De Palma", + "author_inst": "IRCCS Istituto Tumori Giovanni Paolo II" + }, + { + "author_name": "Angela Maria Vittoria Larocca", + "author_inst": "University of Bari" + }, + { + "author_name": "Maria Chironna", + "author_inst": "University of Bari" + }, + { + "author_name": "Vincenzo D'Addabbo", + "author_inst": "IRCCS Istituto Tumori Giovanni Paolo II" + }, + { + "author_name": "Donata Raffaele", + "author_inst": "IRCCS Istituto Tumori Giovanni Paolo II" + }, + { + "author_name": "Vito Cafagna", + "author_inst": "IRCCS Istituto Tumori Giovanni Paolo II" + }, + { + "author_name": "Vito Garrisi", + "author_inst": "IRCCS Istituto Tumori Giovanni Paolo II" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1537356,77 +1536981,29 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.04.16.20061127", - "rel_title": "Outcomes of the 2019 Novel Coronavirus in patients with or without a history of cancer - a multi-centre North London experience", + "rel_doi": "10.1101/2020.04.12.20062828", + "rel_title": "Estimation of airborne viral emission: quanta emission rate of SARS-CoV-2 for infection risk assessment", "rel_date": "2020-04-17", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.16.20061127", - "rel_abs": "BackgroundFour months after the first known case of the 2019 novel coronavirus disease (COVID-19), on the 11th March 2020, the WHO declared the outbreak a pandemic and acknowledged the potential to overwhelm national healthcare systems. The high prevalence and associated healthcare, social and economic challenges of COVID-19 suggest this pandemic is likely to have a major impact on cancer management, and has been shown to potentially have worse outcomes in this cohort of vulnerable patients (1). This study aims to compare the outcomes of reverse transcriptase polymerase chain reaction (RT-PCR) confirmed COVID-19 positive disease in patients with or without a history of cancer.\n\nMethodWe retrospectively collected clinical, pathological and radiological characteristics and outcomes of COVID-19 RT-PCR positive cancer patients treated consecutively in four different North London hospitals (cohort A). Outcomes recorded included morbidity, mortality and length of hospital stay. All clinically relevant outcomes were then compared to consecutively admitted COVID-19 positive patients, without a history of cancer (cohort B), treated at the primary centre during the same time period (12th March-7th April 2020).\n\nResultsA total of 52 electronic patient records during the study time period were reviewed. Cohort A (median age 76 years, 56% males) and cohort B (median age 58 years, 62% male) comprised of 26 patients each. With the exclusion of cancer, both had a median of 2 comorbidities. Within cohort A, the most frequent underlying cancer was colorectal (5/26) and prostate cancer (5/26), and 77% of patients in Cohort A had received previous anti-cancer therapy. The most common presenting symptoms were cough and pyrexia in both cohorts. Frequent laboratory findings included lymphopenia, anaemia and elevated CRP in both cohorts, whilst hypokalaemia, hypoalbuminaemia and hypoproteinaemia was predominantly seen amongst patients with cancer. Median duration of admission was 7 days in both cohorts. The mortality rate was the same in both cohorts (23%), with median age of mortality of 80 years. Of cancer patients who died, all were advanced stage, had been treated with palliative intent and had received anti-cancer therapy within 13 days of admission.\n\nConclusionOld age, late stage of cancer diagnosis and multiple co-morbidities adversely influence the outcome of patients with COVID-19 positive patients. Whilst extra caution is warranted in the administration of anti-cancer therapies pertaining to the risk of immune-suppression, this data does not demonstrate a higher risk to cancer patients compared to their non-cancer counterparts.", - "rel_num_authors": 15, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.12.20062828", + "rel_abs": "Airborne transmission is a pathway of contagion that is still not sufficiently investigated despite the evidence in the scientific literature of the role it can play in the context of an epidemic. While the medical research area dedicates efforts to find cures and remedies to counteract the effects of a virus, the engineering area is involved in providing risk assessments in indoor environments by simulating the airborne transmission of the virus during an epidemic. To this end, virus air emission data are needed. Unfortunately, this information is usually available only after the outbreak, based on specific reverse engineering cases. In this work, a novel approach to estimate the viral load emitted by a contagious subject on the basis of the viral load in the mouth, the type of respiratory activity (e.g. breathing, speaking), respiratory physiological parameters (e.g. inhalation rate), and activity level (e.g. resting, standing, light exercise) is proposed. The estimates of the proposed approach are in good agreement with values of viral loads of well-known diseases from the literature. The quanta emission rates of an asymptomatic SARS-CoV-2 infected subject, with a viral load in the mouth of 108 copies mL-1, were 10.5 quanta h-1 and 320 quanta h-1 for breathing and speaking respiratory activities, respectively, at rest. In the case of light activity, the values would increase to 33.9 quanta h-1 and 1.03x103 quanta h-1, respectively.\n\nThe findings in terms of quanta emission rates were then adopted in infection risk models to demonstrate its application by evaluating the number of people infected by an asymptomatic SARS-CoV-2 subject in Italian indoor microenvironments before and after the introduction of virus containment measures. The results obtained from the simulations clearly highlight that a key role is played by proper ventilation in containment of the virus in indoor environments.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Nalinie Joharatnam-Hogan", - "author_inst": "University College London Hospital" - }, - { - "author_name": "Daniel Hochhauser", - "author_inst": "University College London Hospital NHS Foundation Trust" - }, - { - "author_name": "Kai-Keen Shiu", - "author_inst": "University College London Hospital NHS Foundation Trust" - }, - { - "author_name": "Hannah Rush", - "author_inst": "University College London" - }, - { - "author_name": "Valerie Crolley", - "author_inst": "North Middlesex University Hospital NHS Trust" - }, - { - "author_name": "Emma Butcher", - "author_inst": "University College London" - }, - { - "author_name": "Anand Sharma", - "author_inst": "Mount Vernon Hospital" - }, - { - "author_name": "Aun Muhammad", - "author_inst": "Whittington Hospital" - }, - { - "author_name": "Nikhil Vasdev", - "author_inst": "Lister Hospital" - }, - { - "author_name": "Muhammad Anwar", - "author_inst": "Princess Alexandra Hospital" - }, - { - "author_name": "Ganna Kantser", - "author_inst": "North Middlesex University Hospital" - }, - { - "author_name": "Aramita Saha", - "author_inst": "North Middlesex University Hospital" - }, - { - "author_name": "Fharat Raja", - "author_inst": "North Middlesex University Hospital" + "author_name": "Giorgio Buonanno", + "author_inst": "Department of Civil and Mechanical Engineering, University of Cassino and Southern Lazio, Cassino, Italy" }, { - "author_name": "John Bridgewater", - "author_inst": "University College London Hospital NHS Foundation Trust" + "author_name": "Luca Stabile", + "author_inst": "Department of Civil and Mechanical Engineering, University of Cassino and Southern Lazio, Cassino, Italy" }, { - "author_name": "Khurum Khan", - "author_inst": "University College London Hospital NHS Trust" + "author_name": "Lidia Morawska", + "author_inst": "International Laboratory for Air Quality and Health, Queensland University of Technology, Brisbane, Australia" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1538546,25 +1538123,21 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.04.13.20064253", - "rel_title": "Population simulations of COVID-19 outbreaks provide tools for risk assessment and continuity planning", + "rel_doi": "10.1101/2020.04.13.20064220", + "rel_title": "Severe underestimation of COVID-19 case numbers: effect of epidemic growth rate and test restrictions", "rel_date": "2020-04-17", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.13.20064253", - "rel_abs": "Essential industrial sectors, healthcare systems, and government agencies must continue operations despite the risk of COVID-19 infection. They need tools to assess risks associated with operations, so they can devise emergency plans. We developed a population-based simulator to study COVID-19 outbreaks in enclosed environments and evaluate the effectiveness of preventative measures and action plans, such as pre-dispatch quarantine and removal of symptomatic cases.\n\nAvailabilityThe simulation tool is publicly available at http://github.com/ictr/covid19-outbreak-simulator and is free for non-commercial use.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.13.20064220", + "rel_abs": "To understand the scope and development of the COVID-19 pandemic, knowledge of the number of infected persons is essential. Often, the number of \"confirmed cases\", which is based on positive RT-PCR test results, is regarded as a reasonable indicator. However, limited COVID-19 test capacities in many countries are restricting the amount of testing that can be done. This can lead to the implementation of testing policies that restrict access to COVID-19 tests, and to testing backlogs and delays. As a result, confirmed case numbers can be significantly lower than the actual number of infections, especially during rapid growth phases of the epidemic.\n\nThis study examines the quantitative relation between infections and reported confirmed case numbers for two different testing strategies, \"limited\" and \"inclusive\" testing, in relation to the growth rate of the epidemic. The results indicate that confirmed case numbers understate the actual number of infections substantially; during rapid growth phases where the daily growth rate can reach or exceed 30%, as has been seen in many countries, the confirmed case numbers under-report actual infections by up to 50 to 100-fold.", + "rel_num_authors": 1, "rel_authors": [ { - "author_name": "Bo Peng", - "author_inst": "Baylor College of Medicine" - }, - { - "author_name": "Christopher I Amos", - "author_inst": "Baylor College of Medicine" + "author_name": "Peter Richterich", + "author_inst": "CodonCode Corporation" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1539767,33 +1539340,45 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.04.10.20061267", - "rel_title": "Public perceptions and experiences of social distancing and social isolation during the COVID-19 pandemic: A UK-based focus group study", + "rel_doi": "10.1101/2020.04.11.20061697", + "rel_title": "Surveillance by age-class and prefecture for emerging infectious febrile diseases with respiratory symptoms, including COVID-19", "rel_date": "2020-04-15", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.10.20061267", - "rel_abs": "OBJECTIVEExplore the perceptions and experiences of the UK public of social distancing and social isolation measures related to the COVID-19 pandemic.\n\nDESIGNQualitative study comprising five focus groups carried out online during the early stages of the UKs social distancing and isolation measures (5-12 days post lockdown).\n\nSETTINGOnline video-conferencing\n\nPARTICIPANTS27 participants, all UK residents aged 18 years and older, representing a range of gender, ethnic, age and occupational backgrounds.\n\nRESULTSThe social distancing and isolation associated with COVID-19 policy has had having substantial negative impacts on the mental health and wellbeing of the UK public within a short time of policy implementation. It has disproportionately negatively affected those in low-paid or precarious employment. Practical social and economic losses - the loss of (in-person) social interaction, loss of income and loss of structure and routine - led to psychological and emotional losses - the loss of motivation, loss of meaning, and loss of self-worth. Participants reported high adherence to distancing and isolation guidelines but reported seeing or hearing of non-adherence in others. A central concern for participants was the uncertainty duration of the measures, and their ability to cope longer-term. Some participants felt they would have lingering concerns over social contact while others were eager to return to high levels of social activity.\n\nCONCLUSIONSA rapid response is necessary in terms of public health programming to mitigate the mental health impacts of COVID-19 social distancing and isolation. Initial high levels of support for, and adherence to, social distancing and isolation is likely to wane over time, particularly where end dates are uncertain. Social distancing and isolation exit strategies must account for the fact that, although some individuals will voluntarily or habitually continue to socially distance, others will seek high levels of social engagement as soon as possible.\n\nO_TEXTBOXWhat is already known on this topic\n\nO_LIAdherence to non-pharmaceutical interventions during pandemics is lower where people have low trust in government and where people perceive themselves at relatively low risk from the disease\nC_LIO_LIThere is a need for evidence on public perceptions and experiences of the psychological and social public experiences of COVID-19 related social distancing and isolation, and its relation to adherence.\nC_LI\n\nWhat this study adds\n\nO_LIPeople lack trust in government and perceive themselves at low personal risk,but closely adhere to social distancing and isolation measures motivated by social conscience, and are critical of non-adherence in others.\nC_LIO_LIPopulation-wide social distancing and isolation can have significant negative social and psychological impacts within a short time of policy implementation.\nC_LIO_LIKey concerns during social distancing and isolation are uncertainty of duration and ability to cope longer-term.\nC_LIO_LIAt the end of pandemic lockdowns, some individuals will likely voluntarily or habitually continue to socially distance, while others will likely seek high levels of social engagement as soon as possible.\nC_LI\n\nC_TEXTBOX", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.11.20061697", + "rel_abs": "ObjectThe COVID-19 outbreak emerged in late 2019 in China, expanding rapidly thereafter. Even in Japan, epidemiological linkage of transmission was probably lost already by February 18, 2020. From that time, it has been necessary to detect clusters using syndromic surveillance.\n\nMethodWe identified common symptoms of COVID-19 as fever and respiratory symptoms. Therefore, we constructed a model to predict the number of patients with antipyretic analgesics (AP) and multi-ingredient cold medications (MIC) controlling well-known pediatric infectious diseases including influenza or RS virus infection. To do so, we used the National Official Sentinel Surveillance for Infectious Diseases (NOSSID), even though NOSSID data are weekly data with 10 day delays, on average. The probability of a cluster with unknown febrile disease with respiratory symptoms is a product of the probabilities of aberrations in AP and MIC, which is defined as one minus the probability of the number of patients prescribed a certain type of drug in PS compared to the number predicted using a model. This analysis was conducted prospectively in 2020 using data from October 1, 2010 through 2019 by prefecture and by age-class.\n\nResultsThe probability of unknown febrile disease with respiratory symptom cluster was estimated as less than 60% in 2020.\n\nDiscussionThe most severe limitation of the present study is that the proposed model cannot be validated. A large outbreak of an unknown febrile disease with respiratory symptoms must be experienced, at which time, practitioners will have to \"wing it\". We expect that no actual cluster of unknown febrile disease with respiratory symptoms will occur, but if it should occur, we hope to detect it.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Simon N Williams", - "author_inst": "Swansea University" + "author_name": "Tomoaki Ueno", + "author_inst": "ORCA Management Organization Co., Ltd." }, { - "author_name": "Christopher J Armitage", - "author_inst": "University of Manchester" + "author_name": "Junko Kurita", + "author_inst": "Department of Nursing, Tokiwa University, Ibaraki,, Japan" }, { - "author_name": "Tova Tampe", - "author_inst": "Independent Consultant, World Health Organization" + "author_name": "Tamie Sugawara", + "author_inst": "National Institute of Infectious Diseases, Tokyo, Japan" }, { - "author_name": "Kimberly Dienes", - "author_inst": "University of Manchester" + "author_name": "Yoshiyuki Sugishita", + "author_inst": "National Institute of Infectious Diseases, Tokyo, Japan" + }, + { + "author_name": "Yasushi Ohkusa", + "author_inst": "National Institute of Infectious Diseases, Tokyo, Japan" + }, + { + "author_name": "Hirokazu Kawanohara", + "author_inst": "EM Systems Co. Ltd., Osaka, Japan" + }, + { + "author_name": "Miwako Kamei", + "author_inst": "School of Pharmacy, Nihon University, Chiba, Japan" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "public and global health" }, @@ -1541053,81 +1540638,125 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2020.04.15.042085", - "rel_title": "TMPRSS2 and furin are both essential for proteolytic activation and spread of SARS-CoV-2 in human airway epithelial cells and provide promising drug targets", + "rel_doi": "10.1101/2020.04.14.039925", + "rel_title": "Multidrug treatment with nelfinavir and cepharanthine against COVID-19", "rel_date": "2020-04-15", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.04.15.042085", - "rel_abs": "In December 2019, a novel coronavirus named SARS-CoV-2 first reported in Wuhan, China, emerged and rapidly spread to numerous other countries globally, causing the current pandemic. SARS-CoV-2 causes acute infection of the respiratory tract (COVID-19) that can result in severe disease and lethality. Currently, there is no approved antiviral drug for treating COVID-19 patients and there is an urgent need for specific antiviral therapies and vaccines.\n\nIn order for SARS-CoV-2 to enter cells, its surface glycoprotein spike (S) must be cleaved at two different sites by host cell proteases, which therefore represent potential drug targets. In the present study we investigated which host cell proteases activate the SARS-CoV-2 S protein in Calu-3 human airway epithelial cells. We show that S can be cleaved by both the proprotein convertase furin at the S1/S2 site and the transmembrane serine protease 2 (TMPRSS2) at the S2 site. We demonstrate that TMPRSS2 is essential for activation of SARS-CoV-2 S in Calu-3 cells through antisense-mediated knockdown of TMPRSS2 expression. Further, we show that SARS-CoV-2 replication can be efficiently inhibited by two synthetic inhibitors of TMPRSS2 and also by the broad range serine protease inhibitor aprotinin. Additionally, SARS-CoV-2 replication was also strongly inhibited by the synthetic furin inhibitor MI-1851. Combining various TMPRSS2 inhibitors with MI-1851 produced more potent antiviral activity against SARS-CoV-2 than an equimolar amount of any single serine protease inhibitor. In contrast, inhibition of endosomal cathepsins by E64d did not affect virus replication.\n\nOur data demonstrate that both TMPRSS2 and furin are essential for SARS-CoV-2 activation in human airway cells and are promising drug targets for the treatment of COVID-19 either by targeting one of these proteases alone or by a combination of furin and TMPRSS2 inhibitors. Therefore, this approach has a high therapeutic potential for treatment of COVID-19.", - "rel_num_authors": 16, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.04.14.039925", + "rel_abs": "Antiviral treatments targeting the emerging coronavirus disease 2019 (COVID-19) are urgently required. We screened a panel of already-approved drugs in a cell culture model of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and identified two new antiviral agents: the HIV protease inhibitor Nelfinavir and the anti-inflammatory drug Cepharanthine. In silico modeling shows Nelfinavir binds the SARS-CoV-2 main protease consistent with its inhibition of viral replication, whilst Cepharanthine inhibits viral attachment and entry into cells. Consistent with their different modes of action, in vitro assays highlight a synergistic effect of this combined treatment to limit SARS-CoV-2 proliferation. Mathematical modeling in vitro antiviral activity coupled with the known pharmacokinetics for these drugs predicts that Nelfinavir will facilitate viral clearance. Combining Nelfinavir/Cepharanthine enhanced their predicted efficacy to control viral proliferation, to ameliorate both the progression of disease and risk of transmission. In summary, this study identifies a new multidrug combination treatment for COVID-19.", + "rel_num_authors": 27, "rel_authors": [ { - "author_name": "Dorothea Bestle", - "author_inst": "Institute of Virology, Philipps-University, Marburg, Germany" + "author_name": "Hirofumi Ohashi", + "author_inst": "National Institute for Infectious Diseases" }, { - "author_name": "Miriam Ruth Heindl", - "author_inst": "Institute of Virology, Philipps-University, Marburg, Germany" + "author_name": "Koichi Watashi", + "author_inst": "National Institute of Infectious Diseases" }, { - "author_name": "Hannah Limburg", - "author_inst": "Institute of Virology, Philipps-University, Marburg, Germany" + "author_name": "Wakana Saso", + "author_inst": "National Institute of Infectious Diseases" }, { - "author_name": "Thuy Van Lam van", - "author_inst": "Institute of Pharmaceutical Chemistry, Philipps-University, Marburg, Germany" + "author_name": "Kaho Shionoya", + "author_inst": "National Institute of Infectious Diseases" }, { - "author_name": "Oliver Pilgram", - "author_inst": "Institute of Pharmaceutical Chemistry, Philipps-University, Marburg, Germany" + "author_name": "Shoya Iwanami", + "author_inst": "Kyushu University" }, { - "author_name": "Hong Moulton", - "author_inst": "Department of Biomedical Sciences, Carlson College of Veterinary Medicine, Oregon State University, Corvallis, USA" + "author_name": "Takatsugu Hirokawa", + "author_inst": "National Institute of Advanced Industrial Science and Technology" }, { - "author_name": "David A. Stein", - "author_inst": "Department of Biomedical Sciences, Carlson College of Veterinary Medicine, Oregon State University, Corvallis, USA" + "author_name": "Tsuyoshi Shirai", + "author_inst": "Nagahama Institute of Bioscience and Technology" }, { - "author_name": "Kornelia Hardes", - "author_inst": "Fraunhofer Institute for Molecular Biology and Applied Ecology, Giessen, Germany" + "author_name": "Shigehiko Kanaya", + "author_inst": "Nara Institute of Science and Technology" }, { - "author_name": "Markus Eickmann", - "author_inst": "Institute of Virology, Philipps-University, Marburg, Germany" + "author_name": "Yusuke Ito", + "author_inst": "Kyushu University" }, { - "author_name": "Olga Dolnik", - "author_inst": "Institute of Virology, Philipps-University, Marburg, Germany" + "author_name": "Kwang Su Kim", + "author_inst": "Kyushu University" }, { - "author_name": "Cornelius Rohde", - "author_inst": "Institute of Virology, Philipps-University, Marburg, Germany" + "author_name": "Kazane Nishioka", + "author_inst": "National Institute of Infectious Diseases" }, { - "author_name": "Stephan Becker", - "author_inst": "Institute of Virology, Philipps-University, Marburg, Germany" + "author_name": "Shuji Ando", + "author_inst": "National Institute of Infectious Diseases" }, { - "author_name": "Hans-Dieter Klenk", - "author_inst": "Institute of Virology, Philipps-University, Marburg, Germany" + "author_name": "Keisuke Ejima", + "author_inst": "Indiana University" }, { - "author_name": "Wolfgang Garten", - "author_inst": "Institute of Virology, Philipps-University, Marburg, Germany" + "author_name": "Yoshiki Koizumi", + "author_inst": "National Center for Global Health and Medicine" }, { - "author_name": "Torsten Steinmetzer", - "author_inst": "Institute of Pharmaceutical Chemistry, Philipps-University, Marburg, Germany" + "author_name": "Tomohiro Tanaka", + "author_inst": "Tokyo University of Science" }, { - "author_name": "Eva Bottcher-Friebertshauser", - "author_inst": "Institute of Virology, Philipps-University, Marburg, Germany" + "author_name": "Shin Aoki", + "author_inst": "Tokyo University of Science" + }, + { + "author_name": "Kouji Kuramochi", + "author_inst": "Tokyo University of Science" + }, + { + "author_name": "Tadaki Suzuki", + "author_inst": "National Institute of Infectious Diseases" + }, + { + "author_name": "Katsumi Maenaka", + "author_inst": "Hokkaido University" + }, + { + "author_name": "Tetsuro Matano", + "author_inst": "National Institute of Infectious Diseases" + }, + { + "author_name": "Masamichi Muramatsu", + "author_inst": "National Institute of Infectious Diseases" + }, + { + "author_name": "Masayuki Saijo", + "author_inst": "National Institute of Infectious Diseases" + }, + { + "author_name": "Kazuyuki Aihara", + "author_inst": "University of Tokyo" + }, + { + "author_name": "Shingo Iwami", + "author_inst": "Kyushu University" + }, + { + "author_name": "Makoto Takeda", + "author_inst": "National Institute of Infectious Diseases" + }, + { + "author_name": "Jane McKeating", + "author_inst": "University of Oxford" + }, + { + "author_name": "Takaji Wakita", + "author_inst": "National Institute of Infectious Diseases" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "new results", "category": "microbiology" }, @@ -1542359,23 +1541988,23 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.04.10.20061036", - "rel_title": "A novel high specificity COVID-19 screening method based on simple blood exams and artificial intelligence", + "rel_doi": "10.1101/2020.04.10.20061069", + "rel_title": "Optimal Control applied to a SEIR model of 2019-nCoV with social distancing", "rel_date": "2020-04-14", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.10.20061036", - "rel_abs": "BackgroundThe SARS-CoV-2 virus responsible for COVID-19 poses a significant challenge to healthcare systems worldwide. Despite governmental initiatives aimed at containing the spread of the disease, several countries are experiencing unmanageable increases in the demand for ICU beds, medical equipment, and larger testing capacity. Efficient COVID-19 diagnosis enables healthcare systems to provide better care for patients while protecting caregivers from the disease. However, many countries are constrained by the limited amount of test kits available, lack of equipment and trained professionals. In the case of patients visiting emergency rooms (ERs) with a suspect of COVID-19, prompt diagnosis may improve the outcome and even provide information for efficient hospital management. In such a context, a quick, inexpensive and readily available test to perform an initial triage in ERs could help to smooth patient flow, provide better patient care, and reduce the backlog of exams.\n\nMethodsIn this Case-control quantitative study, we developed a strategy backed by artificial intelligence to perform an initial screening of suspect COVID-19 patients. We developed a machine learning classifier that takes widely available simple blood exams as input and classifies samples as likely to be positive (having SARS-CoV-2) or negative (not having SARS-CoV-2). Based on this initial classification, positive cases can be referred for further highly sensitive testing (e.g. CT scan, or specific antibodies). We used publicly available data from the Albert Einstein Hospital in Brazil from 5,644 patients. Focusing on simple blood exam figures as main predictors, a sample of 599 subjects that had the fewest missing values for 16 common exams were selected. From these 599 patients, 81 tested positive for SARS-CoV-2 (determined by RT-PCR). Based on the reduced dataset, we built an artificial intelligence classification framework, ER-CoV, aiming at determining if suspect patients arriving in ER were likely to be negative for SARS-CoV-2, that is, to predict if that suspect patient is negative for COVID-19. The primary goal of this investigation is to develop a classifier with high specificity and high negative predictive values, with reasonable sensitivity.\n\nFindingsWe identified that our AI framework achieved an average specificity of 85.98% [95%CI: 84.94 - 86.84] and negative predictive value (NPV) of 94.92% [95%CI: 94.37% - 95.37%]. Those values are completely aligned with our goal of providing an effective low-cost system to triage suspect patients in ERs. As for sensitivity, our model achieved an average of 70.25% [95%CI: 66.57% - 73.12%] and positive predictive value (PPV) of 44.96% [95%CI: 43.15% - 46.87%]. The area under the curve (AUC) of the receiver operating characteristic (ROC) was 86.78% [95%CI: 85.65% - 87.90%]. An error analysis (inspection of which patients were misclassified) identified that, on average, 28% of the false negative results would have been hospitalized anyway; thus the model is making mistakes for severe cases that would not be overlooked, partially mitigating the fact that the test is not highly sensitive. All code for our AI model, called ER-CoV is publicly available at https://github.com/soares-f/ER-CoV.\n\nInterpretationBased on the capacity of our model to accurately predict which cases are negative from suspect patients arriving in emergency rooms, we envision that this framework may play an important role in patient triage. Probably the most important outcome is related to testing availability, which at this point is extremely low in many countries. Considering the achieved specificity, we could reduce by at least 90% the number of SARS-CoV-2 tests performed in emergency rooms, with around 5% chance of getting a false negative. The second important outcome is related to patient management in hospitals. Patients predicted as positive by our framework could be immediately separated from other patients while waiting for the results of confirmatory tests. This could reduce the spread rate within hospitals since in many of them all suspect cases are kept in the same ward. In Brazil, where the data was collected, rate infection is starting to quickly spread and the lead time of a SARS-CoV-2 may be up to 2 weeks.", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.10.20061069", + "rel_abs": "Does the implementation of social distancing measures have merit in controlling the spread of the novel coronavirus? In this study, we develop a mathematical model to explore the effects of social distancing on new disease infections. Mathematical analyses of our model indicate that successful eradication of the disease is strongly dependent on the chosen preventive measure. Numerical computations of the model solution demonstrate that the ability to flatten the curve becomes easier as social distancing is strictly enforced. Based on our model, we also formulate an optimal control problem and solve it using Pontryagins Maximum Principle and an efficient numerical iterative method. Our numerical results of an optimal 2019-nCoV treatment protocol that yields a minimum disease burden from this disease indicates that social distancing is vitally important.", "rel_num_authors": 1, "rel_authors": [ { - "author_name": "Felipe Soares", - "author_inst": "University of Sheffield" + "author_name": "Abhishek Mallela", + "author_inst": "University of California Davis" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "health informatics" + "category": "epidemiology" }, { "rel_doi": "10.1101/2020.04.10.20060954", @@ -1543789,55 +1543418,35 @@ "category": "molecular biology" }, { - "rel_doi": "10.1101/2020.04.09.20059154", - "rel_title": "COVID-19 pandemic in the African continent: forecasts of cumulative cases, new infections, and mortality", + "rel_doi": "10.1101/2020.04.12.038216", + "rel_title": "Detection of spreader nodes and ranking of interacting edges in Human-SARS-CoV protein interaction network", "rel_date": "2020-04-14", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.09.20059154", - "rel_abs": "BackgroundThe epidemiology of COVID-19 remains speculative in Africa. To the best of our knowledge, no study, using robust methodology provides its trajectory for the region or accounts for local context. This paper is the first systematic attempt to provide prevalence, incidence, and mortality estimates across Africa.\n\nMethodsCaseloads and incidence forecasts are from a co-variate-based instrumental variable regression model. Fatality rates from Italy and China were applied to generate mortality estimates after making relevant health system and population-level characteristics related adjustments between each of the African countries.\n\nResultsBy June 30 2020, around 16.3 million people in Africa will contract COVID-19 (95% CI 718,403 to 98,358,799). Northern and Eastern Africa will be the most and least affected areas. Cumulative cases by June 30 are expected to reach around 2.9 million (95% CI 465,028 to 18,286,358) in Southern Africa, 2.8 million (95% CI 517,489 to 15,056,314) in Western Africa, and 1.2 million (95% CI 229,111 to 6,138,692) in Central Africa. Incidence for the month of April 2020 is expected to be highest in Djibouti, 32.8 per 1000 (95% CI 6.25 to 171.77), while Morocco will experience among the highest fatalities (1,045 deaths, 95% CI 167 to 6,547).\n\nConclusionLess urbanized countries with low levels of socio-economic development (hence least connected to the world), are likely to register lower and slower transmissions at the early stages of an epidemic. However, the same enabling factors that worked for their benefit can hinder interventions that have lessened the impact of COVID-19 elsewhere.", - "rel_num_authors": 9, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2020.04.12.038216", + "rel_abs": "The entire world has recently witnessed the commencement of coronavirus disease 19 (COVID-19) pandemic. It is caused by a novel coronavirus (n-CoV) generally distinguished as Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). It has exploited human vulnerabilities to coronavirus outbreak. SARS-CoV-2 promotes fatal chronic respiratory disease followed by multiple organ failure which ultimately puts an end to human life. No proven vaccine for n-CoV is available till date in spite of significant research efforts worldwide. International Committee on Taxonomy of Viruses (ICTV) has reached to a consensus that the virus SARS-CoV-2 is highly genetically similar to Severe Acute Respiratory Syndrome Coronavirus (SARS-CoV) outbreak of 2003. It has been reported that SARS-CoV has [~]89% genetic similarities with n-CoV. With this hypothesis, the current work focuses on the identification of spreader nodes in SARS-CoV protein interaction network. Various network characteristics like edge ratio, neighborhood density and node weight have been explored for defining a new feature spreadability index by virtue of which spreader nodes and edges are identified. The selected top spreader nodes having high spreadability index have been also validated by Susceptible-Infected-Susceptible (SIS) disease model. Initially, the proposed method is applied on a synthetic protein interaction network followed by SARS-CoV-human protein interaction network. Hence, key spreader nodes and edges (ranked edges) are unmasked in SARS-CoV proteins and its connected level 1 and level 2 human proteins. The new network attribute spreadability index along with generated SIS values of selected top spreader nodes when compared with the other network centrality based methodologies like Degree centrality (DC), Closeness centrality (CC), Local average centrality (LAC) and Betweeness centrality (BC) is found to perform relatively better than the existing-state-of-art.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Tom Achoki", - "author_inst": "School of Health Systems and Public Health, University of Pretoria, South Africa" - }, - { - "author_name": "Uzma Alam", - "author_inst": "Africa Institute for Health Policy Foundation, Kenya" + "author_name": "Sovan Saha", + "author_inst": "Dr. Sudhir Chandra Sur Degree Engineering College" }, { - "author_name": "Lawrence Were", - "author_inst": "Department of Health Sciences & Department of Global Health, Boston University, Boston, MA." + "author_name": "Piyali Chatterjee", + "author_inst": "Netaji Subhash Engineering College" }, { - "author_name": "Tesfaye Gebremedhin", - "author_inst": "Department of Economics, Faculty of Business, Government and Law, University of Canberra." - }, - { - "author_name": "Flavia Senkubuge", - "author_inst": "School of Health Systems and Public Health, University of Pretoria, South Africa" - }, - { - "author_name": "Abaleng Lesego", - "author_inst": "Kudu Communications - Health Services" - }, - { - "author_name": "Shuangzhe Liu", - "author_inst": "Faculty of Science and Technology, University of Canberra" - }, - { - "author_name": "Richard Wamai", - "author_inst": "Department of Cultures, Societies and Global Studies, and Integrated Initiative for Global Health, Northeastern University" + "author_name": "Subhadip Basu", + "author_inst": "Jadavpur University" }, { - "author_name": "Yohannes Kinfu", - "author_inst": "Faculty of Health, University of Canberra, Australia" + "author_name": "Mita Nasipuri", + "author_inst": "Jadavpur University" } ], "version": "1", - "license": "cc_by_nc_nd", - "type": "PUBLISHAHEADOFPRINT", - "category": "health policy" + "license": "cc_no", + "type": "new results", + "category": "bioinformatics" }, { "rel_doi": "10.1101/2020.04.09.20058651", @@ -1545267,53 +1544876,69 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.04.09.20058859", - "rel_title": "Epidemic prevention and control measures in China significantly curbed the epidemic of COVID-19 and influenza", + "rel_doi": "10.1101/2020.04.09.20059626", + "rel_title": "Neutrophil extracellular traps (NETs) as markers of disease severity in COVID-19", "rel_date": "2020-04-14", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.09.20058859", - "rel_abs": "At the end of 2019, an outbreak of unknown pathogen pneumonia occurred in China, then it was named corona virus disease 2019 (COVID-19). With the rapid spread of COVID-19, a series of strict prevention and control measures were implemented to cut the spread of the epidemic. Influenza as a respiratory tract infection disease as COVID-19 might also be controlled. To assess the effects, we used the total passenger numbers sent in mainland China from 2018 to 2020 and the daily number of railway passenger (DNRP) flow in 2020 during Spring Festival travel rush to reflect the population movement and further to analyze newly and cumulative confirmed COVID-19 and influenza. We found that with implementing the series measures on COVID-19, not only COVID-19, but also influenza mitigated in China. The prevention and control measures for COVID-19 might be used in controlling respiratory tract diseases, and reducing the national health economic burden. When other countries issue measures on COVID-19 and influenza, they should consider adopting more aggressive epidemic prevention and control strategies.", - "rel_num_authors": 9, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.09.20059626", + "rel_abs": "In severe cases of coronavirus disease 2019 (COVID-19), viral pneumonia progresses to respiratory failure. Neutrophil extracellular traps (NETs) are extracellular webs of chromatin, microbicidal proteins, and oxidant enzymes that are released by neutrophils to contain infections. However, when not properly regulated, NETs have potential to propagate inflammation and microvascular thrombosis--including in the lungs of patients with acute respiratory distress syndrome. While elevated levels of blood neutrophils predict worse outcomes in COVID-19, the role of NETs has not been investigated. We now report that sera from patients with COVID-19 (n=50 patients, n=84 samples) have elevated levels of cell-free DNA, myeloperoxidase(MPO)-DNA, and citrullinated histone H3 (Cit-H3); the latter two are highly specific markers of NETs. Highlighting the potential clinical relevance of these findings, cell-free DNA strongly correlated with acute phase reactants including C-reactive protein, D-dimer, and lactate dehydrogenase, as well as absolute neutrophil count. MPO-DNA associated with both cell-free DNA and absolute neutrophil count, while Cit-H3 correlated with platelet levels. Importantly, both cell-free DNA and MPO-DNA were higher in hospitalized patients receiving mechanical ventilation as compared with hospitalized patients breathing room air. Finally, sera from individuals with COVID-19 triggered NET release from control neutrophils in vitro. In summary, these data reveal high levels of NETs in many patients with COVID-19, where they may contribute to cytokine release and respiratory failure. Future studies should investigate the predictive power of circulating NETs in longitudinal cohorts, and determine the extent to which NETs may be novel therapeutic targets in severe COVID-19.", + "rel_num_authors": 13, "rel_authors": [ { - "author_name": "Xiang Sha Kong", - "author_inst": "Peking University People's Hospital" + "author_name": "Yu Zuo", + "author_inst": "University of Michigan" }, { - "author_name": "Feng Liu", - "author_inst": "Peking University People's Hospital" + "author_name": "Srilakshmi Yalavarthi", + "author_inst": "University of Michigan" }, { - "author_name": "Hai Bo Wang", - "author_inst": "Peking University Clinical Research Institute" + "author_name": "Hui Shi", + "author_inst": "University of Michigan" }, { - "author_name": "Rui Feng Yang", - "author_inst": "Peking University People's Hospital" + "author_name": "Kelsey Gockman", + "author_inst": "University of Michigan" }, { - "author_name": "Dong Bo Chen", - "author_inst": "Peking University People's Hospital" + "author_name": "Melanie Zuo", + "author_inst": "University of Michigan" }, { - "author_name": "Xiao Xiao Wang", - "author_inst": "Peking University People's Hospital" + "author_name": "Jacqueline A. Madison", + "author_inst": "University of Michigan" }, { - "author_name": "Feng Min Lu", - "author_inst": "Peking University People's Hospital, School of Basic Medical Sciences" + "author_name": "Christopher Blair", + "author_inst": "University of Michigan" }, { - "author_name": "Hui Ying Rao", - "author_inst": "Peking University People's Hospital" + "author_name": "Andrew Weber", + "author_inst": "Northwell Health" }, { - "author_name": "Hong Song Chen", - "author_inst": "Peking University People's Hospital" + "author_name": "Betsy J. Barnes", + "author_inst": "Feinstein Institutes for Medical Research" + }, + { + "author_name": "Mikala Egeblad", + "author_inst": "Cold Spring Harbor Laboratory" + }, + { + "author_name": "Robert J. Woods", + "author_inst": "University of Michigan" + }, + { + "author_name": "Yogendra Kanthi", + "author_inst": "University of Michigan" + }, + { + "author_name": "Jason S. Knight", + "author_inst": "University of Michigan" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1546637,49 +1546262,33 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.04.07.20056184", - "rel_title": "Modelling the impact of COVID-19 in Australia to inform transmission reducing measures and health system preparedness", + "rel_doi": "10.1101/2020.04.06.20055863", + "rel_title": "Outbreak dynamics of COVID-19 in China and the United States", "rel_date": "2020-04-11", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.07.20056184", - "rel_abs": "BackgroundThe ability of global health systems to cope with increasing numbers of COVID-19 cases is of major concern. In readiness for this challenge, Australia has drawn on clinical pathway models developed over many years in preparation for influenza pandemics. These models have been used to estimate health care requirements for COVID-19 patients, in the context of broader public health measures.\n\nMethodsAn age and risk stratified transmission model of COVID-19 infection was used to simulate an unmitigated epidemic with parameter ranges reflecting uncertainty in current estimates of transmissibility and severity. Overlaid public health measures included case isolation and quarantine of contacts, and broadly applied social distancing. Clinical presentations and patient flows through the Australian health care system were simulated, including expansion of available intensive care capacity and alternative clinical assessment pathways.\n\nFindingsAn unmitigated COVID-19 epidemic would dramatically exceed the capacity of the Australian health system, over a prolonged period. Case isolation and contact quarantine alone will be insufficient to constrain case presentations within a feasible level of expansion of health sector capacity. Overlaid social restrictions will need to be applied at some level over the course of the epidemic to ensure that systems do not become overwhelmed, and that essential health sector functions, including care of COVID-19 patients, can be maintained. Attention to the full pathway of clinical care is needed to ensure access to critical care.\n\nInterpretationReducing COVID-19 morbidity and mortality will rely on a combination of measures to strengthen and extend public health and clinical capacity, along with reduction of overall infection transmission in the community. Ongoing attention to maintaining and strengthening the capacity of health care systems and workers to manage cases is needed.\n\nFundingAustralian Government Department of Health Office of Health Protection, Australian Government National Health and Medical Research Council", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.06.20055863", + "rel_abs": "On March 11, 2020, the World Health Organization declared the coronavirus disease 2019, COVID19, a global pandemic. In an unprecedented collective effort, massive amounts of data are now being collected worldwide to estimate the immediate and long-term impact of this pandemic on the health system and the global economy. However, the precise timeline of the disease, its transmissibility, and the effect of mitigation strategies remain incompletely understood. Here we integrate a global network model with a local epidemic SEIR model to quantify the outbreak dynamics of COVID-19 in China and the United States. For the outbreak in China, in n = 30 provinces, we found a latent period of 2.56{+/-}0.72 days, a contact period of 1.47{+/-}0.32 days, and an infectious period of 17.82{+/-}2.95 days. We postulate that the latent and infectious periods are disease-specific, whereas the contact period is behavior-specific and can vary between different provinces, states, or countries. For the early stages of the outbreak in the United States, in n = 50 states, we adopted the disease-specific values from China, and found a contact period of 3.38{+/-}0.69 days. Our network model predicts that-without the massive political mitigation strategies that are in place today-the United states would have faced a basic reproduction number of 5.3{+/-}0.95 and a nationwide peak of the outbreak on May 10, 2020 with 3 million infections. Our results demonstrate how mathematical modeling can help estimate outbreak dynamics and provide decision guidelines for successful outbreak control. We anticipate that our model will become a valuable tool to estimate the potential of vaccination and quantify the effect of relaxing political measures including total lock down, shelter in place, and travel restrictions for low-risk subgroups of the population or for the population as a whole.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Robert Moss", - "author_inst": "Modelling and Simulation Unit, Melbourne School of Population and Global Health, The University of Melbourne" - }, - { - "author_name": "James Wood", - "author_inst": "School of Public Health and Community Medicine, UNSW Sydney" - }, - { - "author_name": "Damien Brown", - "author_inst": "Victorian Infectious Diseases Laboratory Epidemiology Unit at The Peter Doherty Institute for Infection and Immunity; The University of Melbourne and Royal Melb" - }, - { - "author_name": "Freya Shearer", - "author_inst": "Modelling and Simulation Unit, Melbourne School of Population and Global Health, The University of Melbourne" - }, - { - "author_name": "Andrew J Black", - "author_inst": "School of Mathematical Sciences, University of Adelaide" + "author_name": "Mathias Peirlinck", + "author_inst": "Stanford University" }, { - "author_name": "Allen Cheng", - "author_inst": "Infection Prevention and Healthcare Epidemiology Unit, Alfred Health; School of Public Health and Preventive Medicine, Monash University" + "author_name": "Francisco Sahli Costabal", + "author_inst": "Pontificia Universidad Catolica de Chile" }, { - "author_name": "James M McCaw", - "author_inst": "School of Mathematics and Statistics, The University of Melbourne" + "author_name": "Kevin Linka", + "author_inst": "Hamburg University of Technology" }, { - "author_name": "Jodie McVernon", - "author_inst": "The Peter Doherty Institute for Infection and Immunity" + "author_name": "Ellen Kuhl", + "author_inst": "Stanford University" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1547935,37 +1547544,29 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.04.09.20059006", - "rel_title": "Effectiveness of quarantine measure on transmission dynamics of COVID-19 in Hong Kong", + "rel_doi": "10.1101/2020.04.06.20055327", + "rel_title": "Analysing and comparing the COVID-19 data: The closed cases of Hubei and South Korea, the dark March in Europe, the beginning of the outbreak in South America", "rel_date": "2020-04-11", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.09.20059006", - "rel_abs": "The rapid expansion of COVID-19 has caused a global pandemic. Although quarantine measures have been used widely, the critical steps among them to suppress the outbreak without a huge social-economic loss remain unknown. Hong Kong, unlike other regions in the world, had a massive number of travellers from Mainland China during the early expansion period, and yet the spread of virus has been relatively limited. Understanding the effect of control measures to reduce the transmission in Hong Kong can improve the control of the virus spreading.\n\nWe have developed a susceptible-exposed-infectious-quarantined-recovered (SEIQR) meta-population model that can stratify the infections into imported and subsequent local infections, and therefore to obtain the control effects on transmissibility in a region with many imported cases. We fitted the model to both imported and local confirmed cases with symptom onset from 18 January to 29 February 2020 in Hong Kong with daily transportation data and the transmission dynamics from Wuhan and Mainland China.\n\nThe model estimated that the reproductive number was dropped from 2.32 to 0.76 (95% CI, 0.66 to 0.86) after an infected case was estimated to be quarantined half day before the symptom onset, corresponding to the incubation time of 5.43 days (95% CI, 1.30-9.47). If the quarantine happened about one day after the onset, community spread would be likely to occur, indicated by the reproductive number larger than one. The results suggest that the early quarantine for a suspected case before the symptom onset is a key factor to suppress COVID-19.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.06.20055327", + "rel_abs": "The present work is a statistical analysis of the COVID-19 pandemic. As the number of cases worldwide overtakes one million, data reveals closed outbreaks in Hubei and South Korea, with a new slight increase in the number of infected people in the latter. Both of these countries have reached a plateau in the number of Total Confirmed Cases per Million (TCCpM) residents, suggesting a trend to be followed by other affected regions. Using Hubeis data as a basis of analysis, we have studied the spreading rate of COVID-19 and modelled the epidemic center for 10 European countries. We have also given the final TCCpM curves for Italy and Lombardia. The introduction of the -factor allows us to analyse the different stages of the outbreak, compare the European countries amongst each other, and, finally, to confront the initial phase of the disease between Europe and South America.\n\nMethodsBy dividing the TCCpM curves in multiple sections spanning short time frames we were able to fit each section to a linear model. By pairing then the angular coefficient ( factor) of each section to the total number of confirmed infections at the center of the corresponding time interval, we have analysed how the spreading rate of Covid-19 changes as more people are infected. Also, by modelling the TCCpM curves with an asymmetrical time integral of a Normal Distribution, we were able to study, by fitting progressively larger data ensembles, how the fitting parameters change as more data becomes available.\n\nFindingsThe data analysis shows that the spreading rate of COVID-19 increases similarly for all countries in its early stage, but changes as the number of TCCpM in each country grows. Regarding the modelling of the TCCpM curves, we have found that the fitting parameters oscillate with time before reaching constant values. The estimation of such values allows the determination of better parameters for the model, which in turn leads to more trustworthy forecasts on the pandemic development.\n\nInterpretationThe analysis of the oscillating fitting parameters allows an early prediction of the TCC, epidemic center and standard deviation of the outbreak. The factor and the recovered over confirmed cases ratio can be used to understand the pandemic development in each country and to compare the protective measures taken by local authorities and their impact on the spreading of the disease.\n\nFundingCNPq (grant number 2018/303911) and Fapesp (grant numebr 2019/06382-9).", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Hsiang-Yu Yuan", - "author_inst": "City University of Hong Kong" - }, - { - "author_name": "Axiu Mao", - "author_inst": "City University of Hong Kong" - }, - { - "author_name": "Guiyuan Han", - "author_inst": "City University of Hong Kong" + "author_name": "Stefano De Leo", + "author_inst": "State University of Campinas" }, { - "author_name": "Hsiangkuo Yuan", - "author_inst": "Thomas Jefferson University Hospital" + "author_name": "Gabriel Gulak Maia", + "author_inst": "Institute for Industrial and Scientific Research, Osaka University, Ibaraki, Japan" }, { - "author_name": "Dirk Pfeiffer", - "author_inst": "City University of Hong Kong" + "author_name": "Leonardo Solidoro", + "author_inst": "Salento University, Lecce, Italy" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1549121,18 +1548722,39 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2020.04.09.20057257", - "rel_title": "Assessing the risk of spread of COVID-19 to the Asia Pacificregion", + "rel_doi": "10.1101/2020.04.11.036855", + "rel_title": "Evaluation of heating and chemical protocols for inactivating SARS-CoV-2", "rel_date": "2020-04-11", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.09.20057257", - "rel_abs": "During the early stages of an emerging disease outbreak, governments are required to make critical decisions on how to respond appropriately, despite limited data being available to inform these decisions. Analytical risk assessment is a valuable approach to guide decision-making on travel restrictions and border measures during the early phase of an outbreak, when transmission is primarily contained within a source country. Here we introduce a modular framework for estimating the importation risk of an emerging disease when the direct travel route is restricted and the risk stems from indirect importation via intermediary countries. This was the situation for Australia in February 2020. The framework was specifically developed to assess the importation risk of COVID-19 into Australia during the early stages of the outbreak from late January to mid-February 2020. The dominant importation risk to Australia at the time of analysis was directly from China, as the only country reporting uncontained transmission. However, with travel restrictions from mainland China to Australia imposed from February 1, our framework was designed to consider the importation risk from China into Australia via potential intermediary countries in the Asia Pacific region. The framework was successfully used to contribute to the evidence base for decisions on border measures and case definitions in the Australian context during the early phase of COVID-19 emergence and is adaptable to other contexts for future outbreak response.", - "rel_num_authors": 0, - "rel_authors": null, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2020.04.11.036855", + "rel_abs": "Clinical samples collected in COVID-19 patients are commonly manipulated in BSL-2 laboratories for diagnostic purpose. We used the French norm NF-EN-14476+A2 derived from the European standard EN-14885. To avoid the risk of exposure of laboratory workers, we showed that Triton-X100 must be added to guanidinium thiocyanate-lysis buffers to obtain a 6-log reduction of infectious virus. Although heating protocol consisting of 92{degrees}C-15min was more effective rather than 56{degrees}C-30min and 60{degrees}C-60min to achieve 6-log reduction, it is not amenable for molecular detection on respiratory specimens because of important decrease of detectable RNA copies in the treated sample vs untreated sample. The 56{degrees}C-30min and 60{degrees}C-60min should be used for inactivation of serum / plasma samples for serology because of the 5log10 reduction of infectivity and low viral loads in blood specimens.", + "rel_num_authors": 5, + "rel_authors": [ + { + "author_name": "Boris Pastorino", + "author_inst": "Unite des Virus Emergents (UVE: Aix Marseille Univ, IRD 190, INSERM U1207, IHU Mediterranee Infection), Marseille, France" + }, + { + "author_name": "Franck Touret", + "author_inst": "Unite des Virus Emergents (UVE: Aix Marseille Univ, IRD 190, INSERM U1207, IHU Mediterranee Infection), Marseille, France" + }, + { + "author_name": "Magali Gilles", + "author_inst": "Unite des Virus Emergents (UVE: Aix Marseille Univ, IRD 190, INSERM U1207, IHU Mediterranee Infection), Marseille, France" + }, + { + "author_name": "Xavier de Lamballerie", + "author_inst": "Unite des Virus Emergents (UVE: Aix Marseille Univ, IRD 190, INSERM U1207, IHU Mediterranee Infection), Marseille, France" + }, + { + "author_name": "Remi N Charrel", + "author_inst": "Unite des Virus Emergents (UVE: Aix Marseille Univ, IRD 190, INSERM U1207, IHU Mediterranee Infection), Marseille, France" + } + ], "version": "1", - "license": "cc_by_nc_nd", - "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "license": "cc_by", + "type": "new results", + "category": "microbiology" }, { "rel_doi": "10.1101/2020.04.10.20058222", @@ -1550274,49 +1549896,17 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2020.04.09.20049288", - "rel_title": "Know Your Epidemic, Know Your Response: Covid-19 in the United States", + "rel_doi": "10.1101/2020.04.07.20056804", + "rel_title": "Non-specific Primers Reveal False-negative Risk in Detection of COVID-19 Infections", "rel_date": "2020-04-11", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.09.20049288", - "rel_abs": "We document that during the week of March 10-16, the Covid-19 pandemic fundamentally affected the perceptions of U.S. residents about the health risks and socioeconomic consequences entailed by the pandemic. During this week, it seems, \"everything changed.\" Not only did the pandemic progress rapidly across the United States, but U.S. residents started to realize that the threat was real: increasing Covid-19 caseloads heightened perceptions of infection risks and excess mortality risks, concerns about the economic implications increased substantially, and behavioral responses became widespread as the pandemic expanded rapidly in the U.S. In early to mid-March 2020, average perceptions about the coronavirus infection risks are broadly consistent with projections about the pandemic, while expectations about dying conditional on infection and expectations about Covid-19-related excess mortality during the next months are possibly too pessimistic. However, some aspects of Covid-19 perceptions are disconcerting from the perspective of implementing and sustaining an effective societal response to the pandemic. For instance, the education gradient in expected infection risks entails the possibility of having different perceptions of the reality of the pandemic between people with and without a college education, potentially resulting in two different levels of behavioral and policy-responses across individuals and regions. Unless addressed by effective health communication that reaches individuals across all social strata, some of the misperceptions about Covid-19 epidemic raise concerns about the ability of the United States to implement and sustain the widespread and harsh policies that are required to curtail the pandemic. Our analyses also reveal perceptions of becoming infected with the virus, and dying from Covid-19, were driven upwards by a rapidly increasing national caseload, and perceptions of the economic consequences and the adaptation of social distancing were affected by both national and state-level cases.", - "rel_num_authors": 9, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.07.20056804", + "rel_abs": "BackgroundA novel coronavirus disease 2019 (COVID-19) broke out in Wuhan of Hubei province and had spread throughout the world since December 2019. Because the clinically diagnosed cases in Hubei province were reported for the first time on February 13, 2020, a very high peak of new cases in China was observed. The reason why so many clinically diagnosed cases appeared was not clear.\n\nMethodsAll data of new cases in China were acquired from WHO situation reports. Linear fitting was used to infer the ability to detect COVID-19 infections. Primer-BLAST and nucleotide blast were applied to check the specificity of primers. Expression data of human mRNA in different tissues was obtained from Human Protein Atlas.\n\nFindingsBased on the data and analysis of changes of new laboratory-confirmed cases and new clinically diagnosed cases, it was inferred that there were many false-negative results in all clinically diagnosed cases in Hubei province. There were eight non-specific primers in dozens of primers used in clinical or research detection of COVID-19. Among them, a pair of primer for the ORF1ab regions of SARS-CoV-2 genome well matched some human mRNAs such as Cathepsin C transcripts. Compared to other transcripts, Cathepsin C mRNA had a high abundance in tonsil, lung and small intestine.\n\nInterpretationSome non-specific RT-PCR primers could cause the serious interference during RT-PCR amplification so as to increase the risk of false-negative diagnoses for COVID-19 infections.\n\nFundingKey Research Project of the Higher Education of Henan Province\n\nResearch in contextO_ST_ABSEvidence before this studyC_ST_ABSThe author searched PubMed on April 15, 2020, for papers that describe false-negative RT-PCR detection of COVID-19 by using the search terms \"COVID-19\", \"false-negative\" and \"RT-PCR\", with no language or time restrictions. Eleven investigations only presented the rate of false-negative detection or the importance of positive chest CT finding. There were no reports referring the primer problems of false-negative detection in COVID-19 infections.\n\nAdded value of this studyThe author had found that some primers could amplify the human mRNA in specimens, which mixed SARS-CoV-2 viral particles and other tissue cells. A pair of primer provided by China CDC could vastly match the sequences of human CTSC transcripts with high abundance. That could lead to false-negative results in detection of COVID-19 infections.\n\nImplications of all the available evidenceAlthough there were so many false-negative results in detection of COVID-19 infections in China, the exact reason was not clear. Problems in sampling and test condition were discussed thoroughly, but conclusions were usually contradictory. Therefore, the work could promote the verification of the false-negative detection of COVID-19 infections in China.", + "rel_num_authors": 1, "rel_authors": [ { - "author_name": "Alberto Ciancio", - "author_inst": "University of Pennsylvania" - }, - { - "author_name": "Fabrice K\u00e4mpfen", - "author_inst": "University of Pennsylvania" - }, - { - "author_name": "Iliana V. Kohler", - "author_inst": "University of Pennsylvania" - }, - { - "author_name": "Daniel Bennett", - "author_inst": "University of Southern California" - }, - { - "author_name": "W\u00e4ndi Bruine de Bruin", - "author_inst": "University of Southern California" - }, - { - "author_name": "Jill Darling", - "author_inst": "University of Southern California" - }, - { - "author_name": "Arie Kapteyn", - "author_inst": "University of Southern California" - }, - { - "author_name": "J\u00e4rgen Maurer", - "author_inst": "University of Lausanne" - }, - { - "author_name": "Hans-Peter Kohler", - "author_inst": "University of Pennsylvania" + "author_name": "Wei Liu", + "author_inst": "Zhengzhou University" } ], "version": "1", @@ -1551664,29 +1551254,21 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.04.08.20057281", - "rel_title": "Spatial modeling cannot currently differentiate SARS-CoV-2 coronavirus and human distributions on the basis of climate in the United States", + "rel_doi": "10.1101/2020.04.07.20052340", + "rel_title": "COVID-19 UK Lockdown Forecasts and R0", "rel_date": "2020-04-10", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.08.20057281", - "rel_abs": "The SARS-CoV-2 coronavirus is wreaking havoc globally, yet knowledge of its biology is limited. Climate and seasonality influence the distributions of many diseases, and studies suggest a link between SARS-CoV-2 and cool weather. One such study, building species distribution models (SDMs), predicted SARS-CoV-2 risk may remain concentrated in the Northern Hemisphere, shifting northward in summer months. Others have highlighted issues with SARS-CoV-2 SDMs, notably: the primary niche of the virus is the host it infects, climate may be a weak distributional predictor, global prevalence data have issues, and the virus is not in a population equilibrium. While these issues should be considered, climate still may be important for predicting the future distribution of SARS-CoV-2. To further examine if there is a link, we model with raw cases and population scaled cases for SARS-CoV-2 county-level data from the United States. We show that SDMs built from population scaled cases data cannot be distinguished from control models built from raw human population data, while SDMs built on raw data fail to predict the current known distribution of cases in the US. The population scaled analyses indicate that climate may not play a central role in current US viral distribution and that human population density is likely a primary driver. Still, we do find slightly more population scaled viral cases in cooler areas. This coupled with our geographically constrained focus make it so we cannot rule out climate as a partial driver of the US SARS-CoV-2 distribution. Climates role on SARS-CoV-2 should continue to be cautiously examined, but at this time we should assume that SARS-CoV-2 can spread anywhere in the US.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.07.20052340", + "rel_abs": "IntroductionThe first reported UK case of COVID-19 occurred on 31 January 2020, and a lockdown of unknown duration began on 24 March. One model to forecast disease spread depends on clinical parameters and transmission rates. Output includes the basic reproduction number R0 and the log growth rate r in the exponential phase.\n\nMethodsUK data on reported deaths is used to estimate r. A likelihood for the transmission parameters is defined from a gaussian density for r using the mean and standard error of the estimate. Parameter samples from the Metropolis-Hastings algorithm lead to an estimate and credible interval for R0 and forecasts for severe and critical cases, and deaths during a lockdown.\n\nResultsIn the exponential phase, the UK growth rate for log(deaths) is r = 0.224 with s.e. 0.005. R0 = 5.81 with 90% CI (5.08, 6.98). In a 12 week lockdown from 24 March with transmission parameters reduced to 20% of their previous values, around 63,000 severely ill patients will need hospitalisation by mid June, 37,000 critically ill will need intensive care, whilst over 81,000 are expected to die. Had the lockdown begun on 17 March around 16,500 severe, 9,250 critical cases and 18,500 deaths would be expected by early June. With 10% transmission, severe and critical cases peak in April.\n\nDiscussionThe R0 estimate is around twice the value quoted by the UK government. The NHS faces extreme pressures, even if transmission is reduced ten-fold. An earlier lockdown could have saved many lives.", + "rel_num_authors": 1, "rel_authors": [ { - "author_name": "Robert S Harbert", - "author_inst": "Stonehill College" - }, - { - "author_name": "Seth W Cunningham", - "author_inst": "American Museum of Natural History" - }, - { - "author_name": "Michael Tessler", - "author_inst": "American Museum of Natural History" + "author_name": "Greg Dropkin", + "author_inst": "independent researcher" } ], "version": "1", - "license": "cc_no", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1552842,47 +1552424,63 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2020.04.09.20056325", - "rel_title": "Evaluation of nine commercial SARS-CoV-2 immunoassays", + "rel_doi": "10.1101/2020.04.06.028712", + "rel_title": "Confronting the COVID-19 Pandemic with Systems Biology", "rel_date": "2020-04-10", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.09.20056325", - "rel_abs": "Due to urgency and demand, numerous severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) immunoassays are rapidly being developed and placed on the market with limited validation on clinical samples. Thorough validation of serological tests are required to facilitate their use in the accurate diagnosis of SARS-CoV-2 infection, confirmation of molecular results, contact tracing, and epidemiological studies. This study evaluated the sensitivity and specificity of nine commercially available serological tests. These included three enzyme-linked immunosorbent assays (ELISAs) and six point-of-care (POC) lateral flow tests. The assays were validated using serum samples from: i) SARS-CoV-2 PCR-positive patients with a documented first day of disease; ii) archived sera obtained from healthy individuals before the emergence of SARS-CoV-2 in China; iii) sera from patients with acute viral respiratory tract infections caused by other coronaviruses or non-coronaviruses; and iv) sera from patients positive for dengue virus, cytomegalovirus and Epstein Barr virus. The results showed 100% specificity for the Wantai SARS-CoV-2 Total Antibody ELISA, 93% for the Euroimmun IgA ELISA, and 96% for the Euroimmun IgG ELISA with sensitivities of 90%, 90%, and 65%, respectively. The overall performance of the POC tests according to manufacturer were in the rank order of AutoBio Diagnostics > Dynamiker Biotechnology = CTK Biotech > Artron Laboratories > Acro Biotech [≥] Hangzhou Alltest Biotech. Overall, these findings will facilitate selection of serological assays for the detection SARS-CoV-2-specific antibodies towards diagnosis as well as sero-epidemiological and vaccine development studies.", - "rel_num_authors": 7, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2020.04.06.028712", + "rel_abs": "Using a Systems Biology approach, we integrated genomic, transcriptomic, proteomic, and molecular structure information to provide a holistic understanding of the COVID-19 pandemic. The expression data analysis of the Renin Angiotensin System indicates mild nasal, oral or throat infections are likely and that the gastrointestinal tissues are a common primary target of SARS-CoV-2. Extreme symptoms in the lower respiratory system likely result from a secondary-infection possibly by a comorbidity-driven upregulation of ACE2 in the lung. The remarkable differences in expression of other RAS elements, the elimination of macrophages and the activation of cytokines in COVID-19 bronchoalveolar samples suggest that a functional immune deficiency is a critical outcome of COVID-19. We posit that using a non-respiratory system as a major pathway of infection is likely determining the unprecedented global spread of this coronavirus.\n\nOne Sentence SummaryA Systems Approach Indicates Non-respiratory Pathways of Infection as Key for the COVID-19 Pandemic", + "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Ria Lassauni\u00e8re", - "author_inst": "Statens Serum Institut, Copenhagen, Denmark" + "author_name": "Erica Teixeira Prates", + "author_inst": "Oak Ridge National Laboratory" }, { - "author_name": "Anders Frische", - "author_inst": "Statens Serum Institut, Copenhagen, Denmark" + "author_name": "Michael R Garvin", + "author_inst": "Oak Ridge National Laboratory" }, { - "author_name": "Zitta B Harboe", - "author_inst": "Nordsjaellands Hospital, Copenhagen, Denmark" + "author_name": "Mirko Pavicic", + "author_inst": "Oak Ridge National Laboratory" }, { - "author_name": "Alex CY Nielsen", - "author_inst": "Rigshospitalet, Copenhagen, Denmark" + "author_name": "Piet Jones", + "author_inst": "University of Tennessee Knoxville" }, { - "author_name": "Anders Fomsgaard", - "author_inst": "Statens Serum Institut, Copenhagen, Denmark" + "author_name": "Manesh Shah", + "author_inst": "Oak Ridge National Laboratory" }, { - "author_name": "Karen A Krogfelt", - "author_inst": "Roskilde University, Roskilde, Denmark and Statens Serum Institut, Copenhagen, Denmark" + "author_name": "Christiane Alvarez", + "author_inst": "Oak Ridge National Laboratory" }, { - "author_name": "Charlotte S J\u00f8rgensen", - "author_inst": "Statens Serum Institut" + "author_name": "David Kainer", + "author_inst": "Oak Ridge National Laboratory" + }, + { + "author_name": "Omar Demerdash", + "author_inst": "Oak Ridge National Laboratory" + }, + { + "author_name": "B Kirtley Amos", + "author_inst": "University of Kentucky" + }, + { + "author_name": "Armin Geiger", + "author_inst": "University of Tennessee Knoxville" + }, + { + "author_name": "Daniel Jacobson", + "author_inst": "Oak Ridge National Laboratory" } ], "version": "1", - "license": "cc_by", - "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "license": "cc_no", + "type": "new results", + "category": "systems biology" }, { "rel_doi": "10.1101/2020.04.07.20056945", @@ -1554888,59 +1554486,51 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.04.06.20055194", - "rel_title": "Acute kidney injury in patients hospitalized with COVID-19 in Wuhan, China: A single-center retrospective observational study", + "rel_doi": "10.1101/2020.04.06.20055103", + "rel_title": "The impact of early social distancing at COVID-19 Outbreak in the largest Metropolitan Area of Brazil.", "rel_date": "2020-04-08", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.06.20055194", - "rel_abs": "BackgroundThe kidney may be affected in coronavirus-2019 disease (COVID-19). This study assessed the predictors and outcomes of acute kidney injury (AKI) among individuals with COVID-19.\n\nMethodsThis observational study, included data on all patients with clinically confirmed COVID-19 admitted to Hankou Hospital, Wuhan, China from January 5 to March 8, 2020. Data were extracted from clinical and laboratory records. Follow-up was censored on March 8, 2020.\n\nThis is a single-center, retrospective, observational study. Patients clinically confirmed COVID-19 and admitted to Hankou Hospital, Wuhan, China from January 5 to March 8, 2020 were enrolled. We evaluated the association between changes in the incidence of AKI and COVID-19 disease and clinical outcomes by using logistic regression models.\n\nResultsA total of 287 patients, 55 with AKI and 232 without AKI, were included in the analysis. Compared to patients without AKI, AKI patients were older, predominantly male, and were more likely to present with hypoxia and have pre-existing hypertension and cerebrovascular disease. Moreover, AKI patients had higher levels of white blood cells, D-dimer, aspartate aminotransferase, total bilirubin, creatine kinase, lactate dehydrogenase, procalcitonin, C-reactive protein, a higher prevalence of hyperkalemia, lower lymphocyte counts, and higher chest computed tomographic scores. The incidence of stage 1 AKI was 14.3%, and the incidence of stage 2 or 3 AKI was 4.9%. Patients with AKI had substantially higher mortality.\n\nConclusionsAKI is an important complication of COVID-19. Older age, male, multiple pre-existing comorbidities, lymphopenia, increased infection indicators, elevated D-dimer, and impaired heart and liver functions were the risk factors of AKI. AKI patients who progressed to stages 2 or 3 AKI had a higher mortality rate. Prevention of AKI and monitoring of kidney function is very important for COVID-19 patients.\n\nTrial registrationNCT04316299(03/19/2020)", - "rel_num_authors": 10, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.06.20055103", + "rel_abs": "We evaluated the impact of early social distancing on the COVID-19 transmission in the Sao Paulo metropolitan area. Using an age-stratified SEIR model, we determined the time-dependent reproductive number, and forecasted the ICU beds necessary to tackle this epidemic. Within 60 days, these measures might prevent 89,450 deaths.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Guanhua Xiao", - "author_inst": "Department of Respiratory and Critical Care Medicine, Chronic Airways Diseases Laboratory, Nanfang Hospital, Southern Medical University" - }, - { - "author_name": "Hongbin Hu", - "author_inst": "Department of Critical Care Medicine, Nanfang Hospital, Southern Medical University" - }, - { - "author_name": "Feng Wu", - "author_inst": "Department of Critical Care Medicine, Nanfang Hospital, Southern Medical University" + "author_name": "Fabiana Ganem", + "author_inst": "Secretariat of Health Surveillance; Department of Immunization and Communicable Diseases; Ministry of Health; Brazil." }, { - "author_name": "Tong Sha", - "author_inst": "Department of Critical Care Medicine, Nanfang Hospital, Southern Medical University" + "author_name": "Fabio Macedo Mendes", + "author_inst": "University of Brasilia; Brazil" }, { - "author_name": "Qiaobing Huang", - "author_inst": "Guangdong Provincial Key Laboratory of Shock and Microcirculation, School of Basic Medical Sciences, Southern Medical University" + "author_name": "Silvano Barbosa Oliveira", + "author_inst": "Secretariat of Health Surveillance; Department of Immunization and Communicable Diseases; Ministry of Health; Brazil." }, { - "author_name": "Haijun Li", - "author_inst": "Department of Radiology, Hankou Hospital of Wuhan" + "author_name": "Victor Bertolo Gomes Porto", + "author_inst": "Secretariat of Health Surveillance; Department of Immunization and Communicable Diseases; Ministry of Health; Brazil." }, { - "author_name": "Jiafa Han", - "author_inst": "Department of Radiology, Hankou Hospital of Wuhan" + "author_name": "Wildo Araujo", + "author_inst": "University of Brasilia;" }, { - "author_name": "Wenhong Song", - "author_inst": "Department of Radiology, Hankou Hospital of Wuhan" + "author_name": "Helder Nakaya", + "author_inst": "Universidade de Sao Paulo Faculdade de Ciencias Farmaceuticas" }, { - "author_name": "Zhongqing Chen", - "author_inst": "Department of Critical Care Medicine, Nanfang Hospital, Southern Medical University" + "author_name": "Fredi A Diaz-Quijano", + "author_inst": "Universidade de Sao Paulo" }, { - "author_name": "Zhenhua Zeng", - "author_inst": "Nanfang Hospital ofouthern Medical University" + "author_name": "Julio Croda", + "author_inst": "Oswaldo Cruz Foundation" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", - "category": "intensive care and critical care medicine" + "category": "epidemiology" }, { "rel_doi": "10.1101/2020.04.05.20047944", @@ -1556157,177 +1555747,37 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.04.07.20054585", - "rel_title": "Proteomic and Metabolomic Characterization of COVID-19 Patient Sera", + "rel_doi": "10.1101/2020.04.03.20052787", + "rel_title": "Susceptible supply limits the role of climate in the COVID-19 pandemic", "rel_date": "2020-04-07", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.07.20054585", - "rel_abs": "Severe COVID-19 patients account for most of the mortality of this disease. Early detection and effective treatment of severe patients remain major challenges. Here, we performed proteomic and metabolomic profiling of sera from 46 COVID-19 and 53 control individuals. We then trained a machine learning model using proteomic and metabolomic measurements from a training cohort of 18 non-severe and 13 severe patients. The model correctly classified severe patients with an accuracy of 93.5%, and was further validated using ten independent patients, seven of which were correctly classified. We identified molecular changes in the sera of COVID-19 patients implicating dysregulation of macrophage, platelet degranulation and complement system pathways, and massive metabolic suppression. This study shows that it is possible to predict progression to severe COVID-19 disease using serum protein and metabolite biomarkers. Our data also uncovered molecular pathophysiology of COVID-19 with potential for developing anti-viral therapies.", - "rel_num_authors": 40, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.03.20052787", + "rel_abs": "Preliminary evidence suggests that climate may modulate the transmission of SARS-CoV-2. Yet it remains unclear whether seasonal and geographic variations in climate can substantially alter the pandemic trajectory, given high susceptibility is a core driver. Here, we use a climate-dependent epidemic model to simulate the SARS-CoV-2 pandemic probing different scenarios of climate-dependence based on known coronavirus biology. We find that while variations in humidity may be important for endemic infections, during the pandemic stage of an emerging pathogen such as SARS-CoV-2 climate may drive only modest changes to pandemic size and duration. Our results suggest that, in the absence of effective control measures, significant cases in the coming months are likely to occur in more humid (warmer) climates, irrespective of the climate-dependence of transmission and that summer temperatures will not substantially limit pandemic growth.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Bo Shen", - "author_inst": "Department of clinical laboratory, Taizhou Hospital,Wenzhou Medical Universtry, 150 Ximen Street,Linhai 317000,Zhejiang Province,China." - }, - { - "author_name": "Xiao Yi", - "author_inst": "Westlake University" - }, - { - "author_name": "Yaoting Sun", - "author_inst": "Westlake University" - }, - { - "author_name": "Xiaojie Bi", - "author_inst": "Taizhou Hospital,Wenzhou Medical Universtry ,150 Ximen Street,Linhai 317000,Zhejiang Province,China." - }, - { - "author_name": "Juping Du", - "author_inst": "Taizhou Hospital,Wenzhou Medical Universtry ,150 Ximen Street,Linhai 317000,Zhejiang Province,China." - }, - { - "author_name": "Chao Zhang", - "author_inst": "Calibra Lab at DIAN Diagnostics, 329 Jinpeng Street, Hangzhou 310030, Zhejiang Province, China." - }, - { - "author_name": "Sheng Quan", - "author_inst": "Calibra Lab at DIAN Diagnostics, 329 Jinpeng Street, Hangzhou 310030, Zhejiang Province, China." - }, - { - "author_name": "Fangfei Zhang", - "author_inst": "Westlake University" - }, - { - "author_name": "Rui Sun", - "author_inst": "Westlake University" - }, - { - "author_name": "Liujia Qian", - "author_inst": "Westlake University" - }, - { - "author_name": "Weigang Ge", - "author_inst": "Westlake University" - }, - { - "author_name": "Wei Liu", - "author_inst": "Westlake University" - }, - { - "author_name": "Shuang Liang", - "author_inst": "Westlake University" - }, - { - "author_name": "Hao Chen", - "author_inst": "Westlake University" - }, - { - "author_name": "Ying Zhang", - "author_inst": "Taizhou Hospital,Wenzhou Medical Universtry ,150 Ximen Street,Linhai 317000,Zhejiang Province,China." - }, - { - "author_name": "Jun Li", - "author_inst": "Taizhou Hospital,Wenzhou Medical Universtry ,150 Ximen Street,Linhai 317000,Zhejiang Province,China." - }, - { - "author_name": "Jiaqin Xu", - "author_inst": "Taizhou Hospital,Wenzhou Medical Universtry ,150 Ximen Street,Linhai 317000,Zhejiang Province,China." - }, - { - "author_name": "Zebao He", - "author_inst": "Taizhou Enze Medical Center (Group) Enze Hospital" - }, - { - "author_name": "Baofu Chen", - "author_inst": "Taizhou Hospital,Wenzhou Medical Universtry ,150 Ximen Street,Linhai 317000, Zhejiang Province,China." - }, - { - "author_name": "Jing Wang", - "author_inst": "Taizhou Hospital,Wenzhou Medical Universtry ,150 Ximen Street,Linhai 317000,Zhejiang Province,China." - }, - { - "author_name": "Haixi Yan", - "author_inst": "Taizhou Hospital,Wenzhou Medical Universtry ,150 Ximen Street,Linhai 317000,Zhejiang Province,China." - }, - { - "author_name": "Yufen Zheng", - "author_inst": "Taizhou Hospital,Wenzhou Medical Universtry ,150 Ximen Street,Linhai 317000,Zhejiang Province,China." - }, - { - "author_name": "Donglian Wang", - "author_inst": "Taizhou Hospital,Wenzhou Medical Universtry ,150 Ximen Street,Linhai 317000,Zhejiang Province,China." - }, - { - "author_name": "Jiansheng Zhu", - "author_inst": "Taizhou Hospital,Wenzhou Medical Universtry ,150 Ximen Street,Linhai 317000,Zhejiang Province,China." - }, - { - "author_name": "Ziqing Kong", - "author_inst": "Calibra Lab at DIAN Diagnostics, 329 Jinpeng Street, Hangzhou 310030, Zhejiang Province,China." - }, - { - "author_name": "Zhouyang Kang", - "author_inst": "Calibra Lab at DIAN Diagnostics, 329 Jinpeng Street, Hangzhou 310030, Zhejiang Province, China." - }, - { - "author_name": "Xiao Liang", - "author_inst": "Westlake University" - }, - { - "author_name": "Xuan Ding", - "author_inst": "Westlake University" - }, - { - "author_name": "Guan Ruan", - "author_inst": "Westlake University" - }, - { - "author_name": "Nan Xiang", - "author_inst": "Westlake University" - }, - { - "author_name": "Xue Cai", - "author_inst": "Westlake University" - }, - { - "author_name": "Huanhuan Gao", - "author_inst": "Westlake University" - }, - { - "author_name": "Lu Li", - "author_inst": "Westlake University" - }, - { - "author_name": "Sainan Li", - "author_inst": "Westlake University" - }, - { - "author_name": "Qi Xiao", - "author_inst": "Westlake University" - }, - { - "author_name": "Tian Lu", - "author_inst": "Westlake University" + "author_name": "Rachel E. Baker", + "author_inst": "Princeton University" }, { - "author_name": "Yi Judy Zhu", - "author_inst": "Westlake University" + "author_name": "Wenchang Yang", + "author_inst": "Princeton University" }, { - "author_name": "Huafen Liu", - "author_inst": "Calibra Lab at DIAN Diagnostics, 329 Jinpeng Street, Hangzhou 310030, Zhejiang Province, China." + "author_name": "Gabriel A. Vecchi", + "author_inst": "Princeton University" }, { - "author_name": "Haixiao Chen", - "author_inst": "Taizhou Hospital,Wenzhou Medical Universtry ,150 Ximen Street,Linhai 317000, Zhejiang Province,China." + "author_name": "C. Jessica E. Metcalf", + "author_inst": "Princeton University" }, { - "author_name": "Tiannan Guo", - "author_inst": "Westlake University" + "author_name": "Bryan T Grenfell", + "author_inst": "Princeton University" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1557447,17 +1556897,45 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.04.05.20054445", - "rel_title": "Efficient sample pooling strategies for COVID-19 data gathering", + "rel_doi": "10.1101/2020.04.05.20053884", + "rel_title": "Study of Epidemiological Characteristics and In-silico Analysis of the Effect of Interventions in the SARS-CoV-2 Epidemic in India", "rel_date": "2020-04-07", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.05.20054445", - "rel_abs": "Sample pooling of CoViD-19 PCR tests has been recently proposed as a low cost alternative to individual tests. We show that sample pooling is efficient as long as the fraction of the population infected is relatively small. Fisher information theory suggests a rule of thumb that for low infection rates p, pooling 2/p samples is close to optimal. We present a simple strategy for survey design when not even a ballpark estimate of the infection rate is available.", - "rel_num_authors": 1, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.05.20053884", + "rel_abs": "After SARS-CoV-2 set foot in India, the Government took a number of steps to limit the spread of the disease in the country. This study involves assessing how the disease affected the population in the initial days of the epidemic. Data was collected from government-controlled and crowdsourced websites and analyzed. Studying age and sex parameters of 413 Indian COVID-19 patients, the median age of the affected individuals was found to be 36 years (IQR, 25-54) with 20-39 years males being the most affected group. The number of affected males (66.34%) was more than that of the females (33.66%). Using Susceptible-Infected-Removed (SIR) model, the range of contact rate ({beta}) of India was calculated and the role of public health interventions was assessed. If current contact rate continues, India may have 5583 to 13785 active cases at the end of 21 days lockdown.\n\nArticle Summary LineThe study gives the epidemiological characteristics of the SARS-CoV-2 epidemic in India, where unlike other countries, the 20-39 years males are most affected, and the SIR model predicts the probable number of cases of COVID-19 by the end of the 21 days lockdown in the country, which will help to develop appropriate public health interventions to control the COVID-19 epidemic.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Istvan Szapudi", - "author_inst": "University of Hawaii" + "author_name": "Archisman Mazumder", + "author_inst": "All India Institute of Medical Sciences New Delhi" + }, + { + "author_name": "Mehak Arora", + "author_inst": "All India Institute of Medical Sciences New Delhi" + }, + { + "author_name": "Vishwesh Bharadiya", + "author_inst": "All India Institute of Medical Sciences New Delhi" + }, + { + "author_name": "Parul Berry", + "author_inst": "All India Institute of Medical Sciences New Delhi" + }, + { + "author_name": "Mudit Agarwal", + "author_inst": "All India Institute of Medical Sciences New Delhi" + }, + { + "author_name": "Mohak Gupta", + "author_inst": "All India Institute of Medical Sciences New Delhi" + }, + { + "author_name": "Giridara Gopal Parameswaran", + "author_inst": "All India Institute of Medical Sciences New Delhi" + }, + { + "author_name": "Priyamadhaba Behera", + "author_inst": "All India Institute of Medical Sciences Raebareli" } ], "version": "1", @@ -1558553,61 +1558031,101 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.03.31.20045401", - "rel_title": "A case of SARS-CoV-2 carrier for 32 days with several times false negative nucleic acid tests", + "rel_doi": "10.1101/2020.04.03.20051763", + "rel_title": "Virologic and clinical characteristics for prognosis of severe COVID-19: a retrospective observational study in Wuhan, China", "rel_date": "2020-04-06", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.31.20045401", - "rel_abs": "In 2019, a novel coronavirus (SARS-CoV-2) was first discovered in Wuhan, Hubei, China, causing severe respiratory disease in humans, and has been identified as a public health emergency of international concern. With the spread of the virus, there are more and more false negative cases of RT-PCR nucleic acid detection in the early stage of potential infection. In this paper, we collected the epidemiological history, clinical manifestations, outcomes, laboratory results and images of a SARS-CoV-2 carrier with no significant past medical history. The patient was quarantined because of her colleague had been diagnosed. After the onset of clinical symptoms, chest CT results showed patchy ground-glass opacity (GGO) in her lungs, but it took a total of nine nucleic acid tests to confirm the diagnosis, among which the first eight RT-PCR results were negative or single-target positive. In addition to coughing up phlegm during her stay in the hospital, she did not develop chills, fever, abdominal pain, diarrhea and other clinical symptoms. Since initial antiviral treatment, the lung lesions were absorbed. But the sputum nucleic acid test was still positive. In combination with antiviral and immune therapy, the patient tested negative for the virus. Notably, SARS-CoV-2 was detected only in the lower respiratory tract samples (sputum) throughout the diagnosis and treatment period. This is a confirmed case of SARS-CoV-2 infection with common symptoms, and her diagnosis has undergone multiple false negatives, suggesting that it is difficult to identify certain carriers of the virus and that such patients may also increase the spread of the SARS-CoV-2.", - "rel_num_authors": 11, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.03.20051763", + "rel_abs": "BackgroundThe severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has progressed to a pandemic associated with substantial morbidity and mortality. The WHO and the United States Center for Disease Control and Prevention (CDC) have issued interim clinical guidance for management of patients with confirmed coronavirus disease (COVID-19), but there is limited data on the virologic and clinical characteristics for prognosis of severe COVID-19.\n\nMethodsA total of 50 patients with severe COVID-19 were divided into good and poor recovery groups. The dynamic viral shedding and serological characteristics of SARS-CoV-2 were explored. The risk factors associated with poor recovery and lung lesion resolutions were identified. In addition, the potential relationships among the viral shedding, the pro-inflammatory response, and lung lesion evolutions were characterized.\n\nResultsA total of 58% of the patients had poor recovery and were more likely to have a prolonged interval of viral shedding. The longest viral shedding was 57 days after symptom onset. Older age, hyperlipemia, hypoproteinemia, corticosteroid therapy, consolidation on chest computed-tomography (CT), and prolonged SARS-CoV-2 IgM positive were all associated with poor recovery. Additionally, the odds of impaired lung lesion resolutions were higher in patients with hypoproteinemia, hyperlipemia, and elevated levels of IL-4 and ferritin. Finally, viral shedding and proinflammatory responses were closely correlated with lung lesion evolutions on chest CT.\n\nConclusionsPatients with severe COVID-19 have prolonged SARS-CoV-2 infection and delayed intermittent viral shedding. Older age, hyperlipemia, hypoproteinemia, corticosteroid usage, and prolonged SARS-CoV-2 IgM positive might be utilized as predicative factors for the patients with poor recovery.", + "rel_num_authors": 21, "rel_authors": [ { - "author_name": "Lingjie Song", - "author_inst": "Non-coding RNA and Drug Discovery Key Laboratory of Sichuan Province, Chengdu Medical College, Chengdu, Sichuan, China." + "author_name": "Sha Fu", + "author_inst": "Xiangya Hospital Central South University" }, { - "author_name": "Guibao Xiao", - "author_inst": "The First People's Hospital of Ziyang City" + "author_name": "Xiaoyu Fu", + "author_inst": "Xiangya Hospital, Central South University" }, { - "author_name": "Xianqin Zhang", - "author_inst": "Chengdu medical college" + "author_name": "Yang Song", + "author_inst": "School of Medicine and Health Management, Tongji Medical College, Huazhong University of Science and Technology" }, { - "author_name": "Zhan Gao", - "author_inst": "Institute of Blood Transfusion, Chinese Academy of Medical Sciences" + "author_name": "Min Li", + "author_inst": "Xiangya Hospital, Central South University" }, { - "author_name": "Shixia Sun", - "author_inst": "The First People's Hospital of Ziyang City" + "author_name": "Pin-hua Pan", + "author_inst": "Xiangya Hospital, Central South University" }, { - "author_name": "Lin Zhang", - "author_inst": "Shaoxing Hospital, Zhejiang University School of Medicine" + "author_name": "Tao Tang", + "author_inst": "Xiangya Hospital, Central South University" }, { - "author_name": "Youjun Feng", - "author_inst": "Zhejiang University" + "author_name": "Chunhu Zhang", + "author_inst": "Xiangya Hospital, Central South University" }, { - "author_name": "Guangxin Luan", - "author_inst": "Chengdu medical college" + "author_name": "Tiejian Jiang", + "author_inst": "Xiangya Hospital, Central South University" }, { - "author_name": "Sheng Lin", - "author_inst": "The First People's Hospital of Ziyang City" + "author_name": "Deming Tan", + "author_inst": "Xiangya Hospital, Central South University" }, { - "author_name": "Miao He", - "author_inst": "Institute of Blood Transfusion, Chinese Academy of Medical Sciences, Chengdu, Sichuan, China." + "author_name": "Xuegong Fan", + "author_inst": "Xiangya Hospital, Central South University" + }, + { + "author_name": "Xinping Sha", + "author_inst": "Xiangya Hospital, Central South University" + }, + { + "author_name": "Jingdong Ma", + "author_inst": "School of Medicine and Health Management, Tongji Medical College, Huazhong University of Science and Technology" + }, + { + "author_name": "Yan Huang", + "author_inst": "Xiangya Hospital, Central South University" + }, + { + "author_name": "Shaling Li", + "author_inst": "Xiangya Hospital, Central South University" + }, + { + "author_name": "Yixiang Zheng", + "author_inst": "Xiangya Hospital, Central South University" }, { - "author_name": "Xu Jia", - "author_inst": "Non-coding RNA and Drug Discovery Key Laboratory of Sichuan Province, Chengdu Medical College, Chengdu, Sichuan, China." + "author_name": "Zhaoxin Qian", + "author_inst": "Xiangya hospital, Central South Univrsity" + }, + { + "author_name": "Zeng Xiong", + "author_inst": "Xiangya Hospital, Central South University" + }, + { + "author_name": "Lizhi Xiao", + "author_inst": "Sun Yat-sen Memorial Hospital of Sun Yat-sen University" + }, + { + "author_name": "Huibao Long", + "author_inst": "Sun Yat-sen Memorial Hospital of Sun Yat-sen University" + }, + { + "author_name": "Jianghai Chen", + "author_inst": "Union Hospital, Tongji Medical College, Huazhong University of Science and Technology" + }, + { + "author_name": "Yi Ouyang", + "author_inst": "Hunan Key Laboratory of Viral Hepatitis, Xiangya Hospital, Central South University,Changsha,China." } ], "version": "1", - "license": "cc_by", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1559895,217 +1559413,33 @@ "category": "health policy" }, { - "rel_doi": "10.1101/2020.04.02.20051284", - "rel_title": "Building an International Consortium for Tracking Coronavirus Health Status", + "rel_doi": "10.1101/2020.04.01.20049478", + "rel_title": "Differential COVID-19-attributable mortality and BCG vaccine use in countries", "rel_date": "2020-04-06", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.02.20051284", - "rel_abs": "Information is the most potent protective weapon we have to combat a pandemic, at both the individual and global level. For individuals, information can help us make personal decisions and provide a sense of security. For the global community, information can inform policy decisions and offer critical insights into the epidemic of COVID-19 disease. Fully leveraging the power of information, however, requires large amounts of data and access to it. To achieve this, we are making steps to form an international consortium, Coronavirus Census Collective (CCC, coronaviruscensuscollective.org), that will serve as a hub for integrating information from multiple data sources that can be utilized to understand, monitor, predict, and combat global pandemics. These sources may include self-reported health status through surveys (including mobile apps), results of diagnostic laboratory tests, and other static and real-time geospatial data. This collective effort to track and share information will be invaluable in predicting hotspots of disease outbreak, identifying which factors control the rate of spreading, informing immediate policy decisions, evaluating the effectiveness of measures taken by health organizations on pandemic control, and providing critical insight on the etiology of COVID-19. It will also help individuals stay informed on this rapidly evolving situation and contribute to other global efforts to slow the spread of disease.\n\nIn the past few weeks, several initiatives across the globe have surfaced to use daily self-reported symptoms as a means to track disease spread, predict outbreak locations, guide population measures and help in the allocation of healthcare resources. The aim of this paper is to put out a call to standardize these efforts and spark a collaborative effort to maximize the global gain while protecting participant privacy.", - "rel_num_authors": 51, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.01.20049478", + "rel_abs": "While mortality attributable to COVID-19 has devastated global health systems and economies, striking regional differences have been observed. The Bacille Calmette Guerin (BCG) vaccine has previously been shown to have non-specific protective effects on infections, as well as long-term efficacy against tuberculosis. Using publicly available data we built a simple log-linear regression model to assess the association of BCG use and COVID-19-attributable mortality per 1 million population after adjusting for confounders including country economic status (GDP per capita), and proportion of elderly among the population. The timing of country entry into the pandemic epidemiological trajectory was aligned by plotting time since the 100th reported case. Countries with economies classified as lower-middle-income, upper-middle-income and high-income countries (LMIC, UMIC, HIC) had median crude COVID-19 log-mortality of 0.4 (Interquartile Range (IQR) 0.1, 0.4), 0.7 (IQR 0.2, 2.2) and 5.5 (IQR 1.6, 13.9), respectively. COVID-19-attributable mortality among BCG-using countries was 5.8 times lower [95% CI 1.8-19.0] than in non BCG-using countries. Notwithstanding limitations due to testing constraints in LMICs, case ascertainment bias and a plausible rise of cases as countries progress along the epidemiological trajectory, these analyses provide intriguing observations that urgently warrant mobilization of resources for prospective randomized interventional studies and institution of systematic disease surveillance, particularly in LMICs.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Eran Segal", - "author_inst": "Weizmann Institute of Science" - }, - { - "author_name": "Feng Zhang", - "author_inst": "Howard Hughes Medical Institute, Core Member, Broad Institute of MIT and Harvard, United States" - }, - { - "author_name": "Xihong Lin", - "author_inst": "Departments of Biostatistics and Statistics, Harvard T.H. Chan School of Public Health" - }, - { - "author_name": "Gary King", - "author_inst": "Albert J. Weatherhead III University, Institute for Quantitative Social Science, Harvard University" - }, - { - "author_name": "Ophir Shalem", - "author_inst": "Department of Genetics, Perelman School of Medicine, University of Pennsylvania, United States" - }, - { - "author_name": "Smadar Shilo", - "author_inst": "Department of Computer Science and Applied Mathematics, and Department of Molecular Cell Biology, Weizmann Institute of Science, Israel" - }, - { - "author_name": "William E. Allen", - "author_inst": "Society of Fellows, Harvard University, United States" - }, - { - "author_name": "Yonatan H. Grad", - "author_inst": "Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, United States" - }, - { - "author_name": "Casey S. Greene", - "author_inst": "Department of Systems Pharmacology and Translational Therapeutics, Perelman School of Medicine, University of Pennsylvania, United States" - }, - { - "author_name": "Faisal Alquaddoomi", - "author_inst": "ETH Zurich, NEXUS Personalized Health Technologies, Zurich, Switzerland" - }, - { - "author_name": "Simon Anders", - "author_inst": "Center for Molecular Biology (ZMBH), University of Heidelberg, Germany" - }, - { - "author_name": "Ran Balicer", - "author_inst": "Clalit Research Institute, Clalit Health Services, Israel" - }, - { - "author_name": "Tal Bauman", - "author_inst": "Mapping and Geo-Information Engineering, Civil and Environmental Engineering Faculty, The Technion, Israel" - }, - { - "author_name": "Ximena Bonilla", - "author_inst": "ETH Zurich, Department for Computer Science, Zurich, University Hospital Zurich, Medical Informatics, Zurich and SIB Swiss Institute of Bioinformatics, Zurich, " - }, - { - "author_name": "Gisel Booman", - "author_inst": "Regen Network, Argentina" - }, - { - "author_name": "Andrew T. Chan", - "author_inst": "Massachusetts General Hospital (MGH), United States" - }, - { - "author_name": "Ori Ori Cohen", - "author_inst": "Department of Computer Science and Applied Mathematics, and Department of Molecular Cell Biology, Weizmann Institute of Science, Israel" - }, - { - "author_name": "Silvano Coletti", - "author_inst": "Chelonia Applied Science, Switzerland" - }, - { - "author_name": "Natalie Davidson", - "author_inst": "ETH Zurich, Department for Computer Science, Zurich, University Hospital Zurich, Medical Informatics, Zurich and SIB Swiss Institute of Bioinformatics, Zurich, " - }, - { - "author_name": "Yuval Dor", - "author_inst": "School of Medicine-IMRIC-Developmental Biology and Cancer Research, The Hebrew University" - }, - { - "author_name": "David A. Drew", - "author_inst": "Massachusetts General Hospital (MGH), United States" - }, - { - "author_name": "Olivier Elemento", - "author_inst": "Englander Institute for Precision Medicine and Department of Physiology and Biophysics, Weill Cornell Medicine, USA" - }, - { - "author_name": "Georgina Evans", - "author_inst": "Institute for Quantitative Social Science, Harvard University" - }, - { - "author_name": "Phil Ewels", - "author_inst": "Science for Life Laboratory (SciLifeLab), Department of Biochemistry and Biophysics, Stockholm University, Sweden" - }, - { - "author_name": "Joshua Gale", - "author_inst": "symptometrics.org" - }, - { - "author_name": "Amir Gavrieli", - "author_inst": "Department of Computer Science and Applied Mathematics, and Department of Molecular Cell Biology, Weizmann Institute of Science, Israel" - }, - { - "author_name": "Benjamin Geiger", - "author_inst": "Department of immunology, Weizmann Institute of Science, Israel" - }, - { - "author_name": "Iman Hajirasouliha", - "author_inst": "Englander Institute for Precision Medicine and Department of Physiology and Biophysics, Weill Cornell Medicine, USA" - }, - { - "author_name": "Roman Jerala", - "author_inst": "Department of Synthetic biology and Immunology, National Institute of Chemistry, Slovenia" - }, - { - "author_name": "Andre Kahles", - "author_inst": "ETH Zurich, Department for Computer Science, Zurich, University Hospital Zurich, Medical Informatics, Zurich and SIB Swiss Institute of Bioinformatics, Zurich, " - }, - { - "author_name": "Olli Kallioniemi", - "author_inst": "Science for Life Laboratory (SciLifeLab), Department of Oncology and Pathology, Karolinska Institutet, Stockholm, Sweden" - }, - { - "author_name": "Ayya Keshet", - "author_inst": "Department of Computer Science and Applied Mathematics, and Department of Molecular Cell Biology, Weizmann Institute of Science, Israel" - }, - { - "author_name": "Gregory Landua", - "author_inst": "Regen Network, United States" - }, - { - "author_name": "Tomer Meir", - "author_inst": "Department of Computer Science and Applied Mathematics, and Department of Molecular Cell Biology, Weizmann Institute of Science, Israel" - }, - { - "author_name": "Aline Muller", - "author_inst": "Luxembourg Institute of Socio-Economic Research and University of Luxembourg, Luxembourg" - }, - { - "author_name": "Long H. Nguyen", - "author_inst": "Massachusetts General Hospital (MGH), United States" - }, - { - "author_name": "Matej Oresic", - "author_inst": "School of Medical Sciences, Orebro University, Orebro, Sweden, and Turku Bioscience Centre, University of Turku and Abo Akademi University, Turku, Finland" - }, - { - "author_name": "Svetlana Ovchinnikova", - "author_inst": "Center for Molecular Biology (ZMBH), University of Heidelberg, Germany" - }, - { - "author_name": "Hedi Peterson", - "author_inst": "Institute of Computer Science, University of Tartu, Estonia, Estonia" - }, - { - "author_name": "Jay Rajagopal", - "author_inst": "Internal Medicine, Harvard Medical School, Department of Pulmonary Medicine and Critical Care, Massachusetts General Hospital (MGH), United States" - }, - { - "author_name": "Gunnar Ratsch", - "author_inst": "ETH Zurich, Department for Computer Science, Zurich, University Hospital Zurich, Medical Informatics, Zurich and SIB Swiss Institute of Bioinformatics, Zurich a" - }, - { - "author_name": "Hagai Rossman", - "author_inst": "Department of Computer Science and Applied Mathematics, and Department of Molecular Cell Biology, Weizmann Institute of Science, Israel" - }, - { - "author_name": "Johan Rung", - "author_inst": "Science for Life Laboratory (SciLifeLab), Department of Immunology, Genetics and Pathology, Uppsala university, Sweden" - }, - { - "author_name": "Andrea Sboner", - "author_inst": "Englander Institute for Precision Medicine and Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, USA" - }, - { - "author_name": "Alexandros Sigaras", - "author_inst": "Englander Institute for Precision Medicine and Department of Physiology and Biophysics, Weill Cornell Medicine, USA" - }, - { - "author_name": "Tim Spector", - "author_inst": "Kings College, United Kingdom" - }, - { - "author_name": "Ron Steinherz", - "author_inst": "Regen Network, United States" + "author_name": "Anita Shet", + "author_inst": "Johns Hopkins Bloomberg School of Public Health, USA" }, { - "author_name": "Irene Stevens", - "author_inst": "Science for Life Laboratory (SciLifeLab), Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet, Sweden" + "author_name": "Debashree Ray", + "author_inst": "Johns Hopkins Bloomberg School of Public Health, USA" }, { - "author_name": "Jaak Vilo", - "author_inst": "Institute of Computer Science, University of Tartu, Estonia, Estonia" + "author_name": "Neelika Malavige", + "author_inst": "University of Sri Jayewardenepura, Sri Lanka" }, { - "author_name": "Paul Wilmes", - "author_inst": "Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Luxembourg" + "author_name": "Mathuram Santosham", + "author_inst": "Johns Hopkins Bloomberg School of Public Health" }, { - "author_name": "CCC (Coronavirus Census Collective)", - "author_inst": "" + "author_name": "Naor Bar-Zeev", + "author_inst": "Johns Hopkins Bloomberg School of Public Health" } ], "version": "1", @@ -1561109,57 +1560443,41 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2020.04.01.20050203", - "rel_title": "Seeding COVID-19 across sub-Saharan Africa: an analysis of reported importation events across 40 countries", + "rel_doi": "10.1101/2020.04.01.20050138", + "rel_title": "Epidemiological Characteristics of COVID-19: A Systemic Review and Meta-Analysis", "rel_date": "2020-04-06", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.01.20050203", - "rel_abs": "BackgroundThe first case of COVID-19 in sub-Saharan Africa (SSA) was reported by Nigeria on February 27, 2020. While case counts in the entire region remain considerably less than those being reported by individual countries in Europe, Asia, and the Americas, SSA countries remain vulnerable to COVID morbidity and mortality due to systemic healthcare weaknesses, less financial resources and infrastructure to address the new crisis, and untreated comorbidities. Variation in preparedness and response capacity as well as in data availability has raised concerns about undetected transmission events.\n\nMethodsConfirmed cases reported by SSA countries were line-listed to capture epidemiological details related to early transmission events into and within countries. Data were retrieved from publicly available sources, including institutional websites, situation reports, press releases, and social media accounts, with supplementary details obtained from news articles. A data availability score was calculated for each imported case in terms of how many indicators (sex, age, travel history, date of arrival in country, reporting date of confirmation, and how detected) could be identified. We assessed the relationship between time to first importation and overall Global Health Security Index (GHSI) using Cox regression. K-means clustering grouped countries according to healthcare capacity and health and demographic risk factors.\n\nResultsA total of 13,201 confirmed cases of COVID-19 were reported by 48 countries in SSA during the 54 days following the first known introduction to the region. Out of the 2516 cases for which travel history information was publicly available, 1129 (44.9%) were considered importation events. At the regional level, imported cases tended to be male (65.0%), were a median 41.0 years old (Range: 6 weeks - 88 years), and most frequently had recent travel history from Europe (53.1%). The median time to reporting an introduction was 19 days; a countrys time to report its first importation was not related to GHSI, after controlling for air traffic. Countries that had, on average, the highest case fatality rates, lowest healthcare capacity, and highest probability of premature death due to non-communicable diseases were among the last to report any cases.\n\nConclusionsCountries with systemic, demographic, and pre-existing health vulnerabilities to severe COVID-related morbidity and mortality are less likely to report any cases or may be reporting with limited public availability of information. Reporting on COVID detection and response efforts, as well as on trends in non-COVID illness and care-seeking behavior, is critical to assessing direct and indirect consequences and capacity needs in resource-constrained settings. Such assessments aid in the ability to make data-driven decisions about interventions, country priorities, and risk assessment.\n\nKey MessagesO_LIWe line-listed epidemiological indicators for the initial cases reported by 48 countries in sub-Saharan Africa by reviewing and synthesizing information provided by official institutional outlets and news sources.\nC_LIO_LIOur findings suggest that countries with the largest proportions of untreated comorbidities, as measured by probability of premature death due to non-communicable diseases, and the fewest healthcare resources tended to not be reporting any cases at one-month post-introduction into the region.\nC_LIO_LIUsing data availability as a measure of gaps in detection and reporting and relating them to COVID-specific parameters for morbidity and mortality provides a measure of vulnerability.\nC_LIO_LIAccurate and available information on initial cases in seeding local outbreaks is key to projecting case counts and assessing the potential impact of intervention approaches, such that support for local data teams will be important as countries make decisions about control strategies.\nC_LI", - "rel_num_authors": 10, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.01.20050138", + "rel_abs": "BackgroundOur understanding of the corona virus disease 2019 (COVID-19) continues to evolve. However, there are many unknowns about its epidemiology.\n\nPurposeTo synthesize the number of deaths from confirmed COVID-19 cases, incubation period, as well as time from onset of COVID-19 symptoms to first medical visit, ICU admission, recovery and death of COVID-19.\n\nData SourcesMEDLINE, Embase, and Google Scholar from December 01, 2019 through to March 11, 2020 without language restrictions as well as bibliographies of relevant articles.\n\nStudy SelectionQuantitative studies that recruited people living with or died due to COVID-19.\n\nData ExtractionTwo independent reviewers extracted the data. Conflicts were resolved through discussion with a senior author.\n\nData SynthesisOut of 1675 non-duplicate studies identified, 57 were included. Pooled mean incubation period was 5.84 (99% CI: 4.83, 6.85) days. Pooled mean number of days from the onset of COVID-19 symptoms to first clinical visit was 4.82 (95% CI: 3.48, 6.15), ICU admission was 10.48 (95% CI: 9.80, 11.16), recovery was 17.76 (95% CI: 12.64, 22.87), and until death was 15.93 (95% CI: 13.07, 18.79). Pooled probability of COVID-19-related death was 0.02 (95% CI: 0.02, 0.03).\n\nLimitationsStudies are observational and findings are mainly based on studies that recruited patient from clinics and hospitals and so may be biased toward more severe cases.\n\nConclusionWe found that the incubation period and lag between the onset of symptoms and diagnosis of COVID-19 is longer than other respiratory viral infections including MERS and SARS; however, the current policy of 14 days of mandatory quarantine for everyone might be too conservative. Longer quarantine periods might be more justified for extreme cases.\n\nFundingNone.\n\nProtocol registrationOpen Science Framework: https://osf.io/a3k94/", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Laura A Skrip", - "author_inst": "Institute for Disease Modeling" - }, - { - "author_name": "Prashanth Selvaraj", - "author_inst": "Institute for Disease Modeling" - }, - { - "author_name": "Brittany Hagedorn", - "author_inst": "Institute for Disease Modeling" - }, - { - "author_name": "Andre Lin Ou\u00e9draogo", - "author_inst": "Institute for Disease Modeling" - }, - { - "author_name": "Navideh Noori", - "author_inst": "Institute for Disease Modeling" + "author_name": "Malahat Khalili", + "author_inst": "Kerman University of Medical Sciences, Kerman, Iran" }, { - "author_name": "Dina Mistry", - "author_inst": "Institute for Disease Modeling" + "author_name": "Mohammad Karamouzian", + "author_inst": "University of British Columbia, Vancouver, BC, Canada" }, { - "author_name": "Jamie Bedson", - "author_inst": "Consultant to the Bill & Melinda Gates Foundation" + "author_name": "Naser Nasiri", + "author_inst": "Kerman University of Medical Sciences, Kerman, Iran" }, { - "author_name": "Laurent H\u00e9bert-Dufresne", - "author_inst": "University of Vermont" + "author_name": "Sara Javadi", + "author_inst": "Kerman University of Medical Sciences, Kerman, Iran" }, { - "author_name": "Samuel V Scarpino", - "author_inst": "Northeastern University" + "author_name": "Ali Mirzazadeh", + "author_inst": "University of California San Francisco, San Francisco, CA, USA" }, { - "author_name": "Benjamin Muir Althouse", - "author_inst": "Institute for Disease Modeling" + "author_name": "Hamid Sharifi", + "author_inst": "Kerman University of Medical Sciences, Kerman, Iran" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "public and global health" }, @@ -1562411,51 +1561729,35 @@ "category": "biochemistry" }, { - "rel_doi": "10.1101/2020.04.04.025080", - "rel_title": "Computational analysis suggests putative intermediate animal hosts of the SARS-CoV-2", + "rel_doi": "10.1101/2020.04.01.020594", + "rel_title": "A snapshot of SARS-CoV-2 genome availability up to 30th March, 2020 and its implications", "rel_date": "2020-04-05", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.04.04.025080", - "rel_abs": "The recent emerged SARS-CoV-2 may first transmit to intermediate animal host from bats before the spread to humans. The receptor recognition of ACE2 protein by SARS-CoVs or bat-originated coronaviruses is one of the most important determinant factors for the cross-species transmission and human-to-human transmission. To explore the hypothesis of possible intermediate animal host, we employed molecular dynamics simulation and free energy calculation to examine the binding of bat coronavirus with ACE2 proteins of 47 representing animal species collected from public databases. Our results suggest that intermediate animal host may exist for the zoonotic transmission of SARS-CoV-2. Furthermore, we found that tree shrew and ferret may be two putative intermediate hosts for the zoonotic spread of SARS-CoV-2. Collectively, the continuous surveillance of pneumonia in human and suspicious animal hosts are crucial to control the zoonotic transmission events caused by SARS-CoV-2.", - "rel_num_authors": 8, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.04.01.020594", + "rel_abs": "The SARS-CoV-2 pandemic has been growing exponentially, affecting nearly 900 thousand people and causing enormous distress to economies and societies worldwide. A plethora of analyses based on viral sequences has already been published, in scientific journals as well as through non-peer reviewed channels, to investigate SARS-CoV-2 genetic heterogeneity and spatiotemporal dissemination. We examined full genome sequences currently available to assess the presence of sufficient information for reliable phylogenetic and phylogeographic studies in countries with the highest toll of confirmed cases. Although number of-available full-genomes is growing daily, and the full dataset contains sufficient phylogenetic information that would allow reliable inference of phylogenetic relationships, country-specific SARS-CoV-2 datasets still present severe limitations. Studies assessing within country spread or transmission clusters should be considered preliminary at best, or hypothesis generating. Hence the need for continuing concerted efforts to increase number and quality of the sequences required for robust tracing of the epidemic.\n\nSignificance StatementAlthough genome sequences of SARS-CoV-2 are growing daily and contain sufficient phylogenetic information, country-specific data still present severe limitations and should be interpreted with caution.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Peng Chu", - "author_inst": "Dalian Medical University" - }, - { - "author_name": "Zheng Zhou", - "author_inst": "Dalian Medical University" - }, - { - "author_name": "Zhichen Gao", - "author_inst": "Dalian University of Technology" - }, - { - "author_name": "Ruiqi Cai", - "author_inst": "Dalian University of Technology" - }, - { - "author_name": "Sijin Wu", - "author_inst": "Ohio State University" + "author_name": "Carla Mavian", + "author_inst": "University of Florida" }, { - "author_name": "Zhaolin Sun", - "author_inst": "Dalian Medical University" + "author_name": "Simone Marini", + "author_inst": "University of Florida" }, { - "author_name": "Shuyuan Chen", - "author_inst": "University of Melbourne" + "author_name": "Mattia Prosperi", + "author_inst": "University of Florida" }, { - "author_name": "Yongliang Yang", - "author_inst": "Dalian University of Technology" + "author_name": "Marco Salemi", + "author_inst": "University of Florida" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "new results", - "category": "bioinformatics" + "category": "evolutionary biology" }, { "rel_doi": "10.1101/2020.04.03.023887", @@ -1563925,21 +1563227,25 @@ "category": "bioinformatics" }, { - "rel_doi": "10.1101/2020.04.01.020941", - "rel_title": "The Spike Protein S1 Subunit of SARS-CoV-2 Contains an LxxIxE-like Motif that is Known to Recruit the Host PP2A-B56 Phosphatase", + "rel_doi": "10.1101/2020.03.31.017459", + "rel_title": "In silico approach for designing of a multi-epitope based vaccine against novel Coronavirus (SARS-COV-2)", "rel_date": "2020-04-03", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.04.01.020941", - "rel_abs": "SARS-CoV-2 is highly contagious and can cause acute respiratory distress syndrome (ARDS) and multiple organ failure that are largely attributed to the cytokine storm. The surface coronavirus spike (S) glycoprotein is considered as a key factor in host specificity because it mediates infection by receptor-recognition and membrane fusion. Here, the analysis of SARS-CoV-2 S protein revealed two B56-binding LxxIxE-like motifs in S1 and S2 subunits that could recruit the host protein phosphatase 2A (PP2A). The motif in S1 subunit is absent in SARS-CoV and MERS-CoV. Phosphatases and kinases are major players in the regulation of pro-inflammatory responses during pathogenic infections. Moreover, studies have shown that viruses target PP2A in order to manipulate hosts antiviral responses. Recent researches have indicated that SARS-CoV-2 is involved in sustained host inflammation. Therefore, by controlling acute inflammation, it is possible to eliminate its dangerous effects on the host. Among efforts to fight COVID-19, the interaction between LxxIxE-like motif and the PP2A-B56-binding pocket could be a target for the discovery and/or development of a bioactive ligand inhibitor for therapeutic purposes. Indeed, a small molecule called Artepillin C (ArtC), a main compound in Brazilian honeybee green propolis, mimics the side chains of LxxLxE motif. Importantly, ArtC is known, among other effects, to have anti-inflammatory activity that makes it an excellent candidate for future clinical trials in COVID-19 patients.", - "rel_num_authors": 1, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.03.31.017459", + "rel_abs": "A novel Coronavirus (SARS-COV-2) has now become a global pandemic. Considering the severity of infection and the associated mortalities, there is an urgent need to develop an effective preventive measure against this virus. In this study, we have designed a novel vaccine construct using computational strategies. Spike (S) glycoprotein is the major antigenic component that trigger the host immune responses. Detailed investigation of S protein with various immunoinformatics tools enabled us to identify 5 MHC I and 5 MHC II B-cell derived T-cell epitopes with VaxiJen score > 1 and IC50 value < 100nM. These epitopes were joined with a suitable adjuvant and appropriate linkers to form a multi-epitope based vaccine construct. Further, in silico testing of the vaccine construct for its antigenicity, allergenicity, solubility, and other physicochemical properties showed it to be safe and immunogenic. Suitable tertiary structure of the vaccine protein was generated using 3Dpro of SCRATCH suite, refined with GalaxyRefine, and validated with ProSA, PROCHECK, and ERRAT server. Finally, molecular docking studies were performed to ensure a favorable binding affinity between the vaccine construct and TLR3 receptor. The designed multi-epitope vaccine showed potential to elicit specific immune responses against the SARS-COV-2. However, further wet lab validation is necessary to confirm the actual effectiveness, safety and immunogenic potency of the vaccine construct against derived in this study.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Halim Maaroufi", - "author_inst": "Institut de Biologie Int\u00e9grative et des Syst\u00e8mes (IBIS) Universit\u00e9 Laval, Quebec, Canada" + "author_name": "Ratnadeep Saha", + "author_inst": "Central Institute of Fisheries Education" + }, + { + "author_name": "Burra VLS Prasad", + "author_inst": "Koneru Lakshmaiah University, Guntur, India" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "new results", "category": "bioinformatics" }, @@ -1565067,25 +1564373,41 @@ "category": "endocrinology" }, { - "rel_doi": "10.1101/2020.03.30.20048009", - "rel_title": "Flattening the curve is not enough, we need to squash it. An explainer using a simple model", + "rel_doi": "10.1101/2020.03.31.20048595", + "rel_title": "Ambient nitrogen dioxide pollution and spread ability of COVID-19 in Chinese cities", "rel_date": "2020-04-02", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.30.20048009", - "rel_abs": "BackgroundAround the world there are examples of both effective control (e.g., South Korea, Japan) and less successful control (e.g., Italy, Spain, United States) of COVID-19 with dramatic differences in the consequent epidemic curves. Models agree that flattening the curve without controlling the epidemic completely is insufficient and will lead to an overwhelmed health service. A recent model, calibrated for the UK and US, demonstrated this starkly.\n\nMethodsWe used a simple compartmental deterministic model of COVID-19 transmission in Australia, to illustrate the dynamics resulting from shifting or flattening the curve versus completely squashing it.\n\nResultsWe find that when the reproduction number is close to one, a small decrease in transmission leads to a large reduction in burden (i.e., cases, deaths and hospitalisations), but achieving this early in the epidemic through social distancing interventions also implies that the community will not reach herd immunity.\n\nConclusionsAustralia needs not just to shift and flatten the curve, but to squash it by getting the reproduction number below one. This will require Australia to achieve transmission rates at least two thirds lower than those seen in the most severely affected countries.\n\nThe knownCOVID-19 has been diagnosed in over 4,000 Australians. Up until mid-March, most were from international travel, but now we are seeing a rise in locally acquired cases.\n\nThe newThis study uses a simple transmission dynamic model to demonstrate the difference between moderate changes to the reproduction number and forcing the reproduction number below one.\n\nThe implicationsLowering local transmission is becoming important in reducing the transmission of COVID-19. To maintain control of the epidemic, the focus should be on those in the community who do not regard themselves as at risk.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.31.20048595", + "rel_abs": "The Coronavirus (COVID-19) epidemic, which was first reported in December 2019 in Wuhan, China, has caused 219,331 confirmed cases as of 20 March 2020, with 81,301 cases being reported in China. It has been declared a pandemic by the World Health Organization in 11 March 2020 (1). Although massive intervention measures have been implemented in China (e.g. shutting down cities, extending holidays and travel ban) and many other countries, the spread of the disease are unlikely to be stopped over the world shortly. It is becoming evident that environmental factors are associated with seasonality of respiratory-borne diseases epidemics (2). Previous studies have suggested that ambient nitrogen dioxide (NO2) exposure may play a role in the phenotypes of respiratory diseases, including, but not limited to, influenza, asthma and severe acute respiratory syndrome (SARS). NO2), for example, might increase the susceptibility of adults to virus infections (3). High exposure to NO2 before the start of a respiratory viral infection is associated with the severity of asthma exacerbation (4). This study aims to assess the associations of ambient NO2 levels with spread ability of COVID-19 across 63 Chinese cities, and provides information for the further prevention and control of COVID-19.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Emma S McBryde", - "author_inst": "James Cook University" + "author_name": "Ye Yao", + "author_inst": "Department of Biostatics, School of Public Health, Fudan University, Shanghai 200032, China" }, { - "author_name": "Michael T Meehan", - "author_inst": "James Cook University" + "author_name": "Jinhua Pan", + "author_inst": "Department of Epidemiology, School of Public Health, Fudan University, Shanghai 200032, China" }, { - "author_name": "James M Trauer", - "author_inst": "Monash University" + "author_name": "Zhixi Liu", + "author_inst": "Department of Epidemiology, School of Public Health, Fudan University, Shanghai 200032, China" + }, + { + "author_name": "Xia Meng", + "author_inst": "Department of Environmental Health, School of Public Health, Fudan University, Shanghai 200032, China" + }, + { + "author_name": "Weidong Wang", + "author_inst": "Department of Environmental Health, School of Public Health, Fudan University, Shanghai 200032, China" + }, + { + "author_name": "Haidong Kan", + "author_inst": "Department of Environmental Health, School of Public Health, Fudan University, Shanghai 200032, China" + }, + { + "author_name": "Weibing Wang", + "author_inst": "Department of Epidemiology, School of Public Health, Fudan University, Shanghai 200032, China" } ], "version": "1", @@ -1566217,21 +1565539,29 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.03.30.20048132", - "rel_title": "Optimal timing for social distancing during an epidemic", + "rel_doi": "10.1101/2020.03.30.20047472", + "rel_title": "COVID-19 Epidemic in Switzerland: Growth Prediction and Containment Strategy Using Artificial Intelligence and Big Data", "rel_date": "2020-04-01", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.30.20048132", - "rel_abs": "Social distancing is an effective way to contain the spread of a contagious disease, particularly when facing a novel pathogen and no pharmacological interventions are available. In such cases, conventional wisdom suggests that social distancing measures should be introduced as soon as possible after the beginning of an outbreak to more effectively mitigate the spread of the disease. Using a simple epidemiological model we show that, however, there is in fact an optimal time to initiate a temporal social distancing intervention if the goal is to reduce the final epidemic size or \"flatten\" the epidemic curve. The optimal timing depends strongly on the effective reproduction number (R0) of the disease, such that as the R0 increases, the optimal time decreases non-linearly. Additionally, if pharmacological interventions (e.g., a vaccine) become available at some point during the epidemic, the sooner these interventions become available the sooner social distancing should be initiated to maximize its effectiveness. Although based on a simple model, we hope that these insights inspire further investigations within the context of more complex and data-driven epidemiological models, and can ultimately help decision makers to improve temporal social distancing policies to mitigate the spread of epidemics.", - "rel_num_authors": 1, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.30.20047472", + "rel_abs": "Using a previously developed agent-based artificial intelligence simulation platform (EnerPol) coupled with Big Data, the evolution and containment of COVID-19 in Switzerland is examined. The EnerPol platform has been used in a broad range of case studies in different sectors in all of Europe, USA, Japan, South Korea and sub Saharan Africa over the last 10 years. In the present study, the entire Swiss population (8.57 million people), including cross-border commuters, and the entire Swiss public and private transport network that is simulated to assess transmission of the COVID-19 virus. The individual contacts within the population, and possible transmission pathways, are established from a simulation of daily activities that are calibrated with micro-census data. Various governmental interventions with regards to closures and social distancing are also implemented. The epidemiology of the COVID-19 virus is based on publicly available statistical data and adapted to Swiss demographics. The predictions estimate that between 22 February and 11 April 2020, there will be 720 deaths from 83300 COVID-19 cases, and 73300 will have recovered; our preliminary variability in these estimates is about 21% over the aforementioned period. In the absence of governmental intervention, 42.7% of the Swiss population would have been infected by 25 April 2020 compared to our prediction of a 1% infection over this time period, saving thousands of lives. It is argued that future scenarios regarding relaxation of the lockdown should be carefully simulated, as by 19 April 2020, there will still remain a substantial number of infected individuals, who could retrigger a second spread of COVID-19. Through the use of a digital tool, such as Enerpol, to evaluate in a data-driven manner the impacts of various policy scenarios, the most effective measures to mitigate a spread of COVID-19 can be devised while we await the deployment of large-scale vaccination for the population globally. By tailoring the spatio-temporal characteristics of the spread to match the capacity of local healthcare facilities, appropriate logistic needs can be determined, in order not to overwhelm the health care services across the country.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Oscar Patterson-Lomba", - "author_inst": "Analysis Group" + "author_name": "Reza S. Abhari", + "author_inst": "ETH Zurich" + }, + { + "author_name": "Marcello Marini", + "author_inst": "ETH Zurich" + }, + { + "author_name": "Ndaona Chokani", + "author_inst": "ETH Zurich" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1567375,39 +1566705,23 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.03.30.20046326", - "rel_title": "Pandemic Politics: Timing State-Level Social Distancing Responses to COVID-19", + "rel_doi": "10.1101/2020.03.28.20036715", + "rel_title": "The first three months of the COVID-19 epidemic: Epidemiological evidence for two separate strains of SARS-CoV-2 viruses spreading and implications for prevention strategies", "rel_date": "2020-03-31", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.30.20046326", - "rel_abs": "Social distancing policies are critical but economically painful measures to flatten the curve against emergent infectious diseases. As the novel coronavirus that causes COVID-19 spread throughout the United States in early 2020, the federal government issued social distancing recommendations but left to the states the most difficult and consequential decisions restricting behavior, such as canceling events, closing schools and businesses, and issuing stay-at-home orders. We present an original dataset of state-level social distancing policy responses to the epidemic and explore how political partisanship, COVID-19 caseload, and policy diffusion explain the timing of governors decisions to mandate social distancing. An event history analysis of five social distancing policies across all fifty states reveals the most important predictors are political: all else equal, Republican governors and governors from states with more Trump supporters were slower to adopt social distancing policies. These delays are likely to produce significant, on-going harm to public health.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.28.20036715", + "rel_abs": "About one month after the COVID-19 epidemic peaked in Mainland China and SARS-CoV-2 migrated to Europe and then the U.S., the epidemiological data begin to provide important insights into the risks associated with the disease and the effectiveness of intervention strategies such as travel restrictions and lockdowns (\"social distancing\"). Respiratory diseases, including the 2003 SARS epidemic, remain only about two months in any given population, although peak incidence and lethality can vary. The epidemiological data suggest that at least two strains of the 2020 SARS-CoV-2 virus have evolved during its migration from Mainland China to Europe. South Korea, Iran, Italy, and Italys neighbors were hit by the more dangerous \"SKII\" variant. While the epidemic in continental Asia is about to end, and in Europe about to level off, the more recent epidemic in the younger US population is still increasing, albeit not exponentially anymore. The peak level will likely depend on which of the strains has entered the U.S. first. The same models that help us to understand the epidemic also help us to choose prevention strategies. Containment of high-risk people, like the elderly, and reducing disease severity, either by vaccination or by early treatment of complications, is the best strategy against a respiratory virus disease. Lockdowns can be effective during the month following the peak incidence in infections, when the exponential increase of cases ends. Earlier containment of low-risk people merely prolongs the time the virus needs to circulate until the incidence is high enough to initiate \"herd immunity\". Later containment is not helpful, unless to prevent a rebound if containment started too early.\n\nAbout the AuthorDr. Wittkowski received his PhD in computer science from the University of Stuttgart and his ScD (Habilitation) in Medical Biometry from the Eberhard-Karls-University Tubingen, both Germany. He worked for 15 years with Klaus Dietz, a leading epidemiologist who coined the term \"reproduction number\", on the Epidemiology of HIV before heading for 20 years the Department of Biostatistics, Epidemiology, and Research Design at The Rockefeller University, New York. Dr. Wittkowski is currently the CEO of ASDERA LLC, a company discovering novel interventions against complex (incl. coronavirus) diseases from data of genome-wide association studies.", + "rel_num_authors": 1, "rel_authors": [ { - "author_name": "Christopher Adolph", - "author_inst": "University of Washington" - }, - { - "author_name": "Kenya Amano", - "author_inst": "University of Washington" - }, - { - "author_name": "Bree Bang-Jensen", - "author_inst": "University of Washington" - }, - { - "author_name": "Nancy Fullman", - "author_inst": "University of Washington" - }, - { - "author_name": "John Wilkerson", - "author_inst": "University of Washington" + "author_name": "Knut M. Wittkowski", + "author_inst": "ASDERA LLC" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "health policy" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2020.03.30.20043513", @@ -1568684,95 +1567998,59 @@ "category": "bioinformatics" }, { - "rel_doi": "10.1101/2020.03.30.015461", - "rel_title": "Potent neutralizing antibodies in the sera of convalescent COVID-19 patients are directed against conserved linear epitopes on the SARS-CoV-2 spike protein", + "rel_doi": "10.1101/2020.03.30.015164", + "rel_title": "Epitope-based chimeric peptide vaccine design against S, M and E proteins of SARS-CoV-2 etiologic agent of global pandemic COVID-19: an in silico approach", "rel_date": "2020-03-31", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.03.30.015461", - "rel_abs": "The ongoing SARS-CoV-2 pandemic demands rapid identification of immunogenic targets for the design of efficient vaccines and serological detection tools. In this report, using pools of overlapping linear peptides and functional assays, we present two immunodominant regions on the spike glycoprotein that were highly recognized by neutralizing antibodies in the sera of COVID-19 convalescent patients. One is highly specific to SARS-CoV-2, and the other is a potential pan-coronavirus target.", - "rel_num_authors": 19, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.03.30.015164", + "rel_abs": "Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the cause of the ongoing pandemic of coronavirus disease 2019 (COVID-19), a public health emergency of international concern declared by the World Health Organization (WHO). An immuno-informatics approach along with comparative genomic was applied to design a multi-epitope-based peptide vaccine against SARS-CoV-2 combining the antigenic epitopes of the S, M and E proteins. The tertiary structure was predicted, refined and validated using advanced bioinformatics tools. The candidate vaccine showed an average of [≥] 90.0% world population coverage for different ethnic groups. Molecular docking of the chimeric vaccine peptide with the immune receptors (TLR3 and TLR4) predicted efficient binding. Immune simulation predicted significant primary immune response with increased IgM and secondary immune response with high levels of both IgG1 and IgG2. It also increased the proliferation of T-helper cells and cytotoxic T-cells along with the increased INF-{gamma} and IL-2 cytokines. The codon optimization and mRNA secondary structure prediction revealed the chimera is suitable for high-level expression and cloning. Overall, the constructed recombinant chimeric vaccine candidate demonstrated significant potential and can be considered for clinical validation to fight against this global threat, COVID-19.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Chek Meng Poh", - "author_inst": "Singapore Immunology Network, Agency of Science, Technology and Research, Immunos, Biopolis, Singapore" - }, - { - "author_name": "Guillaume Carissimo", - "author_inst": "Singapore Immunology Network" - }, - { - "author_name": "Wang Bei", - "author_inst": "Singapore Immunology Network" - }, - { - "author_name": "Siti Naqiah Amrun", - "author_inst": "Singapore Immunology Network" - }, - { - "author_name": "Cheryl Yi-Pin Lee", - "author_inst": "Singapore Immunology Network" - }, - { - "author_name": "Rhonda Sin-Ling Chee", - "author_inst": "Singapore Immunology Network" - }, - { - "author_name": "Nicholas Kim-Wah Yeo", - "author_inst": "Singapore Immunology Network" - }, - { - "author_name": "Wen-Hsin Lee", - "author_inst": "Singapore Immunology Network" - }, - { - "author_name": "Yee-Sin Leo", - "author_inst": "National Centre for Infectious Diseases, Singapore" - }, - { - "author_name": "Mark I-Cheng Chen", - "author_inst": "National Centre for Infectious Diseases, Singapore" + "author_name": "M. Shaminur Rahman", + "author_inst": "Department of Microbiology, University of Dhaka" }, { - "author_name": "Seow-Yen Tan", - "author_inst": "Department of Infectious Diseases, Changi General Hospital, Singapore" + "author_name": "M. Nazmul Hoque", + "author_inst": "Bangabandhu Sheikh Mujibur Rahman Agricultural University Gazipur-1706, Bangladesh" }, { - "author_name": "Louis Yi Ann Chai", - "author_inst": "Department of Infectious Diseases, Tan Tock Seng Hospital, Singapore" + "author_name": "M. Rafiul Islam", + "author_inst": "Department of Microbiology, University of Dhaka" }, { - "author_name": "Shirin Kalimuddin", - "author_inst": "Department of Infectious Diseases, Singapore General Hospital, Singapore" + "author_name": "Salma Akter", + "author_inst": "Department of Microbiology, University of Dhaka" }, { - "author_name": "Siew-Yee Thien", - "author_inst": "Department of Infectious Diseases, Singapore General Hospital, Singapore" + "author_name": "A. S. M. Rubayet-Ul-Alam", + "author_inst": "Department of Microbiology, Jashore University of Science and Technology, Jashore 7408, Bangladesh" }, { - "author_name": "Barnaby Edward Young", - "author_inst": "National Centre for Infectious Diseases, Singapore" + "author_name": "Mohammad Anwar Siddique", + "author_inst": "Department of Microbiology, University of Dhaka" }, { - "author_name": "David C. Lye", - "author_inst": "National Centre for Infectious Diseases, Singapore" + "author_name": "Otun Saha", + "author_inst": "Department of Microbiology, University of Dhaka" }, { - "author_name": "Cheng-I Wang", - "author_inst": "Singapore Immunology Network" + "author_name": "Md. Mizanur Rahaman", + "author_inst": "Department of Microbiology, University of Dhaka" }, { - "author_name": "Laurent Renia", - "author_inst": "Singapore Immunology Network" + "author_name": "Munawar Sultana", + "author_inst": "Department of Microbiology, University of Dhaka" }, { - "author_name": "Lisa FP Ng", - "author_inst": "Singapore Immunology Network" + "author_name": "M. Anwar Hossain", + "author_inst": "Department of Microbiology, University of Dhaka" } ], "version": "1", - "license": "cc_no", + "license": "cc_by", "type": "new results", - "category": "immunology" + "category": "microbiology" }, { "rel_doi": "10.1101/2020.03.30.015891", @@ -1570250,55 +1569528,55 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.03.27.20045203", - "rel_title": "Triage assessment of cardiorespiratory risk status based on measurement of the anaerobic threshold, and estimation by patient-reported activity limitation", + "rel_doi": "10.1101/2020.03.27.20045195", + "rel_title": "A mathematical model of COVID-19 transmission between frontliners and the general public", "rel_date": "2020-03-30", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.27.20045203", - "rel_abs": "BO_SCPLOWACKGROUNDC_SCPLOWRapid triaging, as in the current COVID-19 pandemic, focuses on age and pre-existing medical conditions. In contrast, preoperative assessments use cardiopulmonary exercise testing (CPET) to categorise patients to higher and lower risk independent of diagnostic labels. Since CPET is not feasible in population-based settings, our aims included evaluation of a triage/screening tool for cardiorespiratory risk.\n\nMO_SCPLOWETHODSC_SCPLOWCPET-derived anaerobic thresholds were evaluated retrospectively in 26 patients with pulmonary arteriovenous malformations (AVMs) who represent a challenging group to risk-categorise. Pulmonary AVM-induced hypoxaemia secondary to intrapulmonary right-to-left shunts, anaemia from underlying hereditary haemorrhagic telangiectasia and metabolic equivalents derived from the 13-point Veterans Specific Activity Questionnaire (VSAQ) were evaluated as part of routine clinical care. Pre-planned analyses evaluated associations and modelling of the anaerobic threshold and patient-specific variables.\n\nRO_SCPLOWESULTSC_SCPLOWIn the 26 patients (aged 21-77, median 57 years), anaerobic threshold ranged from 7.6-24.5 (median 12.35) ml.min-1kg-1 and placed more than half of the patients (15, 57.7%) in the >11 ml.min-1kg-1 category suggested as \"lower-risk\" for intra-abdominal surgeries. Neither age nor baseline SpO2 predicted anaerobic threshold, or lower/higher risk categories, either alone or in multivariate analyses, despite baseline oxygen saturation (SpO2) ranging from 79 to 99 (median 92)%, haemoglobin from 108 to 183 (median 156)g.L-1. However, lower haemoglobin, and particularly, arterial oxygen content and oxygen pulse were associated with increased cardiorespiratory risk: Modelling a haemoglobin increase of 25g.L-1 placed a further 7/26 (26.9%) patients in a lower risk category. For patients completing the VSAQ, derived metabolic equivalents were strongly associated with anaerobic threshold enabling risk evaluations through a simple questionnaire.\n\nCO_SCPLOWONCLUSIONSC_SCPLOWBaseline exercise tolerance may override age and diagnostic labels in triage settings. These data support approaches to risk reduction by aerobic conditioning and attention to anaemia. The VSAQ is suggested as a rapid screening tool for cardiorespiratory risk assessment to implement during triage/screening.\n\nKey Messages\n\nWhat is already knownO_LIAlongside age, pre-existing medical conditions are perceived negatively during triage assessments, particularly if rare, and/or theoretically expected to influence cardiorespiratory risk;\nC_LIO_LIAnaesthetists use cardiopulmonary exercise testing to categorise patients to higher and lower risk independently to diagnostic labels, but this is not feasible in acute settings;\nC_LIO_LIPulmonary arteriovenous malformations are an exemplar of a condition where, due to expected or measured abnormalities (hypoxaemia-low PaO2 SpO2), poor physiological capacity might be predicted.\nC_LI\n\nWhat this study addsO_LINeither age nor usual SpO2 predicted lower/higher risk categories by anaerobic threshold, but haemoglobin-dependent indices of oxygen delivery to the tissues were associated with higher risk, offering opportunities for improvement by attention to anaemia and aerobic conditioning;\nC_LIO_LIBaseline exercise tolerance may override age and diagnostic labels in triage settings: the 13-point VSAQ Veterans Specific Activity Questionnaire (VSAQ) is suggested as a rapid screening tool for cardiorespiratory risk assessment.\nC_LI", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.27.20045195", + "rel_abs": "The number of COVID-19 cases is continuously increasing in different countries (as of March 2020) including the Philippines. It is estimated that the basic reproductive number of COVID-19 is around 1.5 to 4. The basic reproductive number characterizes the average number of persons that a primary case can directly infect in a population full of susceptible individuals. However, there can be superspreaders that can infect more than this estimated basic reproductive number. In this study, we formulate a conceptual mathematical model on the transmission dynamics of COVID-19 between the frontliners and the general public. We assume that the general public has a reproductive number between 1.5 to 4, and frontliners (e.g. healthcare workers, customer service and retail personnel, food service crews, and transport or delivery workers) have a higher reproduction number. Our simulations show that both the frontliners and the general public should be protected or resilient against the disease. Protecting only the frontliners will not result in flattening the epidemic curve. Protecting only the general public may flatten the epidemic curve but the infection risk faced by the frontliners is still high, which may eventually affect their work. Our simple model does not consider all factors involved in COVID-19 transmission in a community, but the insights from our model results remind us of the importance of community effort in controlling the transmission of the disease. All in all, the take-home message is that everyone in the community, whether a frontliner or not, should be protected or should implement preventive measures to avoid being infected.", "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Saranya Thurairatnam", - "author_inst": "Imperial College London" + "author_name": "Christian Alvin H Buhat", + "author_inst": "University of the Philippines Los Banos" }, { - "author_name": "Filip Gawecki", - "author_inst": "Imprial College London" + "author_name": "Monica C Torres", + "author_inst": "University of the Philippines Los Banos" }, { - "author_name": "Timothy Strangeways", - "author_inst": "Imperial College London" + "author_name": "Yancee H Olave", + "author_inst": "University of the Philippines Los Banos" }, { - "author_name": "Joseph Perks", - "author_inst": "Imperial College Healthcare NHS Trust" + "author_name": "Maica Krizna A Gavina", + "author_inst": "University of the Philippines Los Banos" }, { - "author_name": "Vatshalan Santhirapala", - "author_inst": "Imperial College London" + "author_name": "Edd Francis O Felix", + "author_inst": "University of the Philippines Los Banos" }, { - "author_name": "Jonathan Myers", - "author_inst": "Palo Alto Health Care System and Stanford University" + "author_name": "Gimelle B Gamilla", + "author_inst": "University of the Philippines Los Banos" }, { - "author_name": "Hannah C Tighe", - "author_inst": "Imperial College Healthcare NHS Trust" + "author_name": "Kyrell Vann B Verano", + "author_inst": "University of the Philippines Los Banos" }, { - "author_name": "Luke SGE Howard", - "author_inst": "Imperial College Healthcare NHS Trust" + "author_name": "Ariel L Babierra", + "author_inst": "University of the Philippines Los Banos" }, { - "author_name": "Claire L Shovlin", - "author_inst": "Imperial College London" + "author_name": "Jomar Fajardo Rabajante", + "author_inst": "University of the Philippines Los Banos" } ], "version": "1", "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "emergency medicine" + "category": "epidemiology" }, { "rel_doi": "10.1101/2020.03.27.20045500", @@ -1571540,25 +1570818,49 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.03.26.20044693", - "rel_title": "Why estimating population-based case fatality rates during epidemics may be misleading", + "rel_doi": "10.1101/2020.03.22.20040758", + "rel_title": "Efficacy of hydroxychloroquine in patients with COVID-19: results of a randomized clinical trial", "rel_date": "2020-03-30", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.26.20044693", - "rel_abs": "Different ways of calculating mortality ratios during epidemics can yield widely different results, particularly during the COVID-19 pandemic. We formulate both a survival probability model and an associated infection duration-dependent SIR model to define individual- and population-based estimates of dynamic mortality ratios. The key parameters that affect the dynamics of the different mortality estimates are the incubation period and the length of time individuals were infected before confirmation of infection. We stress that none of these ratios are accurately represented by the often misinterpreted case fatality ratio (CFR), the number of deaths to date divided by the total number of infected cases to date. Using available data on the recent SARS-CoV-2 outbreaks and simple assumptions, we estimate and compare the different dynamic mortality ratios and highlight their differences. Informed by our modeling, we propose a more systematic method to determine mortality ratios during epidemic outbreaks and discuss sensitivity to confounding effects and errors in the data.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.22.20040758", + "rel_abs": "AimsStudies have indicated that chloroquine (CQ) shows antagonism against COVID-19 in vitro. However, evidence regarding its effects in patients is limited. This study aims to evaluate the efficacy of hydroxychloroquine (HCQ) in the treatment of patients with COVID-19.\n\nMain methodsFrom February 4 to February 28, 2020, 62 patients suffering from COVID-19 were diagnosed and admitted to Renmin Hospital of Wuhan University. All participants were randomized in a parallel-group trial, 31 patients were assigned to receive an additional 5-day HCQ (400 mg/d) treatment, Time to clinical recovery (TTCR), clinical characteristics, and radiological results were assessed at baseline and 5 days after treatment to evaluate the effect of HCQ.\n\nKey findingsFor the 62 COVID-19 patients, 46.8% (29 of 62) were male and 53.2% (33 of 62) were female, the mean age was 44.7 (15.3) years. No difference in the age and sex distribution between the control group and the HCQ group. But for TTCR, the body temperature recovery time and the cough remission time were significantly shortened in the HCQ treatment group. Besides, a larger proportion of patients with improved pneumonia in the HCQ treatment group (80.6%, 25 of 31) compared with the control group (54.8%, 17 of 31). Notably, all 4 patients progressed to severe illness that occurred in the control group. However, there were 2 patients with mild adverse reactions in the HCQ treatment group. Significance: Among patients with COVID-19, the use of HCQ could significantly shorten TTCR and promote the absorption of pneumonia.\n\nSignificanceAmong patients with COVID-19, the use of HCQ could significantly shorten TTCR and promote the absorption of pneumonia.\n\nTrial registrationURL: https://www.clinicaltrials.gov/. The unique identifier: ChiCTR2000029559.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Lucas B\u00f6ttcher", - "author_inst": "UCLA" + "author_name": "Zhaowei Chen", + "author_inst": "Renmin Hospital of Wuhan University" }, { - "author_name": "Mingtao Xia", - "author_inst": "UCLA" + "author_name": "Jijia Hu", + "author_inst": "Renmin hospital of Wuhan University" }, { - "author_name": "Tom Chou", - "author_inst": "UCLA" + "author_name": "Zongwei Zhang", + "author_inst": "Renmin Hospital of Wuhan University" + }, + { + "author_name": "Shan Jiang", + "author_inst": "Renmin Hospital of Wuhan University" + }, + { + "author_name": "Shoumeng Han", + "author_inst": "Renmin Hospital of Wuhan University," + }, + { + "author_name": "Dandan Yan", + "author_inst": "Renmin Hospital of Wuhan University" + }, + { + "author_name": "Ruhong Zhuang", + "author_inst": "Renmin Hospital of Wuhan University" + }, + { + "author_name": "Ben Hu", + "author_inst": "Wuhan Institute of Virology" + }, + { + "author_name": "Zhan Zhang", + "author_inst": "Renmin Hospital of Wuhan University" } ], "version": "1", @@ -1572810,21 +1572112,29 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.03.26.20044271", - "rel_title": "Negligible Risk of the COVID-19 Resurgence Caused by Work Resuming in China (outside Hubei): a Statistical Probability Study", + "rel_doi": "10.1101/2020.03.25.20043315", + "rel_title": "Analysis of the scientific literature in the first 30 Days of the novel coronavirus outbreak.", "rel_date": "2020-03-30", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.26.20044271", - "rel_abs": "The COVID-19 outbreak in China appears to reach the late stage since late February 2020, and a stepwise restoration of economic operations is implemented. Risk assessment for such economic restoration is of significance. Here we estimated the probability of COVID-19 resurgence caused by work resuming in typical provinces/cities, and found that such probability is very limited (<5% for all the regions except Beijing). Our work may inform provincial governments to make risk level-based, differentiated control measures.", - "rel_num_authors": 1, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.25.20043315", + "rel_abs": "IntroductionRecent events highlight how emerging and re-emerging pathogens are becoming global challenges for public health. In December 2019, a novel coronavirus has emerged. This has suddenly turned out into global health concern.\n\nObjectivesAim of this research is to focus on the bibliometric aspects in order to measure what is published in the first 30-days of a global epidemic outbreak\n\nMethodsWe searched PubMed database in order to find all relevant studies in the first 30-days from the first publication.\n\nResultsFrom the initial 442 identified articles, 234 were read in-extenso. The majority of papers come from China, UK and USA. 63.7% of the papers were commentaries, editorials and reported data and only 17.5% of the sources used data directly collected on the field. Topics mainly addressed were \"epidemiology\", \"preparedness\" and \"generic discussion\". NNR showed a reduction for both the objectives assessed from January to February.\n\nConclusions\"Diagnosis\" and effective preventive and therapeutic measures were the fields in which more research is still needed. The vast majority of scientific literature in the first 30-days of an epidemic outbreak is based on reported data rather than primary data. Nevertheless, the scientific statements and public health decisions rely on these data.\n\nStrengths of our studyThis is the first bibliometric research in Pubmed Database on the first 30 days of publications regarding the novel Coronavirus (SARS-nCoV-2) outbreak of 2019.\n\nThe vast majority of publication in the first 30-days of an epidemic outbreak are reported data or comments, and only a small fraction of the papers have directly collected data.\n\nLimitations of our studyOur research is only PubMed based. It ill be auspicable to consult more than one relevant database in future papers.\n\nIn addition, we excluded non-English publications leading to a potential bias due to the fact that the outbreak started in China.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "XINMIAO FU", - "author_inst": "Fujian Normal University" + "author_name": "DAVIDE GORI", + "author_inst": "University of Bologna" + }, + { + "author_name": "Erik Boetto", + "author_inst": "University of Bologna" + }, + { + "author_name": "Maria Pia Fantini", + "author_inst": "University of Bologna" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1574108,27 +1573418,43 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2020.03.25.008904", - "rel_title": "Modeling of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Proteins by Machine Learning and Physics-Based Refinement", + "rel_doi": "10.1101/2020.03.27.009480", + "rel_title": "SARS-CoV-2 exhibits intra-host genomic plasticity and low-frequency polymorphic quasispecies", "rel_date": "2020-03-28", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.03.25.008904", - "rel_abs": "Protein structures are crucial for understanding their biological activities. Since the outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), there is an urgent need to understand the biological behavior of the virus and provide a basis for developing effective therapies. Since the proteome of the virus was determined, some of the protein structures could be determined experimentally, and others were predicted via template-based modeling approaches. However, tertiary structures for several proteins are still not available from experiment nor they could be accurately predicted by template-based modeling because of lack of close homolog structures. Previous efforts to predict structures for these proteins include efforts by DeepMind and the Zhang group via machine learning-based structure prediction methods, i.e. AlphaFold and C-I-TASSER. However, the predicted models vary greatly and have not yet been subjected to refinement. Here, we are reporting new predictions from our in-house structure prediction pipeline. The pipeline takes advantage of inter-residue contact predictions from trRosetta, a machine learning-based method. The predicted models were further improved by applying molecular dynamics simulation-based refinement. We also took the AlphaFold models and refined them by applying the same refinement method. Models based on our structure prediction pipeline and the refined AlphaFold models were analyzed and compared with the C-I-TASSER models. All of our models are available at https://github.com/feiglab/sars-cov-2-proteins.", - "rel_num_authors": 2, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.03.27.009480", + "rel_abs": "In December 2019, an outbreak of atypical pneumonia (Coronavirus disease 2019 - COVID-19) associated with a novel coronavirus (SARS-CoV-2) was reported in Wuhan city, Hubei province, China. The outbreak was traced to a seafood wholesale market and human to human transmission was confirmed. The rapid spread and the death toll of the new epidemic warrants immediate intervention. The intra-host genomic variability of SARS-CoV-2 plays a pivotal role in the development of effective antiviral agents and vaccines, but also in the design of accurate diagnostics.\n\nWe analyzed NGS data derived from clinical samples of three Chinese patients infected with SARS-CoV-2, in order to identify small- and large-scale intra-host variations in the viral genome. We identified tens of low- or higher-frequency single nucleotide variations (SNVs) with variable density across the viral genome, affecting 7 out of 10 protein-coding viral genes. The majority of these SNVs corresponded to missense changes. The annotation of the identified SNVs but also of all currently circulating strain variations revealed colocalization of intra-host but also strain specific SNVs with primers and probes currently used in molecular diagnostics assays. Moreover, we de-novo assembled the viral genome, in order to isolate and validate intra-host structural variations and recombination breakpoints. The bioinformatics analysis disclosed genomic rearrangements over poly-A / poly-U regions located in ORF1ab and spike (S) gene, including a potential recombination hot-spot within S gene.\n\nOur results highlight the intra-host genomic diversity and plasticity of SARS-CoV-2, pointing out genomic regions that are prone to alterations. The isolated SNVs and genomic rearrangements, reflect the intra-patient capacity of the polymorphic quasispecies, which may arise rapidly during the outbreak, allowing immunological escape of the virus, offering resistance to anti-viral drugs and affecting the sensitivity of the molecular diagnostics assays.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Lim Heo", - "author_inst": "Michigan State University" + "author_name": "Timokratis Karamitros", + "author_inst": "Unit of Bioinformatics and Applied Genomics, Department of Microbiology, Hellenic Pasteur Institute, Athens, Greece" }, { - "author_name": "Michael Feig", - "author_inst": "Michigan State University" + "author_name": "Gethsimani Papadopoulou", + "author_inst": "Unit of Bioinformatics and Applied Genomics, Department of Microbiology, Hellenic Pasteur Institute, Athens, Greece" + }, + { + "author_name": "Maria Bousali", + "author_inst": "Unit of Bioinformatics and Applied Genomics, Department of Microbiology, Hellenic Pasteur Institute, Athens, Greece" + }, + { + "author_name": "Anastasios Mexias", + "author_inst": "Unit of Bioinformatics and Applied Genomics, Department of Microbiology, Hellenic Pasteur Institute, Athens, Greece" + }, + { + "author_name": "Sotiris Tsiodras", + "author_inst": "4th Academic Department of Medicine, National and Kapodistrian University of Athens, Medical School, Athens, Greece." + }, + { + "author_name": "Andreas Mentis", + "author_inst": "Public Health Laboratories, Department of Microbiology, Hellenic Pasteur Institute, Athens, Greece" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "new results", - "category": "biophysics" + "category": "genomics" }, { "rel_doi": "10.1101/2020.03.27.012013", @@ -1575626,33 +1574952,37 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.03.23.20041863", - "rel_title": "Modelling strategies to organize healthcare workforce during pandemics: application to COVID-19", + "rel_doi": "10.1101/2020.03.22.20041145", + "rel_title": "Global transmission network of SARS-CoV-2: from outbreak to pandemic", "rel_date": "2020-03-27", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.23.20041863", - "rel_abs": "Protection of healthcare workforce who are at increased risk to become infected is of paramount relevance for the care of patients in the setting of a pandemic such as coronavirus disease 2019 (COVID-19). The ideal organisational strategy to protect the workforce in a situation in which social distancing cannot be maintained remains to be determined. In this study, we have mathematically modelled strategies for the employment of hospital workforce with the goal to simulate health and productivity of the workers. The models were designed to determine if desynchronization of medical teams by dichotomizing the workers may protect the workforce. Our studies model workforce productivity depending on the infection rate, the presence of reinfection and the efficiency of home office and apply our theory to the case of COVID-19. The results reveal that a desynchronization strategy in which two medical teams work alternating for 7 days increases the available workforce.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.22.20041145", + "rel_abs": "BackgroundThe COVID-19 pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is straining health systems around the world. Although the Chinese government implemented a number of severe restrictions on peoples movement in an attempt to contain its local and international spread, the virus had already reached many areas of the world in part due to its potent transmissibility and the fact that a substantial fraction of infected individuals develop little or no symptoms at all. Following its emergence, the virus started to generate sustained transmission in neighboring countries in Asia, Western Europe, Australia, Canada and the United States, and finally in South America and Africa. As the virus continues its global spread, a clear and evidence-based understanding of properties and dynamics of the global transmission network of SARS-CoV-2 is essential to design and put in place efficient and globally coordinated interventions.\n\nMethodsWe employ molecular surveillance data of SARS-CoV-2 epidemics for inference and comprehensive analysis of its global transmission network before the pandemic declaration. Our goal was to characterize the spatial-temporal transmission pathways that led to the establishment of the pandemic. We exploited a network-based approach specifically tailored to emerging outbreak settings. Specifically, it traces the accumulation of mutations in viral genomic variants via mutation trees, which are then used to infer transmission networks, revealing an up-to-date picture of the spread of SARS-CoV-2 between and within countries and geographic regions.\n\nResults and ConclusionsThe analysis suggest multiple introductions of SARS-CoV-2 into the majority of world regions by means of heterogeneous transmission pathways. The transmission network is scale-free, with a few genomic variants responsible for the majority of possible transmissions. The network structure is in line with the available temporal information represented by sample collection times and suggest the expected sampling time difference of few days between potential transmission pairs. The inferred network structural properties, transmission clusters and pathways and virus introduction routes emphasize the extent of the global epidemiological linkage and demonstrate the importance of internationally coordinated public health measures.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Daniel Sanchez-Taltavull", - "author_inst": "Department for Visceral Surgery and Medicine, Bern University Hospital, University of Bern, Switzerland" + "author_name": "Pavel Skums", + "author_inst": "Georgia State University" }, { - "author_name": "Daniel Candinas", - "author_inst": "Department for Visceral Surgery and Medicine, Bern University Hospital, University of Bern, Switzerland" + "author_name": "Alexander Kirpich", + "author_inst": "Georgia State University" }, { - "author_name": "Edgar Roldan", - "author_inst": "The Abdus Salam International Centre for Theoretical Physics, Trieste, Italy" + "author_name": "Pelin Icer Baykal", + "author_inst": "Georgia State University" }, { - "author_name": "Guido Beldi", - "author_inst": "Department for Visceral Surgery and Medicine, Bern University Hospital, University of Bern, Switzerland" + "author_name": "Alex Zelikovsky", + "author_inst": "Georgia State University" + }, + { + "author_name": "Gerardo Chowell", + "author_inst": "Georgia State University School of Public Health" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1577188,23 +1576518,31 @@ "category": "intensive care and critical care medicine" }, { - "rel_doi": "10.1101/2020.03.25.20043570", - "rel_title": "Acute gastrointestinal injury in critically ill patients with coronavirus disease 2019 in Wuhan, China", + "rel_doi": "10.1101/2020.03.24.20043026", + "rel_title": "A Computational Model for Estimating the Progression of COVID-19 Cases in the US West and East Coasts", "rel_date": "2020-03-27", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.25.20043570", - "rel_abs": "BackgroundTo investigate the prevalence and outcomes of acute gastrointestinal injury (AGI) in critically ill patients with coronavirus disease 2019 (COVID-19).\n\nMethodsIn this clinical retrospective study, demographic data, laboratory parameters, AGI grades, clinical severity and outcomes were collected. The primary endpoints were AGI incidence and 28-day mortality, the secondary endpoints were organ dysfunction and septic shock incidence.\n\nResultsFrom February 10 to March 10 2020, 83 critically ill patients of 1314 patients with COVID-19 were enrolled. Seventy-two (86.7%) patients had AGI during hospital stay, of them, 30 had AGI grade I, 35 had AGI grade II, 5 had AGI grade III, and 2 had AGI grade IV. The incidence of AGI grade II and above was 50.6%. As of March 16, 40 (48.2%) patients died within 28 days of admission, the median hospital stay was 12.0 days, ranging from 3 days to 27 days. Multiple organ dysfunction syndrome developed in 58 (69.9%) patients, septic shock in 16 (19.3%) patients. Patients with worse AGI grades had worse clinical variables, higher septic shock incidence and 28-day mortality. Sequential organ failure assessment scores (SOFA) (95% CI, 1.374-2.860; P <0.001), white blood cell (WBC) counts (95% CI, 1.037-1.379; P =0.014), duration of mechanical ventilation (MV) (95% CI, 1.020-1.340; P =0.025) were risk factors for the development of AGI grade II and above. Non-survivors were accompanied by higher incidence of AGI grade III to IV than survivors (17.5% vs. 0.0%, P =0.004).\n\nConclusionsThe AGI incidence was 86.7%, and hospital mortality was 48.2% in critically ill patients with COVID-19. SOFA scores, WBC counts, and duration of MV were risk factors for the development of AGI grade II and above. Patients with worse AGI grades had worse clinical severity variables, higher septic shock incidence and 28-day mortality.", - "rel_num_authors": 1, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.24.20043026", + "rel_abs": "The ongoing coronavirus disease 2019 (COVID-19) pandemic is of global concern and has recently emerged in the US. In this paper, we construct a stochastic variant of the SEIR model to make a quasi-worst-case scenario prediction of the COVID-19 outbreak in the US West and East Coasts. The model is then fitted to current data and implemented using Runge-Kutta methods. Our computation results predict that the number of new cases would peak around mid-April 2000 and begin to abate by July, and that the number of cases of COVID-19 might be significantly mitigated by having greater numbers of functional testing kits available for screening. The model also showed how small changes in variables can make large differences in outcomes and highlights the importance of healthcare preparedness during pandemics.\n\nAuthor SummaryCoronavirus disease 2019 (COVID-19) has escalated into a global pandemic and has recently emerged in the US. While some countries have managed to contain COVID-19 efficiently, other countries previously thought to have been well-prepared for outbreaks due to higher living standards and healthcare quality have witnessed an unexpected number of cases. It is currently unclear how the US can cope with the COVID-19 pandemic, especially after mishaps during the initial stages. Our study combines conditions unique to the US and transmission dynamics in regions affected most by COVID-19 to produce a quasi-worse-case scenario of COVID-19 in the US and shows the importance of healthcare preparedness during pandemics.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Jia-Kui Sun", - "author_inst": "Nanjing First Hospital" + "author_name": "Yao Yu Yeo", + "author_inst": "Cornell University" + }, + { + "author_name": "Yao-Rui Yeo", + "author_inst": "University of Pennsylvania" + }, + { + "author_name": "Wan-Jin Yeo", + "author_inst": "University of Washington" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "intensive care and critical care medicine" + "category": "epidemiology" }, { "rel_doi": "10.1101/2020.03.25.20043679", @@ -1578650,59 +1577988,67 @@ "category": "bioinformatics" }, { - "rel_doi": "10.1101/2020.03.24.20042762", - "rel_title": "A model to estimate bed demand for COVID-19 related hospitalization", + "rel_doi": "10.1101/2020.03.26.009803", + "rel_title": "The potential SARS-CoV-2 entry inhibitor", "rel_date": "2020-03-26", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.24.20042762", - "rel_abs": "As of March 23, 2020 there have been over 354,000 confirmed cases of coronavirus disease 2019 (COVID-19) in over 180 countries, the World Health Organization characterized COVID-19 as a pandemic, and the United States (US) announced a national state of emergency.1, 2, 3 In parts of China and Italy the demand for intensive care (IC) beds was higher than the number of available beds.4, 5 We sought to build an accessible interactive model that could facilitate hospital capacity planning in the presence of significant uncertainty about the proportion of the population that is COVID-19+ and the rate at which COVID-19 is spreading in the population. Our approach was to design a tool with parameters that hospital leaders could adjust to reflect their local data and easily modify to conduct sensitivity analyses.\n\nWe developed a model to facilitate hospital planning with estimates of the number of Intensive Care (IC) beds, Acute Care (AC) beds, and ventilators necessary to accommodate patients who require hospitalization for COVID-19 and how these compare to the available resources. Inputs to the model include estimates of the characteristics of the patient population and hospital capacity. We deployed this model as an interactive online tool.6 The model is implemented in R 3.5, RStudio, RShiny 1.4.0 and Python 3.7. The parameters used may be modified as data become available, for use at other institutions, and to generate sensitivity analyses.\n\nWe illustrate the use of the model by estimating the demand generated by COVID-19+ arrivals for a hypothetical acute care medical center. The model calculated that the number of patients requiring an IC bed would equal the number of IC beds on Day 23, the number of patients requiring a ventilator would equal the number of ventilators available on Day 27, and the number of patients requiring an AC bed and coverage by the Medicine Service would equal the capacity of the Medicine service on Day 21.\n\nIn response to the COVID-19 epidemic, hospitals must understand their current and future capacity to care for patients with severe illness. While there is significant uncertainty around the parameters used to develop this model, the analysis is based on transparent logic and starts from observed data to provide a robust basis of projections for hospital managers. The model demonstrates the need and provides an approach to address critical questions about staffing patterns for IC and AC, and equipment capacity such as ventilators.", - "rel_num_authors": 10, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2020.03.26.009803", + "rel_abs": "Outbreak of coronavirus disease 2019 (COVID-19) occurred in Wuhan and has rapidly spread to almost all parts of world. In coronaviruses, the receptor binding domain (RBD) in the distal part of S1 subunit of SARS-CoV-2 spike protein can directly bind to angiotensin converting enzyme 2 (ACE2). RBD promote viral entry into the host cells and is an important therapeutic target. In this study, we discovered that theaflavin showed the lower idock score (idock score: -7.95 kcal/mol). To confirm the result, we discovered that theaflavin showed FullFitness score of -991.21 kcal/mol and estimated {Delta}G of -8.53 kcal/mol for the most favorable interaction with contact area of SARS-CoV-2 RBD by SwissDock service. Regarding contact modes, hydrophobic interactions contribute significantly in binding and additional hydrogen bonds were formed between theaflavin and Arg454, Phe456, Asn460, Cys480, Gln493, Asn501 and Val503 of SARS-CoV-2 RBD, near the direct contact area with ACE2. Our results suggest that theaflavin could be the candidate of SARS-CoV-2 entry inhibitor for further study.", + "rel_num_authors": 12, "rel_authors": [ { - "author_name": "Teng Zhang", - "author_inst": "Stanford University School of Engineering" + "author_name": "Jrhau Lung", + "author_inst": "Chiayi Chang Gung Memorial Hospital" }, { - "author_name": "Kelly McFarlane", - "author_inst": "Stanford University Graduate School of Business, Harvard Medical School" + "author_name": "Yu-Shih Lin", + "author_inst": "Chiayi Chang Gung Memorial Hospital" }, { - "author_name": "Jacqueline Vallon", - "author_inst": "Stanford University School of Engineering" + "author_name": "Yao-Hsu Yang", + "author_inst": "Chiayi Chang Gung Memorial Hospital" }, { - "author_name": "Linying Yang", - "author_inst": "Stanford University School of Engineering" + "author_name": "Yu-Lun Chou", + "author_inst": "Chang Gung Memorial Hospital Kaohsiung Branch" }, { - "author_name": "Jin Xie", - "author_inst": "Stanford University School of Engineering" + "author_name": "Geng-He Chang", + "author_inst": "Chiayi Chang Gung Memorial Hospital" }, { - "author_name": "Jose Blanchet", - "author_inst": "Stanford University School of Engineering" + "author_name": "Ming-Shao Tsai", + "author_inst": "Chiayi Chang Gung Memorial Hospital" }, { - "author_name": "Peter Glynn", - "author_inst": "Stanford University School of Engineering" + "author_name": "Cheng-Ming Hsu", + "author_inst": "Chiayi Chang Gung Memorial Hospital" }, { - "author_name": "Kristan Staudenmayer", - "author_inst": "Stanford University School of Medicine" + "author_name": "Reming-Albert Yeh", + "author_inst": "Chiayi Chang Gung Memorial Hospital" }, { - "author_name": "Kevin Schulman", - "author_inst": "Stanford University School of Medicine" + "author_name": "Li-Hsin Shu", + "author_inst": "Chiayi Chang Gung Memorial Hospital" }, { - "author_name": "David Scheinker", - "author_inst": "Stanford University School of Engineering, Stanford University School of Medicine, Lucile Packard Children's Hospital" + "author_name": "Yu-Ching Cheng", + "author_inst": "Chiayi Chang Gung Memorial Hospital" + }, + { + "author_name": "Hung Te Liu", + "author_inst": "Chiayi Chang Gung Memorial Hospital" + }, + { + "author_name": "Ching-Yuan Wu", + "author_inst": "Chiayi Chang Gung Memorial Hospital" } ], "version": "1", - "license": "cc_by_nc_nd", - "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "license": "cc_by", + "type": "new results", + "category": "bioinformatics" }, { "rel_doi": "10.1101/2020.03.23.20039446", @@ -1580408,63 +1579754,27 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.03.22.20040782", - "rel_title": "A comparative multi-centre study on the clinical and imaging features of comfirmed and uncomfirmed patients with COVID-19", + "rel_doi": "10.1101/2020.03.21.20040154", + "rel_title": "Predicting the number of reported and unreported cases for the COVID-19 epidemic in South Korea, Italy, France and Germany", "rel_date": "2020-03-24", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.22.20040782", - "rel_abs": "BackgroundPrevious studies had described the differences in clinical characteristics between ICU and non-ICU patients. However, seldom study focused on confirmed and unconfirmed groups. Our aim was to compare clinical and imaging characteristics of COVID-19 patients outside Hubei province between confirmed and unconfirmed group.\n\nMethodsWe retrospectively enrolled 163 consecutive adult patients with suspected COVID-19 from three tertiary hospitals in two provinces outside Hubei province from January 12, 2020 to February 13, 2020 and the differences in epidemiological, clinical, laboratory and imaging characteristics between the two groups were compared.\n\nResultsThis study enrolled 163 patients with 62 confirmed cases and 101 unconfirmed cases. Most confirmed patients were clustered (31, 50.0%) and with definite epidemiological exposure. Symptoms of COVID-19 were nonspecific, largely fever and dry cough. Laboratory findings in confirmed group were characterized by normal or reduced white blood cell count, reduced the absolute value of lymphocytes, and elevated levels of C-reactive protein (CRP) and accelerated Erythrocyte sedimentation rate (ESR). The typical chest CT imaging features of patients with confirmed COVID-19 were peripherally distributed multifocal GGO with predominance in the lower lung lobe. Compared with unconfirmed patients, confirmed patients had significantly higher proportion of dry cough, leucopenia, lymphopenia and accelerated ESR (P<0.05); but not with alanine aminotransferase, aspartate aminotransferase, D-dimer, lactic dehydrogenase, and myoglobin (P>0.05). Proportion of peripheral, bilateral or lower lung distribution and multi-lobe involvement, GGO, crazy-paving pattern, air bronchogram and pleural thickening in the confirmed group were also higher (P<0.05).\n\nConclusionsSymptoms of COVID-19 were nonspecific. Leukopenia, lymphopenia and ESR, as well as chest CT could be used as a clue for clinical diagnosis of COVID-19.", - "rel_num_authors": 11, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.21.20040154", + "rel_abs": "We model the COVID-19 coronavirus epidemic in South Korea, Italy, France, and Germany. We use early reported case data to predict the cumulative number of reported cases to a final size. The key features of our model are the timing of implementation of major public policies restricting social movement, the identification and isolation of unreported cases, and the impact of asymptomatic infectious cases.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Congliang Miao", - "author_inst": "Shanghai General Hospital, Shanghai Jiao Tong University" - }, - { - "author_name": "Jinqiang Zhuang", - "author_inst": "Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine" - }, - { - "author_name": "Mengdi Jin", - "author_inst": "Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine" - }, - { - "author_name": "Huanwen Xiong", - "author_inst": "High-tech Hospital, First Hospital Affiliated to Nanchang University" - }, - { - "author_name": "Peng Huang", - "author_inst": "People's Hospital of Yichun city" - }, - { - "author_name": "Qi Zhao", - "author_inst": "Shanghai General Hospital, Shanghai Jiao Tong University" - }, - { - "author_name": "Li Miao", - "author_inst": "High-tech Hospital, First Hospital Affiliated to Nanchang University" - }, - { - "author_name": "Jiang Du", - "author_inst": "Shanghai General Hospital, Shanghai Jiao Tong University" - }, - { - "author_name": "Xinying Yang", - "author_inst": "Shanghai General Hospital of Nanjing Medical University" - }, - { - "author_name": "Peijie Huang", - "author_inst": "Shanghai General Hospital, Shanghai Jiao Tong University" + "author_name": "pierre magal", + "author_inst": "University of Bordeaux" }, { - "author_name": "Jiang Hong", - "author_inst": "Shanghai General Hospital, Shanghai Jiao Tong University" + "author_name": "Glenn Webb", + "author_inst": "Vanderbilt University" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2020.03.20.20040048", @@ -1582134,75 +1581444,23 @@ "category": "intensive care and critical care medicine" }, { - "rel_doi": "10.1101/2020.03.16.20037259", - "rel_title": "High incidence of asymptomatic SARS-CoV-2 infection, Chongqing, China", + "rel_doi": "10.1101/2020.03.19.20039388", + "rel_title": "Chinese and Italian COVID-19 outbreaks can be correctly described by a modified SIRD model", "rel_date": "2020-03-23", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.16.20037259", - "rel_abs": "BackgroundSARS-CoV-2 has been a global pandemic, but the emergence of asymptomatic patients has caused difficulties in the prevention of the epidemic. Therefore, it is significant to understand the epidemiological characteristics of asymptomatic patients with SARS-CoV-2 infection.\n\nMethodsIn this single-center, retrospective and observational study, we collected data from 167 patients with SARS-CoV-2 infection treated in Chongqing Public Health Medical Center (Chongqing, China) from January to March 2020. The epidemiological characteristics and variable of these patients were collected and analyzed.\n\nFindings82.04% of the SARS-CoV-2 infected patients had a travel history in Wuhan or a history of contact with returnees from Wuhan, showing typical characteristics of imported cases, and the proportion of severe Covid-19 patients was 13.2%, of which 59% were imported from Wuhan. For the patients who was returnees from Wuhan, 18.1% was asymptomatic patients. In different infection periods, compared with the proportion after 1/31/2020, the proportion of asymptomatic patient among SARS-CoV-2 infected patient was higher(19% VS 1.5%). In different age groups, the proportion of asymptomatic patient was the highest(28.6%) in children group under 14, next in elder group over 70 (27.3%). Compared with mild and common Covid-19 patients, the mean latency of asymptomatic was longer (11.25 days VS 8.86 days), but the hospital length of stay was shorter (14.3 days VS 16.96 days).\n\nConclusionThe SARS-CoV-2 prevention needs to focus on the screening of asymptomatic patients in the community with a history of contact with the imported population, especially for children and the elderly population.", - "rel_num_authors": 14, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.19.20039388", + "rel_abs": "The COVID-19 disease is rapidly spreading in whole globe, affecting millions of people and pushing governments to take drastic measures to contain the outbreaks. The understanding of the dynamics of the epidemic is of great interest for the governments and health authorities that are facing COVID-19 outbreaks. The scarce presence of epidemiologic data, due to the still ongoing outbreaks, makes prediction difficult and mainly based on heuristic (fitting) models. However, these models with non-physical based parameters, can only give limited insight in the evolution of the outbreaks. In this work a SIRD compartmental model was developed to describe and predict the evolution of the Chinese and Italian outbreaks. Exploiting the similarities of the measures taken by the governments to contain the virus and of the total population number of Hubei province and Italy, the model was tuned on the Chinese outbreak (almost extinguished) and by perturbation the Italian outbreak was describe and predicted.", + "rel_num_authors": 1, "rel_authors": [ { - "author_name": "Yang Tao", - "author_inst": "Beibei Tranditional Chinese Medical Hospital, Chongqing, 400000, China" - }, - { - "author_name": "Panke Cheng", - "author_inst": "Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China" - }, - { - "author_name": "Wen Chen", - "author_inst": "Army Medical University (Third Military Medical University)" - }, - { - "author_name": "Peng Wan", - "author_inst": "Beibei Tranditional Chinese Medical Hospital, Chongqing, 400000, China" - }, - { - "author_name": "Yaokai Chen", - "author_inst": "Chongqing Public Health Medical Center, Chongqing, 400000, China" - }, - { - "author_name": "Guodan Yuan", - "author_inst": "Chongqing Public Health Medical Center, Chongqing, 400000, China" - }, - { - "author_name": "Junjie Chen", - "author_inst": "Army Medical University (Third Military Medical University)" - }, - { - "author_name": "Da Huo", - "author_inst": "Army Medical University (Third Military Medical University)" - }, - { - "author_name": "Ge Guan", - "author_inst": "Army Medical University (Third Military Medical University)" - }, - { - "author_name": "Dayu Sun", - "author_inst": "Army Medical University (Third Military Medical University)" - }, - { - "author_name": "Ju Tan", - "author_inst": "Army Medical University (Third Military Medical University)" - }, - { - "author_name": "Guanyuan Yang", - "author_inst": "Army Medical University (Third Military Medical University)" - }, - { - "author_name": "Wen Zeng", - "author_inst": "Army Medical University (Third Military Medical University)" - }, - { - "author_name": "Chuhong Zhu", - "author_inst": "Army Medical University (Third Military Medical University), Chongqing 400038, China" + "author_name": "Diego Caccavo", + "author_inst": "Department of Industrial Engineering, University of Salerno" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "emergency medicine" + "category": "epidemiology" }, { "rel_doi": "10.1101/2020.03.20.20038406", @@ -1583340,21 +1582598,65 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.03.20.20039891", - "rel_title": "COVID-19 outbreak in Algeria: A mathematical model to predict the incidence", + "rel_doi": "10.1101/2020.03.19.20033175", + "rel_title": "Characteristics of patients with COVID-19 during epidemic ongoing outbreak in Wuhan, China", "rel_date": "2020-03-23", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.20.20039891", - "rel_abs": "IntroductionSince December 29, 2019 a pandemic of new novel coronavirus-infected pneumonia named COVID-19 has started from Wuhan, China, has led to 254 996 confirmed cases until midday March 20, 2020. Sporadic cases have been imported worldwide, in Algeria, the first case reported on February 25, 2020 was imported from Italy, and then the epidemic has spread to other parts of the country very quickly with 139 confirmed cases until March 21, 2020.\n\nMethodsIt is crucial to estimate the cases number growth in the early stages of the outbreak, to this end, we have implemented the Alg-COVID-19 Model which allows to predict the incidence and the reproduction number R0 in the coming months in order to help decision makers.\n\nThe Alg-COVIS-19 Model initial equation 1, estimates the cumulative cases at t prediction time using two parameters: the reproduction number R0 and the serial interval SI.\n\nResultsWe found R0=2.55 based on actual incidence at the first 25 days, using the serial interval SI= 4,4 and the prediction time t=26. The herd immunity HI estimated is HI=61%. Also, The Covid-19 incidence predicted with the Alg-COVID-19 Model fits closely the actual incidence during the first 26 days of the epidemic in Algeria Fig. 1.A. which allows us to use it.\n\nO_FIG O_LINKSMALLFIG WIDTH=123 HEIGHT=200 SRC=\"FIGDIR/small/20039891v2_fig1.gif\" ALT=\"Figure 1\">\nView larger version (20K):\norg.highwire.dtl.DTLVardef@baae3org.highwire.dtl.DTLVardef@5cb4org.highwire.dtl.DTLVardef@1c65fb0org.highwire.dtl.DTLVardef@b41ec6_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFig. 1.C_FLOATNO A: Alg-COVID-19 Model match to actual data (Cases number) of the first 26 days of epidemic. B: Alg-COVID-19 Model before and before (R0=2.55) and after mitigation (R0<2.55).\n\nC_FIG According to Alg-COVID-19 Model, the number of cases will exceed 5000 on the 42th day (April 7th) and it will double to 10000 on 46th day of the epidemic (April 11th), thus, exponential phase will begin (Table 1; Fig.1.B) and increases continuously until reaching a herd immunity of 61% unless serious preventive measures are considered.\n\nO_TBL View this table:\norg.highwire.dtl.DTLVardef@1506af6org.highwire.dtl.DTLVardef@9e6d5dorg.highwire.dtl.DTLVardef@11e014borg.highwire.dtl.DTLVardef@e7086dorg.highwire.dtl.DTLVardef@1da5599_HPS_FORMAT_FIGEXP M_TBL O_FLOATNOTable 1.C_FLOATNO O_TABLECAPTIONAlg-COVID-19 Model results for next weeks\n\nC_TABLECAPTION C_TBL DiscussionThis model is valid only when the majority of the population is vulnerable to COVID-19 infection, however, it can be updated to fit the new parameters values.", - "rel_num_authors": 1, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.19.20033175", + "rel_abs": "BackgroundSince Dec 2019, SARS-CoV-2 has caused about fifty thousand patients and over two thousand deaths in Wuhan, China. We reported characteristics of patients with COVID-19 during epidemic ongoing outbreak in Wuhan.\n\nMethodsData of COVID-19 patients with clinical outcome in a designated hospital in Wuhan, were retrospectively collected from electronic medical records. Characteristics were compared between patients who died or recovered, and between patients with different disease severity.\n\nResultsBy Feb 25, 2020, 403 patients were enrolled, 100 died and 303 recovered. Most of non-survivors tended to be males, old aged, or with chronic diseases. Duration from illness onset to admission was 9 (7-12) days. Patients with severe or critical illness had more days from onset to admission compared to those with ordinary illness. Lymphopenia, anemia, hypoproteinemia, and abnormal serum sodium were presented in 52.6%, 54.6%, 69.8%, and 21.8% cases, respectively. Patients who died or with severe/critical illness showed increased white blood cell and neutrophil count, serum total bilirubin, creatinine, hypersensitive troponin I, D-dimer, procalcitonin, and C-reactive protein, and decreased red blood cell, lymphocyte, platelet count, and serum albumin on admission compared to those who recovered or with ordinary illness. Complications of acute organ injury and secondary infection were common in patients with COVID-19, especially in non-survivors.\n\nConclusionsMultiple homeostasis disturbances were common in patients with severe or critical illness at admission. Early support should be provided, especially for old men with chronic disease, which is vital to control disease progression and reduce mortality of COVID-19 during epidemic ongoing outbreak.", + "rel_num_authors": 12, "rel_authors": [ { - "author_name": "Mohamed HAMIDOUCHE Sr.", - "author_inst": "Pasteur Institute of Algeria" + "author_name": "Xiaomin Luo", + "author_inst": "Renmin hospital of Wuhan University" + }, + { + "author_name": "Hongxia Xia", + "author_inst": "Renmin Hospital of Wuhan University" + }, + { + "author_name": "Weize Yang", + "author_inst": "Renmin Hospital of Wuhan University" + }, + { + "author_name": "Benchao Wang", + "author_inst": "Renmin Hospital of Wuhan University" + }, + { + "author_name": "Tangxi Guo", + "author_inst": "Renmin Hospital of Wuhan University" + }, + { + "author_name": "Jun Xiong", + "author_inst": "Renmin Hospital of Wuhan University" + }, + { + "author_name": "Zongping Jiang", + "author_inst": "Renmin Hospital of Wuhan University" + }, + { + "author_name": "Yu Liu", + "author_inst": "Renmin Hospital of Wuhan University" + }, + { + "author_name": "Xiaojie Yan", + "author_inst": "Renmin Hospital of Wuhan University" + }, + { + "author_name": "Wei Zhou", + "author_inst": "Renmin Hospital of Wuhan University" + }, + { + "author_name": "Lu Ye", + "author_inst": "Renmin Hospital of Wuhan University" + }, + { + "author_name": "Bicheng Zhang", + "author_inst": "Renmin Hospital of Wuhan University" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1585334,37 +1584636,29 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.03.15.20036756", - "rel_title": "Analysis of Epidemic Situation of New Coronavirus Infection at Home and Abroad Based on Rescaled Range (R/S) Method", + "rel_doi": "10.1101/2020.03.16.20037036", + "rel_title": "Transmissibility of 2019 Novel Coronavirus: zoonotic vs. human to human transmission, China, 2019-2020", "rel_date": "2020-03-20", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.15.20036756", - "rel_abs": "11.1 BackgroundThe outbreak of the new coronavirus infection broke out in Wuhan City, Hubei Province in December 2019, and has spread to 97 countries and regions around the world. Apart from China, there are currently three other severely affected areas, namely Italy, South Korea, and Iran. This poses a huge threat to Chinas and even global public health security, challenges scientific research work such as disease surveillance and tracking, clinical treatment, and vaccine development, and it also brings huge uncertainty to the global economy. As of March 11, 2020, the epidemic situation in China is nearing its end, but the epidemic situation abroad is in the outbreak period. Italy has even taken measures to close the city nationwide, with a total of 118,020 cases of infection worldwide.\n\n1.2 MethodThis article selects the data of newly confirmed cases of COVID-19 at home and abroad as the data sample. Among them: the data of newly confirmed cases abroad is represented by Italy, and the span is from February 13 to March 10. The data of newly confirmed cases at home are divided into two parts: Hubei Province and other provinces except Hubei Province, spanning from January 23 to March 3, and with February 12 as the cutting point, it\"s divided into two periods, the growth period and the recession period. The rescaled range (R / S) analysis method and the dimensionless fractal Hurst exponent are used to measure the correlation of time series to determine whether the time series conforms to the fractal Brownian motion, that is, a biased random process. Contrast analysis of the meaning of H value in different stages and different overall H values in the same stage.\n\n1.3 ResultsBased on R / S analysis and calculated Hurst value of newly confirmed cases in Hubei and non-Hubei provinces, it was found that the H value of Hubei Province in the first stage was 0.574, which is greater than 0.5, indicating that the future time series has a positive correlation and Fractal characteristics; The H value in the second stage is 1.368, which is greater than 1, which indicates that the future epidemic situation is completely preventable and controllable, and the second stage has a downward trend characteristic, which indicates that there is a high probability that the future time series will decline. The H values of the first and second stages of non-Hubei Province are 0.223 and 0.387, respectively, which are both less than 0.5, indicating that the time series of confirmed cases in the future is likely to return to historical points, and the H value in the second stage is greater than that in the first stage, indicating that the time series of confirmed cases in the second stage is more long-term memory than the time series of confirmed cases in the first stage. The daily absolute number of newly confirmed cases in Italy was converted to the daily growth rate of confirmed cases to eliminate the volatility of the data. The H value was 1.853, which was greater than 1, indicating that the time series of future confirmed cases is similar to the trend of historical changes. The daily rate of change in cases will continue to rise.\n\n1.4 ConclusionAccording to the different interpretation of the H value obtained by the R / S analysis method, hierarchical isolation measures are adopted accordingly. When the H value is greater than 0.5, it indicates that the development of the epidemic situation in the area has more long-term memory, that is, when the number of confirmed cases in the past increases rapidly, the probability of the time series of confirmed cases in the future will continue the historical trend. Therefore, it is necessary to formulate strict anti-epidemic measures in accordance with the actual conditions of various countries, to detect, isolate, and treat early to reduce the base of infectious agents.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.16.20037036", + "rel_abs": "ObjectivesThe novel coronavirus (2019-nCoV) originating from Wuhan has rapidly spread throughout China. While the origin of the outbreak remains uncertain, accumulating evidence links a wet market in Wuhan for the early spread of 2019-nCoV. Similarly, the influence of the marketplace on the early transmission dynamics is yet to be investigated.\n\nMethodsUsing the daily series of 2019-nCov incidenceincluding contact history with the market, we have conducted quantitative modeling analyses to estimate the reproduction numbers (R) for the market-to-human and human-to-human transmission together with the reporting probability and the early effects of public health interventions.\n\nResultsOur mean R estimates for China in 2019-2020 are estimated at 0.37 (95%CrI: 0.02-1.78) for market-to-human transmission, and 3.87 (95%CrI: 3.18-4.78) for human-to-human transmission, respectively. Moreover we estimated that the reporting rate cases stemming from market-to-human transmission was 3-31 fold higher than that for cases stemming from human-to-human transmission, suggesting that contact history with the wet market played a key role in identifying 2019-nCov cases.\n\nConclusionsOur findings suggest that the proportions of asymptomatic and subclinical patients constitute a substantial component of the epidemics magnitude. Findings suggest that the development of rapid diagnostic tests could help bring the epidemic more rapidly under control.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Xiaofeng Ji", - "author_inst": "Sichuan Academy of Social Sciences" - }, - { - "author_name": "Zhou Tang", - "author_inst": "Sichuan Academy of Social Sciences" - }, - { - "author_name": "Kejian Wang", - "author_inst": "Sichuan Academy of Social Sciences" + "author_name": "Kenji Mizumoto", + "author_inst": "Kyoto University" }, { - "author_name": "Xianbin Li", - "author_inst": "Sichuan Academy of Social Sciences" + "author_name": "Katsushi Kagaya", + "author_inst": "Kyoto University" }, { - "author_name": "Houqiang Li", - "author_inst": "Sichuan Academy of Social Sciences" + "author_name": "Gerardo Chowell", + "author_inst": "Georgia State University School of Public Health" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1586684,65 +1585978,21 @@ "category": "palliative medicine" }, { - "rel_doi": "10.1101/2020.03.17.20037515", - "rel_title": "A Tool to Early Predict Severe 2019-Novel Coronavirus Pneumonia (COVID-19) : A Multicenter Study using the Risk Nomogram in Wuhan and Guangdong, China", + "rel_doi": "10.1101/2020.03.18.20038638", + "rel_title": "Spatial Visualization of Cluster-Specific COVID-19 Transmission Network in South Korea During the Early Epidemic Phase", "rel_date": "2020-03-20", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.17.20037515", - "rel_abs": "BackgroundDue to no reliable risk stratification tool for severe corona virus disease 2019 (COVID-19) patients at admission, we aimed to construct an effective model for early identifying cases at high risk of progression to severe COVID-19.\n\nMethodsIn this retrospective three-centers study, 372 non-severe COVID-19 patients during hospitalization were followed for more than 15 days after admission. Patients who deteriorated to severe or critical COVID-19 and patients who kept non-severe state were assigned to the severe and non-severe group, respectively. Based on baseline data of the two groups, we constructed a risk prediction nomogram for severe COVID-19 and evaluate its performance.\n\nResultsThe train cohort consisted of 189 patients, while the two independent validation cohorts consisted of 165 and 18 patients. Among all cases, 72 (19.35%) patients developed severe COVID-19. We found that old age, and higher serum lactate dehydrogenase, C-reactive protein, the coefficient of variation of red blood cell distribution width, blood urea nitrogen, direct bilirubin, lower albumin, are associated with severe COVID-19. We generated the nomogram for early identifying severe COVID-19 in the train cohort (AUC 0.912 [95% CI 0.846-0.978], sensitivity 85.71%, specificity 87.58%); in validation cohort (0.853 [0.790-0.916], 77.5%, 78.4%). The calibration curve for probability of severe COVID-19 showed optimal agreement between prediction by nomogram and actual observation. Decision curve and clinical impact curve analysis indicated that nomogram conferred high clinical net benefit.\n\nConclusionOur nomogram could help clinicians to early identify patients who will exacerbate to severe COVID-19, which will enable better centralized management and early treatment of severe patients.\n\nSummaryOlder age; higher LDH, CRP, RDW, DBIL, BUN; lower ALB on admission correlated with higher odds of severe COVID-19. An effective prognostic nomogram composed of 7 features could allow early identification of patients at risk of exacerbation to severe COVID-19.", - "rel_num_authors": 12, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.18.20038638", + "rel_abs": "BackgroundCoronavirus disease 2019 (COVID-19) has been rapidly spreading throughout China and other countries including South Korea. As of March 12, 2020, a total number of 7,869 cases and 66 deaths had been documented in South Korea. Although the first confirmed case in South Korea was identified on January 20, 2020, the number of confirmed cases showed a rapid growth on February 19, 2020 with a total number of 1,261 cases with 12 deaths based on the Korea Centers for Disease Control and Prevention (KCDC).\n\nMethodUsing the data of confirmed cases of COVID-19 in South Korea that are publicly available from the KCDC, this paper aims to create spatial visualizations of COVID-19 transmission between January 20, 2020 and February 19, 2020.\n\nResultsUsing spatial visualization, this paper identified two early transmission clusters in South Korea (Daegu cluster and capital area cluster). Using a degree-weighted centrality measure, this paper proposes potential super-spreaders of the virus in the visualized clusters.\n\nConclusionCompared to various epidemiological measures such as the basic reproduction number, spatial visualizations of the cluster-specific transmission networks and the proposed centrality measure may be more useful to characterize super-spreaders and the spread of the virus especially in the early epidemic phase.", + "rel_num_authors": 1, "rel_authors": [ { - "author_name": "Jiao Gong", - "author_inst": "Third Affiliated Hospital of Sun Yat-sen University" - }, - { - "author_name": "Jingyi Ou", - "author_inst": "Guangzhou Eighth People's Hospital" - }, - { - "author_name": "Xueping Qiu", - "author_inst": "Zhongnan Hospital of Wuhan University" - }, - { - "author_name": "Yusheng Jie", - "author_inst": "Third Affiliated Hospital of Sun Yat-sen University" - }, - { - "author_name": "Yaqiong Chen", - "author_inst": "Third Affiliated Hospital of Sun Yat-sen University" - }, - { - "author_name": "Lianxiong Yuan", - "author_inst": "Third Affiliated Hospital of Sun Yat-sen University" - }, - { - "author_name": "Jing Cao", - "author_inst": "Third Affiliated Hospital of Sun Yat-sen University" - }, - { - "author_name": "Mingkai Tan", - "author_inst": "Guangzhou Eighth People's Hospital" - }, - { - "author_name": "Wenxiong Xu", - "author_inst": "Third Affiliated Hospital of Sun Yat-sen University" - }, - { - "author_name": "Fang Zheng", - "author_inst": "Zhongnan Hospital of Wuhan University" - }, - { - "author_name": "Yaling Shi", - "author_inst": "Clinical Laboratory of Guangzhou Eighth People's Hospital" - }, - { - "author_name": "Bo Hu", - "author_inst": "Third Affiliated Hospital of Sun Yat-sen University" + "author_name": "James Yeongjun Park", + "author_inst": "Harvard T.H. Chan School of Public Health" } ], "version": "1", - "license": "cc_no", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", "category": "public and global health" }, @@ -1588170,59 +1587420,39 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.03.15.20036392", - "rel_title": "Routes for COVID-19 importation in Brazil", + "rel_doi": "10.1101/2020.03.15.20036319", + "rel_title": "The clinical and epidemiological features and hints of 82 confirmed COVID-19 pediatric cases aged 0-16 in Wuhan, China", "rel_date": "2020-03-18", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.15.20036392", - "rel_abs": "HighlightThe global outbreak caused by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has been declared a pandemic by the WHO. As the number of imported SARS-CoV-2 cases is on the rise in Brazil, we use incidence and historical air travel data to estimate the most important routes of importation into the country.", - "rel_num_authors": 10, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.15.20036319", + "rel_abs": "Although COVID-19 pediatric patients just account for 1% of the overall cases, they are nonnegligible invisible infection sources. We quantitatively analyzed the clinical and epidemiological features of 82 confirmed cases aged 0-16 admitted to Wuhan Childrens Hospital, which are expected to shed some lights onto the pediatric diagnosis and therapy.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Darlan da Silva Candido", - "author_inst": "Department of Zoology, University of Oxford, United Kingdom." - }, - { - "author_name": "Alexander Watts", - "author_inst": "Department of Medicine, Division of Infectious Diseases, University of Toronto, Canada" - }, - { - "author_name": "Leandro Abade", - "author_inst": "Department of Zoology, University of Oxford, United Kingdom." - }, - { - "author_name": "Moritz UG Kraemer", - "author_inst": "Department of Zoology, University of Oxford, United Kingdom" - }, - { - "author_name": "Oliver G Pybus", - "author_inst": "Department of Zoology, University of Oxford, United Kingdom" - }, - { - "author_name": "Julio Croda", - "author_inst": "Laboratorio de Pesquisa em Ciencias da Saude, Universidade Federal da Grande Dourados, Dourados, Mato Grosso do Sul, Brazil" + "author_name": "Hui Yu", + "author_inst": "Wuhan Children's Hospital" }, { - "author_name": "Wanderson de Oliveira", - "author_inst": "Secretaria de Vigilancia em Saude, Coordenacao Geral de Laboratorios de Saude Publica, Ministerio da Saude, Brasilia-DF, Brazil" + "author_name": "Qinzhen Cai", + "author_inst": "Wuhan Children's Hospital" }, { - "author_name": "Kamran Khan", - "author_inst": "Department of Medicine, Division of Infectious Diseases, University of Toronto, Canada" + "author_name": "Xiang Dai", + "author_inst": "Wuhan Children's Hospital" }, { - "author_name": "Ester C Sabino", - "author_inst": "Instituto Medicina Tropical, University of Sao Paulo, Brazil" + "author_name": "Xiuzhen Liu", + "author_inst": "Wuhan Children's Hospital" }, { - "author_name": "Nuno R. Faria", - "author_inst": "University of Oxford" + "author_name": "Hongs Sun", + "author_inst": "Wuhan Children's Hospital" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "pediatrics" }, { "rel_doi": "10.1101/2020.03.15.20036582", @@ -1589808,31 +1589038,27 @@ "category": "biochemistry" }, { - "rel_doi": "10.1101/2020.03.14.20035964", - "rel_title": "Covid-19 pandemic: on a simple way to visualize the epidemic states and trajectories of some European countries, and to assess the effect of delays in official response", + "rel_doi": "10.1101/2020.03.15.992438", + "rel_title": "Computational analysis of microRNA-mediated interactions in SARS-CoV-2 infection", "rel_date": "2020-03-17", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.14.20035964", - "rel_abs": "We present a self-synchronizing and robust method for comparing the progression of the Covid-19 epidemics among multiple countries. In their growth phase the epidemics show power law rather than exponential law time dependences. They are similar enough for the earlier China outbreak to guide other countries projections. The delayed reaction of European countries is shown to produce a significantly worse outcome compared to China.", - "rel_num_authors": 3, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2020.03.15.992438", + "rel_abs": "MicroRNAs (miRNAs) are post-transcriptional regulators of gene expression that have been found in more than 200 diverse organisms. Although it is still not fully established if RNA viruses could generate miRNAs that would target their own genes or alter the host gene expression, there are examples of miRNAs functioning as an antiviral defense mechanism. In the case of Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), there are several mechanisms that would make miRNAs impact the virus, like interfering with replication, translation and even modulating the host expression. In this study, we performed a machine learning based miRNA prediction analysis for the SARS-CoV-2 genome to identify miRNA-like hairpins and searched for potential miRNA - based interactions between the viral miRNAs and human genes and human miRNAs and viral genes. Our PANTHER gene function analysis results indicate that viral derived miRNA candidates could target various human genes involved in crucial cellular processes including transcription. For instance, a transcriptional regulator, STAT1 and transcription machinery might be targeted by virus-derived miRNAs. In addition, many known human miRNAs appear to be able to target viral genes. Considering the fact that miRNA-based therapies have been successful before, comprehending mode of actions of miRNAs and their possible roles during SARS-CoV-2 infections could create new opportunities for the development and improvement of new therapeutics.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Antoine Kevorkian", - "author_inst": "TEEM PHOTONICS" - }, - { - "author_name": "Thierry Grenet", - "author_inst": "CNRS" + "author_name": "Muserref Duygu Sacar Demirci", + "author_inst": "Abdullah Gul University" }, { - "author_name": "Hubert Gallee", - "author_inst": "IGE UGA-CNRS" + "author_name": "Aysun Adan", + "author_inst": "Abdullah Gul University" } ], "version": "1", "license": "cc_by_nc_nd", - "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "type": "new results", + "category": "bioinformatics" }, { "rel_doi": "10.1101/2020.03.13.20035261", @@ -1591326,49 +1590552,73 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.03.11.20030957", - "rel_title": "Clinical features and outcomes of 2019 novel coronavirus-infected patients with cardiac injury", + "rel_doi": "10.1101/2020.03.07.20032052", + "rel_title": "Duration of viral detection in throat and rectum of a patient with COVID-19", "rel_date": "2020-03-16", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.11.20030957", - "rel_abs": "AimsTo explore the epidemiological and clinical features of 2019 novel coronavirus(2019-nCoV)-infected patients with cardiac injury.\n\nMethods and resultsData were collected from patients medical records, and we defined cardiac injury according to cardiac biomarker troponin I level > 0.03 g/L. Among the 291 patients, 15 (5.2%) showed evidence of cardiac injury. Of 15 hospitalized patients with cardiac injury, the median age was 65 years, and 11/15 (73.3%) were men. Underlying cardiovascular diseases in some patients were hypertension (n=7, 46.7%), coronary heart disease (n=3, 20%) and diabetes (n=3, 20%). The most common symptoms at illness onset in patients with cardiac injury were fever (n=11, 73.3%), cough (n=7, 46.7%), headache or fatigue (n=5, 33.3%) and dyspnea (n=4, 26.7%). These patients had higher systolic pressures, white blood cell count, neutrophil count, troponin I, brain natriuretic peptide, D-dimer and lower lymphocyte count, and platelet count, compared with patients without cardiac injury, respectively. Bilateral infiltrates on chest X-ray and elevated C-reactive protein occurred in all patients with cardiac injury. Compared with patients without cardiac injury, patients with cardiac injury were more likely to develop acute respiratory distress syndrome, and receive mechanical ventilation, continuous renal replacement therapy, extracorporeal membrane oxygenation and vasopressor therapy and be admitted to the intensive care unit.\n\nConclusionCardiac injury is a common condition among patients infected with 2019-nCoV. Compared with patients without cardiac injury, the clinical outcomes of patients with cardiac injury are relatively worse.", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.07.20032052", + "rel_abs": "The rapid spread of coronavirus disease 2019 (COVID-19) raises concern about a global pandemic. Knowledge about the duration of viral shedding remains important for patient management and infection control. We report the duration of viral detection in throat and rectum of a COVID-19 patient treated at the Hospital for Tropical Diseases in Ho Chi Minh City, Vietnam. Despite clinical recovery, SARS-CoV-2 RNA remained detectable by real time RT-PCR in throat and rectal swabs until day 11 and 18 of hospitalization, respectively. Because live SARS-CoV-2 has been successfully isolated from a stool sample from a COVID-19 patient in China, the results demonstrate that COVID-19 patients may remain infectious for long periods, and fecal-oral transmission may be possible. Therefore, our finding has important implications for infection control.", + "rel_num_authors": 14, "rel_authors": [ { - "author_name": "youbin liu", - "author_inst": "Department of Cardiology, Guangzhou Eighth People's Hospital" + "author_name": "Le Van Tan", + "author_inst": "OUCRU-VN" }, { - "author_name": "Jinglong Li", - "author_inst": "Department of Cardiology, Guangzhou Eighth People's Hospital, Guangzhou, PR China" + "author_name": "Nghiem My Ngoc", + "author_inst": "Hospital for Tropical Diseases, HCMC, Vietnam" }, { - "author_name": "Dehui liu", - "author_inst": "Department of Cardiology, Guangzhou Eighth People's Hospital, Guangzhou, PR China" + "author_name": "Bui Thi Ton That", + "author_inst": "Hospital for Tropical Diseases, HCMC, Vietnam" }, { - "author_name": "Huafeng Song", - "author_inst": "Department of Cardiology, Guangzhou Eighth People's Hospital, Guangzhou, PR China" + "author_name": "Le Thi Tam Uyen", + "author_inst": "Hospital for Tropical Diseases, HCMC, Vietnam" }, { - "author_name": "Chunlin chen", - "author_inst": "Department of Cardiology, Guangzhou Eighth People's Hospital, Guangzhou, PR China" + "author_name": "Nguyen Thi Thu Hong", + "author_inst": "OUCRU-VN" }, { - "author_name": "Mingfang lv", - "author_inst": "Department of Cardiology, Guangzhou Eighth People's Hospital, Guangzhou, PR China" + "author_name": "Nguyen Thi Phuong Dung", + "author_inst": "OUCRU-VN" }, { - "author_name": "Xing pei", - "author_inst": "Department of Cardiology, Guangzhou Eighth People's Hospital, Guangzhou, PR China" + "author_name": "Le Nguyen Truc Nhu", + "author_inst": "OUCRU-VN" }, { - "author_name": "Zhongwei Hu", - "author_inst": "Department of Internal medicine, Guangzhou Eighth People's Hospital" + "author_name": "Tran Tan Thanh", + "author_inst": "OUCRU-VN" + }, + { + "author_name": "Dinh Nguyen Huy Man", + "author_inst": "Hospital for Tropical Diseases, HCMC, Vietnam" + }, + { + "author_name": "Nguyen Thanh Phong", + "author_inst": "Hospital for Tropical Diseases, HCMC, Vietnam" + }, + { + "author_name": "Tran Tinh Hien", + "author_inst": "OUCRU-VN" + }, + { + "author_name": "Nguyen Thanh Truong", + "author_inst": "Hospital for Tropical Diseases, HCMC, Vietnam" + }, + { + "author_name": "Guy Thwaites", + "author_inst": "OUCRU-VN" + }, + { + "author_name": "Nguyen Van Vinh Chau", + "author_inst": "Hospital for Tropical Diseases, HCMC, Vietnam" } ], "version": "1", - "license": "cc_no", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1593164,6 +1592414,85 @@ "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, + { + "rel_doi": "10.1101/2020.03.10.20033761", + "rel_title": "Inferring the number of COVID-19 cases from recently reported deaths", + "rel_date": "2020-03-13", + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.10.20033761", + "rel_abs": "We estimate the number of COVID-19 cases from newly reported deaths in a population without previous reports. Our results suggest that by the time a single death occurs, hundreds to thousands of cases are likely to be present in that population. This suggests containment via contact tracing will be challenging at this point, and other response strategies should be considered. Our approach is implemented in a publicly available, user-friendly, online tool.", + "rel_num_authors": 16, + "rel_authors": [ + { + "author_name": "Thibaut Jombart", + "author_inst": "London School of Hygiene and Tropical Medicine (LSHTM)" + }, + { + "author_name": "Kevin van Zandvoort", + "author_inst": "London School of Hygiene and Tropical Medicine" + }, + { + "author_name": "Tim Russell", + "author_inst": "London School of Hygiene and Tropical Medicine" + }, + { + "author_name": "Christopher Jarvis", + "author_inst": "London School of Hygiene and Tropical Medicine" + }, + { + "author_name": "Amy Gimma", + "author_inst": "London School of Hygiene and Tropical Medicine" + }, + { + "author_name": "Sam Abbott", + "author_inst": "London School of Hygiene and Tropical Medicine" + }, + { + "author_name": "Samuel Clifford", + "author_inst": "London School of Hygiene and Tropical Medicine" + }, + { + "author_name": "Sebastian Funk", + "author_inst": "London School of Hygiene & Tropical Medicine" + }, + { + "author_name": "Hamish Gibbs", + "author_inst": "London School of Hygiene and Tropical Medicine" + }, + { + "author_name": "Yang Liu", + "author_inst": "London School of Hygiene and Tropical Medicine" + }, + { + "author_name": "Carl Pearson", + "author_inst": "London School of Hygiene and Tropical Medicine" + }, + { + "author_name": "Nikos Bosse", + "author_inst": "London School of Hygiene and Tropical Medicine" + }, + { + "author_name": "Centre for the Mathematical Modelling of Infectious Diseases COVID-19 Working Group", + "author_inst": "" + }, + { + "author_name": "Rosalind M Eggo", + "author_inst": "London School of Hygiene & Tropical Medicine" + }, + { + "author_name": "Adam J Kucharski", + "author_inst": "London School of Hygiene & Tropical Medicine" + }, + { + "author_name": "John Edmunds", + "author_inst": "London School of Hygiene and Tropical Medicine" + } + ], + "version": "1", + "license": "cc_by", + "type": "PUBLISHAHEADOFPRINT", + "category": "epidemiology" + }, { "rel_doi": "10.1101/2020.03.11.20034314", "rel_title": "Predicting the cumulative number of cases for the COVID-19 epidemic in China from early data", @@ -1594703,29 +1594032,6 @@ "type": "new results", "category": "microbiology" }, - { - "rel_doi": "10.1101/2020.03.10.20032995", - "rel_title": "Revealing the influence of national public health policies for the outbreak of the SARS-CoV-2 epidemic in Wuhan, China through status dynamic modeling", - "rel_date": "2020-03-12", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.10.20032995", - "rel_abs": "BackgroundThe epidemic caused by SARS-CoV-2 was first reported in Wuhan, China, and now is spreading worldwide. The Chinese government responded to this epidemic with multiple public health policies including locking down the city of Wuhan, establishing multiple temporary hospitals, and prohibiting public gathering events. Here, we constructed a new real-time status dynamic model of SEIO (MH) to reveal the influence of national public health policies and to model the epidemic in Wuhan.\n\nMethodsA real-time status dynamic model was proposed to model the population of Wuhan in status Susceptible (S), Exposed (E), Infected with symptoms (I), with Medical care (M), and Out of the system (O) daily. Model parameters were fitted according to the daily report of new infections from Jan. 27th, 2020 to Feb. 2nd, 2020. Using the fitted parameters, the epidemic under different conditions was simulated and compared with the current situation.\n\nFindingAccording to our study, the first patient is most likely appeared on Nov. 29th, 2019. There had already been 4,153 infected people and 6,536 exposed ones with the basic reproduction number R0 of 2.65 before lockdown, whereas R0 dropped to 1.98 for the first 30 days after the lockdown. The peak point is Feb. 17th, 2020 with 24,115 infected people and the end point is Jun. 17th, 2020. In total, 77,453 people will be infected. If lockdown imposed 7 days earlier, the total number of infected people would be 21,508, while delaying the lockdown by 1-6 days would expand the infection scale 1.23 to 4.94 times. A delay for 7 days would make the epidemic finally out of control. Doubling the number of beds in hospitals would decrease the total infections by 28%, and further investment in bed numbers would yield a diminishing return. Last, public gathering events that increased the transmission parameter by 5% in one single day would increase 4,243 infected people eventually.\n\nInterpretationOur model forecasted that the peak time in Wuhan was Feb. 17th, 2020 and the epidemic in Wuhan is now under control. The outbreak of SARS-CoV-2 is currently a global public health threat for all nations. Multiple countries including South Korea, Japan, Iran, Italy, and the United States are suffering from SARS-CoV-2. Our study, which simulated the epidemic in Wuhan, the first city in the world fighting against SARS-CoV-2, may provide useful guidance for other countries in dealing with similar situations.\n\nFundingNational Natural Science Foundation of China (31900483) and Shanghai Sailing program (19YF1441100).\n\nResearch in contextO_ST_ABSEvidence before this studyC_ST_ABSThe epidemic of SARS-CoV-2 has been currently believed to started from Wuhan, China. The Chinese government started to report the data including infected, cured and dead since Jan 20th, 2020. We searched PubMed and preprint archives for articles published up to Feb 28th, 2020, which contained information about the Wuhan outbreak using the terms of \"SARS-CoV-2\", \"2019-nCoV\", \"COVID-19\", \"public health policies\", \"coronavirus\", \"CoV\", \"Wuhan\", \"transmission model\", etc. And a number of articles were found to forecast the early dynamics of the SARS-CoV-2 epidemic and clinical characteristics of COVID-19. Several of them mentioned the influence of city lockdown, whereas lacked research focused on revealing the impact of public health policies for the outbreak of SARS-CoV-2 through modeling study.\n\nAdded value of this studyAs the first study systemically analysis the effect of three major public health policies including 1) lockdown of Wuhan City, 2) construction of temporary hospitals and 3) reduction of crowed gathering events in Wuhan city. The results demonstrated the epidemic in Wuhan from the potential first patient to the end point as well as the influence of public health policies are expected to provide useful guidance for other countries in fighting against the epidemic of SRAS-CoV-2.\n\nImplications of all the available evidenceAvailable evidence illustrated the human-to-human transmission of SARS-CoV-2, in which the migration of people in China during the epidemic may quickly spread the epidemic to the rest of the nation. These findings also suggested that the lockdown of Wuhan city may slow down the spread of the epidemic in the rest of China.", - "rel_num_authors": 2, - "rel_authors": [ - { - "author_name": "tianyi qiu", - "author_inst": "Fudan University" - }, - { - "author_name": "Han Xiao", - "author_inst": "Aalto University" - } - ], - "version": "1", - "license": "cc_by_nc_nd", - "type": "PUBLISHAHEADOFPRINT", - "category": "health policy" - }, { "rel_doi": "10.1101/2020.03.06.20032342", "rel_title": "Early, low-dose and short-term application of corticosteroid treatment in patients with severe COVID-19 pneumonia: single-center experience from Wuhan, China", @@ -1594773,6 +1594079,33 @@ "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, + { + "rel_doi": "10.1101/2020.03.09.20032045", + "rel_title": "The effectiveness of full and partial travel bans against COVID-19 spread in Australia for travellers from China.", + "rel_date": "2020-03-12", + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.09.20032045", + "rel_abs": "Australia implemented a travel ban on China on February 1st 2020. Partial lifting of the ban is being considered, given the decline in incidence of COVID-19 in China. We modelled three scenarios to test the impact of travel bans on epidemic control in Australia. Scenario one was no ban, scenario two was the current ban followed by a full lifting from the 8th of March 2020, scenario three was a partial lifting of the current ban to allow over 100,000 university students to enter Australia, but not tourists. We used disease incidence data from China and air travel passenger movements between China and Australia, derived from incoming passenger arrival cards. We estimated the true incidence of disease in China using data on expected proportion of under-ascertainment of cases. We used an age specific deterministic model divided in 18 age stratified groups to model the epidemic in each scenario. The modelled epidemic with the full ban fitted the observed incidence of cases well. The modelled epidemic of the current ban predicts 57 cases on March 6th in Australia, compared to 66 observed on this date, however we did not account for imported cases from other countries. The modelled impact without a travel ban implemented on February the 1st shows the epidemic would continue for more than a year resulting in more than 2000 cases and about 400 deaths. The impact of a partial lifting of a ban is minimal, and may be a policy option. Travel restrictions were highly effective for containing the COVID-19 epidemic in Australia and averted a much larger epidemic. The epidemic is still containable if other measures are used in tandem as cases surge in other countries. This research can inform decisions on placing or lifting travel bans as a control measure for the COVID-19 epidemic.", + "rel_num_authors": 3, + "rel_authors": [ + { + "author_name": "Valentina Costantino", + "author_inst": "The Kirby Institute, UNSW Medicine, University of New South Wales, Australia" + }, + { + "author_name": "David James Heslop", + "author_inst": "School of Public Health and Community Medicine, UNSW Medicine, University of New South Wales, Australia" + }, + { + "author_name": "Chandini Raina MacIntyre", + "author_inst": "The Kirby Institute, UNSW Medicine, University of New South Wales" + } + ], + "version": "1", + "license": "cc_by_nc_nd", + "type": "PUBLISHAHEADOFPRINT", + "category": "infectious diseases" + }, { "rel_doi": "10.1101/2020.03.08.20032946", "rel_title": "Quantifying dynamics of SARS-CoV-2 transmission suggests that epidemic control and avoidance is feasible through instantaneous digital contact tracing", @@ -1596784,81 +1596117,6 @@ "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, - { - "rel_doi": "10.1101/2020.03.07.20032524", - "rel_title": "Diagnosis of Acute Respiratory Syndrome Coronavirus 2 Infection by Detection of Nucleocapsid Protein", - "rel_date": "2020-03-10", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.07.20032524", - "rel_abs": "BACKGROUNDNucleic acid test and antibody assay have been employed in the diagnosis for SARS-CoV-2 infection, but the use of viral antigen for diagnosis has not been successfully developed. Theoretically, viral antigen is the specific marker of the virus and precedes antibody appearance within the infected population. There is a clear need of detection of viral antigen for rapid and early diagnosis.\n\nMETHODSWe included a cohort of 239 participants with suspected SARS-CoV-2 infection from 7 centers for the study. We measured nucleocapsid protein in nasopharyngeal swab samples in parallel with the nucleic acid test. Nucleic acid test was taken as the reference standard, and statistical evaluation was taken in blind. We detected nucleocapsid protein in 20 urine samples in another center, employing nasopharyngeal swab nucleic acid test as reference standard.\n\nRESULTSWe developed a fluorescence immunochromatographic assay for detecting nucleocapsid protein of SARS-CoV-2 in nasopharyngeal swab sample and urine within 10 minutes. 100% of nucleocapsid protein positive and negative participants accord with nucleic acid test for same samples. Further, earliest participant after 3 days of fever can be identified by the method. In an additional preliminary study, we detected nucleocapsid protein in urine in 73.6% of diagnosed COVID-19 patients.\n\nCONCLUSIONSThose findings indicate that nucleocapsid protein assay is an accurate, rapid, early and simple method for diagnosis of COVID-19. Appearance of nucleocapsid protein in urine coincides our finding of the SARS-CoV-2 invading kidney and might be of diagnostic value.", - "rel_num_authors": 15, - "rel_authors": [ - { - "author_name": "Bo Diao", - "author_inst": "Department of Medical Laboratory Center, General Hospital of Central Theater Command, Wuhan,People's Republic of China" - }, - { - "author_name": "Kun Wen", - "author_inst": "Microbiome Medicine Center, State Key Laboratory of Organ Failure Research, Division of Laboratory Medicine, Zhujiang Hospital, Southern Medical University, Gua" - }, - { - "author_name": "Jian Chen", - "author_inst": "Institute of Immunology, PLA, Third Military Medical University, Chongqing, People's Republic of China" - }, - { - "author_name": "Yueping Liu", - "author_inst": "Department of Medical Laboratory Center, General Hospital of Central Theater Command, Wuhan, People's Republic of China" - }, - { - "author_name": "Zilin Yuan", - "author_inst": "Department of Medical Laboratory Center, General Hospital of Central Theater Command, Wuhan,People's Republic of China" - }, - { - "author_name": "Chao Han", - "author_inst": "Institute of Immunology, PLA, Third Military Medical University, Chongqing, People's Republic of China" - }, - { - "author_name": "Jiahui Chen", - "author_inst": "Microbiome Medicine Center, State Key Laboratory of Organ Failure Research, Division of Laboratory Medicine, Zhujiang Hospital, Southern Medical University, Gua" - }, - { - "author_name": "Yuxian Pan", - "author_inst": "Microbiome Medicine Center, State Key Laboratory of Organ Failure Research, Division of Laboratory Medicine, Zhujiang Hospital, Southern Medical University, Gua" - }, - { - "author_name": "Li Chen", - "author_inst": "Shenzhen Bioeasy Biotechnology Co. Ltd., Shenzhen,People's Republic of China" - }, - { - "author_name": "Yunjie Dan", - "author_inst": "Department of Infectious Diseases Southwest Hospital,Chongqing,People's Republic of China" - }, - { - "author_name": "Jing Wang", - "author_inst": "Department of Laboratory Diagnosis Chongqing Public Health Medical Center Public Health Hospital of Southwest University Chongqing, People's Republic of China" - }, - { - "author_name": "Yongwen Chen", - "author_inst": "Institute of Immunology, PLA, Third Military Medical University,Chongqing,People's Republic of China" - }, - { - "author_name": "Guohong Deng", - "author_inst": "Department of Infectious Diseases Southwest Hospital,Chongqing,People's Republic of China" - }, - { - "author_name": "Hongwei Zhou", - "author_inst": "Microbiome Medicine Center, State Key Laboratory of Organ Failure Research, Division of Laboratory Medicine, Zhujiang Hospital, Southern Medical University, Gua" - }, - { - "author_name": "Yuzhang Wu", - "author_inst": "Institute of Immunology, PLA, Third Military Medical University,Chongqing,People's Republic of China" - } - ], - "version": "1", - "license": "cc_no", - "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" - }, { "rel_doi": "10.1101/2020.03.09.20032219", "rel_title": "Data-driven discovery of clinical routes for severity detection in COVID-19 pediatric cases", @@ -1596898,6 +1596156,33 @@ "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, + { + "rel_doi": "10.1101/2020.03.08.20032821", + "rel_title": "Clinical Characteristics of Two Human to Human Transmitted Coronaviruses: Corona Virus Disease 2019 versus Middle East Respiratory Syndrome Coronavirus.", + "rel_date": "2020-03-10", + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.08.20032821", + "rel_abs": "After the outbreak of the middle east respiratory syndrome (MERS) worldwide in 2012. Currently, a novel human coronavirus has caused a major disease outbreak, and named corona virus disease 2019 (COVID-19). The emergency of MRES-COV and COVID-19 has caused global panic and threatened health security. Unfortunately, the similarities and differences between the two coronavirus diseases remain to be unknown. The aim of this study, therefore, is to perform a systematic review to compare epidemiological, clinical and laboratory features of COVID-19 and MERS-COV population. We searched PubMed, EMBASE and Cochrane Register of Controlled Trials database to identify potential studies reported COVID-19 or MERS-COV. Epidemiological, clinical and laboratory outcomes, the admission rate of intensive cure unit (ICU), discharge rate and fatality rate were evaluated using GraphPad Prism software. Thirty-two studies involving 3770 patients (COVID-19 = 1062, MERS-COV = 2708) were included in this study. The present study revealed that compared with COVID-19 population, MERS-COV population had a higher rate of ICU admission, discharge and fatality and longer incubation time. It pointed out that fever, cough and generalised weakness and myalgia were main clinical manifestations of both COVID-19 and MERS-COV, whereas ARDS was main complication. The most effective drug for MERS-COV is ribavirin and interferon.", + "rel_num_authors": 3, + "rel_authors": [ + { + "author_name": "Ping Xu", + "author_inst": "Department of Spinal Surgery, The First Affiliated Hospital of Jinan University" + }, + { + "author_name": "Guo-Dong Sun", + "author_inst": "Department of Spinal Surgery, The First Affiliated Hospital of Jinan University" + }, + { + "author_name": "Zhi-Zhong Li", + "author_inst": "The First Affiliated Hospital of Jinan University" + } + ], + "version": "1", + "license": "cc_by_nc_nd", + "type": "PUBLISHAHEADOFPRINT", + "category": "epidemiology" + }, { "rel_doi": "10.1101/2020.03.07.982264", "rel_title": "SARS-CoV-2 sensitive to type I interferon pretreatment.", @@ -1598369,81 +1597654,6 @@ "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, - { - "rel_doi": "10.1101/2020.03.05.976167", - "rel_title": "Direct RNA sequencing and early evolution of SARS-CoV-2", - "rel_date": "2020-03-07", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.03.05.976167", - "rel_abs": "Fundamental aspects of SARS-CoV-2 biology remain to be described, having the potential to provide insight to the response effort for this high-priority pathogen. Here we describe the first native RNA sequence of SARS-CoV-2, detailing the coronaviral transcriptome and epitranscriptome, and share these data publicly. A data-driven inference of viral genetic features and evolutionary rate is also made. The rapid sharing of sequence information throughout the SARS-CoV-2 pandemic represents an inflection point for public health and genomic epidemiology, providing early insights into the biology and evolution of this emerging pathogen.", - "rel_num_authors": 15, - "rel_authors": [ - { - "author_name": "George Taiaroa", - "author_inst": "Department of Microbiology and Immunology, University of Melbourne at The Peter Doherty Institute for Infection and Immunity, Melbourne, Australia" - }, - { - "author_name": "Daniel Rawlinson", - "author_inst": "Department of Microbiology and Immunology, University of Melbourne at The Peter Doherty Institute for Infection and Immunity, Melbourne, Australia" - }, - { - "author_name": "Leo Featherstone", - "author_inst": "Department of Microbiology and Immunology, University of Melbourne at The Peter Doherty Institute for Infection and Immunity, Melbourne, Australia" - }, - { - "author_name": "Miranda Pitt", - "author_inst": "Department of Microbiology and Immunology, University of Melbourne at The Peter Doherty Institute for Infection and Immunity, Melbourne, Australia" - }, - { - "author_name": "Leon Caly", - "author_inst": "Victorian Infectious Diseases Reference Laboratory, Royal Melbourne Hospital, at the Peter Doherty Institute for Infection and Immunity, Victoria, Australia" - }, - { - "author_name": "Julian Druce", - "author_inst": "Victorian Infectious Diseases Reference Laboratory, Royal Melbourne Hospital, at the Peter Doherty Institute for Infection and Immunity, Victoria, Australia" - }, - { - "author_name": "Damian Purcell", - "author_inst": "Department of Microbiology and Immunology, University of Melbourne at The Peter Doherty Institute for Infection and Immunity, Melbourne, Australia" - }, - { - "author_name": "Leigh Harty", - "author_inst": "Department of Microbiology and Immunology, University of Melbourne at The Peter Doherty Institute for Infection and Immunity, Melbourne, Australia" - }, - { - "author_name": "Thomas Tran", - "author_inst": "Victorian Infectious Diseases Reference Laboratory, Royal Melbourne Hospital, at the Peter Doherty Institute for Infection and Immunity, Victoria, Australia" - }, - { - "author_name": "Jason Roberts", - "author_inst": "Victorian Infectious Diseases Reference Laboratory, Royal Melbourne Hospital, at the Peter Doherty Institute for Infection and Immunity, Victoria, Australia" - }, - { - "author_name": "Nichollas Scott", - "author_inst": "Department of Microbiology and Immunology, University of Melbourne at The Peter Doherty Institute for Infection and Immunity, Melbourne, Australia" - }, - { - "author_name": "Mike Catton", - "author_inst": "Victorian Infectious Diseases Reference Laboratory, Royal Melbourne Hospital, at the Peter Doherty Institute for Infection and Immunity, Victoria, Australia" - }, - { - "author_name": "Deborah Williamson", - "author_inst": "Department of Microbiology and Immunology, University of Melbourne at The Peter Doherty Institute for Infection and Immunity, Melbourne, Australia" - }, - { - "author_name": "Lachlan Coin", - "author_inst": "Department of Microbiology and Immunology, University of Melbourne at The Peter Doherty Institute for Infection and Immunity, Melbourne, Australia" - }, - { - "author_name": "Sebastian Duchene", - "author_inst": "Department of Microbiology and Immunology, University of Melbourne at The Peter Doherty Institute for Infection and Immunity, Melbourne, Australia" - } - ], - "version": "1", - "license": "cc_no", - "type": "new results", - "category": "microbiology" - }, { "rel_doi": "10.1101/2020.03.04.976027", "rel_title": "In silico study of the spike protein from SARS-CoV-2 interaction with ACE2: similarity with SARS-CoV, hot-spot analysis and effect of the receptor polymorphism", @@ -1598491,6 +1597701,25 @@ "type": "new results", "category": "bioinformatics" }, + { + "rel_doi": "10.1101/2020.03.04.976258", + "rel_title": "Cryo-electron microscopy structure of the SADS-CoV spike glycoprotein provides insights into an evolution of unique coronavirus spike proteins", + "rel_date": "2020-03-07", + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2020.03.04.976258", + "rel_abs": "The current outbreak of Coronavirus Disease 2019 (COVID-19) by a novel betacoronavirus severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has aroused great public health concern. Coronavirus has a history of causing epidemics in human and animals. In 2017 an outbreak in piglets by a novel coronavirus was emerged designated as swine acute diarrhea syndrome coronavirus (SADS-CoV) which is originated from the same genus of horseshoe bats (Rhinolophus) as Severe Acute Respiratory Syndrome CoV (SARS-CoV) having a broad species tropism. In addition to human cells, it can also infect cell lines from diverse species. Coronavirus host range is determined by its spike glycoprotein (S). Given the importance of S protein in viral entry to cells and host immune responses, here we report the cryo-EM structure of the SADS-CoV S in the prefusion conformation at a resolution of 3.55 [A]. Our study reveals that SADS-CoV S structure takes an intra-subunit quaternary packing mode where the NTD and CTD from the same subunit pack together by facing each other. The comparison of NTD and CTD with that of the other four genera suggests the evolutionary process of the SADS-CoV S. Moreover, SADS-CoV S has several characteristic structural features, such as more compact architecture of S trimer, and masking of epitopes by glycan shielding, which may facilitate viral immune evasion. These data provide new insights into the evolutionary relationships of SADS-CoV S and would extend our understanding of structural and functional diversity, which will facilitate to vaccine development.", + "rel_num_authors": 1, + "rel_authors": [ + { + "author_name": "Songying Ouyang", + "author_inst": "Fujian Normal University" + } + ], + "version": "1", + "license": "cc_by", + "type": "new results", + "category": "microbiology" + }, { "rel_doi": "10.1101/2020.03.04.977736", "rel_title": "Novel Immunoglobulin Domain Proteins Provide Insights into Evolution and Pathogenesis Mechanisms of SARS-Related Coronaviruses", @@ -1600075,33 +1599304,6 @@ "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, - { - "rel_doi": "10.1101/2020.03.02.20030007", - "rel_title": "The timing of one-shot interventions for epidemic control", - "rel_date": "2020-03-06", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.02.20030007", - "rel_abs": "The apparent early success in Chinas large-scale intervention to control the COVID-19 epidemic has led to interest in whether other countries can replicate it as well as concerns about a resurgence of the epidemic if or when China relaxes the interventions. In this paper we look at the impact of a single short-term intervention on an epidemic. We see that if an intervention cannot be sustained long-term, it has the greatest impact if it is imposed once infection levels have become large enough that there is an appreciable number of infections present. For minimising the total number infected it should start close to the peak so that there is no rebound once the intervention is stopped, while to minimise the peak prevalence, it should start earlier, allowing two peaks of comparable size rather than one very large peak. In populations with distinct subgroups, synchronized interventions are less effective than targeting the interventions in each sub-population separately.\n\nWe do not attempt to clearly determine what makes an intervention sustainable or not. We believe that is a policy question. If an intervention is sustainable, it should be kept in place. Our intent is to offer insight into how best to time an intervention whose impact on society is too great to maintain.", - "rel_num_authors": 3, - "rel_authors": [ - { - "author_name": "Francesco Di Lauro", - "author_inst": "University of Sussex" - }, - { - "author_name": "Istv\u00e1n Z Kiss", - "author_inst": "University of Sussex" - }, - { - "author_name": "Joel Miller", - "author_inst": "La Trobe University" - } - ], - "version": "1", - "license": "cc_by", - "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" - }, { "rel_doi": "10.1101/2020.03.02.20030049", "rel_title": "Estimation of COVID-19 outbreak size in Italy based on international case exportations", @@ -1600133,6 +1599335,29 @@ "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, + { + "rel_doi": "10.1101/2020.03.01.20029884", + "rel_title": "Preliminary epidemiological analysis on children and adolescents with novel coronavirus disease 2019 outside Hubei Province in China: an observational study utilizing crowdsourced data", + "rel_date": "2020-03-06", + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.01.20029884", + "rel_abs": "BackgroundThe outbreak of coronavirus disease 2019 (COVID-19) continues to expand across the world. Though both the number of cases and mortality rate in children and adolescents is reported to be low in comparison to adults, limited data has been reported on the outbreak with respect to pediatric patients. To elucidate information, we utilized crowdsourced data to perform a preliminary epidemiologic analysis of pediatric patients with COVID-19\n\nMethodsIn this observational study, data was collected from two open-access, line list crowdsourced online databases. Pediatric cases of COVID-19 were defined as patients [≤]19 years of age with a laboratory confirmed diagnosis. The primary outcomes were case counts and cumulative case counts. Secondary outcomes included days between symptoms onset and first medical care and days between first medical care and reporting. Tertiary outcomes were rate of travel to Wuhan, rate of infected family members and rates of symptoms.\n\nResultsA total of 82 patients were included. The median age was 10 [IQR: 5-15] years. Patients from mainland China (outside Hubei) accounted for 46.3% of cases, while the remaining 53.7% of cases were international. Males and females accounted for 52.4% and 32.9% of cases, respectively, with the remaining 14.6% being designated as unknown. A male skew persisted across subgroup analyses by age group (p=1.0) and location (inside/outside China) (p=0.22). While the number of reported international cases has been steadily increasing over the study period, the number of reported cases in China rapidly decreased from the start point. The median reporting delay was 3 [IQR: 2-4.8] days. The median delay between symptom onset and first seeking medical care was 1 [IQR: 0-3.25] day. In international cases, time to first seeking medical care was a median of 2.5 days longer than in China (p=0.04). When clinical features were reported, fever was the most common presentation (68.0%), followed by cough (36.0%).\n\nConclusionsThe number of reported international pediatric COVID-19 cases is rapidly increasing. COVID-19 infections are, to-date, more common in males than females in both the children and adolescent age groups. Additionally, this male predominance remains the case both inside and outside of China. Crowdsourced data enabled early analysis of epidemiologic variables in pediatric patients with COVID-19. Further data sharing is required to enable analyses that are required to understand the course of this infection in children.", + "rel_num_authors": 2, + "rel_authors": [ + { + "author_name": "Brandon Michael Henry", + "author_inst": "Cardiac Intensive Care Unit, The Heart Institute, Cincinnati Children's Hospital Medical Center" + }, + { + "author_name": "Maria Helena S Oliveira", + "author_inst": "Department of Statistics, Federal University of Parana, Curitiba, Brazil" + } + ], + "version": "1", + "license": "cc_by_nc_nd", + "type": "PUBLISHAHEADOFPRINT", + "category": "infectious diseases" + }, { "rel_doi": "10.1101/2020.03.02.20029975", "rel_title": "Exuberant elevation of IP-10, MCP-3 and IL-1ra during SARS-CoV-2 infection is associated with disease severity and fatal outcome", @@ -1601768,53 +1600993,6 @@ "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, - { - "rel_doi": "10.1101/2020.03.01.20029819", - "rel_title": "COVID-19 Epidemic Outside China: 34 Founders and Exponential Growth", - "rel_date": "2020-03-03", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.01.20029819", - "rel_abs": "BackgroundIn December 2019, pneumonia infected with a novel coronavirus burst in Wuhan, China. Now the situation is almost controlled in China but is worse outside China. We aimed to build a mathematical model to capture the global trend of epidemics outside China.\n\nMethodsIn this retrospective, outside-China diagnosis number reported from Jan 21 to Feb 28, 2020 was downloaded from WHO website. We develop a simple regression model on these numbers: O_FD O_INLINEFIG[Formula 1]C_INLINEFIGM_FD(1)C_FD where Nt is the total diagnosed patient till the ith day, t=1 at Feb 1.\n\nFindingsBased on this model, we estimate that there have been about 34 unobserved founder patients at the beginning of spread outside China. The global trend is approximately exponential, with the rate of 10 folds every 19 days.\n\nResearch in contextO_ST_ABSEvidence before this studyC_ST_ABSIn December 2019, pneumonia infected with a novel coronavirus burst in Wuhan, China. Now the situation is almost controlled in China but is worse outside China. Now there are 4,691 patients across 51 countries and territories outside China. We searched PubMed and the China National Knowledge Infrastructure database for articles published up to Feb 28, 2020, using the keywords \"COVID\", \"novel coronavirus\", \"2019-nCoV\" or \"2019 novel coronavirus\". No published work about the global trend of epidemics outside China could be identified.\n\nAdded value of this studyWe built a simple \"log-plus\" linear model to capture the global trend of epidemics outside China. We estimate that there have been about 34 unobserved founder patients at the beginning of spread outside China. The global trend is approximately exponential, with the rate of 10 folds every 19 days.\n\nImplications of all the available evidenceWith the limited number of data points and the complexity of the real situation, a straightforward model is expected to work better. Our model suggests that the COVID-19 disease follows an approximate exponential growth model stably at the very beginning. We predict that the number of confirmed patients outside China will increase ten folds in every 19 days without strong intervention by applying our model. Powerful actions on public health should be taken to combat this epidemic all over the world.", - "rel_num_authors": 8, - "rel_authors": [ - { - "author_name": "Yi Li", - "author_inst": "Fudan University" - }, - { - "author_name": "Meng Liang", - "author_inst": "Fudan University" - }, - { - "author_name": "Xianhong Yin", - "author_inst": "Fudan University" - }, - { - "author_name": "Xiaoyu Liu", - "author_inst": "Fudan University" - }, - { - "author_name": "Meng Hao", - "author_inst": "Fudan University" - }, - { - "author_name": "Zixin Hu", - "author_inst": "Fudan University" - }, - { - "author_name": "Yi Wang", - "author_inst": "Fudan University" - }, - { - "author_name": "Li Jin", - "author_inst": "Fudan University" - } - ], - "version": "1", - "license": "cc_by_nc_nd", - "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" - }, { "rel_doi": "10.1101/2020.02.29.20029322", "rel_title": "Vicarious traumatization in the general public, members, and non-members of medical teams aiding in COVID-19 control", @@ -1601926,6 +1601104,37 @@ "type": "PUBLISHAHEADOFPRINT", "category": "psychiatry and clinical psychology" }, + { + "rel_doi": "10.1101/2020.02.29.20029413", + "rel_title": "The spatiotemporal estimation of the dynamic risk and the international transmission of 2019 Novel Coronavirus (COVID-19) outbreak: A global perspective", + "rel_date": "2020-03-03", + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.02.29.20029413", + "rel_abs": "An ongoing novel coronavirus SARS-CoV-2 pneumonia infection outbreak called COVID-19 started in Wuhan, Hubei Province, China, in December 2019. It both spread rapidly to all provinces in China and started spreading around the world quickly through international human movement from January 2020. Currently, the spatiotemporal epidemic transmission patterns, prediction models, and possible risk analysis for the future are insufficient for COVID-19 but we urgently need relevant information, particularly from the global perspective.\n\nWe have developed a novel two-stage simulation model to simulate the spatiotemporal changes in the number of COVID-19 cases and estimate the future worldwide risk. Based on the connectivity of countries to China and the countrys medical and epidemic prevention capabilities, different scenarios are generated to analyze the possible transmission throughout the world and use this information to evaluate each countrys vulnerability to and the dynamic risk of COVID-19.\n\nCountries vulnerability to the COVID-19 outbreak from China is calculated for 63 countries around the world. Taiwan, South Korea, Hong Kong, and Japan are the most vulnerable areas. The relationship between each countrys vulnerability and days before the first imported case occurred shows a very high exponential decrease. The cumulative number of cases in each country also has a linear relationship with vulnerability, which can compare and quantify the initial epidemic prevention capabilities to various countries management strategies. In total, 1,000 simulation results of future cases around the world are generated for the spatiotemporal risk assessment. According to the simulation results of this study, if there is no specific medicine for it, it will likely form a global pandemic. This method can be used as a preliminary risk assessment of the spatiotemporal spread for a new global epidemic. * Note: This study was completed on February 15, 2020.", + "rel_num_authors": 4, + "rel_authors": [ + { + "author_name": "Yuan-Chien Lin", + "author_inst": "Department of Civil Engineering, National Central University" + }, + { + "author_name": "Wan-Ju Chi", + "author_inst": "Department of Civil Engineering, National Central University" + }, + { + "author_name": "Yu-Ting Lin", + "author_inst": "Department of Civil Engineering, National Central University" + }, + { + "author_name": "Chun-Yeh Lai", + "author_inst": "Department of Civil Engineering, National Central University" + } + ], + "version": "1", + "license": "cc_by_nc_nd", + "type": "PUBLISHAHEADOFPRINT", + "category": "public and global health" + }, { "rel_doi": "10.1101/2020.02.29.20029561", "rel_title": "A simple model to assess Wuhan lock-down effect and region efforts during COVID-19 epidemic in China Mainland", @@ -1603778,41 +1602987,6 @@ "type": "new results", "category": "bioinformatics" }, - { - "rel_doi": "10.1101/2020.02.27.969006", - "rel_title": "Comparative genomic analysis revealed specific mutation pattern between human coronavirus SARS-CoV-2 and Bat-SARSr-CoV RaTG13", - "rel_date": "2020-03-02", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.02.27.969006", - "rel_abs": "The novel coronavirus SARS-CoV-2 (2019-nCoV) is a member of the family coronaviridae and contains a single-stranded RNA genome with positive-polarity. To reveal the evolution mechanism of SARS-CoV-2 genome, we performed comprehensive genomic analysis with newly sequenced SARS-CoV-2 strains and 20 closely related coronavirus strains. Among 98 nucleotide mutations at 93 sites of the genome among different SARS-CoV-2 strains, 58 of them caused amino acid change, indicating a result of neutral evolution. However, the ratio of nucleotide substitutions to amino acid substitutions of spike gene (9.07) between SARS-CoV-2 WIV04 and Bat-SARSr-CoV RaTG13 was extensively higher than those from comparisons between other coronaviruses (range 1.29 - 4.81). The elevated synonymous mutations between SARS-CoV-2 and RaTG13, suggesting they underwent stronger purifying selection. Moreover, their nucleotide substitutions are enriched with T:C transition, which is consistent with the mutation signature caused by deactivity of RNA 3-to-5 exoribonuclease (ExoN). The codon usage was similar between SARS-CoV-2 and other strains in beta-coronavirus lineage B, suggesting it had small impact on the mutation pattern. In comparison of SARS-CoV-2 WIV04 with Bat-SARSr-CoV RaTG13, the ratios of non-synonymous to synonymous substitution rates (dN/dS) was the lowest among all performed comparisons, reconfirming the evolution of SARS-CoV-2 under stringent selective pressure. Moreover, some sites of spike protein might be subjected to positive selection. Therefore, our results will help understanding the evolutionary mechanisms contribute to viral pathogenicity and its adaptation with hosts.", - "rel_num_authors": 5, - "rel_authors": [ - { - "author_name": "Longxian Lv", - "author_inst": "College of Medicine, Zhejiang University" - }, - { - "author_name": "Gaolei Li", - "author_inst": "Zhejiang Gongshang University" - }, - { - "author_name": "Jinhui Chen", - "author_inst": "Jiaxing University" - }, - { - "author_name": "Xinle Liang", - "author_inst": "Zhejiang Gongshang University" - }, - { - "author_name": "Yudong Li", - "author_inst": "Zhejiang Gongshang University" - } - ], - "version": "1", - "license": "cc_by_nd", - "type": "new results", - "category": "genomics" - }, { "rel_doi": "10.1101/2020.03.01.971499", "rel_title": "Kallikrein 13: a new player in coronaviral infections.", @@ -1603876,6 +1603050,45 @@ "type": "new results", "category": "microbiology" }, + { + "rel_doi": "10.1101/2020.02.27.968008", + "rel_title": "Molecular Dynamics Simulations Indicate the COVID-19 Mpro Is Not a Viable Target for Small-Molecule Inhibitors Design", + "rel_date": "2020-03-02", + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2020.02.27.968008", + "rel_abs": "The novel coronavirus whose outbreak took place in December 2019 continues to spread at a rapid rate worldwide. In the absence of an effective vaccine, inhibitor repurposing or de novo drug design may offer a longer-term strategy to combat this and future infections due to similar viruses. Here, we report on detailed classical and mix-solvent molecular dynamics simulations of the main protease (Mpro) enriched by evolutionary and stability analysis of the protein. The results were compared with those for a highly similar SARS Mpro protein. In spite of a high level of sequence similarity, the active sites in both proteins show major differences in both shape and size indicating that repurposing SARS drugs for COVID-19 may be futile. Furthermore, analysis of the binding sites conformational changes during the simulation time indicates its flexibility and plasticity, which dashes hopes for rapid and reliable drug design. Conversely, structural stability of the protein with respect to flexible loop mutations indicates that the virus mutability will pose a further challenge to the rational design of small-molecule inhibitors. However, few residues contribute significantly to the protein stability and thus can be considered as key anchoring residues for Mpro inhibitor design.", + "rel_num_authors": 6, + "rel_authors": [ + { + "author_name": "Maria Bzowka", + "author_inst": "Tunneling Group, Biotechnology Centre, Silesian University of Technology" + }, + { + "author_name": "Karolina Mitusinska", + "author_inst": "Tunneling Group, Biotechnology Centre, Silesian University of Technology" + }, + { + "author_name": "Agata Raczynska", + "author_inst": "Tunneling Group, Biotechnology Centre, Silesian University of Technology" + }, + { + "author_name": "Aleksandra Samol", + "author_inst": "Tunneling Group, Biotechnology Centre, Silesian University of Technology" + }, + { + "author_name": "Jack Adam Tuszynski", + "author_inst": "Department of Physics, University of Alberta, Edmonton" + }, + { + "author_name": "Artur Gora", + "author_inst": "Tunneling Group, Biotechnology Centre, Silesian University of Technology" + } + ], + "version": "1", + "license": "cc_by_nc_nd", + "type": "new results", + "category": "molecular biology" + }, { "rel_doi": "10.1101/2020.02.29.965418", "rel_title": "The within-host viral kinetics of SARS-CoV-2", @@ -1605087,41 +1604300,6 @@ "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, - { - "rel_doi": "10.1101/2020.02.27.967885", - "rel_title": "Prediction of receptorome for human-infecting virome", - "rel_date": "2020-02-28", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.02.27.967885", - "rel_abs": "The virus receptors are key for the viral infection of host cells. Identification of the virus receptors is still challenging at present. Our previous study has shown that human virus receptor proteins have some unique features including high N-glycosylation level, high number of interaction partners and high expression level. Here, a random-forest model was built to identify human virus receptorome from human cell membrane proteins with an accepted accuracy based on the combination of the unique features of human virus receptors and protein sequences. A total of 1380 human cell membrane proteins were predicted to constitute the receptorome of the human-infecting virome. In addition, the combination of the random-forest model with protein-protein interactions between human and viruses predicted in previous studies enabled further prediction of the receptors for 693 human-infecting viruses, such as the Enterovirus, Norovirus and West Nile virus. As far as we know, this study is the first attempt to predict the receptorome for the human-infecting virome and would greatly facilitate the identification of the receptors for viruses.", - "rel_num_authors": 5, - "rel_authors": [ - { - "author_name": "Zheng Zhang", - "author_inst": "College of Biology, Hunan Provincial Key Laboratory of Medical Virology, Hunan University, Changsha 410082, China" - }, - { - "author_name": "Sifan Ye", - "author_inst": "College of Biology, Hunan Provincial Key Laboratory of Medical Virology, Hunan University, Changsha 410082, China" - }, - { - "author_name": "Aiping Wu", - "author_inst": "Center for Systems Medicine, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100005, Suzhou Ins" - }, - { - "author_name": "Taijiao Jiang", - "author_inst": "Center for Systems Medicine, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100005, Suzhou Ins" - }, - { - "author_name": "Yousong Peng", - "author_inst": "College of Biology, Hunan Provincial Key Laboratory of Medical Virology, Hunan University, Changsha 410082, China" - } - ], - "version": "1", - "license": "cc_no", - "type": "new results", - "category": "bioinformatics" - }, { "rel_doi": "10.1101/2020.02.26.20028191", "rel_title": "Clinical characteristics of 82 death cases with COVID-19", @@ -1605249,6 +1604427,85 @@ "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, + { + "rel_doi": "10.1101/2020.02.26.20028225", + "rel_title": "Clinical features and sexual transmission potential of SARS-CoV-2 infected female patients: a descriptive study in Wuhan, China", + "rel_date": "2020-02-27", + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.02.26.20028225", + "rel_abs": "BackgroundAs of March 2, 2020, SARS-CoV-2 has infected more than 80174 people and caused 2915 deaths in China. This virus rapidly spreads to 56 countries worldwide. Thus, in order to effectively block its transmission, it is urgent to uncover all the possible transmission routes of SARS-CoV-2.\n\nMethodsFrom January 28 to February 18, 2020, 35 female patients diagnosed with COVID-19 in Tongji Hospital were included in this descriptive study. The gynecologic history, clinical characteristics, laboratory findings and chest computed tomography (CT) of all patients were recorded in detail. To examine whether there is sexual transmission through vaginal from female to her partner, we employed real-time polymerase chain reaction testing (RT-PCR) to detect SARS-CoV-2 in vaginal environment (including vaginal discharge, cervical or vaginal residual exfoliated cells) and anal swab samples, and inquired recent sexual behaviors from the patients.\n\nFindingsThe age range of the 35 patients with COVID-19 was 37-88 years. Over 50% patients infected with SARS-CoV-2 had chronic diseases. We tested the vaginal environment and anal swabs from the 35 female patients with COVID-19 and found that only an anal swab sample from one patient was positive for SARS-CoV-2. All the samples from vaginal environment were negative for SARS-CoV-2. The infection rate of the patients sexual partner was 42{middle dot}9%. Additionally, two female patients admitted having sex with their partners during a possible infection incubation period, while one patients partner was uninfected and the other patients partner was diagnosed with COVID-19 (after the diagnosis of the female patient).\n\nConclusionNo positive RT-PCR result was found in the vaginal environment perhaps due to the lack of ACE2 expression, which is the receptor of SARS-CoV-2, in the vagina and cervix tissues (human protein atlas). The results from this study show no evidence of transmission of SARS-CoV-2 through vaginal sex from female to her partner. However, the risk of infection of non vaginal sex and other intimate contacts during vaginal sex should not be ignored.\n\nFundingThis work was financially supported by the Clinical Research Pilot Project of Tongji hospital, Huazhong University of Science and Technology (No. 2019CR205).", + "rel_num_authors": 16, + "rel_authors": [ + { + "author_name": "Pengfei Cui", + "author_inst": "Department of Obstetrics and Gynecology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China." + }, + { + "author_name": "Zhe Chen", + "author_inst": "Department of Obstetrics and Gynecology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China." + }, + { + "author_name": "Tian Wang", + "author_inst": "Department of Obstetrics and Gynecology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China." + }, + { + "author_name": "Jun Dai", + "author_inst": "Department of Obstetrics and Gynecology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China." + }, + { + "author_name": "Jinjin Zhang", + "author_inst": "Department of Obstetrics and Gynecology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China." + }, + { + "author_name": "Ting Ding", + "author_inst": "Department of Obstetrics and Gynecology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China." + }, + { + "author_name": "Jingjing Jiang", + "author_inst": "Department of Obstetrics and Gynecology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China." + }, + { + "author_name": "Jia Liu", + "author_inst": "Department of Obstetrics and Gynecology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China." + }, + { + "author_name": "Cong Zhang", + "author_inst": "Department of Obstetrics and Gynecology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China." + }, + { + "author_name": "Wanying Shan", + "author_inst": "Department of Obstetrics and Gynecology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China." + }, + { + "author_name": "Sheng Wang", + "author_inst": "Department of Obstetrics and Gynecology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China." + }, + { + "author_name": "Yueguang Rong", + "author_inst": "Department of Pathogen Biology, School of Basic Medicine, Huazhong University of Science and Technology, Wuhan, 430030, China" + }, + { + "author_name": "Jiang Chang", + "author_inst": "Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of" + }, + { + "author_name": "Xiaoping Miao", + "author_inst": "Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of" + }, + { + "author_name": "Xiangyi Ma", + "author_inst": "Department of Obstetrics and Gynecology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China." + }, + { + "author_name": "Shixuan Wang", + "author_inst": "Department of Obstetrics and Gynecology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China." + } + ], + "version": "1", + "license": "cc_no", + "type": "PUBLISHAHEADOFPRINT", + "category": "infectious diseases" + }, { "rel_doi": "10.1101/2020.02.26.20028308", "rel_title": "Perceptions of the Adult US Population regarding the Novel Coronavirus Outbreak", @@ -1606882,100 +1606139,76 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.02.23.20026690", - "rel_title": "The landscape of lung bronchoalveolar immune cells in COVID-19 revealed by single-cell RNA sequencing", + "rel_doi": "10.1101/2020.02.26.20028076", + "rel_title": "Case fatality rate of novel coronavirus disease 2019 in China", "rel_date": "2020-02-26", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.02.23.20026690", - "rel_abs": "The novel coronavirus SARS-CoV-2, etiological agent of recently named Coronavirus infected disease (COVID-19) by WHO, has caused more than 2, 000 deaths worldwide since its emergency in Wuhan City, Hubei province, China, in December, 2019. The symptoms of COVID-19 varied from modest, mild to acute respiratory distress syndrome (ARDS), and the latter of which is generally associated with deregulated immune cytokine production; however, we currently know little as to the interplay between the extent of clinical symptoms and the compositions of lung immune microenvironment. Here, we comprehensively characterized the lung immune microenvironment with the bronchoalveolar lavage fluid (BALF) from 3 severe and 3 mild COVID-19 patients and 8 previously reported healthy lung controls through single-cell RNA sequence (scRNA-seq) combined with TCR-seq. Our data shows that monocyte-derived FCN1+ macrophages, whereas notFABP4+ alveolar macrophages that represent a predominant macrophage subset in BALF from patients with mild diseases, overwhelm in the severely damaged lungs from patients with ARDS. These cells are highly inflammatory and enormous chemokine producers implicated in cytokine storm. Furthermore, the formation of tissue resident, highly expanded clonal CD8+ T cells in the lung microenvironment of mild symptom patients suggests a robust adaptive immune response connected to a better control of COVID-19. This study first reported the cellular atlas of lung bronchoalveolar immune microenvironment in COVID-19 patients at the single-cell resolution, and unveiled the potential immune mechanisms underlying disease progression and protection in COVID-19.\n\nHighlightsO_LIImmune microenvironment of SARS-CoV-2-infected lungs revealed by scRNA/TCR seq\nC_LIO_LIIncreased inflammatory FCN1+ macrophages are replacing FABP4+ macrophages in the BALF from severe COVID-19 patients\nC_LIO_LIHighly expanded and functional competent tissue resident clonal CD8+ T cells in mild COVID-19 patients\nC_LI", - "rel_num_authors": 13, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.02.26.20028076", + "rel_abs": "BackgroundA pandemic of coronavirus disease 2019 (COVID-19) which have caused more than 80 thousand persons infected globally is still ongoing. This study aims to calculate its case fatality rate (CFR).\n\nMethodsThe method, termed as converged CFR calculation, was based on the formula of dividing the number of known deaths by the number of confirmed cases T days before, where T was an average time period from case confirmation to death. It was found that supposing a T, if it was smaller (bigger) than the true T, calculated CFRs would gradually increase (decrease) to infinitely near the true T with time went on. According to the law, the true T value could be determined by trends of daily CFRs calculated with different assumed T values (left of true T is decreasing, right is increasing). Then the CFR could be calculated.\n\nResultsCFR of COVID-19 in China except Hubei Province was 0.8% to 0.9%. So far, the CFR had accurately predicted the death numbers more than 3 weeks. CFR in Hubei of China was 5.4% by which the calculated death number corresponded with the reported number for 2 weeks.\n\nConclusionThe method could be used for CFR calculating while pandemics are still ongoing. Dynamic monitoring of the daily CFRs trends could help outbreak-controller to have a clear vision in the timeliness of the case confirmation.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Minfeng Liao", - "author_inst": "Institute for Hepatology" - }, - { - "author_name": "Yang Liu", - "author_inst": "Institute for Hepatology" - }, - { - "author_name": "Jin Yuan", - "author_inst": "Shenzhen Third Peoples Hospital" - }, - { - "author_name": "Yanling Wen", - "author_inst": "Institute for Hepatology" - }, - { - "author_name": "Gang Xu", - "author_inst": "Institute for Hepatology" - }, - { - "author_name": "Juanjuan Zhao", - "author_inst": "Institute for Hepatology" - }, - { - "author_name": "Lin Chen", - "author_inst": "Institute for Hepatology" - }, - { - "author_name": "Jinxiu Li", - "author_inst": "Shenzhen Third Peoples Hospital" - }, - { - "author_name": "Xin Wang", - "author_inst": "Institute for Hepatology" - }, - { - "author_name": "Fuxiang Wang", - "author_inst": "Shenzhen Third Peoples Hospital" + "author_name": "Rui Qi", + "author_inst": "Wuhan University" }, { - "author_name": "Lei Liu", - "author_inst": "Shenzhen Third Peoples Hospital" + "author_name": "Chao Ye", + "author_inst": "Shandong Maternal and Child Health Care Hospital" }, { - "author_name": "Shuye Zhang", - "author_inst": "Shanghai Public Health Clinical Center and Institute of Biomedical Sciences" + "author_name": "Xiang-rong Qin", + "author_inst": "Wuhan University" }, { - "author_name": "Zheng Zhang", - "author_inst": "Institute for Hepatology" + "author_name": "Xue-Jie Yu", + "author_inst": "Wuhan University School of Health Sciences, State Key Laboratory of Virology, Wuhan University, Wuhan, Hubei Province, China." } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "allergy and immunology" + "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.02.26.20028076", - "rel_title": "Case fatality rate of novel coronavirus disease 2019 in China", + "rel_doi": "10.1101/2020.02.21.20026229", + "rel_title": "Epidemiological Development of Novel Coronavirus Pneumonia in China and Its Forecast", "rel_date": "2020-02-26", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.02.26.20028076", - "rel_abs": "BackgroundA pandemic of coronavirus disease 2019 (COVID-19) which have caused more than 80 thousand persons infected globally is still ongoing. This study aims to calculate its case fatality rate (CFR).\n\nMethodsThe method, termed as converged CFR calculation, was based on the formula of dividing the number of known deaths by the number of confirmed cases T days before, where T was an average time period from case confirmation to death. It was found that supposing a T, if it was smaller (bigger) than the true T, calculated CFRs would gradually increase (decrease) to infinitely near the true T with time went on. According to the law, the true T value could be determined by trends of daily CFRs calculated with different assumed T values (left of true T is decreasing, right is increasing). Then the CFR could be calculated.\n\nResultsCFR of COVID-19 in China except Hubei Province was 0.8% to 0.9%. So far, the CFR had accurately predicted the death numbers more than 3 weeks. CFR in Hubei of China was 5.4% by which the calculated death number corresponded with the reported number for 2 weeks.\n\nConclusionThe method could be used for CFR calculating while pandemics are still ongoing. Dynamic monitoring of the daily CFRs trends could help outbreak-controller to have a clear vision in the timeliness of the case confirmation.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.02.21.20026229", + "rel_abs": "BACKGROUND AND OBJECTIVEThe novel coronavirus (SARS-Cov-2) infected coronavirus disease 2019 (COVID-19) was broken out in Wuhan and Hubei province for more than a month. It severely threats peoples health of thousands in Chin and even other countries. In order to prevent its wide spread, it is necessary to understand the development of the epidemic with precise mathematical language.\n\nMETHODSThe various data of novel coronavirus pneumonia were collected from the official websites of the National Health Committee of the Peoples Republic of China. According to epidemic and administrative division, three groups were divided to analyze the data, Hubei Province (including Wuhan), nationwide without Hubei and Henan Province. With classic SIR models, the fitting epidemiological curves of incidence have made, and basic reproduction number (R0) was also calculated as well. Therefore the diseases infection intensity, peak time and the epidemiological end time can be deduced.\n\nRESULTS(1) Wuhan was the origin place of the epidemic, then it spread to Hubei province quickly. The patients in Hubei had increased rapidly with exponential rise. According to data in Hubei province, the fitting parabolas were made, and some with 51,673 cases. R0 curve shows with S-curve, at early breakout, R0 was as high as 6.27, then it decrease gradually. It is expected to approach to zero in early May; (2) In the group of nationwide without Hubei, the patient cases were much lower than Hubei, but its epidemiological fitting curve also shows a parabola as Hubei. The peak will arrive around February 10 with 9,145 cases. At beginning, R0 was as high as 2.44, then it decreases gradually and approach to zero in the end of March. (3) In Henan Province, the incidence stays very low, the parabolic fitting curve is similar to the nationwide without Hubei. The epidemic is expected to reach the peak on around February 12 and end in early April.\n\nCONCLUSIONThe epidemic development in all three groups shows parabolic curves. Their incidences are expected to reach their peaks on February 18 in Hubei, on February 10 in other areas of China. The epidemic will end in early May in Hubei, and in early April in other areas of China. Our study may provide useful knowledge for the government to make prevention and treatment policies.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Rui Qi", - "author_inst": "Wuhan University" + "author_name": "Shan shan Wu", + "author_inst": "Research Institute of Population and Family Planning" }, { - "author_name": "Chao Ye", - "author_inst": "Shandong Maternal and Child Health Care Hospital" + "author_name": "Pan pan Sun", + "author_inst": "Research Institute of Population and Family Planning" }, { - "author_name": "Xiang-rong Qin", - "author_inst": "Wuhan University" + "author_name": "Rui ling Li", + "author_inst": "Henan university" }, { - "author_name": "Xue-Jie Yu", - "author_inst": "Wuhan University School of Health Sciences, State Key Laboratory of Virology, Wuhan University, Wuhan, Hubei Province, China." + "author_name": "Liang Zhao", + "author_inst": "Research Institute of Population and Family Planning" + }, + { + "author_name": "Yan li Wang IV", + "author_inst": "Research Institute of Population and Family Planning" + }, + { + "author_name": "Li fang Jiang", + "author_inst": "Research Institute of Population and Family Planning" + }, + { + "author_name": "Jin Bo Deng", + "author_inst": "Research Institute of Population and Family Planning" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1608475,37 +1607708,6 @@ "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, - { - "rel_doi": "10.1101/2020.02.23.961912", - "rel_title": "Cryo-EM structures of HKU2 and SADS-CoV spike glycoproteins and insights into coronavirus evolution", - "rel_date": "2020-02-24", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.02.23.961912", - "rel_abs": "A new porcine coronavirus SADS-CoV was recently identified from suckling piglets with severe diarrhea in southern China and its genome sequence is most identical (~95% identity) to that of bat -coronavirus HKU2. It again indicates bats are the natural reservoir of many coronaviruses that have great potential for cross-species transmission to animals and humans by recombination and/or mutation. Here we report the cryo-EM structures of HKU2 and SADS-CoV spike glycoprotein trimers at 2.38 [A] and 2.83 [A] resolution, respectively. HKU2 and SADS-CoV spikes exhibit very high structural similarity, with subtle differences mainly distributed in the NTD and CTD of the S1 subunit responsible for cell attachment and receptor binding. We systematically analyzed and compared the NTD, CTD, SD1 and SD2 domains of the S1 subunit and the S2 subunit of HKU2 spike with those of -, {beta}-, {gamma}-, and {delta}-coronavirus spikes. The results show that the NTD and CTD of HKU2/SADS-CoV are probably the most ancestral in the evolution of spike. Although the S2 subunit mediating membrane fusion is highly conserved, the connecting region after fusion peptide in HKU2/SADS-CoV S2 subunit also adopts a conformation distinct from other coronaviruses. These results structurally demonstrate a close evolutionary relationship between HKU2 /SADS-CoV and {beta}-coronavirus spikes and provide new insights into the evolution and cross-species transmission of coronaviruses.", - "rel_num_authors": 4, - "rel_authors": [ - { - "author_name": "Jinfang Yu", - "author_inst": "Tsinghua University" - }, - { - "author_name": "Shuyuan Qiao", - "author_inst": "Tsinghua University" - }, - { - "author_name": "Runyu Guo", - "author_inst": "Tsinghua University" - }, - { - "author_name": "Xinquan Wang", - "author_inst": "Tsinghua University" - } - ], - "version": "1", - "license": "cc_no", - "type": "new results", - "category": "biochemistry" - }, { "rel_doi": "10.1101/2020.02.20.20025957", "rel_title": "From Isolation to Coordination: How Can Telemedicine Help Combat the COVID-19 Outbreak?", @@ -1608561,6 +1607763,93 @@ "type": "PUBLISHAHEADOFPRINT", "category": "health systems and quality improvement" }, + { + "rel_doi": "10.1101/2020.02.19.20024885", + "rel_title": "Comparative study of the lymphocyte change between COVID-19 and non-COVID-19 pneumonia cases suggesting uncontrolled inflammation might not be the main reason of tissue injury", + "rel_date": "2020-02-23", + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.02.19.20024885", + "rel_abs": "Disclaimer statementThe authors have withdrawn this manuscript because the statistical methods in our manuscript need to be modified and we are going to improve the statistical methods and try to give more precise model. Therefore, the authors do not wish this work to be cited as reference for the project. If you have any questions, please contact the corresponding author.", + "rel_num_authors": 18, + "rel_authors": [ + { + "author_name": "Yishan Zheng", + "author_inst": "The Second Hospital of Nanjing" + }, + { + "author_name": "Zhen Huang", + "author_inst": "Nanjing University" + }, + { + "author_name": "Guoping Ying", + "author_inst": "The Second Hospital of Nanjing" + }, + { + "author_name": "Xia Zhang", + "author_inst": "The Second Hospital of Nanjing" + }, + { + "author_name": "Wei Ye", + "author_inst": "The Second Hospital of Nanjing" + }, + { + "author_name": "Zhiliang Hu", + "author_inst": "The Second Hospital of Nanjing" + }, + { + "author_name": "Chunmei Hu", + "author_inst": "The Second Hospital of Nanjing" + }, + { + "author_name": "Hongxia Wei", + "author_inst": "The Second Hospital of Nanjing" + }, + { + "author_name": "Yi Zeng", + "author_inst": "The Second Hospital of Nanjing" + }, + { + "author_name": "Yun Chi", + "author_inst": "The Second Hospital of Nanjing" + }, + { + "author_name": "Cong Cheng", + "author_inst": "The Second Hospital of Nanjing" + }, + { + "author_name": "Feishen Lin", + "author_inst": "The Second Hospital of Nanjing" + }, + { + "author_name": "Hu Lu", + "author_inst": "The Second Hospital of Nanjing" + }, + { + "author_name": "Lingyan Xiao", + "author_inst": "The Second Hospital of Nanjing" + }, + { + "author_name": "Yan Song", + "author_inst": "The Second Hospital of Nanjing" + }, + { + "author_name": "Chunming Wang", + "author_inst": "University of Macau" + }, + { + "author_name": "Yongxiang Yi", + "author_inst": "The Second Hospital of Nanjing" + }, + { + "author_name": "Lei Dong", + "author_inst": "Nanjing University" + } + ], + "version": "1", + "license": "cc_no", + "type": "PUBLISHAHEADOFPRINT", + "category": "infectious diseases" + }, { "rel_doi": "10.1101/2020.02.21.20026328", "rel_title": "Evolving epidemiology of novel coronavirus diseases 2019 and possible interruption of local transmission outside Hubei Province in China: a descriptive and modeling study", @@ -1610172,85 +1609461,6 @@ "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, - { - "rel_doi": "10.1101/2020.02.15.20023457", - "rel_title": "Profiling ACE2 expression in colon tissue of healthy adults and colorectal cancer patients by single-cell transcriptome analysis", - "rel_date": "2020-02-23", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.02.15.20023457", - "rel_abs": "A newly identified novel coronavirus (2019-nCoV) has caused numerous acute respiratory syndrome cases in Wuhan China from December 2019 to Feb 2020. Its fast spreading to other provinces in China and overseas is very likely causing a pandemic. Since the novel coronavirus has been reported to be capable of endangering thousands of lives, it is extremely important to find out how the coronavirus is transmitted in human organs. Apart from fever and respiratory complications, gastrointestinal symptoms are observed in some patients with 2019-nCoV but the significance remains undetermined. The cell receptor angiotensin covering enzyme II (ACE2), which is the major receptor of SARS-nCoV, has been reported to be a cellular entry receptor of 2019-nCoV as well. Here, to more precisely explore the potential pathogen transmission route of the 2019-nCoV infections in the gastrointestinal tract, we analyzed the ACE2 RNA expression profile in the colon tissue of healthy adults and colorectal cancer patients of our cohort and other databases. The data indicates that ACE2 is mainly expressed in epithelial cells of the colon. The expression of ACE2 is gradually increased from healthy control, adenoma to colorectal cancer patients in our cohort as well as in the external Asian datasets. According to the expression profile of ACE2 in colon epithelial cells, we speculate adenoma and colorectal cancer patients are more likely to be infected with 2019-nCoV than healthy people. Our data may provide a theoretical basis for the classification and management of future 2019-nCoV susceptibility people in clinical application.", - "rel_num_authors": 16, - "rel_authors": [ - { - "author_name": "Haoyan Chen", - "author_inst": "Shanghai Jiao Tong University School of Medicine" - }, - { - "author_name": "Baoqin Xuan", - "author_inst": "State Key Laboratory for Oncogenes and Related Genes,Renji Hospital, School of Medicine, Shanghai Jiao Tong University." - }, - { - "author_name": "Yuqing Yan", - "author_inst": "State Key Laboratory for Oncogenes and Related Genes; Key Laboratory of Gastroenterology & Hepatology, Ministry of Health; Division of Gastroenterology and Hepa" - }, - { - "author_name": "Xiaoqiang Zhu", - "author_inst": "State Key Laboratory for Oncogenes and Related Genes; Key Laboratory of Gastroenterology & Hepatology, Ministry of Health; Division of Gastroenterology and Hepa" - }, - { - "author_name": "Chaoqin Shen", - "author_inst": "State Key Laboratory for Oncogenes and Related Genes; Key Laboratory of Gastroenterology & Hepatology, Ministry of Health; Division of Gastroenterology and Hepa" - }, - { - "author_name": "Gang Zhao", - "author_inst": "Department of Gastrointestinal Surgery, Renji Hospital, School of Medicine, Shanghai Jiao Tong University" - }, - { - "author_name": "Linhua Ji", - "author_inst": "Department of Gastrointestinal Surgery, Renji Hospital, School of Medicine, Shanghai Jiao Tong University" - }, - { - "author_name": "Danhua Xu", - "author_inst": "Department of Gastrointestinal Surgery, Renji Hospital, School of Medicine, Shanghai Jiao Tong University" - }, - { - "author_name": "Hua Xiong", - "author_inst": "Division of Gastroenterology and Hepatology; Shanghai Institute of Digestive Disease; Renji Hospital, School of Medicine, Shanghai Jiao Tong University." - }, - { - "author_name": "TaChung Yu", - "author_inst": "Department of Gastrointestinal Surgery, Renji Hospital, School of Medicine, Shanghai Jiao Tong University" - }, - { - "author_name": "Xiaobo Li", - "author_inst": "Division of Gastroenterology and Hepatology; Shanghai Institute of Digestive Disease; Renji Hospital, School of Medicine, Shanghai Jiao Tong University" - }, - { - "author_name": "Qiang Liu", - "author_inst": "Department of Pathology, Renji Hospital, Shanghai Jiao Tong University School of Medicine" - }, - { - "author_name": "Yingxuan Chen", - "author_inst": "Division of Gastroenterology and Hepatology; Shanghai Institute of Digestive Disease; Renji Hospital, School of Medicine, Shanghai Jiao Tong University" - }, - { - "author_name": "Yun Cui", - "author_inst": "Division of Gastroenterology and Hepatology; Shanghai Institute of Digestive Disease; Renji Hospital, School of Medicine, Shanghai Jiao Tong University" - }, - { - "author_name": "Jie Hong", - "author_inst": "State Key Laboratory for Oncogenes and Related Genes; Key Laboratory of Gastroenterology & Hepatology, Ministry of Health; Division of Gastroenterology and Hepa" - }, - { - "author_name": "Jing-Yuan Fang", - "author_inst": "State Key Laboratory for Oncogenes and Related Genes; Key Laboratory of Gastroenterology & Hepatology, Ministry of Health; Division of Gastroenterology and Hepa" - } - ], - "version": "1", - "license": "cc_by_nc_nd", - "type": "PUBLISHAHEADOFPRINT", - "category": "gastroenterology" - }, { "rel_doi": "10.1101/2020.02.20.20025338", "rel_title": "COVID-19 in Wuhan: Immediate Psychological Impact on 5062 Health Workers", @@ -1610326,6 +1609536,53 @@ "type": "PUBLISHAHEADOFPRINT", "category": "psychiatry and clinical psychology" }, + { + "rel_doi": "10.1101/2020.02.21.20026146", + "rel_title": "Public Exposure to Live Animals, Behavioural Change, and Support in Containment Measures in response to COVID-19 Outbreak: a population-based cross sectional survey in China", + "rel_date": "2020-02-23", + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.02.21.20026146", + "rel_abs": "BackgroundIn response to the COVID-19 outbreak, we aimed to investigate behavioural change on exposure to live animals before and during the outbreak, and public support and confidence for governmental containment measures.\n\nMethodsA population-based cross-sectional telephone survey via random dialing was conducted in Wuhan (the epicentre) and Shanghai (an affected city with imported cases) between 1 and 10 February, 2020. 510 residents in Wuhan and 501 residents in Shanghai were randomly sampled. Differences of outcome measures were compared before and during the outbreak, and between two cities.\n\nFindingsProportion of respondents visiting wet markets at usual was 23.3% (119/510) in Wuhan and 20.4% (102/501) in Shanghai. During the outbreak, it decreased to 3.1% (16) in Wuhan (p<0{middle dot}001), and 4.4% (22) in Shanghai (p<0{middle dot}001). Proportion of those consuming wild animal products declined from 10.2% (52) to 0.6% (3) in Wuhan (p<0{middle dot}001), and from 5.2% (26) to 0.8% (4) in Shanghai (p<0{middle dot}001). 79.0% (403) of respondents in Wuhan and 66.9% (335) of respondents in Shanghai supported permanent closure of wet markets (P<0.001). 95% and 92% of respondents supported banning wild animal trade and quarantining Wuhan, and 75% were confident towards containment measures. Females and the more educated were more supportive for the above containment measures.\n\nInterpretationThe public responded quickly to the outbreak, and reduced exposure to live animals, especially in Wuhan. With high public support in containment measures, better regulation of wet markets and healthy diets should be promoted.\n\nFundingNational Science Fund for Distinguished Young Scholars, H2020 MOOD project.\n\nResearch in contextO_ST_ABSEvidence before this studyC_ST_ABSOn February 19, 2020, we searched PubMed for papers published after January 1, 2020, containing the following terms: \"2019 nCoV\" or \"COVID-19\". We identified 179 studies, most of which are research on clinical and epidemiological characteristics of COVID-19. To date there is no primary research to quantify public behavioural response and support in containment measures in response to the outbreak. Only four commentaries mentioned the influence of the outbreak on mental health. One commentary introduced the habit of consuming wild animal products in China. Another commentary briefly introduced isolation, quarantine, social distancing and community containment as public health measures in the outbreak. The Chinese government has introduced a series of strict containment measures, and societal acceptability of these measure is important for effective and sustained response. Evidence is urgently needed to help policy makers understand public response to the outbreak and support for the containment measures, but no evidence available to date.\n\nAdded value of this studyWe conducted a population-based cross-sectional telephone survey via random digital dialing in Wuhan (the epicentre) and Shanghai (an affected city with imported cases) between 1 and 10 February, 2020. To date, this is the only few analyses on behavioural response to the outbreak and societal acceptability of governmental containment measures, which has been listed as the current priority of China CDC. We provide an assessment of behavioural change on exposure to live animals during the outbreak, by comparison before and during the outbreak, and between two cities with diverse exposure intensities to COVID-19. We also provide evidence on public support in governmental containment measures, including strict regulation on wet markets to reduce animal-to-human transmission and city quarantine to reduce human transmission.\n\nImplications of all the available evidenceWe found that wild animal consumption was more prevalent in Wuhan (10.2%) than in Shanghai (5.2%). The public responded quickly to the outbreak, and significantly reduced exposure to live animals and stopped wild animal consumption, especially in Wuhan. They were very supportive of governmental containment measures. With high public support, wet markets should be better regulated, and healthy diets, including changing the traditional habit of eating wild animal products, should be promoted. This can inform policy makers in China and other countries to implement and adjust containment strategies in response to the outbreak in the future.", + "rel_num_authors": 8, + "rel_authors": [ + { + "author_name": "Zhiyuan Hou", + "author_inst": "Fudan University" + }, + { + "author_name": "Leesa Lin", + "author_inst": "Department of Global Health and Development Faculty of Public Health and Policy London School of Hygiene & Tropical Medicine" + }, + { + "author_name": "Liang Lu", + "author_inst": "West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China" + }, + { + "author_name": "Fanxing Du", + "author_inst": "School of Public Health, Fudan University, Shanghai, China" + }, + { + "author_name": "Mengcen Qian", + "author_inst": "Fudan University" + }, + { + "author_name": "Yuxia Liang", + "author_inst": "School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China" + }, + { + "author_name": "Juanjuan Zhang", + "author_inst": "School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China" + }, + { + "author_name": "Hongjie Yu", + "author_inst": "School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China" + } + ], + "version": "1", + "license": "cc_no", + "type": "PUBLISHAHEADOFPRINT", + "category": "public and global health" + }, { "rel_doi": "10.1101/2020.02.16.951913", "rel_title": "Single cell RNA sequencing of 13 human tissues identify cell types and receptors of human coronaviruses", @@ -1611695,92 +1610952,104 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.02.18.20023242", - "rel_title": "Kidney impairment is associated with in-hospital death of COVID-19 patients", + "rel_doi": "10.1101/2020.02.18.20024570", + "rel_title": "Modeling and Prediction of the 2019 Coronavirus Disease Spreading in China Incorporating Human Migration Data", "rel_date": "2020-02-20", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.02.18.20023242", - "rel_abs": "BackgroundInformation on kidney impairment in patients with coronavirus disease 2019 (COVID-19) is limited. This study aims to assess the prevalence and impact of abnormal urine analysis and kidney dysfunction in hospitalized COVID-19 patients in Wuhan.\n\nMethodsWe conducted a consecutive cohort study of COVID-19 patients admitted in a tertiary teaching hospital with 3 branches following a major outbreak in Wuhan in 2020. Hematuria, proteinuria, serum creatinine concentration and other clinical parameters were extracted from the electronic hospitalization databases and laboratory databases. Incidence rate for acute kidney injury (AKI) was examined during the study period. Association between kidney impairment and in-hospital death was analyzed.\n\nResultsWe included 710 consecutive COVID-19 patients, 89 (12.3%) of whom died in hospital. The median age of the patients was 63 years (inter quartile range, 51-71), including 374 men and 336 women. On admission, 44% of patients have proteinuria hematuria and 26.9% have hematuria, and the prevalence of elevated serum creatinine and blood urea nitrogen were 15.5% and 14.1% respectively. During the study period, AKI occurred in 3.2% patients. Kaplan-Meier analysis demonstrated that patients with kidney impairment have higher risk for in-hospital death. Cox proportional hazard regression confirmed that elevated serum creatinine, elevated urea nitrogen, AKI, proteinuria and hematuria was an independent risk factor for in-hospital death after adjusting for age, sex, disease severity, leukocyte count and lymphocyte count.\n\nConclusionsThe prevalence of kidney impairment (hematuria, proteinuria and kidney dysfunction) in hospitalized COVID-19 patients was high. After adjustment for confounders, kidney impairment indicators were associated with higher risk of in-hospital death. Clinicians should increase their awareness of kidney impairment in hospitalized COVID-19 patients.", - "rel_num_authors": 10, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.02.18.20024570", + "rel_abs": "This study integrates the daily intercity migration data with the classic Susceptible-Exposed-Infected-Removed (SEIR) model to construct a new model suitable for describing the dynamics of epidemic spreading of Coronavirus Disease 2019 (COVID-19) in China. Daily intercity migration data for 367 cities in China are collected from Baidu Migration, a mobile-app based human migration tracking data system. Historical data of infected, recovered and death cases from official source are used for model fitting. The set of model parameters obtained from best data fitting using a constrained nonlinear optimization procedure is used for estimation of the dynamics of epidemic spreading in the coming weeks. Our results show that the number of infections in most cities in China will peak between mid February to early March 2020, with about 0.8%, less than 0.1% and less than 0.01% of the population eventually infected in Wuhan, Hubei Province and the rest of China, respectively.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Yichun Cheng", - "author_inst": "Department of Nephrology, Tongji Hospital Affiliated to Tongji Medical College, Huazhong University of Science and Technology," + "author_name": "Choujun Zhan", + "author_inst": "South China Normal University, Guangzhou, China" }, { - "author_name": "Ran Luo", - "author_inst": "Department of Nephrology, Tongji Hospital Affiliated to Tongji Medical College, Huazhong University of Science and Technology" + "author_name": "Chi K. Tse", + "author_inst": "City University of Hong Kong, Hong Kong" }, { - "author_name": "Kun Wang", - "author_inst": "Department of Nephrology, Tongji Hospital Affiliated to Tongji Medical College, Huazhong University of Science and Technology" + "author_name": "Yuxia Fu", + "author_inst": "Nanfang College of Sun Yat-Sen University, Guangzhou, China" }, { - "author_name": "Meng Zhang", - "author_inst": "Department of Nephrology, Tongji Hospital Affiliated to Tongji Medical College, Huazhong University of Science and Technology" + "author_name": "Zhikang Lai", + "author_inst": "Nanfang College of Sun Yat-Sen University, Guangzhou, China" }, { - "author_name": "Zhixiang Wang", - "author_inst": "Department of Nephrology, Tongji Hospital Affiliated to Tongji Medical College, Huazhong University of Science and Technology" + "author_name": "Haijun Zhang", + "author_inst": "Harbin Institute of Technology, Shenzhen, China" + } + ], + "version": "1", + "license": "cc_by_nc", + "type": "PUBLISHAHEADOFPRINT", + "category": "infectious diseases" + }, + { + "rel_doi": "10.1101/2020.02.18.20024315", + "rel_title": "Estimation of the epidemic properties of the 2019 novel coronavirus: A mathematical modeling study", + "rel_date": "2020-02-20", + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.02.18.20024315", + "rel_abs": "BackgroundThe 2019 novel Coronavirus (COVID-19) emerged in Wuhan, China in December 2019 and has been spreading rapidly in China. Decisions about its pandemic threat and the appropriate level of public health response depend heavily on estimates of its basic reproduction number and assessments of interventions conducted in the early stages of the epidemic.\n\nMethodsWe conducted a mathematical modeling study using five independent methods to assess the basic reproduction number (R0) of COVID-19, using data on confirmed cases obtained from the China National Health Commission for the period 10th January - 8th February. We analyzed the data for the period before the closure of Wuhan city (10th January - 23rd January) and the post-closure period (23rd January - 8th February) and for the whole period, to assess both the epidemic risk of the virus and the effectiveness of the closure of Wuhan city on spread of COVID-19.\n\nFindingsBefore the closure of Wuhan city the basic reproduction number of COVID-19 was 4.38 (95% CI: 3.63 - 5.13), dropping to 3.41 (95% CI: 3.16 - 3.65) after the closure of Wuhan city. Over the entire epidemic period COVID-19 had a basic reproduction number of 3.39 (95% CI: 3.09 - 3.70), indicating it has a very high transmissibility.\n\nInterpretationCOVID-19 is a highly transmissible virus with a very high risk of epidemic outbreak once it emerges in metropolitan areas. The closure of Wuhan city was effective in reducing the severity of the epidemic, but even after closure of the city and the subsequent expansion of that closure to other parts of Hubei the virus remained extremely infectious. Emergency planners in other cities should consider this high infectiousness when considering responses to this virus.\n\nFundingNational Natural Science Foundation of China, China Medical Board, National Science and Technology Major Project of China", + "rel_num_authors": 13, + "rel_authors": [ + { + "author_name": "Jinghua Li", + "author_inst": "Sun Yat Sen University" }, { - "author_name": "Lei Dong", - "author_inst": "Department of Nephrology, Tongji Hospital Affiliated to Tongji Medical College, Huazhong University of Science and Technology" + "author_name": "Yijing Wang", + "author_inst": "St. Luke's International University" }, { - "author_name": "Junhua Li", - "author_inst": "Department of Nephrology, Tongji Hospital Affiliated to Tongji Medical College, Huazhong University of Science and Technology" + "author_name": "Stuart Gilmour", + "author_inst": "St. Luke's International University" }, { - "author_name": "Ying Yao", - "author_inst": "Department of Nephrology, Tongji Hospital Affiliated to Tongji Medical College, Huazhong University of Science and Technology" + "author_name": "Mengying Wang", + "author_inst": "Jiangxi University of Finance and Economics" }, { - "author_name": "Shuwang Ge", - "author_inst": "Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology" + "author_name": "Daisuke Yoneoka", + "author_inst": "St. Luke's International University" }, { - "author_name": "Gang Xu", - "author_inst": "Department of Nephrology, Tongji Hospital Affiliated to Tongji Medical College, Huazhong University of Science and Technology" - } - ], - "version": "1", - "license": "cc_no", - "type": "PUBLISHAHEADOFPRINT", - "category": "nephrology" - }, - { - "rel_doi": "10.1101/2020.02.18.20024570", - "rel_title": "Modeling and Prediction of the 2019 Coronavirus Disease Spreading in China Incorporating Human Migration Data", - "rel_date": "2020-02-20", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.02.18.20024570", - "rel_abs": "This study integrates the daily intercity migration data with the classic Susceptible-Exposed-Infected-Removed (SEIR) model to construct a new model suitable for describing the dynamics of epidemic spreading of Coronavirus Disease 2019 (COVID-19) in China. Daily intercity migration data for 367 cities in China are collected from Baidu Migration, a mobile-app based human migration tracking data system. Historical data of infected, recovered and death cases from official source are used for model fitting. The set of model parameters obtained from best data fitting using a constrained nonlinear optimization procedure is used for estimation of the dynamics of epidemic spreading in the coming weeks. Our results show that the number of infections in most cities in China will peak between mid February to early March 2020, with about 0.8%, less than 0.1% and less than 0.01% of the population eventually infected in Wuhan, Hubei Province and the rest of China, respectively.", - "rel_num_authors": 5, - "rel_authors": [ + "author_name": "Ying Wang", + "author_inst": "Sun Yat Sen University" + }, { - "author_name": "Choujun Zhan", - "author_inst": "South China Normal University, Guangzhou, China" + "author_name": "Xinyi You", + "author_inst": "Sun Yat Sen University" }, { - "author_name": "Chi K. Tse", - "author_inst": "City University of Hong Kong, Hong Kong" + "author_name": "Jing Gu", + "author_inst": "Sun Yat Sen University" }, { - "author_name": "Yuxia Fu", - "author_inst": "Nanfang College of Sun Yat-Sen University, Guangzhou, China" + "author_name": "Chun Hao", + "author_inst": "Sun Yat Sen University" }, { - "author_name": "Zhikang Lai", - "author_inst": "Nanfang College of Sun Yat-Sen University, Guangzhou, China" + "author_name": "Liping Peng", + "author_inst": "Sun Yat Sen University" }, { - "author_name": "Haijun Zhang", - "author_inst": "Harbin Institute of Technology, Shenzhen, China" + "author_name": "Zhicheng Du", + "author_inst": "Sun Yat Sen University" + }, + { + "author_name": "Dong Roman Xu", + "author_inst": "Sun Yat Sen University" + }, + { + "author_name": "Yuantao Hao", + "author_inst": "Sun Yat Sen University" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1613100,37 +1612369,6 @@ "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, - { - "rel_doi": "10.1101/2020.02.16.20023838", - "rel_title": "Risk map of the novel coronavirus (2019-nCoV) in China: proportionate control is needed", - "rel_date": "2020-02-18", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.02.16.20023838", - "rel_abs": "BackgroundChina is running a national level antivirus campaign against the novel coronavirus (2019-nCoV). Strict control measures are being enforced in either the populated areas and remote regions. While the virus is closed to be under control, tremendous economic loss has been caused.\n\nMethods and findingsWe assessed the pandemic risk of 2019-nCoV for all cities/regions in China using the random forest algorithm, taking into account the effect of five factors: the accumulative and increased numbers of confirmed cases, total population, population density, and GDP. We defined four levels of the risk, corresponding to the four response levels to public health emergencies in China. The classification system has good consistency among cities in China, as the error rate of the confusion matrix is 1.58%.\n\nConclusionsThe pandemic risk of 2019-nCoV is dramatically different among the 442 cities/regions. We recommend to adopt proportionate control policy according to the risk level to reduce unnecessary economic loss.", - "rel_num_authors": 4, - "rel_authors": [ - { - "author_name": "Xinhai Li", - "author_inst": "Institute of Zoology, Chinese Academy of Sciences" - }, - { - "author_name": "Xumao Zhao", - "author_inst": "Lanzhou University" - }, - { - "author_name": "Yingqiang Lou", - "author_inst": "University of Chinese Academy of Sciences" - }, - { - "author_name": "Yuehua Sun", - "author_inst": "Institute of Zoology, Chinese Academy of Sciences" - } - ], - "version": "1", - "license": "cc_by", - "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" - }, { "rel_doi": "10.1101/2020.02.16.20023804", "rel_title": "When will the battle against novel coronavirus end in Wuhan: a SEIR modeling analysis", @@ -1613170,6 +1612408,25 @@ "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, + { + "rel_doi": "10.1101/2020.02.15.20023440", + "rel_title": "Evaluating new evidence in the early dynamics of the novel coronavirus COVID-19 outbreak in Wuhan, China with real time domestic traffic and potential asymptomatic transmissions", + "rel_date": "2020-02-18", + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.02.15.20023440", + "rel_abs": "The novel coronavirus (COVID-19), first detected in Wuhan, China in December 2019, has spread to 28 countries/regions with over 43,000 confirmed cases. Much about this outbreak is still unknown. At this early stage of the epidemic, it is important to investigate alternative sources of information to understand its dynamics and spread. With updated real time domestic traffic, this study aims to integrate recent evidence of international evacuees extracted from Wuhan between Jan. 29 and Feb. 2, 2020 to infer the dynamics of the COVD-19 outbreak in Wuhan. In addition, a modified SEIR model was used to evaluate the empirical support for the presence of asymptomatic transmissions. Based on the data examined, this study found little evidence for the presence of asymptomatic transmissions. However, it is still too early to rule out its presence conclusively due to sample size and other limitations. The updated basic reproductive number was found to be 2.12 on average with a 95% credible interval of [2.04, 2.18]. It is smaller than previous estimates probably because the new estimate factors in the social and non-pharmaceutical mitigation implemented in Wuhan through the evacuee dataset. Detailed predictions of infected individuals exported both domestically and internationally were produced. The estimated case confirmation rate has been low but has increased steadily to 23.37% on average. The findings of this study depend on the validity of the underlying assumptions, and continuing work is needed, especially in monitoring the current infection status of Wuhan residents.", + "rel_num_authors": 1, + "rel_authors": [ + { + "author_name": "Can Zhou", + "author_inst": "Texas A&M University" + } + ], + "version": "1", + "license": "cc_by_nc_nd", + "type": "PUBLISHAHEADOFPRINT", + "category": "epidemiology" + }, { "rel_doi": "10.1101/2020.02.16.20023606", "rel_title": "Estimation of the final size of the coronavirus epidemic by the logistic model", @@ -1614379,60 +1613636,64 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.02.12.20022434", - "rel_title": "Early epidemiological assessment of the transmission potential and virulence of 2019 Novel Coronavirus in Wuhan City: China, 2019-2020", + "rel_doi": "10.1101/2020.02.11.20022228", + "rel_title": "Single-cell RNA expression profiling of ACE2, the putative receptor of Wuhan 2019-nCoV, in the nasal tissue", "rel_date": "2020-02-13", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.02.12.20022434", - "rel_abs": "BackgroundSince the first cluster of cases was identified in Wuhan City, China, in December, 2019, coronavirus disease 2019 (COVID-19) rapidly spread around the world. Despite the scarcity of publicly available data, scientists around the world have made strides in estimating the magnitude of the epidemic, the basic reproduction number, and transmission patterns. Accumulating evidence suggests that a substantial fraction of the infected individuals with the novel coronavirus show little if any symptoms, which highlights the need to reassess the transmission potential of this emerging disease. In this study, we derive estimates of the transmissibility and virulence of COVID-19 in Wuhan City, China, by reconstructing the underlying transmission dynamics using multiple data sources.\n\nMethodsWe employ statistical methods and publicly available epidemiological datasets to jointly derive estimates of transmissibility and severity associated with the novel coronavirus. For this purpose, the daily series of laboratory-confirmed COVID-19 cases and deaths in Wuhan City together with epidemiological data of Japanese repatriated from Wuhan City on board government-chartered flights were integrated into our analysis.\n\nResultsOur posterior estimates of basic reproduction number (R) in Wuhan City, China in 2019-2020 reached values at 3.49 (95%CrI: 3.39-3.62) with a mean serial interval of 6.0 days, and the enhanced public health intervention after January 23rd in 2020 was associated with a significantly reduced R at 0.84 (95%CrI: 0.81-0.88), with the total number of infections (i.e. cumulative infections) estimated at 1906634 (95%CrI: 1373500-2651124) in Wuhan City, elevating the overall proportion of infected individuals to 19.1% (95%CrI: 13.5-26.6%). We also estimated the most recent crude infection fatality ratio (IFR) and time-delay adjusted IFR at 0.04% (95% CrI: 0.03%-0.06%) and 0.12% (95%CrI: 0.08-0.17%), respectively, estimates that are several orders of magnitude smaller than the crude CFR estimated at 4.06%\n\nConclusionsWe have estimated key epidemiological parameters of the transmissibility and virulence of COVID-19 in Wuhan, China during January-February, 2020 using an ecological modelling approach. The power of this approach lies in the ability to infer epidemiological parameters with quantified uncertainty from partial observations collected by surveillance systems.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.02.11.20022228", + "rel_abs": "A novel coronavirus (2019-nCoV) was first identified in Wuhan, Hubei Province, and then spreads to the other Provinces of China. WHO decides to determine a Public Health Emergency of International Concern (PHEIC) of 2019-nCoV. 2019-nCov was reported to share the same receptor, Angiotensin-converting enzyme 2 (ACE2), with SARS-Cov. Here based on the public single-cell RNA-Seq datasets, we analyzed the ACE2 RNA expression profile in the tissues at different locations of the respiratory tract. The result indicates that the ACE2 expression appears in nasal epithelial cells. We found that the size of this population of ACE2-expressing nasal epithelial cells is comparable with the size of the population of ACE2-expression type II alveolar cells (AT2) in the Asian sample reported by Yu Zhao et al. We further detected 2019-nCoV by polymerase chain reaction (PCR) from the nasal-swab and throat-swab of seven suspected cases. We found that 2019-nCoV tends to have a higher concentration in the nasal-swab comparing to the throat-swab, which could attribute to the ACE2-expressing nasal epithelial cells. We hope this study could be informative for virus-prevention strategy development, especially the treatment of nasal mucus.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Kenji Mizumoto", - "author_inst": "Kyoto University" + "author_name": "CHAO WU", + "author_inst": "Zhe Jiang University, China" }, { - "author_name": "Katsushi Kagaya", - "author_inst": "Kyoto University" + "author_name": "Shufa Zheng", + "author_inst": "Zhe Jiang University" }, { - "author_name": "Gerardo Chowell", - "author_inst": "Georgia State University" + "author_name": "Yu Chen", + "author_inst": "Zhe Jiang University" + }, + { + "author_name": "Min Zheng", + "author_inst": "Zhe Jiang University" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.02.11.20022228", - "rel_title": "Single-cell RNA expression profiling of ACE2, the putative receptor of Wuhan 2019-nCoV, in the nasal tissue", + "rel_doi": "10.1101/2020.02.11.20022186", + "rel_title": "Data-Based Analysis, Modelling and Forecasting of the novel Coronavirus (2019-nCoV) outbreak", "rel_date": "2020-02-13", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.02.11.20022228", - "rel_abs": "A novel coronavirus (2019-nCoV) was first identified in Wuhan, Hubei Province, and then spreads to the other Provinces of China. WHO decides to determine a Public Health Emergency of International Concern (PHEIC) of 2019-nCoV. 2019-nCov was reported to share the same receptor, Angiotensin-converting enzyme 2 (ACE2), with SARS-Cov. Here based on the public single-cell RNA-Seq datasets, we analyzed the ACE2 RNA expression profile in the tissues at different locations of the respiratory tract. The result indicates that the ACE2 expression appears in nasal epithelial cells. We found that the size of this population of ACE2-expressing nasal epithelial cells is comparable with the size of the population of ACE2-expression type II alveolar cells (AT2) in the Asian sample reported by Yu Zhao et al. We further detected 2019-nCoV by polymerase chain reaction (PCR) from the nasal-swab and throat-swab of seven suspected cases. We found that 2019-nCoV tends to have a higher concentration in the nasal-swab comparing to the throat-swab, which could attribute to the ACE2-expressing nasal epithelial cells. We hope this study could be informative for virus-prevention strategy development, especially the treatment of nasal mucus.", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.02.11.20022186", + "rel_abs": "Since the first suspected case of coronavirus disease-2019 (COVID-19) on December 1st, 2019, in Wuhan, Hubei Province, China, a total of 40,235 confirmed cases and 909 deaths have been reported in China up to February 10, 2020, evoking fear locally and internationally. Here, based on the publicly available epidemiological data for Hubei, China from January 11 to February 10, 2020, we provide estimates of the main epidemiological parameters. In particular, we provide an estimation of the case fatality and case recovery ratios, along with their 90% confidence intervals as the outbreak evolves. On the basis of a Susceptible-Infected-Recovered-Dead (SIDR) model, we provide estimations of the basic reproduction number (R0), and the per day infection mortality and recovery rates. By calibrating the parameters of the SIRD model to the reported data, we also attempt to forecast the evolution of the of the outbreak at the epicenter three weeks ahead, i.e. until February 29. As the number of infected individuals, especially of those with asymptomatic or mild courses, is suspected to be much higher than the official numbers, which can be considered only as a subset of the actual numbers of infected and recovered cases in the total population, we have repeated the calculations under a second scenario that considers twenty times the number of confirmed infected cases and forty times the number of recovered, leaving the number of deaths unchanged. Based on the reported data, the expected value of R0 as computed considering the period from the 11th of January until the 18th of January, using the official counts of confirmed cases was found to be [~]4.6, while the one computed under the second scenario was found to be [~]3.2. Thus, based on the SIRD simulations, the estimated average value of R0 was found to be [~] 2.6 based on confirmed cases and2 based on the second scenario. Our forecasting flashes a note of caution for the presently unfolding outbreak in China. Based on the official counts for confirmed cases, the simulations suggest that the cumulative number of infected could reach 180,000 (with lower bound of 45,000) by February 29. Regarding the number of deaths, simulations forecast that on the basis of the up to the 10th of February reported data, the death toll might exceed 2,700 (as a lower bound) by February 29. Our analysis further reveals a significant decline of the case fatality ratio from January 26 to which various factors may have contributed, such as the severe control measures taken in Hubei, China (e.g. quarantine and hospitalization of infected individuals), but mainly because of the fact that the actual cumulative numbers of infected and recovered cases in the population most likely are much higher than the reported ones. Thus, in a scenario where we have taken twenty times the confirmed number of infected and forty times the confirmed number of recovered cases, the case fatality ratio is around [~] 0.15% in the total population. Importantly, based on this scenario, simulations suggest a slow down of the outbreak in Hubei at the end of February.", "rel_num_authors": 4, "rel_authors": [ { - "author_name": "CHAO WU", - "author_inst": "Zhe Jiang University, China" + "author_name": "Cleo Anastassopoulou", + "author_inst": "Department of Microbiology, Medical School, University of Athens" }, { - "author_name": "Shufa Zheng", - "author_inst": "Zhe Jiang University" + "author_name": "Lucia Russo", + "author_inst": "Consiglio Nazionale delle Ricerche, Science and Technology for Energy and Sustainable Mobility" }, { - "author_name": "Yu Chen", - "author_inst": "Zhe Jiang University" + "author_name": "Athanasios Tsakris", + "author_inst": "Department of Microbiology, Medical School, University of Athens" }, { - "author_name": "Min Zheng", - "author_inst": "Zhe Jiang University" + "author_name": "Constantinos Siettos", + "author_inst": "University of Naples Federico II" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1615764,53 +1615025,6 @@ "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, - { - "rel_doi": "10.1101/2020.02.07.939124", - "rel_title": "Exploring the coronavirus epidemic using the new WashU Virus Genome Browser", - "rel_date": "2020-02-11", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.02.07.939124", - "rel_abs": "Since its debut in mid-December, 2019, the novel coronavirus (2019-nCoV) has rapidly spread from its origin in Wuhan, China, to several countries across the globe, leading to a global health crisis. As of February 7, 2020, 44 strains of the virus have been sequenced and uploaded to NCBIs GenBank [1], providing insight into the viruss evolutionary history and pathogenesis. Here, we present the WashU Virus Genome Browser, a web-based portal for viewing virus genomic data. The browser is home to 16 complete 2019-nCoV genome sequences, together with hundreds of related viral sequences including severe acute respiratory syndrome coronavirus (SARS-CoV), Middle East respiratory syndrome coronavirus (MERS-CoV), and Ebola virus. In addition, the browser features unique customizability, supporting user-provided upload of novel viral sequences in various formats. Sequences can be viewed in both a track-based representation as well as a phylogenetic tree-based view, allowing the user to easily compare sequence features across multiple strains. The WashU Virus Genome Browser inherited many features and track types from the WashU Epigenome Browser, and additionally incorporated a new type of SNV track to address the specific needs of viral research. Our Virus Browser portal can be accessed at https://virusgateway.wustl.edu, and documentation is available at https://virusgateway.readthedocs.io/.", - "rel_num_authors": 8, - "rel_authors": [ - { - "author_name": "Jennifer Flynn", - "author_inst": "Washington University in St. Louis" - }, - { - "author_name": "Deepak Purushotham", - "author_inst": "Washington University in St. Louis" - }, - { - "author_name": "Mayank NK Choudhary", - "author_inst": "Washington University in St. Louis" - }, - { - "author_name": "Xiaoyu Zhuo", - "author_inst": "Washington University in St. Louis" - }, - { - "author_name": "Changxu Fan", - "author_inst": "Washington University in St. Louis" - }, - { - "author_name": "Gavriel Matt", - "author_inst": "Washington University in St. Louis" - }, - { - "author_name": "Daofeng Li", - "author_inst": "Washington University in St. Louis" - }, - { - "author_name": "Ting Wang", - "author_inst": "Washington University in St. Louis" - } - ], - "version": "1", - "license": "cc_by_nc_nd", - "type": "new results", - "category": "genomics" - }, { "rel_doi": "10.1101/2020.02.08.20021311", "rel_title": "Assessing the plausibility of subcritical transmission of 2019-nCoV in the United States", @@ -1615842,6 +1615056,217 @@ "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, + { + "rel_doi": "10.1101/2020.02.07.939389", + "rel_title": "The Pathogenicity of 2019 Novel Coronavirus in hACE2 Transgenic Mice", + "rel_date": "2020-02-11", + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2020.02.07.939389", + "rel_abs": "Severe acute respiratory syndrome CoV-2 (SARS-CoV-2) caused the Corona Virus Disease 2019 (COVID-19) cases in China has become a public health emergency of international concern (PHEIC). Based on angiotensin converting enzyme 2 (ACE2) as cell entry receptor of SARS-CoV, we used the hACE2 transgenic mice infected with SARS-CoV-2 to study the pathogenicity of the virus. Weight loss and virus replication in lung were observed in hACE2 mice infected with SARS-CoV-2. The typical histopathology was interstitial pneumonia with infiltration of significant lymphocytes and monocytes in alveolar interstitium, and accumulation of macrophages in alveolar cavities. Viral antigens were observed in the bronchial epithelial cells, alveolar macrophages and alveolar epithelia. The phenomenon was not found in wild type mice with SARS-CoV-2 infection. The pathogenicity of SARS-CoV-2 in hACE2 mice was clarified and the Kochs postulates were fulfilled as well, and the mouse model may facilitate the development of therapeutics and vaccines against SARS-CoV-2.", + "rel_num_authors": 49, + "rel_authors": [ + { + "author_name": "Linlin Bao", + "author_inst": "Institute of Laboratory Animal Science, Chinese Academy of Medical Sciences" + }, + { + "author_name": "Wei Deng", + "author_inst": "Institute of Laboratory Animal Science, Chinese Academy of Medical Sciences" + }, + { + "author_name": "Baoying Huang", + "author_inst": "MHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and Prevention, China CDC" + }, + { + "author_name": "Hong Gao", + "author_inst": "Institute of Laboratory Animal Science, Chinese Academy of Medical Sciences" + }, + { + "author_name": "Jiangning Liu", + "author_inst": "Institute of Laboratory Animal Science, Chinese Academy of Medical Sciences" + }, + { + "author_name": "Lili Ren", + "author_inst": "Institute of Pathogen Biology, Chinese Academy of Medical Science" + }, + { + "author_name": "Qiang Wei", + "author_inst": "Institute of Laboratory Animal Science, Chinese Academy of Medical Sciences" + }, + { + "author_name": "Pin Yu", + "author_inst": "Institute of Laboratory Animal Science, Chinese Academy of Medical Sciences" + }, + { + "author_name": "Yanfeng Xu", + "author_inst": "Institute of Laboratory Animal Science, Chinese Academy of Medical Sciences" + }, + { + "author_name": "Feifei Qi", + "author_inst": "Institute of Laboratory Animal Science, Chinese Academy of Medical Sciences" + }, + { + "author_name": "Yajin Qu", + "author_inst": "Institute of Laboratory Animal Science, Chinese Academy of Medical Sciences" + }, + { + "author_name": "Fengdi Li", + "author_inst": "Institute of Laboratory Animal Science, Chinese Academy of Medical Sciences" + }, + { + "author_name": "Qi Lv", + "author_inst": "Institute of Laboratory Animal Science, Chinese Academy of Medical Sciences" + }, + { + "author_name": "Wenling Wang", + "author_inst": "MHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and Prevention, China CDC" + }, + { + "author_name": "Jing Xue", + "author_inst": "Institute of Laboratory Animal Science, Chinese Academy of Medical Sciences" + }, + { + "author_name": "Shuran Gong", + "author_inst": "Institute of Laboratory Animal Science, Chinese Academy of Medical Sciences" + }, + { + "author_name": "Mingya Liu", + "author_inst": "Institute of Laboratory Animal Science, Chinese Academy of Medical Sciences" + }, + { + "author_name": "Guanpeng Wang", + "author_inst": "Institute of Laboratory Animal Science, Chinese Academy of Medical Sciences" + }, + { + "author_name": "Shunyi Wang", + "author_inst": "Institute of Laboratory Animal Science, Chinese Academy of Medical Sciences" + }, + { + "author_name": "Zhiqi Song", + "author_inst": "Institute of Laboratory Animal Science, Chinese Academy of Medical Sciences" + }, + { + "author_name": "Linna Zhao", + "author_inst": "Institute of Laboratory Animal Science, Chinese Academy of Medical Sciences" + }, + { + "author_name": "Peipei Liu", + "author_inst": "MHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and Prevention, China CDC" + }, + { + "author_name": "Li Zhao", + "author_inst": "MHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and Prevention, China CDC" + }, + { + "author_name": "Fei Ye", + "author_inst": "MHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and Prevention, China CDC" + }, + { + "author_name": "Huijuan Wang", + "author_inst": "MHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and Prevention, China CDC" + }, + { + "author_name": "Weimin Zhou", + "author_inst": "MHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and Prevention, China CDC" + }, + { + "author_name": "Na Zhu", + "author_inst": "MHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and Prevention, China CDC" + }, + { + "author_name": "Wei Zhen", + "author_inst": "MHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and Prevention, China CDC" + }, + { + "author_name": "Haisheng Yu", + "author_inst": "Institute of Laboratory Animal Science, Chinese Academy of Medical Sciences" + }, + { + "author_name": "Xiaojuan Zhang", + "author_inst": "Institute of Laboratory Animal Science, Chinese Academy of Medical Sciences" + }, + { + "author_name": "Li Guo", + "author_inst": "Institute of Pathogen Biology, Chinese Academy of Medical Sciences" + }, + { + "author_name": "Lan Chen", + "author_inst": "Institute of Pathogen Biology, Chinese Academy of Medical Sciences" + }, + { + "author_name": "Conghui Wang", + "author_inst": "Institute of Pathogen Biology, Chinese Academy of Medical Sciences" + }, + { + "author_name": "Ying Wang", + "author_inst": "Institute of Pathogen Biology, Chinese Academy of Medical Sciences" + }, + { + "author_name": "Xinmin Wang", + "author_inst": "Institute of Pathogen Biology, Chinese Academy of Medical Sciences" + }, + { + "author_name": "Yan Xiao", + "author_inst": "Institute of Pathogen Biology, Chinese Academy of Medical Sciences" + }, + { + "author_name": "Qiangming Sun", + "author_inst": "Institute of Medical Biology,Chinese Academy of Medical Sciences" + }, + { + "author_name": "Hongqi Liu", + "author_inst": "Institute of Medical Biology,Chinese Academy of Medical Sciences" + }, + { + "author_name": "Fanli Zhu", + "author_inst": "Institute of Medical Biology,Chinese Academy of Medical Sciences" + }, + { + "author_name": "Chunxia Ma", + "author_inst": "Institute of Medical Biology,Chinese Academy of Medical Sciences" + }, + { + "author_name": "Lingmei Yan", + "author_inst": "Institute of Medical Biology,Chinese Academy of Medical Sciences" + }, + { + "author_name": "Mengli Yang", + "author_inst": "Institute of Medical Biology,Chinese Academy of Medical Sciences" + }, + { + "author_name": "Jun Han", + "author_inst": "MHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and Prevention, China CDC" + }, + { + "author_name": "Wenbo Xu", + "author_inst": "MHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and Prevention, China CDC" + }, + { + "author_name": "Wenjie Tan", + "author_inst": "MHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and Prevention, China CDC" + }, + { + "author_name": "Xiaozhong Peng", + "author_inst": "Institute of Medical Biology,Chinese Academy of Medical Sciences" + }, + { + "author_name": "Qi Jin", + "author_inst": "Institute of Pathogen Biology, Chinese Academy of Medical Sciences" + }, + { + "author_name": "Guizhen Wu", + "author_inst": "MHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and Prevention, China CDC" + }, + { + "author_name": "Chuan Qin", + "author_inst": "Institute of Laboratory Animal Science, Chinese Academy of Medical Sciences" + } + ], + "version": "1", + "license": "cc_no", + "type": "new results", + "category": "microbiology" + }, { "rel_doi": "10.1101/2020.02.09.20021261", "rel_title": "The effect of travel restrictions on the spread of the 2019 novel coronavirus (2019-nCoV) outbreak", @@ -1617378,29 +1616803,6 @@ "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, - { - "rel_doi": "10.1101/2020.02.02.931162", - "rel_title": "Phylogenomic analysis of the 2019-nCoV coronavirus", - "rel_date": "2020-02-04", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.02.02.931162", - "rel_abs": "There is rising global concern for the recently emerged novel Coronavirus (2019-nCov). Full genomic sequences have been released by the worldwide scientific community in the last few weeks in order to understand the evolutionary origin and molecular characteristics of this virus. Taking advantage of all the genomic information currently available, we constructed a phylogenetic tree including also representatives of other coronaviridae, such as Bat coronavirus (BCoV) and SARS. We confirm high sequence similarity (>99%) between all sequenced 2019-nCoVs genomes available, with the closest BCoV sequence sharing 96.2% sequence identity, confirming the notion of a zoonotic origin of 2019-nCoV. Despite the low heterogeneity of the 2019-nCoV genomes, we could identify at least two hyper-variable genomic hotspots, one of which is responsible for a Serine/Leucine variation in the viral ORF8-encoded protein. Finally, we perform a full proteomic comparison with other coronaviridae, identifying key aminoacidic differences to be considered for antiviral strategies deriving from previous anti-coronavirus approaches.", - "rel_num_authors": 2, - "rel_authors": [ - { - "author_name": "Carmine Ceraolo", - "author_inst": "University of Bologna" - }, - { - "author_name": "Federico M Giorgi", - "author_inst": "University of Bologna" - } - ], - "version": "1", - "license": "cc_by_nc", - "type": "new results", - "category": "bioinformatics" - }, { "rel_doi": "10.1101/2020.02.03.931766", "rel_title": "Specific ACE2 Expression in Cholangiocytes May Cause Liver Damage After 2019-nCoV Infection", @@ -1617468,6 +1616870,37 @@ "type": "new results", "category": "genomics" }, + { + "rel_doi": "10.1101/2020.01.30.927889", + "rel_title": "Machine intelligence design of 2019-nCoV drugs", + "rel_date": "2020-02-04", + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2020.01.30.927889", + "rel_abs": "Wuhan coronavirus, called 2019-nCoV, is a newly emerged virus that infected more than 9692 people and leads to more than 213 fatalities by January 30, 2020. Currently, there is no effective treatment for this epidemic. However, the viral protease of a coronavirus is well-known to be essential for its replication and thus is an effective drug target. Fortunately, the sequence identity of the 2019-nCoV protease and that of severe-acute respiratory syndrome virus (SARS-CoV) is as high as 96.1%. We show that the protease inhibitor binding sites of 2019-nCoV and SARS-CoV are almost identical, which means all potential anti-SARS-CoV chemotherapies are also potential 2019-nCoV drugs. Here, we report a family of potential 2019-nCoV drugs generated by a machine intelligence-based generative network complex (GNC). The potential effectiveness of treating 2019-nCoV by using some existing HIV drugs is also analyzed.", + "rel_num_authors": 4, + "rel_authors": [ + { + "author_name": "Duc Duy Nguyen", + "author_inst": "Michigan State University" + }, + { + "author_name": "Kaifu Gao", + "author_inst": "Michigan State University" + }, + { + "author_name": "Rui Wang", + "author_inst": "Michigan State University" + }, + { + "author_name": "Guowei Wei", + "author_inst": "Michigan State University" + } + ], + "version": "1", + "license": "cc_by_nc", + "type": "new results", + "category": "bioinformatics" + }, { "rel_doi": "10.1101/2020.02.03.932350", "rel_title": "Machine learning-based analysis of genomes suggests associations between Wuhan 2019-nCoV and bat Betacoronaviruses", @@ -1618589,78 +1618022,58 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.01.26.20018887", - "rel_title": "Epidemiological identification of a novel infectious disease in real time: Analysis of the atypical pneumonia outbreak in Wuhan, China, 2019-20", + "rel_doi": "10.1101/2020.01.27.20018986", + "rel_title": "The incubation period of 2019-nCoV infections among travellers from Wuhan, China", "rel_date": "2020-01-28", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.01.26.20018887", - "rel_abs": "ObjectiveVirological tests indicate that a novel coronavirus is the most likely explanation for the 2019-20 pneumonia outbreak in Wuhan, China. We demonstrate that non-virological descriptive characteristics could have determined that the outbreak is caused by a novel pathogen in advance of virological testing.\n\nMethodsCharacteristics of the ongoing outbreak were collected in real time from two medical social media sites. These were compared against characteristics of ten existing pathogens that can induce atypical pneumonia. The probability that the current outbreak is due to \"Disease X\" (i.e., previously unknown etiology) as opposed to one of the known pathogens was inferred, and this estimate was updated as the outbreak continued.\n\nResultsThe probability that Disease X is driving the outbreak was assessed as over 32% on 31 December 2019, one week before virus identification. After some specific pathogens were ruled out by laboratory tests on 5 Jan 2020, the inferred probability of Disease X was over 59%.\n\nConclusionsWe showed quantitatively that the emerging outbreak of atypical pneumonia cases is consistent with causation by a novel pathogen. The proposed approach, that uses only routinely-observed non-virological data, can aid ongoing risk assessments even before virological test results become available.", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.01.27.20018986", + "rel_abs": "Currently, a novel coronavirus 2019-nCoV causes an outbreak of viral pneumonia in Wuhan, China. Little is known about its epidemiological characteristics. Using the travel history and symptom onset of 88 confirmed cases that were detected outside Wuhan, we estimate the mean incubation period to be 6.4 (5.6 - 7.7, 95% CI) days, ranging from 2.1 to 11.1 days (2.5th to 97.5th percentile). These values help to inform case definitions for 2019-nCoV and appropriate durations for quarantine.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Sung-mok Jung", - "author_inst": "Hokkaido University" - }, - { - "author_name": "Ryo Kinoshita", - "author_inst": "Hokkaido University" - }, - { - "author_name": "Robin N. Thompson", - "author_inst": "University of Oxford" - }, - { - "author_name": "Katsuma Hayashi", - "author_inst": "Hokkaido University" - }, - { - "author_name": "Natalie M. Linton", - "author_inst": "Hokkaido University" - }, - { - "author_name": "Yichi Yang", - "author_inst": "Hokkaido University" + "author_name": "Jantien A. Backer", + "author_inst": "National Institute for Public Health and the Environment" }, { - "author_name": "Andrei R. Akhmetzhanov", - "author_inst": "Hokkaido University" + "author_name": "Don Klinkenberg", + "author_inst": "National Institute for Public Health and the Environment" }, { - "author_name": "Hiroshi Nishiura", - "author_inst": "Hokkaido University" + "author_name": "Jacco Wallinga", + "author_inst": "National Institute for Public Health and the Environment, Leiden University Medical Center" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.01.27.20018986", - "rel_title": "The incubation period of 2019-nCoV infections among travellers from Wuhan, China", + "rel_doi": "10.1101/2020.01.27.922443", + "rel_title": "Breaking down of the healthcare system: Mathematical modelling for controlling the novel coronavirus (2019-nCoV) outbreak in Wuhan, China", "rel_date": "2020-01-28", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.01.27.20018986", - "rel_abs": "Currently, a novel coronavirus 2019-nCoV causes an outbreak of viral pneumonia in Wuhan, China. Little is known about its epidemiological characteristics. Using the travel history and symptom onset of 88 confirmed cases that were detected outside Wuhan, we estimate the mean incubation period to be 6.4 (5.6 - 7.7, 95% CI) days, ranging from 2.1 to 11.1 days (2.5th to 97.5th percentile). These values help to inform case definitions for 2019-nCoV and appropriate durations for quarantine.", + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2020.01.27.922443", + "rel_abs": "A novel coronavirus pneumonia initially identified in Wuhan, China and provisionally named 2019-nCoV has surged in the public. In anticipation of substantial burdens on healthcare system following this human-to-human spread, we aim to scrutinise the currently available information and evaluate the burden of healthcare systems during this outbreak in Wuhan. We applied a modified SIR model to project the actual number of infected cases and the specific burdens on isolation wards and intensive care units, given the scenarios of different diagnosis rates as well as different public health intervention efficacy. Our estimates suggest the actual number of infected cases could be much higher than the reported, with estimated 26,701 cases (as of 28th January 2020) assuming 50% diagnosis rate if no public health interventions were implemented. The estimated burdens on healthcare system could be largely reduced if at least 70% efficacy of public health intervention is achieved.", "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Jantien A. Backer", - "author_inst": "National Institute for Public Health and the Environment" + "author_name": "Wai-kit Ming", + "author_inst": "Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, China" }, { - "author_name": "Don Klinkenberg", - "author_inst": "National Institute for Public Health and the Environment" + "author_name": "Jian Huang", + "author_inst": "Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom" }, { - "author_name": "Jacco Wallinga", - "author_inst": "National Institute for Public Health and the Environment, Leiden University Medical Center" + "author_name": "Casper J.P. Zhang", + "author_inst": "School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China" } ], "version": "1", "license": "cc_by_nc_nd", - "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "type": "new results", + "category": "microbiology" }, { "rel_doi": "10.1101/2020.01.27.921536",